Physiographic and land cover attributes of the Puget Lowland and the active streamflow gaging network, Puget Sound Basin

USGS Publications Warehouse

Konrad, Christopher; Sevier, Maria

2014-01-01

Geospatial information for the active streamflow gaging network in the Puget Sound Basin was compiled to support regional monitoring of stormwater effects to small streams. The compilation includes drainage area boundaries and physiographic and land use attributes that affect hydrologic processes. Three types of boundaries were used to tabulate attributes: Puget Sound Watershed Characterization analysis units (AU); the drainage area of active streamflow gages; and the catchments of Regional Stream Monitoring Program (RSMP) sites. The active streamflow gaging network generally includes sites that represent the ranges of attributes for lowland AUs, although there are few sites with low elevations (less than 60 meters), low precipitation (less than 1 meter year), or high stream density (greater than 5 kilometers per square kilometers). The active streamflow gaging network can serve to provide streamflow information in some AUs and RSMP sites, particularly where the streamflow gage measures streamflow generated from a part of the AU or that drains to the RSMP site, and that part of the AU or RSMP site is a significant fraction of the drainage area of the streamgage. The maximum fraction of each AU or RSMP catchment upstream of a streamflow gage and the maximum fraction of any one gaged basin in an AU or RSMP along with corresponding codes are provided in the attribute tables.

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.

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.

Hydrostratigraphic and structural controls on streamflow generation in the Chuska Mountains, Navajo Nation, AZ/NM

NASA Astrophysics Data System (ADS)

Tsinnajinnie, L.; Frisbee, M. D.; Wilson, J. L.

2017-12-01

A conceptual model of hydrostratigraphic and structural influences on 3D streamflow generation processes is tested in the Whiskey Creek watershed located in the Chuska Mountains of the Navajo Nation along the northern NM/AZ border. The role of hydrostratigraphy and structure in groundwater processes has been well studied. However, influences of heterogeneity due to geologic structure and stratigraphy of mountain blocks on 3D streamflow generation has received less attention. Three-dimensional flow in mountainous watersheds, such as Saguache Creek (CO) and Rio Hondo (NM), contributes significant amounts of groundwater from deep circulation to streamflow. This fully 3D conceptual model is fundamentally different than watersheds characterized as 2D, those dominated by surface and shallow subsurface runoff, because 3D watersheds can have much longer flowpaths and mean residence times (up to 1000s of years). In contrast to Saguache Creek (volcanic bedrock) and Rio Hondo (crystalline metamorphic), the bedrock geology of the watersheds draining the Chuska Mountains is primarily comprised of sedimentary bedrock capped by extrusive volcanics. We test this conceptual model using a combination of stream gauging, tritium analyses, and endmember mixing analysis (EMMA) on the general ion chemistry and stable isotope composition of water samples collected in 2013-2016. Springs that emerge from the Chuska Sandstone are tritium dead indicative of a large component of pre-bomb pulse water in discharge and deeper 3D flow. EMMA indicates that most streamflow is generated from groundwater emerging from the Chuska Sandstone. Gaining/losing conditions in Whiskey Creek are strongly related to hydrostratigraphy as evidenced by a transition from gaining conditions largely found in the Chuska Sandstone to losing conditions where the underlying Chinle Formation outcrops. Although tritium in Whiskey Creek suggests 3D interactions are present, hydrostratigraphic and structural controls may limit the occurrence of longer residence times and longer flow paths. Mountainous watersheds similar to the 3D hydrostratigraphic and structurally controlled models will exhibit different responses to perturbations, such as climate change, than watersheds that fit existing 2D and 3D conceptual models.

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.

Hydrologic functioning of the deep Critical Zone and contributions to streamflow in a high elevation catchment: testing of multiple conceptual models

NASA Astrophysics Data System (ADS)

Dwivedi, R.; Meixner, T.; McIntosh, J. C.; Ferre, T. P. A.; Eastoe, C. J.; Minor, R. L.; Barron-Gafford, G.; Chorover, J.

2017-12-01

The composition of natural mountainous waters maintains important control over the water quality available to downstream users. Furthermore, the geochemical constituents of stream water in the mountainous catchments represent the result of the spatial and temporal evolution of critical zone structure and processes. A key problem is that high elevation catchments involve rugged terrain and are subject to extreme climate and landscape gradients; therefore, high density or high spatial resolution hydro-geochemical observations are rare. Despite such difficulties, the Santa Catalina Mountains Critical Zone Observatory (SCM-CZO), Tucson, AZ, generates long-term hydrogeochemical data for understanding not only hydrological processes and their seasonal characters, but also the geochemical impacts of such processes on streamflow chemical composition. Using existing instrumentation and hydrogeochemical observations from the last 9+ years (2009 through 2016 and an initial part of 2017), we employed a multi-tracer approach along with principal component analysis to identify water sources and their seasonal character. We used our results to inform hydrological process understanding (flow paths, residence times, and water sources) for our study site. Our results indicate that soil water is the largest contributor to streamflow, which is ephemeral in nature. Although a 3-dimensional mixing space involving precipitation, soil water, interflow, and deep groundwater end-members could explain most of the streamflow chemistry, geochemical complexity was observed to grow with catchment storage. In terms of processes and their seasonal character, we found soil water and interflow were the primary end-member contributors to streamflow in all seasons. Deep groundwater only contributes to streamflow at high catchment storage conditions, but it provides major ions such as Na, Mg, and Ca that are lacking in other water types. In this way, our results indicate that any future efforts aimed at explaining concentration-discharge behavior of our field site should consider at least three-dimensional mixing space or 4 end-members.

Streamflow data: Chapter 13

USGS Publications Warehouse

Wiche, Gregg J.; Holmes, Robert R.

2016-01-01

Streamflow data are vital for a variety of water-resources issues, from flood warning to water supply planning. The collection of streamflow data is usually an involved and complicated process. This chapter serves as an overview of the streamflow data collection process. Readers with the need for the detailed information on the streamflow data collection process are referred to the many references noted in this chapter.

Environmental flow allocation and statistics calculator

USGS Publications Warehouse

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.

Improving medium-range ensemble streamflow forecasts through statistical post-processing

NASA Astrophysics Data System (ADS)

Mendoza, Pablo; Wood, Andy; Clark, Elizabeth; Nijssen, Bart; Clark, Martyn; Ramos, Maria-Helena; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

Probabilistic hydrologic forecasts are a powerful source of information for decision-making in water resources operations. A common approach is the hydrologic model-based generation of streamflow forecast ensembles, which can be implemented to account for different sources of uncertainties - e.g., from initial hydrologic conditions (IHCs), weather forecasts, and hydrologic model structure and parameters. In practice, hydrologic ensemble forecasts typically have biases and spread errors stemming from errors in the aforementioned elements, resulting in a degradation of probabilistic properties. In this work, we compare several statistical post-processing techniques applied to medium-range ensemble streamflow forecasts obtained with the System for Hydromet Applications, Research and Prediction (SHARP). SHARP is a fully automated prediction system for the assessment and demonstration of short-term to seasonal streamflow forecasting applications, developed by the National Center for Atmospheric Research, University of Washington, U.S. Army Corps of Engineers, and U.S. Bureau of Reclamation. The suite of post-processing techniques includes linear blending, quantile mapping, extended logistic regression, quantile regression, ensemble analogs, and the generalized linear model post-processor (GLMPP). We assess and compare these techniques using multi-year hindcasts in several river basins in the western US. This presentation discusses preliminary findings about the effectiveness of the techniques for improving probabilistic skill, reliability, discrimination, sharpness and resolution.

From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

NASA Astrophysics Data System (ADS)

Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

2016-02-01

This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the dominant processes associated with different landscape types, and the spatial relations of catchment processes. This article was corrected on 14 MAR 2016. See the end of the full text for details.

Impacts of Recent Climatic Wetting on Distributed Snow and Streamflow Responses in a Terminal Lake Basin.

NASA Astrophysics Data System (ADS)

Van Hoy, D.; Mahmood, T. H.; Jeannotte, T.; Todhunter, P. E.

2017-12-01

The recent shift in hydroclimatic conditions in the Northern Great Plains (NGP) has led to an increase in precipitation, rainfall rate, and wetland connectivity over the last few decades. These changes yield an integrated response resulting in high mean annual streamflow and subsequent flooding in many NGP basins such as the terminal Devils Lake Basin (DLB). In this study, we investigate the impacts of recent climatic wetting on distributed hydrologic responses such as snow processes and streamflow using a field-tested and physically-based cold region hydrologic model (CRHM). CHRM is designed for cold prairie regions and has modules to simulate major processes such as blowing snow transport, sublimation, interception, frozen soil infiltration, snowmelt and subsequent streamflow generation. Our modeling focuses on a tributary basin of the DLB known as the Mauvais Coulee Basin (MCB). Since there were no snow observations in the MCB, we conducted a detailed snow survey at distributed locations estimating snow depth, density, and snow water equivalent (SWE) using a prairie snow tube four times during winter of 2016-17. The MCB model was evaluated against distributed snow observations and streamflow measured at the basin outlet (USGS) for the year 2016-2017. Preliminary results indicate that the simulated SWEs at distributed locations and streamflow (NSE ≈ 0.70) are in good agreement with observations. The simulated SWE maps exhibit large spatiotemporal variation during 2016-17 winter due to spatial variability in precipitation, snow redistribution from stubble field to wooded areas, and snow accumulations in small depressions across the subbasins. The main source of snow appears to be the hills and ridges of the eastern and western edges of the basin, while the main sink is the large flat central valleys. The model will be used to examine the effect of recent changes to precipitation and temperature on snow processes and subsequent streamflow for 2004-2017 season. We will also investigate the hydrologic sensitivity to precipitation and temperature changes by altering input temperature and precipitation. Finally, our findings will point toward future process-based studies and simulated hydrologic responses that can be used to prepare flood hazard maps for cities around Devils Lake.

Stochastic Watershed Models for Risk Based Decision Making

NASA Astrophysics Data System (ADS)

Vogel, R. M.

2017-12-01

Over half a century ago, the Harvard Water Program introduced the field of operational or synthetic hydrology providing stochastic streamflow models (SSMs), which could generate ensembles of synthetic streamflow traces useful for hydrologic risk management. The application of SSMs, based on streamflow observations alone, revolutionized water resources planning activities, yet has fallen out of favor due, in part, to their inability to account for the now nearly ubiquitous anthropogenic influences on streamflow. This commentary advances the modern equivalent of SSMs, termed `stochastic watershed models' (SWMs) useful as input to nearly all modern risk based water resource decision making approaches. SWMs are deterministic watershed models implemented using stochastic meteorological series, model parameters and model errors, to generate ensembles of streamflow traces that represent the variability in possible future streamflows. SWMs combine deterministic watershed models, which are ideally suited to accounting for anthropogenic influences, with recent developments in uncertainty analysis and principles of stochastic simulation

Precipitation-Runoff Modeling System (PRMS) and Streamflow Response to Spatially Distributed Precipitation in Two Large Watersheds in Northern California

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.

Streamflow data

USGS Publications Warehouse

Holmes, Robert R.; Singh, Vijay P.

2016-01-01

The importance of streamflow data to the world’s economy, environmental health, and public safety continues to grow as the population increases. The collection of streamflow data is often an involved and complicated process. The quality of streamflow data hinges on such things as site selection, instrumentation selection, streamgage maintenance and quality assurance, proper discharge measurement techniques, and the development and continued verification of the streamflow rating. This chapter serves only as an overview of the streamflow data collection process as proper treatment of considerations, techniques, and quality assurance cannot be addressed adequately in the space limitations of this chapter. Readers with the need for the detailed information on the streamflow data collection process are referred to the many references noted in this chapter. 

Stormflow generation in a small rainforest catchment in the Luquillo Experimental Forest, Puerto Rico.

Treesearch

J. Schellekens; F. N. Scatena; L.A. Bruijnzee; A. I. J. M. van Dijk; M. M. A. Groen; R. J. P. van Hogezand

2004-01-01

Various complementary techniques were used to investigate the stormflow generating processes in a small headwater catchment in northeastern Puerto Rico. Over 100 samples were taken of soil matrix water, macropore flow, streamflow and precipitation, mainly during two storms of contrasting magnitude, for the analysis of calcium, magnesium, silicon, potassium, sodium and...

Catchment hydrological responses to forest harvest amount and spatial pattern

Treesearch

Alex Abdelnour; Marc Stieglitz; Feifei Pan; Robert McKane

2011-01-01

Forest harvest effects on streamflow generation have been well described experimentally, but a clear understanding of process-level hydrological controls can be difficult to ascertain from data alone. We apply a new model, Visualizing Ecosystems for Land Management Assessments (VELMA), to elucidate how hillslope and catchment-scale processes control stream discharge in...

Exploring changes in the spatial distribution of stream baseflow generation during a seasonal recession

Treesearch

R.A. Payn; M.N. Gooseff; B.L. McGlynn; K.E. Bencala; S.M. Wondzell

2012-01-01

Relating watershed structure to streamflow generation is a primary focus of hydrology. However, comparisons of longitudinal variability in stream discharge with adjacent valley structure have been rare, resulting in poor understanding of the distribution of the hydrologic mechanisms that cause variability in streamflow generation along valleys. This study explores...

Multiple regression and inverse moments improve the characterization of the spatial scaling behavior of daily streamflows in the Southeast United States

USGS Publications Warehouse

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. 

Water, energy, and biogeochemical budgets investigation at Panola Mountain research watershed, Stockbridge, Georgia; a research plan

USGS Publications Warehouse

Huntington, T.G.; Hooper, R.P.; Peters, N.E.; Bullen, T.D.; Kendall, Carol

1993-01-01

The Panola Mountain Research Watershed (PMRW), located in the Panola Mountain State Conservation Park near Stockbridge, Georgia has been selected as a core research watershed under the Water, Energy and Biogeochemical Budgets (WEBB) research initiative of the U.S. Geological Survey (USGS) Global Climate Change Program. This research plan describes ongoing and planned research activities at PMRW from 1984 to 1994. Since 1984, PMRW has been studied as a geochemical process research site under the U.S. Acid Precipitation Thrust Program. Research conducted under this Thrust Program focused on the estimation of dry atmospheric deposition, short-term temporal variability of streamwater chemistry, sulfate adsorption characteristics of the soils, groundwater chemistry, throughfall chemistry, and streamwater quality. The Acid Precipitation Thrust Program continues (1993) to support data collection and a water-quality laboratory. Proposed research to be supported by the WEBB program is organized in 3 interrelated categories: streamflow generation and water-quality evolution, weathering and geochemical evolution, and regulation of soil-water chemistry. Proposed research on streamflow generation and water-quality evolution will focus on subsurface water movement, its influence in streamflow generation, and the associated chemical changes of the water that take place along its flowpath. Proposed research on weathering and geochemical evolution will identify the sources of cations observed in the streamwater at Panola Mountain and quantify the changes in cation source during storms. Proposed research on regulation of soil-water chemistry will focus on the poorly understood processes that regulate soil-water and groundwater chemistry. (USGS)

Spatial interpolation schemes of daily precipitation for hydrologic modeling

USGS Publications Warehouse

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.

Importance of Wetlands to Streamflow Generation

Treesearch

E. S. Verry; R. K. Kolka

2003-01-01

Hewlett (1961) proposed the variable-source-area concept of streamflow origin in the mountains of North Carolina suggesting streamflow was produced from water leaving saturated areas near the channel. Dunne and Black confirmed this concept on the Sleepers River watershed in Vermont (1970). Areas near the river were saturated by subsurface or interflow from adjacent...

Construction of estimated flow- and load-duration curves for Kentucky using the Water Availability Tool for Environmental Resources (WATER)

USGS Publications Warehouse

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.

NEXRAD quantitative precipitation estimates, data acquisition, and processing for the DuPage County, Illinois, streamflow-simulation modeling system

USGS Publications Warehouse

Ortel, Terry W.; Spies, Ryan R.

2015-11-19

Next-Generation Radar (NEXRAD) has become an integral component in the estimation of precipitation (Kitzmiller and others, 2013). The high spatial and temporal resolution of NEXRAD has revolutionized the ability to estimate precipitation across vast regions, which is especially beneficial in areas without a dense rain-gage network. With the improved precipitation estimates, hydrologic models can produce reliable streamflow forecasts for areas across the United States. NEXRAD data from the National Weather Service (NWS) has been an invaluable tool used by the U.S. Geological Survey (USGS) for numerous projects and studies; NEXRAD data processing techniques similar to those discussed in this Fact Sheet have been developed within the USGS, including the NWS Quantitative Precipitation Estimates archive developed by Blodgett (2013).

Comparison of TOPMODEL streamflow simulations using NEXRAD-based and measured rainfall data, McTier Creek watershed, South Carolina

USGS Publications Warehouse

Feaster, Toby D.; Westcott, Nancy E.; Hudson, Robert J.M.; Conrads, Paul; Bradley, Paul M.

2012-01-01

Rainfall is an important forcing function in most watershed models. As part of a previous investigation to assess interactions among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations in the Edisto River Basin, the topography-based hydrological model (TOPMODEL) was applied in the McTier Creek watershed in Aiken County, South Carolina. Measured rainfall data from six National Weather Service (NWS) Cooperative (COOP) stations surrounding the McTier Creek watershed were used to calibrate the McTier Creek TOPMODEL. Since the 1990s, the next generation weather radar (NEXRAD) has provided rainfall estimates at a finer spatial and temporal resolution than the NWS COOP network. For this investigation, NEXRAD-based rainfall data were generated at the NWS COOP stations and compared with measured rainfall data for the period June 13, 2007, to September 30, 2009. Likewise, these NEXRAD-based rainfall data were used with TOPMODEL to simulate streamflow in the McTier Creek watershed and then compared with the simulations made using measured rainfall data. NEXRAD-based rainfall data for non-zero rainfall days were lower than measured rainfall data at all six NWS COOP locations. The total number of concurrent days for which both measured and NEXRAD-based data were available at the COOP stations ranged from 501 to 833, the number of non-zero days ranged from 139 to 209, and the total difference in rainfall ranged from -1.3 to -21.6 inches. With the calibrated TOPMODEL, simulations using NEXRAD-based rainfall data and those using measured rainfall data produce similar results with respect to matching the timing and shape of the hydrographs. Comparison of the bias, which is the mean of the residuals between observed and simulated streamflow, however, reveals that simulations using NEXRAD-based rainfall tended to underpredict streamflow overall. Given that the total NEXRAD-based rainfall data for the simulation period is lower than the total measured rainfall at the NWS COOP locations, this bias would be expected. Therefore, to better assess the use of NEXRAD-based rainfall estimates as compared to NWS COOP rainfall data on the hydrologic simulations, TOPMODEL was recalibrated and updated simulations were made using the NEXRAD-based rainfall data. Comparisons of observed and simulated streamflow show that the TOPMODEL results using measured rainfall data and NEXRAD-based rainfall are comparable. Nonetheless, TOPMODEL simulations using NEXRAD-based rainfall still tended to underpredict total streamflow volume, although the magnitude of differences were similar to the simulations using measured rainfall. The McTier Creek watershed was subdivided into 12 subwatersheds and NEXRAD-based rainfall data were generated for each subwatershed. Simulations of streamflow were generated for each subwatershed using NEXRAD-based rainfall and compared with subwatershed simulations using measured rainfall data, which unlike the NEXRAD-based rainfall were the same data for all subwatersheds (derived from a weighted average of the six NWS COOP stations surrounding the basin). For the two simulations, subwatershed streamflow were summed and compared to streamflow simulations at two U.S. Geological Survey streamgages. The percentage differences at the gage near Monetta, South Carolina, were the same for simulations using measured rainfall data and NEXRAD-based rainfall. At the gage near New Holland, South Carolina, the percentage differences using the NEXRAD-based rainfall were twice as much as those using the measured rainfall. Single-mass curve comparisons showed an increase in the total volume of rainfall from north to south. Similar comparisons of the measured rainfall at the NWS COOP stations showed similar percentage differences, but the NEXRAD-based rainfall variations occurred over a much smaller distance than the measured rainfall. Nonetheless, it was concluded that in some cases, using NEXRAD-based rainfall data in TOPMODEL streamflow simulations may provide an effective alternative to using measured rainfall data. For this investigation, however, TOPMODEL streamflow simulations using NEXRAD-based rainfall data for both calibration and simulations did not show significant improvements with respect to matching observed streamflow over simulations generated using measured rainfall data.

Quantifying streamflow change caused by forest disturbance at a large spatial scale: A single watershed study

NASA Astrophysics Data System (ADS)

Wei, Xiaohua; Zhang, Mingfang

2010-12-01

Climatic variability and forest disturbance are commonly recognized as two major drivers influencing streamflow change in large-scale forested watersheds. The greatest challenge in evaluating quantitative hydrological effects of forest disturbance is the removal of climatic effect on hydrology. In this paper, a method was designed to quantify respective contributions of large-scale forest disturbance and climatic variability on streamflow using the Willow River watershed (2860 km2) located in the central part of British Columbia, Canada. Long-term (>50 years) data on hydrology, climate, and timber harvesting history represented by equivalent clear-cutting area (ECA) were available to discern climatic and forestry influences on streamflow by three steps. First, effective precipitation, an integrated climatic index, was generated by subtracting evapotranspiration from precipitation. Second, modified double mass curves were developed by plotting accumulated annual streamflow against annual effective precipitation, which presented a much clearer picture of the cumulative effects of forest disturbance on streamflow following removal of climatic influence. The average annual streamflow changes that were attributed to forest disturbances and climatic variability were then estimated to be +58.7 and -72.4 mm, respectively. The positive (increasing) and negative (decreasing) values in streamflow change indicated opposite change directions, which suggest an offsetting effect between forest disturbance and climatic variability in the study watershed. Finally, a multivariate Autoregressive Integrated Moving Average (ARIMA) model was generated to establish quantitative relationships between accumulated annual streamflow deviation attributed to forest disturbances and annual ECA. The model was then used to project streamflow change under various timber harvesting scenarios. The methodology can be effectively applied to any large-scale single watershed where long-term data (>50 years) are available.

Effects of groundwater levels and headwater wetlands on streamflow in the Charlie Creek basin, Peace River watershed, west-central Florida

USGS Publications Warehouse

Lee, T.M.; Sacks, L.A.; Hughes, J.D.

2010-01-01

The Charlie Creek basin was studied from April 2004 to December 2005 to better understand how groundwater levels in the underlying aquifers and storage and overflow of water from headwater wetlands preserve the streamflows exiting this least-developed tributary basin of the Peace River watershed. The hydrogeologic framework, physical characteristics, and streamflow were described and quantified for five subbasins of the 330-square mile Charlie Creek basin, allowing the contribution of its headwaters area and tributary subbasins to be separately quantified. A MIKE SHE model simulation of the integrated surface-water and groundwater flow processes in the basin was used to simulate daily streamflow observed over 21 months in 2004 and 2005 at five streamflow stations, and to quantify the monthly and annual water budgets for the five subbasins including the changing amount of water stored in wetlands. Groundwater heads were mapped in Zone 2 of the intermediate aquifer system and in the Upper Floridan aquifer, and were used to interpret the location of artesian head conditions in the Charlie Creek basin and its relation to streamflow. Artesian conditions in the intermediate aquifer system induce upward groundwater flow into the surficial aquifer and help sustain base flow which supplies about two-thirds of the streamflow from the Charlie Creek basin. Seepage measurements confirmed seepage inflow to Charlie Creek during the study period. The upper half of the basin, comprised largely of the Upper Charlie Creek subbasin, has lower runoff potential than the lower basin, more storage of runoff in wetlands, and periodically generates no streamflow. Artesian head conditions in the intermediate aquifer system were widespread in the upper half of the Charlie Creek basin, preventing downward leakage from expansive areas of wetlands and enabling them to act as headwaters to Charlie Creek once their storage requirements were met. Currently, the dynamic balance between wetland storage, rainfall-runoff processes, and groundwater-level differences in the upper basin allow it to generate approximately half of the streamflow from the Charlie Creek basin. Therefore, future development in the upper basin that would alter the hydraulic connectivity of wetlands during high flow conditions or expand recharging groundwater conditions could substantially affect streamflow in Charlie Creek. LIDAR (Light detection and ranging) based topographic maps and integrated modeling results were used to quantify the water stored in wetlands and other topographic depressions, and to describe the network of shallow stream channels connecting wetlands to Charlie Creek and its tributaries over distances of several thousand feet. Peak flows at all but one streamflow station were underpredicted in MIKE SHE simulations, possibly because the hydraulics of surface channels connecting wetlands to stream channels were not explicitly simulated in the model. Explicitly simulating the smaller channels connecting wetlands and stream channels should improve the ability of future watershed models to simulate peak flows in streams with headwater wetlands. The runoff potential was greater in the lower half of the Charlie Creek basin than in the upper half, and the streambed of Charlie Creek had greater potential to both directly gain streamflow from groundwater and lose streamflow to groundwater. Charlie Creek is more incised into the surficial aquifer in the lower basin than in the upper basin, and the streambed intersects the top of the intermediate aquifer system at two known locations. Groundwater levels in the intermediate aquifer system varied widely in the lower half of the basin from artesian conditions inducing upward flow toward the surficial aquifer and streams, to recharging conditions allowing downward flow and stream leakage. Recharge areas were greatest in May 2004 when rainfall was at a seasonal low and irrigation pumping was at a seasonal high. Recharge conditions

Evaluation of Stochastic Rainfall Models in Capturing Climate Variability for Future Drought and Flood Risk Assessment

NASA Astrophysics Data System (ADS)

Chowdhury, A. F. M. K.; Lockart, N.; Willgoose, G. R.; Kuczera, G. A.; Kiem, A.; Nadeeka, P. M.

2016-12-01

One of the key objectives of stochastic rainfall modelling is to capture the full variability of climate system for future drought and flood risk assessment. However, it is not clear how well these models can capture the future climate variability when they are calibrated to Global/Regional Climate Model data (GCM/RCM) as these datasets are usually available for very short future period/s (e.g. 20 years). This study has assessed the ability of two stochastic daily rainfall models to capture climate variability by calibrating them to a dynamically downscaled RCM dataset in an east Australian catchment for 1990-2010, 2020-2040, and 2060-2080 epochs. The two stochastic models are: (1) a hierarchical Markov Chain (MC) model, which we developed in a previous study and (2) a semi-parametric MC model developed by Mehrotra and Sharma (2007). Our hierarchical model uses stochastic parameters of MC and Gamma distribution, while the semi-parametric model uses a modified MC process with memory of past periods and kernel density estimation. This study has generated multiple realizations of rainfall series by using parameters of each model calibrated to the RCM dataset for each epoch. The generated rainfall series are used to generate synthetic streamflow by using a SimHyd hydrology model. Assessing the synthetic rainfall and streamflow series, this study has found that both stochastic models can incorporate a range of variability in rainfall as well as streamflow generation for both current and future periods. However, the hierarchical model tends to overestimate the multiyear variability of wet spell lengths (therefore, is less likely to simulate long periods of drought and flood), while the semi-parametric model tends to overestimate the mean annual rainfall depths and streamflow volumes (hence, simulated droughts are likely to be less severe). Sensitivity of these limitations of both stochastic models in terms of future drought and flood risk assessment will be discussed.

Statistical summaries of streamflow data for selected gaging stations on and near the Idaho National Engineering Laboratory, Idaho, through September 1990

USGS Publications Warehouse

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.

Exploiting Soil Moisture, Precipitation, and Streamflow Observations to Evaluate Soil Moisture/Runoff Coupling in Land Surface Models

NASA Astrophysics Data System (ADS)

Crow, W. T.; Chen, F.; Reichle, R. H.; Xia, Y.; Liu, Q.

2018-05-01

Accurate partitioning of precipitation into infiltration and runoff is a fundamental objective of land surface models tasked with characterizing the surface water and energy balance. Temporal variability in this partitioning is due, in part, to changes in prestorm soil moisture, which determine soil infiltration capacity and unsaturated storage. Utilizing the National Aeronautics and Space Administration Soil Moisture Active Passive Level-4 soil moisture product in combination with streamflow and precipitation observations, we demonstrate that land surface models (LSMs) generally underestimate the strength of the positive rank correlation between prestorm soil moisture and event runoff coefficients (i.e., the fraction of rainfall accumulation volume converted into stormflow runoff during a storm event). Underestimation is largest for LSMs employing an infiltration-excess approach for stormflow runoff generation. More accurate coupling strength is found in LSMs that explicitly represent subsurface stormflow or saturation-excess runoff generation processes.

Impact of Different Time Series Streamflow Data on Energy Generation of a Run-of-River Hydropower Plant

NASA Astrophysics Data System (ADS)

Kentel, E.; Cetinkaya, M. A.

2013-12-01

Global issues such as population increase, power supply crises, oil prices, social and environmental concerns have been forcing countries to search for alternative energy sources such as renewable energy to satisfy the sustainable development goals. Hydropower is the most common form of renewable energy in the world. Hydropower does not require any fuel, produces relatively less pollution and waste and it is a reliable energy source with relatively low operating cost. In order to estimate the average annual energy production of a hydropower plant, sufficient and dependable streamflow data is required. The goal of this study is to investigate impact of streamflow data on annual energy generation of Balkusan HEPP which is a small run-of-river hydropower plant at Karaman, Turkey. Two different stream gaging stations are located in the vicinity of Balkusan HEPP and these two stations have different observation periods: one from 1986 to 2004 and the other from 2000 to 2009. These two observation periods show different climatic characteristics. Thus, annual energy estimations based on data from these two different stations differ considerably. Additionally, neither of these stations is located at the power plant axis, thus streamflow observations from these two stream gaging stations need to be transferred to the plant axis. This requirement introduces further errors into energy estimations. Impact of different streamflow data and transfer of streamflow observations to plant axis on annual energy generation of a small hydropower plant is investigated in this study.

A unified approach for process-based hydrologic modeling: Part 2. Model implementation and case studies

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...

United States streamflow probabilities based on forecasted La Nina, winter-spring 2000

USGS Publications Warehouse

Dettinger, M.D.; Cayan, D.R.; Redmond, K.T.

1999-01-01

Although for the last 5 months the TahitiDarwin Southern Oscillation Index (SOI) has hovered close to normal, the “equatorial” SOI has remained in the La Niña category and predictions are calling for La Niña conditions this winter. In view of these predictions of continuing La Niña and as a direct extension of previous studies of the relations between El NiñoSouthern Oscil-lation (ENSO) conditions and streamflow in the United States (e.g., Redmond and Koch, 1991; Cayan and Webb, 1992; Redmond and Cayan, 1994; Dettinger et al., 1998; Garen, 1998; Cayan et al., 1999; Dettinger et al., in press), the probabilities that United States streamflows from December 1999 through July 2000 will be in upper and lower thirds (terciles) of the historical records are estimated here. The processes that link ENSO to North American streamflow are discussed in detail in these diagnostics studies. Our justification for generating this forecast is threefold: (1) Cayan et al. (1999) recently have shown that ENSO influences on streamflow variations and extremes are proportionately larger than the corresponding precipitation teleconnections. (2) Redmond and Cayan (1994) and Dettinger et al. (in press) also have shown that the low-frequency evolution of ENSO conditions support long-lead correlations between ENSO and streamflow in many rivers of the conterminous United States. (3) In many rivers, significant (weeks-to-months) delays between precipitation and the release to streams of snowmelt or ground-water discharge can support even longer term forecasts of streamflow than is possible for precipitation. The relatively slow, orderly evolution of El Niño-Southern Oscillation episodes, the accentuated dependence of streamflow upon ENSO, and the long lags between precipitation and flow encourage us to provide the following analysis as a simple prediction of this year’s river flows.

Towards an Australian ensemble streamflow forecasting system for flood prediction and water management

NASA Astrophysics Data System (ADS)

Bennett, J.; David, R. E.; Wang, Q.; Li, M.; Shrestha, D. L.

2016-12-01

Flood forecasting in Australia has historically relied on deterministic forecasting models run only when floods are imminent, with considerable forecaster input and interpretation. These now co-existed with a continually available 7-day streamflow forecasting service (also deterministic) aimed at operational water management applications such as environmental flow releases. The 7-day service is not optimised for flood prediction. We describe progress on developing a system for ensemble streamflow forecasting that is suitable for both flood prediction and water management applications. Precipitation uncertainty is handled through post-processing of Numerical Weather Prediction (NWP) output with a Bayesian rainfall post-processor (RPP). The RPP corrects biases, downscales NWP output, and produces reliable ensemble spread. Ensemble precipitation forecasts are used to force a semi-distributed conceptual rainfall-runoff model. Uncertainty in precipitation forecasts is insufficient to reliably describe streamflow forecast uncertainty, particularly at shorter lead-times. We characterise hydrological prediction uncertainty separately with a 4-stage error model. The error model relies on data transformation to ensure residuals are homoscedastic and symmetrically distributed. To ensure streamflow forecasts are accurate and reliable, the residuals are modelled using a mixture-Gaussian distribution with distinct parameters for the rising and falling limbs of the forecast hydrograph. In a case study of the Murray River in south-eastern Australia, we show ensemble predictions of floods generally have lower errors than deterministic forecasting methods. We also discuss some of the challenges in operationalising short-term ensemble streamflow forecasts in Australia, including meeting the needs for accurate predictions across all flow ranges and comparing forecasts generated by event and continuous hydrological models.

Genetic Algorithm Based Framework for Automation of Stochastic Modeling of Multi-Season Streamflows

NASA Astrophysics Data System (ADS)

Srivastav, R. K.; Srinivasan, K.; Sudheer, K.

2009-05-01

Synthetic streamflow data generation involves the synthesis of likely streamflow patterns that are statistically indistinguishable from the observed streamflow data. The various kinds of stochastic models adopted for multi-season streamflow generation in hydrology are: i) parametric models which hypothesize the form of the periodic dependence structure and the distributional form a priori (examples are PAR, PARMA); disaggregation models that aim to preserve the correlation structure at the periodic level and the aggregated annual level; ii) Nonparametric models (examples are bootstrap/kernel based methods), which characterize the laws of chance, describing the stream flow process, without recourse to prior assumptions as to the form or structure of these laws; (k-nearest neighbor (k-NN), matched block bootstrap (MABB)); non-parametric disaggregation model. iii) Hybrid models which blend both parametric and non-parametric models advantageously to model the streamflows effectively. Despite many of these developments that have taken place in the field of stochastic modeling of streamflows over the last four decades, accurate prediction of the storage and the critical drought characteristics has been posing a persistent challenge to the stochastic modeler. This is partly because, usually, the stochastic streamflow model parameters are estimated by minimizing a statistically based objective function (such as maximum likelihood (MLE) or least squares (LS) estimation) and subsequently the efficacy of the models is being validated based on the accuracy of prediction of the estimates of the water-use characteristics, which requires large number of trial simulations and inspection of many plots and tables. Still accurate prediction of the storage and the critical drought characteristics may not be ensured. In this study a multi-objective optimization framework is proposed to find the optimal hybrid model (blend of a simple parametric model, PAR(1) model and matched block bootstrap (MABB) ) based on the explicit objective functions of minimizing the relative bias and relative root mean square error in estimating the storage capacity of the reservoir. The optimal parameter set of the hybrid model is obtained based on the search over a multi- dimensional parameter space (involving simultaneous exploration of the parametric (PAR(1)) as well as the non-parametric (MABB) components). This is achieved using the efficient evolutionary search based optimization tool namely, non-dominated sorting genetic algorithm - II (NSGA-II). This approach helps in reducing the drudgery involved in the process of manual selection of the hybrid model, in addition to predicting the basic summary statistics dependence structure, marginal distribution and water-use characteristics accurately. The proposed optimization framework is used to model the multi-season streamflows of River Beaver and River Weber of USA. In case of both the rivers, the proposed GA-based hybrid model yields a much better prediction of the storage capacity (where simultaneous exploration of both parametric and non-parametric components is done) when compared with the MLE-based hybrid models (where the hybrid model selection is done in two stages, thus probably resulting in a sub-optimal model). This framework can be further extended to include different linear/non-linear hybrid stochastic models at other temporal and spatial scales as well.

Effects of snow persistence on streamflow generation in mountain regions of the western U.S.

NASA Astrophysics Data System (ADS)

Hammond, J. C.; Kampf, S. K.

2015-12-01

In mountain regions, both snowpack trend analyses and modeling studies suggest that streamflow generation is sensitive to loss of snow, yet we still lack understanding of where the most snow-sensitive regions are located. Snow persistence (SP), defined as the fraction of year that an area is snow-covered, is a useful variable for identifying snow-sensitive regions because it is easily observed globally using remote sensing. SP can affect streamflow generation by shifting the timing and magnitude of water input. All other factors being equal, we hypothesize that declining SP decreases the ratio of streamflow to precipitation (runoff ratio), and the magnitude of this effect is greater in arid climates than in humid climates. To evaluate whether streamflow generation declines with decreasing SP, we used the MODSCAG fractional snow cover product and 68 USGS reference catchments across five mountainous regions of the Western U.S. to compute annual and mean annual SP and discharge for water years 2000 to 2011. We used PRISM precipitation to compute the annual and mean annual runoff ratio for each catchment. Results show strong positive relationships between annual SP and annual runoff ratio in the Northern Rockies, Southern Rockies, and Basin and Range, where annual precipitation ranges from 0.25 m at low elevations in the Basin and Range to 2.5 m at high elevations in the Northern Rockies. Mean annual runoff ratios for these regions range from 0.32-0.53, and they also increase with mean annual SP. No relationships between annual SP and runoff ratios are evident in the wetter North Cascades and Sierra Nevada ranges, where annual precipitation ranges from 0.44 m in the low elevation Sierras to 4.8 m in the high elevation Cascades. Mean annual runoff ratios for these regions are 0.53-0.87 and show no clear dependence on SP. These results suggest that streamflow generation in arid regions may be most sensitive to loss of persistent winter snow.

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.

Carbon isotope fractionation of dissolved inorganic carbon (DIC) due to outgassing of carbon dioxide from a headwater stream

Treesearch

Daniel H. Doctor; Carol Kendall; Stephen D. Sebestyen; James B. Shanley; Nobuhito Ohte; Elizabeth W. Boyer

2008-01-01

The stable isotopic composition of dissolved inorganic carbon (δ13C-DIC) was investigated as a potential tracer of streamflow generation processes at the Sleepers River Research Watershed, Vermont, USA. Downstream sampling showed δ13C-DIC increased between 3-5% from the stream source to the outlet weir...

Hydrological connectivity of hillslopes and streams: characteristic time scales and nonlinearities

Treesearch

Kevin J. McGuire; Jeffrey J. McDonnell

2010-01-01

Subsurface flow from hillslopes is widely recognized as an important contributor to streamflow generation; however, processes that control how and when hillslopes connect to streams remain unclear. We investigated stream and hillslope runoff dynamics through a wet-up period in watershed 10 of the H. J. Andrews Experimental Forest in the western Cascades of Oregon where...

Reconciling Streamflow Uncertainty Estimation and River Bed Morphology Dynamics. Insights from a Probabilistic Assessment of Streamflow Uncertainties Using a Reliability Diagram

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.

Insights into hydrologic and hydrochemical processes based on concentration-discharge and end-member mixing analyses in the mid-Merced River Basin, Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Liu, Fengjing; Conklin, Martha H.; Shaw, Glenn D.

2017-01-01

Both concentration-discharge relation and end-member mixing analysis were explored to elucidate the connectivity of hydrologic and hydrochemical processes using chemical data collected during 2006-2008 at Happy Isles (468 km2), Pohono Bridge (833 km2), and Briceburg (1873 km2) in the snowmelt-fed mid-Merced River basin, augmented by chemical data collected by the USGS during 1990-2014 at Happy Isles. Concentration-discharge (C-Q) in streamflow was dominated by a well-defined power law relation, with the magnitude of exponent (0.02-0.6) and R2 values (p < 0.001) lower on rising than falling limbs. Concentrations of conservative solutes in streamflow resulted from mixing of two end-members at Happy Isles and Pohono Bridge and three at Briceburg, with relatively constant solute concentrations in end-members. The fractional contribution of groundwater was higher on rising than falling limbs at all basin scales. The relationship between the fractional contributions of subsurface flow and groundwater and streamflow (F-Q) followed the same relation as C-Q as a result of end-member mixing. The F-Q relation was used as a simple model to simulate subsurface flow and groundwater discharges to Happy Isles from 1990 to 2014 and was successfully validated by solute concentrations measured by the USGS. It was also demonstrated that the consistency of F-Q and C-Q relations is applicable to other catchments where end-members and the C-Q relationships are well defined, suggesting hydrologic and hydrochemical processes are strongly coupled and mutually predictable. Combining concentration-discharge and end-member mixing analyses could be used as a diagnostic tool to understand streamflow generation and hydrochemical controls in catchment hydrologic studies.

Changes in Stream Peak Flow and Regulation in Naoli River Watershed as a Result of Wetland Loss

PubMed Central

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

Combination of geochemical and hydrobiological tracers for the analysis of runoff generating processes in a lowland catchment

NASA Astrophysics Data System (ADS)

Faber, Claas; Wu, Naicheng; Ulrich, Uta; Fohrer, Nicola

2015-04-01

Since lowlands are characterised by flat topography and low hydraulic gradients, groundwater inflow has a large influence to streamflow generation in such catchments. In catchments with intense agricultural land use, artificial drainages are often another major contributor to streamflow. They shorten the soil passage and thus change the matter retention potential as well as runoff dynamics of a catchment. Contribution of surface runoff to streamflow is usually less important in volume. However, due to high concentrations of agrochemicals, surface runoff can constitute an important entry pathway into water bodies, especially if strong precipitation events coincide with fertilizer or pesticide application. The DFG funded project "Separating surface runoff from tile drainage flow in agricultural lowland catchments based on diatoms to improve modelled runoff components and phosphorous transport" investigates prevalent processes in this context in a 50 km² lowland catchment (Kielstau, Schleswig-Holstein, Germany) with the goal of improving existing models. End Member Mixing Analysis (EMMA) is used in the project to determine the relative importance of groundwater, tile drainage and surface runoff to streamflow at daily time steps. It became apparent that geochemical tracers are suitable for distinguishing surface runoff, but are weak for the separation of tile drainage and groundwater influence. We attribute this to the strong and complex interaction between soil water and shallow groundwater tables in the catchment. Recent studies (e.g. Pfister et al. 2011, Tauro et al. 2013) show the potential of diatoms as indicators for hydrological processes. Since we found diatoms to be suitable for the separation of tile drainage and stream samples (Wu et al., unpublished data) in our catchment, we are able to include diatom derived indices (e.g. density, species moisture indices, diversity indices) as traces in EMMA. Our results show that the inclusion of diatom data in the EMMA dataset improves the ability to distinguish tile drainage, groundwater and surface runoff influence to streamflow in our agriculturally dominated lowland catchment. Keywords: tile drainage, surface runoff, groundwater, hydrograph separation, EMMA, dia-toms, water quality, lowland catchments References: Pfister L, Wetzel CE, Martínez-Carreras N, Frentress J, Ector L, Hoffmann L, McDonnell JJ. 2011. Do diatoms run downhill? Using biodiversity of terrestrial and aquatic diatoms to identify hydrological connectivity between aquatic zones in Luxembourg. AGU Fall Meeting. Tauro F, Martínez-Carreras N, Wetzel CE, Hissler C, Barnich F, Frentress J, Ector L, Hoff-mann L, McDonnell JJ, Pfister L. 2013. Fluorescent diatoms as hydrological tracers: a proof of concept percolation experiment. EGU abstract, EGU2013-7687-4.

Calculation of streamflow statistics for Ontario and the Great Lakes states

USGS Publications Warehouse

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.

What Do They Have in Common? Drivers of Streamflow Spatial Correlation and Prediction of Flow Regimes in Ungauged Locations

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.

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.

Modelling the effects of Prairie wetlands on streamflow

NASA Astrophysics Data System (ADS)

Shook, K.; Pomeroy, J. W.

2015-12-01

Recent research has demonstrated that the contributing areas of Prairie streams dominated by depressional (wetland) storage demonstrate hysteresis with respect to catchment water storage. As such contributing fractions can vary over time from a very small percentage of catchment area to the entire catchment during floods. However, catchments display complex memories of past storage states and their contributing fractions cannot be modelled accurately by any single-valued function. The Cold Regions Hydrological Modelling platform, CRHM, which is capable of modelling all of the hydrological processes of cold regions using a hydrological response unit discretization of the catchment, was used to further investigate dynamical contributing area response to hydrological processes. Contributing fraction in CRHM is also controlled by the episodic nature of runoff generation in this cold, sub-humid environment where runoff is dominated by snowmelt over frozen soils, snowdrifts define the contributing fraction in late spring, unfrozen soils have high water holding capacity and baseflow from sub-surface flow does not exist. CRHM was improved by adding a conceptual model of individual Prairie depression fill and spill runoff generation that displays hysteresis in the storage - contributing fraction relationship and memory of storage state. The contributing area estimated by CRHM shows strong sensitivity to hydrological inputs, storage and the threshold runoff rate chosen. The response of the contributing area to inputs from various runoff generating processes from snowmelt to rain-on-snow to rainfall with differing degrees of spatial variation was investigated as was the importance of the memory of storage states on streamflow generation. The importance of selecting hydrologically and ecologically meaningful runoff thresholds in estimating contributing area is emphasized.

Improvement of Operational Streamflow Prediction with MODIS-derived Fractional Snow Covered Area Observations

NASA Astrophysics Data System (ADS)

Bender, S.; Burgess, A.; Goodale, C. E.; Mattmann, C. A.; Miller, W. P.; Painter, T. H.; Rittger, K. E.; Stokes, M.; Werner, K.

2013-12-01

Water managers in the western United States depend heavily on the timing and magnitude of snowmelt-driven runoff for municipal supply, irrigation, maintenance of environmental flows, and power generation. The Colorado Basin River Forecast Center (CBRFC) of the National Weather Service issues operational forecasts of snowmelt-driven streamflow for watersheds within the Colorado River Basin (CRB) and eastern Great Basin (EGB), across a wide variety of scales. Therefore, the CBRFC and its stakeholders consider snowpack observations to be highly valuable. Observations of fractional snow covered area (fSCA) from satellite-borne instrumentation can better inform both forecasters and water users with respect to subsequent snowmelt runoff, particularly when combined with observations from ground-based station networks and/or airborne platforms. As part of a multi-year collaborative effort, CBRFC has partnered with the Jet Propulsion Laboratory (JPL) under funding from NASA to incorporate observations of fSCA from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) into the operational CBRFC hydrologic forecasting and modeling process. In the first year of the collaboration, CBRFC and NASA/JPL integrated snow products into the forecasting and decision making processes of the CBRFC and showed preliminary improvement in operational streamflow forecasts. In late 2012, CBRFC and NASA/JPL began retrospective analysis of relationships between the MODIS Snow Covered Area and Grain size (MODSCAG) fSCA and streamflow patterns for several watersheds within the CRB and the EGB. During the 2013 snowmelt runoff season, CBRFC forecasters used MODIS-derived fSCA semi-quantitatively as a binary indicator of the presence or lack of snow. Indication of the presence or lack of snow by MODIS assisted CBRFC forecasters in determining the cause of divergence between modeled and recently observed streamflow. Several examples of improved forecasts from across the CRB and EGB, informed by MODIS-derived fSCA, are described. Our analysis shows the value of MODIS fSCA to CBRFC and to users of CBRFC's streamflow forecasts. The relationships between the MODIS fSCA and the melt season streamflow vary with the magnitude of runoff, which is important to resource managers. The analysis also emphasizes the importance of the invaluable collaboration between an operational forecasting agency (CBRFC) and a research-oriented agency (NASA/JPL) specializing in remote sensing science. The collaboration is expected to continue over the next several years as CBRFC and JPL work to further improve modeling of snowmelt and prediction of snowmelt-driven streamflow in the CRB and EGB.

Physically Based Mountain Hydrological Modelling using Reanalysis Data in Patagonia

NASA Astrophysics Data System (ADS)

Krogh, S.; Pomeroy, J. W.; McPhee, J. P.

2013-05-01

Remote regions in South America are often characterized by insufficient observations of meteorology for robust hydrological model operation. Yet water resources must be quantified, understood and predicted in order to develop effective water management policies. Here, we developed a physically based hydrological model for a major river in Patagonia using the modular Cold Regions Hydrological Modelling Platform (CRHM) in order to better understand hydrological processes leading to streamflow generation in this remote region. The Baker River -with the largest mean annual streamflow in Chile-, drains snowy mountains, glaciers, wet forests, peat and semi-arid pampas into a large lake. Meteorology over the basin is poorly monitored in that there are no high elevation weather stations and stations at low elevations are sparsely distributed, only measure temperature and rainfall and are poorly maintained. Streamflow in the basin is gauged at several points where there are high quality hydrometric stations. In order to quantify the impact of meteorological data scarcity on prediction, two additional data sources were used: the ERA-Interim (ECMWF Re-analyses) and CFSR (Climate Forecast System Reanalysis) atmospheric reanalyses. Precipitation temporal distribution and magnitude from the models and observations were compared and the reanalysis data was found to have about three times the number of days with precipitation than the observations did. Better synchronization between measured peak streamflows and modeled precipitation was found compared to observed precipitation. These differences are attributed to: (i) lack of any snowfall observations (so precipitation records does not consider snowfall events) and (ii) available rainfall observations are all located at low altitude (<500 m a.s.l), and miss the occurrence of high altitude precipitation events. CRHM parameterization was undertaken by using local physiographic and vegetation characteristics where available and transferring locally unknown hydrological process parameters from cold regions mountain environments in Canada. Some soil moisture parameters were calibrated from streamflow observations. Model performance was estimated through comparison with observed streamflow records. Simulations using observed precipitation had negligible representativeness of streamflow (Nash-Sutcliffe coefficient, NS ≈ 0.2), while those using any of the two reanalyses as forcing data had reasonable model performance (NS ≈ 0.7). In spite of the better spatial resolution of the CFSR, the ability to simulate streamflow were not significantly different using either CFSR or ERA-Interim. The modeled water balance shows that snowfall is about 30% of the total precipitation input, but snowmelt superficial runoff comprises about 10% of total runoff. About 75% of all precipitation is infiltrated, and approximately 15% of the losses are attributed to evapotranspiration from soil and lake evaporation.

Hydrologic classification of rivers based on cluster analysis of dimensionless hydrologic signatures: Applications for environmental instream flows

NASA Astrophysics Data System (ADS)

Praskievicz, S. J.; Luo, C.

2017-12-01

Classification of rivers is useful for a variety of purposes, such as generating and testing hypotheses about watershed controls on hydrology, predicting hydrologic variables for ungaged rivers, and setting goals for river management. In this research, we present a bottom-up (based on machine learning) river classification designed to investigate the underlying physical processes governing rivers' hydrologic regimes. The classification was developed for the entire state of Alabama, based on 248 United States Geological Survey (USGS) stream gages that met criteria for length and completeness of records. Five dimensionless hydrologic signatures were derived for each gage: slope of the flow duration curve (indicator of flow variability), baseflow index (ratio of baseflow to average streamflow), rising limb density (number of rising limbs per unit time), runoff ratio (ratio of long-term average streamflow to long-term average precipitation), and streamflow elasticity (sensitivity of streamflow to precipitation). We used a Bayesian clustering algorithm to classify the gages, based on the five hydrologic signatures, into distinct hydrologic regimes. We then used classification and regression trees (CART) to predict each gaged river's membership in different hydrologic regimes based on climatic and watershed variables. Using existing geospatial data, we applied the CART analysis to classify ungaged streams in Alabama, with the National Hydrography Dataset Plus (NHDPlus) catchment (average area 3 km2) as the unit of classification. The results of the classification can be used for meeting management and conservation objectives in Alabama, such as developing statewide standards for environmental instream flows. Such hydrologic classification approaches are promising for contributing to process-based understanding of river systems.

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.

Trends in selected streamflow statistics at 19 long-term streamflow-gaging stations indicative of outflows from Texas to Arkansas, Louisiana, Galveston Bay, and the Gulf of Mexico, 1922-2009

USGS Publications Warehouse

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.

A Comparison of Turbidity-Based and Streamflow-Based Estimates of Suspended-Sediment Concentrations in Three Chesapeake Bay Tributaries

USGS Publications Warehouse

Jastram, John D.; Moyer, Douglas; Hyer, Kenneth

2009-01-01

Fluvial transport of sediment into the Chesapeake Bay estuary is a persistent water-quality issue with major implications for the overall health of the bay ecosystem. Accurately and precisely estimating the suspended-sediment concentrations (SSC) and loads that are delivered to the bay, however, remains challenging. Although manual sampling of SSC produces an accurate series of point-in-time measurements, robust extrapolation to unmeasured periods (especially highflow periods) has proven to be difficult. Sediment concentrations typically have been estimated using regression relations between individual SSC values and associated streamflow values; however, suspended-sediment transport during storm events is extremely variable, and it is often difficult to relate a unique SSC to a given streamflow. With this limitation for estimating SSC, innovative approaches for generating detailed records of suspended-sediment transport are needed. One effective method for improved suspended-sediment determination involves the continuous monitoring of turbidity as a surrogate for SSC. Turbidity measurements are theoretically well correlated to SSC because turbidity represents a measure of water clarity that is directly influenced by suspended sediments; thus, turbidity-based estimation models typically are effective tools for generating SSC data. The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency Chesapeake Bay Program and Virginia Department of Environmental Quality, initiated continuous turbidity monitoring on three major tributaries of the bay - the James, Rappahannock, and North Fork Shenandoah Rivers - to evaluate the use of turbidity as a sediment surrogate in rivers that deliver sediment to the bay. Results of this surrogate approach were compared to the traditionally applied streamflow-based approach for estimating SSC. Additionally, evaluation and comparison of these two approaches were conducted for nutrient estimations. Results demonstrate that the application of turbidity-based estimation models provides an improved method for generating a continuous record of SSC, relative to the classical approach that uses streamflow as a surrogate for SSC. Turbidity-based estimates of SSC were found to be more accurate and precise than SSC estimates from streamflow-based approaches. The turbidity-based SSC estimation models explained 92 to 98 percent of the variability in SSC, while streamflow-based models explained 74 to 88 percent of the variability in SSC. Furthermore, the mean absolute error of turbidity-based SSC estimates was 50 to 87 percent less than the corresponding values from the streamflow-based models. Statistically significant differences were detected between the distributions of residual errors and estimates from the two approaches, indicating that the turbidity-based approach yields estimates of SSC with greater precision than the streamflow-based approach. Similar improvements were identified for turbidity-based estimates of total phosphorus, which is strongly related to turbidity because total phosphorus occurs predominantly in particulate form. Total nitrogen estimation models based on turbidity and streamflow generated estimates of similar quality, with the turbidity-based models providing slight improvements in the quality of estimations. This result is attributed to the understanding that nitrogen transport is dominated by dissolved forms that relate less directly to streamflow and turbidity. Improvements in concentration estimation resulted in improved estimates of load. Turbidity-based suspended-sediment loads estimated for the James River at Cartersville, VA, monitoring station exhibited tighter confidence interval bounds and a coefficient of variation of 12 percent, compared with a coefficient of variation of 38 percent for the streamflow-based load.

Post-processing ECMWF precipitation and temperature ensemble reforecasts for operational hydrologic forecasting at various spatial scales

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.

Water's Way at Sleepers River watershed – revisiting flow generation in a post-glacial landscape, Vermont USA

USGS Publications Warehouse

Shanley, James B.; Sebestyen, Stephen D.; McDonnell, Jeffrey J.; McGlynn, Brian L.; Dunne, Thomas

2015-01-01

The Sleepers River Research Watershed (SRRW) in Vermont, USA, has been the site of active hydrologic research since 1959 and was the setting where Dunne and Black demonstrated the importance and controls of saturation-excess overland flow (SOF) on streamflow generation. Here, we review the early studies from the SRRW and show how they guided our conceptual approach to hydrologic research at the SRRW during the most recent 25 years. In so doing, we chronicle a shift in the field from early studies that relied exclusively on hydrometric measurements to today's studies that include chemical and isotopic approaches to further elucidate streamflow generation mechanisms. Highlights of this evolution in hydrologic understanding include the following: (i) confirmation of the importance of SOF to streamflow generation, and at larger scales than first imagined; (ii) stored catchment water dominates stream response, except under unusual conditions such as deep frozen ground; (iii) hydrometric, chemical and isotopic approaches to hydrograph separation yield consistent and complementary results; (iv) nitrate and sulfate isotopic compositions specific to atmospheric inputs constrain new water contributions to streamflow; and (v) convergent areas, or ‘hillslope hollows’, contribute disproportionately to event hydrographs. We conclude by summarizing some remaining challenges that lead us to a vision for the future of research at the SRRW to address fundamental questions in the catchment sciences.

Framework for a hydrologic climate-response network in New England

USGS Publications Warehouse

Lent, Robert M.; Hodgkins, Glenn A.; Dudley, Robert W.; Schalk, Luther F.

2015-01-01

Many climate-related hydrologic variables in New England have changed in the past century, and many are expected to change during the next century. It is important to understand and monitor these changes because they can affect human water supply, hydroelectric power generation, transportation infrastructure, and stream and riparian ecology. This report describes a framework for hydrologic monitoring in New England by means of a climate-response network. The framework identifies specific inland hydrologic variables that are sensitive to climate variation; identifies geographic regions with similar hydrologic responses; proposes a fixed-station monitoring network composed of existing streamflow, groundwater, lake ice, snowpack, and meteorological data-collection stations for evaluation of hydrologic response to climate variation; and identifies streamflow basins for intensive, process-based studies and for estimates of future hydrologic conditions.

Using snow data assimilation to improve ensemble streamflow forecasting for the Upper Colorado River Basin

NASA Astrophysics Data System (ADS)

Micheletty, P. D.; Perrot, D.; Day, G. N.; Lhotak, J.; Quebbeman, J.; Park, G. H.; Carney, S.

2017-12-01

Water supply forecasting in the western United States is inextricably linked to snowmelt processes, as approximately 70-85% of total annual runoff comes from water stored in seasonal mountain snowpacks. Snowmelt-generated streamflow is vital to a variety of downstream uses; the Upper Colorado River Basin (UCRB) alone provides water supply for 25 million people, irrigation water for 3.5 million acres, and drives hydropower generation at Lake Powell. April-July water supply forecasts produced by the National Weather Service (NWS) Colorado Basin River Forecast Center (CBRFC) are critical to basin water management. The primary objective of this project as part of the NASA Water Resources Applied Science Program, is to improve water supply forecasting for the UCRB by assimilating satellite and ground snowpack observations into a distributed hydrologic model at various times during the snow accumulation and melt seasons. To do this, we have built a framework that uses an Ensemble Kalman Filter (EnKF) to update modeled snow water equivalent (SWE) states in the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) with spatially interpolated SNOTEL snow water equivalent (SWE) observations and products from the MODIS Snow Covered-Area and Grain size retrieval algorithm (when available). We have generated April-July water supply reforecasts for a 20-year period (1991-2010) for several headwater catchments in the UCRB using HL-RDHM and snow data assimilation in the Ensemble Streamflow Prediction (ESP) framework. The existing CBRFC ESP reforecasts will provide a baseline for comparison to determine whether the data assimilation process adds skill to the water supply forecasts. Preliminary results from one headwater basin show improved skill in water supply forecasting when HL-RDHM is run with the data assimilation step compared to HL-RDHM run without the data assimilation step, particularly in years when MODSCAG data were available (2000-2010). The final forecasting framework developed during this project will be delivered to CBRFC and run operationally for a set of pilot basins.

AOIPS water resources data management system

NASA Technical Reports Server (NTRS)

Vanwie, P.

1977-01-01

The text and computer-generated displays used to demonstrate the AOIPS (Atmospheric and Oceanographic Information Processing System) water resources data management system are investigated. The system was developed to assist hydrologists in analyzing the physical processes occurring in watersheds. It was designed to alleviate some of the problems encountered while investigating the complex interrelationships of variables such as land-cover type, topography, precipitation, snow melt, surface runoff, evapotranspiration, and streamflow rates. The system has an interactive image processing capability and a color video display to display results as they are obtained.

Streamflow predictions in Alpine Catchments by using artificial neural networks. Application in the Alto Genil Basin (South Spain)

NASA Astrophysics Data System (ADS)

Jimeno-Saez, Patricia; Pegalajar-Cuellar, Manuel; Pulido-Velazquez, David

2017-04-01

This study explores techniques of modeling water inflow series, focusing on techniques of short-term steamflow prediction. An appropriate estimation of streamflow in advance is necessary to anticipate measures to mitigate the impacts and risks related to drought conditions. This study analyzes the prediction of future streamflow of nineteen subbasins in the Alto-Genil basin in Granada (Southeast of Spain). Some of these basin streamflow have an important component of snowmelt due to part of the system is located in Sierra Nevada Mountain Range, the highest mountain of continental Spain. Streamflow prediction models have been calibrated using time series of historical natural streamflows. The available streamflow measurements have been downloaded from several public data sources. These original data have been preprocessed to turn them to the original natural regime, removing the anthropic effects. The missing values in the adopted horizon period to calibrate the prediction models have been estimated by using a Temez hydrological balance model, approaching the snowmelt processes with a hybrid degree day method. In the experimentation, ARIMA models are used as baseline method, and recurrent neural networks ELMAN and nonlinear autoregressive neural network (NAR) to test if the prediction accuracy can be improved. After performing the multiple experiments with these models, non-parametric statistical tests are applied to select the best of these techniques. In the experiments carried out with ARIMA, it is concluded that ARIMA models are not adequate in this case study due to the existence of a nonlinear component that cannot be modeled. Secondly, ELMAN and NAR neural networks with multi-start training is performed with each network structure to deal with the local optimum problem, since in neural network training there is a very strong dependence on the initial weights of the network. The obtained results suggest that both neural networks are efficient for the short term prediction, surpassing the limitations of the ARIMA models and, in general, the experiments showed that NAR networks are the ones with the greatest generalization capability. Therefore, NAR networks are chosen as the starting point for other works, in which we study the streamflow predictions incorporating exogenous variables (as the Snow Cover Area), the sensitivity of the prediction to the initial conditions, multivariate streamflow predictions considering the spatial correlation between the sub-basins streamflow and the synthetic generations to assess droughts statistic. This research has been partially supported by the CGL2013-48424-C2-2-R (MINECO) and the PMAFI/06/14 (UCAM) projects.

