A statistical analysis of the daily streamflow hydrograph
NASA Astrophysics Data System (ADS)
Kavvas, M. L.; Delleur, J. W.
1984-03-01
In this study a periodic statistical analysis of daily streamflow data in Indiana, U.S.A., was performed to gain some new insight into the stochastic structure which describes the daily streamflow process. This analysis was performed by the periodic mean and covariance functions of the daily streamflows, by the time and peak discharge -dependent recession limb of the daily streamflow hydrograph, by the time and discharge exceedance level (DEL) -dependent probability distribution of the hydrograph peak interarrival time, and by the time-dependent probability distribution of the time to peak discharge. Some new statistical estimators were developed and used in this study. In general features, this study has shown that: (a) the persistence properties of daily flows depend on the storage state of the basin at the specified time origin of the flow process; (b) the daily streamflow process is time irreversible; (c) the probability distribution of the daily hydrograph peak interarrival time depends both on the occurrence time of the peak from which the inter-arrival time originates and on the discharge exceedance level; and (d) if the daily streamflow process is modeled as the release from a linear watershed storage, this release should depend on the state of the storage and on the time of the release as the persistence properties and the recession limb decay rates were observed to change with the state of the watershed storage and time. Therefore, a time-varying reservoir system needs to be considered if the daily streamflow process is to be modeled as the release from a linear watershed storage.
Archfield, Stacey A.; Steeves, Peter A.; Guthrie, John D.; Ries, Kernell G.
2013-01-01
Streamflow information is critical for addressing any number of hydrologic problems. Often, streamflow information is needed at locations that are ungauged and, therefore, have no observations on which to base water management decisions. Furthermore, there has been increasing need for daily streamflow time series to manage rivers for both human and ecological functions. To facilitate negotiation between human and ecological demands for water, this paper presents the first publicly available, map-based, regional software tool to estimate historical, unregulated, daily streamflow time series (streamflow not affected by human alteration such as dams or water withdrawals) at any user-selected ungauged river location. The map interface allows users to locate and click on a river location, which then links to a spreadsheet-based program that computes estimates of daily streamflow for the river location selected. For a demonstration region in the northeast United States, daily streamflow was, in general, shown to be reliably estimated by the software tool. Estimating the highest and lowest streamflows that occurred in the demonstration region over the period from 1960 through 2004 also was accomplished but with more difficulty and limitations. The software tool provides a general framework that can be applied to other regions for which daily streamflow estimates are needed.
Multi-site Stochastic Simulation of Daily Streamflow with Markov Chain and KNN Algorithm
NASA Astrophysics Data System (ADS)
Mathai, J.; Mujumdar, P.
2017-12-01
A key focus of this study is to develop a method which is physically consistent with the hydrologic processes that can capture short-term characteristics of daily hydrograph as well as the correlation of streamflow in temporal and spatial domains. In complex water resource systems, flow fluctuations at small time intervals require that discretisation be done at small time scales such as daily scales. Also, simultaneous generation of synthetic flows at different sites in the same basin are required. We propose a method to equip water managers with a streamflow generator within a stochastic streamflow simulation framework. The motivation for the proposed method is to generate sequences that extend beyond the variability represented in the historical record of streamflow time series. The method has two steps: In step 1, daily flow is generated independently at each station by a two-state Markov chain, with rising limb increments randomly sampled from a Gamma distribution and the falling limb modelled as exponential recession and in step 2, the streamflow generated in step 1 is input to a nonparametric K-nearest neighbor (KNN) time series bootstrap resampler. The KNN model, being data driven, does not require assumptions on the dependence structure of the time series. A major limitation of KNN based streamflow generators is that they do not produce new values, but merely reshuffle the historical data to generate realistic streamflow sequences. However, daily flow generated using the Markov chain approach is capable of generating a rich variety of streamflow sequences. Furthermore, the rising and falling limbs of daily hydrograph represent different physical processes, and hence they need to be modelled individually. Thus, our method combines the strengths of the two approaches. We show the utility of the method and improvement over the traditional KNN by simulating daily streamflow sequences at 7 locations in the Godavari River basin in India.
Archfield, Stacey A.; Vogel, Richard M.; Steeves, Peter A.; Brandt, Sara L.; Weiskel, Peter K.; Garabedian, Stephen P.
2010-01-01
Federal, State and local water-resource managers require a variety of data and modeling tools to better understand water resources. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a statewide, interactive decision-support tool to meet this need. The decision-support tool, referred to as the Massachusetts Sustainable-Yield Estimator (MA SYE) provides screening-level estimates of the sustainable yield of a basin, defined as the difference between the unregulated streamflow and some user-specified quantity of water that must remain in the stream to support such functions as recreational activities or aquatic habitat. The MA SYE tool was designed, in part, because the quantity of surface water available in a basin is a time-varying quantity subject to competing demands for water. To compute sustainable yield, the MA SYE tool estimates a daily time series of unregulated, daily mean streamflow for a 44-year period of record spanning October 1, 1960, through September 30, 2004. Selected streamflow quantiles from an unregulated, daily flow-duration curve are estimated by solving six regression equations that are a function of physical and climate basin characteristics at an ungaged site on a stream of interest. Streamflow is then interpolated between the estimated quantiles to obtain a continuous daily flow-duration curve. A time series of unregulated daily streamflow subsequently is created by transferring the timing of the daily streamflow at a reference streamgage to the ungaged site by equating exceedence probabilities of contemporaneous flow at the two locations. One of 66 reference streamgages is selected by kriging, a geostatistical method, which is used to map the spatial relation among correlations between the time series of the logarithm of daily streamflows at each reference streamgage and the ungaged site. Estimated unregulated, daily mean streamflows show good agreement with observed unregulated, daily mean streamflow at 18 streamgages located across southern New England. Nash-Sutcliffe efficiency goodness-of-fit values are between 0.69 and 0.98, and percent root-mean-square-error values are between 19 and 283 percent. The MA SYE tool provides an estimate of streamflow adjusted for current (2000-04) water withdrawals and discharges using a spatially referenced database of permitted groundwater and surface-water withdrawal and discharge volumes. For a user-selected basin, the database is queried to obtain the locations of water withdrawal or discharge volumes within the basin. Groundwater and surface-water withdrawals and discharges are subtracted and added, respectively, from the unregulated, daily streamflow at an ungaged site to obtain a streamflow time series that includes the effects of these withdrawals and discharges. Users also have the option of applying an analytical solution to the time-varying, groundwater withdrawal and discharge volumes that take into account the effects of the aquifer properties on the timing and magnitude of streamflow alteration. For the MA SYE tool, it is assumed that groundwater and surface-water divides are coincident. For areas of southeastern Massachusetts and Cape Cod where this assumption is known to be violated, groundwater-flow models are used to estimate average monthly streamflows at fixed locations. There are several limitations to the quality and quantity of the spatially referenced database of groundwater and surface-water withdrawals and discharges. The adjusted streamflow values do not account for the effects on streamflow of climate change, septic-system discharge, impervious area, non-public water-supply withdrawals less than 100,000 gallons per day, and impounded surface-water bodies.
Ordinary kriging as a tool to estimate historical daily streamflow records
Farmer, William H.
2016-01-01
Efficient and responsible management of water resources relies on accurate streamflow records. However, many watersheds are ungaged, limiting the ability to assess and understand local hydrology. Several tools have been developed to alleviate this data scarcity, but few provide continuous daily streamflow records at individual streamgages within an entire region. Building on the history of hydrologic mapping, ordinary kriging was extended to predict daily streamflow time series on a regional basis. Pooling parameters to estimate a single, time-invariant characterization of spatial semivariance structure is shown to produce accurate reproduction of streamflow. This approach is contrasted with a time-varying series of variograms, representing the temporal evolution and behavior of the spatial semivariance structure. Furthermore, the ordinary kriging approach is shown to produce more accurate time series than more common, single-index hydrologic transfers. A comparison between topological kriging and ordinary kriging is less definitive, showing the ordinary kriging approach to be significantly inferior in terms of Nash–Sutcliffe model efficiencies while maintaining significantly superior performance measured by root mean squared errors. Given the similarity of performance and the computational efficiency of ordinary kriging, it is concluded that ordinary kriging is useful for first-order approximation of daily streamflow time series in ungaged watersheds.
Technique for estimation of streamflow statistics in mineral areas of interest in Afghanistan
Olson, Scott A.; Mack, Thomas J.
2011-01-01
A technique for estimating streamflow statistics at ungaged stream sites in areas of mineral interest in Afghanistan using drainage-area-ratio relations of historical streamflow data was developed and is documented in this report. The technique can be used to estimate the following streamflow statistics at ungaged sites: (1) 7-day low flow with a 10-year recurrence interval, (2) 7-day low flow with a 2-year recurrence interval, (3) daily mean streamflow exceeded 90 percent of the time, (4) daily mean streamflow exceeded 80 percent of the time, (5) mean monthly streamflow for each month of the year, (6) mean annual streamflow, and (7) minimum monthly streamflow for each month of the year. Because they are based on limited historical data, the estimates of streamflow statistics at ungaged sites are considered preliminary.
Parrett, Charles; Hull, J.A.
1990-01-01
Five streamflow-gaging stations were installed in the Rock Creek basin north of the Milk River near Hinsdale, Montana. Streamflow was monitored at these stations and at an existing gaging station upstream on Rock Creek from May 1983 through September 1987. The data collected were used to describe the flow characteristics of four small tributary streams. Annual mean streamflow ranges from 2.8 to 57 cu ft/sec in the mainstem and from 0 to 0.60 cu ft/sec in the tributaries. Monthly mean streamflow ranged from 0 to 528 cu ft/sec in Rock Creek and from zero to 5.3 cu ft/sec in the four tributaries. The six gaged sites show similar patterns of daily mean streamflow during periods of large runoff, but substantial individual variations during periods of lesser runoff. During periods of lesser runoff , the small tributaries may have small daily mean streamflows. At other times, daily mean streamflow at the two mainstem sites decreased downstream. Daily mean streamflow in the tributaries appears to be closely related to daily mean streamflow in the mainstem only during periods of substantial area-wide runoff. Thus, streamflow in the tributaries resulting from local storms or local snowmelt may not contribute to streamflow in the mainstem. (USGS)
Farmer, William H.; Knight, Rodney R.; Eash, David A.; Kasey J. Hutchinson,; Linhart, S. Mike; Christiansen, Daniel E.; Archfield, Stacey A.; Over, Thomas M.; Kiang, Julie E.
2015-08-24
Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.
Stogner, Sr., Robert W.
2000-01-01
The Fountain Creek watershed, located in and along the eastern slope of the Front Range section of the southern Rocky Mountains, drains approximately 930 square miles of parts of Teller, El Paso, and Pueblo Counties in eastern Colorado. Streamflow in the watershed is dominated by spring snowmelt runoff and storm runoff during the summer monsoon season. Flooding during the 1990?s has resulted in increased streambank erosion. Property loss and damage associated with flooding and bank erosion has cost area residents, businesses, utilities, municipalities, and State and Federal agencies millions of dollars. Precipitation (4 stations) and streamflow (6 stations) data, aerial photographs, and channel reconnaissance were used to evaluate trends in precipitation and streamflow and changes in channel morphology. Trends were evaluated for pre-1977, post-1976, and period-of-record time periods. Analysis revealed the lack of trend in total annual and seasonal precipitation during the pre-1977 time period. In general, the analysis also revealed the lack of trend in seasonal precipitation for all except the spring season during the post-1976 time period. Trend analysis revealed a significant upward trend in long-term (period of record) total annual and spring precipitation data, apparently due to a change in total annual precipitation throughout the Fountain Creek watershed. During the pre-1977 time period, precipitation was generally below average; during the post- 1976 time period, total annual precipitation was generally above average. During the post- 1976 time period, an upward trend in total annual and spring precipitation was indicated at two stations. Because two of four stations evaluated had upward trends for the post-1976 period and storms that produce the most precipitation are isolated convection storms, it is plausible that other parts of the watershed had upward precipitation trends that could affect trends in streamflow. Also, because of the isolated nature of convection storms that hit some areas of the watershed and not others, it is difficult to draw strong conclusions on relations between streamflow and precipitation. Trends in annual instantaneous peak streamflow, 70th percentile, 90th percentile, maximum daily-mean streamflow (100th percentile), 7-, 14-, and 30-day high daily-mean stream- flow duration, minimum daily-mean streamflow (0th percentile), 10th percentile, 30th percentile, and 7-, 14-, 30-day low daily-mean streamflow duration were evaluated. In general, instantaneous peak streamflow has not changed significantly at most of the stations evaluated. Trend analysis revealed the lack of a significant upward trend in streamflow at all stations for the pre-1977 time period. Trend tests indicated a significant upward trend in high and low daily-mean streamflow statistics for the post-1976 period. Upward trends in high daily-mean streamflow statistics may be an indication that changes in land use within the watershed have increased the rate and magnitude of runoff. Upward trends in low daily-mean 2 Trends in Precipitation and Streamflow and Changes in Stream Morphology in the Fountain Creek Watershed, Colorado, 1939-99 streamflow statistics may be related to changes in water use and management. An analysis of the relation between streamflow and precipitation indicated that changes in water management have had a marked effect on streamflow. Observable change in channel morphology and changes in distribution and density of vegetation varied with magnitude, duration, and frequency of large streamflow events, and increases in the magnitude and duration of low streamflows. Although more subtle, low stream- flows were an important component of day-to-day channel erosion. Substantial changes in channel morphology were most often associated with infrequent large or catastrophic streamflow events that erode streambed and banks, alter stream course, and deposit large amounts of sediment in the flood plain.
NASA Astrophysics Data System (ADS)
Boulariah, Ouafik; Longobardi, Antonia; Meddi, Mohamed
2017-04-01
One of the major challenges scientists, practitioners and stakeholders are nowadays involved in, is to provide the worldwide population with reliable water supplies, protecting, at the same time, the freshwater ecosystems quality and quantity. Climate and land use changes undermine the balance between water demand and water availability, causing alteration of rivers flow regime. Knowledge of hydro-climate variables temporal and spatial variability is clearly helpful to plan drought and flood hazard mitigation strategies but also to adapt them to future environmental scenarios. The present study relates to the coastal semi-arid Tafna catchment, located in the North-West of Algeria, within the Mediterranean basin. The aim is the investigation of streamflow and rainfall indices temporal variability in six sub-basins of the large catchment Tafna, attempting to relate streamflow and rainfall changes. Rainfall and streamflow time series have been preliminary tested for data quality and homogeneity, through the coupled application of two-tailed t test, Pettitt test and Cumsum tests (significance level of 0.1, 0.05 and 0.01). Subsequently maximum annual daily rainfall and streamflow and average daily annual rainfall and streamflow time series have been derived and tested for temporal variability, through the application of the Mann Kendall and Sen's test. Overall maximum annual daily streamflow time series exhibit a negative trend which is however significant for only 30% of the station. Maximum annual daily rainfall also e exhibit a negative trend which is intend significant for the 80% of the stations. In the case of average daily annual streamflow and rainfall, the tendency for decrease in time is unclear and, in both cases, appear significant for 60% of stations.
Asquith, William H.; Vrabel, Joseph; Roussel, Meghan C.
2007-01-01
Analysts and managers of surface-water resources might have interest in selected statistics of daily mean streamflow for U.S. Geological Survey (USGS) streamflow-gaging stations in Texas. The selected statistics are the annual mean, maximum, minimum, and L-scale of daily meanstreamflow. Annual L-scale of streamflow is a robust measure of the variability of the daily mean streamflow for a given year. The USGS, in cooperation with the Texas Commission on Environmental Quality, initiated in 2006a data and reporting process to generate annual statistics for 712 USGS streamflow-gaging stations in Texas. A graphical depiction of the history of the annual statistics for most active and inactive, continuous-record gaging stations in Texas provides valuable information by conveying the historical perspective of streamflow for the watershed. Each figure consists off our time-series plots of the annual statistics of daily mean streamflow for each streamflow-gaging station. Each of the four plots is augmented with horizontal lines that depict the mean and median annual values of the corresponding statistic for the period of record. Monotonic trends for each of the four annual statistics also are identified using Kendall's T. The history of one or more streamflow-gaging stations could be used in a watershed, river basin, or other regional context by analysts and managers of surface-water resources to guide scientific, regulatory, or other inquiries of streamflow conditions in Texas.
Assessment of the timing of daily peak streamflow during melt season in a snow dominated watershed
USDA-ARS?s Scientific Manuscript database
Previous studies have shown that gauge-observed daily streamflow peak times (DPT) during spring snowmelt can exhibit distinct temporal shifts through the season. These shifts have been attributed to three processes that affect the timing of snowmelt arrival: 1) melt flux translation through the snow...
NASA Astrophysics Data System (ADS)
Demaria, E. M.; Valdes, J. B.; Wi, S.; Serrat-Capdevila, A.; Valdés-Pineda, R.; Durcik, M.
2016-12-01
In under-instrumented basins around the world, accurate and timely forecasts of river streamflows have the potential of assisting water and natural resource managers in their management decisions. The Upper Zambezi river basin is the largest basin in southern Africa and its water resources are critical to sustainable economic growth and poverty reduction in eight riparian countries. We present a real-time streamflow forecast for the basin using a multi-model-multi-satellite approach that allows accounting for model and input uncertainties. Three distributed hydrologic models with different levels of complexity: VIC, HYMOD_DS, and HBV_DS are setup at a daily time step and a 0.25 degree spatial resolution for the basin. The hydrologic models are calibrated against daily observed streamflows at the Katima-Mulilo station using a Genetic Algorithm. Three real-time satellite products: Climate Prediction Center's morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Tropical Rainfall Measuring Mission (TRMM-3B42RT) are bias-corrected with daily CHIRPS estimates. Uncertainty bounds for predicted flows are estimated with the Inverse Variance Weighting method. Because concentration times in the basin range from a few days to more than a week, we include the use of precipitation forecasts from the Global Forecasting System (GFS) to predict daily streamflows in the basin with a 10-days lead time. The skill of GFS-predicted streamflows is evaluated and the usefulness of the forecasts for short term water allocations is presented.
NASA Astrophysics Data System (ADS)
Do, Hong Xuan; Gudmundsson, Lukas; Leonard, Michael; Westra, Seth
2018-04-01
This is the first part of a two-paper series presenting the Global Streamflow Indices and Metadata archive (GSIM), a worldwide collection of metadata and indices derived from more than 35 000 daily streamflow time series. This paper focuses on the compilation of the daily streamflow time series based on 12 free-to-access streamflow databases (seven national databases and five international collections). It also describes the development of three metadata products (freely available at https://doi.pangaea.de/10.1594/PANGAEA.887477): (1) a GSIM catalogue collating basic metadata associated with each time series, (2) catchment boundaries for the contributing area of each gauge, and (3) catchment metadata extracted from 12 gridded global data products representing essential properties such as land cover type, soil type, and climate and topographic characteristics. The quality of the delineated catchment boundary is also made available and should be consulted in GSIM application. The second paper in the series then explores production and analysis of streamflow indices. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.
Environmental flow allocation and statistics calculator
Konrad, Christopher P.
2011-01-01
The Environmental Flow Allocation and Statistics Calculator (EFASC) is a computer program that calculates hydrologic statistics based on a time series of daily streamflow values. EFASC will calculate statistics for daily streamflow in an input file or will generate synthetic daily flow series from an input file based on rules for allocating and protecting streamflow and then calculate statistics for the synthetic time series. The program reads dates and daily streamflow values from input files. The program writes statistics out to a series of worksheets and text files. Multiple sites can be processed in series as one run. EFASC is written in MicrosoftRegistered Visual BasicCopyright for Applications and implemented as a macro in MicrosoftOffice Excel 2007Registered. EFASC is intended as a research tool for users familiar with computer programming. The code for EFASC is provided so that it can be modified for specific applications. All users should review how output statistics are calculated and recognize that the algorithms may not comply with conventions used to calculate streamflow statistics published by the U.S. Geological Survey.
Asquith, William H.; Heitmuller, Franklin T.
2008-01-01
Analysts and managers of surface-water resources have interest in annual mean and annual harmonic mean statistics of daily mean streamflow for U.S. Geological Survey (USGS) streamflow-gaging stations in Texas. The mean streamflow represents streamflow volume, whereas the harmonic mean streamflow represents an appropriate statistic for assessing constituent concentrations that might adversely affect human health. In 2008, the USGS, in cooperation with the Texas Commission on Environmental Quality, conducted a large-scale documentation of mean and harmonic mean streamflow for 620 active and inactive, continuous-record, streamflow-gaging stations using period of record data through water year 2007. About 99 stations within the Texas USGS streamflow-gaging network are part of the larger national Hydroclimatic Data Network and are identified. The graphical depictions of annual mean and annual harmonic mean statistics in this report provide a historical perspective of streamflow at each station. Each figure consists of three time-series plots, two flow-duration curves, and a statistical summary of the mean annual and annual harmonic mean streamflow statistics for available data for each station.The first time-series plot depicts daily mean streamflow for the period 1900-2007. Flow-duration curves follow and are a graphical depiction of streamflow variability. Next, the remaining two time-series plots depict annual mean and annual harmonic mean streamflow and are augmented with horizontal lines that depict mean and harmonic mean for the period of record. Monotonic trends for the annual mean streamflow and annual harmonic mean streamflow also are identified using Kendall's tau, and the slope of the trend is depicted using the nonparametric (linear) Theil-Sen line, which is only drawn for p-values less than .10 of tau. The history of annual mean and annual harmonic mean streamflow of one or more streamflow-gaging stations could be used in a watershed, river basin, or other regional context by analysts and managers of surface-water resources to guide scientific, regulatory, or other inquiries of streamflow conditions in Texas.
On the probability distribution of daily streamflow in the United States
Blum, Annalise G.; Archfield, Stacey A.; Vogel, Richard M.
2017-01-01
Daily streamflows are often represented by flow duration curves (FDCs), which illustrate the frequency with which flows are equaled or exceeded. FDCs have had broad applications across both operational and research hydrology for decades; however, modeling FDCs has proven elusive. Daily streamflow is a complex time series with flow values ranging over many orders of magnitude. The identification of a probability distribution that can approximate daily streamflow would improve understanding of the behavior of daily flows and the ability to estimate FDCs at ungaged river locations. Comparisons of modeled and empirical FDCs at nearly 400 unregulated, perennial streams illustrate that the four-parameter kappa distribution provides a very good representation of daily streamflow across the majority of physiographic regions in the conterminous United States (US). Further, for some regions of the US, the three-parameter generalized Pareto and lognormal distributions also provide a good approximation to FDCs. Similar results are found for the period of record FDCs, representing the long-term hydrologic regime at a site, and median annual FDCs, representing the behavior of flows in a typical year.
A nonparametric stochastic method for generating daily climate-adjusted streamflows
NASA Astrophysics Data System (ADS)
Stagge, J. H.; Moglen, G. E.
2013-10-01
A daily stochastic streamflow generation model is presented, which successfully replicates statistics of the historical streamflow record and can produce climate-adjusted daily time series. A monthly climate model relates general circulation model (GCM)-scale climate indicators to discrete climate-streamflow states, which in turn control parameters in a daily streamflow generation model. Daily flow is generated by a two-state (increasing/decreasing) Markov chain, with rising limb increments randomly sampled from a Weibull distribution and the falling limb modeled as exponential recession. When applied to the Potomac River, a 38,000 km2 basin in the Mid-Atlantic United States, the model reproduces the daily, monthly, and annual distribution and dynamics of the historical streamflow record, including extreme low flows. This method can be used as part of water resources planning, vulnerability, and adaptation studies and offers the advantage of a parsimonious model, requiring only a sufficiently long historical streamflow record and large-scale climate data. Simulation of Potomac streamflows subject to the Special Report on Emissions Scenarios (SRES) A1b, A2, and B1 emission scenarios predict a slight increase in mean annual flows over the next century, with the majority of this increase occurring during the winter and early spring. Conversely, mean summer flows are projected to decrease due to climate change, caused by a shift to shorter, more sporadic rain events. Date of the minimum annual flow is projected to shift 2-5 days earlier by the 2070-2099 period.
NASA Astrophysics Data System (ADS)
Dhakal, A. S.; Adera, S.
2017-12-01
Accurate daily streamflow prediction in ungauged watersheds with sparse information is challenging. The ability of a hydrologic model calibrated using nearby gauged watersheds to predict streamflow accurately depends on hydrologic similarities between the gauged and ungauged watersheds. This study examines daily streamflow predictions using the Precipitation-Runoff Modeling System (PRMS) for the largely ungauged San Antonio Creek watershed, a 96 km2 sub-watershed of the Alameda Creek watershed in Northern California. The process-based PRMS model is being used to improve the accuracy of recent San Antonio Creek streamflow predictions generated by two empirical methods. Although San Antonio Creek watershed is largely ungauged, daily streamflow data exists for hydrologic years (HY) 1913 - 1930. PRMS was calibrated for HY 1913 - 1930 using streamflow data, modern-day land use and PRISM precipitation distribution, and gauged precipitation and temperature data from a nearby watershed. The PRMS model was then used to generate daily streamflows for HY 1996-2013, during which the watershed was ungauged, and hydrologic responses were compared to two nearby gauged sub-watersheds of Alameda Creek. Finally, the PRMS-predicted daily flows between HY 1996-2013 were compared to the two empirically-predicted streamflow time series: (1) the reservoir mass balance method and (2) correlation of historical streamflows from 80 - 100 years ago between San Antonio Creek and a nearby sub-watershed located in Alameda Creek. While the mass balance approach using reservoir storage and transfers is helpful for estimating inflows to the reservoir, large discrepancies in daily streamflow estimation can arise. Similarly, correlation-based predicted daily flows which rely on a relationship from flows collected 80-100 years ago may not represent current watershed hydrologic conditions. This study aims to develop a method of streamflow prediction in the San Antonio Creek watershed by examining PRMS's model outputs as well as empirically generated flow data for their use in water resources management decisions. PRMS is also being used to better understand the streamflow patterns in the San Antonio Creek watershed for a variety of antecedent soil moisture conditions as the creek is generally dry between late Spring and early Fall.
Chase, Katherine J.; Caldwell, Rodney R.; Stanley, Andrea K.
2014-01-01
This report documents the construction of a precipitation-runoff model for simulating natural streamflow in the Smith River watershed, Montana. This Precipitation-Runoff Modeling System model, constructed in cooperation with the Meagher County Conservation District, can be used to examine the general hydrologic framework of the Smith River watershed, including quantification of precipitation, evapotranspiration, and streamflow; partitioning of streamflow between surface runoff and subsurface flow; and quantifying contributions to streamflow from several parts of the watershed. The model was constructed by using spatial datasets describing watershed topography, the streams, and the hydrologic characteristics of the basin soils and vegetation. Time-series data (daily total precipitation, and daily minimum and maximum temperature) were input to the model to simulate daily streamflow. The model was calibrated for water years 2002–2007 and evaluated for water years 1996–2001. Though water year 2008 was included in the study period to evaluate water-budget components, calibration and evaluation data were unavailable for that year. During the calibration and evaluation periods, simulated-natural flow values were compared to reconstructed-natural streamflow data. These reconstructed-natural streamflow data were calculated by adding Bureau of Reclamation’s depletions data to the observed streamflows. Reconstructed-natural streamflows represent estimates of streamflows for water years 1996–2007 assuming there was no agricultural water-resources development in the watershed. Additional calibration targets were basin mean monthly solar radiation and potential evapotranspiration. The model estimated the hydrologic processes in the Smith River watershed during the calibration and evaluation periods. Simulated-natural mean annual and mean monthly flows generally were the same or higher than the reconstructed-natural streamflow values during the calibration period, whereas they were lower during the evaluation period. The shape of the annual hydrographs for the simulated-natural daily streamflow values matched the shape of the hydrographs for the reconstructed-natural values for most of the calibration period, but daily streamflow values were underestimated during the evaluation period for water years 1996–1998. The model enabled a detailed evaluation of the components of the water budget within the Smith River watershed during the water year 1996–2008 study period. During this study period, simulated mean annual precipitation across the Smith River watershed was 16 inches, out of which 14 inches evaporated or transpired and 2 inches left the basin as streamflow. Per the precipitation-runoff model simulations, during most of the year, surface runoff rarely (less than 2 percent of the time during water years 2002–2008) makes up more than 10 percent of the total streamflow. Subsurface flow (the combination of interflow and groundwater flow) makes up most of the total streamflow (99 or more percent of total streamflow for 71 percent of the time during water years 2002–2008).
Barbie, Dana L.; Wehmeyer, Loren L.
2012-01-01
Trends in selected streamflow statistics during 1922-2009 were evaluated at 19 long-term streamflow-gaging stations considered indicative of outflows from Texas to Arkansas, Louisiana, Galveston Bay, and the Gulf of Mexico. The U.S. Geological Survey, in cooperation with the Texas Water Development Board, evaluated streamflow data from streamflow-gaging stations with more than 50 years of record that were active as of 2009. The outflows into Arkansas and Louisiana were represented by 3 streamflow-gaging stations, and outflows into the Gulf of Mexico, including Galveston Bay, were represented by 16 streamflow-gaging stations. Monotonic trend analyses were done using the following three streamflow statistics generated from daily mean values of streamflow: (1) annual mean daily discharge, (2) annual maximum daily discharge, and (3) annual minimum daily discharge. The trend analyses were based on the nonparametric Kendall's Tau test, which is useful for the detection of monotonic upward or downward trends with time. A total of 69 trend analyses by Kendall's Tau were computed - 19 periods of streamflow multiplied by the 3 streamflow statistics plus 12 additional trend analyses because the periods of record for 2 streamflow-gaging stations were divided into periods representing pre- and post-reservoir impoundment. Unless otherwise described, each trend analysis used the entire period of record for each streamflow-gaging station. The monotonic trend analysis detected 11 statistically significant downward trends, 37 instances of no trend, and 21 statistically significant upward trends. One general region studied, which seemingly has relatively more upward trends for many of the streamflow statistics analyzed, includes the rivers and associated creeks and bayous to Galveston Bay in the Houston metropolitan area. Lastly, the most western river basins considered (the Nueces and Rio Grande) had statistically significant downward trends for many of the streamflow statistics analyzed.
Esralew, Rachel A.; Andrews, William J.; Smith, S. Jerrod
2011-01-01
The U.S. Geological Survey, in cooperation with the city of Oklahoma City, collected water-quality samples from the North Canadian River at the streamflow-gaging station near Harrah, Oklahoma (Harrah station), since 1968, and at an upstream streamflow-gaging station at Britton Road at Oklahoma City, Oklahoma (Britton Road station), since 1988. Statistical summaries and frequencies of detection of water-quality constituent data from water samples, and summaries of water-quality constituent data from continuous water-quality monitors are described from the start of monitoring at those stations through 2009. Differences in concentrations between stations and time trends for selected constituents were evaluated to determine the effects of: (1) wastewater effluent discharges, (2) changes in land-cover, (3) changes in streamflow, (4) increases in urban development, and (5) other anthropogenic sources of contamination on water quality in the North Canadian River downstream from Oklahoma City. Land-cover changes between 1992 and 2001 in the basin between the Harrah station and Lake Overholser upstream included an increase in developed/barren land-cover and a decrease in pasture/hay land cover. There were no significant trends in median and greater streamflows at either streamflow-gaging station, but there were significant downward trends in lesser streamflows, especially after 1999, which may have been associated with decreases in precipitation between 1999 and 2009 or construction of low-water dams on the river upstream from Oklahoma City in 1999. Concentrations of dissolved chloride, lead, cadmium, and chlordane most frequently exceeded the Criterion Continuous Concentration (a water-quality standard for protection of aquatic life) in water-quality samples collected at both streamflow-gaging stations. Visual trends in annual frequencies of detection were investigated for selected pesticides with frequencies of detection greater than 10 percent in all water samples collected at both streamflow-gaging stations. Annual frequencies of detection of 2,4-dichlorophenoxyacetic acid and bromacil increased with time. Annual frequencies of detection of atrazine, chlorpyrifos, diazinon, dichlorprop, and lindane decreased with time. Dissolved nitrogen and phosphorus concentrations were significantly greater in water samples collected at the Harrah station than at the Britton Road station, whereas specific conductance was greater at the Britton Road station. Concentrations of dissolved oxygen, biochemical oxygen demand, and fecal coliform bacteria were not significantly different between stations. Daily minimum, mean, and maximum specific conductance collected from continuous water-quality monitors were significantly greater at the Britton Road station than in water samples collected at the Harrah station. Daily minimum, maximum, and diurnal fluctuations of water temperature collected from continuous water-quality monitors were significantly greater at the Harrah station than at the Britton Road station. The daily maximums and diurnal range of dissolved oxygen concentrations were significantly greater in water samples collected at the Britton Road station than at the Harrah station, but daily mean dissolved oxygen concentrations in water at those streamflow-gaging stations were not significantly different. Daily mean and diurnal water temperature ranges increased with time at the Britton Road and Harrah streamflow-gaging stations, whereas daily mean and diurnal specific conductance ranges decreased with time at both streamflow-gaging stations from 1988–2009. Daily minimum dissolved oxygen concentrations collected from continuous water-quality monitors more frequently indicated hypoxic conditions at the Harrah station than at the Britton Road station after 1999. Fecal coliform bacteria counts in water decreased slightly from 1988–2009 at the Britton Road station. The Seasonal Kendall's tau test indicated significant downward trends in
Stuckey, Marla H.
2016-06-09
The ability to characterize baseline streamflow conditions, compare them with current conditions, and assess effects of human activities on streamflow is fundamental to water-management programs addressing water allocation, human-health issues, recreation needs, and establishment of ecological flow criteria. The U.S. Geological Survey, through the National Water Census, has developed the Delaware River Basin Streamflow Estimator Tool (DRB-SET) to estimate baseline (minimally altered) and altered (affected by regulation, diversion, mining, or other anthropogenic activities) and altered streamflow at a daily time step for ungaged stream locations in the Delaware River Basin for water years 1960–2010. Daily mean baseline streamflow is estimated by using the QPPQ method to equate streamflow expressed as a percentile from the flow-duration curve (FDC) for a particular day at an ungaged stream location with the percentile from a FDC for the same day at a hydrologically similar gaged location where streamflow is measured. Parameter-based regression equations were developed for 22 exceedance probabilities from the FDC for ungaged stream locations in the Delaware River Basin. Water use data from 2010 is used to adjust the baseline daily mean streamflow generated from the QPPQ method at ungaged stream locations in the Delaware River Basin to reflect current, or altered, conditions. To evaluate the effectiveness of the overall QPPQ method contained within DRB-SET, a comparison of observed and estimated daily mean streamflows was performed for 109 reference streamgages in and near the Delaware River Basin. The Nash-Sutcliffe efficiency (NSE) values were computed as a measure of goodness of fit. The NSE values (using log10 streamflow values) ranged from 0.22 to 0.98 (median of 0.90) for 45 streamgages in the Upper Delaware River Basin and from -0.37 to 0.98 (median of 0.79) for 41 streamgages in the Lower Delaware River Basin.
Linhart, S. Mike; Nania, Jon F.; Sanders, Curtis L.; Archfield, Stacey A.
2012-01-01
The U.S. Geological Survey (USGS) maintains approximately 148 real-time streamgages in Iowa for which daily mean streamflow information is available, but daily mean streamflow data commonly are needed at locations where no streamgages are present. Therefore, the USGS conducted a study as part of a larger project in cooperation with the Iowa Department of Natural Resources to develop methods to estimate daily mean streamflow at locations in ungaged watersheds in Iowa by using two regression-based statistical methods. The regression equations for the statistical methods were developed from historical daily mean streamflow and basin characteristics from streamgages within the study area, which includes the entire State of Iowa and adjacent areas within a 50-mile buffer of Iowa in neighboring states. Results of this study can be used with other techniques to determine the best method for application in Iowa and can be used to produce a Web-based geographic information system tool to compute streamflow estimates automatically. The Flow Anywhere statistical method is a variation of the drainage-area-ratio method, which transfers same-day streamflow information from a reference streamgage to another location by using the daily mean streamflow at the reference streamgage and the drainage-area ratio of the two locations. The Flow Anywhere method modifies the drainage-area-ratio method in order to regionalize the equations for Iowa and determine the best reference streamgage from which to transfer same-day streamflow information to an ungaged location. Data used for the Flow Anywhere method were retrieved for 123 continuous-record streamgages located in Iowa and within a 50-mile buffer of Iowa. The final regression equations were computed by using either left-censored regression techniques with a low limit threshold set at 0.1 cubic feet per second (ft3/s) and the daily mean streamflow for the 15th day of every other month, or by using an ordinary-least-squares multiple linear regression method and the daily mean streamflow for the 15th day of every other month. The Flow Duration Curve Transfer method was used to estimate unregulated daily mean streamflow from the physical and climatic characteristics of gaged basins. For the Flow Duration Curve Transfer method, daily mean streamflow quantiles at the ungaged site were estimated with the parameter-based regression model, which results in a continuous daily flow-duration curve (the relation between exceedance probability and streamflow for each day of observed streamflow) at the ungaged site. By the use of a reference streamgage, the Flow Duration Curve Transfer is converted to a time series. Data used in the Flow Duration Curve Transfer method were retrieved for 113 continuous-record streamgages in Iowa and within a 50-mile buffer of Iowa. The final statewide regression equations for Iowa were computed by using a weighted-least-squares multiple linear regression method and were computed for the 0.01-, 0.05-, 0.10-, 0.15-, 0.20-, 0.30-, 0.40-, 0.50-, 0.60-, 0.70-, 0.80-, 0.85-, 0.90-, and 0.95-exceedance probability statistics determined from the daily mean streamflow with a reporting limit set at 0.1 ft3/s. The final statewide regression equation for Iowa computed by using left-censored regression techniques was computed for the 0.99-exceedance probability statistic determined from the daily mean streamflow with a low limit threshold and a reporting limit set at 0.1 ft3/s. For the Flow Anywhere method, results of the validation study conducted by using six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 1,016 to 138 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 1,690 to 237 ft3/s. Values of the percent root-mean-square error ranged from 115 percent to 26.2 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 13.0 to 5.3 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.80 to 0.40. Percent-bias values ranged from 25.4 to 4.0 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.35. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.86 to 0.56. For the streamgage with the best agreement between observed and estimated streamflow, higher streamflows appear to be underestimated. For the streamgage with the worst agreement between observed and estimated streamflow, low flows appear to be overestimated whereas higher flows seem to be underestimated. Estimated cumulative streamflows for the period October 1, 2004, to September 30, 2009, are underestimated by -25.8 and -7.4 percent for the closest and poorest comparisons, respectively. For the Flow Duration Curve Transfer method, results of the validation study conducted by using the same six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 437 to 93.9 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 906 to 169 ft3/s. Values of the percent root-mean-square-error ranged from 67.0 to 25.6 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 12.5 to 4.4 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.79 to 0.40. Percent-bias values ranged from 22.7 to 0.94 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.38. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.89 to 0.48. For the streamgage with the closest agreement between observed and estimated streamflow, there is relatively good agreement between observed and estimated streamflows. For the streamgage with the poorest agreement between observed and estimated streamflow, streamflows appear to be substantially underestimated for much of the time period. Estimated cumulative streamflow for the period October 1, 2004, to September 30, 2009, are underestimated by -9.3 and -22.7 percent for the closest and poorest comparisons, respectively.
Stuckey, Marla H.; Koerkle, Edward H.; Ulrich, James E.
2012-01-01
BaSE uses the map correlation method and flow-duration exceedance probability regression equations to estimate baseline daily mean streamflow for an ungaged location. The output from BaSE is a Microsoft Excel® report file that summarizes the reference streamgage and ungaged location information, including basin characteristics, percent difference in basin characteristics between the two locations, any warning associated with the basin characteristics, mean and median streamflow for the ungaged location, and a daily hydrograph of streamflow for water years 1960–2008 for the ungaged location. The daily mean streamflow for the ungaged location can be exported as a text file to be used as input into other statistical software packages. BaSE estimates daily mean streamflow for baseline conditions only, and any alterations to streamflow from regulation, large water use, or substantial mining are not reflected in the estimated streamflow.
Spatial Correlation Of Streamflows: An Analytical Approach
NASA Astrophysics Data System (ADS)
Betterle, A.; Schirmer, M.; Botter, G.
2016-12-01
The interwoven space and time variability of climate and landscape properties results in complex and non-linear hydrological response of streamflow dynamics. Understanding how meteorologic and morphological characteristics of catchments affect similarity/dissimilarity of streamflow timeseries at their outlets represents a scientific challenge with application in water resources management, ecological studies and regionalization approaches aimed to predict streamflows in ungauged areas. In this study, we establish an analytical approach to estimate the spatial correlation of daily streamflows in two arbitrary locations within a given hydrologic district or river basin at seasonal and annual time scales. The method is based on a stochastic description of the coupled streamflow dynamics at the outlet of two catchments. The framework aims to express the correlation of daily streamflows at two locations along a river network as a function of a limited number of physical parameters characterizing the main underlying hydrological drivers, that include climate conditions, precipitation regime and catchment drainage rates. The proposed method portrays how heterogeneity of climate and landscape features affect the spatial variability of flow regimes along river systems. In particular, we show that frequency and intensity of synchronous effective rainfall events in the relevant contributing catchments are the main driver of the spatial correlation of daily discharge, whereas only pronounced differences in the drainage rate of the two basins bear a significant effect on the streamflow correlation. The topological arrangement of the two outlets also influences the underlying streamflow correlation, as we show that nested catchments tend to maximize the spatial correlation of flow regimes. The application of the method to a set of catchments in the South-Eastern US suggests the potential of the proposed tool for the characterization of spatial connections of flow regimes in the absence of discharge measurements.
Analysis of trends in selected streamflow statistics for the Concho River Basin, Texas, 1916-2009
Barbie, Dana L.; Wehmeyer, Loren L.; May, Jayne E.
2012-01-01
Six U.S. Geological Survey streamflow-gaging stations were selected for analysis. Streamflow-gaging station 08128000 South Concho River at Christoval has downward trends for annual maximum daily discharge and annual instantaneous peak discharge for the combined period 1931-95, 2002-9. Streamflow-gaging station 08128400 Middle Concho River above Tankersley has downward trends for annual maximum daily discharge and annual instantaneous peak discharge for the combined period 1962-95, 2002-9. Streamflow-gaging station 08128500 Middle Concho River near Tankersley has no significant trends in the streamflow statistics considered for the period 1931-60. Streamflow-gaging station 08134000 North Concho River near Carlsbad has downward trends for annual mean daily discharge, annual 7-day minimum daily discharge, annual maximum daily discharge, and annual instantaneous peak discharge for the period 1925-2009. Streamflow-gaging stations 08136000 Concho River at San Angelo and 08136500 Concho River at Paint Rock have downward trends for 1916-2009 for all streamflow statistics calculated, but streamflow-gaging station 08136000 Concho River at San Angelo has an upward trend for annual maximum daily discharge during 1964-2009. The downward trends detected during 1916-2009 for the Concho River at San Angelo are not unexpected because of three reservoirs impounding and profoundly regulating streamflow.
NASA Astrophysics Data System (ADS)
Do, Hong; Gudmundsson, Lukas; Leonard, Michael; Westra, Seth; Senerivatne, Sonia
2017-04-01
In-situ observations of daily streamflow with global coverage are a crucial asset for understanding large-scale freshwater resources which are an essential component of the Earth system and a prerequisite for societal development. Here we present the Global Streamflow Indices and Metadata archive (G-SIM), a collection indices derived from more than 20,000 daily streamflow time series across the globe. These indices are designed to support global assessments of change in wet and dry extremes, and have been compiled from 12 free-to-access online databases (seven national databases and five international collections). The G-SIM archive also includes significant metadata to help support detailed understanding of streamflow dynamics, with the inclusion of drainage area shapefile and many essential catchment properties such as land cover type, soil and topographic characteristics. The automated procedure in data handling and quality control of the project makes G-SIM a reproducible, extendible archive and can be utilised for many purposes in large-scale hydrology. Some potential applications include the identification of observational trends in hydrological extremes, the assessment of climate change impacts on streamflow regimes, and the validation of global hydrological models.
Wiley, Jeffrey B.; Evaldi, Ronald D.; Eychaner, James H.; Chambers, Douglas B.
2001-01-01
The effects of mountaintop removal coal mining and the valley fills created by this mining method in southern West Virginia were investigated by comparing data collected at valley-fill, mined, and unmined sites. Bed material downstream of valley-fill sites had a greater number of particles less than 2 millimeters and a smaller median particle size than the mined and unmined sites. At the 84th percentile of sampled data, however, bed material at each site type had about the same size particles. Bankfull cross-sectional areas at a riffle section were approximately equal at valley-fill and unmined sites, but not enough time has passed and insufficient streamflows since the land was disturbed may have prevented the stream channel at valley-fill sites from reaching equilibrium. The 90-percent flow durations at valley-fill sites generally were 6-7 times greater than at unmined sites. Some valley-fill sites, however, exhibited streamflows similar to unmined sites, and some unmined sites exhibited streamflows similar to valley-fill sites. Daily streamflows from valley-fill sites generally are greater than daily streamflows from unmined sites during periods of low streamflow. Valley-fill sites have a greater percentage of base-flow and a lower percentage of flow from storm runoff than unmined sites. Water temperatures from a valley-fill site exhibited lower daily fluctuations and seasonal variations than water temperatures from an unmined site.
Wood, Molly S.; Fosness, Ryan L.
2013-01-01
The U.S. Geological Survey, in cooperation with the Bureau of Land Management (BLM), collected streamflow data in 2012 and estimated streamflow statistics for stream segments designated "Wild," "Scenic," or "Recreational" under the National Wild and Scenic Rivers System in the Owyhee Canyonlands Wilderness in southwestern Idaho. The streamflow statistics were used by BLM to develop and file a draft, federal reserved water right claim in autumn 2012 to protect federally designated "outstanding remarkable values" in the stream segments. BLM determined that the daily mean streamflow equaled or exceeded 20 and 80 percent of the time during bimonthly periods (two periods per month) and the bankfull streamflow are important streamflow thresholds for maintaining outstanding remarkable values. Prior to this study, streamflow statistics estimated using available datasets and tools for the Owyhee Canyonlands Wilderness were inaccurate for use in the water rights claim. Streamflow measurements were made at varying intervals during February–September 2012 at 14 monitoring sites; 2 of the monitoring sites were equipped with telemetered streamgaging equipment. Synthetic streamflow records were created for 11 of the 14 monitoring sites using a partial‑record method or a drainage-area-ratio method. Streamflow records were obtained directly from an operating, long-term streamgage at one monitoring site, and from discontinued streamgages at two monitoring sites. For 10 sites analyzed using the partial-record method, discrete measurements were related to daily mean streamflow at a nearby, telemetered “index” streamgage. Resulting regression equations were used to estimate daily mean and annual peak streamflow at the monitoring sites during the full period of record for the index sites. A synthetic streamflow record for Sheep Creek was developed using a drainage-area-ratio method, because measured streamflows did not relate well to any index site to allow use of the partial-record method. The synthetic and actual daily mean streamflow records were used to estimate daily mean streamflow that was exceeded 80, 50, and 20 percent of the time (80-, 50-, and 20-percent exceedances) for bimonthly and annual periods. Bankfull streamflow statistics were calculated by fitting the synthetic and actual annual peak streamflow records to a log Pearson Type III distribution using Bulletin 17B guidelines in the U.S. Geological Survey PeakFQ program. The coefficients of determination (R2) for the regressions between the monitoring and index sites ranged from 0.74 for Wickahoney Creek to 0.98 for the West Fork Bruneau River and Deep Creek. Confidence in computed streamflow statistics is highest among other sites for the East Fork Owyhee River and the West Fork Bruneau River on the basis of regression statistics, visual fit of the related data, and the range and number of streamflow measurements. Streamflow statistics for sites with the greatest uncertainty included Big Jacks, Little Jacks, Cottonwood, Wickahoney, and Sheep Creeks. The uncertainty in computed streamflow statistics was due to a number of factors which included the distance of index sites relative to monitoring sites, relatively low streamflow conditions that occurred during the study, and the limited number and range of streamflow measurements. However, the computed streamflow statistics are considered the best possible estimates given available datasets in the remote study area. Streamflow measurements over a wider range of hydrologic and climatic conditions would improve the relations between streamflow characteristics at monitoring and index sites. Additionally, field surveys are needed to verify if the streamflows selected for the water rights claims are sufficient for maintaining outstanding remarkable values in the Wild and Scenic rivers included in the study.
Dash, R.G.; Edelmann, P.R.
1997-01-01
Traveltime and gains and losses within a stream are important basic characteristics of streamflow. The lower Purgatoire River flows more than 160 river miles from Trinidad to the Arkansas River near Las Animas. A better knowledge of streamflow traveltime and streamflow gains and losses along the lower Purgatoire River would enable more informed management decisions about the availability of water supplies for irrigation use in southeastern Colorado. In 1994-95, the U.S.\\x11Geological Survey, in cooperation with the Purgatoire River Water Conservancy District and the Arkansas River Compact Administration, evaluated streamflow traveltime and estimated streamflow gains and losses using historical surface-water records. Traveltime analyses were used along the lower Purgatoire River to determine when streamflows would arrive at selected downstream sites. The substantial effects of diversions for irrigation and unmeasured return flows in the most upstream reach of the river prevented the tracking of streamflow through reach\\x111. Therefore, the estimation of streamflow traveltime for the 60.6 miles of river downstream from Trinidad could not be made.Hourly streamflow data from 1990 through 1994 were used to estimate traveltimes of more than 30 streamflow events for about 100 miles of the lower Purgatoire River. In the middle reach of the river, the traveltime of streamflow for the 40.1\\x11miles ranged from about 11 to about 47\\x11hours, and in the lower reach of the river, traveltime for the 58.5 miles ranged from about 6 to about 61 hours.Traveltime in the river reaches generally increased as streamflow decreased, but also varied for a specific streamflow in both reaches. Streamflow gains and losses were estimated using daily streamflow data at the upstream and downstream sites, available tributary inflow data, and daily diversion data. Differences between surface-water inflows and surface-water outflows in a reach determined the quantity of water gained or lost. In the most upstream reach of the river near Trinidad, difficulties in establishing streamflow traveltimes prevented the estimation of streamflow gains or losses. From 1984 through 1992, more than 2,900 daily estimates of streamflow gains or losses were made for the last 100\\x11miles of the lower Purgatoire River that indicated daily gains and losses in streamflow were common during all four seasons of the year. Although some large daily streamflow gains and losses were computed, most daily estimates indicated small gains and losses in streamflow. The daily median streamflow gain or loss for the middle reach of the river was close to zero during every season, whereas median values for the lower most reach of the river indicated a daily gain in streamflow during every season.
User’s guide for the Delaware River Basin Streamflow Estimator Tool (DRB-SET)
Stuckey, Marla H.; Ulrich, James E.
2016-06-09
IntroductionThe Delaware River Basin Streamflow Estimator Tool (DRB-SET) is a tool for the simulation of streamflow at a daily time step for an ungaged stream location in the Delaware River Basin. DRB-SET was developed by the U.S. Geological Survey (USGS) and funded through WaterSMART as part of the National Water Census, a USGS research program on national water availability and use that develops new water accounting tools and assesses water availability at the regional and national scales. DRB-SET relates probability exceedances at a gaged location to those at an ungaged stream location. Once the ungaged stream location has been identified by the user, an appropriate streamgage is automatically selected in DRB-SET using streamflow correlation (map correlation method). Alternately, the user can manually select a different streamgage or use the closest streamgage. A report file is generated documenting the reference streamgage and ungaged stream location information, basin characteristics, any warnings, baseline (minimally altered) and altered (affected by regulation, diversion, mining, or other anthropogenic activities) daily mean streamflow, and the mean and median streamflow. The estimated daily flows for the ungaged stream location can be easily exported as a text file that can be used as input into a statistical software package to determine additional streamflow statistics, such as flow duration exceedance or streamflow frequency statistics.
Progress report on daily flow-routing simulation for the Carson River, California and Nevada
Hess, G.W.
1996-01-01
A physically based flow-routing model using Hydrological Simulation Program-FORTRAN (HSPF) was constructed for modeling streamflow in the Carson River at daily time intervals as part of the Truckee-Carson Program of the U.S. Geological Survey (USGS). Daily streamflow data for water years 1978-92 for the mainstem river, tributaries, and irrigation ditches from the East Fork Carson River near Markleeville and West Fork Carson River at Woodfords down to the mainstem Carson River at Fort Churchill upstream from Lahontan Reservoir were obtained from several agencies and were compiled into a comprehensive data base. No previous physically based flow-routing model of the Carson River has incorporated multi-agency streamflow data into a single data base and simulated flow at a daily time interval. Where streamflow data were unavailable or incomplete, hydrologic techniques were used to estimate some flows. For modeling purposes, the Carson River was divided into six segments, which correspond to those used in the Alpine Decree that governs water rights along the river. Hydraulic characteristics were defined for 48 individual stream reaches based on cross-sectional survey data obtained from field surveys and previous studies. Simulation results from the model were compared with available observed and estimated streamflow data. Model testing demonstrated that hydraulic characteristics of the Carson River are adequately represented in the models for a range of flow regimes. Differences between simulated and observed streamflow result mostly from inadequate data characterizing inflow and outflow from the river. Because irrigation return flows are largely unknown, irrigation return flow percentages were used as a calibration parameter to minimize differences between observed and simulated streamflows. Observed and simulated streamflow were compared for daily periods for the full modeled length of the Carson River and for two major subreaches modeled with more detailed input data. Hydrographs and statistics presented in this report describe these differences. A sensitivity analysis of four estimated components of the hydrologic system evaluated which components were significant in the model. Estimated ungaged tributary streamflow is not a significant component of the model during low runoff, but is significant during high runoff. The sensitivity analysis indicates that changes in the estimated irrigation diversion and estimated return flow creates a noticeable change in the statistics. The modeling for this study is preliminary. Results of the model are constrained by current availability and accuracy of observed hydrologic data. Several inflows and outflows of the Carson River are not described by time-series data and therefore are not represented in the model.
Sun, Wenchao; Ishidaira, Hiroshi; Bastola, Satish; Yu, Jingshan
2015-05-01
Lacking observation data for calibration constrains applications of hydrological models to estimate daily time series of streamflow. Recent improvements in remote sensing enable detection of river water-surface width from satellite observations, making possible the tracking of streamflow from space. In this study, a method calibrating hydrological models using river width derived from remote sensing is demonstrated through application to the ungauged Irrawaddy Basin in Myanmar. Generalized likelihood uncertainty estimation (GLUE) is selected as a tool for automatic calibration and uncertainty analysis. Of 50,000 randomly generated parameter sets, 997 are identified as behavioral, based on comparing model simulation with satellite observations. The uncertainty band of streamflow simulation can span most of 10-year average monthly observed streamflow for moderate and high flow conditions. Nash-Sutcliffe efficiency is 95.7% for the simulated streamflow at the 50% quantile. These results indicate that application to the target basin is generally successful. Beyond evaluating the method in a basin lacking streamflow data, difficulties and possible solutions for applications in the real world are addressed to promote future use of the proposed method in more ungauged basins. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Relation of nitrate concentrations to baseflow in the Raccoon River, Iowa
Schilling, K.E.; Lutz, D.S.
2004-01-01
Excessive nitrate-nitrogen (nitrate) export from the Raccoon River in west central Iowa is an environmental concern to downstream receptors. The 1972 to 2000 record of daily streamflow and the results from 981 nitrate measurements were examined to describe the relation of nitrate to streamflow in the Raccoon River. No long term trends in streamflow and nitrate concentrations were noted in the 28-year record. Strong seasonal patterns were evident in nitrate concentrations, with higher concentrations occurring in spring and fall. Nitrate concentrations were linearly related to streamflow at daily, monthly, seasonal, and annual time scales. At all time scales evaluated, the relation was improved when baseflow was used as the discharge variable instead of total streamflow. Nitrate concentrations were found to be highly stratified according to flow, but there was little relation of nitrate to streamflow within each flow range. Simple linear regression models developed to predict monthly mean nitrate concentrations explained as much as 76 percent of the variability in the monthly nitrate concentration data for 2001. Extrapolation of current nitrate baseflow relations to historical conditions in the Raccoon River revealed that increasing baseflow over the 20th century could account for a measurable increase in nitrate concentrations.
Determination of streamflow of the Arkansas River near Bentley in south-central Kansas
Perry, Charles A.
2012-01-01
The Kansas Department of Agriculture, Division of Water Resources, requires that the streamflow of the Arkansas River just upstream from Bentley in south-central Kansas be measured or calculated before groundwater can be pumped from the well field. When the daily streamflow of the Arkansas River near Bentley is less than 165 cubic feet per second (ft3/s), pumping must be curtailed. Daily streamflow near Bentley was calculated by determining the relations between streamflow data from two reference streamgages with a concurrent record of 24 years, one located 17.2 miles (mi) upstream and one located 10.9 mi downstream, and streamflow at a temporary gage located just upstream from Bentley (Arkansas River near Bentley, Kansas). Flow-duration curves for the two reference streamgages indicate that during 1988?2011, the mean daily streamflow was less than 165 ft3/s 30 to 35 percent of the time. During extreme low-flow (drought) conditions, the reach of the Arkansas River between Hutchinson and Maize can lose flow to the adjacent alluvial aquifer, with streamflow losses as much as 1.6 cubic feet per second per mile. Three models were developed to calculate the streamflow of the Arkansas River near Bentley, Kansas. The model chosen depends on the data available and on whether the reach of the Arkansas River between Hutchinson and Maize is gaining or losing groundwater from or to the adjacent alluvial aquifer. The first model was a pair of equations developed from linear regressions of the relation between daily streamflow data from the Bentley streamgage and daily streamflow data from either the Arkansas River near Hutchinson, Kansas, station (station number 07143330) or the Arkansas River near Maize, Kansas, station (station number 07143375). The standard error of the Hutchinson-only equation was 22.8 ft3/s, and the standard error of the Maize-only equation was 22.3 ft3/s. The single-station model would be used if only one streamgage was available. In the second model, the flow gradient between the streamflow near Hutchinson and the streamflow near Maize was used to calculate the streamflow at the Bentley streamgage. This equation resulted in a standard error of 26.7 ft3/s. In the third model, a multiple regression analysis between both the daily streamflow of the Arkansas River near Hutchinson, Kansas, and the daily streamflow of the Arkansas River near Maize, Kansas, was used to calculate the streamflow at the Bentley streamgage. The multiple regression equation had a standard error of 21.2 ft3/s, which was the smallest of the standard errors for all the models. An analysis of the number of low-flow days and the number of days when the reach between Hutchinson and Maize loses flow to the adjacent alluvial aquifer indicates that the long-term trend is toward fewer days of losing conditions. This trend may indicate a long-term increase in water levels in the alluvial aquifer, which could be caused by one or more of several conditions, including an increase in rainfall, a decrease in pumping, a decrease in temperature, and an increase in streamflow upstream from the Hutchinson-to-Maize reach of the Arkansas River.
Ryberg, Karen R.; Vecchia, Aldo V.
2012-01-01
Hydrologic time series data and associated anomalies (multiple components of the original time series representing variability at longer-term and shorter-term time scales) are useful for modeling trends in hydrologic variables, such as streamflow, and for modeling water-quality constituents. An R package, called waterData, has been developed for importing daily hydrologic time series data from U.S. Geological Survey streamgages into the R programming environment. In addition to streamflow, data retrieval may include gage height and continuous physical property data, such as specific conductance, pH, water temperature, turbidity, and dissolved oxygen. The package allows for importing daily hydrologic data into R, plotting the data, fixing common data problems, summarizing the data, and the calculation and graphical presentation of anomalies.
Burns, Douglas A.; Gazoorian, Christopher L.
2015-01-01
Natural discharge at the Mount Marion streamgage was estimated by summing the natural discharge estimated for the Coldbrook streamgage and the discharge estimated for the intervening basin area through application of the New York Streamflow Estimation Tool, recently developed for estimating unaltered streamflow at ungaged locations in the State. Estimates of natural daily discharge at the Mount Marion streamgage were about three times greater than gaged daily discharge throughout the moderate- to low-flow range from October 1, 1970, to September 30, 2012, the period of record for full water years at this streamgage. The relative difference between the two discharge time series declined as flow increased beyond the moderate range, but gaged daily discharge was still 25 to 43 percent less than estimated natural daily discharge for the high-flow metrics calculated in this analysis, and the mean relative difference was 43 percent for the annual 1-day maximum discharge. Overall, these estimates of natural discharge reflect the absence of effects of the Shandaken Tunnel and Ashokan Reservoir on flows in the Esopus Creek over broad time frames. However, caution is warranted if one is attempting to apply the natural estimates at short time scales because the regression prediction intervals indicate that uncertainty at a daily time step ranges from about 40 to 80 percent.
Yurewicz, M.C.; Carey, W.P.; Garrett, J.W.
1988-01-01
Streamflow and water quality data were collected for three major tributaries to Reelfoot Lake, in West Tennessee, for the period October 1987 through March 1988. The data are presented in graphs and tables. Mean daily discharge data were collected at one site each in the drainage basins of North Reelfoot Creek, South Reelfoot Creek, and Running Slough. Daily mean suspended-sediment concentration data were collected at a site in the North Reelfoot Creek basin. Water quality samples were collected during storm events at the same locations that daily mean streamflow data were collected. Water quality samples were analyzed for concentrations of nutrients and triazine herbicides. Water temperature and specific conductance were measured at the time that samples were collected. (USGS)
NASA Astrophysics Data System (ADS)
Gudmundsson, Lukas; Do, Hong Xuan; Leonard, Michael; Westra, Seth
2018-04-01
This is Part 2 of a two-paper series presenting the Global Streamflow Indices and Metadata Archive (GSIM), which is a collection of daily streamflow observations at more than 30 000 stations around the world. While Part 1 (Do et al., 2018a) describes the data collection process as well as the generation of auxiliary catchment data (e.g. catchment boundary, land cover, mean climate), Part 2 introduces a set of quality controlled time-series indices representing (i) the water balance, (ii) the seasonal cycle, (iii) low flows and (iv) floods. To this end we first consider the quality of individual daily records using a combination of quality flags from data providers and automated screening methods. Subsequently, streamflow time-series indices are computed for yearly, seasonal and monthly resolution. The paper provides a generalized assessment of the homogeneity of all generated streamflow time-series indices, which can be used to select time series that are suitable for a specific task. The newly generated global set of streamflow time-series indices is made freely available with an digital object identifier at https://doi.pangaea.de/10.1594/PANGAEA.887470 and is expected to foster global freshwater research, by acting as a ground truth for model validation or as a basis for assessing the role of human impacts on the terrestrial water cycle. It is hoped that a renewed interest in streamflow data at the global scale will foster efforts in the systematic assessment of data quality and provide momentum to overcome administrative barriers that lead to inconsistencies in global collections of relevant hydrological observations.
Free internet datasets for streamflow modelling using SWAT in the Johor river basin, Malaysia
NASA Astrophysics Data System (ADS)
Tan, M. L.
2014-02-01
Streamflow modelling is a mathematical computational approach that represents terrestrial hydrology cycle digitally and is used for water resources assessment. However, such modelling endeavours require a large amount of data. Generally, governmental departments produce and maintain these data sets which make it difficult to obtain this data due to bureaucratic constraints. In some countries, the availability and quality of geospatial and climate datasets remain a critical issue due to many factors such as lacking of ground station, expertise, technology, financial support and war time. To overcome this problem, this research used public domain datasets from the Internet as "input" to a streamflow model. The intention is simulate daily and monthly streamflow of the Johor River Basin in Malaysia. The model used is the Soil and Water Assessment Tool (SWAT). As input free data including a digital elevation model (DEM), land use information, soil and climate data were used. The model was validated by in-situ streamflow information obtained from Rantau Panjang station for the year 2006. The coefficient of determination and Nash-Sutcliffe efficiency were 0.35/0.02 for daily simulated streamflow and 0.92/0.21 for monthly simulated streamflow, respectively. The results show that free data can provide a better simulation at a monthly scale compared to a daily basis in a tropical region. A sensitivity analysis and calibration procedure should be conducted in order to maximize the "goodness-of-fit" between simulated and observed streamflow. The application of Internet datasets promises an acceptable performance of streamflow modelling. This research demonstrates that public domain data is suitable for streamflow modelling in a tropical river basin within acceptable accuracy.
NASA Astrophysics Data System (ADS)
Farmer, W. H.; Archfield, S. A.; Over, T. M.; Kiang, J. E.
2015-12-01
In the United States and across the globe, the majority of stream reaches and rivers are substantially impacted by water use or remain ungaged. The result is large gaps in the availability of natural streamflow records from which to infer hydrologic understanding and inform water resources management. From basin-specific to continent-wide scales, many efforts have been undertaken to develop methods to estimate ungaged streamflow. This work applies and contrasts several statistical models of daily streamflow to more than 1,700 reference-quality streamgages across the conterminous United States using a cross-validation methodology. The variability of streamflow simulation performance across the country exhibits a pattern familiar to other continental scale modeling efforts performed for the United States. For portions of the West Coast and the dense, relatively homogeneous and humid regions of the eastern United States models produce reliable estimates of daily streamflow using many different prediction methods. Model performance for the middle portion of the United States, marked by more heterogeneous and arid conditions, and with larger contributing areas and sparser networks of streamgages, is consistently poor. A discussion of the difficulty of statistical interpolation and regionalization in these regions raises additional questions of data availability and quality, hydrologic process representation and dominance, and intrinsic variability.
NASA Astrophysics Data System (ADS)
Tanguy, M.; Prudhomme, C.; Harrigan, S.; Smith, K. A.; Parry, S.
2017-12-01
Forecasting hydrological extremes is challenging, especially at lead times over 1 month for catchments with limited hydrological memory and variable climates. One simple way to derive monthly or seasonal hydrological forecasts is to use historical climate data to drive hydrological models using the Ensemble Streamflow Prediction (ESP) method. This gives a range of possible future streamflow given known initial hydrologic conditions alone. The degree of skill of ESP depends highly on the forecast initialisation month and catchment type. Using dynamic rainfall forecasts as driving data instead of historical data could potentially improve streamflow predictions. A lot of effort is being invested within the meteorological community to improve these forecasts. However, while recent progress shows promise (e.g. NAO in winter), the skill of these forecasts at monthly to seasonal timescales is generally still limited, and the extent to which they might lead to improved hydrological forecasts is an area of active research. Additionally, these meteorological forecasts are currently being produced at 1 month or seasonal time-steps in the UK, whereas hydrological models require forcings at daily or sub-daily time-steps. Keeping in mind these limitations of available rainfall forecasts, the objectives of this study are to find out (i) how accurate monthly dynamical rainfall forecasts need to be to outperform ESP, and (ii) how the method used to disaggregate monthly rainfall forecasts into daily rainfall time series affects results. For the first objective, synthetic rainfall time series were created by increasingly degrading observed data (proxy for a `perfect forecast') from 0 % to +/-50 % error. For the second objective, three different methods were used to disaggregate monthly rainfall data into daily time series. These were used to force a simple lumped hydrological model (GR4J) to generate streamflow predictions at a one-month lead time for over 300 catchments representative of the range of UK's hydro-climatic conditions. These forecasts were then benchmarked against the traditional ESP method. It is hoped that the results of this work will help the meteorological community to identify where to focus their efforts in order to increase the usefulness of their forecasts within hydrological forecasting systems.
New method for calculating a mathematical expression for streamflow recession
Rutledge, Albert T.
1991-01-01
An empirical method has been devised to calculate the master recession curve, which is a mathematical expression for streamflow recession during times of negligible direct runoff. The method is based on the assumption that the storage-delay factor, which is the time per log cycle of streamflow recession, varies linearly with the logarithm of streamflow. The resulting master recession curve can be nonlinear. The method can be executed by a computer program that reads a data file of daily mean streamflow, then allows the user to select several near-linear segments of streamflow recession. The storage-delay factor for each segment is one of the coefficients of the equation that results from linear least-squares regression. Using results for each recession segment, a mathematical expression of the storage-delay factor as a function of the log of streamflow is determined by linear least-squares regression. The master recession curve, which is a second-order polynomial expression for time as a function of log of streamflow, is then derived using the coefficients of this function.
WaterWatch - Maps, graphs, and tables of current, recent, and past streamflow conditions
Jian, Xiaodong; Wolock, David; Lins, Harry F.
2008-01-01
WaterWatch (http://water.usgs.gov/waterwatch/) is a U.S. Geological Survey (USGS) World Wide Web site that displays maps, graphs, and tables describing real-time, recent, and past streamflow conditions for the United States. The real-time information generally is updated on an hourly basis. WaterWatch provides streamgage-based maps that show the location of more than 3,000 long-term (30 years or more) USGS streamgages; use colors to represent streamflow conditions compared to historical streamflow; feature a point-and-click interface allowing users to retrieve graphs of stream stage (water elevation) and flow; and highlight locations where extreme hydrologic events, such as floods and droughts, are occurring.The streamgage-based maps show streamflow conditions for real-time, average daily, and 7-day average streamflow. The real-time streamflow maps highlight flood and high flow conditions. The 7-day average streamflow maps highlight below-normal and drought conditions.WaterWatch also provides hydrologic unit code (HUC) maps. HUC-based maps are derived from the streamgage-based maps and illustrate streamflow conditions in hydrologic regions. These maps show average streamflow conditions for 1-, 7-, 14-, and 28-day periods, and for monthly average streamflow; highlight regions of low flow or hydrologic drought; and provide historical runoff and streamflow conditions beginning in 1901.WaterWatch summarizes streamflow conditions in a region (state or hydrologic unit) in terms of the long-term typical condition at streamgages in the region. Summary tables are provided along with time-series plots that depict variations through time. WaterWatch also includes tables of current streamflow information and locations of flooding.
ModABa Model: Annual Flow Duration Curves Assessment in Ephemeral Basins
NASA Astrophysics Data System (ADS)
Pumo, Dario; Viola, Francesco; Noto, Leonardo V.
2013-04-01
A representation of the streamflow regime for a river basin is required for a variety of hydrological analyses and engineering applications, from the water resource allocation and utilization to the environmental flow management. The flow duration curve (FDC) represents a comprehensive signature of temporal runoff variability often used to synthesize catchment rainfall-runoff responses. Several models aimed to the theoretical reconstruction of the FDC have been recently developed under different approaches, and a relevant scientific knowledge specific to this topic has been already acquired. In this work, a new model for the probabilistic characterization of the daily streamflows in perennial and ephemeral catchments is introduced. The ModABa model (MODel for Annual flow duration curves assessment in intermittent BAsins) can be thought as a wide mosaic whose tesserae are frameworks, models or conceptual schemes separately developed in different recent studies. Such tesserae are harmoniously placed and interconnected, concurring together towards a unique final aim that is the reproduction of the FDC of daily streamflows in a river basin. Two separated periods within the year are firstly identified: a non-zero period, typically characterized by significant streamflows, and a dry period, that, in the cases of ephemeral basins, is the period typically characterized by absence of streamflow. The proportion of time the river is dry, providing an estimation of the probability of zero flow occurring, is empirically estimated. Then, an analysis concerning the non-zero period is performed, considering the streamflow disaggregated into a slow subsuperficial component and a fast superficial component. A recent analytical model is adopted to derive the non zero FDC relative to the subsuperficial component; this last is considered to be generated by the soil water excess over the field capacity in the permeable portion of the basin. The non zero FDC relative to the fast streamflow component is directly derived from the precipitation duration curve through a simple filter model. The fast component of streamflow is considered to be formed by two contributions that are the entire amount of rainfall falling onto the impervious portion of the basin and the excess of rainfall over a fixed threshold, defining heavy rain events, falling onto the permeable portion. The two obtained FDCs are then overlapped, providing a unique non-zero FDC relative to the total streamflow. Finally, once the probability that the river is dry and the non zero FDC are known, the annual FDC of the daily total streamflow is derived applying the theory of total probability. The model is calibrated on a small catchment with ephemeral streamflows using a long period of daily precipitation, temperature and streamflow measurements, and it is successively validated in the same basin using two different time periods. The high model performances obtained in both the validation periods, demonstrate how the model, once calibrated, is able to accurately reproduce the empirical FDC starting from easily derivable parameters arising from a basic ecohydrological knowledge of the basin and commonly available climatic data such as daily precipitation and temperatures. In this sense, the model reveals itself as a valid tool for streamflow predictions in ungauged basins.
Chase, K.J.
2011-01-01
This report documents the development of a precipitation-runoff model for the South Fork Flathead River Basin, Mont. The Precipitation-Runoff Modeling System model, developed in cooperation with the Bureau of Reclamation, can be used to simulate daily mean unregulated streamflow upstream and downstream from Hungry Horse Reservoir for water-resources planning. Two input files are required to run the model. The time-series data file contains daily precipitation data and daily minimum and maximum air-temperature data from climate stations in and near the South Fork Flathead River Basin. The parameter file contains values of parameters that describe the basin topography, the flow network, the distribution of the precipitation and temperature data, and the hydrologic characteristics of the basin soils and vegetation. A primary-parameter file was created for simulating streamflow during the study period (water years 1967-2005). The model was calibrated for water years 1991-2005 using the primary-parameter file. This calibration was further refined using snow-covered area data for water years 2001-05. The model then was tested for water years 1967-90. Calibration targets included mean monthly and daily mean unregulated streamflow upstream from Hungry Horse Reservoir, mean monthly unregulated streamflow downstream from Hungry Horse Reservoir, basin mean monthly solar radiation and potential evapotranspiration, and daily snapshots of basin snow-covered area. Simulated streamflow generally was in better agreement with observed streamflow at the upstream gage than at the downstream gage. Upstream from the reservoir, simulated mean annual streamflow was within 0.0 percent of observed mean annual streamflow for the calibration period and was about 2 percent higher than observed mean annual streamflow for the test period. Simulated mean April-July streamflow upstream from the reservoir was about 1 percent lower than observed streamflow for the calibration period and about 4 percent higher than observed for the test period. Downstream from the reservoir, simulated mean annual streamflow was 17 percent lower than observed streamflow for the calibration period and 12 percent lower than observed streamflow for the test period. Simulated mean April-July streamflow downstream from the reservoir was 13 percent lower than observed streamflow for the calibration period and 6 percent lower than observed streamflow for the test period. Calibrating to solar radiation, potential evapotranspiration, and snow-covered area improved the model representation of evapotranspiration, snow accumulation, and snowmelt processes. Simulated basin mean monthly solar radiation values for both the calibration and test periods were within 9 percent of observed values except during the month of December (28 percent different). Simulated basin potential evapotranspiration values for both the calibration and test periods were within 10 percent of observed values except during the months of January (100 percent different) and February (13 percent different). The larger percent errors in simulated potential evaporation occurred in the winter months when observed potential evapotranspiration values were very small; in January the observed value was 0.000 inches and in February the observed value was 0.009 inches. Simulated start of melting of the snowpack occurred at about the same time as observed start of melting. The simulated snowpack accumulated to 90-100 percent snow-covered area 1 to 3 months earlier than observed snowpack. This overestimated snowpack during the winter corresponded to underestimated streamflow during the same period. In addition to the primary-parameter file, four other parameter files were created: for a "recent" period (1991-2005), a historical period (1967-90), a "wet" period (1989-97), and a "dry" period (1998-2005). For each data file of projected precipitation and air temperature, a single parameter file can be used to simulate a s
Asquith, William H.; Vrabel, Joseph; Roussel, Meghan C.
2007-01-01
Analysts and managers of surface-water resources might have interest in the zero-flow potential for U.S.Geological Survey (USGS) streamflow-gaging stations in Texas. The USGS, in cooperation with the Texas Commission on Environmental Quality, initiated a data and reporting process to generate summaries of percentages of zero daily mean streamflow for 712 USGS streamflow-gaging stations in Texas. A summary of the percentages of zero daily mean streamflow for most active and inactive, continuous-record gaging stations in Texas provides valuable information by conveying the historical perspective for zero-flow potential for the watershed. The summaries of percentages of zero daily mean streamflow for each station are graphically depicted using two thematic perspectives: annual and monthly. The annual perspective consists of graphs of annual percentages of zero streamflow by year with the addition of lines depicting the mean and median annual percentage of zero streamflow. Monotonic trends in the percentages of zero streamflow also are identified using Kendall's T. The monthly perspective consists of graphs of the percentage of zero streamflow by month with lines added to indicate the mean and median monthly percentage of zero streamflow. One or more summaries could be used in a watershed, river basin, or other regional context by analysts and managers of surface-water resources to guide scientific, regulatory, or other inquiries of zero-flow or other low-flow conditions in Texas.
Multi-year encoding of daily rainfall and streamflow via the fractal-multifractal method
NASA Astrophysics Data System (ADS)
Puente, C. E.; Maskey, M.; Sivakumar, B.
2017-12-01
A deterministic geometric approach, the fractal-multifractal (FM) method, which has been proven to be faithful in encoding daily geophysical sets over a year, is used to describe records over multiple years at a time. Looking for FM parameter trends over longer periods, the present study shows FM descriptions of daily rainfall and streamflow gathered over five consecutive years optimizing deviations on accumulated sets. The results for 100 and 60 sets of five years for rainfall streamflow, respectively, near Sacramento, California illustrate that: (a) encoding of both types of data sets may be accomplished with relatively small errors; and (b) predicting the geometry of both variables appears to be possible, even five years ahead, training neural networks on the respective FM parameters. It is emphasized that the FM approach not only captures the accumulated sets over successive pentades but also preserves other statistical attributes including the overall "texture" of the records.
Streamflow record extension for selected streams in the Susitna River Basin, Alaska
Curran, Janet H.
2012-01-01
Daily streamflow records for water years 1950–2010 in the Susitna River Basin range in length from 4 to 57 years, and many are distributed within that period in a way that might not adequately represent long-term streamflow conditions. Streamflow in the basin is affected by the Pacific Decadal Oscillation (PDO), a multi-decadal climate pattern that shifted from a cool phase to a warm phase in 1976. Records for many streamgages in the basin fell mostly within one phase of the PDO, such that monthly and annual statistics from observed records might not reflect streamflow conditions over a longer period. Correlations between daily discharge values sufficed for extending streamflow records at 11 of the 14 streamgages in the basin on the basis of relatively long-term records for one or more of the streamgages within the basin, or one outside the basin, that were defined as index stations. Streamflow at the index stations was hydrologically responsive to glacier melt and snowmelt, and correlated well with flow from similar high-elevation, glaciated basins, but flow in low-elevation basins without glaciers could not be correlated to flow at any of the index stations. Kendall-Theil Robust Line multi-segment regression equations developed for one or more index stations were used to extend daily discharge values to the full 61-year period for all 11 streamgages. Monthly and annual statistics prepared for the extended records show shifts in timing of breakup and freeze-up and magnitude of snowmelt peaks largely predicted by the PDO phase.
Gazoorian, Christopher L.
2015-01-01
A graphical user interface, with an integrated spreadsheet summary report, has been developed to estimate and display the daily mean streamflows and statistics and to evaluate different water management or water withdrawal scenarios with the estimated monthly data. This package of regression equations, U.S. Geological Survey streamgage data, and spreadsheet application produces an interactive tool to estimate an unaltered daily streamflow hydrograph and streamflow statistics at ungaged sites in New York. Among other uses, the New York Streamflow Estimation Tool can assist water managers with permitting water withdrawals, implementing habitat protection, estimating contaminant loads, or determining the potential affect from chemical spills.
Kuhn, Gerhard
1988-01-01
The U.S. Geological Survey 's precipitation-runoff modeling system was calibrated for this study by using daily streamflow data for April through September, 1980 and 1981, from the Williams Draw basin in Jackson County, Colorado. The calibrated model then was verified by using daily streamflow data for April through September, 1982 and 1983. Transferability of the model was tested by application to adjoining Bush Draw basin by using daily streamflow data for April through September, 1981 through 1983. Four model parameters were optimized in the calibration: (1) BST, base air temperature used to determine the form of precipitation (rain, snow, or a mixture); (2) SMAX, maximum available water-holding capacity of the soil zone; (3) TRNCF, transmission coefficient for the vegetation canopy over the snowpack; and (4) DSCOR, daily precipitation correction factor for snow. For calibration and verification, volume and timing of simulated streamflow were reasonably close to recorded streamflow; differences were least during years that had considerable snowpack accumulation and were most during years that had minimal or no snowpack accumulation. Calibration and optimization of parameters were facilitated by snowpack water-equivalent data. Application of the model to Bush Draw basin to test for transferability indicated inaccurate results in simulation of streamflow volume. Weighted values of SMAX, TRNCF, and DSCOR from the calibration basin were used for Bush Draw. The inadequate results obtained by use of weighted parameters indicate that snowpack water-equivalent data are needed for successful application of the precipitation-runoff modeling system in this area, because frequent windy conditions cause variations in snowpack accumulation. (USGS)
Aerial photography provides a historical vehicle for determining long term urban landscape change and, with concurrent daily streamflow and precipitation records, allows the historical relationship of impervious surfaces and streamflow to be explored. Impervious surface area in ...
Aerial photography provides a historical vehicle for determining long term urban landscape change and, with concurrent daily streamflow and precipitation records, allows the historical relationship of impervious surfaces and streamflow to be explored. Impervious surfac...
Stone, M.A.J.; Mann, Larry J.; Kjelstrom, L.C.
1993-01-01
Statistical summaries and graphs of streamflow data were prepared for 13 gaging stations with 5 or more years of continuous record on and near the Idaho National Engineering Laboratory. Statistical summaries of streamflow data for the Big and Little Lost Rivers and Birch Creek were analyzed as a requisite for a comprehensive evaluation of the potential for flooding of facilities at the Idaho National Engineering Laboratory. The type of statistical analyses performed depended on the length of streamflow record for a gaging station. Streamflow statistics generated for stations with 5 to 9 years of record were: (1) magnitudes of monthly and annual flows; (2) duration of daily mean flows; and (3) maximum, median, and minimum daily mean flows. Streamflow statistics generated for stations with 10 or more years of record were: (1) magnitudes of monthly and annual flows; (2) magnitudes and frequencies of daily low, high, instantaneous peak (flood frequency), and annual mean flows; (3) duration of daily mean flows; (4) exceedance probabilities of annual low, high, instantaneous peak, and mean annual flows; (5) maximum, median, and minimum daily mean flows; and (6) annual mean and mean annual flows.
Reconstruction of missing daily streamflow data using dynamic regression models
NASA Astrophysics Data System (ADS)
Tencaliec, Patricia; Favre, Anne-Catherine; Prieur, Clémentine; Mathevet, Thibault
2015-12-01
River discharge is one of the most important quantities in hydrology. It provides fundamental records for water resources management and climate change monitoring. Even very short data-gaps in this information can cause extremely different analysis outputs. Therefore, reconstructing missing data of incomplete data sets is an important step regarding the performance of the environmental models, engineering, and research applications, thus it presents a great challenge. The objective of this paper is to introduce an effective technique for reconstructing missing daily discharge data when one has access to only daily streamflow data. The proposed procedure uses a combination of regression and autoregressive integrated moving average models (ARIMA) called dynamic regression model. This model uses the linear relationship between neighbor and correlated stations and then adjusts the residual term by fitting an ARIMA structure. Application of the model to eight daily streamflow data for the Durance river watershed showed that the model yields reliable estimates for the missing data in the time series. Simulation studies were also conducted to evaluate the performance of the procedure.
Effect of monthly areal rainfall uncertainty on streamflow simulation
NASA Astrophysics Data System (ADS)
Ndiritu, J. G.; Mkhize, N.
2017-08-01
Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic monthly rainfalls were 86 and 90% of the mean naturalised streamflow. In calibration, 33% of the naturalised flow located within the streamflow ranges with historic rainfall simulations and using stochastic rainfalls increased this to 66%. In validation the respective percentages of naturalised flows located within the simulated streamflow ranges were 32 and 72% respectively. The analysis reveals that monthly areal rainfall uncertainty is significant and incorporating it into streamflow simulation would add validity to the results.
Simulation of streamflow in small drainage basins in the southern Yampa River basin, Colorado
Parker, R.S.; Norris, J.M.
1989-01-01
Coal mining operations in northwestern Colorado commonly are located in areas that have minimal available water-resource information. Drainage-basin models can be a method for extending water-resource information to include periods for which there are no records or to transfer the information to areas that have no streamflow-gaging stations. To evaluate the magnitude and variability of the components of the water balance in the small drainage basins monitored, and to provide some method for transfer of hydrologic data, the U.S. Geological Survey 's Precipitation-Runoff Modeling System was used for small drainage basins in the southern Yampa River basin to simulate daily mean streamflow using daily precipitation and air-temperature data. The study area was divided into three hydrologic regions, and in each of these regions, three drainage basins were monitored. Two of the drainage basins in each region were used to calibrate the Precipitation-Runoff Modeling System. The model was not calibrated for the third drainage basin in each region; instead, parameter values were transferred from the model that was calibrated for the two drainage basins. For all of the drainage basins except one, period of record used for calibration and verification included water years 1976-81. Simulated annual volumes of streamflow for drainage basins used in calibration compared well with observed values; individual hydrographs indicated timing differences between the observed and simulated daily mean streamflow. Observed and simulated annual average streamflows compared well for the periods of record, but values of simulated high and low streamflows were different than observed values. Similar results were obtained when calibrated model parameter values were transferred to drainage basins that were uncalibrated. (USGS)
Stamey, Timothy C.
1998-01-01
Simple and reliable methods for estimating hourly streamflow are needed for the calibration and verification of a Chattahoochee River basin model between Buford Dam and Franklin, Ga. The river basin model is being developed by Georgia Department of Natural Resources, Environmental Protection Division, as part of their Chattahoochee River Modeling Project. Concurrent streamflow data collected at 19 continuous-record, and 31 partial-record streamflow stations, were used in ordinary least-squares linear regression analyses to define estimating equations, and in verifying drainage-area prorations. The resulting regression or drainage-area ratio estimating equations were used to compute hourly streamflow at the partial-record stations. The coefficients of determination (r-squared values) for the regression estimating equations ranged from 0.90 to 0.99. Observed and estimated hourly and daily streamflow data were computed for May 1, 1995, through October 31, 1995. Comparisons of observed and estimated daily streamflow data for 12 continuous-record tributary stations, that had available streamflow data for all or part of the period from May 1, 1995, to October 31, 1995, indicate that the mean error of estimate for the daily streamflow was about 25 percent.
Spatiotemporal tracer variability in glacier melt and its influence on hydrograph separation
NASA Astrophysics Data System (ADS)
Schmieder, Jan; Marke, Thomas; Strasser, Ulrich
2017-04-01
Glaciers are important seasonal water contributors in many mountainous regions. Knowledge on the timing and amount of glacier melt water is crucial for water resources management, especially in downstream regions where the water is needed (hydropower, drinking water) or where it represents a potential risk (drought, flood). This becomes even more relevant in a changing climate. Environmental tracers are a useful tool in the assessment of ice water resources, because they provide information about the sources, flow paths and traveling times of water contributing to streamflow at the catchment scale. Hydrometric and meteorological measurements combined with tracer analyses help to unravel streamflow composition and improve the understanding of hydroclimatological processes. Empirical studies on runoff composition are necessary to parameterize and validate hydrological models in a process-oriented manner, rather than comparing total measured and simulated runoff only. In the present study three approaches of hydrograph separation are compared to decide which sampling frequency is required to capture the spatiotemporal variability of glacier melt, and to draw implications for future studies of streamflow partitioning. Therefore glacier melt contributions to a proglacial stream at the sub-daily, daily, and seasonal scale were estimated using electrical conductivity and oxygen-18 as tracers. The field work was conducted during December 2015 and September 2016 in the glaciated (34%) high-elevation catchment of the Hochjochbach, a small sub-basin (17 km2) of the Oetztaler Ache river in the Austrian Alps, ranging from 2400 to 3500 m a.s.l. in elevation. Hydroclimatological data was provided by an automatic weather station and a streamflow gauging station equipped with a pressure transducer. Water samples of streamflow, glacier melt, and rain were collected throughout the winter period (December to March) and the ablation season (July to September). In the proposed contribution, the experimental setup and preliminary results are described and discussed for the three approaches (sub-daily, daily, seasonal) of three-component hydrograph separations (glacier melt, rain, and groundwater).
Zarriello, Phillip J.; Bent, Gardner C.
2004-01-01
The 36.1-square-mile UsquepaugQueen River Basin in south-central Rhode Island is an important water resource. Streamflow records indicate that withdrawals may have diminished flows enough to affect aquatic habitat. Concern over the effect of withdrawals on streamflow and aquatic habitat prompted the development of a Hydrologic Simulation ProgramFORTRAN (HSPF) model to evaluate the water-management alternatives and land-use change in the basin. Climate, streamflow, and water-use data were collected to support the model development. A logistic-regression equation was developed for long-term simulations to predict the likelihood of irrigation, the primary water use in the basin, from antecedent potential evapotranspiration and precipitation for generating irrigation demands. The HSPF model represented the basin by 13 pervious-area and 2 impervious-area land-use segments and 20 stream reaches. The model was calibrated to the period January 1, 2000 to September 30, 2001, at three continuous streamflow-gaging stations that monitor flow from 10, 54, and 100 percent of the basin drainage area. Hydrographs and flow-duration curves of observed and simulated discharges, along with statistics compiled for various model-fit metrics, indicate a satisfactory model performance. The calibrated HSPF model was modified to evaluate streamflow (1) under no withdrawals to streamflow under current (200001) withdrawal conditions under long-term (19602001) climatic conditions, (2) under withdrawals by the former Ladd School water-supply wells, and (3) under fully developed land use. The effects of converting from direct-stream withdrawals to ground-water withdrawals were evaluated outside of the HSPF model by use of the STRMDEPL program, which calculates the time delayed response of ground-water withdrawals on streamflow depletion. Simulated effects of current withdrawals relative to no withdrawals indicate about a 20-percent decrease in the lowest mean daily streamflows at the basin outlet, but withdrawals have little effect on flows that are exceeded less than about 90 percent of the time. Tests of alternative model structures to evaluate model uncertainty indicate that the lowest mean daily flows ranged between 3 and 5 cubic feet per second (ft3/s) without withdrawals and 2.2 to 4 ft3/s with withdrawals. Changes in the minimum daily streamflows are more pronounced, however; at the upstream streamflow-gaging station, a minimum daily flow of 0.2 ft3/s was sustained without withdrawals, but simulations with withdrawals indicate that the reach would stop flowing part of a day about 5 percent of the time. The effect on streamflow of potential ground-water withdrawals of 0.20, 0.90, and 1.78 million gallons per day (Mgal/d) at the former Ladd School near the central part of the basin were evaluated. The lowest daily mean flows in model reach 3, the main stem of the Queen River closest to the pumped wells, decreased by about 50 percent for withdrawals of 0.20 Mgal/d (from about 0.4 to 0.2 ft3/s) in comparison to current withdrawals. Reach 3 would occasionally stop flowing during part of the day at the 0.20-Mgal/d withdrawal rate because of diurnal fluctuation in streamflow. The higher withdrawal rates (0.90 and 1.78 Mgal/d) would cause reach 3 to stop flowing about 10 to 20 percent of the time, but the effects of pumping rapidly diminished downstream because of tributary inflows. Simulation results indicate little change in the annual 1-, 7-, and 30-day low flows at the 0.20 Mgal/d pumping rate, but at the 1.78 Mgal/d pumping rate, reach 3 stopped flowing for nearly a 7-day period every year and for a 30-day period about every other year. At the 0.90 Mgal/d pumping rate, reach 3 stopped flowing about every other year for a 7-day period and about once every 5 years for a 30-day period. Land-use change was simulated by converting model hydrologic-response units (HRUs) representing undeveloped areas to HRUs representing developed areas o
The effect of flow data resolution on sediment yield estimation and channel design
NASA Astrophysics Data System (ADS)
Rosburg, Tyler T.; Nelson, Peter A.; Sholtes, Joel S.; Bledsoe, Brian P.
2016-07-01
The decision to use either daily-averaged or sub-daily streamflow records has the potential to impact the calculation of sediment transport metrics and stream channel design. Using bedload and suspended load sediment transport measurements collected at 138 sites across the United States, we calculated the effective discharge, sediment yield, and half-load discharge using sediment rating curves over long time periods (median record length = 24 years) with both daily-averaged and sub-daily streamflow records. A comparison of sediment transport metrics calculated with both daily-average and sub-daily stream flow data at each site showed that daily-averaged flow data do not adequately represent the magnitude of high stream flows at hydrologically flashy sites. Daily-average stream flow data cause an underestimation of sediment transport and sediment yield (including the half-load discharge) at flashy sites. The degree of underestimation was correlated with the level of flashiness and the exponent of the sediment rating curve. No consistent relationship between the use of either daily-average or sub-daily streamflow data and the resultant effective discharge was found. When used in channel design, computed sediment transport metrics may have errors due to flow data resolution, which can propagate into design slope calculations which, if implemented, could lead to unwanted aggradation or degradation in the design channel. This analysis illustrates the importance of using sub-daily flow data in the calculation of sediment yield in urbanizing or otherwise flashy watersheds. Furthermore, this analysis provides practical charts for estimating and correcting these types of underestimation errors commonly incurred in sediment yield calculations.
Application of ANN and fuzzy logic algorithms for streamflow modelling of Savitri catchment
NASA Astrophysics Data System (ADS)
Kothari, Mahesh; Gharde, K. D.
2015-07-01
The streamflow prediction is an essentially important aspect of any watershed modelling. The black box models (soft computing techniques) have proven to be an efficient alternative to physical (traditional) methods for simulating streamflow and sediment yield of the catchments. The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years (1992-2011) rainfall and other hydrological data were considered, of which 13 years (1992-2004) was for training and rest 7 years (2005-2011) for validation of the models. The mode performance was evaluated by R, RMSE, EV, CE, and MAD statistical parameters. It was found that, ANN model performance improved with increasing input vectors. The results with fuzzy logic models predict the streamflow with single input as rainfall better in comparison to multiple input vectors. While comparing both ANN and FL algorithms for prediction of streamflow, ANN model performance is quite superior.
Simulated hydrologic response to climate change during the 21st century in New Hampshire
Bjerklie, David M.; Sturtevant, Luke P.
2018-01-24
The U.S. Geological Survey, in cooperation with the New Hampshire Department of Environmental Services and the Department of Health and Human Services, has developed a hydrologic model to assess the effects of short- and long-term climate change on hydrology in New Hampshire. This report documents the model and datasets developed by using the model to predict how climate change will affect the hydrologic cycle and provide data that can be used by State and local agencies to identify locations that are vulnerable to the effects of climate change in areas across New Hampshire. Future hydrologic projections were developed from the output of five general circulation models for two future climate scenarios. The scenarios are based on projected future greenhouse gas emissions and estimates of land-use and land-cover change within a projected global economic framework. An evaluation of the possible effect of projected future temperature on modeling of evapotranspiration is summarized to address concerns regarding the implications of the future climate on model parameters that are based on climate variables. The results of the model simulations are hydrologic projections indicating increasing streamflow across the State with large increases in streamflow during winter and early spring and general decreases during late spring and summer. Wide spatial variability in changes to groundwater recharge is projected, with general decreases in the Connecticut River Valley and at high elevations in the northern part of the State and general increases in coastal and lowland areas of the State. In general, total winter snowfall is projected to decrease across the State, but there is a possibility of increasing snow in some locations, particularly during November, February, and March. The simulated future changes in recharge and snowfall vary by watershed across the State. This means that each area of the State could experience very different changes, depending on topography or other factors. Therefore, planning for infrastructure and public safety needs to be flexible in order to address the range of possible outcomes indicated by the various model simulations. The absolute magnitude and timing of the daily streamflows, especially the larger floods, are not considered to be reliably simulated compared to changes in frequency and duration of daily streamflows and changes in accumulated monthly and seasonal streamflow volumes. Simulated current and future streamflow, groundwater recharge, and snowfall datasets include simulated data derived from the five general circulation models used in this study for a current reference time period and two future time periods. Average monthly streamflow time series datasets are provided for 27 streamgages in New Hampshire. Fourteen of the 27 streamgages associated with daily streamflow time series showed a good calibration. Average monthly groundwater recharge and snowfall time series for the same reference time period and two future time periods are also provided for each of the 467 hydrologic response units that compose the model.
Surface-Water Conditions in Georgia, Water Year 2005
Painter, Jaime A.; Landers, Mark N.
2007-01-01
INTRODUCTION The U.S. Geological Survey (USGS) Georgia Water Science Center-in cooperation with Federal, State, and local agencies-collected surface-water streamflow, water-quality, and ecological data during the 2005 Water Year (October 1, 2004-September 30, 2005). These data were compiled into layers of an interactive ArcReaderTM published map document (pmf). ArcReaderTM is a product of Environmental Systems Research Institute, Inc (ESRI?). Datasets represented on the interactive map are * continuous daily mean streamflow * continuous daily mean water levels * continuous daily total precipitation * continuous daily water quality (water temperature, specific conductance dissolved oxygen, pH, and turbidity) * noncontinuous peak streamflow * miscellaneous streamflow measurements * lake or reservoir elevation * periodic surface-water quality * periodic ecological data * historical continuous daily mean streamflow discontinued prior to the 2005 water year The map interface provides the ability to identify a station in spatial reference to the political boundaries of the State of Georgia and other features-such as major streams, major roads, and other collection stations. Each station is hyperlinked to a station summary showing seasonal and annual stream characteristics for the current year and for the period of record. For continuous discharge stations, the station summary includes a one page graphical summary page containing five graphs, a station map, and a photograph of the station. The graphs provide a quick overview of the current and period-of-record hydrologic conditions of the station by providing a daily mean discharge graph for the water year, monthly statistics graph for the water year and period of record, an annual mean streamflow graph for the period of record, an annual minimum 7-day average streamflow graph for the period of record, and an annual peak streamflow graph for the period of record. Additionally, data can be accessed through the layer's link to the National Water Inventory System Web (NWISWeb) Interface.
Flow characteristics at U.S. Geological Survey streamgages in the conterminous United States
Wolock, David
2003-01-01
This dataset represents point locations and flow characteristics for current (as of November 20, 2001) and historical U.S. Geological Survey (USGS) streamgages in the conterminous United States. The flow characteristics were computed from the daily streamflow data recorded at each streamgage for the period of record. The attributes associated with each streamgage include: Station number Station name Station latitude (decimal degrees in North American Datum of 1983, NAD 83) Station longitude (decimal degrees in NAD 83) First date (year, month, day) of streamflow data Last date (year, month, day) of streamflow data Number of days of streamflow data Minimum and maximum daily flow for the period of record (cubic feet per second) Percentiles (1, 5, 10, 20, 25, 50, 75, 80, 90, 95, 99) of daily flow for the period of record (cubic feet per second) Average and standard deviation of daily flow for the period of record (cubic feet per second) Mean annual base-flow index (BFI: see supplemental information) computed for the period of record (fraction, ranging from 0 to 1) Year-to-year standard deviation of the annual base-flow index computed for the period of record (fraction) Number of years of data used to compute the base-flow index (years) Reported drainage area (square miles) Reported contributing drainage area (square miles) National Water Information System (NWIS)-Web page URL for streamgage Hydrologic Unit Code (HUC, 8 digit) Hydrologic landscape region (HLR) River Reach File 1 (RF1) segment identification number (E2RF1##) Station numbers, names, locations, and drainage areas were acquired through the National Water Information System (NWIS)-Web (http://water.usgs.gov/nwis) on November 20, 2001. The streamflow data used to compute flow characteristics were copied from the Water server (water.usgs.gov:/www/htdocs/nwisweb/data1/discharge/) on November 2, 2001. The missing value indicator for all attributes is -99. Some streamflow characteristics are missing for: (1) streamgages measuring flow subject to tidal effects, which cause flow to reverse directions, (2) streamgages with site information but no streamflow data at the time the data were retrieved, and (3) streamgages with record length too short to compute the base-flow index.