Measuring real-time streamflow using emerging technologies: Radar, hydroacoustics, and the probability concept

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.

Measuring real-time streamflow using emerging technologies: Radar, hydroacoustics, and the probability concept

USGS Publications Warehouse

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.

Nationwide validation of ensemble streamflow forecasts from the Hydrologic Ensemble Forecast Service (HEFS) of the U.S. National Weather Service

NASA Astrophysics Data System (ADS)

Lee, H. S.; Liu, Y.; Ward, J.; Brown, J.; Maestre, A.; Herr, H.; Fresch, M. A.; Wells, E.; Reed, S. M.; Jones, E.

2017-12-01

The National Weather Service's (NWS) Office of Water Prediction (OWP) recently launched a nationwide effort to verify streamflow forecasts from the Hydrologic Ensemble Forecast Service (HEFS) for a majority of forecast locations across the 13 River Forecast Centers (RFCs). Known as the HEFS Baseline Validation (BV), the project involves a joint effort between the OWP and the RFCs. It aims to provide a geographically consistent, statistically robust validation, and a benchmark to guide the operational implementation of the HEFS, inform practical applications, such as impact-based decision support services, and to provide an objective framework for evaluating strategic investments in the HEFS. For the BV, HEFS hindcasts are issued once per day on a 12Z cycle for the period of 1985-2015 with a forecast horizon of 30 days. For the first two weeks, the hindcasts are forced with precipitation and temperature ensemble forecasts from the Global Ensemble Forecast System of the National Centers for Environmental Prediction, and by resampled climatology for the remaining period. The HEFS-generated ensemble streamflow hindcasts are verified using the Ensemble Verification System. Skill is assessed relative to streamflow hindcasts generated from NWS' current operational system, namely climatology-based Ensemble Streamflow Prediction. In this presentation, we summarize the results and findings to date.

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.

Attribution of Observed Streamflow Changes in Key British Columbia Drainage Basins

NASA Astrophysics Data System (ADS)

Najafi, Mohammad Reza; Zwiers, Francis W.; Gillett, Nathan P.

2017-11-01

We study the observed decline in summer streamflow in four key river basins in British Columbia (BC), Canada, using a formal detection and attribution (D&A) analysis procedure. Reconstructed and simulated streamflow is generated using the semidistributed variable infiltration capacity hydrologic model, which is driven by 1/16° gridded observations and downscaled climate model data from the Coupled Model Intercomparison Project phase 5 (CMIP5), respectively. The internal variability of the regional hydrologic components using 5100 years of streamflow was simulated using CMIP5 preindustrial control runs. Results show that the observed changes in summer streamflow are inconsistent with simulations representing the responses to natural forcing factors alone, while the response to anthropogenic and natural forcing factors combined is detected in these changes. A two-signal D&A analysis indicates that the effects of anthropogenic (ANT) forcing factors are discernable from natural forcing in BC, albeit with large uncertainties.

Hydrological effects of cropland and climatic changes in arid and semi-arid river basins: A case study from the Yellow River basin, China

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.

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.

"HIP" new software: The Hydroecological Integrity Assessment Process

USGS Publications Warehouse

Henriksen, Jim; Wilson, Juliette T.

2006-01-01

Center (FORT) have developed the Hydroecological Integrity Assessment Process (HIP) and a suite of software tools for conducting a hydrologic classification of streams, addressing instream flow needs, and assessing past and proposed hydrologic alterations on streamflow and other ecosystem components. The HIP recognizes that streamflow is strongly related to many critical physiochemical components of rivers, such as dissolved oxygen, channel geomorphology, and habitats. Streamflow is considered a “master variable” that limits the distribution, abundance, and diversity of many aquatic plant and animal species.

System dynamics model for predicting floods from snowmelt in North American prairie watersheds

NASA Astrophysics Data System (ADS)

Li, L.; Simonovic, S. P.

2002-09-01

This study uses a system dynamics approach to explore hydrological processes in the geographic locations where the main contribution to flooding is coming from the snowmelt. Temperature is identified as a critical factor that affects watershed hydrological processes. Based on the dynamic processes of the hydrologic cycle occurring in a watershed, the feedback relationships linking the watershed structure, as well as the climate factors, to the streamflow generation were identified prior to the development of a system dynamics model. The model is used to simulate flood patterns generated by snowmelt under temperature change in the spring. Model structure captures a vertical water balance using five tanks representing snow, interception, surface, subsurface and groundwater storage. Calibration and verification results show that temperature change and snowmelt play a key role in flood generation. Results indicate that simulated values match observed data very well. The goodness-of-fit between simulated and observed peak flow data is measured using coefficient of efficiency, coefficient of determination and square of the residual mass curve coefficient. For the Assiniboine River all three measures were in the interval between 0·92 and 0·96 and for the Red River between 0·89 and 0·97. The model is capable of capturing the essential dynamics of streamflow formation. Model input requires a set of initial values for all state variables and the time series of daily temperature and precipitation information. Data from the Red River Basin, shared by Canada and the USA, are used in the model development and testing.

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.

Hydrologic resilience of a Canadian Foothills watershed to forest harvest

NASA Astrophysics Data System (ADS)

Goodbrand, Amy; Anderson, Axel

2016-04-01

Recent investigations of long-term hydrometeorological, groundwater, and streamflow data from watersheds on the eastern slopes of the Canadian Rocky Mountains showed the streamflow regime was resilient to forest harvest. These watersheds had low levels of harvest relative to their size and a large area of sparsely vegetated alpine talus slopes and exposed bedrock; an area shown to generate the majority of runoff for streamflow. In contrast, watersheds located in the foothills of the Rocky Mountains are of lower relief and typically have harvestable timber throughout the watershed; therefore, these watersheds may be more sensitive to forest disturbance and have increased potential for streamflow response. This project assesses the hydrologic resilience of an Alberta Foothills watershed to forest harvest using a 23-year dataset from the Tri-Creeks Experimental Watershed (Tri-Creeks). Tri-Creeks has been the site of intensive streamflow, groundwater, snow accumulation, and precipitation observations from 1967 - 1990. During the early 1980s, forestry experiments were conducted to compare the effects of timber harvest and riparian buffers, and the effectiveness of timber harvesting ground rules in protecting fisheries and maintaining water resources within three sub-watersheds: Eunice (16.8 km2; control); Deerlick (15.2 km2; 36% streamside timber removal); and, Wampus (28.3 km2; 37% clear-cut). Statistical analyses were used to compare the pre-and post-harvest ratios of treatment to control sub-watershed runoff for: water year, monthly (April - October), snowmelt peak flow, and low flow (10th percentile streamflow) periods as an assessment of hydrologic resilience to forest harvest. The only significant post-harvest change was an increase in water yield during May at Wampus (Mann-Whitney (MW), p<0.05) and Deerlick (MW, p<0.1) Creeks. The lack of change in snowmelt peak flow timing or magnitude was not expected, particularly in Deerlick, which had 36% streamside timber removal. The streamflow regime of Tri-Creeks displayed remarkable resilience to forest harvest. We hypothesize on the processes and characteristics that result in this watershed to exhibit greater resilience compared to other forested watersheds.

Constraining the JULES land-surface model for different land-use types using citizen-science generated hydrological data

NASA Astrophysics Data System (ADS)

Chou, H. K.; Ochoa-Tocachi, B. F.; Buytaert, W.

2017-12-01

Community land surface models such as JULES are increasingly used for hydrological assessment because of their state-of-the-art representation of land-surface processes. However, a major weakness of JULES and other land surface models is the limited number of land surface parameterizations that is available. Therefore, this study explores the use of data from a network of catchments under homogeneous land-use to generate parameter "libraries" to extent the land surface parameterizations of JULES. The network (called iMHEA) is part of a grassroots initiative to characterise the hydrological response of different Andean ecosystems, and collects data on streamflow, precipitation, and several weather variables at a high temporal resolution. The tropical Andes are a useful case study because of the complexity of meteorological and geographical conditions combined with extremely heterogeneous land-use that result in a wide range of hydrological responses. We then calibrated JULES for each land-use represented in the iMHEA dataset. For the individual land-use types, the results show improved simulations of streamflow when using the calibrated parameters with respect to default values. In particular, the partitioning between surface and subsurface flows can be improved. But also, on a regional scale, hydrological modelling was greatly benefitted from constraining parameters using such distributed citizen-science generated streamflow data. This study demonstrates the modelling and prediction on regional hydrology by integrating citizen science and land surface model. In the context of hydrological study, the limitation of data scarcity could be solved indeed by using this framework. Improved predictions of such impacts could be leveraged by catchment managers to guide watershed interventions, to evaluate their effectiveness, and to minimize risks.

Analysis of the hydrological response of a distributed physically-based model using post-assimilation (EnKF) diagnostics of streamflow and in situ soil moisture observations

NASA Astrophysics Data System (ADS)

Trudel, Mélanie; Leconte, Robert; Paniconi, Claudio

2014-06-01

Data assimilation techniques not only enhance model simulations and forecast, they also provide the opportunity to obtain a diagnostic of both the model and observations used in the assimilation process. In this research, an ensemble Kalman filter was used to assimilate streamflow observations at a basin outlet and at interior locations, as well as soil moisture at two different depths (15 and 45 cm). The simulation model is the distributed physically-based hydrological model CATHY (CATchment HYdrology) and the study site is the Des Anglais watershed, a 690 km2 river basin located in southern Quebec, Canada. Use of Latin hypercube sampling instead of a conventional Monte Carlo method to generate the ensemble reduced the size of the ensemble, and therefore the calculation time. Different post-assimilation diagnostics, based on innovations (observation minus background), analysis residuals (observation minus analysis), and analysis increments (analysis minus background), were used to evaluate assimilation optimality. An important issue in data assimilation is the estimation of error covariance matrices. These diagnostics were also used in a calibration exercise to determine the standard deviation of model parameters, forcing data, and observations that led to optimal assimilations. The analysis of innovations showed a lag between the model forecast and the observation during rainfall events. Assimilation of streamflow observations corrected this discrepancy. Assimilation of outlet streamflow observations improved the Nash-Sutcliffe efficiencies (NSE) between the model forecast (one day) and the observation at both outlet and interior point locations, owing to the structure of the state vector used. However, assimilation of streamflow observations systematically increased the simulated soil moisture values.

Hydrological response to changing climate conditions: Spatial streamflow variability in the boreal region

NASA Astrophysics Data System (ADS)

Teutschbein, Claudia; Grabs, Thomas; Karlsen, Reinert H.; Laudon, Hjalmar; Bishop, Kevin

2016-04-01

It has long been recognized that streamflow-generating processes are not only dependent on climatic conditions, but also affected by physical catchment properties such as topography, geology, soils and land cover. We hypothesize that these landscape characteristics do not only lead to highly variable hydrologic behavior of rather similar catchments under the same stationary climate conditions (Karlsen et al., 2014), but that they also play a fundamental role for the sensitivity of a catchment to a changing climate (Teutschbein et al., 2015). A multi-model ensemble based on 15 regional climate models was combined with a multi-catchment approach to explore the hydrologic sensitivity of 14 partially nested and rather similar catchments in Northern Sweden to changing climate conditions and the importance of small-scale spatial variability. Current (1981-2010) and future (2061-2090) streamflow was simulated with the HBV model. As expected, projected increases in temperature and precipitation resulted in increased total available streamflow, with lower spring and summer flows, but substantially higher winter streamflow. Furthermore, significant changes in flow durations with lower chances of both high and low flows can be expected in boreal Sweden in the future. This overall trend in projected streamflow pattern changes was comparable among the analyzed catchments while the magnitude of change differed considerably. This suggests that catchments belonging to the same region can show distinctly different degrees of hydrological responses to the same external climate change signal. We reason that differences in spatially distributed physical catchment properties at smaller scales are not only of great importance for current streamflow behavior, but also play a major role as first-order control for the sensitivity of catchments to changing climate conditions. References Karlsen, R.H., T. Grabs, K. Bishop, H. Laudon, and J. Seibert (2014). Landscape controls on spatiotemporal variability of specific discharge in a boreal region, Abstract #H52B-07 presented at 2014 Fall Meeting, AGU, San Francisco, Calif., 15-19 Dec. [Available at http://adsabs.harvard.edu/abs/2014AGUFM.H52B..07K, last accessed 11 Jan 2016]. Teutschbein, C., T. Grabs, R.H. Karlsen, H. Laudon and K. Bishop (2015). Hydrological Response to Changing Climate Conditions: Spatial Streamflow Variability in the Boreal Region, Water Resour Res, doi: 10.1002/2015WR017337. [Available at http://onlinelibrary.wiley.com/doi/10.1002/2015WR017337/abstract, last accessed 11 Jan 2016].

What Do They Have in Common? Physical Drivers of Streamflow Spatial Correlation and Prediction of Flow Regimes at Ungauged Locations in the Contiguous United States

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.

Assessing streamflow sensitivity to variations in glacier mass balance

USGS Publications Warehouse

O'Neel, Shad; Hood, Eran; Arendt, Anthony; Sass, Louis

2014-01-01

The purpose of this paper is to evaluate relationships among seasonal and annual glacier mass balances, glacier runoff and streamflow in two glacierized basins in different climate settings. We use long-term glacier mass balance and streamflow datasets from the United States Geological Survey (USGS) Alaska Benchmark Glacier Program to compare and contrast glacier-streamflow interactions in a maritime climate (Wolverine Glacier) with those in a continental climate (Gulkana Glacier). Our overall goal is to improve our understanding of how glacier mass balance processes impact streamflow, ultimately improving our conceptual understanding of the future evolution of glacier runoff in continental and maritime climates.

User’s guide for the Delaware River Basin Streamflow Estimator Tool (DRB-SET)

USGS Publications Warehouse

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.

Covariability of Climate and Streamflow in the Upper Rio Grande from Interannual to Interdecadal Timescales

NASA Technical Reports Server (NTRS)

Pascolini-Campbell, M.; Seager, Richard; Pinson, Ariane; Cook, Benjamin I.

2017-01-01

Study region: The Upper Rio Grande (URG) flows from its headwaters in Colorado, U.S., and provides an important source of water to millions of people in the U.S. states of Colorado, New Mexico, Texas, and also Mexico. Study focus: We reassess the explanatory power of the relationship of sea surface temperatures (SST) on URG streamflow variability on interannual to interdecadal timescales. We find a significant amount of the variance of spring-summer URG streamflow cannot be fully explained by SST. New hydrological insights: We find that the interdecadal teleconnection between SST and streamflow is more clear than on interannual timescales. The highest ranked years tend to be clustered during positive phases of the Pacific Decadal Oscillation (PDO). During the periods of decadal high flow (1900-1920, and 1979-1995), Pacific SST resembles a positive PDO pattern and the Atlantic a negative Atlantic Multidecadal Oscillation (AMO) pattern; an interbasin pattern shown in prior studies to be conducive to high precipitation and streamflow. To account for the part of streamflow variance not explained by SST, we analyze atmospheric Reanalysis data for the months preceding the highest spring-summer streamflow events. A variety of atmospheric configurations are found to precede the highest flow years through anomalous moisture convergence. This lack of consistency suggests that, on interannual timescales, weather and not climate can dominate the generation of high streamflow events.

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.

Estimating daily time series of streamflow using hydrological model calibrated based on satellite observations of river water surface width: Toward real world applications.

PubMed

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.

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.

Land Cover Influence on Wet Season Storm Runoff Generation and Hydrologic Flowpaths in Central Panama

NASA Astrophysics Data System (ADS)

Birch, A. L.; Stallard, R. F.; Barnard, H. R.

2017-12-01

While relationships between land use/land cover and hydrology are well studied and understood in temperate parts of the world, little research exists in the humid tropics, where hydrologic research is often decades behind. Specifically, quantitative information on how physical and biological differences across varying land covers influence runoff generation and hydrologic flowpaths in the humid tropics is scarce; frequently leading to poorly informed hydrologic modelling and water policy decision making. This research effort seeks to quantify how tropical land cover change may alter physical hydrologic processes in the economically important Panama Canal Watershed (Republic of Panama) by separating streamflow into its different runoff components using end member mixing analysis. The samples collected for this project come from small headwater catchments of four varying land covers (mature tropical forest, young secondary forest, active pasture, recently clear-cut tropical forest) within the Smithsonian Tropical Research Institute's Agua Salud Project. During the past three years, samples have been collected at the four study catchments from streamflow and from a number of water sources within hillslope transects, and have been analyzed for stable water isotopes, major cations, and major anions. Major ion analysis of these samples has shown distinct geochemical differences for the potential runoff generating end members sampled (soil moisture/ preferential flow, groundwater, overland flow, throughfall, and precipitation). Based on this finding, an effort was made from May-August 2017 to intensively sample streamflow during wet season storm events, yielding a total of 5 events of varying intensity in each land cover/catchment, with sampling intensity ranging from sub-hourly to sub-daily. The focus of this poster presentation will be to present the result of hydrograph separation's done using end member mixing analysis from this May-August 2017 storm dataset. Expected results presented will yield an increase in the quantitative understanding of how land cover may influence physical hydrologic flowpaths and runoff generation in the humid tropics.

Drivers of annual to decadal streamflow variability in the lower Colorado River Basin

NASA Astrophysics Data System (ADS)

Lambeth-Beagles, R. S.; Troch, P. A.

2010-12-01

The Colorado River is the main water supply to the southwest region. As demand reaches the limit of supply in the southwest it becomes increasingly important to understand the dynamics of streamflow in the Colorado River and in particular the tributaries to the lower Colorado River. Climate change may pose an additional threat to the already-scarce water supply in the southwest. Due to the narrowing margin for error, water managers are keen on extending their ability to predict streamflow volumes on a mid-range to decadal scale. Before a predictive streamflow model can be developed, an understanding of the physical drivers of annual to decadal streamflow variability in the lower Colorado River Basin is needed. This research addresses this need by applying multiple statistical methods to identify trends, patterns and relationships present in streamflow, precipitation and temperature over the past century in four contributing watersheds to the lower Colorado River. The four watersheds selected were the Paria, Little Colorado, Virgin/Muddy, and Bill Williams. Time series data over a common period from 1906-2007 for streamflow, precipitation and temperature were used for the initial analysis. Through statistical analysis the following questions were addressed: 1) are there observable trends and patterns in these variables during the past century and 2) if there are trends or patterns, how are they related to each other? The Mann-Kendall test was used to identify trends in the three variables. Assumptions regarding autocorrelation and persistence in the data were taken into consideration. Kendall’s tau-b test was used to establish association between any found trends in the data. Initial results suggest there are two primary processes occurring. First, statistical analysis reveals significant upward trends in temperatures and downward trends in streamflow. However, there appears to be no trend in precipitation data. These trends in streamflow and temperature speak to increasing evaporation and transpiration processes. Second, annual variability in streamflow is not statistically correlated with annual temperature variability but appears to be highly correlated with annual precipitation variability. This implies that on a year-to-year basis, changes in streamflow volumes are directly affected by precipitation and not temperature. Future development of a predictive streamflow model will need to take into consideration these two processes to obtain accurate results. In order to extend predictive skill to the multi-year scale relationships between precipitation, temperature and persistent climate indices such as the Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation and El Nino/Southern Oscillation will need to be examined.

Exploring changes in the spatial distribution of stream baseflow generation during a seasonal recession

USGS Publications Warehouse

Payn, R.A.; Gooseff, M.N.; McGlynn, B.L.; Bencala, K.E.; Wondzell, S.M.

2012-01-01

Relating watershed structure to streamflow generation is a primary focus of hydrology. However, comparisons of longitudinal variability in stream discharge with adjacent valley structure have been rare, resulting in poor understanding of the distribution of the hydrologic mechanisms that cause variability in streamflow generation along valleys. This study explores detailed surveys of stream base flow across a gauged, 23 km2 mountain watershed. Research objectives were (1) to relate spatial variability in base flow to fundamental elements of watershed structure, primarily topographic contributing area, and (2) to assess temporal changes in the spatial patterns of those relationships during a seasonal base flow recession. We analyzed spatiotemporal variability in base flow using (1) summer hydrographs at the study watershed outlet and 5 subwatershed outlets and (2) longitudinal series of discharge measurements every ~100 m along the streams of the 3 largest subwatersheds (1200 to 2600 m in valley length), repeated 2 to 3 times during base flow recession. Reaches within valley segments of 300 to 1200 m in length tended to demonstrate similar streamflow generation characteristics. Locations of transitions between these segments were consistent throughout the recession, and tended to be collocated with abrupt longitudinal transitions in valley slope or hillslope-riparian characteristics. Both within and among subwatersheds, correlation between the spatial distributions of streamflow and topographic contributing area decreased during the recession, suggesting a general decrease in the influence of topography on stream base flow contributions. As topographic controls on base flow evidently decreased, multiple aspects of subsurface structure were likely to have gained influence.

Estimating the Exceedance Probability of the Reservoir Inflow Based on the Long-Term Weather Outlooks

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.

Estimation of daily mean streamflow for ungaged stream locations in the Delaware River Basin, water years 1960–2010

USGS Publications Warehouse

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.

Simulating Streamflow Using Bias-corrected Multiple Satellite Rainfall Products in the Tekeze Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Abitew, T. A.; Roy, T.; Serrat-Capdevila, A.; van Griensven, A.; Bauwens, W.; Valdes, J. B.

2016-12-01

The Tekeze Basin supports one of Africans largest Arch Dam located in northern Ethiopian has vital role in hydropower generation. However, little has been done on the hydrology of the basin due to limited in situ hydroclimatological data. Therefore, the main objective of this research is to simulate streamflow upstream of the Tekeze Dam using Soil and Water Assessment Tool (SWAT) forced by bias-corrected multiple satellite rainfall products (CMORPH, TMPA and PERSIANN-CCS). This talk will present the potential as well as skills of bias-corrected satellite rainfall products for streamflow prediction in in Tropical Africa. Additionally, the SWAT model results will also be compared with previous conceptual Hydrological models (HyMOD and HBV) from SERVIR Streamflow forecasting in African Basin project (http://www.swaat.arizona.edu/index.html).

Limits on characteristics of invertebrate assemblages associated with streamflow patterns in the western United States

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.

Technical Manual for the Geospatial Stream Flow Model (GeoSFM)

USGS Publications Warehouse

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.

Monthly streamflow forecasting using continuous wavelet and multi-gene genetic programming combination

NASA Astrophysics Data System (ADS)

Hadi, Sinan Jasim; Tombul, Mustafa

2018-06-01

Streamflow is an essential component of the hydrologic cycle in the regional and global scale and the main source of fresh water supply. It is highly associated with natural disasters, such as droughts and floods. Therefore, accurate streamflow forecasting is essential. Forecasting streamflow in general and monthly streamflow in particular is a complex process that cannot be handled by data-driven models (DDMs) only and requires pre-processing. Wavelet transformation is a pre-processing technique; however, application of continuous wavelet transformation (CWT) produces many scales that cause deterioration in the performance of any DDM because of the high number of redundant variables. This study proposes multigene genetic programming (MGGP) as a selection tool. After the CWT analysis, it selects important scales to be imposed into the artificial neural network (ANN). A basin located in the southeast of Turkey is selected as case study to prove the forecasting ability of the proposed model. One month ahead downstream flow is used as output, and downstream flow, upstream, rainfall, temperature, and potential evapotranspiration with associated lags are used as inputs. Before modeling, wavelet coherence transformation (WCT) analysis was conducted to analyze the relationship between variables in the time-frequency domain. Several combinations were developed to investigate the effect of the variables on streamflow forecasting. The results indicated a high localized correlation between the streamflow and other variables, especially the upstream. In the models of the standalone layout where the data were entered to ANN and MGGP without CWT, the performance is found poor. In the best-scale layout, where the best scale of the CWT identified as the highest correlated scale is chosen and enters to ANN and MGGP, the performance increased slightly. Using the proposed model, the performance improved dramatically particularly in forecasting the peak values because of the inclusion of several scales in which seasonality and irregularity can be captured. Using hydrological and meteorological variables also improved the ability to forecast the streamflow.

Understanding performance measures of reservoirs

NASA Astrophysics Data System (ADS)

McMahon, Thomas A.; Adeloye, Adebayo J.; Zhou, Sen-Lin

2006-06-01

This paper examines 10 reservoir performance metrics including time and volume based reliability, several measures of resilience and vulnerability, drought risk index and sustainability. Both historical and stochastically generated streamflows are considered as inflows to a range of hypothetical storage on four rivers—Earn river in the United Kingdom, Hatchie river in the United States, Richmond river in Australia and the Vis river in South Africa. The monthly stochastic sequences were generated applying an autoregressive lag one model to Box-Cox transformed annual streamflows incorporating parameter uncertainty by the Stedinger-Taylor method and the annual flows disaggregated by the method of fragments.

Precipitation-runoff processes in the Feather River basin, northeastern California, and streamflow predictability, water years 1971-97

USGS Publications Warehouse

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

Long-term enrichment of the stable isotopic composition of stream water due to the release of groundwater recharge from extreme precipitation events

NASA Astrophysics Data System (ADS)

Boutt, D. F.

2017-12-01

The isotopic composition of surface and groundwater is impacted by a multitude of hydrologic processes. The long-term response of these systems to hydrologic change is critical for appropriately interpreting isotopic information for streamflow generation, stream-aquifer-coupling, sources of water to wells, and understanding recharge processes. To evaluate the response time of stream-aquifer systems to extreme precipitation events we use a long-term isotope dataset from Western Massachusetts with drainage areas ranging from 0.1 to > 800 km2. The year of 2011 was the wettest calendar year on record and the months of August and September of 2011 were the wettest consecutive two-month period in the 123 year record. Stable isotopic composition of surface waters of catchments ranging from 1 - 1000 km2 show an enrichment due to summertime and Tropical Storm precipitation. Enrichment in potential recharge water is shown to have a significant long-term impact (> 3 hydrologic years) on the isotopic composition of both surface and groundwater. This highlights the importance of groundwater sources of baseflow to streams and the transient storage and release mechanisms of shallow groundwater storage. The length of isotopic recession of stream water are also a strong function of watershed area. It is concluded that the stream water isotopes are consistent with a large pulse of water being stored and released from enriched groundwater emplaced during this period of above-average precipitation. Ultimately the results point to the importance of considering hydrological processes of streamflow generation and their role in hydrologic processes beyond traditional catchment response analysis.

Effects of Uncertainties in Hydrological Modelling. A Case Study of a Mountainous Catchment in Southern Norway

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.

Consistent and efficient processing of ADCP streamflow measurements

USGS Publications Warehouse

Mueller, David S.; Constantinescu, George; Garcia, Marcelo H.; Hanes, Dan

2016-01-01

The use of Acoustic Doppler Current Profilers (ADCPs) from a moving boat is a commonly used method for measuring streamflow. Currently, the algorithms used to compute the average depth, compute edge discharge, identify invalid data, and estimate velocity and discharge for invalid data vary among manufacturers. These differences could result in different discharges being computed from identical data. Consistent computational algorithm, automated filtering, and quality assessment of ADCP streamflow measurements that are independent of the ADCP manufacturer are being developed in a software program that can process ADCP moving-boat discharge measurements independent of the ADCP used to collect the data.

Runoff Generation Mechanisms and Mean Transit Time in a High-Elevation Tropical Ecosystem

NASA Astrophysics Data System (ADS)

Mosquera, G.

2015-12-01

Understanding runoff generation processes in tropical mountainous regions remains poorly understood, particularly in ecosystems above the tree line. Here, we provide insights on the process dominating the ecohydrology of the tropical alpine biome (i.e., páramo) of the Zhurucay River Ecohydrological Observatory. The study site is located in south Ecuador between 3400-3900 m in elevation. We used a nested monitoring system with eight catchments (20-753 ha) to measure hydrometric data since December 2010. Biweekly samples of rainfall, streamflow, and soil water at low tension were collected for three years (May 2011-May2014) and analyzed for water stable isotopes. We conducted an isotopic characterization of rainfall, streamflow, and soil waters to investigate runoff generation. These data were also integrated into a lumped model to estimate the mean transit time (MTT) and to investigate landscape features that control its variability. The isotopic characterization evidenced that the water stored in the shallow organic horizon of the Histosol soils (Andean wetlands) located near the streams is the major contributor of water to the streams year-round, whereas the water draining through the hillslope soils, the Andosols, regulates discharge by recharging the wetlands at the valley bottoms. The MTT evaluation indicated relatively short MTTs (0.15-0.73 yr) linked to short subsurface flow paths of water. We also found evidence for topographic controls on the MTT variability. These results reveal that: 1) the ecohydrology of this ecosystem is dominated by shallow subsurface flow in the organic horizon of the soils and 2) the combination of the high storage capacity of the Andean wetlands and the slope of the catchments controls runoff generation and the high water regulation capacity of the ecosystem.

Mapping Active Stream Lengths as a Tool for Understanding Spatial Variations in Runoff Generation

NASA Astrophysics Data System (ADS)

Erwin, E. G.; Gannon, J. P.; Zimmer, M. A.

2016-12-01

Recent studies have shown temporary stream channels respond in complex ways to precipitation. By investigating how stream networks expand and recede throughout rain events, we may further develop our understanding of runoff generation. This study focused on mapping the expansion and contraction of the stream network in two headwater catchments characterized by differing soil depths and slopes, located in North Carolina, USA. The first is a 43 ha catchment located in the Southern Appalachian region, characterized by incised, steep slopes and soils of varying thickness. The second is a 3.3 ha catchment located in the Piedmont region, characterized as low relief with deep, highly weathered soils. Over a variety of flow conditions, surveys of the entire stream network were conducted at 10 m intervals to determine presence or absence of surface water. These surveys revealed several reaches within the networks that were intermittent, with perennial flow upstream and downstream. Furthermore, in some tributaries, the active stream head moved up the channel in response to precipitation and at others it remained anchored in place. Moreover, when repeat surveys were performed during the same storm, hysteresis was observed in active stream length variations: stream length was not the same on the rising limb and falling limb of the hydrograph. These observations suggest there are different geomorphological controls or runoff generation processes occurring spatially throughout these catchments. Observations of wide spatial and temporal variability of active stream length over a variety of flow conditions suggest runoff dynamics, generation mechanisms, and contributing flowpath depths producing streamflow may be highly variable and not easily predicted from streamflow observations at a fixed point. Finally, the observation of similar patterns in differing geomorphic regions suggests these processes extend beyond unique site characterizations.

Evaluation of multiple hydraulic models in generating design/near-real time flood inundation extents under various geophysical settings

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.

Streamstats: U.S. Geological Survey Web Application for Streamflow Statistics for Connecticut

USGS Publications Warehouse

Ahearn, Elizabeth A.; Ries, Kernell G.; Steeves, Peter A.

2006-01-01

Introduction An important mission of the U. S. Geological Survey (USGS) is to provide information on streamflow in the Nation's rivers. Streamflow statistics are used by water managers, engineers, scientists, and others to protect people and property during floods and droughts, and to manage land, water, and biological resources. Common uses for streamflow statistics include dam, bridge, and culvert design; water-supply planning and management; water-use appropriations and permitting; wastewater and industrial discharge permitting; hydropower-facility design and regulation; and flood-plain mapping for establishing flood-insurance rates and land-use zones. In an effort to improve access to published streamflow statistics, and to make the process of computing streamflow statistics for ungaged stream sites easier, more accurate, and more consistent, the USGS and the Environmental Systems Research Institute, Inc. (ESRI) developed StreamStats (Ries and others, 2004). StreamStats is a Geographic Information System (GIS)-based Web application for serving previously published streamflow statistics and basin characteristics for USGS data-collection stations, and computing streamflow statistics and basin characteristics for ungaged stream sites. The USGS, in cooperation with the Connecticut Department of Environmental Protection and the Connecticut Department of Transportation, has implemented StreamStats for Connecticut.

Decomposition of Sources of Errors in Seasonal Streamflow Forecasts in a Rainfall-Runoff Dominated Basin

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.

Sensitivity of Alpine Snow and Streamflow Regimes to Climate Changes

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Marks, D. G.; Bernhardt, M.

2014-12-01

Understanding the sensitivity of hydrological processes to climate change in alpine areas with snow dominated regimes is of paramount importance as alpine basins show both high runoff efficiency associated with the melt of the seasonal snowpack and great sensitivity of snow processes to temperature change. In this study, meteorological data measured in a selection of alpine headwaters basins including Reynolds Mountain East, Idaho, USA, Wolf Creek, Yukon in Canada, and Zugspitze Mountain, Germany with climates ranging from arctic to continental temperate were used to study the snow and streamflow sensitivity to climate change. All research sites have detailed multi-decadal meteorological and snow measurements. The Cold Regions Hydrological Modelling platform (CRHM) was used to create a model representing a typical alpine headwater basin discretized into hydrological response units with physically based representations of snow redistribution by wind, complex terrain snowmelt energetics and runoff processes in alpine tundra. The sensitivity of snow hydrology to climate change was investigated by changing air temperature and precipitation using weather generating methods based on the change factors obtained from different climate model projections for future and current periods. The basin mean and spatial variability of peak snow water equivalent, sublimation loss, duration of snow season, snowmelt rates, streamflow peak, and basin discharge were assessed under varying climate scenarios and the most sensitive hydrological mechanisms to the changes in the different alpine climates were detected. The results show that snow hydrology in colder alpine climates is more resilient to warming than that in warmer climates, but that compensatory factors to warming such as reduced blowing snow sublimation loss and reduced melt rate should also be assessed when considering climate change impacts on alpine hydrology.

The Water Availability Tool for Environmental Resources (WATER): A Water-Budget Modeling Approach for Managing Water-Supply Resources in Kentucky - Phase I: Data Processing, Model Development, and Application to Non-Karst Areas

USGS Publications Warehouse

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.

Evaluating CONUS-Scale Runoff Simulation across the National Water Model WRF-Hydro Implementation to Disentangle Regional Controls on Streamflow Generation and Model Error Contribution

NASA Astrophysics Data System (ADS)

Dugger, A. L.; Rafieeinasab, A.; Gochis, D.; Yu, W.; McCreight, J. L.; Karsten, L. R.; Pan, L.; Zhang, Y.; Sampson, K. M.; Cosgrove, B.

2016-12-01

Evaluation of physically-based hydrologic models applied across large regions can provide insight into dominant controls on runoff generation and how these controls vary based on climatic, biological, and geophysical setting. To make this leap, however, we need to combine knowledge of regional forcing skill, model parameter and physics assumptions, and hydrologic theory. If we can successfully do this, we also gain information on how well our current approximations of these dominant physical processes are represented in continental-scale models. In this study, we apply this diagnostic approach to a 5-year retrospective implementation of the WRF-Hydro community model configured for the U.S. National Weather Service's National Water Model (NWM). The NWM is a water prediction model in operations over the contiguous U.S. as of summer 2016, providing real-time estimates and forecasts out to 30 days of streamflow across 2.7 million stream reaches as well as distributed snowpack, soil moisture, and evapotranspiration at 1-km resolution. The WRF-Hydro system permits not only the standard simulation of vertical energy and water fluxes common in continental-scale models, but augments these processes with lateral redistribution of surface and subsurface water, simple groundwater dynamics, and channel routing. We evaluate 5 years of NLDAS-2 precipitation forcing and WRF-Hydro streamflow and evapotranspiration simulation across the contiguous U.S. at a range of spatial (gage, basin, ecoregion) and temporal (hourly, daily, monthly) scales and look for consistencies and inconsistencies in performance in terms of bias, timing, and extremes. Leveraging results from other CONUS-scale hydrologic evaluation studies, we translate our performance metrics into a matrix of likely dominant process controls and error sources (forcings, parameter estimates, and model physics). We test our hypotheses in a series of controlled model experiments on a subset of representative basins from distinct "problem" environments (Southeast U.S. Coastal Plain, Central and Coastal Texas, Northern Plains, and Arid Southwest). The results from these longer-term model diagnostics will inform future improvements in forcing bias correction, parameter calibration, and physics developments in the National Water Model.

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.

Effects of streamflows on stream-channel morphology in the eastern Niobrara National Scenic River, Nebraska, 1988–2010

USGS Publications Warehouse

Schaepe, Nathaniel J.; Alexander, Jason S.; Folz-Donahue, Kiernan

2016-03-09

Changes in channel metrics generally corresponded to changes in streamflow conditions, but other than changes in incipient flood-plain area, these changes were small and were not measured in all three segments simultaneously. Increases in total channel width (except in segment 1) and incipient flood-plain area between 1993 and 1999 corresponded to increases in streamflow. Channel narrowing (except in segment 1) between 1999 and 2003 corresponded to lower summer streamflows and extended durations of very low summer streamflow. Although the pattern of low summer streamflow and extended durations of very low summer streamflow continued during the 2004–6 period and at the beginning of the 2007–10 period, no further narrowing was measured. Consistent tributary summer inflows help to explain the resistance of segments 2 and 3 to further narrowing. Because segment 1 is already much narrower than segments 2 and 3, its average current velocity is likely to be swifter and, therefore, competent to offset further effects of the processes that led to its narrowness.

Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method in the Jing River of China

NASA Astrophysics Data System (ADS)

Li, Zhi; Jin, Jiming

2017-11-01

Projected hydrological variability is important for future resource and hazard management of water supplies because changes in hydrological variability can cause more disasters than changes in the mean state. However, climate change scenarios downscaled from Earth System Models (ESMs) at single sites cannot meet the requirements of distributed hydrologic models for simulating hydrological variability. This study developed multisite multivariate climate change scenarios via three steps: (i) spatial downscaling of ESMs using a transfer function method, (ii) temporal downscaling of ESMs using a single-site weather generator, and (iii) reconstruction of spatiotemporal correlations using a distribution-free shuffle procedure. Multisite precipitation and temperature change scenarios for 2011-2040 were generated from five ESMs under four representative concentration pathways to project changes in streamflow variability using the Soil and Water Assessment Tool (SWAT) for the Jing River, China. The correlation reconstruction method performed realistically for intersite and intervariable correlation reproduction and hydrological modeling. The SWAT model was found to be well calibrated with monthly streamflow with a model efficiency coefficient of 0.78. It was projected that the annual mean precipitation would not change, while the mean maximum and minimum temperatures would increase significantly by 1.6 ± 0.3 and 1.3 ± 0.2 °C; the variance ratios of 2011-2040 to 1961-2005 were 1.15 ± 0.13 for precipitation, 1.15 ± 0.14 for mean maximum temperature, and 1.04 ± 0.10 for mean minimum temperature. A warmer climate was predicted for the flood season, while the dry season was projected to become wetter and warmer; the findings indicated that the intra-annual and interannual variations in the future climate would be greater than in the current climate. The total annual streamflow was found to change insignificantly but its variance ratios of 2011-2040 to 1961-2005 increased by 1.25 ± 0.55. Streamflow variability was predicted to become greater over most months on the seasonal scale because of the increased monthly maximum streamflow and decreased monthly minimum streamflow. The increase in streamflow variability was attributed mainly to larger positive contributions from increased precipitation variances rather than negative contributions from increased mean temperatures.

Evaluation of Methods Used for Estimating Selected Streamflow Statistics, and Flood Frequency and Magnitude, for Small Basins in North Coastal California

USGS Publications Warehouse

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.

Monitoring Areal Snow Cover Using NASA Satellite Imagery

NASA Technical Reports Server (NTRS)

Harshburger, Brian J.; Blandford, Troy; Moore, Brandon

2011-01-01

The objective of this project is to develop products and tools to assist in the hydrologic modeling process, including tools to help prepare inputs for hydrologic models and improved methods for the visualization of streamflow forecasts. In addition, this project will facilitate the use of NASA satellite imagery (primarily snow cover imagery) by other federal and state agencies with operational streamflow forecasting responsibilities. A GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts is being developed. This toolkit will be packaged as multiple extensions for ArcGIS 9.x and an opensource GIS software package. The toolkit will provide users with a means for ingesting NASA EOS satellite imagery (snow cover analysis), preparing hydrologic model inputs, and visualizing streamflow forecasts. Primary products include a software tool for predicting the presence of snow under clouds in satellite images; a software tool for producing gridded temperature and precipitation forecasts; and a suite of tools for visualizing hydrologic model forecasting results. The toolkit will be an expert system designed for operational users that need to generate accurate streamflow forecasts in a timely manner. The Remote Sensing of Snow Cover Toolbar will ingest snow cover imagery from multiple sources, including the MODIS Operational Snowcover Data and convert them to gridded datasets that can be readily used. Statistical techniques will then be applied to the gridded snow cover data to predict the presence of snow under cloud cover. The toolbar has the ability to ingest both binary and fractional snow cover data. Binary mapping techniques use a set of thresholds to determine whether a pixel contains snow or no snow. Fractional mapping techniques provide information regarding the percentage of each pixel that is covered with snow. After the imagery has been ingested, physiographic data is attached to each cell in the snow cover image. This data can be obtained from a digital elevation model (DEM) for the area of interest.

How important is the spatiotemporal structure of a rainfall field when generating a streamflow hydrograph? An investigation using Reverse Hydrology

NASA Astrophysics Data System (ADS)

Kretzschmar, Ann; Tych, Wlodek; Beven, Keith; Chappell, Nick

2017-04-01

Flooding is the most widely occurring natural disaster affecting thousands of lives and businesses worldwide each year, and the size and frequency of flood-events are predicted to increase with climate change. The main input-variable for models used in flood prediction is rainfall. Estimating the rainfall input is often based on a sparse network of raingauges, which may or may not be representative of the salient rainfall characteristics responsible for generating of storm-hydrographs. A method based on Reverse Hydrology (Kretzschmar et al 2014 Environ Modell Softw) has been developed and is being tested using the intensively-instrumented Brue catchment (Southwest England) to explore the spatiotemporal structure of the rainfall-field (using 23 rain gauges over the 135.2 km2 basin). We compare how well the rainfall measured at individual gauges, or averaged over the basin, represent the rainfall inferred from the streamflow signal. How important is it to get the detail of the spatiotemporal rainfall structure right? Rainfall is transformed by catchment processes as it moves to streams, so exact duplication of the structure may not be necessary. 'True' rainfall estimated using 23 gauges / 135.2 km2 is likely to be a good estimate of the overall-catchment-rainfall, however, the integration process 'smears' the rainfall patterns in time, i.e. reduces the number of and lengthens rain-events as they travel across the catchment. This may have little impact on the simulation of stream-hydrographs when events are extensive across the catchment (e.g., frontal rainfall events) but may be significant for high-intensity, localised convective events. The Reverse Hydrology approach uses the streamflow record to infer a rainfall sequence with a lower time-resolution than the original input time-series. The inferred rainfall series is, however, able simulate streamflow as well as the observed, high resolution rainfall (Kretzschmar et al 2015 Hydrol Res). Most gauged catchments in the UK of a similar size would only have data available for 1 to 3 raingauges. The high density of the Brue raingauge network allows a good estimate of the 'True' catchment rainfall to be made and compared with data from an individual raingauge as if that was the only data available. In addition the rainfall from each raingauge is compared with rainfall inferred from streamflow using data from the selected individual raingauge, and also inferred from the full catchment network. The stochastic structure of the rainfall from all of these datasets is compared using a combination of traditional statistical measures, i.e., the first 4 moments of rainfall totals and its residuals; plus the number, length and distribution of wet and dry periods; rainfall intensity characteristics; and their ability to generate the observed stream hydrograph. Reverse Hydrology, which utilises information present in both the input rainfall and the output hydrograph, has provided a method of investigating the quality of the information each gauge adds to the catchment-average (Kretzschmar et al 2016 Procedia Eng.). Further, it has been used to ascertain how important reproducing the detailed rainfall structure really is, when used for flow prediction.

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.

Comparison of Two Conceptually Different Physically-based Hydrological Models - Looking Beyond Streamflows

NASA Astrophysics Data System (ADS)

Rousseau, A. N.; Álvarez; Yu, X.; Savary, S.; Duffy, C.

2015-12-01

Most physically-based hydrological models simulate to various extents the relevant watershed processes occurring at different spatiotemporal scales. These models use different physical domain representations (e.g., hydrological response units, discretized control volumes) and numerical solution techniques (e.g., finite difference method, finite element method) as well as a variety of approximations for representing the physical processes. Despite the fact that several models have been developed so far, very few inter-comparison studies have been conducted to check beyond streamflows whether different modeling approaches could simulate in a similar fashion the other processes at the watershed scale. In this study, PIHM (Qu and Duffy, 2007), a fully coupled, distributed model, and HYDROTEL (Fortin et al., 2001; Turcotte et al., 2003, 2007), a pseudo-coupled, semi-distributed model, were compared to check whether the models could corroborate observed streamflows while equally representing other processes as well such as evapotranspiration, snow accumulation/melt or infiltration, etc. For this study, the Young Womans Creek watershed, PA, was used to compare: streamflows (channel routing), actual evapotranspiration, snow water equivalent (snow accumulation and melt), infiltration, recharge, shallow water depth above the soil surface (surface flow), lateral flow into the river (surface and subsurface flow) and height of the saturated soil column (subsurface flow). Despite a lack of observed data for contrasting most of the simulated processes, it can be said that the two models can be used as simulation tools for streamflows, actual evapotranspiration, infiltration, lateral flows into the river, and height of the saturated soil column. However, each process presents particular differences as a result of the physical parameters and the modeling approaches used by each model. Potentially, these differences should be object of further analyses to definitively confirm or reject modeling hypotheses.

Computer Programs for Obtaining and Analyzing Daily Mean Steamflow Data from the U.S. Geological Survey National Water Information System Web Site

USGS Publications Warehouse

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

Tree-ring reconstruction of streamflow in the Snare River Basin, Northwest Territories, Canada

NASA Astrophysics Data System (ADS)

Martin, J. P.; Pisaric, M. F.

2017-12-01

Drought is a component of many ecosystems in North America causing environmental and socioeconomical impacts. In the ongoing context of climatic and environmental changes, drought-related issues are becoming problematic in northern Canada, which have not been associated with drought-like conditions in the past. Dryer than average conditions threatens the energy security of northern canadian communities, since this region relies on the production of hydroelectricity as an energy source. In the North Slave Region of Northwest Territory (NWT), water levels and streamflows were significantly lower in 2014/2015. The Government of the NWT had to spend nearly $50 million to purchase diesel fuel to generate enough electricity to supplement the reduced power generation of the Snare River hydroelectric system, hence the need to better understand the multi-decadal variability in streamflow. The aims of this presentation are i) to present jack pine and white spruce tree-ring chronologies of Southern NWT; ii) to reconstruct past streamflow of the Snare River Basin; iii) to evaluate the frequency and magnitude of extreme drought conditions, and iv) to identify which large-scale atmospheric or oceanic patterns are teleconnected to regional hydraulic conditions. Preliminary results show that the growth of jack pine and white spruce populations is better correlated with precipitation and temperature, respectively, than hydraulic conditions. Nonetheless, we present a robust streamflow reconstruction of the Snare River that is well correlated with the summer North Atlantic Oscillation (NAO) index, albeit the strength of the correlation is non-stationary. Spectral analysis corroborate the synchronicity between negative NAO conditions and drought conditions. From an operational standpoint, considering that the general occurrence of positive/negative NAO can be predicted, it the hope of the authors that these results can facilitate energetic planning in the Northwest Territories through the assessment of the prevailing streamflow scenario.

A framework for improving a seasonal hydrological forecasting system using sensitivity analysis

NASA Astrophysics Data System (ADS)

Arnal, Louise; Pappenberger, Florian; Smith, Paul; Cloke, Hannah

2017-04-01

Seasonal streamflow forecasts are of great value for the socio-economic sector, for applications such as navigation, flood and drought mitigation and reservoir management for hydropower generation and water allocation to agriculture and drinking water. However, as we speak, the performance of dynamical seasonal hydrological forecasting systems (systems based on running seasonal meteorological forecasts through a hydrological model to produce seasonal hydrological forecasts) is still limited in space and time. In this context, the ESP (Ensemble Streamflow Prediction) remains an attractive forecasting method for seasonal streamflow forecasting as it relies on forcing a hydrological model (starting from the latest observed or simulated initial hydrological conditions) with historical meteorological observations. This makes it cheaper to run than a standard dynamical seasonal hydrological forecasting system, for which the seasonal meteorological forecasts will first have to be produced, while still producing skilful forecasts. There is thus the need to focus resources and time towards improvements in dynamical seasonal hydrological forecasting systems which will eventually lead to significant improvements in the skill of the streamflow forecasts generated. Sensitivity analyses are a powerful tool that can be used to disentangle the relative contributions of the two main sources of errors in seasonal streamflow forecasts, namely the initial hydrological conditions (IHC; e.g., soil moisture, snow cover, initial streamflow, among others) and the meteorological forcing (MF; i.e., seasonal meteorological forecasts of precipitation and temperature, input to the hydrological model). Sensitivity analyses are however most useful if they inform and change current operational practices. To this end, we propose a method to improve the design of a seasonal hydrological forecasting system. This method is based on sensitivity analyses, informing the forecasters as to which element of the forecasting chain (i.e., IHC or MF) could potentially lead to the highest increase in seasonal hydrological forecasting performance, after each forecast update.

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.

Runoff and solute mobilization processes in a semiarid headwater catchment

NASA Astrophysics Data System (ADS)

Hughes, Justin D.; Khan, Shahbaz; Crosbie, Russell S.; Helliwell, Stuart; Michalk, David L.

2007-09-01

Runoff and solute transport processes contributing to streamflow were determined in a small headwater catchment in the eastern Murray-Darling Basin of Australia using hydrometric and tracer methods. Streamflow and electrical conductivity were monitored from two gauges draining a portion of the upper catchment area (UCA) and a saline scalded area, respectively. Runoff in the UCA was related to the formation of a seasonally perched aquifer in the near-surface zone (0-0.4 m). A similar process was responsible for runoff generation in the saline scalded area. However, saturation in the scald area was related to the proximity of groundwater rather than low subsurface hydraulic conductivity. Because of higher antecedent water content, runoff commenced earlier in winter from the scald than did the UCA. Additionally, areal runoff from the scald was far greater than from the UCA. Total runoff from the UCA was higher than the scald (15.7 versus 3.5 mL), but salt export was far lower (0.6 and 5.4 t for the UCA and scald area, respectively) since salinity of the scald runoff was far higher than that from the UCA, indicating the potential impact of saline scalded areas at the catchment scale. End-member mixing analysis modeling using six solutes indicated that most runoff produced from the scald was "new" (40-71%) despite the proximity of the groundwater surface and the high antecedent moisture levels. This is a reflection of the very low hydraulic conductivity of soils in the study area. Nearly all chloride exported to the stream from the scald emanated from the near-surface zone (77-87%). Runoff and solute mobilization processes depend upon seasonal saturation occurring in the near-surface zone during periods of low evaporative demand and generation of saturated overland flow.

Changes in seasonality and timing of peak streamflow in snow and semi-arid climates of the north-central United States, 1910–2012

USGS Publications Warehouse

Ryberg, Karen R.; Akyüz, F. Adnan; Wiche, Gregg J.; Lin, Wei

2015-01-01

Changes in the seasonality and timing of annual peak streamflow in the north-central USA are likely because of changes in precipitation and temperature regimes. A source of long-term information about flood events across the study area is the U.S. Geological Survey peak streamflow database. However, one challenge of answering climate-related questions with this dataset is that even in snowmelt-dominated areas, it is a mixed population of snowmelt/spring rain generated peaks and summer/fall rain generated peaks. Therefore, a process was developed to divide the annual peaks into two populations, or seasons, snowmelt/spring, and summer/fall. The two series were then tested for the hypotheses that because of changes in precipitation regimes, the odds of summer/fall peaks have increased and, because of temperature changes, snowmelt/spring peaks happen earlier. Over climatologically and geographically similar regions in the north-central USA, logistic regression was used to model the odds of getting a summer/fall peak. When controlling for antecedent wet and dry conditions and geographical differences, the odds of summer/fall peaks occurring have increased across the study area. With respect to timing within the seasons, trend analysis showed that in northern portions of the study region, snowmelt/spring peaks are occurring earlier. The timing of snowmelt/spring peaks in three regions in the northern part of the study area is earlier by 8.7– 14.3 days. These changes have implications for water interests, such as potential changes in lead-time for flood forecasting or changes in the operation of flood-control dams.

Validated Metrics of Quick Flow Improve Assessments of Streamflow Generation Processes at the Long-Term Sleepers River Research Site

NASA Astrophysics Data System (ADS)

Sebestyen, S. D.; Shanley, J. B.

2015-12-01

There are multiple approaches to quantify quick flow components of streamflow. Physical hydrograph separations of quick flow using recession analysis (RA) are objective, reproducible, and easily calculated for long-duration streamflow records (years to decades). However, this approach has rarely been validated to have a physical basis for interpretation. In contrast, isotopic hydrograph separation (IHS) and end member mixing analysis using multiple solutes (EMMA) have been used to identify flow components and flowpath routing through catchment soils. Nonetheless, these two approaches are limited by data from limited and isolated periods (hours to weeks) during which more-intensive grab samples were analyzed. These limitations oftentimes make IHS and EMMA difficult to generalize beyond brief windows of time. At the Sleepers River Research Watershed (SRRW) in northern Vermont, USA, we have data from multiple snowmelt events over a two decade period and from multiple nested catchments to assess relationships among RA, IHS, and EMMA. Quick flow separations were highly correlated among the three techniques, which shows links among metrics of quick flow, water sources, and flow path routing in a small (41 ha), forested catchment (W-9) The similarity in responses validates a physical interpretation for a particular RA approach (the Ekhardt recursive RA filter). This validation provides a new tool to estimate new water inputs and flowpath routing for more and longer periods when chemical or isotopic tracers may not have been measured. At three other SRRW catchments, we found similar strong correlations among the three techniques. Consistent responses across four catchments provide evidence to support other research at the SRRW that shows that runoff generation mechanisms are similar despite differences in catchment sizes and land covers.

Integrated surface-subsurface model to investigate the role of groundwater in headwater catchment runoff generation: A minimalist approach to parameterisation

NASA Astrophysics Data System (ADS)

Ala-aho, Pertti; Soulsby, Chris; Wang, Hailong; Tetzlaff, Doerthe

2017-04-01

Understanding the role of groundwater for runoff generation in headwater catchments is a challenge in hydrology, particularly so in data-scarce areas. Fully-integrated surface-subsurface modelling has shown potential in increasing process understanding for runoff generation, but high data requirements and difficulties in model calibration are typically assumed to preclude their use in catchment-scale studies. We used a fully integrated surface-subsurface hydrological simulator to enhance groundwater-related process understanding in a headwater catchment with a rich background in empirical data. To set up the model we used minimal data that could be reasonably expected to exist for any experimental catchment. A novel aspect of our approach was in using simplified model parameterisation and including parameters from all model domains (surface, subsurface, evapotranspiration) in automated model calibration. Calibration aimed not only to improve model fit, but also to test the information content of the observations (streamflow, remotely sensed evapotranspiration, median groundwater level) used in calibration objective functions. We identified sensitive parameters in all model domains (subsurface, surface, evapotranspiration), demonstrating that model calibration should be inclusive of parameters from these different model domains. Incorporating groundwater data in calibration objectives improved the model fit for groundwater levels, but simulations did not reproduce well the remotely sensed evapotranspiration time series even after calibration. Spatially explicit model output improved our understanding of how groundwater functions in maintaining streamflow generation primarily via saturation excess overland flow. Steady groundwater inputs created saturated conditions in the valley bottom riparian peatlands, leading to overland flow even during dry periods. Groundwater on the hillslopes was more dynamic in its response to rainfall, acting to expand the saturated area extent and thereby promoting saturation excess overland flow during rainstorms. Our work shows the potential of using integrated surface-subsurface modelling alongside with rigorous model calibration to better understand and visualise the role of groundwater in runoff generation even with limited datasets.

Potential effects of tree-to-shrub type conversion on streamflow in California's Sierra Nevada

NASA Astrophysics Data System (ADS)

Baguskas, S. A.; Bart, R.; Molinari, N.; Tague, C.; Moritz, M.

2014-12-01

There is widespread concern that changes in climate and fire regime may lead to vegetation change across California, which in turn may influence watershed hydrology. Although plant cover is known to affect numerous hydrological processes, sensitivities to vegetation type and spatial arrangement of species within watersheds are not well understood. The primary objective of our research was to generate mechanistically-based projections of how potential type conversion from forested to shrub dominated systems may affect streamflow. During the 2014 growing season, we measured ecophysiological responses (plant water status and leaf gas exchange rates) of two dominant tree and shrub species to changes in seasonal water availability at two sites within the southern Sierra Nevada Critical Zone Observatory. Plant physiological observations were used to parameterize a process-based eco-hydrological model, RHESSys. This model was used to evaluate the impact of changes in seasonal water availability and vegetation type-conversion on streamflow. Based on our field observations, shrubs and trees had similar access to water through the early part of the growing season (April-early June); however, by late July, available water to shrubs was twice that of trees (shrubs, -0.55 ± 0.08 MPa; trees, -1.07 ± 0.08 MPa, p<0.05). Likewise, maximum transpiration (E) and carbon assimilation (A) rates per unit leaf area were twice as high for shrubs then trees in July (shrubs, A= 21 ± 2.3 μmol m-2 s-1, E=6.6 ± 1.8 mmol m-2 s-1; trees, A=8.2 ± 1.9 μmol m-2 s-1, E=2.4 ± 0.3 mmol m-2 s-1). Preliminary modeled changes in streamflow following simulated vegetation conversion were found to affect both the timing and amount of discharge. Controls on pre vs. post-conversion streamflow included changes in interception, rooting depth, energy balance, and plant response to changes in seasonal water availability. Our research demonstrates how linking strategic field data collection and mechanistic ecohydrologic models can be used as a robust tool for assessing the potential impact of vegetation change on the water balance of an ecosystem. This is an increasingly valuable approach to inform management decisions focused on adapting strategies based on projected changes in climate.

Recent tree die-off has little effect on streamflow in contrast to expected increases from historical studies

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.

Streamflow depletion by wells--Understanding and managing the effects of groundwater pumping on streamflow

USGS Publications Warehouse

Barlow, Paul M.; Leake, Stanley A.

2012-11-02

Groundwater is an important source of water for many human needs, including public supply, agriculture, and industry. With the development of any natural resource, however, adverse consequences may be associated with its use. One of the primary concerns related to the development of groundwater resources is the effect of groundwater pumping on streamflow. Groundwater and surface-water systems are connected, and groundwater discharge is often a substantial component of the total flow of a stream. Groundwater pumping reduces the amount of groundwater that flows to streams and, in some cases, can draw streamflow into the underlying groundwater system. Streamflow reductions (or depletions) caused by pumping have become an important water-resource management issue because of the negative impacts that reduced flows can have on aquatic ecosystems, the availability of surface water, and the quality and aesthetic value of streams and rivers. Scientific research over the past seven decades has made important contributions to the basic understanding of the processes and factors that affect streamflow depletion by wells. Moreover, advances in methods for simulating groundwater systems with computer models provide powerful tools for estimating the rates, locations, and timing of streamflow depletion in response to groundwater pumping and for evaluating alternative approaches for managing streamflow depletion. The primary objective of this report is to summarize these scientific insights and to describe the various field methods and modeling approaches that can be used to understand and manage streamflow depletion. A secondary objective is to highlight several misconceptions concerning streamflow depletion and to explain why these misconceptions are incorrect.

Ecosystem processes and human influences regulate streamflow response to climate change at long-term ecological research sites

Treesearch

Julia A. Jones; Irena F. Creed; Kendra L. Hatcher; Robert J. Warren; Mary Beth Adams; Melinda H. Benson; Emery Boose; Warren A. Brown; John L. Campbell; Alan Covich; David W. Clow; Clifford N. Dahm; Kelly Elder; Chelcy R. Ford; Nancy B. Grimm; Donald L Henshaw; Kelli L. Larson; Evan S. Miles; Kathleen M. Miles; Stephen D. Sebestyen; Adam T. Spargo; Asa B. Stone; James M. Vose; Mark W. Williams

2012-01-01

Analyses of long-term records at 35 headwater basins in the United States and Canada indicate that climate change effects on streamflow are not as clear as might be expected, perhaps because of ecosystem processes and human influences. Evapotranspiration was higher than was predicted by temperature in water-surplus ecosystems and lower than was predicted in water-...

SAM 2.1—A computer program for plotting and formatting surveying data for estimating peak discharges by the slope-area method

USGS Publications Warehouse

Hortness, J.E.

2004-01-01

The U.S. Geological Survey (USGS) measures discharge in streams using several methods. However, measurement of peak discharges is often impossible or impractical due to difficult access, inherent danger of making measurements during flood events, and timing often associated with flood events. Thus, many peak discharge values often are calculated after the fact by use of indirect methods. The most common indirect method for estimating peak dis- charges in streams is the slope-area method. This, like other indirect methods, requires measuring the flood profile through detailed surveys. Processing the survey data for efficient entry into computer streamflow models can be time demanding; SAM 2.1 is a program designed to expedite that process. The SAM 2.1 computer program is designed to be run in the field on a portable computer. The program processes digital surveying data obtained from an electronic surveying instrument during slope- area measurements. After all measurements have been completed, the program generates files to be input into the SAC (Slope-Area Computation program; Fulford, 1994) or HEC-RAS (Hydrologic Engineering Center-River Analysis System; Brunner, 2001) computer streamflow models so that an estimate of the peak discharge can be calculated.

Presenting the master of all conductivity meters, and how it tastes streamflow

NASA Astrophysics Data System (ADS)

Weijs, S. V.; Parlange, M. B.

2012-04-01

For measuring streamflow in small Alpine streams, the salt dilution method is suitable and often used. By injecting a known mass of salt in the stream and measuring the downstream salt concentration as a function of time, we can obtain the streamflow by integration of the time signal. The underlying assumption is that the salt is well mixed within the stream cross-section. In this method, the salt concentration us usually measured through its relation with conductivity. Several commercial systems exist to do these conductivity measurements and automatically process the results. The problem we encountered when using these systems, however, is that uncertainty is often hidden under the hood. Because the processing happens onboard, researchers may be tempted to put too much trust in the final measurement outcomes. This is somewhat remediated by using a system with two probes which are individually processed to a streamflow outcome. We found that the salt-wave was differently shaped for the faster part of the stream compared to the sides, and therefore gave different readings for the discharge. To come a more probabilistic characterization of streamflow, and to know what is under the hood, we decided to build our own conductivity meter, equipped with eight probes covering the cross section. This enables quantifying some of the uncertainty in the streamflow measurements, which is important for testing hydrological models. This poster shows the first results and the hardware setup. We based our hardware on the open source hardware platform Arduino, and believe that by sharing both the design and the drawbacks, we contribute to the evolution of better measurement equipment or at least better understanding of its shortcomings.

Application of two hydrologic models with different runoff mechanisms to a hillslope dominated watershed in the northeastern US: A comparison of HSPF and SMR

USGS Publications Warehouse

Johnson, M.S.; Coon, W.F.; Mehta, V.K.; Steenhuis, T.S.; Brooks, E.S.; Boll, J.

2003-01-01

Differences in the simulation of hydrologic processes by watershed models directly affect the accuracy of results. Surface runoff generation can be simulated as either: (1) infiltration-excess (or Hortonian) overland flow, or (2) saturation-excess overland flow. This study compared the Hydrological Simulation Program - FORTRAN (HSPF) and the Soil Moisture Routing (SMR) models, each representing one of these mechanisms. These two models were applied to a 102 km2 watershed in the upper part of the Irondequoit Creek basin in central New York State over a seven-year simulation period. The models differed in both the complexity of simulating snowmelt and baseflow processes as well as the detail in which the geographic information was preserved by each model. Despite their differences in structure and representation of hydrologic processes, the two models simulated streamflow with almost equal accuracy. Since streamflow is an integral response and depends mainly on the watershed water balance, this was not unexpected. Model efficiency values for the seven-year simulation period were 0.67 and 0.65 for SMR and HSPF, respectively. HSPF simulated winter streamflow slightly better than SMR as a result of its complex snowmelt routine, whereas SMR simulated summer flows better than HSPF as a result of its runoff and baseflow processes. An important difference between model results was the ability to predict the spatial distribution of soil moisture content. HSPF aggregates soil moisture content, which is generally related to a specific pervious land unit across the entire watershed, whereas SMR predictions of moisture content distribution are geographically specific and matched field observations reasonably well. Important is that the saturated area was predicted well by SMR and confirmed the validity of using saturation-excess mechanisms for this hillslope dominated watershed. ?? 2003 Elsevier B.V. All rights reserved.

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.

Geological controls on isotopic signatures of streamflow: results from a nested catchment experiment in Luxembourg (Europe)

NASA Astrophysics Data System (ADS)

Pfister, Laurent; McDonnell, Jeffrey J.; Hissler, Christophe; Martinez-Carreras, Nuria; Gourdol, Laurent; Klaus, Julian; François Iffly, Jean; Barnich, François; Stewart, Mike K.

2014-05-01

Controls of geology and topography on hydrological metrics, like summer low flow (Grant and Tague, 2004) or dynamic storage (Sayama et al., 2011), have been identified in nested catchment experiments. However, most tracer-based studies on streamflow generation have been carried out in small (10 km2) homogenous catchments (Klaus and McDonnell, 2013). The controlling effects of catchment physiography on how catchments store and release water, and how this eventually controls stream isotope behaviour over a large range of scale are poorly understood. Here, we present results from a nested catchment analysis in the Alzette River basin (Luxembourg, Europe). Our hydro-climatological network consists of 16 recording streamgauges and 21 pluviographs. Catchment areas range from 0.47 to 285 km2, with clean and mixed combinations of distinct geologies ranging from schists to marls, sandstone, dolomite and limestone. Our objective was to identify geological controls on (i) winter runoff ratios, (ii) maximum storage and (iii) isotopic signatures in streamflow. For each catchment we determined average runoff ratios from winter season precipitation-discharge double-mass curves. Maximum catchment storage was based on the dynamic storage change approach of Sayama et al. (2011). Changes in isotopic signatures of streamflow were documented along individual catchment flow duration curves. We found strong correlations between average winter runoff ratios, maximum storage and the prevailing geological settings. Catchments with impermeable bedrock (e.g. marls or schists) were characterised by small storage potential and high average filling ratios. As a consequence, these catchments also exhibited the highest average runoff ratios. In catchments underlain by permeable bedrock (e.g. sandstone), storage potential was significantly higher and runoff ratios were considerably smaller. The isotopic signatures of streamflow showed large differences between catchments. In catchments dominated by permeable bedrock, isotopic signatures of streamflow remained stable throughout the entire flow duration curve consistent with a large storage and mixing potential. On less permeable bedrock substrate, we have observed that isotopic signatures in streamflow were much more variable, due to reduced storage volume and comparatively smaller mixing potential. Other metrics such as catchment size and flowpath length exerted a smaller secondary control on isotopic signatures of streamflow in the Alzette River sub-basins. Tague, C., Grant, G.E., 2004. A geological framework for interpreting the low-flow regimes of Cascade streams, Willamette River Basin, Oregon. Water Resources Research, 40(4), doi:10.1029/2003WR002629 Sayama, T., McDonnell, J.J., Dhakal, A., Sullivan, K., 2011. How much water can a watershed store ? Hydrological Processes 25, 3899-3908. Klaus, J., McDonnell, J.J., 2013. Hydrograph separation using stable isotopes: Review and evaluation. Journal of Hydrology 505, 47-64.

Effects of including surface depressions in the application of the Precipitation-Runoff Modeling System in the Upper Flint River Basin, Georgia

USGS Publications Warehouse

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.

Prediction of Hydrological Drought: What Can We Learn From Continental-Scale Offline Simulations?

NASA Technical Reports Server (NTRS)

Koster, Randal; Mahanama, Sarith; Livneh, Ben; Lettenmaier, Dennis; Reichle, Rolf

2011-01-01

Land surface model experiments are used to quantify, across the coterminous United States, the contributions (isolated and combined) of soil moisture and snowpack initialization to the skill of seasonal streamflow forecasts at multiple leads and for different start dates. Forecasted streamflows are compared to naturalized streamflow observations where available and to synthetic (model-generated) streamflow data elsewhere. We find that snow initialization has a major impact on skill in the mountainous western U.S. and in a portion of the northern Great Plains; a mid-winter (January 1) initialization of snow in these areas leads to significant skill in the spring melting season. Soil moisture initialization also contributes to skill, and although the maximum contributions are not as large as those seen for snow initialization, the soil moisture contributions extend across a much broader geographical area. Soil moisture initialization can contribute to skill at long leads (up to 5 or 6 months), particularly for forecasts issued during winter.

Evaluating Snow Data Assimilation Framework for Streamflow Forecasting Applications Using Hindcast Verification

NASA Astrophysics Data System (ADS)

Barik, M. G.; Hogue, T. S.; Franz, K. J.; He, M.

2012-12-01

Snow water equivalent (SWE) estimation is a key factor in producing reliable streamflow simulations and forecasts in snow dominated areas. However, measuring or predicting SWE has significant uncertainty. Sequential data assimilation, which updates states using both observed and modeled data based on error estimation, has been shown to reduce streamflow simulation errors but has had limited testing for forecasting applications. In the current study, a snow data assimilation framework integrated with the National Weather System River Forecasting System (NWSRFS) is evaluated for use in ensemble streamflow prediction (ESP). Seasonal water supply ESP hindcasts are generated for the North Fork of the American River Basin (NFARB) in northern California. Parameter sets from the California Nevada River Forecast Center (CNRFC), the Differential Evolution Adaptive Metropolis (DREAM) algorithm and the Multistep Automated Calibration Scheme (MACS) are tested both with and without sequential data assimilation. The traditional ESP method considers uncertainty in future climate conditions using historical temperature and precipitation time series to generate future streamflow scenarios conditioned on the current basin state. We include data uncertainty analysis in the forecasting framework through the DREAM-based parameter set which is part of a recently developed Integrated Uncertainty and Ensemble-based data Assimilation framework (ICEA). Extensive verification of all tested approaches is undertaken using traditional forecast verification measures, including root mean square error (RMSE), Nash-Sutcliffe efficiency coefficient (NSE), volumetric bias, joint distribution, rank probability score (RPS), and discrimination and reliability plots. In comparison to the RFC parameters, the DREAM and MACS sets show significant improvement in volumetric bias in flow. Use of assimilation improves hindcasts of higher flows but does not significantly improve performance in the mid flow and low flow categories.

Dendrohydrology and water resources management in south-central Chile: lessons from the Río Imperial streamflow reconstruction

NASA Astrophysics Data System (ADS)

Fernández, Alfonso; Muñoz, Ariel; González-Reyes, Álvaro; Aguilera-Betti, Isabella; Toledo, Isadora; Puchi, Paulina; Sauchyn, David; Crespo, Sebastián; Frene, Cristian; Mundo, Ignacio; González, Mauro; Vignola, Raffaele

2018-05-01

Streamflow in south-central Chile (SCC, ˜ 37-42° S) is vital for agriculture, forestry production, hydroelectricity, and human consumption. Recent drought episodes have generated hydrological deficits with damaging effects on these activities. This region is projected to undergo major reductions in water availability, concomitant with projected increases in water demand. However, the lack of long-term records hampers the development of accurate estimations of natural variability and trends. In order to provide more information on long-term streamflow variability and trends in SCC, here we report findings of an analysis of instrumental records and a tree-ring reconstruction of the summer streamflow of the Río Imperial ( ˜ 37° 40' S-38° 50' S). This is the first reconstruction in Chile targeted at this season. Results from the instrumental streamflow record ( ˜ 1940 onwards) indicated that the hydrological regime is fundamentally pluvial with a small snowmelt contribution during spring, and evidenced a decreasing trend, both for the summer and the full annual record. The reconstruction showed that streamflow below the average characterized the post-1980 period, with more frequent, but not more intense, drought episodes. We additionally found that the recent positive phase of the Southern Annular Mode has significantly influenced streamflow. These findings agree with previous studies, suggesting a robust regional signal and a shift to a new hydrological scenario. In this paper, we also discuss implications of these results for water managers and stakeholders; we provide rationale and examples that support the need for the incorporation of tree-ring reconstructions into water resources management.

LOCAL VS. REGIONAL EFFECTS ON FISH DIVERSITY AS MEDIATED BY STREAMFLOW DISTURBANCE REGIME

EPA Science Inventory

abstract

The interplay of local and regional processes on fish diversity is poorly understood, especially related to patterns of streamflow disturbance regime. Articulation of the relationship between flow disturbance patterns and river fishes across local to regional scal...

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.

Analysis of Future Streamflow Regimes under Global Change Scenarios in Central Chile for Ecosystem Sustainability

NASA Astrophysics Data System (ADS)

Henriquez Dole, L. E.; Gironas, J. A.; Vicuna, S.

2015-12-01

Given the critical role of the streamflow regime for ecosystem sustainability, modeling long term effects of climate change and land use change on streamflow is important to predict possible impacts in stream ecosystems. Because flow duration curves are largely used to characterize the streamflow regime and define indices of ecosystem health, they were used to represent and analyze in this study the stream regime in the Maipo River Basin in Central Chile. Water and Environmental Assessment and Planning (WEAP) model and the Plant Growth Model (PGM) were used to simulate water distribution, consumption in rural areas and stream flows on a weekly basis. Historical data (1990-2014), future land use scenarios (2030/2050) and climate change scenarios were included in the process. Historical data show a declining trend in flows mainly by unprecedented climatic conditions, increasing interest among users on future streamflow scenarios. In the future, under an expected decline in water availability coupled with changes in crop water demand, water users will be forced to adapt by changing water allocation rules. Such adaptation actions would in turns affect the streamflow regime. Future scenarios for streamflow regime show dramatic changes in water availability and temporal distribution. Annual weekly mean flows can reduce in 19% in the worst scenario and increase in 3.3% in the best of them, and variability in streamflow increases nearly 90% in all scenarios under evaluation. The occurrence of maximum and minimum monthly flows changes, as June instead of July becomes the driest month, and December instead of January becomes the month with maximum flows. Overall, results show that under future scenarios streamflow is affected and altered by water allocation rules to satisfy water demands, and thus decisions will need to consider the streamflow regime (and habitat) in order to be sustainable.

Impacts of the active layer on runoff in an upland permafrost basin, northern Tibetan Plateau

PubMed Central

Zhang, Tingjun; Guo, Hong; Hu, Yuantao; Shang, Jianguo; Zhang, Yulan

2018-01-01

The paucity of studies on permafrost runoff generation processes, especially in mountain permafrost, constrains the understanding of permafrost hydrology and prediction of hydrological responses to permafrost degradation. This study investigated runoff generation processes, in addition to the contribution of summer thaw depth, soil temperature, soil moisture, and precipitation to streamflow in a small upland permafrost basin in the northern Tibetan Plateau. Results indicated that the thawing period and the duration of the zero-curtain were longer in permafrost of the northern Tibetan Plateau than in the Arctic. Limited snowmelt delayed the initiation of surface runoff in the peat permafrost in the study area. The runoff displayed intermittent generation, with the duration of most runoff events lasting less than 24 h. Precipitation without runoff generation was generally correlated with lower soil moisture conditions. Combined analysis suggested runoff generation in this region was controlled by soil temperature, thaw depth, precipitation frequency and amount, and antecedent soil moisture. This study serves as an important baseline to evaluate future environmental changes on the Tibetan Plateau. PMID:29470510

Impacts of the active layer on runoff in an upland permafrost basin, northern Tibetan Plateau.

PubMed

Gao, Tanguang; Zhang, Tingjun; Guo, Hong; Hu, Yuantao; Shang, Jianguo; Zhang, Yulan

2018-01-01

The paucity of studies on permafrost runoff generation processes, especially in mountain permafrost, constrains the understanding of permafrost hydrology and prediction of hydrological responses to permafrost degradation. This study investigated runoff generation processes, in addition to the contribution of summer thaw depth, soil temperature, soil moisture, and precipitation to streamflow in a small upland permafrost basin in the northern Tibetan Plateau. Results indicated that the thawing period and the duration of the zero-curtain were longer in permafrost of the northern Tibetan Plateau than in the Arctic. Limited snowmelt delayed the initiation of surface runoff in the peat permafrost in the study area. The runoff displayed intermittent generation, with the duration of most runoff events lasting less than 24 h. Precipitation without runoff generation was generally correlated with lower soil moisture conditions. Combined analysis suggested runoff generation in this region was controlled by soil temperature, thaw depth, precipitation frequency and amount, and antecedent soil moisture. This study serves as an important baseline to evaluate future environmental changes on the Tibetan Plateau.

Chapter 3. Hydrology

Treesearch

Robert R. Ziemer; Thomas E. Lisle

1998-01-01

Streamflow is an essential variable in understanding the functioning of watersheds and associated ecosystems because it supplies the primary medium and source of energy for the movement of water, sediment, organic material, nutrients, and thermal energy. Changes in streamflow are almost invariably linked to changes in other watershed processes such as erosion,...

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.

Linking river management to species conservation using dynamic landscape scale models

USGS Publications Warehouse

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.

Ensemble hydro-meteorological forecasting for early warning of floods and scheduling of hydropower production

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.

Representation of spatial cross correlations in large stochastic seasonal streamflow models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oliveira, G.C.; Kelman, J.; Pereira, M.V.F.

1988-05-01

Pereira et al. (1984) presented a special disaggregation procedure for generating cross-correlated monthly flows at many sites while using what are essentially univariate disaggregation models for the flows at each site. This was done by using a nonparametric procedure for constructing residual innovations or noise vectors with cross-correlated components. This note considers the theoretical underpinnings of that streamflow disaggregation procedure and a proposed variation and their ability to reproduce the observed historical cross correlations among concurrent monthly flows at nine Brazilian stations.

A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

NASA Astrophysics Data System (ADS)

Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

2017-04-01

The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of land-use/land-cover changes and river regulation on network-scale connectivity.

Insights into streamflow generation mechanisms using high-frequency analysis of isotopes and water quality in streamflow and precipitation

NASA Astrophysics Data System (ADS)

von Freyberg, Jana; Kirchner, James W.

2017-04-01

In the pre-Alpine Alptal catchment in central Switzerland, snowmelt and rainfall events cause rapid changes not only in hydrological conditions, but also in water quality. A flood forecasting model for such a mountainous catchment thus requires process understanding that is informed by high-frequency monitoring of hydrological and hydrochemical parameters. Therefore, we installed a high-frequency sampling and analysis system near the outlet of the 0.7 km2 Erlenbach catchment, a headwater tributary of the Alp river. We measured stable water isotopes (δ18O, δ2H) in precipitation and streamwater using Picarro, Inc.'s (Santa Clara, CA, USA) newly developed Continuous Water Sampler Module (CWS) coupled to their L2130-i Cavity Ring-Down Spectrometer, at 30 min temporal resolution. Water quality was monitored with a dual-channel ion chomatograph (Metrohm AG, Herisau, Switzerland) for analysis of major cations and anions, as well as with a UV-Vis spectroscopy system and electrochemical probes (s::can Messtechnik GmbH, Vienna, Austria) for characterization of nutrients and basic water quality parameters. For quantification of trace elements and metals, we collected additional water samples for subsequent ICP-MS analysis in the laboratory. To illustrate the applicability of our newly developed automated analysis and sampling system under field conditions, we will present initial results from the 2016 fall and winter seasons at the Erlenbach catchment. During this period, river discharge was mainly fed by groundwater, as well as intermittent snowmelt and rain-on-snow events. Our high-frequency data set, along with spatially distributed sampling of snowmelt, enables a detailed analysis of source areas, flow pathways and biogeochemical processes that control chemical dynamics in streamflow and the discharge regime.

Spatial and temporal variability of runoff and streamflow generation within and among headwater catchments: a combined hydrometric and stable isotope approach

NASA Astrophysics Data System (ADS)

Singh, N. K.; Emanuel, R. E.; McGlynn, B. L.

2012-12-01

The combined influence of topography and vegetation on runoff generation and streamflow in headwater catchments remains unclear. We aim to understand how spatial, hydrological and climate variables affect runoff generation and streamflow at hillslope and watershed scales at the Coweeta Hydrologic Laboratory (CHL) in the southern Appalachian Mountains by analyzing stable isotopes of hydrogen (2H) and oxygen (18O) coupled with measurements of hydrological variables (stream discharge, soil moisture, shallow groundwater) and landscape variables (upslope accumulated area, vegetation density slope, and aspect). We investigated four small catchments, two of which contained broadleaf deciduous vegetation and two of which contained evergreen coniferous vegetation. Beginning in June 2011, we collected monthly water samples at 25 m intervals along each stream, monthly samples from 24 shallow groundwater wells, and weekly to monthly samples from 10 rain gauges distributed across CHL. Water samples were analyzed for 2H and 18O using cavity ring-down spectroscopy. During the same time period we recorded shallow groundwater stage at 30 min intervals from each well, and beginning in fall 2011 we collected volumetric soil moisture data at 30 min intervals from multiple depths at 16 landscape positions. Results show high spatial and temporal variability in δ2H and δ18O within and among streams, but in general we found isotopic enrichment with increasing contributing area along each stream. We used a combination of hydrometric observations and geospatial analyses to understand why stream isotope patterns varied during the year and among watersheds, and we used complementary measurements of δ2H and δ18O from other pools within the watersheds to understand the movement and mixing of precipitation that precedes runoff formation. This combination of high resolution stable isotope data and hydrometric observations facilitates a clearer understanding of spatial controls on streamflow generation. In addition, understanding the relative influences of topography and vegetation on runoff generation could help scientists and managers better assess potential impacts of disturbance on water supplies downstream of forested headwater catchments.

How Does Snow Persistence Relate to Annual Streamflow in Mountain Watersheds of the Western U.S. With Wet Maritime and Dry Continental Climates?

NASA Astrophysics Data System (ADS)

Hammond, John C.; Saavedra, Freddy A.; Kampf, Stephanie K.

2018-04-01

With climate warming, many regions are experiencing changes in snow accumulation and persistence. These changes are known to affect streamflow volume, but the magnitude of the effect varies between regions. This research evaluates whether variables derived from remotely sensed snow cover can be used to estimate annual streamflow at the small watershed scale across the western U.S., a region with a wide range of climate types. We compared snow cover variables derived from MODIS, snow persistence (SP), and snow season (SS), to more commonly utilized metrics, snow fraction (fraction of precipitation falling as snow, SF), and peak snow water equivalent (SWE). Each variable represents different information about snow, and this comparison assesses similarities and differences between the snow metrics. Next, we evaluated how two snow variables, SP and SWE, related to annual streamflow (Q) for 119 USGS reference watersheds and examined whether these relationships varied for wet/warm (precipitation surplus) and dry/cold (precipitation deficit) watersheds. Results showed high correlations between all snow variables, but the slopes of these relationships differed between climates, with wet/warm watersheds displaying lower SF and higher SWE for the same SP. In dry/cold watersheds, both SP and SNODAS SWE correlated with Q spatially across all watersheds and over time within individual watersheds. We conclude that SP can be used to map spatial patterns of annual streamflow generation in dry/cold parts of the region. Applying this approach to the Upper Colorado River Basin demonstrates that 50% of streamflow comes from areas >3,000 masl. If the relationship between SP and Q is similar in other dry/cold regions, this approach could be used to estimate annual streamflow in ungauged basins.

A retrospective streamflow ensemble forecast for an extreme hydrologic event: a case study of Hurricane Irene and on the Hudson River basin

NASA Astrophysics Data System (ADS)

Saleh, Firas; Ramaswamy, Venkatsundar; Georgas, Nickitas; Blumberg, Alan F.; Pullen, Julie

2016-07-01

This paper investigates the uncertainties in hourly streamflow ensemble forecasts for an extreme hydrological event using a hydrological model forced with short-range ensemble weather prediction models. A state-of-the art, automated, short-term hydrologic prediction framework was implemented using GIS and a regional scale hydrological model (HEC-HMS). The hydrologic framework was applied to the Hudson River basin ( ˜ 36 000 km2) in the United States using gridded precipitation data from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) and was validated against streamflow observations from the United States Geologic Survey (USGS). Finally, 21 precipitation ensemble members of the latest Global Ensemble Forecast System (GEFS/R) were forced into HEC-HMS to generate a retrospective streamflow ensemble forecast for an extreme hydrological event, Hurricane Irene. The work shows that ensemble stream discharge forecasts provide improved predictions and useful information about associated uncertainties, thus improving the assessment of risks when compared with deterministic forecasts. The uncertainties in weather inputs may result in false warnings and missed river flooding events, reducing the potential to effectively mitigate flood damage. The findings demonstrate how errors in the ensemble median streamflow forecast and time of peak, as well as the ensemble spread (uncertainty) are reduced 48 h pre-event by utilizing the ensemble framework. The methodology and implications of this work benefit efforts of short-term streamflow forecasts at regional scales, notably regarding the peak timing of an extreme hydrologic event when combined with a flood threshold exceedance diagram. Although the modeling framework was implemented on the Hudson River basin, it is flexible and applicable in other parts of the world where atmospheric reanalysis products and streamflow data are available.

Deep nitrogen acquisition in warming permafrost soils: Contributions of belowground plant traits and fungal symbioses in the permafrost carbon feedback to climate

NASA Astrophysics Data System (ADS)

Hartnett, H. E.; Palta, M. M.; Grimm, N. B.; Ruhi, A.; van Shaijik, M.

2016-12-01

Tempe Town Lake (TTL) is a hydrologically-regulated reservoir in Tempe, Arizona. The lake has high primary production and receives dissolved organic carbon (DOC) from rainfall, storm flow, and upstream river discharge. We applied an ARIMA time-series model to a three-year period for which we have high-frequency chemistry, meteorology, and streamflow data and analyzed external (rainfall, stream flow) and internal (dissolved O2) drivers of DOC content and composition. DOC composition was represented by fluorescence-based indices (fluorescence index, humification index, freshness) related to DOC source (microbially- vs. terrestrially-derived) and reactivity DOC. Patterns in DOC concentration and composition suggest carbon cycling in the lake responds to both meteorological events and to anthropogenic activity. The fluorescence-derived DOC composition is consistent with seasonally-distinct inputs of algal- and terrestrially-derived carbon. For example, Tempe Town Lake is supersaturated in O2 over 70% of the time, suggesting the system is autotrophic and primary productivity (i.e., O2 saturation state) was the strongest driver of DOC concentration. In contrast, external drivers (rainfall pattern, streamflow) were the strongest determinants of DOC composition. Biological processes (e.g., algal growth) generate carbon in the lake during spring and summer, and high Fluorescence Index and Freshness values at this time are indicative of algal-derived material; these parameters generally decrease with rain or flow suggesting algal-derived carbon is diluted by external water inputs. During dry periods, carbon builds up on the land surface and subsequent rainfall events deliver terrestrial carbon to the lake. Further evidence that rain and streamflow deliver land-derived material are increases in the Humification Index (an indicator of terrestrial material) following rain/flow events. Our results indicate that Tempe Town Lake generates autochthonous carbon and has the capacity to process allochthonous carbon from the urban environment. Ongoing work is comparing these results to other periods in the 10-year time series to test if the driver-DOC relationships are robust over longer time-scales and evaluating how changes in lake management and climate have altered DOC over time.

Temporal Patterns in Dissolved Organic Carbon Composition in an Urban Lake

NASA Astrophysics Data System (ADS)

Hartnett, H. E.; Palta, M. M.; Grimm, N. B.; Ruhi, A.; van Shaijik, M.

2017-12-01

Tempe Town Lake (TTL) is a hydrologically-regulated reservoir in Tempe, Arizona. The lake has high primary production and receives dissolved organic carbon (DOC) from rainfall, storm flow, and upstream river discharge. We applied an ARIMA time-series model to a three-year period for which we have high-frequency chemistry, meteorology, and streamflow data and analyzed external (rainfall, stream flow) and internal (dissolved O2) drivers of DOC content and composition. DOC composition was represented by fluorescence-based indices (fluorescence index, humification index, freshness) related to DOC source (microbially- vs. terrestrially-derived) and reactivity DOC. Patterns in DOC concentration and composition suggest carbon cycling in the lake responds to both meteorological events and to anthropogenic activity. The fluorescence-derived DOC composition is consistent with seasonally-distinct inputs of algal- and terrestrially-derived carbon. For example, Tempe Town Lake is supersaturated in O2 over 70% of the time, suggesting the system is autotrophic and primary productivity (i.e., O2 saturation state) was the strongest driver of DOC concentration. In contrast, external drivers (rainfall pattern, streamflow) were the strongest determinants of DOC composition. Biological processes (e.g., algal growth) generate carbon in the lake during spring and summer, and high Fluorescence Index and Freshness values at this time are indicative of algal-derived material; these parameters generally decrease with rain or flow suggesting algal-derived carbon is diluted by external water inputs. During dry periods, carbon builds up on the land surface and subsequent rainfall events deliver terrestrial carbon to the lake. Further evidence that rain and streamflow deliver land-derived material are increases in the Humification Index (an indicator of terrestrial material) following rain/flow events. Our results indicate that Tempe Town Lake generates autochthonous carbon and has the capacity to process allochthonous carbon from the urban environment. Ongoing work is comparing these results to other periods in the 10-year time series to test if the driver-DOC relationships are robust over longer time-scales and evaluating how changes in lake management and climate have altered DOC over time.

Model simulation of the Manasquan water-supply system in Monmouth County, New Jersey

USGS Publications Warehouse

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.

Droughts in Georgia

USGS Publications Warehouse

Barber, Nancy L.; Stamey, Timothy C.

2000-01-01

Droughts do not have the immediate effects of floods, but sustained droughts can cause economic stress throughout the State. The word 'drought' has various meanings, depending on a person's perspective. To a farmer, a drought is a period of moisture deficiency that affects the crops under cultivation - even two weeks without rainfall can stress many crops during certain periods of the growing cycle. To a meteorologist, a drought is a prolonged period when precipitation is less than normal. To a water manager, a drought is a deficiency in water supply that affects water availability and water quality. To a hydrologist, a drought is an extended period of decreased precipitation and streamflow. Droughts in Georgia have severely affected municipal and industrial water supplies, agriculture, stream water quality, recreation at major reservoirs, hydropower generation, navigation, and forest resources. In Georgia, droughts have been documented at U.S. Geological Survey (USGS) streamflow gaging stations since the 1890's. From 1910 to 1940, about 20 streamflow gaging stations were in operation. Since the early 1950's through the late 1980's, about 100 streamflow gaging stations were in operation. Currently (2000), the USGS streamflow gaging network consists of more than 135 continuous-recording gages. Ground-water levels are currently monitored at 165 wells equipped with continuous recorders.

Potential for real-time understanding of coupled hydrologic and biogeochemical processes in stream ecosystems: Future integration of telemetered data with process models for glacial meltwater streams

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.

Response of streamflow to climate change in a sub-basin of the source region of the Yellow River based on a tank model

NASA Astrophysics Data System (ADS)

Wu, Pan; Wang, Xu-Sheng; Liang, Sihai

2018-06-01

Though extensive researches were conducted in the source region of the Yellow River (SRYR) to analyse climate change influence on streamflow, however, few researches concentrate on streamflow of the sub-basin above the Huangheyan station in the SRYR (HSRYR) where a water retaining dam was built in the outlet in 1999. To improve the reservoir regulation strategies, this study analysed streamflow change of the HSRYR in a mesoscale. A tank model (TM) was proposed and calibrated with monthly observation streamflow from 1991 to 1998. In the validation period, though there is a simulation deviation during the water storage and power generation period, simulated streamflow agrees favourably with observation data from 2008 to 2013. The model was further validated by two inside lakes area obtained from Landsat 5, 7, 8 datasets from 2000 to 2014, and significant correlations were found between the simulated lake outlet runoff and respective lake area. Then 21 Global Climate Models (GCM) ensembled data of three emission scenarios (SRA2, SRA1B and SRB1) were downscaled and used as input to the TM to simulate the runoff change of three benchmark periods 2011-2030 (2020s), 2046-2065 (2050s), 2080-2099 (2090s), respectively. Though temperature increase dramatically, these projected results similarly indicated that streamflow shows an increase trend in the long term. Runoff increase is mainly caused by increasing precipitation and decreasing evaporation. Water resources distribution is projected to change from summer-autumn dominant to autumn winter dominant. Annual lowest runoff will occur in May caused by earlier snow melting and increasing evaporation in March. According to the obtained results, winter runoff should be artificially stored by reservoir regulation in the future to prevent zero-flow occurrent in May. This research is helpful for water resources management and provides a better understand of streamflow change caused by climate change in the future.

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.

Managing Groundwater Recharge and Pumping for Late Summer Streamflow Increases: Quantifying Uncertainty Using Null Space Monte Carlo

NASA Astrophysics Data System (ADS)

Tolley, D. G., III; Foglia, L.; Harter, T.

2017-12-01

Late summer and early fall streamflow decreases caused by climate change and agricultural pumping contribute to increased water temperatures and result in large disconnected sections during dry years in many semi-arid regions with Mediterranean climate. This negatively impacts aquatic habitat of fish species such as coho and fall-run Chinook salmon. In collaboration with local stakeholders, the Scott Valley Integrated Hydrologic Model (SVIHMv3) was developed to assess future water management scenarios with the goal of improving aquatic species habitat while maintaining agricultural production in the valley. The Null Space Monte Carlo (NSMC) method available in PEST was used to quantify the range of predicted streamflow changes for three conjunctive use scenarios: 1) managed aquifer recharge (MAR), 2) in lieu recharge (ILR, substituting surface-water irrigation for irrigation with groundwater while flows are available), and 3) MAR + ILR. Random parameter sets were generated using the calibrated covariance matrix of the model, which were then recalibrated if the sum of squared residuals was greater than 10% of the original sum of squared weighted residuals. These calibration-constrained stochastic parameter sets were then used to obtain a distribution of streamflow changes resulting from implementing the conjunctive use scenarios. Preliminary results show that while the range of streamflow increases using managed aquifer recharge is much narrower (i.e., greater degree of certainty) than in lieu recharge, there are potentially much greater benefits to streamflow by implementing in lieu recharge (although also greater costs). Combining the two scenarios provides the greatest benefit for increasing late summer and early fall streamflow, as most of the MAR streamflow increases are during the spring and early summer which ILR is able to take advantage of. Incorporation of uncertainty into model predictions is critical for establishing and maintaining stakeholder trust, and can help identify management strategies that are most likely to produce desired outcomes.

Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal adjustment scale

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.

Use of medium-range numerical weather prediction model output to produce forecasts of streamflow

USGS Publications Warehouse

Clark, M.P.; Hay, L.E.

2004-01-01

This paper examines an archive containing over 40 years of 8-day atmospheric forecasts over the contiguous United States from the NCEP reanalysis project to assess the possibilities for using medium-range numerical weather prediction model output for predictions of streamflow. This analysis shows the biases in the NCEP forecasts to be quite extreme. In many regions, systematic precipitation biases exceed 100% of the mean, with temperature biases exceeding 3??C. In some locations, biases are even higher. The accuracy of NCEP precipitation and 2-m maximum temperature forecasts is computed by interpolating the NCEP model output for each forecast day to the location of each station in the NWS cooperative network and computing the correlation with station observations. Results show that the accuracy of the NCEP forecasts is rather low in many areas of the country. Most apparent is the generally low skill in precipitation forecasts (particularly in July) and low skill in temperature forecasts in the western United States, the eastern seaboard, and the southern tier of states. These results outline a clear need for additional processing of the NCEP Medium-Range Forecast Model (MRF) output before it is used for hydrologic predictions. Techniques of model output statistics (MOS) are used in this paper to downscale the NCEP forecasts to station locations. Forecasted atmospheric variables (e.g., total column precipitable water, 2-m air temperature) are used as predictors in a forward screening multiple linear regression model to improve forecasts of precipitation and temperature for stations in the National Weather Service cooperative network. This procedure effectively removes all systematic biases in the raw NCEP precipitation and temperature forecasts. MOS guidance also results in substantial improvements in the accuracy of maximum and minimum temperature forecasts throughout the country. For precipitation, forecast improvements were less impressive. MOS guidance increases he accuracy of precipitation forecasts over the northeastern United States, but overall, the accuracy of MOS-based precipitation forecasts is slightly lower than the raw NCEP forecasts. Four basins in the United States were chosen as case studies to evaluate the value of MRF output for predictions of streamflow. Streamflow forecasts using MRF output were generated for one rainfall-dominated basin (Alapaha River at Statenville, Georgia) and three snowmelt-dominated basins (Animas River at Durango, Colorado: East Fork of the Carson River near Gardnerville, Nevada: and Cle Elum River near Roslyn, Washington). Hydrologic model output forced with measured-station data were used as "truth" to focus attention on the hydrologic effects of errors in the MRF forecasts. Eight-day streamflow forecasts produced using the MOS-corrected MRF output as input (MOS) were compared with those produced using the climatic Ensemble Streamflow Prediction (ESP) technique. MOS-based streamflow forecasts showed increased skill in the snowmelt-dominated river basins, where daily variations in streamflow are strongly forced by temperature. In contrast, the skill of MOS forecasts in the rainfall-dominated basin (the Alapaha River) were equivalent to the skill of the ESP forecasts. Further improvements in streamflow forecasts require more accurate local-scale forecasts of precipitation and temperature, more accurate specification of basin initial conditions, and more accurate model simulations of streamflow. ?? 2004 American Meteorological Society.

An approach to the rationalization of streamflow data collection networks

NASA Astrophysics Data System (ADS)

Burn, Donald H.; Goulter, Ian C.

1991-01-01

A new procedure for rationalizing a streamflow data collection network is developed. The procedure is a two-phase approach in which in the first phase, a hierarchical clustering technique is used to identify groups of similar gauging stations. In the second phase, a single station from each identified group of gauging stations is selected to be retained in the rationalized network. The station selection phase is an inherently heuristic process that incorporates information about the characteristics of the individual stations in the network. The methodology allows the direct inclusion of user judgement into the station selection process in that it is possible to select more than one station from a group, if conditions warrant. The technique is demonstrated using streamflow gauging stations in and near the Pembina River basin, southern Manitoba, Canada.

Benchmarking Ensemble Streamflow Prediction Skill in the UK

NASA Astrophysics Data System (ADS)

Harrigan, Shaun; Smith, Katie; Parry, Simon; Tanguy, Maliko; Prudhomme, Christel

2017-04-01

Skilful hydrological forecasts at weekly to seasonal lead times would be extremely beneficial for decision-making in operational water management, especially during drought conditions. Hydro-meteorological ensemble forecasting systems are an attractive approach as they use two sources of streamflow predictability: (i) initial hydrologic conditions (IHCs), where soil moisture, groundwater and snow storage states can provide an estimate of future streamflow situations, and (ii) atmospheric predictability, where skilful forecasts of weather and climate variables can be used to force hydrological models. In the UK, prediction of rainfall at long lead times and for summer months in particular is notoriously difficult given the large degree of natural climate variability in ocean influenced mid-latitude regions, but recent research has uncovered exciting prospects for improved rainfall skill at seasonal lead times due to improved prediction of the North Atlantic Oscillation. However, before we fully understand what this improved atmospheric predictability might mean in terms of improved hydrological forecasts, we must first evaluate how much skill can be gained from IHCs alone. Ensemble Streamflow Prediction (ESP) is a well-established method for generating an ensemble of streamflow forecasts in the absence of skilful future meteorological predictions. The aim of this study is therefore to benchmark when (lead time/forecast initialisation month) and where (spatial pattern/catchment characteristics) ESP is skilful across a diverse set of catchments in the UK. Forecast skill was evaluated seamlessly from lead times of 1-day to 12-months and forecasts were initialised at the first of each month over the 1965-2015 hindcast period. This ESP output also provides a robust benchmark against which to assess how much improvement in skill can be achieved when meteorological forecasts are incorporated (next steps). To provide a 'tough to beat' benchmark, several variants of ESP with increasing complexity were produced, including better model representation of hydrological processes and sub-sampling of historic climate sequences (e.g. NAO+/NAO- years). This work is part of the Improving Predictions of Drought for User Decision Making (IMPETUS) project and provides insight to where advancements in atmospheric predictability is most needed in the UK in the context of water management.

A precipitation-runoff model for simulating natural streamflow conditions in the Smith River watershed, Montana, water years 1996-2008

USGS Publications Warehouse

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).

Using tracers to evaluate streamflow gain-loss characteristics of Terror Creek, in the vicinity of a mine-permit area, Delta County, Colorado, water year 2003

USGS Publications Warehouse

Williams, Cory A.; Leib, Kenneth J.

2005-01-01

In 2003, the U.S. Geological Survey, in cooperation with Delta County, initiated a study to characterize streamflow gainloss in a reach of Terror Creek, in the vicinity of a mine-permit area planned for future coal mining. This report describes the methods of the study and includes results from a comparison of two sets of streamflow measurements using tracer techniques following the constant-rate injection method. Two measurement sets were used to characterize the streamflow gain-loss associated with reservoir-supplemented streamflow conditions and with natural base-flow conditions. A comparison of the measurement sets indicates that the streamflow gain-loss characteristics of the Terror Creek study reach are consistent between the two hydrologic conditions evaluated. A substantial streamflow gain occurs between measurement locations 4 and 5 in both measurement sets, and streamflow is lost between measurement locations 5 and 7 (measurement set 1, measurement location 6 not visited) and 5 and 6 (measurement set 2). A comparison of the measurement sets above and below the mine-permit area (measurement locations 3 and 7) shows a consistent loss of 0.37 and 0.31 cubic foot per second (representing 5- and 12-percent streamflow losses normalized to measurement location 3) for measurement sets 1 and 2, respectively. This indicates that similar streamflow losses occur both during reservoir-supplemented and natural base-flow conditions, with a mean streamflow loss of 0.34 cubic foot per second for measurement sets 1 and 2. Findings from a previous investigation support the observed streamflow loss between measurement locations 3 and 7 in this study. The findings from the previous investigation indicate a streamflow loss of 0.59 cubic foot per second occurs between these measurement locations. Statistical testing of the differences in streamflow between measurement locations 3 and 7 indicates that there is a discernible streamflow loss. The p-value of 0.0236 for the parametric paired t-test indicates that there is a 2.36-percent probability of observing a sample mean difference of 0.34 cubic foot per second if the population mean is zero. The p-value of 0.125 for the nonparametric exact Wilcoxon signed rank test indicates that there is a 12.5-percent probability of observing a sample mean difference this large if the population mean is zero. The similarity in streamflow gain-loss between measurement sets indicates that the process controlling streamflow may be the same between the two hydrologic conditions evaluated. Gains between measurement locations 4 and 5 may be related to hyporheic flow from tributaries that were dry during the study. No other obvious sources of surface water were identified during the investigation. The cause for the observed streamflow loss between measurement locations 5 and 6 is unknown but may be related to mapped local faulting, 100 years of coal mining in the area, and aquifer recharge.

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...

A multi-site reconstruction algorithm for bottom-up vulnerability assessment of water resource systems to changing streamflow conditions

NASA Astrophysics Data System (ADS)

Nazemi, A.; Zaerpour, M.

2016-12-01

Current paradigm for assessing the vulnerability of water resource systems to changing streamflow conditions often involves a cascade application of climate and hydrological models to project the future states of streamflow regime, entering to a given water resource system. It is widely warned, however, that the overall uncertainty in this "top-down" modeling enterprise can be large due to the limitations in representing natural and anthropogenic processes that affect future streamflow variability and change. To address this, various types of stress-tests are suggested to assess the vulnerability of water resources systems under a wide range of possible changes in streamflow conditions. The scope of such "bottom-up" assessments can go well beyond top-down projections and therefore provide a basis for monitoring different response modes, under which water resource systems become vulnerable. Despite methodological differences, all bottom-up assessments are equipped with a systematic sampling procedure, with which different possibilities for future climate and/or streamflow conditions can be realized. Regardless of recent developments, currently available streamflow sampling algorithms are still limited, particularly in regional contexts, for which accurate representation of spatiotemporal dependencies in streamflow regime are of major importance. In this presentation, we introduce a new development that enables handling temporal and spatial dependencies in regional streamflow regimes through a unified stochastic reconstruction algorithm. We demonstrate the application of this algorithm accross various Canadian regions. By considering a real-world regional water resources system, we show how the new multi-site reconstruction algorithm can extend the practical utility of bottom-up vulnerability assessment and improve quantifying the associated risk in natural and anthropogenic water systems under unknown future conditions.

Streamflow characteristics of the Colorado River Basin in Utah through September 1981

USGS Publications Warehouse

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.

Streamflow Bias Correction for Climate Change Impact Studies: Harmless Correction or Wrecking Ball?

NASA Astrophysics Data System (ADS)

Nijssen, B.; Chegwidden, O.

2017-12-01

Projections of the hydrologic impacts of climate change rely on a modeling chain that includes estimates of future greenhouse gas emissions, global climate models, and hydrologic models. The resulting streamflow time series are used in turn as input to impact studies. While these flows can sometimes be used directly in these impact studies, many applications require additional post-processing to remove model errors. Water resources models and regulation studies are a prime example of this type of application. These models rely on specific flows and reservoir levels to trigger reservoir releases and diversions and do not function well if the unregulated streamflow inputs are significantly biased in time and/or amount. This post-processing step is typically referred to as bias-correction, even though this step corrects not just the mean but the entire distribution of flows. Various quantile-mapping approaches have been developed that adjust the modeled flows to match a reference distribution for some historic period. Simulations of future flows are then post-processed using this same mapping to remove hydrologic model errors. These streamflow bias-correction methods have received far less scrutiny than the downscaling and bias-correction methods that are used for climate model output, mostly because they are less widely used. However, some of these methods introduce large artifacts in the resulting flow series, in some cases severely distorting the climate change signal that is present in future flows. In this presentation, we discuss our experience with streamflow bias-correction methods as part of a climate change impact study in the Columbia River basin in the Pacific Northwest region of the United States. To support this discussion, we present a novel way to assess whether a streamflow bias-correction method is merely a harmless correction or is more akin to taking a wrecking ball to the climate change signal.

Looking Deeper Into Hydrologic Connectivity and Streamflow Generation: A Groundwater Hydrologist's Perspective.

NASA Astrophysics Data System (ADS)

Gardner, W. P.

2016-12-01

In this presentation the definition of hydraulic connection will be explored with a focus on the role of deep groundwater in streamflow generation and its time and space limits. Regional groundwater flow paths can be important sources of baseflow and potentially event response in surface water systems. This deep groundwater discharge plays an important role in determining how the watershed responds to climatic forcing, whether watersheds are a carbon source or sink and can be significant for watershed geochemistry and nutrient loading. These flow paths potentially "connect" to surface water systems and saturated soil zones at large distances, and over long time scales. However, these flow paths are challenging to detect, especially with hydraulic techniques. Here we will discuss some of the basic physical processes that affect the hydraulic signal along a groundwater flow path and their implications for the definition of hydrologic connection. Methods of measuring hydraulic connection using groundwater head response and their application in detecting regional groundwater discharge will be discussed. Environmental tracers are also a powerful method for identifying connected flowpaths in groundwater systems, and are commonly used to determine flow connection and flow rates in groundwater studies. Isotopic tracer methods for detecting deep, regional flow paths in watersheds will be discussed, along with observations of deep groundwater discharge in shallow alluvial systems around the world. The goal of this talk is to discuss hydraulic and hydrologic connection from a groundwater hydrologist's perspective, spark conversation on the meaning of hydrologic connection, the processes which govern hydraulic response and methods to measure flow connections and flux.

Effects of Urbanization and Climate Change on Hydrological Processes over the San Antonio River Basin, Texas

NASA Astrophysics Data System (ADS)

Zhao, G.; Gao, H.; Cuo, L.

2014-12-01

With the rapid population growth and economic development in the State of Texas, a fast urbanization process has occurred over the past several decades. The direct consequences of the increased impervious area are greater surface runoff and higher flood peaks. Meanwhile, climate change has led to more frequent extreme events. Therefore, a thorough understanding of the hydrological processes under urbanization and climate change is indispensable for sustainable water management. In this investigation, a case study was conducted by applying the Distributed Hydrology Soil Vegetation Model (DHSVM) to the San Antonio River Basin (SARB), Texas. Hosting the seventh largest city in the U.S. (i.e., City of San Antonio), the SARB is vulnerable to both floods and droughts. A set of historical and future land cover maps were assembled to represent the urbanization process. Two forcing datasets were employed to drive the DHSVM model. The first is a long-term observation based dataset (1915-2011), which was used as inputs for calibrating and validating DHSVM, as well as evaluating the urbanization effect. The second is the statistically downscaled climate simulations (1950-2099) from the Coupled Model Intercomparison Project Phase 5 (CMIP5), which were applied for understanding impacts related to climate change. Results show that urbanization exerts a much larger influence on streamflow than climate change does. Under the same observed forcings, annual average streamflow increased from 993.0 cfs (with 1929 land cover) to 1777.7 cfs (with 2011 land cover). As for climate change, results suggest that it will exacerbate the drought severity — with reduced evapotranspiration and soil moisture caused by decreased precipitation. However, the projected future streamflow does not show a clear increasing or decreasing trend. Regarding the combined effect from urbanization and climate change, the results indicate that the seasonal streamflow pattern will be notably changed (i.e., streamflow in October will be significantly increased, which makes it a second flow peak in addition to May). Furthermore, with significantly decreased evapotranspiration and slightly increased soil moisture, more water will be available for streamflow, increasing the possibility of flood risk in the region.

Streamflow responses in Chile to megathrust earthquakes in the 20th and 21st centuries

NASA Astrophysics Data System (ADS)

Mohr, Christian; Manga, Michael; Wang, Chi-yuen; Korup, Oliver

2016-04-01

Both coseismic static stress and dynamic stresses associated with seismic waves may cause responses in hydrological systems. Such responses include changes in the water level, hydrochemistry and streamflow discharge. Earthquake effects on hydrological systems provide a means to study the interaction between stress changes and regional hydrology, which is otherwise rarely possible. Chile is a country of frequent and large earthquakes and thus provides abundant opportunities to study such interactions and processes. We analyze streamflow responses in Chile to several megathrust earthquakes, including the 1943 Mw 8.1 Coquimbo, 1950 Mw 8.2 Antofagasta, 1960 Mw 9.5 Valdivia, 1985 Mw 8.0 Valparaiso, 1995 Mw 8.0 Antofagasta, 2010 Mw 8.8 Maule, and the 2014 Mw 8.2 Iquique earthquakes. We use data from 716 stream gauges distributed from the Altiplano in the North to Tierra del Fuego in the South. This network covers the Andes mountain ranges, the central valley, the Coastal Mountain ranges and (mainly in the more southern parts) the Coastal flats. We combine empirical magnitude-distance relationships, machine learning tools, and process-based modeling to characterize responses. We first assess the streamflow anomalies and relate these to topographical, hydro-climatic, geological and earthquake-related (volumetric and dynamic strain) factors using various classifiers. We then apply 1D-groundwater flow modeling to selected catchments in order to test competing hypotheses for the origin of streamflow changes. We show that the co-seismic responses of streamflow mostly involved increasing discharges. We conclude that enhanced vertical permeability can explain most streamflow responses at the regional scale. The total excess water released by a single earthquake, i.e. the Maule earthquake, yielded up to 1 km3. Against the background of megathrust earthquakes frequently hitting Chile, the amount of water released by earthquakes is substantial, particularly for the arid northern areas that depend exclusively on groundwater resources.

A method for extending stage-discharge relationships using a hydrodynamic model and quantifying the associated uncertainty

NASA Astrophysics Data System (ADS)

Shao, Quanxi; Dutta, Dushmanta; Karim, Fazlul; Petheram, Cuan

2018-01-01

Streamflow discharge is a fundamental dataset required to effectively manage water and land resources. However, developing robust stage - discharge relationships called rating curves, from which streamflow discharge is derived, is time consuming and costly, particularly in remote areas and especially at high stage levels. As a result stage - discharge relationships are often heavily extrapolated. Hydrodynamic (HD) models are physically based models used to simulate the flow of water along river channels and over adjacent floodplains. In this paper we demonstrate a method by which a HD model can be used to generate a 'synthetic' stage - discharge relationship at high stages. The method uses a both-side Box-Cox transformation to calibrate the synthetic rating curve such that the regression residuals are as close to the normal distribution as possible. By doing this both-side transformation, the statistical uncertainty in the synthetically derived stage - discharge relationship can be calculated. This enables people trying to make decisions to determine whether the uncertainty in the synthetically generated rating curve at high stage levels is acceptable for their decision. The proposed method is demonstrated in two streamflow gauging stations in north Queensland, Australia.

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.

Identifying Hydrologic Processes in Agricultural Watersheds Using Precipitation-Runoff Models

USGS Publications Warehouse

Linard, Joshua I.; Wolock, David M.; Webb, Richard M.T.; Wieczorek, Michael

2009-01-01

Understanding the fate and transport of agricultural chemicals applied to agricultural fields will assist in designing the most effective strategies to prevent water-quality impairments. At a watershed scale, the processes controlling the fate and transport of agricultural chemicals are generally understood only conceptually. To examine the applicability of conceptual models to the processes actually occurring, two precipitation-runoff models - the Soil and Water Assessment Tool (SWAT) and the Water, Energy, and Biogeochemical Model (WEBMOD) - were applied in different agricultural settings of the contiguous United States. Each model, through different physical processes, simulated the transport of water to a stream from the surface, the unsaturated zone, and the saturated zone. Models were calibrated for watersheds in Maryland, Indiana, and Nebraska. The calibrated sets of input parameters for each model at each watershed are discussed, and the criteria used to validate the models are explained. The SWAT and WEBMOD model results at each watershed conformed to each other and to the processes identified in each watershed's conceptual hydrology. In Maryland the conceptual understanding of the hydrology indicated groundwater flow was the largest annual source of streamflow; the simulation results for the validation period confirm this. The dominant source of water to the Indiana watershed was thought to be tile drains. Although tile drains were not explicitly simulated in the SWAT model, a large component of streamflow was received from lateral flow, which could be attributed to tile drains. Being able to explicitly account for tile drains, WEBMOD indicated water from tile drains constituted most of the annual streamflow in the Indiana watershed. The Nebraska models indicated annual streamflow was composed primarily of perennial groundwater flow and infiltration-excess runoff, which conformed to the conceptual hydrology developed for that watershed. The hydrologic processes represented in the parameter sets resulting from each model were comparable at individual watersheds, but varied between watersheds. The models were unable to show, however, whether hydrologic processes other than those included in the original conceptual models were major contributors to streamflow. Supplemental simulations of agricultural chemical transport could improve the ability to assess conceptual models.

Factors Affecting Firm Yield and the Estimation of Firm Yield for Selected Streamflow-Dominated Drinking-Water-Supply Reservoirs in Massachusetts

USGS Publications Warehouse

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.

The Role of Multimodel Combination in Improving Streamflow Prediction

NASA Astrophysics Data System (ADS)

Arumugam, S.; Li, W.

2008-12-01

Model errors are the inevitable part in any prediction exercise. One approach that is currently gaining attention to reduce model errors is by optimally combining multiple models to develop improved predictions. The rationale behind this approach primarily lies on the premise that optimal weights could be derived for each model so that the developed multimodel predictions will result in improved predictability. In this study, we present a new approach to combine multiple hydrological models by evaluating their predictability contingent on the predictor state. We combine two hydrological models, 'abcd' model and Variable Infiltration Capacity (VIC) model, with each model's parameter being estimated by two different objective functions to develop multimodel streamflow predictions. The performance of multimodel predictions is compared with individual model predictions using correlation, root mean square error and Nash-Sutcliffe coefficient. To quantify precisely under what conditions the multimodel predictions result in improved predictions, we evaluate the proposed algorithm by testing it against streamflow generated from a known model ('abcd' model or VIC model) with errors being homoscedastic or heteroscedastic. Results from the study show that streamflow simulated from individual models performed better than multimodels under almost no model error. Under increased model error, the multimodel consistently performed better than the single model prediction in terms of all performance measures. The study also evaluates the proposed algorithm for streamflow predictions in two humid river basins from NC as well as in two arid basins from Arizona. Through detailed validation in these four sites, the study shows that multimodel approach better predicts the observed streamflow in comparison to the single model predictions.

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.

Users Manual for the Geospatial Stream Flow Model (GeoSFM)

USGS Publications Warehouse

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.

Winter streamflow analysis in frozen, alpine catchments to quantify groundwater contribution and properties

NASA Astrophysics Data System (ADS)

Stoelzle, Michael; Weiler, Markus

2016-04-01

Alpine catchments are often considered as quickly responding systems where streamflow contributions from subsurface storages (groundwater) are mostly negligible due to the steep topography, low permeable bedrock and the absence of well-developed soils. Many studies in high altitude catchments have hence focused on water stored in snowpack and glaciers or on rainfall-runoff processes as the dominant streamflow contributions. Interestingly less effort has been devoted to winter streamflow analysis when melt- or rainfall-driven contributions are switched off due to the frozen state of the catchment. Considering projected changes in the alpine cryosphere (e.g. snow, glacier, permafrost) quantification of groundwater storage and contribution to streamflow is crucial to assess the social and ecological implications for downstream areas (e.g. water temperature, drought propagation). In this study we hypothesize that groundwater is the main streamflow contribution during winter and thus being responsible for the perennial regime of many alpine catchments. The hypothesis is investigated with well-known methods based on recession and breakpoint analysis of the streamflow regimes and temperature data to determine frozen periods. Analyzing nine catchments in Switzerland with mean elevation between 1000 and 2400 m asl, we found that above a mean elevation of 1800 m asl winter recessions are sufficient long and persistent enough to quantify groundwater contribution to streamflow and to characterize the properties of subsurface storage. The results show that groundwater in alpine catchment is the dominant streamflow contribution for nearly half a year and accountable for several hundred millimeter of annual streamflow. In sub-alpine catchments, driven by a mix of snowmelt and rainfall, a clear quantification of groundwater contributions is rather challenging due to discontinuous frozen periods in winter. We found that the inter-annual variability of different streamflow contributions is helpful to assess the water sustainability of alpine catchments functioning as water towers for downstream water basins. We outline how well-known hydrograph and recession analyses in alpine catchments can help to explore the role of catchment storage and to advance our understanding of (ground-)water management in alpine environments.

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.

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).

High-Elevation Evapotranspiration Estimates During Drought: Using Streamflow and NASA Airborne Snow Observatory SWE Observations to Close the Upper Tuolumne River Basin Water Balance

NASA Astrophysics Data System (ADS)

Henn, Brian; Painter, Thomas H.; Bormann, Kat J.; McGurk, Bruce; Flint, Alan L.; Flint, Lorraine E.; White, Vince; Lundquist, Jessica D.

2018-02-01

Hydrologic variables such as evapotranspiration (ET) and soil water storage are difficult to observe across spatial scales in complex terrain. Streamflow and lidar-derived snow observations provide information about distributed hydrologic processes such as snowmelt, infiltration, and storage. We use a distributed streamflow data set across eight basins in the upper Tuolumne River region of Yosemite National Park in the Sierra Nevada mountain range, and the NASA Airborne Snow Observatory (ASO) lidar-derived snow data set over 3 years (2013-2015) during a prolonged drought in California, to estimate basin-scale water balance components. We compare snowmelt and cumulative precipitation over periods from the ASO flight to the end of the water year against cumulative streamflow observations. The basin water balance residual term (snow melt plus precipitation minus streamflow) is calculated for each basin and year. Using soil moisture observations and hydrologic model simulations, we show that the residual term represents short-term changes in basin water storage over the snowmelt season, but that over the period from peak snow water equivalent (SWE) to the end of summer, it represents cumulative basin-mean ET. Warm-season ET estimated from this approach is 168 (85-252 at 95% confidence), 162 (0-326) and 191 (48-334) mm averaged across the basins in 2013, 2014, and 2015, respectively. These values are lower than previous full-year and point ET estimates in the Sierra Nevada, potentially reflecting reduced ET during drought, the effects of spatial variability, and the part-year time period. Using streamflow and ASO snow observations, we quantify spatially-distributed hydrologic processes otherwise difficult to observe.

Linking Statistically- and Physically-Based Models for Improved Streamflow Simulation in Gaged and Ungaged Areas

NASA Astrophysics Data System (ADS)

Lafontaine, J.; Hay, L.; Archfield, S. A.; Farmer, W. H.; Kiang, J. E.

2014-12-01

The U.S. Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the continental US. The portion of the NHM located within the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC) is being used to test the feasibility of improving streamflow simulations in gaged and ungaged watersheds by linking statistically- and physically-based hydrologic models. The GCPO LCC covers part or all of 12 states and 5 sub-geographies, totaling approximately 726,000 km2, and is centered on the lower Mississippi Alluvial Valley. A total of 346 USGS streamgages in the GCPO LCC region were selected to evaluate the performance of this new calibration methodology for the period 1980 to 2013. Initially, the physically-based models are calibrated to measured streamflow data to provide a baseline for comparison. An enhanced calibration procedure then is used to calibrate the physically-based models in the gaged and ungaged areas of the GCPO LCC using statistically-based estimates of streamflow. For this application, the calibration procedure is adjusted to address the limitations of the statistically generated time series to reproduce measured streamflow in gaged basins, primarily by incorporating error and bias estimates. As part of this effort, estimates of uncertainty in the model simulations are also computed for the gaged and ungaged watersheds.

Economic and ecological costs and benefits of streamflow augmentation using recycled water in a California coastal stream.

PubMed

Halaburka, Brian J; Lawrence, Justin E; Bischel, Heather N; Hsiao, Janet; Plumlee, Megan H; Resh, Vincent H; Luthy, Richard G

2013-10-01

Streamflow augmentation has the potential to become an important application of recycled water in water scarce areas. We assessed the economic and ecological merits of a recycled water project that opted for an inland release of tertiary-treated recycled water in a small stream and wetland compared to an ocean outfall discharge. Costs for the status-quo scenario of discharging secondary-treated effluent to the ocean were compared to those of the implemented scenario of inland streamflow augmentation using recycled water. The benefits of the inland-discharge scenario were greater than the increase in associated costs by US$1.8M, with recreational value and scenic amenity generating the greatest value. We also compared physical habitat quality, water quality, and benthic macroinvertebrate community upstream and downstream of the recycled water discharge to estimate the effect of streamflow augmentation on the ecosystem. The physical-habitat quality was higher downstream of the discharge, although streamflow came in unnatural diurnal pulses. Water quality remained relatively unchanged with respect to dissolved oxygen, pH, and ammonia-nitrogen, although temperatures were elevated. Benthic macroinvertebrates were present in higher abundances, although the diversity was relatively low. A federally listed species, the California red-legged frog (Rana draytonii), was present. Our results may support decision-making for wastewater treatment alternatives and recycled water applications in Mediterranean climates.