Savoie, Jennifer G.; Mullaney, John R.; Bent, Gardner C.
2017-02-21
Trends in long-term water-quality and streamflow data from six water-quality-monitoring stations within three major river basins in Massachusetts and Rhode Island that flow into Narragansett Bay and Little Narragansett Bay were evaluated for water years 1979–2015. In this study, conducted by the U.S. Geological Survey in cooperation with the Rhode Island Department of Environmental Management, the Rhode Island Water Resources Board, and the U.S. Environmental Protection Agency, water-quality and streamflow data were evaluated with a Weighted Regressions on Time, Discharge, and Season smoothing method, which removes the effects of year-to-year variation in water-quality conditions due to variations in streamflow (discharge). Trends in annual mean, annual median, annual maximum, and annual 7-day minimum flows at four continuous streamgages were evaluated by using a time-series smoothing method for water years 1979–2015.Water quality at all monitoring stations changed over the study period. Decreasing trends in flow-normalized nutrient concentrations and loads were observed during the period at most monitoring stations for total nitrogen, nitrite plus nitrate, and total phosphorus. Average flow-normalized loads for water years 1979–2015 decreased in the Blackstone River by up to 46 percent in total nitrogen, 17 percent in nitrite plus nitrate, and 69 percent in total phosphorus. The other rivers also had decreasing flow-normalized trends in nutrient concentrations and loads, except for the Pawtuxet River, which had an increasing trend in nitrite plus nitrate. Increasing trends in flow-normalized chloride concentrations and loads were observed during the study period at all of the rivers, with increases of more than 200 percent in the Blackstone River.Small increasing trends in annual mean daily streamflow were observed in 3 of the 4 rivers, with increases of 1.2 to 11 percent; however, the trends were not significant. All 4 rivers had decreases in streamflow for the annual 7-day minimums, but only 3 of the 4 rivers had decreases that were significant (34 to 54 percent). The Branch River had decreasing annual mean daily streamflow (7.5 percent) and the largest decrease in the annual 7-day minimum streamflow. The Blackstone and Pawtuxet Rivers had the largest increases in annual maximum daily flows but had decreases in the annual 7-day minimum flows.
NASA Astrophysics Data System (ADS)
Dhakal, A. S.; Adera, S.; Niswonger, R. G.; Gardner, M.
2016-12-01
The ability of the Precipitation-Runoff Modeling System (PRMS) to predict peak intensity, peak timing, base flow, and volume of streamflow was examined in Arroyo Hondo (180 km2) and Upper Alameda Creek (85 km2), two sub-watersheds of the Alameda Creek watershed in Northern California. Rainfall-runoff volume ratios vary widely, and can exceed 0.85 during mid-winter flashy rainstorm events. Due to dry antecedent soil moisture conditions, the first storms of the hydrologic year often produce smaller rainfall-runoff volume ratios. Runoff response in this watershed is highly hysteretic; large precipitation events are required to generate runoff following a 4-week period without precipitation. After about 150 mm of cumulative rainfall, streamflow responds quickly to subsequent storms, with variations depending on rainstorm intensity. Inputs to PRMS included precipitation, temperature, topography, vegetation, soils, and land cover data. The data was prepared for input into PRMS using a suite of data processing Python scripts written by the Desert Research Institute and U.S. Geological Survey. PRMS was calibrated by comparing simulated streamflow to measured streamflow at a daily time step during the period 1995 - 2014. The PRMS model is being used to better understand the different patterns of streamflow observed in the Alameda Creek watershed. Although Arroyo Hondo receives more rainfall than Upper Alameda Creek, it is not clear whether the differences in streamflow patterns are a result of differences in rainfall or other variables, such as geology, slope and aspect. We investigate the ability of PRMS to simulate daily streamflow in the two sub-watersheds for a variety of antecedent soil moisture conditions and rainfall intensities. After successful simulation of watershed runoff processes, the model will be expanded using GSFLOW to simulate integrated surface water and groundwater to support water resources planning and management in the Alameda Creek watershed.
Farmer, William H.; Koltun, Greg
2017-01-01
Study regionThe state of Ohio in the United States, a humid, continental climate.Study focusThe estimation of nonexceedance probabilities of daily streamflows as an alternative means of establishing the relative magnitudes of streamflows associated with hydrologic and water-quality observations.New hydrological insights for the regionSeveral methods for estimating nonexceedance probabilities of daily mean streamflows are explored, including single-index methodologies (nearest-neighboring index) and geospatial tools (kriging and topological kriging). These methods were evaluated by conducting leave-one-out cross-validations based on analyses of nearly 7 years of daily streamflow data from 79 unregulated streamgages in Ohio and neighboring states. The pooled, ordinary kriging model, with a median Nash–Sutcliffe performance of 0.87, was superior to the single-site index methods, though there was some bias in the tails of the probability distribution. Incorporating network structure through topological kriging did not improve performance. The pooled, ordinary kriging model was applied to 118 locations without systematic streamgaging across Ohio where instantaneous streamflow measurements had been made concurrent with water-quality sampling on at least 3 separate days. Spearman rank correlations between estimated nonexceedance probabilities and measured streamflows were high, with a median value of 0.76. In consideration of application, the degree of regulation in a set of sample sites helped to specify the streamgages required to implement kriging approaches successfully.
van Heeswijk, Marijke
2006-01-01
Surface water has been diverted from the Salmon Creek Basin for irrigation purposes since the early 1900s, when the Bureau of Reclamation built the Okanogan Project. Spring snowmelt runoff is stored in two reservoirs, Conconully Reservoir and Salmon Lake Reservoir, and gradually released during the growing season. As a result of the out-of-basin streamflow diversions, the lower 4.3 miles of Salmon Creek typically has been a dry creek bed for almost 100 years, except during the spring snowmelt season during years of high runoff. To continue meeting the water needs of irrigators but also leave water in lower Salmon Creek for fish passage and to help restore the natural ecosystem, changes are being considered in how the Okanogan Project is operated. This report documents development of a precipitation-runoff model for the Salmon Creek Basin that can be used to simulate daily unregulated streamflows. The precipitation-runoff model is a component of a Decision Support System (DSS) that includes a water-operations model the Bureau of Reclamation plans to develop to study the water resources of the Salmon Creek Basin. The DSS will be similar to the DSS that the Bureau of Reclamation and the U.S. Geological Survey developed previously for the Yakima River Basin in central southern Washington. The precipitation-runoff model was calibrated for water years 1950-89 and tested for water years 1990-96. The model was used to simulate daily streamflows that were aggregated on a monthly basis and calibrated against historical monthly streamflows for Salmon Creek at Conconully Dam. Additional calibration data were provided by the snowpack water-equivalent record for a SNOTEL station in the basin. Model input time series of daily precipitation and minimum and maximum air temperatures were based on data from climate stations in the study area. Historical records of unregulated streamflow for Salmon Creek at Conconully Dam do not exist for water years 1950-96. Instead, estimates of historical monthly mean unregulated streamflow based on reservoir outflows and storage changes were used as a surrogate for the missing data and to calibrate and test the model. The estimated unregulated streamflows were corrected for evaporative losses from Conconully Reservoir (about 1 ft3/s) and ground-water losses from the basin (about 2 ft3/s). The total of the corrections was about 9 percent of the mean uncorrected streamflow of 32.2 ft3/s (23,300 acre-ft/yr) for water years 1949-96. For the calibration period, the basinwide mean annual evapotranspiration was simulated to be 19.1 inches, or about 83 percent of the mean annual precipitation of 23.1 inches. Model calibration and testing indicated that the daily streamflows simulated using the precipitation-runoff model should be used only to analyze historical and forecasted annual mean and April-July mean streamflows for Salmon Creek at Conconully Dam. Because of the paucity of model input data and uncertainty in the estimated unregulated streamflows, the model is not adequately calibrated and tested to estimate monthly mean streamflows for individual months, such as during low-flow periods, or for shorter periods such as during peak flows. No data were available to test the accuracy of simulated streamflows for lower Salmon Creek. As a result, simulated streamflows for lower Salmon Creek should be used with caution. For the calibration period (water years 1950-89), both the simulated mean annual streamflow and the simulated mean April-July streamflow compared well with the estimated uncorrected unregulated streamflow (UUS) and corrected unregulated streamflow (CUS). The simulated mean annual streamflow exceeded UUS by 5.9 percent and was less than CUS by 2.7 percent. Similarly, the simulated mean April-July streamflow exceeded UUS by 1.8 percent and was less than CUS by 3.1 percent. However, streamflow was significantly undersimulated during the low-flow, baseflow-dominated months of November through F
Wagner, Daniel M.; Krieger, Joshua D.; Merriman, Katherine R.
2014-01-01
The U.S. Geological Survey (USGS) and the U.S. Army Corps of Engineers (USACE) conducted a statistical analysis of trends in precipitation, streamflow, reservoir pool elevations, and reservoir releases in Arkansas and selected sites in Louisiana, Missouri, and Oklahoma for the period 1951–2011. The Mann-Kendall test was used to test for trends in annual and seasonal precipitation, annual and seasonal streamflows of 42 continuous-record USGS streamflow-gaging stations, annual pool elevations and releases from 16 USACE reservoirs, and annual releases from 11 dams on the Arkansas River. A statistically significant (p≤0.10) upward trend was observed in annual precipitation for the State, with a Sen slope of approximately 0.10 inch per year. Autumn and winter were the only seasons that had statistically significant trends in precipitation. Five of six physiographic sections and six of seven 4-digit hydrologic unit code (HUC) regions in Arkansas had statistically significant upward trends in autumn precipitation, with Sen slopes of approximately 0.06 to 0.10 inch per year. Sixteen sites had statistically significant upward trends in the annual mean daily streamflow and were located on streams that drained regions with statistically significant upward trends in annual precipitation. Expected annual rates of change corresponding to statistically significant trends in annual mean daily streamflows, which ranged from 0.32 to 0.88 percent, were greater than those corresponding to regions with statistically significant upward trends in annual precipitation, which ranged from 0.19 to 0.28 percent, suggesting that the observed trends in regional annual precipitation do not fully account for the observed trends in annual mean daily streamflows. Trends in annual maximum daily streamflows were similar to trends in the annual mean daily streamflows but were only statistically significant at seven sites. There were more statistically significant trends (28 of 42 sites) in the annual minimum daily streamflows than in the annual means or maximums. Statistically significant trends in the annual minimum daily streamflows were upward at 18 sites and downward at 10 sites. Despite autumn being the only season that had statistically significant upward trends in seasonal precipitation, statistically significant upward trends in seasonal mean streamflows occurred in every season but spring. Trends in the annual mean, maximum, and minimum daily pool elevations of USACE reservoirs were consistent between metrics for reservoirs in the White, Arkansas, and Ouachita River watersheds, while trends varied between metrics at DeQueen Lake, Millwood Lake, and Lake Chicot. Most of the statistically significant trends in pool elevation metrics were upward and gradual—Sen slopes were less than 0.37 foot per year—and were likely the result of changes in reservoir regulation plans. Trends in the annual mean and maximum daily releases from USACE reservoirs were generally upward in all HUC regions. There were few statistically significant trends in the annual mean daily releases because the reservoirs are operated to maintain a regulation stage at a downstream site according to guidelines set forth in the regulation plans of the reservoirs. The annual number of low-flow days was both increasing and decreasing for reservoirs in northern Arkansas and southern Missouri and generally increasing for reservoirs in southern Arkansas.
Methods to estimate historical daily streamflow for ungaged stream locations in Minnesota
Lorenz, David L.; Ziegeweid, Jeffrey R.
2016-03-14
Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water; however, streamgages cannot be installed at every location where streamflow information is needed. Therefore, methods for estimating streamflow at ungaged stream locations need to be developed. This report presents a statewide study to develop methods to estimate the structure of historical daily streamflow at ungaged stream locations in Minnesota. Historical daily mean streamflow at ungaged locations in Minnesota can be estimated by transferring streamflow data at streamgages to the ungaged location using the QPPQ method. The QPPQ method uses flow-duration curves at an index streamgage, relying on the assumption that exceedance probabilities are equivalent between the index streamgage and the ungaged location, and estimates the flow at the ungaged location using the estimated flow-duration curve. Flow-duration curves at ungaged locations can be estimated using recently developed regression equations that have been incorporated into StreamStats (http://streamstats.usgs.gov/), which is a U.S. Geological Survey Web-based interactive mapping tool that can be used to obtain streamflow statistics, drainage-basin characteristics, and other information for user-selected locations on streams.
Christiansen, Daniel E.; Haj, Adel E.; Risley, John C.
2017-10-24
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for 12 river basins in western Iowa that drain into the Missouri River. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration periods for each basin varied depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations.A geographic information system tool was used to delineate each basin and estimate initial values for model parameters based on basin physical and geographical features. A U.S. Geological Survey automatic calibration tool that uses a shuffled complex evolution algorithm was used for initial calibration, and then manual modifications were made to parameter values to complete the calibration of each basin model. The main objective of the calibration was to match daily discharge values of simulated streamflow to measured daily discharge values. The Precipitation-Runoff Modeling System model was calibrated at 42 sites located in the 12 river basins in western Iowa.The accuracy of the simulated daily streamflow values at the 42 calibration sites varied by river and by site. The models were satisfactory at 36 of the sites based on statistical results. Unsatisfactory performance at the six other sites can be attributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) limited availability and accuracy of meteorological input data. The Precipitation-Runoff Modeling System models of 12 river basins in western Iowa will provide water-resource managers with a consistent and documented method for estimating streamflow at ungaged sites and aid in environmental studies, hydraulic design, water management, and water-quality projects.
NASA Astrophysics Data System (ADS)
Ye, Xuchun; Xu, Chong-Yu; Li, Xianghu; Zhang, Qi
2018-05-01
The occurrence of flood and drought frequency is highly correlated with the temporal fluctuations of streamflow series; understanding of these fluctuations is essential for the improved modeling and statistical prediction of extreme changes in river basins. In this study, the complexity of daily streamflow fluctuations was investigated by using multifractal detrended fluctuation analysis (MF-DFA) in a large heterogeneous lake basin, the Poyang Lake basin in China, and the potential impacts of human activities were also explored. Major results indicate that the multifractality of streamflow fluctuations shows significant regional characteristics. In the study catchment, all the daily streamflow series present a strong long-range correlation with Hurst exponents bigger than 0.8. The q-order Hurst exponent h( q) of all the hydrostations can be characterized well by only two parameters: a (0.354 ≤ a ≤ 0.384) and b (0.627 ≤ b ≤ 0.677), with no pronounced differences. Singularity spectrum analysis pointed out that small fluctuations play a dominant role in all daily streamflow series. Our research also revealed that both the correlation properties and the broad probability density function (PDF) of hydrological series can be responsible for the multifractality of streamflow series that depends on watershed areas. In addition, we emphasized the relationship between watershed area and the estimated multifractal parameters, such as the Hurst exponent and fitted parameters a and b from the q-order Hurst exponent h( q). However, the relationship between the width of the singularity spectrum (Δ α) and watershed area is not clear. Further investigation revealed that increasing forest coverage and reservoir storage can effectively enhance the persistence of daily streamflow, decrease the hydrological complexity of large fluctuations, and increase the small fluctuations.
Rutledge, A.T.
1998-01-01
The computer programs included in this report can be used to develop a mathematical expression for recession of ground-water discharge and estimate mean ground-water recharge and discharge. The programs are intended for analysis of the daily streamflow record of a basin where one can reasonably assume that all, or nearly all, ground water discharges to the stream except for that which is lost to riparian evapotranspiration, and where regulation and diversion of flow can be considered to be negligible. The program RECESS determines the master reces-sion curve of streamflow recession during times when all flow can be considered to be ground-water discharge and when the profile of the ground-water-head distribution is nearly stable. The method uses a repetitive interactive procedure for selecting several periods of continuous recession, and it allows for nonlinearity in the relation between time and the logarithm of flow. The program RORA uses the recession-curve displacement method to estimate the recharge for each peak in the streamflow record. The method is based on the change in the total potential ground-water discharge that is caused by an event. Program RORA is applied to a long period of record to obtain an estimate of the mean rate of ground-water recharge. The program PART uses streamflow partitioning to estimate a daily record of base flow under the streamflow record. The method designates base flow to be equal to streamflow on days that fit a requirement of antecedent recession, linearly interpolates base flow for other days, and is applied to a long period of record to obtain an estimate of the mean rate of ground-water discharge. The results of programs RORA and PART correlate well with each other and compare reasonably with results of the corresponding manual method.
Dudley, Robert W.; Nielsen, Martha G.
2011-01-01
The U.S. Geological Survey (USGS) began a study in 2008 to investigate anticipated changes in summer streamflows and stream temperatures in four coastal Maine river basins and the potential effects of those changes on populations of endangered Atlantic salmon. To achieve this purpose, it was necessary to characterize the quantity and timing of streamflow in these rivers by developing and evaluating a distributed-parameter watershed model for a part of each river basin by using the USGS Precipitation-Runoff Modeling System (PRMS). The GIS (geographic information system) Weasel, a USGS software application, was used to delineate the four study basins and their many subbasins, and to derive parameters for their geographic features. The models were calibrated using a four-step optimization procedure in which model output was evaluated against four datasets for calibrating solar radiation, potential evapotranspiration, annual and seasonal water balances, and daily streamflows. The calibration procedure involved thousands of model runs that used the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The calibrated watershed models performed satisfactorily, in that Nash-Sutcliffe efficiency (NSE) statistic values for the calibration periods ranged from 0.59 to 0.75 (on a scale of negative infinity to 1) and NSE statistic values for the evaluation periods ranged from 0.55 to 0.73. The calibrated watershed models simulate daily streamflow at many locations in each study basin. These models enable natural resources managers to characterize the timing and amount of streamflow in order to support a variety of water-resources efforts including water-quality calculations, assessments of water use, modeling of population dynamics and migration of Atlantic salmon, modeling and assessment of habitat, and simulation of anticipated changes to streamflow and water temperature resulting from changes forecast for air temperature and precipitation.
Jeton, A.E.; Dettinger, M.D.; Smith, J. LaRue
1996-01-01
Precipitation-runoff models of the East Fork Carson and North Fork American Rivers were developed and calibrated for use in evaluating the sensitivity of streamflow in the north-central Sierra Nevada to climate change. The East Fork Carson River drains part of the rain-shadowed, eastern slope of the Sierra Nevada and is generally higher than the North Fork American River, which drains the wetter, western slope. First, a geographic information system was developed to describe the spatial variability of basin characteristics and to help estimate model parameters. The result was a partitioning of each basin into noncontiguous, but hydrologically uniform, land units. Hydrologic descriptions of these units were developed and the Precipitation- Runoff Modeling System (PRMS) was used to simulate water and energy balances for each unit in response to daily weather conditions. The models were calibrated and verified using historical streamflows over 22-year (Carson River) and 42-year (American River) periods. Simulated annual streamflow errors average plus 10 percent of the observed flow for the East Fork Carson River basin and plus 15 percent for the North Fork American River basin. Interannual variability is well simulated overall, but, at daily scales, wet periods are simulated more accurately than drier periods. The simulated water budgets for the two basins are significantly different in seasonality of streamflow, sublimation, evapotranspiration, and snowmelt. The simulations indicate that differences in snowpack and snowmelt timing can play pervasive roles in determining the sensitivity of water resources to climate change, in terms of both resource availability and amount. The calibrated models were driven by more than 25 hypothetical climate-change scenarios, each 100 years long. The scenarios were synthesized and spatially disaggregated by methods designed to preserve realistic daily, monthly, annual, and spatial statistics. Simulated streamflow timing was not very sensitive to changes in mean precipitation, but was sensitive to changes in mean temperatures. Changes in annual streamflow amounts were amplified reflections of imposed mean precipitation changes, with especially large responses to wetter climates. In contrast, streamflow amount was surprisingly insensitive to mean temperature changes as a result of temporal links between peak snowmelt and the beginning of warm-season evapotranspiration. Comparisons of simulations driven by temporally detailed climate-model changes in which mean temperature changes vary from month to month and simulations in which uniform climate changes were imposed throughout the year indicate that the snowpack accumulates the influences of short-term conditions so that season average climate changes were more important than shorter term changes.
NASA Astrophysics Data System (ADS)
Liu, Z.; Rajib, M. A.; Jafarzadegan, K.; Merwade, V.
2015-12-01
Application of land surface/hydrologic models within an operational flood forecasting system can provide probable time of occurrence and magnitude of streamflow at specific locations along a stream. Creating time-varying spatial extent of flood inundation and depth requires the use of a hydraulic or hydrodynamic model. Models differ in representing river geometry and surface roughness which can lead to different output depending on the particular model being used. The result from a single hydraulic model provides just one possible realization of the flood extent without capturing the uncertainty associated with the input or the model parameters. The objective of this study is to compare multiple hydraulic models toward generating ensemble flood inundation extents. Specifically, relative performances of four hydraulic models, including AutoRoute, HEC-RAS, HEC-RAS 2D, and LISFLOOD are evaluated under different geophysical conditions in several locations across the United States. By using streamflow output from the same hydrologic model (SWAT in this case), hydraulic simulations are conducted for three configurations: (i) hindcasting mode by using past observed weather data at daily time scale in which models are being calibrated against USGS streamflow observations, (ii) validation mode using near real-time weather data at sub-daily time scale, and (iii) design mode with extreme streamflow data having specific return periods. Model generated inundation maps for observed flood events both from hindcasting and validation modes are compared with remotely sensed images, whereas the design mode outcomes are compared with corresponding FEMA generated flood hazard maps. The comparisons presented here will give insights on probable model-specific nature of biases and their relative advantages/disadvantages as components of an operational flood forecasting system.
LaFontaine, Jacob H.; Hay, Lauren E.; Viger, Roland J.; Markstrom, Steve L.; Regan, R. Steve; Elliott, Caroline M.; Jones, John W.
2013-01-01
A hydrologic model of the Apalachicola–Chattahoochee–Flint River Basin (ACFB) has been developed as part of a U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center effort to provide integrated science that helps resource managers understand the effect of climate change on a range of ecosystem responses. The hydrologic model was developed as part of the Southeast Regional Assessment Project using the Precipitation Runoff Modeling System (PRMS), a deterministic, distributed-parameter, process-based system that simulates the effects of precipitation, temperature, and land use on basin hydrology. The ACFB PRMS model simulates streamflow throughout the approximately 50,700 square-kilometer basin on a daily time step for the period 1950–99 using gridded climate forcings of air temperature and precipitation, and parameters derived from spatial data layers of altitude, land cover, soils, surficial geology, depression storage (small water bodies), and data from 56 USGS streamgages. Measured streamflow data from 35 of the 56 USGS streamgages were used to calibrate and evaluate simulated basin streamflow; the remaining gage locations were used for model delineation only. The model matched measured daily streamflow at 31 of the 35 calibration gages with Nash-Sutcliffe Model Efficiency Index (NS) greater than 0.6. Streamflow data for some calibration gages were augmented for regulation and water use effects to represent more natural flow volumes. Time-static parameters describing land cover limited the ability of the simulation to match historical runoff in the more developed subbasins. Overall, the PRMS simulation of the ACFB provides a good representation of basin hydrology on annual and monthly time steps. Calibration subbasins were analyzed by separating the 35 subbasins into five classes based on physiography, land use, and stream type (tributary or mainstem). The lowest NS values were rarely below 0.6, whereas the median NS for all five classes was within 0.74 to 0.96 for annual mean streamflow, 0.89 to 0.98 for mean monthly streamflow, and 0.82 to 0.98 for monthly mean streamflow. The median bias for all five classes was within –4.3 to 0.8 percent for annual mean streamflow, –6.3 to 0.5 percent for mean monthly streamflow, and –9.3 to 1.3 percent for monthly mean streamflow. The NS results combined with the percent bias results indicated a good to very good streamflow volume simulation for all subbasins. This simulation of the ACFB provides a foundation for future modeling and interpretive studies. Streamflow and other components of the hydrologic cycle simulated by PRMS can be used to inform other types of simulations; water-temperature, hydrodynamic, and ecosystem-dynamics simulations are three examples. In addition, possible future hydrologic conditions could be studied using this model in combination with land cover projections and downscaled general circulation model results.
Guay, Joel R.
2002-01-01
To better understand the rainfall-runoff characteristics of the eastern part of the San Jacinto River Basin and to estimate the effects of increased urbanization on streamflow, channel infiltration, and land-surface infiltration, a long-term (1950?98) time series of monthly flows in and out of the channels and land surfaces were simulated using the Hydrologic Simulation Program- FORTRAN (HSPF) rainfall-runoff model. Channel and land-surface infiltration includes rainfall or runoff that infiltrates past the zone of evapotranspiration and may become ground-water recharge. The study area encompasses about 256 square miles of the San Jacinto River drainage basin in Riverside County, California. Daily streamflow (for periods with available data between 1950 and 1998), and daily rainfall and evaporation (1950?98) data; monthly reservoir storage data (1961?98); and estimated mean annual reservoir inflow data (for 1974 conditions) were used to calibrate the rainfall-runoff model. Measured and simulated mean annual streamflows for the San Jacinto River near San Jacinto streamflow-gaging station (North-South Fork subbasin) for 1950?91 and 1997?98 were 14,000 and 14,200 acre-feet, respectively, a difference of 1.4 percent. The standard error of the mean for measured and simulated annual streamflow in the North-South Fork subbasin was 3,520 and 3,160 acre-feet, respectively. Measured and simulated mean annual streamflows for the Bautista Creek streamflow-gaging station (Bautista Creek subbasin) for 1950?98 were 980 acre-feet and 991 acre-feet, respectively, a difference of 1.1 percent. The standard error of the mean for measured and simulated annual streamflow in the Bautista Creek subbasin was 299 and 217 acre-feet, respectively. Measured and simulated annual streamflows for the San Jacinto River above State Street near San Jacinto streamflow-gaging station (Poppet subbasin) for 1998 were 23,400 and 23,500 acre-feet, respectively, a difference of 0.4 percent. The simulated mean annual streamflow for the State Street gaging station at the outlet of the study basin and the simulated mean annual basin infiltration (combined infiltration from all the channels and land surfaces) were 8,720 and 41,600 acre-feet, respectively, for water years 1950-98. Simulated annual streamflow at the State Street gaging station ranged from 16.8 acre-feet in water year 1961 to 70,400 acre-feet in water year 1993, and simulated basin infiltration ranged from 2,770 acre-feet in water year 1961 to 149,000 acre-feet in water year 1983.The effects of increased urbanization on the hydrology of the study basin were evaluated by increasing the size of the effective impervious and non-effective impervious urban areas simulated in the calibrated rainfall-runoff model by 50 and 100 percent, respectively. The rainfall-runoff model simulated a long-term time series of monthly flows in and out of the channels and land surfaces using daily rainfall and potential evaporation data for water years 1950?98. Increasing the effective impervious and non-effective impervious urban areas by 100 percent resulted in a 5-percent increase in simulated mean annual streamflow at the State Street gaging station, and a 2.2-percent increase in simulated basin infiltration. Results of a frequency analysis of the simulated annual streamflow at the State Street gaging station showed that when effective impervious and non-effective impervious areas were increased 100 percent, simulated annual streamflow increased about 100 percent for low-flow conditions and was unchanged for high-flow conditions. The simulated increase in streamflow at the State Street gaging station potentially could infiltrate along the stream channel further downstream, outside of the model area.
Trends in snowmelt-related streamflow timing in the conterminous United States
NASA Astrophysics Data System (ADS)
Dudley, R. W.; Hodgkins, G. A.; McHale, M. R.; Kolian, M. J.; Renard, B.
2017-04-01
Changes in snowmelt-related streamflow timing have implications for water availability and use as well as ecologically relevant shifts in streamflow. Historical trends in snowmelt-related streamflow timing (winter-spring center volume date, WSCVD) were computed for minimally disturbed river basins in the conterminous United States. WSCVD was computed by summing daily streamflow for a seasonal window then calculating the day that half of the seasonal volume had flowed past the gage. We used basins where at least 30 percent of annual precipitation was received as snow, and streamflow data were restricted to regionally based winter-spring periods to focus the analyses on snowmelt-related streamflow. Trends over time in WSCVD at gages in the eastern U.S. were relatively homogenous in magnitude and direction and statistically significant; median WSCVD was earlier by 8.2 days (1.1 days/decade) and 8.6 days (1.6 days/decade) for 1940-2014 and 1960-2014 periods respectively. Fewer trends in the West were significant though most trends indicated earlier WSCVD over time. Trends at low-to-mid elevation (<1600 m) basins in the West, predominantly located in the Northwest, had median earlier WSCVD by 6.8 days (1940-2014, 0.9 days/decade) and 3.4 days (1960-2014, 0.6 days/decade). Streamflow timing at high-elevation (⩾1600 m) basins in the West had median earlier WSCVD by 4.0 days (1940-2014, 0.5 days/decade) and 5.2 days (1960-2014, 0.9 days/decade). Trends toward earlier WSCVD in the Northwest were not statistically significant, differing from previous studies that observed many large and (or) significant trends in this region. Much of this difference is likely due to the sensitivity of trend tests to the time period being tested, as well as differences in the streamflow timing metrics used among the studies. Mean February-May air temperature was significantly correlated with WSCVD at 100 percent of the study gages (field significant, p < 0.0001), demonstrating the sensitivity of WSCVD to air temperature across snowmelt dominated basins in the U.S. WSCVD in high elevation basins in the West, however, was related to both air temperature and precipitation yielding earlier snowmelt-related streamflow timing under warmer and drier conditions.
Ockerman, Darwin J.
2005-01-01
The U.S. Geological Survey, in cooperation with the San Antonio Water System, constructed three watershed models using the Hydrological Simulation Program—FORTRAN (HSPF) to simulate streamflow and estimate recharge to the Edwards aquifer in the Hondo Creek, Verde Creek, and San Geronimo Creek watersheds in south-central Texas. The three models were calibrated and tested with available data collected during 1992–2003. Simulations of streamflow and recharge were done for 1951–2003. The approach to construct the models was to first calibrate the Hondo Creek model (with an hourly time step) using 1992–99 data and test the model using 2000–2003 data. The Hondo Creek model parameters then were applied to the Verde Creek and San Geronimo Creek watersheds to construct the Verde Creek and San Geronimo Creek models. The simulated streamflows for Hondo Creek are considered acceptable. Annual, monthly, and daily simulated streamflows adequately match measured values, but simulated hourly streamflows do not. The accuracy of streamflow simulations for Verde Creek is uncertain. For San Geronimo Creek, the match of measured and simulated annual and monthly streamflows is acceptable (or nearly so); but for daily and hourly streamflows, the calibration is relatively poor. Simulated average annual total streamflow for 1951–2003 to Hondo Creek, Verde Creek, and San Geronimo Creek is 45,400; 32,400; and 11,100 acre-feet, respectively. Simulated average annual streamflow at the respective watershed outlets is 13,000; 16,200; and 6,920 acre-feet. The difference between total streamflow and streamflow at the watershed outlet is streamflow lost to channel infiltration. Estimated average annual Edwards aquifer recharge for Hondo Creek, Verde Creek, and San Geronimo Creek watersheds for 1951–2003 is 37,900 acrefeet (5.04 inches), 26,000 acre-feet (3.36 inches), and 5,940 acre-feet (1.97 inches), respectively. Most of the recharge (about 77 percent for the three watersheds together) occurs as streamflow channel infiltration. Diffuse recharge (direct infiltration of rainfall to the aquifer) accounts for the remaining 23 percent of recharge. For the Hondo Creek watershed, the HSPF recharge estimates for 1992–2003 averaged about 22 percent less than those estimated by the Puente method, a method the U.S. Geological Survey has used to compute annual recharge to the Edwards aquifer since 1978. HSPF recharge estimates for the Verde Creek watershed average about 40 percent less than those estimated by the Puente method.
Koczot, Kathryn M.; Jeton, Anne E.; McGurk, Bruce; Dettinger, Michael D.
2005-01-01
Precipitation-runoff processes in the Feather River Basin of northern California determine short- and long-term streamflow variations that are of considerable local, State, and Federal concern. The river is an important source of water and power for the region. The basin forms the headwaters of the California State Water Project. Lake Oroville, at the outlet of the basin, plays an important role in flood management, water quality, and the health of fisheries as far downstream as the Sacramento-San Joaquin Delta. Existing models of the river simulate streamflow in hourly, daily, weekly, and seasonal time steps, but cannot adequately describe responses to climate and land-use variations in the basin. New spatially detailed precipitation-runoff models of the basin have been developed to simulate responses to climate and land-use variations at a higher spatial resolution than was available previously. This report characterizes daily rainfall, snowpack evolution, runoff, water and energy balances, and streamflow variations from, and within, the basin above Lake Oroville. The new model's ability to predict streamflow is assessed. The Feather River Basin sits astride geologic, topographic, and climatic divides that establish a hydrologic character that is relatively unusual among the basins of the Sierra Nevada. It straddles a north-south geologic transition in the Sierra Nevada between the granitic bedrock that underlies and forms most of the central and southern Sierra Nevada and volcanic bedrock that underlies the northernmost parts of the range (and basin). Because volcanic bedrock generally is more permeable than granitic, the northern, volcanic parts of the basin contribute larger fractions of ground-water flow to streams than do the southern, granitic parts of the basin. The Sierra Nevada topographic divide forms a high altitude ridgeline running northwest to southeast through the middle of the basin. The topography east of this ridgeline is more like the rain-shadowed basins of the northeastern Sierra Nevada than the uplands of most western Sierra Nevada river basins. The climate is mediterranean, with most of the annual precipitation occurring in winter. Because the basin includes large areas that are near the average snowline, rainfall and rain-snow mixtures are common during winter storms. Consequently, the overall timing and rates of runoff from the basin are highly sensitive to winter temperature fluctuations. The models were developed to simulate runoff-generating processes in eight drainages of the Feather River Basin. Together, these models simulate streamflow from 98 percent of the basin above Lake Oroville. The models simulate daily water and heat balances, snowpack evolution and snowmelt, evaporation and transpiration, subsurface water storage and outflows, and streamflow to key streamflow gage sites. The drainages are modeled as 324 hydrologic-response units, each of which is assumed homogeneous in physical characteristics and response to precipitation and runoff. The models were calibrated with emphasis on reproducing monthly streamflow rates, and model simulations were compared to the total natural inflows into Lake Oroville as reconstructed by the California Department of Water Resources for April-July snowmelt seasons from 1971 to 1997. The models are most sensitive to input values and patterns of precipitation and soil characteristics. The input precipitation values were allowed to vary on a daily basis to reflect available observations by making daily transformations to an existing map of long-term mean monthly precipitation rates that account for altitude and rain-shadow effects. The models effectively simulate streamflow into Lake Oroville during water years (October through September) 1971-97, which is demonstrated in hydrographs and statistical results presented in this report. The Butt Creek model yields the most accurate historical April-July simulations, whereas the West Branch
Trend analysis of hydro-climatic variables in the north of Iran
NASA Astrophysics Data System (ADS)
Nikzad Tehrani, E.; Sahour, H.; Booij, M. J.
2018-04-01
Trend analysis of climate variables such as streamflow, precipitation, and temperature provides useful information for understanding the hydrological changes associated with climate change. In this study, a nonparametric Mann-Kendall test was employed to evaluate annual, seasonal, and monthly trends of precipitation and streamflow for the Neka basin in the north of Iran over a 44-year period (1972 to 2015). In addition, the Inverse Distance Weight (IDW) method was used for annual seasonal, monthly, and daily precipitation trends in order to investigate the spatial correlation between precipitation and streamflow trends in the study area. Results showed a downward trend in annual and winter precipitation (Z < -1.96) and an upward trend in annual maximum daily precipitation. Annual and monthly mean flows for most of the months in the Neka basin decreased by 14% significantly, but the annual maximum daily flow increased by 118%. Results for the trend analysis of streamflow and climatic variables showed that there are statistically significant relationships between precipitation and streamflow (p value < 0.05). Correlation coefficients for Kendall, Spearman's rank and linear regression are 0.43, 0.61, and 0.67, respectively. The spatial presentation of the detected precipitation and streamflow trends showed a downward trend for the mean annual precipitation observed in the upstream part of the study area which is consistent with the streamflow trend. Also, there is a good correlation between monthly and seasonal precipitation and streamflow for all sub-basins (Sefidchah, Gelvard, Abelu). In general, from a hydro-climatic point of view, the results showed that the study area is moving towards a situation with more severe drought events.
NASA Technical Reports Server (NTRS)
Schumann, H. H. (Principal Investigator)
1973-01-01
The author has identified the following significant results. The DCS water-stage data from the USGS streamflow gaging station on the Verde River near Camp Verde furnished information sufficient for the accurate computation of daily mean streamflow rates during the first 2 months of operation. Daily mean flow rates computed from the DCS data agreed with those computed from the digital recorder data within + or - 5% during periods of stable or slowly changing flow and within + or - 10% during periods of rapidly changing high flow. The SRP was furnished near-real time DCS information on snow moisture content and streamflow rates for use in the management and operation of the multiple-use reservoir system. The SRP, by prudent water management and the use of near-real time hydrologic data furnished by microwave and ERTS DCS telemetry, was successful in anticipating the amount of flow into the Salt and Verde Rivers and in the subsequent release of water at rates that did not create flooding in metropolitan Phoenix. Only minor flooding occurred along the Gila River west of Phoenix. According to the Maricopa County Civil Defense agency, wage and salary losses of about $11,400,000 resulted from closing of roads across the Salt River in the winter and spring of 1972-73; however, the number and duration of the closing were minimized by use of DCS data.
Brigode, Pierre; Brissette, Francois; Nicault, Antoine; ...
2016-09-06
Over the last decades, different methods have been used by hydrologists to extend observed hydro-climatic time series, based on other data sources, such as tree rings or sedimentological datasets. For example, tree ring multi-proxies have been studied for the Caniapiscau Reservoir in northern Québec (Canada), leading to the reconstruction of flow time series for the last 150 years. In this paper, we applied a new hydro-climatic reconstruction method on the Caniapiscau Reservoir and compare the obtained streamflow time series against time series derived from dendrohydrology by other authors on the same catchment and study the natural streamflow variability over themore » 1881–2011 period in that region. This new reconstruction is based not on natural proxies but on a historical reanalysis of global geopotential height fields, and aims firstly to produce daily climatic time series, which are then used as inputs to a rainfall–runoff model in order to obtain daily streamflow time series. The performances of the hydro-climatic reconstruction were quantified over the observed period, and showed good performances, in terms of both monthly regimes and interannual variability. The streamflow reconstructions were then compared to two different reconstructions performed on the same catchment by using tree ring data series, one being focused on mean annual flows and the other on spring floods. In terms of mean annual flows, the interannual variability in the reconstructed flows was similar (except for the 1930–1940 decade), with noteworthy changes seen in wetter and drier years. For spring floods, the reconstructed interannual variabilities were quite similar for the 1955–2011 period, but strongly different between 1880 and 1940. Here, the results emphasize the need to apply different reconstruction methods on the same catchments. Indeed, comparisons such as those above highlight potential differences between available reconstructions and, finally, allow a retrospective analysis of the proposed reconstructions of past hydro-climatological variabilities.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brigode, Pierre; Brissette, Francois; Nicault, Antoine
Over the last decades, different methods have been used by hydrologists to extend observed hydro-climatic time series, based on other data sources, such as tree rings or sedimentological datasets. For example, tree ring multi-proxies have been studied for the Caniapiscau Reservoir in northern Québec (Canada), leading to the reconstruction of flow time series for the last 150 years. In this paper, we applied a new hydro-climatic reconstruction method on the Caniapiscau Reservoir and compare the obtained streamflow time series against time series derived from dendrohydrology by other authors on the same catchment and study the natural streamflow variability over themore » 1881–2011 period in that region. This new reconstruction is based not on natural proxies but on a historical reanalysis of global geopotential height fields, and aims firstly to produce daily climatic time series, which are then used as inputs to a rainfall–runoff model in order to obtain daily streamflow time series. The performances of the hydro-climatic reconstruction were quantified over the observed period, and showed good performances, in terms of both monthly regimes and interannual variability. The streamflow reconstructions were then compared to two different reconstructions performed on the same catchment by using tree ring data series, one being focused on mean annual flows and the other on spring floods. In terms of mean annual flows, the interannual variability in the reconstructed flows was similar (except for the 1930–1940 decade), with noteworthy changes seen in wetter and drier years. For spring floods, the reconstructed interannual variabilities were quite similar for the 1955–2011 period, but strongly different between 1880 and 1940. Here, the results emphasize the need to apply different reconstruction methods on the same catchments. Indeed, comparisons such as those above highlight potential differences between available reconstructions and, finally, allow a retrospective analysis of the proposed reconstructions of past hydro-climatological variabilities.« less
Aerial photography provides a historical vehicle for determining long term urban landscape change and, with concurrent daily streamflow and precipitation records, allows the historical relationship of impervious surfaces and streamflow to be explored. Impervious surface a...
Christiansen, Daniel E.
2012-01-01
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, conducted a study to examine techniques for estimation of daily streamflows using hydrological models and statistical methods. This report focuses on the use of a hydrologic model, the U.S. Geological Survey's Precipitation-Runoff Modeling System, to estimate daily streamflows at gaged and ungaged locations. The Precipitation-Runoff Modeling System is a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The Cedar River Basin was selected to construct a Precipitation-Runoff Modeling System model that simulates the period from January 1, 2000, to December 31, 2010. The calibration period was from January 1, 2000, to December 31, 2004, and the validation periods were from January 1, 2005, to December 31, 2010 and January 1, 2000 to December 31, 2010. A Geographic Information System tool was used to delineate the Cedar River Basin and subbasins for the Precipitation-Runoff Modeling System model and to derive parameters based on the physical geographical features. Calibration of the Precipitation-Runoff Modeling System model was completed using a U.S. Geological Survey calibration software tool. The main objective of the calibration was to match the daily streamflow simulated by the Precipitation-Runoff Modeling System model with streamflow measured at U.S. Geological Survey streamflow gages. The Cedar River Basin daily streamflow model performed with a Nash-Sutcliffe efficiency ranged from 0.82 to 0.33 during the calibration period, and a Nash-Sutcliffe efficiency ranged from 0.77 to -0.04 during the validation period. The Cedar River Basin model is meeting the criteria of greater than 0.50 Nash-Sutcliffe and is a good fit for streamflow conditions for the calibration period at all but one location, Austin, Minnesota. The Precipitation-Runoff Modeling System model accurately simulated streamflow at four of six uncalibrated sites within the basin. Overall, there was good agreement between simulated and measured seasonal and annual volumes throughout the basin for calibration and validation sites. The calibration period ranged from 0.2 to 20.8 percent difference, and the validation period ranged from 0.0 to 19.5 percent difference across all seasons and total annual runoff. The Precipitation-Runoff Modeling System model tended to underestimate lower streamflows compared to the observed streamflow values. This is an indication that the Precipitation-Runoff Modeling model needs more detailed groundwater and storage information to properly model the low-flow conditions in the Cedar River Basin.
Regionalization of harmonic-mean streamflows in Kentucky
Martin, Gary R.; Ruhl, Kevin J.
1993-01-01
Harmonic-mean streamflow (Qh), defined as the reciprocal of the arithmetic mean of the reciprocal daily streamflow values, was determined for selected stream sites in Kentucky. Daily mean discharges for the available period of record through the 1989 water year at 230 continuous record streamflow-gaging stations located in and adjacent to Kentucky were used in the analysis. Periods of record affected by regulation were identified and analyzed separately from periods of record unaffected by regulation. Record-extension procedures were applied to short-term stations to reducetime-sampling error and, thus, improve estimates of the long-term Qh. Techniques to estimate the Qh at ungaged stream sites in Kentucky were developed. A regression model relating Qh to total drainage area and streamflow-variability index was presented with example applications. The regression model has a standard error of estimate of 76 percent and a standard error of prediction of 78 percent.
Lambing, J.H.
1987-01-01
A sampling program was conducted at six stream sites. The purpose of the study was to collect baseline data on concentrations of suspended sediment and selected trace metals in streamflow. Included in this report are tables of daily data for mean streamflow, suspended sediment concentration, and suspended sediment discharge at two streamflow gaging stations on the Clark Fork; periodic data for instantaneous streamflow, onsite water quality, and trace metal and suspended sediment concentrations in the Clark Fork and tributaries; and summary statistics for all the water quality data. Also included are graphs for each site showing median concentrations of trace metals, relationship of concentrations of trace metals to suspended sediment, and median concentrations of trace metals in suspended sediments. Hydrographs for two sites on the main stem show daily mean streamflow, suspended sediment concentration, and suspended sediment discharge for the period of study. (Author 's abstract)
Stamey, Timothy C.
2001-01-01
In 1999, the U.S. Geological Survey, in cooperation with the U.S. Army Signal Center and Fort Gordon, began collection of periodic streamflow data at four streams on the military base to assess and estimate streamflow characteristics of those streams for potential water-supply sources. Simple and reliable methods of determining streamflow characteristics of selected streams on the military base are needed for the initial implementation of the Fort Gordon Integrated Natural Resources Management Plan. Long-term streamflow data from the Butler Creek streamflow gaging station were used along with several concurrent discharge measurements made at three selected partial-record streamflow stations on Fort Gordon to determine selected low-flow streamflow characteristics. Streamflow data were collected and analyzed using standard U.S. Geological Survey methods and computer application programs to verify the use of simple drainage area to discharge ratios, which were used to estimate the low-flow characteristics for the selected streams. Low-flow data computed based on daily mean streamflow include: mean discharges for consecutive 1-, 3-, 7-, 14-, and 30-day period and low-flow estimates of 7Q10, 30Q2, 60Q2, and 90Q2 recurrence intervals. Flow-duration data also were determined for the 10-, 30-, 50-, 70-, and 90-percent exceedence flows. Preliminary analyses of the streamflow indicate that the flow duration and selected low-flow statistics for the selected streams averages from about 0.15 to 2.27 cubic feet per square mile. The long-term gaged streamflow data indicate that the streamflow conditions for the period analyzed were in the 50- to 90-percent flow range, or in which streamflow would be exceeded about 50 to 90 percent of the time.
Dudley, Robert W.
2008-01-01
The U.S. Geological Survey (USGS), in cooperation with the Maine Department of Marine Resources Bureau of Sea Run Fisheries and Habitat, began a study in 2004 to characterize the quantity, variability, and timing of streamflow in the Dennys River. The study included a synoptic summary of historical streamflow data at a long-term streamflow gage, collecting data from an additional four short-term streamflow gages, and the development and evaluation of a distributed-parameter watershed model for the Dennys River Basin. The watershed model used in this investigation was the USGS Precipitation-Runoff Modeling System (PRMS). The Geographic Information System (GIS) Weasel was used to delineate the Dennys River Basin and subbasins and derive parameters for their physical geographic features. Calibration of the models used in this investigation involved a four-step procedure in which model output was evaluated against four calibration data sets using computed objective functions for solar radiation, potential evapotranspiration, annual and seasonal water budgets, and daily streamflows. The calibration procedure involved thousands of model runs and was carried out using the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The SCE method reliably produces satisfactory solutions for large, complex optimization problems. The primary calibration effort went into the Dennys main stem watershed model. Calibrated parameter values obtained for the Dennys main stem model were transferred to the Cathance Stream model, and a similar four-step SCE calibration procedure was performed; this effort was undertaken to determine the potential to transfer modeling information to a nearby basin in the same region. The calibrated Dennys main stem watershed model performed with Nash-Sutcliffe efficiency (NSE) statistic values for the calibration period and evaluation period of 0.79 and 0.76, respectively. The Cathance Stream model had an NSE value of 0.68. The Dennys River Basin models make use of limited streamflow-gaging station data and provide information to characterize subbasin hydrology. The calibrated PRMS watershed models of the Dennys River Basin provide simulated daily streamflow time series from October 1, 1985, through September 30, 2006, for nearly any location within the basin. These models enable natural-resources managers to characterize the timing and quantity of water moving through the basin to support many endeavors including geochemical calculations, water-use assessment, Atlantic salmon population dynamics and migration modeling, habitat modeling and assessment, and other resource-management scenario evaluations. Characterizing streamflow contributions from subbasins in the basin and the relative amounts of surface- and ground-water contributions to streamflow throughout the basin will lead to a better understanding of water quantity and quality in the basin. Improved water-resources information will support Atlantic salmon protection efforts.
Technical Manual for the Geospatial Stream Flow Model (GeoSFM)
Asante, Kwabena O.; Artan, Guleid A.; Pervez, Md Shahriar; Bandaragoda, Christina; Verdin, James P.
2008-01-01
The monitoring of wide-area hydrologic events requires the use of geospatial and time series data available in near-real time. These data sets must be manipulated into information products that speak to the location and magnitude of the event. Scientists at the U.S. Geological Survey Earth Resources Observation and Science (USGS EROS) Center have implemented a hydrologic modeling system which consists of an operational data processing system and the Geospatial Stream Flow Model (GeoSFM). The data processing system generates daily forcing evapotranspiration and precipitation data from various remotely sensed and ground-based data sources. To allow for rapid implementation in data scarce environments, widely available terrain, soil, and land cover data sets are used for model setup and initial parameter estimation. GeoSFM performs geospatial preprocessing and postprocessing tasks as well as hydrologic modeling tasks within an ArcView GIS environment. The integration of GIS routines and time series processing routines is achieved seamlessly through the use of dynamically linked libraries (DLLs) embedded within Avenue scripts. GeoSFM is run operationally to identify and map wide-area streamflow anomalies. Daily model results including daily streamflow and soil water maps are disseminated through Internet map servers, flood hazard bulletins and other media.
NASA Astrophysics Data System (ADS)
Sinha, T.; Arumugam, S.
2012-12-01
Seasonal streamflow forecasts contingent on climate forecasts can be effectively utilized in updating water management plans and optimize generation of hydroelectric power. Streamflow in the rainfall-runoff dominated basins critically depend on forecasted precipitation in contrast to snow dominated basins, where initial hydrological conditions (IHCs) are more important. Since precipitation forecasts from Atmosphere-Ocean-General Circulation Models are available at coarse scale (~2.8° by 2.8°), spatial and temporal downscaling of such forecasts are required to implement land surface models, which typically runs on finer spatial and temporal scales. Consequently, multiple sources are introduced at various stages in predicting seasonal streamflow. Therefore, in this study, we addresses the following science questions: 1) How do we attribute the errors in monthly streamflow forecasts to various sources - (i) model errors, (ii) spatio-temporal downscaling, (iii) imprecise initial conditions, iv) no forecasts, and (iv) imprecise forecasts? and 2) How does monthly streamflow forecast errors propagate with different lead time over various seasons? In this study, the Variable Infiltration Capacity (VIC) model is calibrated over Apalachicola River at Chattahoochee, FL in the southeastern US and implemented with observed 1/8° daily forcings to estimate reference streamflow during 1981 to 2010. The VIC model is then forced with different schemes under updated IHCs prior to forecasting period to estimate relative mean square errors due to: a) temporally disaggregation, b) spatial downscaling, c) Reverse Ensemble Streamflow Prediction (imprecise IHCs), d) ESP (no forecasts), and e) ECHAM4.5 precipitation forecasts. Finally, error propagation under different schemes are analyzed with different lead time over different seasons.
NASA Astrophysics Data System (ADS)
Konrad, C.; Brasher, A.; May, J.
2007-12-01
River restoration depends on re-establishment of the range of physical and biological processes that comprise the river ecosystem. Streamflow is the definitive physical processes for river ecosystems, so hydrologic alteration represents a potentially significant issue to be addressed by restoration efforts. Given adaptation of lotic species to naturally variable streamflow patterns over evolutionary time scales, however, lotic communities are resilient to at least some forms of hydrologic variability. As a result, river restoration may be successful despite limited but biologically insignificant hydrologic alteration. The responses of benthic invertebrate assemblages to variation in streamflow patterns across the western United States were investigated to identify biologically important forms and magnitudes of hydrologic variability. Biological responses to streamflow patterns were analyzed in terms of ceilings and floors on invertebrate assemblage diversity and structure using a non-parametric screening procedure and quantile regression. Variability at daily and monthly time scales was the most common streamflow pattern associated with broad metrics of invertebrate assemblages including abundance; richness and relative abundance of Ephemeroptera, Plecoptera, Trichoptera and non-insects; dominance; and diversity. Low flow magnitude and annual variability were associated with richness and trophic structure. The frequency, magnitude, and duration of high flows were associated with abundance and richness. Longer term streamflow metrics (calculated over at least 5 years) were more important than recent flows (30 and 100 days prior to invertebrate sampling). The results can be used as general guidance about when hydrologic alteration is likely to be an important factor and what streamflow patterns may need to be re-established for successful river restoration.
NASA Astrophysics Data System (ADS)
Arumugam, S.; Mazrooei, A.; Lakshmi, V.; Wood, A.
2017-12-01
Subseasonal-to-seasonal (S2S) forecasts of soil moisture and streamflow provides critical information for water and agricultural systems to support short-term planning and mangement. This study evaluates the role of observed streamflow and remotely-sensed soil moisture from SMAP (Soil Moisture Active Passive) mission in improving S2S streamflow and soil moisture forecasting using data assimilation (DA). We first show the ability to forecast soil moisture at monthly-to-seaasonal time scale by forcing climate forecasts with NASA's Land Information System and then compares the developed soil moisture forecast with the SMAP data over the Southeast US. Our analyses show significant skill in forecasting real-time soil moisture over 1-3 months using climate information. We also show that the developed soil moisture forecasts capture the observed severe drought conditions (2007-2008) over the Southeast US. Following that, we consider both SMAP data and observed streamflow for improving S2S streamflow and soil moisture forecasts for a pilot study area, Tar River basin, in NC. Towards this, we consider variational assimilation (VAR) of gauge-measured daily streamflow data in improving initial hydrologic conditions of Variable Infiltration Capacity (VIC) model. The utility of data assimilation is then assessed in improving S2S forecasts of streamflow and soil moisture through a retrospective analyses. Furthermore, the optimal frequency of data assimilation and optimal analysis window (number of past observations to use) are also assessed in order to achieve the maximum improvement in S2S forecasts of streamflow and soil moisture. Potential utility of updating initial conditions using DA and providing skillful forcings are also discussed.
Low-flow characteristics of streams in Ohio through water year 1997
Straub, David E.
2001-01-01
This report presents selected low-flow and flow-duration characteristics for 386 sites throughout Ohio. These sites include 195 long-term continuous-record stations with streamflow data through water year 1997 (October 1 to September 30) and for 191 low-flow partial-record stations with measurements into water year 1999. The characteristics presented for the long-term continuous-record stations are minimum daily streamflow; average daily streamflow; harmonic mean flow; 1-, 7-, 30-, and 90-day minimum average low flow with 2-, 5-, 10-, 20-, and 50-year recurrence intervals; and 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 20-, and 10-percent daily duration flows. The characteristics presented for the low-flow partial-record stations are minimum observed streamflow; estimated 1-, 7-, 30-, and 90-day minimum average low flow with 2-, 10-, and 20-year recurrence intervals; and estimated 98-, 95-, 90-, 85- and 80-percent daily duration flows. The low-flow frequency and duration analyses were done for three seasonal periods (warm weather, May 1 to November 30; winter, December 1 to February 28/29; and autumn, September 1 to November 30), plus the annual period based on the climatic year (April 1 to March 31).
Payne, G.A.
1983-01-01
Streamflow and suspended-sediment-transport data were collected in Garvin Brook watershed in Winona County, southeastern Minnesota, during 1982. The data collection was part of a study to determine the effectiveness of agricultural best-management practices designed to improve rural water quality. The study is part of a Rural Clean Water Program demonstration project undertaken by the U.S. Department of Agriculture. Continuous streamflow data were collected at three gaging stations during March through September 1982. Suspended-sediment samples were collected at two of the gaging stations. Samples were collected manually at weekly intervals. During periods of rapidly changing stage, samples were collected at 30-minute to 12-hour intervals by stage-activated automatic samplers. The samples were analyzed for suspendedsediment concentration and particle-size distribution. Particlesize distributions were also determined for one set of bedmaterial samples collected at each sediment-sampling site. The streamflow and suspended-sediment-concentration data were used to compute records of mean-daily flow, mean-daily suspended-sediment concentration, and daily suspended-sediment discharge. The daily records are documented and results of analyses for particle-size distribution and of vertical sampling in the stream cross sections are given.
Lambing, John H.; Sando, Steven K.
2009-01-01
This report presents estimated daily and cumulative loads of suspended sediment and selected trace elements transported during water year 2008 at three streamflow-gaging stations that bracket the Milltown Reservoir project area in the upper Clark Fork basin of western Montana. Milltown Reservoir is a National Priorities List Superfund site where sediments enriched in trace elements from historical mining and ore processing have been deposited since the construction of Milltown Dam in 1907. Milltown Dam was breached on March 28, 2008, as part of Superfund remedial activities to remove the dam and contaminated sediment that had accumulated in Milltown Reservoir. The estimated loads transported through the project area during the periods before and after the breaching of Milltown Dam, and for the entire water year 2008, were used to quantify the net gain or loss (mass balance) of suspended sediment and trace elements within the project area during the transition from a reservoir environment to a free-flowing river. This study was done in cooperation with the U.S. Environmental Protection Agency. Streamflow during water year 2008 compared to long-term streamflow, as represented by the record for Clark Fork above Missoula (water years 1930-2008), generally was below normal (long-term median) from about October 2007 through April 2008. Sustained runoff started in mid-April, which increased flows to near normal by mid-May. After mid-May, flows sharply increased to above normal, reaching a maximum daily mean streamflow of 16,800 cubic feet per second (ft3/s) on May 21, which essentially equaled the long-term 10th-exceedance percentile for that date. Flows substantially above normal were sustained through June, then decreased through the summer and reached near-normal by August. Annual mean streamflow during water year 2008 (3,040 ft3/s) was 105 percent of the long-term mean annual streamflow (2,900 ft3/s). The annual peak flow (17,500 ft3/s) occurred on May 21 and was 112 percent of the long-term mean annual peak flow (15,600 ft3/s). About 81 percent of the annual flow volume was discharged during the post-breach period. Daily loads of suspended sediment were estimated directly by using high-frequency sampling of the daily sediment monitoring. Daily loads of unfiltered-recoverable arsenic, cadmium, copper, iron, lead, manganese, and zinc were estimated by using regression equations relating trace-element discharge to either streamflow or suspended-sediment discharge. Regression equations for estimating trace-element discharge in water year 2008 were developed from instantaneous streamflow and concentration data for periodic water-quality samples collected during all or part of water years 2004-08. The equations were applied to records of daily mean streamflow or daily suspended-sediment loads to produce estimated daily trace-element loads. Variations in daily suspended-sediment and trace-element loads generally coincided with variations in streamflow. Relatively small to moderately large daily net losses from the project area were common during the pre-breach period when low-flow conditions were prevalent. Outflow loads from the project area sharply increased immediately after the breaching of Milltown Dam and during the rising limb and peak flow of the annual hydrograph. Net losses of suspended sediment and trace elements from the project area decreased as streamflow decreased during the summer, eventually becoming small or reaching an approximate net balance between inflow and outflow. Estimated daily loads of suspended sediment and trace elements for all three stations were summed to determine cumulative inflow and outflow loads for the pre-breach and post-breach periods, as well as for the entire water year 2008. Overall, the mass balance between the combined inflow loads from two upstream source areas (upper Clark Fork and Blackfoot River basins) and the outflow loads at Clark Fork above Missoula indicates net losses
A physically based analytical model of flood frequency curves
NASA Astrophysics Data System (ADS)
Basso, S.; Schirmer, M.; Botter, G.
2016-09-01
Predicting magnitude and frequency of floods is a key issue in hydrology, with implications in many fields ranging from river science and geomorphology to the insurance industry. In this paper, a novel physically based approach is proposed to estimate the recurrence intervals of seasonal flow maxima. The method links the extremal distribution of streamflows to the stochastic dynamics of daily discharge, providing an analytical expression of the seasonal flood frequency curve. The parameters involved in the formulation embody climate and landscape attributes of the contributing catchment and can be estimated from daily rainfall and streamflow data. Only one parameter, which is linked to the antecedent wetness condition in the watershed, needs to be calibrated on the observed maxima. The performance of the method is discussed through a set of applications in four rivers featuring heterogeneous daily flow regimes. The model provides reliable estimates of seasonal maximum flows in different climatic settings and is able to capture diverse shapes of flood frequency curves emerging in erratic and persistent flow regimes. The proposed method exploits experimental information on the full range of discharges experienced by rivers. As a consequence, model performances do not deteriorate when the magnitude of events with return times longer than the available sample size is estimated. The approach provides a framework for the prediction of floods based on short data series of rainfall and daily streamflows that may be especially valuable in data scarce regions of the world.
NASA Astrophysics Data System (ADS)
KIM, J.; Smith, M. B.; Koren, V.; Salas, F.; Cui, Z.; Johnson, D.
2017-12-01
The National Oceanic and Atmospheric Administration (NOAA)-National Weather Service (NWS) developed the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) framework as an initial step towards spatially distributed modeling at River Forecast Centers (RFCs). Recently, the NOAA/NWS worked with the National Center for Atmospheric Research (NCAR) to implement the National Water Model (NWM) for nationally-consistent water resources prediction. The NWM is based on the WRF-Hydro framework and is run at a 1km spatial resolution and 1-hour time step over the contiguous United States (CONUS) and contributing areas in Canada and Mexico. In this study, we compare streamflow simulations from HL-RDHM and WRF-Hydro to observations from 279 USGS stations. For streamflow simulations, HL-RDHM is run on 4km grids with the temporal resolution of 1 hour for a 5-year period (Water Years 2008-2012), using a priori parameters provided by NOAA-NWS. The WRF-Hydro streamflow simulations for the same time period are extracted from NCAR's 23 retrospective run of the NWM (version 1.0) over CONUS based on 1km grids. We choose 279 USGS stations which are relatively less affected by dams or reservoirs, in the domains of six different RFCs. We use the daily average values of simulations and observations for the convenience of comparison. The main purpose of this research is to evaluate how HL-RDHM and WRF-Hydro perform at USGS gauge stations. We compare daily time-series of observations and both simulations, and calculate the error values using a variety of error functions. Using these plots and error values, we evaluate the performances of HL-RDHM and WRF-Hydro models. Our results show a mix of model performance across geographic regions.
Farmer, William H.; Over, Thomas M.; Vogel, Richard M.
2015-01-01
Understanding the spatial structure of daily streamflow is essential for managing freshwater resources, especially in poorly-gaged regions. Spatial scaling assumptions are common in flood frequency prediction (e.g., index-flood method) and the prediction of continuous streamflow at ungaged sites (e.g. drainage-area ratio), with simple scaling by drainage area being the most common assumption. In this study, scaling analyses of daily streamflow from 173 streamgages in the southeastern US resulted in three important findings. First, the use of only positive integer moment orders, as has been done in most previous studies, captures only the probabilistic and spatial scaling behavior of flows above an exceedance probability near the median; negative moment orders (inverse moments) are needed for lower streamflows. Second, assessing scaling by using drainage area alone is shown to result in a high degree of omitted-variable bias, masking the true spatial scaling behavior. Multiple regression is shown to mitigate this bias, controlling for regional heterogeneity of basin attributes, especially those correlated with drainage area. Previous univariate scaling analyses have neglected the scaling of low-flow events and may have produced biased estimates of the spatial scaling exponent. Third, the multiple regression results show that mean flows scale with an exponent of one, low flows scale with spatial scaling exponents greater than one, and high flows scale with exponents less than one. The relationship between scaling exponents and exceedance probabilities may be a fundamental signature of regional streamflow. This signature may improve our understanding of the physical processes generating streamflow at different exceedance probabilities.
Streamflow characteristics of the Colorado River Basin in Utah through September 1981
Christensen, R.C.; Johnson, E.B.; Plantz, G.G.
1987-01-01
This report summarizes discharge data and other streamflow characteristics developed from gag ing-station records collected through September 1981 at 337 stations in the Colorado River Basin in Utah. Data also are included for 14 stations in adjacent areas of the bordering states of Arizona, Colorado, and Wyoming (fig. 1). The study leading to this report was done in cooperation with the U.S. Bureau of Land Management, which needs the streamflow data in order to evaluate impacts of mining on the hydrologic system. The report also will be beneficial to other Federal, State, and county agencies and to individuals concerned with water supply and water problems in the Colorado River Basin.The streamflow characteristics in the report could be useful in many water-related studies that involve the following:Definition of baseline-hydrologic conditions; studies of the effects of man's activities on streamflow; frequency analyses of low and high flows; regional analyses of streamflow characteristics; design of water-supply systems; water-power studies; forecasting of stream discharge; time-series analyses of streamflow; design of flood-control structures; stream-pollution studies; and water-chemistry transport studies.The basic data used to develop the summaries in this report are records of daily and peak discharge collected by the U.S. Geological Survey and other Federal agencies. Much of the work of the Geological Survey was done in cooperation with Federal, State, and county agencies. Discharge recordsincluded in the report generally were for stations with at least 1 complete water year of record and nearby stations that were on the same stream and had different streamflow characteristics. A water year is a 12-month period ending September 30, and it is designated by the calendar year in which it ends. For streams that have had significant changes in regulation by reservoirs or diversions, the records before and after those changes were used separately to provide streamflow characteristics for each period of homogeneous streamflow and to show the change in the characteristics. Summaries for annual peak discharge are included only for stations with 5 or more years of data. The summaries of annual lowest and highest mean-discharge frequency are reported for stations with 10 or more years of daily-discharge record and for which computer-generated frequency curves provided a reasonable fit of the plotted data.
Decomposition of Sources of Errors in Seasonal Streamflow Forecasting over the U.S. Sunbelt
NASA Technical Reports Server (NTRS)
Mazrooei, Amirhossein; Sinah, Tusshar; Sankarasubramanian, A.; Kumar, Sujay V.; Peters-Lidard, Christa D.
2015-01-01
Seasonal streamflow forecasts, contingent on climate information, can be utilized to ensure water supply for multiple uses including municipal demands, hydroelectric power generation, and for planning agricultural operations. However, uncertainties in the streamflow forecasts pose significant challenges in their utilization in real-time operations. In this study, we systematically decompose various sources of errors in developing seasonal streamflow forecasts from two Land Surface Models (LSMs) (Noah3.2 and CLM2), which are forced with downscaled and disaggregated climate forecasts. In particular, the study quantifies the relative contributions of the sources of errors from LSMs, climate forecasts, and downscaling/disaggregation techniques in developing seasonal streamflow forecast. For this purpose, three month ahead seasonal precipitation forecasts from the ECHAM4.5 general circulation model (GCM) were statistically downscaled from 2.8deg to 1/8deg spatial resolution using principal component regression (PCR) and then temporally disaggregated from monthly to daily time step using kernel-nearest neighbor (K-NN) approach. For other climatic forcings, excluding precipitation, we considered the North American Land Data Assimilation System version 2 (NLDAS-2) hourly climatology over the years 1979 to 2010. Then the selected LSMs were forced with precipitation forecasts and NLDAS-2 hourly climatology to develop retrospective seasonal streamflow forecasts over a period of 20 years (1991-2010). Finally, the performance of LSMs in forecasting streamflow under different schemes was analyzed to quantify the relative contribution of various sources of errors in developing seasonal streamflow forecast. Our results indicate that the most dominant source of errors during winter and fall seasons is the errors due to ECHAM4.5 precipitation forecasts, while temporal disaggregation scheme contributes to maximum errors during summer season.
Streamflow characteristics and trends in New Jersey, water years 1897-2003
Watson, Kara M.; Reiser, Robert G.; Nieswand, Steven P.; Schopp, Robert D.
2005-01-01
Streamflow statistics were computed for 111 continuous-record streamflow-gaging stations with 20 or more years of continuous record and for 500 low-flow partial-record stations, including 66 gaging stations with less than 20 years of continuous record. Daily mean streamflow data from water year 1897 through water year 2001 were used for the computations at the gaging stations. (The water year is the 12-month period, October 1 through September 30, designated by the calendar year in which it ends). The characteristics presented for the long-term continuous-record stations are daily streamflow, harmonic mean flow, flow frequency, daily flow durations, trend analysis, and streamflow variability. Low-flow statistics for gaging stations with less than 20 years of record and for partial-record stations were estimated by correlating base-flow measurements with daily mean flows at long-term (more than 20 years) continuous-record stations. Instantaneous streamflow measurements through water year 2003 were used to estimate low-flow statistics at the partial-record stations. The characteristics presented for partial-record stations are mean annual flow; harmonic mean flow; and annual and winter low-flow frequency. The annual 1-, 7-, and 30-day low- and high-flow data sets were tested for trends. The results of trend tests for high flows indicate relations between upward trends for high flows and stream regulation, and high flows and development in the basin. The relation between development and low-flow trends does not appear to be as strong as for development and high-flow trends. Monthly, seasonal, and annual precipitation data for selected long-term meteorological stations also were tested for trends to analyze the effects of climate. A significant upward trend in precipitation in northern New Jersey, Climate Division 1 was identified. For Climate Division 2, no general increase in average precipitation was observed. Trend test results indicate that high flows at undeveloped, unregulated sites have not been affected by the increase in average precipitation. The ratio of instantaneous peak flow to 3-day mean flow, ratios of flow duration, ratios of high-flow/low-flow frequency, and coefficient of variation were used to define streamflow variability. Streamflow variability was significantly greater among the group of gaging stations located outside the Coastal Plain than among the group of gaging stations located in the Coastal Plain.
Kuhn, Gerhard
2002-01-01
The U.S Geological Survey, in cooperation with the Grand Mesa, Uncompahgre, and Gunnison National Forests, began a study in 2000 to develop selected streamflow characteristics for 60 streamflow-gaging stations in and near the Grand Mesa, Uncompahgre, and Gunnison National Forests. The study area is located in southwestern Colorado within the Gunnison River, Dolores River, and Plateau Creek Basins, which are tributaries of the Colorado River. In addition to presenting the compiled daily, monthly, and annual discharge data for the 60 stations, the report presents tabular and graphical results for the following computed streamflow characteristics: (1) Instantaneous peak-flow frequency; (2) flow duration for daily mean discharges on an annual (water year) basis and on a monthly basis, and flow duration for the annual and monthly mean discharges; (3) low-flow and high-flow frequency of daily mean discharges for periods of 1, 3, 7, 15, 30, 60, 120, and 183 consecutive days; and (4) annual and monthly mean and median discharges for each year and month of record, and frequency of the annual and monthly mean and median discharges. All discharge data and results from the streamflow-characteristics analyses are presented in Microsoft Excel workbooks on the enclosed CD-ROM.
Herbert Ssegane; Devendra M. Amatya; E.W. Tollner; Zhaohua Dai; Jami E. Nettles
2013-01-01
Commonly used methods to predict streamflow at ungauged watersheds implicitly predict streamflow magnitude and temporal sequence concurrently. An alternative approach that has not been fully explored is the conceptualization of streamflow as a composite of two separable components of magnitude and sequence, where each component is estimated separately and then combined...
Analytical flow duration curves for summer streamflow in Switzerland
NASA Astrophysics Data System (ADS)
Santos, Ana Clara; Portela, Maria Manuela; Rinaldo, Andrea; Schaefli, Bettina
2018-04-01
This paper proposes a systematic assessment of the performance of an analytical modeling framework for streamflow probability distributions for a set of 25 Swiss catchments. These catchments show a wide range of hydroclimatic regimes, including namely snow-influenced streamflows. The model parameters are calculated from a spatially averaged gridded daily precipitation data set and from observed daily discharge time series, both in a forward estimation mode (direct parameter calculation from observed data) and in an inverse estimation mode (maximum likelihood estimation). The performance of the linear and the nonlinear model versions is assessed in terms of reproducing observed flow duration curves and their natural variability. Overall, the nonlinear model version outperforms the linear model for all regimes, but the linear model shows a notable performance increase with catchment elevation. More importantly, the obtained results demonstrate that the analytical model performs well for summer discharge for all analyzed streamflow regimes, ranging from rainfall-driven regimes with summer low flow to snow and glacier regimes with summer high flow. These results suggest that the model's encoding of discharge-generating events based on stochastic soil moisture dynamics is more flexible than previously thought. As shown in this paper, the presence of snowmelt or ice melt is accommodated by a relative increase in the discharge-generating frequency, a key parameter of the model. Explicit quantification of this frequency increase as a function of mean catchment meteorological conditions is left for future research.
NASA Astrophysics Data System (ADS)
Li, Huazhen; Zhang, Qiang; Singh, Vijay P.; Shi, Peijun; Sun, Peng
2017-06-01
The Yellow River basin is a typical semi-arid river basin in northern China. Serious water shortages have negative impacts on regional socioeconomic development. Recent years have witnessed changes in streamflow processes due to increasing human activities, such as agricultural activities and construction of dams and water reservoirs, and climatic changes, e.g. precipitation and temperature. This study attempts to investigate factors potentially driving changes in different streamflow components defined by different quantiles. The data used were daily streamflow data for the 1959-2005 period from 5 hydrological stations, daily precipitation and temperature data from 77 meteorological stations and data pertaining to cropland and large reservoirs. Results indicate a general decrease in streamflow across the Yellow River basin. Moreover significant decreasing streamflow has been observed in the middle and lower Yellow River basin with change points during the mid-1980s till the mid-1990s. The changes of cropland affect the streamflow components and also the cumulative effects on streamflow variations. Recent years have witnessed moderate cropland variations which result in moderate streamflow changes. Further, precipitation also plays a critical role in changes of streamflow components and human activities, i.e. cropland changes, temperature changes and building of water reservoirs, tend to have increasing impacts on hydrological processes across the Yellow River basin. This study provides a theoretical framework for the study of the hydrological effects of human activities and climatic changes on basins over the globe.
Lind, Greg D.; Stonewall, Adam J.
2018-02-13
In this study, “naturalized” daily streamflow records, created by the U.S. Army Corps of Engineers and the Bureau of Reclamation, were used to compute 1-, 3-, 7-, 10-, 15-, 30-, and 60-day annual maximum streamflow durations, which are running averages of daily streamflow for the number of days in each duration. Once the annual maximum durations were computed, the floodduration frequencies could be estimated. The estimated flood-duration frequencies correspond to the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent probabilities of their occurring or being exceeded each year. For this report, the focus was on the Willamette River Basin in Oregon, which is a subbasin of the Columbia River Basin. This study is part of a larger one encompassing the entire Columbia Basin.
NASA Astrophysics Data System (ADS)
Jamaludin, Suhaila
2017-05-01
Extreme rainfall events such as floods and prolonged dry spells have become common phenomena in tropical countries like Malaysia. Floods are regular natural disasters in Malaysia, and happen nearly every year during the monsoon season. Recently, the magnitude of streamflow seems to have altered frequently, both spatially and temporally. Therefore, in order to have effective planning and an efficient water management system, it is advisable that streamflow data are analysed continuously over a period of time. If the data are treated as a set of functions rather than as a set of discrete values, then this ensures that they are not restricted by physical time. In addition, the derivatives of the functions may themselves be treated as functional data, which provides new information. The objective of this study is to develop a functional framework for hydrological applications using streamflow as the functional data. The daily flow series from the Kelantan River Basin were used as the main input in this study. Seven streamflow stations were employed in the analysis. Classification between the stations was done using the functional principal component, which was based on the results of the factor scores. The results indicated that two stations, namely the Kelantan River (Guillemard Bridge) and the Galas River, have a different flow pattern from the other streamflow stations. The flow curves of these two rivers are considered as the extreme curves because of their different magnitude and shape.
Hutchinson, Kasey J.; Christiansen, Daniel E.
2013-01-01
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, used the Soil and Water Assessment Tool to simulate streamflow and nitrate loads within the Cedar River Basin, Iowa. The goal was to assess the ability of the Soil and Water Assessment Tool to estimate streamflow and nitrate loads in gaged and ungaged basins in Iowa. The Cedar River Basin model uses measured streamflow data from 12 U.S. Geological Survey streamflow-gaging stations for hydrology calibration. The U.S. Geological Survey software program, Load Estimator, was used to estimate annual and monthly nitrate loads based on measured nitrate concentrations and streamflow data from three Iowa Department of Natural Resources Storage and Retrieval/Water Quality Exchange stations, located throughout the basin, for nitrate load calibration. The hydrology of the model was calibrated for the period of January 1, 2000, to December 31, 2004, and validated for the period of January 1, 2005, to December 31, 2010. Simulated daily, monthly, and annual streamflow resulted in Nash-Sutcliffe coefficient of model efficiency (ENS) values ranging from 0.44 to 0.83, 0.72 to 0.93, and 0.56 to 0.97, respectively, and coefficient of determination (R2) values ranging from 0.55 to 0.87, 0.74 to 0.94, and 0.65 to 0.99, respectively, for the calibration period. The percent bias ranged from -19 to 10, -16 to 10, and -19 to 10 for daily, monthly, and annual simulation, respectively. The validation period resulted in daily, monthly, and annual ENS values ranging from 0.49 to 0.77, 0.69 to 0.91, and -0.22 to 0.95, respectively; R2 values ranging from 0.59 to 0.84, 0.74 to 0.92, and 0.36 to 0.92, respectively; and percent bias ranging from -16 for all time steps to percent bias of 14, 15, and 15, respectively. The nitrate calibration was based on a small subset of the locations used in the hydrology calibration with limited measured data. Model performance ranges from unsatisfactory to very good for the calibration period (January 1, 2000, to December 31, 2004). Results for the validation period (January 1, 2005, to December 31, 2010) indicate a need for an increase of measured data as well as more refined documented management practices at a higher resolution. Simulated nitrate loads resulted in monthly and annual ENS values ranging from 0.28 to 0.82 and 0.61 to 0.86, respectively, and monthly and annual R2 values ranging from 0.65 to 0.81 and 0.65 to 0.88, respectively, for the calibration period. The monthly and annual calibration percent bias ranged from 4 to 7 and 5 to 7, respectively. The validation period resulted in all but two ENS values less than zero. Monthly and annual validation R2 values ranged from 0.5 to 0.67 and 0.25 to 0.48, respectively. Monthly and annual validation percent bias ranged from 46 to 68 for both time steps. A daily calibration and validation for nitrate loads was not performed because of the poor monthly and annual results; measured daily nitrate data are available for intervals of time in 2009 and 2010 during which a successful monthly and annual calibration could not be achieved. The Cedar River Basin is densely gaged relative to other basins in Iowa; therefore, an alternative hydrology scenario was created to assess the predictive capabilities of the Soil and Water Assessment Tool using fewer locations of measured data for model hydrology calibration. Although the ability of the model to reproduce measured values improves with the number of calibration locations, results indicate that the Soil and Water Assessment Tool can be used to adequately estimate streamflow in less densely gaged basins throughout the State, especially at the monthly time step. However, results also indicate that caution should be used when calibrating a subbasin that consists of physically distinct regions based on only one streamflow-gaging station.
Integrating remotely sensed surface water extent into continental scale hydrology
NASA Astrophysics Data System (ADS)
Revilla-Romero, Beatriz; Wanders, Niko; Burek, Peter; Salamon, Peter; de Roo, Ad
2016-12-01
In hydrological forecasting, data assimilation techniques are employed to improve estimates of initial conditions to update incorrect model states with observational data. However, the limited availability of continuous and up-to-date ground streamflow data is one of the main constraints for large-scale flood forecasting models. This is the first study that assess the impact of assimilating daily remotely sensed surface water extent at a 0.1° × 0.1° spatial resolution derived from the Global Flood Detection System (GFDS) into a global rainfall-runoff including large ungauged areas at the continental spatial scale in Africa and South America. Surface water extent is observed using a range of passive microwave remote sensors. The methodology uses the brightness temperature as water bodies have a lower emissivity. In a time series, the satellite signal is expected to vary with changes in water surface, and anomalies can be correlated with flood events. The Ensemble Kalman Filter (EnKF) is a Monte-Carlo implementation of data assimilation and used here by applying random sampling perturbations to the precipitation inputs to account for uncertainty obtaining ensemble streamflow simulations from the LISFLOOD model. Results of the updated streamflow simulation are compared to baseline simulations, without assimilation of the satellite-derived surface water extent. Validation is done in over 100 in situ river gauges using daily streamflow observations in the African and South American continent over a one year period. Some of the more commonly used metrics in hydrology were calculated: KGE', NSE, PBIAS%, R2, RMSE, and VE. Results show that, for example, NSE score improved on 61 out of 101 stations obtaining significant improvements in both the timing and volume of the flow peaks. Whereas the validation at gauges located in lowland jungle obtained poorest performance mainly due to the closed forest influence on the satellite signal retrieval. The conclusion is that remotely sensed surface water extent holds potential for improving rainfall-runoff streamflow simulations, potentially leading to a better forecast of the peak flow.
Spatial interpolation schemes of daily precipitation for hydrologic modeling
Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.
2012-01-01
Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.
Ziegeweid, Jeffrey R.; Magdalene, Suzanne
2015-01-01
The new regression equations were used to calculate revised estimates of historical streamflows for Stillwater and Prescott starting in 1910 and ending when index-velocity streamgages were installed. Monthly, annual, 30-year, and period of record statistics were examined between previous and revised estimates of historical streamflows. The abilities of the new regression equations to estimate historical streamflows were evaluated by using percent differences to compare new estimates of historical daily streamflows to discrete streamflow measurements made at Stillwater and Prescott before the installation of index-velocity streamgages. Although less variability was observed between estimated and measured streamflows at Stillwater compared to Prescott, the percent difference data indicated that the new estimates closely approximated measured streamflows at both locations.
Wood, Molly S.
2014-01-01
The U.S. Geological Survey (USGS), in cooperation with the Bureau of Land Management (BLM), estimated streamflow statistics for stream segments designated “Wild,” “Scenic,” or “Recreational” under the National Wild and Scenic Rivers System in the Owyhee Canyonlands Wilderness in southwestern Idaho. The streamflow statistics were used by the BLM to develop and file a draft, federal reserved water right claim to protect federally designated “outstanding remarkable values” in the Jarbidge River. The BLM determined that the daily mean streamflow equaled or exceeded 20, 50, and 80 percent of the time during bimonthly periods (two periods per month) and the bankfull (66.7-percent annual exceedance probability) streamflow are important thresholds for maintaining outstanding remarkable values. Although streamflow statistics for the Jarbidge River below Jarbidge, Nevada (USGS 13162225) were published previously in 2013 and used for the draft water right claim, the BLM and USGS have since recognized the need to refine streamflow statistics given the approximate 40 river mile distance and intervening tributaries between the original point of estimation (USGS 13162225) and at the mouth of the Jarbidge River, which is the downstream end of the Wild and Scenic River segment. A drainage-area-ratio method was used in 2013 to estimate bimonthly exceedance probability streamflow statistics at the mouth of the Jarbidge River based on available streamgage data on the Jarbidge and East Fork Jarbidge Rivers. The resulting bimonthly streamflow statistics were further adjusted using a scaling factor calculated from a water balance on streamflow statistics calculated for the Bruneau and East Fork Bruneau Rivers and Sheep Creek. The final, adjusted bimonthly exceedance probability and bankfull streamflow statistics compared well with available verification datasets (including discrete streamflow measurements made at the mouth of the Jarbidge River) and are considered the best available estimates for streamflow statistics in the Jarbidge Wild and Scenic River segment.
Statewide analysis of the drainage-area ratio method for 34 streamflow percentile ranges in Texas
Asquith, William H.; Roussel, Meghan C.; Vrabel, Joseph
2006-01-01
The drainage-area ratio method commonly is used to estimate streamflow for sites where no streamflow data are available using data from one or more nearby streamflow-gaging stations. The method is intuitive and straightforward to implement and is in widespread use by analysts and managers of surface-water resources. The method equates the ratio of streamflow at two stream locations to the ratio of the respective drainage areas. In practice, unity often is assumed as the exponent on the drainage-area ratio, and unity also is assumed as a multiplicative bias correction. These two assumptions are evaluated in this investigation through statewide analysis of daily mean streamflow in Texas. The investigation was made by the U.S. Geological Survey in cooperation with the Texas Commission on Environmental Quality. More than 7.8 million values of daily mean streamflow for 712 U.S. Geological Survey streamflow-gaging stations in Texas were analyzed. To account for the influence of streamflow probability on the drainage-area ratio method, 34 percentile ranges were considered. The 34 ranges are the 4 quartiles (0-25, 25-50, 50-75, and 75-100 percent), the 5 intervals of the lower tail of the streamflow distribution (0-1, 1-2, 2-3, 3-4, and 4-5 percent), the 20 quintiles of the 4 quartiles (0-5, 5-10, 10-15, 15-20, 20-25, 25-30, 30-35, 35-40, 40-45, 45-50, 50-55, 55-60, 60-65, 65-70, 70-75, 75-80, 80-85, 85-90, 90-95, and 95-100 percent), and the 5 intervals of the upper tail of the streamflow distribution (95-96, 96-97, 97-98, 98-99 and 99-100 percent). For each of the 253,116 (712X711/2) unique pairings of stations and for each of the 34 percentile ranges, the concurrent daily mean streamflow values available for the two stations provided for station-pair application of the drainage-area ratio method. For each station pair, specific statistical summarization (median, mean, and standard deviation) of both the exponent and bias-correction components of the drainage-area ratio method were computed. Statewide statistics (median, mean, and standard deviation) of the station-pair specific statistics subsequently were computed and are tabulated herein. A separate analysis considered conditioning station pairs to those stations within 100 miles of each other and with the absolute value of the logarithm (base-10) of the ratio of the drainage areas greater than or equal to 0.25. Statewide statistics of the conditional station-pair specific statistics were computed and are tabulated. The conditional analysis is preferable because of the anticipation that small separation distances reflect similar hydrologic conditions and the observation of large variation in exponent estimates for similar-sized drainage areas. The conditional analysis determined that the exponent is about 0.89 for streamflow percentiles from 0 to about 50 percent, is about 0.92 for percentiles from about 50 to about 65 percent, and is about 0.93 for percentiles from about 65 to about 85 percent. The exponent decreases rapidly to about 0.70 for percentiles nearing 100 percent. The computation of the bias-correction factor is sensitive to the range analysis interval (range of streamflow percentile); however, evidence suggests that in practice the drainage-area method can be considered unbiased. Finally, for general application, suggested values of the exponent are tabulated for 54 percentiles of daily mean streamflow in Texas; when these values are used, the bias correction is unity.
Esralew, Rachel A.; Baker, Ronald J.
2008-01-01
Hydrologic changes in New Jersey stream basins resulting from human activity can affect the flow and ecology of the streams. To assess future changes in streamflow resulting from human activity an understanding of the natural variability of streamflow is needed. The natural variability can be classified using Ecologically Relevant Hydrologic Indices (ERHIs). ERHIs are defined as selected streamflow statistics that characterize elements of the flow regime that substantially affect biological health and ecological sustainability. ERHIs are used to quantitatively characterize aspects of the streamflow regime, including magnitude, duration, frequency, timing, and rate of change. Changes in ERHI values can occur as a result of human activity, and changes in ERHIs over time at various stream locations can provide information about the degree of alteration in aquatic ecosystems at or near those locations. New Jersey streams can be divided into four classes (A, B, C, or D), where streams with similar ERHI values (determined from cluster analysis) are assigned the same stream class. In order to detect and quantify changes in ERHIs at selected streamflow-gaging stations, a 'baseline' period is needed. Ideally, a baseline period is a period of continuous daily streamflow record at a gaging station where human activity along the contributing stream reach or in the stream's basin is minimal. Because substantial urbanization and other development had already occurred before continuous streamflow-gaging stations were installed, it is not possible to identify baseline periods that meet this criterion for many reaches in New Jersey. Therefore, the baseline period for a considerably altered basin can be defined as a period prior to a substantial human-induced change in the drainage basin or stream reach (such as regulations or diversions), or a period during which development did not change substantially. Index stations (stations with minimal urbanization) were defined as streamflow-gaging stations in basins that contain less than 15 percent urban land use throughout the period of continuous streamflow record. A minimum baseline period of record for each stream class was determined by comparing the variability of selected ERHIs among consecutive 5-, 10-, 15-, and 20-year time increments for index stations. On the basis of this analysis, stream classes A and D were assigned a minimum of 20 years of continuous record as a baseline period and stream classes B and C, a minimum of 10 years. Baseline periods were calculated for 85 streamflow-gaging stations in New Jersey with 10 or more years of continuous daily streamflow data, and the values of 171 ERHIs also were calculated for these baseline periods for each station. Baseline periods were determined by using historical streamflow-gaging station data, estimated changes in impervious surface in the drainage basin, and statistically significant changes in annual base flow and runoff. Historical records were reviewed to identify years during which regulation, diversions, or withdrawals occurred in the drainage basins. Such years were not included in baseline periods of record. For some sites, the baseline period of record was shorter than the minimum period of record specified for the given stream class. In such cases, the baseline period was rated as 'poor'. Impervious surface was used as an indicator of urbanization and change in streamflow characteristics owing to increases in storm runoff and decreases in base flow. Percentages of impervious surface were estimated for 85 streamflow-gaging stations from available municipal population-density data by using a regression model. Where the period of record was sufficiently long, all years after the impervious surface exceeded 10 to 20 percent were excluded from the baseline period. The percentage of impervious surface also was used as a criterion in assigning qualitative ratings to baseline periods. Changes in trends of annual base fl
Linhart, S. Mike; Nania, Jon F.; Christiansen, Daniel E.; Hutchinson, Kasey J.; Sanders, Curtis L.; Archfield, Stacey A.
2013-01-01
A variety of individuals from water resource managers to recreational users need streamflow information for planning and decisionmaking at locations where there are no streamgages. To address this problem, two statistically based methods, the Flow Duration Curve Transfer method and the Flow Anywhere method, were developed for statewide application and the two physically based models, the Precipitation Runoff Modeling-System and the Soil and Water Assessment Tool, were only developed for application for the Cedar River Basin. Observed and estimated streamflows for the two methods and models were compared for goodness of fit at 13 streamgages modeled in the Cedar River Basin by using the Nash-Sutcliffe and the percent-bias efficiency values. Based on median and mean Nash-Sutcliffe values for the 13 streamgages the Precipitation Runoff Modeling-System and Soil and Water Assessment Tool models appear to have performed similarly and better than Flow Duration Curve Transfer and Flow Anywhere methods. Based on median and mean percent bias values, the Soil and Water Assessment Tool model appears to have generally overestimated daily mean streamflows, whereas the Precipitation Runoff Modeling-System model and statistical methods appear to have underestimated daily mean streamflows. The Flow Duration Curve Transfer method produced the lowest median and mean percent bias values and appears to perform better than the other models.
Arnold, L.R.
2017-08-03
The U.S. Army Garrison Fort Carson (AGFC) and the Piñon Canyon Maneuver Site (PCMS) are facilities operated by the U.S. Department of the Army in southern Colorado. The U.S. Geological Survey, in cooperation with the U.S. Department of the Army, established a hydrologic and water-quality data-collection network at the AGFC in June 1978 and at the PCMS in October 1982. The data-collection networks are designed to assess the quantity and quality of water resources and monitor the effects of military training activities on streamflow and water quality. Two preexisting U.S. Geological Survey streamgages at the PCMS were incorporated into the data-collection network at the time it was established, providing periods of record that begin as early as 1966. This report presents and summarizes precipitation, streamflow, suspended-sediment, and water-quality data from 34 U.S. Geological Survey sites on or near the AGFC and the PCMS for the period of record at each site. (Streamflow data are presented as discharge in cubic feet per second.)At AGFC, daily sum precipitation ranged from 0 to 11.85 inches, daily mean discharge ranged from 0 to 836 cubic feet per second, and daily mean suspended-sediment discharge ranged from 0 to 39,900 tons per day. With the exception of total (unfiltered) mercury and filtered sulfate at two sites and filtered manganese at three sites, 95th percentile trace element concentrations and median total (unfiltered) metal concentrations were less than regulatory numeric standards for all samples. However, individual water-quality results occasionally exceeded respective regulatory numeric standards.At the PCMS, daily sum precipitation ranged from 0 to 4.59 inches, daily mean discharge ranged from 0 to 4,190 cubic feet per second, and daily mean suspended-sediment discharge ranged from 0 to 21,100 tons per day. Water-quality results, 95th percentile trace element concentrations, and median total (unfiltered) metal concentrations were less than regulatory numeric standards for most properties and constituents except for filtered chloride at one site, filtered sulfate at six sites, filtered phosphorus at one site, filtered manganese at three sites, and total (unfiltered) iron at three sites. Individual water-quality values also occasionally exceeded respective regulatory numeric standards.
Exploring the Link Between Streamflow Trends and Climate Change in Indiana, USA
NASA Astrophysics Data System (ADS)
Kumar, S.; Kam, J.; Thurner, K.; Merwade, V.
2007-12-01
Streamflow trends in Indiana are evaluated for 85 USGS streamflow gaging stations that have continuous unregulated streamflow records varying from 10 to 80 years. The trends are analyzed by using the non-parametric Mann-Kendall test with prior trend-free pre-whitening to remove serial correlation in the data. Bootstrap method is used to establish field significance of the results. Trends are computed for 12 streamflow statistics to include low-, medium- (median and mean flow), and high-flow conditions on annual and seasonal time step. The analysis is done for six study periods, ranging from 10 years to more than 65 years, all ending in 2003. The trends in annual average streamflow, for 50 years study period, are compared with annual average precipitation trends from 14 National Climatic Data Center (NCDC) stations in Indiana, that have 50 years of continuous daily record. The results show field significant positive trends in annual low and medium streamflow statistics at majority of gaging stations for study periods that include 40 or more years of records. In seasonal analysis, all flow statistics in summer and fall (low flow seasons), and only low flow statistics in winter and spring (high flow seasons) are showing positive trends. No field significant trends in annual and seasonal flow statistics are observed for study periods that include 25 or fewer years of records, except for northern Indiana where localized negative trends are observed in 10 and 15 years study periods. Further, stream flow trends are found to be highly correlated with precipitation trends on annual time step. No apparent climate change signal is observed in Indiana stream flow records.
Haj, Adel E.; Christiansen, Daniel E.; Hutchinson, Kasey J.
2015-10-14
The accuracy of Precipitation-Runoff Modeling System model streamflow estimates of nine river basins in eastern Iowa as compared to measured values at U.S. Geological Survey streamflow-gaging stations varied. The Precipitation-Runoff Modeling System models of nine river basins in eastern Iowa were satisfactory at estimating daily streamflow at 57 of the 79 calibration sites and 13 of the 14 validation sites based on statistical results. Unsatisfactory performance can be contributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) the availability and accuracy of meteorological input data. The Precipitation- Runoff Modeling System models of nine river basins in eastern Iowa will provide water-resource managers with a consistent and documented method for estimating streamflow at ungaged sites and aid in environmental studies, hydraulic design, water management, and water-quality projects.
Griffin, Eleanor R.; Wiele, Stephen M.
1996-01-01
A one-dimensional model of unsteady discharge waves was applied to research flowr that were released from Glen Canyon Dam in support of the Glen Canyon Environmental Studies. These research flows extended over periods of 11 days during which the discharge followed specific, regular patterns repeated on a daily cycle that were similar to the daily releases for power generation. The model was used to produce discharge hydrographs at 38 selected sites in Marble and Grand Canyons for each of nine unsteady flows released from the dam in 1990 and 1991. In each case, the discharge computed from stage measurements and the associated stage-discharge relation at the streamflow-gaging station just below the dam (09379910 Colorado River Hlow Glen Canyon Dam) was routed to Diamond Creek, which is 386 kilometers downstream. Steady and unsteady tributary inflows downstream from the dam were included in the model calculations. Steady inflow to the river from tributaries downstream from the dam was determined for each case by comparing the steady base flow preceding and following the unsteady flow measured at six streamflow-gaging stations between Glen Canyon Dam and Diamond Creek. During three flow periods, significant unsteady inflow was received from the Paria River, or the Little Colorado River, or both. The amount and timing of unsteady inflow was determined using the discharge computed from records of streamflow-gaging stations on the tributaries. Unsteady flow then was added to the flow calculated by the model at the appropriate location. Hydrographs were calculated using the model at 5 streamflow-gaging stations downstream from the dam and at 33 beach study sites. Accuracy of model results was evaluated by comparing the results to discharge hydrographs computed from the records of the five streamflow-gaging stations between Lees Ferry and Lake Mead. Results show that model predictions of wave speed and shape agree well with data from the five streamflow-gaging stations.
Williamson, Tanja N.; Lant, Jeremiah G.; Claggett, Peter; Nystrom, Elizabeth A.; Milly, Paul C.D.; Nelson, Hugh L.; Hoffman, Scott A.; Colarullo, Susan J.; Fischer, Jeffrey M.
2015-11-18
The Water Availability Tool for Environmental Resources (WATER) is a decision support system for the nontidal part of the Delaware River Basin that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions. In order to quantify the uncertainty associated with these simulations, however, streamflow and the associated hydroclimatic variables of potential evapotranspiration, actual evapotranspiration, and snow accumulation and snowmelt must be simulated and compared to long-term, daily observations from sites. This report details model development and optimization, statistical evaluation of simulations for 57 basins ranging from 2 to 930 km2 and 11.0 to 99.5 percent forested cover, and how this statistical evaluation of daily streamflow relates to simulating environmental changes and management decisions that are best examined at monthly time steps normalized over multiple decades. The decision support system provides a database of historical spatial and climatic data for simulating streamflow for 2001–11, in addition to land-cover and general circulation model forecasts that focus on 2030 and 2060. WATER integrates geospatial sampling of landscape characteristics, including topographic and soil properties, with a regionally calibrated hillslope-hydrology model, an impervious-surface model, and hydroclimatic models that were parameterized by using three hydrologic response units: forested, agricultural, and developed land cover. This integration enables the regional hydrologic modeling approach used in WATER without requiring site-specific optimization or those stationary conditions inferred when using a statistical model.
Forecasting daily streamflow using online sequential extreme learning machines
NASA Astrophysics Data System (ADS)
Lima, Aranildo R.; Cannon, Alex J.; Hsieh, William W.
2016-06-01
While nonlinear machine methods have been widely used in environmental forecasting, in situations where new data arrive continually, the need to make frequent model updates can become cumbersome and computationally costly. To alleviate this problem, an online sequential learning algorithm for single hidden layer feedforward neural networks - the online sequential extreme learning machine (OSELM) - is automatically updated inexpensively as new data arrive (and the new data can then be discarded). OSELM was applied to forecast daily streamflow at two small watersheds in British Columbia, Canada, at lead times of 1-3 days. Predictors used were weather forecast data generated by the NOAA Global Ensemble Forecasting System (GEFS), and local hydro-meteorological observations. OSELM forecasts were tested with daily, monthly or yearly model updates. More frequent updating gave smaller forecast errors, including errors for data above the 90th percentile. Larger datasets used in the initial training of OSELM helped to find better parameters (number of hidden nodes) for the model, yielding better predictions. With the online sequential multiple linear regression (OSMLR) as benchmark, we concluded that OSELM is an attractive approach as it easily outperformed OSMLR in forecast accuracy.