A Statistical Weather-Driven Streamflow Model: Enabling future flow predictions in data-scarce headwater streams

NASA Astrophysics Data System (ADS)

Rosner, A.; Letcher, B. H.; Vogel, R. M.

2014-12-01

Predicting streamflow in headwaters and over a broad spatial scale pose unique challenges due to limited data availability. Flow observation gages for headwaters streams are less common than for larger rivers, and gages with records lengths of ten year or more are even more scarce. Thus, there is a great need for estimating streamflows in ungaged or sparsely-gaged headwaters. Further, there is often insufficient basin information to develop rainfall-runoff models that could be used to predict future flows under various climate scenarios. Headwaters in the northeastern U.S. are of particular concern to aquatic biologists, as these stream serve as essential habitat for native coldwater fish. In order to understand fish response to past or future environmental drivers, estimates of seasonal streamflow are needed. While there is limited flow data, there is a wealth of data for historic weather conditions. Observed data has been modeled to interpolate a spatially continuous historic weather dataset. (Mauer et al 2002). We present a statistical model developed by pairing streamflow observations with precipitation and temperature information for the same and preceding time-steps. We demonstrate this model's use to predict flow metrics at the seasonal time-step. While not a physical model, this statistical model represents the weather drivers. Since this model can predict flows not directly tied to reference gages, we can generate flow estimates for historic as well as potential future conditions.

Rescaled range analysis of streamflow records in the São Francisco River Basin, Brazil

NASA Astrophysics Data System (ADS)

Araujo, Marcelo Vitor Oliveira; Celeste, Alcigeimes B.

2018-01-01

Hydrological time series are sometimes found to have a distinctive behavior known as long-term persistence, in which subsequent values depend on each other even under very large time scales. This implies multiyear consecutive droughts or floods. Typical models used to generate synthetic hydrological scenarios, widely used in the planning and management of water resources, fail to preserve this kind of persistence in the generated data and therefore may have a major impact on projects whose design lives span for long periods of time. This study deals with the evaluation of long-term persistence in streamflow records by means of the rescaled range analysis proposed by British engineer Harold E. Hurst, who first observed the phenomenon in the mid-twentieth century. In this paper, Hurst's procedure is enhanced by a strategy based on statistical hypothesis testing. The case study comprises the six main hydroelectric power plants located in the São Francisco River Basin, part of the Brazilian National Grid. Historical time series of inflows to the major reservoirs of the system are investigated and 5/6 sites show significant persistence, with values for the so-called Hurst exponent near or greater than 0.7, i.e., around 40% above the value 0.5 that represents a white noise process, suggesting that decision makers should take long-term persistence into consideration when conducting water resources planning and management studies in the region.

The National Streamflow Statistics Program: A Computer Program for Estimating Streamflow Statistics for Ungaged Sites

USGS Publications Warehouse

Ries(compiler), Kernell G.; With sections by Atkins, J. B.; Hummel, P.R.; Gray, Matthew J.; Dusenbury, R.; Jennings, M.E.; Kirby, W.H.; Riggs, H.C.; Sauer, V.B.; Thomas, W.O.

2007-01-01

The National Streamflow Statistics (NSS) Program is a computer program that should be useful to engineers, hydrologists, and others for planning, management, and design applications. NSS compiles all current U.S. Geological Survey (USGS) regional regression equations for estimating streamflow statistics at ungaged sites in an easy-to-use interface that operates on computers with Microsoft Windows operating systems. NSS expands on the functionality of the USGS National Flood Frequency Program, and replaces it. The regression equations included in NSS are used to transfer streamflow statistics from gaged to ungaged sites through the use of watershed and climatic characteristics as explanatory or predictor variables. Generally, the equations were developed on a statewide or metropolitan-area basis as part of cooperative study programs. Equations are available for estimating rural and urban flood-frequency statistics, such as the 1 00-year flood, for every state, for Puerto Rico, and for the island of Tutuila, American Samoa. Equations are available for estimating other statistics, such as the mean annual flow, monthly mean flows, flow-duration percentiles, and low-flow frequencies (such as the 7-day, 0-year low flow) for less than half of the states. All equations available for estimating streamflow statistics other than flood-frequency statistics assume rural (non-regulated, non-urbanized) conditions. The NSS output provides indicators of the accuracy of the estimated streamflow statistics. The indicators may include any combination of the standard error of estimate, the standard error of prediction, the equivalent years of record, or 90 percent prediction intervals, depending on what was provided by the authors of the equations. The program includes several other features that can be used only for flood-frequency estimation. These include the ability to generate flood-frequency plots, and plots of typical flood hydrographs for selected recurrence intervals, estimates of the probable maximum flood, extrapolation of the 500-year flood when an equation for estimating it is not available, and weighting techniques to improve flood-frequency estimates for gaging stations and ungaged sites on gaged streams. This report describes the regionalization techniques used to develop the equations in NSS and provides guidance on the applicability and limitations of the techniques. The report also includes a users manual and a summary of equations available for estimating basin lagtime, which is needed by the program to generate flood hydrographs. The NSS software and accompanying database, and the documentation for the regression equations included in NSS, are available on the Web at http://water.usgs.gov/software/.

Regional stochastic generation of streamflows using an ARIMA (1,0,1) process and disaggregation

USGS Publications Warehouse

Armbruster, Jeffrey T.

1979-01-01

An ARIMA (1,0,1) model was calibrated and used to generate long annual flow sequences at three sites in the Juniata River basin, Pennsylvania. The model preserves the mean, variance, and cross correlations of the observed station data. In addition, it has a desirable blend of both high and low frequency characteristics and therefore is capable of preserving the Hurst coefficient, h. The generated annual flows are disaggregated into monthly sequences using a modification of the Valencia-Schaake model. The low-flow frequency and flow duration characteristics of the generated monthly flows, with length equal to the historical data, compare favorably with the historical data. Once the models were verified, 100-year sequences were generated and analyzed for their low flow characteristics. One-, three- and six- month low-flow frequencies at recurrence intervals greater than 10 years are generally found to be lower than flow computed from the historical flows. A method is proposed for synthesizing flows at ungaged sites. (Kosco-USGS)

Regional variability in the accuracy of statistical reproductions of historical time series of daily streamflow at ungaged locations

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.

Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

DOE PAGES

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

Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

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

Forecasting drought risks for a water supply storage system using bootstrap position analysis

USGS Publications Warehouse

Tasker, Gary; Dunne, Paul

1997-01-01

Forecasting the likelihood of drought conditions is an integral part of managing a water supply storage and delivery system. Position analysis uses a large number of possible flow sequences as inputs to a simulation of a water supply storage and delivery system. For a given set of operating rules and water use requirements, water managers can use such a model to forecast the likelihood of specified outcomes such as reservoir levels falling below a specified level or streamflows falling below statutory passing flows a few months ahead conditioned on the current reservoir levels and streamflows. The large number of possible flow sequences are generated using a stochastic streamflow model with a random resampling of innovations. The advantages of this resampling scheme, called bootstrap position analysis, are that it does not rely on the unverifiable assumption of normality and it allows incorporation of long-range weather forecasts into the analysis.

Simulating long-term landcover change and water yield dynamics in a forested, snow-dominated Rocky Mountain watershed

Treesearch

R. S. Ahl; S. W. Woods

2006-01-01

Changes in the extent, composition, and configuration of forest cover over time due to succession or disturbance processes can result in measurable changes in streamflow and water yield. Removal of forest cover generally increases streamflow due to reduced canopy interception and evapotranspiration. In watersheds where snow is the dominant source of water, yield...

Fast response to fast-forwarding nature: instream large wood habitat restoration

Treesearch

Cheryl A. Hayhurst; William R. Short

2017-01-01

How quickly and in what way does a channel bed respond when large wood elements are introduced in a way that imitates natural wood loading processes (un-anchored or anchored by burial)? Using a design streamflow threshold for determining the size of key large wood elements, what changes in channel bed and habitat complexity occur after streamflow events above...

Changes in precipitation-streamflow transformation around the world: interdecadal variability and trends.

NASA Astrophysics Data System (ADS)

Saft, M.; Peel, M. C.; Andreassian, V.; Parajka, J.; Coxon, G.; Freer, J. E.; Woods, R. A.

2017-12-01

Accurate prediction of hydrologic response to potentially changing climatic forcing is a key current challenge in hydrology. Recent studies exploring decadal to multidecadal climate drying in the African Sahel and south-eastern and south-western Australia demonstrated that long dry periods also had an indirect cumulative impact on streamflow via altered catchment biophysical properties. As a result, hydrologic response to persisting change in climatic conditions, i.e. precipitation, cannot be confidently inferred from the hydrologic response to short-term interannual climate fluctuations of similar magnitude. This study aims to characterise interdecadal changes in precipitation-runoff conversion processes globally. The analysis is based on long continuous records from near-natural baseline catchments in North America, Europe, and Australia. We used several complimentary metrics characterising precipitation-runoff relationship to assess how partitioning changed over recent decades. First, we explore the hypothesis that during particularly dry or wet decades the precipitation elasticity of streamflow increases over what can be expected from inter-annual variability. We found this hypothesis holds for both wet and dry periods in some regions, but not everywhere. Interestingly, trend-like behaviour in the precipitation-runoff partitioning, unrelated to precipitation changes, offset the impact of persisting precipitation change in some regions. Therefore, in the second part of this study we explored longer-term trends in precipitation-runoff partitioning, and related them to climate and streamflow changes. We found significant changes in precipitation-runoff relationship around the world, which implies that runoff response to a given precipitation can vary over decades even in near-natural catchments. When significant changes occur, typically less runoff is generated for a given precipitation over time - even when precipitation is increasing. We discuss the consistency of the results and how the likely drivers differ between regions, and between water-limited and energy limited environments. We argue that when considering the impact of climatic change on hydrological systems we need to consider potential cumulative impacts of climatic shifts.

Objective Use of Climate Indices to Inform Ensemble Streamflow Forecasts in the Columbia River Basin - An Initial Review

NASA Astrophysics Data System (ADS)

Pytlak, E.; McManamon, A.; Hughes, S. P.; Van Der Zweep, R. A.; Butcher, P.; Karafotias, C.; Beckers, J.; Welles, E.

2016-12-01

Numerous studies have documented the impacts that large scale weather patterns and climate phenomenon like the El Niño Southern Oscillation (ENSO), Pacific-North American (PNA) Pattern, and others can have on seasonal temperature and precipitation in the Columbia River Basin (CRB). While far from perfect in terms of seasonal predictability in specific locations, these intra-annual weather and climate signal do tilt the odds toward different temperature and precipitation outcomes, which in turn can have impacts on seasonal snowpacks, streamflows and water supply in large river basins like the CRB. We hypothesize that intraseasonal climate signals and long wave jet stream patterns can be objectively incorporated into what it is otherwise a climatology-based set of Ensemble Streamflow Forecasts, and can increase the predictive skill and utility of these forecasts used for mid-range hydropower planning. The Bonneville Power Administration (BPA) and Deltares have developed a subsampling-resampling method to incorporate climate mode information into the Ensemble Streamflow Prediction (ESP) forecasts (Beckers, et al., 2016). Since 2015, BPA and Deltares USA have experimented with this method in pre-operational use, using five objective multivariate climate indices that appear to have the greatest predictive value for seasonal temperature and precipitation in the CRB. The indices are used to objectively select historical weather from about twenty analog years in the 66-year (1949-2015) historical ESP set. These twenty scenarios then serve as the starting point to generate monthly synthetic weather and streamflow time series to return to a set of 66 streamflow traces. Our poster will share initial results from the 2015 and 2016 water years, which included large swings in the Quasi-Biennial Oscillation, persistent blocking jet stream patterns, and the development of a strong El Niño event. While the results are very preliminary and for only two seasons, there may be some value in incorporating objectively-identified climate signals into ESP-based streamflow forecasts.Beckers, J. V. L., Weerts, A. H., Tijdeman, E., and Welles, E.: ENSO-Conditioned Weather Resampling Method for Seasonal Ensemble Streamflow Prediction, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-72, in review, 2016.

Impact of LUCC on streamflow based on the SWAT model over the Wei River basin on the Loess Plateau in China

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.

Distributed HUC-based modeling with SUMMA for ensemble streamflow forecasting over large regional domains.

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.

Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment

NASA Astrophysics Data System (ADS)

Jha, Sanjeev K.; Shrestha, Durga L.; Stadnyk, Tricia A.; Coulibaly, Paulin

2018-03-01

Flooding in Canada is often caused by heavy rainfall during the snowmelt period. Hydrologic forecast centers rely on precipitation forecasts obtained from numerical weather prediction (NWP) models to enforce hydrological models for streamflow forecasting. The uncertainties in raw quantitative precipitation forecasts (QPFs) are enhanced by physiography and orography effects over a diverse landscape, particularly in the western catchments of Canada. A Bayesian post-processing approach called rainfall post-processing (RPP), developed in Australia (Robertson et al., 2013; Shrestha et al., 2015), has been applied to assess its forecast performance in a Canadian catchment. Raw QPFs obtained from two sources, Global Ensemble Forecasting System (GEFS) Reforecast 2 project, from the National Centers for Environmental Prediction, and Global Deterministic Forecast System (GDPS), from Environment and Climate Change Canada, are used in this study. The study period from January 2013 to December 2015 covered a major flood event in Calgary, Alberta, Canada. Post-processed results show that the RPP is able to remove the bias and reduce the errors of both GEFS and GDPS forecasts. Ensembles generated from the RPP reliably quantify the forecast uncertainty.

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.

Hydrologic drought of water year 2011 compared to four major drought periods of the 20th century in Oklahoma

USGS Publications Warehouse

Shivers, Molly J.; Andrews, William J.

2013-01-01

Water year 2011 (October 1, 2010, through September 30, 2011) was a year of hydrologic drought (based on streamflow) in Oklahoma and the second-driest year to date (based on precipitation) since 1925. Drought conditions worsened substantially in the summer, with the highest monthly average temperature record for all States being broken by Oklahoma in July (89.1 degrees Fahrenheit), June being the second hottest and August being the hottest on record for those months for the State since 1895. Drought conditions continued into the fall, with all of the State continuing to be in severe to exceptional drought through the end of September. In addition to effects on streamflow and reservoirs, the 2011 drought increased damage from wildfires, led to declarations of states of emergency, water-use restrictions, and outdoor burning bans; caused at least $2 billion of losses in the agricultural sector and higher prices for food and other agricultural products; caused losses of tourism and wildlife; reduced hydropower generation; and lowered groundwater levels in State aquifers. The U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, conducted an investigation to compare the severity of the 2011 drought with four previous major hydrologic drought periods during the 20th century – water years 1929–41, 1952–56, 1961–72, and 1976–81. The period of water years 1925–2011 was selected as the period of record because few continuous record streamflow-gaging stations existed before 1925, and gaps in time existed where no streamflow-gaging stations were operated before 1925. In water year 2011, statewide annual precipitation was the 2d lowest, statewide annual streamflow was 16th lowest, and statewide annual runoff was 42d lowest of those 87 years of record. Annual area-averaged precipitation totals by the nine National Weather Service climate divisions from water year 2011 were compared to those during four previous major hydrologic drought periods to show how precipitation deficits in Oklahoma varied by region. The nine climate divisions in Oklahoma had precipitation in water year 2011 ranging from 43 to 76 percent of normal annual precipitation, with the Northeast Climate Division having the closest to normal precipitation and the Southwest Climate Division having the greatest percentage of annual deficit. Based on precipitation amounts, water year 2011 ranked as the second driest of the 1925–2011 period, being exceeded only in one year of the 1952 to 1956 drought period. Regional streamflow patterns for water year 2011 indicate that streamflow in the Arkansas-White-Red water resources region, which includes all of Oklahoma, was relatively large, being only the 26th lowest since 1930, primarily because of normal or above-normal streamflow in the northern part of the region. Twelve long-term streamflow-gaging stations with periods of record ranging from 67 to 83 years were selected to show how streamflow deficits varied by region in Oklahoma. Statewide, streamflow in water year 2011 was greater than streamflows measured in years during the drought periods of 1929–41, 1952–56, 1961–72, and 1976–81. The hydrologic drought worsened going from the northeast toward the southwest in Oklahoma, ranging from 140 percent (above normal streamflow) in the northeast, to 13 percent of normal streamflow in southwestern Oklahoma. The relatively low streamflow in 2011 resulted in 83.3 percent of the statewide conservation storage being available at the end of the water year in major reservoirs, similar to conservation storage in the preceding severe drought year of 2006. The ranking of streamflow as the 16th smallest for the 1925–2011 period, despite precipitation being ranked the 2d smallest, may have been caused, in part, by the relatively large streamflow in northeastern Oklahoma during water year 2011.

Comparison of Strategies for Climate Change Adaptation of Water Supply and Flood Control Reservoirs

NASA Astrophysics Data System (ADS)

Ng, T. L.; Yang, P.; Bhushan, R.

2016-12-01

With climate change, streamflows are expected to become more fluctuating, with more frequent and intense floods and droughts. This complicates reservoir operation, which is highly sensitive to inflow variability. We make a comparative evaluation of three strategies for adapting reservoirs to climate-induced shifts in streamflow patterns. Specifically, we examine the effectiveness of (i) expanding the capacities of reservoirs by way of new off-stream reservoirs, (ii) introducing wastewater reclamation to augment supplies, and (iii) improving real-time streamflow forecasts for more optimal decision-making. The first two are hard strategies involving major infrastructure modifications, while the third a soft strategy entailing adjusting the system operation. A comprehensive side-by-side comparison of the three strategies is as yet lacking in the literature despite the many past studies investigating the strategies individually. To this end, we developed an adaptive forward-looking linear program that solves to yield the optimal decisions for the current time as a function of an ensemble forecast of future streamflows. Solving the model repeatedly on a rolling basis with regular updating of the streamflow forecast simulates the system behavior over the entire operating horizon. Results are generated for two hypothetical water supply and flood control reservoirs of differing inflows and demands. Preliminary findings suggest that of the three strategies, improving streamflow forecasts to be most effective in mitigating the effects of climate change. We also found that, in average terms, both additional reservoir capacity and wastewater reclamation have potential to reduce water shortage and downstream flooding. However, in the worst case, the potential of the former to reduce water shortage is limited, and similarly so the potential of the latter to reduce downstream 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.

Flooding and Atmospheric Rivers across the Western United States

NASA Astrophysics Data System (ADS)

Villarini, G.; Barth, N. A.; White, K. D.

2017-12-01

Flood frequency analysis across the western United States is complicated by annual peak flow records that frequently contain flows generated from distinctly different flood generating mechanisms. Among the different flood agents, atmospheric rivers (ARs) are responsible for large, regional scale floods. USGS streamgaging stations in the central Columbia River Basin in the Pacific Northwest, the Sierra Nevada, the central and southern California coast, and central Arizona show a mixture of 30-70% AR-generated flood peaks among the complete period of record. Bulletin17B and its proposed update (Draft Bulletin 17C) continue to recognize difficulties in determining flood frequency estimates among streamflow records that contain flood peaks coming from different flood-generating mechanisms, as is the case in the western United States. They recommend developing separate frequency curves when the hydrometeorologic mechanisms that generated the annual peak flows can be separated into distinct subpopulations. Yet challenges arise when trying to consistently quantify the physical (hydrometeorologic) processes that generated the observed flows, and even more when trying to account for them in flood frequency estimation. This study provides a general statistical framework to perform a process-driven flood frequency analysis using a weighted mixed population approach, highlighting the role that ARs play on the flood peak distribution.

Hurricane impacts on a pair of coastal forested watersheds: implications of selective hurricane damage to forest structure and streamflow dynamics

Treesearch

A.D. Jayakaran; T.M. Williams; H. Ssegane; D.M. Amatya; B. Song; C.C. Trettin

2014-01-01

Hurricanes are infrequent but influential disruptors of ecosystem processes in the southeastern Atlantic and Gulf coasts. Every southeastern forested wetland has the potential to be struck by a tropical cyclone. We examined the impact of Hurricane Hugo on two paired coastal South Carolina watersheds in terms of streamflow and vegetation dynamics, both before and after...

Simulating the influence of snow surface processes on soil moisture dynamics and streamflow generation in an alpine catchment

NASA Astrophysics Data System (ADS)

Wever, Nander; Comola, Francesco; Bavay, Mathias; Lehning, Michael

2017-08-01

The assessment of flood risks in alpine, snow-covered catchments requires an understanding of the linkage between the snow cover, soil and discharge in the stream network. Here, we apply the comprehensive, distributed model Alpine3D to investigate the role of soil moisture in the predisposition of the Dischma catchment in Switzerland to high flows from rainfall and snowmelt. The recently updated soil module of the physics-based multilayer snow cover model SNOWPACK, which solves the surface energy and mass balance in Alpine3D, is verified against soil moisture measurements at seven sites and various depths inside and in close proximity to the Dischma catchment. Measurements and simulations in such terrain are difficult and consequently, soil moisture was simulated with varying degrees of success. Differences between simulated and measured soil moisture mainly arise from an overestimation of soil freezing and an absence of a groundwater description in the Alpine3D model. Both were found to have an influence in the soil moisture measurements. Using the Alpine3D simulation as the surface scheme for a spatially explicit hydrologic response model using a travel time distribution approach for interflow and baseflow, streamflow simulations were performed for the discharge from the catchment. The streamflow simulations provided a closer agreement with observed streamflow when driving the hydrologic response model with soil water fluxes at 30 cm depth in the Alpine3D model. Performance decreased when using the 2 cm soil water flux, thereby mostly ignoring soil processes. This illustrates that the role of soil moisture is important to take into account when understanding the relationship between both snowpack runoff and rainfall and catchment discharge in high alpine terrain. However, using the soil water flux at 60 cm depth to drive the hydrologic response model also decreased its performance, indicating that an optimal soil depth to include in surface simulations exists and that the runoff dynamics are controlled by only a shallow soil layer. Runoff coefficients (i.e. ratio of rainfall over discharge) based on measurements for high rainfall and snowmelt events were found to be dependent on the simulated initial soil moisture state at the onset of an event, further illustrating the important role of soil moisture for the hydrological processes in the catchment. The runoff coefficients using simulated discharge were found to reproduce this dependency, which shows that the Alpine3D model framework can be successfully applied to assess the predisposition of the catchment to flood risks from both snowmelt and rainfall events.

Searching for signposts: Adaptive planning thresholds in long-term water supply projections for the Western U.S.

NASA Astrophysics Data System (ADS)

Robinson, B.; Herman, J. D.

2017-12-01

Long-term water supply planning is challenged by highly uncertain streamflow projections across climate models and emissions scenarios. Recent studies have devised infrastructure and policy responses that can withstand or adapt to an ensemble of scenarios, particularly those outside the envelope of historical variability. An important aspect of this process is whether the proposed thresholds for adaptation (i.e., observations that trigger a response) truly represent a trend toward future change. Here we propose an approach to connect observations of annual mean streamflow with long-term projections by filtering GCM-based streamflow ensembles. Visualizations are developed to investigate whether observed changes in mean annual streamflow can be linked to projected changes in end-of-century mean and variance relative to the full ensemble. A key focus is identifying thresholds that point to significant long-term changes in the distribution of streamflow (+/- 20% or greater) as early as possible. The analysis is performed on 87 sites in the Western United States, using streamflow ensembles through 2100 from a recent study by the U.S. Bureau of Reclamation. Results focus on three primary questions: (1) how many years of observed data are needed to identify the most extreme scenarios, and by what year can they be identified? (2) are these features different between sites? and (3) using this analysis, do observed flows to date at each site point to significant long-term changes? This study addresses the challenge of severe uncertainty in long-term streamflow projections by identifying key thresholds that can be observed to support water supply planning.

Changes toward earlier streamflow timing across western North America

USGS Publications Warehouse

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.

An assessment of the tracer-based approach to quantifying groundwater contributions to streamflow

NASA Astrophysics Data System (ADS)

Jones, J. P.; Sudicky, E. A.; Brookfield, A. E.; Park, Y.-J.

2006-02-01

The use of conservative geochemical and isotopic tracers along with mass balance equations to determine the pre-event groundwater contributions to streamflow during a rainfall event is widely used for hydrograph separation; however, aspects related to the influence of surface and subsurface mixing processes on the estimates of the pre-event contribution remain poorly understood. Moreover, the lack of a precise definition of "pre-event" versus "event" contributions on the one hand and "old" versus "new" water components on the other hand has seemingly led to confusion within the hydrologic community about the role of Darcian-based groundwater flow during a storm event. In this work, a fully integrated surface and subsurface flow and solute transport model is used to analyze flow system dynamics during a storm event, concomitantly with advective-dispersive tracer transport, and to investigate the role of hydrodynamic mixing processes on the estimates of the pre-event component. A number of numerical experiments are presented, including an analysis of a controlled rainfall-runoff experiment, that compare the computed Darcian-based groundwater fluxes contributing to streamflow during a rainfall event with estimates of these contributions based on a tracer-based separation. It is shown that hydrodynamic mixing processes can dramatically influence estimates of the pre-event water contribution estimated by a tracer-based separation. Specifically, it is demonstrated that the actual amount of bulk flowing groundwater contributing to streamflow may be much smaller than the quantity indirectly estimated from a separation based on tracer mass balances, even if the mixing processes are weak.

Use of flow-normalization to evaluate nutrient concentration and flux changes in Lake Champlain tributaries, 1990-2009

USGS Publications Warehouse

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.

Seasonal streamflow prediction using ensemble streamflow prediction technique for the Rangitata and Waitaki River basins on the South Island of New Zealand

NASA Astrophysics Data System (ADS)

Singh, Shailesh Kumar

2014-05-01

Streamflow forecasts are essential for making critical decision for optimal allocation of water supplies for various demands that include irrigation for agriculture, habitat for fisheries, hydropower production and flood warning. The major objective of this study is to explore the Ensemble Streamflow Prediction (ESP) based forecast in New Zealand catchments and to highlights the present capability of seasonal flow forecasting of National Institute of Water and Atmospheric Research (NIWA). In this study a probabilistic forecast framework for ESP is presented. The basic assumption in ESP is that future weather pattern were experienced historically. Hence, past forcing data can be used with current initial condition to generate an ensemble of prediction. Small differences in initial conditions can result in large difference in the forecast. The initial state of catchment can be obtained by continuously running the model till current time and use this initial state with past forcing data to generate ensemble of flow for future. The approach taken here is to run TopNet hydrological models with a range of past forcing data (precipitation, temperature etc.) with current initial conditions. The collection of runs is called the ensemble. ESP give probabilistic forecasts for flow. From ensemble members the probability distributions can be derived. The probability distributions capture part of the intrinsic uncertainty in weather or climate. An ensemble stream flow prediction which provide probabilistic hydrological forecast with lead time up to 3 months is presented for Rangitata, Ahuriri, and Hooker and Jollie rivers in South Island of New Zealand. ESP based seasonal forecast have better skill than climatology. This system can provide better over all information for holistic water resource management.

Thermal effects of dams in the Willamette River basin, Oregon

USGS Publications Warehouse

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

RWater - A Novel Cyber-enabled Data-driven Educational Tool for Interpreting and Modeling Hydrologic Processes

NASA Astrophysics Data System (ADS)

Rajib, M. A.; Merwade, V.; Zhao, L.; Song, C.

2014-12-01

Explaining the complex cause-and-effect relationships in hydrologic cycle can often be challenging in a classroom with the use of traditional teaching approaches. With the availability of observed rainfall, streamflow and other hydrology data on the internet, it is possible to provide the necessary tools to students to explore these relationships and enhance their learning experience. From this perspective, a new online educational tool, called RWater, is developed using Purdue University's HUBzero technology. RWater's unique features include: (i) its accessibility including the R software from any java supported web browser; (ii) no installation of any software on user's computer; (iii) all the work and resulting data are stored in user's working directory on RWater server; and (iv) no prior programming experience with R software is necessary. In its current version, RWater can dynamically extract streamflow data from any USGS gaging station without any need for post-processing for use in the educational modules. By following data-driven modules, students can write small scripts in R and thereby create visualizations to identify the effect of rainfall distribution and watershed characteristics on runoff generation, investigate the impacts of landuse and climate change on streamflow, and explore the changes in extreme hydrologic events in actual locations. Each module contains relevant definitions, instructions on data extraction and coding, as well as conceptual questions based on the possible analyses which the students would perform. In order to assess its suitability in classroom implementation, and to evaluate users' perception over its utility, the current version of RWater has been tested with three different groups: (i) high school students, (ii) middle and high school teachers; and (iii) upper undergraduate/graduate students. The survey results from these trials suggest that the RWater has potential to improve students' understanding on various relationships in hydrologic cycle, leading towards effective dissemination of hydrology education ranging from K-12 to the graduate level. RWater is a publicly available for use at: https://mygeohub.org/tools/rwater.

Testing resiliency of hydrologic dynamics of a paired forested watershed after a hurricane in Atlantic coastal plain using long-term data

Treesearch

Devendra Amatya; Herbert Ssegane; Charles Andy Harrison; Carl Trettin

2016-01-01

Hurricanes are infrequent but influential disruptors of ecosystem processes, including streamflow and evapotranspiration dynamics in the southeastern Atlantic and Gulf coasts. However, literature on hurricane effects on long-term streamflow dynamics is lacking in this highly urbanizing region characterized by a poorly drained low-gradient forested landscape.

Development of a precipitation-runoff model to simulate unregulated streamflow in the South Fork Flathead River Basin, Montana

USGS Publications Warehouse

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

Impacts of Recent Wetting on Snow Processes and Runoff Generation in a Terminal Lake Basin, Devils Lake, North Dakota.

NASA Astrophysics Data System (ADS)

Mahmood, T. H.; Van Hoy, D.

2016-12-01

The Devils Lake Basin, only terminal lake basin in North America, drains to a terminal lake called Devils Lake. Terminal lakes are susceptible to climate and land use changes as their water levels fluctuate to these changes. The streamflow from the headwater catchments of the Devils Lake basin exerts a strong control on the water level of the lake. Since, the mid-1980s, the Devils Lake Basin as well as other basins in the northern Great Plains have faced a large and abrupt surge in precipitation regime resulting in a series of wetter climatic condition and flooding around the Devils Lake area. Nevertheless, the impacts of the recent wetting on snow processes such as snow accumulations, blowing snow transport, in-transit sublimation, frozen soil infiltration and snowmelt runoff generations in a headwater catchment of the Devils Lake basin are poorly understood. In this study, I utilize a physically-based, distributed cold regions hydrological model to simulate the hydrological responses in the Mauvais Coulee basin that drains to Devils Lake. The Mauvais Coulee basin ( 1072 km2), located in the north-central North Dakota, is set in a gently rolling landscape with low relief ( 220 m) and an average elevation of 500 m. Major land covers are forest areas in turtle mountains ( 10%) and crops ( 86%), with wheat ( 25%) and canola ( 20%) as the major crops. The model set up includes ten sub-basins, each of which is divided into several hydrological response units (HRUs): riparian forest, river channel, reservoir, wheat, canola, other crops, and marsh. The model is parameterized using local and regional measurements and the findings from previous scientific studies. The model is evaluated against streamflow observations at the Mauvais Coulee gauge (USGS) during 1994-2013 periods using multiple performance criteria. Finally, the impacts of recent increases in precipitation on hydrologic responses are investigated using modeled hydrologic processes.

The Water Erosion Prediction Project (WEPP) model for saturation excess conditions: application to an agricultural and a forested watershed.

NASA Astrophysics Data System (ADS)

Crabtree, B.; Brooks, E.; Ostrowski, K.; Elliot, W. J.; Boll, J.

2006-12-01

We incorporated saturation excess overland flow processes in the Water Erosion Prediction Project (WEPP) model for the evaluation of human disturbances in watersheds. In this presentation, we present results of the modified WEPP model to two watersheds: an agricultural watershed with mixed land use, and a forested watershed. The agricultural watershed is Paradise Creek, an intensively monitored watershed with continuous climate, flow and sediment data collection at multiple locations. Restoration efforts in Paradise Creek watershed include changing to minimal tillage or no-tillage sytems, and implementation of structural practices. The forested watershed is the 28 km2 Mica Creek Experimental Watershed (MCEW) where disturbances include clear and partial cutting, and road building. The MCEW has a nested study design, which allows for the analysis of cumulative effects as well as the traditional comparison of treatment versus control. Mica Creek watershed is a high elevation watershed where streamflow is generated mostly by snowmelt. Treatments include road building in 1997, and clearcut and partial-cut logging in 2001. Our results include the simulation of streamflow and sediment delivery at multiple locations within each watershed, and evaluation of the human disturbances.

Overview of ground-water recharge study sites

USGS Publications Warehouse

Constantz, Jim; Adams, Kelsey S.; Stonestrom, David A.; Stonestrom, David A.; Constantz, Jim; Ferré, Ty P.A.; Leake, Stanley A.

2007-01-01

Multiyear studies were done to examine meteorologic and hydrogeologic controls on ephemeral streamflow and focused ground-water recharge at eight sites across the arid and semiarid southwestern United States. Campaigns of intensive data collection were conducted in the Great Basin, Mojave Desert, Sonoran Desert, Rio Grande Rift, and Colorado Plateau physiographic areas. During the study period (1997 to 2002), the southwestern region went from wetter than normal conditions associated with a strong El Niño climatic pattern (1997–1998) to drier than normal conditions associated with a La Niña climatic pattern marked by unprecedented warmth in the western tropical Pacific and Indian Oceans (1998–2002). The strong El Niño conditions roughly doubled precipitation at the Great Basin, Mojave Desert, and Colorado Plateau study sites. Precipitation at all sites trended generally lower, producing moderate- to severe-drought conditions by the end of the study. Streamflow in regional rivers indicated diminishing ground-water recharge conditions, with annual-flow volumes declining to 10–46 percent of their respective long-term averages by 2002. Local streamflows showed higher variability, reflecting smaller scales of integration (in time and space) of the study-site watersheds. By the end of the study, extended periods (9–15 months) of zero or negligible flow were observed at half the sites. Summer monsoonal rains generated the majority of streamflow and associated recharge in the Sonoran Desert sites and the more southerly Rio Grande Rift site, whereas winter storms and spring snowmelt dominated the northern and westernmost sites. Proximity to moisture sources (primarily the Pacific Ocean and Gulf of California) and meteorologic fluctuations, in concert with orography, largely control the generation of focused ground-water recharge from ephemeral streamflow, although other factors (geology, soil, and vegetation) also are important. Watershed area correlated weakly with focused infiltration volumes, the latter providing an upper bound on associated ground-water recharge. Estimates of annual focused infiltration for the research sites ranged from about 105 to 107 cubic meters from contributing areas that ranged from 26 to 2,260 square kilometers.

Hydrologic Drought of Water Year 2006 Compared with Four Major Drought Periods of the 20th Century in Oklahoma

USGS Publications Warehouse

Tortorelli, Robert L.

2008-01-01

Water Year 2006 (October 1, 2005, to September 30, 2006) was a year of extreme hydrologic drought and the driest year in the recent 2002-2006 drought in Oklahoma. The severity of this recent drought can be evaluated by comparing it with four previous major hydrologic droughts, water years 1929-41, 1952-56, 1961-72, and 1976-81. The U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, completed an investigation to summarize the Water Year 2006 hydrologic drought and compare it to the four previous major hydrologic droughts in the 20th century. The period of water years 1925-2006 was selected as the period of record because before 1925 few continuous record streamflow-gaging sites existed and gaps existed where no streamflow-gaging sites were operated. Statewide annual precipitation in Water Year 2006 was second driest and statewide annual runoff in Water Year 2006 was sixth driest in the 82 years of record. Annual area-averaged precipitation totals by the nine National Weather Service Climate Divisions from Water Year 2006 are compared to those during four previous major hydrologic droughts to show how rainfall deficits in Oklahoma varied by region. Only two of the nine climate divisions, Climate Division 1 Panhandle and Climate Division 4 West Central, had minor rainfall deficits, while the rest of the climate divisions had severe rainfall deficits in Water Year 2006 ranging from only 65 to 73 percent of normal annual precipitation. Regional streamflow patterns for Water Year 2006 indicate that Oklahoma was part of the regionwide below-normal streamflow conditions for Arkansas-White-Red River Basin, the sixth driest since 1930. The percentage of long-term stations in Oklahoma (with at least 30 years of record) having below-normal streamflow reached 80 to 85 percent for some days in August and November 2006. Twelve long-term streamflow-gaging sites with periods of record ranging from 62 to 78 years were selected to show how streamflow deficits varied by region. The hydrologic drought worsened going from north to south in Oklahoma, ranging from 45 percent in the north, to just 14 percent in east-central Oklahoma, and 20 percent of normal annual streamflow in the southwest. The low streamflows resulted in only 86.3 percent of the statewide conservation storage available at the end of the water year in major reservoirs, and 7 to 47 percent of hydroelectric power generation at sites in Oklahoma in Calendar Year 2005.

Debris-flow generation from recently burned watersheds

USGS Publications Warehouse

Cannon, S.H.

2001-01-01

Evaluation of the erosional response of 95 recently burned drainage basins in Colorado, New Mexico and southern California to storm rainfall provides information on the conditions that result in fire-related debris flows. Debris flows were produced from only 37 of 95 (~40 percent) basins examined; the remaining basins produced either sediment-laden streamflow or no discernable response. Debris flows were thus not the prevalent response of the burned basins. The debris flows that did occur were most frequently the initial response to significant rainfall events. Although some hillslopes continued to erode and supply material to channels in response to subsequent rainfall events, debris flows were produced from only one burned basin following the initial erosive event. Within individual basins, debris flows initiated through both runoff and infiltration-triggered processes. The fact that not all burned basins produced debris flows suggests that specific geologic and geomorphic conditions may control the generation of fire-related debris flows. The factors that best distinguish between debris-flow producing drainages and those that produced sediment-laden streamflow are drainage-basin morphology and lithology, and the presence or absence of water-repellent soils. Basins underlain by sedimentary rocks were most likely to produce debris flows that contain large material, and sand- and gravel-dominated flows were generated primarily from terrain underlain by decomposed granite. Basin-area and relief thresholds define the morphologic conditions under which both types of debris flows occur. Debris flows containing large material are more likely to be produced from basins without water-repellent soils than from basins with water repellency. The occurrence of sand-and gravel-dominated debris flows depends on the presence of water-repellent soils.

Seasonal Prediction of Taiwan's Streamflow Using Teleconnection Patterns

NASA Astrophysics Data System (ADS)

Chen, Chia-Jeng; Lee, Tsung-Yu

2017-04-01

Seasonal streamflow as an integrated response to complex hydro-climatic processes can be subject to activity of prevailing weather systems potentially modulated by large-scale climate oscillations (e.g., El Niño-Southern Oscillation, ENSO). To develop a seamless seasonal forecasting system in Taiwan, this study assesses how significant Taiwan's precipitation and streamflow in different seasons correlate with selected teleconnection patterns. Long-term precipitation and streamflow data in three major precipitation seasons, namely the spring rains (February to April), Mei-Yu (May and June), and typhoon (July to September) seasons, are derived at 28 upstream and 13 downstream catchments in Taiwan. The three seasons depict a complete wet period of Taiwan as well as many regions bearing similar climatic conditions in East Asia. Lagged correlation analysis is then performed to investigate how the precipitation and streamflow data correlate with predominant teleconnection indices at varied lead times. Teleconnection indices are selected only if they show certain linkage with weather systems and activity in the three seasons based on previous literature. For instance, the ENSO and Quasi-Biennial Oscillation, proven to influence East Asian climate across seasons and summer typhoon activity, respectively, are included in the list of climate indices for correlation analysis. Significant correlations found between Taiwan's precipitation and streamflow and teleconnection indices are further examined by a climate regime shift (CRS) test to identify any abrupt changes in the correlations. The understanding of existing CRS is useful for informing the forecasting system of the changes in the predictor-predictand relationship. To evaluate prediction skill in the three seasons and skill differences between precipitation and streamflow, hindcasting experiments of precipitation and streamflow are conducted using stepwise linear regression models. Discussion and suggestions for coping with extreme events in empirical seasonal predictions are also carried out. Findings from this work will contribute to the development of an integrated water resources planning and management system.

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

Wavelet-based time series bootstrap model for multidecadal streamflow simulation using climate indicators

NASA Astrophysics Data System (ADS)

Erkyihun, Solomon Tassew; Rajagopalan, Balaji; Zagona, Edith; Lall, Upmanu; Nowak, Kenneth

2016-05-01

A model to generate stochastic streamflow projections conditioned on quasi-oscillatory climate indices such as Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO) is presented. Recognizing that each climate index has underlying band-limited components that contribute most of the energy of the signals, we first pursue a wavelet decomposition of the signals to identify and reconstruct these features from annually resolved historical data and proxy based paleoreconstructions of each climate index covering the period from 1650 to 2012. A K-Nearest Neighbor block bootstrap approach is then developed to simulate the total signal of each of these climate index series while preserving its time-frequency structure and marginal distributions. Finally, given the simulated climate signal time series, a K-Nearest Neighbor bootstrap is used to simulate annual streamflow series conditional on the joint state space defined by the simulated climate index for each year. We demonstrate this method by applying it to simulation of streamflow at Lees Ferry gauge on the Colorado River using indices of two large scale climate forcings: Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO), which are known to modulate the Colorado River Basin (CRB) hydrology at multidecadal time scales. Skill in stochastic simulation of multidecadal projections of flow using this approach is demonstrated.

Climate change streamflow scenarios designed for critical period water resources planning studies

NASA Astrophysics Data System (ADS)

Hamlet, A. F.; Snover, A. K.; Lettenmaier, D. P.

2003-04-01

Long-range water planning in the United States is usually conducted by individual water management agencies using a critical period planning exercise based on a particular period of the observed streamflow record and a suite of internally-developed simulation tools representing the water system. In the context of planning for climate change, such an approach is flawed in that it assumes that the future climate will be like the historic record. Although more sophisticated planning methods will probably be required as time goes on, a short term strategy for incorporating climate uncertainty into long-range water planning as soon as possible is to create alternate inputs to existing planning methods that account for climate uncertainty as it affects both supply and demand. We describe a straight-forward technique for constructing streamflow scenarios based on the historic record that include the broad-based effects of changed regional climate simulated by several global climate models (GCMs). The streamflow scenarios are based on hydrologic simulations driven by historic climate data perturbed according to regional climate signals from four GCMs using the simple "delta" method. Further data processing then removes systematic hydrologic model bias using a quantile-based bias correction scheme, and lastly, the effects of random errors in the raw hydrologic simulations are removed. These techniques produce streamflow scenarios that are consistent in time and space with the historic streamflow record while incorporating fundamental changes in temperature and precipitation from the GCM scenarios. Planning model simulations based on these climate change streamflow scenarios can therefore be compared directly to planning model simulations based on the historic record of streamflows to help planners understand the potential impacts of climate uncertainty. The methods are currently being tested and refined in two large-scale planning exercises currently being conducted in the Pacific Northwest (PNW) region of the US, and the resulting streamflow scenarios will be made freely available on the internet for a large number of sites in the PNW to help defray the costs of including climate change information in other studies.

Terrain and subsurface influences on runoff generation in a steep, deep, highly weathered system

NASA Astrophysics Data System (ADS)

Mallard, J. M.; McGlynn, B. L.; Richter, D. D., Jr.

2017-12-01

Our understanding of runoff generation in regions characterized by deep, highly weathered soils is incomplete, despite the prevalence occupation of these landscapes worldwide. To address this, we instrumented a first-order watershed in the Piedmont of South Carolina, USA, a region that extends east of the Appalachians from Maryland to Alabama, and home to some of the most rapid population growth in the country. Although regionally the relief is modest, the landscape is often highly dissected and local slopes can be steep and highly varied. The typical soils of the region are kaolinite dominated ultisols, with hydrologic properties controlled by argillic Bt horizons, often with >50% clay-size fraction. The humid subtropical climate creates relatively consistent precipitation intra-annually and seasonally variable energy availability. Consequently, the mixed deciduous and coniferous tree cover creates a strong evapotranspiration-mediated hydrologic dynamic. While moist soils and extended stream networks are typical from late fall through spring, relatively dry soils and contracting stream networks emerge in the summer and early fall. Here, we seek to elucidate the relative influence of the vertical soil and spatial terrain structure of this region on watershed hillslope hydrology and subsequent runoff generation. We installed a network of nested, shallow groundwater wells and soil water content probes within an ephemeral to first-order watershed to continuously measure soil and groundwater dynamics across soil horizons and landscape position. We also recorded local precipitation and discharge from this watershed. Most landscape positions exhibited minimal water table response to precipitation throughout dry summer periods, with infrequently observed responses rarely coincident with streamflow generation. In contrast, during the wetter late fall through early spring period, streamflow was driven by the interaction between transient perched water tables and topographically mediated redistribution of shallow groundwater downslope. Our findings suggest that understanding streamflow generation in regions possessing both complex terrain and complex vertical soil structure requires synchronous characterization of terrain mediated water redistribution and subsurface soil hydrology.

A historical perspective on precipitation, drought severity, and streamflow in Texas during 1951-56 and 2011

USGS Publications Warehouse

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.

Temporal Differences in the Hydrologic Regime of the Lower Platte River, Nebraska, 1895-2006

USGS Publications Warehouse

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

Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: Chapter E in Montana StreamStats

USGS Publications Warehouse

McCarthy, Peter M.

2016-04-05

Chapter E of this Scientific Investigations Report documents results from a study by the U.S. Geological Survey, in cooperation with the Montana Department of Environmental Quality and the Montana Department of Natural Resources and Conservation, to provide an update of statewide streamflow characteristics based on data through water year 2009 for streamflow-gaging stations in or near Montana. Streamflow characteristics are presented for 408 streamflow-gaging stations in Montana and adjacent areas having 10 or more years of record. Data include the magnitude and probability of annual low and high streamflow, the magnitude and probability of low streamflow for three seasons (March–June, July–October, and November–February), streamflow duration statistics for monthly and annual periods, and mean streamflows for monthly and annual periods. Streamflow is considered to be regulated at streamflow-gaging stations where dams or other large-scale human modifications affect 20 percent or more of the contributing drainage basin. Separate streamflow characteristics are presented for the unregulated and regulated periods of record for streamflow-gaging stations with sufficient data.

Low-Flow Characteristics and Regionalization of Low-Flow Characteristics for Selected Streams in Arkansas

USGS Publications Warehouse

Funkhouser, Jaysson E.; Eng, Ken; Moix, Matthew W.

2008-01-01

Water use in Arkansas has increased dramatically in recent years. Since 1990, the use of water for all purposes except power generation has increased 53 percent (4,004 cubic feet per second in 1990 to 6,113 cubic feet per second in 2005). The biggest users are agriculture (90 percent), municipal water supply (4 percent) and industrial supply (2 percent). As the population of the State continues to grow, so does the demand for the State's water resources. The low-flow characteristics of a stream ultimately affect its utilization by humans. Specific information on the low-flow characteristics of streams is essential to State water-management agencies such as the Arkansas Department of Environmental Quality, the Arkansas Natural Resources Commission, and the Arkansas Game and Fish Commission when dealing with problems related to irrigation, municipal and industrial water supplies, fish and wildlife conservation, and dilution of waste. Low-flow frequency data are of particular value to management agencies responsible for the development and management of the State's water resources. This report contains the low-flow characteristics for 70 active continuous-streamflow record gaging stations, 59 inactive continuous-streamflow record stations, and 101 partial-record gaging stations. These characteristics are the annual 7-day, 10-year low flow and the annual 7-day, 2-year low flow, and the seasonal, bimonthly, and monthly 7-day, 10-year low flow for the 129 active and inactive continuous-streamflow record and 101 partial-record gaging stations. Low-flow characteristics were computed on the basis of streamflow data for the period of record through September 2005 for the continuous-streamflow record and partial-record streamflow gaging stations. The low-flow characteristics of these continuous- and partial-record streamflow gaging stations were utilized in a regional regression analysis to produce equations for estimating the annual, seasonal, bimonthly, and monthly (November through April) 7-day, 10-year low flows and the annual 7-day, 2-year low flow for ungaged streams in the western two-thirds of Arkansas.

Evaluation of uncertainty in capturing the spatial variability and magnitudes of extreme hydrological events for the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Kusangaya, Samuel; Warburton Toucher, Michele L.; van Garderen, Emma Archer

2018-02-01

Downscaled General Circulation Models (GCMs) output are used to forecast climate change and provide information used as input for hydrological modelling. Given that our understanding of climate change points towards an increasing frequency, timing and intensity of extreme hydrological events, there is therefore the need to assess the ability of downscaled GCMs to capture these extreme hydrological events. Extreme hydrological events play a significant role in regulating the structure and function of rivers and associated ecosystems. In this study, the Indicators of Hydrologic Alteration (IHA) method was adapted to assess the ability of simulated streamflow (using downscaled GCMs (dGCMs)) in capturing extreme river dynamics (high and low flows), as compared to streamflow simulated using historical climate data from 1960 to 2000. The ACRU hydrological model was used for simulating streamflow for the 13 water management units of the uMngeni Catchment, South Africa. Statistically downscaled climate models obtained from the Climate System Analysis Group at the University of Cape Town were used as input for the ACRU Model. Results indicated that, high flows and extreme high flows (one in ten year high flows/large flood events) were poorly represented both in terms of timing, frequency and magnitude. Simulated streamflow using dGCMs data also captures more low flows and extreme low flows (one in ten year lowest flows) than that captured in streamflow simulated using historical climate data. The overall conclusion was that although dGCMs output can reasonably be used to simulate overall streamflow, it performs poorly when simulating extreme high and low flows. Streamflow simulation from dGCMs must thus be used with caution in hydrological applications, particularly for design hydrology, as extreme high and low flows are still poorly represented. This, arguably calls for the further improvement of downscaling techniques in order to generate climate data more relevant and useful for hydrological applications such as in design hydrology. Nevertheless, the availability of downscaled climatic output provide the potential of exploring climate model uncertainties in different hydro climatic regions at local scales where forcing data is often less accessible but more accurate at finer spatial scales and with adequate spatial detail.

Effect of initial conditions of a catchment on seasonal streamflow prediction using ensemble streamflow prediction (ESP) technique for the Rangitata and Waitaki River basins on the South Island of New Zealand

NASA Astrophysics Data System (ADS)

Singh, Shailesh Kumar; Zammit, Christian; Hreinsson, Einar; Woods, Ross; Clark, Martyn; Hamlet, Alan

2013-04-01

Increased access to water is a key pillar of the New Zealand government plan for economic growths. Variable climatic conditions coupled with market drivers and increased demand on water resource result in critical decision made by water managers based on climate and streamflow forecast. Because many of these decisions have serious economic implications, accurate forecast of climate and streamflow are of paramount importance (eg irrigated agriculture and electricity generation). New Zealand currently does not have a centralized, comprehensive, and state-of-the-art system in place for providing operational seasonal to interannual streamflow forecasts to guide water resources management decisions. As a pilot effort, we implement and evaluate an experimental ensemble streamflow forecasting system for the Waitaki and Rangitata River basins on New Zealand's South Island using a hydrologic simulation model (TopNet) and the familiar ensemble streamflow prediction (ESP) paradigm for estimating forecast uncertainty. To provide a comprehensive database for evaluation of the forecasting system, first a set of retrospective model states simulated by the hydrologic model on the first day of each month were archived from 1972-2009. Then, using the hydrologic simulation model, each of these historical model states was paired with the retrospective temperature and precipitation time series from each historical water year to create a database of retrospective hindcasts. Using the resulting database, the relative importance of initial state variables (such as soil moisture and snowpack) as fundamental drivers of uncertainties in forecasts were evaluated for different seasons and lead times. The analysis indicate that the sensitivity of flow forecast to initial condition uncertainty is depend on the hydrological regime and season of forecast. However initial conditions do not have a large impact on seasonal flow uncertainties for snow dominated catchments. Further analysis indicates that this result is valid when the hindcast database is conditioned by ENSO classification. As a result hydrological forecasts based on ESP technique, where present initial conditions with histological forcing data are used may be plausible for New Zealand catchments.

Translating Climate Projections for Bridge Engineering

NASA Astrophysics Data System (ADS)

Anderson, C.; Takle, E. S.; Krajewski, W.; Mantilla, R.; Quintero, F.

2015-12-01

A bridge vulnerability pilot study was conducted by Iowa Department of Transportation (IADOT) as one of nineteen pilots supported by the Federal Highway Administration Climate Change Resilience Pilots. Our pilot study team consisted of the IADOT senior bridge engineer who is the preliminary design section leader as well as climate and hydrological scientists. The pilot project culminated in a visual graphic designed by the bridge engineer (Figure 1), and an evaluation framework for bridge engineering design. The framework has four stages. The first two stages evaluate the spatial and temporal resolution needed in climate projection data in order to be suitable for input to a hydrology model. The framework separates streamflow simulation error into errors from the streamflow model and from the coarseness of input weather data series. In the final two stages, the framework evaluates credibility of climate projection streamflow simulations. Using an empirically downscaled data set, projection streamflow is generated. Error is computed in two time frames: the training period of the empirical downscaling methodology, and an out-of-sample period. If large errors in projection streamflow were observed during the training period, it would indicate low accuracy and, therefore, low credibility. If large errors in streamflow were observed during the out-of-sample period, it would mean the approach may not include some causes of change and, therefore, the climate projections would have limited credibility for setting expectations for changes. We address uncertainty with confidence intervals on quantiles of streamflow discharge. The results show the 95% confidence intervals have significant overlap. Nevertheless, the use of confidence intervals enabled engineering judgement. In our discussions, we noted the consistency in direction of change across basins, though the flood mechanism was different across basins, and the high bound of bridge lifetime period quantiles exceeded that of the historical period. This suggested the change was not isolated, and it systemically altered the risk profile. One suggestion to incorporate engineering judgement was to consider degrees of vulnerability using the median discharge of the historical period and the upper bound discharge for the bridge lifetime period.

Global analysis of seasonal streamflow predictability using an ensemble prediction system and observations from 6192 small catchments worldwide

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.

Short-term streamflow forecasting with global climate change implications A comparative study between genetic programming and neural network models

NASA Astrophysics Data System (ADS)

Makkeasorn, A.; Chang, N. B.; Zhou, X.

2008-05-01

SummarySustainable water resources management is a critically important priority across the globe. While water scarcity limits the uses of water in many ways, floods may also result in property damages and the loss of life. To more efficiently use the limited amount of water under the changing world or to resourcefully provide adequate time for flood warning, the issues have led us to seek advanced techniques for improving streamflow forecasting on a short-term basis. This study emphasizes the inclusion of sea surface temperature (SST) in addition to the spatio-temporal rainfall distribution via the Next Generation Radar (NEXRAD), meteorological data via local weather stations, and historical stream data via USGS gage stations to collectively forecast discharges in a semi-arid watershed in south Texas. Two types of artificial intelligence models, including genetic programming (GP) and neural network (NN) models, were employed comparatively. Four numerical evaluators were used to evaluate the validity of a suite of forecasting models. Research findings indicate that GP-derived streamflow forecasting models were generally favored in the assessment in which both SST and meteorological data significantly improve the accuracy of forecasting. Among several scenarios, NEXRAD rainfall data were proven its most effectiveness for a 3-day forecast, and SST Gulf-to-Atlantic index shows larger impacts than the SST Gulf-to-Pacific index on the streamflow forecasts. The most forward looking GP-derived models can even perform a 30-day streamflow forecast ahead of time with an r-square of 0.84 and RMS error 5.4 in our study.

Simulation of streamflow and sediment transport in two surface-coal-mined basins in Fayette County, Pennsylvania

USGS Publications Warehouse

Sams, J. I.; Witt, E. C.

1995-01-01

The Hydrological Simulation Program - Fortran (HSPF) was used to simulate streamflow and sediment transport in two surface-mined basins of Fayette County, Pa. Hydrologic data from the Stony Fork Basin (0.93 square miles) was used to calibrate HSPF parameters. The calibrated parameters were applied to an HSPF model of the Poplar Run Basin (8.83 square miles) to evaluate the transfer value of model parameters. The results of this investigation provide information to the Pennsylvania Department of Environmental Resources, Bureau of Mining and Reclamation, regarding the value of the simulated hydrologic data for use in cumulative hydrologic-impact assessments of surface-mined basins. The calibration period was October 1, 1985, through September 30, 1988 (water years 1986-88). The simulated data were representative of the observed data from the Stony Fork Basin. Mean simulated streamflow was 1.64 cubic feet per second compared to measured streamflow of 1.58 cubic feet per second for the 3-year period. The difference between the observed and simulated peak stormflow ranged from 4.0 to 59.7 percent for 12 storms. The simulated sediment load for the 1987 water year was 127.14 tons (0.21 ton per acre), which compares to a measured sediment load of 147.09 tons (0.25 ton per acre). The total simulated suspended-sediment load for the 3-year period was 538.2 tons (0.30 ton per acre per year), which compares to a measured sediment load of 467.61 tons (0.26 ton per acre per year). The model was verified by comparing observed and simulated data from October 1, 1988, through September 30, 1989. The results obtained were comparable to those from the calibration period. The simulated mean daily discharge was representative of the range of data observed from the basin and of the frequency with which specific discharges were equalled or exceeded. The calibrated and verified parameters from the Stony Fork model were applied to an HSPF model of the Poplar Run Basin. The two basins are in a similar physical setting. Data from October 1, 1987, through September 30, 1989, were used to evaluate the Poplar Run model. In general, the results from the Poplar Run model were comparable to those obtained from the Stony Fork model. The difference between observed and simulated total streamflow was 1.1 percent for the 2-year period. The mean annual streamflow simulated by the Poplar Run model was 18.3 cubic feet per second. This compares to an observed streamflow of 18.15 cubic feet per second. For the 2-year period, the simulated sediment load was 2,754 tons (0.24 ton per acre per year), which compares to a measured sediment load of 3,051.2 tons (0.27 ton per acre per year) for the Poplar Run Basin. Cumulative frequency-distribution curves of the observed and simulated streamflow compared well. The comparison between observed and simulated data improved as the time span increased. Simulated annual means and totals were more representative of the observed data than hourly data used in comparing storm events. The structure and organization of the HSPF model facilitated the simulation of a wide range of hydrologic processes. The simulation results from this investigation indicate that model parameters may be transferred to ungaged basins to generate representative hydrologic data through modeling techniques.

Reconstructing streamflow variation of the Baker River from tree-rings in Northern Patagonia since 1765

NASA Astrophysics Data System (ADS)

Lara, Antonio; Bahamondez, Alejandra; González-Reyes, Alvaro; Muñoz, Ariel A.; Cuq, Emilio; Ruiz-Gómez, Carolina

2015-10-01

The understanding of the long-term variation of large rivers streamflow with a high economic and social relevance is necessary in order to improve the planning and management of water resources in different regions of the world. The Baker River has the highest mean discharge of those draining both slopes of the Andes South of 20°S and it is among the six rivers with the highest mean streamflow in the Pacific domain of South America (1100 m3 s-1 at its outlet). It drains an international basin of 29,000 km2 shared by Chile and Argentina and has a high ecologic and economic value including conservation, tourism, recreational fishing, and projected hydropower. This study reconstructs the austral summer - early fall (January-April) streamflow for the Baker River from Nothofagus pumilio tree-rings for the period 1765-2004. Summer streamflow represents 45.2% of the annual discharge. The regression model for the period (1961-2004) explains 54% of the variance of the Baker River streamflow (R2adj = 0.54). The most significant temporal pattern in the record is the sustained decline since the 1980s (τ = -0.633, p = 1.0144 ∗ 10-5 for the 1985-2004 period), which is unprecedented since 1765. The Correlation of the Baker streamflow with the November-April observed Southern Annular Mode (SAM) is significant (1961-2004, r = -0.55, p < 0.001). The Baker record is also correlated with the available SAM tree-ring reconstruction based on other species when both series are filtered with a 25-year spline and detrended (1765-2004, r = -0.41, p < 0.01), emphasizing SAM as the main climatic forcing of the Baker streamflow. Three of the five summers with the highest streamflow in the entire reconstructed record occurred after the 1950s (1977, 1958 and 1959). The causes of this high streamflow events are not yet clear and cannot be associated with the reported recent increase in the frequency of glacial-lake outburst floods (GLOFs). The decreasing trend in the observed and reconstructed streamflow of the Baker River documented here for the 1980-2004 period is consistent with precipitation decrease associated with the SAM. Conversely, other studies have reported an increase of summer streamflow for a portion of the Baker River for the 1994-2008 period, explained by ice melt associated with temperature increase and glacier retreat and thinning. Future research should consider the development of new tree-ring reconstructions to increase the geographic range and to cover the last 1000 or more years using long-lived species (e.g. Fitzroya cupressoides and Pilgerodendron uviferum). Expanding the network and quality of instrumental weather, streamflow and other monitoring stations as well as the study and modeling of the complex hydrological processes in the Baker basin are necessary. This should be the basis for planning, policy design and decision making regarding water resources in the Baker basin.

Application of the Precipitation-Runoff Modeling System (PRMS) in the Apalachicola-Chattahoochee-Flint River Basin in the southeastern United States

USGS Publications Warehouse

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.

Evaluation of Streamflow Gain-Loss Characteristics of Hubbard Creek, in the Vicinity of a Mine-Permit Area, Delta County, Colorado, 2007

USGS Publications Warehouse

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.

Measuring discharge with acoustic Doppler current profilers from a moving boat

USGS Publications Warehouse

Mueller, David S.; Wagner, Chad R.; Rehmel, Michael S.; Oberg, Kevin A.; Rainville, Francois

2013-01-01

The use of acoustic Doppler current profilers (ADCPs) from a moving boat is now a commonly used method for measuring streamflow. The technology and methods for making ADCP-based discharge measurements are different from the technology and methods used to make traditional discharge measurements with mechanical meters. Although the ADCP is a valuable tool for measuring streamflow, it is only accurate when used with appropriate techniques. This report presents guidance on the use of ADCPs for measuring streamflow; this guidance is based on the experience of U.S. Geological Survey employees and published reports, papers, and memorandums of the U.S. Geological Survey. The guidance is presented in a logical progression, from predeployment planning, to field data collection, and finally to post processing of the collected data. Acoustic Doppler technology and the instruments currently (2013) available also are discussed to highlight the advantages and limitations of the technology. More in-depth, technical explanations of how an ADCP measures streamflow and what to do when measuring in moving-bed conditions are presented in the appendixes. ADCP users need to know the proper procedures for measuring discharge from a moving boat and why those procedures are required, so that when the user encounters unusual field conditions, the procedures can be adapted without sacrificing the accuracy of the streamflow-measurement data.

Model calibration criteria for estimating ecological flow characteristics

USGS Publications Warehouse

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.

Simulation of streamflow and the effects of brush management on water yields in the upper Guadalupe River watershed, south-central Texas, 1995-2010

USGS Publications Warehouse

Bumgarner, Johnathan R.; Thompson, Florence E.

2012-01-01

The U.S. Geological Survey, in cooperation with the Texas State Soil and Water Conservation Board and the Upper Guadalupe River Authority, developed and calibrated a Soil and Water Assessment Tool watershed model of the upper Guadalupe River watershed in south-central Texas to simulate streamflow and the effects of brush management on water yields in the watershed and to Canyon Lake for 1995-2010. Model simulations were done to quantify the possible change in water yield of individual subbasins in the upper Guadalupe River watershed as a result of the replacement of ashe juniper (Juniperus ashei) with grasslands. The simulation results will serve as a tool for resource managers to guide their brush-management efforts. Model hydrology was calibrated with streamflow data collected at the U.S. Geological Survey streamflow-gaging station 08167500 Guadalupe River near Spring Branch, Tex., for 1995-2010. Simulated monthly streamflow showed very good agreement with measured monthly streamflow: a percent bias of -5, a coefficient of determination of 0.91, and a Nash-Sutcliffe coefficient of model efficiency of 0.85. Modified land-cover input datasets were generated for the model in order to simulate the replacement of ashe juniper with grasslands in 23 brush-management subbasins in the watershed. Each of the 23 simulations showed an increase in simulated water yields in the targeted subbasins and to Canyon Lake. The simulated increases in average annual water yields in the subbasins ranged from 6,370 to 119,000 gallons per acre of ashe juniper replaced with grasslands with an average of 38,900 gallons. The simulated increases in average annual water yields to Canyon Lake from upstream subbasins ranged from 6,640 to 72,700 gallons per acre of ashe juniper replaced with grasslands with an average of 34,700 gallons.

Calculated hydrographs for unsteady research flows at selected sites along the Colorado River downstream from Glen Canyon Dam, Arizona, 1990 and 1991

USGS Publications Warehouse

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.

Development of a software framework for data assimilation and its applications for streamflow forecasting in Japan

NASA Astrophysics Data System (ADS)

Noh, S. J.; Tachikawa, Y.; Shiiba, M.; Yorozu, K.; Kim, S.

2012-04-01

Data assimilation methods have received increased attention to accomplish uncertainty assessment and enhancement of forecasting capability in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modeling software are based on a deterministic approach. In this study, we developed a hydrological modeling framework for sequential data assimilation, so called MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modeling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. Sequential data assimilation based on the particle filters is available for any hydrologic models based on MPI-OHyMoS considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for short-term streamflow forecasting of several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and remotely-sensed rainfall data such as X-band or C-band radar is estimated and mitigated in the sequential data assimilation.

Time series analysis of the long-term hydrologic impacts of afforestation in the Águeda watershed of north-central Portugal

NASA Astrophysics Data System (ADS)

Hawtree, D.; Nunes, J. P.; Keizer, J. J.; Jacinto, R.; Santos, J.; Rial-Rivas, M. E.; Boulet, A.-K.; Tavares-Wahren, F.; Feger, K.-H.

2015-07-01

The north-central region of Portugal has undergone significant land cover change since the early 1900s, with large-scale replacement of natural vegetation types with plantation forests. This transition consisted of an initial conversion primarily to Pinus pinaster, followed by a secondary transition to Eucalyptus globulus. This land cover change is likely to have altered the hydrologic functioning of this region; however, these potential impacts are not fully understood. To contribute to a better understanding of the potential hydrologic impacts of this land cover change, this study examines the temporal trends in 75 years of data from the Águeda watershed (part of the Vouga Basin) over the period of 1936-2010. A number of hydrometeorological variables were analyzed using a combined Thiel-Sen/Mann-Kendall trend-testing approach, to assess the magnitude and significance of patterns in the observed data. These trend tests indicated that there have been no significant reductions in streamflow over either the entire test period, or during sub-record periods, despite the large-scale afforestation which has occurred. This lack of change in streamflow is attributed to the specific characteristics of the watershed and land cover change. By contrast, a number of significant trends were found for baseflow index, with positive trends in the early data record (primarily during Pinus pinaster afforestation), followed by negative trends later in the data record (primarily during Eucalyptus globulus afforestation). These trends are attributed to land use and vegetation impacts on streamflow generating processes, both due to species differences and to alterations in soil properties (i.e., infiltration capacity, soil water repellency). These results highlight the importance of considering both vegetation types/dynamics and watershed characteristic when assessing hydrologic impacts, in particular with respect to soil properties.

No Snow No Flow: How Montane Stream Networks Respond to Drought

NASA Astrophysics Data System (ADS)

Grant, G.; Nolin, A. W.; Selker, J. S.; Lewis, S.; Hempel, L. A.; Jefferson, A.; Walter, C.; Roques, C.

2015-12-01

Hydrologic extremes, such as drought, offer an exceptional opportunity to explore how runoff generation mechanisms and stream networks respond to changing precipitation regimes. The winter of 2014-2015 was the warmest on record in western Oregon, US, with record low snowpacks, and was followed by an anomalously warm, dry spring, resulting in historically low streamflows. But a year like 2015 is more than an outlier meteorological year. It provides a unique opportunity to test fundamental hypotheses for how montane hydrologic systems will respond to anticipated changes in amount and timing of recharge. In particular, the volcanic Cascade Mountains represent a "landscape laboratory" comprised of two distinct runoff regimes: the surface-flow dominated Western Cascade watersheds, with flashy streamflow regimes, rapid baseflow recession, and very low summer flows; and (b) the spring-fed High Cascade watersheds, with a slow-responding streamflow regime, and a long and sustained baseflow recession that maintains late summer streamflow through deep-groundwater contributions to high volume, coldwater springs. We hypothesize that stream network response to the extremely low snowpack and recharge varies sharply in these two regions. In surface flow dominated streams, the location of channel heads can migrate downstream, contracting the network longitudinally; wetted channel width and depth contract laterally as summer recession proceeds and flows diminish. In contrast, in spring-fed streams, channel heads "jump" to the next downstream spring when upper basin spring flow diminishes to zero. Downstream of flowing springs, wetted channel width and depth contract laterally as flows recede. To test these hypotheses, we conducted a field campaign to measure changing discharge, hydraulic geometry, and channel head location in both types of watersheds throughout the summer and early fall. Multiple cross-section sites were established on 6 streams representing both flow regime types on either side of the Cascade crest. We also took Isotopic water samples to determine recharge elevations of receding streams. Taken together these measurements reveal the processes by which drainage networks contract as flows diminish - a fundamental property of montane stream systems both now and in the future.

Water's Way at Sleepers River watershed - revisiting flow generation in a post-glacial landscape, Vermont USA

Treesearch

James B. Shanley; Stephen D. Sebestyen; Jeffrey J. McDonnell; Brian L. McGlynn; Thomas Dunne

2015-01-01

The Sleepers River Research Watershed (SRRW) in Vermont, USA, has been the site of active hydrologic research since 1959 and was the setting where Dunne and Black demonstrated the importance and controls of saturation-excess overland flow (SOF) on streamflow generation. Here, we review the early studies from the SRRW and show how they guided our conceptual approach to...

Evaluation of streamflow traveltime and streamflow gains and losses along the lower Purgatoire River, southeastern Colorado, 1984-92

USGS Publications Warehouse

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.

Summary of annual mean and annual harmonic mean statistics of daily mean streamflow for 620 U.S. Geological Survey streamflow-gaging stations in Texas through water year 2007

USGS Publications Warehouse

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.

StreamStats in Oklahoma - Drainage-Basin Characteristics and Peak-Flow Frequency Statistics for Ungaged Streams

USGS Publications Warehouse

Smith, S. Jerrod; Esralew, Rachel A.

2010-01-01

The USGS Streamflow Statistics (StreamStats) Program was created to make geographic information systems-based estimation of streamflow statistics easier, faster, and more consistent than previously used manual techniques. The StreamStats user interface is a map-based internet application that allows users to easily obtain streamflow statistics, basin characteristics, and other information for user-selected U.S. Geological Survey data-collection stations and ungaged sites of interest. The application relies on the data collected at U.S. Geological Survey streamflow-gaging stations, computer aided computations of drainage-basin characteristics, and published regression equations for several geographic regions comprising the United States. The StreamStats application interface allows the user to (1) obtain information on features in selected map layers, (2) delineate drainage basins for ungaged sites, (3) download drainage-basin polygons to a shapefile, (4) compute selected basin characteristics for delineated drainage basins, (5) estimate selected streamflow statistics for ungaged points on a stream, (6) print map views, (7) retrieve information for U.S. Geological Survey streamflow-gaging stations, and (8) get help on using StreamStats. StreamStats was designed for national application, with each state, territory, or group of states responsible for creating unique geospatial datasets and regression equations to compute selected streamflow statistics. With the cooperation of the Oklahoma Department of Transportation, StreamStats has been implemented for Oklahoma and is available at http://water.usgs.gov/osw/streamstats/. The Oklahoma StreamStats application covers 69 processed hydrologic units and most of the state of Oklahoma. Basin characteristics available for computation include contributing drainage area, contributing drainage area that is unregulated by Natural Resources Conservation Service floodwater retarding structures, mean-annual precipitation at the drainage-basin outlet for the period 1961-1990, 10-85 channel slope (slope between points located at 10 percent and 85 percent of the longest flow-path length upstream from the outlet), and percent impervious area. The Oklahoma StreamStats application interacts with the National Streamflow Statistics database, which contains the peak-flow regression equations in a previously published report. Fourteen peak-flow (flood) frequency statistics are available for computation in the Oklahoma StreamStats application. These statistics include the peak flow at 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals for rural, unregulated streams; and the peak flow at 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals for rural streams that are regulated by Natural Resources Conservation Service floodwater retarding structures. Basin characteristics and streamflow statistics cannot be computed for locations in playa basins (mostly in the Oklahoma Panhandle) and along main stems of the largest river systems in the state, namely the Arkansas, Canadian, Cimarron, Neosho, Red, and Verdigris Rivers, because parts of the drainage areas extend outside of the processed hydrologic units.

How are streamflow responses to the El Nino Southern Oscillation affected by watershed characteristics?

NASA Astrophysics Data System (ADS)

Rice, Joshua S.; Emanuel, Ryan E.

2017-05-01

Understanding the factors that influence how global climate phenomena, such as the El-Nino Southern Oscillation (ENSO), affect streamflow behavior is an important area of research in the hydrologic sciences. While large-scale patterns in ENSO-streamflow relationships have been thoroughly studied, and are relatively well-understood, information is scarce concerning factors that affect variation in ENSO responses from one watershed to another. To this end, we examined relationships between variability in ENSO activity and streamflow for 2731 watersheds across the conterminous U.S. from 1970 to 2014 using a novel approach to account for the intermediary role of precipitation. We applied an ensemble of regression techniques to describe relationships between variability in ENSO activity and streamflow as a function of watershed characteristics including: hydroclimate, topography, geomorphology, geographic location, land cover, soil characteristics, bedrock geology, and anthropogenic influences. We found that variability in watershed scale ENSO-streamflow relationships was strongly related to factors including: precipitation timing and phase, forest cover, and interactions between watershed topography and geomorphology. These, and other influential factors, share in common the ability to affect the partitioning and movement of water within watersheds. Our results demonstrate that the conceptualization of watersheds as signal filters for hydroclimate inputs, commonly applied to short-term rainfall-runoff responses, also applies to long-term hydrologic responses to sources of recurrent climate variability. These results also show that watershed processes, which are typically studied at relatively fine spatial scales, are also critical for understanding continental scale hydrologic responses to global climate.

Changes in the relation between snow station observations and basin scale snow water resources

NASA Astrophysics Data System (ADS)

Sexstone, G. A.; Penn, C. A.; Clow, D. W.; Moeser, D.; Liston, G. E.

2017-12-01

Snow monitoring stations that measure snow water equivalent or snow depth provide fundamental observations used for predicting water availability and flood risk in mountainous regions. In the western United States, snow station observations provided by the Natural Resources Conservation Service Snow Telemetry (SNOTEL) network are relied upon for forecasting spring and summer streamflow volume. Streamflow forecast accuracy has declined for many regions over the last several decades. Changes in snow accumulation and melt related to climate, land use, and forest cover are not accounted for in current forecasts, and are likely sources of error. Therefore, understanding and updating relations between snow station observations and basin scale snow water resources is crucial to improve accuracy of streamflow prediction. In this study, we investigated the representativeness of snow station observations when compared to simulated basin-wide snow water resources within the Rio Grande headwaters of Colorado. We used the combination of a process-based snow model (SnowModel), field-based measurements, and remote sensing observations to compare the spatiotemporal variability of simulated basin-wide snow accumulation and melt with that of SNOTEL station observations. Results indicated that observations are comparable to simulated basin-average winter precipitation but overestimate both the simulated basin-average snow water equivalent and snowmelt rate. Changes in the representation of snow station observations over time in the Rio Grande headwaters were also investigated and compared to observed streamflow and streamflow forecasting errors. Results from this study provide important insight in the context of non-stationarity for future water availability assessments and streamflow predictions.

Processes Controlling Baseflow and Climatic Warming Effects in Merced River, Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Liu, F.; Conklin, M. H.; Shaw, G.; Bales, R. C.; Conrad, M. E.; Rice, R.

2006-12-01

Sources of streamflow in Merced River were determined using stable isotopes and chemical tracers in order to improve our understanding of hydrologic controls on streamflow and their relationship with climatic warming in the region. Samples were collected from streamflow, groundwater, and natural springs from 2003 to 2006. Both stable isotopes and specific conductivity in streamflow showed a strong seasonality, with lower values from April to July during the snowmelt season, higher values from August to October during dry season, and intermediate values from November to March during winter rainfall and snowfall. Two components controlling baseflow (streamflow from August to October) in the Upper Merced River were identified: shallow subsurface runoff from snowmelt infiltration and groundwater from fractured bedrock. Conductivity in baseflow increased rapidly with discharge, following a power law (R2 > 0.96, p < 0.05), and peaked in October, indicating that the contribution of shallow subsurface runoff to baseflow was significant but decreased rapidly from August to October. Baseflow appears to be very sensitive to the snowmelt timing and regime. From 1976 to 2005, during a period of increasing temperature in the region, streamflow tended to decrease significantly during October (p < 0.05) and increase during March (p < 0.05). However, total annual precipitation did not change significantly, indicating that the shift in baseflow discharge is a result of the early onset of snowmelt due to climatic warming. If climatic warming continues in the region, baseflow in the Sierra Nevada may continue decreasing and water supply may suffer increased stress during the late summer, high water-demand period.

Historical perspective of statewide streamflows during the 2002 and 1977 droughts in Colorado

USGS Publications Warehouse

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

Technique for estimation of streamflow statistics in mineral areas of interest in Afghanistan

USGS Publications Warehouse

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.

Monthly streamflow forecasting with auto-regressive integrated moving average

NASA Astrophysics Data System (ADS)

Nasir, Najah; Samsudin, Ruhaidah; Shabri, Ani

2017-09-01

Forecasting of streamflow is one of the many ways that can contribute to better decision making for water resource management. The auto-regressive integrated moving average (ARIMA) model was selected in this research for monthly streamflow forecasting with enhancement made by pre-processing the data using singular spectrum analysis (SSA). This study also proposed an extension of the SSA technique to include a step where clustering was performed on the eigenvector pairs before reconstruction of the time series. The monthly streamflow data of Sungai Muda at Jeniang, Sungai Muda at Jambatan Syed Omar and Sungai Ketil at Kuala Pegang was gathered from the Department of Irrigation and Drainage Malaysia. A ratio of 9:1 was used to divide the data into training and testing sets. The ARIMA, SSA-ARIMA and Clustered SSA-ARIMA models were all developed in R software. Results from the proposed model are then compared to a conventional auto-regressive integrated moving average model using the root-mean-square error and mean absolute error values. It was found that the proposed model can outperform the conventional model.

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.

Streamflow changes in the Sierra Nevada, California, simulated using a statistically downscaled general circulation model scenario of climate change

USGS Publications Warehouse

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.

Streamflow transport of radionuclides and other chemical constituents in the Puerco and the Little Colorado river basins, Arizona and New Mexico

USGS Publications Warehouse

Graf, Julia B.; Wirt, Laurie; Swanson, E.K.; Fisk, G.G.; Gray, J.R.

1996-01-01

Samples collected at streamflow-gaging stations in the Puerco and Little Colorado rivers show that radioactivity of suspended sediment at gaging stations downstream from inactive uranium mines was not significantly higher than at gaging stations where no mining has occurred upstream. Drinking-water standards for many constituents, however, commonly are exceeded during runoff because concentration of these constituents on sediment from natural processes is high and suspended-sediment loads are high during runoff.

Unorganized machines for seasonal streamflow series forecasting.

PubMed

Siqueira, Hugo; Boccato, Levy; Attux, Romis; Lyra, Christiano

2014-05-01

Modern unorganized machines--extreme learning machines and echo state networks--provide an elegant balance between processing capability and mathematical simplicity, circumventing the difficulties associated with the conventional training approaches of feedforward/recurrent neural networks (FNNs/RNNs). This work performs a detailed investigation of the applicability of unorganized architectures to the problem of seasonal streamflow series forecasting, considering scenarios associated with four Brazilian hydroelectric plants and four distinct prediction horizons. Experimental results indicate the pertinence of these models to the focused task.

Modeling the Effects of Land Use and Climate Change on Streamflow in the Delaware River Basin

NASA Astrophysics Data System (ADS)

Kwon, P. Y. S.; Endreny, T. A.; Kroll, C. N.; Williamson, T. N.

2014-12-01

Forest-cover loss and drinking-water reservoirs in the upper Delaware River Basin of New York may alter summer low streamflows, which could degrade the in-stream habitat for the endangered dwarf wedgemussel. Our project analyzes how flow statistics change with land-cover change for 30-year increments of model-simulated streamflow hydrographs for three watersheds of concern to the National Park Service: the East Branch, West Branch, and main stem of the Delaware River. We use four treatments for land cover ranging from historical high to low forest cover. We subject each land cover to adjusted GCM climate scenarios for 1600, 1900, 1940, and 2040 to isolate land cover from potential climate-change effects. Hydrographs are simulated using the Water Availability Tool for Environmental Resources (WATER), a TOPMODEL-based United States Geological Survey hydrologic decision-support tool, which uses the variable-source-area concept and water budgets to generate streamflow. Model parameters for each watershed change with land-use, and capture differences in soil-physical properties that control how rainfall infiltrates, evaporates, transpires, is stored in the soil, and moves to the stream. Our results analyze flow statistics used as indicators of hydrologic alteration, and access streamflow events below the critical flow needed to provide sustainable habitat for dwarf wedgemussels. These metrics will demonstrate how changes in climate and land use might affect flow statistics. Initial results show that the 1940 WATER simulation outputs generally match observed unregulated low flows from that time period, while performance for regulated flow from the same time period and from 1600, 1900, and 2040 require model input adjustments. Our study will illustrate how increased forest cover could potentially restore in-stream habitat for the endangered dwarf wedgemussel for current and future climate conditions.

Hydrologic cost-effectiveness ratio favors switchgrass production on marginal croplands over existing grasslands

PubMed Central

Yimam, Yohannes Tadesse; Ochsner, Tyson E.; Fox, Garey A.

2017-01-01

Switchgrass (Panicum virgatum L.) has attracted attention as a promising second generation biofuel feedstock. Both existing grasslands and marginal croplands have been suggested as targets for conversion to switchgrass, but the resulting production potentials and hydrologic impacts are not clear. The objectives of this study were to model switchgrass production on existing grasslands (scenario-I) and on marginal croplands that have severe to very severe limitations for crop production (scenario-II) and to evaluate the effects on evapotranspiration (ET) and streamflow. The Soil and Water Assessment Tool (SWAT) was applied to the 1063 km2 Skeleton Creek watershed in north-central Oklahoma, a watershed dominated by grasslands (35%) and winter wheat cropland (47%). The simulated average annual yield (2002–2011) for rainfed Alamo switchgrass for both scenarios was 12 Mg ha-1. Yield varied spatially under scenario-I from 6.1 to 15.3 Mg ha-1, while under scenario-II the range was from 8.2 to 13.8 Mg ha-1. Comparison of average annual ET and streamflow between the baseline simulation (existing land use) and scenario-I showed that scenario-I had 5.6% (37 mm) higher average annual ET and 27.7% lower streamflow, representing a 40.7 million m3 yr-1 streamflow reduction. Compared to the baseline, scenario-II had only 0.5% higher ET and 3.2% lower streamflow, but some monthly impacts were larger. In this watershed, the water yield reduction per ton of biomass production (i.e. hydrologic cost-effectiveness ratio) was more than 5X greater under scenario-I than under scenario-II. These results suggest that, from a hydrologic perspective, it may be preferable to convert marginal cropland to switchgrass production rather than converting existing grasslands. PMID:28792541

Hydrologic cost-effectiveness ratio favors switchgrass production on marginal croplands over existing grasslands.

PubMed

Yimam, Yohannes Tadesse; Ochsner, Tyson E; Fox, Garey A

2017-01-01

Switchgrass (Panicum virgatum L.) has attracted attention as a promising second generation biofuel feedstock. Both existing grasslands and marginal croplands have been suggested as targets for conversion to switchgrass, but the resulting production potentials and hydrologic impacts are not clear. The objectives of this study were to model switchgrass production on existing grasslands (scenario-I) and on marginal croplands that have severe to very severe limitations for crop production (scenario-II) and to evaluate the effects on evapotranspiration (ET) and streamflow. The Soil and Water Assessment Tool (SWAT) was applied to the 1063 km2 Skeleton Creek watershed in north-central Oklahoma, a watershed dominated by grasslands (35%) and winter wheat cropland (47%). The simulated average annual yield (2002-2011) for rainfed Alamo switchgrass for both scenarios was 12 Mg ha-1. Yield varied spatially under scenario-I from 6.1 to 15.3 Mg ha-1, while under scenario-II the range was from 8.2 to 13.8 Mg ha-1. Comparison of average annual ET and streamflow between the baseline simulation (existing land use) and scenario-I showed that scenario-I had 5.6% (37 mm) higher average annual ET and 27.7% lower streamflow, representing a 40.7 million m3 yr-1 streamflow reduction. Compared to the baseline, scenario-II had only 0.5% higher ET and 3.2% lower streamflow, but some monthly impacts were larger. In this watershed, the water yield reduction per ton of biomass production (i.e. hydrologic cost-effectiveness ratio) was more than 5X greater under scenario-I than under scenario-II. These results suggest that, from a hydrologic perspective, it may be preferable to convert marginal cropland to switchgrass production rather than converting existing grasslands.

Relations between winter climatic variables and April streamflows in New England and implications for summer streamflows

USGS Publications Warehouse

Hodgkins, Glenn A.; Dudley, Robert W.; Schalk, Luther F.

2012-01-01

A period of much below normal streamflow in southern New England during April 2012 raised concerns that a long-term period of drought could evolve through late spring and summer, leading to potential water availability issues. To understand better the relations between winter climatic variables and April streamflows, April streamflows from 31 streamflow gages in New England that drain relatively natural watersheds were tested for year-to-year correlation with winter precipitation and air temperature from nearby meteorological sites. Higher winter (December through March) precipitation is associated with higher April streamflows at many gages in northern and central New England. This implies that snowpack accumulation is an important mechanism for winter water storage and subsequently important for spring streamflows in this area. Higher March air temperatures are associated with lower April streamflows at many gages in central and southern New England, likely because the majority of snowmelt runoff occurs before April in warm years. A warm March 2012 contributed to early snowmelt runoff in New England and to much below normal April streamflows in southern New England. However, no strong relation was found between historical April streamflows and late-spring or summer streamflows in New England. The lack of a strong relation implies that summer precipitation, rather than spring conditions, controls summer streamflows.

Simulation of daily streamflow for 12 river basins in western Iowa using the Precipitation-Runoff Modeling System

USGS Publications Warehouse

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.

Simulating the effects of ground-water withdrawals on streamflow in a precipitation-runoff model

USGS Publications Warehouse

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.

Documentation for the State Variables Package for the Groundwater-Management Process of MODFLOW-2005 (GWM-2005)

USGS Publications Warehouse

Ahlfeld, David P.; Barlow, Paul M.; Baker, Kristine M.

2011-01-01

Many groundwater-management problems are concerned with the control of one or more variables that reflect the state of a groundwater-flow system or a coupled groundwater/surface-water system. These system state variables include the distribution of heads within an aquifer, streamflow rates within a hydraulically connected stream, and flow rates into or out of aquifer storage. This report documents the new State Variables Package for the Groundwater-Management Process of MODFLOW-2005 (GWM-2005). The new package provides a means to explicitly represent heads, streamflows, and changes in aquifer storage as state variables in a GWM-2005 simulation. The availability of these state variables makes it possible to include system state in the objective function and enhances existing capabilities for constructing constraint sets for a groundwater-management formulation. The new package can be used to address groundwater-management problems such as the determination of withdrawal strategies that meet water-supply demands while simultaneously maximizing heads or streamflows, or minimizing changes in aquifer storage. Four sample problems are provided to demonstrate use of the new package for typical groundwater-management applications.

Comparison of ensemble post-processing approaches, based on empirical and dynamical error modelisation of rainfall-runoff model forecasts

NASA Astrophysics Data System (ADS)

Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.

2012-04-01

In the context of a national energy company (EDF : Electricité de France), hydro-meteorological forecasts are necessary to ensure safety and security of installations, meet environmental standards and improve water ressources management and decision making. Hydrological ensemble forecasts allow a better representation of meteorological and hydrological forecasts uncertainties and improve human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. An operational hydrological ensemble forecasting chain has been developed at EDF since 2008 and is being used since 2010 on more than 30 watersheds in France. This ensemble forecasting chain is characterized ensemble pre-processing (rainfall and temperature) and post-processing (streamflow), where a large human expertise is solicited. The aim of this paper is to compare 2 hydrological ensemble post-processing methods developed at EDF in order improve ensemble forecasts reliability (similar to Monatanari &Brath, 2004; Schaefli et al., 2007). The aim of the post-processing methods is to dress hydrological ensemble forecasts with hydrological model uncertainties, based on perfect forecasts. The first method (called empirical approach) is based on a statistical modelisation of empirical error of perfect forecasts, by streamflow sub-samples of quantile class and lead-time. The second method (called dynamical approach) is based on streamflow sub-samples of quantile class and streamflow variation, and lead-time. On a set of 20 watersheds used for operational forecasts, results show that both approaches are necessary to ensure a good post-processing of hydrological ensemble, allowing a good improvement of reliability, skill and sharpness of ensemble forecasts. The comparison of the empirical and dynamical approaches shows the limits of the empirical approach which is not able to take into account hydrological dynamic and processes, i. e. sample heterogeneity. For a same streamflow range corresponds different processes such as rising limbs or recession, where uncertainties are different. The dynamical approach improves reliability, skills and sharpness of forecasts and globally reduces confidence intervals width. When compared in details, the dynamical approach allows a noticeable reduction of confidence intervals during recessions where uncertainty is relatively lower and a slight increase of confidence intervals during rising limbs or snowmelt where uncertainty is greater. The dynamic approach, validated by forecaster's experience that considered the empirical approach not discriminative enough, improved forecaster's confidence and communication of uncertainties. Montanari, A. and Brath, A., (2004). A stochastic approach for assessing the uncertainty of rainfall-runoff simulations. Water Resources Research, 40, W01106, doi:10.1029/2003WR002540. Schaefli, B., Balin Talamba, D. and Musy, A., (2007). Quantifying hydrological modeling errors through a mixture of normal distributions. Journal of Hydrology, 332, 303-315.

The value of model averaging and dynamical climate model predictions for improving statistical seasonal streamflow forecasts over Australia

NASA Astrophysics Data System (ADS)

Pokhrel, Prafulla; Wang, Q. J.; Robertson, David E.

2013-10-01

Seasonal streamflow forecasts are valuable for planning and allocation of water resources. In Australia, the Bureau of Meteorology employs a statistical method to forecast seasonal streamflows. The method uses predictors that are related to catchment wetness at the start of a forecast period and to climate during the forecast period. For the latter, a predictor is selected among a number of lagged climate indices as candidates to give the "best" model in terms of model performance in cross validation. This study investigates two strategies for further improvement in seasonal streamflow forecasts. The first is to combine, through Bayesian model averaging, multiple candidate models with different lagged climate indices as predictors, to take advantage of different predictive strengths of the multiple models. The second strategy is to introduce additional candidate models, using rainfall and sea surface temperature predictions from a global climate model as predictors. This is to take advantage of the direct simulations of various dynamic processes. The results show that combining forecasts from multiple statistical models generally yields more skillful forecasts than using only the best model and appears to moderate the worst forecast errors. The use of rainfall predictions from the dynamical climate model marginally improves the streamflow forecasts when viewed over all the study catchments and seasons, but the use of sea surface temperature predictions provide little additional benefit.

El Niño-southern oscillation influences on the Mahaweli streamflow in Sri Lanka

NASA Astrophysics Data System (ADS)

Zubair, Lareef

2003-01-01

Despite advances over the last two decades in the capacity to predict the evolution of the El Niño-southern oscillation (ENSO) phenomenon and advances in understanding of the relationship between ENSO and climate, there has been little use of climate predictions for water resources management in the tropics. As part of an effort to develop such a prediction scheme, the ENSO influences on streamflow and rainfall in the upper catchment of the Mahaweli river in Sri Lanka were investigated with correlation analysis, composite analysis and contingency tables. El Niño conditions were often associated with decreased annual flows and La Niña with increased flows. The relationship of streamflow and rainfall with the ENSO index of NINO3 contrasted between January to September and October to December. During El Niño episodes the streamflow declines from January to September, but from October to December there is no clear relationship. On the other hand, rainfall shows a clear increase from October to December and declines during January, February, March, July and August. The simultaneous correlations of NINO3 with the aggregate January to September streamflow (r = -0.50), with January to September rainfall (r = -0.44) and with October to December rainfall (r = 0.48) are all significant at the 99% level. The correlation between one-season-in-advance NINO3 with both January to September streamflow and October to December rainfall remained significant at the 99% level.This study demonstrates the potential of using ENSO-based predictors for a seasonal hydro-climatic prediction scheme in the Mahaweli basin. It shows the significant contrasts in ENSO influence on rainfall and streamflow due to various hydrological processes. It has demonstrated that the potential for prediction is improved by investigating ENSO influences for the appropriate season for the given river catchment.

Contradictory hydrological impacts of afforestation in the humid tropics evidenced by long-term field monitoring and simulation modelling

NASA Astrophysics Data System (ADS)

Lacombe, Guillaume; Ribolzi, Olivier; de Rouw, Anneke; Pierret, Alain; Latsachak, Keoudone; Silvera, Norbert; Pham Dinh, Rinh; Orange, Didier; Janeau, Jean-Louis; Soulileuth, Bounsamai; Robain, Henri; Taccoen, Adrien; Sengphaathith, Phouthamaly; Mouche, Emmanuel; Sengtaheuanghoung, Oloth; Tran Duc, Toan; Valentin, Christian

2016-07-01

The humid tropics are exposed to an unprecedented modernisation of agriculture involving rapid and mixed land-use changes with contrasted environmental impacts. Afforestation is often mentioned as an unambiguous solution for restoring ecosystem services and enhancing biodiversity. One consequence of afforestation is the alteration of streamflow variability which controls habitats, water resources, and flood risks. We demonstrate that afforestation by tree planting or by natural forest regeneration can induce opposite hydrological changes. An observatory including long-term field measurements of fine-scale land-use mosaics and of hydrometeorological variables has been operating in several headwater catchments in tropical southeast Asia since 2000. The GR2M water balance model, repeatedly calibrated over successive 1-year periods and used in simulation mode with the same year of rainfall input, allowed the hydrological effect of land-use change to be isolated from that of rainfall variability in two of these catchments in Laos and Vietnam. Visual inspection of hydrographs, correlation analyses, and trend detection tests allowed causality between land-use changes and changes in seasonal streamflow to be ascertained. In Laos, the combination of shifting cultivation system (alternation of rice and fallow) and the gradual increase of teak tree plantations replacing fallow led to intricate streamflow patterns: pluri-annual streamflow cycles induced by the shifting system, on top of a gradual streamflow increase over years caused by the spread of the plantations. In Vietnam, the abandonment of continuously cropped areas combined with patches of mix-trees plantations led to the natural re-growth of forest communities followed by a gradual drop in streamflow. Soil infiltrability controlled by surface crusting is the predominant process explaining why two modes of afforestation (natural regeneration vs. planting) led to opposite changes in streamflow regime. Given that commercial tree plantations will continue to expand in the humid tropics, careful consideration is needed before attributing to them positive effects on water and soil conservation.

The significance of spatial variability of rainfall on streamflow: A synthetic analysis at the Upper Lee catchment, UK

NASA Astrophysics Data System (ADS)

Pechlivanidis, Ilias; McIntyre, Neil; Wheater, Howard

2017-04-01

Rainfall, one of the main inputs in hydrological modeling, is a highly heterogeneous process over a wide range of scales in space, and hence the ignorance of the spatial rainfall information could affect the simulated streamflow. Calibration of hydrological model parameters is rarely a straightforward task due to parameter equifinality and parameters' 'nature' to compensate for other uncertainties, i.e. structural and forcing input. In here, we analyse the significance of spatial variability of rainfall on streamflow as a function of catchment scale and type, and antecedent conditions using the continuous time, semi-distributed PDM hydrological model at the Upper Lee catchment, UK. The impact of catchment scale and type is assessed using 11 nested catchments ranging in scale from 25 to 1040 km2, and further assessed by artificially changing the catchment characteristics and translating these to model parameters with uncertainty using model regionalisation. Synthetic rainfall events are introduced to directly relate the change in simulated streamflow to the spatial variability of rainfall. Overall, we conclude that the antecedent catchment wetness and catchment type play an important role in controlling the significance of the spatial distribution of rainfall on streamflow. Results show a relationship between hydrograph characteristics (streamflow peak and volume) and the degree of spatial variability of rainfall for the impermeable catchments under dry antecedent conditions, although this decreases at larger scales; however this sensitivity is significantly undermined under wet antecedent conditions. Although there is indication that the impact of spatial rainfall on streamflow varies as a function of catchment scale, the variability of antecedent conditions between the synthetic catchments seems to mask this significance. Finally, hydrograph responses to different spatial patterns in rainfall depend on assumptions used for model parameter estimation and also the spatial variation in parameters indicating the need of an uncertainty framework in such investigation.

The Application of Censored Regression Models in Low Streamflow Analyses

NASA Astrophysics Data System (ADS)

Kroll, C.; Luz, J.

2003-12-01

Estimation of low streamflow statistics at gauged and ungauged river sites is often a daunting task. This process is further confounded by the presence of intermittent streamflows, where streamflow is sometimes reported as zero, within a region. Streamflows recorded as zero may be zero, or may be less than the measurement detection limit. Such data is often referred to as censored data. Numerous methods have been developed to characterize intermittent streamflow series. Logit regression has been proposed to develop regional models of the probability annual lowflows series (such as 7-day lowflows) are zero. In addition, Tobit regression, a method of regression that allows for censored dependent variables, has been proposed for lowflow regional regression models in regions where the lowflow statistic of interest estimated as zero at some sites in the region. While these methods have been proposed, their use in practice has been limited. Here a delete-one jackknife simulation is presented to examine the performance of Logit and Tobit models of 7-day annual minimum flows in 6 USGS water resource regions in the United States. For the Logit model, an assessment is made of whether sites are correctly classified as having at least 10% of 7-day annual lowflows equal to zero. In such a situation, the 7-day, 10-year lowflow (Q710), a commonly employed low streamflow statistic, would be reported as zero. For the Tobit model, a comparison is made between results from the Tobit model, and from performing either ordinary least squares (OLS) or principal component regression (PCR) after the zero sites are dropped from the analysis. Initial results for the Logit model indicate this method to have a high probability of correctly classifying sites into groups with Q710s as zero and non-zero. Initial results also indicate the Tobit model produces better results than PCR and OLS when more than 5% of the sites in the region have Q710 values calculated as zero.

Temporal rainfall estimation using input data reduction and model inversion

NASA Astrophysics Data System (ADS)

Wright, A. J.; Vrugt, J. A.; Walker, J. P.; Pauwels, V. R. N.

2016-12-01

Floods are devastating natural hazards. To provide accurate, precise and timely flood forecasts there is a need to understand the uncertainties associated with temporal rainfall and model parameters. The estimation of temporal rainfall and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of rainfall input to be considered when estimating model parameters and provides the ability to estimate rainfall from poorly gauged catchments. Current methods to estimate temporal rainfall distributions from streamflow are unable to adequately explain and invert complex non-linear hydrologic systems. This study uses the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia. The reduction of rainfall to DWT coefficients allows the input rainfall time series to be simultaneously estimated along with model parameters. The estimation process is conducted using multi-chain Markov chain Monte Carlo simulation with the DREAMZS algorithm. The use of a likelihood function that considers both rainfall and streamflow error allows for model parameter and temporal rainfall distributions to be estimated. Estimation of the wavelet approximation coefficients of lower order decomposition structures was able to estimate the most realistic temporal rainfall distributions. These rainfall estimates were all able to simulate streamflow that was superior to the results of a traditional calibration approach. It is shown that the choice of wavelet has a considerable impact on the robustness of the inversion. The results demonstrate that streamflow data contains sufficient information to estimate temporal rainfall and model parameter distributions. The extent and variance of rainfall time series that are able to simulate streamflow that is superior to that simulated by a traditional calibration approach is a demonstration of equifinality. The use of a likelihood function that considers both rainfall and streamflow error combined with the use of the DWT as a model data reduction technique allows the joint inference of hydrologic model parameters along with rainfall.

mizuRoute version 1: A river network routing tool for a continental domain water resources applications

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Sampson, Kevin; Nijssen, Bart; Mao, Yixin; McMillan, Hilary; Viger, Roland; Markstrom, Steven; Hay, Lauren E.; Woods, Ross; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

This paper describes the first version of a stand-alone runoff routing tool, mizuRoute. The mizuRoute tool post-processes runoff outputs from any distributed hydrologic model or land surface model to produce spatially distributed streamflow at various spatial scales from headwater basins to continental-wide river systems. The tool can utilize both traditional grid-based river network and vector-based river network data. Both types of river network include river segment lines and the associated drainage basin polygons, but the vector-based river network can represent finer-scale river lines than the grid-based network. Streamflow estimates at any desired location in the river network can be easily extracted from the output of mizuRoute. The routing process is simulated as two separate steps. First, hillslope routing is performed with a gamma-distribution-based unit-hydrograph to transport runoff from a hillslope to a catchment outlet. The second step is river channel routing, which is performed with one of two routing scheme options: (1) a kinematic wave tracking (KWT) routing procedure; and (2) an impulse response function – unit-hydrograph (IRF-UH) routing procedure. The mizuRoute tool also includes scripts (python, NetCDF operators) to pre-process spatial river network data. This paper demonstrates mizuRoute's capabilities to produce spatially distributed streamflow simulations based on river networks from the United States Geological Survey (USGS) Geospatial Fabric (GF) data set in which over 54 000 river segments and their contributing areas are mapped across the contiguous United States (CONUS). A brief analysis of model parameter sensitivity is also provided. The mizuRoute tool can assist model-based water resources assessments including studies of the impacts of climate change on streamflow.

Nine Hundred Years of Weekly Streamflows: Stochastic Downscaling of Ensemble Tree-Ring Reconstructions

NASA Astrophysics Data System (ADS)

Sauchyn, David; Ilich, Nesa

2017-11-01

We combined the methods and advantages of stochastic hydrology and paleohydrology to estimate 900 years of weekly flows for the North and South Saskatchewan Rivers at Edmonton and Medicine Hat, Alberta, respectively. Regression models of water-year streamflow were constructed using historical naturalized flow data and a pool of 196 tree-ring (earlywood, latewood, and annual) ring-width chronologies from 76 sites. The tree-ring models accounted for up to 80% of the interannual variability in historical naturalized flows. We developed a new algorithm for generating stochastic time series of weekly flows constrained by the statistical properties of both the historical record and proxy streamflow data, and by the necessary condition that weekly flows correlate between the end of a year and the start of the next. A second innovation, enabled by the density of our tree-ring network, is to derive the paleohydrology from an ensemble of 100 statistically significant reconstructions at each gauge. Using paleoclimatic data to generate long series of weekly flow estimates augments the short historical record with an expanded range of hydrologic variability, including sequences of wet and dry years of greater length and severity. This unique hydrometric time series will enable evaluation of the reliability of current water supply and management systems given the range of hydroclimatic variability and extremes contained in the stochastic paleohydrology. It also could inform evaluation of the uncertainty in climate model projections, given that internal hydroclimatic variability is the dominant source of uncertainty.

Streamflow monitoring and statistics for development of water rights claims for Wild and Scenic Rivers, Owyhee Canyonlands Wilderness, Idaho, 2012

USGS Publications Warehouse

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.

Hydrologic response across a snow persistence gradient on the west and east slopes of the Rocky Mountains in Colorado

NASA Astrophysics Data System (ADS)

Richard, G. A.; Hammond, J. C.; Kampf, S. K.; Moore, C. D.; Eurich, A.

2017-12-01

Snowpack trend analyses and modeling studies suggest that lower elevation snowpacks in mountain regions are most sensitive to drought and warming temperatures, however, in Colorado, most snow monitoring occurs in the high elevations where snow lasts throughout the winter and most streamflow monitoring occurs at lower elevations. The lack of combined snow and streamflow monitoring in watersheds along the transition from intermittent to persistent snow creates a gap in our understanding of snowmelt and runoff within the intermittent-persistent snow transition. Expanded hydrologic monitoring that spans the gradient of snow conditions in Colorado can help improve streamflow prediction and inform land and water managers. This study established hydrologic monitoring watersheds in intermittent, transitional, and persistent snow zones on the east slope and west slope of the Rocky Mountains in Colorado, and uses this monitoring network to improve understanding of how snow accumulation and melt affect soil moisture and streamflow generation under different snow conditions. We monitored six small watersheds (three west slope, three east slope) (0.8 to 3.9 km2) that drain intermittent, transitional, and persistent snow zones. At each site, we measured: streamflow, snow depth, soil moisture, precipitation, air temperature, and snow water equivalent (SWE). In our first season of monitoring, the west slope persistent and transitional sites had more mid-winter melt and infiltration, shorter snowpack duration, and lower peak SWE than the east slope sites. Snow cover remained at the east slope persistent site into June, whereas much of the snow at the persistent site on the west slope had already melted by early June. The difference in soil water input likely has consequences for streamflow response that we will continue to examine in future years. At the west slope intermittent site, the stream did not flow during the entire first year of monitoring, while at the east slope intermittent site, the streams flowed intermittently during winter and spring, likely a result of different subsurface geology. With our ongoing watershed monitoring across a broad range of snow conditions in Colorado, we continue to learn about the factors that increase or decrease streamflow in the headwater streams that supply the state's major rivers.

Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model

NASA Astrophysics Data System (ADS)

Yaseen, Zaher Mundher; Ebtehaj, Isa; Bonakdari, Hossein; Deo, Ravinesh C.; Danandeh Mehr, Ali; Mohtar, Wan Hanna Melini Wan; Diop, Lamine; El-shafie, Ahmed; Singh, Vijay P.

2017-11-01

The present study proposes a new hybrid evolutionary Adaptive Neuro-Fuzzy Inference Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a novel combination of the ANFIS model with the firefly algorithm as an optimizer tool to construct a hybrid ANFIS-FFA model. The results of the ANFIS-FFA model is compared with the classical ANFIS model, which utilizes the fuzzy c-means (FCM) clustering method in the Fuzzy Inference Systems (FIS) generation. The historical monthly streamflow data for Pahang River, which is a major river system in Malaysia that characterized by highly stochastic hydrological patterns, is used in the study. Sixteen different input combinations with one to five time-lagged input variables are incorporated into the ANFIS-FFA and ANFIS models to consider the antecedent seasonal variations in historical streamflow data. The mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (r) are used to evaluate the forecasting performance of ANFIS-FFA model. In conjunction with these metrics, the refined Willmott's Index (Drefined), Nash-Sutcliffe coefficient (ENS) and Legates and McCabes Index (ELM) are also utilized as the normalized goodness-of-fit metrics. Comparison of the results reveals that the FFA is able to improve the forecasting accuracy of the hybrid ANFIS-FFA model (r = 1; RMSE = 0.984; MAE = 0.364; ENS = 1; ELM = 0.988; Drefined = 0.994) applied for the monthly streamflow forecasting in comparison with the traditional ANFIS model (r = 0.998; RMSE = 3.276; MAE = 1.553; ENS = 0.995; ELM = 0.950; Drefined = 0.975). The results also show that the ANFIS-FFA is not only superior to the ANFIS model but also exhibits a parsimonious modelling framework for streamflow forecasting by incorporating a smaller number of input variables required to yield the comparatively better performance. It is construed that the FFA optimizer can thus surpass the accuracy of the traditional ANFIS model in general, and is able to remove the false (inaccurately) forecasted data in the ANFIS model for extremely low flows. The present results have wider implications not only for streamflow forecasting purposes, but also for other hydro-meteorological forecasting variables requiring only the historical data input data, and attaining a greater level of predictive accuracy with the incorporation of the FFA algorithm as an optimization tool in an ANFIS model.

Multi-time-scale hydroclimate dynamics of a regional watershed and links to large-scale atmospheric circulation: Application to the Seine river catchment, France

NASA Astrophysics Data System (ADS)

Massei, N.; Dieppois, B.; Hannah, D. M.; Lavers, D. A.; Fossa, M.; Laignel, B.; Debret, M.

2017-03-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating correlation between large and local scales, empirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: (i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and (ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the links between large and local scales were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach, which integrated discrete wavelet multiresolution analysis for reconstructing monthly regional hydrometeorological processes (predictand: precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector). This approach basically consisted in three steps: 1 - decomposing large-scale climate and hydrological signals (SLP field, precipitation or streamflow) using discrete wavelet multiresolution analysis, 2 - generating a statistical downscaling model per time-scale, 3 - summing up all scale-dependent models in order to obtain a final reconstruction of the predictand. The results obtained revealed a significant improvement of the reconstructions for both precipitation and streamflow when using the multiresolution ESD model instead of basic ESD. In particular, the multiresolution ESD model handled very well the significant changes in variance through time observed in either precipitation or streamflow. For instance, the post-1980 period, which had been characterized by particularly high amplitudes in interannual-to-interdecadal variability associated with alternating flood and extremely low-flow/drought periods (e.g., winter/spring 2001, summer 2003), could not be reconstructed without integrating wavelet multiresolution analysis into the model. In accordance with previous studies, the wavelet components detected in SLP, precipitation and streamflow on interannual to interdecadal time-scales could be interpreted in terms of influence of the Gulf-Stream oceanic front on atmospheric circulation.

Streamflow characteristics of small tributaries of Rock Creek, Milk River basin, Montana, base period water years 1983-87

USGS Publications Warehouse

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)

Modeling streamflow from coupled airborne laser scanning and acoustic Doppler current profiler data

USGS Publications Warehouse

Norris, Lam; Kean, Jason W.; Lyon, Steve

2016-01-01

The rating curve enables the translation of water depth into stream discharge through a reference cross-section. This study investigates coupling national scale airborne laser scanning (ALS) and acoustic Doppler current profiler (ADCP) bathymetric survey data for generating stream rating curves. A digital terrain model was defined from these data and applied in a physically based 1-D hydraulic model to generate rating curves for a regularly monitored location in northern Sweden. Analysis of the ALS data showed that overestimation of the streambank elevation could be adjusted with a root mean square error (RMSE) block adjustment using a higher accuracy manual topographic survey. The results of our study demonstrate that the rating curve generated from the vertically corrected ALS data combined with ADCP data had lower errors (RMSE = 0.79 m3/s) than the empirical rating curve (RMSE = 1.13 m3/s) when compared to streamflow measurements. We consider these findings encouraging as hydrometric agencies can potentially leverage national-scale ALS and ADCP instrumentation to reduce the cost and effort required for maintaining and establishing rating curves at gauging station sites similar to the Röån River.

Geochemical baseline studies and relations between water quality and streamflow in the upper Blackfoot Watershed, Montana: data for July 1997-December 1998

USGS Publications Warehouse

Nagorski, Sonia A.; Moore, Johnnie N.; Smith, David B.

2001-01-01

We used ultraclean sampling techniques to study the solute (operationally defined as <0.2 ?m) surface water geochemistry at five sites along the Upper Blackfoot River and four sites along the Landers Fork, some in more detail and more regularly than others. We collected samples also from Hogum Creek, a tributary to the Blackfoot, from Copper Creek, a tributary to the Landers Fork, and from ground water seeps contributing to the flow along the Landers Fork. To better define the physical dynamics of the hydrologic system and to determine geochemical loads, we measured streamflow at all the sites where we took samples for water quality analysis. The Upper Blackfoot River, which drains historic mines ca. 20 Km upstream of the study area, had higher trace metal concentrations than did the Landers Fork, which drains the pristine Scapegoat Wilderness area. In both rivers, many of the major elements were inversely related to streamflow, and at some sites, several show a hysteresis effect in which the concentrations were lower on the rising limb of the hydrograph than on the falling limb. However, many of the trace elements followed far more irregular trends, especially in the Blackfoot River. Elements such as As, Cu, Fe, Mn, S, and Zn exhibited complex and variable temporal patterns, which included almost no response to streamflow differences, increased concentrations following a summer storm and at the start of snowmelt in the spring, and/or increased concentrations throughout the course of spring runoff. In summary, complex interactions between the timing and magnitude of streamflow with physical and chemical processes within the watershed appeared to greatly influence the geochemistry at the sites, and streamflow values alone were not good predictors of solute concentrations in the rivers.

Predicting long-term streamflow variability in moist eucalypt forests using forest growth models and a sapwood area index

NASA Astrophysics Data System (ADS)

Jaskierniak, D.; Kuczera, G.; Benyon, R.

2016-04-01

A major challenge in surface hydrology involves predicting streamflow in ungauged catchments with heterogeneous vegetation and spatiotemporally varying evapotranspiration (ET) rates. We present a top-down approach for quantifying the influence of broad-scale changes in forest structure on ET and hence streamflow. Across three catchments between 18 and 100 km2 in size and with regenerating Eucalyptus regnans and E. delegatensis forest, we demonstrate how variation in ET can be mapped in space and over time using LiDAR data and commonly available forest inventory data. The model scales plot-level sapwood area (SA) to the catchment-level using basal area (BA) and tree stocking density (N) estimates in forest growth models. The SA estimates over a 69 year regeneration period are used in a relationship between SA and vegetation induced streamflow loss (L) to predict annual streamflow (Q) with annual rainfall (P) estimates. Without calibrating P, BA, N, SA, and L to Q data, we predict annual Q with R2 between 0.68 and 0.75 and Nash Sutcliffe efficiency (NSE) between 0.44 and 0.48. To remove bias, the model was extended to allow for runoff carry-over into the following year as well as minor correction to rainfall bias, which produced R2 values between 0.72 and 0.79, and NSE between 0.70 and 0.79. The model under-predicts streamflow during drought periods as it lacks representation of ecohydrological processes that reduce L with either reduced growth rates or rainfall interception during drought. Refining the relationship between sapwood thickness and forest inventory variables is likely to further improve results.

Guidelines and Procedures for Computing Time-Series Suspended-Sediment Concentrations and Loads from In-Stream Turbidity-Sensor and Streamflow Data

USGS Publications Warehouse

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.

Spatiotemporal variability of inorganic nutrients during wastewater effluent dominated streamflow conditions in Indian Creek, Johnson County, Kansas, 2012–15

USGS Publications Warehouse

Foster, Guy M.; Graham, Jennifer L.; Williams, Thomas J.; King, Lindsey R.

2016-10-31

Nutrients, particularly nitrogen and phosphorus, are a leading cause of water-quality impairment in Kansas and the Nation. Indian Creek is one of the most urban drainage basins in Johnson County, Kansas, and environmental and biological conditions are affected by contaminants from point and other urban sources. The Johnson County Douglas L. Smith Middle Basin (hereinafter Middle Basin) wastewater treatment facility (WWTF) is the largest point-source discharge on Indian Creek. A second facility, the Tomahawk Creek WWTF, discharges into Indian Creek approximately 11.6 kilometers downstream from the Middle Basin WWTF. To better characterize the spatiotemporal variability of nutrients in Indian Creek, the U.S. Geological Survey, in cooperation with the Kansas Department of Health and Environment and Johnson County Wastewater, collected high-resolution spatial and temporal (a large number of samples collected over the entire reach or at single locations over a long period of time) inorganic nutrient (nitrate plus nitrite and orthophosphorus) data using a combination of discrete samples and sensor-measured data during 2012 through 2015.Nutrient patterns observed in Indian Creek along the upstream-downstream gradient during wastewater effluent dominated streamflow conditions were largely affected by the WWTFs and by travel time of the parcels of water. Nitrate plus nitrite concentrations in the Middle Basin WWTF effluent and at downstream sites varied by as much as 6 milligrams per liter over a 24-hour period. The cyclical variability in the Middle Basin WWTF effluent generated a nitrate plus nitrite pulse that could be tracked for approximately 11.5 kilometers downstream in Indian Creek, until the effect was masked by the Tomahawk Creek WWTF effluent discharge. All longitudinal surveys showed the same general patterns along the upstream-downstream gradient, though streamflows, wastewater effluent contributions to streamflow, and nutrient concentrations spanned a wide range. Differences in orthophosphorus and nitrate plus nitrite patterns were clear along the upstream-downstream gradient in Indian Creek, and orthophosphorus concentrations were not as variable as nitrate plus nitrite concentrations. In general, nitrate plus nitrite concentrations decreased downstream from the Middle Basin WWTF to minima near the confluence with Tomahawk Creek, increased downstream from the Tomahawk Creek WWTF, and then varied little within the study reach. Orthophosphorus concentrations generally decreased downstream from the Middle Basin WWTF.Despite the marked variability in nitrate plus nitrite concentrations caused by the Middle Basin WWTF effluent discharges, decreases in nitrate plus nitrite concentrations were discernable along the study reach between the two WWTFs. Decreases in nitrate plus nitrite concentrations along study reach were less variable than the cyclical variability typically measured, reiterating the effect of the Middle Basin WWTF effluent discharges on the spatiotemporal variability of nitrate plus nitrite in Indian Creek. Although decreases and rates of change in nitrate plus nitrite concentration were similar between the upper and lower reaches of Indian Creek, relations with initial nitrate plus nitrite concentrations and seasonal patterns were different between the upper (from College to the Marty study sites) and lower reaches (from Marty to the Mission Farms study sites) and did not reflect patterns observed for the overall reach. Quantifying the decreases in nitrate plus nitrite concentration caused by dilution and other in-stream processes were beyond the scope of this study, and were limited by available data. The data that are available suggest that dilution and other in-stream processes play a role in decreasing nitrate plus nitrite concentrations downstream from the Middle Basin WWTF in Indian Creek.Analysis of the spatiotemporal variability of nutrients focused on below-normal and normal streamflow conditions, when streamflow and nutrient conditions in Indian Creek were largely controlled by WWTF effluent flows and nutrient removal processes. Spatial and temporal data indicate there are decreases in nutrient concentrations along the upstream-downstream gradient in Indian Creek, but quantifying decreases is complicated by the variability in nutrient concentrations caused by the WWTFs. During below-normal and normal streamflow conditions, Indian Creek nutrient concentrations downstream from the Middle Basin WWTF primarily reflect effluent concentrations in the hours or days before depending on relative distance downstream.

Trends in timing, magnitude, and duration of summer and fall/winter streamflows for unregulated coastal river basins in Maine during the 20th century

USGS Publications Warehouse

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.

Streamflow Statistics for the Narraguagus River at Cherryfield, Maine

USGS Publications Warehouse

Dudley, Robert W.; Nielsen, Joseph P.

2000-01-01

Streamflow data have been collected for the Narraguagus River from 1948 to the present (2000) at the U.S. Geological Survey (USGS) streamgaging station at Cherryfield, Maine. This report describes a study done by the USGS to determine streamflow statistics using the streamflow record at the Narraguagus River station for use in total water use management plans implemented by State and Federal agencies. Because the effect of changes in irrigation practices from 1993 to the present on streamflow in the Narraguagus basin is unknown and potentially significant, streamflow data after December 1992 were not used in the determination of the streamflow statistics. For the period 1948- 92, monthly median streamflows range from 93.0 ft3/s (August) to 1,000 ft3/s (April). The median streamflow for the selected period of record for all days (1948-92) is 302 ft3/s.

Influence of groundwater pumping on streamflow restoration following upstream dam removal

USGS Publications Warehouse

Constantz, J.; Essaid, H.

2007-01-01

We compared streamflow in basins under the combined impacts of an upland dam and groundwater pumping withdrawals, by examining streamflow in the presence and absence of each impact. As a qualitative analysis, inter-watersbed streamflow comparisons were performed for several rivers flowing into the east side of the Central Valley, CA. Results suggest that, in the absence of upland dams supporting large reservoirs, some reaches of these rivers might develop ephemeral streamflow in late summer. As a quantitative analysis, we conducted a series of streamflow/ groundwater simulations (using MODFLOW-2000 plus the streamflow routing package, SFR1) for a representative hypothetical watershed, with an upland dam and groundwater pumping in the downstream basin, under humid, semi-arid, and and conditions. As a result of including the impact of groundwater pumping, post-dam removal simulated streamflow was significantly less than natural streamflow. The model predicts extensive ephemeral conditions in the basin during September for both the arid and semi-arid cases. The model predicts continued perennial conditions in the humid case, but spatially weighted, average streamflow of only 71% of natural September streamflow, as a result of continued pumping after dam removal.

Comprehensive, Process-based Identification of Hydrologic Models using Satellite and In-situ Water Storage Data: A Multi-objective calibration Approach

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.

Comparison of historical streamflows to 2013 Streamflows in the Williamson, Sprague, and Wood Rivers, Upper Klamath Lake Basin, Oregon

USGS Publications Warehouse

Hess, Glen W.; Stonewall, Adam J.

2014-01-01

In 2013, the Upper Klamath Lake Basin, Oregon, experienced a dry spring, resulting in an executive order declaring a state of drought emergency in Klamath County. The 2013 drought limited the water supply and led to a near-total cessation of surface-water diversions for irrigation above Upper Klamath Lake once regulation was implemented. These conditions presented a unique opportunity to understand the effects of water right regulation on streamflows. The effects of regulation of diversions were evaluated by comparing measured 2013 streamflow with data from hydrologically similar years. Years with spring streamflow similar to that in 2013 measured at the Sprague River gage at Chiloquin from water years 1973 to 2012 were used to define a Composite Index Year (CIY; with diversions) for comparison to measured 2013 streamflows (no diversions). The best-fit 6 years (1977, 1981, 1990, 1991, 1994, and 2001) were used to determine the CIY. Two streams account for most of the streamflow into Upper Klamath Lake: the Williamson and Wood Rivers. Most streamflow into the lake is from the Williamson River Basin, which includes the Sprague River. Because most of the diversion regulation affecting the streamflow of the Williamson River occurred in the Sprague River Basin, and because of uncertainties about historical flows in a major diversion above the Williamson River gage, streamflow data from the Sprague River were used to estimate the change in streamflow from regulation of diversions for the Williamson River Basin. Changes in streamflow outside of the Sprague River Basin were likely minor relative to total streamflow. The effect of diversion regulation was evaluated using the “Baseflow Method,” which compared 2013 baseflow to baseflow of the CIY. The Baseflow Method reduces the potential effects of summer precipitation events on the calculations. A similar method using streamflow produced similar results, however, despite at least one summer precipitation event. The result of the analysis estimates that streamflow from the Williamson River Basin to Upper Klamath Lake increased by approximately 14,100 acre-feet between July 1 and September 30 relative to prior dry years as a result of regulation of surface-water diversions in 2013. Quantifying the change in streamflow from regulation of diversion for the Wood River Basin was likely less accurate due to a lack of long-term streamflow data. An increase in streamflow from regulation of diversions in the Wood River Basin of roughly 5,500 acre-feet was estimated by comparing the average August and September streamflow in 2013 with historical August and September streamflow. Summing the results of the estimated streamflow gain of the Williamson River Basin (14,100 acre-feet) and Wood River (5,500 acre-feet) gives a total estimated increase in streamflow into Upper Klamath Lake resulting from the July 1–September 2013 regulation of diversions of approximately 19,600 acre-feet.