Winters, Karl E.
2013-01-01
Annual mean streamflow and streamflow-duration curves for the 1951–56 and 2011 water years were assessed for 19 unregulated U.S. Geological Survey (USGS) streamflow-gaging stations. At eight of these streamflow-gaging stations, the annual mean streamflow was lower in 2011 than for any year during 1951–56; many of these stations are located in eastern Texas. Annual mean streamflows for streamflow-gaging stations in the Guadalupe, Blanco, and upper Frio River Basins were lower in 1956 than in 2011. The streamflow-duration curves for many streamflow-gaging stations indicate a lack of (or diminished) storm runoff during 2011. Low streamflows (those exceeded 90 to 95 percent of days) were lower for 1956 than for 2011 at seven streamflow-gaging stations. For most of these stations, the lowest of the low streamflows during 1951–56 occurred in 1956. During March to September 2011, record daily lows were measured at USGS streamflow-gaging station 08041500 Village Creek near Kountze, Tex., which has more than 70 years of record. Many other USGS streamflow-gaging stations in Texas started the 2011 water year with normal streamflow but by the end of the water year were flowing at near-record lows.
Evaluation of selected surface-water-quality stations in Wyoming
Rucker, S.J.; DeLong, L.L.
1987-01-01
The U.S. Geological Survey, in cooperation with the Wyoming Department of Agriculture, has conducted a surface-water-quality program in Wyoming since 1965. The purpose has been to determine the chemical quality of the water in terms of the major dissolved constituents (salinity). Changing agricultural techniques and energy development have stimulated a need for an expanded program involving additional types of data. This report determines the adequacy of the data collected thus far to describe the chemical quality. The sampling program was evaluated by determining how well the data describe the dissolved-solids load of the streams. Monthly mean loads were estimated at 16 stations throughout the network where daily streamflow and daily specific conductance were available. Monthly loads were then compared with loads estimated from daily streamflow and data derived from analyses of samples collected on a monthly basis at these same stations. Agreement was good. Solute-load hydrographs were constructed for 37 stations and from some reaches where streamflow records were available. Because stations where no discharge records are available are not amenable to this type of analysis, data collected at these stations are of limited usefulness. This report covers analyses of data for all qualifying sites in Wyoming except those in the Green River Basin, which were analyzed in U.S. Geological Survey Water Resources Investigations 77-103. The salinity in most of the streams evaluated is adequately described by the data collected. Reduced sampling is feasible, and time and money can be diverted to collecting other data. (USGS)
Granato, Gregory E.; Ries, Kernell G.; Steeves, Peter A.
2017-10-16
Streamflow statistics are needed by decision makers for many planning, management, and design activities. The U.S. Geological Survey (USGS) StreamStats Web application provides convenient access to streamflow statistics for many streamgages by accessing the underlying StreamStatsDB database. In 2016, non-interpretive streamflow statistics were compiled for streamgages located throughout the Nation and stored in StreamStatsDB for use with StreamStats and other applications. Two previously published USGS computer programs that were designed to help calculate streamflow statistics were updated to better support StreamStats as part of this effort. These programs are named “GNWISQ” (Get National Water Information System Streamflow (Q) files), updated to version 1.1.1, and “QSTATS” (Streamflow (Q) Statistics), updated to version 1.1.2.Statistics for 20,438 streamgages that had 1 or more complete years of record during water years 1901 through 2015 were calculated from daily mean streamflow data; 19,415 of these streamgages were within the conterminous United States. About 89 percent of the 20,438 streamgages had 3 or more years of record, and about 65 percent had 10 or more years of record. Drainage areas of the 20,438 streamgages ranged from 0.01 to 1,144,500 square miles. The magnitude of annual average streamflow yields (streamflow per square mile) for these streamgages varied by almost six orders of magnitude, from 0.000029 to 34 cubic feet per second per square mile. About 64 percent of these streamgages did not have any zero-flow days during their available period of record. The 18,122 streamgages with 3 or more years of record were included in the StreamStatsDB compilation so they would be available via the StreamStats interface for user-selected streamgages. All the statistics are available in a USGS ScienceBase data release.
Use of hydrologic landscape classification to diagnose streamflow predictability in Oregon
We implement a spatially lumped rainfall-runoff model to predict daily streamflow at 88 catchments within Oregon, USA and analyze its performance within the context of Oregon Hydrologic Landscapes (OHL) classification. OHL classification is used to characterize the physio-climat...
USDA-ARS?s Scientific Manuscript database
Understanding and prediction of snowmelt-generated streamflow at sub-daily time scales is important for reservoir scheduling and climate change characterization. This is particularly important in the Western U.S. where over 50% of water supply is provided by snowmelt during the melting period. Previ...
Improvement of the variable storage coefficient method with water surface gradient as a variable
USDA-ARS?s Scientific Manuscript database
The variable storage coefficient (VSC) method has been used for streamflow routing in continuous hydrological simulation models such as the Agricultural Policy/Environmental eXtender (APEX) and the Soil and Water Assessment Tool (SWAT) for more than 30 years. APEX operates on a daily time step and ...
NASA Astrophysics Data System (ADS)
van Dijk, Albert I. J. M.; Peña-Arancibia, Jorge L.; Wood, Eric F.; Sheffield, Justin; Beck, Hylke E.
2013-05-01
Ideally, a seasonal streamflow forecasting system would ingest skilful climate forecasts and propagate these through calibrated hydrological models initialized with observed catchment conditions. At global scale, practical problems exist in each of these aspects. For the first time, we analyzed theoretical and actual skill in bimonthly streamflow forecasts from a global ensemble streamflow prediction (ESP) system. Forecasts were generated six times per year for 1979-2008 by an initialized hydrological model and an ensemble of 1° resolution daily climate estimates for the preceding 30 years. A post-ESP conditional sampling method was applied to 2.6% of forecasts, based on predictive relationships between precipitation and 1 of 21 climate indices prior to the forecast date. Theoretical skill was assessed against a reference run with historic forcing. Actual skill was assessed against streamflow records for 6192 small (<10,000 km2) catchments worldwide. The results show that initial catchment conditions provide the main source of skill. Post-ESP sampling enhanced skill in equatorial South America and Southeast Asia, particularly in terms of tercile probability skill, due to the persistence and influence of the El Niño Southern Oscillation. Actual skill was on average 54% of theoretical skill but considerably more for selected regions and times of year. The realized fraction of the theoretical skill probably depended primarily on the quality of precipitation estimates. Forecast skill could be predicted as the product of theoretical skill and historic model performance. Increases in seasonal forecast skill are likely to require improvement in the observation of precipitation and initial hydrological conditions.
Cross-entropy clustering framework for catchment classification
NASA Astrophysics Data System (ADS)
Tongal, Hakan; Sivakumar, Bellie
2017-09-01
There is an increasing interest in catchment classification and regionalization in hydrology, as they are useful for identification of appropriate model complexity and transfer of information from gauged catchments to ungauged ones, among others. This study introduces a nonlinear cross-entropy clustering (CEC) method for classification of catchments. The method specifically considers embedding dimension (m), sample entropy (SampEn), and coefficient of variation (CV) to represent dimensionality, complexity, and variability of the time series, respectively. The method is applied to daily streamflow time series from 217 gauging stations across Australia. The results suggest that a combination of linear and nonlinear parameters (i.e. m, SampEn, and CV), representing different aspects of the underlying dynamics of streamflows, could be useful for determining distinct patterns of flow generation mechanisms within a nonlinear clustering framework. For the 217 streamflow time series, nine hydrologically homogeneous clusters that have distinct patterns of flow regime characteristics and specific dominant hydrological attributes with different climatic features are obtained. Comparison of the results with those obtained using the widely employed k-means clustering method (which results in five clusters, with the loss of some information about the features of the clusters) suggests the superiority of the cross-entropy clustering method. The outcomes from this study provide a useful guideline for employing the nonlinear dynamic approaches based on hydrologic signatures and for gaining an improved understanding of streamflow variability at a large scale.
NASA Astrophysics Data System (ADS)
Nickles, C.; Zhao, Y.; Beighley, E.; Durand, M. T.; David, C. H.; Lee, H.
2017-12-01
The Surface Water and Ocean Topography (SWOT) satellite mission is jointly developed by NASA, the French space agency (CNES), with participation from the Canadian and UK space agencies to serve both the hydrology and oceanography communities. The SWOT mission will sample global surface water extents and elevations (lakes/reservoirs, rivers, estuaries, oceans, sea and land ice) at a finer spatial resolution than is currently possible enabling hydrologic discovery, model advancements and new applications that are not currently possible or likely even conceivable. Although the mission will provide global cover, analysis and interpolation of the data generated from the irregular space/time sampling represents a significant challenge. In this study, we explore the applicability of the unique space/time sampling for understanding river discharge dynamics throughout the Ohio River Basin. River network topology, SWOT sampling (i.e., orbit and identified SWOT river reaches) and spatial interpolation concepts are used to quantify the fraction of effective sampling of river reaches each day of the three-year mission. Streamflow statistics for SWOT generated river discharge time series are compared to continuous daily river discharge series. Relationships are presented to transform SWOT generated streamflow statistics to equivalent continuous daily discharge time series statistics intended to support hydrologic applications using low-flow and annual flow duration statistics.
Optimising seasonal streamflow forecast lead time for operational decision making in Australia
NASA Astrophysics Data System (ADS)
Schepen, Andrew; Zhao, Tongtiegang; Wang, Q. J.; Zhou, Senlin; Feikema, Paul
2016-10-01
Statistical seasonal forecasts of 3-month streamflow totals are released in Australia by the Bureau of Meteorology and updated on a monthly basis. The forecasts are often released in the second week of the forecast period, due to the onerous forecast production process. The current service relies on models built using data for complete calendar months, meaning the forecast production process cannot begin until the first day of the forecast period. Somehow, the bureau needs to transition to a service that provides forecasts before the beginning of the forecast period; timelier forecast release will become critical as sub-seasonal (monthly) forecasts are developed. Increasing the forecast lead time to one month ahead is not considered a viable option for Australian catchments that typically lack any predictability associated with snowmelt. The bureau's forecasts are built around Bayesian joint probability models that have antecedent streamflow, rainfall and climate indices as predictors. In this study, we adapt the modelling approach so that forecasts have any number of days of lead time. Daily streamflow and sea surface temperatures are used to develop predictors based on 28-day sliding windows. Forecasts are produced for 23 forecast locations with 0-14- and 21-day lead time. The forecasts are assessed in terms of continuous ranked probability score (CRPS) skill score and reliability metrics. CRPS skill scores, on average, reduce monotonically with increase in days of lead time, although both positive and negative differences are observed. Considering only skilful forecast locations, CRPS skill scores at 7-day lead time are reduced on average by 4 percentage points, with differences largely contained within +5 to -15 percentage points. A flexible forecasting system that allows for any number of days of lead time could benefit Australian seasonal streamflow forecast users by allowing more time for forecasts to be disseminated, comprehended and made use of prior to the commencement of a forecast season. The system would allow for forecasts to be updated if necessary.
Liu, Xiaomang; Yang, Tiantian; Hsu, Koulin; ...
2017-01-10
On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks $-$ Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basinsmore » on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. Finally, the evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Xiaomang; Yang, Tiantian; Hsu, Koulin
On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks $-$ Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basinsmore » on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. Finally, the evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.« less
Statistical summaries of streamflow in Oklahoma through 1999
Tortorelli, R.L.
2002-01-01
Statistical summaries of streamflow records through 1999 for gaging stations in Oklahoma and parts of adjacent states are presented for 188 stations with at least 10 years of streamflow record. Streamflow at 113 of the stations is regulated for specific periods. Data for these periods were analyzed separately to account for changes in streamflow due to regulation by dams or other human modification of streamflow. A brief description of the location, drainage area, and period of record is given for each gaging station. A brief regulation history also is given for stations with a regulated streamflow record. This descriptive information is followed by tables of mean annual discharges, magnitude and probability of exceedance of annual high flows, magnitude and probability of exceedance of annual instantaneous peak flows, durations of daily mean flow, magnitude and probability of non-exceedance of annual low flows, and magnitude and probability of non-exceedance of seasonal low flows.
Jordan recurrent neural network versus IHACRES in modelling daily streamflows
NASA Astrophysics Data System (ADS)
Carcano, Elena Carla; Bartolini, Paolo; Muselli, Marco; Piroddi, Luigi
2008-12-01
SummaryA study of possible scenarios for modelling streamflow data from daily time series, using artificial neural networks (ANNs), is presented. Particular emphasis is devoted to the reconstruction of drought periods where water resource management and control are most critical. This paper considers two connectionist models: a feedforward multilayer perceptron (MLP) and a Jordan recurrent neural network (JNN), comparing network performance on real world data from two small catchments (192 and 69 km 2 in size) with irregular and torrential regimes. Several network configurations are tested to ensure a good combination of input features (rainfall and previous streamflow data) that capture the variability of the physical processes at work. Tapped delayed line (TDL) and memory effect techniques are introduced to recognize and reproduce temporal dependence. Results show a poor agreement when using TDL only, but a remarkable improvement can be obtained with JNN and its memory effect procedures, which are able to reproduce the system memory over a catchment in a more effective way. Furthermore, the IHACRES conceptual model, which relies on both rainfall and temperature input data, is introduced for comparative study. The results suggest that when good input data is unavailable, metric models perform better than conceptual ones and, in general, it is difficult to justify substantial conceptualization of complex processes.
User's manual for computer program BASEPLOT
Sanders, Curtis L.
2002-01-01
The checking and reviewing of daily records of streamflow within the U.S. Geological Survey is traditionally accomplished by hand-plotting and mentally collating tables of data. The process is time consuming, difficult to standardize, and subject to errors in computation, data entry, and logic. In addition, the presentation of flow data on the internet requires more timely and accurate computation of daily flow records. BASEPLOT was developed for checking and review of primary streamflow records within the U.S. Geological Survey. Use of BASEPLOT enables users to (1) provide efficiencies during the record checking and review process, (2) improve quality control, (3) achieve uniformity of checking and review techniques of simple stage-discharge relations, and (4) provide a tool for teaching streamflow computation techniques. The BASEPLOT program produces tables of quality control checks and produces plots of rating curves and discharge measurements; variable shift (V-shift) diagrams; and V-shifts converted to stage-discharge plots, using data stored in the U.S. Geological Survey Automatic Data Processing System database. In addition, the program plots unit-value hydrographs that show unit-value stages, shifts, and datum corrections; input shifts, datum corrections, and effective dates; discharge measurements; effective dates for rating tables; and numeric quality control checks. Checklist/tutorial forms are provided for reviewers to ensure completeness of review and standardize the review process. The program was written for the U.S. Geological Survey SUN computer using the Statistical Analysis System (SAS) software produced by SAS Institute, Incorporated.
Kane, Thomas G.; Bauer, David J.; Martinez, Clair M.
1994-01-01
Streamflow and precipitation data collected at and near Yucca Mountain, Nevada, during water years 1986-90 are presented in this report. The data were collected and compiled as part of the studies by the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, to characterize surface-water hydrology in the Yucca Mountain area. Streamflow data include daily-mean discharges and peak discharges at 5 continuous-record gaging stations, and peak discharges at 10 crest-stage, partial-record stations and 2 miscellaneous sites. Precipitation data include cumulative totals at 20 stations maintained by the U.S. Geological Survey and daily totals at 15 stations maintained by the Weather Service Nuclear Support Office, National Oceanic and Atmospheric Administration.
Dettinger, M.D.; Cayan, D.R.; Meyer, M.K.; Jeton, A.
2004-01-01
Hydrologic responses of river basins in the Sierra Nevada of California to historical and future climate variations and changes are assessed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-yr period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th century until about 1975 when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st century with an attendant +2.5??C warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. The various projected trends in the business-as-usual simulations become readily visible despite realistic simulated natural climatic and hydrologic variability by about 2025. In contrast to these changes that are mostly associated with streamflow timing, long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. A control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995 yields climate and streamflow timing conditions much like the 1980s and 1990s throughout its duration. The availability of continuous climate-change projection outputs and careful design of initial conditions and control experiments, like those utilized here, promise to improve the quality and usability of future climate-change impact assessments.
Hydrometeorological model for streamflow prediction
Tangborn, Wendell V.
1979-01-01
The hydrometeorological model described in this manual was developed to predict seasonal streamflow from water in storage in a basin using streamflow and precipitation data. The model, as described, applies specifically to the Skokomish, Nisqually, and Cowlitz Rivers, in Washington State, and more generally to streams in other regions that derive seasonal runoff from melting snow. Thus the techniques demonstrated for these three drainage basins can be used as a guide for applying this method to other streams. Input to the computer program consists of daily averages of gaged runoff of these streams, and daily values of precipitation collected at Longmire, Kid Valley, and Cushman Dam. Predictions are based on estimates of the absolute storage of water, predominately as snow: storage is approximately equal to basin precipitation less observed runoff. A pre-forecast test season is used to revise the storage estimate and improve the prediction accuracy. To obtain maximum prediction accuracy for operational applications with this model , a systematic evaluation of several hydrologic and meteorologic variables is first necessary. Six input options to the computer program that control prediction accuracy are developed and demonstrated. Predictions of streamflow can be made at any time and for any length of season, although accuracy is usually poor for early-season predictions (before December 1) or for short seasons (less than 15 days). The coefficient of prediction (CP), the chief measure of accuracy used in this manual, approaches zero during the late autumn and early winter seasons and reaches a maximum of about 0.85 during the spring snowmelt season. (Kosco-USGS)
Integrating remotely sensed surface water extent into continental scale hydrology.
Revilla-Romero, Beatriz; Wanders, Niko; Burek, Peter; Salamon, Peter; de Roo, Ad
2016-12-01
In hydrological forecasting, data assimilation techniques are employed to improve estimates of initial conditions to update incorrect model states with observational data. However, the limited availability of continuous and up-to-date ground streamflow data is one of the main constraints for large-scale flood forecasting models. This is the first study that assess the impact of assimilating daily remotely sensed surface water extent at a 0.1° × 0.1° spatial resolution derived from the Global Flood Detection System (GFDS) into a global rainfall-runoff including large ungauged areas at the continental spatial scale in Africa and South America. Surface water extent is observed using a range of passive microwave remote sensors. The methodology uses the brightness temperature as water bodies have a lower emissivity. In a time series, the satellite signal is expected to vary with changes in water surface, and anomalies can be correlated with flood events. The Ensemble Kalman Filter (EnKF) is a Monte-Carlo implementation of data assimilation and used here by applying random sampling perturbations to the precipitation inputs to account for uncertainty obtaining ensemble streamflow simulations from the LISFLOOD model. Results of the updated streamflow simulation are compared to baseline simulations, without assimilation of the satellite-derived surface water extent. Validation is done in over 100 in situ river gauges using daily streamflow observations in the African and South American continent over a one year period. Some of the more commonly used metrics in hydrology were calculated: KGE', NSE, PBIAS%, R 2 , RMSE, and VE. Results show that, for example, NSE score improved on 61 out of 101 stations obtaining significant improvements in both the timing and volume of the flow peaks. Whereas the validation at gauges located in lowland jungle obtained poorest performance mainly due to the closed forest influence on the satellite signal retrieval. The conclusion is that remotely sensed surface water extent holds potential for improving rainfall-runoff streamflow simulations, potentially leading to a better forecast of the peak flow.
Variability and predictability of the streamflows in Coastal and Andean Ecuador
NASA Astrophysics Data System (ADS)
Quishpe-Vásquez, César; Córdoba-Machado, Samir; Palomino-Lemus, Reiner; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María
2017-04-01
The main objective of this study is to examine the variability and the predictability in available water resources in Coastal and Andean Ecuador. For this aim, we use the streamflow data from a network of hydrological stations, provided by the National Institute of Meteorology and Hydrology of Ecuador (IHNAMI), distributed over the Ecuadorian territory and strategically located in the watersheds of its main rivers. A number of 20 stations with a continuous period of daily data covering a period of 42 years (1973-2015) were selected. To analyze the spatio-temporal variability of streamflow in Ecuador, principal component analysis (PCA) along with a study of trends have been applied to the streamflow data at monthly time scales. The significance and magnitude of trends have been analyzed using Man-Kendall test and Sen slope. Moreover, to analyze the predictability of the streamflow, the spatio-temporal effects of the ENSO phenomenon on the country have been evaluated through a correlation analysis using different lags between different El Niño indices (Niño 1+2, Niño Modoki, Trans-Niño and Niño 3.4) and the seasonal streamflow. The results show two main regions that differ in terms of variability. We found that the variations in water resources have a close relationship between the magnitude and the seasonal distribution of the streamflow and the ENSO. However, each index shows a different impact on the streamflow depending on the season and the region. In general, the higher correlations between the ENSO indices and the streamflow are observed in the stations closer to the coast. KEY WORDS: Ecuador streamflow; trends; PCA; variability; predictability; ENSO. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).
This study presents a method to predict flow duration curves (FDCs) and streamflow for ungauged catchments in the Mid-Atlantic Region, USA. We selected 29 catchments from the Appalachian Plateau, Ridge and Valley, and Piedmont physiographic provinces to develop and test the propo...
For many water quality-impaired stream segments, streamflow and water quality monitoring sites are not available. Lack of available streamflow data at impaired ungauged sites leads to uncertainties in total maximum daily load (TMDL) estimation. We developed a technique to minimiz...
Calculation of streamflow statistics for Ontario and the Great Lakes states
Piggott, Andrew R.; Neff, Brian P.
2005-01-01
Basic, flow-duration, and n-day frequency statistics were calculated for 779 current and historical streamflow gages in Ontario and 3,157 streamflow gages in the Great Lakes states with length-of-record daily mean streamflow data ending on December 31, 2000 and September 30, 2001, respectively. The statistics were determined using the U.S. Geological Survey’s SWSTAT and IOWDM, ANNIE, and LIBANNE software and Linux shell and PERL programming that enabled the mass processing of the data and calculation of the statistics. Verification exercises were performed to assess the accuracy of the processing and calculations. The statistics and descriptions, longitudes and latitudes, and drainage areas for each of the streamflow gages are summarized in ASCII text files and ESRI shapefiles.
Holmberg, Michael J.; Stogner, Sr., Robert W.; Bruce, James F.
2016-11-29
To evaluate the influence of military training activities on streamflow and water quality, the U.S. Geological Survey, in cooperation with the U.S. Department of the Army, began a hydrologic data collection network on the U.S. Army Garrison Fort Carson in 1978 and on the Piñon Canyon Maneuver Site in 1983. This report is a summary and characterization of the precipitation, streamflow, and water-quality data collected at 43 sites between October 1, 2012, and September 30, 2014 (water years 2013 and 2014).Variations in the frequency of daily precipitation, seasonal distribution, and seasonal and annual precipitation at 5 stations at the U.S. Army Garrison Fort Carson and 18 stations at or near the Piñon Canyon Maneuver Site were evaluated. Isohyetal diagrams indicated a general pattern of increase in total annual precipitation from east to west at the U.S. Army Garrison Fort Carson and the Piñon Canyon Maneuver Site. Between about 54 and 79 percent of daily precipitation was 0.1 inch or less in magnitude. Precipitation events were larger and more frequent between July and September.Daily streamflow data from 16 sites were used to evaluate temporal and spatial variations in streamflow for the water years 2013 and 2014. At all sites, median daily mean streamflow for the 2-year period ranged from 0.0 to 9.60 cubic feet per second. Daily mean streamflow hydrographs are included in this report. Five sites on the Piñon Canyon Maneuver Site were monitored for peak stage using crest-stage gages.At the Piñon Canyon Maneuver Site, five sites had a stage recorder and precipitation gage, providing a paired streamflow-precipitation dataset. There was a statistically significant correlation between precipitation and streamflow based on Spearman’s rho correlation (rho values ranged from 0.17 to 0.35).Suspended-sediment samples were collected in April through October for water years 2013–14 at one site at the U.S. Army Garrison Fort Carson and five sites at the Piñon Canyon Maneuver Site. Suspended-sediment-transport curves were used to illustrate the relation between streamflow and suspended-sediment concentration. All these sediment-transport curves showed a streamflow dependent suspended-sediment concentration relation except for the U.S. Geological Survey station Bent Canyon Creek at mouth near Timpas, CO.Water-quality data were collected and reported from seven sites on the U.S. Army Garrison Fort Carson and the Piñon Canyon Maneuver Site during water years 2013–14. Sample results exceeding an established water-quality standard were identified. Selected water-quality properties and constituents were stratified to compare spatial variation among selected characteristics using boxplots.Trilinear diagrams were used to classify water type based on ionic concentrations of water-quality samples collected during the study period.At the U.S. Army Garrison Fort Carson and the Piñon Canyon Maneuver Site, 27 samples were classified as very hard or brackish. Seven samples had a lower hardness character relative to the other samples. Four of those nine samples were collected at two U.S. Geological Survey stations (Turkey Creek near Fountain, CO, and Little Fountain Creek above Highway 115 at Fort Carson, CO), which have different geologic makeup. Three samples collected at the Piñon Canyon Maneuver Site had a markedly lower hardness likely because of dilution from an increase in streamflow.
Uncertainty in low-flow data from three streamflow-gaging stations on the upper Verde River, Arizona
Anning, D.W.; ,
2004-01-01
The evaluation of uncertainty in low-flow data collected from three streamflow-gaging stations on the upper Verde River, Arizona, was presented. In downstream order, the stations are Verde River near Paulden, Verde River near Clarkdale, and Verde River near Camp Verde. A monitoring objective of the evaluation was to characterize discharge of the lower flow regime through a variety of procedures such as frequency analysis and base-flow analysis. For Verde River near Paulden and near Camp Verde, the uncertainty of daily low flows can be reduced by decreasing the uncertainty of discharge-measurement frequency, or building an artificial control that would have a stable stage-discharge relation over time.
Web services in the U.S. geological survey streamstats web application
Guthrie, J.D.; Dartiguenave, C.; Ries, Kernell G.
2009-01-01
StreamStats is a U.S. Geological Survey Web-based GIS application developed as a tool for waterresources planning and management, engineering design, and other applications. StreamStats' primary functionality allows users to obtain drainage-basin boundaries, basin characteristics, and streamflow statistics for gaged and ungaged sites. Recently, Web services have been developed that provide the capability to remote users and applications to access comprehensive GIS tools that are available in StreamStats, including delineating drainage-basin boundaries, computing basin characteristics, estimating streamflow statistics for user-selected locations, and determining point features that coincide with a National Hydrography Dataset (NHD) reach address. For the state of Kentucky, a web service also has been developed that provides users the ability to estimate daily time series of drainage-basin average values of daily precipitation and temperature. The use of web services allows the user to take full advantage of the datasets and processes behind the Stream Stats application without having to develop and maintain them. ?? 2009 IEEE.
NASA Technical Reports Server (NTRS)
Schumann, H. H. (Principal Investigator)
1972-01-01
The author has identified the following significant results. Preliminary analysis of DCS data from the USGS Verde River stream flow measuring site indicates the DCS system is furnishing high quality data more frequently than had been expected. During the 43-day period between Nov. 3, and Dec. 15, 1972, 552 DCS transmissions were received during 193 data passes. The amount of data received far exceeded the single high quality transmission per 12-hour period expected from the DCS system. The digital-parallel ERTS-1 data has furnished sufficient to accurately compute mean daily gage heights. These in turn, are used to compute average daily streamflow rates during periods of stable or slowly changing flow conditions. The digital-parallel data has also furnished useful information during peak flow periods. However, the serial-digital DCS capability, currently under development for transmitting streamflow data, should provide data of greater utility for determining times of flood peaks.
NASA Astrophysics Data System (ADS)
Naz, Bibi S.; Kao, Shih-Chieh; Ashfaq, Moetasim; Gao, Huilin; Rastogi, Deeksha; Gangrade, Sudershan
2018-01-01
The magnitude and frequency of hydrometeorological extremes are expected to increase in the conterminous United States (CONUS) over the rest of this century, and their increase will significantly impact water resource management. In this study, we evaluated the large-scale climate change effects on extreme hydrological events and their implications for reservoir inflows in 138 headwater subbasins located upstream of reservoirs across CONUS using the Variable Infiltration Capacity (VIC) hydrologic model. The VIC model was forced with a 10-member ensemble of global circulation models under the Representative Concentration Pathway 8.5 that were dynamically downscaled using a regional climate model (RegCM4) and bias-corrected to 1/24° grid cell resolution. Four commonly used indices, including mean annual flow, annual center timing, 100-year daily high streamflow, and 10-year 7-day average low streamflow were used for evaluation. The results projected an increase in the high streamflow by 44% for a majority of subbasins upstream of flood control reservoirs in the central United States (US) and a decrease in the low streamflow by 11% for subbasins upstream of hydropower reservoirs across the western US. In the eastern US, frequencies of both high and low streamflow were projected to increase in the majority of subbasins upstream of both hydropower and flood control reservoirs. Increased frequencies of both high and low streamflow events can potentially make reservoirs across CONUS more vulnerable to future climate conditions. This study estimates reservoir inflow changes over the next several decades, which can be used to optimize water supply management downstream.
Quantifying mountain block recharge by means of catchment-scale storage-discharge relationships
NASA Astrophysics Data System (ADS)
Ajami, Hoori; Troch, Peter A.; Maddock, Thomas, III; Meixner, Thomas; Eastoe, Chris
2011-04-01
Despite the importance of mountainous catchments for providing freshwater resources, especially in semi-arid regions, little is known about key hydrological processes such as mountain block recharge (MBR). Here we implement a data-based method informed by isotopic data to quantify MBR rates using recession flow analysis. We applied our hybrid method in a semi-arid sky island catchment in southern Arizona, United States. Sabino Creek is a 91 km2 catchment with its sources near the summit of the Santa Catalina Mountains northeast of Tucson. Southern Arizona's climate has two distinct wet seasons separated by prolonged dry periods. Winter frontal storms (November-March) provide about 50% of annual precipitation, and summers are dominated by monsoon convective storms from July to September. Isotope analyses of springs and surface water in the Sabino Creek catchment indicate that streamflow during dry periods is derived from groundwater storage in fractured bedrock. Storage-discharge relationships are derived from recession flow analysis to estimate changes in storage during wet periods. To provide reliable estimates, several corrections and improvements to classic base flow recession analysis are considered. These corrections and improvements include adaptive time stepping, data binning, and the choice of storage-discharge functions. Our analysis shows that (1) incorporating adaptive time steps to correct for streamflow measurement errors improves the coefficient of determination, (2) the quantile method is best for streamflow data binning, (3) the choice of the regression model is critical when the stage-discharge function is used to predict changes in bedrock storage beyond the maximum observed flow in the catchment, and (4) the use of daily or night-time hourly streamflow does not affect the form of the storage-discharge relationship but will impact MBR estimates because of differences in the observed range of streamflow in each series.
NASA Astrophysics Data System (ADS)
Engeland, K.; Steinsland, I.; Petersen-Øverleir, A.; Johansen, S.
2012-04-01
The aim of this study is to assess the uncertainties in streamflow simulations when uncertainties in both observed inputs (precipitation and temperature) and streamflow observations used in the calibration of the hydrological model are explicitly accounted for. To achieve this goal we applied the elevation distributed HBV model operating on daily time steps to a small catchment in high elevation in Southern Norway where the seasonal snow cover is important. The uncertainties in precipitation inputs were quantified using conditional simulation. This procedure accounts for the uncertainty related to the density of the precipitation network, but neglects uncertainties related to measurement bias/errors and eventual elevation gradients in precipitation. The uncertainties in temperature inputs were quantified using a Bayesian temperature interpolation procedure where the temperature lapse rate is re-estimated every day. The uncertainty in the lapse rate was accounted for whereas the sampling uncertainty related to network density was neglected. For every day a random sample of precipitation and temperature inputs were drawn to be applied as inputs to the hydrologic model. The uncertainties in observed streamflow were assessed based on the uncertainties in the rating curve model. A Bayesian procedure was applied to estimate the probability for rating curve models with 1 to 3 segments and the uncertainties in their parameters. This method neglects uncertainties related to errors in observed water levels. Note that one rating curve was drawn to make one realisation of a whole time series of streamflow, thus the rating curve errors lead to a systematic bias in the streamflow observations. All these uncertainty sources were linked together in both calibration and evaluation of the hydrologic model using a DREAM based MCMC routine. Effects of having less information (e.g. missing one streamflow measurement for defining the rating curve or missing one precipitation station) was also investigated.
Hydrograph separation techniques in snowmelt-dominated watersheds
NASA Astrophysics Data System (ADS)
Miller, S.; Miller, S. N.
2017-12-01
This study integrates hydrological, geochemical, and isotopic data for a better understanding of different streamflow generation pathways and residence times in a snowmelt-dominated region. A nested watershed design with ten stream gauging sites recording sub-hourly stream stage has been deployed in a snowmelt-dominated region in southeastern Wyoming, heavily impacted by the recent bark beetle epidemic. LiDAR-derived digital elevation models help elucidate effects from topography and watershed metrics. At each stream gauging site, sub-hourly stream water conductivity and temperature data are also recorded. Hydrograph separation is a useful technique for determining different sources of runoff and how volumes from each source vary over time. Following previous methods, diurnal cycles from sub-hourly recorded streamflow and specific conductance data are analyzed and used to separate hydrographs into overland flow and baseflow components, respectively. A final component, vadose-zone flow, is assumed to be the remaining water from the total hydrograph. With access to snowmelt and precipitation data from nearby instruments, runoff coefficients are calculated for the different mechanisms, providing information on watershed response. Catchments are compared to understand how different watershed characteristics translate snowmelt or precipitation events into runoff. Portable autosamplers were deployed at two of the gauging sites for high-frequency analysis of stream water isotopic composition during peak flow to compare methods of hydrograph separation. Sampling rates of one or two hours can detect the diurnal streamflow cycle common during peak snowmelt. Prior research suggests the bark beetle epidemic has had little effect on annual streamflow patterns; however, several results show an earlier shift in the day of year in which peak annual streamflow is observed. The diurnal cycle is likely to comprise a larger percentage of daily streamflow during snowmelt in post-epidemic forests, as more solar radiation is available to penetrate to the ground surface and induce snowmelt, contributing to the effect of an earlier observed peak annual streamflow.
Simulation of streamflow in the McTier Creek watershed, South Carolina
Feaster, Toby D.; Golden, Heather E.; Odom, Kenneth R.; Lowery, Mark A.; Conrads, Paul; Bradley, Paul M.
2010-01-01
The McTier Creek watershed is located in the Sand Hills ecoregion of South Carolina and is a small catchment within the Edisto River Basin. Two watershed hydrology models were applied to the McTier Creek watershed as part of a larger scientific investigation to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River Basin. The two models are the topography-based hydrological model (TOPMODEL) and the grid-based mercury model (GBMM). TOPMODEL uses the variable-source area concept for simulating streamflow, and GBMM uses a spatially explicit modified curve-number approach for simulating streamflow. The hydrologic output from TOPMODEL can be used explicitly to simulate the transport of mercury in separate applications, whereas the hydrology output from GBMM is used implicitly in the simulation of mercury fate and transport in GBMM. The modeling efforts were a collaboration between the U.S. Geological Survey and the U.S. Environmental Protection Agency, National Exposure Research Laboratory. Calibrations of TOPMODEL and GBMM were done independently while using the same meteorological data and the same period of record of observed data. Two U.S. Geological Survey streamflow-gaging stations were available for comparison of observed daily mean flow with simulated daily mean flow-station 02172300, McTier Creek near Monetta, South Carolina, and station 02172305, McTier Creek near New Holland, South Carolina. The period of record at the Monetta gage covers a broad range of hydrologic conditions, including a drought and a significant wet period. Calibrating the models under these extreme conditions along with the normal flow conditions included in the record enhances the robustness of the two models. Several quantitative assessments of the goodness of fit between model simulations and the observed daily mean flows were done. These included the Nash-Sutcliffe coefficient of model-fit efficiency index, Pearson's correlation coefficient, the root mean square error, the bias, and the mean absolute error. In addition, a number of graphical tools were used to assess how well the models captured the characteristics of the observed data at the Monetta and New Holland streamflow-gaging stations. The graphical tools included temporal plots of simulated and observed daily mean flows, flow-duration curves, single-mass curves, and various residual plots. The results indicated that TOPMODEL and GBMM generally produced simulations that reasonably capture the quantity, variability, and timing of the observed streamflow. For the periods modeled, the total volume of simulated daily mean flows as compared to the total volume of the observed daily mean flow from TOPMODEL was within 1 to 5 percent, and the total volume from GBMM was within 1 to 10 percent. A noticeable characteristic of the simulated hydrographs from both models is the complexity of balancing groundwater recession and flow at the streamgage when flows peak and recede rapidly. However, GBMM results indicate that groundwater recession, which affects the receding limb of the hydrograph, was more difficult to estimate with the spatially explicit curve number approach. Although the purpose of this report is not to directly compare both models, given the characteristics of the McTier Creek watershed and the fact that GBMM uses the spatially explicit curve number approach as compared to the variable-source-area concept in TOPMODEL, GBMM was able to capture the flow characteristics reasonably well.
NASA Astrophysics Data System (ADS)
Kumar, Brijesh; Lakshmi, Venkat
2018-03-01
The paper examines the quality of Tropical Rainfall Monitoring Mission (TRMM) 3B42 V7 precipitation product to simulate the streamflow using Soil Water Assessment Tool (SWAT) model for various rainfall intensities over the Himalayan region. The SWAT model has been set up for Gandak River Basin with 41 sub-basins and 420 HRUs. Five stream gauge locations are used to simulate the streamflow for a time span of 10 years (2000-2010). Daily streamflow for the simulation period is collected from Central Water Commission (CWC), India and Department of Hydrology and Meteorology (DHM), Nepal. The simulation results are found good in terms of Nash-Sutcliffe efficiency (NSE) {>}0.65, coefficient of determination (R2) {>}0.67 and Percentage Bias (PBIAS){<}15%, at each stream gauge sites. Thereafter, we have calculated the PBIAS and RMSE-observations standard deviation ratio (RSR) statistics between TRMM simulated and observed streamflow for various rainfall intensity classes, viz., light ({<}7.5 mm/d), moderate (7.5 to 35.4 mm/d), heavy (35.5 to 124.4 mm/d) and extremely heavy ({>}124.4 mm/d). The PBIAS and RSR show that TRMM simulated streamflow is suitable for moderate to heavy rainfall intensities. However, it does not perform well for light- and extremely-heavy rainfall intensities. The finding of the present work is useful for the problems related to water resources management, irrigation planning and hazard analysis over the Himalayan regions.
A Flexible Framework Hydrological Informatic Modeling System - HIMS
NASA Astrophysics Data System (ADS)
WANG, L.; Wang, Z.; Changming, L.; Li, J.; Bai, P.
2017-12-01
Simulating water cycling process temporally and spatially fitting for the characteristics of the study area was important for floods prediction and streamflow simulation with high accuracy, as soil properties, land scape, climate, and land managements were the critical factors influencing the non-linear relationship of rainfall-runoff at watershed scales. Most existing hydrological models cannot simulate water cycle process at different places with customized mechanisms with fixed single structure and mode. This study develops Hydro-Informatic Modeling System (HIMS) model with modular of each critical hydrological process with multiple choices for various scenarios to solve this problem. HIMS has the structure accounting for two runoff generation mechanisms of infiltration excess and saturation excess and estimated runoff with different methods including Time Variance Gain Model (TVGM), LCM which has good performance at ungauged areas, besides the widely used Soil Conservation Service-Curve Number (SCS-CN) method. Channel routing model contains the most widely used Muskingum, and kinematic wave equation with new solving method. HIMS model performance with its symbolic runoff generation model LCM was evaluated through comparison with the observed streamflow datasets of Lasha river watershed at hourly, daily, and monthly time steps. Comparisons between simulational and obervational streamflows were found with NSE higher than 0.87 and WE within ±20%. Water balance analysis about precipitation, streamflow, actual evapotranspiration (ET), and soil moisture change was conducted temporally at annual time step and it has been proved that HIMS model performance was reliable through comparison with literature results at the Lhasa River watershed.
McKean, Sarah E.; Anderholm, Scott K.
2014-01-01
The Albuquerque Bernalillo County Water Utility Authority supplements the municipal water supply for the Albuquerque metropolitan area, in central New Mexico, with surface water diverted from the Rio Grande. The U.S. Geological Survey, in cooperation with the Albuquerque Bernalillo County Water Utility Authority, undertook this study in which water-chemistry data and historical streamflow were compiled and new water-chemistry data were collected to characterize the water chemistry and streamflow of the San Juan-Chama Project (SJCP). Characterization of streamflow included analysis of the variability of annual streamflow and comparison of the theoretical amount of water that could have been diverted into the SJCP to the actual amount of water that was diverted for the SJCP. Additionally, a seepage investigation was conducted along the channel between Azotea Tunnel Outlet and the streamflow-gaging station at Willow Creek above Heron Reservoir to estimate the magnitude of the gain or loss in streamflow resulting from groundwater interaction over the approximately 10-mile reach. Generally, surface-water chemistry varied with streamflow throughout the year. Streamflow ranged from high flow to low flow on the basis of the quantity of water diverted from the Rio Blanco, Little Navajo River, and Navajo River for the SJCP. Vertical profiles of the water temperature over the depth of the water column at Heron Reservoir indicated that the reservoir is seasonally stratified. The results from the seepage investigations indicated a small amount of loss of streamflow along the channel. Annual variability in streamflow for the SJCP was an indication of the variation in the climate parameters that interact to contribute to streamflow in the Rio Blanco, Little Navajo River, Navajo River, and Willow Creek watersheds. For most years, streamflow at Azotea Tunnel Outlet started in March and continued for approximately 3 months until the middle of July. The majority of annual streamflow at Azotea Tunnel Outlet occurred from May through June, with a median duration of slightly longer than a month. Years with higher maximum daily streamflow generally are associated with higher annual streamflow than years with lower maximum daily streamflow. The amount of water that can be diverted for the SJCP is controlled by the availability of streamflow and is limited by several factors including legal limits for diversion, limits from the SJCP infrastructure including the size of the diversion dams and tunnels, the capacity of Heron Reservoir, and operational constraints that limit when water can be diverted. The average annual streamflow at Azotea Tunnel Outlet was 94,710 acre-feet, and the annual streamflow at Azotea Tunnel Outlet was approximately 75 percent of the annual streamflow available for the SJCP. The average annual percentage of available streamflow not diverted for the SJCP was 14 percent because of structural limitations of the capacity of infrastructure, 1 percent because of limitations of the reservoir storage capacity, and 29 percent because of the limitations from operations. For most years, the annual available streamflow not diverted for unknown reasons exceeded the sum of the water not diverted because of structural, capacity, and operational limitations.
Thomas, Blakemore E.; Pool, Don R.
2006-01-01
This study was done to improve the understanding of trends in streamflow of the San Pedro River in southeastern Arizona. Annual streamflow of the river at Charleston, Arizona, has decreased by more than 50 percent during the 20th century. The San Pedro River is one of the few remaining free-flowing perennial streams in the arid Southwestern United States, and the riparian forest along the river supports several endangered species and is an important habitat for migratory birds. Trends in seasonal and annual precipitation and streamflow were evaluated for surrounding areas in southeastern Arizona and southwestern New Mexico to provide a regional perspective for the trends of the San Pedro River. Seasonal and annual streamflow trends and the relation between precipitation and streamflow in the San Pedro River Basin were evaluated to improve the understanding of the causes of trends. There were few significant trends in seasonal and annual precipitation or streamflow for the regional study area. Precipitation and streamflow records were analyzed for 11 time periods ranging from 1930 to 2002; no significant trends were found in 92 percent of the trend tests for precipitation, and no significant trends were found in 79 percent of the trend tests for streamflow. For the trends in precipitation that were significant, 90 percent were positive and most of those positive trends were in records of winter, spring, or annual precipitation that started during the mid-century drought in 1945-60. For the trends in streamflow that were significant, about half were positive and half were negative. Trends in precipitation in the San Pedro River Basin were similar to regional precipitation trends for spring and fall values and were different for summer and annual values. The largest difference was in annual precipitation, for which no trend tests were significant in the San Pedro River Basin, and 23 percent of the trend tests were significantly positive in the rest of the study area. Streamflow trends for the San Pedro River were different from regional streamflow trends. All seasonal flows for the San Pedro River, except winter flows, had significant decreasing trends, and seasonal flows for most streams in the rest of the study area had either no trend or a significant increasing trend. Two streams adjacent to the San Pedro River Basin (Whitewater Draw and Santa Cruz River), however, had significant decreasing trends in summer streamflow. Factors that caused the decreasing trends in streamflow of the San Pedro River at Charleston were investigated. Possible factors were fluctuations in precipitation and air temperature, changes in watershed characteristics, human activities, or changes in seasonal distribution of bank storage. This study statistically removed or accounted for the variation in streamflow caused by fluctuations in precipitation. Thus, the remaining variation or trend in streamflow was caused by factors other than precipitation. Two methods were used to partition the variation in streamflow and to determine trends in the partitioned variation: (1) regression analysis between precipitation and streamflow using all years in the record and evaluation of time trends in regression residuals, and (2) development of regression equations between precipitation and streamflow for three time periods (early, middle, and late parts of the record) and testing to determine if the three regression equations were significantly different. The methods were applied to monthly values of total flow (average flow) and storm runoff (maximum daily mean flow) for 1913-2002, and to monthly values of low flow (3-day low flow) for 1931-2002. Statistical tests provide strong evidence that factors other than precipitation caused a decrease in streamflow of the San Pedro River. Factors other than precipitation caused significant decreasing trends in streamflows for late spring through early winter and did not cause significant trends f
Assessing the skill of seasonal precipitation and streamflow forecasts in sixteen French catchments
NASA Astrophysics Data System (ADS)
Crochemore, Louise; Ramos, Maria-Helena; Pappenberger, Florian
2015-04-01
Meteorological centres make sustained efforts to provide seasonal forecasts that are increasingly skilful. Streamflow forecasting is one of the many applications than can benefit from these efforts. Seasonal flow forecasts generated using seasonal ensemble precipitation forecasts as input to a hydrological model can help to take anticipatory measures for water supply reservoir operation or drought risk management. The objective of the study is to assess the skill of seasonal precipitation and streamflow forecasts in France. First, we evaluated the skill of ECMWF SYS4 seasonal precipitation forecasts for streamflow forecasting in sixteen French catchments. Daily flow forecasts were produced using raw seasonal precipitation forecasts as input to the GR6J hydrological model. Ensemble forecasts are issued every month with 15 or 51 members according to the month of the year and evaluated for up to 90 days ahead. In a second step, we applied eight variants of bias correction approaches to the precipitation forecasts prior to generating the flow forecasts. The approaches were based on the linear scaling and the distribution mapping methods. The skill of the ensemble forecasts was assessed in accuracy (MAE), reliability (PIT Diagram) and overall performance (CRPS). The results show that, in most catchments, raw seasonal precipitation and streamflow forecasts are more skilful in terms of accuracy and overall performance than a reference prediction based on historic observed precipitation and watershed initial conditions at the time of forecast. Reliability is the only attribute that is not significantly improved. The skill of the forecasts is, in general, improved when applying bias correction. Two bias correction methods showed the best performance for the studied catchments: the simple linear scaling of monthly values and the empirical distribution mapping of daily values. L. Crochemore is funded by the Interreg IVB DROP Project (Benefit of governance in DROught adaPtation).
NASA Astrophysics Data System (ADS)
Leta, O. T.; El-Kadi, A. I.; Dulaiova, H.
2016-12-01
Extreme events, such as flooding and drought, are expected to occur at increased frequencies worldwide due to climate change influencing the water cycle. This is particularly critical for tropical islands where the local freshwater resources are very sensitive to climate. This study examined the impact of climate change on extreme streamflow, reservoir water volume and outflow for the Nuuanu watershed, using the Soil and Water Assessment Tool (SWAT) model. Based on the sensitive parameters screened by the Latin Hypercube-One-factor-At-a-Time (LH-OAT) method, SWAT was calibrated and validated to daily streamflow using the SWAT Calibration and Uncertainty Program (SWAT-CUP) at three streamflow gauging stations. Results showed that SWAT adequately reproduced the observed daily streamflow hydrographs at all stations. This was verified with Nash-Sutcliffe Efficiency that resulted in acceptable values of 0.58 to 0.88, whereby more than 90% of observations were bracketed within 95% model prediction uncertainty interval for both calibration and validation periods, signifying the potential applicability of SWAT for future prediction. The climate change impact on extreme flows, reservoir water volume and outflow was assessed under the Representative Concentration Pathways of 4.5 and 8.5 scenarios. We found wide changes in extreme peak and low flows ranging from -44% to 20% and -50% to -2%, respectively, compared to baseline. Consequently, the amount of water stored in Nuuanu reservoir will be decreased up to 27% while the corresponding outflow rates are expected to decrease up to 37% relative to the baseline. In addition, the stored water and extreme flows are highly sensitive to rainfall change when compared to temperature and solar radiation changes. It is concluded that the decrease in extreme low and peak flows can have serious consequences, such as flooding, drought, with detrimental effects on riparian ecological functioning. This study's results are expected to aid in reservoir operation as well as in identifying appropriate climate change adaptation strategies.
Techniques for estimating selected streamflow characteristics of rural unregulated streams in Ohio
Koltun, G.F.; Whitehead, Matthew T.
2002-01-01
This report provides equations for estimating mean annual streamflow, mean monthly streamflows, harmonic mean streamflow, and streamflow quartiles (the 25th-, 50th-, and 75th-percentile streamflows) as a function of selected basin characteristics for rural, unregulated streams in Ohio. The equations were developed from streamflow statistics and basin-characteristics data for as many as 219 active or discontinued streamflow-gaging stations on rural, unregulated streams in Ohio with 10 or more years of homogenous daily streamflow record. Streamflow statistics and basin-characteristics data for the 219 stations are presented in this report. Simple equations (based on drainage area only) and best-fit equations (based on drainage area and at least two other basin characteristics) were developed by means of ordinary least-squares regression techniques. Application of the best-fit equations generally involves quantification of basin characteristics that require or are facilitated by use of a geographic information system. In contrast, the simple equations can be used with information that can be obtained without use of a geographic information system; however, the simple equations have larger prediction errors than the best-fit equations and exhibit geographic biases for most streamflow statistics. The best-fit equations should be used instead of the simple equations whenever possible.
A comparison of hydrologic models for ecological flows and water availability
Peter V. Caldwell; Jonathan G. Kennen; Ge Sun; Julie E. Kiang; Jon B. Butcher; Michele C. Eddy; Lauren E. Hay; Jacob H. LaFontaine; Ernie F. Hain; Stacy A. C. Nelson; Steve G. McNulty
2015-01-01
Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems and reliable water supplies for people, but there is a lack of comprehensive model comparison studies that quantify differences in streamflow predictions among model applications developed to answer management questions. We assessed differences in daily streamflow...
Methods for estimating drought streamflow probabilities for Virginia streams
Austin, Samuel H.
2014-01-01
Maximum likelihood logistic regression model equations used to estimate drought flow probabilities for Virginia streams are presented for 259 hydrologic basins in Virginia. Winter streamflows were used to estimate the likelihood of streamflows during the subsequent drought-prone summer months. The maximum likelihood logistic regression models identify probable streamflows from 5 to 8 months in advance. More than 5 million streamflow daily values collected over the period of record (January 1, 1900 through May 16, 2012) were compiled and analyzed over a minimum 10-year (maximum 112-year) period of record. The analysis yielded the 46,704 equations with statistically significant fit statistics and parameter ranges published in two tables in this report. These model equations produce summer month (July, August, and September) drought flow threshold probabilities as a function of streamflows during the previous winter months (November, December, January, and February). Example calculations are provided, demonstrating how to use the equations to estimate probable streamflows as much as 8 months in advance.
Changes in the timing of snowmelt and streamflow in Colorado: A response to recent warming
Clow, David W.
2010-01-01
Trends in the timing of snowmelt and associated runoff in Colorado were evaluated for the 1978-2007 water years using the regional Kendall test (RKT) on daily snow-water equivalent (SWE) data from snowpack telemetry (SNOTEL) sites and daily streamflow data from headwater streams. The RKT is a robust, nonparametric test that provides an increased power of trend detection by grouping data from multiple sites within a given geographic region. The RKT analyses indicated strong, pervasive trends in snowmelt and streamflow timing, which have shifted toward earlier in the year by a median of 2-3 weeks over the 29-yr study period. In contrast, relatively few statistically significant trends were detected using simple linear regression. RKT analyses also indicated that November-May air temperatures increased by a median of 0.9 degrees C decade-1, while 1 April SWE and maximum SWE declined by a median of 4.1 and 3.6 cm decade-1, respectively. Multiple linear regression models were created, using monthly air temperatures, snowfall, latitude, and elevation as explanatory variables to identify major controlling factors on snowmelt timing. The models accounted for 45% of the variance in snowmelt onset, and 78% of the variance in the snowmelt center of mass (when half the snowpack had melted). Variations in springtime air temperature and SWE explained most of the interannual variability in snowmelt timing. Regression coefficients for air temperature were negative, indicating that warm temperatures promote early melt. Regression coefficients for SWE, latitude, and elevation were positive, indicating that abundant snowfall tends to delay snowmelt, and snowmelt tends to occur later at northern latitudes and high elevations. Results from this study indicate that even the mountains of Colorado, with their high elevations and cold snowpacks, are experiencing substantial shifts in the timing of snowmelt and snowmelt runoff toward earlier in the year.
Wilby, Robert L.; Dettinger, Michael D.
2000-01-01
Simulations of future climate using general circulation models (GCMs) suggest that rising concentrations of greenhouse gases may have significant consequences for the global climate. Of less certainty is the extent to which regional scale (i.e., sub-GCM grid) environmental processes will be affected. In this chapter, a range of downscaling techniques are critiqued. Then a relatively simple (yet robust) statistical downscaling technique and its use in the modelling of future runoff scenarios for three river basins in the Sierra Nevada, California, is described. This region was selected because GCM experiments driven by combined greenhouse-gas and sulphate-aerosol forcings consistently show major changes in the hydro-climate of the southwest United States by the end of the 21st century. The regression-based downscaling method was used to simulate daily rainfall and temperature series for streamflow modelling in three Californian river basins under current-and future-climate conditions. The downscaling involved just three predictor variables (specific humidity, zonal velocity component of airflow, and 500 hPa geopotential heights) supplied by the U.K. Meteorological Office couple ocean-atmosphere model (HadCM2) for the grid point nearest the target basins. When evaluated using independent data, the model showed reasonable skill at reproducing observed area-average precipitation, temperature, and concomitant streamflow variations. Overall, the downscaled data resulted in slight underestimates of mean annual streamflow due to underestimates of precipitation in spring and positive temperature biases in winter. Differences in the skill of simulated streamflows amongst the three basins were attributed to the smoothing effects of snowpack on streamflow responses to climate forcing. The Merced and American River basins drain the western, windward slope of the Sierra Nevada and are snowmelt dominated, whereas the Carson River drains the eastern, leeward slope and is a mix of rainfall runoff and snowmelt runoff. Simulated streamflow in the American River responds rapidly and sensitively to daily-scale temperature and precipitation fluctuations and errors; in the Merced and Carson Rivers, the response to the same short-term influences is much less. Consequently, the skill of simulated flows was significantly lower in the American River model than in the Carson and Merced. The physiography of the three basins also accounts for differences in their sensitivities to future climate change. Increases in winter precipitation exceeding +100% coupled with mean temperature rises greater than +2°C result in increased winter streamflows in all three basins. In the Merced and Carson basins, these streamflow increases reflect large changes in winter snowpack, whereas the streamflow changes in the lower elevation American basin are driven primarily by rainfall runoff. Furthermore, reductions in winter snowpack in the American River basin, owing to less precipitation falling as snow and earlier melting of snow at middle elevations, lead to less spring and summer streamflow. Taken collectively, the downscaling results suggest significant changes to both the timing and magnitude of streamflows in the Sierra Nevada by the end of the 21st Century. In the higher elevation basins, the HadCM2 scenario implies more annual streamflow and more streamflow during the spring and summer months that are critical for water-resources management in California. Depending on the relative significance of rainfall runoff and snowmelt, each basin responds in its own way to regional climate forcing. Generally, then, climate scenarios need to be specified — by whatever means — with sufficient temporal and spatial resolution to capture subtle orographic influences if projections of climate-change responses are to be useful and reproducible.
Modeling Streamflow and Water Temperature in the North Santiam and Santiam Rivers, Oregon, 2001-02
Sullivan, Annett B.; Roundsk, Stewart A.
2004-01-01
To support the development of a total maximum daily load (TMDL) for water temperature in the Willamette Basin, the laterally averaged, two-dimensional model CE-QUAL-W2 was used to construct a water temperature and streamflow model of the Santiam and North Santiam Rivers. The rivers were simulated from downstream of Detroit and Big Cliff dams to the confluence with the Willamette River. Inputs to the model included bathymetric data, flow and temperature from dam releases, tributary flow and temperature, and meteorologic data. The model was calibrated for the period July 1 through November 21, 2001, and confirmed with data from April 1 through October 31, 2002. Flow calibration made use of data from two streamflow gages and travel-time and river-width data. Temperature calibration used data from 16 temperature monitoring locations in 2001 and 5 locations in 2002. A sensitivity analysis was completed by independently varying input parameters, including point-source flow, air temperature, flow and water temperature from dam releases, and riparian shading. Scenario analyses considered hypothetical river conditions without anthropogenic heat inputs, with restored riparian vegetation, with minimum streamflow from the dams, and with a more-natural seasonal water temperature regime from dam releases.
Luo, Chuan; Jiang, Kaixia; Wan, Rongrong; Li, Hengpeng
2017-01-01
The Hydrological Simulation Program–Fortran (HSPF) is a hydrological and water quality computer model that was developed by the United States Environmental Protection Agency. Comprehensive performance evaluations were carried out for hydrological and nutrient simulation using the HSPF model in the Xitiaoxi watershed in China. Streamflow simulation was calibrated from 1 January 2002 to 31 December 2007 and then validated from 1 January 2008 to 31 December 2010 using daily observed data, and nutrient simulation was calibrated and validated using monthly observed data during the period from July 2009 to July 2010. These results of model performance evaluation showed that the streamflows were well simulated over the study period. The determination coefficient (R2) was 0.87, 0.77 and 0.63, and the Nash-Sutcliffe coefficient of efficiency (Ens) was 0.82, 0.76 and 0.65 for the streamflow simulation in annual, monthly and daily time-steps, respectively. Although limited to monthly observed data, satisfactory performance was still achieved during the quantitative evaluation for nutrients. The R2 was 0.73, 0.82 and 0.92, and the Ens was 0.67, 0.74 and 0.86 for nitrate, ammonium and orthophosphate simulation, respectively. Some issues may affect the application of HSPF were also discussed, such as input data quality, parameter values, etc. Overall, the HSPF model can be successfully used to describe streamflow and nutrients transport in the mesoscale watershed located in the East Asian monsoon climate area. This study is expected to serve as a comprehensive and systematic documentation of understanding the HSPF model for wide application and avoiding possible misuses. PMID:29257117
Li, Zhaofu; Luo, Chuan; Jiang, Kaixia; Wan, Rongrong; Li, Hengpeng
2017-12-19
The Hydrological Simulation Program-Fortran (HSPF) is a hydrological and water quality computer model that was developed by the United States Environmental Protection Agency. Comprehensive performance evaluations were carried out for hydrological and nutrient simulation using the HSPF model in the Xitiaoxi watershed in China. Streamflow simulation was calibrated from 1 January 2002 to 31 December 2007 and then validated from 1 January 2008 to 31 December 2010 using daily observed data, and nutrient simulation was calibrated and validated using monthly observed data during the period from July 2009 to July 2010. These results of model performance evaluation showed that the streamflows were well simulated over the study period. The determination coefficient ( R ²) was 0.87, 0.77 and 0.63, and the Nash-Sutcliffe coefficient of efficiency (Ens) was 0.82, 0.76 and 0.65 for the streamflow simulation in annual, monthly and daily time-steps, respectively. Although limited to monthly observed data, satisfactory performance was still achieved during the quantitative evaluation for nutrients. The R ² was 0.73, 0.82 and 0.92, and the Ens was 0.67, 0.74 and 0.86 for nitrate, ammonium and orthophosphate simulation, respectively. Some issues may affect the application of HSPF were also discussed, such as input data quality, parameter values, etc. Overall, the HSPF model can be successfully used to describe streamflow and nutrients transport in the mesoscale watershed located in the East Asian monsoon climate area. This study is expected to serve as a comprehensive and systematic documentation of understanding the HSPF model for wide application and avoiding possible misuses.
NASA Astrophysics Data System (ADS)
David, McInerney; Mark, Thyer; Dmitri, Kavetski; George, Kuczera
2017-04-01
This study provides guidance to hydrological researchers which enables them to provide probabilistic predictions of daily streamflow with the best reliability and precision for different catchment types (e.g. high/low degree of ephemerality). Reliable and precise probabilistic prediction of daily catchment-scale streamflow requires statistical characterization of residual errors of hydrological models. It is commonly known that hydrological model residual errors are heteroscedastic, i.e. there is a pattern of larger errors in higher streamflow predictions. Although multiple approaches exist for representing this heteroscedasticity, few studies have undertaken a comprehensive evaluation and comparison of these approaches. This study fills this research gap by evaluating 8 common residual error schemes, including standard and weighted least squares, the Box-Cox transformation (with fixed and calibrated power parameter, lambda) and the log-sinh transformation. Case studies include 17 perennial and 6 ephemeral catchments in Australia and USA, and two lumped hydrological models. We find the choice of heteroscedastic error modelling approach significantly impacts on predictive performance, though no single scheme simultaneously optimizes all performance metrics. The set of Pareto optimal schemes, reflecting performance trade-offs, comprises Box-Cox schemes with lambda of 0.2 and 0.5, and the log scheme (lambda=0, perennial catchments only). These schemes significantly outperform even the average-performing remaining schemes (e.g., across ephemeral catchments, median precision tightens from 105% to 40% of observed streamflow, and median biases decrease from 25% to 4%). Theoretical interpretations of empirical results highlight the importance of capturing the skew/kurtosis of raw residuals and reproducing zero flows. Recommendations for researchers and practitioners seeking robust residual error schemes for practical work are provided.
Unthank, Michael D.; Newson, Jeremy K.; Williamson, Tanja N.; Nelson, Hugh L.
2012-01-01
Flow- and load-duration curves were constructed from the model outputs of the U.S. Geological Survey's Water Availability Tool for Environmental Resources (WATER) application for streams in Kentucky. The WATER application was designed to access multiple geospatial datasets to generate more than 60 years of statistically based streamflow data for Kentucky. The WATER application enables a user to graphically select a site on a stream and generate an estimated hydrograph and flow-duration curve for the watershed upstream of that point. The flow-duration curves are constructed by calculating the exceedance probability of the modeled daily streamflows. User-defined water-quality criteria and (or) sampling results can be loaded into the WATER application to construct load-duration curves that are based on the modeled streamflow results. Estimates of flow and streamflow statistics were derived from TOPographically Based Hydrological MODEL (TOPMODEL) simulations in the WATER application. A modified TOPMODEL code, SDP-TOPMODEL (Sinkhole Drainage Process-TOPMODEL) was used to simulate daily mean discharges over the period of record for 5 karst and 5 non-karst watersheds in Kentucky in order to verify the calibrated model. A statistical evaluation of the model's verification simulations show that calibration criteria, established by previous WATER application reports, were met thus insuring the model's ability to provide acceptably accurate estimates of discharge at gaged and ungaged sites throughout Kentucky. Flow-duration curves are constructed in the WATER application by calculating the exceedence probability of the modeled daily flow values. The flow-duration intervals are expressed as a percentage, with zero corresponding to the highest stream discharge in the streamflow record. Load-duration curves are constructed by applying the loading equation (Load = Flow*Water-quality criterion) at each flow interval.
NASA Astrophysics Data System (ADS)
Mathevet, T.; Kuentz, A.; Gailhard, J.; Andreassian, V.
2013-12-01
Improving the understanding of mountain watersheds hydrological variability is a great scientific issue, for both researchers and water resources managers, such as Electricite de France (Energy and Hydropower Company). The past and current context of climate variability enhances the interest on this topic, since multi-purposes water resources management is highly sensitive to this variability. The Durance River watershed (14000 km2), situated in the French Alps, is a good example of the complexity of this issue. It is characterized by a variety of hydrological processes (from snowy to Mediterranean regimes) and a wide range of anthropogenic influences (hydropower, irrigation, flood control, tourism and water supply), mixing potential causes of changes in its hydrological regimes. As water related stakes are numerous in this watershed, improving knowledge on the hydrological variability of the Durance River appears to be essential. In this presentation, we would like to focus on a methodology we developed to build long-term historical hydrometeorological time-series, based on atmospheric reanalysis (20CR : 20th Century Reanalysis) and historical local observations. This methodology allowed us to generate precipitation, air temperature and streamflow time-series at a daily time-step for a sample of 22 watersheds, for the 1883-2010 period. These long-term streamflow reconstructions have been validated thanks to historical searches that allowed to bring to light ten long historical series of daily streamflows, beginning on the early 20th century. Reconstructions appear to have rather good statistical properties, with good correlation (greater than 0.8) and limited mean and variance bias (less than 5%). Then, these long-term hydrometeorological time-series allowed us to characterize the past variability in terms of available water resources, droughts or hydrological regime. These analyses help water resources managers to better know the range of hydrological variabilities, which are usually greatly underestimated with classical available time-series (less than 50 years).
Fabian Nippgen; Brian L. McGlynn; Ryan E. Emanuel; James M. Vose
2016-01-01
The rainfall-runoff response of watersheds is affected by the legacy of past hydroclimatic conditions. We examined how variability in precipitation affected streamflow using 21 years of daily streamflow and precipitation data from five watersheds at the Coweeta Hydrologic Laboratory in southwestern North Carolina, USA. The gauged watersheds contained both...
Simulating the effects of ground-water withdrawals on streamflow in a precipitation-runoff model
Zarriello, Philip J.; Barlow, P.M.; Duda, P.B.
2004-01-01
Precipitation-runoff models are used to assess the effects of water use and management alternatives on streamflow. Often, ground-water withdrawals are a major water-use component that affect streamflow, but the ability of surface-water models to simulate ground-water withdrawals is limited. As part of a Hydrologic Simulation Program-FORTRAN (HSPF) precipitation-runoff model developed to analyze the effect of ground-water and surface-water withdrawals on streamflow in the Ipswich River in northeastern Massachusetts, an analytical technique (STRMDEPL) was developed for calculating the effects of pumped wells on streamflow. STRMDEPL is a FORTRAN program based on two analytical solutions that solve equations for ground-water flow to a well completed in a semi-infinite, homogeneous, and isotropic aquifer in direct hydraulic connection to a fully penetrating stream. One analytical method calculates unimpeded flow at the stream-aquifer boundary and the other method calculates the resistance to flow caused by semipervious streambed and streambank material. The principle of superposition is used with these analytical equations to calculate time-varying streamflow depletions due to daily pumping. The HSPF model can readily incorporate streamflow depletions caused by a well or surface-water withdrawal, or by multiple wells or surface-water withdrawals, or both, as a combined time-varying outflow demand from affected channel reaches. These demands are stored as a time series in the Watershed Data Management (WDM) file. This time-series data is read into the model as an external source used to specify flow from the first outflow gate in the reach where these withdrawals are located. Although the STRMDEPL program can be run independently of the HSPF model, an extension was developed to run this program within GenScn, a scenario generator and graphical user interface developed for use with the HSPF model. This extension requires that actual pumping rates for each well be stored in a unique WDM dataset identified by an attribute that associates each well with the model reach from which water is withdrawn. Other attributes identify the type and characteristics of the data. The interface allows users to easily add new pumping wells, delete exiting pumping wells, or change properties of the simulated aquifer or well. Development of this application enhanced the ability of the HSPF model to simulate complex water-use conditions in the Ipswich River Basin. The STRMDEPL program and the GenScn extension provide a valuable tool for water managers to evaluate the effects of pumped wells on streamflow and to test alternative water-use scenarios. Copyright ASCE 2004.
Heimann, David C.; Richards, Joseph M.; Brewer, Shannon K.; Norman, Richard D.
2005-01-01
The U.S. Geological Survey, in cooperation with the Missouri Department of Conservation, undertook a study to quantify fish habitat by using relations between streamflow and the spatial and temporal distributions of fish habitat at five sites in the Marmaton and Marais des Cygnes Rivers in western Missouri. Twenty-six fish habitat categories were selected for nine species under varying seasonal (spring, summer, and fall), diel (summer day and night), and life-stage (spawning, juvenile, and adult) conditions. Physical habitat characteristics were determined for each category using depth, velocity, and channel substrate criteria. Continuous streamflow data were then combined with the habitat-streamflow relations to compile a habitat time series for each habitat category at each site. Fish habitat categories were assessed as to their vulnerability to habitat alteration based on critical life stages (spawning and juvenile rearing periods) and susceptibility to habitat limitations from dewatering or high flows. Species categories representing critical life stages with physical habitat limitations represent likely bottlenecks in fish populations. Categories with potential bottlenecks can serve as indicator categories and aid managers when determining the flows necessary for maintaining these habitats under altered flow regimes. The relation between the area of each habitat category and streamflow differed greatly between category, season, and stream reach. No single flow maximized selected habitat area for all categories or even for all species/category within a particular season at a site. However, some similarities were noted among habitat characteristics, including the streamflow range for which habitat availability is maximized and the range of streamflows for which a habitat category area is available at the Marmaton River sites. A monthly habitat time series was created for all 26 habitat categories at two Marmaton River sites. A daily habitat time series was created at three Marais des Cygnes River sites for two periods: 1941 through 1963 (pre-regulation) and 1982 through 2003 (post-regulation). The habitat category with the highest median area in spring was paddlefish (Polyodon spathula) with normalized areas of up to 2,000 square meters per 100 meters of stream channel. Flathead catfish (Pylodictis olivaris) habitat area generally was the category area most available in summer and fall. Differences in daily selected habitat area time series between pre- and post-regulation time periods varied by species/category and by site. For instance, whereas there was a decline in the distribution of spring spawning habitat for suckermouth minnow (Phenacobius mirabilis) and slenderhead darter (Percina phoxocephala) from pre- to post-regulation periods at all three sites, the 25 to 75 percentile habitat area substantially increased for paddlefish under post-regulation conditions. Potential habitat area for most species was maximized at the Marmaton River sites at flows of about 1 to 10 cubic meters per second, whereas median monthly streamflows ranged from less than 1 to 20 cubic meters per second depending on site and season. Paddlefish habitat was available beginning at higher flows than other categories (4 to 7 cubic meters per second) and also maximized at higher flows (greater than 50 to 100 cubic meters per second). Selected potential habitat area was maximized for most species at the Marais des Cygnes River sites at flows of about 1 to 50 cubic meters per second, whereas median monthly streamflows ranged from 4 to 55 cubic meters per second depending on site and season. The range of streamflows for which selected habitat area was available in summer and fall was substantially less at the channelized Marais des Cygnes River site when compared to the non-channelized sites, and, therefore, the susceptibility of categories to high-flow habitat limitations was greater at this site. The channelized reach was more unifor
NASA Astrophysics Data System (ADS)
Solvang Johansen, Stian; Steinsland, Ingelin; Engeland, Kolbjørn
2016-04-01
Running hydrological models with precipitation and temperature ensemble forcing to generate ensembles of streamflow is a commonly used method in operational hydrology. Evaluations of streamflow ensembles have however revealed that the ensembles are biased with respect to both mean and spread. Thus postprocessing of the ensembles is needed in order to improve the forecast skill. The aims of this study is (i) to to evaluate how postprocessing of streamflow ensembles works for Norwegian catchments within different hydrological regimes and to (ii) demonstrate how post processed streamflow ensembles are used operationally by a hydropower producer. These aims were achieved by postprocessing forecasted daily discharge for 10 lead-times for 20 catchments in Norway by using EPS forcing from ECMWF applied the semi-distributed HBV-model dividing each catchment into 10 elevation zones. Statkraft Energi uses forecasts from these catchments for scheduling hydropower production. The catchments represent different hydrological regimes. Some catchments have stable winter condition with winter low flow and a major flood event during spring or early summer caused by snow melting. Others has a more mixed snow-rain regime, often with a secondary flood season during autumn, and in the coastal areas, the stream flow is dominated by rain, and the main flood season is autumn and winter. For post processing, a Bayesian model averaging model (BMA) close to (Kleiber et al 2011) is used. The model creates a predictive PDF that is a weighted average of PDFs centered on the individual bias corrected forecasts. The weights are here equal since all ensemble members come from the same model, and thus have the same probability. For modeling streamflow, the gamma distribution is chosen as a predictive PDF. The bias correction parameters and the PDF parameters are estimated using a 30-day sliding window training period. Preliminary results show that the improvement varies between catchments depending on where they are situated and the hydrological regime. There is an improvement in CRPS for all catchments compared to raw EPS ensembles. The improvement is up to lead-time 5-7. The postprocessing also improves the MAE for the median of the predictive PDF compared to the median of the raw EPS. But less compared to CRPS, often up to lead-time 2-3. The streamflow ensembles are to some extent used operationally in Statkraft Energi (Hydro Power company, Norway), with respect to early warning, risk assessment and decision-making. Presently all forecast used operationally for short-term scheduling are deterministic, but ensembles are used visually for expert assessment of risk in difficult situations where e.g. there is a chance of overflow in a reservoir. However, there are plans to incorporate ensembles in the daily scheduling of hydropower production.
Simulation of water-quality data at selected stream sites in the Missouri River Basin, Montana
Knapton, J.R.; Jacobson, M.A.
1980-01-01
Modification of sampling programs at some water-quality stations in the Missouri River basin in Montana has eliminated the means by which solute loads have been directly obtained in past years. To compensate for this loss, water-quality and streamflow data were statistically analyzed and solute loads were simulated using computer techniques.Functional relationships existing between specific conductance and solute concentration for monthly samples were used to develop linear regression models. The models were then used to simulate daily solute concentrations using daily specific conductance as the independent variable. Once simulated, the solute concentrations, in milligrams per liter, were transformed into daily solute loads, in tons, using mean daily streamflow records.Computer output was formatted into tables listing simulated mean monthly solute concentrations, in milligrams per liter, and the monthly and annual solute loads, in tons, for water years 1975-78.
Ely, D. Matthew; Kahle, Sue C.
2012-01-01
A three-dimensional, transient numerical model of groundwater and surface-water flow was constructed for Chamokane Creek basin to better understand the groundwater-flow system and its relation to surface-water resources. The model described in this report can be used as a tool by water-management agencies and other stakeholders to quantitatively evaluate the effects of potential increases in groundwater pumping on groundwater and surface-water resources in the basin. The Chamokane Creek model was constructed using the U.S. Geological Survey (USGS) integrated model, GSFLOW. GSFLOW was developed to simulate coupled groundwater and surface-water resources. The model uses 1,000-foot grid cells that subdivide the model domain by 102 rows and 106 columns. Six hydrogeologic units in the model are represented using eight model layers. Daily precipitation and temperature were spatially distributed and subsequent groundwater recharge was computed within GSFLOW. Streamflows in Chamokane Creek and its major tributaries are simulated in the model by routing streamflow within a stream network that is coupled to the groundwater-flow system. Groundwater pumpage and surface-water diversions and returns specified in the model were derived from monthly and annual pumpage values previously estimated from another component of this study and new data reported by study partners. The model simulation period is water years 1980-2010 (October 1, 1979, to September 30, 2010), but the model was calibrated to the transient conditions for water years 1999-2010 (October 1, 1998, to September 30, 2010). Calibration was completed by using traditional trial-and-error methods and automated parameter-estimation techniques. The model adequately reproduces the measured time-series groundwater levels and daily streamflows. At well observation points, the mean difference between simulated and measured hydraulic heads is 7 feet with a root-mean-square error divided by the total difference in water levels of 4.7 percent. Simulated streamflow was compared to measured streamflow at the USGS streamflow-gaging station-Chamokane Creek below Falls, near Long Lake (12433200). Annual differences between measured and simulated streamflow for the site ranged from -63 to 22 percent. Calibrated model output includes a 31-year estimate of monthly water budget components for the hydrologic system. Five model applications (scenarios) were completed to obtain a better understanding of the relation between groundwater pumping and surface-water resources. The calibrated transient model was used to evaluate: (1) the connection between the upper- and middle-basin groundwater systems, (2) the effect of surface-water and groundwater uses in the middle basin, (3) the cumulative impacts of claims registry use and permit-exempt wells on Chamokane Creek streamflow, (4) the frequency of regulation due to impacted streamflow, and (5) the levels of domestic and stockwater use that can be regulated. The simulation results indicated that streamflow is affected by existing groundwater pumping in the upper and middle basins. Simulated water-management scenarios show streamflow increased relative to historical conditions as groundwater and surface-water withdrawals decreased.
Assessment of catchments' flooding potential: a physically-based analytical tool
NASA Astrophysics Data System (ADS)
Botter, G.; Basso, S.; Schirmer, M.
2016-12-01
The assessment of the flooding potential of river catchments is critical in many research and applied fields, ranging from river science and geomorphology to urban planning and the insurance industry. Predicting magnitude and frequency of floods is key to prevent and mitigate the negative effects of high flows, and has therefore long been the focus of hydrologic research. Here, the recurrence intervals of seasonal flow maxima are estimated through a novel physically-based analytic approach, which links the extremal distribution of streamflows to the stochastic dynamics of daily discharge. An analytical expression of the seasonal flood-frequency curve is provided, whose parameters embody climate and landscape attributes of the contributing catchment and can be estimated from daily rainfall and streamflow data. Only one parameter, which expresses catchment saturation prior to rainfall events, needs to be calibrated on the observed maxima. The method has been tested in a set of catchments featuring heterogeneous daily flow regimes. The model is able to reproduce characteristic shapes of flood-frequency curves emerging in erratic and persistent flow regimes and provides good estimates of seasonal flow maxima in different climatic regions. Performances are steady when the magnitude of events with return times longer than the available sample size is estimated. This makes the approach especially valuable for regions affected by data scarcity.
21st Century Projections of High Streamflow Events in the UK and Germany
NASA Astrophysics Data System (ADS)
Cioffi, Francesco; Rosario Conticello, Federico; Lall, Upmanu; Merz, Bruno
2017-04-01
Radiative effects of anthropogenic changes in atmospheric composition are expected to enhance the hydrological cycle leading to more frequent and intense floods. To explore if there will be an increased risk of river flooding in the future, 21st century projections under global warming scenarios of High Streamflow Events (HSEs) for UK and German rivers are carried out, using a model that statistically relates large-scale atmospheric predictors - 850 hPa Geopotential Height (GPH850) and Integrated Water Vapor Transport (IVT) - to the occurrence of HSEs in one or simultaneously in several streamflow gauges. Here, HSE is defined as the streamflow exceeding the 99th percentile of daily flowrate time series measured at streamflow gauges. For the common period 1960-2012, historical data from 57 streamflow gauges in UK and 61 streamflow gauges in Germany, as well as, reanalysis data of GPH850 and IVT fields, bounded from 90W to 70E and from 20N to 80N are used. The link between GPH850 configurations and HSEs, and more precisely, identification of the GPH850 states potentially able to generate HSEs, is performed by a combined Kohonen Networks (Self Organized Map, SOM) and Event Syncronization approach. Complex network and modularity methods are used to cluster streamflow gauges that share common GPH850 configurations. Then a model based on a conditional Poisson distribution, in which the parameter of the Poisson distribution is assumed to be a nonlinear function of GPH850 and IVT, allows for the identification of GPH850 state and threshold of IVT beyond which there is the HSE highest probability. Using that model, projections of 21st century changes in frequency of HSEs occurrence in UK and Germany are estimated using the simulated fields of GPH850 and IVT from selected GCMs belonging to the Coupled Model Inter-comparison Project Phase 5 (CMIP5). Among the different GCMs, those are selected whose retrospective predictor fields have consistent statistics with the corresponding reanalysis data.
Temporal variability in the suspended sediment load and streamflow of the Doce River
NASA Astrophysics Data System (ADS)
Oliveira, Kyssyanne Samihra Santos; Quaresma, Valéria da Silva
2017-10-01
Long-term records of streamflow and suspended sediment load provide a better understanding of the evolution of a river mouth, and its adjacent waters and a support for mitigation programs associated with extreme events and engineering projects. The aim of this study is to investigate the temporal variability in the suspended sediment load and streamflow of the Doce River to the Atlantic Ocean, between 1990 and 2013. Streamflow and suspended sediment load were analyzed at the daily, seasonal, and interannual scales. The results showed that at the daily scale, Doce River flood events are due to high intensity and short duration rainfalls, which means that there is a flashy response to rainfall. At the monthly and season scales, approximately 94% of the suspended sediment supply occurs during the wet season. Extreme hydrological events are important for the interannual scale for Doce River sediment supply to the Atlantic Ocean. The results suggest that a summation of anthropogenic interferences (deforestation, urbanization and soil degradation) led to an increase of extreme hydrological events. The findings of this study shows the importance of understanding the typical behavior of the Doce River, allowing the detection of extreme hydrological conditions, its causes and possible environmental and social consequences.
Gazetteer of hydrologic characteristics of streams in Massachusetts; Housatonic River basin
Wandle, S.W.; Lippert, R.G.
1984-01-01
The Housatonic River basin includes streams that drain 504 square miles in western Massachusetts and 30.5 square miles in eastern New York. Drainage areas, using the latest available 1:24,000 scale topographic maps, were computed for the first time for streams draining more than 3 square miles and were recomputed for data-collection sites. Streamflow characteristics for four gaged streams were calculated using a new data base with daily flow records through 1981. These characteristics include annual and monthly flow statistics, duration of daily flow values, and the annual 7-day mean low flow at the 2-year and 10-year recurrence intervals. Seven-day low-flow statistics are presented for 52 partial-record sites, and the procedures used to determine the hydrologic characteristics of the basin are summarized. Basin characteristics representing 14 commonly used indices to estimate various streamflows are provided for selected gaging stations. This gazetteer will aid in the planning and siting of water-resources related activities and will provide a common data base for governmental agencies and the engineering and planning communities. (USGS)
NASA Astrophysics Data System (ADS)
Betterle, A.; Radny, D.; Schirmer, M.; Botter, G.
2017-12-01
The spatial correlation of daily streamflows represents a statistical index encapsulating the similarity between hydrographs at two arbitrary catchment outlets. In this work, a process-based analytical framework is utilized to investigate the hydrological drivers of streamflow spatial correlation through an extensive application to 78 pairs of stream gauges belonging to 13 unregulated catchments in the eastern United States. The analysis provides insight on how the observed heterogeneity of the physical processes that control flow dynamics ultimately affect streamflow correlation and spatial patterns of flow regimes. Despite the variability of recession properties across the study catchments, the impact of heterogeneous drainage rates on the streamflow spatial correlation is overwhelmed by the spatial variability of frequency and intensity of effective rainfall events. Overall, model performances are satisfactory, with root mean square errors between modeled and observed streamflow spatial correlation below 10% in most cases. We also propose a method for estimating streamflow correlation in the absence of discharge data, which proves useful to predict streamflow regimes in ungauged areas. The method consists in setting a minimum threshold on the modeled flow correlation to individuate hydrologically similar sites. Catchment outlets that are most correlated (ρ>0.9) are found to be characterized by analogous streamflow distributions across a broad range of flow regimes.
NASA Astrophysics Data System (ADS)
Davids, Jeffrey; Rutten, Martine; van de Giesen, Nick; Mehl, Steffen; Norris, James
2016-04-01
Traditional approaches to hydrologic data collection rely on permanent installations of sophisticated and relatively accurate but expensive monitoring equipment at limited numbers of sites. Consequently, the spatial coverage of the data is limited and the cost is high. Moreover, achieving adequate maintenance of the sophisticated equipment often exceeds local technical and resource capacity, and experience has shown that permanently deployed monitoring equipment is susceptible to vandalism, theft, and other hazards. Rather than using expensive, vulnerable installations at a few points, SmartPhones4Water (S4W), a form of citizen science, leverages widely available mobile technology to gather hydrologic data at many sites in a manner that is highly repeatable and scalable. The tradeoff for increased spatial resolution, however, is reduced observation frequency. As a first step towards evaluating the tradeoffs between the traditional continuous monitoring approach and emerging citizen science methods, 50 U.S. Geological Survey (USGS) streamflow gages were randomly selected from the population of roughly 350 USGS gages operated in California. Gaging station metadata and historical 15 minute flow data for the period from 01/10/2007 through 31/12/2014 were compiled for each of the selected gages. Historical 15 minute flow data were then used to develop daily, monthly, and yearly determinations of average, minimum, maximum streamflow, cumulative runoff, and streamflow distribution. These statistics were then compared to similar statistics developed from randomly selected daily and weekly spot measurements of streamflow. Cumulative runoff calculated from daily and weekly observations were within 10 percent of actual runoff calculated from 15 minute data for 75 percent and 46 percent of sites respectively. As anticipated, larger watersheds with less dynamic temporal variability compared more favorably for all statistics evaluated than smaller watersheds. Based on the results of these analyses it appears that, in certain circumstances, citizen science based observations of hydrologic data can provide sufficiently reliable information for both real-time management and water resources planning purposes. To further evaluate the merits of citizen science methodologies, S4W is launching field pilot projects in Nepal.
Environmental Setting of the Sugar Creek and Leary Weber Ditch Basins, Indiana, 2002-04
Lathrop, Timothy R.
2006-01-01
The U.S. Geological Survey operates streamflow-gaging stations at Sugar Creek at New Palestine and at Leary Weber Ditch at Mohawk within the study area. Mean daily streamflow for Sugar Creek is higher than streamflow at Leary Weber Ditch. Through most of its length, Sugar Creek is a gaining stream and base flow is supported by ground-water sources. At Leary Weber Ditch, there is little to no streamflow when tile drains are dry. Modifications to the natural hydrology of the study area include a large system of tile drains, the intersection of Sugar Creek by several major roads, and outflows from nearby wastewater-treatment plants. Leary Weber Ditch is affected only by tile drains.
NASA Astrophysics Data System (ADS)
Moore, R. D.; Mahrlein, M.; Chuang, Y. C. M.
2016-12-01
Forest cover changes associated with natural disturbance and forest management can have significant influences on the magnitude and timing of streamflow. This study quantified the effect of a wildfire that burned over 60% of the catchment of Fishtrap Creek in the southern interior of British Columbia in August 2003. Fishtrap Creek has been gauged from 1970 to present. The catchment drains 158 km2 at the gauging station and has a snow-dominated hydrologic regime. In 2006, about one-third of the burned area was salvage logged. A semi-distributed hydrologic model was calibrated and tested using the pre-fire streamflow data. Simulated daily streamflow based on the "best" parameter set, and assuming pre-fire forest cover, was used as a "virtual" control in a paired-catchment analysis. Each year was divided into 73 five-day periods (pentads), and separate pre-fire regressions were fit for each of the 73 pentad time series. This approach avoids issues with autocorrelation and can address seasonally varying model bias. Statistically significant increases in streamflow were detected in late winter and through the month of April, with no evidence for increased peak flows, which is inferred to reflect a de-synchronization of snowmelt between disturbed and undisturbed areas of the catchment. The results of the model-based change detection are consistent with statistical analyses using climatic variables as covariates, but have the advantage of providing more temporal detail. However, the power of the change detection can be limited by insufficiently long records of streamflow and driving weather variables for both the pre- and post-fire periods and model structural errors (e.g., an inability to reproduce winter baseflow). An interesting side result of the study was the identification of parameter uncertainty associated with uncertainty regarding forest cover during the calibration period.
Factors related to the joint probability of flooding on paired streams
Koltun, G.F.; Sherwood, J.M.
1998-01-01
The factors related to the joint probabilty of flooding on paired streams were investigated and quantified to provide information to aid in the design of hydraulic structures where the joint probabilty of flooding is an element of the design criteria. Stream pairs were considered to have flooded jointly at the design-year flood threshold (corresponding to the 2-, 10-, 25-, or 50-year instantaneous peak streamflow) if peak streamflows at both streams in the pair were observed or predicted to have equaled or exceeded the threshold on a given calendar day. Daily mean streamflow data were used as a substitute for instantaneous peak streamflow data to determine which flood thresholds were equaled or exceeded on any given day. Instantaneous peak streamflow data, when available, were used preferentially to assess flood-threshold exceedance. Daily mean streamflow data for each stream were paired with concurrent daily mean streamflow data at the other streams. Observed probabilities of joint flooding, determined for the 2-, 10-, 25-, and 50-year flood thresholds, were computed as the ratios of the total number of days when streamflows at both streams concurrently equaled or exceeded their flood thresholds (events) to the total number of days where streamflows at either stream equaled or exceeded its flood threshold (trials). A combination of correlation analyses, graphical analyses, and logistic-regression analyses were used to identify and quantify factors associated with the observed probabilities of joint flooding (event-trial ratios). The analyses indicated that the distance between drainage area centroids, the ratio of the smaller to larger drainage area, the mean drainage area, and the centroid angle adjusted 30 degrees were the basin characteristics most closely associated with the joint probabilty of flooding on paired streams in Ohio. In general, the analyses indicated that the joint probabilty of flooding decreases with an increase in centroid distance and increases with increases in drainage area ratio, mean drainage area, and centroid angle adjusted 30 degrees. Logistic-regression equations were developed, which can be used to estimate the probability that streamflows at two streams jointly equal or exceed the 2-year flood threshold given that the streamflow at one of the two streams equals or exceeds the 2-year flood threshold. The logistic-regression equations are applicable to stream pairs in Ohio (and border areas of adjacent states) that are unregulated, free of significant urban influences, and have characteristics similar to those of the 304 gaged stream pairs used in the logistic-regression analyses. Contingency tables were constructed and analyzed to provide information about the bivariate distribution of floods on paired streams. The contingency tables showed that the percentage of trials in which both streams in the pair concurrently flood at identical recurrence-interval ranges generally increased as centroid distances decreased and was greatest for stream pairs with adjusted centroid angles greater than or equal to 60 degrees and drainage area ratios greater than or equal to 0.01. Also, as centroid distance increased, streamflow at one stream in the pair was more likely to be in a less than 2-year recurrence-interval range when streamflow at the second stream was in a 2-year or greater recurrence-interval range.
NASA Astrophysics Data System (ADS)
Rice, Joshua S.; Emanuel, Ryan E.; Vose, James M.; Nelson, Stacy A. C.
2015-08-01
Changes in streamflow are an important area of ongoing research in the hydrologic sciences. To better understand spatial patterns in past changes in streamflow, we examined relationships between watershed-scale spatial characteristics and trends in streamflow. Trends in streamflow were identified by analyzing mean daily flow observations between 1940 and 2009 from 967 U.S. Geological Survey stream gages. Results indicated that streamflow across the continental U.S., as a whole, increased while becoming less extreme between 1940 and 2009. However, substantial departures from the continental U.S. (CONUS) scale pattern occurred at the regional scale, including increased annual maxima, decreased annual minima, overall drying trends, and changes in streamflow variability. A subset of watersheds belonging to a reference data set exhibited significantly smaller trend magnitudes than those observed in nonreference watersheds. Boosted regression tree models were applied to examine the influence of watershed characteristics on streamflow trend magnitudes at both the CONUS and regional scale. Geographic location was found to be of particular importance at the CONUS scale while local variability in hydroclimate and topography tended to have a strong influence on regional-scale patterns in streamflow trends. This methodology facilitates detailed, data-driven analyses of how the characteristics of individual watersheds interact with large-scale hydroclimate forces to influence how changes in streamflow manifest.
Streamflow response to increasing precipitation extremes altered by forest management
NASA Astrophysics Data System (ADS)
Kelly, Charlene N.; McGuire, Kevin J.; Miniat, Chelcy Ford; Vose, James M.
2016-04-01
Increases in extreme precipitation events of floods and droughts are expected to occur worldwide. The increase in extreme events will result in changes in streamflow that are expected to affect water availability for human consumption and aquatic ecosystem function. We present an analysis that may greatly improve current streamflow models by quantifying the impact of the interaction between forest management and precipitation. We use daily long-term data from paired watersheds that have undergone forest harvest or species conversion. We find that interactive effects of climate change, represented by changes in observed precipitation trends, and forest management regime, significantly alter expected streamflow most often during extreme events, ranging from a decrease of 59% to an increase of 40% in streamflow, depending upon management. Our results suggest that vegetation might be managed to compensate for hydrologic responses due to climate change to help mitigate effects of extreme changes in precipitation.
Physical habitat simulation system reference manual: version II
Milhous, Robert T.; Updike, Marlys A.; Schneider, Diane M.
1989-01-01
There are four major components of a stream system that determine the productivity of the fishery (Karr and Dudley 1978). These are: (1) flow regime, (2) physical habitat structure (channel form, substrate distribution, and riparian vegetation), (3) water quality (including temperature), and (4) energy inputs from the watershed (sediments, nutrients, and organic matter). The complex interaction of these components determines the primary production, secondary production, and fish population of the stream reach. The basic components and interactions needed to simulate fish populations as a function of management alternatives are illustrated in Figure I.1. The assessment process utilizes a hierarchical and modular approach combined with computer simulation techniques. The modular components represent the "building blocks" for the simulation. The quality of the physical habitat is a function of flow and, therefore, varies in quality and quantity over the range of the flow regime. The conceptual framework of the Incremental Methodology and guidelines for its application are described in "A Guide to Stream Habitat Analysis Using the Instream Flow Incremental Methodology" (Bovee 1982). Simulation of physical habitat is accomplished using the physical structure of the stream and streamflow. The modification of physical habitat by temperature and water quality is analyzed separately from physical habitat simulation. Temperature in a stream varies with the seasons, local meteorological conditions, stream network configuration, and the flow regime; thus, the temperature influences on habitat must be analysed on a stream system basis. Water quality under natural conditions is strongly influenced by climate and the geological materials, with the result that there is considerable natural variation in water quality. When we add the activities of man, the possible range of water quality possibilities becomes rather large. Consequently, water quality must also be analysed on a stream system basis. Such analysis is outside the scope of this manual, which concentrates on simulation of physical habitat based on depth, velocity, and a channel index. The results form PHABSIM can be used alone or by using a series of habitat time series programs that have been developed to generate monthly or daily habitat time series from the Weighted Usable Area versus streamflow table resulting from the habitat simulation programs and streamflow time series data. Monthly and daily streamflow time series may be obtained from USGS gages near the study site or as the output of river system management models.
Williamson, Tanja N.; Odom, Kenneth R.; Newson, Jeremy K.; Downs, Aimee C.; Nelson, Hugh L.; Cinotto, Peter J.; Ayers, Mark A.
2009-01-01
The Water Availability Tool for Environmental Resources (WATER) was developed in cooperation with the Kentucky Division of Water to provide a consistent and defensible method of estimating streamflow and water availability in ungaged basins. WATER is process oriented; it is based on the TOPMODEL code and incorporates historical water-use data together with physiographic data that quantitatively describe topography and soil-water storage. The result is a user-friendly decision tool that can estimate water availability in non-karst areas of Kentucky without additional data or processing. The model runs on a daily time step, and critical source data include a historical record of daily temperature and precipitation, digital elevation models (DEMs), the Soil Survey Geographic Database (SSURGO), and historical records of water discharges and withdrawals. The model was calibrated and statistically evaluated for 12 basins by comparing the estimated discharge to that observed at U.S. Geological Survey streamflow-gaging stations. When statistically evaluated over a 2,119-day time period, the discharge estimates showed a bias of -0.29 to 0.42, a root mean square error of 1.66 to 5.06, a correlation of 0.54 to 0.85, and a Nash-Sutcliffe Efficiency of 0.26 to 0.72. The parameter and input modifications that most significantly improved the accuracy and precision of streamflow-discharge estimates were the addition of Next Generation radar (NEXRAD) precipitation data, a rooting depth of 30 centimeters, and a TOPMODEL scaling parameter (m) derived directly from SSURGO data that was multiplied by an adjustment factor of 0.10. No site-specific optimization was used.
NASA Astrophysics Data System (ADS)
Shoaib, Syed Abu; Marshall, Lucy; Sharma, Ashish
2018-06-01
Every model to characterise a real world process is affected by uncertainty. Selecting a suitable model is a vital aspect of engineering planning and design. Observation or input errors make the prediction of modelled responses more uncertain. By way of a recently developed attribution metric, this study is aimed at developing a method for analysing variability in model inputs together with model structure variability to quantify their relative contributions in typical hydrological modelling applications. The Quantile Flow Deviation (QFD) metric is used to assess these alternate sources of uncertainty. The Australian Water Availability Project (AWAP) precipitation data for four different Australian catchments is used to analyse the impact of spatial rainfall variability on simulated streamflow variability via the QFD. The QFD metric attributes the variability in flow ensembles to uncertainty associated with the selection of a model structure and input time series. For the case study catchments, the relative contribution of input uncertainty due to rainfall is higher than that due to potential evapotranspiration, and overall input uncertainty is significant compared to model structure and parameter uncertainty. Overall, this study investigates the propagation of input uncertainty in a daily streamflow modelling scenario and demonstrates how input errors manifest across different streamflow magnitudes.
NASA Astrophysics Data System (ADS)
Masih, Ilyas; Ahmad, Mobin-ud-Din; Uhlenbrook, Stefan; Turral, Hugh; Karimi, Poolad
This study provides a comprehensive spatio-temporal assessment of the surface water resources of the semi-arid Karkheh basin, Iran, and consequently enables decision makers to work towards a sustainable water development in that region. The analysis is based on the examination of statistical parameters, flow duration characteristics, base flow separation and trend analysis for which data of seven key gauging stations were used for the period of 1961-2001. Additionally, basin level water accounting was carried out for the water year 1993-94. The study shows that observed daily, monthly and annual streamflows are highly variable in space and time within the basin. The streamflows have not been changed significantly at annual scale, but few months have shown significant trends, most notably a decline during May and June and an increase during December and March. The major causes were related to changes in climate, land use and reservoir operations. The study concludes that the water allocations to different sectors were lower than the totally available resources during the study period. However, looking at the high variability of streamflows, changes in climate and land use and ongoing water resources development planning, it will be extremely difficult to meet the demands of all sectors in the future, particularly during dry years.
Identify the dominant variables to predict stream water temperature
NASA Astrophysics Data System (ADS)
Chien, H.; Flagler, J.
2016-12-01
Stream water temperature is a critical variable controlling water quality and the health of aquatic ecosystems. Accurate prediction of water temperature and the assessment of the impacts of environmental variables on water temperature variation are critical for water resources management, particularly in the context of water quality and aquatic ecosystem sustainability. The objective of this study is to measure stream water temperature and air temperature and to examine the importance of streamflow on stream water temperature prediction. The measured stream water temperature and air temperature will be used to test two hypotheses: 1) streamflow is a relatively more important factor than air temperature in regulating water temperature, and 2) by combining air temperature and streamflow data stream water temperature can be more accurately estimated. Water and air temperature data loggers are placed at two USGS stream gauge stations #01362357and #01362370, located in the upper Esopus Creek watershed in Phonecia, NY. The ARIMA (autoregressive integrated moving average) time series model is used to analyze the measured water temperature data, identify the dominant environmental variables, and predict the water temperature with identified dominant variable. The preliminary results show that streamflow is not a significant variable in predicting stream water temperature at both USGS gauge stations. Daily mean air temperature is sufficient to predict stream water temperature at this site scale.
Simulated CONUS Flash Flood Climatologies from Distributed Hydrologic Models
NASA Astrophysics Data System (ADS)
Flamig, Z.; Gourley, J. J.; Vergara, H. J.; Kirstetter, P. E.; Hong, Y.
2016-12-01
This study will describe a CONUS flash flood climatology created over the period from 2002 through 2011. The MRMS reanalysis precipitation dataset was used as forcing into the Ensemble Framework For Flash Flood Forecasting (EF5). This high resolution 1-sq km 5-minute dataset is ideal for simulating flash floods with a distributed hydrologic model. EF5 features multiple water balance components including SAC-SMA, CREST, and a hydrophobic model all coupled with kinematic wave routing. The EF5/SAC-SMA and EF5/CREST water balance schemes were used for the creation of dual flash flood climatologies based on the differing water balance principles. For the period from 2002 through 2011 the daily maximum streamflow, unit streamflow, and time of peak streamflow was stored along with the minimum soil moisture. These variables are used to describe the states of the soils right before a flash flood event and the peak streamflow that was simulated during the flash flood event. The results will be shown, compared and contrasted. The resulting model simulations will be verified on basins less than 1,000-sq km with USGS gauges to ensure the distributed hydrologic models are reliable. The results will also be compared spatially to Storm Data flash flood event observations to judge the degree of agreement between the simulated climatologies and observations.
Linking river management to species conservation using dynamic landscape scale models
Freeman, Mary C.; Buell, Gary R.; Hay, Lauren E.; Hughes, W. Brian; Jacobson, Robert B.; Jones, John W.; Jones, S.A.; LaFontaine, Jacob H.; Odom, Kenneth R.; Peterson, James T.; Riley, Jeffrey W.; Schindler, J. Stephen; Shea, C.; Weaver, J.D.
2013-01-01
Efforts to conserve stream and river biota could benefit from tools that allow managers to evaluate landscape-scale changes in species distributions in response to water management decisions. We present a framework and methods for integrating hydrology, geographic context and metapopulation processes to simulate effects of changes in streamflow on fish occupancy dynamics across a landscape of interconnected stream segments. We illustrate this approach using a 482 km2 catchment in the southeastern US supporting 50 or more stream fish species. A spatially distributed, deterministic and physically based hydrologic model is used to simulate daily streamflow for sub-basins composing the catchment. We use geographic data to characterize stream segments with respect to channel size, confinement, position and connectedness within the stream network. Simulated streamflow dynamics are then applied to model fish metapopulation dynamics in stream segments, using hypothesized effects of streamflow magnitude and variability on population processes, conditioned by channel characteristics. The resulting time series simulate spatially explicit, annual changes in species occurrences or assemblage metrics (e.g. species richness) across the catchment as outcomes of management scenarios. Sensitivity analyses using alternative, plausible links between streamflow components and metapopulation processes, or allowing for alternative modes of fish dispersal, demonstrate large effects of ecological uncertainty on model outcomes and highlight needed research and monitoring. Nonetheless, with uncertainties explicitly acknowledged, dynamic, landscape-scale simulations may prove useful for quantitatively comparing river management alternatives with respect to species conservation.
NASA Astrophysics Data System (ADS)
Dettinger, M. D.; Cayan, D. R.; Cayan, D. R.; Meyer, M. K.
2001-12-01
Sensitivities of river basins in the Sierra Nevada of California to historical and future climate variations and changes are analyzed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-year period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th Century until about 1975, when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st Century with an attendant +2.5ºC warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. In contrast, a control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995, yields climate and streamflow-timing conditions much like the 1980s and 1990s throughout its duration. Long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. The various projected trends in the business-as-usual simulations become readily visible above simulated natural climatic and hydrologic variability by about 2020.
Dudley, Robert W.; Hodgkins, Glenn A.
2005-01-01
The U.S. Geological Survey (USGS), in cooperation with the Maine Atlantic Salmon Commission (ASC), began a study in 2003 to examine the timing, magnitude, and duration of summer (June through October) and fall/early winter (September through January) seasonal streamflows of unregulated coastal river basins in Maine and to correlate them to meteorological variables and winter/spring (January through May) seasonal streamflows. This study overlapped the summer seasonal window with the fall/early winter seasonal window to completely bracket the low-streamflow period during July, August, and September between periods of high streamflows in June and October. The ASC is concerned with the impacts of potentially changing meteorological and hydrologic conditions on Atlantic salmon survival. Because winter/spring high streamflows appear to have trended toward earlier dates over the 20th century in coastal Maine, it was hypothesized that the spring/summer recession to low streamflows could have a similar trend toward earlier, and possibly lower, longer lasting, late summer/early fall low streamflows during the 20th century. There were few statistically significant trends in the timing, magnitude, or duration of summer low streamflows for coastal river basins in Maine during the 20th century. The hypothesis that earlier winter/spring high streamflows may result in earlier or lower low streamflows is not supported by the data. No statistically significant trends in the magnitude of total runoff volume during the low-streamflow months of August and September were observed. The magnitude and timing of summer low streamflows correlated with the timing of fall/winter high streamflows and the amount of summer precipitation. The magnitude and timing of summer low streamflows did not correlate with the timing of spring snowmelt runoff. There were few correlations between the magnitude and timing of summer low streamflows and monthly mean surface air temperatures. There were few statistically significant trends in the timing or duration of fall/winter high streamflows for coastal river basins in Maine during the 20th century. The timing of the bulk of fall/winter high streamflows correlated with seasonal precipitation. Earlier fall/winter center-of-volume dates correlated with higher September and October precipitation. In general, little evidence was observed of trends in the magnitude of seasonal runoff volume during fall/winter. The magnitude of fall/winter high streamflows positively correlated with November and December precipitation amounts. There were few correlations between the magnitude and timing of fall/winter high streamflows and monthly mean surface air temperatures.
NASA Astrophysics Data System (ADS)
Saharia, M.; Wood, A.; Clark, M. P.; Bennett, A.; Nijssen, B.; Clark, E.; Newman, A. J.
2017-12-01
Most operational streamflow forecasting systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow require an experienced human forecaster. But this approach faces challenges surrounding process reproducibility, hindcasting capability, and extension to large domains. The operational hydrologic community is increasingly moving towards `over-the-loop' (completely automated) large-domain simulations yet recent developments indicate a widespread lack of community knowledge about the strengths and weaknesses of such systems for forecasting. A realistic representation of land surface hydrologic processes is a critical element for improving forecasts, but often comes at the substantial cost of forecast system agility and efficiency. While popular grid-based models support the distributed representation of land surface processes, intermediate-scale Hydrologic Unit Code (HUC)-based modeling could provide a more efficient and process-aligned spatial discretization, reducing the need for tradeoffs between model complexity and critical forecasting requirements such as ensemble methods and comprehensive model calibration. The National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the USACE to implement, assess, and demonstrate real-time, over-the-loop distributed streamflow forecasting for several large western US river basins and regions. In this presentation, we present early results from short to medium range hydrologic and streamflow forecasts for the Pacific Northwest (PNW). We employ a real-time 1/16th degree daily ensemble model forcings as well as downscaled Global Ensemble Forecasting System (GEFS) meteorological forecasts. These datasets drive an intermediate-scale configuration of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model, which represents the PNW using over 11,700 HUCs. The system produces not only streamflow forecasts (using the MizuRoute channel routing tool) but also distributed model states such as soil moisture and snow water equivalent. We also describe challenges in distributed model-based forecasting, including the application and early results of real-time hydrologic data assimilation.
USGS Streamgages Linked to the Medium Resolution NHD
Stewart, David W.; Rea, Alan; Wolock, David M.
2006-01-01
The locations of approximately 23,000 current and historical U.S. Geological Survey (USGS) streamgages in the United States and Puerto Rico (with the exception of Alaska) have been snapped to the medium resolution National Hydrography Dataset (NHD). The NHD contains geospatial information about mapped surface-water features, such as streams, lakes, and reservoirs, etc., creating a hydrologic network that can be used to determine what is upstream or downstream from a point of interest on the NHD network. An automated snapping process made the initial determination of the NHD location of each streamgage. These initial NHD locations were comprehensively reviewed by local USGS personnel to ensure that streamgages were snapped to the correct NHD reaches. About 75 percent of the streamgages snapped to the appropriate NHD reach location initially and 25 percent required adjustment and relocation. This process resulted in approximately 23,000 gages being successfully snapped to the NHD. This dataset contains the latitude and longitude coordinates of the point on the NHD to which the streamgage is snapped and the location of the gage house for each streamgage. A process known as indexing may be used to create reference points (event tables) to the NHD reaches, expressed as a reach code and measure (distance along the reach). Indexing is dependent on the version of NHD to which the indexing is referenced. These data are well suited for use in indexing because nearly all the streamgage NHD locations have been reviewed and adjusted if necessary, to ensure they will index to the appropriate NHD reach. Flow characteristics were computed from the daily streamflow data recorded at each streamgage for the period of record. The flow characteristics associated with each streamgage include: *First date (year, month, day) of streamflow data *Last date (year, month, day) of streamflow data *Number of days of streamflow data *Number of days of non-zero streamflow data *Minimum and maximum daily flow for the period of record (cubic feet per second) *Percentiles (1, 5, 10, 20, 25, 50, 75, 80, 90, 95, 99) of daily flow for the period of record (cubic feet per second) *Average and standard deviation of daily flow for the period of record (cubic feet per second) *Mean annual base-flow index (BFI) computed for the period of record (fraction, ranging from 0 to 1) *Year-to-year standard deviation of the annual base-flow index computed for the period of record (fraction) *Number of years of data used to compute the base-flow index (years) The streamflow data used to compute flow characteristics were copied from the NWIS-Web historical daily discharge archive (nadww01.er.usgs.gov:/www/htdocs/nwisweb/data/discharge) on June 15, 2005.
Farmer, William H.; Archfield, Stacey A.; Over, Thomas M.; Hay, Lauren E.; LaFontaine, Jacob H.; Kiang, Julie E.
2015-01-01
Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water. Streamgages cannot be installed at every location where streamflow information is needed. As part of its National Water Census, the U.S. Geological Survey is planning to provide streamflow predictions for ungaged locations. In order to predict streamflow at a useful spatial and temporal resolution throughout the Nation, efficient methods need to be selected. This report examines several methods used for streamflow prediction in ungaged basins to determine the best methods for regional and national implementation. A pilot area in the southeastern United States was selected to apply 19 different streamflow prediction methods and evaluate each method by a wide set of performance metrics. Through these comparisons, two methods emerged as the most generally accurate streamflow prediction methods: the nearest-neighbor implementations of nonlinear spatial interpolation using flow duration curves (NN-QPPQ) and standardizing logarithms of streamflow by monthly means and standard deviations (NN-SMS12L). It was nearly impossible to distinguish between these two methods in terms of performance. Furthermore, neither of these methods requires significantly more parameterization in order to be applied: NN-SMS12L requires 24 regional regressions—12 for monthly means and 12 for monthly standard deviations. NN-QPPQ, in the application described in this study, required 27 regressions of particular quantiles along the flow duration curve. Despite this finding, the results suggest that an optimal streamflow prediction method depends on the intended application. Some methods are stronger overall, while some methods may be better at predicting particular statistics. The methods of analysis presented here reflect a possible framework for continued analysis and comprehensive multiple comparisons of methods of prediction in ungaged basins (PUB). Additional metrics of comparison can easily be incorporated into this type of analysis. By considering such a multifaceted approach, the top-performing models can easily be identified and considered for further research. The top-performing models can then provide a basis for future applications and explorations by scientists, engineers, managers, and practitioners to suit their own needs.
NASA Astrophysics Data System (ADS)
Bowman, A. L.; Franz, K.; Hogue, T. S.
2015-12-01
We are investigating the implications for use of satellite data in operational streamflow prediction. Specifically, the consequence of potential hydrologic model structure deficiencies on the ability to achieve improved forecast accuracy through the use of satellite data. We want to understand why advanced data do not lead to improved streamflow simulations by exploring how various fluxes and states differ among models of increasing complexity. In a series of prior studies, we investigated the use of a daily satellite-derived potential evapotranspiration (PET) estimate as input to the National Weather Service (NWS) streamflow forecast models for watersheds in the Upper Mississippi and Red river basins. Although the spatial PET product appears to represent the day-to-day variability in PET more realistically than current climatological methods used by the NWS, the impact of the satellite data on streamflow simulations results in slightly poorer model efficiency overall. Analysis of the model states indicates the model progresses differently between simulations with baseline PET and the satellite-derived PET input, though variation in streamflow simulations overall is negligible. For instance, the upper zone states, responsible for the high flows of a hydrograph, show a profound difference, while simulation of the peak flows tend to show little variation in the timing and magnitude. Using the spatial PET input, the lower zone states show improvement with simulating the recession limb and baseflow portion of the hydrograph. We anticipate that through a better understanding of the relationship between model structure, model states, and simulated streamflow we will be able to diagnose why simulations of discharge from the forecast model have failed to improve when provided seemingly more representative input data. Identifying model limitations are critical to demonstrating the full benefit of a satellite data for operational use.
Blodgett, J.C.; Oltmann, R.N.; Poeschel, K.R.
1984-01-01
Daily mean and monthly discharges were estimated for 10 sites on the Carson and Truckee Rivers for periods of incomplete records and for tributary sites affected by reservoir regulation. On the basis of the hydrologic characteristics, stream-flow data for a water year were grouped by month or season for subsequent regression analysis. In most cases, simple linear regressions adequately defined a relation of streamflow between gaging stations, but in some instances a nonlinear relation for several months of the water year was derived. Statistical data are presented to indicate the reliability of the estimated streamflow data. Records of discharges including historical and estimated data for the gaging stations for the water years 1944-80 are presented. (USGS)
Ryberg, Karen R.; Vecchia, Aldo V.
2006-01-01
This report presents the results of a study conducted by the U.S. Geological Survey, in cooperation with the North Dakota State Water Commission, the Devils Lake Basin Joint Water Resource Board, and the Red River Joint Water Resource District, to analyze historical water-quality trends in three dissolved major ions, three nutrients, and one dissolved trace element for eight stations in the Devils Lake Basin in North Dakota and to develop an efficient sampling design to monitor the future trends. A multiple-regression model was used to detect and remove streamflow-related variability in constituent concentrations. To separate the natural variability in concentration as a result of variability in streamflow from the variability in concentration as a result of other factors, the base-10 logarithm of daily streamflow was divided into four components-a 5-year streamflow anomaly, an annual streamflow anomaly, a seasonal streamflow anomaly, and a daily streamflow anomaly. The constituent concentrations then were adjusted for streamflow-related variability by removing the 5-year, annual, seasonal, and daily variability. Constituents used for the water-quality trend analysis were evaluated for a step trend to examine the effect of Channel A on water quality in the basin and a linear trend to detect gradual changes with time from January 1980 through September 2003. The fitted upward linear trends for dissolved calcium concentrations during 1980-2003 for two stations were significant. The fitted step trends for dissolved sulfate concentrations for three stations were positive and similar in magnitude. Of the three upward trends, one was significant. The fitted step trends for dissolved chloride concentrations were positive but insignificant. The fitted linear trends for the upstream stations were small and insignificant, but three of the downward trends that occurred during 1980-2003 for the remaining stations were significant. The fitted upward linear trends for dissolved nitrite plus nitrate as nitrogen concentrations during 1987-2003 for two stations were significant. However, concentrations during recent years appear to be lower than those for the 1970s and early 1980s but higher than those for the late 1980s and early 1990s. The fitted downward linear trend for dissolved ammonia concentrations for one station was significant. The fitted linear trends for total phosphorus concentrations for two stations were significant. Upward trends for total phosphorus concentrations occurred from the late 1980s to 2003 for most stations, but a small and insignificant downward trend occurred for one station. Continued monitoring will be needed to determine if the recent trend toward higher dissolved nitrite plus nitrate as nitrogen and total phosphorus concentrations continues in the future. For continued monitoring of water-quality trends in the upper Devils Lake Basin, an efficient sampling design consists of five major-ion, nutrient, and trace-element samples per year at three existing stream stations and at three existing lake stations. This sampling design requires the collection of 15 stream samples and 15 lake samples per year rather than 16 stream samples and 20 lake samples per year as in the 1992-2003 program. Thus, the design would result in a program that is less costly and more efficient than the 1992-2003 program but that still would provide the data needed to monitor water-quality trends in the Devils Lake Basin.
Thermal effects of dams in the Willamette River basin, Oregon
Rounds, Stewart A.
2010-01-01
Methods were developed to assess the effects of dams on streamflow and water temperature in the Willamette River and its major tributaries. These methods were used to estimate the flows and temperatures that would occur at 14 dam sites in the absence of upstream dams, and river models were applied to simulate downstream flows and temperatures under a no-dams scenario. The dams selected for this study include 13 dams built and operated by the U.S. Army Corps of Engineers (USACE) as part of the Willamette Project, and 1 dam on the Clackamas River owned and operated by Portland General Electric (PGE). Streamflows in the absence of upstream dams for 2001-02 were estimated for USACE sites on the basis of measured releases, changes in reservoir storage, a correction for evaporative losses, and an accounting of flow effects from upstream dams. For the PGE dam, no-project streamflows were derived from a previous modeling effort that was part of a dam-relicensing process. Without-dam streamflows were characterized by higher peak flows in winter and spring and much lower flows in late summer, as compared to with-dam measured flows. Without-dam water temperatures were estimated from measured temperatures upstream of the reservoirs (the USACE sites) or derived from no-project model results (the PGE site). When using upstream data to estimate without-dam temperatures at dam sites, a typical downstream warming rate based on historical data and downstream river models was applied over the distance from the measurement point to the dam site, but only for conditions when the temperature data indicated that warming might be expected. Regressions with measured temperatures from nearby or similar sites were used to extend the without-dam temperature estimates to the entire 2001-02 time period. Without-dam temperature estimates were characterized by a more natural seasonal pattern, with a maximum in July or August, in contrast to the measured patterns at many of the tall dam sites where the annual maximum temperature typically occurred in September or October. Without-dam temperatures also tended to have more daily variation than with-dam temperatures. Examination of the without-dam temperature estimates indicated that dam sites could be grouped according to the amount of streamflow derived from high-elevation, spring-fed, and snowmelt-driven areas high in the Cascade Mountains (Cougar, Big Cliff/Detroit, River Mill, and Hills Creek Dams: Group A), as opposed to flow primarily derived from lower-elevation rainfall-driven drainages (Group B). Annual maximum temperatures for Group A ranged from 15 to 20 degree(s)C, expressed as the 7-day average of the daily maximum (7dADM), whereas annual maximum 7dADM temperatures for Group B ranged from 21 to 25 degrees C. Because summertime stream temperature is at least somewhat dependent on the upstream water source, it was important when estimating without-dam temperatures to use correlations to sites with similar upstream characteristics. For that reason, it also is important to maintain long-term, year-round temperature measurement stations at representative sites in each of the Willamette River basin's physiographic regions. Streamflow and temperature estimates downstream of the major dam sites and throughout the Willamette River were generated using existing CE-QUAL-W2 flow and temperature models. These models, originally developed for the Willamette River water-temperature Total Maximum Daily Load process, required only a few modifications to allow them to run under the greatly reduced without-dam flow conditions. Model scenarios both with and without upstream dams were run. Results showed that Willamette River streamflow without upstream dams was reduced to levels much closer to historical pre-dam conditions, with annual minimum streamflows approximately one-half or less of dam-augmented levels. Thermal effects of the dams varied according to the time of year, from cooling in mid-summer to warm
IOD and ENSO impacts on the extreme stream-flows of Citarum river in Indonesia
NASA Astrophysics Data System (ADS)
Sahu, Netrananda; Behera, Swadhin K.; Yamashiki, Yosuke; Takara, Kaoru; Yamagata, Toshio
2012-10-01
Extreme stream-flow events of Citarum River are derived from the daily stream-flows at the Nanjung gauge station. Those events are identified based on their persistently extreme flows for 6 or more days during boreal fall when the seasonal mean stream-flow starts peaking-up from the lowest seasonal flows of June-August. Most of the extreme events of high-streamflows were related to La Niña conditions of tropical Pacific. A few of them were also associated with the negative phases of IOD and the newly identified El Niño Modoki. Unlike the cases of extreme high streamflows, extreme low streamflow events are seen to be associated with the positive IODs. Nevertheless, it was also found that the low-stream-flow events related to positive IOD events were also associated with El Niño events except for one independent event of 1977. Because the occurrence season coincides the peak season of IOD, not only the picked extreme events are seen to fall under the IOD seasons but also there exists a statistically significant correlation of 0.51 between the seasonal IOD index and the seasonal streamflows. There also exists a significant lag correlation when IOD of June-August season leads the streamflows of September-November. A significant but lower correlation coefficient (0.39) is also found between the seasonal streamflow and El Niño for September-November season only.
NASA Astrophysics Data System (ADS)
Engeland, Kolbjorn; Steinsland, Ingelin
2016-04-01
The aim of this study is to investigate how the inclusion of uncertainties in inputs and observed streamflow influence the parameter estimation, streamflow predictions and model evaluation. In particular we wanted to answer the following research questions: • What is the effect of including a random error in the precipitation and temperature inputs? • What is the effect of decreased information about precipitation by excluding the nearest precipitation station? • What is the effect of the uncertainty in streamflow observations? • What is the effect of reduced information about the true streamflow by using a rating curve where the measurement of the highest and lowest streamflow is excluded when estimating the rating curve? To answer these questions, we designed a set of calibration experiments and evaluation strategies. We used the elevation distributed HBV model operating on daily time steps combined with a Bayesian formulation and the MCMC routine Dream for parameter inference. The uncertainties in inputs was represented by creating ensembles of precipitation and temperature. The precipitation ensemble were created using a meta-gaussian random field approach. The temperature ensembles were created using a 3D Bayesian kriging with random sampling of the temperature laps rate. The streamflow ensembles were generated by a Bayesian multi-segment rating curve model. Precipitation and temperatures were randomly sampled for every day, whereas the streamflow ensembles were generated from rating curve ensembles, and the same rating curve was always used for the whole time series in a calibration or evaluation run. We chose a catchment with a meteorological station measuring precipitation and temperature, and a rating curve of relatively high quality. This allowed us to investigate and further test the effect of having less information on precipitation and streamflow during model calibration, predictions and evaluation. The results showed that including uncertainty in the precipitation and temperature input has a negligible effect on the posterior distribution of parameters and for the Nash-Sutcliffe (NS) efficiency for the predicted flows, while the reliability and the continuous rank probability score (CRPS) improves. Reduced information in precipitation input resulted in a and a shift in the water balance parameter Pcorr, a model producing smoother streamflow predictions giving poorer NS and CRPS, but higher reliability. The effect of calibrating the hydrological model using wrong rating curves is mainly seen as variability in the water balance parameter Pcorr. When evaluating predictions obtained using a wrong rating curve, the evaluation scores varies depending on the true rating curve. Generally, the best evaluation scores were not achieved for the rating curve used for calibration, but for a rating curves giving low variance in streamflow observations. Reduced information in streamflow influenced the water balance parameter Pcorr, and increased the spread in evaluation scores giving both better and worse scores. This case study shows that estimating the water balance is challenging since both precipitation inputs and streamflow observations have pronounced systematic component in their uncertainties.
Petsch, Harold E.
1979-01-01
Statistical summaries of daily streamflow data for 189 stations west of the Continental Divide in Colorado are presented in this report. Duration tables, high-flow sequence tables, and low-flow sequence tables provide information about daily mean discharge. The mean, variance, standard deviation, skewness, and coefficient of variation are provided for monthly and annual flows. Percentages of average flow are provided for monthly flows and first-order serial-correlation coefficients are provided for annual flows. The text explain the nature and derivation of the data and illustrates applications of the tabulated information by examples. The data may be used by agencies and individuals engaged in water studies. (USGS)
NASA Astrophysics Data System (ADS)
Niu, Jun; Chen, Ji; Wang, Keyi; Sivakumar, Bellie
2017-08-01
This paper examines the multi-scale streamflow variability responses to precipitation over 16 headwater catchments in the Pearl River basin, South China. The long-term daily streamflow data (1952-2000), obtained using a macro-scale hydrological model, the Variable Infiltration Capacity (VIC) model, and a routing scheme, are studied. Temporal features of streamflow variability at 10 different timescales, ranging from 6 days to 8.4 years, are revealed with the Haar wavelet transform. The principal component analysis (PCA) is performed to categorize the headwater catchments with the coherent modes of multi-scale wavelet spectra. The results indicate that three distinct modes, with different variability distributions at small timescales and seasonal scales, can explain 95% of the streamflow variability. A large majority of the catchments (i.e. 12 out of 16) exhibit consistent mode feature on multi-scale variability throughout three sub-periods (1952-1968, 1969-1984, and 1985-2000). The multi-scale streamflow variability responses to precipitation are identified to be associated with the regional flood and drought tendency over the headwater catchments in southern China.
Time-varying parameter models for catchments with land use change: the importance of model structure
NASA Astrophysics Data System (ADS)
Pathiraja, Sahani; Anghileri, Daniela; Burlando, Paolo; Sharma, Ashish; Marshall, Lucy; Moradkhani, Hamid
2018-05-01
Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2) in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD) that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors) contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.
NASA Astrophysics Data System (ADS)
Wang, Hong; Sun, Fubao; Xia, Jun; Liu, Wenbin
2017-04-01
Under the Grain for Green Project in China, vegetation recovery construction has been widely implemented on the Loess Plateau for the purpose of soil and water conservation. Now it is becoming controversial whether the recovery construction involving vegetation, particularly forest, is reducing the streamflow in the rivers of the Yellow River basin. In this study, we chose the Wei River, the largest branch of the Yellow River, with revegetated construction area as the study area. To do that, we apply the widely used Soil and Water Assessment Tool (SWAT) model for the upper and middle reaches of the Wei River basin. The SWAT model was forced with daily observed meteorological forcings (1960-2009) calibrated against daily streamflow for 1960-1969, validated for the period of 1970-1979, and used for analysis for 1980-2009. To investigate the impact of LUCC (land use and land cover change) on the streamflow, we firstly use two observed land use maps from 1980 and 2005 that are based on national land survey statistics merged with satellite observations. We found that the mean streamflow generated by using the 2005 land use map decreased in comparison with that using the 1980 one, with the same meteorological forcings. Of particular interest here is that the streamflow decreased on agricultural land but increased in forest areas. More specifically, the surface runoff, soil flow, and baseflow all decreased on agricultural land, while the soil flow and baseflow of forest areas increased. To investigate that, we then designed five scenarios: (S1) the present land use (1980) and (S2) 10 %, (S3) 20 %, (S4) 40 %, and (S5) 100 % of agricultural land that was converted into mixed forest. We found that the streamflow consistently increased with agricultural land converted into forest by about 7.4 mm per 10 %. Our modeling results suggest that forest recovery construction has a positive impact on both soil flow and baseflow by compensating for reduced surface runoff, which leads to a slight increase in the streamflow in the Wei River with the mixed landscapes on the Loess Plateau that include earth-rock mountain area.
Regional regression equations for estimation of natural streamflow statistics in Colorado
Capesius, Joseph P.; Stephens, Verlin C.
2009-01-01
The U.S. Geological Survey (USGS), in cooperation with the Colorado Water Conservation Board and the Colorado Department of Transportation, developed regional regression equations for estimation of various streamflow statistics that are representative of natural streamflow conditions at ungaged sites in Colorado. The equations define the statistical relations between streamflow statistics (response variables) and basin and climatic characteristics (predictor variables). The equations were developed using generalized least-squares and weighted least-squares multilinear regression reliant on logarithmic variable transformation. Streamflow statistics were derived from at least 10 years of streamflow data through about 2007 from selected USGS streamflow-gaging stations in the study area that are representative of natural-flow conditions. Basin and climatic characteristics used for equation development are drainage area, mean watershed elevation, mean watershed slope, percentage of drainage area above 7,500 feet of elevation, mean annual precipitation, and 6-hour, 100-year precipitation. For each of five hydrologic regions in Colorado, peak-streamflow equations that are based on peak-streamflow data from selected stations are presented for the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year instantaneous-peak streamflows. For four of the five hydrologic regions, equations based on daily-mean streamflow data from selected stations are presented for 7-day minimum 2-, 10-, and 50-year streamflows and for 7-day maximum 2-, 10-, and 50-year streamflows. Other equations presented for the same four hydrologic regions include those for estimation of annual- and monthly-mean streamflow and streamflow-duration statistics for exceedances of 10, 25, 50, 75, and 90 percent. All equations are reported along with salient diagnostic statistics, ranges of basin and climatic characteristics on which each equation is based, and commentary of potential bias, which is not otherwise removed by log-transformation of the variables of the equations from interpretation of residual plots. The predictor-variable ranges can be used to assess equation applicability for ungaged sites in Colorado.
NASA Astrophysics Data System (ADS)
Schnier, S.; Cai, X.; Sivapalan, M.
2014-12-01
About half of all humans alive today live in cities, with that number projected to grow to 70% by 2050. Because most people live in cities, urban streamflow patterns and precipitation events have a large impact on the global population. Urban environments can alter natural streamflow and precipitation patterns in a localized area. This study introduces a novel way to characterize this interference: the weekly hydrometeorological signature. Daily streamflow and precipitation data is collected from USGS gages around three climatically-different major American cities: Chicago, Los Angeles, and Charlotte. The following hypothesis is tested: a persistent weekly pattern (Monday through Sunday) exists in the hydrometeorological data which is unique to each city. All three cities appear to exhibit a persistent weekly pattern which is unique to that city for various climatological, industrial, and topographic reasons. Further study is needed; however these findings have important implications for understanding urban weather and can serve as a unique identifier, or fingerprint, for human interference to local streamflow and precipitation patterns.
NASA Astrophysics Data System (ADS)
Davids, J. C.; Rutten, M.; Van De Giesen, N.
2016-12-01
Hydrologic data has traditionally been collected with permanent installations of sophisticated and relatively accurate but expensive monitoring equipment at limited numbers of sites. Consequently, the spatial coverage of the data is limited and costs are high. Achieving adequate maintenance of sophisticated monitoring equipment often exceeds local technical and resource capacity, and permanently deployed monitoring equipment is susceptible to vandalism, theft, and other hazards. Rather than using expensive, vulnerable installations at a few points, SmartPhones4Water (S4W), a form of Citizen Hydrology, leverages widely available mobile technology to gather hydrologic data at many sites in a manner that is repeatable and scalable. However, there is currently a limited understanding of the impact of decreased observational frequency on the accuracy of key streamflow statistics like minimum flow, maximum flow, and runoff. As a first step towards evaluating the tradeoffs between traditional continuous monitoring approaches and emerging Citizen Hydrology methods, we randomly selected 50 active U.S. Geological Survey (USGS) streamflow gauges in California. We used historical 15 minute flow data from 01/01/2008 through 12/31/2014 to develop minimum flow, maximum flow, and runoff values (7 year total) for each gauge. In order to mimic lower frequency Citizen Hydrology observations, we developed a bootstrap randomized subsampling with replacement procedure. We calculated the same statistics, along with their respective distributions, from 50 subsample iterations with four different subsampling intervals (i.e. daily, three day, weekly, and monthly). Based on our results we conclude that, depending on the types of questions being asked, and the watershed characteristics, Citizen Hydrology streamflow measurements can provide useful and accurate information. Depending on watershed characteristics, minimum flows were reasonably estimated with subsample intervals ranging from daily to monthly. However, maximum flows in most cases were poorly characterized, even at daily subsample intervals. In general, runoff volumes were accurately estimated from daily, three day, weekly, and even in some cases, monthly observations.
Granato, Gregory E.
2009-01-01
Streamflow information is important for many planning and design activities including water-supply analysis, habitat protection, bridge and culvert design, calibration of surface and ground-water models, and water-quality assessments. Streamflow information is especially critical for water-quality assessments (Warn and Brew, 1980; Di Toro, 1984; Driscoll and others, 1989; Driscoll and others, 1990, a,b). Calculation of streamflow statistics for receiving waters is necessary to estimate the potential effects of point sources such as wastewater-treatment plants and nonpoint sources such as highway and urban-runoff discharges on receiving water. Streamflow statistics indicate the amount of flow that may be available for dilution and transport of contaminants (U.S. Environmental Protection Agency, 1986; Driscoll and others, 1990, a,b). Streamflow statistics also may be used to indicate receiving-water quality because concentrations of water-quality constituents commonly vary naturally with streamflow. For example, concentrations of suspended sediment and sediment-associated constituents (such as nutrients, trace elements, and many organic compounds) commonly increase with increasing flows, and concentrations of many dissolved constituents commonly decrease with increasing flows in streams and rivers (O'Connor, 1976; Glysson, 1987; Vogel and others, 2003, 2005). Reliable, efficient and repeatable methods are needed to access and process streamflow information and data. For example, the Nation's highway infrastructure includes an innumerable number of stream crossings and stormwater-outfall points for which estimates of stream-discharge statistics may be needed. The U.S. Geological Survey (USGS) streamflow data-collection program is designed to provide streamflow data at gaged sites and to provide information that can be used to estimate streamflows at almost any point along any stream in the United States (Benson and Carter, 1973; Wahl and others, 1995; National Research Council, 2004). The USGS maintains the National Water Information System (NWIS), a distributed network of computers and file servers used to store and retrieve hydrologic data (Mathey, 1998; U.S. Geological Survey, 2008). NWISWeb is an online version of this database that includes water data from more than 24,000 streamflow-gaging stations throughout the United States (U.S. Geological Survey, 2002, 2008). Information from NWISWeb is commonly used to characterize streamflows at gaged sites and to help predict streamflows at ungaged sites. Five computer programs were developed for obtaining and analyzing streamflow from the National Water Information System (NWISWeb). The programs were developed as part of a study by the U.S. Geological Survey, in cooperation with the Federal Highway Administration, to develop a stochastic empirical loading and dilution model. The programs were developed because reliable, efficient, and repeatable methods are needed to access and process streamflow information and data. The first program is designed to facilitate the downloading and reformatting of NWISWeb streamflow data. The second program is designed to facilitate graphical analysis of streamflow data. The third program is designed to facilitate streamflow-record extension and augmentation to help develop long-term statistical estimates for sites with limited data. The fourth program is designed to facilitate statistical analysis of streamflow data. The fifth program is a preprocessor to create batch input files for the U.S. Environmental Protection Agency DFLOW3 program for calculating low-flow statistics. These computer programs were developed to facilitate the analysis of daily mean streamflow data for planning-level water-quality analyses but also are useful for many other applications pertaining to streamflow data and statistics. These programs and the associated documentation are included on the CD-ROM accompanying this report. This report and the appendixes on the
NASA Astrophysics Data System (ADS)
Miller, S.; Miller, S. N.
2016-12-01
Natural diurnal fluctuations in streamflow are common in many types of streams and scales for different reasons (i.e. snowmelt, evapotranspiration, infiltration, precipitation). Scientific literature has placed little consideration on the role diurnal cycles as they may appear insignificant from a water management point of view; however, recent insights into the timing and shape of the diurnal cycle have led to new methods for eco-hydrologic characterization of a given watershed. The diurnal effect is usually not detectible from visual investigation of a stream, but requires a minimum of hourly continuous measurement. In the 1990s the United States Geological Survey began collecting hourly river stage measurements for thousands of stream gauge stations across the US, ushering in new methods of analysis and comparison. A nested watershed study with ten stream gauging stations recording sub-hourly river stage was deployed in a snowmelt-dominated region of the Medicine Bow National Forest in southeastern Wyoming in 2013. In addition, at each stream gauging station sub-hourly conductivity and temperature data was recorded to aid in eco-hydrologic characterization of the different watersheds. Early summer results show asymmetry in the diurnal cycle during snowmelt, with a steeper rising and a flatter falling limb. As snowmelt becomes a less contributing component of streamflow later in the season, the asymmetry shifts to a flatter rising limb and steeper falling limb. Stream conductivity is low during snowmelt and begins to gradually increase as baseflow becomes a larger portion of total streamflow. The study region is recovering from a mountain pine beetle epidemic that peaked in 2008. Prior research suggests the bark beetle epidemic has had little effect on annual streamflow patterns; however, several results show an earlier shift in the day of year in which peak annual streamflow is observed. The diurnal cycle is likely to comprise a larger percentage of daily streamflow during snowmelt in post-epidemic forests, as more solar radiation is available to penetrate to the ground surface and induce snowmelt, contributing to the effect of an earlier observed peak annual streamflow.
NASA Astrophysics Data System (ADS)
Dugger, A. L.; Zhang, Y.; Gochis, D.; Yu, W.; McCreight, J. L.; Karsten, L.; Rafieeinasab, A.; Sampson, K. M.; Salas, F.; Read, L.; Pan, L.; Yates, D. N.; Cosgrove, B.; Clark, E. P.
2017-12-01
Streamflow extremes (lows and peaks) tend to have disproportionately higher impacts on the human and natural systems compared to mean streamflow. Examining and understanding the spatiotemporal distributions of streamflow extremes is of significant interests to both the research community and the water resources management. In this work, the output from the 24-year (1993 through 2016) retrospective runs of the National Water Model (NWM) version of WRF-Hydro will be analyzed for streamflow extremes over the CONUS domain. The CONUS domain was configured at 1-km resolution for land surface grid and 250-m resolution for terrain routing. The WRF-Hydro runs were forced by the regridded and downscaled NLDAS2 data. The analyses focus on daily mean streamflow values over the full water year and within the summer and winter seasons. Connections between NWM streamflow and other hydrologic variables (e.g. snowpack, soil moisture/saturation and ET) with variations in large-scale climate phenomena, e.g., El Niño - Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and North American monsoon are examined. The CONUS domain has a diverse environment and is characterized by complex terrain, heterogeneous land surfaces and ecosystems, and numerous hydrological basins. The potential dependence of streamflow extremes on regional terrain character, climatic conditions, and ecologic zones will also be investigated.
Konrad, Christopher P.
2004-01-01
A precipitation-runoff model for the Methow River Basin was used to simulate six alternatives: (1) baseline of current flow, (2) line irrigation canals to limit seepage losses, (3) increase surface-water diversions through unlined canals for aquifer recharge, (4) convert from surface-water to ground-water resources to supply water for irrigation, and (5) reduce tree density in forested headwater catchments, and (6) natural flow. Daily streamflow from October 1, 1959, to September 30, 2001 (water years 1960?2001) was simulated. Lining irrigation canals (alternative 2) increased flows in the Chewuch, Twisp, and the Methow (upstream and at Twisp) Rivers during September because of lower diversion rates, but not in the Methow River near Pateros. Increasing diversions for aquifer recharge (alternative 3) increased streamflow from September into January, but reduced streamflow earlier in the summer. Conversion of surface-water diversions to ground-water wells (alternative 4) resulted in the largest increase in September streamflow of any alternative, but also marginally lower January flows (at most -8 percent in the 90-percent exceedence value). Forest-cover reduction (alternative 5) produced large increases in streamflow during high-flow periods in May and June and earlier onset of high flows and small increases in January streamflows. September streamflows were largely unaffected by alternative 5. Natural streamflow (alternative 6) was higher in September and lower in January than the baseline alternative.
NASA Astrophysics Data System (ADS)
Betterle, A.; Schirmer, M.; Botter, G.
2017-12-01
Streamflow dynamics strongly influence anthropogenic activities and the ecological functions of riverine and riparian habitats. However, the widespread lack of direct discharge measurements often challenges the set-up of conscious and effective decision-making processes, including droughts and floods protection, water resources management and river restoration practices. By characterizing the spatial correlation of daily streamflow timeseries at two arbitrary locations, this study provides a method to evaluate how spatially variable catchment-scale hydrological process affects the resulting streamflow dynamics along and across river systems. In particular, streamflow spatial correlation is described analytically as a function of morphological, climatic and vegetation properties in the contributing catchments, building on a joint probabilistic description of flow dynamics at pairs of outlets. The approach enables an explicit linkage between similarities of flow dynamics and spatial patterns of hydrologically relevant features of climate and landscape. Therefore, the method is suited to explore spatial patterns of streamflow dynamics across geomorphoclimatic gradients. In particular, we show how the streamflow correlation can be used at the continental scale to individuate catchment pairs with similar hydrological dynamics, thereby providing a useful tool for the estimate of flow duration curves in poorly gauged areas.
Austin, Samuel H.; Nelms, David L.
2017-01-01
Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5-11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best-performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid-Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.
Petsch, Harold E.
1979-01-01
Statistical summaries of daily streamflow data for 246 stations east of the Continental Divide in Colorado and adjacent States are presented in this report. Duration tables, high-flow sequence tables, and low-flow sequence tables provide information about daily mean discharge. The mean, variance, standard deviation, skewness, and coefficient of variation are provided for monthly and annual flows. Percentages of average flow are provided for monthly flows and first-order serial-correlation coefficients are provided for annual flows. The text explains the nature and derivation of the data and illustrates applications of the tabulated information by examples. The data may be used by agencies and individuals engaged in water studies. (USGS)
Viger, Roland J.; Hay, Lauren E.; Jones, John W.; Buell, Gary R.
2010-01-01
This report documents an extension of the Precipitation Runoff Modeling System that accounts for the effect of a large number of water-holding depressions in the land surface on the hydrologic response of a basin. Several techniques for developing the inputs needed by this extension also are presented. These techniques include the delineation of the surface depressions, the generation of volume estimates for the surface depressions, and the derivation of model parameters required to describe these surface depressions. This extension is valuable for applications in basins where surface depressions are too small or numerous to conveniently model as discrete spatial units, but where the aggregated storage capacity of these units is large enough to have a substantial effect on streamflow. In addition, this report documents several new model concepts that were evaluated in conjunction with the depression storage functionality, including: ?hydrologically effective? imperviousness, rates of hydraulic conductivity, and daily streamflow routing. All of these techniques are demonstrated as part of an application in the Upper Flint River Basin, Georgia. Simulated solar radiation, potential evapotranspiration, and water balances match observations well, with small errors for the first two simulated data in June and August because of differences in temperatures from the calibration and evaluation periods for those months. Daily runoff simulations show increasing accuracy with streamflow and a good fit overall. Including surface depression storage in the model has the effect of decreasing daily streamflow for all but the lowest flow values. The report discusses the choices and resultant effects involved in delineating and parameterizing these features. The remaining enhancements to the model and its application provide a more realistic description of basin geography and hydrology that serve to constrain the calibration process to more physically realistic parameter values.
Operational Hydrologic Forecasts in the Columbia River Basin
NASA Astrophysics Data System (ADS)
Shrestha, K. Y.; Curry, J. A.; Webster, P. J.; Toma, V. E.; Jelinek, M.
2013-12-01
The Columbia River Basin (CRB) covers an area of ~670,000 km2 and stretches across parts of seven U.S. states and one Canadian province. The basin is subject to a variable climate, and moisture stored in snowpack during the winter is typically released in spring and early summer. These releases contribute to rapid increases in flow. A number of impoundments have been constructed on the Columbia River main stem and its tributaries for the purposes of flood control, navigation, irrigation, recreation, and hydropower. Storage reservoirs allow water managers to adjust natural flow patterns to benefit water and energy demands. In the past decade, the complexity of water resource management issues in the basin has amplified the importance of streamflow forecasting. Medium-range (1-10 day) numerical weather forecasts of precipitation and temperature can be used to drive hydrological models. In this work, probabilistic meteorological variables from the European Center for Medium Range Weather Forecasting (ECMWF) are used to force the Variable Infiltration Capacity (VIC) model. Soil textures were obtained from FAO data; vegetation types / land cover information from UMD land cover data; stream networks from USGS HYDRO1k; and elevations from CGIAR version 4 SRTM data. The surface energy balance in 0.25° (~25 km) cells is closed through an iterative process operating at a 6 hour timestep. Output fluxes from a number of cells in the basin are combined through one-dimensional flow routing predicated on assumptions of linearity and time invariance. These combinations lead to daily mean streamflow estimates at key locations throughout the basin. This framework is suitable for ingesting daily numerical weather prediction data, and was calibrated using USGS mean daily streamflow data at the Dalles Dam (TDA). Operational streamflow forecasts in the CRB have been active since October 2012. These are 'naturalized' or unregulated forecasts. In 2013, increases of ~2600 m3/s (~48% of average discharge for water years 1879-2012) or greater were observed at TDA during the following periods: 29 March to 12 April, 5 May to 11 May, and 19 June to 29 June. Precipitation and temperature forecasts during these periods are shown along with changes in the model simulated snowpack. We evaluate the performance of the ensemble mean 10 days in advance of each of these three events, and comment on how the distribution of ensemble members affected forecast confidence in each situation.
Streamflow Prediction based on Chaos Theory
NASA Astrophysics Data System (ADS)
Li, X.; Wang, X.; Babovic, V. M.
2015-12-01
Chaos theory is a popular method in hydrologic time series prediction. Local model (LM) based on this theory utilizes time-delay embedding to reconstruct the phase-space diagram. For this method, its efficacy is dependent on the embedding parameters, i.e. embedding dimension, time lag, and nearest neighbor number. The optimal estimation of these parameters is thus critical to the application of Local model. However, these embedding parameters are conventionally estimated using Average Mutual Information (AMI) and False Nearest Neighbors (FNN) separately. This may leads to local optimization and thus has limitation to its prediction accuracy. Considering about these limitation, this paper applies a local model combined with simulated annealing (SA) to find the global optimization of embedding parameters. It is also compared with another global optimization approach of Genetic Algorithm (GA). These proposed hybrid methods are applied in daily and monthly streamflow time series for examination. The results show that global optimization can contribute to the local model to provide more accurate prediction results compared with local optimization. The LM combined with SA shows more advantages in terms of its computational efficiency. The proposed scheme here can also be applied to other fields such as prediction of hydro-climatic time series, error correction, etc.
Living with a large reduction in permited loading by using a hydrograph-controlled release scheme
Conrads, P.A.; Martello, W.P.; Sullins, N.R.
2003-01-01
The Total Maximum Daily Load (TMDL) for ammonia and biochemical oxygen demand for the Pee Dee, Waccamaw, and Atlantic Intracoastal Waterway system near Myrtle Beach, South Carolina, mandated a 60-percent reduction in point-source loading. For waters with a naturally low background dissolved-oxygen concentrations, South Carolina anti-degradation rules in the water-quality regulations allows a permitted discharger a reduction of dissolved oxygen of 0.1 milligrams per liter (mg/L). This is known as the "0.1 rule." Permitted dischargers within this region of the State operate under the "0.1 rule" and cannot cause a cumulative impact greater than 0.1 mg/L on dissolved-oxygen concentrations. For municipal water-reclamation facilities to serve the rapidly growing resort and retirement community near Myrtle Beach, a variable loading scheme was developed to allow dischargers to utilize increased assimilative capacity during higher streamflow conditions while still meeting the requirements of a recently established TMDL. As part of the TMDL development, an extensive real-time data-collection network was established in the lower Waccamaw and Pee Dee River watershed where continuous measurements of streamflow, water level, dissolved oxygen, temperature, and specific conductance are collected. In addition, the dynamic BRANCH/BLTM models were calibrated and validated to simulate the water quality and tidal dynamics of the system. The assimilative capacities for various streamflows were also analyzed. The variable-loading scheme established total loadings for three streamflow levels. Model simulations show the results from the additional loading to be less than a 0.1 mg/L reduction in dissolved oxygen. As part of the loading scheme, the real-time network was redesigned to monitor streamflow entering the study area and water-quality conditions in the location of dissolved-oxygen "sags." The study reveals how one group of permit holders used a variable-loading scheme to implement restrictive permit limits without experiencing prohibitive capital expenditures or initiating a lengthy appeals process.
Artificial Neural Network Models for Long Lead Streamflow Forecasts using Climate Information
NASA Astrophysics Data System (ADS)
Kumar, J.; Devineni, N.
2007-12-01
Information on season ahead stream flow forecasts is very beneficial for the operation and management of water supply systems. Daily streamflow conditions at any particular reservoir primarily depend on atmospheric and land surface conditions including the soil moisture and snow pack. On the other hand recent studies suggest that developing long lead streamflow forecasts (3 months ahead) typically depends on exogenous climatic conditions particularly Sea Surface Temperature conditions (SST) in the tropical oceans. Examples of some oceanic variables are El Nino Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Identification of such conditions that influence the moisture transport into a given basin poses many challenges given the nonlinear dependency between the predictors (SST) and predictand (stream flows). In this study, we apply both linear and nonlinear dependency measures to identify the predictors that influence the winter flows into the Neuse basin. The predictor identification approach here adopted uses simple correlation coefficients to spearman rank correlation measures for detecting nonlinear dependency. All these dependency measures are employed with a lag 3 time series of the high flow season (January - February - March) using 75 years (1928-2002) of stream flows recorded in to the Falls Lake, Neuse River Basin. Developing streamflow forecasts contingent on these exogenous predictors will play an important role towards improved water supply planning and management. Recently, the soft computing techniques, such as artificial neural networks (ANNs) have provided an alternative method to solve complex problems efficiently. ANNs are data driven models which trains on the examples given to it. The ANNs functions as universal approximators and are non linear in nature. This paper presents a study aiming towards using climatic predictors for 3 month lead time streamflow forecast. ANN models representing the physical process of the system are developed between the identified predictors and the predictand. Predictors used are the scores of Principal Components Analysis (PCA). The models were tested and validated. The feed- forward multi-layer perceptron (MLP) type neural networks trained using the back-propagation algorithms are employed in the current study. The performance of the ANN-model forecasts are evaluated using various performance evaluation measures such as correlation coefficient, root mean square error (RMSE). The preliminary results shows that ANNs are efficient to forecast long lead time streamflows using climatic predictors.
NASA Astrophysics Data System (ADS)
Huang, Q. Z.; Hsu, S. Y.; Li, M. H.
2016-12-01
The long-term streamflow prediction is important not only to estimate water-storage of a reservoir but also to the surface water intakes, which supply people's livelihood, agriculture, and industry. Climatology forecasts of streamflow have been traditionally used for calculating the exceedance probability curve of streamflow and water resource management. In this study, we proposed a stochastic approach to predict the exceedance probability curve of long-term streamflow with the seasonal weather outlook from Central Weather Bureau (CWB), Taiwan. The approach incorporates a statistical downscale weather generator and a catchment-scale hydrological model to convert the monthly outlook into daily rainfall and temperature series and to simulate the streamflow based on the outlook information. Moreover, we applied Bayes' theorem to derive a method for calculating the exceedance probability curve of the reservoir inflow based on the seasonal weather outlook and its imperfection. The results show that our approach can give the exceedance probability curves reflecting the three-month weather outlook and its accuracy. We also show how the improvement of the weather outlook affects the predicted exceedance probability curves of the streamflow. Our approach should be useful for the seasonal planning and management of water resource and their risk assessment.
NASA Astrophysics Data System (ADS)
McKnight, Diane M.; Cozzetto, Karen; Cullis, James D. S.; Gooseff, Michael N.; Jaros, Christopher; Koch, Joshua C.; Lyons, W. Berry; Neupauer, Roseanna; Wlostowski, Adam
2015-08-01
While continuous monitoring of streamflow and temperature has been common for some time, there is great potential to expand continuous monitoring to include water quality parameters such as nutrients, turbidity, oxygen, and dissolved organic material. In many systems, distinguishing between watershed and stream ecosystem controls can be challenging. The usefulness of such monitoring can be enhanced by the application of quantitative models to interpret observed patterns in real time. Examples are discussed primarily from the glacial meltwater streams of the McMurdo Dry Valleys, Antarctica. Although the Dry Valley landscape is barren of plants, many streams harbor thriving cyanobacterial mats. Whereas a daily cycle of streamflow is controlled by the surface energy balance on the glaciers and the temporal pattern of solar exposure, the daily signal for biogeochemical processes controlling water quality is generated along the stream. These features result in an excellent outdoor laboratory for investigating fundamental ecosystem process and the development and validation of process-based models. As part of the McMurdo Dry Valleys Long-Term Ecological Research project, we have conducted field experiments and developed coupled biogeochemical transport models for the role of hyporheic exchange in controlling weathering reactions, microbial nitrogen cycling, and stream temperature regulation. We have adapted modeling approaches from sediment transport to understand mobilization of stream biomass with increasing flows. These models help to elucidate the role of in-stream processes in systems where watershed processes also contribute to observed patterns, and may serve as a test case for applying real-time stream ecosystem models.
NASA Technical Reports Server (NTRS)
Hollyday, E. F. (Principal Investigator)
1975-01-01
The author has identified the following significant results. Streamflow characteristics in the Delmarva Peninsula derived from the records of daily discharge of 20 gaged basins are representative of the full range in flow conditions and include all of those commonly used for design or planning purposes. They include annual flood peaks with recurrence intervals of 2, 5, 10, 25, and 50 years, mean annual discharge, standard deviation of the mean annual discharge, mean monthly discharges, standard deviation of the mean monthly discharges, low-flow characteristics, flood volume characteristics, and the discharge equalled or exceeded 50 percent of the time. Streamflow and basin characteristics were related by a technique of multiple regression using a digital computer. A control group of equations was computed using basin characteristics derived from maps and climatological records. An experimental group of equations was computed using basin characteristics derived from LANDSAT imagery as well as from maps and climatological records. Based on a reduction in standard error of estimate equal to or greater than 10 percent, the equations for 12 stream flow characteristics were substantially improved by adding to the analyses basin characteristics derived from LANDSAT imagery.
Waldron, Marcus C.; Archfield, Stacey A.
2006-01-01
Factors affecting reservoir firm yield, as determined by application of the Massachusetts Department of Environmental Protection's Firm Yield Estimator (FYE) model, were evaluated, modified, and tested on 46 streamflow-dominated reservoirs representing 15 Massachusetts drinking-water supplies. The model uses a mass-balance approach to determine the maximum average daily withdrawal rate that can be sustained during a period of record that includes the 1960s drought-of-record. The FYE methodology to estimate streamflow to the reservoir at an ungaged site was tested by simulating streamflow at two streamflow-gaging stations in Massachusetts and comparing the simulated streamflow to the observed streamflow. In general, the FYE-simulated flows agreed well with observed flows. There were substantial deviations from the measured values for extreme high and low flows. A sensitivity analysis determined that the model's streamflow estimates are most sensitive to input values for average annual precipitation, reservoir drainage area, and the soil-retention number-a term that describes the amount of precipitation retained by the soil in the basin. The FYE model currently provides the option of using a 1,000-year synthetic record constructed by randomly sampling 2-year blocks of concurrent streamflow and precipitation records 500 times; however, the synthetic record has the potential to generate records of precipitation and streamflow that do not reflect the worst historical drought in Massachusetts. For reservoirs that do not have periods of drawdown greater than 2 years, the bootstrap does not offer any additional information about the firm yield of a reservoir than the historical record does. For some reservoirs, the use of a synthetic record to determine firm yield resulted in as much as a 30-percent difference between firm-yield values from one simulation to the next. Furthermore, the assumption that the synthetic traces of streamflow are statistically equivalent to the historical record is not valid. For multiple-reservoir systems, the firm-yield estimate was dependent on the reservoir system's configuration. The firm yield of a system is sensitive to how the water is transferred from one reservoir to another, the capacity of the connection between the reservoirs, and how seasonal variations in demand are represented in the FYE model. Firm yields for 25 (14 single-reservoir systems and 11 multiple-reservoir systems) reservoir systems were determined by using the historical records of streamflow and precipitation. Current water-use data indicate that, on average, 20 of the 25 reservoir systems in the study were operating below their estimated firm yield; during months with peak demands, withdrawals exceeded the firm yield for 8 reservoir systems.
Davids, Jeffrey C; van de Giesen, Nick; Rutten, Martine
2017-07-01
Hydrologic data has traditionally been collected with permanent installations of sophisticated and accurate but expensive monitoring equipment at limited numbers of sites. Consequently, observation frequency and costs are high, but spatial coverage of the data is limited. Citizen Hydrology can possibly overcome these challenges by leveraging easily scaled mobile technology and local residents to collect hydrologic data at many sites. However, understanding of how decreased observational frequency impacts the accuracy of key streamflow statistics such as minimum flow, maximum flow, and runoff is limited. To evaluate this impact, we randomly selected 50 active United States Geological Survey streamflow gauges in California. We used 7 years of historical 15-min flow data from 2008 to 2014 to develop minimum flow, maximum flow, and runoff values for each gauge. To mimic lower frequency Citizen Hydrology observations, we developed a bootstrap randomized subsampling with replacement procedure. We calculated the same statistics, and their respective distributions, from 50 subsample iterations with four different subsampling frequencies ranging from daily to monthly. Minimum flows were estimated within 10% for half of the subsample iterations at 39 (daily) and 23 (monthly) of the 50 sites. However, maximum flows were estimated within 10% at only 7 (daily) and 0 (monthly) sites. Runoff volumes were estimated within 10% for half of the iterations at 44 (daily) and 12 (monthly) sites. Watershed flashiness most strongly impacted accuracy of minimum flow, maximum flow, and runoff estimates from subsampled data. Depending on the questions being asked, lower frequency Citizen Hydrology observations can provide useful hydrologic information.
Oden, Timothy D.; Asquith, William H.; Milburn, Matthew S.
2009-01-01
In December 2005, the U.S. Geological Survey in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria (total coliform and Escherichia coli), atrazine, and suspended sediment at two U.S. Geological Survey streamflow-gaging stations upstream from Lake Houston near Houston (08068500 Spring Creek near Spring, Texas, and 08070200 East Fork San Jacinto River near New Caney, Texas). The data from the discrete water-quality samples collected during 2005-07, in conjunction with monitored real-time data already being collected - physical properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), streamflow, and rainfall - were used to develop regression models for predicting water-quality constituent concentrations for inflows to Lake Houston. Rainfall data were obtained from a rain gage monitored by Harris County Homeland Security and Emergency Management and colocated with the Spring Creek station. The leaps and bounds algorithm was used to find the best subsets of possible regression models (minimum residual sum of squares for a given number of variables). The potential explanatory or predictive variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, rainfall, and time (to account for seasonal variations inherent in some water-quality data). The response variables at each site were nitrite plus nitrate nitrogen, total phosphorus, organic carbon, Escherichia coli, atrazine, and suspended sediment. The explanatory variables provide easily measured quantities as a means to estimate concentrations of the various constituents under investigation, with accompanying estimates of measurement uncertainty. Each regression equation can be used to estimate concentrations of a given constituent in real time. In conjunction with estimated concentrations, constituent loads were estimated by multiplying the estimated concentration by the corresponding streamflow and applying the appropriate conversion factor. By computing loads from estimated constituent concentrations, a continuous record of estimated loads can be available for comparison to total maximum daily loads. The regression equations presented in this report are site specific to the Spring Creek and East Fork San Jacinto River streamflow-gaging stations; however, the methods that were developed and documented could be applied to other tributaries to Lake Houston for estimating real-time water-quality data for streams entering Lake Houston.
Mann, Michael P.; Rizzardo, Jule; Satkowski, Richard
2004-01-01
Accurate streamflow statistics are essential to water resource agencies involved in both science and decision-making. When long-term streamflow data are lacking at a site, estimation techniques are often employed to generate streamflow statistics. However, procedures for accurately estimating streamflow statistics often are lacking. When estimation procedures are developed, they often are not evaluated properly before being applied. Use of unevaluated or underevaluated flow-statistic estimation techniques can result in improper water-resources decision-making. The California State Water Resources Control Board (SWRCB) uses two key techniques, a modified rational equation and drainage basin area-ratio transfer, to estimate streamflow statistics at ungaged locations. These techniques have been implemented to varying degrees, but have not been formally evaluated. For estimating peak flows at the 2-, 5-, 10-, 25-, 50-, and 100-year recurrence intervals, the SWRCB uses the U.S. Geological Surveys (USGS) regional peak-flow equations. In this study, done cooperatively by the USGS and SWRCB, the SWRCB estimated several flow statistics at 40 USGS streamflow gaging stations in the north coast region of California. The SWRCB estimates were made without reference to USGS flow data. The USGS used the streamflow data provided by the 40 stations to generate flow statistics that could be compared with SWRCB estimates for accuracy. While some SWRCB estimates compared favorably with USGS statistics, results were subject to varying degrees of error over the region. Flow-based estimation techniques generally performed better than rain-based methods, especially for estimation of December 15 to March 31 mean daily flows. The USGS peak-flow equations also performed well, but tended to underestimate peak flows. The USGS equations performed within reported error bounds, but will require updating in the future as peak-flow data sets grow larger. Little correlation was discovered between estimation errors and geographic locations or various basin characteristics. However, for 25-percentile year mean-daily-flow estimates for December 15 to March 31, the greatest estimation errors were at east San Francisco Bay area stations with mean annual precipitation less than or equal to 30 inches, and estimated 2-year/24-hour rainfall intensity less than 3 inches.
NASA Astrophysics Data System (ADS)
Beamer, J. P.; Hill, D. F.; Liston, G. E.; Arendt, A. A.; Hood, E. W.
2013-12-01
In Prince William Sound (PWS), Alaska, there is a pressing need for accurate estimates of the spatial and temporal variations in coastal freshwater discharge (FWD). FWD into PWS originates from streamflow due to rainfall, annual snowmelt, and changes in stored glacier mass and is important because it helps establish spatial and temporal patterns in ocean salinity and temperature, and is a time-varying boundary condition for oceanographic circulation models. Previous efforts to model FWD into PWS have been heavily empirical, with many physical processes absorbed into calibration coefficients that, in many cases, were calibrated to streams and rivers not hydrologically similar to those discharging into PWS. In this work we adapted and validated a suite of high-resolution (in space and time), physically-based, distributed weather, snowmelt, and runoff-routing models designed specifically for snow melt- and glacier melt-dominated watersheds like PWS in order to: 1) provide high-resolution, real-time simulations of snowpack and FWD, and 2) provide a record of historical variations of FWD. SnowModel, driven with gridded topography, land cover, and 32 years (1979-2011) of 3-hourly North American Regional Reanalysis (NARR) atmospheric forcing data, was used to simulate snowpack accumulation and melt across a PWS model domain. SnowModel outputs of daily snow water equivalent (SWE) depth and grid-cell runoff volumes were then coupled with HydroFlow, a runoff-routing model which routed snowmelt, glacier-melt, and rainfall to each watershed outlet (PWS coastline) in the simulation domain. The end product was a continuous 32-year simulation of daily FWD into PWS. In order to validate the models, SWE and snow depths from SnowModel were compared with observed SWE and snow depths from SnoTel and snow survey data, and discharge from HydroFlow was compared with observed streamflow measurements. As a second phase of this research effort, the coupled models will be set-up to run in real-time, where daily measurements from weather stations in the PWS will be used to drive simulations of snow cover and streamflow. In addition, we will deploy a strategic array of instrumentation aimed at validating the simulated weather estimates and the calculations of freshwater discharge. Upon successful implementation and validation of the modeling system, it will join established and ongoing computational and observational efforts that have a common goal of establishing a comprehensive understanding of the physical behavior of PWS.
Predictors of High Streamflow Events in the Fraser River Basin of British Columbia, Canada
NASA Astrophysics Data System (ADS)
Curry, C.
2016-12-01
The Fraser River basin (FRB) of British Columbia is one of the largest and most important watersheds in Western North America, and is home to a rich diversity of biological species and economic assets that depend implicitly upon its extensive riverine habitats. The hydrology of the FRB is dominated by snow accumulation and melt processes, leading to a prominent annual peak streamflow invariably occurring in June-July. However, while annual peak daily streamflow (APDF) during the spring freshet in the FRB is historically well correlated with basin-averaged, annual maximum snow water equivalent (SWEmax), there are numerous occurrences of anomalously large APDF in below- or near-normal SWEmax years, some of which have resulted in damaging floods in the region. An imperfect understanding of which other climatic factors contribute to these anomalously large APDFs complicates future projections of streamflow magnitude and frequency. We employ the Variable Infiltration Capacity (VIC) process-based hydrological model driven by both observations and an ensemble of CMIP3 climate models in an attempt to discover the proximate causes of anomalous APDF events in the FRB. At several hydrometric stations representing a range of elevations, the relative importance of a set of predictors characterizing the magnitude and timing of rainfall, snowfall, and temperature is examined within a regression framework. The results indicate that next to the magnitude of SWEmax, the rate of warming subsequent to the date of SWEmax is the most influential variable for predicting APDF magnitudes in the lower FRB. Finally, the role of large-scale climate modes of variability for APDF magnitude and timing in the basin will be briefly discussed.
Kessler, Erich; Lorenz, David L.
2010-01-01
The U.S. Geological Survey, in cooperation with the Metropolitan Council, conducted a study to characterize regional low flows during 1932?2007 in the Mississippi River upstream from the Twin Cities metropolitan area in Minnesota and to describe the low-flow profile of the Mississippi River between the confluence of the Crow River and St. Anthony Falls. Probabilities of extremely low flow were estimated for the streamflow-gaging station (Mississippi River near Anoka) and the coincidence of low-flow periods, defined as the extended periods (at least 7 days) when all the daily flows were less than the 10th percentile of daily mean flows for the entire period of record, at four selected streamflow-gaging stations located upstream. The likelihood of extremely low flows was estimated by a superposition method for the Mississippi River near Anoka that created 5,776 synthetic hydrographs resulting in a minimum synthetic low flow of 398 cubic feet per second at a probability of occurrence of 0.0002 per year. Low-flow conditions at the Mississippi River above Anoka were associated with low-flow conditions at two or fewer of four upstream streamflow-gaging stations 42 percent of the time, indicating that sufficient water is available within the basin for many low flows and the occurrence of extremely low-flows is small. However, summer low-flow conditions at the Mississippi River above Anoka were almost always associated with low-stage elevations in three or more of the six upper basin reservoirs. A low-flow profile of the Mississippi River between the confluence of the Crow River and St. Anthony Falls was completed using a real-time kinematic global positioning system, and the water-surface profile was mapped during October 8?9, 2008, and annotated with local landmarks. This was done so that water-use planners could relate free-board elevations of selected water utility structures to the lowest flow conditions during 2008.
Statistical Approaches for Spatiotemporal Prediction of Low Flows
NASA Astrophysics Data System (ADS)
Fangmann, A.; Haberlandt, U.
2017-12-01
An adequate assessment of regional climate change impacts on streamflow requires the integration of various sources of information and modeling approaches. This study proposes simple statistical tools for inclusion into model ensembles, which are fast and straightforward in their application, yet able to yield accurate streamflow predictions in time and space. Target variables for all approaches are annual low flow indices derived from a data set of 51 records of average daily discharge for northwestern Germany. The models require input of climatic data in the form of meteorological drought indices, derived from observed daily climatic variables, averaged over the streamflow gauges' catchments areas. Four different modeling approaches are analyzed. Basis for all pose multiple linear regression models that estimate low flows as a function of a set of meteorological indices and/or physiographic and climatic catchment descriptors. For the first method, individual regression models are fitted at each station, predicting annual low flow values from a set of annual meteorological indices, which are subsequently regionalized using a set of catchment characteristics. The second method combines temporal and spatial prediction within a single panel data regression model, allowing estimation of annual low flow values from input of both annual meteorological indices and catchment descriptors. The third and fourth methods represent non-stationary low flow frequency analyses and require fitting of regional distribution functions. Method three is subject to a spatiotemporal prediction of an index value, method four to estimation of L-moments that adapt the regional frequency distribution to the at-site conditions. The results show that method two outperforms successive prediction in time and space. Method three also shows a high performance in the near future period, but since it relies on a stationary distribution, its application for prediction of far future changes may be problematic. Spatiotemporal prediction of L-moments appeared highly uncertain for higher-order moments resulting in unrealistic future low flow values. All in all, the results promote an inclusion of simple statistical methods in climate change impact assessment.
Performance of a system of reservoirs on futuristic front
NASA Astrophysics Data System (ADS)
Saha, Satabdi; Roy, Debasri; Mazumdar, Asis
2017-10-01
Application of simulation model HEC-5 to analyze the performance of the DVC Reservoir System (a multipurpose system with a network of five reservoirs and one barrage) on the river Damodar in Eastern India in meeting projected future demand as well as controlling flood for synthetically generated future scenario is addressed here with a view to develop an appropriate strategy for its operation. Thomas-Fiering model (based on Markov autoregressive model) has been adopted for generation of synthetic scenario (monthly streamflow series) and subsequently downscaling of modeled monthly streamflow to daily values was carried out. The performance of the system (analysed on seasonal basis) in terms of `Performance Indices' (viz., both quantity based reliability and time based reliability, mean daily deficit, average failure period, resilience and maximum vulnerability indices) for the projected scenario with enhanced demand turned out to be poor compared to that for historical scenario. However, judicious adoption of resource enhancement (marginal reallocation of reservoir storage capacity) and demand management strategy (curtailment of projected high water requirements and trading off between demands) was found to be a viable option for improvement of the performance of the reservoir system appreciably [improvement being (1-51 %), (2-35 %), (16-96 %), (25-50 %), (8-36 %) and (12-30 %) for the indices viz., quantity based reliability, time based reliability, mean daily deficit, average failure period, resilience and maximum vulnerability, respectively] compared to that with normal storage and projected demand. Again, 100 % reliability for flood control for current as well as future synthetically generated scenarios was noted. The results from the study would assist concerned authority in successful operation of reservoirs in the context of growing demand and dwindling resource.
Kuhn, Gerhard; Arnold, L. Rick
2006-01-01
The U.S. Geological Survey, in cooperation with Colorado Springs Utilities, the Colorado Water Conservation Board, and the El Paso County Water Authority, began a study in 2004 to (1) apply a stream-aquifer model to Monument Creek, (2) use the results of the modeling to develop a transit-loss accounting program for Monument Creek, (3) revise the existing transit-loss accounting program for Fountain Creek to incorporate new water-management strategies and allow for incorporation of future changes in water-management strategies, and (4) integrate the two accounting programs into a single program with a Web-based user interface. The purpose of this report is to present the results of applying a stream-aquifer model to the Monument Creek study reach.Transit losses were estimated for reusable-water flows in Monument Creek that ranged from 1 to 200 cubic feet per second (ft3/s) and for native streamflows that ranged from 0 to 1,000 ft3/s. Transit losses were estimated for bank-storage, channel-storage, and evaporative losses. The same stream-aquifer model used in the previously completed (1988) Fountain Creek study was used in the Monument Creek study.Sixteen model nodes were established for the Monument Creek study reach, defining 15 subreaches. Channel length, aquifer length, and aquifer width for the subreaches were estimated from available topographic and geologic maps. Thickness of alluvial deposits and saturated thickness were estimated using lithologic and water-level data from about 100 wells and test holes in or near the Monument Creek study reach. Estimated average transmissivities for the subreaches ranged from 2,000 to 12,000 feet squared per day, and a uniform value of 0.20 was used for storage coefficient.Qualitative comparison of recorded and simulated streamflow at the downstream node for the calibration and verification simulations indicated that the two streamflows compared reasonably well. No adjustments were made to the model parameters. Differences between recorded and simulated streamflow volumes for all calibration and verification simulations ranged from about –8.8 to 7.5 percent; the total error for all simulations was about –0.7 percent.The model was used to estimate bank-storage losses for 10 to 15 native streamflows for each reusable-water flow of 1, 3, 5, 7, 10, 15, 20, 30, 40, 50, 100, and 200 ft3/s. Then the 10 to 15 bank-storage loss values were used in least-squares linear regression to estimate a relation between bank-storage loss and native streamflow for each of the 12 reusable-water flow rates. The 12 regression relations then were used to develop “look-up” tables of bank-storage loss for reusable-water flows ranging from 1 to 200 ft3/s (in 1-ft3/s increments). Additional model simulations indicated that (1) when the ratio of downstream native streamflow to upstream native streamflow was less than 1, bank-storage loss generally increased and (2) when the ratio of downstream native streamflow to upstream native streamflow was larger than 1, bank-storage loss generally decreased. These results were used to develop a bank-storage loss adjustment factor based on the ratio of native streamflow at the downstream node to native streamflow at the upstream node. The model also was used to estimate a recovery period, which is the length of time needed for the bank-storage loss to return to the stream. The recovery period was 1 day for six subreaches; 2 days for four subreaches; between 3 and 12 days for four subreaches; and 28 days for one subreach.Channel-storage losses are about 10 percent of the reusable-water flow for most of the subreaches, except for two subreaches, where the channel-storage losses are about 20 percent, and one subreach, where the losses are about 30 percent, owing to the greater channel lengths. Evaporative losses were estimated by the use of monthly pan-evaporation data and the incremental increase in stream width resulting from any reusable-water flows. Monthly pan-evaporation data were converted to a daily rate. The daily rate, when multiplied by the stream-width increase (in feet) that results from reusable-water flow and by the subreach length (in miles) gives the daily evaporative loss in cubic feet per second.
NASA Astrophysics Data System (ADS)
Demirel, M. C.; Mai, J.; Stisen, S.; Mendiguren González, G.; Koch, J.; Samaniego, L. E.
2016-12-01
Distributed hydrologic models are traditionally calibrated and evaluated against observations of streamflow. Spatially distributed remote sensing observations offer a great opportunity to enhance spatial model calibration schemes. For that it is important to identify the model parameters that can change spatial patterns before the satellite based hydrologic model calibration. Our study is based on two main pillars: first we use spatial sensitivity analysis to identify the key parameters controlling the spatial distribution of actual evapotranspiration (AET). Second, we investigate the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale Hydrologic Model (mHM). This distributed model is selected as it allows for a change in the spatial distribution of key soil parameters through the calibration of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) directly as input. In addition the simulated AET can be estimated at the spatial resolution suitable for comparison to the spatial patterns observed using MODIS data. We introduce a new dynamic scaling function employing remotely sensed vegetation to downscale coarse reference evapotranspiration. In total, 17 parameters of 47 mHM parameters are identified using both sequential screening and Latin hypercube one-at-a-time sampling methods. The spatial patterns are found to be sensitive to the vegetation parameters whereas streamflow dynamics are sensitive to the PTF parameters. The results of multi-objective model calibration show that calibration of mHM against observed streamflow does not reduce the spatial errors in AET while they improve only the streamflow simulations. We will further examine the results of model calibration using only multi spatial objective functions measuring the association between observed AET and simulated AET maps and another case including spatial and streamflow metrics together.
The impact of lake and reservoir parameterization on global streamflow simulation.
Zajac, Zuzanna; Revilla-Romero, Beatriz; Salamon, Peter; Burek, Peter; Hirpa, Feyera A; Beck, Hylke
2017-05-01
Lakes and reservoirs affect the timing and magnitude of streamflow, and are therefore essential hydrological model components, especially in the context of global flood forecasting. However, the parameterization of lake and reservoir routines on a global scale is subject to considerable uncertainty due to lack of information on lake hydrographic characteristics and reservoir operating rules. In this study we estimated the effect of lakes and reservoirs on global daily streamflow simulations of a spatially-distributed LISFLOOD hydrological model. We applied state-of-the-art global sensitivity and uncertainty analyses for selected catchments to examine the effect of uncertain lake and reservoir parameterization on model performance. Streamflow observations from 390 catchments around the globe and multiple performance measures were used to assess model performance. Results indicate a considerable geographical variability in the lake and reservoir effects on the streamflow simulation. Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) metrics improved for 65% and 38% of catchments respectively, with median skill score values of 0.16 and 0.2 while scores deteriorated for 28% and 52% of the catchments, with median values -0.09 and -0.16, respectively. The effect of reservoirs on extreme high flows was substantial and widespread in the global domain, while the effect of lakes was spatially limited to a few catchments. As indicated by global sensitivity analysis, parameter uncertainty substantially affected uncertainty of model performance. Reservoir parameters often contributed to this uncertainty, although the effect varied widely among catchments. The effect of reservoir parameters on model performance diminished with distance downstream of reservoirs in favor of other parameters, notably groundwater-related parameters and channel Manning's roughness coefficient. This study underscores the importance of accounting for lakes and, especially, reservoirs and using appropriate parameterization in large-scale hydrological simulations.
Singh, R.; Archfield, S.A.; Wagener, T.
2014-01-01
Daily streamflow information is critical for solving various hydrologic problems, though observations of continuous streamflow for model calibration are available at only a small fraction of the world’s rivers. One approach to estimate daily streamflow at an ungauged location is to transfer rainfall–runoff model parameters calibrated at a gauged (donor) catchment to an ungauged (receiver) catchment of interest. Central to this approach is the selection of a hydrologically similar donor. No single metric or set of metrics of hydrologic similarity have been demonstrated to consistently select a suitable donor catchment. We design an experiment to diagnose the dominant controls on successful hydrologic model parameter transfer. We calibrate a lumped rainfall–runoff model to 83 stream gauges across the United States. All locations are USGS reference gauges with minimal human influence. Parameter sets from the calibrated models are then transferred to each of the other catchments and the performance of the transferred parameters is assessed. This transfer experiment is carried out both at the scale of the entire US and then for six geographic regions. We use classification and regression tree (CART) analysis to determine the relationship between catchment similarity and performance of transferred parameters. Similarity is defined using physical/climatic catchment characteristics, as well as streamflow response characteristics (signatures such as baseflow index and runoff ratio). Across the entire US, successful parameter transfer is governed by similarity in elevation and climate, and high similarity in streamflow signatures. Controls vary for different geographic regions though. Geology followed by drainage, topography and climate constitute the dominant similarity metrics in forested eastern mountains and plateaus, whereas agricultural land use relates most strongly with successful parameter transfer in the humid plains.
NASA Astrophysics Data System (ADS)
McInerney, David; Thyer, Mark; Kavetski, Dmitri; Lerat, Julien; Kuczera, George
2017-03-01
Reliable and precise probabilistic prediction of daily catchment-scale streamflow requires statistical characterization of residual errors of hydrological models. This study focuses on approaches for representing error heteroscedasticity with respect to simulated streamflow, i.e., the pattern of larger errors in higher streamflow predictions. We evaluate eight common residual error schemes, including standard and weighted least squares, the Box-Cox transformation (with fixed and calibrated power parameter λ) and the log-sinh transformation. Case studies include 17 perennial and 6 ephemeral catchments in Australia and the United States, and two lumped hydrological models. Performance is quantified using predictive reliability, precision, and volumetric bias metrics. We find the choice of heteroscedastic error modeling approach significantly impacts on predictive performance, though no single scheme simultaneously optimizes all performance metrics. The set of Pareto optimal schemes, reflecting performance trade-offs, comprises Box-Cox schemes with λ of 0.2 and 0.5, and the log scheme (λ = 0, perennial catchments only). These schemes significantly outperform even the average-performing remaining schemes (e.g., across ephemeral catchments, median precision tightens from 105% to 40% of observed streamflow, and median biases decrease from 25% to 4%). Theoretical interpretations of empirical results highlight the importance of capturing the skew/kurtosis of raw residuals and reproducing zero flows. Paradoxically, calibration of λ is often counterproductive: in perennial catchments, it tends to overfit low flows at the expense of abysmal precision in high flows. The log-sinh transformation is dominated by the simpler Pareto optimal schemes listed above. Recommendations for researchers and practitioners seeking robust residual error schemes for practical work are provided.
NASA Astrophysics Data System (ADS)
Hevesi, J. A.; Woolfenden, L. R.; Nishikawa, T.
2014-12-01
Communities in the Santa Rosa Plain watershed (SRPW), Sonoma County, CA, USA are experiencing increasing demand for limited water resources. Streamflow in the SRPW is runoff dominated; however, groundwater also is an important resource in the basin. The watershed has an area of 262 mi2 that includes natural, agricultural, and urban land uses. To evaluate the hydrologic system, an integrated hydrologic model was developed using the U.S. Geological Survey coupled groundwater and surface-water flow model, GSFLOW. The model uses a daily time step and a grid-based discretization of the SRPW consisting of 16,741 10-acre cells for 8 model layers to simulate all water budget components of the surface and subsurface hydrologic system. Simulation results indicate significant impacts on streamflow and recharge in response to the below average precipitation during the dry periods. The recharge and streamflow distributions simulated for historic dry periods were compared to future dry periods projected from 4 GCM realizations (two different GCMs and two different CO2 forcing scenarios) for the 21st century, with the dry periods defined as 3 consecutive years of below average precipitation. For many of the projected dry periods, the decreases in recharge and streamflow were greater than for the historic dry periods due to a combination of lower precipitation and increases in simulated evapotranspiration for the warmer 21st century projected by the GCM realizations. The greatest impact on streamflow for both historic and projected future dry periods is the diminished baseflow from late spring to early fall, with an increase in the percentage of intermittent and dry stream reaches. The results indicate that the coupled model is a useful tool for water managers to better understand the potential effects of future dry periods on spatially and temporally distributed streamflow and recharge, as well as other components of the water budget.
Trends and variability in streamflow and snowmelt runoff timing in the southern Tianshan Mountains
NASA Astrophysics Data System (ADS)
Shen, Yan-Jun; Shen, Yanjun; Fink, Manfred; Kralisch, Sven; Chen, Yaning; Brenning, Alexander
2018-02-01
Streamflow and snowmelt runoff timing of mountain rivers are susceptible to climate change. Trends and variability in streamflow and snowmelt runoff timing in four mountain basins in the southern Tianshan were analyzed in this study. Streamflow trends were detected by Mann-Kendall tests and changes in snowmelt runoff timing were analyzed based on the winter/spring snowmelt runoff center time (WSCT). Pearson's correlation coefficient was further calculated to analyze the relationships between climate variables, streamflow and WSCT. Annual streamflow increased significantly in past decades in the southern Tianshan, especially in spring and winter months. However, the relations between streamflow and temperature/precipitation depend on the different streamflow generation processes. Annual precipitation plays a vital role in controlling recharge in the Toxkon basin, while the Kaidu and Huangshuigou basins are governed by both precipitation and temperature. Seasonally, temperature has a strong effect on streamflow in autumn and winter, while summer streamflow appears more sensitive to changes in precipitation. However, temperature is the dominant factor for streamflow in the glacierized Kunmalik basin at annual and seasonal scales. An uptrend in streamflow begins in the 1990s at both annual and seasonal scales, which is generally consistent with temperature and precipitation fluctuations. Average WSCT dates in the Kaidu and Huangshuigou basins are earlier than in the Toxkon and Kunmalik basins, and shifted towards earlier dates since the mid-1980s in all the basins. It is plausible that WSCT dates are more sensitive to warmer temperature in spring period compared to precipitation, except for the Huangshuigou basin. Taken together, these findings are useful for applications in flood risk regulation, future hydropower projects and integrated water resources management.
Runoff characteristics of California streams
Rantz, S.E.
1972-01-01
California streams exhibit a wide range of runoff characteristics that are related to the climatologic, topographic, and geologic characteristics of the basins they drain. The annual volume of runoff of a stream, expressed in inches, may be large or small, and daily discharge rates may be highly variable or relatively steady. The bulk of the annual runoff may be storm runoff, or snowmelt runoff, or a combination of both. The streamflow may be ephemeral, intermittent, or perennial; if perennial, base flow may be well sustained or poorly sustained. In this report the various runoff characteristics are identified by numerical index values. They are shown to be related generally to mean annual precipitation, altitude, latitude, and location with respect to the 11 geomorphic provinces in the California Region. With respect to mean annual precipitation on the watershed, streamflow is generally (1) ephemeral if the mean annual precipitation is less than 10 inches, (2) intermittent if the mean annual precipitation is between 10 and 40 inches, and (3) perennial if the mean annual precipitation is more than 40 inches. Departures from those generalizations are associated with (a) the areal variation of such geologic factors as the infiltration and storage capacities of the rocks underlying the watersheds, and (b) the areal variation of evapotranspiration loss as influenced by varying conditions of climate, soil, vegetal cover, and geologic structure. Latitude and altitude determine the proportion of the winter precipitation that will be stored for subsequent runoff in the late spring and summer. In general, if a watershed has at least 30 percent of its area above the normal altitude of the snowline on April 1, it will have significant snowmelt runoff. Snowmelt runoff in California is said to be significant if at least 30 percent of the annual runoff occurs during the 4 months, April through July. Storm runoff is said to be predominant if at least 65 percent of the annual runoff occurs during the 6 months, October through March. Base flow (ground-water outflow), as a factor in the regimen of streamflow, is qualified on the basis of the percentage of the mean annual runoff that occurs during the fair-weather months of August and September. If the sum of the August and September runoff exceeds 3.0 percent of the annual runoff, base flow is considered to be well sustained; if the percentage is between 1.5 and 3.0, base flow is considered to be fairly well sustained; if the percentage is less than 1.5, baseflow is considered to be poorly sustained. The characteristics of duration curves of daily streamflow are influenced by the regimen of runoff. The distribution of daily flow is skewed for all streams, but it is more skewed for streams whose flow is predominantly storm runoff than for streams that carry significantly large quantities of snowmelt. Least skewed is the distribution for streams that carry large quantities of base flow. Either of two characteristics of the duration curve may be used as an index of skew--the percentage of time that the mean discharge is equaled or exceeded or the ratio of the median discharge to the mean discharge. As for variability of daily discharge, the variability of storm-runoff streams is greater than that of snowmelt streams, and the lowest values of variability are associated with streams that carry large quantities of base flow. The index of variability used in this study was the ratio of the discharge equaled or exceeded 10 percent of the time to the discharge equaled or exceeded 90 percent of the time. The identification of streamflow characteristics by numerical index figures greatly facilitates comparison of the diverse runoff regimens of streams in the California Region.
USDA-ARS?s Scientific Manuscript database
Historical streamflow data from the Pacific Northwest indicate that the precipitation amount has been the dominant control on the magnitude of low streamflow extremes compared to the air temperature-affected timing of snowmelt runoff. The relative sensitivities of low streamflow to precipitation and...
Accuracy of selected techniques for estimating ice-affected streamflow
Walker, John F.
1991-01-01
This paper compares the accuracy of selected techniques for estimating streamflow during ice-affected periods. The techniques are classified into two categories - subjective and analytical - depending on the degree of judgment required. Discharge measurements have been made at three streamflow-gauging sites in Iowa during the 1987-88 winter and used to established a baseline streamflow record for each site. Using data based on a simulated six-week field-tip schedule, selected techniques are used to estimate discharge during the ice-affected periods. For the subjective techniques, three hydrographers have independently compiled each record. Three measures of performance are used to compare the estimated streamflow records with the baseline streamflow records: the average discharge for the ice-affected period, and the mean and standard deviation of the daily errors. Based on average ranks for three performance measures and the three sites, the analytical and subjective techniques are essentially comparable. For two of the three sites, Kruskal-Wallis one-way analysis of variance detects significant differences among the three hydrographers for the subjective methods, indicating that the subjective techniques are less consistent than the analytical techniques. The results suggest analytical techniques may be viable tools for estimating discharge during periods of ice effect, and should be developed further and evaluated for sites across the United States.
Diverse multi-decadal changes in streamflow within a rapidly urbanizing region
NASA Astrophysics Data System (ADS)
Diem, Jeremy E.; Hill, T. Chee; Milligan, Richard A.
2018-01-01
The impact of urbanization on streamflow depends on a variety of factors (e.g., climate, initial land cover, inter-basin transfers, water withdrawals, wastewater effluent, etc.). The purpose of this study is to examine trends in streamflow from 1986 to 2015 in a range of watersheds within the rapidly urbanizing Atlanta, GA metropolitan area. This study compares eight watersheds over three decades, while minimizing the influence of inter-annual precipitation variability. Population and land-cover data were used to analyze changes over approximately twenty years within the watersheds. Precipitation totals for the watersheds were estimated using precipitation totals at nearby weather stations. Multiple streamflow variables, such as annual streamflow, frequencies of high-flow days (HFDs), flashiness, and precipitation-adjusted streamflow, for the eight streams were calculated using daily streamflow data. Variables were tested for significant trends from 1986 to 2015 and significant differences between 1986-2000 and 2001-2015. Flashiness increased for all streams without municipal water withdrawals, and the four watersheds with the largest increase in developed land had significant increases in flashiness. Significant positive trends in precipitation-adjusted mean annual streamflow and HFDs occurred for the two watersheds (Big Creek and Suwanee Creek) that experienced the largest increases in development, and these were the only watersheds that went from majority forest land in 1986 to majority developed land in 2015. With a disproportionate increase in HFD occurrence during summer, Big Creek and Suwannee Creek also had a reduction in intra-annual variability of HFD occurrence. Watersheds that were already substantially developed at the beginning of the period and did not have wastewater discharge had declining streamflow. The most urbanized watershed (Peachtree Creek) had a significant decrease in streamflow, and a possible cause of the decrease was increasing groundwater infiltration into sewers. The impacts of urbanization on streamflow within the metropolitan area have undoubtedly been felt by a wide of range of communities.
Weaver, J. Curtis
2015-03-12
In 2013, the U.S. Geological Survey, in cooperation with the North Carolina Division of Water Resources, compiled updated low-flow characteristics and flow-duration statistics for selected continuous-record streamgages in North Carolina. The compilation of updated streamflow statistics provides regulators and planners with relevant hydrologic information reflective of the recent droughts, which can be used to better manage the quantity and quality of streams in North Carolina. Streamflow records available through the 2012 water year1 were used to determine the annual (based on climatic year2) and winter 7-day, 10-year (7Q10, W7Q10) low-flow discharges, the 30-day, 2-year (30Q2) low-flow discharge, and the 7-day, 2-year (7Q2) low-flow discharge. Consequently, streamflow records available through March 31, 2012 (or the 2011 climatic year) were used to determine the updated low-flow characteristics. Low-flow characteristics were published for 177 unregulated sites, 56 regulated sites, and 33 sites known or considered to be affected by varying degrees of minor regulation and (or) diversions upstream from the streamgages (266 sites total). The updated 7Q10 discharges were compared for 63 streamgages across North Carolina where (1) long-term streamflow record consisted of 30 or more climatic years of data available as of the 1998 climatic year, and (2) streamflows were not known to be regulated. The 7Q10 discharges did not change for 3 sites, whereas increases and decreases were noted at 5 and 55 sites, respectively. Positive changes (increases) ranged from 4.3 percent (site 362) to 34.1 percent (site 112) with a median of 13.2 percent. Negative percentage changes (decreases) ranged from –3.3 percent (site 514) to –80.0 percent (site 308) with a median of –22.2 percent. The median percentage change for all 63 streamgages was –18.4 percent. Streamflow statistics determined as a part of this compilation included minimum, mean, maximum, and flow-duration statistics of daily mean discharges for categorical periods. Flow-duration statistics based on the daily mean discharge records were compiled in this study for the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles. Flow-duration statistics were determined for each complete water year of record at a streamgage as well as the available period of record (or selected periods if flows were regulated) and selected seasonal, monthly, and calendar day periods. In addition to the streamflow statistics compiled for each of the water years, the number of days the daily mean discharge was at or below the 10th percentile was summed for each water year as well as the number of events during the water year when streamflow was consistently at or below the 10th percentile. All low-flow characteristics for the streamgages were added into the StreamStatsDB, which is a database accessible to users through the recently released USGS StreamStats application for North Carolina. The minimum, mean, maximum, and flow-duration statistics of daily mean discharges based on the available (or selected if regulated flows) period of record were updated in the North Carolina StreamStatsDB. However, for the selected seasonal, monthly, calendar day, and annual water year periods, tab-delimited American Standard Code for Information Interchange (ASCII) tables of the streamflow statistics are available online to users from a link provided in the StreamStats application. 1The annual period from October 1 through September 30, designated by the year in which the period ends. 2The annual period from April 1 through March 31, designated by the year in which the period begins.
Risley, John; Moradkhani, Hamid; Hay, Lauren E.; Markstrom, Steve
2011-01-01
In an earlier global climate-change study, air temperature and precipitation data for the entire twenty-first century simulated from five general circulation models were used as input to precalibrated watershed models for 14 selected basins across the United States. Simulated daily streamflow and energy output from the watershed models were used to compute a range of statistics. With a side-by-side comparison of the statistical analyses for the 14 basins, regional climatic and hydrologic trends over the twenty-first century could be qualitatively identified. Low-flow statistics (95% exceedance, 7-day mean annual minimum, and summer mean monthly streamflow) decreased for almost all basins. Annual maximum daily streamflow also decreased in all the basins, except for all four basins in California and the Pacific Northwest. An analysis of the supply of available energy and water for the basins indicated that ratios of evaporation to precipitation and potential evapotranspiration to precipitation for most of the basins will increase. Probability density functions (PDFs) were developed to assess the uncertainty and multimodality in the impact of climate change on mean annual streamflow variability. Kolmogorov?Smirnov tests showed significant differences between the beginning and ending twenty-first-century PDFs for most of the basins, with the exception of four basins that are located in the western United States. Almost none of the basin PDFs were normally distributed, and two basins in the upper Midwest had PDFs that were extremely dispersed and skewed.
Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin
Shrestha, M.S.; Artan, Guleid A.; Bajracharya, S.R.; Sharma, R. R.
2008-01-01
In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.
Siemion, Jason; McHale, Michael R.; Davis, Wae Danyelle
2016-12-05
Suspended-sediment concentrations (SSCs) and turbidity were monitored within the Beaver Kill, Stony Clove Creek, and Warner Creek tributaries to the upper Esopus Creek in New York, the main source of water to the Ashokan Reservoir, from October 1, 2010, through September 30, 2014. The purpose of the monitoring was to determine the effects of suspended-sediment and turbidity reduction projects (STRPs) on SSC and turbidity in two of the three streams; no STRPs were constructed in the Beaver Kill watershed. During the study period, four STRPs were completed in the Stony Clove Creek and Warner Creek watersheds. Daily mean SSCs decreased significantly for a given streamflow after the STRPs were completed. The most substantial decreases in daily mean SSCs were measured at the highest streamflows. Background SSCs, as measured in water samples collected in upstream reference stream reaches, in all three streams in this study were less than 5 milligrams per liter during low and high streamflows. Longitudinal stream sampling identified stream reaches with failing hillslopes in contact with the stream channel as the primary sediment sources in the Beaver Kill and Stony Clove Creek watersheds.
Patrick R. Kormos; Charlie Luce; Seth J. Wenger; Wouter R. Berghuijs
2016-01-01
Path analyses of historical streamflow data from the Pacific Northwest indicate that the precipitation amount has been the dominant control on the magnitude of low streamflow extremes compared to the air temperature-affected timing of snowmelt runoff. The relative sensitivities of low streamflow to precipitation and temperature changes have important...
Users Manual for the Geospatial Stream Flow Model (GeoSFM)
Artan, Guleid A.; Asante, Kwabena; Smith, Jodie; Pervez, Md Shahriar; Entenmann, Debbie; Verdin, James P.; Rowland, James
2008-01-01
The monitoring of wide-area hydrologic events requires the manipulation of large amounts of geospatial and time series data into concise information products that characterize the location and magnitude of the event. To perform these manipulations, scientists at the U.S. Geological Survey Center for Earth Resources Observation and Science (EROS), with the cooperation of the U.S. Agency for International Development, Office of Foreign Disaster Assistance (USAID/OFDA), have implemented a hydrologic modeling system. The system includes a data assimilation component to generate data for a Geospatial Stream Flow Model (GeoSFM) that can be run operationally to identify and map wide-area streamflow anomalies. GeoSFM integrates a geographical information system (GIS) for geospatial preprocessing and postprocessing tasks and hydrologic modeling routines implemented as dynamically linked libraries (DLLs) for time series manipulations. Model results include maps that depicting the status of streamflow and soil water conditions. This Users Manual provides step-by-step instructions for running the model and for downloading and processing the input data required for initial model parameterization and daily operation.
On the Performance of Alternate Conceptual Ecohydrological Models for Streamflow Prediction
NASA Astrophysics Data System (ADS)
Naseem, Bushra; Ajami, Hoori; Cordery, Ian; Sharma, Ashish
2016-04-01
A merging of a lumped conceptual hydrological model with two conceptual dynamic vegetation models is presented to assess the performance of these models for simultaneous simulations of streamflow and leaf area index (LAI). Two conceptual dynamic vegetation models with differing representation of ecological processes are merged with a lumped conceptual hydrological model (HYMOD) to predict catchment scale streamflow and LAI. The merged RR-LAI-I model computes relative leaf biomass based on transpiration rates while the RR-LAI-II model computes above ground green and dead biomass based on net primary productivity and water use efficiency in response to soil moisture dynamics. To assess the performance of these models, daily discharge and 8-day MODIS LAI product for 27 catchments of 90 - 1600km2 in size located in the Murray - Darling Basin in Australia are used. Our results illustrate that when single-objective optimisation was focussed on maximizing the objective function for streamflow or LAI, the other un-calibrated predicted outcome (LAI if streamflow is the focus) was consistently compromised. Thus, single-objective optimization cannot take into account the essence of all processes in the conceptual ecohydrological models. However, multi-objective optimisation showed great strength for streamflow and LAI predictions. Both response outputs were better simulated by RR-LAI-II than RR-LAI-I due to better representation of physical processes such as net primary productivity (NPP) in RR-LAI-II. Our results highlight that simultaneous calibration of streamflow and LAI using a multi-objective algorithm proves to be an attractive tool for improved streamflow predictions.
Effects of water-supply reservoirs on streamflow in Massachusetts
Levin, Sara B.
2016-10-06
State and local water-resource managers need modeling tools to help them manage and protect water-supply resources for both human consumption and ecological needs. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a decision-support tool to estimate the effects of reservoirs on natural streamflow. The Massachusetts Reservoir Simulation Tool is a model that simulates the daily water balance of a reservoir. The reservoir simulation tool provides estimates of daily outflows from reservoirs and compares the frequency, duration, and magnitude of the volume of outflows from reservoirs with estimates of the unaltered streamflow that would occur if no dam were present. This tool will help environmental managers understand the complex interactions and tradeoffs between water withdrawals, reservoir operational practices, and reservoir outflows needed for aquatic habitats.A sensitivity analysis of the daily water balance equation was performed to identify physical and operational features of reservoirs that could have the greatest effect on reservoir outflows. For the purpose of this report, uncontrolled releases of water (spills or spillage) over the reservoir spillway were considered to be a proxy for reservoir outflows directly below the dam. The ratio of average withdrawals to the average inflows had the largest effect on spillage patterns, with the highest withdrawals leading to the lowest spillage. The size of the surface area relative to the drainage area of the reservoir also had an effect on spillage; reservoirs with large surface areas have high evaporation rates during the summer, which can contribute to frequent and long periods without spillage, even in the absence of water withdrawals. Other reservoir characteristics, such as variability of inflows, groundwater interactions, and seasonal demand patterns, had low to moderate effects on the frequency, duration, and magnitude of spillage. The reservoir simulation tool was used to simulate 35 single- and multiple-reservoir systems in Massachusetts over a 44-year period (water years 1961 to 2004) under two water-use scenarios. The no-pumping scenario assumes no water withdrawal pumping, and the pumping scenario incorporates average annual pumping rates from 2000 to 2004. By comparing the results of the two scenarios, the total streamflow alteration can be parsed into the portion of streamflow alteration caused by the presence of a reservoir and the additional streamflow alteration caused by the level of water use of the system.For each reservoir system, the following metrics were computed to characterize the frequency, duration, and magnitude of reservoir outflow volumes compared with unaltered streamflow conditions: (1) the median number of days per year in which the reservoir did not spill, (2) the median duration of the longest consecutive period of no-spill days per year, and (3) the lowest annual flow duration exceedance probability at which the outflows are significantly different from estimated unaltered streamflow at the 95-percent confidence level. Most reservoirs in the study do not spill during the summer months even under no-pumping conditions. The median number of days during which there was no spillage was less than 365 for all reservoirs in the study, indicating that, even under reported pumping conditions, the reservoirs refill to full volume and spill at least once during nondrought years, typically in the spring.Thirteen multiple-reservoir systems consisting of two or three hydrologically connected reservoirs were included in the study. Because operating rules used to manage multiple-reservoir systems are not available, these systems were simulated under two pumping scenarios, one in which water transfers between reservoirs are minimal and one in which reservoirs continually transferred water to intermediate or terminal reservoirs. These two scenarios provided upper and lower estimates of spillage under average pumping conditions from 2000 to 2004.For sites with insufficient data to simulate daily water balances, a proxy method to estimate the three spillage metrics was developed. A series of 4,000 Monte Carlo simulations of the reservoir water balance were run. In each simulation, streamflow, physical reservoir characteristics, and daily climate inputs were randomly varied. Tobit regression equations that quantify the relation between streamflow alteration and physical and operational characteristics of reservoirs were developed from the results of the Monte Carlo simulations and can be used to estimate each of the three spillage metrics using only the withdrawal ratio and the ratio of the surface area to the drainage area, which are available statewide for all reservoirs.A graphical user-interface for the Massachusetts Reservoir Simulation Tool was developed in a Microsoft Access environment. The simulation tool contains information for 70 reservoirs in Massachusetts and allows for simulation of additional scenarios than the ones considered in this report, including controlled releases, dam seepage and leakage, demand management plans, and alternative water withdrawal and transfer rules.