Preliminary assessment of streamflow characteristics for selected streams at Fort Gordon, Georgia, 1999-2000

USGS Publications Warehouse

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.

WaterWatch - Maps, graphs, and tables of current, recent, and past streamflow conditions

USGS Publications Warehouse

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.

Low flows and water temperature risks to Asian coal power plants in a warming world

NASA Astrophysics Data System (ADS)

Wang, Y.; Byers, E.; Parkinson, S.; Wanders, N.; Wada, Y.; Bielicki, J. M.

2017-12-01

Thermoelectric power generation requires cooling, normally provided by wet cooling systems. The withdrawal and discharge of cooling water are subject to regulation. Therefore, operation of power plants may be vulnerable to changes in streamflow and rises in water temperatures. In Asia, about 489 GW of coal-fired power plants are currently under construction, permitted, or announced. Using a comprehensive dataset of these planned coal power plants (PCPPs) and cooling water use models, we investigated whether electricity generation at these power plants will be limited by streamflow and water temperature. Daily streamflow and water temperature time series are from the high-resolution (0.08ox0.08o) runs of the PCRGLOBWB hydrological model, driven by downscaled meteorological forcing from five global climate models. We compared three climate change scenarios (1.5oC, 2oC, and 3oC warming in global mean temperature) and three cooling system choice scenarios (freshwater once-through, freshwater cooling tower, and "business-as-usual" - where a PCPP uses the same cooling system as the nearest existing coal power plant). The potential available capacity of the PCPPs increase slightly from the 1.5oC to the 2oC and 3oC warming scenario due to increase in streamflow. The once-through cooling scenario results in virtually zero available capacity at the PCPPs. The other two cooling scenarios result in about 20% of the planned capacity being unavailable under all warming scenarios. Hotspots of the most water-limited PCPPs are in Pakistan, northwestern India, northwestern and north-central China, and northern Vietnam, where most of the PCPPs will face 30% to 90% unavailable nameplate capacity on annual average. Since coal power plants cannot operate effectively when the capacity factor falls below a minimum load level (about 20% to 50%), the actual limitation on generation capacity would be larger. In general, the PCPPs that will have the highest limitation on annual average capacity will also have the most frequent and longest periods of interrupted operation. These results suggest that to ensure security of energy supply and avoid over-withdrawing water resources, the water-limited PCPPs should implement adaptation measures such as dry-cooling, combined heat- and power, or using recycled wastewater.

Water chemistry, seepage investigation, streamflow, reservoir storage, and annual availability of water for the San Juan-Chama Project, northern New Mexico, 1942-2010

USGS Publications Warehouse

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.

Analysis of snow-glacial historical and projected flows in Olivares river basin. Comparison between DHSVM and WEAP models.

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.

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.

A century of hydrological variability and trends in the Fraser River Basin

NASA Astrophysics Data System (ADS)

Déry, Stephen J.; Hernández-Henríquez, Marco A.; Owens, Philip N.; Parkes, Margot W.; Petticrew, Ellen L.

2012-06-01

This study examines the 1911-2010 variability and trends in annual streamflow at 139 sites across the Fraser River Basin (FRB) of British Columbia (BC), Canada. The Fraser River is the largest Canadian waterway flowing to the Pacific Ocean and is one of the world’s greatest salmon rivers. Our analyses reveal high runoff rates and low interannual variability in alpine and coastal rivers, and low runoff rates and high interannual variability in most streams in BC’s interior. The interannual variability in streamflow is also low in rivers such as the Adams, Chilko, Quesnel and Stuart where the principal salmon runs of the Fraser River occur. A trend analysis shows a spatially coherent signal with increasing interannual variability in streamflow across the FRB in recent decades, most notably in spring and summer. The upward trend in the coefficient of variation in annual runoff coincides with a period of near-normal annual runoff for the Fraser River at Hope. The interannual variability in streamflow is greater in regulated rather than natural systems; however, it is unclear whether it is predominantly flow regulation that leads to these observed differences. Environmental changes such as rising air temperatures, more frequent polarity changes in large-scale climate teleconnections such as El Niño-Southern Oscillation and Pacific Decadal Oscillation, and retreating glaciers may be contributing to the greater range in annual runoff fluctuations across the FRB. This has implications for ecological processes throughout the basin, for example affecting migrating and spawning salmon, a keystone species vital to First Nations communities as well as to commercial and recreational fisheries. To exemplify this linkage between variable flows and biological responses, the unusual FRB runoff anomalies observed in 2010 are discussed in the context of that year’s sockeye salmon run. As the climate continues to warm, greater variability in annual streamflow, and hence in hydrological extremes, may influence ecological processes and human usage throughout the FRB in the 21st century.

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).

Regional Climate and Streamflow Projections in North America Under IPCC CMIP5 Scenarios

NASA Astrophysics Data System (ADS)

Chang, H. I.; Castro, C. L.; Troch, P. A. A.; Mukherjee, R.

2014-12-01

The Colorado River system is the predominant source of water supply for the Southwest U.S. and is already fully allocated, making the region's environmental and economic health particularly sensitive to annual and multi-year streamflow variability. Observed streamflow declines in the Colorado Basin in recent years are likely due to synergistic combination of anthropogenic global warming and natural climate variability, which are creating an overall warmer and more extreme climate. IPCC assessment reports have projected warmer and drier conditions in arid to semi-arid regions (e.g. Solomon et al. 2007). The NAM-related precipitation contributes to substantial Colorado streamflows. Recent climate change studies for the Southwest U.S. region project a dire future, with chronic drought, and substantially reduced Colorado River flows. These regional effects reflect the general observation that climate is being more extreme globally, with areas climatologically favored to be wet getting wetter and areas favored to be dry getting drier (Wang et al. 2012). Multi-scale downscaling modeling experiments are designed using recent IPCC AR5 global climate projections, which incorporate regional climate and hydrologic modeling components. The Weather Research and Forecasting model (WRF) has been selected as the main regional modeling tool; the Variable Infiltration Capacity model (VIC) will be used to generate streamflow projections for the Colorado River Basin. The WRF domain is set up to follow the CORDEX-North America guideline with 25km grid spacing, and VIC model is individually calibrated for upper and lower Colorado River basins in 1/8° resolution. The multi-scale climate and hydrology study aims to characterize how the combination of climate change and natural climate variability is changing cool and warm season precipitation. Further, to preserve the downscaled RCM sensitivity and maintain a reasonable climatology mean based on observed record, a new bias correction technique is applied when using the RCM climatology to the streamflow model. Of specific interest is how major droughts associated with La Niña-like conditions may worsen in the future, as these are the times when the Colorado River system is most critically stressed and would define the "worst case" scenario for water resource planning.

Significance of Bioturbated Layer (BTL) and Deep Groundwater Storage on Runoff in Steep Saprolitic Tropical Lowlands Catchment

NASA Astrophysics Data System (ADS)

Cheng, Y.; Ogden, F. L.; Zhu, J.

2016-12-01

Bioturbated soil layers (BTLs) play a significant role in hydrological response and provisioning of ecosystem services in steep, saprolitic, tropical lowlands catchments. In this study, a new physically-based model formulation was developed for testing of runoff generation hypotheses. A main feature in the model formulation is explicit simulation of hydrological processes in the BTL including macropores, which our field observations show are ubiquitous, and deep groundwater stores that provide streamflow during the dry season The numerical model developed includes two main flow paths in the BTL, including one-dimensional (1D) vertical infiltration and two-dimensional (2D) lateral flows in both macropores and the soil matrix. Hydrological processes incorporated along with the BTL processes include intercepted rainfall, evapotranspiration, 2D surface flow and 1D deep groundwater discharge. This model was first tested in a 6.5 ha secondary succession catchment, that is under study by the Smithsonian Tropical Research Institute, Agua Salud project in Panama, which is dominated by steep slopes. With the incorporation of lateral macropore flow mechanism in the BTL, the model performs better than only including soil matrix flow in the BTL especially in simulating baseflow dynamics, which illustrates the importance of preferential flow from the BTL to stream discharge dynamics. The increase in the BTL thickness promotes more flow through the BTL and increases storage in both the BTL and the deep groundwater reservoir, but decreases the total streamflow and overland flow. Lateral macropore diameter distribution influences flows more than the macropore number or distribution type. The model has thus far passed falsification tests during the early wet season. Complexity in subsurface storage and base flow generation offer a new challenge for this model. The overall objective is to develop a model formulation that is useful in practical applications related to land-use management, provisioning of ecosystem services, and water security in similar tropical settings with distinct dry and wet seasons or in the humid tropics during periods of drought.

Separating the impacts of climate change and human activities on streamflow: A review of methodologies and critical assumptions

NASA Astrophysics Data System (ADS)

Dey, Pankaj; Mishra, Ashok

2017-05-01

Climate change and human activity are two major drivers that alter hydrological cycle processes and cause change in spatio-temporal distribution of water availability. Streamflow, the most important component of hydrological cycle undergoes variation which is expected to be influenced by climate change as well as human activities. Since these two affecting conditions are time dependent, having unequal influence, identification of the change point in natural flow regime is of utmost important to separate the individual impact of climate change and human activities on streamflow variability. Subsequently, it is important as well for framing adaptation strategies and policies for regional water resources planning and management. In this paper, a comprehensive review of different approaches used by research community to isolate the impacts of climate change and human activities on streamflow are presented. The important issues pertaining to different approaches, to make rational use of methodology, are discussed so that researcher and policymaker can understand the importance of individual methodology and its use in water resources management. A new approach has also been suggested to select a representative change point under different scenarios of human activities with incorporation of climate variability/change.

Rainier Mesa CAU Infiltration Model using INFILv3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levitt, Daniel G.; Kwicklis, Edward M.

The outline of this presentation are: (1) Model Inputs - DEM, Precipitation, Air temp, Soil props, Surface geology, Vegetation; (2) Model Pre-processing - Runoff Routing and sinks, Slope and Azimuth, Soil Ksat reduction with slope (to mitigate bathtub ring), Soil-Bedrock Interface permeabilities; (3) Model Calibration - ET using PEST, Chloride mass balance data, Streamflow using PEST; (4) Model Validation - Streamflow data not used for calibration; (5) Uncertainty Analysis; and (6) Results. Conclusions are: (1) Average annual infiltration rates =11 to 18 mm/year for RM domain; (2) Average annual infiltration rates = 7 to 11 mm/year for SM domain; (3)more » ET = 70% of precipitation for both domains; (4) Runoff = 8-9% for RM; and 22-24% for SM - Apparently high average runoff is caused by the truncation of the lowerelevation portions of watersheds where much of the infiltration of runoff waters would otherwise occur; (5) Model results are calibrated to measured ET, CMB data, and streamflow observations; (6) Model results are validated using streamflow observations discovered after model calibration was complete; (7) Use of soil Ksat reduction with slope to mitigate bathtub ring was successful (based on calibration results); and (8) Soil-bedrock K{_}interface is innovative approach.« less

Predicting future land cover change and its impact on streamflow and sediment load in a trans-boundary river basin

NASA Astrophysics Data System (ADS)

Wang, Jie; Wang, Hao; Ning, Shaowei; Hiroshi, Ishidaira

2018-06-01

Sediment load can provide very important perspective on erosion of river basin. The changes of human-induced vegetation cover, such as deforestation or afforestation, affect sediment yield process of a catchment. We have already evaluated that climate change and land cover change changed the historical streamflow and sediment yield, and land cover change is the main factor in Red river basin. But future streamflow and sediment yield changes under potential future land cover change scenario still have not been evaluated. For this purpose, future scenario of land cover change is developed based on historical land cover changes and land change model (LCM). In addition, future leaf area index (LAI) is simulated by ecological model (Biome-BGC) based on future land cover scenario. Then future scenarios of land cover change and LAI are used to drive hydrological model and new sediment rating curve. The results of this research provide information that decision-makers need in order to promote water resources planning efforts. Besides that, this study also contributes a basic framework for assessing climate change impacts on streamflow and sediment yield that can be applied in the other basins around the world.

Montana StreamStats—A method for retrieving basin and streamflow characteristics in Montana: Chapter A in Montana StreamStats

USGS Publications Warehouse

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.

Regional regression equations for estimation of natural streamflow statistics in Colorado

USGS Publications Warehouse

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.

Spatial patterns of March and September streamflow trends in Pacific Northwest Streams, 1958-2008

USGS Publications Warehouse

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.

The role of glacier changes and threshold definition in the characterisation of future streamflow droughts in glacierised catchments

NASA Astrophysics Data System (ADS)

Van Tiel, Marit; Teuling, Adriaan J.; Wanders, Niko; Vis, Marc J. P.; Stahl, Kerstin; Van Loon, Anne F.

2018-01-01

Glaciers are essential hydrological reservoirs, storing and releasing water at various timescales. Short-term variability in glacier melt is one of the causes of streamflow droughts, here defined as deficiencies from the flow regime. Streamflow droughts in glacierised catchments have a wide range of interlinked causing factors related to precipitation and temperature on short and long timescales. Climate change affects glacier storage capacity, with resulting consequences for discharge regimes and streamflow drought. Future projections of streamflow drought in glacierised basins can, however, strongly depend on the modelling strategies and analysis approaches applied. Here, we examine the effect of different approaches, concerning the glacier modelling and the drought threshold, on the characterisation of streamflow droughts in glacierised catchments. Streamflow is simulated with the Hydrologiska Byråns Vattenbalansavdelning (HBV-light) model for two case study catchments, the Nigardsbreen catchment in Norway and the Wolverine catchment in Alaska, and two future climate change scenarios (RCP4.5 and RCP8.5). Two types of glacier modelling are applied, a constant and dynamic glacier area conceptualisation. Streamflow droughts are identified with the variable threshold level method and their characteristics are compared between two periods, a historical (1975-2004) and future (2071-2100) period. Two existing threshold approaches to define future droughts are employed: (1) the threshold from the historical period; (2) a transient threshold approach, whereby the threshold adapts every year in the future to the changing regimes. Results show that drought characteristics differ among the combinations of glacier area modelling and thresholds. The historical threshold combined with a dynamic glacier area projects extreme increases in drought severity in the future, caused by the regime shift due to a reduction in glacier area. The historical threshold combined with a constant glacier area results in a drastic decrease of the number of droughts. The drought characteristics between future and historical periods are more similar when the transient threshold is used, for both glacier area conceptualisations. With the transient threshold, factors causing future droughts can be analysed. This study revealed the different effects of methodological choices on future streamflow drought projections and it highlights how the options can be used to analyse different aspects of future droughts: the transient threshold for analysing future drought processes, the historical threshold to assess changes between periods, the constant glacier area to analyse the effect of short-term climate variability on droughts and the dynamic glacier area to model more realistic future discharges under climate change.

QRev—Software for computation and quality assurance of acoustic doppler current profiler moving-boat streamflow measurements—Technical manual for version 2.8

USGS Publications Warehouse

Mueller, David S.

2016-06-21

The software program, QRev applies common and consistent computational algorithms combined with automated filtering and quality assessment of the data to improve the quality and efficiency of streamflow measurements and helps ensure that U.S. Geological Survey streamflow measurements are consistent, accurate, and independent of the manufacturer of the instrument used to make the measurement. Software from different manufacturers uses different algorithms for various aspects of the data processing and discharge computation. The algorithms used by QRev to filter data, interpolate data, and compute discharge are documented and compared to the algorithms used in the manufacturers’ software. QRev applies consistent algorithms and creates a data structure that is independent of the data source. QRev saves an extensible markup language (XML) file that can be imported into databases or electronic field notes software. This report is the technical manual for version 2.8 of QRev.

Techniques for estimating selected streamflow characteristics of rural unregulated streams in Ohio

USGS Publications Warehouse

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.

Analysis of trends in selected streamflow statistics for the Concho River Basin, Texas, 1916-2009

USGS Publications Warehouse

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.

Linear genetic programming application for successive-station monthly streamflow prediction

NASA Astrophysics Data System (ADS)

Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit

2014-09-01

In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.

Ground-Water Flow Model of the Sierra Vista Subwatershed and Sonoran Portions of the Upper San Pedro Basin, Southeastern Arizona, United States, and Northern Sonora, Mexico

USGS Publications Warehouse

Pool, D.R.; Dickinson, Jesse

2007-01-01

A numerical ground-water model was developed to simulate seasonal and long-term variations in ground-water flow in the Sierra Vista subwatershed, Arizona, United States, and Sonora, Mexico, portions of the Upper San Pedro Basin. This model includes the simulation of details of the groundwater flow system that were not simulated by previous models, such as ground-water flow in the sedimentary rocks that surround and underlie the alluvial basin deposits, withdrawals for dewatering purposes at the Tombstone mine, discharge to springs in the Huachuca Mountains, thick low-permeability intervals of silt and clay that separate the ground-water flow system into deep-confined and shallow-unconfined systems, ephemeral-channel recharge, and seasonal variations in ground-water discharge by wells and evapotranspiration. Steady-state and transient conditions during 1902-2003 were simulated by using a five-layer numerical ground- water flow model representing multiple hydrogeologic units. Hydraulic properties of model layers, streamflow, and evapotranspiration rates were estimated as part of the calibration process by using observed water levels, vertical hydraulic gradients, streamflow, and estimated evapotranspiration rates as constraints. Simulations approximate observed water-level trends throughout most of the model area and streamflow trends at the Charleston streamflow-gaging station on the San Pedro River. Differences in observed and simulated water levels, streamflow, and evapotranspiration could be reduced through simulation of climate-related variations in recharge rates and recharge from flood-flow infiltration.

Capture Versus Capture Zones: Clarifying Terminology Related to Sources of Water to Wells.

PubMed

Barlow, Paul M; Leake, Stanley A; Fienen, Michael N

2018-03-15

The term capture, related to the source of water derived from wells, has been used in two distinct yet related contexts by the hydrologic community. The first is a water-budget context, in which capture refers to decreases in the rates of groundwater outflow and (or) increases in the rates of recharge along head-dependent boundaries of an aquifer in response to pumping. The second is a transport context, in which capture zone refers to the specific flowpaths that define the three-dimensional, volumetric portion of a groundwater flow field that discharges to a well. A closely related issue that has become associated with the source of water to wells is streamflow depletion, which refers to the reduction in streamflow caused by pumping, and is a type of capture. Rates of capture and streamflow depletion are calculated by use of water-budget analyses, most often with groundwater-flow models. Transport models, particularly particle-tracking methods, are used to determine capture zones to wells. In general, however, transport methods are not useful for quantifying actual or potential streamflow depletion or other types of capture along aquifer boundaries. To clarify the sometimes subtle differences among these terms, we describe the processes and relations among capture, capture zones, and streamflow depletion, and provide proposed terminology to distinguish among them. Published 2018. This article is a U.S. Government work and is in the public domain in the USA. Groundwater published by Wiley Periodicals, Inc. on behalf of National Ground Water Association.

A hydrometric and geochemical approach to test the transmissivity feedback hypothesis during snowmelt

USGS Publications Warehouse

Kendall, K.A.; Shanley, J.B.; McDonnell, Jeffery J.

1999-01-01

To test the transmissivity feedback hypothesis of runoff generation, surface and subsurface waters were monitored and sampled during the 1996 snowmelt at various topographic positions in a 41 ha forested headwater catchment at Sleepers River, Vermont. Two conditions that promote transmissivity feedback existed in the catchment during the melt period. First, saturated hydraulic conductivity increased toward land surface, from a geometric mean of 3.6 mm h-1 in glacial till to 25.6 mm h-1 in deep soil to 54.0 mm h-1 in shallow soil. Second, groundwater levels rose to within 0.3 m of land surface at all riparian sites and most hillslope sites at peak melt. The importance of transmissivity feedback to streamflow generation was tested at the catchment scale by examination of physical and chemical patterns of groundwater in near-stream (discharge) and hillslope (recharge/lateral flow) zones, and within a geomorphic hollow (convergent flow). The presence of transmissivity feedback was supported by the abrupt increase in streamflow as the water table rose into the surficial, transmissive zone; a flattening of the groundwater level vs. streamflow curve occurred at most sites. This relation had a clockwise hysteresis (higher groundwater level for given discharge on rising limb than at same discharge on falling limb) at riparian sites, suggesting that the riparian zone was the dominant source area during the rising limb of the melt hydrograph. Hysteresis was counterclockwise at hillslope sites, suggesting that hillslope drainage controlled the snowmelt recession. End member mixing analysis using Ca, Mg, Na, dissolved organic carbon (DOC), and Si showed that stream chemistry could be explained as a two-component mixture of groundwater high in base cations and an O-horizon/overland flow water high in DOC. The dominance of shallow flow paths during events was indicated by the high positive correlation of DOC with streamflow (r2 = 0.82). Despite the occurrence of transmissivity feedback, hillslope till and soil water were ruled out as end members primarily because their distinctive high-Si composition had little or no effect on streamwater composition. Till water from the geomorphic hollow had a chemistry very close to streamwater base flow, and may represent the base flow end member better than the more concentrated riparian groundwater. During snowmelt, streamwater composition shifted as this base flow was diluted - not by shallow groundwater from the hillslope, but rather by a more surficial O-horizon/overland flow water.Surface and subsurface waters were analyzed to test the transmissivity feedback of runoff generation during the 1996 snowmelt in a catchment at Sleepers River, Vermont. The importance of transmissivity feedback to stream flow generation was tested by examination of physical and chemical patterns of groundwater in near-stream and hillslope zones within a geomorphic hollow. End member mixing analysis of Ca, Mg, Na, dissolved organic carbon (DOC), and Si showed that stream chemistry could be explained as a two-component mixture of groundwater high in base cations and an O-horizon/overland flow water high in DOC. The dominance of shallow water paths during the events was indicated by the high positive correlation of DOC with streamflow (r2 = 0.82).

Development of regression equations to revise estimates of historical streamflows for the St. Croix River at Stillwater, Minnesota (water years 1910-2011), and Prescott, Wisconsin (water years 1910-2007)

USGS Publications Warehouse

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.

Simulation of streamflow and estimation of streamflow constituent loads in the San Antonio River watershed, Bexar County, Texas, 1997-2001

USGS Publications Warehouse

Ockerman, Darwin J.; McNamara, Kenna C.

2003-01-01

The U.S. Geological Survey developed watershed models (Hydrological Simulation Program—FORTRAN) to simulate streamflow and estimate streamflow constituent loads from five basins that compose the San Antonio River watershed in Bexar County, Texas. Rainfall and streamflow data collected during 1997–2001 were used to calibrate and test the model. The model was configured so that runoff from various land uses and discharges from other sources (such as wastewater recycling facilities) could be accounted for to indicate sources of streamflow. Simulated streamflow volumes were used with land-use-specific, water-quality data to compute streamflow loads of selected constituents from the various streamflow sources.Model simulations for 1997–2001 indicate that inflow from the upper Medina River (originating outside Bexar County) represents about 22 percent of total streamflow. Recycled wastewater discharges account for about 20 percent and base flow (ground-water inflow to streams) about 18 percent. Storm runoff from various land uses represents about 33 percent. Estimates of sources of streamflow constituent loads indicate recycled wastewater as the largest source of dissolved solids and nitrate plus nitrite nitrogen (about 38 and 66 percent, respectively, of the total loads) during 1997–2001. Stormwater runoff from urban land produced about 49 percent of the 1997–2001 total suspended solids load. Stormwater runoff from residential and commercial land (about 23 percent of the land area) produced about 70 percent of the total lead streamflow load during 1997–2001.

Disentangling the response of streamflow to forest management and climate

NASA Astrophysics Data System (ADS)

Dymond, S.; Miniat, C.; Bladon, K. D.; Keppeler, E.; Caldwell, P. V.

2016-12-01

Paired watershed studies have showcased the relationships between forests, management, and streamflow. However, classical analyses of paired-watershed studies have done little to disentangle the effects of management from overarching climatic signals, potentially masking the interaction between management and climate. Such approaches may confound our understanding of how forest management impacts streamflow. Here we use a 50-year record of streamflow and climate data from the Caspar Creek Experimental Watersheds (CCEW), California, USA to separate the effects of forest management and climate on streamflow. CCEW has two treatment watersheds that have been harvested in the past 50 years. We used a nonlinear mixed model to combine the pre-treatment relationship between streamflow and climate and the post-treatment relationship via an interaction between climate and management into one equation. Our results show that precipitation and potential evapotranspiration alone can account for >95% of the variability in pre-treatment streamflow. Including management scenarios into the model explained most of the variability in streamflow (R2 > 0.98). While forest harvesting altered streamflow in both of our modeled watersheds, removing 66% of the vegetation via selection logging using a tractor yarding system over the entire watershed had a more substantial impact on streamflow than clearcutting small portions of a watershed using cable-yarding. These results suggest that forest harvesting may result in differing impacts on streamflow and highlights the need to incorporate climate into streamflow analyses of paired-watershed studies.

Floods in Central Texas, September 7-14, 2010

USGS Publications Warehouse

Winters, Karl E.

2012-01-01

Severe flooding occurred near the Austin metropolitan area in central Texas September 7–14, 2010, because of heavy rainfall associated with Tropical Storm Hermine. The U.S. Geological Survey, in cooperation with the Upper Brushy Creek Water Control and Improvement District, determined rainfall amounts and annual exceedance probabilities for rainfall resulting in flooding in Bell, Williamson, and Travis counties in central Texas during September 2010. We documented peak streamflows and the annual exceedance probabilities for peak streamflows recorded at several streamflow-gaging stations in the study area. The 24-hour rainfall total exceeded 12 inches at some locations, with one report of 14.57 inches at Lake Georgetown. Rainfall probabilities were estimated using previously published depth-duration frequency maps for Texas. At 4 sites in Williamson County, the 24-hour rainfall had an annual exceedance probability of 0.002. Streamflow measurement data and flood-peak data from U.S. Geological Survey surface-water monitoring stations (streamflow and reservoir gaging stations) are presented, along with a comparison of September 2010 flood peaks to previous known maximums in the periods of record. Annual exceedance probabilities for peak streamflow were computed for 20 streamflow-gaging stations based on an analysis of streamflow-gaging station records. The annual exceedance probability was 0.03 for the September 2010 peak streamflow at the Geological Survey's streamflow-gaging stations 08104700 North Fork San Gabriel River near Georgetown, Texas, and 08154700 Bull Creek at Loop 360 near Austin, Texas. The annual exceedance probability was 0.02 for the peak streamflow for Geological Survey's streamflow-gaging station 08104500 Little River near Little River, Texas. The lack of similarity in the annual exceedance probabilities computed for precipitation and streamflow might be attributed to the small areal extent of the heaviest rainfall over these and the other gaged watersheds.

Estimation of streamflow gains and losses in the lower San Antonio River watershed, south-central Texas, 2006-10

USGS Publications Warehouse

Lizarraga, Joy S.; Wehmeyer, Loren L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the San Antonio River Authority, the Evergreen Underground Water Conservation District, and the Goliad County Groundwater Conservation District, investigated streamflow gains and losses during 2006-10 in the lower San Antonio River watershed in south-central Texas. Streamflow gains and losses were estimated using 2006-10 continuous streamflow records from 11 continuous streamflow-gaging stations, and discrete streamflow measurements made at as many as 20 locations on the San Antonio River and selected tributaries during four synoptic surveys during 2006-7. From the continuous streamflow records, the greatest streamflow gain on the lower San Antonio River occurred in the reach from Falls City, Tex., to Goliad, Tex. The greatest streamflow gain on Cibolo Creek during 2006-10 occurred in the reach from near Saint Hedwig, Tex., to Sutherland Springs, Tex. The San Antonio River between Floresville, Tex., and Falls City was the only reach that had an estimated streamflow loss during 2006-10. During all four synoptic streamflow measurement surveys, the only substantially flowing tributary reach to the main stem of the lower San Antonio River was Cibolo Creek. Along the main stem of the lower San Antonio River, verifiable gains larger than the potential measurement error were estimated in two of the four synoptic streamflow measurement surveys. These gaining reaches occurred in the two most downstream reaches of the San Antonio River between Goliad and Farm Road (FM) 2506 near Fannin, Tex., and between FM 2506 near Fannin to near McFaddin. There were verifiable gains in streamflow in Cibolo Creek, between La Vernia, Tex., and the town of Sutherland Springs during all four surveys, estimated at between 4.8 and 14 ft3/s.

Determination of baseline periods of record for selected streamflow-gaging stations in and near Oklahoma for use in modeling applications

USGS Publications Warehouse

Esralew, Rachel A.

2010-01-01

Use of historical streamflow data from a least-altered period of record can be used in calibration of various modeling applications that are used to characterize least-altered flow and predict the effects of proposed streamflow alteration. This information can be used to enhance water-resources planning. A baseline period of record was determined for selected streamflow-gaging stations that can be used as a calibration dataset for modeling applications. The baseline period of record was defined as a period that is least-altered by anthropogenic activity and has sufficient streamflow record length to represent extreme climate variability. Streamflow data from 171 stations in and near Oklahoma with a minimum of 10 complete water years of daily streamflow record through water year 2007 and drainage areas that were less than 2,500 square miles were considered for use in the baseline period analysis. The first step to determine the least-altered period of record was to evaluate station information by using previous publications, historical station record notes, and information gathered from oral and written communication with hydrographers familiar with selected stations. The second step was to indentify stations that had substantial effects from upstream regulation by evaluating the location and extent of dams in the drainage basin. The third step was (a) the analysis of annual hydrographs and included visual hydrograph analysis for selected stations with 20 or more years of streamflow record, (b) analysis of covariance of double-mass curves, and (c) Kendall's tau trend analysis to detect statistically significant trends in base flow, runoff, total flow, and base-flow index related to anthropogenic activity for selected stations with 15 or more years of streamflow record. A preliminary least-altered period of record for each stream was identified by removing the period of streamflow record when streams were substantially affected by anthropogenic activity. After streamflow record was removed from designation as a least-altered period, stations that did not have at least 10 years of remaining continuous streamflow record were considered to have an insufficient baseline period for modeling applications. An optimum minimum period of record was determined for each of the least-altered periods for each station to ensure a sufficient streamflow record length to provide a representative sample of annual climate variability. An optimum minimum period of 10 years or more was evaluated by analyzing the variability of annual precipitation for selected 5-, 10-, 15-, 25-, and 35-year periods for each of 20 climate divisions that contained stations used in the baseline period analysis. The distribution of annual precipitation was compared for each consecutive overlapping 5-year period to the period 1925-2007 by using a Wilcoxon rank-sum test. The least-altered period of record for stations was also compared to the period 1925-2007 by using a Wilcoxon rank-sum test. The results of this analysis were used to determine how many years of annual precipitation data were needed for the selected period to be statistically similar to the distribution of annual precipitation data for a long-term period, 1925-2007. Minimum optimum periods ranged from 10 to 35 years and varied by climate division. A final baseline period was determined for 111 stations that had a baseline period of at least 10 years of continuous streamflow record after the record-elimination process. A suitable baseline period of record for use in modeling applications could not be identified for 58 of the initial 171 stations because of substantial anthropogenic alteration of the stream or drainage basin and for 2 stations because the least-altered period of record was not representative of annual climate variability. The baseline period for each station was rated ?excellent?, ?good?, ?fair?, ?poor?, or ?no baseline period.? This rating was based on a qualitative evaluation of t

August median streamflow on ungaged streams in Eastern Coastal Maine

USGS Publications Warehouse

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.

Quantitative predictions of streamflow variability in the Susquehanna River Basin

NASA Astrophysics Data System (ADS)

Alexander, R.; Boyer, E. W.; Leonard, L. N.; Duffy, C.; Schwarz, G. E.; Smith, R. A.

2012-12-01

Hydrologic researchers and water managers have increasingly sought an improved understanding of the major processes that control fluxes of water and solutes across diverse environmental settings and large spatial scales. Regional analyses of observed streamflow data have led to advances in our knowledge of relations among land use, climate, and streamflow, with methodologies ranging from statistical assessments of multiple monitoring sites to the regionalization of the parameters of catchment-scale mechanistic simulation models. However, gaps remain in our understanding of the best ways to transfer the knowledge of hydrologic response and governing processes among locations, including methods for regionalizing streamflow measurements and model predictions. We developed an approach to predict variations in streamflow using the SPARROW (SPAtially Referenced Regression On Watershed attributes) modeling infrastructure, with mechanistic functions, mass conservation constraints, and statistical estimation of regional and sub-regional parameters. We used the model to predict discharge in the Susquehanna River Basin (SRB) under varying hydrological regimes that are representative of contemporary flow conditions. The resulting basin-scale water balance describes mean monthly flows in stream reaches throughout the entire SRB (represented at a 1:100,000 scale using the National Hydrologic Data network), with water supply and demand components that are inclusive of a range of hydrologic, climatic, and cultural properties (e.g., precipitation, evapotranspiration, soil and groundwater storage, runoff, baseflow, water use). We compare alternative models of varying complexity that reflect differences in the number and types of explanatory variables and functional expressions as well as spatial and temporal variability in the model parameters. Statistical estimation of the models reveals the levels of complexity that can be uniquely identified, subject to the information content and uncertainties of the hydrologic and climate measurements. Assessment of spatial variations in the model parameters and predictions provides an improved understanding of how much of the hydrologic response to land use, climate, and other properties is unique to specific locations versus more universally observed across catchments of the SRB. This approach advances understanding of water cycle variability at any location throughout the stream network, as a function of both landscape characteristics (e.g., soils, vegetation, land use) and external forcings (e.g., precipitation quantity and frequency). These improvements in predictions of streamflow dynamics will advance the ability to predict spatial and temporal variability in key solutes, such as nutrients, and their delivery to the Chesapeake Bay.

Streamflow and water-quality conditions including geologic sources and processes affecting selenium loading in the Toll Gate Creek watershed, Aurora, Arapahoe County, Colorado, 2007

USGS Publications Warehouse

Paschke, Suzanne S.; Runkel, Robert L.; Walton-Day, Katherine; Kimball, Briant A.; Schaffrath, Keelin R.

2013-01-01

Toll Gate Creek is a perennial stream draining a suburban area in Aurora, Colorado, where selenium concentrations have consistently exceeded the State of Colorado aquatic-life standard for selenium of 4.6 micrograms per liter since the early 2000s. In cooperation with the City of Aurora, Colorado, Utilities Department, a synoptic water-quality study was performed along an 18-kilometer reach of Toll Gate Creek extending from downstream from Quincy Reservoir to the confluence with Sand Creek to develop a detailed understanding of streamflow and concentrations and loads of selenium in Toll Gate Creek. Streamflow and surface-water quality were characterized for summer low-flow conditions (July–August 2007) using four spatially overlapping synoptic-sampling subreaches. Mass-balance methods were applied to the synoptic-sampling and tracer-injection results to estimate streamflow and develop spatial profiles of concentration and load for selenium and other chemical constituents in Toll Gate Creek surface water. Concurrent groundwater sampling determined concentrations of selenium and other chemical constituents in groundwater in areas surrounding the Toll Gate Creek study reaches. Multivariate principal-component analysis was used to group samples and to suggest common sources for dissolved selenium and major ions. Hydrogen and oxygen stable-isotope ratios, groundwater-age interpretations, and chemical analysis of water-soluble paste extractions from core samples are presented, and interpretation of the hydrologic and geochemical data support conclusions regarding geologic sources of selenium and the processes affecting selenium loading in the Toll Gate Creek watershed.

User's manual for computer program BASEPLOT

USGS Publications Warehouse

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.

Hydrologic and Water-Quality Characterization and Modeling of the Onondaga Lake Basin, Onondaga County, New York

USGS Publications Warehouse

Coon, William F.; Reddy, James E.

2008-01-01

Onondaga Lake in Onondaga County, New York, has been identified as one of the Nation?s most contaminated lakes as a result of industrial and sanitary-sewer discharges and stormwater nonpoint sources, and has received priority cleanup status under the national Water Resources Development Act of 1990. A basin-scale precipitation-runoff model of the Onondaga Lake basin was identified as a desirable water-resources management tool to better understand the processes responsible for the generation of loads of sediment and nutrients that are transported to Onondaga Lake. During 2003?07, the U.S. Geological Survey (USGS) developed a model based on the computer program, Hydrological Simulation Program?FORTRAN (HSPF), which simulated overland flow to, and streamflow in, the major tributaries of Onondaga Lake, and loads of sediment, phosphorus, and nitrogen transported to the lake. The simulation period extends from October 1997 through September 2003. The Onondaga Lake basin was divided into 107 subbasins and within these subbasins, the land area was apportioned among 19 pervious and impervious land types on the basis of land use and land cover, hydrologic soil group (HSG), and aspect. Precipitation data were available from three sources as input to the model. The model simulated streamflow, water temperature, concentrations of dissolved oxygen, and concentrations and loads of sediment, orthophosphate, total phosphorus, nitrate, ammonia, and organic nitrogen in the four major tributaries to Onondaga Lake?Onondaga Creek, Harbor Brook, Ley Creek, and Ninemile Creek. Simulated flows were calibrated to data from nine USGS streamflow-monitoring sites; simulated nutrient concentrations and loads were calibrated to data collected at six of the nine streamflow-monitoring sites. Water-quality samples were collected, processed, and analyzed by personnel from the Onondaga County Department of Water Environment Protection. Several time series of flow, and sediment and nutrient loads were generated for known sources of these constituents, including the Tully Valley mudboils (flow and sediment), Otisco Lake (flow and nutrients), the Marcellus wastewater-treatment plant (flow and nutrients), and springs from carbonate bedrock (flow). Runoff from the impervious sewered areas of the City of Syracuse was adjusted for the quantity that was treatable at the county wastewater-treatment plant; the excess flows were routed to nearby streams through combined-sanitary-and-storm-sewer overflows. The mitigative effects that the Onondaga Reservoir and Otisco Lake were presumed to have on loads of sediment and particulate constituents were simulated by adjustment of parameter values that controlled sediment settling rates, deposition, and scour in the reservoir and lake. Graphical representations of observed and simulated data, and relevant statistics, were compared to assess model performance. Simulated daily and monthly streamflows were rated ?very good? (within 10 percent of observed flows) at all calibration sites, except Onondaga Creek at Cardiff, which was rated ?fair? (10?15 percent difference). Simulations of monthly average water temperatures were rated ?very good? (within 7 percent of observed temperatures) at all sites. No observed data were available by which to directly assess the model?s simulation of suspended sediment loads. Available measured total suspended solids data provided an indirect means of comparison but, not surprisingly, yielded only ?fair? to ?poor? ratings (greater than 30 percent difference) for simulated monthly sediment loads at half the water-quality calibration sites. Simulations of monthly orthophosphate loads ranged from ?very good? (within 15 percent of measured loads) at three sites to ?poor? (greater than 35 percent difference) at one site; simulations of ammonia nitrogen loads ranged from ?very good? at one site to ?fair? (25?35 percent difference) at two sites. Simulations of monthly total phosphorus, nitrate, and or

Estimation of baseline daily mean streamflows for ungaged locations on Pennsylvania streams, water years 1960-2008

USGS Publications Warehouse

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.

Rainfall-Runoff Dynamics Following Wildfire in Mountainous Headwater Catchments, Alberta, Canada.

NASA Astrophysics Data System (ADS)

Williams, C.; Silins, U.; Bladon, K. D.; Martens, A. M.; Wagner, M. J.; Anderson, A.

2015-12-01

Severe wildfire has been shown to increase the magnitude and advance the timing of rainfall-generated stormflows across a range of hydro-climate regions. Loss of canopy and forest floor interception results in increased net precipitation which, along with the removal of forest organic layers and increased shorter-term water repellency, can result in strongly increased surface flow pathways and efficient routing of precipitation to streams. These abrupt changes have the potential to exacerbate flood impacts and alter the timing of runoff delivery to streams. However, while these effects are well documented in drier temperate mountain regions, changes in post-fire rainfall-runoff processes are less well understood in colder, more northern, snowfall dominated regimes. The objectives of this study are to explore longer term precipitation and runoff dynamics of burned and unburned (reference) watersheds from the Southern Rockies Watershed Project (SRWP) after the 2003 Lost Creek wildfire in the front-range Rocky Mountains of southwestern Alberta, Canada. Streamflow and precipitation were measured in 5 watersheds (3.7 - 10.4 km2) for 10 years following the wildfire (2005-2014). Measurements were collected from a dense network of meteorological and hydrometric stations. Stormflow volume, peak flow, time to peak flow, and total annual streamflow were compared between burned and reference streams. Event-based data were separated into 3 post-fire periods to detect changes in rainfall-runoff dynamics as vegetation regenerated. Despite large increases in post-fire snowpacks and net summer rainfall, rainfall-generated runoff from fire-affected watersheds was not large in comparison to that reported from more temperate snowfall-dominated Rocky Mountain hydrologic settings. High proportions of groundwater contribution to annual runoff regimes (as opposed to surface flow pathways) and groundwater storage were likely contributors to greater watershed resistance to wildfire effects in these northern Rocky Mountain catchments.

Distributed snow data as a tool to inform water management decisions: Using Airborne Snow Observatory (ASO) at the Hetch Hetchy Reservoir in Yosemite National Park, City and County of San Francisco.

NASA Astrophysics Data System (ADS)

Graham, C. B.

2016-12-01

The timing and magnitude of spring snowmelt and runoff is critical in managing reservoirs in the Western United States. The Hetch Hetchy Reservoir in Yosemite National Park provides drinking water for 2.6 million customers in over 30 communities in the San Francisco Bay Area. Power generation from Hetch Hetchy meets the municipal load of the City and County of San Francisco. Water from the Hetch Hetchy Reservoir is also released in the Tuolumne River, supporting critical ecosystems in Yosemite National Park and the Stanislaus National Forest. Better predictions of long (seasonal) and short (weekly) term streamflow allow for more secure water resource planning, earlier power generation and ecologically beneficial releases from the Reservoir. Hetch Hetchy Reservoir is fed by snow dominated watersheds in the Sierra Mountains. Better knowledge of snowpack conditions allow for better predictions of inflows, both at the seasonal and at the weekly time scales. The ASO project has provided the managers of Hetch Hetchy Reservoir with high resolution estimates of total snowpack and snowpack distribution in the 460 mi2 Hetch Hetchy. We show that there is a tight correlation between snowpack estimates and future streamflow, allowing earlier, more confident operational decisions. We also show how distributed SWE estimates were used to develop and test a hydrologic model of the system (PRMS). This model, calibrated directly to snowpack conditions, is shown to correctly simulate snowpack volume and distribution, as well as streamflow patterns.

Influence of various water quality sampling strategies on load estimates for small streams

USGS Publications Warehouse

Robertson, Dale M.; Roerish, Eric D.

1999-01-01

Extensive streamflow and water quality data from eight small streams were systematically subsampled to represent various water‐quality sampling strategies. The subsampled data were then used to determine the accuracy and precision of annual load estimates generated by means of a regression approach (typically used for big rivers) and to determine the most effective sampling strategy for small streams. Estimation of annual loads by regression was imprecise regardless of the sampling strategy used; for the most effective strategy, median absolute errors were ∼30% based on the load estimated with an integration method and all available data, if a regression approach is used with daily average streamflow. The most effective sampling strategy depends on the length of the study. For 1‐year studies, fixed‐period monthly sampling supplemented by storm chasing was the most effective strategy. For studies of 2 or more years, fixed‐period semimonthly sampling resulted in not only the least biased but also the most precise loads. Additional high‐flow samples, typically collected to help define the relation between high streamflow and high loads, result in imprecise, overestimated annual loads if these samples are consistently collected early in high‐flow events.

Utilizing Climate Forecasts for Improving Water and Power Systems Coordination

NASA Astrophysics Data System (ADS)

Arumugam, S.; Queiroz, A.; Patskoski, J.; Mahinthakumar, K.; DeCarolis, J.

2016-12-01

Climate forecasts, typically monthly-to-seasonal precipitation forecasts, are commonly used to develop streamflow forecasts for improving reservoir management. Irrespective of their high skill in forecasting, temperature forecasts in developing power demand forecasts are not often considered along with streamflow forecasts for improving water and power systems coordination. In this study, we consider a prototype system to analyze the utility of climate forecasts, both precipitation and temperature, for improving water and power systems coordination. The prototype system, a unit-commitment model that schedules power generation from various sources, is considered and its performance is compared with an energy system model having an equivalent reservoir representation. Different skill sets of streamflow forecasts and power demand forecasts are forced on both water and power systems representations for understanding the level of model complexity required for utilizing monthly-to-seasonal climate forecasts to improve coordination between these two systems. The analyses also identify various decision-making strategies - forward purchasing of fuel stocks, scheduled maintenance of various power systems and tradeoff on water appropriation between hydropower and other uses - in the context of various water and power systems configurations. Potential application of such analyses for integrating large power systems with multiple river basins is also discussed.

Analysis of trends in streamflow and its linkages with rainfall and anthropogenic factors in Gomti River basin of North India

NASA Astrophysics Data System (ADS)

Abeysingha, N. S.; Singh, Man; Sehgal, V. K.; Khanna, Manoj; Pathak, Himanshu

2016-02-01

Trend analysis of hydro-climatic variables such as streamflow, rainfall, and temperature provides useful information for effective water resources planning, designing, and management. Trends in observed streamflow at four gauging stations in the Gomti River basin of North India were assessed using the Mann-Kendall and Sen's slope for the 1982 to 2012 period. The relationships between trends in streamflow and rainfall were studied by correlation analyses. There was a gradual decreasing trend of annual, monsoonal, and winter seasonal streamflow ( p < 0.05) from the midstream to the downstream of the river and also a decreasing trend of annual streamflow for the 5-year moving averaged standardized anomalies of streamflow for the entire basin. The declining trend in the streamflow was attributed partly to the increased water withdrawal, to increased air temperature, to higher population, and partly to significant reducing trend of post monsoon rainfall especially at downstream. Upstream gauging station showed a significant increasing trend of streamflow (1.6 m3/s/year) at annual scale, and this trend was attributed to the significant increasing trend of catchment rainfall (9.54 mm/year). It was further evident in the significant coefficient of positive correlation ( ρ = 0.8) between streamflow and catchment rainfall. The decreasing trend in streamflow and post-monsoon rainfall especially towards downstream area with concurrent increasing trend of temperature indicates a drying tendency of the Gomti River basin over the study period. The results of this study may help stakeholders to design streamflow restoration strategies for sustainable water management planning of the Gomti River basin.

Physical habitat simulation system reference manual: version II

USGS Publications Warehouse

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.

Preliminary stage and streamflow data at selected U.S. Geological Survey streamgages in Maine and New Hampshire for the flood of October 30–31, 2017

USGS Publications Warehouse

Kiah, Richard G.; Stasulis, Nicholas W.

2018-03-08

Rainfall from a storm on October 24–27, 2017, and Tropical Storm Philippe on October 29–30, created conditions that led to flooding across portions of New Hampshire and western Maine. On the basis of streamflow data collected at 30 selected U.S. Geological Survey (USGS) streamgages in the Androscoggin River, Connecticut River, Merrimack River, and Saco River Basins, the storms caused minor to moderate flooding in those basins on October 30–31, 2017. During the storms, the USGS deployed hydrographers to take discrete measurements of streamflow. The measurements were used to confirm the stage-to-streamflow relation (rating curve) at the selected USGS streamgages. Following the storms, hydrographers documented high-water marks in support of indirect measurements of streamflow. Seven streamgages with greater than 50 years of streamflow data recorded preliminary streamflow peaks within the top five for the periods of record. Twelve streamgages recorded preliminary peak streamflows greater than an estimate of the 100-year streamflow based on drainage area.

Human influences on streamflow drought characteristics in England and Wales

NASA Astrophysics Data System (ADS)

Tijdeman, Erik; Hannaford, Jamie; Stahl, Kerstin

2018-02-01

Human influences can affect streamflow drought characteristics and propagation. The question is where, when and why? To answer these questions, the impact of different human influences on streamflow droughts were assessed in England and Wales, across a broad range of climate and catchments conditions. We used a dataset consisting of catchments with near-natural flow as well as catchments for which different human influences have been indicated in the metadata (Factors Affecting Runoff) of the UK National River Flow Archive (NRFA). A screening approach was applied on the streamflow records to identify human-influenced records with drought characteristics that deviated from those found for catchments with near-natural flow. Three different deviations were considered, specifically deviations in (1) the relationship between streamflow drought duration and the base flow index, BFI (specifically, BFIHOST, the BFI predicted from the hydrological properties of soils), (2) the correlation between streamflow and precipitation and (3) the temporal occurrence of streamflow droughts compared to precipitation droughts, i.e. an increase or decrease in streamflow drought months relative to precipitation drought months over the period of record. The identified deviations were then related to the indicated human influences. Results showed that the majority of catchments for which human influences were indicated did not show streamflow drought characteristics that deviated from those expected under near-natural conditions. For the catchments that did show deviating streamflow drought characteristics, prolonged streamflow drought durations were found in some of the catchments affected by groundwater abstractions. Weaker correlations between streamflow and precipitation were found for some of the catchments with reservoirs, water transfers or groundwater augmentation schemes. An increase in streamflow drought occurrence towards the end of their records was found for some of the catchments affected by groundwater abstractions and a decrease in streamflow drought occurrence for some of the catchments with either reservoirs or groundwater abstractions. In conclusion, the proposed screening approaches were sometimes successful in identifying streamflow records with deviating drought characteristics that are likely related to different human influences. However, a quantitative attribution of the impact of human influences on streamflow drought characteristics requires more detailed case-by-case information about the type and degree of all different human influences. Given that, in many countries, such information is often not readily accessible, the approaches adopted here could provide useful in targeting future efforts. In England and Wales specifically, the catchments with deviating streamflow drought characteristics identified in this study could serve as the starting point of detailed case study research.

Reducing hydrologic model uncertainty in monthly streamflow predictions using multimodel combination

NASA Astrophysics Data System (ADS)

Li, Weihua; Sankarasubramanian, A.

2012-12-01

Model errors are inevitable in any prediction exercise. One approach that is currently gaining attention in reducing model errors is by combining multiple models to develop improved predictions. The rationale behind this approach primarily lies on the premise that optimal weights could be derived for each model so that the developed multimodel predictions will result in improved predictions. A new dynamic approach (MM-1) to combine multiple hydrological models by evaluating their performance/skill contingent on the predictor state is proposed. We combine two hydrological models, "abcd" model and variable infiltration capacity (VIC) model, to develop multimodel streamflow predictions. To quantify precisely under what conditions the multimodel combination results in improved predictions, we compare multimodel scheme MM-1 with optimal model combination scheme (MM-O) by employing them in predicting the streamflow generated from a known hydrologic model (abcd model orVICmodel) with heteroscedastic error variance as well as from a hydrologic model that exhibits different structure than that of the candidate models (i.e., "abcd" model or VIC model). Results from the study show that streamflow estimated from single models performed better than multimodels under almost no measurement error. However, under increased measurement errors and model structural misspecification, both multimodel schemes (MM-1 and MM-O) consistently performed better than the single model prediction. Overall, MM-1 performs better than MM-O in predicting the monthly flow values as well as in predicting extreme monthly flows. Comparison of the weights obtained from each candidate model reveals that as measurement errors increase, MM-1 assigns weights equally for all the models, whereas MM-O assigns higher weights for always the best-performing candidate model under the calibration period. Applying the multimodel algorithms for predicting streamflows over four different sites revealed that MM-1 performs better than all single models and optimal model combination scheme, MM-O, in predicting the monthly flows as well as the flows during wetter months.

Practical implementation of a particle filter data assimilation approach to estimate initial hydrologic conditions and initialize medium-range streamflow forecasts

NASA Astrophysics Data System (ADS)

Clark, E.; Wood, A.; Nijssen, B.; Newman, A. J.; Mendoza, P. A.

2016-12-01

The System for Hydrometeorological Applications, Research and Prediction (SHARP), developed at the National Center for Atmospheric Research (NCAR), University of Washington, U.S. Army Corps of Engineers, and U.S. Bureau of Reclamation, is a fully automated ensemble prediction system for short-term to seasonal applications. It incorporates uncertainty in initial hydrologic conditions (IHCs) and in hydrometeorological predictions. In this implementation, IHC uncertainty is estimated by propagating an ensemble of 100 plausible temperature and precipitation time series through the Sacramento/Snow-17 model. The forcing ensemble explicitly accounts for measurement and interpolation uncertainties in the development of gridded meteorological forcing time series. The resulting ensemble of derived IHCs exhibits a broad range of possible soil moisture and snow water equivalent (SWE) states. To select the IHCs that are most consistent with the observations, we employ a particle filter (PF) that weights IHC ensemble members based on observations of streamflow and SWE. These particles are then used to initialize ensemble precipitation and temperature forecasts downscaled from the Global Ensemble Forecast System (GEFS), generating a streamflow forecast ensemble. We test this method in two basins in the Pacific Northwest that are important for water resources management: 1) the Green River upstream of Howard Hanson Dam, and 2) the South Fork Flathead River upstream of Hungry Horse Dam. The first of these is characterized by mixed snow and rain, while the second is snow-dominated. The PF-based forecasts are compared to forecasts based on a single IHC (corresponding to median streamflow) paired with the full GEFS ensemble, and 2) the full IHC ensemble, without filtering, paired with the full GEFS ensemble. In addition to assessing improvements in the spread of IHCs, we perform a hindcast experiment to evaluate the utility of PF-based data assimilation on streamflow forecasts at 1- to 7-day lead times.

Moving horizon estimation for assimilating H-SAF remote sensing data into the HBV hydrological model

NASA Astrophysics Data System (ADS)

Montero, Rodolfo Alvarado; Schwanenberg, Dirk; Krahe, Peter; Lisniak, Dmytro; Sensoy, Aynur; Sorman, A. Arda; Akkol, Bulut

2016-06-01

Remote sensing information has been extensively developed over the past few years including spatially distributed data for hydrological applications at high resolution. The implementation of these products in operational flow forecasting systems is still an active field of research, wherein data assimilation plays a vital role on the improvement of initial conditions of streamflow forecasts. We present a novel implementation of a variational method based on Moving Horizon Estimation (MHE), in application to the conceptual rainfall-runoff model HBV, to simultaneously assimilate remotely sensed snow covered area (SCA), snow water equivalent (SWE), soil moisture (SM) and in situ measurements of streamflow data using large assimilation windows of up to one year. This innovative application of the MHE approach allows to simultaneously update precipitation, temperature, soil moisture as well as upper and lower zones water storages of the conceptual model, within the assimilation window, without an explicit formulation of error covariance matrixes and it enables a highly flexible formulation of distance metrics for the agreement of simulated and observed variables. The framework is tested in two data-dense sites in Germany and one data-sparse environment in Turkey. Results show a potential improvement of the lead time performance of streamflow forecasts by using perfect time series of state variables generated by the simulation of the conceptual rainfall-runoff model itself. The framework is also tested using new operational data products from the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) of EUMETSAT. This study is the first application of H-SAF products to hydrological forecasting systems and it verifies their added value. Results from assimilating H-SAF observations lead to a slight reduction of the streamflow forecast skill in all three cases compared to the assimilation of streamflow data only. On the other hand, the forecast skill of soil moisture shows a significant improvement.

Links between large-scale circulation patterns and streamflow in Central Europe: A review

NASA Astrophysics Data System (ADS)

Steirou, Eva; Gerlitz, Lars; Apel, Heiko; Merz, Bruno

2017-06-01

We disentangle the relationships between streamflow and large-scale atmospheric circulation in Central Europe (CE), an area affected by climatic influences from different origins (Atlantic, Mediterranean and Continental) and characterized by diverse topography and flow regimes. Our literature review examines in detail the links between mean, high and low flows in CE and large-scale circulation patterns, with focus on two closely related phenomena, the North Atlantic Oscillation (NAO) and the Western-zonal circulation (WC). For both patterns, significant relations, consistent between different studies, are found for large parts of CE. The strongest links are found for the winter season, forming a dipole-like pattern with positive relationships with streamflow north of the Alps and the Carpathians for both indices and negative relationships for the NAO in the south. An influence of winter NAO is also detected in the amplitude and timing of snowmelt flows later in the year. Discharge in CE has further been linked to other large-scale climatic modes such as the Scandinavia pattern (SCA), the East Atlantic/West Russian pattern (EA/WR), the El Niño-Southern Oscillation (ENSO) and synoptic weather patterns such as the Vb weather regime. Different mechanisms suggested in the literature to modulate links between streamflow and the NAO are combined with topographical characteristics of the target area in order to explain the divergent NAO/WC influence on streamflow in different parts of CE. In particular, a precipitation mechanism seems to regulate winter flows in North-Western Germany, an area with short duration of snow cover and with rainfall-generated floods. The precipitation mechanism is also likely in Southern CE, where correlations between the NAO and temperature are low. Finally, in the rest of the study area (Northern CE, Alpine region), a joint precipitation-snow mechanism influences floods not only in winter, but also in the spring/snowmelt period, providing some possibilities for flood forecasting.

Towards a publicly available, map-based regional software tool to estimate unregulated daily streamflow at ungauged rivers

USGS Publications Warehouse

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.

Trends in annual, seasonal, and monthly streamflow characteristics at 227 streamgages in the Missouri River watershed, water years 1960-2011

USGS Publications Warehouse

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.

Streamflow gain-loss characteristics of Elkhead Creek downstream from Elkhead Reservoir near Craig, Colorado, 2009

USGS Publications Warehouse

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.

Multi-model analysis in hydrological prediction

NASA Astrophysics Data System (ADS)

Lanthier, M.; Arsenault, R.; Brissette, F.

2017-12-01

Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been largely corrected on short-term predictions. For the longer term, the addition of the multi-model member has been beneficial to the quality of the predictions, although it is too early to determine whether the gain is related to the addition of a member or if multi-model member has plus-value itself.

Changing characteristics of streamflow in the Midwest and its relation to oceanic-atmospheric oscillations

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.

A precipitation-runoff model for the analysis of the effects of water withdrawals and land-use change on streamflow in the Usquepaug-Queen River Basin, Rhode Island

USGS Publications Warehouse

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

Timing and Duration of Flow in Ephemeral Streams of the Sierra Vista Subwatershed of the Upper San Pedro Basin, Cochise County, Southeastern Arizona

USGS Publications Warehouse

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.

Comparing statistical and process-based flow duration curve models in ungauged basins and changing rain regimes

NASA Astrophysics Data System (ADS)

Müller, M. F.; Thompson, S. E.

2016-02-01

The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash-Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drivers of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by frequent wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are favored over statistical models.

Modelling the effects of land use changes on the streamflow of a peri-urban catchment in central Portugal

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.

USGS Streamgages Linked to the Medium Resolution NHD

USGS Publications Warehouse

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.

Extracting Hydrologic Understanding from the Unique Space-time Sampling of the Surface Water and Ocean Topography (SWOT) Mission

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.

Soil water storage, rainfall and runoff relationships in a tropical dry forest catchment

NASA Astrophysics Data System (ADS)

Farrick, Kegan K.; Branfireun, Brian A.

2014-12-01

In forested catchments, the exceedance of rainfall and antecedent water storage thresholds is often required for runoff generation, yet to our knowledge these threshold relationships remain undescribed in tropical dry forest catchments. We, therefore, identified the controls of streamflow activation and the timing and magnitude of runoff in a tropical dry forest catchment near the Pacific coast of central Mexico. During a 52 day transition phase from the dry to wet season, soil water movement was dominated by vertical flow which continued until a threshold soil moisture content of 26% was reached at 100 cm below the surface. This satisfied a 162 mm storage deficit and activated streamflow, likely through lateral subsurface flow pathways. High antecedent soil water conditions were maintained during the wet phase but had a weak influence on stormflow. We identified a threshold value of 289 mm of summed rainfall and antecedent soil water needed to generate >4 mm of stormflow per event. Above this threshold, stormflow response and magnitude was almost entirely governed by rainfall event characteristics and not antecedent soil moisture conditions. Our results show that over the course of the wet season in tropical dry forests the dominant controls on runoff generation changed from antecedent soil water and storage to the depth of rainfall.

A Nonparametric Approach For Representing Interannual Dependence In Monthly Streamflow Sequences

NASA Astrophysics Data System (ADS)

Sharma, A.; Oneill, R.

The estimation of risks associated with water management plans requires generation of synthetic streamflow sequences. The mathematical algorithms used to generate these sequences at monthly time scales are found lacking in two main respects: inability in preserving dependence attributes particularly at large (seasonal to interannual) time lags; and, a poor representation of observed distributional characteristics, in partic- ular, representation of strong assymetry or multimodality in the probability density function. Proposed here is an alternative that naturally incorporates both observed de- pendence and distributional attributes in the generated sequences. Use of a nonpara- metric framework provides an effective means for representing the observed proba- bility distribution, while the use of a Svariable kernelT ensures accurate modeling of & cedil;streamflow data sets that contain a substantial number of zero flow values. A careful selection of prior flows imparts the appropriate short-term memory, while use of an SaggregateT flow variable allows representation of interannual dependence. The non- & cedil;parametric simulation model is applied to monthly flows from the Beaver River near Beaver, Utah, USA, and the Burrendong dam inflows, New South Wales, Australia. Results indicate that while the use of traditional simulation approaches leads to an inaccurate representation of dependence at long (annual and interannual) time scales, the proposed model can simulate both short and long-term dependence. As a result, the proposed model ensures a significantly improved representation of reservoir storage statistics, particularly for systems influenced by long droughts. It is important to note that the proposed method offers a simpler and better alternative to conventional dis- aggregation models as: (a) a separate annual flow series is not required, (b) stringent assumptions relating annual and monthly flows are not needed, and (c) the method does not require the specification of a "water year", instead ensuring that the sum of any sequence of flows lasting twelve months will result in the type of dependence that is observed in the historical annual flow series.