Uncertainties in Forecasting Streamflow using Entropy Theory
NASA Astrophysics Data System (ADS)
Cui, H.; Singh, V. P.
2017-12-01
Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.
Ockerman, Darwin J.; Roussel, Meghan C.
2009-01-01
The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers and the San Antonio River Authority, configured, calibrated, and tested a Hydrological Simulation Program ? FORTRAN watershed model for the approximately 238-square-mile Leon Creek watershed in Bexar County, Texas, and used the model to simulate streamflow and water quality (focusing on loads and yields of selected constituents). Streamflow in the model was calibrated and tested with available data from five U.S. Geological Survey streamflow-gaging stations for 1997-2004. Simulated streamflow volumes closely matched measured streamflow volumes at all streamflow-gaging stations. Total simulated streamflow volumes were within 10 percent of measured values. Streamflow volumes are greatly influenced by large storms. Two months that included major floods accounted for about 50 percent of all the streamflow measured at the most downstream gaging station during 1997-2004. Water-quality properties and constituents (water temperature, dissolved oxygen, suspended sediment, dissolved ammonia nitrogen, dissolved nitrate nitrogen, and dissolved and total lead and zinc) in the model were calibrated using available data from 13 sites in and near the Leon Creek watershed for varying periods of record during 1992-2005. Average simulated daily mean water temperature and dissolved oxygen at the most downstream gaging station during 1997-2000 were within 1 percent of average measured daily mean water temperature and dissolved oxygen. Simulated suspended-sediment load at the most downstream gaging station during 2001-04 (excluding July 2002 because of major storms) was 77,700 tons compared with 74,600 tons estimated from a streamflow-load regression relation (coefficient of determination = .869). Simulated concentrations of dissolved ammonia nitrogen and dissolved nitrate nitrogen closely matched measured concentrations after calibration. At the most downstream gaging station, average simulated monthly mean concentrations of dissolved ammonia and nitrate concentrations during 1997-2004 were 0.03 and 0.37 milligram per liter, respectively. For the most downstream station, the measured and simulated concentrations of dissolved and total lead and zinc for stormflows during 1993-97 after calibration do not match particularly closely. For base-flow conditions during 1997-2004 at the most downstream station, the simulated/measured match is better. For example, median simulated concentration of total lead (for 2,041 days) was 0.96 microgram per liter, and median measured concentration (for nine samples) of total lead was 1.0 microgram per liter. To demonstrate an application of the Leon Creek watershed model, streamflow constituent loads and yields for suspended sediment, dissolved nitrate nitrogen, and total lead were simulated at the mouth of Leon Creek (outlet of the watershed) for 1997-2004. The average suspended-sediment load was 51,800 tons per year. The average suspended-sediment yield was 0.34 ton per acre per year. The average load of dissolved nitrate at the outlet of the watershed was 802 tons per year. The corresponding yield was 10.5 pounds per acre per year. The average load of lead at the outlet was 3,900 pounds per year. The average lead yield was 0.026 pound per acre per year. The degree to which available rainfall data represent actual rainfall is potentially the most serious source of measurement error associated with the Leon Creek model. Major storms contribute most of the streamflow loads for certain constituents. For example, the three largest stormflows contributed about 64 percent of the entire suspended-sediment load at the most downstream station during 1997-2004.
Hereford, Richard
2006-01-01
The software described here is used to process and analyze daily weather and surface-water data. The programs are refinements of earlier versions that include minor corrections and routines to calculate frequencies above a threshold on an annual or seasonal basis. Earlier versions of this software were used successfully to analyze historical precipitation patterns of the Mojave Desert and the southern Colorado Plateau regions, ecosystem response to climate variation, and variation of sediment-runoff frequency related to climate (Hereford and others, 2003; 2004; in press; Griffiths and others, 2006). The main program described here (Day_Cli_Ann_v5.3) uses daily data to develop a time series of various statistics for a user specified accounting period such as a year or season. The statistics include averages and totals, but the emphasis is on the frequency of occurrence in days of relatively rare weather or runoff events. These statistics are indices of climate variation; for a discussion of climate indices, see the Climate Research Unit website of the University of East Anglia (http://www.cru.uea.ac.uk/projects/stardex/) and the Climate Change Indices web site (http://cccma.seos.uvic.ca/ETCCDMI/indices.html). Specifically, the indices computed with this software are the frequency of high intensity 24-hour rainfall, unusually warm temperature, and unusually high runoff. These rare, or extreme events, are those greater than the 90th percentile of precipitation, streamflow, or temperature computed for the period of record of weather or gaging stations. If they cluster in time over several decades, extreme events may produce detectable change in the physical landscape and ecosystem of a given region. Although the software has been tested on a variety of data, as with any software, the user should carefully evaluate the results with their data. The programs were designed for the range of precipitation, temperature, and streamflow measurements expected in the semiarid Southwest United States. The user is encouraged to review the examples provided with the software. The software is written in Fortran 90 with Fortran 95 extensions and was compiled with the Digital Visual Fortran compiler version 6.6. The executables run on Windows 2000 and XP, and they operate in a MS-DOS console window that has only very simple graphical options such as font size and color, background color, and size of the window. Error trapping was not written into the programs. Typically, when an error occurs, the console window closes without a message.
NASA Astrophysics Data System (ADS)
Regonda, Satish Kumar; Seo, Dong-Jun; Lawrence, Bill; Brown, James D.; Demargne, Julie
2013-08-01
We present a statistical procedure for generating short-term ensemble streamflow forecasts from single-valued, or deterministic, streamflow forecasts produced operationally by the U.S. National Weather Service (NWS) River Forecast Centers (RFCs). The resulting ensemble streamflow forecast provides an estimate of the predictive uncertainty associated with the single-valued forecast to support risk-based decision making by the forecasters and by the users of the forecast products, such as emergency managers. Forced by single-valued quantitative precipitation and temperature forecasts (QPF, QTF), the single-valued streamflow forecasts are produced at a 6-h time step nominally out to 5 days into the future. The single-valued streamflow forecasts reflect various run-time modifications, or "manual data assimilation", applied by the human forecasters in an attempt to reduce error from various sources in the end-to-end forecast process. The proposed procedure generates ensemble traces of streamflow from a parsimonious approximation of the conditional multivariate probability distribution of future streamflow given the single-valued streamflow forecast, QPF, and the most recent streamflow observation. For parameter estimation and evaluation, we used a multiyear archive of the single-valued river stage forecast produced operationally by the NWS Arkansas-Red River Basin River Forecast Center (ABRFC) in Tulsa, Oklahoma. As a by-product of parameter estimation, the procedure provides a categorical assessment of the effective lead time of the operational hydrologic forecasts for different QPF and forecast flow conditions. To evaluate the procedure, we carried out hindcasting experiments in dependent and cross-validation modes. The results indicate that the short-term streamflow ensemble hindcasts generated from the procedure are generally reliable within the effective lead time of the single-valued forecasts and well capture the skill of the single-valued forecasts. For smaller basins, however, the effective lead time is significantly reduced by short basin memory and reduced skill in the single-valued QPF.
Climate model assessment of changes in winter-spring streamflow timing over North America
Kam, Jonghun; Knutson, Thomas R.; Milly, Paul C. D.
2018-01-01
Over regions where snow-melt runoff substantially contributes to winter-spring streamflows, warming can accelerate snow melt and reduce dry-season streamflows. However, conclusive detection of changes and attribution to anthropogenic forcing is hindered by brevity of observational records, model uncertainty, and uncertainty concerning internal variability. In this study, a detection/attribution of changes in mid-latitude North American winter-spring streamflow timing is examined using nine global climate models under multiple forcing scenarios. In this study, robustness across models, start/end dates for trends, and assumptions about internal variability is evaluated. Marginal evidence for an emerging detectable anthropogenic influence (according to four or five of nine models) is found in the north-central U.S., where winter-spring streamflows have been coming earlier. Weaker indications of detectable anthropogenic influence (three of nine models) are found in the mountainous western U.S./southwestern Canada and in extreme northeastern U.S./Canadian Maritimes. In the former region, a recent shift toward later streamflows has rendered the full-record trend toward earlier streamflows only marginally significant, with possible implications for previously published climate change detection findings for streamflow timing in this region. In the latter region, no forced model shows as large a shift toward earlier streamflow timing as the detectable observed shift. In other (including warm, snow-free) regions, observed trends are typically not detectable, although in the U.S. central plains we find detectable delays in streamflow, which are inconsistent with forced model experiments.
August median streamflow on ungaged streams in Eastern Coastal Maine
Lombard, Pamela J.
2004-01-01
Methods for estimating August median streamflow were developed for ungaged, unregulated streams in eastern coastal Maine. The methods apply to streams with drainage areas ranging in size from 0.04 to 73.2 square miles and fraction of basin underlain by a sand and gravel aquifer ranging from 0 to 71 percent. The equations were developed with data from three long-term (greater than or equal to 10 years of record) continuous-record streamflow-gaging stations, 23 partial-record streamflow- gaging stations, and 5 short-term (less than 10 years of record) continuous-record streamflow-gaging stations. A mathematical technique for estimating a standard low-flow statistic, August median streamflow, at partial-record streamflow-gaging stations and short-term continuous-record streamflow-gaging stations was applied by relating base-flow measurements at these stations to concurrent daily streamflows at nearby long-term continuous-record streamflow-gaging stations (index stations). Generalized least-squares regression analysis (GLS) was used to relate estimates of August median streamflow at streamflow-gaging stations to basin characteristics at these same stations to develop equations that can be applied to estimate August median streamflow on ungaged streams. GLS accounts for different periods of record at the gaging stations and the cross correlation of concurrent streamflows among gaging stations. Thirty-one stations were used for the final regression equations. Two basin characteristics?drainage area and fraction of basin underlain by a sand and gravel aquifer?are used in the calculated regression equation to estimate August median streamflow for ungaged streams. The equation has an average standard error of prediction from -27 to 38 percent. A one-variable equation uses only drainage area to estimate August median streamflow when less accuracy is acceptable. This equation has an average standard error of prediction from -30 to 43 percent. Model error is larger than sampling error for both equations, indicating that additional or improved estimates of basin characteristics could be important to improved estimates of low-flow statistics. Weighted estimates of August median streamflow at partial- record or continuous-record gaging stations range from 0.003 to 31.0 cubic feet per second or from 0.1 to 0.6 cubic feet per second per square mile. Estimates of August median streamflow on ungaged streams in eastern coastal Maine, within the range of acceptable explanatory variables, range from 0.003 to 45 cubic feet per second or 0.1 to 0.6 cubic feet per second per square mile. Estimates of August median streamflow per square mile of drainage area generally increase as drainage area and fraction of basin underlain by a sand and gravel aquifer increase.
A comparison of hydrologic models for ecological flows and water availability
Caldwell, Peter V; Kennen, Jonathan G.; Sun, Ge; Kiang, Julie E.; Butcher, John B; Eddy, Michelle C; Hay, Lauren E.; LaFontaine, Jacob H.; Hain, Ernie F.; Nelson, Stacy C; McNulty, Steve G
2015-01-01
Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems and reliable water supplies for people, but there is a lack of comprehensive model comparison studies that quantify differences in streamflow predictions among model applications developed to answer management questions. We assessed differences in daily streamflow predictions by four fine-scale models and two regional-scale monthly time step models by comparing model fit statistics and bias in ecologically relevant flow statistics (ERFSs) at five sites in the Southeastern USA. Models were calibrated to different extents, including uncalibrated (level A), calibrated to a downstream site (level B), calibrated specifically for the site (level C) and calibrated for the site with adjusted precipitation and temperature inputs (level D). All models generally captured the magnitude and variability of observed streamflows at the five study sites, and increasing level of model calibration generally improved performance. All models had at least 1 of 14 ERFSs falling outside a +/−30% range of hydrologic uncertainty at every site, and ERFSs related to low flows were frequently over-predicted. Our results do not indicate that any specific hydrologic model is superior to the others evaluated at all sites and for all measures of model performance. Instead, we provide evidence that (1) model performance is as likely to be related to calibration strategy as it is to model structure and (2) simple, regional-scale models have comparable performance to the more complex, fine-scale models at a monthly time step.
NASA Astrophysics Data System (ADS)
Yang, Yuhui; Chen, Yaning; Wang, Minzhong; Sun, Huilan
2017-07-01
We examined the changes in streamflow on the northern slopes of the Tianshan Mountains in northern Xinjiang, China, over two time scales: the past 500 years, based on dendrochronology data; and the past 50 years, based on streamflow data from hydrological stations. The method of artificial neural networks built from the data of the 50-year period was used to reconstruct the streamflow of the 500-year period. The results indicate that streamflow has undergone seven high-flow periods and four low-flow periods during the past 500 years. To identify possible transition points in the streamflow, we applied the Mann-Kendall and running T tests to the 50- and 500-year periods, respectively. During the past 500 years, streamflow has changed significantly from low to high flow about three to four times, and from high to low flow about three to five times. Over the recent 50 years, there have been three phases of variation in river runoff, and the most distinct transition of streamflow occurred in 1996.
NASA Astrophysics Data System (ADS)
Liu, Shulun; Li, Yuan; Pauwels, Valentijn R. N.; Walker, Jeffrey P.
2017-12-01
Rain gauges are widely used to obtain temporally continuous point rainfall records, which are then interpolated into spatially continuous data to force hydrological models. However, rainfall measurements and interpolation procedure are subject to various uncertainties, which can be reduced by applying quality control and selecting appropriate spatial interpolation approaches. Consequently, the integrated impact of rainfall quality control and interpolation on streamflow simulation has attracted increased attention but not been fully addressed. This study applies a quality control procedure to the hourly rainfall measurements obtained in the Warwick catchment in eastern Australia. The grid-based daily precipitation from the Australian Water Availability Project was used as a reference. The Pearson correlation coefficient between the daily accumulation of gauged rainfall and the reference data was used to eliminate gauges with significant quality issues. The unrealistic outliers were censored based on a comparison between gauged rainfall and the reference. Four interpolation methods, including the inverse distance weighting (IDW), nearest neighbors (NN), linear spline (LN), and ordinary Kriging (OK), were implemented. The four methods were firstly assessed through a cross-validation using the quality-controlled rainfall data. The impacts of the quality control and interpolation on streamflow simulation were then evaluated through a semi-distributed hydrological model. The results showed that the Nash–Sutcliffe model efficiency coefficient (NSE) and Bias of the streamflow simulations were significantly improved after quality control. In the cross-validation, the IDW and OK methods resulted in good interpolation rainfall, while the NN led to the worst result. In term of the impact on hydrological prediction, the IDW led to the most consistent streamflow predictions with the observations, according to the validation at five streamflow-gauged locations. The OK method performed second best according to streamflow predictions at the five gauges in the calibration period (01/01/2007–31/12/2011) and four gauges during the validation period (01/01/2012–30/06/2014). However, NN produced the worst prediction at the outlet of the catchment in the validation period, indicating a low robustness. While the IDW exhibited the best performance in the study catchment in terms of accuracy, robustness and efficiency, more general recommendations on the selection of rainfall interpolation methods need to be further explored.
NASA Astrophysics Data System (ADS)
Liu, Shulun; Li, Yuan; Pauwels, Valentijn R. N.; Walker, Jeffrey P.
2018-01-01
Rain gauges are widely used to obtain temporally continuous point rainfall records, which are then interpolated into spatially continuous data to force hydrological models. However, rainfall measurements and interpolation procedure are subject to various uncertainties, which can be reduced by applying quality control and selecting appropriate spatial interpolation approaches. Consequently, the integrated impact of rainfall quality control and interpolation on streamflow simulation has attracted increased attention but not been fully addressed. This study applies a quality control procedure to the hourly rainfall measurements obtained in the Warwick catchment in eastern Australia. The grid-based daily precipitation from the Australian Water Availability Project was used as a reference. The Pearson correlation coefficient between the daily accumulation of gauged rainfall and the reference data was used to eliminate gauges with significant quality issues. The unrealistic outliers were censored based on a comparison between gauged rainfall and the reference. Four interpolation methods, including the inverse distance weighting (IDW), nearest neighbors (NN), linear spline (LN), and ordinary Kriging (OK), were implemented. The four methods were firstly assessed through a cross-validation using the quality-controlled rainfall data. The impacts of the quality control and interpolation on streamflow simulation were then evaluated through a semi-distributed hydrological model. The results showed that the Nash–Sutcliffe model efficiency coefficient (NSE) and Bias of the streamflow simulations were significantly improved after quality control. In the cross-validation, the IDW and OK methods resulted in good interpolation rainfall, while the NN led to the worst result. In term of the impact on hydrological prediction, the IDW led to the most consistent streamflow predictions with the observations, according to the validation at five streamflow-gauged locations. The OK method performed second best according to streamflow predictions at the five gauges in the calibration period (01/01/2007–31/12/2011) and four gauges during the validation period (01/01/2012–30/06/2014). However, NN produced the worst prediction at the outlet of the catchment in the validation period, indicating a low robustness. While the IDW exhibited the best performance in the study catchment in terms of accuracy, robustness and efficiency, more general recommendations on the selection of rainfall interpolation methods need to be further explored.
Crow, Cassi L.; Banta, J. Ryan; Opsahl, Stephen P.
2014-01-01
San Antonio and surrounding municipalities in Bexar County, Texas, are in a rapidly urbanizing region in the San Antonio River Basin. The U.S. Geological Survey, in cooperation with the San Antonio River Authority and the Texas Water Development Board, compiled historical sediment data collected between 1996 and 2004 and collected suspended-sediment and bedload samples over a range of hydrologic conditions in the San Antonio River Basin downstream from San Antonio, Tex., and at a site on the Guadalupe River downstream from the San Antonio River Basin during 2011–13. In the suspended-sediment samples collected during 2011–13, an average of about 94 percent of the particles was less than 0.0625 millimeter (silt and clay sized particles); the 50 samples for which a complete sediment-size analysis was performed indicated that an average of about 69 percent of the particles was less than 0.002 millimeter. In the bedload samples collected during 2011–13, an average of 51 percent of sediment particles was sand-sized particles in the 0.25–0.5 millimeter-size range. In general, the loads calculated from the samples indicated that bedload typically composed less than 1 percent of the total sediment load. A least-squares log-linear regression was developed between suspended-sediment concentration and instantaneous streamflow and was used to estimate daily mean suspended-sediment loads based on daily mean streamflow. The daily mean suspended-sediment loads computed for each of the sites indicated that during 2011–12, the majority of the suspended-sediment loads originated upstream from the streamflow-gaging station on the San Antonio River near Elmendorf, Tex. A linear regression relation was developed between turbidity and suspended-sediment concentration data collected at the San Antonio River near Elmendorf site because the high-resolution data can facilitate understanding of the complex suspended-sediment dynamics over time and throughout the river basin.
Skilful seasonal forecasts of streamflow over Europe?
NASA Astrophysics Data System (ADS)
Arnal, Louise; Cloke, Hannah L.; Stephens, Elisabeth; Wetterhall, Fredrik; Prudhomme, Christel; Neumann, Jessica; Krzeminski, Blazej; Pappenberger, Florian
2018-04-01
This paper considers whether there is any added value in using seasonal climate forecasts instead of historical meteorological observations for forecasting streamflow on seasonal timescales over Europe. A Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) seasonal streamflow forecasts (produced by forcing the Lisflood model with the ECMWF System 4 seasonal climate forecasts), benchmarked against the ensemble streamflow prediction (ESP) forecasting approach (produced by forcing the Lisflood model with historical meteorological observations), is undertaken. The results suggest that, on average, the System 4 seasonal climate forecasts improve the streamflow predictability over historical meteorological observations for the first month of lead time only (in terms of hindcast accuracy, sharpness and overall performance). However, the predictability varies in space and time and is greater in winter and autumn. Parts of Europe additionally exhibit a longer predictability, up to 7 months of lead time, for certain months within a season. In terms of hindcast reliability, the EFAS seasonal streamflow hindcasts are on average less skilful than the ESP for all lead times. The results also highlight the potential usefulness of the EFAS seasonal streamflow forecasts for decision-making (measured in terms of the hindcast discrimination for the lower and upper terciles of the simulated streamflow). Although the ESP is the most potentially useful forecasting approach in Europe, the EFAS seasonal streamflow forecasts appear more potentially useful than the ESP in some regions and for certain seasons, especially in winter for almost 40 % of Europe. Patterns in the EFAS seasonal streamflow hindcast skill are however not mirrored in the System 4 seasonal climate hindcasts, hinting at the need for a better understanding of the link between hydrological and meteorological variables on seasonal timescales, with the aim of improving climate-model-based seasonal streamflow forecasting.
Temporal Differences in the Hydrologic Regime of the Lower Platte River, Nebraska, 1895-2006
Ginting, Daniel; Zelt, Ronald B.; Linard, Joshua I.
2008-01-01
In cooperation with the Lower Platte South Natural Resources District for a collaborative study of the cumulative effects of water and channel management practices on stream and riparian ecology, the U.S. Geological Survey (USGS) compiled, analyzed, and summarized hydrologic information from long-term gaging stations on the lower Platte River to determine any significant temporal differences among six discrete periods during 1895-2006 and to interpret any significant changes in relation to changes in climatic conditions or other factors. A subset of 171 examined hydrologic indices (HIs) were selected for use as indices that (1) included most of the variance in the larger set of indices, (2) retained utility as indicators of the streamflow regime, and (3) provided information at spatial and temporal scale(s) that were most indicative of streamflow regime(s). The study included the most downstream station within the central Platte River segment that flowed to the confluence with the Loup River and all four active streamflow-gaging stations (2006) on the lower Platte River main stem extending from the confluence of the Loup River and Platte River to the confluence of the Platte River and Missouri River south of Omaha. The drainage areas of the five streamflow-gaging stations covered four (of eight) climate divisions in Nebraska?division 2 (north central), 3 (northeast), 5 (central), and 6 (east central). Historical climate data and daily streamflow records from 1895 through 2006 at the five streamflow-gaging stations were divided into six 11-water-year periods: 1895?1905, 1934?44, 1951?61, 1966?76, 1985?95, and 1996?2006. Analysis of monthly climate variables?precipitation and Palmer Hydrological Drought Index?was used to determine the degree of hydroclimatic association between streamflow and climate. Except for the 1895?1905 period, data gaps in the streamflow record were filled by data estimation techniques, and 171 hydrologic indices were calculated using the Hydroecological Integrity Assessment Process software developed by the U.S. Geological Survey. A subset of 27 nonredundant indices (of the 171 indices) was selected using principal component analysis. Indices that described monthly streamflow?mean, maximum, minimum, skewness, and coefficients of variation?also were used. Comparison of these selected indices allowed determination of temporal differences among the six 11-water-year periods for each gaging station. The lower Platte River basin was affected by moderate to severe drought conditions in the 1934?44 period. The widespread drought was preceded by mildly to moderately wet conditions in the 1895?1906 period, followed by incipient drought to incipiently wet conditions in the 1951?61 periods and mildly wet conditions in 1966?76 period, moderately wet conditions in the 1985?1995 period, and incipient drought to mildly wet conditions in the 1996?2006 period. Monthly streamflow of the Platte River from Duncan through Louisville, Nebraska, correlated significantly with the monthly Palmer Hydrological Drought Index. Temporal differences in median values of monthly-mean and monthly-maximum streamflow measured at Duncan, North Bend, and Ashland stations between the two moderately wet periods (1895?1905 and 1985?95) indicated that streamflow storage reservoirs and regulation some time after 1906 significantly reduced monthly streamflow magnitude and amplitude?the difference between the highest and lowest median values of monthly mean streamflow. Effects of storage reservoirs on the median values of monthly-minimum streamflow were less obvious. Temporal differences among the other five periods, from 1934 through 2006 when streamflow was affected by storage and regulation, indicated the predominant effects of contrasting climate conditions on median values of monthly mean, maximum, and minimum streamflow. Significant temporal differences in monthly streamflow values were evident mainly between the two periods of greatly
Ries, Kernell G.; Eng, Ken
2010-01-01
The U.S. Geological Survey, in cooperation with the Maryland Department of the Environment, operated a network of 20 low-flow partial-record stations during 2008 in a region that extends from southwest of Baltimore to the northeastern corner of Maryland to obtain estimates of selected streamflow statistics at the station locations. The study area is expected to face a substantial influx of new residents and businesses as a result of military and civilian personnel transfers associated with the Federal Base Realignment and Closure Act of 2005. The estimated streamflow statistics, which include monthly 85-percent duration flows, the 10-year recurrence-interval minimum base flow, and the 7-day, 10-year low flow, are needed to provide a better understanding of the availability of water resources in the area to be affected by base-realignment activities. Streamflow measurements collected for this study at the low-flow partial-record stations and measurements collected previously for 8 of the 20 stations were related to concurrent daily flows at nearby index streamgages to estimate the streamflow statistics. Three methods were used to estimate the streamflow statistics and two methods were used to select the index streamgages. Of the three methods used to estimate the streamflow statistics, two of them--the Moments and MOVE1 methods--rely on correlating the streamflow measurements at the low-flow partial-record stations with concurrent streamflows at nearby, hydrologically similar index streamgages to determine the estimates. These methods, recommended for use by the U.S. Geological Survey, generally require about 10 streamflow measurements at the low-flow partial-record station. The third method transfers the streamflow statistics from the index streamgage to the partial-record station based on the average of the ratios of the measured streamflows at the partial-record station to the concurrent streamflows at the index streamgage. This method can be used with as few as one pair of streamflow measurements made on a single streamflow recession at the low-flow partial-record station, although additional pairs of measurements will increase the accuracy of the estimates. Errors associated with the two correlation methods generally were lower than the errors associated with the flow-ratio method, but the advantages of the flow-ratio method are that it can produce reasonably accurate estimates from streamflow measurements much faster and at lower cost than estimates obtained using the correlation methods. The two index-streamgage selection methods were (1) selection based on the highest correlation coefficient between the low-flow partial-record station and the index streamgages, and (2) selection based on Euclidean distance, where the Euclidean distance was computed as a function of geographic proximity and the basin characteristics: drainage area, percentage of forested area, percentage of impervious area, and the base-flow recession time constant, t. Method 1 generally selected index streamgages that were significantly closer to the low-flow partial-record stations than method 2. The errors associated with the estimated streamflow statistics generally were lower for method 1 than for method 2, but the differences were not statistically significant. The flow-ratio method for estimating streamflow statistics at low-flow partial-record stations was shown to be independent from the two correlation-based estimation methods. As a result, final estimates were determined for eight low-flow partial-record stations by weighting estimates from the flow-ratio method with estimates from one of the two correlation methods according to the respective variances of the estimates. Average standard errors of estimate for the final estimates ranged from 90.0 to 7.0 percent, with an average value of 26.5 percent. Average standard errors of estimate for the weighted estimates were, on average, 4.3 percent less than the best average standard errors of estima
NASA Astrophysics Data System (ADS)
Paul, M.; Negahban-Azar, M.
2017-12-01
The hydrologic models usually need to be calibrated against observed streamflow at the outlet of a particular drainage area through a careful model calibration. However, a large number of parameters are required to fit in the model due to their unavailability of the field measurement. Therefore, it is difficult to calibrate the model for a large number of potential uncertain model parameters. This even becomes more challenging if the model is for a large watershed with multiple land uses and various geophysical characteristics. Sensitivity analysis (SA) can be used as a tool to identify most sensitive model parameters which affect the calibrated model performance. There are many different calibration and uncertainty analysis algorithms which can be performed with different objective functions. By incorporating sensitive parameters in streamflow simulation, effects of the suitable algorithm in improving model performance can be demonstrated by the Soil and Water Assessment Tool (SWAT) modeling. In this study, the SWAT was applied in the San Joaquin Watershed in California covering 19704 km2 to calibrate the daily streamflow. Recently, sever water stress escalating due to intensified climate variability, prolonged drought and depleting groundwater for agricultural irrigation in this watershed. Therefore it is important to perform a proper uncertainty analysis given the uncertainties inherent in hydrologic modeling to predict the spatial and temporal variation of the hydrologic process to evaluate the impacts of different hydrologic variables. The purpose of this study was to evaluate the sensitivity and uncertainty of the calibrated parameters for predicting streamflow. To evaluate the sensitivity of the calibrated parameters three different optimization algorithms (Sequential Uncertainty Fitting- SUFI-2, Generalized Likelihood Uncertainty Estimation- GLUE and Parameter Solution- ParaSol) were used with four different objective functions (coefficient of determination- r2, Nash-Sutcliffe efficiency- NSE, percent bias- PBIAS, and Kling-Gupta efficiency- KGE). The preliminary results showed that using the SUFI-2 algorithm with the objective function NSE and KGE has improved significantly the calibration (e.g. R2 and NSE is found 0.52 and 0.47 respectively for daily streamflow calibration).
Analysis of the U.S. geological survey streamgaging network
Scott, A.G.
1987-01-01
This paper summarizes the results from the first 3 years of a 5-year cost-effectiveness study of the U.S. Geological Survey streamgaging network. The objective of the study is to define and document the most cost-effective means of furnishing streamflow information. In the first step of this study, data uses were identified for 3,493 continuous-record stations currently being operated in 32 States. In the second step, evaluation of alternative methods of providing streamflow information, flow-routing models, and regression models were developed for estimating daily flows at 251 stations of the 3,493 stations analyzed. In the third step of the analysis, relationships were developed between the accuracy of the streamflow records and the operating budget. The weighted standard error for all stations, with current operating procedures, was 19.9 percent. By altering field activities, as determined by the analyses, this could be reduced to 17.8 percent. The existing streamgaging networks in four Districts were further analyzed to determine the impacts that satellite telemetry would have on the cost effectiveness. Satellite telemetry was not found to be cost effective on the basis of hydrologic data collection alone, given present cost of equipment and operation.This paper summarizes the results from the first 3 years of a 5-year cost-effectiveness study of the U. S. Geological Survey streamgaging network. The objective of the study is to define and document the most cost-effective means of furnishing streamflow information. In the first step of this study, data uses were identified for 3,493 continuous-record stations currently being operated in 32 States. In the second step, evaluation of alternative methods of providing streamflow information, flow-routing models, and regression models were developed for estimating daily flows at 251 stations of the 3, 493 stations analyzed. In the third step of the analysis, relationships were developed between the accuracy of the streamflow records and the operating budget. The weighted standard error for all stations, with current operating procedures, was 19. 9 percent. By altering field activities, as determined by the analyses, this could be reduced to 17. 8 percent. Additional study results are discussed.
NASA Astrophysics Data System (ADS)
Ashouri, H.; Nguyen, P.; Thorstensen, A. R.; Hsu, K. L.; Sorooshian, S.
2014-12-01
This study evaluates the performance of a newly developed long-term high-resolution satellite-based precipitation products, named Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network - Climate Data Record (PERSIANN-CDR), in hydrological modeling. PERSIANN-CDR estimations are biased corrected using GPCP monthly climatology data. PERSIANN-CDR provides daily rainfall estimates at 0.25° x 0.25° grid boxes for 1983-2014 (delayed present). This newly released product makes it feasible to model the streamflow over the past 30 years. Three test basins from the Distributed Hydrologic Model Intercomparison Project - Phase 2 (DMIP 2) are chosen. Comparing with other satellite products, the Version 7 TRMM Multi-satellite Precipitation Analysis (TMPA) product is used. Stage IV radar data is used as a reference data for evaluating the PERSIANN-CDR and TMPA precipitation data. All products are scaled to 0.25° and daily spatiotemporal resolution. The study is performed in two phases. In the first phase, the 2003-2011 period where all the products are available is chosen. Precipitation evaluation results, presented on Taylor Diagrams, show that TMPA and PERSIANN-CDR have close performances. The National Weather Service (NWS) Office of Hydrologic Development (OHD) Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) is then forced with the PERSIANN-CDR and the TMPA precipitation products, as well as the stage IV radar data. USGS Streamflow observations at the outlet of the basins are used as the reference streamflow data. The results show that in general, in all the three DMIP 2 basins the simulated hydrographs forced with PERSIANN-CDR and TMPA show good agreement, as the statistical measures such as root mean square error, bias, and correlation coefficient are close. In addition, with respect to the streamflow peaks, PERSIANN-CDR shows better performance than Stage IV radar data in capturing the extreme streamflow magnitudes. Based on the results from the first phase of the study and given the fact that PERSIANN-CDR covers the 1983-2014, in the second phase of the study we model the streamflow for the period of 1983-2014. The results will be presented in the meeting.
NASA Astrophysics Data System (ADS)
Alvarez-Garreton, C. D.; Mendoza, P. A.; Zambrano-Bigiarini, M.; Galleguillos, M. H.; Boisier, J. P.; Lara, A.; Cortés, G.; Garreaud, R.; McPhee, J. P.; Addor, N.; Puelma, C.
2017-12-01
We provide the first catchment-based hydrometeorological, vegetation and physical data set over 531 catchments in Chile (17.8 S - 55.0 S). We compiled publicly available streamflow records at daily time steps for the period 1980-2015, and generated basin-averaged time series of the following hydrometeorological variables: 1) daily precipitation coming from three different gridded sources (re-analysis and satellite-based); 2) daily maximum and minimum temperature; 3) 8-days potential evapotranspiration (PET) based on MODIS imagery and daily PET based on Hargreaves formula; and 4) daily snow water equivalent. Additionally, catchments are characterized by their main physical (area, mean elevation, mean slope) and land cover characteristics. We synthetized these datasets with several indices characterizing the spatial distribution of climatic, hydrological, topographic and vegetation attributes. The new catchment-based dataset is unprecedented in the region and provides information that can be used in a myriad of applications, including catchment classification and regionalization studies, impacts of different land cover types on catchment response, characterization of drought history and projections, climate change impacts on hydrological processes, etc. Derived practical applications include water management and allocation strategies, decision making and adaptation planning to climate change. This data set will be publicly available and we encourage the community to use it.
Statistical summaries of selected Iowa streamflow data through September 2013
Eash, David A.; O'Shea, Padraic S.; Weber, Jared R.; Nguyen, Kevin T.; Montgomery, Nicholas L.; Simonson, Adrian J.
2016-01-04
Statistical summaries of streamflow data collected at 184 streamgages in Iowa are presented in this report. All streamgages included for analysis have at least 10 years of continuous record collected before or through September 2013. This report is an update to two previously published reports that presented statistical summaries of selected Iowa streamflow data through September 1988 and September 1996. The statistical summaries include (1) monthly and annual flow durations, (2) annual exceedance probabilities of instantaneous peak discharges (flood frequencies), (3) annual exceedance probabilities of high discharges, and (4) annual nonexceedance probabilities of low discharges and seasonal low discharges. Also presented for each streamgage are graphs of the annual mean discharges, mean annual mean discharges, 50-percent annual flow-duration discharges (median flows), harmonic mean flows, mean daily mean discharges, and flow-duration curves. Two sets of statistical summaries are presented for each streamgage, which include (1) long-term statistics for the entire period of streamflow record and (2) recent-term statistics for or during the 30-year period of record from 1984 to 2013. The recent-term statistics are only calculated for streamgages with streamflow records pre-dating the 1984 water year and with at least 10 years of record during 1984–2013. The streamflow statistics in this report are not adjusted for the effects of water use; although some of this water is used consumptively, most of it is returned to the streams.
Potential Impact of Climate Change on Streamflow of Major Ethiopian Rivers
NASA Astrophysics Data System (ADS)
Gizaw, M. S.; Zhang, S.; Biftu, G. F.; Gan, T. Y.; Tan, X.; Moges, S. A.; Koivusalo, H.
2017-12-01
In this study, HSPF (Hydrologic Simulation Program-FORTRAN) was used to analyze the potential impact of climate change on the streamflow of four major river basins in Ethiopia: Awash, Baro, Genale and Tekeze. The calibrated and validated HSPF model was forced with daily climate data of 10 CMIP5 (Coupled Model Intercomparison Project phase 5) Global Climate Models (GCMs) for the 1971-2000 control period and the RCP4.5 and RCP8.5 climate projections of 2041-2070 (2050s) and 2071-2100 (2080s). The ensemble median of these 10 GCMs projects the temperature in the four study areas to increase by about 2.3 ˚C (3.3 ˚C) in 2050s (2080s) whereas the mean annual precipitation is projected to increase by about 6% (9%) in 2050s (2080s). This results in about 3% (6%) increase in the projected annual streamflow in Awash, Baro and Tekeze rivers whereas the annual streamflow of Genale river is projected to increase by about 18% (33%) in the 2050s (2080s). However, such projected increase in the mean annual streamflow due to increasing precipitation over Ethiopia contradicts the decreasing trends in mean annual precipitation observed in recent decades. Regional climate models of high resolutions could provide more realistic climate projections for Ethiopia's complex topography, thus reducing the uncertainties in future streamflow projections.
Estimating ice-affected streamflow by extended Kalman filtering
Holtschlag, D.J.; Grewal, M.S.
1998-01-01
An extended Kalman filter was developed to automate the real-time estimation of ice-affected streamflow on the basis of routine measurements of stream stage and air temperature and on the relation between stage and streamflow during open-water (ice-free) conditions. The filter accommodates three dynamic modes of ice effects: sudden formation/ablation, stable ice conditions, and eventual elimination. The utility of the filter was evaluated by applying it to historical data from two long-term streamflow-gauging stations, St. John River at Dickey, Maine and Platte River at North Bend, Nebr. Results indicate that the filter was stable and that parameters converged for both stations, producing streamflow estimates that are highly correlated with published values. For the Maine station, logarithms of estimated streamflows are within 8% of the logarithms of published values 87.2% of the time during periods of ice effects and within 15% 96.6% of the time. Similarly, for the Nebraska station, logarithms of estimated streamflows are within 8% of the logarithms of published values 90.7% of the time and within 15% 97.7% of the time. In addition, the correlation between temporal updates and published streamflows on days of direct measurements at the Maine station was 0.777 and 0.998 for ice-affected and open-water periods, respectively; for the Nebraska station, corresponding correlations were 0.864 and 0.997.
Assessing the Impact of Climate Change on Stream Temperatures in the Methow River Basin, Washington
NASA Astrophysics Data System (ADS)
Gangopadhyay, S.; Caldwell, R. J.; Lai, Y.; Bountry, J.
2011-12-01
The Methow River in Washington offers prime spawning habitat for salmon and other cold-water fishes. During the summer months, low streamflows on the Methow result in cutoff side channels that limit the habitat available to these fishes. Future climate scenarios of increasing air temperature and decreasing precipitation suggest the potential for increasing loss of habitat and fish mortality as stream temperatures rise in response to lower flows and additional heating. To assess the impacts of climate change on stream temperature in the Methow River, the US Bureau of Reclamation is developing an hourly time-step, two-dimensional hydraulic model of the confluence of the Methow and Chewuch Rivers above Winthrop. The model will be coupled with a physical stream temperature model to generate spatial representations of stream conditions conducive for fish habitat. In this study, we develop a statistical framework for generating stream temperature time series from global climate model (GCM) and hydrologic model outputs. Regional observations of stream temperature and hydrometeorological conditions are used to develop statistical models of daily mean stream temperature for the Methow River at Winthrop, WA. Temperature and precipitation projections from 10 global climate models (GCMs) are coupled with the streamflow generated using the University of Washington Variable Infiltration Capacity model. The projections serve as input to the statistical models to generate daily time series of mean daily stream temperature. Since the output from the GCM, VIC, and statistical models offer only daily data, a k-nearest neighbor (k-nn) resampling technique is employed to select appropriate proportion vectors for disaggregating the Winthrop daily flow and temperature to an upstream location on each of the rivers above the confluence. Hourly proportion vectors are then used to disaggregate the daily flow and temperature to hourly values to be used in the hydraulic model. Historical meteorological variables are also selected using the k-nn method. We present the statistical modeling framework using Generalized Linear Models (GLMs), along with diagnostics and measurements of skill. We will also provide a comparison of the stream temperature projections from the future years of 2020, 2040, and 2080 and discuss the potential implications on fish habitat in the Methow River. Future integration of the hourly climate scenarios in the hydraulic model will provide the ability to assess the spatial extent of habitat impacts and allow the USBR to evaluate the effectiveness of various river restoration projects in maintaining or improving habitat in a changing climate.
Asquith, W.H.; Mosier, J. G.; Bush, P.W.
1997-01-01
The watershed simulation model Hydrologic Simulation Program—Fortran (HSPF) was used to generate simulated flow (runoff) from the 13 watersheds to the six bay systems because adequate gaged streamflow data from which to estimate freshwater inflows are not available; only about 23 percent of the adjacent contributing watershed area is gaged. The model was calibrated for the gaged parts of three watersheds—that is, selected input parameters (meteorologic and hydrologic properties and conditions) that control runoff were adjusted in a series of simulations until an adequate match between model-generated flows and a set (time series) of gaged flows was achieved. The primary model input is rainfall and evaporation data and the model output is a time series of runoff volumes. After calibration, simulations driven by daily rainfall for a 26-year period (1968–93) were done for the 13 watersheds to obtain runoff under current (1983–93), predevelopment (pre-1940 streamflow and pre-urbanization), and future (2010) land-use conditions for estimating freshwater inflows and for comparing runoff under the three land-use conditions; and to obtain time series of runoff from which to estimate time series of freshwater inflows for trend analysis.
Lizarraga, Joy S.; Ockerman, Darwin J.
2011-01-01
The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; the City of Corpus Christi; the Guadalupe-Blanco River Authority; the San Antonio River Authority; and the San Antonio Water System, configured, calibrated, and tested a watershed model for a study area consisting of about 5,490 mi2 of the Frio River watershed in south Texas. The purpose of the model is to contribute to the understanding of watershed processes and hydrologic conditions in the lower Frio River watershed. The model simulates streamflow, evapotranspiration (ET), and groundwater recharge by using a numerical representation of physical characteristics of the landscape, and meteorological and streamflow data. Additional time-series inputs to the model include wastewater-treatment-plant discharges, surface-water withdrawals, and estimated groundwater inflow from Leona Springs. Model simulations of streamflow, ET, and groundwater recharge were done for various periods of record depending upon available measured data for input and comparison, starting as early as 1961. Because of the large size of the study area, the lower Frio River watershed was divided into 12 subwatersheds; separate Hydrological Simulation Program-FORTRAN models were developed for each subwatershed. Simulation of the overall study area involved running simulations in downstream order. Output from the model was summarized by subwatershed, point locations, reservoir reaches, and the Carrizo-Wilcox aquifer outcrop. Four long-term U.S. Geological Survey streamflow-gaging stations and two short-term streamflow-gaging stations were used for streamflow model calibration and testing with data from 1991-2008. Calibration was based on data from 2000-08, and testing was based on data from 1991-99. Choke Canyon Reservoir stage data from 1992-2008 and monthly evaporation estimates from 1999-2008 also were used for model calibration. Additionally, 2006-08 ET data from a U.S. Geological Survey meteorological station in Medina County were used for calibration. Streamflow and ET calibration were considered good or very good. For the 2000-08 calibration period, total simulated flow volume and the flow volume of the highest 10 percent of simulated daily flows were calibrated to within about 10 percent of measured volumes at six U.S. Geological Survey streamflow-gaging stations. The flow volume of the lowest 50 percent of daily flows was not simulated as accurately but represented a small percent of the total flow volume. The model-fit efficiency for the weekly mean streamflow during the calibration periods ranged from 0.60 to 0.91, and the root mean square error ranged from 16 to 271 percent of the mean flow rate. The simulated total flow volumes during the testing periods at the long-term gaging stations exceeded the measured total flow volumes by approximately 22 to 50 percent at three stations and were within 7 percent of the measured total flow volumes at one station. For the longer 1961-2008 simulation period at the long-term stations, simulated total flow volumes were within about 3 to 18 percent of measured total flow volumes. The calibrations made by using Choke Canyon reservoir volume for 1992-2008, reservoir evaporation for 1999-2008, and ET in Medina County for 2006-08, are considered very good. Model limitations include possible errors related to model conceptualization and parameter variability, lack of data to better quantify certain model inputs, and measurement errors. Uncertainty regarding the degree to which available rainfall data represent actual rainfall is potentially the most serious source of measurement error. A sensitivity analysis was performed for the Upper San Miguel subwatershed model to show the effect of changes to model parameters on the estimated mean recharge, ET, and surface runoff from that part of the Carrizo-Wilcox aquifer outcrop. Simulated recharge was most sensitive to the changes in the lower-zone ET (LZ
NASA Astrophysics Data System (ADS)
Lima, Aranildo R.; Hsieh, William W.; Cannon, Alex J.
2017-12-01
In situations where new data arrive continually, online learning algorithms are computationally much less costly than batch learning ones in maintaining the model up-to-date. The extreme learning machine (ELM), a single hidden layer artificial neural network with random weights in the hidden layer, is solved by linear least squares, and has an online learning version, the online sequential ELM (OSELM). As more data become available during online learning, information on the longer time scale becomes available, so ideally the model complexity should be allowed to change, but the number of hidden nodes (HN) remains fixed in OSELM. A variable complexity VC-OSELM algorithm is proposed to dynamically add or remove HN in the OSELM, allowing the model complexity to vary automatically as online learning proceeds. The performance of VC-OSELM was compared with OSELM in daily streamflow predictions at two hydrological stations in British Columbia, Canada, with VC-OSELM significantly outperforming OSELM in mean absolute error, root mean squared error and Nash-Sutcliffe efficiency at both stations.
Changes in the flood frequency in the Mahanadi basin under observed and projected future climate
NASA Astrophysics Data System (ADS)
Modi, P. A.; Lakshmi, V.; Mishra, V.
2017-12-01
The Mahanadi river basin is vulnerable to multiple types of extreme events due to its topography and river networks. These extreme events are not efficiently captured by the current LSMs partly due to lack of spatial hydrological data and uncertainty in the models. This study compares and evaluates the hydrologic simulations of the recently developed community Noah model with multi-parameterization options which is an upgradation of baseline Noah LSM. The model is calibrated and validated for the Mahanadi river basin and is driven by major atmospheric forcing from the Indian Meteorological Department (IMD), Global Precipitation Measurement (GPM), Tropical rainfall Measurement Mission (TRMM) and Multi-Source Weighted-Ensemble Precipitation (MSWEP designed for hydrological modeling) precipitation datasets along with some additional forcing derived from the VIC model at 0.25-degree spatial resolution. The Noah-MP LSM is calibrated using observed daily streamflow data from 1978-1989 (India-WRIS) at the gauge stations with least human interventions with a Nash Sutcliffe Efficiency higher than 0.60. Noah MP was calibrated using different schemes for runoff with variation in all parameters sensitive to surface and sub-surface runoff. Streamflow routing was performed using a stand-alone model (VIC model) to route daily model runoff at required gauge station. Surface runoff is mainly affected by the uncertainties in major atmospheric forcing and highly sensitive parameters pertaining to soil properties. Noah MP is validated using observed streamflow from 1975-2010 which indicates the consistency of streamflow with the historical observations (NSE>0.65) thus indicating an increase in probability of future flood events.
Slack, J.R.; Landwehr, Jurate Maciunas
1992-01-01
Records of streamflow can provide an account of climatic variation over a hydrologic basin. The ability to do so is conditioned on the absence of confounding factors that diminish the climate signal. A national data set of streamflow records that are relatively free of confounding anthropogenic influences has been developed for the purpose of studying the variation in surface-water conditions throughout the United States. Records in the U.S. Geological Survey (USGS) National Water Storage and Retrieval System (WATSTORE) data base for active and discontinued streamflow gaging stations through water year 1988 (that is, through September 30, 1988) were reviewed jointly with data specialists in each USGS District office. The resulting collection of stations, each with its respective period of record satisfying the qualifying criteria, is called the Hydro-Climatic Data Network, or HCDN. The HCDN consists of 1,659 sites throughout the United States and its territories, totaling 73,231 water years of daily mean discharge values. For each station in the HCDN, information necessary for its identification, along with any qualifying comments about the available record and a set of descriptive watershed characteristics are provided in tabular format in this report, both on paper and on computer disk (enclosed). For each station in the HCDN, the appropriate daily mean discharge values were compiled, and statistical characteristics, including monthly mean discharges and annual mean, minimum and maximum discharges, were derived. The discharge data values are provided in a companion report.
Modeled streamflow metrics on small, ungaged stream reaches in the Upper Colorado River Basin
Reynolds, Lindsay V.; Shafroth, Patrick B.
2016-01-20
Modeling streamflow is an important approach for understanding landscape-scale drivers of flow and estimating flows where there are no streamgage records. In this study conducted by the U.S. Geological Survey in cooperation with Colorado State University, the objectives were to model streamflow metrics on small, ungaged streams in the Upper Colorado River Basin and identify streams that are potentially threatened with becoming intermittent under drier climate conditions. The Upper Colorado River Basin is a region that is critical for water resources and also projected to experience large future climate shifts toward a drying climate. A random forest modeling approach was used to model the relationship between streamflow metrics and environmental variables. Flow metrics were then projected to ungaged reaches in the Upper Colorado River Basin using environmental variables for each stream, represented as raster cells, in the basin. Last, the projected random forest models of minimum flow coefficient of variation and specific mean daily flow were used to highlight streams that had greater than 61.84 percent minimum flow coefficient of variation and less than 0.096 specific mean daily flow and suggested that these streams will be most threatened to shift to intermittent flow regimes under drier climate conditions. Map projection products can help scientists, land managers, and policymakers understand current hydrology in the Upper Colorado River Basin and make informed decisions regarding water resources. With knowledge of which streams are likely to undergo significant drying in the future, managers and scientists can plan for stream-dependent ecosystems and human water users.
Ranking streamflow model performance based on Information theory metrics
NASA Astrophysics Data System (ADS)
Martinez, Gonzalo; Pachepsky, Yakov; Pan, Feng; Wagener, Thorsten; Nicholson, Thomas
2016-04-01
The accuracy-based model performance metrics not necessarily reflect the qualitative correspondence between simulated and measured streamflow time series. The objective of this work was to use the information theory-based metrics to see whether they can be used as complementary tool for hydrologic model evaluation and selection. We simulated 10-year streamflow time series in five watersheds located in Texas, North Carolina, Mississippi, and West Virginia. Eight model of different complexity were applied. The information-theory based metrics were obtained after representing the time series as strings of symbols where different symbols corresponded to different quantiles of the probability distribution of streamflow. The symbol alphabet was used. Three metrics were computed for those strings - mean information gain that measures the randomness of the signal, effective measure complexity that characterizes predictability and fluctuation complexity that characterizes the presence of a pattern in the signal. The observed streamflow time series has smaller information content and larger complexity metrics than the precipitation time series. Watersheds served as information filters and and streamflow time series were less random and more complex than the ones of precipitation. This is reflected the fact that the watershed acts as the information filter in the hydrologic conversion process from precipitation to streamflow. The Nash Sutcliffe efficiency metric increased as the complexity of models increased, but in many cases several model had this efficiency values not statistically significant from each other. In such cases, ranking models by the closeness of the information-theory based parameters in simulated and measured streamflow time series can provide an additional criterion for the evaluation of hydrologic model performance.
Asquith, William H.; Cleveland, Theodore G.; Roussel, Meghan C.
2011-01-01
Estimates of peak and time of peak streamflow for small watersheds (less than about 640 acres) in a suburban to urban, low-slope setting are needed for drainage design that is cost-effective and risk-mitigated. During 2007-10, the U.S. Geological Survey (USGS), in cooperation with the Harris County Flood Control District and the Texas Department of Transportation, developed a method to estimate peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area. To develop the method, 24 watersheds in the study area with drainage areas less than about 3.5 square miles (2,240 acres) and with concomitant rainfall and runoff data were selected. The method is based on conjunctive analysis of rainfall and runoff data in the context of the unit hydrograph method and the rational method. For the unit hydrograph analysis, a gamma distribution model of unit hydrograph shape (a gamma unit hydrograph) was chosen and parameters estimated through matching of modeled peak and time of peak streamflow to observed values on a storm-by-storm basis. Watershed mean or watershed-specific values of peak and time to peak ("time to peak" is a parameter of the gamma unit hydrograph and is distinct from "time of peak") of the gamma unit hydrograph were computed. Two regression equations to estimate peak and time to peak of the gamma unit hydrograph that are based on watershed characteristics of drainage area and basin-development factor (BDF) were developed. For the rational method analysis, a lag time (time-R), volumetric runoff coefficient, and runoff coefficient were computed on a storm-by-storm basis. Watershed-specific values of these three metrics were computed. A regression equation to estimate time-R based on drainage area and BDF was developed. Overall arithmetic means of volumetric runoff coefficient (0.41 dimensionless) and runoff coefficient (0.25 dimensionless) for the 24 watersheds were used to express the rational method in terms of excess rainfall (the excess rational method). Both the unit hydrograph method and excess rational method are shown to provide similar estimates of peak and time of peak streamflow. The results from the two methods can be combined by using arithmetic means. A nomograph is provided that shows the respective relations between the arithmetic-mean peak and time of peak streamflow to drainage areas ranging from 10 to 640 acres. The nomograph also shows the respective relations for selected BDF ranging from undeveloped to fully developed conditions. The nomograph represents the peak streamflow for 1 inch of excess rainfall based on drainage area and BDF; the peak streamflow for design storms from the nomograph can be multiplied by the excess rainfall to estimate peak streamflow. Time of peak streamflow is readily obtained from the nomograph. Therefore, given excess rainfall values derived from watershed-loss models, which are beyond the scope of this report, the nomograph represents a method for estimating peak and time of peak streamflow for applicable watersheds in the Houston metropolitan area. Lastly, analysis of the relative influence of BDF on peak streamflow is provided, and the results indicate a 0:04log10 cubic feet per second change of peak streamflow per positive unit of change in BDF. This relative change can be used to adjust peak streamflow from the method or other hydrologic methods for a given BDF to other BDF values; example computations are provided.
Historical perspective of statewide streamflows during the 2002 and 1977 droughts in Colorado
Kuhn, Gerhard
2005-01-01
Since 1890, Colorado has experienced a number of widespread drought periods; the most recent statewide drought began during 1999 and includes 2002, a year characterized by precipitation, snowpack accumulation, and streamflows that were much lower than normal. Because the drought of 2002 had a substantial effect on streamflows in Colorado, the U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board, began a study in 2004 to analyze statewide streamflows during 2002 and develop a historical perspective of those streamflows. The purpose of this report is to describe an analysis of streamflows recorded throughout Colorado during the drought of 2002, as well as other drought years such as 1977, and to provide some historical perspective of drought-diminished streamflows in Colorado. Because most streamflows in Colorado are derived from melting of mountain snowpacks during April through July, streamflows primarily were analyzed for the snowmelt (high-flow) period, but streamflows also were analyzed for the winter (low-flow) period. The snowmelt period is defined as April 1 through September 30 and the winter period is defined as October 1 through March 31. Historical daily average streamflows were analyzed on the basis of 7, 30, 90, and 180 consecutive-day periods (N-day) for 154 selected stations in Colorado. Methods used for analysis of the N-day snowmelt and winter streamflows include evaluation of trends in the historical streamflow records, computation of the rank of each annual N-day streamflow value for each station, analysis for years other than 2002 and 1977 with drought-diminished streamflows, and frequency analysis (on the basis of nonexceedance probability) of the 180-day streamflows. Ranking analyses for the N-day snowmelt streamflows indicated that streamflows during 2002 were ranked as the lowest or second lowest historical values at 114-123 stations, or about 74-80 percent of the stations; by comparison, the N-day snowmelt streamflows during 1977 were ranked as the lowest or second lowest historical values at 69-87 stations, or about 47-59 percent of the stations. Many of the stations in the mountainous headwaters where snowmelt streamflows were ranked lowest during 2002 were ranked second lowest during 1977. These results indicate that snowmelt streamflows during 2002 were considerably more diminished than those during 1977. The 180-day snowmelt streamflows were ranked among the five lowest historical values at about 90 percent of the stations during 2002 and were ranked among the five lowest historical values at about 77 percent of the stations during 1977. Other years during which the 180-day snowmelt streamflows were ranked among the five lowest values at a substantial percentage of stations include 1934, 1954, 1963, and 1981, but the percentages of stations with 180-day snowmelt streamflows ranked among the five lowest values were smaller during those years than during 2002 and 1977. Frequency analysis of snowmelt streamflows indicated that recurrence intervals for the 180-day snowmelt streamflows during 2002 were greater than 50 years for about 57 percent of the stations and were more than 100 years for about 14 percent of the stations. By comparison, recurrence intervals for the 180-day snowmelt streamflows during 1977 were greater than 50 years only for about 15 percent of the stations and were more than 100 years only for about 1 percent of the stations. Generally, snowmelt streamflows during 2002 were more diminished and have higher recurrence intervals than snowmelt streamflows during 1977. The N-day winter streamflows during 2002 and 1977 were not ranked among the five lowest historical values at about 86-103 stations, or about 58-70 percent of the stations, compared to about 10-27 percent of the stations for the N-day snowmelt streamflows. These results indicate that winter streamflows during the 2002 and 1977 droughts were diminished to a lesser extent than t
June and August median streamflows estimated for ungaged streams in southern Maine
Lombard, Pamela J.
2010-01-01
Methods for estimating June and August median streamflows were developed for ungaged, unregulated streams in southern Maine. The methods apply to streams with drainage areas ranging in size from 0.4 to 74 square miles, with percentage of basin underlain by a sand and gravel aquifer ranging from 0 to 84 percent, and with distance from the centroid of the basin to a Gulf of Maine line paralleling the coast ranging from 14 to 94 miles. Equations were developed with data from 4 long-term continuous-record streamgage stations and 27 partial-record streamgage stations. Estimates of median streamflows at the continuous-record and partial-record stations are presented. A mathematical technique for estimating standard low-flow statistics, such as June and August median streamflows, at partial-record streamgage stations was applied by relating base-flow measurements at these stations to concurrent daily streamflows at nearby long-term (at least 10 years of record) continuous-record streamgage stations (index stations). Weighted least-squares regression analysis (WLS) was used to relate estimates of June and August median streamflows at streamgage stations to basin characteristics at these same stations to develop equations that can be used to estimate June and August median streamflows on ungaged streams. WLS accounts for different periods of record at the gaging stations. Three basin characteristics-drainage area, percentage of basin underlain by a sand and gravel aquifer, and distance from the centroid of the basin to a Gulf of Maine line paralleling the coast-are used in the final regression equation to estimate June and August median streamflows for ungaged streams. The three-variable equation to estimate June median streamflow has an average standard error of prediction from -35 to 54 percent. The three-variable equation to estimate August median streamflow has an average standard error of prediction from -45 to 83 percent. Simpler one-variable equations that use only drainage area to estimate June and August median streamflows were developed for use when less accuracy is acceptable. These equations have average standard errors of prediction from -46 to 87 percent and from -57 to 133 percent, respectively.
HYSEP: A Computer Program for Streamflow Hydrograph Separation and Analysis
Sloto, Ronald A.; Crouse, Michele Y.
1996-01-01
HYSEP is a computer program that can be used to separate a streamflow hydrograph into base-flow and surface-runoff components. The base-flow component has traditionally been associated with ground-water discharge and the surface-runoff component with precipitation that enters the stream as overland runoff. HYSEP includes three methods of hydrograph separation that are referred to in the literature as the fixed interval, sliding-interval, and local-minimum methods. The program also describes the frequency and duration of measured streamflow and computed base flow and surface runoff. Daily mean stream discharge is used as input to the program in either an American Standard Code for Information Interchange (ASCII) or binary format. Output from the program includes table,s graphs, and data files. Graphical output may be plotted on the computer screen or output to a printer, plotter, or metafile.
NASA Astrophysics Data System (ADS)
García-Valdecasas Ojeda, Matilde; De Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Esteban-Parra, María Jesus
2016-04-01
Variable Infiltration Capacity (VIC) model is a large-scale, semi-distributed hydrologic model [1]. Its most important properties are related to the land surface, modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), as well as to the local water influx (i.e. water can only enter a grid cell via the atmosphere and the channel flow between grid cells is ignored). The portions of surface and subsurface water runoff that reach the local channel network, are assumed to stay in the channel, and cannot flow back into the soil. In a second step, routing of streamflow is performed separately from the land surface simulation, using a separate model, the Routing Model, described in [2]. The final goal of our research consists into set an optimal hydrological and climate model to study the evolution of the streamflow of Guadalquivir Basin with different future land use, land cover and climate scenarios. In this work we study the coupling between VIC model, Routing model and Weather Research and Forecasting (WRF) model in order to perform the evolution of the streamflow for the Guadalquivir Basin (Spain). For this end, a calibration of the most relevant VIC model parameters using real streamflow daily time series, obtained from CEDEX (Centro de Estudios y Experimentación de Obras Públicas, Spain) database [3] was performed. In the time period under study, i.e. the decades 1988-1997 (calibration step) and 1998-2007 (verification step), the VIC model has been coupled with observational climate data, obtained from SPAIN02 database [4]. Additionally, we carried out a sensitivity analysis of WRF model to different parameterizations using different cumulus, microphysics and surface/planetary boundary layer schemes for the period 1995-1996. WRF runs were carried over a domain encompassing the Iberian Peninsula and nested in the coarser EURO-CORDEX domain [5]. The optimal parameters set resulting from such analysis have been used to obtain a high-resolution 35 yr period (1980-2014) dataset, driven by Interim ECMWF Re-Analysis (ERA-Interim) data [6]. Finally, the real streamflow daily time series were compared with the ones obtained by the previously calibrated VIC with SPAIN02 dataset and with WRF dataset, using different groups of meteorological variables. This last analysis allows us to check the robustness of VIC and WRF coupling, and to find the most relevant meteorological inputs for Guadalquivir streamflow system. Key words: Regional Climate Models, VIC, WRF, calibration, meteorological variables Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER). [1] http://vic.readthedocs.org/en/master/ [2] Lohmann D, Raschke E, Nijssen B, Lettenmaier D P, 1998: Regional scale hydrology: I. Formulation of the VIC-2L model coupled to a routing model, Hydrolog. Sci. J., 43(1), 131-141. [3] www.cedex.es [4] http://www.meteo.unican.es/en/datasets/spain02 [5] EUROCORDEX: http://www.euro-cordex.net/ [6] Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Hólm E V, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally A P, Monge-Sanz B M, Morcrette J-J, Park B-K, Peubey C, de Rosnay P, Tavolato C, Thépaut J-N, Vitart F, 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. Roy. Meteor. Soc. 137:553-597.
Hydrological impact of high-density small dams in a humid catchment, Southeast China
NASA Astrophysics Data System (ADS)
Lu, W.; Lei, H.; Yang, D.
2017-12-01
The Jiulong River basin is a humid catchment with a drainage area of 14,741 km2; however, it has over 1000 hydropower stations within it. Such catchment with high-density small dams is scarce in China. Yet few is known about the impact of high-density small dams on streamflow changes. To what extent the large number of dams alters the hydrologic patterns is a fundamental scientific issue for water resources management, flood control, and aquatic ecological environment protection. Firstly, trend and change point analyses are applied to determine the characteristics of inter-annual streamflow. Based on the detected change point, the study period is divided into two study periods, the ``natural'' and ``disturbed'' periods. Then, a geomorphology-based hydrological model (GBHM) and the fixing-changing method are adopted to evaluate the relative contributions of climate variations and damming to the changes in streamflow at each temporal scale (i.e., from daily, monthly to annual). Based on the simulated natural streamflow, the impact of dam construction on hydrologic alteration and aquatic ecological environment will be evaluated. The hydrologic signatures that will be investigated include flood peak, seasonality of streamflow, and the inter-annual variability of streamflow. In particular, the impacts of damming on aquatic ecological environment will be investigated using eco-flow metrics and indicators of hydrologic alteration (IHA) which contains 33 individual streamflow statistics that are closely related to aquatic ecosystem. The results of this study expect to provide a reference for reservoir operation considering both ecological and economic benefits of such operations in the catchment with high-density dams.
Associations of stream health to altered flow and water temperature in the Sierra Nevada, California
Carlisle, Daren M.; S. Mark Nelson,; May, Jason
2016-01-01
Alteration of streamflow and thermal conditions may adversely affect lotic invertebrate communities, but few studies have assessed these phenomena using indicators that control for the potentially confounding influence of natural variability. We designed a study to assess how flow and thermal alteration influence stream health – as indicated by the condition of invertebrate communities. We studied thirty streams in the Sierra Nevada, California, that span a wide range of hydrologic modification due to storage reservoirs and hydroelectric diversions. Daily water temperature and streamflows were monitored, and basic chemistry and habitat conditions were characterized when invertebrate communities were sampled. Streamflow alteration, thermal alteration, and invertebrate condition were quantified by predicting site-specific natural expectations using statistical models developed using data from regional reference sites. Monthly flows were typically depleted (relative to natural expectations) during fall, winter, and spring. Most hydrologically altered sites experienced cooled thermal conditions in summer, with mean daily temperatures as much 12 °C below natural expectations. The most influential predictor of invertebrate community condition was the degree of alteration of March flows, which suggests that there are key interactions between hydrological and biological processes during this month in Sierra Nevada streams. Thermal alteration was also an important predictor – particularly at sites with the most severe hydrological alteration.
A Sequential Monte Carlo Approach for Streamflow Forecasting
NASA Astrophysics Data System (ADS)
Hsu, K.; Sorooshian, S.
2008-12-01
As alternatives to traditional physically-based models, Artificial Neural Network (ANN) models offer some advantages with respect to the flexibility of not requiring the precise quantitative mechanism of the process and the ability to train themselves from the data directly. In this study, an ANN model was used to generate one-day-ahead streamflow forecasts from the precipitation input over a catchment. Meanwhile, the ANN model parameters were trained using a Sequential Monte Carlo (SMC) approach, namely Regularized Particle Filter (RPF). The SMC approaches are known for their capabilities in tracking the states and parameters of a nonlinear dynamic process based on the Baye's rule and the proposed effective sampling and resampling strategies. In this study, five years of daily rainfall and streamflow measurement were used for model training. Variable sample sizes of RPF, from 200 to 2000, were tested. The results show that, after 1000 RPF samples, the simulation statistics, in terms of correlation coefficient, root mean square error, and bias, were stabilized. It is also shown that the forecasted daily flows fit the observations very well, with the correlation coefficient of higher than 0.95. The results of RPF simulations were also compared with those from the popular back-propagation ANN training approach. The pros and cons of using SMC approach and the traditional back-propagation approach will be discussed.
Kuhn, Gerhard; Nickless, R.C.
1994-01-01
Part of the storage space of Pueblo Reservoir consists of a 65,950 acre-foot joint-use pool (JUP) that can be used to provide additional conservation capacity from November 1 to April 14; however, the JUP must be evacuated by April 15 and used only for flood-control capacity until November 1. A study was completed to determine if the JUP possibly could be used for conservation storage for any number of days from April 15 through May 14 under certain hydrologic conditions. The methods of the study were: (1) Frequency analysis of recorded daily mean discharge data for streamflow-gaging stations upstream and downstream from Pueblo Reservoir, and (2) Implementation of the extended streamflow prediction (ESP) procedure for the Arkansas River basin upstream from the reservoir. The frequency analyses enabled estimation of daily discharges at selected exceedance probabilities (EP's), including the 0.01 EP that was used in design of the flood- storage capacity of Pueblo Reservoir. The ESP procedure enabled probabilistic forecasts of inflow volume to the reservoir for April 15 through May 14. Daily discharges derived from the frequency analyses were routed through Pueblo Reservoir to estimate evacuation dates of the JUP for different reservoir inflow volumes; the estimates indicated a relation between the inflow volume and the JUP evacuation date. To apply the study results, only a ESP forecast of the April 15-May 14 reservoir inflow volume is needed. Study results indicate the JUP possibly could be used as late as May 5 depending on the forecast inflow volume.
Carlisle, Daren M.; Wolock, David M.; Howard, Jeannette K.; Grantham, Theodore E.; Fesenmyer, Kurt; Wieczorek, Michael
2016-12-12
Because natural patterns of streamflow are a fundamental property of the health of streams, there is a critical need to quantify the degree to which human activities have modified natural streamflows. A requirement for assessing streamflow modification in a given stream is a reliable estimate of flows expected in the absence of human influences. Although there are many techniques to predict streamflows in specific river basins, there is a lack of approaches for making predictions of natural conditions across large regions and over many decades. In this study conducted by the U.S. Geological Survey, in cooperation with The Nature Conservancy and Trout Unlimited, the primary objective was to develop empirical models that predict natural (that is, unaffected by land use or water management) monthly streamflows from 1950 to 2012 for all stream segments in California. Models were developed using measured streamflow data from the existing network of streams where daily flow monitoring occurs, but where the drainage basins have minimal human influences. Widely available data on monthly weather conditions and the physical attributes of river basins were used as predictor variables. Performance of regional-scale models was comparable to that of published mechanistic models for specific river basins, indicating the models can be reliably used to estimate natural monthly flows in most California streams. A second objective was to develop a model that predicts the likelihood that streams experience modified hydrology. New models were developed to predict modified streamflows at 558 streamflow monitoring sites in California where human activities affect the hydrology, using basin-scale geospatial indicators of land use and water management. Performance of these models was less reliable than that for the natural-flow models, but results indicate the models could be used to provide a simple screening tool for identifying, across the State of California, which streams may be experiencing anthropogenic flow modification.
Statistical procedures for evaluating daily and monthly hydrologic model predictions
Coffey, M.E.; Workman, S.R.; Taraba, J.L.; Fogle, A.W.
2004-01-01
The overall study objective was to evaluate the applicability of different qualitative and quantitative methods for comparing daily and monthly SWAT computer model hydrologic streamflow predictions to observed data, and to recommend statistical methods for use in future model evaluations. Statistical methods were tested using daily streamflows and monthly equivalent runoff depths. The statistical techniques included linear regression, Nash-Sutcliffe efficiency, nonparametric tests, t-test, objective functions, autocorrelation, and cross-correlation. None of the methods specifically applied to the non-normal distribution and dependence between data points for the daily predicted and observed data. Of the tested methods, median objective functions, sign test, autocorrelation, and cross-correlation were most applicable for the daily data. The robust coefficient of determination (CD*) and robust modeling efficiency (EF*) objective functions were the preferred methods for daily model results due to the ease of comparing these values with a fixed ideal reference value of one. Predicted and observed monthly totals were more normally distributed, and there was less dependence between individual monthly totals than was observed for the corresponding predicted and observed daily values. More statistical methods were available for comparing SWAT model-predicted and observed monthly totals. The 1995 monthly SWAT model predictions and observed data had a regression Rr2 of 0.70, a Nash-Sutcliffe efficiency of 0.41, and the t-test failed to reject the equal data means hypothesis. The Nash-Sutcliffe coefficient and the R r2 coefficient were the preferred methods for monthly results due to the ability to compare these coefficients to a set ideal value of one.
Danz, Mari E.; Corsi, Steven R.; Graczyk, David J.; Bannerman, Roger T.
2010-01-01
Knowledge of the daily, monthly, and yearly distribution of contaminant loadings and streamflow can be critical for the successful implementation and evaluation of water-quality management practices. Loading data for solids (suspended sediment and total suspended solids) and total phosphorus and streamflow data for 23 watersheds were summarized for four ecoregions of Wisconsin: the Driftless Area Ecoregion, the Northern Lakes and Forests Ecoregion, the North Central Hardwoods Ecoregion, and the Southeastern Wisconsin Till Plains Ecoregion. The Northern Lakes and Forests and the North Central Hardwoods Ecoregions were combined into one region for analysis due to a lack of sufficient data in each region. Urban watersheds, all located in the Southeastern Wisconsin Till Plains, were analyzed separately from rural watersheds as the Rural Southeastern Wisconsin Till Plains region and the Urban Southeastern Wisconsin Till Plains region. Results provide information on the distribution of loadings and streamflow between base flow and stormflow, the timing of loadings and streamflow throughout the year, and information regarding the number of days in which the majority of the annual loading is transported. The average contribution to annual solids loading from stormflow periods for the Driftless Area Ecoregion was 84 percent, the Northern Lakes and Forests/North Central Hardwoods region was 71 percent, the Rural Southeastern Wisconsin Till Plains region was 70 percent, and the Urban Southeastern Wisconsin Till Plains region was 90 percent. The average contributions to annual total phosphorus loading from stormflow periods were 72, 49, 61, and 76 percent for each of the respective regions. The average contributions to annual streamflow from stormflow periods are 20, 23, 31, and 50 percent for each of the respective regions. In all regions, the most substantial loading contributions for solids were in the late winter (February through March), spring (April through May), and early summer (June through July), with fall (October through November) and early winter (December through January) contributing the smallest loadings. The Northern Lakes and Forests/North Central Hardwoods region had some substantial loading in September. There was a similar pattern for total phosphorus loading in all regions, with the pattern somewhat less pronounced in urban watersheds. As with the loading results, average monthly streamflow values were greatest in late winter, spring, and early summer, with the lowest values typically in fall and early winter. Loading contributions were greater from stormflow than from base flow in all instances, except total phosphorus in the Northern Lakes and Forests/North Central Hardwoods region, which had equal or greater base-flow contribution for several months. Base flow constituted a greater percentage of the total streamflow than stormflow in all rural watersheds for all regions. Only a few storms each year dominated the annual loading totals for solids and total phosphorus. When daily loading values were ranked for the year, all regions reached 50 percent of the annual solids loading in the 5 highest loading days and nearly 50 percent of the annual total phosphorus loading in the 14 highest loading days.
Breault, Robert F.; Smith, Kirk P.
2010-01-01
Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board (PWSB), Rhode Island's largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgage stations; 13 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance and water temperature. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2009 (October 1, 2008, to September 30, 2009). Water-quality samples also were collected at 37 sampling stations by the PWSB and at 14 monitoring stations by the USGS during WY 2009 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by PWSB are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2009. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed a mean streamflow of about 27 cubic feet per second (ft3/s) to the reservoir during WY 2009. For the same time period, annual mean1 streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.50 to 17 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,400,000 kilograms (kg) of sodium and 2,200,000 kg of chloride to the Scituate Reservoir during WY 2009; sodium and chloride yields for the tributaries ranged from 10,000 to 64,000 kilograms per square mile (kg/mi2) and from 15,000 to 110,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the PWSB, the median of the median chloride concentrations was 21.7 milligrams per liter (mg/L), median nitrite concentration was 0.001 mg/L as N, median nitrate concentration was 0.02 mg/L as N, median orthophosphate concentration was 0.09 mg/L as P, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 61 and 16 colony forming units per 100 milliliters (CFU/100 mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 190 kg/d (61 kg/d/mi2), 12 g/d (4.5 g/d/mi2), 93 g/d (32 g/d/mi2), 420 g/d (290 g/d/mi2), 6,200 million colony forming units per day (CFU?106/d) (2,600 CFU?106/d/mi2), and 1,100 CFU?106/d (340 CFU?106/d/mi2), respectively. 1The arithmetic mean of the individual daily mean discharges for the year noted or for the designated period.
NASA Astrophysics Data System (ADS)
Carey, Sean K.; Tetzlaff, Doerthe; Buttle, Jim; Laudon, Hjalmar; McDonnell, Jeff; McGuire, Kevin; Seibert, Jan; Soulsby, Chris; Shanley, Jamie
2013-10-01
The higher midlatitudes of the northern hemisphere are particularly sensitive to change due to the important role the 0°C isotherm plays in the phase of precipitation and intermediate storage as snow. An international intercatchment comparison program called North-Watch seeks to improve our understanding of the sensitivity of northern catchments to change by examining their hydrological and biogeochemical variability and response. Here eight North-Watch catchments located in Sweden (Krycklan), Scotland (Girnock and Strontian), the United States (Sleepers River, Hubbard Brook, and HJ Andrews), and Canada (Dorset and Wolf Creek) with 10 continuous years of daily precipitation and runoff data were selected to assess daily to seasonal coupling of precipitation (P) and runoff (Q) using wavelet coherency, and to explore the patterns and scales of variability in streamflow using color maps. Wavelet coherency revealed that P and Q were decoupled in catchments with cold winters, yet were strongly coupled during and immediately following the spring snowmelt freshet. In all catchments, coupling at shorter time scales occurred during wet periods when the catchment was responsive and storage deficits were small. At longer time scales, coupling reflected coherence between seasonal cycles, being enhanced at sites with enhanced seasonality in P. Color maps were applied as an alternative method to identify patterns and scales of flow variability. Seasonal versus transient flow variability was identified along with the persistence of that variability on influencing the flow regime. While exploratory in nature, this intercomparison exercise highlights the importance of climate and the 0°C isotherm on the functioning of northern catchments.
Assessing uncertainties in superficial water provision by different bootstrap-based techniques
NASA Astrophysics Data System (ADS)
Rodrigues, Dulce B. B.; Gupta, Hoshin V.; Mendiondo, Eduardo Mario
2014-05-01
An assessment of water security can incorporate several water-related concepts, characterizing the interactions between societal needs, ecosystem functioning, and hydro-climatic conditions. The superficial freshwater provision level depends on the methods chosen for 'Environmental Flow Requirement' estimations, which integrate the sources of uncertainty in the understanding of how water-related threats to aquatic ecosystem security arise. Here, we develop an uncertainty assessment of superficial freshwater provision based on different bootstrap techniques (non-parametric resampling with replacement). To illustrate this approach, we use an agricultural basin (291 km2) within the Cantareira water supply system in Brazil monitored by one daily streamflow gage (24-year period). The original streamflow time series has been randomly resampled for different times or sample sizes (N = 500; ...; 1000), then applied to the conventional bootstrap approach and variations of this method, such as: 'nearest neighbor bootstrap'; and 'moving blocks bootstrap'. We have analyzed the impact of the sampling uncertainty on five Environmental Flow Requirement methods, based on: flow duration curves or probability of exceedance (Q90%, Q75% and Q50%); 7-day 10-year low-flow statistic (Q7,10); and presumptive standard (80% of the natural monthly mean ?ow). The bootstrap technique has been also used to compare those 'Environmental Flow Requirement' (EFR) methods among themselves, considering the difference between the bootstrap estimates and the "true" EFR characteristic, which has been computed averaging the EFR values of the five methods and using the entire streamflow record at monitoring station. This study evaluates the bootstrapping strategies, the representativeness of streamflow series for EFR estimates and their confidence intervals, in addition to overview of the performance differences between the EFR methods. The uncertainties arisen during EFR methods assessment will be propagated through water security indicators referring to water scarcity and vulnerability, seeking to provide meaningful support to end-users and water managers facing the incorporation of uncertainties in the decision making process.
NASA Astrophysics Data System (ADS)
Abdo Yassin, Fuad; Wheater, Howard; Razavi, Saman; Sapriza, Gonzalo; Davison, Bruce; Pietroniro, Alain
2015-04-01
The credible identification of vertical and horizontal hydrological components and their associated parameters is very challenging (if not impossible) by only constraining the model to streamflow data, especially in regions where the vertical processes significantly dominate the horizontal processes. The prairie areas of the Saskatchewan River basin, a major water system in Canada, demonstrate such behavior, where the hydrologic connectivity and vertical fluxes are mainly controlled by the amount of surface and sub-surface water storages. In this study, we develop a framework for distributed hydrologic model identification and calibration that jointly constrains the model response (i.e., streamflows) as well as a set of model state variables (i.e., water storages) to observations. This framework is set up in the form of multi-objective optimization, where multiple performance criteria are defined and used to simultaneously evaluate the fidelity of the model to streamflow observations and observed (estimated) changes of water storage in the gridded landscape over daily and monthly time scales. The time series of estimated changes in total water storage (including soil, canopy, snow and pond storages) used in this study were derived from an experimental study enhanced by the information obtained from the GRACE satellite. We test this framework on the calibration of a Land Surface Scheme-Hydrology model, called MESH (Modélisation Environmentale Communautaire - Surface and Hydrology), for the Saskatchewan River basin. Pareto Archived Dynamically Dimensioned Search (PA-DDS) is used as the multi-objective optimization engine. The significance of using the developed framework is demonstrated in comparison with the results obtained through a conventional calibration approach to streamflow observations. The approach of incorporating water storage data into the model identification process can more potentially constrain the posterior parameter space, more comprehensively evaluate the model fidelity, and yield more credible predictions.
Haro, Alexander J.; Mulligan, Kevin; Suro, Thomas P.; Noreika, John; McHugh, Amy
2017-10-16
Recent efforts to advance river connectivity for the Millstone River watershed in New Jersey have led to the evaluation of a low-flow gauging weir that spans the full width of the river. The methods and results of a desktop modelling exercise were used to evaluate the potential ability of three anadromous fish species (Alosa sapidissima [American shad], Alosa pseudoharengus [alewife], and Alosa aestivalis [blueback herring]) to pass upstream over the U.S. Geological Survey Blackwells Mills streamgage (01402000) and weir on the Millstone River, New Jersey, at various streamflows, and to estimate the probability that the weir will be passable during the spring migratory season. Based on data from daily fishway counts downstream from the Blackwells Mills streamgage and weir between 1996 and 2014, the general migratory period was defined as April 14 to May 28. Recorded water levels and flow data were used to theoretically estimate water depths and velocities over the weir, as well as flow exceedances occurring during the migratory period.Results indicate that the weir is a potential depth barrier to fish passage when streamflows are below 200 cubic feet per second using a 1-body-depth criterion for American shad (the largest fish among the target species). Streamflows in that range occur on average 35 percent of the time during the migratory period. An increase of the depth criterion to 2 body depths causes the weir to become a possible barrier to passage when flows are below 400 cubic feet per second. Streamflows in that range occur on average 73 percent of the time during the migration season. Average cross-sectional velocities at several points along the weir do not seem to be limiting to the fish migration, but maximum theoretical velocities estimated without friction loss over the face of the weir could be potentially limiting.
A time-corrector device for adjusting streamflow records
Raymond W. Lavigne
1960-01-01
The first job in compiling streamflow data from streamflow charts is to mark storm rises and storm peaks, make corrections as necessary for time and stage height, and account for irregularities on the chart. Errors in the time scale can result from faulty clock operation, irregularities in chart take-up by the drum, or expansion of the paper. This note suggests a...
Water Resources Data, Puerto Rico and the U.S. Virgin Islands, Water Year 2002
Diaz, Pedro L.; Aquino, Zaida; Figueroa-Alamo, Carlos; Garcia, Rene; Sanchez, Ana V.
2004-01-01
The Water Resources Division of the U.S. Geological Survey, in cooperation with local and Federal agencies obtains a large amount of data pertaining to the water resources of the Commonwealth of Puerto Rico and the Territory of the U.S. Virgin Islands each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the area. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data for Puerto Rico and the U.S. Virgin Islands, 2002.' This report includes records on both surface and ground water. Specifically, it contains: (1) discharge records for 95 streamflow gaging stations, daily sediment records for 28 streamflow stations, 27 partial-record or miscellaneous streamflow stations, stage records for 17 reservoirs, and (2) water-quality records for 17 streamflow-gaging stations, and for 42 ungaged stream sites, 11 lake sites, 2 lagoons, and 1 bay, and (3) water-level records for 102 observation wells.
Water Resources Data, Puerto Rico and the U.S. Virgin Islands, Water Year 2001
Diaz, Pedro L.; Aquino, Zaida; Figueroa-Alamo, Carlos; Garcia, Rene; Sanchez, Ana V.
2002-01-01
The Water Resources Division of the U.S. Geological Survey, in cooperation with local and Federal agencies obtains a large amount of data pertaining to the water resources of the Commonwealth of Puerto Rico and the Territory of the U.S. Virgin Islands each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the area. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data for Puerto Rico and the U.S. Virgin Islands, 2001.' This report includes records on both surface and ground water. Specifically, it contains: (1) discharge records for 95 streamflow gaging stations, daily sediment records for 23 streamflow stations, 20 partial-record or miscellaneous streamflow stations, stage records for 18 reservoirs, and (2) water-quality records for 17 streamflow-gaging stations, and for 42 ungaged stream sites, 11 lake sites, 2 lagoons, and 1 bay, and (3) water-level records for 103 observation wells.
Water Resources Data, Puerto Rico and the U.S. Virgin Islands, Water Year 2000
Diaz, Pedro L.; Aquino, Zaida; Figueroa-Alamo, Carlos; Vachier, Ricardo J.; Sanchez, Ana V.
2001-01-01
The Water Resources Division of the U.S. Geological Survey, in cooperation with local and federal agencies obtains a large amount of data pertaining to the water resources of the Commonwealth of Puerto Rico and the Territory of the U.S. Virgin Islands each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the area. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data for Puerto Rico and the U.S. Virgin Islands, 2000.' This report includes records on both surface and ground water. Specifically, it contains: (1) discharge records for 85 streamflow gaging stations, daily sediment records for 26 streamflow stations, 21 partial-record or miscellaneous streamflow stations, stage records for 18 reservoirs, and (2) water-quality records for 16 streamflow-gaging stations, and for 42 ungaged stream sites, 11 lake sites, 2 lagoons, and 1 bay, and (3) water-level records for 108 observation wells.
Water resources data, Puerto Rico and the U.S. Virgin Islands, Water Year 1998
Diaz, Pedro L.; Aquino, Zaida; Figueroa-Alamo, Carlos; Vachier, Ricardo J.; Sanchez, Ana V.
1999-01-01
The Water Resources Division of the U.S. Geological Survey, in cooperation with local and federal agencies obtains a large amount of data pertaining to the water resources of the Commonwealth of Puerto Rico and the Territory of the U.S. Virgin Islands each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the area. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data for Puerto Rico and the U.S. Virgin Islands, 1998.' This report includes records on both surface and ground water. Specifically, it contains: (1) discharge records for 76 streamflow gaging stations, daily sediment records for 27 streamflow stations, 99 partial-record or miscellaneous streamflow stations, stage records for 17 reservoirs, and (2) water-quality records for 16 streamflow-gaging stations, and for 42 ungaged stream sites, 11 lake sites, 2 lagoons, and 1 bay, and (3) water-level records for 97 observation wells.
Using 3D dynamic cartography and hydrological modelling for linear streamflow mapping
NASA Astrophysics Data System (ADS)
Drogue, G.; Pfister, L.; Leviandier, T.; Humbert, J.; Hoffmann, L.; El Idrissi, A.; Iffly, J.-F.
2002-10-01
This paper presents a regionalization methodology and an original representation of the downstream variation of daily streamflow using a conceptual rainfall-runoff model (HRM) and the 3D visualization tools of the GIS ArcView. The regionalization of the parameters of the HRM model was obtained by fitting simultaneously the runoff series from five sub-basins of the Alzette river basin (Grand-Duchy of Luxembourg) according to the permeability of geological formations. After validating the transposability of the regional parameter values on five test basins, streamflow series were simulated with the model at ungauged sites in one medium size geologically contrasted test basin and interpolated assuming a linear increase of streamflow between modelling points. 3D spatio-temporal cartography of mean annual and high raw and specific discharges are illustrated. During a severe flooding, the propagation of the flood waves in the different parts of the stream network shows an important contribution of sub-basins lying on impervious geological formations (direct runoff) compared with those including permeable geological formations which have a more contrasted hydrological response. The effect of spatial variability of rainfall is clearly perceptible.
Model simulation of the Manasquan water-supply system in Monmouth County, New Jersey
Chang, Ming; Tasker, Gary D.; Nieswand, Steven
2001-01-01
Model simulation of the Manasquan Water Supply System in Monmouth County, New Jersey, was completed using historic hydrologic data to evaluate the effects of operational and withdrawal alternatives on the Manasquan reservoir and pumping system. Changes in the system operations can be simulated with the model using precipitation forecasts. The Manasquan Reservoir system model operates by using daily streamflow values, which were reconstructed from historical U.S. Geological Survey streamflow-gaging station records. The model is able to run in two modes--General Risk analysis Model (GRAM) and Position Analysis Model (POSA). The GRAM simulation procedure uses reconstructed historical streamflow records to provide probability estimates of certain events, such as reservoir storage levels declining below a specific level, when given an assumed set of operating rules and withdrawal rates. POSA can be used to forecast the likelihood of specified outcomes, such as streamflows falling below statutory passing flows, associated with a specific working plan for the water-supply system over a period of months. The user can manipulate the model and generate graphs and tables of streamflows and storage, for example. This model can be used as a management tool to facilitate the development of drought warning and drought emergency rule curves and safe yield values for the water-supply system.
Regional flow duration curves: Geostatistical techniques versus multivariate regression
Pugliese, Alessio; Farmer, William H.; Castellarin, Attilio; Archfield, Stacey A.; Vogel, Richard M.
2016-01-01
A period-of-record flow duration curve (FDC) represents the relationship between the magnitude and frequency of daily streamflows. Prediction of FDCs is of great importance for locations characterized by sparse or missing streamflow observations. We present a detailed comparison of two methods which are capable of predicting an FDC at ungauged basins: (1) an adaptation of the geostatistical method, Top-kriging, employing a linear weighted average of dimensionless empirical FDCs, standardised with a reference streamflow value; and (2) regional multiple linear regression of streamflow quantiles, perhaps the most common method for the prediction of FDCs at ungauged sites. In particular, Top-kriging relies on a metric for expressing the similarity between catchments computed as the negative deviation of the FDC from a reference streamflow value, which we termed total negative deviation (TND). Comparisons of these two methods are made in 182 largely unregulated river catchments in the southeastern U.S. using a three-fold cross-validation algorithm. Our results reveal that the two methods perform similarly throughout flow-regimes, with average Nash-Sutcliffe Efficiencies 0.566 and 0.662, (0.883 and 0.829 on log-transformed quantiles) for the geostatistical and the linear regression models, respectively. The differences between the reproduction of FDC's occurred mostly for low flows with exceedance probability (i.e. duration) above 0.98.
NASA Astrophysics Data System (ADS)
Pan, Feng; Pachepsky, Yakov A.; Guber, Andrey K.; McPherson, Brian J.; Hill, Robert L.
2012-01-01
SummaryUnderstanding streamflow patterns in space and time is important for improving flood and drought forecasting, water resources management, and predictions of ecological changes. Objectives of this work include (a) to characterize the spatial and temporal patterns of streamflow using information theory-based measures at two thoroughly-monitored agricultural watersheds located in different hydroclimatic zones with similar land use, and (b) to elucidate and quantify temporal and spatial scale effects on those measures. We selected two USDA experimental watersheds to serve as case study examples, including the Little River experimental watershed (LREW) in Tifton, Georgia and the Sleepers River experimental watershed (SREW) in North Danville, Vermont. Both watersheds possess several nested sub-watersheds and more than 30 years of continuous data records of precipitation and streamflow. Information content measures (metric entropy and mean information gain) and complexity measures (effective measure complexity and fluctuation complexity) were computed based on the binary encoding of 5-year streamflow and precipitation time series data. We quantified patterns of streamflow using probabilities of joint or sequential appearances of the binary symbol sequences. Results of our analysis illustrate that information content measures of streamflow time series are much smaller than those for precipitation data, and the streamflow data also exhibit higher complexity, suggesting that the watersheds effectively act as filters of the precipitation information that leads to the observed additional complexity in streamflow measures. Correlation coefficients between the information-theory-based measures and time intervals are close to 0.9, demonstrating the significance of temporal scale effects on streamflow patterns. Moderate spatial scale effects on streamflow patterns are observed with absolute values of correlation coefficients between the measures and sub-watershed area varying from 0.2 to 0.6 in the two watersheds. We conclude that temporal effects must be evaluated and accounted for when the information theory-based methods are used for performance evaluation and comparison of hydrological models.
Low Streamflow Forcasting using Minimum Relative Entropy
NASA Astrophysics Data System (ADS)
Cui, H.; Singh, V. P.
2013-12-01
Minimum relative entropy spectral analysis is derived in this study, and applied to forecast streamflow time series. Proposed method extends the autocorrelation in the manner that the relative entropy of underlying process is minimized so that time series data can be forecasted. Different prior estimation, such as uniform, exponential and Gaussian assumption, is taken to estimate the spectral density depending on the autocorrelation structure. Seasonal and nonseasonal low streamflow series obtained from Colorado River (Texas) under draught condition is successfully forecasted using proposed method. Minimum relative entropy determines spectral of low streamflow series with higher resolution than conventional method. Forecasted streamflow is compared to the prediction using Burg's maximum entropy spectral analysis (MESA) and Configurational entropy. The advantage and disadvantage of each method in forecasting low streamflow is discussed.
NASA Astrophysics Data System (ADS)
Safeeq, M.; Grant, G. E.; Lewis, S. L.; Kramer, M. G.; Staab, B.
2014-09-01
Summer streamflows in the Pacific Northwest are largely derived from melting snow and groundwater discharge. As the climate warms, diminishing snowpack and earlier snowmelt will cause reductions in summer streamflow. Most regional-scale assessments of climate change impacts on streamflow use downscaled temperature and precipitation projections from general circulation models (GCMs) coupled with large-scale hydrologic models. Here we develop and apply an analytical hydrogeologic framework for characterizing summer streamflow sensitivity to a change in the timing and magnitude of recharge in a spatially explicit fashion. In particular, we incorporate the role of deep groundwater, which large-scale hydrologic models generally fail to capture, into streamflow sensitivity assessments. We validate our analytical streamflow sensitivities against two empirical measures of sensitivity derived using historical observations of temperature, precipitation, and streamflow from 217 watersheds. In general, empirically and analytically derived streamflow sensitivity values correspond. Although the selected watersheds cover a range of hydrologic regimes (e.g., rain-dominated, mixture of rain and snow, and snow-dominated), sensitivity validation was primarily driven by the snow-dominated watersheds, which are subjected to a wider range of change in recharge timing and magnitude as a result of increased temperature. Overall, two patterns emerge from this analysis: first, areas with high streamflow sensitivity also have higher summer streamflows as compared to low-sensitivity areas. Second, the level of sensitivity and spatial extent of highly sensitive areas diminishes over time as the summer progresses. Results of this analysis point to a robust, practical, and scalable approach that can help assess risk at the landscape scale, complement the downscaling approach, be applied to any climate scenario of interest, and provide a framework to assist land and water managers in adapting to an uncertain and potentially challenging future.
Conrads, Paul; Erbland, John W.
2009-01-01
A three-dimensional model of Bass and Cinder Creeks on Kiawah Island, South Carolina, was developed to evaluate methodologies for determining fecal coliform total maximum daily loads for shellfish waters. To calibrate the model, two index-velocity sites on the creeks were instrumented with continuous acoustic velocity meters and water-level sensors to compute a 21-day continuous record of tidal streamflows. In addition to monitoring tidal cycles, streamflow measurements were made at the index-velocity sites, and tidal-cycle streamflow measurements were made at the mouth of Bass Creek and on the Stono River to characterize the streamflow dynamics near the ocean boundary of the three-dimensional model at the beginning, September 6, 2007, and end, September 26, 2007, of the index-velocity meter deployment. The maximum floodtide and ebbtide measured on the Stono River by the mouth of Bass Creek for the two measurements were -155,000 and 170,000 cubic feet per second (ft3/s). At the mouth of Bass Creek, the maximum floodtide and ebbtide measurements during the 2 measurement days were +/-10,200 ft3/s. Tidal streamflows for the 21-day deployment on Bass Creek ranged from -2,510 ft3/s for an incoming tide to 4,360 ft3/s for an outgoing tide. On Cinder Creek, the incoming and outgoing tide varied from -2,180 to 2,400 ft3/s during the same period.
An experimental system for flood risk forecasting and monitoring at global scale
NASA Astrophysics Data System (ADS)
Dottori, Francesco; Alfieri, Lorenzo; Kalas, Milan; Lorini, Valerio; Salamon, Peter
2017-04-01
Global flood forecasting and monitoring systems are nowadays a reality and are being applied by a wide range of users and practitioners in disaster risk management. Furthermore, there is an increasing demand from users to integrate flood early warning systems with risk based forecasting, combining streamflow estimations with expected inundated areas and flood impacts. Finally, emerging technologies such as crowdsourcing and social media monitoring can play a crucial role in flood disaster management and preparedness. Here, we present some recent advances of an experimental procedure for near-real time flood mapping and impact assessment. The procedure translates in near real-time the daily streamflow forecasts issued by the Global Flood Awareness System (GloFAS) into event-based flood hazard maps, which are then combined with exposure and vulnerability information at global scale to derive risk forecast. Impacts of the forecasted flood events are evaluated in terms of flood prone areas, potential economic damage, and affected population, infrastructures and cities. To increase the reliability of our forecasts we propose the integration of model-based estimations with an innovative methodology for social media monitoring, which allows for real-time verification and correction of impact forecasts. Finally, we present the results of preliminary tests which show the potential of the proposed procedure in supporting emergency response and management.
Kuhn, Gerhard; Williams, Cory A.