Recent changes in ecologically-relevant streamflows in North America

NASA Astrophysics Data System (ADS)

Ficklin, D. L.; Abatzoglou, J. T.; Knouft, J.; Robeson, S. M.

2017-12-01

The streamflow regime is a primary regulator of the composition and functioning of freshwater ecosystems. Growth, behavior, and/or reproduction of most freshwater organisms are influenced in some way by the amount of water, including high and low flows, and seasonal fluctuations in water availability in a particular habitat. This work examines trends in ecologically-relevant measures of streamflows from 1980-2015 for over 3,000 streamflow gauges located throughout Canada and United States. Specifically, we examine trends in water year mean flow and variability, as well as trends in high (95th and 99th percentile), low (1st and 5th percentile), and 7- and 3-day maximum and minimum streamflows. The results indicate a clear regional delineation of significant increases of ecologically-relevant streamflows in the northern Central Plains/south-central Canada, upper Midwest (except Michigan and Wisconsin) and northeastern United States/southeastern Canada, while significant decreases are found throughout the southeastern and southwestern United States. The regional agreement between streamflow trends in regulated and unregulated watersheds indicate a widespread climatic influence that is not masked by human alteration of streamflows. We explore the degree to which climate factors explain both interannual variability and observed trends in streamflow to better elucidate the role of top-down climate drivers versus bottom-up land surface drivers on recent trends in ecologically-relevant streamflow. We also explore how these changes in streamflow are affecting water quality such as water temperature and sediment concentration. This type of analysis will aid in highlighting streamflow regions in the United States that are currently sensitive to changes in climate, but may also aid in understanding which regions may be sensitive to future climatic changes.

Characterizing a Century of Climate and Hydrological Variability of a Mediterranean and Mountainous Watersheds: the Durance River Case-Study

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).

Diagnosis of the hydrology of a small Arctic basin at the tundra-taiga transition using a physically based hydrological model

NASA Astrophysics Data System (ADS)

Krogh, Sebastian A.; Pomeroy, John W.; Marsh, Philip

2017-07-01

A better understanding of cold regions hydrological processes and regimes in transitional environments is critical for predicting future Arctic freshwater fluxes under climate and vegetation change. A physically based hydrological model using the Cold Regions Hydrological Model platform was created for a small Arctic basin in the tundra-taiga transition region. The model represents snow redistribution and sublimation by wind and vegetation, snowmelt energy budget, evapotranspiration, subsurface flow through organic terrain, infiltration to frozen soils, freezing and thawing of soils, permafrost and streamflow routing. The model was used to reconstruct the basin water cycle over 28 years to understand and quantify the mass fluxes controlling its hydrological regime. Model structure and parameters were set from the current understanding of Arctic hydrology, remote sensing, field research in the basin and region, and calibration against streamflow observations. Calibration was restricted to subsurface hydraulic and storage parameters. Multi-objective evaluation of the model using observed streamflow, snow accumulation and ground freeze/thaw state showed adequate simulation. Significant spatial variability in the winter mass fluxes was found between tundra, shrubs and forested sites, particularly due to the substantial blowing snow redistribution and sublimation from the wind-swept upper basin, as well as sublimation of canopy intercepted snow from the forest (about 17% of snowfall). At the basin scale, the model showed that evapotranspiration is the largest loss of water (47%), followed by streamflow (39%) and sublimation (14%). The models streamflow performance sensitivity to a set of parameter was analysed, as well as the mean annual mass balance uncertainty associated with these parameters.

Impact of state updating and multi-parametric ensemble for streamflow hindcasting in European river basins

NASA Astrophysics Data System (ADS)

Noh, S. J.; Rakovec, O.; Kumar, R.; Samaniego, L. E.

2015-12-01

Accurate and reliable streamflow prediction is essential to mitigate social and economic damage coming from water-related disasters such as flood and drought. Sequential data assimilation (DA) may facilitate improved streamflow prediction using real-time observations to correct internal model states. In conventional DA methods such as state updating, parametric uncertainty is often ignored mainly due to practical limitations of methodology to specify modeling uncertainty with limited ensemble members. However, if parametric uncertainty related with routing and runoff components is not incorporated properly, predictive uncertainty by model ensemble may be insufficient to capture dynamics of observations, which may deteriorate predictability. Recently, a multi-scale parameter regionalization (MPR) method was proposed to make hydrologic predictions at different scales using a same set of model parameters without losing much of the model performance. The MPR method incorporated within the mesoscale hydrologic model (mHM, http://www.ufz.de/mhm) could effectively represent and control uncertainty of high-dimensional parameters in a distributed model using global parameters. In this study, we evaluate impacts of streamflow data assimilation over European river basins. Especially, a multi-parametric ensemble approach is tested to consider the effects of parametric uncertainty in DA. Because augmentation of parameters is not required within an assimilation window, the approach could be more stable with limited ensemble members and have potential for operational uses. To consider the response times and non-Gaussian characteristics of internal hydrologic processes, lagged particle filtering is utilized. The presentation will be focused on gains and limitations of streamflow data assimilation and multi-parametric ensemble method over large-scale basins.

Estimating rainfall time series and model parameter distributions using model data reduction and inversion techniques

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.

Streamflow statistics for development of water rights claims for the Jarbidge Wild and Scenic River, Owyhee Canyonlands Wilderness, Idaho, 2013-14: a supplement to Scientific Investigations Report 2013-5212

USGS Publications Warehouse

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.

Reference manual for generation and analysis of Habitat Time Series: version II

USGS Publications Warehouse

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.

Attributing uncertainty in streamflow simulations due to variable inputs via the Quantile Flow Deviation metric

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.

Annual Peak-Flow Frequency Characteristics and (or) Peak Dam-Pool-Elevation Frequency Characteristics of Dry Dams and Selected Streamflow-Gaging Stations in the Great Miami River Basin, Ohio

USGS Publications Warehouse

Koltun, G.F.

2009-01-01

This report describes the results of a study to determine frequency characteristics of postregulation annual peak flows at streamflow-gaging stations at or near the Lockington, Taylorsville, Englewood, Huffman, and Germantown dry dams in the Miami Conservancy District flood-protection system (southwestern Ohio) and five other streamflow-gaging stations in the Great Miami River Basin further downstream from one or more of the dams. In addition, this report describes frequency characteristics of annual peak elevations of the dry-dam pools. In most cases, log-Pearson Type III distributions were fit to postregulation annual peak-flow values through 2007 (the most recent year of published peak-flow values at the time of this analysis) and annual peak dam-pool storage values for the period 1922-2008 to determine peaks with recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years. For one streamflow-gaging station (03272100) with a short period of record, frequency characteristics were estimated by means of a process involving interpolation of peak-flow yields determined for an upstream and downstream gage. Once storages had been estimated for the various recurrence intervals, corresponding dam-pool elevations were determined from elevation-storage ratings provided by the Miami Conservancy District.

Characterizing Macro Scale Patterns Of Uncertainty For Improved Operational Flood Forecasting Over The Conterminous United States

NASA Astrophysics Data System (ADS)

Vergara, H. J.; Kirstetter, P.; Gourley, J. J.; Flamig, Z.; Hong, Y.

2015-12-01

The macro scale patterns of simulated streamflow errors are studied in order to characterize uncertainty in a hydrologic modeling system forced with the Multi-Radar/Multi-Sensor (MRMS; http://mrms.ou.edu) quantitative precipitation estimates for flood forecasting over the Conterminous United States (CONUS). The hydrologic model is centerpiece of the Flooded Locations And Simulated Hydrograph (FLASH; http://flash.ou.edu) real-time system. The hydrologic model is implemented at 1-km/5-min resolution to generate estimates of streamflow. Data from the CONUS-wide stream gauge network of the United States' Geological Survey (USGS) were used as a reference to evaluate the discrepancies with the hydrological model predictions. Streamflow errors were studied at the event scale with particular focus on the peak flow magnitude and timing. A total of 2,680 catchments over CONUS and 75,496 events from a 10-year period are used for the simulation diagnostic analysis. Associations between streamflow errors and geophysical factors were explored and modeled. It is found that hydro-climatic factors and radar coverage could explain significant underestimation of peak flow in regions of complex terrain. Furthermore, the statistical modeling of peak flow errors shows that other geophysical factors such as basin geomorphometry, pedology, and land cover/use could also provide explanatory information. Results from this research demonstrate the utility of uncertainty characterization in providing guidance to improve model adequacy, parameter estimates, and input quality control. Likewise, the characterization of uncertainty enables probabilistic flood forecasting that can be extended to ungauged locations.

Incorporating probabilistic seasonal climate forecasts into river management using a risk-based framework

USGS Publications Warehouse

Sojda, Richard S.; Towler, Erin; Roberts, Mike; Rajagopalan, Balaji

2013-01-01

[1] Despite the influence of hydroclimate on river ecosystems, most efforts to date have focused on using climate information to predict streamflow for water supply. However, as water demands intensify and river systems are increasingly stressed, research is needed to explicitly integrate climate into streamflow forecasts that are relevant to river ecosystem management. To this end, we present a five step risk-based framework: (1) define risk tolerance, (2) develop a streamflow forecast model, (3) generate climate forecast ensembles, (4) estimate streamflow ensembles and associated risk, and (5) manage for climate risk. The framework is successfully demonstrated for an unregulated watershed in southwest Montana, where the combination of recent drought and water withdrawals has made it challenging to maintain flows needed for healthy fisheries. We put forth a generalized linear modeling (GLM) approach to develop a suite of tools that skillfully model decision-relevant low flow characteristics in terms of climate predictors. Probabilistic precipitation forecasts are used in conjunction with the GLMs, resulting in season-ahead prediction ensembles that provide the full risk profile. These tools are embedded in an end-to-end risk management framework that directly supports proactive fish conservation efforts. Results show that the use of forecasts can be beneficial to planning, especially in wet years, but historical precipitation forecasts are quite conservative (i.e., not very “sharp”). Synthetic forecasts show that a modest “sharpening” can strongly impact risk and improve skill. We emphasize that use in management depends on defining relevant environmental flows and risk tolerance, requiring local stakeholder involvement.

Contribution of human and climate change impacts to changes in streamflow of Canada.

PubMed

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.

Methods for estimating tributary streamflow in the Chattahoochee River basin between Buford Dam and Franklin, Georgia

USGS Publications Warehouse

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.

Trends in selected streamflow and stream-channel characteristics for the Chagrin River at Willoughby, Ohio

USGS Publications Warehouse

Koltun, G.F.; Kunze, Allison E.

2002-01-01

Monotonic upward trends in annual mean streamflows and annual 7-day low flows were identified statistically for the streamflow-gaging station on the Chagrin River at Willoughby, Ohio. No monotonic trends were identified for the annual peak streamflow series or partial-duration series of peak streamflows augmented with annual peak streamflows that did not exceed a base discharge of 4,000 cubic feet per second. A plot of cumulative departure of annual precipitation from the long-term mean annual precipitation for the weather-observation station at Hiram, Ohio, indicates a relatively dry period extending from about 1910 to about 1968, followed by a relatively wet period extending from about 1968 to the late 1990s. A plot of cumulative departure of annual mean streamflow from the mean annual streamflow for the Chagrin River at Willoughby, Ohio, closely mimics the shape of the precipitation departure plot, indicating that the annual mean streamflows increased in concert with annual precipitation. These synchronous trends likely explain why upward trends in annual mean streamflows and annual 7-day low flows were observed. A lack of trend in peak streamflows indicates that the intensity and severity of flood-producing storms did not increase appreciably along with the increases in annual precipitation. An analysis of point-of-zero-flow data indicates that the low-water control of the Chagrin River streamflow-gaging station tended to aggrade over the period 1930?93; however, the magnitude of aggradation is sufficiently small that its effect on stages of moderate to large floods would be negligible. Stage values associated with reference streamflows of 500 and 5,000 cubic feet per second tended to remain fairly stable during the period from about 1950 to 1970 and then decreased slightly during the period from about 1970 to 1980, suggesting that the flood-carrying capacity of the stream increased somewhat during the latter period. Since a large flood on May 26, 1989, significant changes have occurred in the relation between stage and streamflow. The most recent relation indicates that stage values associated with streamflows of 500 and 5,000 cubic feet per second are about 0.5 foot and 0.1 foot higher, respectively, than the pre-1989 levels.

Continental U.S. streamflow trends from 1940 to 2009 and their relationships with watershed spatial characteristics

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.

Estimating the Magnitude and Frequency of Peak Streamflows for Ungaged Sites on Streams in Alaska and Conterminous Basins in Canada

USGS Publications Warehouse

Curran, Janet H.; Meyer, David F.; Tasker, Gary D.

2003-01-01

Estimates of the magnitude and frequency of peak streamflow are needed across Alaska for floodplain management, cost-effective design of floodway structures such as bridges and culverts, and other water-resource management issues. Peak-streamflow magnitudes for the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence-interval flows were computed for 301 streamflow-gaging and partial-record stations in Alaska and 60 stations in conterminous basins of Canada. Flows were analyzed from data through the 1999 water year using a log-Pearson Type III analysis. The State was divided into seven hydrologically distinct streamflow analysis regions for this analysis, in conjunction with a concurrent study of low and high flows. New generalized skew coefficients were developed for each region using station skew coefficients for stations with at least 25 years of systematic peak-streamflow data. Equations for estimating peak streamflows at ungaged locations were developed for Alaska and conterminous basins in Canada using a generalized least-squares regression model. A set of predictive equations for estimating the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year peak streamflows was developed for each streamflow analysis region from peak-streamflow magnitudes and physical and climatic basin characteristics. These equations may be used for unregulated streams without flow diversions, dams, periodically releasing glacial impoundments, or other streamflow conditions not correlated to basin characteristics. Basin characteristics should be obtained using methods similar to those used in this report to preserve the statistical integrity of the equations.

Streamflow alteration at selected sites in Kansas

USGS Publications Warehouse

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.

Estimating current and future streamflow characteristics at ungaged sites, central and eastern Montana, with application to evaluating effects of climate change on fish populations

USGS Publications Warehouse

Sando, Roy; Chase, Katherine J.

2017-03-23

A common statistical procedure for estimating streamflow statistics at ungaged locations is to develop a relational model between streamflow and drainage basin characteristics at gaged locations using least squares regression analysis; however, least squares regression methods are parametric and make constraining assumptions about the data distribution. The random forest regression method provides an alternative nonparametric method for estimating streamflow characteristics at ungaged sites and requires that the data meet fewer statistical conditions than least squares regression methods.Random forest regression analysis was used to develop predictive models for 89 streamflow characteristics using Precipitation-Runoff Modeling System simulated streamflow data and drainage basin characteristics at 179 sites in central and eastern Montana. The predictive models were developed from streamflow data simulated for current (baseline, water years 1982–99) conditions and three future periods (water years 2021–38, 2046–63, and 2071–88) under three different climate-change scenarios. These predictive models were then used to predict streamflow characteristics for baseline conditions and three future periods at 1,707 fish sampling sites in central and eastern Montana. The average root mean square error for all predictive models was about 50 percent. When streamflow predictions at 23 fish sampling sites were compared to nearby locations with simulated data, the mean relative percent difference was about 43 percent. When predictions were compared to streamflow data recorded at 21 U.S. Geological Survey streamflow-gaging stations outside of the calibration basins, the average mean absolute percent error was about 73 percent.

Development of a Precipitation-Runoff Model to Simulate Unregulated Streamflow in the Salmon Creek Basin, Okanogan County, Washington

USGS Publications Warehouse

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

Trends in streamflow of the San Pedro River, southeastern Arizona, and regional trends in precipitation and streamflow in southeastern Arizona and southwestern New Mexico

USGS Publications Warehouse

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

Hydrologic Drought Decision Support System (HyDroDSS)

USGS Publications Warehouse

Granato, Gregory E.

2014-01-01

The hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below user-defined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought. This report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drought-projection analysis. All three methods are designed to inform decisions made by drought steering committees and decisionmakers on the basis of quantitative risk assessment. All three methods use estimates of unaltered streamflow, which is the measured or modeled flow without major withdrawals or discharges, to approximate a natural low-flow regime. Retrospective streamflow-depletion analysis can be used by water-resource managers to evaluate relations between withdrawal plans and the potential effects of withdrawal plans on streams at one or more sites of interest in an area. Retrospective streamflow-depletion analysis indicates the historical risk of being below user-defined flow targets if different pumping plans were implemented for the period of record. Retrospective streamflow-depletion analysis also indicates the risk for creating hydrologic drought conditions caused by use of a pumping plan. Retrospective streamflow-depletion analysis is done by calculating the net streamflow depletions from withdrawals and discharges and applying these depletions to a simulated record of unaltered streamflow. Rank correlation analysis in the HyDroDSS indicates the persistence of hydrologic measurements from month to month for the prediction of developing hydrologic drought conditions and quantitatively indicates which hydrologic variables may be used to indicate the onset of hydrologic drought conditions. Rank correlation analysis also indicates the potential use of each variable for estimating the monthly minimum unaltered flow at a site of interest for use in the drought-projection analysis. Rank correlation analysis in the HyDroDSS is done by calculating Spearman’s rho for paired samples and the 95-percent confidence limits of this rho value. Rank correlation analysis can be done by using precipitation, groundwater levels, measured streamflows, and estimated unaltered streamflows. Serial correlation analysis, which indicates relations between current and future values, can be done for a single site. Cross correlation analysis, which indicates relations among current values at one site and current and future values at a second site, also can be done. Drought-projection analysis in the HyDroDSS indicates the risk for being in a hydrologic drought condition during the current month and the five following months with and without pumping. Drought-projection analysis also indicates the potential effectiveness of water-conservation methods for mitigating the effect of withdrawals in the coming months on the basis of the amount of depletion caused by different pumping plans and on the risk of unaltered flows being below streamflow targets. Drought-projection analysis in the HyDroDSS is done with Monte Carlo methods by using the position analysis method. In this method the initial value of estimated unaltered streamflows is calculated by correlation to a measured hydrologic variable (monthly precipitation, groundwater levels, or streamflows from an index station identified with the rank correlation analysis). Then a pseudorandom number generator is used to create 251 six-month-long flow traces by using a bootstrap method. Serial correlation of the estimated unaltered monthly minimum streamflows determined from the rank correlation analysis is preserved within each flow trace. The sample of unaltered streamflows indicates the risk of being below flow targets in the coming months under simulated natural conditions (without historic withdrawals). The streamflow-depletion algorithms are then used to estimate risks of flow being below targets if selected pumping plans are used. This report also describes the implementation of the HyDroDSS. The HyDroDSS was developed as a Microsoft Access® database application to facilitate storage, handling, and use of hydrologic datasets with a simple graphical user interface. The program is implemented in the database by using the Visual Basic for Applications® (VBA) programming language. Program source code for the analytical techniques is provided in the HyDroDSS and in electronic text files accompanying this report. Program source code for the graphical user interface and for data-handling code, which is specific to Microsoft Access® and the HyDroDSS, is provided in the database. An installation package with a run-time version of the software is available with this report for potential users who do not have a compatible copy of Microsoft Access®. Administrative rights are needed to install this version of the HyDroDSS. A case study, to demonstrate the use of HyDroDSS and interpretation of results for a site of interest, is detailed for the USGS streamgage on the Hunt River (station 01117000) near East Greenwich in central Rhode Island. The Hunt River streamgage was used because it has a long record of streamflow and is in a well-studied basin with a substantial amount of hydrologic and water-use data including groundwater pumping for municipal water supply.

On improving cold region hydrological processes in the Canadian Land Surface Scheme

NASA Astrophysics Data System (ADS)

Ganji, Arman; Sushama, Laxmi; Verseghy, Diana; Harvey, Richard

2017-01-01

Regional and global climate model simulated streamflows for high-latitude regions show systematic biases, particularly in the timing and magnitude of spring peak flows. Though these biases could be related to the snow water equivalent and spring temperature biases in models, a good part of these biases is due to the unaccounted effects of non-uniform infiltration capacity of the frozen ground and other related processes. In this paper, the treatment of frozen water in the Canadian Land Surface Scheme (CLASS), which is used in the Canadian regional and global climate models, is modified to include fractional permeable area, supercooled liquid water and a new formulation for hydraulic conductivity. The impact of these modifications on the regional hydrology, particularly streamflow, is assessed by comparing three simulations performed with the original and two modified versions of CLASS, driven by atmospheric forcing data from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis (ERA-Interim) for the 1990-2001 period over a northeast Canadian domain. The two modified versions of CLASS differ in the soil hydraulic conductivity and matric potential formulations, with one version being based on formulations from a previous study and the other one is newly proposed. Results suggest statistically significant decreases in infiltration and therefore soil moisture during the snowmelt season for the simulation with the new hydraulic conductivity and matric potential formulations and fractional permeable area concept compared to the original version of CLASS, which is also reflected in the increased spring surface runoff and streamflows in this simulation with modified CLASS over most of the study domain. The simulated spring peaks and their timing in this simulation are also in better agreement to those observed. This study thus demonstrates the importance of treatment of frozen water for realistic simulation of streamflows.

Hurricane impacts on a pair of coastal forested watersheds: implications of selective hurricane damage to forest structure and streamflow dynamics

NASA Astrophysics Data System (ADS)

Jayakaran, A. D.; Williams, T. M.; Ssegane, H.; Amatya, D. M.; Song, B.; Trettin, C. C.

2014-03-01

Hurricanes are infrequent but influential disruptors of ecosystem processes in the southeastern Atlantic and Gulf coasts. Every southeastern forested wetland has the potential to be struck by a tropical cyclone. We examined the impact of Hurricane Hugo on two paired coastal South Carolina watersheds in terms of streamflow and vegetation dynamics, both before and after the hurricane's passage in 1989. The study objectives were to quantify the magnitude and timing of changes including a reversal in relative streamflow difference between two paired watersheds, and to examine the selective impacts of a hurricane on the vegetative composition of the forest. We related these impacts to their potential contribution to change watershed hydrology through altered evapotranspiration processes. Using over 30 years of monthly rainfall and streamflow data we showed that there was a significant transformation in the hydrologic character of the two watersheds - a transformation that occurred soon after the hurricane's passage. We linked the change in the rainfall-runoff relationship to a catastrophic change in forest vegetation due to selective hurricane damage. While both watersheds were located in the path of the hurricane, extant forest structure varied between the two watersheds as a function of experimental forest management techniques on the treatment watershed. We showed that the primary damage was to older pines, and to some extent larger hardwood trees. We believe that lowered vegetative water use impacted both watersheds with increased outflows on both watersheds due to loss of trees following hurricane impact. However, one watershed was able to recover to pre hurricane levels of evapotranspiration at a quicker rate due to the greater abundance of pine seedlings and saplings in that watershed.

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.

Field manual for the collection of Navajo Nation streamflow-gage data

USGS Publications Warehouse

Hart, Robert J.; Fisk, Gregory G.

2014-01-01

The Field Manual for the Collection of Navajo Nation Streamflow-Gage Data (Navajo Field Manual) is based on established (standard) U.S. Geological Survey streamflow-gaging methods and provides guidelines specifically designed for the Navajo Department of Water Resources personnel who establish and maintain streamflow gages. The Navajo Field Manual addresses field visits, including essential field equipment and the selection of and routine visits to streamflow-gaging stations, examines surveying methods for determining peak flows (indirect measurements), discusses safety considerations, and defines basic terms.

The cold rain-on-snow event of June 2013 in the Canadian Rockies – characteristics and diagnosis

USDA-ARS?s Scientific Manuscript database

The June 2013 flood in the Canadian Rockies featured rain-on-snow (ROS) runoff generation at alpine elevations that contributed to the high streamflows observed during the event. Such a mid-summer ROS event has not been diagnosed in detail, but may be typical of high discharge producing hydrometeoro...

Flow velocity and the hydrologic behavior of streams during baseflow.

Treesearch

Steven M. Wondzell; Michael N. Gooseff; Brian L. McGlynn

2007-01-01

Diel variations in stream discharge have long been recognized, but are relatively little studied. Here we demonstrate that these diel fluctuations can be used to investigate both streamflow generation and network routing. We treat evapo-transpiration (ET) as a distributed impulse function in an advection model and analyze the effect of ET on diel fluctuations in...

Initial sediment transport model of the mining-affected Aries River Basin, Romania

USGS Publications Warehouse

Friedel, Michael J.; Linard, Joshua I.

2008-01-01

The Romanian government is interested in understanding the effects of existing and future mining activities on long-term dispersal, storage, and remobilization of sediment-associated metals. An initial Soil and Water Assessment Tool (SWAT) model was prepared using available data to evaluate hypothetical failure of the Valea Sesei tailings dam at the Rosia Poieni mine in the Aries River basin. Using the available data, the initial Aries River Basin SWAT model could not be manually calibrated to accurately reproduce monthly streamflow values observed at the Turda gage station. The poor simulation of the monthly streamflow is attributed to spatially limited soil and precipitation data, limited constraint information due to spatially and temporally limited streamflow measurements, and in ability to obtain optimal parameter values when using a manual calibration process. Suggestions to improve the Aries River basin sediment transport model include accounting for heterogeneity in model input, a two-tier nonlinear calibration strategy, and analysis of uncertainty in predictions.

Application of the Streamflow Prediction Tool to Estimate Sediment Dredging Volumes in Texas Coastal Waterways

NASA Astrophysics Data System (ADS)

Yeates, E.; Dreaper, G.; Afshari, S.; Tavakoly, A. A.

2017-12-01

Over the past six fiscal years, the United States Army Corps of Engineers (USACE) has contracted an average of about a billion dollars per year for navigation channel dredging. To execute these funds effectively, USACE Districts must determine which navigation channels need to be dredged in a given year. Improving this prioritization process results in more efficient waterway maintenance. This study uses the Streamflow Prediction Tool, a runoff routing model based on global weather forecast ensembles, to estimate dredged volumes. This study establishes regional linear relationships between cumulative flow and dredged volumes over a long-term simulation covering 30 years (1985-2015), using drainage area and shoaling parameters. The study framework integrates the National Hydrography Dataset (NHDPlus Dataset) with parameters from the Corps Shoaling Analysis Tool (CSAT) and dredging record data from USACE District records. Results in the test cases of the Houston Ship Channel and the Sabine and Port Arthur Harbor waterways in Texas indicate positive correlation between the simulated streamflows and actual dredging records.

Computation of records of streamflow at control structures

USGS Publications Warehouse

Collins, Dannie L.

1977-01-01

Traditional methods of computing streamflow records on large, low-gradient streams require a continuous record of water-surface slope over a natural channel reach. This slope must be of sufficient magnitude to be accuratly measured with available stage measuring devices. On highly regulated streams, this slope approaches zero during periods of low flow and accurate measurement is difficult. Methods are described to calibrate multipurpose regulating control structures to more accurately compute streamflow records on highly-regulated streams. Hydraulic theory, assuming steady, uniform flow during a computational interval, is described for five different types of flow control. The controls are: Tainter gates, hydraulic turbines, fixed spillways, navigation locks, and crest gates. Detailed calibration procedures are described for the five different controls as well as for several flow regimes for some of the controls. The instrumentation package and computer programs necessary to collect and process the field data are discussed. Two typical calibration procedures and measurement data are presented to illustrate the accuracy of the methods. (Woodard-USGS)

Improved large-scale hydrological modelling through the assimilation of streamflow and downscaled satellite soil moisture observations.

NASA Astrophysics Data System (ADS)

López López, Patricia; Wanders, Niko; Sutanudjaja, Edwin; Renzullo, Luigi; Sterk, Geert; Schellekens, Jaap; Bierkens, Marc

2015-04-01

The coarse spatial resolution of global hydrological models (typically > 0.25o) often limits their ability to resolve key water balance processes for many river basins and thus compromises their suitability for water resources management, especially when compared to locally-tunes river models. A possible solution to the problem may be to drive the coarse resolution models with high-resolution meteorological data as well as to assimilate ground-based and remotely-sensed observations of key water cycle variables. While this would improve the modelling resolution of the global model, the impact of prediction accuracy remains largely an open question. In this study we investigated the impact that assimilating streamflow and satellite soil moisture observations have on global hydrological model estimation, driven by coarse- and high-resolution meteorological observations, for the Murrumbidgee river basin in Australia. The PCR-GLOBWB global hydrological model is forced with downscaled global climatological data (from 0.5o downscaled to 0.1o resolution) obtained from the WATCH Forcing Data (WFDEI) and local high resolution gauging station based gridded datasets (0.05o), sourced from the Australian Bureau of Meteorology. Downscaled satellite derived soil moisture (from 0.5o downscaled to 0.1o resolution) from AMSR-E and streamflow observations collected from 25 gauging stations are assimilated using an ensemble Kalman filter. Several scenarios are analysed to explore the added value of data assimilation considering both local and global climatological data. Results show that the assimilation of streamflow observations result in the largest improvement of the model estimates. The joint assimilation of both streamflow and downscaled soil moisture observations leads to further improved in streamflow simulations (10% reduction in RMSE), mainly in the headwater catchments (up to 10,000 km2). Results also show that the added contribution of data assimilation, for both soil moisture and streamflow, is more pronounced when the global meteorological data are used to force the models. This is caused by the higher uncertainty and coarser resolution of the global forcing. This study demonstrates that it is possible to improve hydrological simulations forced by coarse resolution meteorological data with downscaled satellite soil moisture and streamflow observations and bring them closer to a hydrological model forced with local climatological data. These findings are important in light of the efforts that are currently done to go to global hyper-resolution modelling and can significantly help to advance this research.

Evaluation of Streamflow Requirements for Habitat Protection by Comparison to Streamflow Characteristics at Index Streamflow-Gaging Stations in Southern New England

USGS Publications Warehouse

Armstrong, David S.; Parker, Gene W.; Richards, Todd A.

2003-01-01

Streamflow characteristics and methods for determining streamflow requirements for habitat protection were investigated at 23 active index streamflow-gaging stations in southern New England. Fish communities sampled near index streamflow-gaging stations in Massachusetts have a high percentage of fish that require flowing-water habitats for some or all of their life cycle. The relatively unaltered flow condition at these sites was assumed to be one factor that has contributed to this condition. Monthly flow durations and low flow statistics were determined for the index streamflow-gaging stations for a 25- year period from 1976 to 2000. Annual hydrographs were prepared for each index station from median streamflows at the 50-percent monthly flow duration, normalized by drainage area. A median monthly flow of 1 ft3/s/mi2 was used to split hydrographs into a high-flow period (November–May), and a low-flow period (June–October). The hydrographs were used to classify index stations into groups with similar median monthly flow durations. Index stations were divided into four regional groups, roughly paralleling the coast, to characterize streamflows for November to May; and into two groups, on the basis of base-flow index and percentage of sand and gravel in the contributing area, for June to October. For the June to October period, for index stations with a high base-flow index and contributing areas greater than 20 percent sand and gravel, median streamflows at the 50-percent monthly flow duration, normalized by drainage area, were 0.57, 0.49, and 0.46 ft3/s/mi2 for July, August, and September, respectively. For index stations with a low base-flow index and contributing areas less than 20 percent sand and gravel, median streamflows at the 50-percent monthly flow duration, normalized by drainage area, were 0.34, 0.28, and 0.27 ft3/s/mi2 for July, August, and September, respectively. Streamflow variability between wet and dry years can be characterized by use of the interquartile range of median streamflows at selected monthly flow durations. For example, the median Q50 discharge for August had an interquartile range of 0.30 to 0.87 ft3/s/mi2 for the high-flow group and 0.16 to 0.47 ft3/s/mi2 for the low-flow group. Streamflow requirements for habitat protection were determined for 23 index stations by use of three methods based on hydrologic records, the Range of Variability Approach, the Tennant method, and the New England Aquatic-Base-Flow method. Normalized flow management targets determined by the Range of Variability Approach for July, August, and September ranged between 0.21 and 0.84 ft3/s/mi2 for the low monthly flow duration group, and 0.37 and 1.27 ft3/s/mi2 for the high monthly flow duration group. Median streamflow requirements for habitat protection during summer for the 23 index streamflow-gaging stations determined by the Tennant method, normalized by drainage area, were 0.81, 0.61, and 0.21 ft3/s/mi2 for the Tennant 40-, 30-, and 10-percent of the mean annual flow methods, representing good, fair, and poor stream habitat conditions in summer, according to Tennant. New England Aquatic-Base-Flow streamflow requirements for habitat protection during summer were determined from median of monthly mean flows for August for index streamflow-gaging stations having drainage areas greater than 50 mi2 . For five index streamflow-gaging stations in the low median monthly flow group, the average median monthly mean streamflow for August, normalized by drainage area, was 0.48 ft3/s/mi2. Streamflow requirements for habitat protection were determined for riffle habitats near 10 index stations by use of two methods based on hydraulic ratings, the Wetted-Perimeter and R2Cross methods. Hydraulic parameters required by these methods were simulated by calibrated HEC-RAS models. Wetted-Perimeter streamflow requirements for habitat protection, normalized by drainage area, ranged between 0.13 and 0.58 ft3/s/mi2, and had a median value of 0.37 ft3/s/mi2. Streamflow requirements determined by the R2Cross 3-of-3 criteria method ranged between 0.39 and 2.1 ft3/s/mi2 , and had a median of 0.84 ft3/s/mi2. Streamflow requirements determined by the R2Cross 2-of-3 criteria method, normalized by drainage area, ranged between 0.16 and 0.85 ft3/s/mi2 and had a median of 0.36 ft3/s/mi2 , respectively. Streamflow requirements determined by the different methods were evaluated by comparison to streamflow statistics from the index streamflow-gaging stations.

Sensitivity of monthly streamflow forecasts to the quality of rainfall forcing: When do dynamical climate forecasts outperform the Ensemble Streamflow Prediction (ESP) method?

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.

Accuracy of time-domain and frequency-domain methods used to characterize catchment transit time distributions

NASA Astrophysics Data System (ADS)

Godsey, S. E.; Kirchner, J. W.

2008-12-01

The mean residence time - the average time that it takes rainfall to reach the stream - is a basic parameter used to characterize catchment processes. Heterogeneities in these processes lead to a distribution of travel times around the mean residence time. By examining this travel time distribution, we can better predict catchment response to contamination events. A catchment system with shorter residence times or narrower distributions will respond quickly to contamination events, whereas systems with longer residence times or longer-tailed distributions will respond more slowly to those same contamination events. The travel time distribution of a catchment is typically inferred from time series of passive tracers (e.g., water isotopes or chloride) in precipitation and streamflow. Variations in the tracer concentration in streamflow are usually damped compared to those in precipitation, because precipitation inputs from different storms (with different tracer signatures) are mixed within the catchment. Mathematically, this mixing process is represented by the convolution of the travel time distribution and the precipitation tracer inputs to generate the stream tracer outputs. Because convolution in the time domain is equivalent to multiplication in the frequency domain, it is relatively straightforward to estimate the parameters of the travel time distribution in either domain. In the time domain, the parameters describing the travel time distribution are typically estimated by maximizing the goodness of fit between the modeled and measured tracer outputs. In the frequency domain, the travel time distribution parameters can be estimated by fitting a power-law curve to the ratio of precipitation spectral power to stream spectral power. Differences between the methods of parameter estimation in the time and frequency domain mean that these two methods may respond differently to variations in data quality, record length and sampling frequency. Here we evaluate how well these two methods of travel time parameter estimation respond to different sources of uncertainty and compare the methods to one another. We do this by generating synthetic tracer input time series of different lengths, and convolve these with specified travel-time distributions to generate synthetic output time series. We then sample both the input and output time series at various sampling intervals and corrupt the time series with realistic error structures. Using these 'corrupted' time series, we infer the apparent travel time distribution, and compare it to the known distribution that was used to generate the synthetic data in the first place. This analysis allows us to quantify how different record lengths, sampling intervals, and error structures in the tracer measurements affect the apparent mean residence time and the apparent shape of the travel time distribution.

Streamflow, infiltration, and ground-water recharge at Abo Arroyo, New Mexico: Chapter D in Ground-water recharge in the arid and semiarid southwestern United States (Professional Paper 1703)

USGS Publications Warehouse

Stewart-Deaker, Amy E.; Stonestrom, David A.; Moore, Stephanie J.; Stonestrom, David A.; Constantz, Jim; Ferré, Ty P.A.; Leake, Stanley A.

2007-01-01

Abo Arroyo, an ephemeral tributary to the Rio Grande, rises in the largest upland catchment on the eastern side of the Middle Rio Grande Basin (MRGB). The 30-kilometer reach of channel between the mountain front and its confluence with the Rio Grande is incised into basin-fill sediments and separated from the regional water table by an unsaturated zone that reaches 120 meters thick. The MRGB portion of the arroyo is dry except for brief flows generated by runoff from the upland catchment. Though brief, ephemeral flows provide a substantial fraction of ground-water recharge in the southeastern portion of the MRGB. Previous estimates of average annual recharge from Abo Arroyo range from 1.3 to 21 million cubic meters. The current study examined the timing, location, and amount of channel infiltration using streamflow data and environmental tracers during a four-year period (water years 1997–2000). A streamflow-gaging station (“gage”) was installed in a bedrock-controlled reach near the catchment outlet to provide high-frequency data on runoff entering the basin. Streamflow at the gage, an approximate bound on potential tributary recharge to the basin, ranged from 0.8 to 15 million cubic meters per year. Storm-generated runoff produced about 98 percent of the flow in the wettest year and 80 percent of the flow in the driest year. Nearly all flows that enter the MRGB arise from monsoonal storms in July through October. A newly developed streambed temperature method indicated the presence and duration of ephemeral flows downstream of the gage. During the monsoon season, abrupt downward shifts in streambed temperatures and suppressed diurnal ranges provided generally clear indications of flow. Streambed temperatures during winter showed that snowmelt is also effective in generating channel infiltration. Controlled infiltration experiments in dry arroyo sediments indicated that most ephemeral flow is lost to seepage before reaching the Rio Grande. Streambed temperature records confirmed this, providing evidence of only two flows reaching the Rio Grande during a three-year period (water years 1998–2000). Sub-channel chloride concentrations indicate that approximately half of the seepage loss eventually becomes ground-water recharge. Vertical profiles of pore-water chloride in transects adjacent to the channel indicate that basin-floor recharge outside the arroyo is negligible under current climatic conditions.

Optimizing multiple reliable forward contracts for reservoir allocation using multitime scale streamflow forecasts

NASA Astrophysics Data System (ADS)

Lu, Mengqian; Lall, Upmanu; Robertson, Andrew W.; Cook, Edward

2017-03-01

Streamflow forecasts at multiple time scales provide a new opportunity for reservoir management to address competing objectives. Market instruments such as forward contracts with specified reliability are considered as a tool that may help address the perceived risk associated with the use of such forecasts in lieu of traditional operation and allocation strategies. A water allocation process that enables multiple contracts for water supply and hydropower production with different durations, while maintaining a prescribed level of flood risk reduction, is presented. The allocation process is supported by an optimization model that considers multitime scale ensemble forecasts of monthly streamflow and flood volume over the upcoming season and year, the desired reliability and pricing of proposed contracts for hydropower and water supply. It solves for the size of contracts at each reliability level that can be allocated for each future period, while meeting target end of period reservoir storage with a prescribed reliability. The contracts may be insurable, given that their reliability is verified through retrospective modeling. The process can allow reservoir operators to overcome their concerns as to the appropriate skill of probabilistic forecasts, while providing water users with short-term and long-term guarantees as to how much water or energy they may be allocated. An application of the optimization model to the Bhakra Dam, India, provides an illustration of the process. The issues of forecast skill and contract performance are examined. A field engagement of the idea is useful to develop a real-world perspective and needs a suitable institutional environment.

Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: comparison between lumped and semi-distributed schemes

NASA Astrophysics Data System (ADS)

Alvarez-Garreton, C.; Ryu, D.; Western, A. W.; Su, C.-H.; Crow, W. T.; Robertson, D. E.; Leahy, C.

2014-09-01

Assimilation of remotely sensed soil moisture data (SM-DA) to correct soil water stores of rainfall-runoff models has shown skill in improving streamflow prediction. In the case of large and sparsely monitored catchments, SM-DA is a particularly attractive tool. Within this context, we assimilate active and passive satellite soil moisture (SSM) retrievals using an ensemble Kalman filter to improve operational flood prediction within a large semi-arid catchment in Australia (>40 000 km2). We assess the importance of accounting for channel routing and the spatial distribution of forcing data by applying SM-DA to a lumped and a semi-distributed scheme of the probability distributed model (PDM). Our scheme also accounts for model error representation and seasonal biases and errors in the satellite data. Before assimilation, the semi-distributed model provided more accurate streamflow prediction (Nash-Sutcliffe efficiency, NS = 0.77) than the lumped model (NS = 0.67) at the catchment outlet. However, this did not ensure good performance at the "ungauged" inner catchments. After SM-DA, the streamflow ensemble prediction at the outlet was improved in both the lumped and the semi-distributed schemes: the root mean square error of the ensemble was reduced by 27 and 31%, respectively; the NS of the ensemble mean increased by 7 and 38%, respectively; the false alarm ratio was reduced by 15 and 25%, respectively; and the ensemble prediction spread was reduced while its reliability was maintained. Our findings imply that even when rainfall is the main driver of flooding in semi-arid catchments, adequately processed SSM can be used to reduce errors in the model soil moisture, which in turn provides better streamflow ensemble prediction. We demonstrate that SM-DA efficacy is enhanced when the spatial distribution in forcing data and routing processes are accounted for. At ungauged locations, SM-DA is effective at improving streamflow ensemble prediction, however, the updated prediction is still poor since SM-DA does not address systematic errors in the model.

Statistical summaries of streamflow in Oklahoma through 1999

USGS Publications Warehouse

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.

Mississippi River streamflow measurement techniques at St. Louis, Missouri

USGS Publications Warehouse

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.

Mitigating the Impacts of Climate Nonstationarity on Seasonal Streamflow Predictability in the U.S. Southwest

NASA Astrophysics Data System (ADS)

Lehner, Flavio; Wood, Andrew W.; Llewellyn, Dagmar; Blatchford, Douglas B.; Goodbody, Angus G.; Pappenberger, Florian

2017-12-01

Seasonal streamflow predictions provide a critical management tool for water managers in the American Southwest. In recent decades, persistent prediction errors for spring and summer runoff volumes have been observed in a number of watersheds in the American Southwest. While mostly driven by decadal precipitation trends, these errors also relate to the influence of increasing temperature on streamflow in these basins. Here we show that incorporating seasonal temperature forecasts from operational global climate prediction models into streamflow forecasting models adds prediction skill for watersheds in the headwaters of the Colorado and Rio Grande River basins. Current dynamical seasonal temperature forecasts now show sufficient skill to reduce streamflow forecast errors in snowmelt-driven regions. Such predictions can increase the resilience of streamflow forecasting and water management systems in the face of continuing warming as well as decadal-scale temperature variability and thus help to mitigate the impacts of climate nonstationarity on streamflow predictability.

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.

Trends and sensitivities of low streamflow extremes to discharge timing and magnitude in pacific northwest mountain streams

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...

Comparing large-scale hydrological model predictions with observed streamflow in the Pacific Northwest: effects of climate and groundwater

Treesearch

Mohammad Safeeq; Guillaume S. Mauger; Gordon E. Grant; Ivan Arismendi; Alan F. Hamlet; Se-Yeun Lee

2014-01-01

Assessing uncertainties in hydrologic models can improve accuracy in predicting future streamflow. Here, simulated streamflows using the Variable Infiltration Capacity (VIC) model at coarse (1/16°) and fine (1/120°) spatial resolutions were evaluated against observed streamflows from 217 watersheds. In...

New method for calculating a mathematical expression for streamflow recession

USGS Publications Warehouse

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.

The effects of changing land cover on streamflow simulation in Puerto Rico

USGS Publications Warehouse

Van Beusekom, Ashley E.; Hay, Lauren E.; Viger, Roland; Gould, William A.; Collazo, Jaime; Henareh Khalyani, Azad

2014-01-01

This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from four land cover scenes for the period 1953-2012. The PRMS simulations based on static land cover illustrated consistent differences in simulated streamflow across the island. It was determined that the scale of the analysis makes a difference: large regions with localized areas that have undergone dramatic land cover change may show negligible difference in total streamflow, but streamflow simulations using dynamic land cover parameters for a highly altered subwatershed clearly demonstrate the effects of changing land cover on simulated streamflow. Incorporating dynamic parameterization in these highly altered watersheds can reduce the predictive uncertainty in simulations of streamflow using PRMS. Hydrologic models that do not consider the projected changes in land cover may be inadequate for water resource management planning for future conditions.

Reconstruction and analysis of the past five centuries of streamflow on northern slopes on Tianshan Mountains in Northern Xinjiang, China

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.

Being an honest broker of hydrology: Uncovering, communicating and addressing model error in a climate change streamflow dataset

NASA Astrophysics Data System (ADS)

Chegwidden, O.; Nijssen, B.; Pytlak, E.

2017-12-01

Any model simulation has errors, including errors in meteorological data, process understanding, model structure, and model parameters. These errors may express themselves as bias, timing lags, and differences in sensitivity between the model and the physical world. The evaluation and handling of these errors can greatly affect the legitimacy, validity and usefulness of the resulting scientific product. In this presentation we will discuss a case study of handling and communicating model errors during the development of a hydrologic climate change dataset for the Pacific Northwestern United States. The dataset was the result of a four-year collaboration between the University of Washington, Oregon State University, the Bonneville Power Administration, the United States Army Corps of Engineers and the Bureau of Reclamation. Along the way, the partnership facilitated the discovery of multiple systematic errors in the streamflow dataset. Through an iterative review process, some of those errors could be resolved. For the errors that remained, honest communication of the shortcomings promoted the dataset's legitimacy. Thoroughly explaining errors also improved ways in which the dataset would be used in follow-on impact studies. Finally, we will discuss the development of the "streamflow bias-correction" step often applied to climate change datasets that will be used in impact modeling contexts. We will describe the development of a series of bias-correction techniques through close collaboration among universities and stakeholders. Through that process, both universities and stakeholders learned about the others' expectations and workflows. This mutual learning process allowed for the development of methods that accommodated the stakeholders' specific engineering requirements. The iterative revision process also produced a functional and actionable dataset while preserving its scientific merit. We will describe how encountering earlier techniques' pitfalls allowed us to develop improved methods for scientists and practitioners alike.

Stochastic or statistic? Comparing flow duration curve models in ungauged basins and changing climates

NASA Astrophysics Data System (ADS)

Müller, M. F.; Thompson, S. E.

2015-09-01

The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash-Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drives of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by a strong wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are strongly favored over statistical models.

Regional equations for estimation of peak-streamflow frequency for natural basins in Texas

USGS Publications Warehouse

Asquith, William H.; Slade, Raymond M.

1997-01-01

Peak-streamflow frequency for 559 Texas stations with natural (unregulated and rural or nonurbanized) basins was estimated with annual peak-streamflow data through 1993. The peak-streamflow frequency and drainage-basin characteristics for the Texas stations were used to develop 16 sets of equations to estimate peak-streamflow frequency for ungaged natural stream sites in each of 11 regions in Texas. The relation between peak-streamflow frequency and contributing drainage area for 5 of the 11 regions is curvilinear, requiring that one set of equations be developed for drainage areas less than 32 square miles and another set be developed for drainage areas greater than 32 square miles. These equations, developed through multiple-regression analysis using weighted least squares, are based on the relation between peak-streamflow frequency and basin characteristics for streamflow-gaging stations. The regions represent areas with similar flood characteristics. The use and limitations of the regression equations also are discussed. Additionally, procedures are presented to compute the 50-, 67-, and 90-percent confidence limits for any estimation from the equations. Also, supplemental peak-streamflow frequency and basin characteristics for 105 selected stations bordering Texas are included in the report. This supplemental information will aid in interpretation of flood characteristics for sites near the state borders of Texas.

Climate model assessment of changes in winter-spring streamflow timing over North America

USGS Publications Warehouse

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.

Reconstructing pre-instrumental streamflow in Eastern Australia using a water balance approach

NASA Astrophysics Data System (ADS)

Tozer, C. R.; Kiem, A. S.; Vance, T. R.; Roberts, J. L.; Curran, M. A. J.; Moy, A. D.

2018-03-01

Streamflow reconstructions based on paleoclimate proxies provide much longer records than the short instrumental period records on which water resource management plans are currently based. In Australia there is a lack of in-situ high resolution paleoclimate proxy records, but remote proxies with teleconnections to Australian climate have utility in producing streamflow reconstructions. Here we investigate, via a case study for a catchment in eastern Australia, the novel use of an Antarctic ice-core based rainfall reconstruction within a Budyko-framework to reconstruct ∼1000 years of annual streamflow. The resulting streamflow reconstruction captures interannual to decadal variability in the instrumental streamflow, validating both the use of the ice core rainfall proxy record and the Budyko-framework method. In the preinstrumental era the streamflow reconstruction shows longer wet and dry epochs and periods of streamflow variability that are higher than observed in the instrumental era. Importantly, for both the instrumental record and preinstrumental reconstructions, the wet (dry) epochs in the rainfall record are shorter (longer) in the streamflow record and this non-linearity must be considered when inferring hydroclimatic risk or historical water availability directly from rainfall proxy records alone. These insights provide a better understanding of present infrastructure vulnerability in the context of past climate variability for eastern Australia. The streamflow reconstruction presented here also provides a better understanding of the range of hydroclimatic variability possible, and therefore represents a more realistic baseline on which to quantify the potential impacts of anthropogenic climate change on water security.

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.

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.

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.

Acoustic Doppler current profiler applications used in rivers and estuaries by the U.S. Geological Survey

USGS Publications Warehouse

Gotvald, Anthony J.; Oberg, Kevin A.

2009-01-01

The U.S. Geological Survey (USGS) has collected streamflow information for the Nation's streams since 1889. Streamflow information is used to predict floods, manage and allocate water resources, design engineering structures, compute water-quality loads, and operate water-control structures. The current (2007) size of the USGS streamgaging network is over 7,400 streamgages nationwide. The USGS has progressively improved the streamgaging program by incorporating new technologies and techniques that streamline data collection while increasing the quality of the streamflow data that are collected. The single greatest change in streamflow measurement technology during the last 100 years has been the development and application of high frequency acoustic instruments for measuring streamflow. One such instrument, the acoustic Doppler current profiler (ADCP), is rapidly replacing traditional mechanical current meters for streamflow measurement (Muste and others, 2007). For more information on how an ADCP works see Simpson (2001) or visit http://hydroacoustics.usgs.gov/. The USGS has used ADCPs attached to manned or tethered boats since the mid-1990s to measure streamflow in a wide variety of conditions (fig. 1). Recent analyses have shown that ADCP streamflow measurements can be made with similar or greater accuracy, efficiency, and resolution than measurements made using conventional current-meter methods (Oberg and Mueller, 2007). ADCPs also have the ability to measure streamflow in streams where traditional current-meter measurements previously were very difficult or costly to obtain, such as streams affected by backwater or tides. In addition to streamflow measurements, the USGS also uses ADCPs for other hydrologic measurements and applications, such as computing continuous records of streamflow for tidally or backwater affected streams, measuring velocity fields with high spatial and temporal resolution, and estimating suspended-sediment concentrations. An overview of these applications is provided in the fact sheet.

A hydrogeologic framework for characterizing summer streamflow sensitivity to climate warming in the Pacific Northwest, USA

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.

Methods for estimating the magnitude and frequency of peak streamflows for unregulated streams in Oklahoma

USGS Publications Warehouse

Lewis, Jason M.

2010-01-01

Peak-streamflow regression equations were determined for estimating flows with exceedance probabilities from 50 to 0.2 percent for the state of Oklahoma. These regression equations incorporate basin characteristics to estimate peak-streamflow magnitude and frequency throughout the state by use of a generalized least squares regression analysis. The most statistically significant independent variables required to estimate peak-streamflow magnitude and frequency for unregulated streams in Oklahoma are contributing drainage area, mean-annual precipitation, and main-channel slope. The regression equations are applicable for watershed basins with drainage areas less than 2,510 square miles that are not affected by regulation. The resulting regression equations had a standard model error ranging from 31 to 46 percent. Annual-maximum peak flows observed at 231 streamflow-gaging stations through water year 2008 were used for the regression analysis. Gage peak-streamflow estimates were used from previous work unless 2008 gaging-station data were available, in which new peak-streamflow estimates were calculated. The U.S. Geological Survey StreamStats web application was used to obtain the independent variables required for the peak-streamflow regression equations. Limitations on the use of the regression equations and the reliability of regression estimates for natural unregulated streams are described. Log-Pearson Type III analysis information, basin and climate characteristics, and the peak-streamflow frequency estimates for the 231 gaging stations in and near Oklahoma are listed. Methodologies are presented to estimate peak streamflows at ungaged sites by using estimates from gaging stations on unregulated streams. For ungaged sites on urban streams and streams regulated by small floodwater retarding structures, an adjustment of the statewide regression equations for natural unregulated streams can be used to estimate peak-streamflow magnitude and frequency.

Wavelet-based variability of Yellow River discharge at 500-, 100-, and 50-year timescales

NASA Astrophysics Data System (ADS)

Su, Lu; Miao, Chiyuan; Duan, Qingyun

2017-04-01

Water scarcity in the Yellow River, China, has become increasingly severe over the past half century. In this paper, wavelet transform analysis was used to detect the variability of observed and reconstructed streamflow in the Yellow River at 500-, 100-, and 50-year timescales. The periodicity of the streamflow series and the co-varying relationships between streamflow and atmospheric circulation indices / sunspot number were assessed via the continuous wavelet transform (CWT) and the wavelet coherence transform (WTC). The CWT results showed intermittent oscillations in streamflow with increasing periodicities of 1-6 years at all timescales. Significant multidecadal and century-scale periodicities were identified in the 500-year streamflow series. The WTC results showed intermittent interannual covariance of streamflow with atmospheric circulation indices and sunspots. At the 50-year timescale, there were significant decadal oscillations between streamflow and the Arctic Oscillation (AO) and the Pacific Decadal Oscillation (PDO), and bidecadal oscillations with the PDO. At the 100-year timescale, there were significant decadal oscillations between streamflow and Niño 3.4, the AO, and sunspots. At the 500-year timescale, streamflow in the middle reaches of the Yellow River showed prominent covariance with the AO with an approximately 32-year periodicity, and with sunspots with an approximately 80-year periodicity. Atmospheric circulation indices modulate streamflow by affecting temperature and precipitation. Sunspots impact streamflow variability by influencing atmospheric circulation, resulting in abundant precipitation. In general, for both the CWT and the WTC results, the periodicities were spatially continuous, with a few gradual changes from upstream to downstream resulting from the varied topography and runoff. At the temporal scale, the periodicities were generally continuous over short timescales and discontinuous over longer timescales.

Wavelet-based Variability of Yellow River Discharge at 500-, 100-, and 50-Year Timescales

NASA Astrophysics Data System (ADS)

Su, L.

2017-12-01

Water scarcity in the Yellow River, China, has become increasingly severe over the past half century. In this paper, wavelet transform analysis was used to detect the variability of natural, observed, and reconstructed streamflow in the Yellow River at 500-, 100-, and 50-year timescales. The periodicity of the streamflow series and the co-varying relationships between streamflow and atmospheric circulation indices/sunspot number were assessed by means of continuous wavelet transform (CWT) and wavelet transform coherence (WTC) analyses. The CWT results showed intermittent oscillations in streamflow with increasing periodicities of 1-6 years at all timescales. Significant multidecadal and century-scale periodicities were identified in the 500-year streamflow series. The WTC results showed intermittent interannual covariance of streamflow with atmospheric circulation indices and sunspots. At the 50-year timescale, there were significant decadal oscillations between streamflow and the Arctic Oscillation (AO) and the Pacific Decadal Oscillation (PDO), and bidecadal oscillations with the PDO. At the 100-year timescale, there were significant decadal oscillations between streamflow and Niño 3.4, the AO, and sunspots. At the 500-year timescale, streamflow in the middle reaches of the Yellow River showed prominent covariance with the AO with an approximately 32-year periodicity, and with sunspots with an approximately 80-year periodicity. Atmospheric circulation indices modulate streamflow by affecting temperature and precipitation. Sunspots impact streamflow variability by influencing atmospheric circulation, resulting in abundant precipitation. In general, for both the CWT and the WTC results, the periodicities were spatially continuous, with a few gradual changes from upstream to downstream resulting from the varied topography and runoff. At the temporal scale, the periodicities were generally continuous over short timescales and discontinuous over longer timescales.

Spatiotemporal patterns of precipitation inferred from streamflow observations across the Sierra Nevada mountain range

NASA Astrophysics Data System (ADS)

Henn, Brian; Clark, Martyn P.; Kavetski, Dmitri; Newman, Andrew J.; Hughes, Mimi; McGurk, Bruce; Lundquist, Jessica D.

2018-01-01

Given uncertainty in precipitation gauge-based gridded datasets over complex terrain, we use multiple streamflow observations as an additional source of information about precipitation, in order to identify spatial and temporal differences between a gridded precipitation dataset and precipitation inferred from streamflow. We test whether gridded datasets capture across-crest and regional spatial patterns of variability, as well as year-to-year variability and trends in precipitation, in comparison to precipitation inferred from streamflow. We use a Bayesian model calibration routine with multiple lumped hydrologic model structures to infer the most likely basin-mean, water-year total precipitation for 56 basins with long-term (>30 year) streamflow records in the Sierra Nevada mountain range of California. We compare basin-mean precipitation derived from this approach with basin-mean precipitation from a precipitation gauge-based, 1/16° gridded dataset that has been used to simulate and evaluate trends in Western United States streamflow and snowpack over the 20th century. We find that the long-term average spatial patterns differ: in particular, there is less precipitation in the gridded dataset in higher-elevation basins whose aspect faces prevailing cool-season winds, as compared to precipitation inferred from streamflow. In a few years and basins, there is less gridded precipitation than there is observed streamflow. Lower-elevation, southern, and east-of-crest basins show better agreement between gridded and inferred precipitation. Implied actual evapotranspiration (calculated as precipitation minus streamflow) then also varies between the streamflow-based estimates and the gridded dataset. Absolute uncertainty in precipitation inferred from streamflow is substantial, but the signal of basin-to-basin and year-to-year differences are likely more robust. The findings suggest that considering streamflow when spatially distributing precipitation in complex terrain may improve its representation, particularly for basins whose orientations (e.g., windward-facing) are favored for orographic precipitation enhancement.

Simulation of streamflow and estimation of recharge to the Edwards aquifer in the Hondo Creek, Verde Creek, and San Geronimo Creek watersheds, south-central Texas, 1951-2003

USGS Publications Warehouse

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.

The influence of north Pacific atmospheric circulation on streamflow in the west

USGS Publications Warehouse

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.

Trends in precipitation and streamflow and changes in stream morphology in the Fountain Creek watershed, Colorado, 1939-99

USGS Publications Warehouse

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.

Application of AFINCH as a tool for evaluating the effects of streamflow-gaging-network size and composition on the accuracy and precision of streamflow estimates at ungaged locations in the southeast Lake Michigan hydrologic subregion

USGS Publications Warehouse

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.

Unravelling connections between river flow and large-scale climate: experiences from Europe

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Kingston, D. G.; Lavers, D.; Stagge, J. H.; Tallaksen, L. M.

2016-12-01

The United Nations has identified better knowledge of large-scale water cycle processes as essential for socio-economic development and global water-food-energy security. In this context, and given the ever-growing concerns about climate change/ variability and human impacts on hydrology, there is an urgent research need: (a) to quantify space-time variability in regional river flow, and (b) to improve hydroclimatological understanding of climate-flow connections as a basis for identifying current and future water-related issues. In this paper, we draw together studies undertaken at the pan-European scale: (1) to evaluate current methods for assessing space-time dynamics for different streamflow metrics (annual regimes, low flows and high flows) and for linking flow variability to atmospheric drivers (circulation indices, air-masses, gridded climate fields and vapour flux); and (2) to propose a plan for future research connecting streamflow and the atmospheric conditions in Europe and elsewhere. We believe this research makes a useful, unique contribution to the literature through a systematic inter-comparison of different streamflow metrics and atmospheric descriptors. In our findings, we highlight the need to consider appropriate atmospheric descriptors (dependent on the target flow metric and region of interest) and to develop analytical techniques that best characterise connections in the ocean-atmosphere-land surface process chain. We call for the need to consider not only atmospheric interactions, but also the role of the river basin-scale terrestrial hydrological processes in modifying the climate signal response of river flows.

A history of annual streamflows from the 21 water-resource regions in the United States and Puerto Rico, 1951-83

USGS Publications Warehouse

Graczyk, D.J.; Krug, W.R.; Gebert, W.A.

1986-01-01

Streamflow from the Upper and Lower Colorado (Regions 14 and 15) appear to be heavily affected by large storage reservoirs. Streamflow from the Upper Colorado (Region 14) shows a decreasing streamflow in 1963 and 1964, which may be due to filling of Lake Powell.

A hydrogeologic framework for characterizing summer streamflow sensitivity to climate warming in the Pacific Northwest, USA

Treesearch

M. Safeeq; G.E. Grant; S.L. Lewis; M.G. Kramer; B. Staab

2014-01-01

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...