2004-01-01
In 2003, the U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board, Upper Colorado River Endangered Fish Recovery Program, Colorado River Water Conservation District, Colorado Division of Water Resources, and Bureau of Reclamation, initiated a study to characterize streamflow losses along a reach of the Gunnison River from the town of Whitewater downstream to the Redlands Canal diversion dam. This describes the methods and results of the study that include: (1) a detailed mass-balance analysis of historical discharge records that were available for the three streamflow-gaging stations along the study reach; and (2) two sets of discharge measurements that were made at the three stations and at four additional locations. Data for these existing streamflow-gaging stations were compiled and analyzed: (1) Gunnison River near Grand Junction (Whitewater station); (2) Gunnison River below Redlands Canal diversion dam (below-Redlands-dam station); and (3) Redlands Canal near Grand Junction (Redlands-Canal station). Data for water years 1995-2003 were used for the mass-balance analysis. Four intermediate sites (M1, M2, M3, and M4) were selected for discharge measurements in addition to the existing stations. The study reach is the approximate 12-mile reach of the Gunnison River from the Whitewater station downstream to the Redlands Canal diversion dam, which is about 3 miles upstream from the confluence with the Colorado River. For the mass-balance analysis, differences between the sum of the annual cumulative daily mean discharge at the two downstream stations and the annual cumulative daily mean discharges at the upstream station ranged from about -8,700 to -69,800 acre-feet (about -.8 to -1.1 percent), indicating that the downstream discharges generally were less than the upstream discharges. Moving 3-day daily mean discharge averages also were computed for each of the three stations to smooth out some of the abrupt differences between the downstream and upstream daily mean discharges. During water years 1995-2002, differences between the downstream and upstream moving 3-day daily mean discharges ranged from about -200 to +100 cubic feet per second (ft3/s) during one-half of each year, but the differences had absolute values as large as about 500 to 1,000 ft3/s during the other one-half of the year. The differences as a percentage of the upstream discharge ranged from 0 to -10 percent within the interquartile range and were as small or large as about -60 to +50. Two sets of discharge measurements were obtained during water year 2003. For measurement set 1 (February 5-6), discharge was measured 5-8 times over a 24-hour period at sites M1-M4, where measured discharges ranged from 527 to 608 ft3/s. Discharge was measured once each day at the Whitewater and below-Redlands-dam stations to verify discharge rating shifts; the Redlands Canal was not in operation at this time, so measurements were not needed at the Redlands-Canal station. Recorded 15-minute (unit) discharges ranged from about 575 to 615 ft3/s at the Whitewater station and from about 560 to 600 ft3/s at the below-Redlands-dam station during the February 5-6 period. Because of the inherent error in discharge measurements (5 percent for measurements rated good), and because the mean discharge at the below-Redlands-dam station, about 580 ft3/s, was only about 2.5 percent smaller than the mean discharge at the Whitewater station, about 595 ft3/s, it is concluded that there was no measurable streamflow loss along the study reach during measurement set 1. For measurement set 2 (May 14-15), discharge in the Gunnison River was about 2,000 ft3/s and increasing because of high-elevation snowmelt. Five discharge measurements were made at site M2 and discharge ranged from 1,668 to 2,117 ft3/s. Measured discharges at the gaging stations were 2,730 ft3/s at the Whitewater station, 1,268 ft3/s at the below-Redlands-dam station, and 819 ft3/s at the
Effect of Using Extreme Years in Hydrologic Model Calibration Performance
NASA Astrophysics Data System (ADS)
Goktas, R. K.; Tezel, U.; Kargi, P. G.; Ayvaz, T.; Tezyapar, I.; Mesta, B.; Kentel, E.
2017-12-01
Hydrological models are useful in predicting and developing management strategies for controlling the system behaviour. Specifically they can be used for evaluating streamflow at ungaged catchments, effect of climate change, best management practices on water resources, or identification of pollution sources in a watershed. This study is a part of a TUBITAK project named "Development of a geographical information system based decision-making tool for water quality management of Ergene Watershed using pollutant fingerprints". Within the scope of this project, first water resources in Ergene Watershed is studied. Streamgages found in the basin are identified and daily streamflow measurements are obtained from State Hydraulic Works of Turkey. Streamflow data is analysed using box-whisker plots, hydrographs and flow-duration curves focusing on identification of extreme periods, dry or wet. Then a hydrological model is developed for Ergene Watershed using HEC-HMS in the Watershed Modeling System (WMS) environment. The model is calibrated for various time periods including dry and wet ones and the performance of calibration is evaluated using Nash-Sutcliffe Efficiency (NSE), correlation coefficient, percent bias (PBIAS) and root mean square error. It is observed that calibration period affects the model performance, and the main purpose of the development of the hydrological model should guide calibration period selection. Acknowledgement: This study is funded by The Scientific and Technological Research Council of Turkey (TUBITAK) under Project Number 115Y064.
Breault, Robert F.; Campbell, Jean P.
2010-01-01
Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board, Rhode Island's largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgage stations; 10 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate instantaneous (15-minute) loads of sodium and chloride during water year (WY) 2006 (October 1, 2005, to September 30, 2006). Water-quality samples were also collected at 37 sampling stations in the Scituate Reservoir drainage area by the Providence Water Supply Board during WY 2006 as part of a long-term sampling program. Water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2006. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed about 42 cubic feet per second (ft3/s) to the reservoir during WY 2006. For the same time period, annual mean streamflows1 measured (or estimated) for the other monitoring stations in this study ranged from about 0.60 to 26 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,600,000 kilograms (kg) of sodium and 2,500,000 kg of chloride to the Scituate Reservoir during WY 2006; sodium and chloride yields for the tributaries ranged from 15,000 to 100,000 kilograms per square mile (kg/mi2) and from 22,000 to 180,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 24.6 milligrams per liter (mg/L), median nitrite concentration was 0.001 mg/L as N, median nitrate concentration was 0.02 mg/L as N, median orthophosphate concentration was 0.07 mg/L as P, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 43 and 23 colony forming units per 100 milliliters (CFU/100 mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 230 kg/d (81 kg/d/mi2), 17 g/d (4.4 g/d/mi2), 130 g/d (50 g/d/mi2), 470 g/d (210 g/d/mi2), and 2,100 million colony forming units per day (CFU?106/d) (1,300 CFU?106/d/mi2) and 670 CFU?106/d (420 CFU?106/d/mi2), respectively. 1The arithmetic mean of the individual daily mean discharges for the year noted or for the designated period.
Breault, Robert F.; Campbell, Jean P.
2010-01-01
Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board, Rhode Island’s largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgage stations; 10 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate instantaneous (15-minute) loads of sodium and chloride during water year (WY) 2005 (October 1, 2004, to September 30, 2005). Water-quality samples were also collected at 37 sampling stations in the Scituate Reservoir drainage area by the Providence Water Supply Board during WY 2005 as part of a long-term sampling program. Water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2005. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed about 30 cubic feet per second (ft3/s) to the reservoir during WY 2005. For the same time period, annual mean streamflows1 measured (or estimated) for the other monitoring stations in this study ranged from about 0.42 to 19 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,300,000 kilograms (kg) of sodium and 2,000,000 kg of chloride to the Scituate Reservoir during WY 2005; sodium and chloride yields for the tributaries ranged from 13,000 to 77,000 kilograms per square mile (kg/mi2) and from 19,000 to 130,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 25.3 milligrams per liter (mg/L), median nitrite concentration was 0.002 mg/L as N, median nitrate concentration was 0.02 mg/L as N, median orthophosphate concentration was 0.07 mg/L as P, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 23 and 15 colony forming units per 100 milliliters (CFU/100 mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 230 kg/d (93 kg/d/mi2), 16 g/d (6.1 g/d/mi2), 150 g/d (71 g/d/mi2), 530 g/d (250 g/d/mi2), and 1,500 million colony forming units per day (CFU×106/d) (630 CFU×106/d/mi2) and 420 CFU×106/d (290 CFU×106/d/mi2), respectively. 1The arithmetic mean of the individual daily mean discharges for the year noted or for the designated period.
NASA Astrophysics Data System (ADS)
Biederman, Joel A.; Somor, Andrew J.; Harpold, Adrian A.; Gutmann, Ethan D.; Breshears, David D.; Troch, Peter A.; Gochis, David J.; Scott, Russell L.; Meddens, Arjan J. H.; Brooks, Paul D.
2015-12-01
Recent bark beetle epidemics have caused regional-scale tree mortality in many snowmelt-dominated headwater catchments of western North America. Initial expectations of increased streamflow have not been supported by observations, and the basin-scale response of annual streamflow is largely unknown. Here we quantified annual streamflow responses during the decade following tree die-off in eight infested catchments in the Colorado River headwaters and one nearby control catchment. We employed three alternative empirical methods: (i) double-mass comparison between impacted and control catchments, (ii) runoff ratio comparison before and after die-off, and (iii) time-trend analysis using climate-driven linear models. In contrast to streamflow increases predicted by historical paired catchment studies and recent modeling, we did not detect streamflow changes in most basins following die-off, while one basin consistently showed decreased streamflow. The three analysis methods produced generally consistent results, with time-trend analysis showing precipitation was the strongest predictor of streamflow variability (R2 = 74-96%). Time-trend analysis revealed post-die-off streamflow decreased in three catchments by 11-29%, with no change in the other five catchments. Although counter to initial expectations, these results are consistent with increased transpiration by surviving vegetation and the growing body of literature documenting increased snow sublimation and evaporation from the subcanopy following die-off in water-limited, snow-dominated forests. The observations presented here challenge the widespread expectation that streamflow will increase following beetle-induced forest die-off and highlight the need to better understand the processes driving hydrologic response to forest disturbance.
Gungle, Bruce
2006-01-01
Frequency, timing, and duration of streamflow were monitored in 20 ephemeral-stream channels across the Sierra Vista Subwatershed of the Upper San Pedro Basin, southeastern Arizona, during an 18-month period. One channel (Walnut Gulch) had Agricultural Research Service streamflow-gaging stations in place. The sediments of the remaining 19 ephemeral-stream channels were instrumented with multiple temperature loggers along the channel lengths. A thermograph-interpretation technique was developed in order to determine frequency, timing, and duration of streamflow in these channels. Streamflow onset was characterized by exceedance of a critical minimum drop in temperature within the channel sediments during any 15-minute interval, whereas streamflow cessation was identified by the local temperature minimum that immediately followed the critical temperature drop. All data for the 18-month period from December 1, 2000, to May 31, 2002, were analyzed in terms of monsoon (June 1 to September 19) and nonmonsoon (September 20 to May 31) periods. Nonmonsoon precipitation during the 2000-2002 study period (excludes October and November 2000) was 82 percent and 39 percent of the 30-year average, respectively, whereas monsoon precipitation during 2001 was 99 percent of the 30-year average. Ephemeral streamflow was detected at least once during the monitoring period at 87 percent of the monitoring sites (45 of the 52 sites that returned useful data; includes 4 streamflow-gaging stations). The summer monsoon period accounted for 82 percent of all streamflow events by number and 71 percent of all events by total streamflow duration. Nonmonsoon streamflow events peaked in number, total streamflow duration, and mean streamflow duration midway between the Huachuca Mountains and the San Pedro River on the west side of the subwatershed. These three streamflow parameters dropped off sharply about 10 kilometers from the mountain front. The number and total duration of nonmonsoon streamflows on the east side of the subwatershed trended downward with increased distance from the mountain fronts. Monsoon streamflow events were more evenly distributed across the subwatershed than nonmonsoon events, and the number and duration of streamflows generally trended upward with distance from the mountain fronts. Additional years of data are needed to determine whether these patterns are consistent year to year, or were due to randomness in the spatial distribution of precipitation. Streamflows in three ephemeral-stream channels were analyzed in detail. More than two-thirds of the streamflow events detected in each of these channels occurred at no more than one monitoring site along the channel length. In only one of the three channels-Garden Canyon-was a streamflow event detected at all logger sites along its length. Five temperature loggers provided data from urbanized areas, and these loggers detected streamflow more than 50 percent more often and of a duration nearly three times greater than did temperature loggers across the rural parts of the subwatershed. Because historical records do not indicate that more precipitation occurs in the urbanized area than in the rural areas, the increased frequency of flow detection in the urban area is attributed to an increase in runoff from the impervious surfaces throughout the urbanized area.
NASA Astrophysics Data System (ADS)
Smitha, P. S.; Narasimhan, B.; Sudheer, K. P.; Annamalai, H.
2018-01-01
Regional climate models (RCMs) are used to downscale the coarse resolution General Circulation Model (GCM) outputs to a finer resolution for hydrological impact studies. However, RCM outputs often deviate from the observed climatological data, and therefore need bias correction before they are used for hydrological simulations. While there are a number of methods for bias correction, most of them use monthly statistics to derive correction factors, which may cause errors in the rainfall magnitude when applied on a daily scale. This study proposes a sliding window based daily correction factor derivations that help build reliable daily rainfall data from climate models. The procedure is applied to five existing bias correction methods, and is tested on six watersheds in different climatic zones of India for assessing the effectiveness of the corrected rainfall and the consequent hydrological simulations. The bias correction was performed on rainfall data downscaled using Conformal Cubic Atmospheric Model (CCAM) to 0.5° × 0.5° from two different CMIP5 models (CNRM-CM5.0, GFDL-CM3.0). The India Meteorological Department (IMD) gridded (0.25° × 0.25°) observed rainfall data was considered to test the effectiveness of the proposed bias correction method. The quantile-quantile (Q-Q) plots and Nash Sutcliffe efficiency (NSE) were employed for evaluation of different methods of bias correction. The analysis suggested that the proposed method effectively corrects the daily bias in rainfall as compared to using monthly factors. The methods such as local intensity scaling, modified power transformation and distribution mapping, which adjusted the wet day frequencies, performed superior compared to the other methods, which did not consider adjustment of wet day frequencies. The distribution mapping method with daily correction factors was able to replicate the daily rainfall pattern of observed data with NSE value above 0.81 over most parts of India. Hydrological simulations forced using the bias corrected rainfall (distribution mapping and modified power transformation methods that used the proposed daily correction factors) was similar to those simulated by the IMD rainfall. The results demonstrate that the methods and the time scales used for bias correction of RCM rainfall data have a larger impact on the accuracy of the daily rainfall and consequently the simulated streamflow. The analysis suggests that the distribution mapping with daily correction factors can be preferred for adjusting RCM rainfall data irrespective of seasons or climate zones for realistic simulation of streamflow.
Multivariate Bias Correction Procedures for Improving Water Quality Predictions from the SWAT Model
NASA Astrophysics Data System (ADS)
Arumugam, S.; Libera, D.
2017-12-01
Water quality observations are usually not available on a continuous basis for longer than 1-2 years at a time over a decadal period given the labor requirements making calibrating and validating mechanistic models difficult. Further, any physical model predictions inherently have bias (i.e., under/over estimation) and require post-simulation techniques to preserve the long-term mean monthly attributes. This study suggests a multivariate bias-correction technique and compares to a common technique in improving the performance of the SWAT model in predicting daily streamflow and TN loads across the southeast based on split-sample validation. The approach is a dimension reduction technique, canonical correlation analysis (CCA) that regresses the observed multivariate attributes with the SWAT model simulated values. The common approach is a regression based technique that uses an ordinary least squares regression to adjust model values. The observed cross-correlation between loadings and streamflow is better preserved when using canonical correlation while simultaneously reducing individual biases. Additionally, canonical correlation analysis does a better job in preserving the observed joint likelihood of observed streamflow and loadings. These procedures were applied to 3 watersheds chosen from the Water Quality Network in the Southeast Region; specifically, watersheds with sufficiently large drainage areas and number of observed data points. The performance of these two approaches are compared for the observed period and over a multi-decadal period using loading estimates from the USGS LOADEST model. Lastly, the CCA technique is applied in a forecasting sense by using 1-month ahead forecasts of P & T from ECHAM4.5 as forcings in the SWAT model. Skill in using the SWAT model for forecasting loadings and streamflow at the monthly and seasonal timescale is also discussed.
Rainfall-runoff model for prediction of waterborne viral contamination in a small river catchment
NASA Astrophysics Data System (ADS)
Gelati, E.; Dommar, C.; Lowe, R.; Polcher, J.; Rodó, X.
2013-12-01
We present a lumped rainfall-runoff model aimed at providing useful information for the prediction of waterborne viral contamination in small rivers. Viral contamination of water bodies may occur because of the discharge of sewage effluents and of surface runoff over areas affected by animal waste loads. Surface runoff is caused by precipitation that cannot infiltrate due to its intensity and to antecedent soil water content. It may transport animal feces to adjacent water bodies and cause viral contamination. We model streamflow by separating it into two components: subsurface flow, which is produced by infiltrated precipitation; and surface runoff. The model estimates infiltrated and non-infiltrated precipitation and uses impulse-response functions to compute the corresponding fractions of streamflow. The developed methodologies are applied to the Glafkos river, whose catchment extends for 102 km2 and includes the city of Patra. Streamflow and precipitation observations are available at a daily time resolution. Waterborne virus concentration measurements were performed approximately every second week from the beginning of 2011 to mid 2012. Samples were taken at several locations: in river water upstream of Patras and in the urban area; in sea water at the river outlet and approximately 2 km south-west of Patras; in sewage effluents before and after treatment. The rainfall-runoff model was calibrated and validated using observed streamflow and precipitation data. The model contribution to waterborne viral contamination prediction was benchmarked by analyzing the virus concentration measurements together with the estimated surface runoff values. The presented methodology may be a first step towards the development of waterborne viral contamination alert systems. Predicting viral contamination of water bodies would benefit sectors such as water supply and tourism.
Estimated flow-duration curves for selected ungaged sites in Kansas
Studley, S.E.
2001-01-01
Flow-duration curves for 1968-98 were estimated for 32 ungaged sites in the Missouri, Smoky Hill-Saline, Solomon, Marais des Cygnes, Walnut, Verdigris, and Neosho River Basins in Kansas. Also included from a previous report are estimated flow-duration curves for 16 ungaged sites in the Cimarron and lower Arkansas River Basins in Kansas. The method of estimation used six unique factors of flow duration: (1) mean streamflow and percentage duration of mean streamflow, (2) ratio of 1-percent-duration streamflow to mean streamflow, (3) ratio of 0.1-percent-duration streamflow to 1-percent-duration streamflow, (4) ratio of 50-percent-duration streamflow to mean streamflow, (5) percentage duration of appreciable streamflow (0.10 cubic foot per second), and (6) average slope of the flow-duration curve. These factors were previously developed from a regionalized study of flow-duration curves using streamflow data for 1921-76 from streamflow-gaging stations with drainage areas of 100 to 3,000 square miles. The method was tested on a currently (2001) measured, continuous-record streamflow-gaging station on Salt Creek near Lyndon, Kansas, with a drainage area of 111 square miles and was found to adequately estimate the computed flow-duration curve for the station. The method also was tested on a currently (2001) measured, continuous-record, streamflow-gaging station on Soldier Creek near Circleville, Kansas, with a drainage area of 49.3 square miles. The results of the test on Soldier Creek near Circleville indicated that the method could adequately estimate flow-duration curves for sites with drainage areas of less than 100 square miles. The low-flow parts of the estimated flow-duration curves were verified or revised using 137 base-flow discharge measurements made during 1999-2000 at the 32 ungaged sites that were correlated with base-flow measurements and flow-duration analyses performed at nearby, long-term, continuous-record, streamflow-gaging stations (index stations). The method did not adequately estimate the flow-duration curves for two sites in the western one-third of the State because of substantial changes in farming practices (terracing and intensive ground-water withdrawal) that were not accounted for in the two previous studies (Furness, 1959; Jordan, 1983). For these two sites, there was enough historic, continuous-streamflow record available to perform record-extension techniques correlated to their respective index stations for the development of the estimated flow-duration curves. The estimated flow-duration curves at the ungaged sites can be used for projecting future flow frequencies for assessment of total maximum daily loads (TMDLs) or other water-quality constituents, water-availability studies, and for basin-characteristic studies.
NASA Astrophysics Data System (ADS)
Firoz, A. B. M.; Nauditt, Alexandra; Fink, Manfred; Ribbe, Lars
2018-01-01
Hydrological droughts are one of the most damaging disasters in terms of economic loss in central Vietnam and other regions of South-east Asia, severely affecting agricultural production and drinking water supply. Their increasing frequency and severity can be attributed to extended dry spells and increasing water abstractions for e.g. irrigation and hydropower development to meet the demand of dynamic socioeconomic development. Based on hydro-climatic data for the period from 1980 to 2013 and reservoir operation data, the impacts of recent hydropower development and other alterations of the hydrological network on downstream streamflow and drought risk were assessed for a mesoscale basin of steep topography in central Vietnam, the Vu Gia Thu Bon (VGTB) River basin. The Just Another Modelling System (JAMS)/J2000 was calibrated for the VGTB River basin to simulate reservoir inflow and the naturalized discharge time series for the downstream gauging stations. The HEC-ResSim reservoir operation model simulated reservoir outflow from eight major hydropower stations as well as the reconstructed streamflow for the main river branches Vu Gia and Thu Bon. Drought duration, severity, and frequency were analysed for different timescales for the naturalized and reconstructed streamflow by applying the daily varying threshold method. Efficiency statistics for both models show good results. A strong impact of reservoir operation on downstream discharge at the daily, monthly, seasonal, and annual scales was detected for four discharge stations relevant for downstream water allocation. We found a stronger hydrological drought risk for the Vu Gia river supplying water to the city of Da Nang and large irrigation systems especially in the dry season. We conclude that the calibrated model set-up provides a valuable tool to quantify the different origins of drought to support cross-sectorial water management and planning in a suitable way to be transferred to similar river basins.
Payne, G.A.
1989-01-01
During March through October 1986, 52,560 acre-feet of water passed the continuous-record stream gaging station on the Clearwater River near Clearbrook, Minnesota, 4.8 river miles upstream from the Red Lake Indian Reservation. Flow at the downstream boundary of the Reservation totaled 93,770 acre-feet. The increase in Clearwater River flow in the reach bordering the Reservation equaled 32,950 acre-feet; 60 percent of the increase occurred during March, April, and May. During those months, flow in the Clearwater River was augmented by flow from Kiwosay Reservoir and Butcher Knife Creek, which are located on the Reservation. Daily streamflow records showed that flow in the river increased in the Reservation reach throughout the study except for 13 days during October when losses occurred. At the downstream Reservation boundary, all daily mean flows exceeded the 36 cubic feet per second minimum flow required by the Minnesota Department of Natural Resources for the gaging station at Plummer, Minnesota located 29.9 miles downstream from the Reservation boundary. Monthly flows generally followed expected seasonal trends, with the highest monthly totals occurring in April and May and the lowest monthly totals occurring during August, September, and October. Seasonal trends were modified by reservoir releases, withdrawals for irrigation, and return flows that resulted from drainage of adjacent wild-rice fields. A series of flow measurements showed that localized withdrawals and return flows at times exceeded 20 percent of total streamflow. Discharge measurements made during low flow indicated higher rates of groundwater discharge in the vicinity of the Kiwosay Reservoir than in other parts of the study reach. Measurements made during August indicated that groundwater discharge in the reach of the river bordering the Reservation resulted in a flow gain of about 20 percent. Analysis of long-term streamflow records showed that near-average hydrologic conditions prevailed during the study period.
Koltun, G.F.
2015-01-01
Streamflow hydrographs were plotted for modeled/computed time series for the Ohio River near the USGS Sardis gage and the Ohio River at the Hannibal Lock and Dam. In general, the time series at these two locations compared well. Some notable differences include the exclusive presence of short periods of negative streamflows in the USGS 15-minute time-series data for the gage on the Ohio River above Sardis, Ohio, and the occurrence of several peak streamflows in the USACE gate/hydropower time series for the Hannibal Lock and Dam that were appreciably larger than corresponding peaks in the other time series, including those modeled/computed for the downstream Sardis gage
NASA Astrophysics Data System (ADS)
Brigandì, Giuseppina; Tito Aronica, Giuseppe; Bonaccorso, Brunella; Gueli, Roberto; Basile, Giuseppe
2017-09-01
The main focus of the paper is to present a flood and landslide early warning system, named HEWS (Hydrohazards Early Warning System), specifically developed for the Civil Protection Department of Sicily, based on the combined use of rainfall thresholds, soil moisture modelling and quantitative precipitation forecast (QPF). The warning system is referred to 9 different Alert Zones
in which Sicily has been divided into and based on a threshold system of three different increasing critical levels: ordinary, moderate and high. In this system, for early flood warning, a Soil Moisture Accounting (SMA) model provides daily soil moisture conditions, which allow to select a specific set of three rainfall thresholds, one for each critical level considered, to be used for issue the alert bulletin. Wetness indexes, representative of the soil moisture conditions of a catchment, are calculated using a simple, spatially-lumped rainfall-streamflow model, based on the SCS-CN method, and on the unit hydrograph approach, that require daily observed and/or predicted rainfall, and temperature data as input. For the calibration of this model daily continuous time series of rainfall, streamflow and air temperature data are used. An event based lumped rainfall-runoff model has been, instead, used for the derivation of the rainfall thresholds for each catchment in Sicily characterised by an area larger than 50 km2. In particular, a Kinematic Instantaneous Unit Hydrograph based lumped rainfall-runoff model with the SCS-CN routine for net rainfall was developed for this purpose. For rainfall-induced shallow landslide warning, empirical rainfall thresholds provided by Gariano et al. (2015) have been included in the system. They were derived on an empirical basis starting from a catalogue of 265 shallow landslides in Sicily in the period 2002-2012. Finally, Delft-FEWS operational forecasting platform has been applied to link input data, SMA model and rainfall threshold models to produce warning on a daily basis for the entire region.
A method to predict streamflow for ungauged basins of the Mid-Atlantic Region, USA was applied to the Rappahannock watershed in Virginia, USA. The method separates streamflow time series into magnitude and time sequence components. It uses the regionalized flow duration curve (RF...
Zhang, Y.-K.; Schilling, K.
2005-01-01
The patterns of temporal variations of precipitation (P), streamflow (SF) and baseflow (BF) as well as their nitrate-nitrogen (nitrate) concentrations (C) and loads (L) from a long-term record (28 years) in the Raccoon River, Iowa, were analyzed using variogram and spectral analyses. The daily P is random but scaling may exist in the daily SF and BF with a possible break point in the scaling at about 18 days and 45 days, respectively. The nitrate concentrations and loads are shown to have a half-year cycle while daily P, SF, and BF have a one-year cycle. Furthermore, there may be a low-frequency cycle of 6-8 years in C. The power spectra of C and L in both SF and BF exhibit fractal 1/f scaling with two characteristic frequencies of half-year and one-year, and are fitted well with the spectrum of the gamma distribution. The nitrate input to SF and BF at the Raccoon watershed seems likely to be a white noise process superimposed on another process with a half-year and one-year cycle. ?? 2005 Elsevier Ltd. All rights reserved.
Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation
NASA Astrophysics Data System (ADS)
Zhao, T.; Cai, X.; Yang, D.
2010-12-01
Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover, streamflow variability and reservoir capacity can change the magnitude of the effects of forecast uncertainty, but not the relative merit of DSF, DPSF, and ESF. Schematic diagram of the increase in forecast uncertainty with forecast lead-time and the dynamic updating property of real-time streamflow forecast
NASA Astrophysics Data System (ADS)
Thakur, B.; Pathak, P.; Kalra, A.; Ahmad, S.
2016-12-01
The identification of primary drivers of streamflow may prove beneficial in forecasting streamflow in the Midwestern U.S. In the past researches, streamflow in the region have been strongly correlated with El Niño-Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO). The present study takes in to account the pre-defined Pacific and Atlantic Ocean regions (e.g., ENSO, PDO, AMO) along with new regions with an intent to identify new significantly correlated regions. This study assesses the interrelationship between sea surface temperatures (SST) anomalies in the Pacific and Atlantic Ocean and seasonal streamflow in the Midwestern U.S. Average Pacific and Atlantic Ocean SST anomalies, were calculated for 2 different 3 month series: September-November and December-February so as to create a lead time varying from 3 to 9 months. Streamflow were averaged for three seasons: spring (April-June), spring-summer (April-August) and summer (June-August). The correlation between streamflow and SST is analyzed using singular value decomposition for a period of 1960-2013. The result of the study showed several regions-other than the known Pacific and Atlantic Ocean regions- that were significantly correlated with streamflow stations. Higher correlation between the climate indices and streamflow were observed as the lead time decreased. The identification of the associations between SST and streamflow and significant SST regions in the Pacific and Atlantic Ocean may enhance the skill of streamflow predictability and water management in the region.
An experimental system for flood risk forecasting at global scale
NASA Astrophysics Data System (ADS)
Alfieri, L.; Dottori, F.; Kalas, M.; Lorini, V.; Bianchi, A.; Hirpa, F. A.; Feyen, L.; Salamon, P.
2016-12-01
Global flood forecasting and monitoring systems are nowadays a reality and are being applied by an increasing range of users and practitioners in disaster risk management. Furthermore, there is an increasing demand from users to integrate flood early warning systems with risk based forecasts, combining streamflow estimations with expected inundated areas and flood impacts. To this end, we have developed an experimental procedure for near-real time flood mapping and impact assessment based on the daily forecasts issued by the Global Flood Awareness System (GloFAS). The methodology translates GloFAS streamflow forecasts into event-based flood hazard maps based on the predicted flow magnitude and the forecast lead time and a database of flood hazard maps with global coverage. Flood hazard maps are then combined with exposure and vulnerability information to derive flood risk. Impacts of the forecasted flood events are evaluated in terms of flood prone areas, potential economic damage, and affected population, infrastructures and cities. To further increase the reliability of the proposed methodology we integrated model-based estimations with an innovative methodology for social media monitoring, which allows for real-time verification of impact forecasts. The preliminary tests provided good results and showed the potential of the developed real-time operational procedure in helping emergency response and management. In particular, the link with social media is crucial for improving the accuracy of impact predictions.
Streamflow variability and classification using false nearest neighbor method
NASA Astrophysics Data System (ADS)
Vignesh, R.; Jothiprakash, V.; Sivakumar, B.
2015-12-01
Understanding regional streamflow dynamics and patterns continues to be a challenging problem. The present study introduces the false nearest neighbor (FNN) algorithm, a nonlinear dynamic-based method, to examine the spatial variability of streamflow over a region. The FNN method is a dimensionality-based approach, where the dimension of the time series represents its variability. The method uses phase space reconstruction and nearest neighbor concepts, and identifies false neighbors in the reconstructed phase space. The FNN method is applied to monthly streamflow data monitored over a period of 53 years (1950-2002) in an extensive network of 639 stations in the contiguous United States (US). Since selection of delay time in phase space reconstruction may influence the FNN outcomes, analysis is carried out for five different delay time values: monthly, seasonal, and annual separation of data as well as delay time values obtained using autocorrelation function (ACF) and average mutual information (AMI) methods. The FNN dimensions for the 639 streamflow series are generally identified to range from 4 to 12 (with very few exceptional cases), indicating a wide range of variability in the dynamics of streamflow across the contiguous US. However, the FNN dimensions for a majority of the streamflow series are found to be low (less than or equal to 6), suggesting low level of complexity in streamflow dynamics in most of the individual stations and over many sub-regions. The FNN dimension estimates also reveal that streamflow dynamics in the western parts of the US (including far west, northwestern, and southwestern parts) generally exhibit much greater variability compared to that in the eastern parts of the US (including far east, northeastern, and southeastern parts), although there are also differences among 'pockets' within these regions. These results are useful for identification of appropriate model complexity at individual stations, patterns across regions and sub-regions, interpolation and extrapolation of data, and catchment classification. An attempt is also made to relate the FNN dimensions with catchment characteristics and streamflow statistical properties.
Puente, Celso
1976-01-01
Water-level, springflow, and streamflow data were used to develop simple and multiple linear-regression equations for use in estimating water levels in wells and the flow of three major springs in the Edwards aquifer in the eastern San Antonio area. The equations provide daily, monthly, and annual estimates that compare very favorably with observed data. Analyses of geologic and hydrologic data indicate that the water discharged by the major springs is supplied primarily by regional underflow from the west and southwest and by local recharge in the infiltration area in northern Bexar, Comal, and Hays Counties.
NASA Astrophysics Data System (ADS)
Rivera, Juan Antonio; Araneo, Diego; Penalba, Olga; Villalba, Ricardo
2017-04-01
In the Central Andes of Argentina (CAA, located between 28° and 38°S), an arid to semi-arid region, the irrigation and a variety of socio-economical activities are highly dependent on river streamflows. Permanent and semi-permanent rivers originate mainly from snowmelt and glacier ablation, enabling the development of large agricultural oasis and the construction of numerous dams and reservoirs for irrigation and power generation. Most of its 2.5 million inhabitants and the main economic activities are located in a small irrigated fraction of the territory, where the variations in the timing and amount of water resources largely determine the socio-economic vulnerability of the region. In this context, the links between climatic variability and the hydrological cycle were assessed considering daily streamflow records from 21 streamgauges in the main rivers of the study area. Principal component analysis of annual hydrographs from 1931 to 2015 allowed to discriminate between precipitation- and temperature-related components associated with variations in snow accumulation (51% of variance) and advances/delays of the streamflow annual peak (16% of variance), respectively. The components related to intraseasonal variability account for 7% and 6% of variance, respectively, mixing both precipitation and thermal factors. The contribution of the precipitation-related component was the main driver of the 2010-15 streamflow drought conditions, although the thermal contribution was relevant during specific seasonal drought events. Based on an empirical decomposition methodology we identified the main modes of streamflow drought variability, which are linked to El Niño-Southern Oscillation on interannual time scales and the Pacific Decadal Oscillation (PDO) for the decadal variations. This result shows the influence of the tropical Pacific Ocean in the development of streamflow drought conditions and its relevance for potential predictability of hydroclimatic variations over the region. Nevertheless, recent studies indicate that, besides the contribution of La Niña and PDO signals, anthropogenic climate change could be responsible for the development of regional extreme drought conditions. In fact, reconstruction of CAA hydroclimate based on centennial-long tree-ring records shows a recent declining precipitation trend that is also evident over North Patagonia (38°-45°S) reconstructions, unprecedented in the last 400 years. This decreasing trend can be linked to the broadening of the sub-tropical dry zones as a displacement of the descending arm of the Hadley Cell circulation, a phenomenon likely forced by increased greenhouse gas concentrations, although its underlying mechanisms still not well understood. The assessment of future drought conditions based on a CMIP5 multi-model ensemble forced under two scenarios (RCP4.5 and RCP8.5) shows an expected increase in the number of drought events, with a decrease in the mean drought duration and non-significant changes in mean drought severity, although these results have a high range of uncertainty and are dependent on the future time horizon and selected scenario. Moreover, projected temperature trends will shift the streamflow peak from summer to late spring, in combination with a decrease in snow accumulation that will decrease the annual cycle amplitude. Both factors will likely change the hydroclimate of the semi-arid Andes, calling for new and improved water management practices over the region.
CrowdWater - Can people observe what models need?
NASA Astrophysics Data System (ADS)
van Meerveld, I. H. J.; Seibert, J.; Vis, M.; Etter, S.; Strobl, B.
2017-12-01
CrowdWater (www.crowdwater.ch) is a citizen science project that explores the usefulness of crowd-sourced data for hydrological model calibration and prediction. Hydrological models are usually calibrated based on observed streamflow data but it is likely easier for people to estimate relative stream water levels, such as the water level above or below a rock, than streamflow. Relative stream water levels may, therefore, be a more suitable variable for citizen science projects than streamflow. In order to test this assumption, we held surveys near seven different sized rivers in Switzerland and asked more than 450 volunteers to estimate the water level class based on a picture with a virtual staff gauge. The results show that people can generally estimate the relative water level well, although there were also a few outliers. We also asked the volunteers to estimate streamflow based on the stick method. The median estimated streamflow was close to the observed streamflow but the spread in the streamflow estimates was large and there were very large outliers, suggesting that crowd-based streamflow data is highly uncertain. In order to determine the potential value of water level class data for model calibration, we converted streamflow time series for 100 catchments in the US to stream level class time series and used these to calibrate the HBV model. The model was then validated using the streamflow data. The results of this modeling exercise show that stream level class data are useful for constraining a simple runoff model. Time series of only two stream level classes, e.g. above or below a rock in the stream, were already informative, especially when the class boundary was chosen towards the highest stream levels. There was hardly any improvement in model performance when more than five water level classes were used. This suggests that if crowd-sourced stream level observations are available for otherwise ungauged catchments, these data can be used to constrain a simple runoff model and to generate simulated streamflow time series from the level observations.
NASA Astrophysics Data System (ADS)
Kunnath-Poovakka, A.; Ryu, D.; Renzullo, L. J.; George, B.
2016-04-01
Calibration of spatially distributed hydrologic models is frequently limited by the availability of ground observations. Remotely sensed (RS) hydrologic information provides an alternative source of observations to inform models and extend modelling capability beyond the limits of ground observations. This study examines the capability of RS evapotranspiration (ET) and soil moisture (SM) in calibrating a hydrologic model and its efficacy to improve streamflow predictions. SM retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and daily ET estimates from the CSIRO MODIS ReScaled potential ET (CMRSET) are used to calibrate a simplified Australian Water Resource Assessment - Landscape model (AWRA-L) for a selection of parameters. The Shuffled Complex Evolution Uncertainty Algorithm (SCE-UA) is employed for parameter estimation at eleven catchments in eastern Australia. A subset of parameters for calibration is selected based on the variance-based Sobol' sensitivity analysis. The efficacy of 15 objective functions for calibration is assessed based on streamflow predictions relative to control cases, and relative merits of each are discussed. Synthetic experiments were conducted to examine the effect of bias in RS ET observations on calibration. The objective function containing the root mean square deviation (RMSD) of ET result in best streamflow predictions and the efficacy is superior for catchments with medium to high average runoff. Synthetic experiments revealed that accurate ET product can improve the streamflow predictions in catchments with low average runoff.
Lundquist, J.D.; Flint, A.L.
2006-01-01
Historic streamflow records show that the onset of snowfed streamflow in the western United States has shifted earlier over the past 50 yr, and March 2004 was one of the earliest onsets on record. Record high temperatures occurred throughout the western United States during the second week of March, and U.S. Geological Survey (USGS) stream gauges throughout the area recorded early onsets of streamflow at this time. However, a set of nested subbasins in Yosemite National Park, California, told a more complicated story. In spite of high air temperatures, many streams draining high-elevation basins did not start flowing until later in the spring. Temperatures during early March 2004 were as high as temperatures in late March 2002, when streams at all of the monitored Yosemite basins began flowing at the same time. However, the March 2004 onset occurred before the spring equinox, when the sun was lower in the sky. Thus, shading and solar radiation differences played a much more important role in 2004, leading to differences in streamflow timing. These results suggest that as temperatures warm and spring melt shifts earlier in the season, topographic effects will play an even more important role than at present in determining snowmelt timing. ?? 2006 American Meteorological Society.
Georgia's Surface-Water Resources and Streamflow Monitoring Network, 2006
Nobles, Patricia L.; ,
2006-01-01
The U.S. Geological Survey (USGS) network of 223 real-time monitoring stations, the 'Georgia HydroWatch,' provides real-time water-stage data, with streamflow computed at 198 locations, and rainfall recorded at 187 stations. These sites continuously record data on 15-minute intervals and transmit the data via satellite to be incorporated into the USGS National Water Information System database. These data are automatically posted to the USGS Web site for public dissemination (http://waterdata.usgs.gov/ga/nwis/nwis). The real-time capability of this network provides information to help emergency-management officials protect human life and property during floods, and mitigate the effects of prolonged drought. The map at right shows the USGS streamflow monitoring network for Georgia and major watersheds. Streamflow is monitored at 198 sites statewide, more than 80 percent of which include precipitation gages. Various Federal, State, and local agencies fund these streamflow monitoring stations.
PFReports: A program for systematic checking of annual peaks in NWISWeb
Ryberg, Karen R.
2008-01-01
The accuracy, characterization, and completeness of the U.S. Geological Survey (USGS) peak-flow data drive the determination of flood-frequency estimates that are used daily to design water and transportation infrastructure, delineate flood-plain boundaries, and regulate development and utilization of lands throughout the Nation and are essential to understanding the implications of climate change on flooding. Indeed, this high-profile database reflects and highlights the quality of USGS water-data collection programs. Its extension and improvement are essential to efforts to strengthen USGS networks and science leadership and is worthy of the attention of Water Science Center (WSC) hydrographers. This document describes a computer program, PFReports, and its output that facilitates efficient and robust review and correction of data in the USGS Peak Flow File (PFF) hosted as part of NWISWeb (the USGS public Web interface to much of the data stored and managed within the National Water Information System or NWIS). Checks embedded in the program are recommended as part of a more comprehensive assessment of peak flow data that will eventually include examination of possible regional changes, seasonal changes, and decadal variations in magnitude, timing, and frequency. Just as important as the comprehensive assessment, cleaning up the database will increase the likelihood of improved WSC regional flood-frequency equations. As an example of the value of cleaning up the PFF, data for 26,921 sites in the PFF were obtained. Of those sites, 17,542 sites had peak streamflow values and daily values. For the 17,542 sites, 1,097 peaks were identified that were less than the daily value for the day on which the peak occurred. Of the 26,921 sites, 11,643 had peak streamflow values, concurrent daily values, and at least 10 peaks. At the 11,643 sites, 2,205 peaks were identified as potential outliers in a regression of peak streamflows on daily values. Previous efforts to identify problems with the PFF were time consuming, laborious, and often ineffective. This new suite of checks represents an effort to automate identification of specific problems without plotting or printing large amounts of data that may not have problems. In addition, the results of the checks of the peak flow files are delivered through the World Wide Web with links to individual reports so that WSCs can focus on specific problems in an organized and standardized fashion. Over the years, technical reviews, regional-flood studies, and user inquiries have identified many minor and some major problems in the PFF. However, the cumbersome nature of the PFF editor and a lack of analytical tools have hampered efforts at quality assurance/quality control (QA/QC) and subsequently to make needed revisions to the database. This document is organized to provide information regarding PFReports, especially those tests involving regression and to provide an overview of the review procedures for utilizing the output. It also may be used as a reference for the data qualification codes and abbreviations for the tests. Results of the checks for all peak flow files (March 2008) are available at http://nd.water.usgs.gov/internal/pfreports/.
August Median Streamflow on Ungaged Streams in Eastern Aroostook County, Maine
Lombard, Pamela J.; Tasker, Gary D.; Nielsen, Martha G.
2003-01-01
Methods for estimating August median streamflow were developed for ungaged, unregulated streams in the eastern part of Aroostook County, Maine, with drainage areas from 0.38 to 43 square miles and mean basin elevations from 437 to 1,024 feet. Few long-term, continuous-record streamflow-gaging stations with small drainage areas were available from which to develop the equations; therefore, 24 partial-record gaging stations were established in this investigation. A mathematical technique for estimating a standard low-flow statistic, August median streamflow, at partial-record stations was applied by relating base-flow measurements at these stations to concurrent daily flows at nearby long-term, continuous-record streamflow- gaging stations (index stations). Generalized least-squares regression analysis (GLS) was used to relate estimates of August median streamflow at gaging stations to basin characteristics at these same stations to develop equations that can be applied to estimate August median streamflow on ungaged streams. GLS accounts for varying periods of record at the gaging stations and the cross correlation of concurrent streamflows among gaging stations. Twenty-three partial-record stations and one continuous-record station were used for the final regression equations. The basin characteristics of drainage area and mean basin elevation are used in the calculated regression equation for ungaged streams to estimate August median flow. The equation has an average standard error of prediction from -38 to 62 percent. A one-variable equation uses only drainage area to estimate August median streamflow when less accuracy is acceptable. This equation has an average standard error of prediction from -40 to 67 percent. Model error is larger than sampling error for both equations, indicating that additional basin characteristics could be important to improved estimates of low-flow statistics. Weighted estimates of August median streamflow, which can be used when making estimates at partial-record or continuous-record gaging stations, range from 0.03 to 11.7 cubic feet per second or from 0.1 to 0.4 cubic feet per second per square mile. Estimates of August median streamflow on ungaged streams in the eastern part of Aroostook County, within the range of acceptable explanatory variables, range from 0.03 to 30 cubic feet per second or 0.1 to 0.7 cubic feet per second per square mile. Estimates of August median streamflow per square mile of drainage area generally increase as mean elevation and drainage area increase.
Watson, Kara M.; McHugh, Amy R.
2014-01-01
Regional regression equations were developed for estimating monthly flow-duration and monthly low-flow frequency statistics for ungaged streams in Coastal Plain and non-coastal regions of New Jersey for baseline and current land- and water-use conditions. The equations were developed to estimate 87 different streamflow statistics, which include the monthly 99-, 90-, 85-, 75-, 50-, and 25-percentile flow-durations of the minimum 1-day daily flow; the August–September 99-, 90-, and 75-percentile minimum 1-day daily flow; and the monthly 7-day, 10-year (M7D10Y) low-flow frequency. These 87 streamflow statistics were computed for 41 continuous-record streamflow-gaging stations (streamgages) with 20 or more years of record and 167 low-flow partial-record stations in New Jersey with 10 or more streamflow measurements. The regression analyses used to develop equations to estimate selected streamflow statistics were performed by testing the relation between flow-duration statistics and low-flow frequency statistics for 32 basin characteristics (physical characteristics, land use, surficial geology, and climate) at the 41 streamgages and 167 low-flow partial-record stations. The regression analyses determined drainage area, soil permeability, average April precipitation, average June precipitation, and percent storage (water bodies and wetlands) were the significant explanatory variables for estimating the selected flow-duration and low-flow frequency statistics. Streamflow estimates were computed for two land- and water-use conditions in New Jersey—land- and water-use during the baseline period of record (defined as the years a streamgage had little to no change in development and water use) and current land- and water-use conditions (1989–2008)—for each selected station using data collected through water year 2008. The baseline period of record is representative of a period when the basin was unaffected by change in development. The current period is representative of the increased development of the last 20 years (1989–2008). The two different land- and water-use conditions were used as surrogates for development to determine whether there have been changes in low-flow statistics as a result of changes in development over time. The State was divided into two low-flow regression regions, the Coastal Plain and the non-coastal region, in order to improve the accuracy of the regression equations. The left-censored parametric survival regression method was used for the analyses to account for streamgages and partial-record stations that had zero flow values for some of the statistics. The average standard error of estimate for the 348 regression equations ranged from 16 to 340 percent. These regression equations and basin characteristics are presented in the U.S. Geological Survey (USGS) StreamStats Web-based geographic information system application. This tool allows users to click on an ungaged site on a stream in New Jersey and get the estimated flow-duration and low-flow frequency statistics. Additionally, the user can click on a streamgage or partial-record station and get the “at-site” streamflow statistics. The low-flow characteristics of a stream ultimately affect the use of the stream by humans. Specific information on the low-flow characteristics of streams is essential to water managers who deal with problems related to municipal and industrial water supply, fish and wildlife conservation, and dilution of wastewater.
NASA Astrophysics Data System (ADS)
Lundquist, Jessica D.; Roche, James W.; Forrester, Harrison; Moore, Courtney; Keenan, Eric; Perry, Gwyneth; Cristea, Nicoleta; Henn, Brian; Lapo, Karl; McGurk, Bruce; Cayan, Daniel R.; Dettinger, Michael D.
2016-09-01
Regions of complex topography and remote wilderness terrain have spatially varying patterns of temperature and streamflow, but due to inherent difficulties of access, are often very poorly sampled. Here we present a data set of distributed stream stage, streamflow, stream temperature, barometric pressure, and air temperature from the Tuolumne River Watershed in Yosemite National Park, Sierra Nevada, California, USA, for water years 2002-2015, as well as a quality-controlled hourly meteorological forcing time series for use in hydrologic modeling. We also provide snow data and daily inflow to the Hetch Hetchy Reservoir for 1970-2015. This paper describes data collected using low-visibility and low-impact installations for wilderness locations and can be used alone or as a critical supplement to ancillary data sets collected by cooperating agencies, referenced herein. This data set provides a unique opportunity to understand spatial patterns and scaling of hydroclimatic processes in complex terrain and can be used to evaluate downscaling techniques or distributed modeling. The paper also provides an example methodology and lessons learned in conducting hydroclimatic monitoring in remote wilderness.
Lundquist, Jessica D.; Roche, James W.; Forrester, Harrison; Moore, Courtney; Keenan, Eric; Perry, Gwyneth; Cristea, Nicoleta; Henn, Brian; Lapo, Karl; McGurk, Bruce; Cayan, Daniel R.; Dettinger, Michael D.
2016-01-01
Regions of complex topography and remote wilderness terrain have spatially varying patterns of temperature and streamflow, but due to inherent difficulties of access, are often very poorly sampled. Here we present a data set of distributed stream stage, streamflow, stream temperature, barometric pressure, and air temperature from the Tuolumne River Watershed in Yosemite National Park, Sierra Nevada, California, USA, for water years 2002–2015, as well as a quality-controlled hourly meteorological forcing time series for use in hydrologic modeling. We also provide snow data and daily inflow to the Hetch Hetchy Reservoir for 1970–2015. This paper describes data collected using low-visibility and low-impact installations for wilderness locations and can be used alone or as a critical supplement to ancillary data sets collected by cooperating agencies, referenced herein. This data set provides a unique opportunity to understand spatial patterns and scaling of hydroclimatic processes in complex terrain and can be used to evaluate downscaling techniques or distributed modeling. The paper also provides an example methodology and lessons learned in conducting hydroclimatic monitoring in remote wilderness.
Gazetteer of hydrologic characteristics of streams in Massachusetts; Blackstone River basin
Wandle, S.W.; Phipps, A.F.
1984-01-01
The Blackstone River basin encompasses 335 square miles in south-central Massachusetts, including parts of Bristol, Middlesex, Norfolk, and Worcester Counties. Drainage areas, using the latest available 1:24,000 scale topographic maps, were computed for the first time for streams draining more than 3 square miles and were recomputed for data-collection sites. Streamflow characteristics, were calculated using a new data base with records through 1980. These characteristics include annual and monthly flow statistics, duration of daily flow values, and the annual 7-day mean low flow at the 2-year and 10-year recurrence intervals. The 7-day, 10-year low-flow values are presented for 31 partial-record sites and the procedures used to determine the hydrologic characteristics of the basin are summarized. Basin characteristics representing 14 commonly used indices to estimate various streamflows are presented for the six gaged streams in the Blackstone River basin. This gazetteer will aid in the planning and siting of water-resources-related activities and will provide a common data base for governmental agencies and the engineering and planning communities. (USGS)
NASA Astrophysics Data System (ADS)
Mouzon, N. R.; Null, S. E.
2014-12-01
Human impacts from land and water development have degraded water quality and altered the physical, chemical, and biological integrity of Nevada's Walker River. Reduced instream flows and increased nutrient concentrations affect native fish populations through warm daily stream temperatures and low nightly dissolved oxygen concentrations. Water rights purchases are being considered to maintain instream flows, improve water quality, and enhance habitat for native fish species, such as Lahontan cutthroat trout. This study uses the River Modeling System (RMSv4), an hourly, physically-based hydrodynamic and water quality model, to estimate streamflows, temperatures, and dissolved oxygen concentrations in the Walker River. We simulate thermal and dissolved oxygen changes from increased streamflow to prioritize the time periods and locations that water purchases most enhance native trout habitat. Stream temperatures and dissolved oxygen concentrations are proxies for trout habitat. Monitoring results indicate stream temperature and dissolved oxygen limitations generally exist in the 115 kilometers upstream of Walker Lake (about 37% of the study area) from approximately May through September, and this reach currently acts as a water quality barrier for fish passage.
Brown, Christopher R.
2014-01-01
In 2013, the U.S. Geological Survey (USGS), in cooperation with the U. S. Department of the Army, compiled available precipitation and streamflow data for the years of 2008–2012 from the Fort Carson Military Reservation (Fort Carson) near Colorado Springs, Colo., and precipitation, streamflow, and suspended-sediment loads from the Piñon Canyon Maneuver Site (PCMS) near Trinidad, Colo. Graphical representations of the data presented herein are a continuation of work completed by the USGS in 2008 to gain a better understanding of spatial and temporal trends within the hydrologic data. Precipitation stations at Fort Carson and the PCMS were divided into groups based on their land-surface altitude (LSA) to determine if there is a spatial difference in precipitation amounts based on LSA for either military facility. Two-sample t-tests and Wilcoxon rank-sum tests indicated statistically significant differences exist between precipitation values at different groups for Fort Carson but not for the PCMS. All five precipitation stations at Fort Carson exhibit a decrease in median daily total precipitation from years 2002–2007 to 2008–2012. For the PCMS, median precipitation values decreased from the first study period to the second for the 13 stations monitored year-round except for Burson and Big Hills. Mean streamflow for 2008–2012 is less than mean streamflow for 1983–2007 for all stream-gaging stations at Fort Carson and at the PCMS. During the study period, each of the stream-gaging stations within the tributary channels at the PCMS accounted for less than three percent of the total streamflow at the Purgatoire River at Rock Crossing gage. Peak streamflow for 2008–2012 is less than peak streamflow for 2002–2007 at both Fort Carson and the PCMS. At the PCMS, mean suspended-sediment yield for 2008–2012 increased by 54 percent in comparison to the mean yield for 2002–2007. This increase is likely related to the destruction of groundcover by a series of wildfires within the PCMS in 2008 and 2011.
Changes toward earlier streamflow timing across western North America
Stewart, I.T.; Cayan, D.R.; Dettinger, M.D.
2005-01-01
The highly variable timing of streamflow in snowmelt-dominated basins across western North America is an important consequence, and indicator, of climate fluctuations. Changes in the timing of snowmelt-derived streamflow from 1948 to 2002 were investigated in a network of 302 western North America gauges by examining the center of mass for flow, spring pulse onset dates, and seasonal fractional flows through trend and principal component analyses. Statistical analysis of the streamflow timing measures with Pacific climate indicators identified local and key large-scale processes that govern the regionally coherent parts of the changes and their relative importance. Widespread and regionally coherent trends toward earlier onsets of springtime snowmelt and streamflow have taken place across most of western North America, affecting an area that is much larger than previously recognized. These timing changes have resulted in increasing fractions of annual flow occurring earlier in the water year by 1-4 weeks. The immediate (or proximal) forcings for the spatially coherent parts of the year-to-year fluctuations and longer-term trends of streamflow timing have been higher winter and spring temperatures. Although these temperature changes are partly controlled by the decadal-scale Pacific climate mode [Pacific decadal oscillation (PDO)], a separate and significant part of the variance is associated with a springtime warming trend that spans the PDO phases. ?? 2005 American Meteorological Society.
Dietsch, Benjamin J.; Godberson, Julie A.; Steele, Gregory V.
2009-01-01
The Nebraska Department of Natural Resources approved instream-flow appropriations on the Platte River to maintain fish communities, whooping crane roost habitat, and wet meadows used by several wild bird species. In the lower Platte River region, the Nebraska Game and Parks Commission owns an appropriation filed to maintain streamflow for fish communities between the Platte River confluence with the Elkhorn River and the mouth of the Platte River. Because Elkhorn River flow is an integral part of the flow in the reach addressed by this appropriation, the Upper Elkhorn and Lower Elkhorn Natural Resources Districts are involved in overall management of anthropogenic effects on the availability of surface water for instream requirements. The Physical Habitat Simulation System (PHABSIM) and other estimation methodologies were used previously to determine instream requirements for Platte River biota, which led to the filing of five water appropriations applications with the Nebraska Department of Natural Resources in 1993 by the Nebraska Game and Parks Commission. One of these requested instream-flow appropriations of 3,700 cubic feet per second was for the reach from the Elkhorn River to the mouth of the Platte River. Four appropriations were granted with modifications in 1998, by the Nebraska Department of Natural Resources. Daily streamflow data for the periods of record were summarized for 17 streamflow-gaging stations in Nebraska to evaluate streamflow characteristics, including low-flow intervals for consecutive durations of 1, 3, 7, 14, 30, 60, and 183 days. Temporal trends in selected streamflow statistics were not adjusted for variability in precipitation. Results indicated significant positive temporal trends in annual flow for the period of record at eight streamflow-gaging stations - Platte River near Duncan (06774000), Platte River at North Bend (06796000), Elkhorn River at Neligh (06798500), Logan Creek near Uehling (06799500), Maple Creek near Nickerson (06800000), Elkhorn River at Waterloo (06800500), Salt Creek at Greenwood (06803555), and Platte River at Louisville (06805500). In general, sites in the Elkhorn River Basin upstream from Norfolk showed fewer significant trends than did sites downstream from Norfolk and sites in the Platte River and Salt Creek basins, where trends in low flows also were positive. Historical Platte River streamflow records for the streamflow-gaging station at Louisville, Nebraska, were used to determine the number of days per water year (Sept. 30 to Oct. 1) when flows failed to satisfy the minimum criteria of the instream-flow appropriation prior to its filing in 1993. Before 1993, the median number of days the criteria were not satisfied was about 120 days per water year. During 1993 through 2004, daily mean flows at Louisville, Nebraska, have failed to satisfy the criteria for 638 days total (median value equals 21.5 days per year). Most of these low-flow intervals occurred in summer through early fall. For water years 1953 through 2004, of the discrete intervals when flow was less that the criteria levels, 61 percent were 3 days or greater in duration, and 38 percent were 7 days or greater in duration. The median duration of intervals of flow less than the criteria levels was 4 consecutive days during 1953 through 2004.
Impact of Deforestation and Recovery on Streamflow Recession Statistics
NASA Astrophysics Data System (ADS)
Krapu, C.; Kumar, M.
2016-12-01
Deforestation is known to influence streamflow and baseflow in particular in sub-humid environments. Baseflow contributions to the recession limb of a flood hydrograph convey information about subsurface stores from which trees also draw water. Recent works based on the assumptions outlined by Brutsaert and Nieber (1977) have proposed analyzing streamflow recession curves on a per-event basis. In this framework, each event's recession curve is governed by a power law relation with per-event scale and shape coefficients. As streamflow recession depends in part upon evapotranspiration demand from trees, these coefficients are hypothesized to contain useful information about catchment vegetation. Analysis was conducted of 13 small experimental catchments in the eastern United States with known forest treatment histories to determine whether or not streamflow recession behavior as observed from daily discharge records could serve as an indicator of deforestation in the drainage basin. Power-law scale coefficients were calculated for each major stormflow event at each test site and a statistical comparison of distribution of fitted coefficients was made between pre-treatment and post-treatment events as well as between pre-treatment and post-recovery events. A second method using these fitted coefficients in conjunction with Gaussian process regression was employed to track the change in the scale coefficient in the 13 catchments described previously as well as two medium-sized catchments in the North Carolina portion of the American Piedmont which did not have extensive records of forest cover. A linear trend analysis of precipitation was performed to determine whether nonstationarity in rainfall could be a confounding cause of changes in event scale coefficients. These results show a statistically significant difference in scale coefficient values in 5/8 treatment catchments and 0/5 control catchments. This suggests that lesser alterations to forest cover may not be detectable but that this method is robust against changes in precipitation. Additionally, we found clear evidence that forest regrowth in the Piedmont sites continued from 1940-1970. As a proof-of-concept, this work suggests that major alterations to forest cover can be inferred from daily data of stream discharge.
NASA Astrophysics Data System (ADS)
Fulton, John; Ostrowski, Joseph
2008-07-01
SummaryForecasting streamflow during extreme hydrologic events such as floods can be problematic. This is particularly true when flow is unsteady, and river forecasts rely on models that require uniform-flow rating curves to route water from one forecast point to another. As a result, alternative methods for measuring streamflow are needed to properly route flood waves and account for inertial and pressure forces in natural channels dominated by nonuniform-flow conditions such as mild water surface slopes, backwater, tributary inflows, and reservoir operations. The objective of the demonstration was to use emerging technologies to measure instantaneous streamflow in open channels at two existing US Geological Survey streamflow-gaging stations in Pennsylvania. Surface-water and instream-point velocities were measured using hand-held radar and hydroacoustics. Streamflow was computed using the probability concept, which requires velocity data from a single vertical containing the maximum instream velocity. The percent difference in streamflow at the Susquehanna River at Bloomsburg, PA ranged from 0% to 8% with an average difference of 4% and standard deviation of 8.81 m 3/s. The percent difference in streamflow at Chartiers Creek at Carnegie, PA ranged from 0% to 11% with an average difference of 5% and standard deviation of 0.28 m 3/s. New generation equipment is being tested and developed to advance the use of radar-derived surface-water velocity and instantaneous streamflow to facilitate the collection and transmission of real-time streamflow that can be used to parameterize hydraulic routing models.
Fulton, J.; Ostrowski, J.
2008-01-01
Forecasting streamflow during extreme hydrologic events such as floods can be problematic. This is particularly true when flow is unsteady, and river forecasts rely on models that require uniform-flow rating curves to route water from one forecast point to another. As a result, alternative methods for measuring streamflow are needed to properly route flood waves and account for inertial and pressure forces in natural channels dominated by nonuniform-flow conditions such as mild water surface slopes, backwater, tributary inflows, and reservoir operations. The objective of the demonstration was to use emerging technologies to measure instantaneous streamflow in open channels at two existing US Geological Survey streamflow-gaging stations in Pennsylvania. Surface-water and instream-point velocities were measured using hand-held radar and hydroacoustics. Streamflow was computed using the probability concept, which requires velocity data from a single vertical containing the maximum instream velocity. The percent difference in streamflow at the Susquehanna River at Bloomsburg, PA ranged from 0% to 8% with an average difference of 4% and standard deviation of 8.81 m3/s. The percent difference in streamflow at Chartiers Creek at Carnegie, PA ranged from 0% to 11% with an average difference of 5% and standard deviation of 0.28 m3/s. New generation equipment is being tested and developed to advance the use of radar-derived surface-water velocity and instantaneous streamflow to facilitate the collection and transmission of real-time streamflow that can be used to parameterize hydraulic routing models.
Clarke, John S.; Painter, Jaime A.
2014-01-01
Septic systems were identified at 241,733 locations in a 2,539-square-mile (mi2) study area that includes all or parts of 12 counties in the Metropolitan Atlanta, Georgia, area. Septic system percolation may locally be an important component of streamflow in small drainage basins where it augments natural groundwater recharge, especially during extreme low-flow conditions. The amount of groundwater reaching streams depends on how much is intercepted by plants or infiltrates to deeper parts of the groundwater system that flows beyond a basin divide and does not discharge into streams within a basin. The potential maximum percolation from septic systems in the study area is 62 cubic feet per second (ft3/s), of which 52 ft3/s is in the Chattahoochee River Basin and 10 ft3/s is in the Flint River Basin. These maximum percolation rates represent 0.4 to 5.7 percent of daily mean streamflow during the 2011–12 period at the farthest downstream gaging site (station 02338000) on the Chattahoochee River, and 0.5 to 179 percent of daily mean streamflow at the farthest downstream gaging site on the Flint River (02344350). To determine the difference in base flow between basins having different septic system densities, hydrograph separation analysis was completed using daily mean streamflow data at streamgaging stations at Level Creek (site 02334578), with a drainage basin having relatively high septic system density of 101 systems per square mile, and Woodall Creek (site 02336313), with a drainage basin having relatively low septic system density of 18 systems per square mile. Results indicated that base-flow yield during 2011–12 was higher at the Level Creek site, with a median of 0.47 cubic feet per second per square mile ([ft3/s]/mi2), compared to a median of 0.16 (ft3/s)/mi2, at the Woodall Creek site. At the less urbanized Level Creek site, there are 515 septic systems with a daily maximum percolation rate of 0.14 ft3/s, accounting for 11 percent of the base flow in September 2012. At the more urban Woodall Creek site, there are 50 septic systems with an average daily maximum percolation rate of 0.0097 ft3/s, accounting for 5 percent of base flow in September 2012. Streamflow measurements at 133 small drainage basins (less than 5 mi2 in area) during September 2012 indicated no statistically significant difference in streamflow or specific conductance between basins having high and low density of septic systems (HDS and LDS, respectively). The median base-flow yield was 0.04 (f3/s)/mi2 for HDS sites, ranging from 0 to 0.52 (ft3/s)/mi2, and 0.10 (ft3/s)/mi2 for LDS sites, ranging from 0 to 0.49 (ft3/s)/mi2. A Wilcoxon rank-sum test indicated the median base-flow yields for HDS and LDS sites were not statistically different, with a p-value of 0.345. Because of the large size of the study area and associated variations in basin characteristics, data collected in September 2012 were also evaluated on the basis of the basins physical characteristics in an attempt to reduce or eliminate other basin characteristics that might affect base flow. Basins were evaluated based on geologic area, four geographic subareas, and 45-meter (147.6 ft) buffer zone; there were no statistically significant differences between median base-flow yield for HDS and LDS basins. It is probable that detection of the contribution from septic system percolation in base flow at many of the sites visited in September 2012 was obscured by a combination of the limitations of measurement accuracy and evapotranspiration. Detection of septic system percolation may also have been complicated by leaky water and sewer mains, which may have resulted in higher streamflows in LDS basins relative to HDS basins.
Hydrologic Response to Climate Change: Missing Precipitation Data Matters for Computed Timing Trends
NASA Astrophysics Data System (ADS)
Daniels, B.
2016-12-01
This work demonstrates the derivation of climate timing statistics and applying them to determine resulting hydroclimate impacts. Long-term daily precipitation observations from 50 California stations were used to compute climate trends of precipitation event Intensity, event Duration and Pause between events. Each precipitation event trend was then applied as input to a PRMS hydrology model which showed hydrology changes to recharge, baseflow, streamflow, etc. An important concern was precipitation uncertainty induced by missing observation values and causing errors in quantification of precipitation trends. Many standard statistical techniques such as ARIMA and simple endogenous or even exogenous imputation were applied but failed to help resolve these uncertainties. What helped resolve these uncertainties was use of multiple imputation techniques. This involved fitting of Weibull probability distributions to multiple imputed values for the three precipitation trends.Permutation resampling techniques using Monte Carlo processing were then applied to the multiple imputation values to derive significance p-values for each trend. Significance at the 95% level for Intensity was found for 11 of the 50 stations, Duration from 16 of the 50, and Pause from 19, of which 12 were 99% significant. The significance weighted trends for California are Intensity -4.61% per decade, Duration +3.49% per decade, and Pause +3.58% per decade. Two California basins with PRMS hydrologic models were studied: Feather River in the northern Sierra Nevada mountains and the central coast Soquel-Aptos. Each local trend was changed without changing the other trends or the total precipitation. Feather River Basin's critical supply to Lake Oroville and the State Water Project benefited from a total streamflow increase of 1.5%. The Soquel-Aptos Basin water supply was impacted by a total groundwater recharge decrease of -7.5% and streamflow decrease of -3.2%.
How would peak rainfall intensity affect runoff predictions using conceptual water balance models?
NASA Astrophysics Data System (ADS)
Yu, B.
2015-06-01
Most hydrological models use continuous daily precipitation and potential evapotranspiration for streamflow estimation. With the projected increase in mean surface temperature, hydrological processes are set to intensify irrespective of the underlying changes to the mean precipitation. The effect of an increase in rainfall intensity on the long-term water balance is, however, not adequately accounted for in the commonly used hydrological models. This study follows from a previous comparative analysis of a non-stationary daily series of stream flow of a forested watershed (River Rimbaud) in the French Alps (area = 1.478 km2) (1966-2006). Non-stationarity in the recorded stream flow occurred as a result of a severe wild fire in 1990. Two daily models (AWBM and SimHyd) were initially calibrated for each of three distinct phases in relation to the well documented land disturbance. At the daily and monthly time scales, both models performed satisfactorily with the Nash-Sutcliffe coefficient of efficiency (NSE) varying from 0.77 to 0.92. When aggregated to the annual time scale, both models underestimated the flow by about 22% with a reduced NSE at about 0.71. Exploratory data analysis was undertaken to relate daily peak hourly rainfall intensity to the discrepancy between the observed and modelled daily runoff amount. Preliminary results show that the effect of peak hourly rainfall intensity on runoff prediction is insignificant, and model performance is unlikely to improve when peak daily precipitation is included. Trend analysis indicated that the large decrease of precipitation when daily precipitation amount exceeded 10-20 mm may have contributed greatly to the decrease in stream flow of this forested watershed.
Bodkin, Lee J.; Oden, Jeannette H.
2010-01-01
To better understand the hydrology (streamflow and water quality) of the West Fork San Jacinto River Basin downstream from Lake Conroe near Conroe, Texas, including spatial and temporal variation in suspended-sediment (SS) and total suspended-solids (TSS) concentrations and loads, the U.S. Geological Survey, in cooperation with the Houston-Galveston Area Council and the Texas Commission on Environmental Quality, measured streamflow and collected continuous and discrete water-quality data during July 2008-August 2009 in the West Fork San Jacinto River Basin downstream from Lake Conroe. During July 2008-August 2009, discrete samples were collected and streamflow measurements were made over the range of flow conditions at two streamflow-gaging stations on the West Fork San Jacinto River: West Fork San Jacinto River below Lake Conroe near Conroe, Texas (station 08067650) and West Fork San Jacinto River near Conroe, Texas (station 08068000). In addition to samples collected at these two main monitoring sites, discrete sediment samples were also collected at five additional monitoring sites to help characterize water quality in the West Fork San Jacinto River Basin. Discrete samples were collected semimonthly, regardless of flow conditions, and during periods of high flow resulting from storms or releases from Lake Conroe. Because the period of data collection was relatively short (14 months) and low flow was prevalent during much of the study, relatively few samples collected were representative of the middle and upper ranges of historical daily mean streamflows. The largest streamflows tended to occur in response to large rainfall events and generally were associated with the largest SS and TSS concentrations. The maximum SS and TSS concentrations at station 08067650 (180 and 133 milligrams per liter [mg/L], respectively) were on April 19, 2009, when the instantaneous streamflow was the third largest associated with a discrete sample at the station. SS concentrations were 25 mg/L or less in 26 of 29 environmental samples and TSS concentrations were 25 mg/L or less in 25 of 28 environmental samples. Median SS and TSS concentrations were 7.0 and 7.6 mg/L, respectively. At station 08068000, the maximum SS concentration (1,270 mg/L) was on April 19, 2009, and the maximum TSS concentration (268 mg/L) was on September 18, 2008. SS concentrations were 25 mg/L or less in 16 of 27 of environmental samples and TSS concentrations were 25 mg/L or less in 18 of 26 environmental samples at the station. Median SS and TSS concentrations were 18.0 and 14.0 mg/L, respectively. The maximum SS and TSS concentrations for all five additional monitoring sites were 3,110 and 390 mg/L, respectively, and the minimum SS and TSS concentrations were 5.0 and 1.0 mg/L, respectively. Median concentrations ranged from 14.0 to 54.0 mg/L for SS and from 11.0 to 14.0 mg/L for TSS. Continuous measurements of streamflow and selected water-quality properties at stations 08067650 and 08068000 were evaluated as possible variables in regression equations developed to estimate SS and TSS concentrations and loads. Surrogate regression equations were developed to estimate SS and TSS loads by using real-time turbidity and streamflow data; turbidity and streamflow resulted in the best regression models for estimating near real-time SS and TSS concentrations for stations 08097650 and 08068000. Relatively large errors are associated with the regression-computed SS and TSS concentrations; the 90-percent prediction intervals for SS and TSS concentrations were (+/-)48.9 and (+/-)43.2 percent, respectively, for station 08067650 and (+/-)47.7 and (+/-)43.2 percent, respectively, for station 08068000. Regression-computed SS and TSS concentrations were corrected for bias before being used to compute SS and TSS loads. The total estimated SS and TSS loads during July 2008-August 2009 were about 3,540 and 1,900 tons, respectively, at station 08067650 and about 156,000 an
Dynamic linear models to explore time-varying suspended sediment-discharge rating curves
NASA Astrophysics Data System (ADS)
Ahn, Kuk-Hyun; Yellen, Brian; Steinschneider, Scott
2017-06-01
This study presents a new method to examine long-term dynamics in sediment yield using time-varying sediment-discharge rating curves. Dynamic linear models (DLMs) are introduced as a time series filter that can assess how the relationship between streamflow and sediment concentration or load changes over time in response to a wide variety of natural and anthropogenic watershed disturbances or long-term changes. The filter operates by updating parameter values using a recursive Bayesian design that responds to 1 day-ahead forecast errors while also accounting for observational noise. The estimated time series of rating curve parameters can then be used to diagnose multiscale (daily-decadal) variability in sediment yield after accounting for fluctuations in streamflow. The technique is applied in a case study examining changes in turbidity load, a proxy for sediment load, in the Esopus Creek watershed, part of the New York City drinking water supply system. The results show that turbidity load exhibits a complex array of variability across time scales. The DLM highlights flood event-driven positive hysteresis, where turbidity load remained elevated for months after large flood events, as a major component of dynamic behavior in the rating curve relationship. The DLM also produces more accurate 1 day-ahead loading forecasts compared to other static and time-varying rating curve methods. The results suggest that DLMs provide a useful tool for diagnosing changes in sediment-discharge relationships over time and may help identify variability in sediment concentrations and loads that can be used to inform dynamic water quality management.
NASA Astrophysics Data System (ADS)
Null, S. E.; Elmore, L.; Mouzon, N. R.; Wood, J. R.
2016-12-01
More than 25 million cubic meters (20,000 acre feet) of water has been purchased from willing agricultural sellers for environmental flows in Nevada's Walker River to improve riverine habitat and connectivity with downstream Walker Lake. Reduced instream flows limit native fish populations, like Lahontan cutthroat trout, through warm daily stream temperatures and low dissolved oxygen concentrations. Environmental water purchases maintain instream flows, although effects on water quality are more varied. We use multi-year water quality monitoring and physically-based hydrodynamic and water quality modeling to estimate streamflow, water temperature, and dissolved oxygen concentrations with alternative environmental water purchases. We simulate water temperature and dissolved oxygen changes from increased streamflow to prioritize the time periods and locations that environmental water purchases most enhance trout habitat as a function of water quality. Monitoring results indicate stream temperature and dissolved oxygen limitations generally exist in the 115 kilometers upstream of Walker Lake (about 37% of the study area) from approximately May through September, and this reach acts as a water quality barrier for fish passage. Model results indicate that low streamflows generally coincide with critically warm stream temperatures, water quality refugia exist on a tributary of the Walker River, and environmental water purchases may improve stream temperature and dissolved oxygen conditions for some reaches and seasons, especially in dry years and prolonged droughts. This research supports environmental water purchase decision-making and allows water purchase decisions to be prioritized with other river restoration alternatives.
Propagation of stage measurement uncertainties to streamflow time series
NASA Astrophysics Data System (ADS)
Horner, Ivan; Le Coz, Jérôme; Renard, Benjamin; Branger, Flora; McMillan, Hilary
2016-04-01
Streamflow uncertainties due to stage measurements errors are generally overlooked in the promising probabilistic approaches that have emerged in the last decade. We introduce an original error model for propagating stage uncertainties through a stage-discharge rating curve within a Bayesian probabilistic framework. The method takes into account both rating curve (parametric errors and structural errors) and stage uncertainty (systematic and non-systematic errors). Practical ways to estimate the different types of stage errors are also presented: (1) non-systematic errors due to instrument resolution and precision and non-stationary waves and (2) systematic errors due to gauge calibration against the staff gauge. The method is illustrated at a site where the rating-curve-derived streamflow can be compared with an accurate streamflow reference. The agreement between the two time series is overall satisfying. Moreover, the quantification of uncertainty is also satisfying since the streamflow reference is compatible with the streamflow uncertainty intervals derived from the rating curve and the stage uncertainties. Illustrations from other sites are also presented. Results are much contrasted depending on the site features. In some cases, streamflow uncertainty is mainly due to stage measurement errors. The results also show the importance of discriminating systematic and non-systematic stage errors, especially for long term flow averages. Perspectives for improving and validating the streamflow uncertainty estimates are eventually discussed.
Bayesian Models for Streamflow and River Network Reconstruction using Tree Rings
NASA Astrophysics Data System (ADS)
Ravindranath, A.; Devineni, N.
2016-12-01
Water systems face non-stationary, dynamically shifting risks due to shifting societal conditions and systematic long-term variations in climate manifesting as quasi-periodic behavior on multi-decadal time scales. Water systems are thus vulnerable to long periods of wet or dry hydroclimatic conditions. Streamflow is a major component of water systems and a primary means by which water is transported to serve ecosystems' and human needs. Thus, our concern is in understanding streamflow variability. Climate variability and impacts on water resources are crucial factors affecting streamflow, and multi-scale variability increases risk to water sustainability and systems. Dam operations are necessary for collecting water brought by streamflow while maintaining downstream ecological health. Rules governing dam operations are based on streamflow records that are woefully short compared to periods of systematic variation present in the climatic factors driving streamflow variability and non-stationarity. We use hierarchical Bayesian regression methods in order to reconstruct paleo-streamflow records for dams within a basin using paleoclimate proxies (e.g. tree rings) to guide the reconstructions. The riverine flow network for the entire basin is subsequently modeled hierarchically using feeder stream and tributary flows. This is a starting point in analyzing streamflow variability and risks to water systems, and developing a scientifically-informed dynamic risk management framework for formulating dam operations and water policies to best hedge such risks. We will apply this work to the Missouri and Delaware River Basins (DRB). Preliminary results of streamflow reconstructions for eight dams in the upper DRB using standard Gaussian regression with regional tree ring chronologies give streamflow records that now span two to two and a half centuries, and modestly smoothed versions of these reconstructed flows indicate physically-justifiable trends in the time series.
Breault, Robert F.; Campbell, Jean P.
2010-01-01
Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board, Rhode Island's largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgage stations; 10 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate instantaneous (15-minute) loads of sodium and chloride during water year (WY) 2003 (October 1, 2002, to September 30, 2003). Water-quality samples were also collected at 37 sampling stations in the Scituate Reservoir drainage area by the Providence Water Supply Board during WY 2003 as part of a long-term sampling program. Water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2003. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed about 31 cubic feet per second (ft3/s) to the reservoir during WY 2003. For the same time period, annual mean streamflows1 measured (or estimated) for the other monitoring stations in this study ranged from about 0.44 to 20 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,200,000 kilograms (kg) of sodium and 1,900,000 kg of chloride to the Scituate Reservoir during WY 2003; sodium and chloride yields for the tributaries ranged from 10,000 to 61,000 kilograms per square mile (kg/mi2) and from 15,000 to 100,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 21.3 milligrams per liter (mg/L), median nitrite concentration was 0.002 mg/L as N, median nitrate concentration was 0.02 mg/L as N, median orthophosphate concentration was 0.06 mg/L as P, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 38 and 9 CFU/100 mL (colony forming units per 100 milliliters), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 140 kg/d (67 kg/d/mi2), 15 g/d (6.5 g/d/mi2), 140 g/d (62 g/d/mi2), 340 g/d (180 g/d/mi2), and 2,200 million colony forming units per day (CFU x 106/d) (1,200 CFU x 106/d/mi2) and 940 CFU x 106/d (490 CFU x 106/d/mi2), respectively. 1The arithmetic mean of the individual daily mean discharges for the year noted or for the designated period.
Breault, Robert F.; Campbell, Jean P.
2010-01-01
Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board, Rhode Island's largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgage stations; 10 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate instantaneous (15-minute) loads of sodium and chloride during water year (WY) 2004 (October 1, 2003, to September 30, 2004). Water-quality samples were also collected at 37 sampling stations in the Scituate Reservoir drainage area by the Providence Water Supply Board during WY 2004 as part of a long-term sampling program. Water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2004. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed about 27 cubic feet per second (ft3/s) to the reservoir during WY 2004. For the same time period, annual mean1 streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.42 to 19 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,100,000 kilograms (kg) of sodium and 1,700,000 kg of chloride to the Scituate Reservoir during WY 2004; sodium and chloride yields for the tributaries ranged from 12,000 to 61,000 kilograms per square mile (kg/mi2) and from 17,000 to 100,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 24.8 milligrams per liter (mg/L), median nitrite concentration was 0.001 mg/L as N, median nitrate concentration was 0.03 mg/L as N, median orthophosphate concentration was 0.07 mg/L as P, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 33 and 23 colony forming units per 100 milliliters (CFU/100 mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 160 kg/d (81 kg/d/mi2), 9.1 g/d (5.2 g/d/mi2), 280 g/d (110 g/d/mi2), 760 g/d (340 g/d/mi2), and 4,700 million colony forming units per day (CFU x 106/d) (1,700 CFU x 106/d/mi2) and 1,900 CFU x 106/d (520 CFU x 106/d/mi2), respectively. 1The arithmetic mean of the individual daily mean discharges for the year noted or for the designated period
Konrad, Christopher P.; Booth, Derek B.; Burges, Stephen J.
2005-01-01
Recovery and protection of streams in urban areas depend on a comprehensive understanding of how human activities affect stream ecosystems. The hydrologic effects of urban development and the consequences for stream channel form and streambed stability were examined in 16 streams in the Puget Lowland, Washington, using three streamflow metrics that integrate storm‐scale effects of urban development over annual to decadal timescales: the fraction of time that streamflow exceeds the mean streamflow (TQmean), the coefficient of variation of annual maximum streamflow (CVAMF), and the fraction of time that streamflow exceeds the 0.5‐year flood (T0.5). Urban streams had low interannual variability in annual maximum streamflow and brief duration of frequent high flows, as indicated by significant correlations between road density and both CVAMFand T0.5. The broader distribution of streamflow indicated by TQmean may be affected by urban development, but differences in TQmean between streams are also likely a result of other physiographic factors. The increase in the magnitude of frequent high flows due to urban development but not their cumulative duration has important consequences for channel form and bed stability in gravel bed streams because geomorphic equilibrium depends on moderate duration streamflow (e.g., exceeded 10% of the time). Streams with low values of TQmean and T0.5 are narrower than expected from hydraulic geometry. Dimensionless boundary shear stress (t*) for the 0.5‐year flood was inversely related to T0.5 among the streams, indicating frequent and extensive bed disturbance in streams with low values of T0.5. Although stream channels expand and the size of bed material increases in response to urban streamflow patterns, these adjustments may be insufficient to reestablish the disturbance regime in urban streams because of the differential increase in the magnitude of frequent high flows causing disturbance relative to any changes in longer duration, moderate flows that establish a stable channel.
Long-term variation analysis of a tropical river's annual streamflow regime over a 50-year period
NASA Astrophysics Data System (ADS)
Seyam, Mohammed; Othman, Faridah
2015-07-01
Studying the long-term changes of streamflow is an important tool for enhancing water resource and river system planning, design, and management. The aim of this work is to identify the long-term variations in annual streamflow regime over a 50-year period from 1961 to 2010 in the Selangor River, which is one of the main tropical rivers in Malaysia. Initially, the data underwent preliminary independence, normality, and homogeneity testing using the Pearson correlation coefficient and Shapiro-Wilk and Pettitt's tests, respectively. The work includes a study and analysis of the changes through nine variables describing the annual streamflow and variations in the yearly duration of high and low streamflows. The analyses were conducted via two time scales: yearly and sub-periodic. The sub-periods were obtained by segmenting the 50 years into seven sub-periods by two techniques, namely the change-point test and direct method. Even though analysis revealed nearly negligible changes in mean annual flow over the study period, the maximum annual flow generally increased while the minimum annual flow significantly decreased with respect to time. It was also observed that the variables describing the dispersion in streamflow continually increased with respect to time. An obvious increase was detected in the yearly duration of danger level of streamflow, a slight increase was noted in the yearly duration of warning and alert levels, and a slight decrease in the yearly duration of low streamflow was found. The perceived changes validate the existence of long-term changes in annual streamflow regime, which increase the probability of floods and droughts occurring in future. In light of the results, attention should be drawn to developing water resource management and flood protection plans in order to avert the harmful effects potentially resulting from the expected changes in annual streamflow regime.
Simulated runoff at many stream locations in the Methow River Basin, Washington
Mastin, Mark C.
2015-01-01
Comparisons of the simulated runoff with observed runoff at six selected long-term streamflow-gaging stations showed that the simulated annual runoff was within +15.4 to -9.6 percent of the annual observed runoff. The simulated runoff generally matched the seasonal flow patterns, with bias at some stations indicated by over-simulation of the October–November late autumn season and under-simulation of the snowmelt runoff months of May and June. Sixty-one time series of daily runoff for a 26-year period representative of the long-term runoff pattern, water years 1988–2013, were simulated and provided to the trophic modeling team.
Refinement and evaluation of the Massachusetts firm-yield estimator model version 2.0
Levin, Sara B.; Archfield, Stacey A.; Massey, Andrew J.
2011-01-01
The firm yield is the maximum average daily withdrawal that can be extracted from a reservoir without risk of failure during an extended drought period. Previously developed procedures for determining the firm yield of a reservoir were refined and applied to 38 reservoir systems in Massachusetts, including 25 single- and multiple-reservoir systems that were examined during previous studies and 13 additional reservoir systems. Changes to the firm-yield model include refinements to the simulation methods and input data, as well as the addition of several scenario-testing capabilities. The simulation procedure was adapted to run at a daily time step over a 44-year simulation period, and daily streamflow and meteorological data were compiled for all the reservoirs for input to the model. Another change to the model-simulation methods is the adjustment of the scaling factor used in estimating groundwater contributions to the reservoir. The scaling factor is used to convert the daily groundwater-flow rate into a volume by multiplying the rate by the length of reservoir shoreline that is hydrologically connected to the aquifer. Previous firm-yield analyses used a constant scaling factor that was estimated from the reservoir surface area at full pool. The use of a constant scaling factor caused groundwater flows during periods when the reservoir stage was very low to be overestimated. The constant groundwater scaling factor used in previous analyses was replaced with a variable scaling factor that is based on daily reservoir stage. This change reduced instability in the groundwater-flow algorithms and produced more realistic groundwater-flow contributions during periods of low storage. Uncertainty in the firm-yield model arises from many sources, including errors in input data. The sensitivity of the model to uncertainty in streamflow input data and uncertainty in the stage-storage relation was examined. A series of Monte Carlo simulations were performed on 22 reservoirs to assess the sensitivity of firm-yield estimates to errors in daily-streamflow input data. Results of the Monte Carlo simulations indicate that underestimation in the lowest stream inflows can cause firm yields to be underestimated by an average of 1 to 10 percent. Errors in the stage-storage relation can arise when the point density of bathymetric survey measurements is too low. Existing bathymetric surfaces were resampled using hypothetical transects of varying patterns and point densities in order to quantify the uncertainty in stage-storage relations. Reservoir-volume calculations and resulting firm yields were accurate to within 5 percent when point densities were greater than 20 points per acre of reservoir surface. Methods for incorporating summer water-demand-reduction scenarios into the firm-yield model were developed as well as the ability to relax the no-fail reliability criterion. Although the original firm-yield model allowed monthly reservoir releases to be specified, there have been no previous studies examining the feasibility of controlled releases for downstream flows from Massachusetts reservoirs. Two controlled-release scenarios were tested—with and without a summer water-demand-reduction scenario—for a scenario with a no-fail criterion and a scenario that allows for a 1-percent failure rate over the entire simulation period. Based on these scenarios, about one-third of the reservoir systems were able to support the flow-release scenarios at their 2000–2004 usage rates. Reservoirs with higher storage ratios (reservoir storage capacity to mean annual streamflow) and lower demand ratios (mean annual water demand to annual firm yield) were capable of higher downstream release rates. For the purposes of this research, all reservoir systems were assumed to have structures which enable controlled releases, although this assumption may not be true for many of the reservoirs studied.
Effects of water-management alternatives on streamflow in the Ipswich River basin, Massachusetts
Zarriello, Philip J.
2001-01-01
Management alternatives that could help mitigate the effects of water withdrawals on streamflow in the Ipswich River Basin were evaluated by simulation with a calibrated Hydrologic Simulation Program--Fortran (HSPF) model. The effects of management alternatives on streamflow were simulated for a 35-year period (196195). Most alternatives examined increased low flows compared to the base simulation of average 1989-93 withdrawals. Only the simulation of no septic-effluent inflow, and the simulation of a 20-percent increase in withdrawals, further lowered flows or caused the river to stop flowing for longer periods of time than the simulation of average 198993 withdrawals. Simulations of reduced seasonal withdrawals by 20 percent, and by 50 percent, resulted in a modest increase in low flow in a critical habitat reach (model reach 8 near the Reading town well field); log-Pearson Type III analysis of simulated daily-mean flow indicated that under these reduced withdrawals, model reach 8 would stop flowing for a period of seven consecutive days about every other year, whereas under average 198993 withdrawals this reach would stop flowing for a seven consecutive day period almost every year. Simulations of no seasonal withdrawals, and simulations that stopped streamflow depletion when flow in model reach 19 was below 22 cubic feet per second, indicated flow would be maintained in model reach 8 at all times. Simulations indicated wastewater-return flows would augment low flow in proportion to the rate of return flow. Simulations of a 1.5 million gallons per day return flow rate indicated model reach 8 would stop flowing for a period of seven consecutive days about once every 5 years; simulated return flow rates of 1.1 million gallons per day indicated that model reach 8 would stop flowing for a period of seven consecutive days about every other year. Simulation of reduced seasonal withdrawals, combined with no septic effluent return flow, indicated only a slight increase in low flow compared to low flows simulated under average 198993 withdrawals. Simulation of reduced seasonal withdrawal, combined with 2.6 million gallons per day wastewater-return flows, provided more flow in model reach 8 than that simulated under no withdrawals.
Cravotta, Charles A.; Sherrod, Laura; Galeone, Daniel G.; Lehman, Wayne G.; Ackman, Terry E.; Kramer, Alexa
2017-01-01
Longitudinal discharge and water-quality campaigns (seepage runs) were combined with surface-geophysical surveys, hyporheic-temperature profiling, and watershed-scale hydrological monitoring to evaluate the locations, magnitude, and impact of streamwater losses from the West Creek subbasin of the West West Branch Schuylkill River into the underground Oak Hill Mine complex that extends beneath the watershed divide. Abandoned mine drainage (AMD), containing iron and other contaminants, from the Oak Hill Boreholes to the West Branch Schuylkill River was sustained during low-flow conditions and correlated to streamflow lost through the West Creek streambed. During high-flow conditions, streamflow was transmitted throughout West Creek; however, during low-flow conditions, all streamflow from the perennial headwaters was lost within the 300-to-600-m "upper reach" where an 1889 mine map indicated steeply dipping coalbeds underlie the channel. During low-flow conditions, the channel within the "intermediate reach" 700-to-1650-m downstream gained groundwater seepage with higher pH and specific conductance than upstream; however, all streamflow 1650-to-2050-m downstream was lost to underlying mines. Electrical resistivity and electromagnetic conductivity surveys indicated conductive zones beneath the upper reach, where flow loss occurred, and through the intermediate reach, where gains and losses occurred. Temperature probes at 0.06-to-0.10-m depth within the hyporheic zone of the intermediate reach indicated potential downward fluxes as high as 2.1x10-5 m/s. Cumulative streamflow lost from West Creek during seepage runs averaged 53.4 L/s, which equates to 19.3 percent of the daily average discharge of AMD from the Oak Hill Boreholes and a downward flux of 1.70x10-5 m/s across the 2.1-km-by-1.5-m West Creek stream-channel area.
Historical floods reconstruction using NOAA 20CR global climate reanalysis over the last 150 years
NASA Astrophysics Data System (ADS)
Mathevet, T.; Brigode, P.; Jégonday, S.; Hingray, B.; Gailhard, J.; Wilhelm, B.
2017-12-01
Since several years, climatologists are producing long reanalysis for studying the variability of global climate over the last 150 years. For hydrologists, these datasets offer interesting opportunities for reconstructing historical flood events, and thus increasing the sample size used for flood frequency analysis. In this study, a streamflow reconstruction method based on the analogy of atmospheric situations (using NOAA 20CR reanalysis) for the reconstruction of climatic series and on a rainfall-runoff model for the streamflow reconstruction has been applied over different French catchments at the daily timestep. The studied catchments have been selected because of the availability of long observed streamflow series (used for quantifying the performances of the flood reconstructions) and for their different hydro-climatological regimes. Different methodologies have been tested for the reconstruction of daily climatic series over the 1851-2014 period, using geopotential heights and additional variables available within the 20CR reanalysis (relative humidity, precipitable water, etc.). Long observed climatic series have also been used when available as a reference for the climatic reconstructions. The different reconstruction methods have been finally ranked in terms of their historical flood reconstruction performances, quantified by flood types (autumn or winter floods) and atmospheric genesis (using a weather pattern classification). The obtained results indicate that using additional 20CR variables to the geopotential heights only slightly improve the flood reconstructions, while using observed climatic series improves significantly the flood reconstruction over the different catchments.
Huffman, Brad A.; Hazell, William F.; Oblinger, Carolyn J.
2017-09-06
Federal, State, and local agencies and organizations have expressed concerns regarding the detrimental effects of excessive sediment transport on aquatic resources and endangered species populations in the upper Little Tennessee River and some of its tributaries. In addition, the storage volume of Lake Emory, which is necessary for flood control and power generation, has been depleted by sediment deposition. To help address these concerns, a 2-year study was conducted in the upper Little Tennessee River Basin to characterize the ambient suspended-sediment concentrations and suspended-sediment loads upstream and downstream from Lake Emory in Franklin, North Carolina. The study was conducted by the U.S. Geological Survey in cooperation with Duke Energy. Suspended-sediment samples were collected periodically, and time series of stage and turbidity data were measured from December 2013 to January 2016 upstream and downstream from Lake Emory. The stage data were used to compute time-series streamflow. Suspended-sediment samples, along with time-series streamflow and turbidity data, were used to develop regression models that were used to estimate time-series suspended-sediment concentrations for the 2014 and 2015 calendar years. These concentrations, along with streamflow data, were used to compute suspended-sediment loads. Selected suspended-sediment samples were collected for analysis of particle-size distribution, with emphasis on high-flow events. Bed-load samples were also collected upstream from Lake Emory.The estimated annual suspended-sediment loads (yields) for the upstream site for the 2014 and 2015 calendar years were 27,000 short tons (92 short tons per square mile) and 63,300 short tons (215 short tons per square mile), respectively. The annual suspended-sediment loads (yields) for the downstream site for 2014 and 2015 were 24,200 short tons (75 short tons per square mile) and 94,300 short tons (292 short tons per square mile), respectively. Overall, the suspended-sediment load at the downstream site was about 28,300 short tons greater than the upstream site over the study period.As expected, high-flow events (the top 5 percent of daily mean flows) accounted for the majority of the sediment load; 80 percent at the upstream site and 90 percent at the downstream site. A similar relation between turbidity (the top 5 percent of daily mean turbidity) and high loads was also noted. In general, when instantaneous streamflows at the upstream site exceeded 5,000 cubic feet per second, increased daily loads were computed at the downstream site. During low to moderate flows, estimated suspended-sediment loads were lower at the downstream site when compared to the upstream site, which suggests that sediment deposition may be occurring in the intervening reach during those conditions. During the high-flow events, the estimated suspended-sediment loads were higher at the downstream site; however, it is impossible to say with certainty whether the increase in loading was due to scouring of lake sediment, contributions from the additional source area, model error, or a combination of one or more of these factors. The computed loads for a one-week period (December 24–31, 2015), during which the two largest high-flow events of the study period occurred, were approximately 52 percent of the 2015 annual sediment load (36 percent of 2-year load) at the upstream site and approximately 72 percent of the 2015 annual sediment load (57 percent of 2-year load) at the downstream site. Six bedload samples were collected during three events; two high-flow events and one base-flow event. The contribution of bedload to the total sediment load was determined to be insignificant for sampled flows. In general, streamflows for long-term streamgages in the study area were below normal for the majority of the study period; however, flows during the last 3 months of the study period were above normal, including the extreme events during the last week of the study period.
NASA Astrophysics Data System (ADS)
Morlot, T.; Mathevet, T.; Perret, C.; Favre Pugin, A. C.
2014-12-01
Streamflow uncertainty estimation has recently received a large attention in the literature. A dynamic rating curve assessment method has been introduced (Morlot et al., 2014). This dynamic method allows to compute a rating curve for each gauging and a continuous streamflow time-series, while calculating streamflow uncertainties. Streamflow uncertainty takes into account many sources of uncertainty (water level, rating curve interpolation and extrapolation, gauging aging, etc.) and produces an estimated distribution of streamflow for each days. In order to caracterise streamflow uncertainty, a probabilistic framework has been applied on a large sample of hydrometric stations of the Division Technique Générale (DTG) of Électricité de France (EDF) hydrometric network (>250 stations) in France. A reliability diagram (Wilks, 1995) has been constructed for some stations, based on the streamflow distribution estimated for a given day and compared to a real streamflow observation estimated via a gauging. To build a reliability diagram, we computed the probability of an observed streamflow (gauging), given the streamflow distribution. Then, the reliability diagram allows to check that the distribution of probabilities of non-exceedance of the gaugings follows a uniform law (i.e., quantiles should be equipropables). Given the shape of the reliability diagram, the probabilistic calibration is caracterised (underdispersion, overdispersion, bias) (Thyer et al., 2009). In this paper, we present case studies where reliability diagrams have different statistical properties for different periods. Compared to our knowledge of river bed morphology dynamic of these hydrometric stations, we show how reliability diagram gives us invaluable information on river bed movements, like a continuous digging or backfilling of the hydraulic control due to erosion or sedimentation processes. Hence, the careful analysis of reliability diagrams allows to reconcile statistics and long-term river bed morphology processes. This knowledge improves our real-time management of hydrometric stations, given a better caracterisation of erosion/sedimentation processes and the stability of hydrometric station hydraulic control.
Moyer, Douglas; Hyer, Kenneth
2003-01-01
Impairment of surface waters by fecal coliform bacteria is a water-quality issue of national scope and importance. Section 303(d) of the Clean Water Act requires that each State identify surface waters that do not meet applicable water-quality standards. In Virginia, more than 175 stream segments are on the 1998 Section 303(d) list of impaired waters because of violations of the water-quality standard for fecal coliform bacteria. A total maximum daily load (TMDL) will need to be developed by 2006 for each of these impaired streams and rivers by the Virginia Departments of Environmental Quality and Conservation and Recreation. A TMDL is a quantitative representation of the maximum load of a given water-quality constituent, from all point and nonpoint sources, that a stream can assimilate without violating the designated water-quality standard. Blacks Run, in Rockingham County, Virginia, is one of the stream segments listed by the State of Virginia as impaired by fecal coliform bacteria. Watershed modeling and bacterial source tracking were used to develop the technical components of the fecal coliform bacteria TMDL for Accotink Creek. The Hydrological Simulation Program?FORTRAN (HSPF) was used to simulate streamflow, fecal coliform concentrations, and source-specific fecal coliform loading in Blacks Run. Ribotyping, a bacterial source tracking technique, was used to identify the dominant sources of fecal coliform bacteria in the Blacks Run watershed. Ribotyping also was used to determine the relative contributions of specific sources to the observed fecal coliform load in Blacks Run. Data from the ribotyping analysis were incorporated into the calibration of the fecal coliform model. Study results provide information regarding the calibration of the streamflow and fecal coliform bacteria models and also identify the reductions in fecal coliform loads required to meet the TMDL for Blacks Run. The calibrated streamflow model simulated observed streamflow characteristics with respect to total annual runoff, seasonal runoff, average daily streamflow, and hourly stormflow. The calibrated fecal coliform model simulated the patterns and range of observed fecal coliform bacteria concentrations. Observed fecal coliform bacteria concentrations during low-flow periods ranged from 40 to 7,000 colonies per 100 milliliters, and peak concentrations during storm-flow periods ranged from 33,000 to 260,000 colonies per 100 milliliters. Simulated source-specific contributions of fecal coliform bacteria to instream load were matched to the observed contributions from the dominant sources, which were cats, cattle, deer, dogs, ducks, geese, horses, humans, muskrats, poultry, raccoons, and sheep. According to model results, a 95-percent reduction in the current fecal coliform load delivered from the watershed to Blacks Run would result in compliance with the designated water-quality goals and associated TMDL.
Moyer, Douglas; Hyer, Kenneth
2003-01-01
Impairment of surface waters by fecal coliform bacteria is a water-quality issue of national scope and importance. Section 303(d) of the Clean Water Act requires that each State identify surface waters that do not meet applicable water-quality standards. In Virginia, more than 175 stream segments are on the 1998 Section 303(d) list of impaired waters because of violations of the water-quality standard for fecal coliform bacteria. A total maximum daily load (TMDL) will need to be developed by 2006 for each of these impaired streams and rivers by the Virginia Departments of Environmental Quality and Conservation and Recreation. A TMDL is a quantitative representation of the maximum load of a given water-quality constituent, from all point and nonpoint sources, that a stream can assimilate without violating the designated water-quality standard. Accotink Creek, in Fairfax County, Virginia, is one of the stream segments listed by the State of Virginia as impaired by fecal coliform bacteria. Watershed modeling and bacterial source tracking were used to develop the technical components of the fecal coliform bacteria TMDL for Accotink Creek. The Hydrological Simulation Program?FORTRAN (HSPF) was used to simulate streamflow, fecal coliform concentrations, and source-specific fecal coliform loading in Accotink Creek. Ribotyping, a bacterial source tracking technique, was used to identify the dominant sources of fecal coliform bacteria in the Accotink Creek watershed. Ribotyping also was used to determine the relative contributions of specific sources to the observed fecal coliform load in Accotink Creek. Data from the ribotyping analysis were incorporated into the calibration of the fecal coliform model. Study results provide information regarding the calibration of the streamflow and fecal coliform bacteria models and also identify the reductions in fecal coliform loads required to meet the TMDL for Accotink Creek. The calibrated streamflow model simulated observed streamflow characteristics with respect to total annual runoff, seasonal runoff, average daily streamflow, and hourly stormflow. The calibrated fecal coliform model simulated the patterns and range of observed fecal coliform bacteria concentrations. Observed fecal coliform bacteria concentrations during low-flow periods ranged from 25 to 800 colonies per 100 milliliters, and peak concentrations during storm-flow periods ranged from 19,000 to 340,000 colonies per 100 milliliters. Simulated source-specific contributions of fecal coliform bacteria to instream load were matched to the observed contributions from the dominant sources, which were cats, deer, dogs, ducks, geese, humans, muskrats, and raccoons. According to model results, an 89-percent reduction in the current fecal coliform load delivered from the watershed to Accotink Creek would result in compliance with the designated water-quality goals and associated TMDL.
Reference manual for generation and analysis of Habitat Time Series: version II
Milhous, Robert T.; Bartholow, John M.; Updike, Marlys A.; Moos, Alan R.
1990-01-01
The selection of an instream flow requirement for water resource management often requires the review of how the physical habitat changes through time. This review is referred to as 'Time Series Analysis." The Tune Series Library (fSLIB) is a group of programs to enter, transform, analyze, and display time series data for use in stream habitat assessment. A time series may be defined as a sequence of data recorded or calculated over time. Examples might be historical monthly flow, predicted monthly weighted usable area, daily electrical power generation, annual irrigation diversion, and so forth. The time series can be analyzed, both descriptively and analytically, to understand the importance of the variation in the events over time. This is especially useful in the development of instream flow needs based on habitat availability. The TSLIB group of programs assumes that you have an adequate study plan to guide you in your analysis. You need to already have knowledge about such things as time period and time step, species and life stages to consider, and appropriate comparisons or statistics to be produced and displayed or tabulated. Knowing your destination, you must first evaluate whether TSLIB can get you there. Remember, data are not answers. This publication is a reference manual to TSLIB and is intended to be a guide to the process of using the various programs in TSLIB. This manual is essentially limited to the hands-on use of the various programs. a TSLIB use interface program (called RTSM) has been developed to provide an integrated working environment where the use has a brief on-line description of each TSLIB program with the capability to run the TSLIB program while in the user interface. For information on the RTSM program, refer to Appendix F. Before applying the computer models described herein, it is recommended that the user enroll in the short course "Problem Solving with the Instream Flow Incremental Methodology (IFIM)." This course is offered by the Aquatic Systems Branch of the National Ecology Research Center. For more information about the TSLIB software, refer to the Memorandum of Understanding. Chapter 1 provides a brief introduction to the Instream Flow Incremental Methodology and TSLIB. Other chapters in this manual provide information on the different aspects of using the models. The information contained in the other chapters includes (2) acquisition, entry, manipulation, and listing of streamflow data; (3) entry, manipulation, and listing of the habitat-versus-streamflow function; (4) transferring streamflow data; (5) water resources systems analysis; (6) generation and analysis of daily streamflow and habitat values; (7) generation of the time series of monthly habitats; (8) manipulation, analysis, and display of month time series data; and (9) generation, analysis, and display of annual time series data. Each section includes documentation for the programs therein with at least one page of information for each program, including a program description, instructions for running the program, and sample output. The Appendixes contain the following: (A) sample file formats; (B) descriptions of default filenames; (C) alphabetical summary of batch-procedure files; (D) installing and running TSLIB on a microcomputer; (E) running TSLIB on a CDC Cyber computer; (F) using the TSLIB user interface program (RTSM); and (G) running WATSTORE on the USGS Amdahl mainframe computer. The number for this version of TSLIB--Version II-- is somewhat arbitrary, as the TSLIB programs were collected into a library some time ago; but operators tended to use and manage them as individual programs. Therefore, we will consider the group of programs from the past that were only on the CDC Cyber computer as Version 0; the programs from the past that were on both the Cyber and the IBM-compatible microcomputer as Version I; and the programs contained in this reference manual as Version II.
Surface waters of Illinois River basin in Arkansas and Oklahoma
Laine, L.L.
1959-01-01
The estimated runoff from the Illinois River basin of 1,660 square miles has averaged 1,160,000 acre-feet per year during the water years 1938-56, equivalent to an average annual runoff depth of 13.1 inches. About 47 percent of the streamflow is contributed from drainage in Arkansas, where an average of 550,000 acre-ft per year runs off from 755 square miles, 45.5 percent of the total drainage area. The streamflow is highly variable. Twenty-two years of record for Illinois River near Tahlequah, Okla., shows a variation in runoff for the water year 1945 in comparison with 1954 in a ratio of almost 10 to 1. Runoff in 1927 may have exceeded that of 1945, according to records for White River at Beaver, Ark., the drainage basin just east of the Illinois River basin. Variation in daily discharge is suggested by a frequency analysis of low flows at the gaging station near Tahlequah, Okla. The mean flow at that site is 901 cfs (cubic feet per second), the median daily flow is 350 cfs, and the lowest 30-day mean flow in a year probably will be less than 130 cfs half of the time and less than 20 cfs every 10 years on the average. The higher runoff tends to occur in the spring months, March to May, a 3-month period that, on the average, accounts for almost half of the annual flow. High runoff may occur during any month in the year, but in general, the streamflow is the lowest in the summer. The mean monthly flow of Illinois River near Tahlequah, Okla., for September is about 11 percent of that for May. Records show that there is flow throughout the year in Illinois River and its principal tributaries Osage Creek, Flint Creek and Barren Fork. The high variability in streamflow in this region requires the development of storage by impoundment if maximum utilization of the available water supplies is to be attained. For example, a 120-day average low flow of 22 cfs occurred in 1954 at Illinois River near Tahlequah, Okla. To have maintained the flow at 350 cfs, the median daily flow during the 19-year base period, an impoundment at that site would have required a usable storage of 185,000 acre-ft to satisfy this demand during the drought years 1954-1956. The surface waters of the Illinois River basin are excellent quality being suitable for municipal, agriculture and most industrial uses. The average concentration of the dissolved mineral content is about 105 ppm (parts per million) and the hardness about 85 ppm. The water is slightly alkaline, having a range of pH values from 7.2 to 8.0. This report gives the estimated average discharge at gaging stations and approximations of average discharge at the State line for 3 sub-basins during the 19-year period October 1937 to September 1956, used as a base period in this report. Duration-of-flow data for various percentages of the time are shown for the period of observed record at the gaging stations; similar data are estimated for the selected base period. Storage requirements to sustain flow during the recent drought years are given for 3 stations. The streamflow records in the basin are presented on a monthly and annual basis through September 1957; provisional records for 3 stations are included through July 1958 for correlation purposes. Results of discharge measurements are given for miscellaneous sites where low-flow observations have been made. (available as photostat copy only)
NASA Astrophysics Data System (ADS)
Fulton, J. W.; Bjerklie, D. M.; Jones, J. W.; Minear, J. T.
2015-12-01
Measuring streamflow, developing, and maintaining rating curves at new streamgaging stations is both time-consuming and problematic. Hydro 21 was an initiative by the U.S. Geological Survey to provide vision and leadership to identify and evaluate new technologies and methods that had the potential to change the way in which streamgaging is conducted. Since 2014, additional trials have been conducted to evaluate some of the methods promoted by the Hydro 21 Committee. Emerging technologies such as continuous-wave radars and computationally-efficient methods such as the Probability Concept require significantly less field time, promote real-time velocity and streamflow measurements, and apply to unsteady flow conditions such as looped ratings and unsteady-flood flows. Portable and fixed-mount radars have advanced beyond the development phase, are cost effective, and readily available in the marketplace. The Probability Concept is based on an alternative velocity-distribution equation developed by C.-L. Chiu, who pioneered the concept. By measuring the surface-water velocity and correcting for environmental influences such as wind drift, radars offer a reliable alternative for measuring and computing real-time streamflow for a variety of hydraulic conditions. If successful, these tools may allow us to establish ratings more efficiently, assess unsteady flow conditions, and report real-time streamflow at new streamgaging stations.
Changes in Stream Peak Flow and Regulation in Naoli River Watershed as a Result of Wetland Loss
Yao, Yunlong; Wang, Lei; Lv, Xianguo; Yu, Hongxian; Li, Guofu
2014-01-01
Hydrology helps determine the character of wetlands; wetlands, in turn, regulate water flow, which influences regional hydrology. To understand these dynamics, we studied the Naoli basin where, from 1954 to 2005, intensive marshland cultivation took place, and the watershed's wetland area declined from 94.4 × 104 ha to 17.8 × 104 ha. More than 80% of the wetland area loss was due to conversion to farmland, especially from 1976 to 1986. The processes of transforming wetlands to cultivated land in the whole Naoli basin and subbasins can be described using a first order exponential decay model. To quantify the effects of wetlands cultivation, we analyzed daily rainfall and streamflow data measured from 1955 to 2005 at two stations (Baoqing Station and Caizuizi Station). We defined a streamflow regulation index (SRI) and applied a Mann-Kendall-Sneyers test to further analyze the data. As the wetland area decreased, the peak streamflow at the Caizuizi station increased, and less precipitation generated heavier peak flows, as the runoff was faster than before. The SRI from 1959 to 2005 showed an increasing trend; the SRI rate of increase was 0.05/10a, demonstrating that the watershed's regulation of streamflow regulation was declined as the wetlands disappeared. PMID:25114956
Entrekin, Sally; Trainor, Anne; Saiers, James; Patterson, Lauren; Maloney, Kelly O.; Fargione, Joseph; Kiesecker, Joseph M.; Baruch-Mordo, Sharon; Konschnik, Katherine E.; Wiseman, Hannah; Nicot, Jean-Philippe; Ryan, Joseph N.
2018-01-01
Demand for high-volume, short duration water withdrawals could create water stress to aquatic organisms in Fayetteville Shale streams sourced for hydraulic fracturing fluids. We estimated potential water stress using permitted water withdrawal volumes and actual water withdrawals compared to monthly median, low, and high streamflows. Risk for biological stress was considered at 20% of long-term median and 10% of high- and low-flow thresholds. Future well build-out projections estimated potential for continued stress. Most water was permitted from small, free-flowing streams and “frack” ponds (dammed streams). Permitted 12-h pumping volumes exceeded median streamflow at 50% of withdrawal sites in June, when flows were low. Daily water usage, from operator disclosures, compared to median streamflow showed possible water stress in 7–51% of catchments from June–November, respectively. If 100% of produced water was recycled, per-well water use declined by 25%, reducing threshold exceedance by 10%. Future water stress was predicted to occur in fewer catchments important for drinking water and species of conservation concern due to the decline in new well installations and increased use of recycled water. Accessible and precise withdrawal and streamflow data are critical moving forward to assess and mitigate water stress in streams that experience high-volume withdrawals.
Entrekin, Sally; Trainor, Anne; Saiers, James; Patterson, Lauren; Maloney, Kelly; Fargione, Joseph; Kiesecker, Joseph; Baruch-Mordo, Sharon; Konschnik, Katherine; Wiseman, Hannah; Nicot, Jean-Philippe; Ryan, Joseph N
2018-02-20
Demand for high-volume, short duration water withdrawals could create water stress to aquatic organisms in Fayetteville Shale streams sourced for hydraulic fracturing fluids. We estimated potential water stress using permitted water withdrawal volumes and actual water withdrawals compared to monthly median, low, and high streamflows. Risk for biological stress was considered at 20% of long-term median and 10% of high- and low-flow thresholds. Future well build-out projections estimated potential for continued stress. Most water was permitted from small, free-flowing streams and "frack" ponds (dammed streams). Permitted 12-h pumping volumes exceeded median streamflow at 50% of withdrawal sites in June, when flows were low. Daily water usage, from operator disclosures, compared to median streamflow showed possible water stress in 7-51% of catchments from June-November, respectively. If 100% of produced water was recycled, per-well water use declined by 25%, reducing threshold exceedance by 10%. Future water stress was predicted to occur in fewer catchments important for drinking water and species of conservation concern due to the decline in new well installations and increased use of recycled water. Accessible and precise withdrawal and streamflow data are critical moving forward to assess and mitigate water stress in streams that experience high-volume withdrawals.
Predicting streamflow regime metrics for ungauged streamsin Colorado, Washington, and Oregon
NASA Astrophysics Data System (ADS)
Sanborn, Stephen C.; Bledsoe, Brian P.
2006-06-01
Streamflow prediction in ungauged basins provides essential information for water resources planning and management and ecohydrological studies yet remains a fundamental challenge to the hydrological sciences. A methodology is presented for stratifying streamflow regimes of gauged locations, classifying the regimes of ungauged streams, and developing models for predicting a suite of ecologically pertinent streamflow metrics for these streams. Eighty-four streamflow metrics characterizing various flow regime attributes were computed along with physical and climatic drainage basin characteristics for 150 streams with little or no streamflow modification in Colorado, Washington, and Oregon. The diverse hydroclimatology of the study area necessitates flow regime stratification and geographically independent clusters were identified and used to develop separate predictive models for each flow regime type. Multiple regression models for flow magnitude, timing, and rate of change metrics were quite accurate with many adjusted R2 values exceeding 0.80, while models describing streamflow variability did not perform as well. Separate stratification schemes for high, low, and average flows did not considerably improve models for metrics describing those particular aspects of the regime over a scheme based on the entire flow regime. Models for streams identified as 'snowmelt' type were improved if sites in Colorado and the Pacific Northwest were separated to better stratify the processes driving streamflow in these regions thus revealing limitations of geographically independent streamflow clusters. This study demonstrates that a broad suite of ecologically relevant streamflow characteristics can be accurately modeled across large heterogeneous regions using this framework. Applications of the resulting models include stratifying biomonitoring sites and quantifying linkages between specific aspects of flow regimes and aquatic community structure. In particular, the results bode well for modeling ecological processes related to high-flow magnitude, timing, and rate of change such as the recruitment of fish and riparian vegetation across large regions.
Statistical summaries of New Jersey streamflow records
Laskowski, Stanley L.
1970-01-01
In 1961 the U.S. Geological Survey prepared a report which was published by the State of New Jersey as Water Resources Circular 6, "New Jersey Streamflow Records analyzed with Electronic Computer" by Miller and McCall. Basic discharge data for periods of record through 1958 were analyzed for 59 stream-gaging stations in New Jersey and flow-duration, low-flow, and high-flow tables were presented.The purpose of the current report is to update and expand Circular 6 by presenting, with a few meaningful statistics and tables, the bulk of the information that may be obtained from the mass of streamflow records available. The records for 79 of approximately 110 stream-gaging stations presently or previously operated in New Jersey, plus records for three stations in Pennsylvania, and one in New York are presented in summarized form. In addition to inclusing a great number of stations in this report, more years of record and more tables are listed for each station. A description of the station, three arrangements of data summarizing the daily flow records and one table listing statistics of the monthly mean flows are provided. No data representing instantaneous extreme flows are given. Plotting positions for the three types of curves describing the characteristics of daily discharge are listed for each station. Statistical parameters are also presented so that alternate curves may be drawn.All stations included in this report have 5 or more years of record. The data presented herein are based on observed flow past the gaging station. For any station where the observed flow is affected by regulation or diversion, a "Remarks" paragraph, explaining the possible effect on the data, is included in the station description.Since any streamflow record is a sample in time, the data derived from these records can provide only a guide to expected future flows. For this reason the flow records are analyzed by statistical techniques, and the magnitude of sampling errors should be recognized.These analyzed data will be useful to a large number of municipal, state, and federal agencies, industries, utilities, engineers, and hydrologists concerned with the availability, conservation, control, and use of surface waters. The tabulated data and curves illustrated herein can be used to select sites for water supplies, to determine flood or drought storage requirements, and to appraise the adequacy of flows for dilution of wastes or generation of power. The statistical values presented herein can be used in computer programs available in many universities, Federal and State agencies, and engineering firms for a broad spectrum of research and other studies.
NASA Astrophysics Data System (ADS)
Saxe, Samuel; Hogue, Terri S.; Hay, Lauren
2018-02-01
This research investigates the impact of wildfires on watershed flow regimes, specifically focusing on evaluation of fire events within specified hydroclimatic regions in the western United States, and evaluating the impact of climate and geophysical variables on response. Eighty-two watersheds were identified with at least 10 years of continuous pre-fire daily streamflow records and 5 years of continuous post-fire daily flow records. Percent change in annual runoff ratio, low flows, high flows, peak flows, number of zero flow days, baseflow index, and Richards-Baker flashiness index were calculated for each watershed using pre- and post-fire periods. Independent variables were identified for each watershed and fire event, including topographic, vegetation, climate, burn severity, percent area burned, and soils data. Results show that low flows, high flows, and peak flows increase in the first 2 years following a wildfire and decrease over time. Relative response was used to scale response variables with the respective percent area of watershed burned in order to compare regional differences in watershed response. To account for variability in precipitation events, runoff ratio was used to compare runoff directly to PRISM precipitation estimates. To account for regional differences in climate patterns, watersheds were divided into nine regions, or clusters, through k-means clustering using climate data, and regression models were produced for watersheds grouped by total area burned. Watersheds in Cluster 9 (eastern California, western Nevada, Oregon) demonstrate a small negative response to observed flow regimes after fire. Cluster 8 watersheds (coastal California) display the greatest flow responses, typically within the first year following wildfire. Most other watersheds show a positive mean relative response. In addition, simple regression models show low correlation between percent watershed burned and streamflow response, implying that other watershed factors strongly influence response. Spearman correlation identified NDVI, aridity index, percent of a watershed's precipitation that falls as rain, and slope as being positively correlated with post-fire streamflow response. This metric also suggested a negative correlation between response and the soil erodibility factor, watershed area, and percent low burn severity. Regression models identified only moderate burn severity and watershed area as being consistently positively/negatively correlated, respectively, with response. The random forest model identified only slope and percent area burned as significant watershed parameters controlling response. Results will help inform post-fire runoff management decisions by helping to identify expected changes to flow regimes, as well as facilitate parameterization for model application in burned watersheds.
NASA Astrophysics Data System (ADS)
Vidal, Jean-Philippe; Caillouet, Laurie; Dayon, Gildas; Boé, Julien; Sauquet, Eric; Thirel, Guillaume; Graff, Benjamin
2017-04-01
The record length of streamflow observations is generally limited to the last 50 years, which is not enough to properly explore the natural hydrometeorological variability, a key to better understand the effects of anthropogenic climate change. This work proposes a comparison of different hydrometeorological reconstruction datasets over France built on the downscaling of the NOAA 20th century global extended reanalysis (20CR, Compo et al., 2011). It aims at assessing the uncertainties related to these reconstructions and improving our knowledge of the multi-decadal hydrometeorological variability over the 20th century. High-resolution daily meteorological reconstructions over the period 1871-2012 are obtained with two statistical downscaling methods based on the analogue approach: the deterministic ANALOG method (Dayon et al., 2015) and the probabilistic SCOPE method (Caillouet et al., 2016). These reconstructions are then used as forcings for the GR6J lumped conceptual rainfall-runoff model and the SIM physically-based distributed hydrological model, in order to derive daily streamflow reconstructions over a set of around 70 reference near-natural catchments. Results show a large multi-decadal streamflow variability over the last 140 years, which is however relatively consistent over France. Empirical estimates of three types of uncertainty - structure of the downscaling method, small-scale internal variability, and hydrological model structure - show roughly equal contributions to the streamflow uncertainty at the annual time scale, with values as high as 20% of the interannual mean. Caillouet, L., Vidal, J.-P., Sauquet, E., and Graff, B.: Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France, Clim. Past, 12, 635-662, doi:10.5194/cp-12-635-2016, 2016. Compo, G. P., Whitaker, J. S., Sardeshmukh, P. D., Matsui, N., Allan, R. J., Yin, X., Gleason, B. E., Vose, R. S., Rutledge, G., Bessemoulin, P., Brönnimann, S., Brunet, M., Crouthamel, R. I., Grant, A. N., Groisman, P. Y., Jones, P. D., Kruk, M. C., Kruger, A. C., Marshall, G. J., Maugeri, M., Mok, H. Y., Nordli, Ø., Ross, T. F., Trigo, R. M., Wang, X. L., Woodruff, S. D., and Worley, S. J.: The Twentieth Century Reanalysis Project. Q. J. R. Meteorol. Soc., 137, 1-28, doi:10.1002/qj.776, 2011. Dayon, G., Boé, J., and Martin, E.: Transferability in the future climate of a statistical downscaling method for precipitation in France, J. Geophys. Res.-Atmos., 120, 1023-1043, doi: 10.1002/2014JD022236, 2015.
Massachusetts reservoir simulation tool—User’s manual
Levin, Sara B.
2016-10-06
IntroductionThe U.S. Geological Survey developed the Massachusetts Reservoir Simulation Tool to examine the effects of reservoirs on natural streamflows in Massachusetts by simulating the daily water balance of reservoirs. The simulation tool was developed to assist environmental managers to better manage water withdrawals in reservoirs and to preserve downstream aquatic habitats.
Computation of major solute concentrations and loads in German rivers using regression analysis.
Steele, T.D.
1980-01-01
Regression functions between concentrations of several inorganic solutes and specific conductance and between specific conductance and stream discharge were derived from intermittent samples collected for 2 rivers in West Germany. These functions, in conjunction with daily records of streamflow, were used to determine monthly and annual solute loadings. -from Author
USDA-ARS?s Scientific Manuscript database
Fecal contamination of surface waters is a critical water quality concern with serious human health implications. Many states use Escherichia coli (E. coli) as an indicator organism for fecal contamination and apply watershed models to develop and support bacterial Total Maximum Daily Loads; howeve...
Ruddy, Barbara C.
2010-01-01
The U.S. Geological Survey (USGS), in cooperation with the Colorado Water Conservation Board, the Upper Colorado River Endangered Fish Recovery Program (UCREFRP), Colorado Division of Water Resources, and City of Craig studied the gain-loss characteristics of Elkhead Creek downstream from Elkhead Reservoir to the confluence with the Yampa River during August through October 2009. Earlier qualitative interpretation of streamflow data downstream from the reservoir indicated that there could be a transit loss of nearly 10 percent. This potential loss could be a significant portion of the releases from Elkhead Reservoir requested by UCREFRP during late summer and early fall for improving critical habitat for endangered fish downstream in the Yampa River. Information on the gain-loss characteristics was needed for the effective management of the reservoir releases. In order to determine streamflow gain-loss characteristics for Elkhead Creek, eight measurement sets were made at four strategic instream sites and at one diversion from August to early October 2009. An additional measurement set was made after the study period during low-flow conditions in November 2009. Streamflow measurements were made using an Acoustic Doppler Velocimeter to provide high accuracy and consistency, especially at low flows. During this study, streamflow ranged from about 5 cubic feet per second up to more than 90 cubic feet per second with step increments in between. Measurements were made at least 24 hours after a change in reservoir release (streamflow) during steady-state conditions. The instantaneous streamflow measurements and the streamflow volume comparisons show the reach of Elkhead Creek immediately downstream from Elkhead Reservoir to the streamflow-gaging station 09246500, Elkhead Creek near Craig, CO, is neither a gaining nor losing reach. The instantaneous measurements immediately downstream from the dam and the combined measurements of Norvell ditch plus streamflow-gaging station 09246500 are mostly within the plus or minus 5-percent measurement error of each other. The variability of data is such that sometimes the streamflow is greater upstream than downstream and sometimes the streamflow is greater downstream than upstream. Streamflow volumes were calculated for multiple time periods as determined by a change in release from the reservoir. Streamflow volumes were greater downstream than upstream for all but one time period. The predominance of greater streamflows downstream is due to the difference between the USGS instantaneous measurements and record computation with the Supervisory Control and Data Acquisition (SCADA) record at the dam. Immediately following an increase in streamflow from the reservoir, the downstream volume was smaller than the upstream volume, but this was an artifact of the traveltime between the two sites and possibly small amounts of water entering the streambank. Traveltimes were shorter at higher streamflows and when streamflow was increasing.
Mississippi River streamflow measurement techniques at St. Louis, Missouri
Wastson, Chester C.; Holmes, Robert R.; Biedenham, David S.
2013-01-01
Streamflow measurement techniques of the Mississippi River at St. Louis have changed through time (1866–present). In addition to different methods used for discrete streamflow measurements, the density and range of discrete measurements used to define the rating curve (stage versus streamflow) have also changed. Several authors have utilized published water surface elevation (stage) and streamflow data to assess changes in the rating curve, which may be attributed to be caused by flood control and/or navigation structures. The purpose of this paper is to provide a thorough review of the available flow measurement data and techniques and to assess how a strict awareness of the limitations of the data may affect previous analyses. It is concluded that the pre-1930s discrete streamflow measurement data are not of sufficient accuracy to be compared with modern streamflow values in establishing long-term trends of river behavior.
Streamflow Modification Through Management of Eastern Forests
James E. Douglass; Wayne T. Swank
1972-01-01
Protection of the water resource was a primary objective in establishing the National Forest System in America, and improving quantity, quality, and timing of streamflow is an important objective of forest management in certain regions of the United States.Effective management of the forest for increased streamflow presupposes that impact of various management...
Bera, Maitreyee; Ortel, Terry W.
2018-01-12
The U.S. Geological Survey, in cooperation with DuPage County Stormwater Management Department, is testing a near real-time streamflow simulation system that assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek and West Branch DuPage River drainage basins in DuPage County, Illinois. As part of this effort, the U.S. Geological Survey maintains a database of hourly meteorological and hydrologic data for use in this near real-time streamflow simulation system. Among these data are next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data, which are retrieved from the North Central River Forecasting Center of the National Weather Service. The DuPage County streamflow simulation system uses these quantitative precipitation forecast data to create streamflow predictions for the two simulated drainage basins. This report discusses in detail how these data are processed for inclusion in the Watershed Data Management files used in the streamflow simulation system for the Salt Creek and West Branch DuPage River drainage basins.
Koltun, G.F.; Holtschlag, David J.
2010-01-01
Bootstrapping techniques employing random subsampling were used with the AFINCH (Analysis of Flows In Networks of CHannels) model to gain insights into the effects of variation in streamflow-gaging-network size and composition on the accuracy and precision of streamflow estimates at ungaged locations in the 0405 (Southeast Lake Michigan) hydrologic subregion. AFINCH uses stepwise-regression techniques to estimate monthly water yields from catchments based on geospatial-climate and land-cover data in combination with available streamflow and water-use data. Calculations are performed on a hydrologic-subregion scale for each catchment and stream reach contained in a National Hydrography Dataset Plus (NHDPlus) subregion. Water yields from contributing catchments are multiplied by catchment areas and resulting flow values are accumulated to compute streamflows in stream reaches which are referred to as flow lines. AFINCH imposes constraints on water yields to ensure that observed streamflows are conserved at gaged locations. Data from the 0405 hydrologic subregion (referred to as Southeast Lake Michigan) were used for the analyses. Daily streamflow data were measured in the subregion for 1 or more years at a total of 75 streamflow-gaging stations during the analysis period which spanned water years 1971–2003. The number of streamflow gages in operation each year during the analysis period ranged from 42 to 56 and averaged 47. Six sets (one set for each censoring level), each composed of 30 random subsets of the 75 streamflow gages, were created by censoring (removing) approximately 10, 20, 30, 40, 50, and 75 percent of the streamflow gages (the actual percentage of operating streamflow gages censored for each set varied from year to year, and within the year from subset to subset, but averaged approximately the indicated percentages).Streamflow estimates for six flow lines each were aggregated by censoring level, and results were analyzed to assess (a) how the size and composition of the streamflow-gaging network affected the average apparent errors and variability of the estimated flows and (b) whether results for certain months were more variable than for others. The six flow lines were categorized into one of three types depending upon their network topology and position relative to operating streamflow-gaging stations. Statistical analysis of the model results indicates that (1) less precise (that is, more variable) estimates resulted from smaller streamflow-gaging networks as compared to larger streamflow-gaging networks, (2) precision of AFINCH flow estimates at an ungaged flow line is improved by operation of one or more streamflow gages upstream and (or) downstream in the enclosing basin, (3) no consistent seasonal trend in estimate variability was evident, and (4) flow lines from ungaged basins appeared to exhibit the smallest absolute apparent percent errors (APEs) and smallest changes in average APE as a function of increasing censoring level. The counterintuitive results described in item (4) above likely reflect both the nature of the base-streamflow estimate from which the errors were computed and insensitivity in the average model-derived estimates to changes in the streamflow-gaging-network size and composition. Another analysis demonstrated that errors for flow lines in ungaged basins have the potential to be much larger than indicated by their APEs if measured relative to their true (but unknown) flows. “Missing gage” analyses, based on examination of censoring subset results where the streamflow gage of interest was omitted from the calibration data set, were done to better understand the true error characteristics for ungaged flow lines as a function of network size. Results examined for 2 water years indicated that the probability of computing a monthly streamflow estimate within 10 percent of the true value with AFINCH decreased from greater than 0.9 at about a 10-percent network-censoring level to less than 0.6 as the censoring level approached 75 percent. In addition, estimates for typically dry months tended to be characterized by larger percent errors than typically wetter months.
Event-scale power law recession analysis: quantifying methodological uncertainty
NASA Astrophysics Data System (ADS)
Dralle, David N.; Karst, Nathaniel J.; Charalampous, Kyriakos; Veenstra, Andrew; Thompson, Sally E.
2017-01-01
The study of single streamflow recession events is receiving increasing attention following the presentation of novel theoretical explanations for the emergence of power law forms of the recession relationship, and drivers of its variability. Individually characterizing streamflow recessions often involves describing the similarities and differences between model parameters fitted to each recession time series. Significant methodological sensitivity has been identified in the fitting and parameterization of models that describe populations of many recessions, but the dependence of estimated model parameters on methodological choices has not been evaluated for event-by-event forms of analysis. Here, we use daily streamflow data from 16 catchments in northern California and southern Oregon to investigate how combinations of commonly used streamflow recession definitions and fitting techniques impact parameter estimates of a widely used power law recession model. Results are relevant to watersheds that are relatively steep, forested, and rain-dominated. The highly seasonal mediterranean climate of northern California and southern Oregon ensures study catchments explore a wide range of recession behaviors and wetness states, ideal for a sensitivity analysis. In such catchments, we show the following: (i) methodological decisions, including ones that have received little attention in the literature, can impact parameter value estimates and model goodness of fit; (ii) the central tendencies of event-scale recession parameter probability distributions are largely robust to methodological choices, in the sense that differing methods rank catchments similarly according to the medians of these distributions; (iii) recession parameter distributions are method-dependent, but roughly catchment-independent, such that changing the choices made about a particular method affects a given parameter in similar ways across most catchments; and (iv) the observed correlative relationship between the power-law recession scale parameter and catchment antecedent wetness varies depending on recession definition and fitting choices. Considering study results, we recommend a combination of four key methodological decisions to maximize the quality of fitted recession curves, and to minimize bias in the related populations of fitted recession parameters.
Restoring Natural Streamflow Variability by Modifying Multi-purpose Reservoir Operation
NASA Astrophysics Data System (ADS)
Shiau, J.
2010-12-01
Multi-purpose reservoirs typically provide benefits of water supply, hydroelectric power, and flood mitigation. Hydroelectric power generations generally do not consume water. However, temporal distribution of downstream flows is highly changed due to hydro-peaking effects. Associated with offstream diversion of water supplies for municipal, industrial, and agricultural requirements, natural streamflow characteristics of magnitude, duration, frequency, timing, and rate of change is significantly altered by multi-purpose reservoir operation. Natural flow regime has long been recognized a master factor for ecosystem health and biodiversity. Restoration of altered flow regime caused by multi-purpose reservoir operation is the main objective of this study. This study presents an optimization framework that modifying reservoir operation to seeking balance between human and environmental needs. The methodology presented in this study is applied to the Feitsui Reservoir, located in northern Taiwan, with main purpose of providing stable water-supply and auxiliary purpose of electricity generation and flood-peak attenuation. Reservoir releases are dominated by two decision variables, i.e., duration of water releases for each day and percentage of daily required releases within the duration. The current releasing policy of the Feitsui Reservoir releases water for water-supply and hydropower purposes during 8:00 am to 16:00 pm each day and no environmental flows releases. Although greater power generation is obtained by 100% releases distributed within 8-hour period, severe temporal alteration of streamflow is observed downstream of the reservoir. Modifying reservoir operation by relaxing these two variables and reserve certain ratio of streamflow as environmental flow to maintain downstream natural variability. The optimal reservoir releasing policy is searched by the multi-criterion decision making technique for considering reservoir performance in terms of shortage ratio and power generation and downstream hydrologic alterations in terms of ecological relevant indicators. The results show that the proposed methodology can mitigate hydro-peaking effects on natural variability, while maintains efficient reservoir operation.
NASA Astrophysics Data System (ADS)
Ravindranath, A.; Devineni, N.
2017-12-01
Studies have shown that streamflow behavior and dynamics have a significant link with climate and climate variability. Patterns of persistent regime behavior from extended streamflow records in many watersheds justify investigating large-scale climate mechanisms as potential drivers of hydrologic regime behavior and streamflow variability. Understanding such streamflow-climate relationships is crucial to forecasting/simulation systems and the planning and management of water resources. In this study, hidden Markov models are used with reconstructed streamflow to detect regime-like behaviors - the hidden states - and state transition phenomena. Individual extreme events and their spatial variability across the basin are then verified with the identified states. Wavelet analysis is performed to examine the signals over time in the streamflow records. Joint analyses of the climatic data in the 20th century and the identified states are undertaken to better understand the hydroclimatic connections within the basin as well as important teleconnections that influence water supply. Compositing techniques are used to identify atmospheric circulation patterns associated with identified states of streamflow. The grouping of such synoptic patterns and their frequency are then examined. Sliding time-window correlation analysis and cross-wavelet spectral analysis are performed to establish the synchronicity of basin flows to the identified synoptic and teleconnection patterns. The Missouri River Basin (MRB) is examined in this study, both as a means of better understanding the synoptic climate controls in this important watershed and as a case study for the techniques developed here. Initial wavelet analyses of reconstructed streamflow at major gauges in the MRB show multidecadal cycles in regime behavior.
River and Reservoir Operations Model, Truckee River basin, California and Nevada, 1998
Berris, Steven N.; Hess, Glen W.; Bohman, Larry R.
2001-01-01
The demand for all uses of water in the Truckee River Basin, California and Nevada, commonly is greater than can be supplied. Storage reservoirs in the system have a maximum effective total capacity equivalent to less than two years of average river flows, so longer-term droughts can result in substantial water-supply shortages for irrigation and municipal users and may stress fish and wildlife ecosystems. Title II of Public Law (P.L.) 101-618, the Truckee?Carson?Pyramid Lake Water Rights Settlement Act of 1990, provides a foundation for negotiating and developing operating criteria, known as the Truckee River Operating Agreement (TROA), to balance interstate and interbasin allocation of water rights among the many interests competing for water from the Truckee River. In addition to TROA, the Truckee River Water Quality Settlement Agreement (WQSA), signed in 1996, provides for acquisition of water rights to resolve water-quality problems during low flows along the Truckee River in Nevada. Efficient execution of many of the planning, management, or environmental assessment requirements of TROA and WQSA will require detailed water-resources data coupled with sound analytical tools. Analytical modeling tools constructed and evaluated with such data could help assess effects of alternative operational scenarios related to reservoir and river operations, water-rights transfers, and changes in irrigation practices. The Truckee?Carson Program of the U.S. Geological Survey, to support U.S. Department of the Interior implementation of P.L. 101-618, is developing a modeling system to support efficient water-resources planning, management, and allocation. The daily operations model documented herein is a part of the modeling system that includes a database management program, a graphical user interface program, and a program with modules that simulate river/reservoir operations and a variety of hydrologic processes. The operations module is capable of simulating lake/ reservoir and river operations including diversion of Truckee River water to the Truckee Canal for transport to the Carson River Basin. In addition to the operations and streamflow-routing modules, the modeling system is structured to allow integration of other modules, such as water-quality and precipitation-runoff modules. The USGS Truckee River Basin operations model was designed to provide simulations that allow comparison of the effects of alternative management practices or allocations on streamflow or reservoir storages in the Truckee River Basin over long periods of time. Because the model was not intended to reproduce historical streamflow or reservoir storage values, a traditional calibration that includes statistical comparisons of observed and simulated values would be problematic with this model and database. This report describes a chronology and background of decrees, agreements, and laws that affect Truckee River operational practices; the construction of the Truckee River daily operations model; the simulation of Truckee River Basin operations, both current and proposed under the draft TROA and WQSA; and suggested model improvements and limitations. The daily operations model uses Hydrological Simulation Program?FORTRAN (HSPF) to simulate flow-routing and reservoir and river operations. The operations model simulates reservoir and river operations that govern streamflow in the Truckee River from Lake Tahoe to Pyramid Lake, including diversions through the Truckee Canal to Lahontan Reservoir in the Carson River Basin. A general overview is provided of daily operations and their simulation. Supplemental information that documents the extremely complex operating rules simulated by the model is available.
Evaluation of meteorological drought indices for streamflow modeling
NASA Astrophysics Data System (ADS)
Haslinger, Klaus; Koffler, Daniel; Blöschl, Günter; Parajka, Juraj; Schöner, Wolfgang; Laaha, Gregor
2013-04-01
In this paper we present a comprehensive analysis which aims to link various meteorological drought indices to streamflow data in Austria and Central Europe. The motivation arises from the fact that discharge time series are usually shorter (beginning in the middle of the 20th century) than meteorological time series. In the European Greater Alpine Region we are fortunate of having a gridded dataset for temperature and solid/liquid precipitation on a monthly time scale that spans from 1801 to 2003 - the HISTALP database. If there is a link between meteorological drought indices and streamflow, a reconstruction of streamflow, with emphasis on low flows, will be possible for the last 200 years. As meteorological drought indices the self-calibrating Palmer Drought Severity Index (scPDSI), the Standardized Precipitation Index (SPI) on various time scales as well as the moisture departure value d from the soil moisture modeling procedure of the scPDSI are used. The analysis focuses on three aspects, (i) temporal co-evolution of meteorological drought and streamflow indices, (ii) their at-site correlation at gauges, and (iii) their regional correlation structure depending on different climate and catchment conditions. The whole analysis is stratified by seasons, what allows us to explore the strength of the link for the dominant low flow generating process. In order to show a connection between these indices and streamflow data the drought event of 2003 serves as a reference. We will show the temporal evolution of the drought indices parallel to streamflow indices like MQ, Q95 and MAM(7) for the period from summer 2002, which encompasses a major flood event in the northern parts of Austria, to fall 2003 when the streamflow drought was most severe. This is carried out for different regions in Austria, representing different climatic and soil-specific characteristics. To quantify the link between drought indices and streamflow indices for the whole time series from 1801-2003, rank correlations are calculated, stratified by three different approaches. First, as mentioned above, a regional assessment is carried out. Second, the correlations are calculated separately for seasons (DJF, MAM, JJA, and SON). Third, different quantiles of the streamflow-data, ranging from Q50 to Q95, will be correlated with the drought indices. The results show that there is definitely a strong connection between the MQ and the scPDSI in one target region in the Northwest of Austria. The results are encouraging for further attempts to reconstruct extreme low flow events from meteorological data only. A statistical model for linking meteorological drought indices with streamflow under dry conditions is currently under development and results will be presented in the near future.
Hoard, C.J.
2010-01-01
The U.S. Geological Survey is evaluating water availability and use within the Great Lakes Basin. This is a pilot effort to develop new techniques and methods to aid in the assessment of water availability. As part of the pilot program, a regional groundwater-flow model for the Lake Michigan Basin was developed using SEAWAT-2000. The regional model was used as a framework for assessing local-scale water availability through grid-refinement techniques. Two grid-refinement techniques, telescopic mesh refinement and local grid refinement, were used to illustrate the capability of the regional model to evaluate local-scale problems. An intermediate model was developed in central Michigan spanning an area of 454 square miles (mi2) using telescopic mesh refinement. Within the intermediate model, a smaller local model covering an area of 21.7 mi2 was developed and simulated using local grid refinement. Recharge was distributed in space and time using a daily output from a modified Thornthwaite-Mather soil-water-balance method. The soil-water-balance method derived recharge estimates from temperature and precipitation data output from an atmosphere-ocean coupled general-circulation model. The particular atmosphere-ocean coupled general-circulation model used, simulated climate change caused by high global greenhouse-gas emissions to the atmosphere. The surface-water network simulated in the regional model was refined and simulated using a streamflow-routing package for MODFLOW. The refined models were used to demonstrate streamflow depletion and potential climate change using five scenarios. The streamflow-depletion scenarios include (1) natural conditions (no pumping), (2) a pumping well near a stream; the well is screened in surficial glacial deposits, (3) a pumping well near a stream; the well is screened in deeper glacial deposits, and (4) a pumping well near a stream; the well is open to a deep bedrock aquifer. Results indicated that a range of 59 to 50 percent of the water pumped originated from the stream for the shallow glacial and deep bedrock pumping scenarios, respectively. The difference in streamflow reduction between the shallow and deep pumping scenarios was compensated for in the deep well by deriving more water from regional sources. The climate-change scenario only simulated natural conditions from 1991-2044, so there was no pumping stress simulated. Streamflows were calculated for the simulated period and indicated that recharge over the period generally increased from the start of the simulation until approximately 2017, and decreased from then to the end of the simulation. Streamflow was highly correlated with recharge so that the lowest streamflows occurred in the later stress periods of the model when recharge was lowest.
Wavelet-linear genetic programming: A new approach for modeling monthly streamflow
NASA Astrophysics Data System (ADS)
Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur
2017-06-01
The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.
Lambing, John H.; Sando, Steven K.
2008-01-01
The purpose of this report is to present estimated daily and annual loads of suspended sediment and selected trace elements for water years 2004-07 at two sites upstream and one site downstream from Milltown Reservoir. Milltown Reservoir is a National Priorities List Superfund site in the upper Clark Fork basin of western Montana where sediments enriched in trace elements from historical mining and ore processing have been deposited since the construction of Milltown Dam in 1907. The estimated loads were used to quantify annual net gains and losses (mass balance) of suspended sediment and trace elements within Milltown Reservoir before and after June 1, 2006, which was the start of Stage 1 of a permanent drawdown of the reservoir in preparation for removal of Milltown Dam. This study was done in cooperation with the U.S. Environmental Protection Agency. Daily loads of suspended sediment were estimated for water years 2004-07 by using either high-frequency sampling as part of daily sediment monitoring or regression equations relating suspended-sediment discharge to streamflow. Daily loads of unfiltered-recoverable arsenic, cadmium, copper, iron, lead, manganese, and zinc were estimated by using regression equations relating trace-element discharge to suspended-sediment discharge. Regression equations were developed from data for eriodic water-quality samples collected during water years 2004-07. The equations were applied to daily records of either streamflow or suspended-sediment discharge to produce estimated daily loads. Variations in daily suspended-sediment and trace-element loads generally coincided with variations in streamflow. For most of the period before June 1, 2006, differences in daily loads transported to and from Milltown Reservoir were minor or indicated small amounts of deposition; however, losses of suspended sediment and trace elements from the reservoir occurred during temporary drawdowns in July-August 2004 and October-December 2005. After the start of Stage 1 of the permanent drawdown on June 1, 2006, losses of suspended sediment and trace elements from the reservoir persisted for all streamflow conditions during the entire interval of the Stage 1 drawdown (June 1, 2006-September 30, 2007) within the study period. Estimated daily loads of suspended sediment and trace elements were summed for each year to produce estimated annual loads used to determine the annual net gains (deposition) or losses (erosion) of each constituent within Milltown Reservoir during water years 2004-07. During water year 2004, there was an annual net gain of suspended sediment in the reservoir. The annual net gains and losses of trace elements were inconsistent in water year 2004, with gains occurring for arsenic ad iron, but losses occurring for cadmium, copper, lead, manganese, and zinc. In water year 2005, there were annual net gains of suspended sediment and all the trace elements within the reservoir. In water year 2006, there were annual net losses of all constituents from the reservoir, likely as the result of sediment erosion from the reservoir during both a temporary drawdown in October-December 2005 and Stage 1 of the permanent drawdown that continued after June 1, 2006. In water year 2007, when the Stage 1 drawdown was in effect for the entire year, there were large annual net losses of suspended sediment and trace elements from the reservoir. The annual net losses of constituents from Milltown Reservoir in water year 2007 were the largest of any year during the 2004-07 study period. In water year 2007, the annual net loss of suspended sediment from the reservoir was 130,000 tons, which was more than double (about 222 percent) the combined inflow to the reservoir. The largest annual net losses of trace elements in water year 2007, in percent of the combined inflow to the reservoir, occurred for cadmium, copper, lead, and zinc-about 190 percent for cadmium, 170 percent for copper, 150 percent for lead, and 238 p
Simulation of groundwater and surface-water flow in the upper Deschutes Basin, Oregon
Gannett, Marshall W.; Lite, Kenneth E.; Risley, John C.; Pischel, Esther M.; La Marche, Jonathan L.
2017-10-20
This report describes a hydrologic model for the upper Deschutes Basin in central Oregon developed using the U.S. Geological Survey (USGS) integrated Groundwater and Surface-Water Flow model (GSFLOW). The upper Deschutes Basin, which drains much of the eastern side of the Cascade Range in Oregon, is underlain by large areas of permeable volcanic rock. That permeability, in combination with the large annual precipitation at high elevations, results in a substantial regional aquifer system and a stream system that is heavily groundwater dominated.The upper Deschutes Basin is also an area of expanding population and increasing water demand for public supply and agriculture. Surface water was largely developed for agricultural use by the mid-20th century, and is closed to additional appropriations. Consequently, water users look to groundwater to satisfy the growing demand. The well‑documented connection between groundwater and the stream system, and the institutional and legal restrictions on streamflow depletion by wells, resulted in the Oregon Water Resources Department (OWRD) instituting a process whereby additional groundwater pumping can be permitted only if the effects to streams are mitigated, for example, by reducing permitted surface-water diversions. Implementing such a program requires understanding of the spatial and temporal distribution of effects to streams from groundwater pumping. A groundwater model developed in the early 2000s by the USGS and OWRD has been used to provide insights into the distribution of streamflow depletion by wells, but lacks spatial resolution in sensitive headwaters and spring areas.The integrated model developed for this project, based largely on the earlier model, has a much finer grid spacing allowing resolution of sensitive headwater streams and important spring areas, and simulates a more complete set of surface processes as well as runoff and groundwater flow. In addition, the integrated model includes improved representation of subsurface geology and explicitly simulates the effects of hydrologically important fault zones not included in the previous model.The upper Deschutes Basin GSFLOW model was calibrated using an iterative trial and error approach using measured water-level elevations (water levels) from 800 wells, 144 of which have time series of 10 or more measurements. Streamflow was calibrated using data from 21 gage locations. At 14 locations where measured flows are heavily influenced by reservoir operations and irrigation diversions, so called “naturalized” flows, with the effects of reservoirs and diversion removed, developed by the Bureau of Reclamation, were used for calibration. Surface energy and moisture processes such as solar radiation, snow accumulation and melting, and evapotranspiration were calibrated using national datasets as well as data from long-term measurement sites in the basin. The calibrated Deschutes GSFLOW model requires daily precipitation, minimum and maximum air temperature data, and monthly data describing groundwater pumping and artificial recharge from leaking irrigation canals (which are a significant source of groundwater recharge).The calibrated model simulates the geographic distribution of hydraulic head over the 5,000 ft range measured in the basin, with a median absolute residual of about 53 ft. Temporal variations in head resulting from climate cycles, pumping, and canal leakage are well simulated over the model area. Simulated daily streamflow matches gaged flows or calculated naturalized flows for streams including the Crooked and Metolius Rivers, and lower parts of the mainstem Deschutes River. Seasonal patterns of runoff are less well fit in some upper basin streams. Annual water balances of streamflow are good over most of the model domain. Model fit and overall capabilities are appropriate for the objectives of the project.The integrated model results confirm findings from other studies and models indicating that most streamflow in the upper Deschutes Basin comes directly from groundwater discharge. The integrated model provides additional insights about the components of streamflow including direct groundwater discharge to streams, interflow, groundwater discharge to the land surface (Dunnian flow), and direct runoff (Hortonian flow). The new model provides improved capability for exploring the timing and distribution of streamflow capture by wells, and the hydrologic response to changes in other external stresses such as canal operation, irrigation, and drought. Because the model uses basic meteorological data as the primary input; and simulates surface energy and moisture balances, groundwater recharge and flow, and all components of streamflow; it is well suited for exploring the hydrologic response to climate change, although no such simulations are included in this report.The model was developed as a tool for future application; however, example simulations are provided in this report. In the example simulations, the model is used to explore the influence of well location and geologic structure on stream capture by pumping wells. Wells were simulated at three locations within a 12-mi area close to known groundwater discharge areas and crossed by a regional fault zone. Simulations indicate that the magnitude and timing of stream capture from pumping is largely controlled by the geographic location of the wells, but that faults can have a large influence on the propagation of pumping stresses.
Improving Streamflow Forecasts Using Predefined Sea Surface Temperature
NASA Astrophysics Data System (ADS)
Kalra, A.; Ahmad, S.
2011-12-01
With the increasing evidence of climate variability, water resources managers in the western United States are faced with greater challenges of developing long range streamflow forecast. This is further aggravated by the increases in climate extremes such as floods and drought caused by climate variability. Over the years, climatologists have identified several modes of climatic variability and their relationship with streamflow. These climate modes have the potential of being used as predictor in models for improving the streamflow lead time. With this as the motivation, the current research focuses on increasing the streamflow lead time using predefine climate indices. A data driven model i.e. Support Vector Machine (SVM) based on the statistical learning theory is used to predict annual streamflow volume 3-year in advance. The SVM model is a learning system that uses a hypothesis space of linear functions in a Kernel induced higher dimensional feature space, and is trained with a learning algorithm from the optimization theory. Annual oceanic-atmospheric indices, comprising of Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), El Niño-Southern Oscillations (ENSO), and a new Sea Surface Temperature (SST) data set of "Hondo" Region for a period of 1906-2005 are used to generate annual streamflow volumes. The SVM model is applied to three gages i.e. Cisco, Green River, and Lees Ferry in the Upper Colorado River Basin in the western United States. Based on the performance measures the model shows very good forecasts, and the forecast are in good agreement with measured streamflow volumes. Previous research has identified NAO and ENSO as main drivers for extending streamflow forecast lead-time in the UCRB. Inclusion of "Hondo Region" SST information further improve the model's forecasting ability. The overall results of this study revealed that the annual streamflow of the UCRB is significantly influenced by predefine climate modes and the proposed SVM modeling technique incorporating oceanic-atmospheric oscillations is expected to be useful to water managers in the long-term management of the water resources within the UCRB.
NASA Astrophysics Data System (ADS)
Sumargo, E.; Cayan, D. R.
2016-12-01
Solar radiation (S) is a key driver of snowmelt and water fluxes, but its effect varies depending on time of year and also upon the hydrological character (e.g., dry or wet) of a given year. In this study, we use remote sensed S to quantify cloudiness variability and its effects on snowmelt and streamflow across mountain basins in the western U.S. We utilize 20 years (1996-2015) of NASA/NOAA GOES-derived cloud albedo (αcloud) at 4-km daily samples to estimate S over relatively fine spatial and temporal resolution during Feb-Jul when snowmelt is most active. Daily snow water equivalent (SWE) records from >200 CDEC and SNOTEL locations, along with daily stream discharge (Q) from USGS HCDN records are used to compute day-to-day changes (dSWE and dQ). Multivariate linear regression models of dSWE and dQ are constructed for each month, wherein αcloud from several days prior up to the concurrent day are the predictors. In Feb-May, the results show predominantly negative correlations between αcloud and dSWE, confirming the cloud-shading effect in preserving snowpack and reducing runoff. The influence of cloudiness variability on snowpack, denoted by the coefficient of determination (R2) between the measured and modeled dSWE, amounts 4%-73% over Feb-Jul, averaging 20% in the northwest and 26% in the southwest. The dQ case exhibits similar patterns, but lower explained variance. In Jun-Jul, most locations in both dSWE and dQ cases display positive correlation but with diminished R2, presumably reflecting the drying effect of summertime. In comparing dry and wet years, the R2 is somewhat higher in dry years, suggesting that the importance of cloud cover and the associated solar insolation variability is higher in cases with greater influence from other hydrological factors, including heavy precipitation events and fluctuations associated with a higher snowpack.
NASA Astrophysics Data System (ADS)
Hävermark, Saga; Santos Ferreira, Carla Sofia; Kalantari, Zahra; Di Baldassarre, Giuliano
2016-04-01
Many river basis around the world are rapidly changing together with societal development. Such developments may involve changes in land use, which in turn affect the surrounding environment in various ways. Since the start of industrialisation, the urban areas have extended worldwide. Urbanization can influence hydrological processes by decreasing evapotranspiration, infiltration and groundwater recharge as well as increasing runoff and overland flow. It is therefore of uttermost importance to understand the relationship between land use and hydrology. Although several studies have been investigating the impacts of urbanization on streamflow over the last decades, less is known on how urbanization affects hydrological processes in peri-urban areas, characterized by a complex mosaic of different land uses. This study aimed to model the impact of land use changes, specifically urbanization and commercial forest plantation, on the hydrological responses of the small Ribeira dos Covões peri-urban catchment (6,2 km2) located in central Portugal. The catchment has undergone rapid land use changes between 1958 and 2012 associated with the conversion of agricultural fields (cover area decreased from 48% to 4%) into woodland and urban areas, which increased from 44% to 56% and from 8% to 40%, respectively. For the study, the fully-distributed, physically-based modelling system MIKE SHE was used. The model was designed to examine both how past land use changes might have affected the streamflow and to investigate the impacts on hydrology of possible future scenarios, including a 50 %, 60 % and 70 % urban cover. To this end, a variety of data including daily rainfall since 1958 and forward, daily potential evapotranspiration from 2009 to 2013, monthly temperature averages from 1971 to 2013, land use for the years 1958, 1973, 1979, 1990, 1995, 2002, 2007 and 2012, streamflow from the hydrological years 2008 to 2013, catchment topography and soil types were used. The model was calibrated for the hydrological years 2008 to 2010 and validated for the three following years using streamflow data. The impact of future land use changes was analysed by investigating the impact of the size and location of the urban areas within the catchment. Modelling results are expected to support the decision making process in planning and developing new urban areas.
Deep groundwater mediates streamflow response to climate warming in the Oregon Cascades
Christina Tague; Gordon Grant; Mike Farrell; Janet Choate; Anne Jefferson
2008-01-01
Recent studies predict that projected climate change will lead to significant reductions in summer streamflow in the mountainous regions of the Western United States. Hydrologic modeling directed at quantifying these potential changes has focused on the magnitude and timing of spring snowmelt as the key control on the spatial temporal pattern of summer streamflow. We...
Norton, Parker A.; Anderson, Mark T.; Stamm, John F.
2014-01-01
The Missouri River and its tributaries are an important resource that serve multiple uses including agriculture, energy, recreation, and municipal water supply. Understanding historical streamflow characteristics provides relevant guidance to adaptive management of these water resources. Streamflow records in the Missouri River watershed were examined for trends in time series of annual, seasonal, and monthly streamflow. A total of 227 streamgages having continuous observational records for water years 1960–2011 were examined. Kendall’s tau nonparametric test was used to determine statistical significance of trends in annual, seasonal, and monthly streamflow. A trend was considered statistically significant for a probability value less than or equal to 0.10 that the Kendall’s tau value equals zero. Significant trends in annual streamflow were indicated for 101 out of a total of 227 streamgages. The Missouri River watershed was divided into six watershed regions and trends within regions were examined. The western and the southern parts of the Missouri River watershed had downward trends in annual streamflow (56 streamgages), whereas the eastern part of the watershed had upward trends in streamflow (45 streamgages). Seasonal and monthly streamflow trends reflected prevailing annual streamflow trends within each watershed region.
Using oceanic-atmospheric oscillations for long lead time streamflow forecasting
NASA Astrophysics Data System (ADS)
Kalra, Ajay; Ahmad, Sajjad
2009-03-01
We present a data-driven model, Support Vector Machine (SVM), for long lead time streamflow forecasting using oceanic-atmospheric oscillations. The SVM is based on statistical learning theory that uses a hypothesis space of linear functions based on Kernel approach and has been used to predict a quantity forward in time on the basis of training from past data. The strength of SVM lies in minimizing the empirical classification error and maximizing the geometric margin by solving inverse problem. The SVM model is applied to three gages, i.e., Cisco, Green River, and Lees Ferry in the Upper Colorado River Basin in the western United States. Annual oceanic-atmospheric indices, comprising Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), and El Nino-Southern Oscillations (ENSO) for a period of 1906-2001 are used to generate annual streamflow volumes with 3 years lead time. The SVM model is trained with 86 years of data (1906-1991) and tested with 10 years of data (1992-2001). On the basis of correlation coefficient, root means square error, and Nash Sutcliffe Efficiency Coefficient the model shows satisfactory results, and the predictions are in good agreement with measured streamflow volumes. Sensitivity analysis, performed to evaluate the effect of individual and coupled oscillations, reveals a strong signal for ENSO and NAO indices as compared to PDO and AMO indices for the long lead time streamflow forecast. Streamflow predictions from the SVM model are found to be better when compared with the predictions obtained from feedforward back propagation artificial neural network model and linear regression.
Knight, Rodney R.; Gregory, M. Brian; Wales, Amy K.
2008-01-01
Analysis of hydrologic time series and fish community data across the Tennessee River Valley identified three hydrologic metrics essential to habitat suitability and food availability for insectivorous fish communities in streams of the Tennessee River Valley: constancy (flow stability or temporal invariance), frequency of moderate flooding (frequency of habitat disturbance), and rate of streamflow recession. Initial datasets included 1100 fish community sites and 300 streamgages. Reduction of these datasets to sites with coexisting data yielded 33 sites with streamflow and fish community data for analysis. Identification of critical hydrologic metrics was completed using a multivariate correlation procedure that maximizes the rank correlation between the hydrologic metrics and fish community resemblance matrices. Quantile regression was used to define thresholds of potential ranges of insectivore scores for given values of the hydrologic metrics. Increased values of constancy and insectivore scores were positively correlated. Constancy of streamflow maintains wetted perimeter, which is important for providing habitat for fish spawning and increased surface area for invertebrate colonization and reproduction. Site scores for insectivorous fish increased as the frequency of moderate flooding (3 times the median annual streamflow) decreased, suggesting that insectivorous fish communities respond positively to less frequent disturbance and a more stable habitat. Increased streamflow recession rates were associated with decreased insectivore scores. Increased streamflow recession can strand fish in pools and other areas that are disconnected from flowing water and remove invertebrates as food sources that were suspended during high-streamflow events.
Estimating Precipitation Input to a Watershed by Combining Gauge and Radar Derived Observations
NASA Astrophysics Data System (ADS)
Ercan, M. B.; Goodall, J. L.
2011-12-01
One challenge in creating an accurate watershed model is obtaining estimates of precipitation intensity over the watershed area. While precipitation measurements are generally available from gauging stations and radar instruments, both of these approaches for measuring precipitation have strengths and weakness. A typical way of addressing this challenge is to use gauged precipitation estimates to calibrate radar based estimates, however this study proposes a slightly different approach in which the optimal daily precipitation value is selected from either the gauged or the radar estimates based on the observed streamflow for that day. Our proposed approach is perhaps most relevant for cases of modeling watersheds that do not have a nearby precipitation gauge, or for regions that experience convective storms that are often highly spatially variable. Using the Eno River watershed located in Orange County, NC, three different precipitation datasets were created to predict streamflow at the watershed outlet for the time period 2005-2010 using the Soil and Water Assessment Tool (SWAT): (1) estimates based on only precipitation gauging stations, (2) estimates based only on gauged-corrected radar observations, and (3) the combination of precipitation estimates from the gauge and radar data determined using our proposed approach. The results show that the combined precipitation approach significantly improves streamflow predictions (Nash-Sutcliffe Coefficient, E = 0.66) when compared to the gauged estimates alone (E = 0.47) and the radar based estimates alone (E = 0.45). Our study was limited to one watershed, therefore additional studies are needed to control for factors such as climate, ecology, and hydrogeology that will likely influence the results of the analysis.
Analysis of stochastic characteristics of the Benue River flow process
NASA Astrophysics Data System (ADS)
Otache, Martins Y.; Bakir, Mohammad; Li, Zhijia
2008-05-01
Stochastic characteristics of the Benue River streamflow process are examined under conditions of data austerity. The streamflow process is investigated for trend, non-stationarity and seasonality for a time period of 26 years. Results of trend analyses with Mann-Kendall test show that there is no trend in the annual mean discharges. Monthly flow series examined with seasonal Kendall test indicate the presence of positive change in the trend for some months, especially the months of August, January, and February. For the stationarity test, daily and monthly flow series appear to be stationary whereas at 1%, 5%, and 10% significant levels, the stationarity alternative hypothesis is rejected for the annual flow series. Though monthly flow appears to be stationary going by this test, because of high seasonality, it could be said to exhibit periodic stationarity based on the seasonality analysis. The following conclusions are drawn: (1) There is seasonality in both the mean and variance with unimodal distribution. (2) Days with high mean also have high variance. (3) Skewness coefficients for the months within the dry season period are greater than those of the wet season period, and seasonal autocorrelations for streamflow during dry season are generally larger than those of the wet season. Precisely, they are significantly different for most of the months. (4) The autocorrelation functions estimated “over time” are greater in the absolute value for data that have not been deseasonalised but were initially normalised by logarithmic transformation only, while autocorrelation functions for i = 1, 2, ..., 365 estimated “over realisations” have their coefficients significantly different from other coefficients.
Medalie, Laura; Hirsch, Robert M.; Archfield, Stacey A.
2012-01-01
The U.S. Geological Survey evaluated 20 years of total phosphorus (P) and total nitrogen (N) concentration data for 18 Lake Champlain tributaries using a new statistical method based on weighted regressions to estimate daily concentration and flux histories based on discharge, season, and trend as explanatory variables. The use of all the streamflow discharge values for a given date in the record, in a process called "flow-normalization," removed the year-to-year variation due to streamflow and generated a smooth time series from which trends were calculated. This approach to data analysis can be of great value to evaluations of the success of restoration efforts because it filters out the large random fluctuations in the flux that are due to the temporal variability in streamflow. Results for the full 20 years of record showed a mixture of upward and downward trends for concentrations and yields of P and N. When the record was broken into two 10-year periods, for many tributaries, the more recent period showed a reversal in N from upward to downward trends and a similar reversal or reduction in magnitude of upward trends for P. Some measures of P and N concentrations and yields appear to be related to intensity of agricultural activities, point-source loads of P, or population density. Total flow-normalized P flux aggregated from the monitored tributaries showed a decrease of 30 metric tons per year from 1991 to 2009, which is about 15% of the targeted reduction established by the operational management plan for the Lake Champlain Basin.
NASA Astrophysics Data System (ADS)
Lee, H.; Seo, D.-J.; Liu, Y.; Koren, V.; McKee, P.; Corby, R.
2012-01-01
State updating of distributed rainfall-runoff models via streamflow assimilation is subject to overfitting because large dimensionality of the state space of the model may render the assimilation problem seriously under-determined. To examine the issue in the context of operational hydrology, we carry out a set of real-world experiments in which streamflow data is assimilated into gridded Sacramento Soil Moisture Accounting (SAC-SMA) and kinematic-wave routing models of the US National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM) with the variational data assimilation technique. Study basins include four basins in Oklahoma and five basins in Texas. To assess the sensitivity of data assimilation performance to dimensionality reduction in the control vector, we used nine different spatiotemporal adjustment scales, where state variables are adjusted in a lumped, semi-distributed, or distributed fashion and biases in precipitation and potential evaporation (PE) are adjusted hourly, 6-hourly, or kept time-invariant. For each adjustment scale, three different streamflow assimilation scenarios are explored, where streamflow observations at basin interior points, at the basin outlet, or at both interior points and the outlet are assimilated. The streamflow assimilation experiments with nine different basins show that the optimum spatiotemporal adjustment scale varies from one basin to another and may be different for streamflow analysis and prediction in all of the three streamflow assimilation scenarios. The most preferred adjustment scale for seven out of nine basins is found to be the distributed, hourly scale, despite the fact that several independent validation results at this adjustment scale indicated the occurrence of overfitting. Basins with highly correlated interior and outlet flows tend to be less sensitive to the adjustment scale and could benefit more from streamflow assimilation. In comparison to outlet flow assimilation, interior flow assimilation at any adjustment scale produces streamflow predictions with a spatial correlation structure more consistent with that of streamflow observations. We also describe diagnosing the complexity of the assimilation problem using the spatial correlation information associated with the streamflow process, and discuss the effect of timing errors in a simulated hydrograph on the performance of the data assimilation procedure.
NASA Astrophysics Data System (ADS)
Nguyen, Hung T. T.; Galelli, Stefano
2018-03-01
Catchment dynamics is not often modeled in streamflow reconstruction studies; yet, the streamflow generation process depends on both catchment state and climatic inputs. To explicitly account for this interaction, we contribute a linear dynamic model, in which streamflow is a function of both catchment state (i.e., wet/dry) and paleoclimatic proxies. The model is learned using a novel variant of the Expectation-Maximization algorithm, and it is used with a paleo drought record—the Monsoon Asia Drought Atlas—to reconstruct 406 years of streamflow for the Ping River (northern Thailand). Results for the instrumental period show that the dynamic model has higher accuracy than conventional linear regression; all performance scores improve by 45-497%. Furthermore, the reconstructed trajectory of the state variable provides valuable insights about the catchment history—e.g., regime-like behavior—thereby complementing the information contained in the reconstructed streamflow time series. The proposed technique can replace linear regression, since it only requires information on streamflow and climatic proxies (e.g., tree-rings, drought indices); furthermore, it is capable of readily generating stochastic streamflow replicates. With a marginal increase in computational requirements, the dynamic model brings more desirable features and value to streamflow reconstructions.
Contribution of human and climate change impacts to changes in streamflow of Canada.
Tan, Xuezhi; Gan, Thian Yew
2015-12-04
Climate change exerts great influence on streamflow by changing precipitation, temperature, snowpack and potential evapotranspiration (PET), while human activities in a watershed can directly alter the runoff production and indirectly through affecting climatic variables. However, to separate contribution of anthropogenic and natural drivers to observed changes in streamflow is non-trivial. Here we estimated the direct influence of human activities and climate change effect to changes of the mean annual streamflow (MAS) of 96 Canadian watersheds based on the elasticity of streamflow in relation to precipitation, PET and human impacts such as land use and cover change. Elasticities of streamflow for each watershed are analytically derived using the Budyko Framework. We found that climate change generally caused an increase in MAS, while human impacts generally a decrease in MAS and such impact tends to become more severe with time, even though there are exceptions. Higher proportions of human contribution, compared to that of climate change contribution, resulted in generally decreased streamflow of Canada observed in recent decades. Furthermore, if without contributions from retreating glaciers to streamflow, human impact would have resulted in a more severe decrease in Canadian streamflow.
Rasmussen, Patrick P.; Gray, John R.; Glysson, G. Douglas; Ziegler, Andrew C.
2009-01-01
In-stream continuous turbidity and streamflow data, calibrated with measured suspended-sediment concentration data, can be used to compute a time series of suspended-sediment concentration and load at a stream site. Development of a simple linear (ordinary least squares) regression model for computing suspended-sediment concentrations from instantaneous turbidity data is the first step in the computation process. If the model standard percentage error (MSPE) of the simple linear regression model meets a minimum criterion, this model should be used to compute a time series of suspended-sediment concentrations. Otherwise, a multiple linear regression model using paired instantaneous turbidity and streamflow data is developed and compared to the simple regression model. If the inclusion of the streamflow variable proves to be statistically significant and the uncertainty associated with the multiple regression model results in an improvement over that for the simple linear model, the turbidity-streamflow multiple linear regression model should be used to compute a suspended-sediment concentration time series. The computed concentration time series is subsequently used with its paired streamflow time series to compute suspended-sediment loads by standard U.S. Geological Survey techniques. Once an acceptable regression model is developed, it can be used to compute suspended-sediment concentration beyond the period of record used in model development with proper ongoing collection and analysis of calibration samples. Regression models to compute suspended-sediment concentrations are generally site specific and should never be considered static, but they represent a set period in a continually dynamic system in which additional data will help verify any change in sediment load, type, and source.
NASA Astrophysics Data System (ADS)
Schepen, Andrew; Zhao, Tongtiegang; Wang, Quan J.; Robertson, David E.
2018-03-01
Rainfall forecasts are an integral part of hydrological forecasting systems at sub-seasonal to seasonal timescales. In seasonal forecasting, global climate models (GCMs) are now the go-to source for rainfall forecasts. For hydrological applications however, GCM forecasts are often biased and unreliable in uncertainty spread, and calibration is therefore required before use. There are sophisticated statistical techniques for calibrating monthly and seasonal aggregations of the forecasts. However, calibration of seasonal forecasts at the daily time step typically uses very simple statistical methods or climate analogue methods. These methods generally lack the sophistication to achieve unbiased, reliable and coherent forecasts of daily amounts and seasonal accumulated totals. In this study, we propose and evaluate a Rainfall Post-Processing method for Seasonal forecasts (RPP-S), which is based on the Bayesian joint probability modelling approach for calibrating daily forecasts and the Schaake Shuffle for connecting the daily ensemble members of different lead times. We apply the method to post-process ACCESS-S forecasts for 12 perennial and ephemeral catchments across Australia and for 12 initialisation dates. RPP-S significantly reduces bias in raw forecasts and improves both skill and reliability. RPP-S forecasts are also more skilful and reliable than forecasts derived from ACCESS-S forecasts that have been post-processed using quantile mapping, especially for monthly and seasonal accumulations. Several opportunities to improve the robustness and skill of RPP-S are identified. The new RPP-S post-processed forecasts will be used in ensemble sub-seasonal to seasonal streamflow applications.
A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction
NASA Astrophysics Data System (ADS)
Danandeh Mehr, Ali; Kahya, Ercan
2017-06-01
Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.
Wesolowski, Edwin A.
1999-01-01
A streamflow and water-quality model was developed for reaches of Sand and Caddo Creeks in south-central Oklahoma to simulate the effects of wastewater discharge from a refinery and a municipal treatment plant.The purpose of the model was to simulate conditions during low streamflow when the conditions controlling dissolved-oxygen concentrations are most severe. Data collected to calibrate and verify the streamflow and water-quality model include continuously monitored streamflow and water-quality data at two gaging stations and three temporary monitoring stations; wastewater discharge from two wastewater plants; two sets each of five water-quality samples at nine sites during a 24-hour period; dye and propane samples; periphyton samples; and sediment oxygen demand measurements. The water-quality sampling, at a 6-hour frequency, was based on a Lagrangian reference frame in which the same volume of water was sampled at each site. To represent the unsteady streamflows and the dynamic water-quality conditions, a transport modeling system was used that included both a model to route streamflow and a model to transport dissolved conservative constituents with linkage to reaction kinetics similar to the U.S. Environmental Protection Agency QUAL2E model to simulate nonconservative constituents. These model codes are the Diffusion Analogy Streamflow Routing Model (DAFLOW) and the branched Lagrangian transport model (BLTM) and BLTM/QUAL2E that, collectively, as calibrated models, are referred to as the Ardmore Water-Quality Model.The Ardmore DAFLOW model was calibrated with three sets of streamflows that collectively ranged from 16 to 3,456 cubic feet per second. The model uses only one set of calibrated coefficients and exponents to simulate streamflow over this range. The Ardmore BLTM was calibrated for transport by simulating dye concentrations collected during a tracer study when streamflows ranged from 16 to 23 cubic feet per second. Therefore, the model is expected to be most useful for low streamflow simulations. The Ardmore BLTM/QUAL2E model was calibrated and verified with water-quality data from nine sites where two sets of five samples were collected. The streamflow during the water-quality sampling in Caddo Creek at site 7 ranged from 8.4 to 20 cubic feet per second, of which about 5.0 to 9.7 cubic feet per second was contributed by Sand Creek. The model simulates the fate and transport of 10 water-quality constituents. The model was verified by running it using data that were not used in calibration; only phytoplankton were not verified.Measured and simulated concentrations of dissolved oxygen exhibited a marked daily pattern that was attributable to waste loading and algal activity. Dissolved-oxygen measurements during this study and simulated dissolved-oxygen concentrations using the Ardmore Water-Quality Model, for the conditions of this study, illustrate that the dissolved-oxygen sag curve caused by the upstream wastewater discharges is confined to Sand Creek.
Water Resources Data, Puerto Rico and the U.S. Virgin Islands, Water Year 1999
Diaz, Pedro L.; Aquino, Zaida; Figueroa-Alamo, Carlos; Vachier, Ricardo J.; Sanchez, Ana V.
2000-01-01
The Water Resources Division of the U.S. Geological Survey, in cooperation with local and federal agencies obtains a large amount of data pertaining to the water resources of the Commonwealth of Puerto Rico and the Territory of the U.S. Virgin Islands each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the area. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data for Puerto Rico and the U.S. Virgin Islands, 1999.' This report includes records on both surface and ground water. Specifically, it contains: (1) discharge records for 76 streamflow gaging stations, daily sediment records for 25 streamflow stations, stage records for 18 reservoirs, and (2) water-quality records for 16 streamflow-gaging stations, and for 42 ungaged stream sites, 11 lake sites, 2 lagoons, and 1 bay, and (3) water-level records for 107 observation wells.
Dettinger, M.D.; Cayan, D.R.; McCabe, G.J.; Redmond, K.T.
2000-01-01
An analysis of historical floods and seasonal streamflows during years with neutral El NiñoSouthern Oscillation (ENSO) conditions in the tropical Pacific and “negative” states of the North Pacific Oscillation (NPO) in the North Pacific—like those expected next year—indicates that (1) chances of having maximum-daily flows next year that are near the longterm averages in many rivers are enhanced, especially in the western states, (2) chances of having near-average seasonal-average flows also may be enhanced across the country, and (3) locally, chances of large floods and winter-season flows may be enhanced in the extreme Northwest, chances of large winter flows may be diminished in rivers in and around Wisconsin, and chances of large spring flows may be diminished in the interior southwest and southeastern coastal plain. The background, methods, and forecast results that lead to these statements are detailed below, followed by a summary of the successes and failures of last year’s streamflow forecast by Dettinger et al. (1999).
Quadroni, Silvia; Crosa, Giuseppe; Gentili, Gaetano; Espa, Paolo
2017-12-31
The present work focuses on evaluating the ecological effects of hydropower-induced streamflow alteration within four catchments in the central Italian Alps. Downstream from the water diversions, minimum flows are released as an environmental protection measure, ranging approximately from 5 to 10% of the mean annual natural flow estimated at the intake section. Benthic macroinvertebrates as well as daily averaged streamflow were monitored for five years at twenty regulated stream reaches, and possible relationships between benthos-based stream quality metrics and environmental variables were investigated. Despite the non-negligible inter-site differences in basic streamflow metrics, benthic macroinvertebrate communities were generally dominated by few highly resilient taxa. The highest level of diversity was detected at sites where upstream minimum flow exceedance is higher and further anthropogenic pressures (other than hydropower) are lower. However, according to the current Italian normative index, the ecological quality was good/high on average at all of the investigated reaches, thus complying the Water Framework Directive standards. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Pierini, J. O.; Restrepo, J. C.; Aguirre, J.; Bustamante, A. M.; Velásquez, G. J.
2017-04-01
A measure of the variability in seasonal extreme streamflow was estimated for the Colombian Caribbean coast, using monthly time series of freshwater discharge from ten watersheds. The aim was to detect modifications in the streamflow monthly distribution, seasonal trends, variance and extreme monthly values. A 20-year length time moving window, with 1-year successive shiftments, was applied to the monthly series to analyze the seasonal variability of streamflow. The seasonal-windowed data were statistically fitted through the Gamma distribution function. Scale and shape parameters were computed using the Maximum Likelihood Estimation (MLE) and the bootstrap method for 1000 resample. A trend analysis was performed for each windowed-serie, allowing to detect the window of maximum absolute values for trends. Significant temporal shifts in seasonal streamflow distribution and quantiles (QT), were obtained for different frequencies. Wet and dry extremes periods increased significantly in the last decades. Such increase did not occur simultaneously through the region. Some locations exhibited continuous increases only at minimum QT.
G.W. Moore; J.A. Jones; B.J. Bond
2011-01-01
The water balance equation dictates that streamflow may be reduced by transpiration. Yet temporal disequilibrium weakens the relationship between transpiration and streamflow in many cases where inputs and outputs are unbalanced. We address two critical knowledge barriers in ecohydrology with respect to time, scale dependence and lags. Study objectives were to...
Real-time streamflow conditions
Graczyk, David J.; Gebert, Warren A.
1996-01-01
Would you like to know streamflow conditions before you go fishing in Wisconsin or in more distant locations? Real-time streamflow data throughout Wisconsin and the United States are available on the Internet from the U.S. Geological Survey. You can see if the stream you are interested in fishing is high due to recent rain or low because of an extended dry spell. Flow conditions at more than 100 stream-gaging stations located throughout Wisconsin can be viewed by accessing the Wisconsin District Home Page at: http://wwwdwimdn.er.usgs.gov
Streamflow characterization using functional data analysis of the Potomac River
NASA Astrophysics Data System (ADS)
Zelmanow, A.; Maslova, I.; Ticlavilca, A. M.; McKee, M.
2013-12-01
Flooding and droughts are extreme hydrological events that affect the United States economically and socially. The severity and unpredictability of flooding has caused billions of dollars in damage and the loss of lives in the eastern United States. In this context, there is an urgent need to build a firm scientific basis for adaptation by developing and applying new modeling techniques for accurate streamflow characterization and reliable hydrological forecasting. The goal of this analysis is to use numerical streamflow characteristics in order to classify, model, and estimate the likelihood of extreme events in the eastern United States, mainly the Potomac River. Functional data analysis techniques are used to study yearly streamflow patterns, with the extreme streamflow events characterized via functional principal component analysis. These methods are merged with more classical techniques such as cluster analysis, classification analysis, and time series modeling. The developed functional data analysis approach is used to model continuous streamflow hydrographs. The forecasting potential of this technique is explored by incorporating climate factors to produce a yearly streamflow outlook.
NASA Astrophysics Data System (ADS)
Maslova, I.; Ticlavilca, A. M.; McKee, M.
2012-12-01
There has been an increased interest in wavelet-based streamflow forecasting models in recent years. Often overlooked in this approach are the circularity assumptions of the wavelet transform. We propose a novel technique for minimizing the wavelet decomposition boundary condition effect to produce long-term, up to 12 months ahead, forecasts of streamflow. A simulation study is performed to evaluate the effects of different wavelet boundary rules using synthetic and real streamflow data. A hybrid wavelet-multivariate relevance vector machine model is developed for forecasting the streamflow in real-time for Yellowstone River, Uinta Basin, Utah, USA. The inputs of the model utilize only the past monthly streamflow records. They are decomposed into components formulated in terms of wavelet multiresolution analysis. It is shown that the model model accuracy can be increased by using the wavelet boundary rule introduced in this study. This long-term streamflow modeling and forecasting methodology would enable better decision-making and managing water availability risk.
Model calibration criteria for estimating ecological flow characteristics
Vis, Marc; Knight, Rodney; Poole, Sandra; Wolfe, William J.; Seibert, Jan; Breuer, Lutz; Kraft, Philipp
2016-01-01
Quantification of streamflow characteristics in ungauged catchments remains a challenge. Hydrological modeling is often used to derive flow time series and to calculate streamflow characteristics for subsequent applications that may differ from those envisioned by the modelers. While the estimation of model parameters for ungauged catchments is a challenging research task in itself, it is important to evaluate whether simulated time series preserve critical aspects of the streamflow hydrograph. To address this question, seven calibration objective functions were evaluated for their ability to preserve ecologically relevant streamflow characteristics of the average annual hydrograph using a runoff model, HBV-light, at 27 catchments in the southeastern United States. Calibration trials were repeated 100 times to reduce parameter uncertainty effects on the results, and 12 ecological flow characteristics were computed for comparison. Our results showed that the most suitable calibration strategy varied according to streamflow characteristic. Combined objective functions generally gave the best results, though a clear underprediction bias was observed. The occurrence of low prediction errors for certain combinations of objective function and flow characteristic suggests that (1) incorporating multiple ecological flow characteristics into a single objective function would increase model accuracy, potentially benefitting decision-making processes; and (2) there may be a need to have different objective functions available to address specific applications of the predicted time series.
Ruddy, Barbara C.; Williams, Cory A.
2007-01-01
In 2007, the U.S. Geological Survey, in cooperation with Bowie Mining Company, initiated a study to characterize the streamflow and streamflow gain-loss in a reach of Hubbard Creek in Delta County, Colorado, in the vicinity of a mine-permit area planned for future coal mining. Premining streamflow characteristics and streamflow gain-loss variation were determined so that pre- and postmining gain-loss characteristics could be compared. This report describes the methods used in this study and the results of two streamflow-measurement sets collected during low-flow conditions. Streamflow gain-loss measurements were collected using rhodamine WT and sodium bromide tracers at four sites spanning the mine-permit area on June 26-28, 2007. Streamflows were estimated and compared between four measurement sites within three stream subreaches of the study reach. Data from two streamflow-gaging stations on Hubbard Creek upstream and downstream from the mine-permit area were evaluated. Streamflows at the stations were continuous, and flow at the upstream station nearly always exceeded the streamflow at the downstream station. Furthermore, streamflow at both stations showed similar diurnal patterns with traveltime offsets. On June 26, streamflow from the gain-loss measurements was greater at site 1 (most upstream site) than at site 4 (most downstream site); on June 27, streamflow was greater at site 4 than at site 2; and on June 27, there was no difference in streamflow between sites 2 and 3. Data from streamflow-gaging stations 09132940 and 09132960 showed diurnal variations and overall decreasing streamflow over time. The data indicate a dynamic system, and streamflow can increase or decrease depending on hydrologic conditions. The streamflow within the study reach was greater than the streamflows at either the upstream or downstream stations. A second set of gain-loss measurements was collected at sites 2 and 4 on November 8-9, 2007. On November 8, streamflow was greater at site 4 than at site 2, and on the following day, November 9, streamflow was greater at site 2 than at site 4. Data collection on November 8 occurred while the streamflow was increasing due to contributions from stream ice melting throughout different parts of the basin. Data collection on November 9 occurred earlier in the day with less stream ice melting and more steady-state conditions, so the indication that streamflow decreased between sites 2 and 4 may be more accurate. Diurnal variations in streamflow are common at both the upper and the lower streamflow-gaging stations. The upper streamflow-gaging station shows a melt-freeze influence from tributaries to Hubbard Creek during the winter season. Downstream from the study reach, observed diurnal variation is likely due to evapotranspiration associated with dense flood-plain vegetation, which consumes water from the creek during the middle of the day. Varying diurnal patterns in streamflow, combined with possible variations in tributary inflows to Hubbard Creek in the study reach, probably account for the observed variations in streamflow at the tracer measurement sites. During both sampling periods in June and November 2007, conditions were less than ideal and not steady state. The June 27 sampling indicates that the streamflow was increasing between measurement sites 2 and 4, and the November 9 sampling indicates that the streamflow was decreasing between measurement sites 2 and 4. The data collected during the diurnal and day-to-day variations in streamflow indicated that the streamflow reach is dynamic and can be gaining, losing, or constant.
Geologic and climatic controls on streamflow generation processes in a complex eogenetic karst basin
NASA Astrophysics Data System (ADS)
Vibhava, F.; Graham, W. D.; Maxwell, R. M.
2012-12-01
Streamflow at any given location and time is representative of surface and subsurface contributions from various sources. The ability to fully identify the factors controlling these contributions is key to successfully understanding the transport of contaminants through the system. In this study we developed a fully integrated 3D surface water-groundwater-land surface model, PARFLOW, to evaluate geologic and climatic controls on streamflow generation processes in a complex eogenetic karst basin in North Central Florida. In addition to traditional model evaluation criterion, such as comparing field observations to model simulated streamflow and groundwater elevations, we quantitatively evaluated the model's predictions of surface-groundwater interactions over space and time using a suite of binary end-member mixing models that were developed using observed specific conductivity differences among surface and groundwater sources throughout the domain. Analysis of model predictions showed that geologic heterogeneity exerts a strong control on both streamflow generation processes and land atmospheric fluxes in this watershed. In the upper basin, where the karst aquifer is overlain by a thick confining layer, approximately 92% of streamflow is "young" event flow, produced by near stream rainfall. Throughout the upper basin the confining layer produces a persistent high surficial water table which results in high evapotranspiration, low groundwater recharge and thus negligible "inter-event" streamflow. In the lower basin, where the karst aquifer is unconfined, deeper water tables result in less evapotranspiration. Thus, over 80% of the streamflow is "old" subsurface flow produced by diffuse infiltration through the epikarst throughout the lower basin, and all surface contributions to streamflow originate in the upper confined basin. Climatic variability provides a secondary control on surface-subsurface and land-atmosphere fluxes, producing significant seasonal and interannual variability in these processes. Spatial and temporal patterns of evapotranspiration, groundwater recharge and streamflow generation processes reveal potential hot spots and hot moments for surface and groundwater contamination in this basin.
Streamflow characteristics at hydrologic bench-mark stations
Lawrence, C.L.
1987-01-01
The Hydrologic Bench-Mark Network was established in the 1960's. Its objectives were to document the hydrologic characteristics of representative undeveloped watersheds nationwide and to provide a comparative base for studying the effects of man on the hydrologic environment. The network, which consists of 57 streamflow gaging stations and one lake-stage station in 39 States, is planned for permanent operation. This interim report describes streamflow characteristics at each bench-mark site and identifies time trends in annual streamflow that have occurred during the data-collection period. The streamflow characteristics presented for each streamflow station are (1) flood and low-flow frequencies, (2) flow duration, (3) annual mean flow, and (4) the serial correlation coefficient for annual mean discharge. In addition, Kendall's tau is computed as an indicator of time trend in annual discharges. The period of record for most stations was 13 to 17 years, although several stations had longer periods of record. The longest period was 65 years for Merced River near Yosemite, Calif. Records of flow at 6 of 57 streamflow sites in the network showed a statistically significant change in annual mean discharge over the period of record, based on computations of Kendall's tau. The values of Kendall's tau ranged from -0.533 to 0.648. An examination of climatological records showed that changes in precipitation were most likely the cause for the change in annual mean discharge.
NASA Astrophysics Data System (ADS)
Wright, Ashley J.; Walker, Jeffrey P.; Pauwels, Valentijn R. N.
2017-08-01
Floods are devastating natural hazards. To provide accurate, precise, and timely flood forecasts, there is a need to understand the uncertainties associated within an entire rainfall time series, even when rainfall was not observed. The estimation of an entire rainfall time series and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of entire rainfall input time series to be considered when estimating model parameters, and provides the ability to improve rainfall estimates from poorly gauged catchments. Current methods to estimate entire rainfall time series from streamflow records are unable to adequately invert complex nonlinear hydrologic systems. This study aims to explore the use of wavelets in the estimation of rainfall time series from streamflow records. Using the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia, it is shown that model parameter distributions and an entire rainfall time series can be estimated. Including rainfall in the estimation process improves streamflow simulations by a factor of up to 1.78. This is achieved while estimating an entire rainfall time series, inclusive of days when none was observed. It is shown that the choice of wavelet can have a considerable impact on the robustness of the inversion. Combining the use of a likelihood function that considers rainfall and streamflow errors with the use of the DWT as a model data reduction technique allows the joint inference of hydrologic model parameters along with rainfall.
McCarthy, Peter M.; Dutton, DeAnn M.; Sando, Steven K.; Sando, Roy
2016-04-05
The U.S. Geological Survey (USGS) provides streamflow characteristics and other related information needed by water-resource managers to protect people and property from floods, plan and manage water-resource activities, and protect water quality. Streamflow characteristics provided by the USGS, such as peak-flow and low-flow frequencies for streamflow-gaging stations, are frequently used by engineers, flood forecasters, land managers, biologists, and others to guide their everyday decisions. In addition to providing streamflow characteristics at streamflow-gaging stations, the USGS also develops regional regression equations and drainage area-adjustment methods for estimating streamflow characteristics at locations on ungaged streams. Regional regression equations can be complex and often require users to determine several basin characteristics, which are physical and climatic characteristics of the stream and its drainage basin. Obtaining these basin characteristics for streamflow-gaging stations and ungaged sites traditionally has been time consuming and subjective, and led to inconsistent results.StreamStats is a Web-based geographic information system application that was created by the USGS to provide users with access to an assortment of analytical tools that are useful for water-resource planning and management. StreamStats allows users to easily obtain streamflow and basin characteristics for USGS streamflow-gaging stations and user-selected locations on ungaged streams. The USGS, in cooperation with Montana Department of Transportation, Montana Department of Environmental Quality, and Montana Department of Natural Resources and Conservation, completed a study to develop a StreamStats application for Montana, compute streamflow characteristics at streamflow-gaging stations, and develop regional regression equations to estimate streamflow characteristics at ungaged sites. Chapter A of this Scientific Investigations Report describes the Montana StreamStats application and the datasets, streamflow-gaging stations, streamflow characteristics, and regression equations (as described fully in Chapters B through G of this report) that are used for development of the StreamStats application for Montana.
Spatial patterns of March and September streamflow trends in Pacific Northwest Streams, 1958-2008
Chang, Heejun; Jung, Il-Won; Steele, Madeline; Gannett, Marshall
2012-01-01
Summer streamflow is a vital water resource for municipal and domestic water supplies, irrigation, salmonid habitat, recreation, and water-related ecosystem services in the Pacific Northwest (PNW) in the United States. This study detects significant negative trends in September absolute streamflow in a majority of 68 stream-gauging stations located on unregulated streams in the PNW from 1958 to 2008. The proportion of March streamflow to annual streamflow increases in most stations over 1,000 m elevation, with a baseflow index of less than 50, while absolute March streamflow does not increase in most stations. The declining trends of September absolute streamflow are strongly associated with seven-day low flow, January–March maximum temperature trends, and the size of the basin (19–7,260 km2), while the increasing trends of the fraction of March streamflow are associated with elevation, April 1 snow water equivalent, March precipitation, center timing of streamflow, and October–December minimum temperature trends. Compared with ordinary least squares (OLS) estimated regression models, spatial error regression and geographically weighted regression (GWR) models effectively remove spatial autocorrelation in residuals. The GWR model results show spatial gradients of local R 2 values with consistently higher local R 2 values in the northern Cascades. This finding illustrates that different hydrologic landscape factors, such as geology and seasonal distribution of precipitation, also influence streamflow trends in the PNW. In addition, our spatial analysis model results show that considering various geographic factors help clarify the dynamics of streamflow trends over a large geographical area, supporting a spatial analysis approach over aspatial OLS-estimated regression models for predicting streamflow trends. Results indicate that transitional rain–snow surface water-dominated basins are likely to have reduced summer streamflow under warming scenarios. Consequently, a better understanding of the relationships among summer streamflow, precipitation, snowmelt, elevation, and geology can help water managers predict the response of regional summer streamflow to global warming.
Lee, Karl K.; Risley, John C.
2002-03-19
Precipitation-runoff models, base-flow-separation techniques, and stream gain-loss measurements were used to study recharge and ground-water surface-water interaction as part of a study of the ground-water resources of the Willamette River Basin. The study was a cooperative effort between the U.S. Geological Survey and the State of Oregon Water Resources Department. Precipitation-runoff models were used to estimate the water budget of 216 subbasins in the Willamette River Basin. The models were also used to compute long-term average recharge and base flow. Recharge and base-flow estimates will be used as input to a regional ground-water flow model, within the same study. Recharge and base-flow estimates were made using daily streamflow records. Recharge estimates were made at 16 streamflow-gaging-station locations and were compared to recharge estimates from the precipitation-runoff models. Base-flow separation methods were used to identify the base-flow component of streamflow at 52 currently operated and discontinued streamflow-gaging-station locations. Stream gain-loss measurements were made on the Middle Fork Willamette, Willamette, South Yamhill, Pudding, and South Santiam Rivers, and were used to identify and quantify gaining and losing stream reaches both spatially and temporally. These measurements provide further understanding of ground-water/surface-water interactions.
NASA Astrophysics Data System (ADS)
Mandal, D.; Bhatia, N.; Srivastav, R. K.
2016-12-01
Soil Water Assessment Tool (SWAT) is one of the most comprehensive hydrologic models to simulate streamflow for a watershed. The two major inputs for a SWAT model are: (i) Digital Elevation Models (DEM), and (ii) Land Use and Land Cover Maps (LULC). This study aims to quantify the uncertainty in streamflow predictions using SWAT for San Bernard River in Brazos-Colorado coastal watershed, Texas, by incorporating the respective datasets from different sources: (i) DEM data will be obtained from ASTER GDEM V2, GMTED2010, NHD DEM, and SRTM DEM datasets with ranging resolution from 1/3 arc-second to 30 arc-second, and (ii) LULC data will be obtained from GLCC V2, MRLC NLCD2011, NOAA's C-CAP, USGS GAP, and TCEQ databases. Weather variables (Precipitation and Max-Min Temperature at daily scale) will be obtained from National Climatic Data Centre (NCDC) and SWAT in-built STASGO tool will be used to obtain the soil maps. The SWAT model will be calibrated using SWAT-CUP SUFI-2 approach and its performance will be evaluated using the statistical indices of Nash-Sutcliffe efficiency (NSE), ratio of Root-Mean-Square-Error to standard deviation of observed streamflow (RSR), and Percent-Bias Error (PBIAS). The study will help understand the performance of SWAT model with varying data sources and eventually aid the regional state water boards in planning, designing, and managing hydrologic systems.
Stern, Michelle A.; Flint, Lorraine E.; Minear, Justin T.; Flint, Alan L.; Wright, Scott A.
2016-01-01
A daily watershed model of the Sacramento River Basin of northern California was developed to simulate streamflow and suspended sediment transport to the San Francisco Bay-Delta. To compensate for sparse data, a unique combination of model inputs was developed, including meteorological variables, potential evapotranspiration, and parameters defining hydraulic geometry. A slight decreasing trend of sediment loads and concentrations was statistically significant in the lowest 50% of flows, supporting the observed historical sediment decline. Historical changes in climate, including seasonality and decline of snowpack, contribute to changes in streamflow, and are a significant component describing the mechanisms responsible for the decline in sediment. Several wet and dry hypothetical climate change scenarios with temperature changes of 1.5 °C and 4.5 °C were applied to the base historical conditions to assess the model sensitivity of streamflow and sediment to changes in climate. Of the scenarios evaluated, sediment discharge for the Sacramento River Basin increased the most with increased storm magnitude and frequency and decreased the most with increases in air temperature, regardless of changes in precipitation. The model will be used to develop projections of potential hydrologic and sediment trends to the Bay-Delta in response to potential future climate scenarios, which will help assess the hydrological and ecological health of the Bay-Delta into the next century.
Estimates of streamflow characteristics for selected small streams, Baker River basin, Washington
Williams, John R.
1987-01-01
Regression equations were used to estimate streamflow characteristics at eight ungaged sites on small streams in the Baker River basin in the North Cascade Mountains, Washington, that could be suitable for run-of-the-river hydropower development. The regression equations were obtained by relating known streamflow characteristics at 25 gaging stations in nearby basins to several physical and climatic variables that could be easily measured in gaged or ungaged basins. The known streamflow characteristics were mean annual flows, 1-, 3-, and 7-day low flows and high flows, mean monthly flows, and flow duration. Drainage area and mean annual precipitation were not the most significant variables in all the regression equations. Variance in the low flows and the summer mean monthly flows was reduced by including an index of glacierized area within the basin as a third variable. Standard errors of estimate of the regression equations ranged from 25 to 88%, and the largest errors were associated with the low flow characteristics. Discharge measurements made at the eight sites near midmonth each month during 1981 were used to estimate monthly mean flows at the sites for that period. These measurements also were correlated with concurrent daily mean flows from eight operating gaging stations. The correlations provided estimates of mean monthly flows that compared reasonably well with those estimated by the regression analyses. (Author 's abstract)
NASA Astrophysics Data System (ADS)
Wood, A. W.; Clark, E.; Newman, A. J.; Nijssen, B.; Clark, M. P.; Gangopadhyay, S.; Arnold, J. R.
2015-12-01
The US National Weather Service River Forecasting Centers are beginning to operationalize short range to medium range ensemble predictions that have been in development for several years. This practice contrasts with the traditional single-value forecast practice at these lead times not only because the ensemble forecasts offer a basis for quantifying forecast uncertainty, but also because the use of ensembles requires a greater degree of automation in the forecast workflow than is currently used. For instance, individual ensemble member forcings cannot (practically) be manually adjusted, a step not uncommon with the current single-value paradigm, thus the forecaster is required to adopt a more 'over-the-loop' role than before. The relative lack of experience among operational forecasters and forecast users (eg, water managers) in the US with over-the-loop approaches motivates the creation of a real-time demonstration and evaluation platform for exploring the potential of over-the-loop workflows to produce usable ensemble short-to-medium range forecasts, as well as long range predictions. We describe the development and early results of such an effort by a collaboration between NCAR and the two water agencies, the US Army Corps of Engineers and the US Bureau of Reclamation. Focusing on small to medium sized headwater basins around the US, and using multi-decade series of ensemble streamflow hindcasts, we also describe early results, assessing the skill of daily-updating, over-the-loop forecasts driven by a set of ensemble atmospheric outputs from the NCEP GEFS for lead times from 1-15 days.
What is the effect of LiDAR-derived DEM resolution on large-scale watershed model results?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ping Yang; Daniel B. Ames; Andre Fonseca
This paper examines the effect of raster cell size on hydrographic feature extraction and hydrological modeling using LiDAR derived DEMs. LiDAR datasets for three experimental watersheds were converted to DEMs at various cell sizes. Watershed boundaries and stream networks were delineated from each DEM and were compared to reference data. Hydrological simulations were conducted and the outputs were compared. Smaller cell size DEMs consistently resulted in less difference between DEM-delineated features and reference data. However, minor differences been found between streamflow simulations resulted for a lumped watershed model run at daily simulations aggregated at an annual average. These findings indicatemore » that while higher resolution DEM grids may result in more accurate representation of terrain characteristics, such variations do not necessarily improve watershed scale simulation modeling. Hence the additional expense of generating high resolution DEM's for the purpose of watershed modeling at daily or longer time steps may not be warranted.« less
Statistical models for estimating daily streamflow in Michigan
Holtschlag, D.J.; Salehi, Habib
1992-01-01
Statistical models for estimating daily streamflow were analyzed for 25 pairs of streamflow-gaging stations in Michigan. Stations were paired by randomly choosing a station operated in 1989 at which 10 or more years of continuous flow data had been collected and at which flow is virtually unregulated; a nearby station was chosen where flow characteristics are similar. Streamflow data from the 25 randomly selected stations were used as the response variables; streamflow data at the nearby stations were used to generate a set of explanatory variables. Ordinary-least squares regression (OLSR) equations, autoregressive integrated moving-average (ARIMA) equations, and transfer function-noise (TFN) equations were developed to estimate the log transform of flow for the 25 randomly selected stations. The precision of each type of equation was evaluated on the basis of the standard deviation of the estimation errors. OLSR equations produce one set of estimation errors; ARIMA and TFN models each produce l sets of estimation errors corresponding to the forecast lead. The lead-l forecast is the estimate of flow l days ahead of the most recent streamflow used as a response variable in the estimation. In this analysis, the standard deviation of lead l ARIMA and TFN forecast errors were generally lower than the standard deviation of OLSR errors for l < 2 days and l < 9 days, respectively. Composite estimates were computed as a weighted average of forecasts based on TFN equations and backcasts (forecasts of the reverse-ordered series) based on ARIMA equations. The standard deviation of composite errors varied throughout the length of the estimation interval and generally was at maximum near the center of the interval. For comparison with OLSR errors, the mean standard deviation of composite errors were computed for intervals of length 1 to 40 days. The mean standard deviation of length-l composite errors were generally less than the standard deviation of the OLSR errors for l < 32 days. In addition, the composite estimates ensure a gradual transition between periods of estimated and measured flows. Model performance among stations of differing model error magnitudes were compared by computing ratios of the mean standard deviation of the length l composite errors to the standard deviation of OLSR errors. The mean error ratio for the set of 25 selected stations was less than 1 for intervals l < 32 days. Considering the frequency characteristics of the length of intervals of estimated record in Michigan, the effective mean error ratio for intervals < 30 days was 0.52. Thus, for intervals of estimation of 1 month or less, the error of the composite estimate is substantially lower than error of the OLSR estimate.
Risser, Dennis W.; Thompson, Ronald E.; Stuckey, Marla H.
2008-01-01
A method was developed for making estimates of long-term, mean annual ground-water recharge from streamflow data at 80 streamflow-gaging stations in Pennsylvania. The method relates mean annual base-flow yield derived from the streamflow data (as a proxy for recharge) to the climatic, geologic, hydrologic, and physiographic characteristics of the basins (basin characteristics) by use of a regression equation. Base-flow yield is the base flow of a stream divided by the drainage area of the basin, expressed in inches of water basinwide. Mean annual base-flow yield was computed for the period of available streamflow record at continuous streamflow-gaging stations by use of the computer program PART, which separates base flow from direct runoff on the streamflow hydrograph. Base flow provides a reasonable estimate of recharge for basins where streamflow is mostly unaffected by upstream regulation, diversion, or mining. Twenty-eight basin characteristics were included in the exploratory regression analysis as possible predictors of base-flow yield. Basin characteristics found to be statistically significant predictors of mean annual base-flow yield during 1971-2000 at the 95-percent confidence level were (1) mean annual precipitation, (2) average maximum daily temperature, (3) percentage of sand in the soil, (4) percentage of carbonate bedrock in the basin, and (5) stream channel slope. The equation for predicting recharge was developed using ordinary least-squares regression. The standard error of prediction for the equation on log-transformed data was 9.7 percent, and the coefficient of determination was 0.80. The equation can be used to predict long-term, mean annual recharge rates for ungaged basins, providing that the explanatory basin characteristics can be determined and that the underlying assumption is accepted that base-flow yield derived from PART is a reasonable estimate of ground-water recharge rates. For example, application of the equation for 370 hydrologic units in Pennsylvania predicted a range of ground-water recharge from about 6.0 to 22 inches per year. A map of the predicted recharge illustrates the general magnitude and variability of recharge throughout Pennsylvania.
Koltun, G.F.; Kula, Stephanie P.
2013-01-01
This report presents the results of a study to develop methods for estimating selected low-flow statistics and for determining annual flow-duration statistics for Ohio streams. Regression techniques were used to develop equations for estimating 10-year recurrence-interval (10-percent annual-nonexceedance probability) low-flow yields, in cubic feet per second per square mile, with averaging periods of 1, 7, 30, and 90-day(s), and for estimating the yield corresponding to the long-term 80-percent duration flow. These equations, which estimate low-flow yields as a function of a streamflow-variability index, are based on previously published low-flow statistics for 79 long-term continuous-record streamgages with at least 10 years of data collected through water year 1997. When applied to the calibration dataset, average absolute percent errors for the regression equations ranged from 15.8 to 42.0 percent. The regression results have been incorporated into the U.S. Geological Survey (USGS) StreamStats application for Ohio (http://water.usgs.gov/osw/streamstats/ohio.html) in the form of a yield grid to facilitate estimation of the corresponding streamflow statistics in cubic feet per second. Logistic-regression equations also were developed and incorporated into the USGS StreamStats application for Ohio for selected low-flow statistics to help identify occurrences of zero-valued statistics. Quantiles of daily and 7-day mean streamflows were determined for annual and annual-seasonal (September–November) periods for each complete climatic year of streamflow-gaging station record for 110 selected streamflow-gaging stations with 20 or more years of record. The quantiles determined for each climatic year were the 99-, 98-, 95-, 90-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 25-, 20-, 10-, 5-, 2-, and 1-percent exceedance streamflows. Selected exceedance percentiles of the annual-exceedance percentiles were subsequently computed and tabulated to help facilitate consideration of the annual risk of exceedance or nonexceedance of annual and annual-seasonal-period flow-duration values. The quantiles are based on streamflow data collected through climatic year 2008.
Falk, Sarah E.; Anderholm, Scott K.; Hafich, Katya A.
2013-01-01
The Albuquerque–Bernalillo County Water Utility Authority supplements the municipal water supply for the Albuquerque metropolitan area, in central New Mexico, with water diverted from the Rio Grande. Water diverted from the Rio Grande for municipal use is derived from the San Juan–Chama Project, which delivers water from streams in the southern San Juan Mountains in the Colorado River Basin in southern Colorado to the Rio Chama watershed and the Rio Grande Basin in northern New Mexico. The U.S. Geological Survey, in cooperation with Albuquerque–Bernalillo County Water Utility Authority, has compiled historical streamflow and water-quality data and collected new water-quality data to characterize the water quality and streamflow conditions and annual flow variability, as characterized by annual flow-duration curves, of streams of the San Juan–Chama Project. Nonparametric statistical methods were applied to calculate annual and monthly summary statistics of streamflow, trends in streamflow conditions were evaluated with the Mann–Kendall trend test, and annual variation in streamflow conditions was evaluated with annual flow-duration curves. The study area is located in northern New Mexico and southern Colorado and includes the Rio Blanco, Little Navajo River, and Navajo River, tributaries of the San Juan River in the Colorado River Basin located in the southern San Juan Mountains, and Willow Creek and Horse Lake Creek, tributaries of the Rio Chama in the Rio Grande Basin. The quality of water in the streams in the study area generally varied by watershed on the basis of the underlying geology and the volume and source of the streamflow. Water from the Rio Blanco and Little Navajo River watersheds, primarily underlain by volcanic deposits, volcaniclastic sediments and landslide deposits derived from these materials, was compositionally similar and had low specific-conductance values relative to the other streams in the study area. Water from the Navajo River, Horse Lake Creek, and Willow Creek watersheds, which are underlain mostly by Cretaceous-aged marine shale, was compositionally similar and had large concentrations of sulfate relative to the other streams in the study area, though the water from the Navajo River had lower specific-conductance values than did the water from Horse Lake Creek above Heron Reservoir and Willow Creek above Azotea Creek. Generally, surface-water quality varied with streamflow conditions throughout the year. Streamflow in spring and summer is generally a mixture of base flow (the component of streamflow derived from groundwater discharged to the stream channel) diluted with runoff from snowmelt and precipitation events, whereas streamflow in fall and winter is generally solely base flow. Major- and trace-element concentrations in the streams sampled were lower than U.S. Environmental Protection Agency primary and secondary drinking-water standards and New Mexico Environment Department surface-water standards for the streams. In general, years with increased annual discharge, compared to years with decreased annual discharge, had a smaller percentage of discharge in March, a larger percentage of discharge in June, an interval of discharge derived from snowmelt runoff that occurred later in the year, and a larger discharge in June. Additionally, years with increased annual discharge generally had a longer duration of runoff, and the streamflow indicators occurred at dates later in the year than the years with less snowmelt runoff. Additionally, the seasonal distribution of streamflow was more strongly controlled by the change in the amount of annual discharge than by changes in streamflow over time. The variation of streamflow conditions over time at one streamflow-gaging station in the study area, Navajo River at Banded Peak Ranch, was not significantly monotonic over the period of record with a Kendall’s tau of 0.0426 and with a p-value of 0.5938 for 1937 to 2009 (a trend was considered statistically significant at a p-value ≤ 0.05). There was a relation, however, such that annual discharge was generally lower than the median during a negative Pacific Decadal Oscillation interval and higher than the median during a positive Pacific Decadal Oscillation interval. Streamflow conditions at Navajo River at Banded Peak Ranch varied nonmonotonically over time and were likely a function of complex climate pattern interactions. Similarly, the monthly distribution of streamflow varied nonmonotonically over time and was likely a function of complex climate pattern interactions that cause variation over time. Study results indicated that the median of the sum of the streamflow available above the minimum monthly bypass requirement from Rio Blanco, Little Navajo River, and Navajo River was 126,240 acre-feet. The results also indicated that diversion of water for the San Juan–Chama Project has been possible for most months of most years.
NASA Astrophysics Data System (ADS)
Jimeno-Saez, Patricia; Pulido-Velazquez, David; Pegalajar-Cuellar, Manuel; Collados-Lara, Antonio-Juan; Pardo-Iguzquiza, Eulogio
2017-04-01
Precipitation (P) measurements show important biases due to under-catch, especially in windy conditions. Gauges modify the wind fields, producing important under-catch in solid P. In this work we intent to perform a global assessment of the under-catch phenomenon in some alpine catchments of Sierra Nevada Mountain Range (Spain) by using different conceptual hydrological models. They are based on the available information about daily natural streamflow and daily fields of P and temperature (T) in each catchment. We want to analyse long time periods (more than 20 years at daily scale) in order to obtain conclusions taking into account the stochastic behaviour of the natural streamflow and P and T variables. The natural streamflowin each basin has been obtained from the streamflow measurements in the gauges by making some simple mathematical operations to eliminate the anthropic influences. The daily climatic fieldswere estimated with spatial resolution of 1kmx1km by applying geostatistic techniques using data coming from 119climatic gauges existing in the area.We have considered to model options: Monthly and yearly variogram to characterize the spatial data correlation. The Elevation has been considered as secondary variable for the estimation. The analysis of the experimental data showed a linear relationhip between mean T and elevation. Therefore, we decided to apply a kriging with linear external drift to estimate the P and T fields. The mean daily P data show a quadratic relationship with the elevation. Different hypothesis have been considered to approach these P fields by applying kriging with linear drift, with quadratic drift, and regression kriging. A cross-validation analysis showed that the best approximation to the data is obtained with the kriging with linear drift. The P and T fields obtained with this technique were employed to feed different hydrological models in which different conceptual approaches of the hydrological processes related with the snow are considered. Correction factors of the solid & liquid P fields have been included in the formulation. We intend to perform an automatic calibration of the parameters of these models. A detailed analysis of global optimization techniques has been performed in order to identify the best possible optimization algorithm (Classic Informed Local Search, Simulated Annealing, Genetic Algorithm and Memetic algorithm) which is important due to the high computational cost of our optimization problems with many parameters and noisy inputs and outputs. Finally with the best calibration algorithm we have performed different optimization experiments (20 realizations). It allows us to obtain a distribution function of the correction factor for the solid and liquid P for each catchment, which can be useful as a preliminary assessment of the global under-catch in the basins. We have also analysed the sensitivity of the results to the spatio-temporal scale (grid with cells of 1x1 kms or 12.5x12.5 Kms; daily or monthly approaches) employed to approach different hydrological processes. We are also working in the analysis of these issues considering multi-objective evolutionary optimization approaches for calibration using multiple target criteria in which the transient calibration try to minimize differences with both, stream flow and snow cover area observations. This research has been partially supported by the CGL2013-48424-C2-2-R (MINECO) and the PMAFI/06/14 (UCAM) projects.
Moyer, Douglas; Hyer, Kenneth
2003-01-01
Impairment of surface waters by fecal coliform bacteria is a water-quality issue of national scope and importance. Section 303(d) of the Clean Water Act requires that each State identify surface waters that do not meet applicable water-quality standards. In Virginia, more than 175 stream segments are on the 1998 Section 303(d) list of impaired waters because of violations of the water-quality standard for fecal coliform bacteria. A total maximum daily load (TMDL) will need to be developed by 2006 for each of these impaired streams and rivers by the Virginia Departments of Environmental Quality and Conservation and Recreation. A TMDL is a quantitative representation of the maximum load of a given water-quality constituent, from all point and nonpoint sources, that a stream can assimilate without violating the designated water-quality standard. Christians Creek, in Augusta County, Virginia, is one of the stream segments listed by the State of Virginia as impaired by fecal coliform bacteria. Watershed modeling and bacterial source tracking were used to develop the technical components of the fecal coliform bacteria TMDL for Christians Creek. The Hydrological Simulation Program?FORTRAN (HSPF) was used to simulate streamflow, fecal coliform concentrations, and source-specific fecal coliform loading in Christians Creek. Ribotyping, a bacterial source tracking technique, was used to identify the dominant sources of fecal coliform bacteria in the Christians Creek watershed. Ribotyping also was used to determine the relative contributions of specific sources to the observed fecal coliform load in Christians Creek. Data from the ribotyping analysis were incorporated into the calibration of the fecal coliform model. Study results provide information regarding the calibration of the streamflow and fecal coliform bacteria models and also identify the reductions in fecal coliform loads required to meet the TMDL for Christians Creek. The calibrated streamflow model simulated observed streamflow characteristics with respect to total annual runoff, seasonal runoff, average daily streamflow, and hourly stormflow. The calibrated fecal coliform model simulated the patterns and range of observed fecal coliform bacteria concentrations. Observed fecal coliform bacteria concentrations during low-flow periods ranged from 40 to 2,000 colonies per 100 milliliters, and peak concentrations during stormflow periods ranged from 23,000 to 730,000 colonies per 100 milliliters. Additionally, fecal coliform bacteria concentrations were generally higher upstream and lower downstream. Simulated source-specific contributions of fecal coliform bacteria to instream load were matched to the observed contributions from the dominant sources, which were beaver, cats, cattle, deer, dogs, ducks, geese, horses, humans, muskrats, poultry, raccoons, and sheep. According to model results, a 96-percent reduction in the current fecal coliform load delivered from the watershed to Christians Creek would result in compliance with the designated water-quality goals and associated TMDL.
Long-term (in)stability of the climate-streamflow relationship
NASA Astrophysics Data System (ADS)
Saft, Margarita; Peel, Murray; Coxon, Gemma; Freer, Jim; Parajka, Juraj; Woods, Ross
2017-04-01
Land use changes have long been known to alter streamflow production for a given climatic input. Recently, extended shifts in climate were also shown to be capable of altering catchment internal functioning and streamflow production for a given climatic input. This study investigates the stability of climate-streamflow relationships in natural catchments in different regions of the world for the first time, using datasets of natural/reference catchments from Europe, US, and Australia. Changes in climate-streamflow relationships are investigated statistically on the interannual to interdecadal timescale and related to interdecadal climate variability. We compare the frequency and magnitude of shifts in climate-streamflow relationship between different regions, and discuss what any differences in shift frequency and magnitude might be related to. This study draws attention to the issues of catchment vulnerability to changes in external factors, catchment-climate co-evolution, and long-term catchment memory.
Impact of Fire on Streamflow in Southern California Watersheds
NASA Astrophysics Data System (ADS)
Bart, R. R.; Hope, A. S.
2007-12-01
Post-fire streamflow dynamics in Southern California have primarily been studied using small watershed experiments. These studies have concluded that increases in streamflow are a consequence of an increase in soil hydrophobicity, along with a decrease in transpiration rates associated with less vegetation. Extrapolation of the results from these studies to large watersheds (>50 km2) has been limited because large watersheds may not burn completely and other processes may emerge at these scales. In this study, six paired watersheds were used to test the hypothesis that there is an increase in streamflow following fire in large California watersheds (54-632 km2). The percentage of area burned in these watersheds ranged from 23 to 100%. The effects of fires on streamflow were examined at annual, seasonal, and monthly time-steps for the five years following fire. In addition, this study attempted to address fundamental regression assumptions that are commonly ignored, and create uncertainty bounds for evaluating the changes in streamflow before and after fire. Results of this experiment indicate that differences in pre and post-fire streamflows, at all time scales and in all the test catchments, were generally within the 95% uncertainty bounds of the regression equation. It is uncertain whether the apparent lack of significant difference between the pre and post-fire streamflow reflects no actual change in streamflow or is a consequence of the errors and uncertainties in the streamflow data. Furthermore, persistent drought in the years following fire made it challenging to interpret differences in pre and post-fire flows using the paired watershed methodology. The effects of hydrophobicity on post-fire streamflow may have been reduced by a limited number of storm flow events during these drought years. Under these dry conditions, soil moisture was the dominant control over transpirational losses, minimizing the effects of a reduction in vegetation cover. These results indicate that the consequences of fires are likely to vary depending on the post-fire meteorological conditions. The study addresses the challenges of using non-experimental watersheds for paired watershed studies.
Ahearn, Elizabeth A.
2008-01-01
Flow durations, low-flow frequencies, and monthly median streamflows were computed for 91 continuous-record, streamflow-gaging stations in Connecticut with 10 or more years of record. Flow durations include the 99-, 98-, 97-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 25-, 20-, 10-, 5-, and 1-percent exceedances. Low-flow frequencies include the 7-day, 10-year (7Q10) low flow; 7-day, 2-year (7Q2) low flow; and 30-day, 2-year (30Q2) low flow. Streamflow estimates were computed for each station using data for the period of record through water year 2005. Estimates of low-flow statistics for 7 short-term (operated between 3 and 10 years) streamflow-gaging stations and 31 partial-record sites were computed. Low-flow estimates were made on the basis of the relation between base flows at a short-term station or partial-record site and concurrent daily mean streamflows at a nearby index station. The relation is defined by the Maintenance of Variance Extension, type 3 (MOVE.3) method. Several short-term stations and partial-record sites had poorly defined relations with nearby index stations; therefore, no low-flow statistics were derived for these sites. The estimated low-flow statistics for the short-term stations and partial-record sites include the 99-, 98-, 97-, 95-, 90-, and 85-percent flow durations; the 7-day, 10-year (7Q10) low flow; 7-day, 2-year (7Q2) low flow; and 30-day, 2-year (30Q2) low-flow frequencies; and the August median flow. Descriptive information on location and record length, measured basin characteristics, index stations correlated to the short-term station and partial-record sites, and estimated flow statistics are provided in this report for each station. Streamflow estimates from this study are stored on USGS's World Wide Web application 'StreamStats' (http://water.usgs.gov/osw/streamstats/connecticut.html).
NASA Astrophysics Data System (ADS)
Lin, Tzu Ping; Lin, Yu Pin; Lien, Wan Yu
2015-04-01
Climate change projects have various levels of impacts on hydrological cycles around the world. The impact of climate change and uncertainty of climate projections from general circulation models (GCMs) from the Coupled Model Intercomparison Project (CMIP5) which has been just be released in Taiwan, 2014. Since the streamflow run into ocean directly due to the steep terrain and the rainfall difference between wet and dry seasons is apparent; as a result, the allocation water resource reasonable is very challenge in Taiwan, particularly under climate change. The purpose of this study was to evaluate the impacts of climate and land use changes on a small watershed in Taiwan. The AR5 General Circulation Models(GCM) output data was adopted in this study and was downscaled from the monthly to the daily weather data as the input data of hydrological model such as Soil and Water Assessment Tool (SWAT) model in this study. The spatially explicit land uses change model, the Conservation of Land Use and its Effects at Small regional extent (CLUE-s), was applied to simulate land use scenarios in 2020-2039. Combined climate and land use change scenarios were adopted as input data of the hydrological model, the SWAT model, to estimate the future streamflows. With the increasing precipitation, increasing urban area and decreasing agricultural and grass land, the annual streamflow in the most of twenty-three subbasins were also increased. Besides, due to the increasing rainfall in wet season and decreasing rainfall in dry season, the difference of streamflow between wet season and dry season are also increased. This result indicates a more stringent challenge on the water resource management in future. Therefore, impacts on water resource caused by climate change and land use change should be considered in water resource planning for the Datuan river watershed. Keywords: SWAT, GCM, CLUE-s, streamflow, climate change, land use change
Assessing the controls and uncertainties on mean transit times in contrasting headwater catchments
NASA Astrophysics Data System (ADS)
Cartwright, Ian; Irvine, Dylan; Burton, Chad; Morgenstern, Uwe
2018-02-01
Estimating the time required for water to travel through headwater catchments from where it recharges to where it discharges into streams (the transit time) is important for understanding catchment behaviour. This study uses tritium (3H) activities of stream water to estimate the mean transit times of water in the upper Latrobe and Yarra catchments, southeast Australia, at different flow conditions. The 3H activities of the stream water were between 1.26 and 1.99 TU, which are lower than those of local rainfall (2.6 to 3.0 TU). 3H activities in individual subcatchments are almost invariably lowest at low streamflows. Mean transit times calculated from the 3H activities using a range of lumped parameter models are between 7 and 62 years and are longest during low streamflows. Uncertainties in the estimated mean transit times result from uncertainties in the geometry of the flow systems, uncertainties in the 3H input, and macroscopic mixing. In addition, simulation of 3H activities in FEFLOW indicates that heterogeneous hydraulic conductivities increase the range of mean transit times corresponding to a specific 3H activity. The absolute uncertainties in the mean transit times may be up to ±30 years. However, differences between mean transit times at different streamflows in the same catchment or between different subcatchments in the same area are more reliably estimated. Despite the uncertainties, the conclusions that the mean transit times are years to decades and decrease with increasing streamflow are robust. The seasonal variation in major ion geochemistry and 3H activities indicate that the higher general streamflows in winter are sustained by water displaced from shallower younger stores (e.g., soils or regolith). Poor correlations between 3H activities and catchment area, drainage density, mean slope, distance to stream, and landuse, imply that mean transit times are controlled by a variety of factors including the hydraulic properties of the soils and aquifers that are difficult to characterise spatially. The long mean transit times imply that there are long-lived stores of water in these catchments that may sustain streamflow over drought periods. Additionally, there may be considerable delay in contaminants reaching the stream.
Long-term streamflow trends on California’s north coast
J. Eli Asarian; Jeffrey D. Walker
2017-01-01
Using streamflow data from the U.S. Geological Survey, we assessed long-term (1953-2012) trends in streamflow on Californiaâs North Coast including many sites in the redwood region. The study area spans from the Smith River to the Mattole River and includes the Eel and Klamath-Trinity basins. Antecedent Precipitation Index (API) is a time-weighted summary of...
Ground-Water Occurrence and Contribution to Streamflow, Northeast Maui, Hawaii
Gingerich, Stephen B.
1999-01-01
The study area lies on the northern flank of the East Maui Volcano (Haleakala) and covers about 129 square miles between the drainage basins of Maliko Gulch to the west and Makapipi Stream to the east. About 989 million gallons per day of rainfall and 176 million gallons per day of fog drip reaches the study area and about 529 million gallons per day enters the ground-water system as recharge. Average annual ground-water withdrawal from wells totals only about 3 million gallons per day; proposed (as of 1998) additional withdrawals total about 18 million gallons per day. Additionally, tunnels and ditches of an extensive irrigation network directly intercept at least 10 million gallons per day of ground water. The total amount of average annual streamflow in gaged stream subbasins upstream of 1,300 feet altitude is about 255 million gallons per day and the total amount of average annual base flow is about 62 million gallons per day. Six major surface-water diversion systems in the study area have diverted an average of 163 million gallons per day of streamflow (including nearly all base flow of diverted streams) for irrigation and domestic supply in central Maui during 1925-97. Fresh ground water is found in two main forms. West of Keanae Valley, ground-water flow appears to be dominated by a variably saturated system. A saturated zone in the uppermost rock unit, the Kula Volcanics, is separated from a freshwater lens near sea level by an unsaturated zone in the underlying Honomanu Basalt. East of Keanae Valley, the ground-water system appears to be fully saturated above sea level to altitudes greater than 2,000 feet. The total average annual streamflow of gaged streams west of Keanae Valley is about 140 million gallons per day at 1,200 feet to 1,300 feet altitude. It is not possible to estimate the total average annual streamflow at the coast. All of the base flow measured in the study area west of Keanae Valley represents ground-water discharge from the high-elevation saturated zone. Total average daily ground-water discharge from the high-elevation saturated zone upstream of 1,200 feet altitude is greater than 38 million gallons per day, all of which is eventually removed from the streams by surface-water diversion systems. Perennial streamflow has been measured at altitudes greater than 3,000 feet in several of the streams. Discharge from the high-elevation saturated zone is persistent even during periods of little rainfall. The total average annual streamflow of the gaged streams east of Keanae Valley is about 109 million gallons per day at about 1,300 feet altitude. It is not possible to estimate the total average annual streamflow at the coast nor at higher altitudes. All of the base flow measured east of Keanae Valley represents ground-water discharge from the vertically extensive freshwater-lens system. Total average daily ground-water discharge to gaged streams upstream of 1,200 feet altitude is about 27 million gallons per day. About 19 million gallons per day of ground water discharges through the Kula and Hana Volcanics between about 500 feet and 1,300 feet altitude in the gaged stream sub-basins. About 13 million gallons per day of this discharge is in Hanawi Stream. The total ground-water discharge above 500 feet altitude in this part of the study area is greater than 56 million gallons per day.
Veenhuis, Jack E.
2002-01-01
The upper middle Rio Grande Basin, as defined by the U.S. Army Corps of Engineers, extends from the headwaters of the Rio Grande in southwestern Colorado to Fort Quitman, Texas. Most of the basin has a semiarid climate typical of the southwestern United States. This climate drives a highly variable streamflow regime that contributes to the complexity of water management in the basin. Currently, rapid population growth in the basin has resulted in increasing demands on the hydrologic system. Water management decisions have become increasingly complex because of the broad range of interests and issues. For these reasons, the U.S. Geological Survey, in cooperation with the City of Albuquerque, New Mexico, conducted paired flow measurements at two cross sections to determine cross-sectional loss in the Albuquerque reach of the Rio Grande. This report statistically summarizes flow losses in the Albuquerque reach of the Rio Grande during the winter nonirrigation season from December 1996 to February 2000. The two previous flow-loss investigations are statistically summarized. Daily mean flow losses are calculated for the winter nonirrigation season using daily mean flows at three selected Rio Grande streamflow-gaging stations.For the winter nonirrigation season cross-sectional measurements (1996-2000), an average of 210 cubic feet per second was returned to the river between the measurement sites, of which 165 cubic feet per second was intercepted by riverside drains along the 21.9-mile reach from the Rio Grande near Bernalillo to the Rio Grande at Rio Bravo Bridge streamflow-gaging stations. Total cross-sectional losses in this reach averaged about 90 cubic feet per second. Regression equations were determined for estimating downstream total outflow from upstream total inflow for all three paired measurement studies. Regression equations relating the three daily mean flow recording stations also were determined. In each succeeding study, additional outside variables were controlled, which provided more accurate flow-loss measurements. Regression-equation losses between measurement cross sections ranged from 1.9 to 7.9 percent during the nonirrigation season and from about 5.9 to 6.4 percent during the irrigation season. Mean and median loss by reach length for all three daily mean flow stations and all three cross-sectional measurement reaches showed consistent flow loss per mile by season with allowance for nonideal river conditions for the initial measurement studies. Unsteady measurement conditions were reflected in the regression equation mean-square errors and ultimately in the change in daily mean discharge at the Rio Grande at Albuquerque gaging station during the measurement periods.
NASA Astrophysics Data System (ADS)
Krishnaswamy, Jagdish; Bonell, Michael; Venkatesh, Basappa; Purandara, Bekal K.; Lele, Sharachchandra; Kiran, M. C.; Reddy, Veerabasawant; Badiger, Shrinivas; Rakesh, K. N.
2012-11-01
SummaryThe effects of forest degradation and use and establishment of tree-plantations on degraded or modified forest ecosystems at multi-decadal time-scales using tree-plantations on the streamflow response are less studied in the humid tropics when compared to deforestation and forest conversion to agriculture. In the Western Ghats of India (Uttar Kannada, Karnataka State), a previous soil hydraulic conductivity survey linked with rain IDF (intensity-duration-frequency) had suggested a greater occurrence of infiltration-excess overland within the degraded forest and reforested areas and thus potentially higher streamflow (Bonell et al., 2010). We further tested these predictions in Uttar Kannada by establishing experimental basins ranging from 7 to 23 ha across three ecosystems, (1) remnant tropical evergreen Forest (NF), (2) heavily-used former evergreen forest which now has been converted to tree savanna, known as degraded forest (DF) and (3) exotic Acacia plantations (AC, Acacia auriculiformis) on degraded former forest land. In total, 11 basins were instrumented (3 NF, 4 AC and 4 DF) in two geomorphological zones, i.e., Coastal and Up-Ghat (Malnaad) and at three sites (one Coastal, two Up-Ghat). The rainfall-streamflow observations collected (at daily and also at a 36 min time resolutions in the Coastal basins) over a 2-3 year period (2003-2005) were analysed. In both the Coastal and Up-Ghat basins, the double mass curves showed during the rainy season a consistent trend in favour of more proportion of streamflow in the rank order DF > AC > NF. These double mass curves provide strong evidence that overland flow is progressively becomes a more dominant stormflow pathway. Across all sites, NF converted 28.4 ± 6.41stdev% of rainfall into total streamflow in comparison to 32.7 ± 6.97stdev% in AC and 45.3 ± 9.61stdev% in DF. Further support for the above trends emerges from the quickflow ratio QF/Q for the Coastal basins. There are much higher values for both the DF and AC land covers, and their rank order DF > AC > NF. The quickflow response ratio QF/P is also the highest for the DF basin, and along with the QF/Q ratio, can exceed 90%. The corresponding delayed flow response ratios, QD/P clearly show the largest QD yields as a proportion of event precipitation from the Forest (NF1). The application of linear model supported these differences (e.g. 10-36% difference between NF and DF, p < 0.001) in the storm hydrologic response of the Coastal basins. The exception was QF/P where there was a higher uncertainty connected with inter-basin mean differences. Cross-correlation plots for rain-streamflow and corresponding lag regression models for three storm events in the Coastal basins suggested the existence of alternative stormflow pathways with multiple lags with peaks between ˜12 and 24 h in NF, compared to respective bimodal peaks at ˜1 and 16 h in AC and ˜1 and 12 h in DF. The long time lags for NF are suggestive of deep subsurface stormflow and groundwater as the contributing sources to the storm hydrograph. The short time lags in DF and AC are indicative of overland flow and so 'memory' of the previous degraded land cover is retained in AC as supported by previous hydraulic conductivity data. As potential and actual evapotranspiration is likely to be depressed during the monsoon, differences in streamflow and run-off responses between land-cover types is largely attributed to differences in soil infiltration and hydrologic pathways. Enhancing infiltration and reducing run-off in managed ecosystems should be explored in the terms of the context of other ecosystem services and biodiversity.
Multi-decadal Decline of Southeast United States Streamflow
NASA Astrophysics Data System (ADS)
Tootle, G. A.; Lakshmi, V.; Therrell, M.; Huffaker, R.; Elliott, E. A.
2017-12-01
Unprecedented population growth combined with environmental and energy demands have led to water conflict in the Southeastern United States. The states of Florida, Georgia and Alabama have recently engaged in litigation on minimum in-stream flows to maintain ecosystems, fisheries and energy demands while satisfying a growing thirst in metropolitan Atlanta. A study of Southeastern United States (Alabama, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina and Tennessee) streamflow identified a declining pattern of flow over the past 25 years with increased dry periods being observed in the last decade. When evaluating calendar year streamflow for (56) unimpaired streamflow stations, a robust period of streamflow in the 1970's was followed by a consistent decline in streamflow from 1990 to present. In evaluating 20-year, 10-year and 5-year time periods of annual streamflow volume, the past decade reveals historic lows for each of these periods. When evaluating the influence of high frequency (e.g., El Nino-Southern Oscillation - ENSO) and low frequency (e.g., Atlantic Multi-decadal Oscillation - AMO) climatic phenomenon, the shift of the AMO from a cold phase to a warm phase in the 1990's combined with multiple La Nina events may be associated with the streamflow decline.
Operational Hydrological Forecasting During the Iphex-iop Campaign - Meet the Challenge
NASA Technical Reports Server (NTRS)
Tao, Jing; Wu, Di; Gourley, Jonathan; Zhang, Sara Q.; Crow, Wade; Peters-Lidard, Christa D.; Barros, Ana P.
2016-01-01
An operational streamflow forecasting testbed was implemented during the Intense Observing Period (IOP) of the Integrated Precipitation and Hydrology Experiment (IPHEx-IOP) in May-June 2014 to characterize flood predictability in complex terrain. Specifically, hydrological forecasts were issued daily for 12 headwater catchments in the Southern Appalachians using the Duke Coupled surface-groundwater Hydrology Model (DCHM) forced by hourly atmospheric fields and QPFs (Quantitative Precipitation Forecasts) produced by the NASA-Unified Weather Research and Forecasting (NU-WRF) model. Previous day hindcasts forced by radar-based QPEs (Quantitative Precipitation Estimates) were used to provide initial conditions for present day forecasts. This manuscript first describes the operational testbed framework and workflow during the IPHEx-IOP including a synthesis of results. Second, various data assimilation approaches are explored a posteriori (post-IOP) to improve operational (flash) flood forecasting. Although all flood events during the IOP were predicted by the IPHEx operational testbed with lead times of up to 6 h, significant errors of over- and, or under-prediction were identified that could be traced back to the QPFs and subgrid-scale variability of radar QPEs. To improve operational flood prediction, three data-merging strategies were pursued post-IOP: (1) the spatial patterns of QPFs were improved through assimilation of satellite-based microwave radiances into NU-WRF; (2) QPEs were improved by merging raingauge observations with ground-based radar observations using bias-correction methods to produce streamflow hindcasts and associated uncertainty envelope capturing the streamflow observations, and (3) river discharge observations were assimilated into the DCHM to improve streamflow forecasts using the Ensemble Kalman Filter (EnKF), the fixed-lag Ensemble Kalman Smoother (EnKS), and the Asynchronous EnKF (i.e. AEnKF) methods. Both flood hindcasts and forecasts were significantly improved by assimilating discharge observations into the DCHM. Specifically, Nash-Sutcliff Efficiency (NSE) values as high as 0.98, 0.71 and 0.99 at 15-min time-scales were attained for three headwater catchments in the inner mountain region demonstrating that the assimilation of discharge observations at the basins outlet can reduce the errors and uncertainties in soil moisture at very small scales. Success in operational flood forecasting at lead times of 6, 9, 12 and 15 h was also achieved through discharge assimilation with NSEs of 0.87, 0.78, 0.72 and 0.51, respectively. Analysis of experiments using various data assimilation system configurations indicates that the optimal assimilation time window depends both on basin properties and storm-specific space-time-structure of rainfall, and therefore adaptive, context-aware configurations of the data assimilation system are recommended to address the challenges of flood prediction in headwater basins.
Operational hydrological forecasting during the IPHEx-IOP campaign - Meet the challenge
NASA Astrophysics Data System (ADS)
Tao, Jing; Wu, Di; Gourley, Jonathan; Zhang, Sara Q.; Crow, Wade; Peters-Lidard, Christa; Barros, Ana P.
2016-10-01
An operational streamflow forecasting testbed was implemented during the Intense Observing Period (IOP) of the Integrated Precipitation and Hydrology Experiment (IPHEx-IOP) in May-June 2014 to characterize flood predictability in complex terrain. Specifically, hydrological forecasts were issued daily for 12 headwater catchments in the Southern Appalachians using the Duke Coupled surface-groundwater Hydrology Model (DCHM) forced by hourly atmospheric fields and QPFs (Quantitative Precipitation Forecasts) produced by the NASA-Unified Weather Research and Forecasting (NU-WRF) model. Previous day hindcasts forced by radar-based QPEs (Quantitative Precipitation Estimates) were used to provide initial conditions for present day forecasts. This manuscript first describes the operational testbed framework and workflow during the IPHEx-IOP including a synthesis of results. Second, various data assimilation approaches are explored a posteriori (post-IOP) to improve operational (flash) flood forecasting. Although all flood events during the IOP were predicted by the IPHEx operational testbed with lead times of up to 6 h, significant errors of over- and, or under-prediction were identified that could be traced back to the QPFs and subgrid-scale variability of radar QPEs. To improve operational flood prediction, three data-merging strategies were pursued post-IOP: (1) the spatial patterns of QPFs were improved through assimilation of satellite-based microwave radiances into NU-WRF; (2) QPEs were improved by merging raingauge observations with ground-based radar observations using bias-correction methods to produce streamflow hindcasts and associated uncertainty envelope capturing the streamflow observations, and (3) river discharge observations were assimilated into the DCHM to improve streamflow forecasts using the Ensemble Kalman Filter (EnKF), the fixed-lag Ensemble Kalman Smoother (EnKS), and the Asynchronous EnKF (i.e. AEnKF) methods. Both flood hindcasts and forecasts were significantly improved by assimilating discharge observations into the DCHM. Specifically, Nash-Sutcliff Efficiency (NSE) values as high as 0.98, 0.71 and 0.99 at 15-min time-scales were attained for three headwater catchments in the inner mountain region demonstrating that the assimilation of discharge observations at the basin's outlet can reduce the errors and uncertainties in soil moisture at very small scales. Success in operational flood forecasting at lead times of 6, 9, 12 and 15 h was also achieved through discharge assimilation with NSEs of 0.87, 0.78, 0.72 and 0.51, respectively. Analysis of experiments using various data assimilation system configurations indicates that the optimal assimilation time window depends both on basin properties and storm-specific space-time-structure of rainfall, and therefore adaptive, context-aware configurations of the data assimilation system are recommended to address the challenges of flood prediction in headwater basins.
Zarriello, Phillip J.; Ries, Kernell G.
2000-01-01
Water withdrawals from the 155-square-mile Ipswich River Basin in northeastern Massachusetts affect aquatic habitat, water quality, and recreational use of the river. To better understand the effects of these withdrawals on streamflow, particularly low flow, the Hydrological Simulation Program-FORTRAN (HSPF) was used to develop a watershed-scale precipitation-runoff model of the Ipswich River to simulate its hydrology and complex water-use patterns.An analytical solution was used to compute time series of streamflow depletions resulting from ground-water withdrawals at wells. The flow depletions caused by pumping from the wells were summed along with any surface-water withdrawals to calculate the total withdrawal along a stream reach. The water withdrawals, records of precipitation, and streamflow records on the Ipswich River at South Middleton and at Ipswich for the period 1989?93 were used to calibrate the model. Model-fit analysis indicates that the simulated flows matched observed flows over a wide range of conditions; at a minimum, the coefficient of model-fit efficiency indicates that the model explained 79 percent of the variance in the observed daily flow.Six alternative water-withdrawal and land-use scenarios were simulated with the model. Three scenarios were examined for the 1989?93 calibration period, and three scenarios were examined for the 1961?95 period to test alternative withdrawals and land use over a wider range of climatic conditions, and to compute 1-, 7-, and 30-day low-flow frequencies using a log-Pearson Type III analysis. Flow-duration curves computed from results of the 1989?93 simulations indicate that, at the South Middleton and Ipswich gaging stations, streamflows when no water withdrawals are being made are nearly identical to streamflows when no ground-water withdrawals are made. Streamflow under no water withdrawals at both stations are about an order of magnitude larger at the 99.8 percent exceedence probability than simulations with only ground-water withdrawals. Long-term simulations indicate that the differences between streamflow with no water withdrawals and average 1989?93 water withdrawals is similar to the difference between simulations for the same water-use conditions made for the 1989?93 period at both sites. The 7-day, 10-year low-flow (7Q10, a widely used regulatory statistic) at the South Middleton station was 4.1 cubic feet per second (ft3/s) with no water withdrawals and 1991 land use, 5.8 ft3/s no withdrawals and undeveloped land, and 0.54 ft3/s with average 1989?93 water withdrawals and 1991 land use. The 7Q10 at the Ipswich station was about 8.3 ft3/s for simulations with no water withdrawals for both the 1991 land use and the undeveloped land conditions, and 2.7 ft3/s for simulations with average 1989?93 water withdrawals and 1991 land use. Simulation results indicate that surface-water withdrawals have little effect on the duration and frequency of low flows, but the cumulative ground-water withdrawals substantially decrease low flows.
NASA Astrophysics Data System (ADS)
Rosario Conticello, Federico; Cioffi, Francesco; Lall, Upmanu; Merz, Bruno
2017-04-01
The role of atmospheric rivers (ARs) in inducing High Streamflow Events (HSEs) in Europe has been confirmed by numerous studies. Here, we assume as HSEs the streamflows exceeding the 99th percentile of daily flowrate time series measured at streamflow gauges. Among the indicators of ARs are: the Integrated Water Vapor (IWV) and Integrated Water Vapor Transport (IVT). For both indicators the literature suggests thresholds in order to identify ARs. Furthermore, local thresholds of such indices are used to assess the occurrence of HSEs in a given region. Recent research on ARs still leaves room for open issues: 1) The literature is not unanimous in defining which of the two indicators is better. 2) The selection of the thresholds is based on subjective assessments. 3) The predictability of HSEs at the local scale associated with these indices seems to be weak and to exist only in the winter months. In order to address these issues, we propose an original methodology: (i) to choose between the two indicators which one is the most suitable for HSEs predictions; (ii) to select IWT and/or IVT (IVT/IWV) local thresholds in a more objective way; (iii) to implement an algorithm able to determine whether a IVT/IWV configuration is inducing HSEs, regardless of the season. In pursuing this goal, besides IWV and IVT fields, we introduce as further predictor the geopotential height at 850 hPa (GPH850) field, that implicitly contains information about the pattern of temperature, direction and intensity of the winds. In fact, the introduction of the GPH850 would help to improve the assessment of the occurrence of HSEs throughout the year. It is also plausible to hypothesize, that IVT/IWV local thresholds could vary in dependence of the GPH850 configuration. In this study, we propose a model to statistically relate these predictors, IVT/IWV and GPH850, to the simultaneous occurrence of HSEs in one or more streamflow gauges in UK and Germany. Historical data from 57 streamflow gauges in UK and 61 streamflow gauges in Germany, as well as reanalysis data of the 850 hPa geopotential fields bounded from 90W to 70E and from 20N to 80N are used. The common period is 1960 to 2012. The link between GPH850 and HSEs, and more precisely, the identification of the GPH850 states potentially able to generate HSEs is performed by a combined Kohonen Networks (Self Organized Map, SOM) and Event Syncronization approach. Complex network and modularity methods are used to cluster streamflow gauges that share common GPH850 configurations. Then a model based on a conditional Poisson distribution is carried out, in which the parameter of the Poisson distribution is assumed to be a nonlinear function of GPH850 state and IVT/ IWV. This model allows for the identification of the threshold of IVT/IWV beyond which there is the HSE highest probability.
Durbin, Timothy J.
1974-01-01
The Stanford Watershed Model was used to simulate the effects of urbanization on the discharge from five drainage basins in the upper Santa Ana Valley, an area with an average annual precipitation of 15 inches. The drainage basins ranged in size from 3.72 to 83.4 square miles. Using the model, synthetic records of streamflow for each basin were generated to represent various degrees of urban development. Examination of the synthetic records indicated that urbanization has the following effects on streamflow in the area:Average annual runoff from a drainage basin with an effective impervious area of 10 percent of the drainage area is approximately 2 inches, and increases by 1 inch for each increase in effective impervious cover equal to 10 percent of the drainage area. About 30 percent of a fully urbanized area is effectively impervious.Urbanization can increase the magnitude of peak discharge and daily mean discharge with a recurrence interval of 2 years by a factor of three to six.Peak discharges and daily mean discharges that have recurrence intervals greater than a limiting value ranging from 50 to 200 years or more are little affected by urbanization.
NCEP/NLDAS Drought Monitoring and Prediction
NASA Astrophysics Data System (ADS)
Xia, Y.; Ek, M.; Wood, E.; Luo, L.; Sheffield, J.; Lettenmaier, D.; Livneh, B.; Cosgrove, B.; Mocko, D.; Meng, J.; Wei, H.; Restrepo, P.; Schaake, J.; Mo, K.
2009-05-01
The NCEP Environmental Modeling Center (EMC) collaborated with its CPPA (Climate Prediction Program of the Americas) partners to develop a North American Land Data Assimilation System (NLDAS, http://www.emc.ncep.noaa.gov/mmb/nldas) to monitor and predict the drought over the Continental United States (CONUS). The realtime NLDAS drought monitor, executed daily at NCEP/EMC, including daily, weekly and monthly anomaly and percentile of six fields (soil moisture, snow water equivalent, total runoff, streamflow, evaporation, precipitation) outputted from four land surface models (Noah, Mosaic, SAC, and VIC) on a common 1/8th degree grid using common hourly land surface forcing. The non-precipitation surface forcing is derived from NCEP's retrospective and realtime North American Regional Reanalysis System (NARR). The precipitation forcing is anchored to a daily gauge-only precipitation analysis over CONUS that applies a Parameter-elevation Regressions on Independent Slopes Model (PRISM) correction. This daily precipitation analysis is then temporally disaggregated to hourly precipitation amounts using radar and satellite precipitation. The NARR- based surface downward solar radiation is bias-corrected using seven years (1997-2004) of GOES satellite- derived solar radiation retrievals. The uncoupled ensemble seasonal drought prediction utilizes the following three independent approaches for generating downscaled ensemble seasonal forecasts of surface forcing: (1) Ensemble Streamflow Prediction, (2) CPC Official Seasonal Climate Outlook, and (3) NCEP CFS ensemble dynamical model prediction. For each of these three approaches, twenty ensemble members of forcing realizations are generated using a Bayesian merging algorithm developed by Princeton University. The three forcing methods are then used to drive the VIC model in seasonal prediction mode over thirteen large river basins that together span the CONUS domain. One to nine month ensemble seasonal prediction products such as air temperature, precipitation, soil moisture, snowpack, total runoff, evaporation and streamflow are derived for each forcing approach. The anomalies and percentiles of the predicted products for each approach may be used for CONUS drought prediction. This system is executed at the beginning of each month and distributes its products by the 10th of each month. The prediction products are evaluated using corresponding monitoring products for the VIC model and are compared with the prediction products from other research groups (e.g., University of Washington at Seattle, NASA Goddard) in the CONUS.
NASA Astrophysics Data System (ADS)
Clark, E.; Wood, A.; Nijssen, B.; Clark, M. P.
2017-12-01
Short- to medium-range (1- to 7-day) streamflow forecasts are important for flood control operations and in issuing potentially life-save flood warnings. In the U.S., the National Weather Service River Forecast Centers (RFCs) issue such forecasts in real time, depending heavily on a manual data assimilation (DA) approach. Forecasters adjust model inputs, states, parameters and outputs based on experience and consideration of a range of supporting real-time information. Achieving high-quality forecasts from new automated, centralized forecast systems will depend critically on the adequacy of automated DA approaches to make analogous corrections to the forecasting system. Such approaches would further enable systematic evaluation of real-time flood forecasting methods and strategies. Toward this goal, we have implemented a real-time Sequential Importance Resampling particle filter (SIR-PF) approach to assimilate observed streamflow into simulated initial hydrologic conditions (states) for initializing ensemble flood forecasts. Assimilating streamflow alone in SIR-PF improves simulated streamflow and soil moisture during the model spin up period prior to a forecast, with consequent benefits for forecasts. Nevertheless, it only consistently limits error in simulated snow water equivalent during the snowmelt season and in basins where precipitation falls primarily as snow. We examine how the simulated initial conditions with and without SIR-PF propagate into 1- to 7-day ensemble streamflow forecasts. Forecasts are evaluated in terms of reliability and skill over a 10-year period from 2005-2015. The focus of this analysis is on how interactions between hydroclimate and SIR-PF performance impact forecast skill. To this end, we examine forecasts for 5 hydroclimatically diverse basins in the western U.S. Some of these basins receive most of their precipitation as snow, others as rain. Some freeze throughout the mid-winter while others experience significant mid-winter melt events. We describe the methodology and present seasonal and inter-basin variations in DA-enhanced forecast skill.
Liscum, Fred; East, Jeffery W.
2000-01-01
The City of Houston is considering the transfer of water from the Trinity River to Lake Houston (on the San Jacinto River) to alleviate concerns about adequate water supplies for future water demands. The U.S. Geological Survey, in cooperation with the City of Houston, conducted a study to estimate the effects on the water quality of Lake Houston from the transfer of Trinity River water. A water-quality model, CE–QUAL–W2, was used to simulate six water-quality properties and constituents for scenarios of interbasin transfer of Trinity River water. Three scenarios involved the transferred Trinity River water augmenting streamflow in the East Fork of Lake Houston, and three scenarios involved the transferred water replacing streamflow from the West Fork of the San Jacinto River.The estimated effects on Lake Houston were determined by comparing volume-weighted daily mean water temperature, phosphorus, ammonia nitrogen, nitrite plus nitrate nitrogen, algal biomass, and dissolved oxygen simulated for each of the transfer scenarios to simulations for a base dataset. The effects of the interbasin transfer on Lake Houston do not appear to be detrimental to water temperature, ammonia nitrogen, or dissolved oxygen. Phosphorus and nitrite plus nitrate nitrogen showed fairly large changes when Trinity River water was transferred to replace West Fork San Jacinto River streamflow. Algal biomass showed large decreases when Trinity River water was transferred to augment East Fork Lake Houston streamflow and large increases when Trinity River water was transferred to replace West Fork San Jacinto River streamflow. Regardless of the scenario simulated, the model indicated that light was the limiting factor for algal biomass growth.
Instream flow characterization of upper Salmon River basin streams, central Idaho, 2004
Maret, Terry R.; Hortness, Jon E.; Ott, Douglas S.
2005-01-01
Anadromous fish populations in the Columbia River Basin have plummeted in the last 100 years. This severe decline led to Federal listing of Chinook salmon (Oncorhynchus tshawytscha) and steelhead trout (Oncorhynchus mykiss) stocks as endangered or threatened under the Endangered Species Act (ESA) in the 1990s. Historically, the upper Salmon River Basin (upstream of the confluence with the Pahsimeroi River) in Idaho provided migration corridors and significant habitat for these ESA-listed species, in addition to the ESA-listed bull trout (Salvelinus confluentus). Human development has modified the original streamflow conditions in many streams in the upper Salmon River Basin. Summer streamflow modifications resulting from irrigation practices, have directly affected quantity and quality of fish habitat and also have affected migration and (or) access to suitable spawning and rearing habitat for these fish. As a result of these ESA listings and Action 149 of the Federal Columbia River Power System Biological Opinion of 2000, the Bureau of Reclamation was tasked to conduct streamflow characterization studies in the upper Salmon River Basin to clearly define habitat requirements for effective species management and habitat restoration. These studies include collection of habitat and streamflow information for the Physical Habitat Simulation System model, a widely applied method to determine relations between habitat and discharge requirements for various fish species and life stages. Model results can be used by resource managers to guide habitat restoration efforts by evaluating potential fish habitat and passage improvements by increasing streamflow. In 2004, instream flow characterization studies were completed on Salmon River and Beaver, Pole, Champion, Iron, Thompson, and Squaw Creeks. Continuous streamflow data were recorded upstream of all diversions on Salmon River and Pole, Iron, Thompson, and Squaw Creeks. In addition, natural summer streamflows were estimated for each study site using regional regression equations. This report describes Physical Habitat Simulation System modeling results for bull trout, Chinook salmon, and steelhead trout during summer streamflows. Habitat/discharge relations were summarized for adult and spawning life stages at each study site. Adult fish passage and discharge relations were evaluated at specific transects identified as a potential low-streamflow passage barrier at each study site. Continuous summer water temperature data for selected study sites were summarized and compared with Idaho Water Quality Standards and various water temperature requirements of targeted fish species. Continuous summer water temperature data recorded in 2003 and streamflow relations were evaluated for Fourth of July Creek using the Stream Segment Temperature model that simulates mean and maximum daily water temperatures with changes in streamflow. Results of these habitat studies can be used to prioritize and direct cost-effective actions to improve fish habitat for ESA-listed anadromous and native fish species in the basin. These actions may include acquiring water during critical low-flow periods by leasing or modifying irrigation delivery systems to minimize out-of-stream diversions.
Retrospective Analysis of Low Flows at Headwater Watersheds in Wyoming
NASA Astrophysics Data System (ADS)
Voutchkova, D. D.; Miller, S. N.
2016-12-01
Understanding summer low-flow variability and change in the mountainous West has important implications for water allocations downstream and for maintaining water availability for drinking water supply, reservoir storage, industrial, agricultural, and ecological needs. Wildfires and insect infestations are classical disturbance hydrology topics. It is unclear, however, what are their effects on streamflow and in particular low-flows, when vegetation disturbances are overlapping in time and combined with highly variable and potentially changing local climate. The purpose of this study, therefore, is to quantify changes in low-flows resulting from disturbance in headwater streams. Here we present a retrospective analysis based on: (1) 49-75 complete water years (wy) of daily streamflow data (USGS) for 14 high-elevation headwater watersheds with varying areas (60-1730 km2, 86-100% of watershed area >2000masl) and evergreen forest cover (15-82%), (2) 25-36 complete wy of daily snow-water equivalent accumulation (SWE) and precipitation data from Wyoming SNOTEL stations, (3) burned area boundaries for 20wy (MTBS project), (4) aerial surveys by R1, R2, R4 Forest Service Regions for 18wy (data on tree mortality). We quantify the change in various low-flow characteristics (e.g. post-snowmelt baseflow, Q90 and Q95, 3-,7-, 30- and 90-day annual minima etc.) while accounting for local inter- and multi-annual climate variability by using SWE accumulation data, as it integrates both temperature and precipitation changes. Our approach differs from typical before-after field-based investigation for paired watersheds, as it provides a synthesis over large temporal and spatial scales, resulting in spectrum of possible hydrologic responses due to varying disturbance severity. Quantifying the changes in low-flows and low-flow variability will improve our understanding and will facilitate water management and planning at local state-wide level.
Outlaw, G.S.; Butner, D.E.; Kemp, R.L.; Oaks, A.T.; Adams, G.S.
1992-01-01
Rainfall, stage, and streamflow data in the Murfreesboro area, Middle Tennessee, were collected from March 1989 through July 1992 from a network of 68 gaging stations. The network consists of 10 tipping-bucket rain gages, 2 continuous-record streamflow gages, 4 partial-record flood hydrograph gages, and 72 crest-stage gages. Data collected by the gages includes 5minute time-step rainfall hyetographs, 15-minute time-step flood hydrographs, and peak-stage elevations. Data are stored in a computer data base and are available for many computer modeling and engineering applications.
Streamflow alteration at selected sites in Kansas
Juracek, Kyle E.; Eng, Ken
2017-06-26
An understanding of streamflow alteration in response to various disturbances is necessary for the effective management of stream habitat for a variety of species in Kansas. Streamflow alteration can have negative ecological effects. Using a modeling approach, streamflow alteration was assessed for 129 selected U.S. Geological Survey streamgages in the State for which requisite streamflow and basin-characteristic information was available. The assessment involved a comparison of the observed condition from 1980 to 2015 with the predicted expected (least-disturbed) condition for 29 streamflow metrics. The metrics represent various characteristics of streamflow including average flow (annual, monthly) and low and high flow (frequency, duration, magnitude).Streamflow alteration in Kansas was indicated locally, regionally, and statewide. Given the absence of a pronounced trend in annual precipitation in Kansas, a precipitation-related explanation for streamflow alteration was not supported. Thus, the likely explanation for streamflow alteration was human activity. Locally, a flashier flow regime (typified by shorter lag times and more frequent and higher peak discharges) was indicated for three streamgages with urbanized basins that had higher percentages of impervious surfaces than other basins in the State. The combination of localized reservoir effects and regional groundwater pumping from the High Plains aquifer likely was responsible, in part, for diminished conditions indicated for multiple streamflow metrics in western and central Kansas. Statewide, the implementation of agricultural land-management practices to reduce runoff may have been responsible, in part, for a diminished duration and magnitude of high flows. In central and eastern Kansas, implemented agricultural land-management practices may have been partly responsible for an inflated magnitude of low flows at several sites.
The influence of north Pacific atmospheric circulation on streamflow in the west
Cayan, Daniel R.; Peterson, David H.
1989-01-01
The annual cycle and nonseasonal variability of streamflow over western North America and Hawaii is studied in terms of atmospheric forcing elements. This study uses several decades of monthly average streamflow beginning as early as the late 1800's over a network of 38 stations. In addition to a strong annual cycle in mean streamflow and its variance at most of the stations, there is also a distinct annual cycle in the autocorrelation of anomalies that is related to the interplay between the annual cycles of temperature and precipitation. Of particular importance to these lag effects is the well-known role of water stored as snow pack, which controls the delay between peak precipitation and peak flow and also introduces persistence into the nonseasonal streamflow anomalies, with time scales from 1 month to over 1 year. The degree to which streamflow is related to winter atmospheric circulation over the North Pacific and western North America is tested using correlations with time averaged, gridded sea level pressure (SLP), which begins in 1899. Streamflow fluctuations show significant large-scale correlations for the winter (December through February) mean SLP anomaly patterns over the North Pacific with maximum correlations ranging from 0.3 to about 0.6. For streams along the west coast corridor the circulation pattern associated with positive streamflow anomalies is low pressure centered off the coast to the west or northwest, indicative of increased winter storms and an anomalous westerly-to-southwesterly wind component. For streams in the interior positive streamflow anomalies are associated with a positive SLP anomaly stationed remotely over the central North Pacific, and with negative but generally weaker SLP anomalies locally. One important influence on streamflow variability is the strength of the Aleutian Low in winter. This is represented by the familiar Pacific-North America (PNA) index and also by an index defined herein the “CNP” (Central North Pacific). This index, beginning in 1899, is taken to be the average of the SLP anomaly south of the Aleutians and the western Gulf of Alaska. Correlations between PNA or CNP and regional anomalies reflect streamflow the alternations in strength and position of the mean North Pacific storm track entering North America as well as shifts in the trade winds over the subtropical North Pacific. Regions whose streamflow is best tuned to the PNA or CNP include coastal Alaska, the northwestern United States, and Hawaii; the latter two regions have the opposite sign anomaly as the former. The pattern of streamflow variations associated with El Niño is similar, but the El Niño signal also includes a tendency for greater than normal streamflow in the southwestern United States. These indices are significantly correlated with streamflow at one to two seasons in advance of the December–August period, which may allow modestly skillful forecasts. It is important to note that streamflow variability in some areas, such as British Columbia and California, does not respond consistently to these broad scale Pacific atmospheric circulation indices, but is related to regional atmospheric anomaly features over the eastern North Pacific. Spatially, streamflow anomalies are fairly well correlated over scales of several hundred kilometers. Inspection of the spatial anomalies of stream-flow in this study suggest an asymmetry in the spatial pattern of positive versus negative streamflow anomalies in the western United States: dry patterns have tended to be larger and more spatially coherent than wet patterns.
Past and future changes in streamflow in the U.S. Midwest: Bridging across time scales
NASA Astrophysics Data System (ADS)
Villarini, G.; Slater, L. J.; Salvi, K. A.
2017-12-01
Streamflows have increased notably across the U.S. Midwest over the past century, principally due to changes in precipitation and land use / land cover. Improving our understanding of the physical drivers that are responsible for the observed changes in discharge may enhance our capability of predicting and projecting these changes, and may have large implications for water resources management over this area. This study will highlight our efforts towards the statistical attribution of changes in discharge across the U.S. Midwest, with analyses performed at the seasonal scale from low to high flows. The main drivers of changing streamflows that we focus on are: urbanization, agricultural land cover, basin-averaged temperature, basin-averaged precipitation, and antecedent soil moisture. Building on the insights from this attribution, we will examine the potential predictability of streamflow across different time scales, with lead times ranging from seasonal to decadal, and discuss a potential path forward for engineering design for future conditions.
Identification of symmetric and asymmetric responses in seasonal streamflow globally to ENSO phase
NASA Astrophysics Data System (ADS)
Lee, Donghoon; Ward, Philip J.; Block, Paul
2018-04-01
The phase of the El Niño Southern Oscillation (ENSO) has large-ranging effects on streamflow and hydrologic conditions globally. While many studies have evaluated this relationship through correlation analysis between annual streamflow and ENSO indices, an assessment of potential asymmetric relationships between ENSO and streamflow is lacking. Here, we evaluate seasonal variations in streamflow by ENSO phase to identify asymmetric (AR) and symmetric (SR) spatial pattern responses globally and further corroborate with local precipitation and hydrological condition. The AR and SR patterns between seasonal precipitation and streamflow are identified at many locations for the first time. Our results identify strong SR patterns in particular regions including northwestern and southern US, northeastern and southeastern South America, northeastern and southern Africa, southwestern Europe, and central-south Russia. The seasonally lagged anomalous streamflow patterns are also identified and attributed to snowmelt, soil moisture, and/or cumulative hydrological processes across river basins. These findings may be useful in water resources management and natural hazards planning by better characterizing the propensity of flood or drought conditions by ENSO phase.
Substantial proportion of global streamflow less than three months old
NASA Astrophysics Data System (ADS)
Jasechko, Scott; Kirchner, James W.; Welker, Jeffrey M.; McDonnell, Jeffrey J.
2016-02-01
Biogeochemical cycles, contaminant transport and chemical weathering are regulated by the speed at which precipitation travels through landscapes and reaches streams. Streamflow is a mixture of young and old precipitation, but the global proportions of these young and old components are not known. Here we analyse seasonal cycles of oxygen isotope ratios in rain, snow and streamflow compiled from 254 watersheds around the world, and calculate the fraction of streamflow that is derived from precipitation that fell within the past two or three months. This young streamflow accounts for about a third of global river discharge, and comprises at least 5% of discharge in about 90% of the catchments we investigated. We conclude that, although typical catchments have mean transit times of years or even decades, they nonetheless can rapidly transmit substantial fractions of soluble contaminant inputs to streams. Young streamflow is less prevalent in steeper landscapes, which suggests they are characterized by deeper vertical infiltration. Because young streamflow is derived from less than 0.1% of global groundwater storage, we conclude that this thin veneer of aquifer storage will have a disproportionate influence on stream water quality.
Evaluation of non-stationarity of floods in the Northeastern and Upper Midwest United States
NASA Astrophysics Data System (ADS)
Dhakal, N.; Palmer, R. N.
2017-12-01
Climate change is likely to impact precipitation as well as snow accumulation and melt in the Northeastern and Upper Midwest Unites States, ultimately affecting the quantity and seasonal distribution of streamflow. Such information is crucial for flood protection polices for example for regional flood frequency analysis. The objective of this study is to analyze seasonality and magnitude of long-term daily annual maximum streamflow (AMF) records and its changes for 158 sites in Northeastern and Upper Midwest Unites States. Temporal trends were analyzed based on two 30-year blocks (1951-1980 and 1981-2010) of AMF. Seasonality is assessed based on nonparametric directional/circular statistical method that allows for an adaptive estimation of seasonal density. The results for temporal change in seasonality showed mixed pattern/trend across the stations. While for majority of the stations, the distribution of AMF timing is strongly unimodal (concentrated around Spring season) for the earlier time period, the strength in the modes have gotten weaker during the recent time period for a number of stations along the coastal states indicating the emergence of multiple modes and change in seasonality therein. Assessment of the temporal change in magnitude of AMF based on the Mann-Kendall nonparametric test shows that majority of the stations do not show significant increasing or decreasing trend for either time period. It is also observed that comparatively more stations show increasing trends in magnitude based on AMF from earlier time period and most of these stations are coastal sites concentrated in the southeastern part of the region. Our study focused on both seasonality and magnitude of AMF has important implications for flood management and mitigation.
Breault, Robert F.
2009-01-01
Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board, Rhode Island's largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamflow-gaging stations; 10 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate instantaneous (15-minute) loads of sodium and chloride during water year (WY) 2002 (October 1, 2001 to September 30, 2002). Water-quality samples were also collected at 35 of 37 sampling stations in the Scituate Reservoir drainage area by the Providence Water Supply Board during WY 2002 as part of a long-term sampling program. Water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2002. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed about 12.6 cubic feet per second (ft3/s) to the reservoir during WY 2002. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.14 to 8.1 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 534,000 kilograms (kg) of sodium and 851,000 kg of chloride to the Scituate Reservoir during WY 2002; sodium and chloride yields for the tributaries ranged from 2,900 to 40,200 kilograms per square mile (kg/mi2) and from 4,200 to 68,200 kg/mi2, respectively. At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 16.8 milligrams per liter (mg/L), median nitrate concentration was 0.02 mg/L as N, median nitrite concentration was 0.002 mg/L as N, median orthophosphate concentration was 0.03 mg/L as P, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 22 and 14 colony forming units per 100 milliliters (CFU/100 mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrate, nitrite, orthophosphate and total coliform and E. coli bacteria were 21 kg/d (12 kg/d/mi2), 0.04 kg/d (0.014 kg/d/mi2), 0.005 kg/d (0.002 kg/d/mi2), 0.08 kg/d (0.035 kg/d/mi2), and 370 million colony forming units per day (CFUx106/d) (120 CFUx106/d/ mi2) and 300 CFUx106/d (75 CFUx106/d/mi2), respectively.
Smith, Kirk P.; Breault, Robert F.
2011-01-01
Streamflow and water-quality data were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board (PWSB), Rhode Island's largest drinking-water supplier. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgages; 14 of these stations were also equipped with instrumentation capable of continuously monitoring specific conductance and water temperature. Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2010 (October 1, 2009, to September 30, 2010). Water-quality samples also were collected at 37 sampling stations by the PWSB and at 14 monitoring stations by the USGS during WY 2010 as part of a long sampling program; all stations are in the Scituate Reservoir drainage area. Waterquality data collected by PWSB are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2010. The largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed a mean streamflow of about 39 cubic feet per second (ft3/s) to the reservoir during WY 2010. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.7 to 27 ft3/s. Together, tributary streams (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,500,000 kilograms (kg) of sodium and 2,500,000 kg of chloride to the Scituate Reservoir during WY 2010; sodium and chloride yields for the tributaries ranged from 11,000 to 66,000 kilograms per square mile (kg/mi2) and from 18,000 to 110,000 kg/mi2, respectively. At the stations where water-quality samples were collected by the PWSB, the median of the median chloride concentrations was 20.2 milligrams per liter (mg/L), median nitrite concentration was 0.002 mg/L as nitrogen (N), median nitrate concentration was 0.01 mg/L as N, median orthophosphate concentration was 0.06 mg/L as phosphorus, and median concentrations of total coliform and Escherichia coli (E. coli) bacteria were 93 and 16 colony forming units per 100 milliliters (CFU/100mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 170 kg/d (73 kg/d/mi2), 11 g/d (5.3 g/d/mi2), 74 g/d (39 g/d/mi2), 340 g/d (170 g/d/mi2), 5,700 million colony forming units per day (CFUx106/d) (2,300 CFUx106/d/mi2), and 620 CFUx106/d (440 CFUx106/d/mi2), respectively.
NASA Astrophysics Data System (ADS)
Cepeda, Javier; Vargas, Ximena
2017-04-01
In the Andes Mountains, in central Chile, glaciers are a key element to both environment and economy, since they contribute highly to streamflow during the summer season. Many studies have been performed in order to understand the actual contribution of glacial-based streamflow and the expected response of glaciers to climatological alterations such as climate change. This work studies and analyses the historical and future streamflow on the Olivares river basin, located close to Chile's capital city, Santiago, under climatic change scenario RCP8.5. For this, we use two hydrological models with different topology, to have more consistency in the results, and analysing the differences because of the conceptualization of the processes and its spatial scale. DHSVM is a distributed, physically based model, while WEAP is a semi-distributed model that represents some processes conceptually and others physically based. Both models are calibrated considering streamflow and snow cover data from the period 2001-2012 at a daily scale. Additionally, comparisons between the modelled glacier area variations and LANDSAT images are performed to strengthen the calibration process. Climate change projections are obtained from five Global Circulation Models (GCM) under RCP8.5 scenario. Changes in glacier area, volume and glacial streamflow contribution to basin discharge are analysed, comparing two future time lapses, near-future period (2015-2044) and far-future (2045-2074), to a baseline period (1985-2004). The basin has an area of 543 km2, with elevations ranging from 1,528 to 6,024 m.a.s.l. and an important glacier presence. According to the National Glacier Cadastre developed by Chile Water Authority (DGA) in 2012, there are 80 uncovered glaciers within the basin, the most important being Juncal Sur, Olivares Alfa, Beta and Gamma. Glacier area represented 17% of the basin in 1985, while they made up only to 11% in 2015.The glaciers are located at altitudes ranging from 3,500 to 6,000 m.a.s.l., most on the vicinity of 4,500 m.a.s.l. Analysing variations in meteorological information between baseline, for the near and far future periods we obtain an increase of 1.3°C and 2.9°C respectively. Analogously, a decrease of 33.6 mm and 93.2 mm for the annual precipitation is projected for the same corresponding periods. Results from both models show that most of the glacial area will have melted away by the end of the far-future period, with only 1.2 km2 and 6.8 km2 remaining, according to DHSVM and WEAP models respectively. Also for the far future period, total streamflow decreases respect to baseline period between 15 and 46%, while glacier streamflow decreases between 53 and 85% in far future, depending of the GCM and hydrological model used.
NASA Astrophysics Data System (ADS)
Gao, H.; Zhang, S.; Nijssen, B.; Zhou, T.; Voisin, N.; Sheffield, J.; Lee, K.; Shukla, S.; Lettenmaier, D. P.
2017-12-01
Despite its errors and uncertainties, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis real-time product (TMPA-RT) has been widely used for hydrological monitoring and forecasting due to its timely availability for real-time applications. To evaluate the utility of TMPA-RT in hydrologic predictions, many studies have compared modeled streamflows driven by TMPA-RT against gauge data. However, because of the limited availability of streamflow observations in data sparse regions, there is still a lack of comprehensive comparisons for TMPA-RT based hydrologic predictions at the global scale. Furthermore, it is expected that its skill is less optimal at the subbasin scale than the basin scale. In this study, we evaluate and characterize the utility of the TMPA-RT product over selected global river basins during the period of 1998 to 2015 using the TMPA research product (TMPA-RP) as a reference. The Variable Infiltration Capacity (VIC) model, which was calibrated and validated previously, is adopted to simulate streamflows driven by TMPA-RT and TMPA-RP, respectively. The objective of this study is to analyze the spatial and temporal characteristics of the hydrologic predictions by answering the following questions: (1) How do the precipitation errors associated with the TMPA-RT product transform into streamflow errors with respect to geographical and climatological characteristics? (2) How do streamflow errors vary across scales within a basin?
NASA Astrophysics Data System (ADS)
Verkade, J. S.; Brown, J. D.; Reggiani, P.; Weerts, A. H.
2013-09-01
The ECMWF temperature and precipitation ensemble reforecasts are evaluated for biases in the mean, spread and forecast probabilities, and how these biases propagate to streamflow ensemble forecasts. The forcing ensembles are subsequently post-processed to reduce bias and increase skill, and to investigate whether this leads to improved streamflow ensemble forecasts. Multiple post-processing techniques are used: quantile-to-quantile transform, linear regression with an assumption of bivariate normality and logistic regression. Both the raw and post-processed ensembles are run through a hydrologic model of the river Rhine to create streamflow ensembles. The results are compared using multiple verification metrics and skill scores: relative mean error, Brier skill score and its decompositions, mean continuous ranked probability skill score and its decomposition, and the ROC score. Verification of the streamflow ensembles is performed at multiple spatial scales: relatively small headwater basins, large tributaries and the Rhine outlet at Lobith. The streamflow ensembles are verified against simulated streamflow, in order to isolate the effects of biases in the forcing ensembles and any improvements therein. The results indicate that the forcing ensembles contain significant biases, and that these cascade to the streamflow ensembles. Some of the bias in the forcing ensembles is unconditional in nature; this was resolved by a simple quantile-to-quantile transform. Improvements in conditional bias and skill of the forcing ensembles vary with forecast lead time, amount, and spatial scale, but are generally moderate. The translation to streamflow forecast skill is further muted, and several explanations are considered, including limitations in the modelling of the space-time covariability of the forcing ensembles and the presence of storages.
NASA Astrophysics Data System (ADS)
White, Jeremy; Stengel, Victoria; Rendon, Samuel; Banta, John
2017-08-01
Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral
in that they reproduce daily mean streamflow acceptably well according to Nash-Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.
NASA Astrophysics Data System (ADS)
Bergeron, Jean
Snow cover estimation is a principal source of error for spring streamflow simulations in Québec, Canada. Optical and near infrared remote sensing can improve snow cover area (SCA) estimation due to high spatial resolution but is limited by cloud cover and incoming solar radiation. Passive microwave remote sensing is complementary by its near-transparence to cloud cover and independence to incoming solar radiation, but is limited by its coarse spatial resolution. The study aims to create an improved SCA product from blended passive microwave (AMSR-E daily L3 Brightness Temperature) and optical (MODIS Terra and Aqua daily snow cover L3) remote sensing data in order to improve estimation of river streamflow caused by snowmelt with Québec's operational MOHYSE hydrological model through direct-insertion of the blended SCA product in a coupled snowmelt module (SPH-AV). SCA estimated from AMSR-E data is first compared with SCA estimated with MODIS, as well as with in situ snow depth measurements. Results show good agreement (+95%) between AMSR-E-derived and MODIS-derived SCA products in spring but comparisons with Environment Canada ground stations and SCA derived from Advanced Very High Resolution Radiometer (AVHRR) data show lesser agreements (83 % and 74% respectively). Results also show that AMSR-E generally underestimates SCA. Assimilating the blended snow product in SPH-AV coupled with MOHYSE yields significant improvement of simulated streamflow for the aux Écorces et au Saumon rivers overall when compared with simulations with no update during thaw events, These improvements are similar to results driven by biweekly ground data. Assimilation of remotely-sensed passive microwave data was also found to have little positive impact on springflood forecast due to the difficulty in differentiating melting snow from snow-free surfaces. Considering the direct-insertion and Newtonian nudging assimilation methods, the study also shows the latter method to be superior to the former, notably when assimilating noisy data. Keywords: Snow cover, spring streamflow, MODIS, AMSR-E, hydrological model.
Wiley, Jeffrey B.; Curran, Janet H.
2003-01-01
Methods for estimating daily mean flow-duration statistics for seven regions in Alaska and low-flow frequencies for one region, southeastern Alaska, were developed from daily mean discharges for streamflow-gaging stations in Alaska and conterminous basins in Canada. The 15-, 10-, 9-, 8-, 7-, 6-, 5-, 4-, 3-, 2-, and 1-percent duration flows were computed for the October-through-September water year for 222 stations in Alaska and conterminous basins in Canada. The 98-, 95-, 90-, 85-, 80-, 70-, 60-, and 50-percent duration flows were computed for the individual months of July, August, and September for 226 stations in Alaska and conterminous basins in Canada. The 98-, 95-, 90-, 85-, 80-, 70-, 60-, and 50-percent duration flows were computed for the season July-through-September for 65 stations in southeastern Alaska. The 7-day, 10-year and 7-day, 2-year low-flow frequencies for the season July-through-September were computed for 65 stations for most of southeastern Alaska. Low-flow analyses were limited to particular months or seasons in order to omit winter low flows, when ice effects reduce the quality of the records and validity of statistical assumptions. Regression equations for estimating the selected high-flow and low-flow statistics for the selected months and seasons for ungaged sites were developed from an ordinary-least-squares regression model using basin characteristics as independent variables. Drainage area and precipitation were significant explanatory variables for high flows, and drainage area, precipitation, mean basin elevation, and area of glaciers were significant explanatory variables for low flows. The estimating equations can be used at ungaged sites in Alaska and conterminous basins in Canada where streamflow regulation, streamflow diversion, urbanization, and natural damming and releasing of water do not affect the streamflow data for the given month or season. Standard errors of estimate ranged from 15 to 56 percent for high-duration flow statistics, 25 to greater than 500 percent for monthly low-duration flow statistics, 32 to 66 percent for seasonal low-duration flow statistics, and 53 to 64 percent for low-flow frequency statistics.
White, Jeremy; Stengel, Victoria G.; Rendon, Samuel H.; Banta, John
2017-01-01
Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash–Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.
Selective Tree-ring Models: A Novel Method for Reconstructing Streamflow Using Tree Rings
NASA Astrophysics Data System (ADS)
Foard, M. B.; Nelson, A. S.; Harley, G. L.
2017-12-01
Surface water is among the most instrumental and vulnerable resources in the Northwest United States (NW). Recent observations show that overall water quantity is declining in streams across the region, while extreme flooding events occur more frequently. Historical streamflow models inform probabilities of extreme flow events (flood or drought) by describing frequency and duration of past events. There are numerous examples of tree-rings being utilized to reconstruct streamflow in the NW. These models confirm that tree-rings are highly accurate at predicting streamflow, however there are many nuances that limit their applicability through time and space. For example, most models predict streamflow from hydrologically altered rivers (e.g. dammed, channelized) which may hinder our ability to predict natural prehistoric flow. They also have a tendency to over/under-predict extreme flow events. Moreover, they often neglect to capture the changing relationships between tree-growth and streamflow over time and space. To address these limitations, we utilized national tree-ring and streamflow archives to investigate the relationships between the growth of multiple coniferous species and free-flowing streams across the NW using novel species-and site-specific streamflow models - a term we coined"selective tree-ring models." Correlation function analysis and regression modeling were used to evaluate the strengths and directions of the flow-growth relationships. Species with significant relationships in the same direction were identified as strong candidates for selective models. Temporal and spatial patterns of these relationships were examined using running correlations and inverse distance weighting interpolation, respectively. Our early results indicate that (1) species adapted to extreme climates (e.g. hot-dry, cold-wet) exhibit the most consistent relationships across space, (2) these relationships weaken in locations with mild climatic variability, and (3) some species appear to be strong candidates for predicting high flow events, while others may be better at pridicting drought. These findings indicate that selective models may outperform traditional models when reconstructing distinctive aspects of streamflow.
NASA Astrophysics Data System (ADS)
Moeeni, Hamid; Bonakdari, Hossein; Fatemi, Seyed Ehsan
2017-04-01
Because time series stationarization has a key role in stochastic modeling results, three methods are analyzed in this study. The methods are seasonal differencing, seasonal standardization and spectral analysis to eliminate the periodic effect on time series stationarity. First, six time series including 4 streamflow series and 2 water temperature series are stationarized. The stochastic term for these series obtained with ARIMA is subsequently modeled. For the analysis, 9228 models are introduced. It is observed that seasonal standardization and spectral analysis eliminate the periodic term completely, while seasonal differencing maintains seasonal correlation structures. The obtained results indicate that all three methods present acceptable performance overall. However, model accuracy in monthly streamflow prediction is higher with seasonal differencing than with the other two methods. Another advantage of seasonal differencing over the other methods is that the monthly streamflow is never estimated as negative. Standardization is the best method for predicting monthly water temperature although it is quite similar to seasonal differencing, while spectral analysis performed the weakest in all cases. It is concluded that for each monthly seasonal series, seasonal differencing is the best stationarization method in terms of periodic effect elimination. Moreover, the monthly water temperature is predicted with more accuracy than monthly streamflow. The criteria of the average stochastic term divided by the amplitude of the periodic term obtained for monthly streamflow and monthly water temperature were 0.19 and 0.30, 0.21 and 0.13, and 0.07 and 0.04 respectively. As a result, the periodic term is more dominant than the stochastic term for water temperature in the monthly water temperature series compared to streamflow series.
Effects of Climate Change on Extreme Streamflow Risks in the Olympic National Park
NASA Astrophysics Data System (ADS)
Tohver, I. M.; Lee, S.; Hamlet, A.
2011-12-01
Conventionally, natural resource management practices are designed within the framework that past conditions serve as a baseline for future conditions. However, the warmer future climate projected for the Pacific Northwest will alter the region's flood and low flow risks, posing considerable challenges to resource managers in the Olympic National Forest (ONF) and Olympic National Park (ONP). Shifts in extreme streamflow will influence two key management objectives in the ONF and ONP: the protection of wildlife and the maintenance of road infrastructure. The ONF is charged with managing habitat for species listed under the Endangered Species Act (ESA), and with maintaining the network of forest roads and culverts. Climate-induced increases in flood severity will introduce additional challenges in road and culvert design. Furthermore, the aging road infrastructure and more extreme summer low flows will compromise aquatic habitats, intrinsic to the health of threatened and endangered fish species listed under the ESA. Current practice uses estimates of Q100 (or the peak flow with an estimated 100 year return frequency) as the standard metric for stream crossing design. Simple regression models relating annual precipitation and basin area to Q100 are used in the design process. Low flow estimates are based on historical streamflow data to calculate the 7-day consecutive lowest flow with a 10-year return interval, or 7Q10. Under the projections a changing climate, these methods for estimating extreme flows are ill equipped to capture the complex and spatially varying effects of seasonal changes in temperature, precipitation, and snowpack on extreme flow risk. As an alternative approach, this study applies a physically-based hydrologic model to estimate historical and future flood risk at 1/16th degree (latitude/longitude) resolution (about 32 km2). We downscaled climate data derived from 10 global climate models to use as input for the Variable Infiltration Capacity (VIC) model, a macro-scale hydrologic model, which simulates various hydrologic variables at a daily time step. Using the VIC estimates for baseflow and run-off, we calculated Q100 and 7Q10 for the historical period and under two emission scenarios, A1B and B1, at three future time intervals: the 2020s, the 2040s and the 2080s. We also calculated Q100 and 7Q10 at the spatial scale of the 12-digit hydrologic unit codes (HUCs) as delineated by the United States Geologic Survey. The results demonstrate the sensitivity of snowpack at mid-elevation basins to a warmer climate, resulting in more severe winter flooding and lower streamflows in the summertime. These ensemble estimates of extreme streamflows will serve as a tool for management practices by providing high-resolution maps of changing risk over the ONF and ONP.
Harmon, J.G.
1983-01-01
Sacramento County expects to begin operation of the Sacramento Regional Wastewater Treatment Plant in 1982. The California State Water Resources Control Board has ruled that the plant will not be allowed to release effluent into the Sacramento River when flow in the river is 4,000 cubic feet per second or less. Depending on tide condition, flows less than 4,000 cubic feet per second may occur either once or twice during each 24-hour 50-minute tide cycle when the daily mean flow is less than about 12,000 cubic feet per second. Daily means flows less than 12,000 cubic feet per second occur about 28% of the time. Riverflow at the plant outfall is monitored by an acoustic streamflow-measuring system. Regulation of effluent released from the plant will normally be based on real-time flow data computed by the acoustic system. A graphical method for determining the occurrence and duration of flows of 4,000 cubic feet per second and less was developed as a backup system to be used if a temporary failure in the acoustic system occurs. (USGS)
A resampling procedure for generating conditioned daily weather sequences
Clark, Martyn P.; Gangopadhyay, Subhrendu; Brandon, David; Werner, Kevin; Hay, Lauren E.; Rajagopalan, Balaji; Yates, David
2004-01-01
A method is introduced to generate conditioned daily precipitation and temperature time series at multiple stations. The method resamples data from the historical record “nens” times for the period of interest (nens = number of ensemble members) and reorders the ensemble members to reconstruct the observed spatial (intersite) and temporal correlation statistics. The weather generator model is applied to 2307 stations in the contiguous United States and is shown to reproduce the observed spatial correlation between neighboring stations, the observed correlation between variables (e.g., between precipitation and temperature), and the observed temporal correlation between subsequent days in the generated weather sequence. The weather generator model is extended to produce sequences of weather that are conditioned on climate indices (in this case the Niño 3.4 index). Example illustrations of conditioned weather sequences are provided for a station in Arizona (Petrified Forest, 34.8°N, 109.9°W), where El Niño and La Niña conditions have a strong effect on winter precipitation. The conditioned weather sequences generated using the methods described in this paper are appropriate for use as input to hydrologic models to produce multiseason forecasts of streamflow.
NASA Astrophysics Data System (ADS)
Dierauer, J. R.; Allen, D. M.
2016-12-01
Climate change is expected to lead to an increase in extremes, including daily maximum temperatures, heat waves, and meteorological droughts, which will likely result in shifts in the hydrological drought regime (i.e. the frequency, timing, duration, and severity of drought events). While many studies have used hydrologic models to simulate climate change impacts on water resources, only a small portion of these studies have analyzed impacts on low flows and/or hydrological drought. This study is the first to use a fully coupled groundwater-surface water (gw-sw) model to study climate change impacts on hydrological drought. Generic catchment-scale gw-sw models were created for each of the six major eco-regions in British Columbia using the MIKE-SHE/MIKE-11 modelling code. Daily precipitation and temperature time series downscaled using bias-correction spatial disaggregation for the simulated period of 1950-2100 were obtained from the Pacific Climate Institute Consortium (PCIC). Streamflow and groundwater drought events were identified from the simulated time series for each catchment model using the moving window quantile threshold. The frequency, timing, duration, and severity of drought events were compared between the reference period (1961-2000) and two future time periods (2031-2060, 2071-2100). Results show how hydrological drought regimes across the different British Columbia eco-regions will be impacted by climate change.
SWAT-CS: Revision and testing of SWAT for Canadian Shield catchments
NASA Astrophysics Data System (ADS)
Fu, Congsheng; James, April L.; Yao, Huaxia
2014-04-01
Canadian Shield catchments are under increasing pressure from various types of development (e.g., mining and increased cottagers) and changing climate. Within the southern part of the Canadian Shield, catchments are generally characterized by shallow forested soils with high infiltration rates and low bedrock infiltration, generating little overland flow, and macropore and subsurface flow are important streamflow generation processes. Large numbers of wetlands and lakes are also key physiographic features, and snow-processes are critical to catchment modeling in this climate. We have revised the existing, publicly available SWAT (version 2009.10.1 Beta 3) to create SWAT-CS, a version representing hydrological processes dominating Canadian Shield catchments, where forest extends over Precambrian Shield bedrock. Prior to this study, very few studies applying SWAT to Canadian Shield catchments exist (we have found three). We tested SWAT-CS using the Harp Lake catchment dataset, an Ontario Ministry of Environment research station located in south-central Ontario. Simulations were evaluated against 30 years of observational data, including streamflow from six headwater sub-catchments (0.1-1.9 km2), outflow from Harp Lake (5.4 km2) and five years of weekly snow water equivalent (SWE). The best Nash-Sutcliffe efficiency (NSE) results for daily streamflow calibration, daily streamflow validation, and SWE were 0.60, 0.65, and 0.87, respectively, for sub-catchment HP4 (with detailed land use and soil data). For this range of catchment scales, land cover and soil properties were found to be transferable across sub-catchments with similar physiographic features, namely streamflow from the remaining five sub-catchments could be modeled well using sub-catchment HP4 parameterization. The Harp Lake outflow was well modeled using the existing reservoir-based target release method, generating NSEs of 0.72 and 0.67 for calibration and verification periods respectively. With significant changes to the infiltration module (introducing macropore flow and reduced bedrock percolation), more than 90% of interflow was generated close to the soil-bedrock interface and the contribution of groundwater flow to total runoff was reduced to small amounts, consistent with hydrological process understanding in this terrain. These two changes also allowed for a positive linear relationship between NSE of SWE and Q, whereas prior to these changes there was a negative relationship. With these key revisions to the infiltration and bedrock percolations modules, it is concluded that SWAT-CS can reasonably capture key hydrological processes within Canadian Shield catchments. Further testing will examine water quality modeling and larger-scale applications.
Floods of Selected Streams in Arkansas, Spring 2008
Funkhouser, Jaysson E.; Eng, Ken
2009-01-01
Floods can cause loss of life and extensive destruction to property. Monitoring floods and understanding the reasons for their occurrence are the responsibility of many Federal agencies. The National Weather Service, the U.S. Army Corps of Engineers, and the U.S. Geological Survey are among the most visible of these agencies. Together, these three agencies collect and analyze floodflow information to better understand the variety of mechanisms that cause floods, and how the characteristics and frequencies of floods vary with time and location. The U.S. Geological Survey (USGS) has monitored and assessed the quantity of streamflow in our Nation's streams since the agency's inception in 1879. Because of ongoing collection and assessment of streamflow data, the USGS can provide information about a range of surface-water issues including the suitability of water for public supply and irrigation and the effects of agriculture and urbanization on streamflow. As part of its streamflow-data collection activities, the USGS measured streamflow in multiple streams during extreme flood events in Arkansas in the spring of 2008. The analysis of streamflow information collected during flood events such as these provides a scientific basis for decision making related to resource management and restoration. Additionally, this information can be used by water-resource managers to better define flood-hazard areas and to design bridges, culverts, dams, levees, and other structures. Water levels (stage) and streamflow (discharge) currently are being monitored in near real-time at approximately 150 locations in Arkansas. The streamflow-gaging stations measure and record hydrologic data at 15-minute or hourly intervals; the data then are transmitted through satellites to the USGS database and displayed on the internet every 1 to 4 hours. Streamflow-gaging stations in Arkansas are part of a network of over 7,500 active streamflow-gaging stations operated by the USGS throughout the United States in cooperation with other Federal, State, and local government agencies. In Arkansas, the major supporters of the streamflow-gaging network are the U.S. Army Corps of Engineers, Arkansas Natural Resources Commission, Arkansas Department of Environmental Quality, and Arkansas Geological Survey. Many other Federal, State, and local government entities provide additional support for streamflow-gaging stations. It is the combined support of the USGS and all funding partners that make it possible to maintain an adequate streamflow-gaging network in Arkansas. Data collected over the years at streamflow-gaging stations can be used to characterize the relative magnitude of flood events and their statistical frequency of occurrence. These analyses provide water-resource managers with accurate and reliable hydrologic information based on present and historical flow conditions. Continued collection of streamflow data, with consideration of changes in land use, agricultural practices, and climate change, will help scientists to more accurately characterize the magnitude of extreme floods in the future.
Potential Utility of the Real-Time TMPA-RT Precipitation Estimates in Streamflow Prediction
NASA Technical Reports Server (NTRS)
Su, Fengge; Gao, Huilin; Huffman, George J.; Lettenmaier, Dennis P.
2010-01-01
We investigate the potential utility of the real-time Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA-RT) data for streamflow prediction, both through direct comparisons of TMPA-RT estimates with a gridded gauge product, and through evaluation of streamflow simulations over four tributaries of La Plata Basin (LPB) in South America using the two precipitation products. Our assessments indicate that the relative accuracy and the hydrologic performance of TMPA-RT-based streamflow simulations generally improved after February 2005. The improvements in TMPA-RT since 2005 are closely related to upgrades in the TMPA-RT algorithm in early February, 2005 which include use of additional microwave sensors (AMSR-E and AMSU-B) and implementation of different calibration schemes. Our work suggests considerable potential for hydrologic prediction using purely satellite-derived precipitation estimates (no adjustments by in situ gauges) in parts of the globe where in situ observations are sparse.
Streamflow Forecasting Using Nuero-Fuzzy Inference System
NASA Astrophysics Data System (ADS)
Nanduri, U. V.; Swain, P. C.
2005-12-01
The prediction of flow into a reservoir is fundamental in water resources planning and management. The need for timely and accurate streamflow forecasting is widely recognized and emphasized by many in water resources fraternity. Real-time forecasts of natural inflows to reservoirs are of particular interest for operation and scheduling. The physical system of the river basin that takes the rainfall as an input and produces the runoff is highly nonlinear, complicated and very difficult to fully comprehend. The system is influenced by large number of factors and variables. The large spatial extent of the systems forces the uncertainty into the hydrologic information. A variety of methods have been proposed for forecasting reservoir inflows including conceptual (physical) and empirical (statistical) models (WMO 1994), but none of them can be considered as unique superior model (Shamseldin 1997). Owing to difficulties of formulating reasonable non-linear watershed models, recent attempts have resorted to Neural Network (NN) approach for complex hydrologic modeling. In recent years the use of soft computing in the field of hydrological forecasting is gaining ground. The relatively new soft computing technique of Adaptive Neuro-Fuzzy Inference System (ANFIS), developed by Jang (1993) is able to take care of the non-linearity, uncertainty, and vagueness embedded in the system. It is a judicious combination of the Neural Networks and fuzzy systems. It can learn and generalize highly nonlinear and uncertain phenomena due to the embedded neural network (NN). NN is efficient in learning and generalization, and the fuzzy system mimics the cognitive capability of human brain. Hence, ANFIS can learn the complicated processes involved in the basin and correlate the precipitation to the corresponding discharge. In the present study, one step ahead forecasts are made for ten-daily flows, which are mostly required for short term operational planning of multipurpose reservoirs. A Neuro-Fuzzy model is developed to forecast ten-daily flows into the Hirakud reservoir on River Mahanadi in the state of Orissa in India. Correlation analysis is carried out to find out the most influential variables on the ten daily flow at Hirakud. Based on this analysis, four variables, namely, flow during the previous time period, ql1, rainfall during the previous two time periods, rl1 and rl2, and flow during the same period in previous year, qpy, are identified as the most influential variables to forecast the ten daily flow. Performance measures such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and coefficient of efficiency R2 are computed for training and testing phases of the model to evaluate its performance. The results indicate that the ten-daily forecasting model is efficient in predicting the high and medium flows with reasonable accuracy. The forecast of low flows is associated with less efficiency. REFERENCES Jang, J.S.R. (1993). "ANFIS: Adaptive - network- based fuzzy inference system." IEEE Trans. on Systems, Man and Cybernetics, 23 (3), 665-685. Shamseldin, A.Y. (1997). "Application of a neural network technique to rainfall-runoff modeling." Journal of Hydrology, 199, 272-294. World Meteorological Organization (1975). Intercomparison of conceptual models used in operational hydrological forecasting. World Meteorological Organization, Technical Report No.429, Geneva, Switzerland.
Devendra M. Amatya; Carl C. Trettin
2010-01-01
Information about streamflow characteristics e.g. runoff-rainfall (R/O) ratio, rate and timing of flow, surface and subsurface drainage (SSD), and response time to rainfall events is necessary to accurately simulate fluxes and for designing best management practices (BMPs). Unfortunately, those data are scarce in the southeastern Atlantic coastal plain, a highly...
Curran, Christopher A.; Olsen, Theresa D.
2009-01-01
Low-flow frequency statistics were computed at 17 continuous-record streamflow-gaging stations and 8 miscellaneous measurement sites in and near the Nooksack River basin in northwestern Washington and Canada, including the 1, 3, 7, 15, 30, and 60 consecutive-day low flows with recurrence intervals of 2 and 10 years. Using these low-flow statistics, 12 regional regression equations were developed for estimating the same low-flow statistics at ungaged sites in the Nooksack River basin using a weighted-least-squares method. Adjusted R2 (coefficient of determination) values for the equations ranged from 0.79 to 0.93 and the root-mean-squared error (RMSE) expressed as a percentage ranged from 77 to 560 percent. Streamflow records from six gaging stations located in mountain-stream or lowland-stream subbasins of the Nooksack River basin were analyzed to determine if any of the gaging stations could be removed from the network without significant loss of information. Using methods of hydrograph comparison, daily-value correlation, variable space, and flow-duration ratios, and other factors relating to individual subbasins, the six gaging stations were prioritized from most to least important as follows: Skookum Creek (12209490), Anderson Creek (12210900), Warm Creek (12207750), Fishtrap Creek (12212050), Racehorse Creek (12206900), and Clearwater Creek (12207850). The optimum streamflow-gaging station network would contain all gaging stations except Clearwater Creek, and the minimum network would include Skookum Creek and Anderson Creek.
Slattery, Richard N.; Furlow, Allen L.; Ockerman, Darwin J.
2006-01-01
The U.S. Geological Survey collected rainfall, streamflow, evapotranspiration, and rainfall and stormflow water-quality data from seven sites in two adjacent watersheds in the Honey Creek State Natural Area, Comal County, Texas, during August 2001–September 2003, in cooperation with the U.S. Department of Agriculture, Natural Resources Conservation Service, and the San Antonio Water System. Data collected during this period represent baseline hydrologic and water-quality conditions before proposed removal of ashe juniper (Juniperus ashei) from one of the two watersheds. Juniper removal is intended as a best-management practice to increase water quantity (aquifer recharge and streamflow) and to protect water quality. Continuous (5-minute interval) rainfall data are collected at four sites; continuous (5-minute interval) streamflow data are collected at three sites. Fifteen-minute averages of meteorological and solar-energy-related data recorded at two sites are used to compute moving 30-minute evapotranspiration values on the basis of the energy-balance Bowen ratio method. Periodic rainfall water-quality data are collected at one site and stormflow water-quality data at three sites. Daily rainfall, streamflow, and evapotranspiration totals are presented in tables; detailed data are listed in an appendix. Results of analyses of the periodic rainfall and stormflow water-quality samples collected during runoff events are summarized in the appendix; not all data types were collected at all sites nor were all data types collected during the entire 26-month period.
Testing the ability of a semidistributed hydrological model to simulate contributing area
NASA Astrophysics Data System (ADS)
Mengistu, S. G.; Spence, C.
2016-06-01
A dry climate, the prevalence of small depressions, and the lack of a well-developed drainage network are characteristics of environments with extremely variable contributing areas to runoff. These types of regions arguably present the greatest challenge to properly understanding catchment streamflow generation processes. Previous studies have shown that contributing area dynamics are important for streamflow response, but the nature of the relationship between the two is not typically understood. Furthermore, it is not often tested how well hydrological models simulate contributing area. In this study, the ability of a semidistributed hydrological model, the PDMROF configuration of Environment Canada's MESH model, was tested to determine if it could simulate contributing area. The study focused on the St. Denis Creek watershed in central Saskatchewan, Canada, which with its considerable topographic depressions, exhibits wide variation in contributing area, making it ideal for this type of investigation. MESH-PDMROF was able to replicate contributing area derived independently from satellite imagery. Daily model simulations revealed a hysteretic relationship between contributing area and streamflow not apparent from the less frequent remote sensing observations. This exercise revealed that contributing area extent can be simulated by a semi-distributed hydrological model with a scheme that assumes storage capacity distribution can be represented with a probability function. However, further investigation is needed to determine if it can adequately represent the complex relationship between streamflow and contributing area that is such a key signature of catchment behavior.