Streamflow responses to road building and harvesting: A comparison with the equivalent clearcut area procedure

Treesearch

John G. King

1989-01-01

lncreases in annual streamflow and peak streamflows were determined on four small watersheds following timber harvesting and road building. The measured hydrologic changes are compared to those predicted by a methodology commonly used in the Forest Service's Northern Region, the equivalent clearcut area procedure. lncreases in peak streamflows are discussed with...

Trends and sensitivities of low streamflow extremes to discharge timing and magnitude in Pacific Northwest mountain streams

Treesearch

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...

Use of the Water, Energy, and Biogeochemical Model (WEBMOD) to Simulate Water Quality at Five U.S. Geological Survey Research Watersheds

NASA Astrophysics Data System (ADS)

Webb, R. M.; Leavesley, G. H.; Shanley, J. B.; Peters, N. E.; Aulenbach, B. T.; Blum, A. E.; Campbell, D. H.; Clow, D. W.; Mast, M. A.; Stallard, R. F.; Larsen, M. C.; Troester, J. W.; Walker, J. F.; White, A. F.

2003-12-01

The Water, Energy, and Biogeochemical Model (WEBMOD) was developed as an aid to compare and contrast basic hydrologic and biogeochemical processes active in the diverse hydroclimatic regions represented by the five U.S. Geological Survey (USGS) Water, Energy, and Biogeochemical Budget (WEBB) sites: Loch Vale, Colorado; Trout Lake, Wisconsin; Sleepers River, Vermont; Panola Mountain, Georgia; and Luquillo Experimental Forest, Puerto Rico. WEBMOD simulates solute concentrations for vegetation canopy, snow pack, impermeable ground, leaf litter, unsaturated and saturated soil zones, riparian zones and streams using selected process modules coupled within the USGS Modular Modeling System (MMS). Source codes for the MMS hydrologic modules include the USGS Precipitation Runoff Modeling System, the National Weather Service Hydro-17 snow model, and TOPMODEL. The hydrologic modules distribute precipitation and temperature to predict evapotranspiration, snow accumulation, snow melt, and streamflow. Streamflow generation mechanisms include infiltration excess, saturated overland flow, preferential lateral flow, and base flow. Input precipitation chemistry, and fluxes and residence times predicted by the hydrologic modules are input into the geochemical module where solute concentrations are computed for a series of discrete well-mixed reservoirs using calls to the geochemical engine PHREEQC. WEBMOD was used to better understand variations in water quality observed at the WEBB sites from October 1991 through September 1997. Initial calibrations were completed by fitting the simulated hydrographs with those measured at the watershed outlets. Model performance was then refined by comparing the predicted export of conservative chemical tracers such as chloride, with those measured at the watershed outlets. The model succeeded in duplicating the temporal variability of net exports of major ions from the watersheds.

How Is Topographic Simplicity Maintained in Ephemeral, Dryland Channels?

NASA Astrophysics Data System (ADS)

Singer, M. B.; Michaelides, K.

2014-12-01

Topography in river channels reflects the time integral of streamflow-driven sediment flux mass balance. In dryland basins, infrequent and spatially heterogeneous rainfall generates a nonuniform sediment supply to ephemeral channels from hillslopes, and this sediment is subsequently sorted by spatially and temporally discontinuous channel flow. Paradoxically, the time integral of these interactions tends to produce simple topography, manifest in straight longitudinal profiles and symmetrical cross sections, which are distinct from bed morphology in perennial channels, but the controlling processes are unclear. We present a set of numerical modeling experiments based on field measurements and scenarios of uniform/nonuniform streamflow to investigate ephemeral channel bed-material flux and net sediment accumulation behavior in response to variations in channel hydrology, width, and grain size distribution. Coupled with variations in valley and channel width and frequent, yet discontinuous hillslope supply of coarse sediment, bed material becomes weakly sorted into coarse and fine sections that then affect rates of channel Qs. We identify three sediment transport thresholds relevant to poorly armored, dryland channels: 1) a low critical value required to entrain any grain sizes from the bed; 2) a value of ~4.5τ*c needed to move all grain sizes within a cross section with equal mobility; and 3) a value of ~50τ*c required to entrain gravel at nearly equivalent rates at all sections along a reach. The latter represents the 'geomorphically effective' event, which resets channel topography. We show that spatially variable flow below ~50τ*c creates and subsequently destroys incipient topography along ephemeral reaches and that large flood events above this threshold apparently dampen fluctuations in longitudinal sediment flux and thus smooth incipient channel bar forms. Both processes contribute to the maintenance of topographic simplicity in ephemeral dryland channels.

Simulating Streamflow and Dissolved Organic Matter Export from small Forested Watersheds

NASA Astrophysics Data System (ADS)

Xu, N.; Wilson, H.; Saiers, J. E.

2010-12-01

Coupling the rainfall-runoff process and solute transport in catchment models is important for understanding the dynamics of water-quality-relevant constituents in a watershed. To simulate the hydrologic and biogeochemical processes in a parametrically parsimonious way remains challenging. The purpose of this study is to quantify the export of water and dissolved organic matter (DOM) from a forested catchment by developing and testing a coupled model for rainfall-runoff and soil-water flushing of DOM. Natural DOM plays an important role in terrestrial and aquatic systems by affecting nutrient cycling, contaminant mobility and toxicity, and drinking water quality. Stream-water discharge and DOM concentrations were measured in a first-order stream in Harvard Forest, Massachusetts. These measurements show that stream water DOM concentrations are greatest during hydrologic events induced by rainfall or snowmelt and decline to low, steady levels during periods of baseflow. Comparison of the stream-discharge data to calculations of a simple rainfall-runoff model reveals a hysteretic relationship between stream-flow rates and the storage of water within the catchment. A modified version of the rainfall-runoff model that accounts for hysteresis in the storage-discharge relationship in a parametrically simple way is capable of describing much, but not all, of the variation in the time-series data on stream discharge. Our ongoing research is aimed at linking the new rainfall-runoff formulation with coupled equations that predict soil-flushing and stream-water concentrations of DOM as functions of the temporal change in catchment water storage. This model will provide a predictive tool for examining how changes in climatic variables would affect the runoff generation and DOM fluxes from terrestrial landscape.

The HEPEX Seasonal Streamflow Forecast Intercomparison Project

NASA Astrophysics Data System (ADS)

Wood, A. W.; Schepen, A.; Bennett, J.; Mendoza, P. A.; Ramos, M. H.; Wetterhall, F.; Pechlivanidis, I.

2016-12-01

The Hydrologic Ensemble Prediction Experiment (HEPEX; www.hepex.org) has launched an international seasonal streamflow forecasting intercomparison project (SSFIP) with the goal of broadening community knowledge about the strengths and weaknesses of various operational approaches being developed around the world. While some of these approaches have existed for decades (e.g. Ensemble Streamflow Prediction - ESP - in the United States and elsewhere), recent years have seen the proliferation of new operational and experimental streamflow forecasting approaches. These have largely been developed independently in each country, thus it is difficult to assess whether the approaches employed in some centers offer more promise for development than others. This motivates us to establish a forecasting testbed to facilitate a diagnostic evaluation of a range of different streamflow forecasting approaches and their components over a common set of catchments, using a common set of validation methods. Rather than prescribing a set of scientific questions from the outset, we are letting the hindcast results and notable differences in methodologies on a watershed-specific basis motivate more targeted analyses and sub-experiments that may provide useful insights. The initial pilot of the testbed involved two approaches - CSIRO's Bayesian joint probability (BJP) and NCAR's sequential regression - for two catchments, each designated by one of the teams (the Murray River, Australia, and Hungry Horse reservoir drainage area, USA). Additional catchments/approaches are in the process of being added to the testbed. To support this CSIRO and NCAR have developed data and analysis tools, data standards and protocols to formalize the experiment. These include requirements for cross-validation, verification, reference climatologies, and common predictands. This presentation describes the SSFIP experiments, pilot basin results and scientific findings to date.

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.

Dissolved oxygen in the Tualatin River, Oregon, during winter flow conditions, 1991 and 1992

USGS Publications Warehouse

Kelly, V.J.

1996-01-01

Throughout the winter period, November through April, wastewater treatment plants in the Tualatin River Basin discharge from 10,000 to 15,000 pounds per day of biochemical oxygen demand to the river. These loads often increase substantially during storms when streamflow is high. During the early winter season, when streamflow is frequently less than the average winter flow, the treatment plants discharge about 2,000 pounds per day of ammonia. This study focused on the capacity of the Tualatin River to assimilat oxygen-demanding loads under winter streamflow conditions during the 1992 water year, with an emphasis on peak-flow conditions in the river, and winter-base-flow conditions during November 1992. Concentrations of dissolved oxygen throughout the main stem of the river during the winter remained generally high relative to the State standard for Oregon of 6 milligrams per liter. The most important factors controlling oxygen consumption during winter-low-flow conditions were carbonaceous biochemical oxygen demand and input of oxygen-depleted waters from tributaries. During peak-flow conditions, reduced travel time and increased dilution associated with the increased streamflow minimized the effect of increased oxygen-demanding loads. During the base-flow period in November 1992, concentrations of dissolved oxygen were consistently below 6 milligrams per liter. A hydrodynamic water-quality model was used to identify the processes depleting dissolved oxygen, including sediment oxygen demand, nitrification, and carbonaceous biochemical oxygen demand. Sediment oxygen demand was the most significant factor; nitrification was also important. Hypothetical scenarios were posed to evaluate the effect of different wastewater treatment plant loads during winter-base-flow conditions. Streamflow and temperature were significant factors governing concentrations of dissolved oxygen in the main-stem river.

On the performance of updating Stochastic Dynamic Programming policy using Ensemble Streamflow Prediction in a snow-covered region

NASA Astrophysics Data System (ADS)

Martin, A.; Pascal, C.; Leconte, R.

2014-12-01

Stochastic Dynamic Programming (SDP) is known to be an effective technique to find the optimal operating policy of hydropower systems. In order to improve the performance of SDP, this project evaluates the impact of re-updating the policy at every time step by using Ensemble Streamflow Prediction (ESP). We present a case study of the Kemano's hydropower system on the Nechako River in British Columbia, Canada. Managed by Rio Tinto Alcan (RTA), this system is subject to large streamflow volumes in spring due to important amount of snow depth during the winter season. Therefore, the operating policy should not only maximize production but also minimize the risk of flooding. The hydrological behavior of the system is simulated with CEQUEAU, a distributed and deterministic hydrological model developed by the Institut national de la recherche scientifique - Eau, Terre et Environnement (INRS-ETE) in Quebec, Canada. On each decision time step, CEQUEAU is used to generate ESP scenarios based on historical meteorological sequences and the current state of the hydrological model. These scenarios are used into the SDP to optimize the new release policy for the next time steps. This routine is then repeated over the entire simulation period. Results are compared with those obtained by using SDP on historical inflow scenarios.

Streamflow response to future land-cover change at a headwaters catchment spanning the alpine-subalpine transition on the Colorado Front Range

NASA Astrophysics Data System (ADS)

Barnhart, T. B.; Vukomanovic, J.; Bourgeron, P.; Molotch, N. P.

2017-12-01

Land-cover change at the alpine-subalpine interface has the potential to change the water balance of mountainous, snow-dominated catchments due to the influence of vegetation on blowing snow, effective precipitation, evapotranspiration, and other processes. Understanding how land-cover change will impact water resources in snow-dominated regions is of critical importance as these locations produce a disproportionate amount of runoff relative to their land area. We coupled the LANdscape DIsturbance and Succession (LANDIS-II) model with a spatially explicit, physics-based, watershed process model, the Regional Hydro-Ecologic Simulation System (RHESSys), to simulate land-cover change and its impact on the water balance in a 6.6 km­2 headwater catchment that spans the alpine-subalpine transition on the Colorado Front Range. We simulated two potential futures of air temperature warming (+4 °C/century) to 2100: a) increased precipitation (+15%, MP) and b) decreased precipitation (-15%, LP). As the LANDIS-II model simulates forest succession in a stochastic manner, we use three LANDIS-II model runs each for the MP and LP future forcing conditions. For both MP and LP, the RHESSys forcing data set was updated to reflect the changes in precipitation and temperature used to generate the land-cover futures. Forest cover in the catchment increased from 72% in 2000 to 84% and 83% in 2050 and to 95% and 92% in 2100 for MP and LP, respectively. Somewhat surprisingly, this increase in forest cover led to mean increases in streamflow production of 9% for MP and 3% for LP in 2050. In 2100, mean streamflow production increased by 15% and 6% for the MP and LP scenarios, respectively. This is likely due to increases in effective precipitation as the catchment forested and blowing snow decreased. Indeed, catchment effective precipitation increased from 94% in 2000 to 97% and 99% in 2050 and 2100, respectively, for both MP and LP conditions. This result counters previous work as runoff production increased with forested area, highlighting the need to better understand the impacts of forest expansion on blowing snow and effective precipitation. Identifying the hydrologic response of mountainous areas to climate warming induced land-cover change is of critical importance due to the potential water resources impacts in downstream regions.

Computing daily mean streamflow at ungaged locations in Iowa by using the Flow Anywhere and Flow Duration Curve Transfer statistical methods

USGS Publications Warehouse

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.

Effect of Tree-to-Shrub Type Conversion in Lower Montane Forests of the Sierra Nevada (USA) on Streamflow

PubMed Central

Tague, Christina L.; Moritz, Max A.

2016-01-01

Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation < 800 mm), with most streamflow change observed during wetter years. These modeling results underscore the importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada. PMID:27575592

Effect of Tree-to-Shrub Type Conversion in Lower Montane Forests of the Sierra Nevada (USA) on Streamflow.

PubMed

Bart, Ryan R; Tague, Christina L; Moritz, Max A

2016-01-01

Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation < 800 mm), with most streamflow change observed during wetter years. These modeling results underscore the importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada.

On the Value of Climate Elasticity Indices to Assess the Impact of Climate Change on Streamflow Projection using an ensemble of bias corrected CMIP5 dataset

NASA Astrophysics Data System (ADS)

Demirel, Mehmet; Moradkhani, Hamid

2015-04-01

Changes in two climate elasticity indices, i.e. temperature and precipitation elasticity of streamflow, were investigated using an ensemble of bias corrected CMIP5 dataset as forcing to two hydrologic models. The Variable Infiltration Capacity (VIC) and the Sacramento Soil Moisture Accounting (SAC-SMA) hydrologic models, were calibrated at 1/16 degree resolution and the simulated streamflow was routed to the basin outlet of interest. We estimated precipitation and temperature elasticity of streamflow from: (1) observed streamflow; (2) simulated streamflow by VIC and SAC-SMA models using observed climate for the current climate (1963-2003); (3) simulated streamflow using simulated climate from 10 GCM - CMIP5 dataset for the future climate (2010-2099) including two concentration pathways (RCP4.5 and RCP8.5) and two downscaled climate products (BCSD and MACA). The streamflow sensitivity to long-term (e.g., 30-year) average annual changes in temperature and precipitation is estimated for three periods i.e. 2010-40, 2040-70 and 2070-99. We compared the results of the three cases to reflect on the value of precipitation and temperature indices to assess the climate change impacts on Columbia River streamflow. Moreover, these three cases for two models are used to assess the effects of different uncertainty sources (model forcing, model structure and different pathways) on the two climate elasticity indices.

Macroinvertebrate community change associated with the severity of streamflow alteration

USGS Publications Warehouse

Carlisle, Daren M.; Eng, Kenny; Nelson, S.M.

2014-01-01

Natural streamflows play a critical role in stream ecosystems, yet quantitative relations between streamflow alteration and stream health have been elusive. One reason for this difficulty is that neither streamflow alteration nor ecological responses are measured relative to their natural expectations. We assessed macroinvertebrate community condition in 25 mountain streams representing a large gradient of streamflow alteration, which we quantified as the departure of observed flows from natural expectations. Observed flows were obtained from US Geological Survey streamgaging stations and discharge records from dams and diversion structures. During low-flow conditions in September, samples of macroinvertebrate communities were collected at each site, in addition to measures of physical habitat, water chemistry and organic matter. In general, streamflows were artificially high during summer and artificially low throughout the rest of the year. Biological condition, as measured by richness of sensitive taxa (Ephemeroptera, Plecoptera and Trichoptera) and taxonomic completeness (O/E), was strongly and negatively related to the severity of depleted flows in winter. Analyses of macroinvertebrate traits suggest that taxa losses may have been caused by thermal modification associated with streamflow alteration. Our study yielded quantitative relations between the severity of streamflow alteration and the degree of biological impairment and suggests that water management that reduces streamflows during winter months is likely to have negative effects on downstream benthic communities in Utah mountain streams. 

Regional patterns of postwildfire streamflow response in the Western United States: The importance of scale-specific connectivity

Treesearch

Dennis W. Hallema; Ge Sun; Kevin D. Bladon; Steven P. Norman; Peter V. Caldwell; Yongqiang Liu; Steven G. McNulty

2017-01-01

Wildfires can impact streamflow by modifying net precipitation, infiltration, evapotranspiration, snowmelt, and hillslope run‐off pathways. Regional differences in fire trends and postwildfire streamflow responses across the conterminous United States have spurred concerns about the impact on streamflow in forests that serve as water resource areas. This is notably the...

Two Topics in Seasonal Streamflow Forecasting: Soil Moisture Initialization Error and Precipitation Downscaling

NASA Technical Reports Server (NTRS)

Koster, Randal; Walker, Greg; Mahanama, Sarith; Reichle, Rolf

2012-01-01

Continental-scale offline simulations with a land surface model are used to address two important issues in the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which the downscaling of seasonal precipitation forecasts, if it could be done accurately, would improve streamflow forecasts. The reduction in streamflow forecast skill (with forecasted streamflow measured against observations) associated with adding noise to a soil moisture field is found to be, to first order, proportional to the average reduction in the accuracy of the soil moisture field itself. This result has implications for streamflow forecast improvement under satellite-based soil moisture measurement programs. In the second and more idealized ("perfect model") analysis, precipitation downscaling is found to have an impact on large-scale streamflow forecasts only if two conditions are met: (i) evaporation variance is significant relative to the precipitation variance, and (ii) the subgrid spatial variance of precipitation is adequately large. In the large-scale continental region studied (the conterminous United States), these two conditions are met in only a somewhat limited area.

Evaluation of drainage-area ratio method used to estimate streamflow for the Red River of the North Basin, North Dakota and Minnesota

USGS Publications Warehouse

Emerson, Douglas G.; Vecchia, Aldo V.; Dahl, Ann L.

2005-01-01

The drainage-area ratio method commonly is used to estimate streamflow for sites where no streamflow data were collected. To evaluate the validity of the drainage-area ratio method and to determine if an improved method could be developed to estimate streamflow, a multiple-regression technique was used to determine if drainage area, main channel slope, and precipitation were significant variables for estimating streamflow in the Red River of the North Basin. A separate regression analysis was performed for streamflow for each of three seasons-- winter, spring, and summer. Drainage area and summer precipitation were the most significant variables. However, the regression equations generally overestimated streamflows for North Dakota stations and underestimated streamflows for Minnesota stations. To correct the bias in the residuals for the two groups of stations, indicator variables were included to allow both the intercept and the coefficient for the logarithm of drainage area to depend on the group. Drainage area was the only significant variable in the revised regression equations. The exponents for the drainage-area ratio were 0.85 for the winter season, 0.91 for the spring season, and 1.02 for the summer season.

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.

Parameterization of the ACRU model for estimating biophysical and climatological change impacts, Beaver Creek, Alberta

NASA Astrophysics Data System (ADS)

Forbes, K. A.; Kienzle, S. W.; Coburn, C. A.; Byrne, J. M.

2006-12-01

Multiple threats, including intensification of agricultural production, non-renewable resource extraction and climate change, are threatening Southern Alberta's water supply. The objective of this research is to calibrate/evaluate the Agricultural Catchments Research Unit (ACRU) agrohydrological model; with the end goal of forecasting the impacts of a changing environment on water quantity. The strength of this model is the intensive multi-layered soil water budgeting routine that integrates water movement between the surface and atmosphere. The ACRU model was parameterized using data from Environment Canada's climate database for a twenty year period (1984-2004) and was used to simulate streamflow for Beaver Creek. The simulated streamflow was compared to Environment Canada's historical streamflow database to validate the model output. The Beaver Creek Watershed, located in the Porcupine Hills southwestern Alberta, Canada contains a heterogeneous cover of deciduous, coniferous, native prairie grasslands and forage crops. In a catchment with highly diversified land cover, canopy architecture cannot be overlooked in rainfall interception parameterization. Preliminary testing of ACRU suggests that streamflows were sensitive to varied levels of leaf area index (LAI), a representative fraction of canopy foliage. Further testing using remotely sensed LAI's will provide a more accurate representation of canopy foliage and ultimately best represent this important element of the hydrological cycle and the associated processes which govern the natural hydrology of the Beaver Creek watershed.

How does forest disturbance and succession affect summer streamflow recession?

NASA Astrophysics Data System (ADS)

Brena, A.; Stahl, K.; Weiler, M.

2011-12-01

Streamflow recession is a main signature of catchment behavior during dry conditions. The storage-discharge relationship of every catchment reflects the aquifer properties and land surface processes including evapotranspiration rates. Commonly, the storage-discharge relationship in watersheds is analyzed through the recession limb of the hydrograph, which generally follows a nonlinear pattern. It is, however, unknown how forest disturbance and succession may modify the degree of nonlinearity of baseflow recession and the magnitude of baseflow. The presented study analyzes and characterizes streamflow recession during summer before and after forest disturbance using data from six experimental paired-watersheds with controlled forest disturbances across different climatic regions and ecozones of the USA. Characteristic non-linear recession parameters were fitted by a Monte Carlo resampling method. No systematic relationship was found between annual precipitation, drainage area, mean elevation, and recession characteristics. However, higher storage rates and low flows across the sites were detected following forest disturbance. Exceptions are the snow-dominated watersheds and changes appear to be stronger in watersheds with deciduous forests. The results are however dependent on the method of recession limb selection, including start level and time. Further research is needed over a wide range of forest sites and according to the type of disturbance (e.g. fire, disease), which may ultimately define the dynamics of forest succession and therefore the streamflow recession behavior.

Implementation of remote sensing data for flood forecasting

NASA Astrophysics Data System (ADS)

Grimaldi, S.; Li, Y.; Pauwels, V. R. N.; Walker, J. P.; Wright, A. J.

2016-12-01

Flooding is one of the most frequent and destructive natural disasters. A timely, accurate and reliable flood forecast can provide vital information for flood preparedness, warning delivery, and emergency response. An operational flood forecasting system typically consists of a hydrologic model, which simulates runoff generation and concentration, and a hydraulic model, which models riverine flood wave routing and floodplain inundation. However, these two types of models suffer from various sources of uncertainties, e.g., forcing data initial conditions, model structure and parameters. To reduce those uncertainties, current forecasting systems are typically calibrated and/or updated using streamflow measurements, and such applications are limited in well-gauged areas. The recent increasing availability of spatially distributed Remote Sensing (RS) data offers new opportunities for flood events investigation and forecast. Based on an Australian case study, this presentation will discuss the use 1) of RS soil moisture data to constrain a hydrologic model, and 2) of RS-derived flood extent and level to constrain a hydraulic model. The hydrological model is based on a semi-distributed system coupled with a two-soil-layer rainfall-runoff model GRKAL and a linear Muskingum routing model. Model calibration was performed using either 1) streamflow data only or 2) both streamflow and RS soil moisture data. The model was then further constrained through the integration of real-time soil moisture data. The hydraulic model is based on LISFLOOD-FP which solves the 2D inertial approximation of the Shallow Water Equations. Streamflow data and RS-derived flood extent and levels were used to apply a multi-objective calibration protocol. The effectiveness with which each data source or combination of data sources constrained the parameter space was quantified and discussed.

The influence of climate, topography and land-use on the hydrology of ephemeral upland catchments

NASA Astrophysics Data System (ADS)

Daly, E.; Webb, J.; Dresel, E.

2016-12-01

We report on an on-going project aimed at determining the effects of climate variability and land use change on water resources in ephemeral productive catchments. Meteorological data (including rainfall, solar radiation, air temperature, humidity and wind speed), streamflow and groundwater levels were collected continuously for over five years in seven ephemeral catchments in southeastern Australia. The catchments, dominated by either pasture for grazing (four) or Eucalyptus globulus (blue gum) plantations of different ages (three), were located in three different geological settings. Rainfall varied from higher than the long-term average of this area for the initial years of the study period to much drier than the long-term average for the last two years. Groundwater levels in the farm sites remained stable or slightly increased through the study period, while levels declined in all the plantation catchments, where evapotranspiration rates were greater than rainfall. The trees intercept groundwater recharge and in some areas of the catchments directly access groundwater. Streamflow occurred mainly during winter, with short-term flows in summer caused by sporadic large rainfall events. Despite the large annual rainfall variability, flow rates in each year were similar in most catchments, with the duration of flow being important in determining the annual flow. The frequency rather than the amount of rainfall events determines the generation of streamflow in the two catchments with steeper slopes. The effect of the tree plantations on streamflow varied from a substantial reduction in one catchment to no effect in another, where the tree rows are oriented predominantly downslope, allowing greater runoff. In the third plantation catchment, geology is the main driver of runoff due to capture into underlying karst conduits.

Assessment of SWE data assimilation for ensemble streamflow predictions

NASA Astrophysics Data System (ADS)

Franz, Kristie J.; Hogue, Terri S.; Barik, Muhammad; He, Minxue

2014-11-01

An assessment of data assimilation (DA) for Ensemble Streamflow Prediction (ESP) using seasonal water supply hindcasting in the North Fork of the American River Basin (NFARB) and the National Weather Service (NWS) hydrologic forecast models is undertaken. Two parameter sets, one from the California Nevada River Forecast Center (RFC) and one from the Differential Evolution Adaptive Metropolis (DREAM) algorithm, are tested. For each parameter set, hindcasts are generated using initial conditions derived with and without the inclusion of a DA scheme that integrates snow water equivalent (SWE) observations. The DREAM-DA scenario uses an Integrated Uncertainty and Ensemble-based data Assimilation (ICEA) framework that also considers model and parameter uncertainty. Hindcasts are evaluated using deterministic and probabilistic forecast verification metrics. In general, the impact of DA on the skill of the seasonal water supply predictions is mixed. For deterministic (ensemble mean) predictions, the Percent Bias (PBias) is improved with integration of the DA. DREAM-DA and the RFC-DA have the lowest biases and the RFC-DA has the lowest Root Mean Squared Error (RMSE). However, the RFC and DREAM-DA have similar RMSE scores. For the probabilistic predictions, the RFC and DREAM have the highest Continuous Ranked Probability Skill Scores (CRPSS) and the RFC has the best discrimination for low flows. Reliability results are similar between the non-DA and DA tests and the DREAM and DREAM-DA have better reliability than the RFC and RFC-DA for forecast dates February 1 and later. Despite producing improved streamflow simulations in previous studies, the hindcast analysis suggests that the DA method tested may not result in obvious improvements in streamflow forecasts. We advocate that integration of hindcasting and probabilistic metrics provides more rigorous insight on model performance for forecasting applications, such as in this study.

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.

Methods for estimating drought streamflow probabilities for Virginia streams

USGS Publications Warehouse

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.

Adjusting Wavelet-based Multiresolution Analysis Boundary Conditions for Robust Long-term Streamflow Forecasting Model

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.

Reduction of forecast uncertainty in the context of hydropower production: a case study for two catchment in Lac-St-Jean, Canada

NASA Astrophysics Data System (ADS)

Brisson, Cathy; Boucher, Marie-Amélie; Latraverse, Marco

2014-05-01

This research focuses on the improvement of streamflow forecasts for two subcatchments in the Lac-St-Jean area, a northern part of the province of Quebec in Canada. Those two subcatchments, named Manouane and Passes-Dangereuses, are part of a bigger system, which comprises many reservoirs and six hydropower plants. This system is managed by Rio Tinto Alcan, an aluminium producer who needs this energy for its processes. Optimal management of the hydropower plants highly depends on the reliability of the inflow forecasts to the reservoirs and also on the reliability of observed streamflow. The latter are not directly measured, but rather deduced from the computation of a water balance. This water balance includes streamflow computation based on rating curves for river sections and upstream reservoirs and a modelling process using CEQUEAU hydrological model (Morin et al., 1981). In addition, mostly during the winter, the model has to account for a transfer of water from Lac Manouane reservoir to Passes-Dangereuses through Bonnard channel. Winter flow though Bonnard channel is controlled by a spillway, and represented in CEQUEAU by a transfer function and a fixed time delay (2 days). However, it is suspected that the evacuation function, as it is currently computed, is inaccurate. The main objective of this work is to reduce predictive uncertainty for Lac Manouane and Passes-Dangereuses catchment, for the one-day ahead horizon. This objective is twofold. First, the uncertainty related to the parameterization of the hydrological model had never been evaluated. It was to be investigated whether it is better to spatialize the calibration of the hydrological model. In its actual form, the calibration of the hydrological model CEQUEAU (Morin et al., 1981) is based exclusively on the downstream outflow. There is, however, intermediate streamflow measurements data available for an intermediate location. Our study shows that calibrating the model using streamflows for both locations (intermediate location and downstream) leads to improved forecasts, as measured by the Nash-Sutcliffe efficiency criterion. The parameter sets thus determined best represent the phenomena of exchange and runoff in the watershed. Second, this study aims at reducing the uncertainty associated to the evacuation function for the Bonnard channel as well as the time delay related to this transfer. Instead of using a fixed 2-day time delay for the transfer, it was attempted to represent the channel in the hydrological model CEQUEAU and compute the time delay from this model. The results show that hydrological modelling does not improve the results and that the 2-day time delay is adequate, especially for first days of opening and few days after closure of the gate. In addition, this research shows that the evacuation function of Bonnard spillway is inexact for large streamflows. It is considered the main source of uncertainty for the prediction of inflows to the reservoirs. We also show that the evacuated streamflows can be successfully corrected by hydrological modelling. This case study shows that a careful revision of the inflow forecasting process for those important watersheds can help reduce predictive uncertainty. Although the application is specific to the Lac-St-Jean area, we believe that our experience could serve other users and water managers with similar issues regarding inflow uncertainty. Reference Morin, G., J.-P. Fortin, J.-P. Lardeau, W. Sochanska and S. Paquette. 1981. Modèle CEQUEAU : Manuel d'utilisation. Rapport de recherche no R-93, INRS-Eau, Sainte-Foy

Streamflow Simulations and Percolation Estimates Using the Soil and Water Assessment Tool for Selected Basins in North-Central Nebraska, 1940-2005

USGS Publications Warehouse

Strauch, Kellan R.; Linard, Joshua I.

2009-01-01

The U.S. Geological Survey, in cooperation with the Upper Elkhorn, Lower Elkhorn, Upper Loup, Lower Loup, Middle Niobrara, Lower Niobrara, Lewis and Clark, and Lower Platte North Natural Resources Districts, used the Soil and Water Assessment Tool to simulate streamflow and estimate percolation in north-central Nebraska to aid development of long-term strategies for management of hydrologically connected ground and surface water. Although groundwater models adequately simulate subsurface hydrologic processes, they often are not designed to simulate the hydrologically complex processes occurring at or near the land surface. The use of watershed models such as the Soil and Water Assessment Tool, which are designed specifically to simulate surface and near-subsurface processes, can provide helpful insight into the effects of surface-water hydrology on the groundwater system. The Soil and Water Assessment Tool was calibrated for five stream basins in the Elkhorn-Loup Groundwater Model study area in north-central Nebraska to obtain spatially variable estimates of percolation. Six watershed models were calibrated to recorded streamflow in each subbasin by modifying the adjustment parameters. The calibrated parameter sets were then used to simulate a validation period; the validation period was half of the total streamflow period of record with a minimum requirement of 10 years. If the statistical and water-balance results for the validation period were similar to those for the calibration period, a model was considered satisfactory. Statistical measures of each watershed model's performance were variable. These objective measures included the Nash-Sutcliffe measure of efficiency, the ratio of the root-mean-square error to the standard deviation of the measured data, and an estimate of bias. The model met performance criteria for the bias statistic, but failed to meet statistical adequacy criteria for the other two performance measures when evaluated at a monthly time step. A primary cause of the poor model validation results was the inability of the model to reproduce the sustained base flow and streamflow response to precipitation that was observed in the Sand Hills region. The watershed models also were evaluated based on how well they conformed to the annual mass balance (precipitation equals the sum of evapotranspiration, streamflow/runoff, and deep percolation). The model was able to adequately simulate annual values of evapotranspiration, runoff, and precipitation in comparison to reported values, which indicates the model may provide reasonable estimates of annual percolation. Mean annual percolation estimated by the model as basin averages varied within the study area from a maximum of 12.9 inches in the Loup River Basin to a minimum of 1.5 inches in the Shell Creek Basin. Percolation also varied within the studied basins; basin headwaters tended to have greater percolation rates than downstream areas. This variance in percolation rates was mainly was because of the predominance of sandy, highly permeable soils in the upstream areas of the modeled basins.

Marginal Economic Value of Streamflow: A Case Study for the Colorado River Basin

NASA Astrophysics Data System (ADS)

Brown, Thomas C.; Harding, Benjamin L.; Payton, Elizabeth A.

1990-12-01

The marginal economic value of streamflow leaving forested areas in the Colorado River Basin was estimated by determining the impact on water use of a small change in streamflow and then applying economic value estimates to the water use changes. The effect on water use of a change in streamflow was estimated with a network flow model that simulated salinity levels and the routing of flow to consumptive uses and hydroelectric dams throughout the Basin. The results show that, under current water management institutions, the marginal value of streamflow in the Colorado River Basin is largely determined by nonconsumptive water uses, principally energy production, rather than by consumptive agricultural or municipal uses. The analysis demonstrates the importance of a systems framework in estimating the marginal value of streamflow.

Determination of streamflow of the Arkansas River near Bentley in south-central Kansas

USGS Publications Warehouse

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.

Season-ahead streamflow forecast informed tax strategies for semi-arid water rights markets

NASA Astrophysics Data System (ADS)

Delorit, J. D.; Block, P. J.

2016-12-01

In many semi-arid regions multisectoral demands stress available water supplies. The Elqui River valley of north central Chile, which draws on limited capacity reservoirs supplied largely by annually variable snowmelt, is one of these cases. This variability forces water managers to develop demand-based allocation strategies which have typically resulted in water right volume reductions, applied equally per right. Compounding this issue is often deferred or delayed infrastructure investments, which has been linked Chile's Coasian approach to water markets, under which rights holders do not pay direct procurement costs, non-use fees, nor taxes. Here we build upon our previous research using forecasts of likely water rights reductions, informed by season-ahead prediction models of October-January (austral growing season) streamflow, to construct annual, forecast-sensitive, per right tax. We believe this tax, to be borne by right holders, will improve the beneficial use of water resources by stimulating water rights trading and improving system efficiency by generating funds for infrastructure investment, thereby reducing free-ridership and conflict between rights holders. Research outputs will include sectoral per right tax assessments, tax revenue generation, Elqui River valley economic output, and water rights trading activity.

Estimated flow-duration curves for selected ungaged sites in Kansas

USGS Publications Warehouse

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.

Cool-Season Moisture Delivery and Multi-Basin Streamflow Anomalies in the Western United States

NASA Astrophysics Data System (ADS)

Malevich, Steven B.

Widespread droughts can have a significant impact on western United States streamflow, but the causes of these events are not fully understood. This dissertation examines streamflow from multiple western US basins and establishes the robust, leading modes of variability in interannual streamflow throughout the past century. I show that approximately 50% of this variability is associated with spatially widespread streamflow anomalies that are statistically independent from streamflow's response to the El Nino-Southern Oscillation (ENSO). The ENSO-teleconnection accounts for approximately 25% of the interannual variability in streamflow, across this network. These atmospheric circulation anomalies associated with the most spatially widespread variability are associated with the Aleutian low and the persistent coastal atmospheric ridge in the Pacific Northwest. I use a watershed segmentation algorithm to explicitly track the position and intensity of these features and compare their variability to the multi-basin streamflow variability. Results show that latitudinal shifts in the coastal atmospheric ridge are more strongly associated with streamflow's north-south dipole response to ENSO variability while more spatially widespread anomalies in streamflow most strongly relate to seasonal changes in the coastal ridge intensity. This likely reflects persistent coastal ridge blocking of cool-season precipitation into western US river basins. I utilize the 35 model runs of the Community Earth System Model Large Ensemble (CESMLE) to determine whether the model ensemble simulates the anomalously strong coastal ridges and extreme widespread wintertime precipitation anomalies found in the observation record. Though there is considerable bias in the CESMLE, the CESMLE runs simulate extremely widespread dry precipitation anomalies with a frequency of approximately one extreme event per century during the historical simulations (1920 - 2005). These extremely widespread dry events correspond significantly with anomalously intense coastal atmospheric ridges. The results from these three papers connect widespread interannual streamflow anomalies in the western US--and especially extremely widespread streamflow droughts--with semi-permanent atmospheric ridge anomalies near the coastal Pacific Northwest. This is important to western US water managers because these widespread events appear to have been a robust feature of the past century. The semi-permanent atmospheric features associated with these widespread dry streamflow anomalies are projected to change position significantly in the next century as a response to global climate change. This may change widespread streamflow anomaly characteristic in the western US, though my results do not show evidence of these changes within the instrument record of last century.

Remediation scenarios for attenuating peak flows and reducing sediment transport in Fountain Creek, Colorado, 2013

USGS Publications Warehouse

Kohn, Michael S.; Fulton, John W.; Williams, Cory A.; Stogner, Sr., Robert W.

2014-01-01

The U.S. Geological Survey (USGS) in cooperation with the Fountain Creek Watershed, Flood Control and Greenway District assessed remediation scenarios to attenuate peak flows and reduce sediment loads in the Fountain Creek watershed. To evaluate these strategies, the U.S. Army Corps of Engineers Hydrologic Engineering Center (HEC) hydrologic and hydraulic models were employed. The U.S. Army Corps of Engineers modeling system HEC-HMS (Hydrologic Modeling System) version 3.5 was used to simulate runoff in the Fountain Creek watershed, Colorado, associated with storms of varying magnitude and duration. Rain-gage precipitation data and radar-based precipitation data from the April 28–30, 1999, and September 14–15, 2011, storm events were used in the calibration process for the HEC-HMS model. The curve number and lag time for each subwatershed and Manning's roughness coefficients for each channel reach were adjusted within an acceptable range so that the simulated and measured streamflow hydrographs for each of the 12 USGS streamgages approximated each other. The U.S. Army Corps of Engineers modeling system HEC-RAS (River Analysis System) versions 4.1 and 4.2 were used to simulate streamflow and sediment transport, respectively, for the Fountain Creek watershed generated by a particular storm event. Data from 15 USGS streamgages were used for model calibration and 7 of those USGS streamgages were used for model validation. The calibration process consisted of comparing the simulated water-surface elevations and the cross-section-averaged velocities from the model with those surveyed in the field at the cross section at the corresponding 15 and 7 streamgages, respectively. The final Manning’s roughness coefficients were adjusted between –30 and 30 percent at the 15 calibration streamgages from the original left, right, and channel-averaged Manning's roughness coefficients upon completion of calibration. The U.S. Army Corps of Engineers modeling system HEC-RAS version 4.2 was used to simulate streamflow and sediment transport for the Fountain Creek watershed generated by a design-storm event. The Laursen-Copeland sediment-transport function was used in conjunction with the Exner 5 sorting method and the Ruby fall-velocity method to predict sediment transport. Six USGS streamgages equipped with suspended-sediment samplers were used to develop sediment-flow rating curves for the sediment-transport-model calibration. The critical Shields number in the Laursen-Copeland sediment-transport function and the volume of sediment available at a given cross section were adjusted during the HEC-RAS sediment-model calibration process. HEC-RAS model simulations used to evaluate the 14 remediation scenarios were based on unsteady-state streamflows associated with a 24-hour, 1-percent annual exceedance probability (100-year) National Oceanic and Atmospheric Administration Type II precipitation event. Scenario 0 represents the baseline or current conditions in the watershed and was used to compare the remaining 13 scenarios. Scenarios 1–8 and 12 rely on side-detention facilities to reduce peak flows and sediment transport. Scenario 9 has a diversion channel, and scenario 10 has a reservoir. Scenarios 11 and 13 incorporate channel armoring and channel widening, respectively. Scenarios 8 and 10, the scenario with the most side-detention facilities, and the scenario with the reservoir, respectively, were the most effective at reducing sediment transport and peak flow at the Pueblo, Colorado, streamgage. Scenarios 8 and 10 altered the peak flow by –58.9 and –56.4 percent, respectively. In turn, scenarios 8 and 10 altered the sediment transport by –17.7 and –62.1 percent, respectively.

Updated techniques for estimating monthly streamflow-duration characteristics at ungaged and partial-record sites in central Nevada

USGS Publications Warehouse

Hess, Glen W.

2002-01-01

Techniques for estimating monthly streamflow-duration characteristics at ungaged and partial-record sites in central Nevada have been updated. These techniques were developed using streamflow records at six continuous-record sites, basin physical and climatic characteristics, and concurrent streamflow measurements at four partial-record sites. Two methods, the basin-characteristic method and the concurrent-measurement method, were developed to provide estimating techniques for selected streamflow characteristics at ungaged and partial-record sites in central Nevada. In the first method, logarithmic-regression analyses were used to relate monthly mean streamflows (from all months and by month) from continuous-record gaging sites of various percent exceedence levels or monthly mean streamflows (by month) to selected basin physical and climatic variables at ungaged sites. Analyses indicate that the total drainage area and percent of drainage area at altitudes greater than 10,000 feet are the most significant variables. For the equations developed from all months of monthly mean streamflow, the coefficient of determination averaged 0.84 and the standard error of estimate of the relations for the ungaged sites averaged 72 percent. For the equations derived from monthly means by month, the coefficient of determination averaged 0.72 and the standard error of estimate of the relations averaged 78 percent. If standard errors are compared, the relations developed in this study appear generally to be less accurate than those developed in a previous study. However, the new relations are based on additional data and the slight increase in error may be due to the wider range of streamflow for a longer period of record, 1995-2000. In the second method, streamflow measurements at partial-record sites were correlated with concurrent streamflows at nearby gaged sites by the use of linear-regression techniques. Statistical measures of results using the second method typically indicated greater accuracy than for the first method. However, to make estimates for individual months, the concurrent-measurement method requires several years additional streamflow data at more partial-record sites. Thus, exceedence values for individual months are not yet available due to the low number of concurrent-streamflow-measurement data available. Reliability, limitations, and applications of both estimating methods are described herein.

Marginal economic value of streamflow: A case study for the Colorado River Basin

Treesearch

Thomas C. Brown; Benjamin L. Harding; Elizabeth A. Payton

1990-01-01

The marginal economic value of streamflow leaving forested areas in the Colorado River Basin was estimated by determining the impact on water use of a small change in streamflow and then applying economic value estimates to the water use changes. The effect on water use of a change in streamflow was estimated with a network flow model that simulated salinity levels and...

Assessing the impacts of climate and land use and land cover change on the freshwater availability in the Brahmaputra River basin

USGS Publications Warehouse

Pervez, Md Shahriar; Henebry, Geoffrey M.

2015-01-01

New hydrological insights for the region: Basin average annual ET was found to be sensitive to changes in CO2 concentration and temperature, while total water yield, streamflow, and groundwater recharge were sensitive to changes in precipitation. The basin hydrological components were predicted to increase with seasonal variability in response to climate and land use change scenarios. Strong increasing trends were predicted for total water yield, streamflow, and groundwater recharge, indicating exacerbation of flooding potential during August–October, but strong decreasing trends were predicted, indicating exacerbation of drought potential during May–July of the 21st century. The model has potential to facilitate strategic decision making through scenario generation integrating climate change adaptation and hazard mitigation policies to ensure optimized allocation of water resources under a variable and changing climate.

Bootstrap position analysis for forecasting low flow frequency

USGS Publications Warehouse

Tasker, Gary D.; Dunne, P.

1997-01-01

A method of random resampling of residuals from stochastic models is used to generate a large number of 12-month-long traces of natural monthly runoff to be used in a position analysis model for a water-supply storage and delivery system. Position analysis uses the traces to forecast the likelihood of specified outcomes such as reservoir levels falling below a specified level or streamflows falling below statutory passing flows conditioned on the current reservoir levels and streamflows. The advantages of this resampling scheme, called bootstrap position analysis, are that it does not rely on the unverifiable assumption of normality, fewer parameters need to be estimated directly from the data, and accounting for parameter uncertainty is easily done. For a given set of operating rules and water-use requirements for a system, water managers can use such a model as a decision-making tool to evaluate different operating rules. ?? ASCE,.

Updated streamflow reconstructions for the Upper Colorado River Basin

USGS Publications Warehouse

Woodhouse, Connie A.; Gray, Stephen T.; Meko, David M.

2006-01-01

Updated proxy reconstructions of water year (October–September) streamflow for four key gauges in the Upper Colorado River Basin were generated using an expanded tree ring network and longer calibration records than in previous efforts. Reconstructed gauges include the Green River at Green River, Utah; Colorado near Cisco, Utah; San Juan near Bluff, Utah; and Colorado at Lees Ferry, Arizona. The reconstructions explain 72–81% of the variance in the gauge records, and results are robust across several reconstruction approaches. Time series plots as well as results of cross‐spectral analysis indicate strong spatial coherence in runoff variations across the subbasins. The Lees Ferry reconstruction suggests a higher long‐term mean than previous reconstructions but strongly supports earlier findings that Colorado River allocations were based on one of the wettest periods in the past 5 centuries and that droughts more severe than any 20th to 21st century event occurred in the past.

Updated streamflow reconstructions for the Upper Colorado River Basin

NASA Astrophysics Data System (ADS)

Woodhouse, Connie A.; Gray, Stephen T.; Meko, David M.

2006-05-01

Updated proxy reconstructions of water year (October-September) streamflow for four key gauges in the Upper Colorado River Basin were generated using an expanded tree ring network and longer calibration records than in previous efforts. Reconstructed gauges include the Green River at Green River, Utah; Colorado near Cisco, Utah; San Juan near Bluff, Utah; and Colorado at Lees Ferry, Arizona. The reconstructions explain 72-81% of the variance in the gauge records, and results are robust across several reconstruction approaches. Time series plots as well as results of cross-spectral analysis indicate strong spatial coherence in runoff variations across the subbasins. The Lees Ferry reconstruction suggests a higher long-term mean than previous reconstructions but strongly supports earlier findings that Colorado River allocations were based on one of the wettest periods in the past 5 centuries and that droughts more severe than any 20th to 21st century event occurred in the past.

Temporal and spatial changes of rainfall and streamflow in the Upper Tekezē-Atbara river basin, Ethiopia

NASA Astrophysics Data System (ADS)

Gebremicael, Tesfay G.; Mohamed, Yasir A.; Zaag, Pieter v.; Hagos, Eyasu Y.

2017-04-01

The Upper Tekezē-Atbara river sub-basin, part of the Nile Basin, is characterized by high temporal and spatial variability of rainfall and streamflow. In spite of its importance for sustainable water use and food security, the changing patterns of streamflow and its association with climate change is not well understood. This study aims to improve the understanding of the linkages between rainfall and streamflow trends and identify possible drivers of streamflow variabilities in the basin. Trend analyses and change-point detections of rainfall and streamflow were analysed using Mann-Kendall and Pettitt tests, respectively, using data records for 21 rainfall and 9 streamflow stations. The nature of changes and linkages between rainfall and streamflow were carefully examined for monthly, seasonal and annual flows, as well as indicators of hydrologic alteration (IHA). The trend and change-point analyses found that 19 of the tested 21 rainfall stations did not show statistically significant changes. In contrast, trend analyses on the streamflow showed both significant increasing and decreasing patterns. A decreasing trend in the dry season (October to February), short season (March to May), main rainy season (June to September) and annual totals is dominant in six out of the nine stations. Only one out of nine gauging stations experienced significant increasing flow in the dry and short rainy seasons, attributed to the construction of Tekezē hydropower dam upstream this station in 2009. Overall, streamflow trends and change-point timings were found to be inconsistent among the stations. Changes in streamflow without significant change in rainfall suggests factors other than rainfall drive the change. Most likely the observed changes in streamflow regimes could be due to changes in catchment characteristics of the basin. Further studies are needed to verify and quantify the hydrological changes shown in statistical tests by identifying the physical mechanisms behind those changes. The findings from this study are useful as a prerequisite for studying the effects of catchment management dynamics on the hydrological variabilities in the basin.

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.

Compilation of streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages

USGS Publications Warehouse

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.

Scale effects on information theory-based measures applied to streamflow patterns in two rural watersheds

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.

Interactive effects of water diversion and climate change for juvenile chinook salmon in the lemhi river basin (USA.).

PubMed

Walters, Annika W; Bartz, Krista K; McClure, Michelle M

2013-12-01

The combined effects of water diversion and climate change are a major conservation challenge for freshwater ecosystems. In the Lemhi Basin, Idaho (U.S.A.), water diversion causes changes in streamflow, and climate change will further affect streamflow and temperature. Shifts in streamflow and temperature regimes can affect juvenile salmon growth, movement, and survival. We examined the potential effects of water diversion and climate change on juvenile Chinook salmon (Oncorhynchus tshawytscha), a species listed as threatened under the U.S. Endangered Species Act (ESA). To examine the effects for juvenile survival, we created a model relating 19 years of juvenile survival data to streamflow and temperature and found spring streamflow and summer temperature were good predictors of juvenile survival. We used these models to project juvenile survival for 15 diversion and climate-change scenarios. Projected survival was 42-58% lower when streamflows were diverted than when streamflows were undiverted. For diverted streamflows, 2040 climate-change scenarios (ECHO-G and CGCM3.1 T47) resulted in an additional 11-39% decrease in survival. We also created models relating habitat carrying capacity to streamflow and made projections for diversion and climate-change scenarios. Habitat carrying capacity estimated for diverted streamflows was 17-58% lower than for undiverted streamflows. Climate-change scenarios resulted in additional decreases in carrying capacity for the dry (ECHO-G) climate model. Our results indicate climate change will likely pose an additional stressor that should be considered when evaluating the effects of anthropogenic actions on salmon population status. Thus, this type of analysis will be especially important for evaluating effects of specific actions on a particular species. Efectos Interactivos de la Desviación del Agua y el Cambio Climático en Individuos Juveniles de Salmón Chinook en la Cuenca del Río Lemhi (E.U.A.). Conservation Biology © 2013 Society for Conservation Biology No claim to original US government works.

Glacial conditioning of stream position and flooding in the braid plain of the Exit Glacier foreland, Alaska

NASA Astrophysics Data System (ADS)

Curran, Janet H.; Loso, Michael G.; Williams, Haley B.

2017-09-01

Flow spilling out of an active braid plain often signals the onset of channel migration or avulsion to previously occupied areas. In a recently deglaciated environment, distinguishing between shifts in active braid plain location, considered reversible by fluvial processes at short timescales, and more permanent glacier-conditioned changes in stream position can be critical to understanding flood hazards. Between 2009 and 2014, increased spilling from the Exit Creek braid plain in Kenai Fjords National Park, Alaska, repeatedly overtopped the only access road to the popular Exit Glacier visitor facilities and trails. To understand the likely cause of road flooding, we consider recent processes and the interplay between glacier and fluvial system dynamics since the maximum advance of the Little Ice Age, around 1815. Patterns of temperature and precipitation, the variables that drive high streamflow via snowmelt, glacier meltwater runoff, and rainfall, could not fully explain the timing of road floods. Comparison of high-resolution topographic data between 2008 and 2012 showed a strong pattern of braid plain aggradation along 3 km of glacier foreland, not unexpected at the base of mountainous glaciers and likely an impetus for channel migration. Historically, a dynamic zone follows the retreating glacier in which channel positions shift rapidly in response to changes in the glacier margin and fresh morainal deposits. This period of paraglacial adjustment lasts one to several decades at Exit Glacier. Subsequently, as moraine breaches consolidate and lock the channel into position, and as the stream regains the lower-elevation valley center, upper-elevation surfaces are abandoned as terraces inaccessible by fluvial processes for timescales of decades to centuries. Where not constrained by these terraces and moraines, the channel is free to migrate, which in this aggradational setting generates an alluvial fan at the breach of the final prominent moraine. The position of this fan is glacially conditioned but the process of migration of the braided channels across it is not. This broad perspective on channel controls identifies incipient avulsion into the roadside forest as part of a long-term fan-building process independent from changes in streamflow or sediment load.

A Streamflow Statistics (StreamStats) Web Application for Ohio

USGS Publications Warehouse

Koltun, G.F.; Kula, Stephanie P.; Puskas, Barry M.

2006-01-01

A StreamStats Web application was developed for Ohio that implements equations for estimating a variety of streamflow statistics including the 2-, 5-, 10-, 25-, 50-, 100-, and 500-year peak streamflows, mean annual streamflow, mean monthly streamflows, harmonic mean streamflow, and 25th-, 50th-, and 75th-percentile streamflows. StreamStats is a Web-based geographic information system application designed to facilitate the estimation of streamflow statistics at ungaged locations on streams. StreamStats can also serve precomputed streamflow statistics determined from streamflow-gaging station data. The basic structure, use, and limitations of StreamStats are described in this report. To facilitate the level of automation required for Ohio's StreamStats application, the technique used by Koltun (2003)1 for computing main-channel slope was replaced with a new computationally robust technique. The new channel-slope characteristic, referred to as SL10-85, differed from the National Hydrography Data based channel slope values (SL) reported by Koltun (2003)1 by an average of -28.3 percent, with the median change being -13.2 percent. In spite of the differences, the two slope measures are strongly correlated. The change in channel slope values resulting from the change in computational method necessitated revision of the full-model equations for flood-peak discharges originally presented by Koltun (2003)1. Average standard errors of prediction for the revised full-model equations presented in this report increased by a small amount over those reported by Koltun (2003)1, with increases ranging from 0.7 to 0.9 percent. Mean percentage changes in the revised regression and weighted flood-frequency estimates relative to regression and weighted estimates reported by Koltun (2003)1 were small, ranging from -0.72 to -0.25 percent and -0.22 to 0.07 percent, respectively.

Streamflow statistics for unregulated and regulated conditions for selected locations on the Yellowstone, Tongue, and Powder Rivers, Montana, 1928-2002

USGS Publications Warehouse

Chase, Katherine J.

2013-01-01

Major floods in 1996 and 1997 on the Yellowstone River in Montana intensified public debate over the effects of human activities on the Yellowstone River. In 1999, the Yellowstone River Conservation District Council was formed to address conservation issues on the river. The Yellowstone River Conservation District Council partnered with the U.S. Army Corps of Engineers to conduct a cumulative-effects study on the main stem of the Yellowstone River. The cumulative-effects study is intended to provide a basis for future management decisions in the watershed. Streamflow statistics, such as flow-frequency and flow-duration data calculated for unregulated and regulated streamflow conditions, are a necessary component of the cumulative effects study. The U.S. Geological Survey, in cooperation with the Yellowstone River Conservation District Council and the U.S. Army Corps of Engineers, calculated streamflow statistics for unregulated and regulated conditions for the Yellowstone, Tongue, and Powder Rivers for the 1928–2002 study period. Unregulated streamflow represents flow conditions that might have occurred during the 1928–2002 study period if there had been no water-resources development in the Yellowstone River Basin. Regulated streamflow represents estimates of flow conditions during the 1928–2002 study period if the level of water-resources development existing in 2002 was in place during the entire study period. Peak-flow frequency estimates for regulated and unregulated streamflow were developed using methods described in Bulletin 17B. High-flow frequency and low-flow frequency data were developed for regulated and unregulated streamflows from the annual series of highest and lowest (respectively) mean flows for specified n-day consecutive periods within the calendar year. Flow-duration data, and monthly and annual streamflow characteristics, also were calculated for the unregulated and regulated streamflows.

Treating pre-instrumental data as "missing" data: using a tree-ring-based paleoclimate record and imputations to reconstruct streamflow in the Missouri River Basin

NASA Astrophysics Data System (ADS)

Ho, M. W.; Lall, U.; Cook, E. R.

2015-12-01

Advances in paleoclimatology in the past few decades have provided opportunities to expand the temporal perspective of the hydrological and climatological variability across the world. The North American region is particularly fortunate in this respect where a relatively dense network of high resolution paleoclimate proxy records have been assembled. One such network is the annually-resolved Living Blended Drought Atlas (LBDA): a paleoclimate reconstruction of the Palmer Drought Severity Index (PDSI) that covers North America on a 0.5° × 0.5° grid based on tree-ring chronologies. However, the use of the LBDA to assess North American streamflow variability requires a model by which streamflow may be reconstructed. Paleoclimate reconstructions have typically used models that first seek to quantify the relationship between the paleoclimate variable and the environmental variable of interest before extrapolating the relationship back in time. In contrast, the pre-instrumental streamflow is here considered as "missing" data. A method of imputing the "missing" streamflow data, prior to the instrumental record, is applied through multiple imputation using chained equations for streamflow in the Missouri River Basin. In this method, the distribution of the instrumental streamflow and LBDA is used to estimate sets of plausible values for the "missing" streamflow data resulting in a ~600 year-long streamflow reconstruction. Past research into external climate forcings, oceanic-atmospheric variability and its teleconnections, and assessments of rare multi-centennial instrumental records demonstrate that large temporal oscillations in hydrological conditions are unlikely to be captured in most instrumental records. The reconstruction of multi-centennial records of streamflow will enable comprehensive assessments of current and future water resource infrastructure and operations under the existing scope of natural climate variability.

Impacts of changes in climate and land use/land cover under IPCC RCP scenarios on streamflow in the Hoeya River Basin, Korea.

PubMed

Kim, Jinsoo; Choi, Jisun; Choi, Chuluong; Park, Soyoung

2013-05-01

This study examined the separate and combined impacts of future changes in climate and land use/land cover (LULC) on streamflow in the Hoeya River Basin, South Korea, using the representative concentration pathway (RCP) 4.5 and 8.5 scenarios of the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). First, a LULC change model was developed using RCP 4.5 and RCP 8.5 storylines and logistic regression. Three scenarios (climate change only, LULC change only, and climate and LULC change combined) were established, and the streamflow in future periods under these scenarios was simulated by the Soil and Water Assessment Tool (SWAT) model. Each scenario showed distinct seasonal variations in streamflow. Under climate change only, streamflow increased in spring and winter but decreased in summer and autumn, whereas LULC change increased high flow during wet periods but decreased low flow in dry periods. Although the LULC change had less effect than climate change on the changes in streamflow, the effect of LULC change on streamflow was significant. The result for the combined scenario was similar to that of the climate change only scenario, but with larger seasonal changes in streamflow. Although the effects of LULC change were smaller than those caused by climate change, LULC changes may heighten the problems of increased seasonal variability in streamflow caused by climate change. The results obtained in this study provide further insight into the availability of future streamflow and can aid in water resource management planning in the study area. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

Response of non-point source pollutant loads to climate change in the Shitoukoumen reservoir catchment.

PubMed

Zhang, Lei; Lu, Wenxi; An, Yonglei; Li, Di; Gong, Lei

2012-01-01

The impacts of climate change on streamflow and non-point source pollutant loads in the Shitoukoumen reservoir catchment are predicted by combining a general circulation model (HadCM3) with the Soil and Water Assessment Tool (SWAT) hydrological model. A statistical downscaling model was used to generate future local scenarios of meteorological variables such as temperature and precipitation. Then, the downscaled meteorological variables were used as input to the SWAT hydrological model calibrated and validated with observations, and the corresponding changes of future streamflow and non-point source pollutant loads in Shitoukoumen reservoir catchment were simulated and analyzed. Results show that daily temperature increases in three future periods (2010-2039, 2040-2069, and 2070-2099) relative to a baseline of 1961-1990, and the rate of increase is 0.63°C per decade. Annual precipitation also shows an apparent increase of 11 mm per decade. The calibration and validation results showed that the SWAT model was able to simulate well the streamflow and non-point source pollutant loads, with a coefficient of determination of 0.7 and a Nash-Sutcliffe efficiency of about 0.7 for both the calibration and validation periods. The future climate change has a significant impact on streamflow and non-point source pollutant loads. The annual streamflow shows a fluctuating upward trend from 2010 to 2099, with an increase rate of 1.1 m(3) s(-1) per decade, and a significant upward trend in summer, with an increase rate of 1.32 m(3) s(-1) per decade. The increase in summer contributes the most to the increase of annual load compared with other seasons. The annual NH (4) (+) -N load into Shitoukoumen reservoir shows a significant downward trend with a decrease rate of 40.6 t per decade. The annual TP load shows an insignificant increasing trend, and its change rate is 3.77 t per decade. The results of this analysis provide a scientific basis for effective support of decision makers and strategies of adaptation to climate change.

A multi-dimensional analysis of the upper Rio Grande-San Luis Valley social-ecological system

NASA Astrophysics Data System (ADS)

Mix, Ken

The Upper Rio Grande (URG), located in the San Luis Valley (SLV) of southern Colorado, is the primary contributor to streamflow to the Rio Grande Basin, upstream of the confluence of the Rio Conchos at Presidio, TX. The URG-SLV includes a complex irrigation-dependent agricultural social-ecological system (SES), which began development in 1852, and today generates more than 30% of the SLV revenue. The diversions of Rio Grande water for irrigation in the SLV have had a disproportionate impact on the downstream portion of the river. These diversions caused the flow to cease at Ciudad Juarez, Mexico in the late 1880s, creating international conflict. Similarly, low flows in New Mexico and Texas led to interstate conflict. Understanding changes in the URG-SLV that led to this event and the interactions among various drivers of change in the URG-SLV is a difficult task. One reason is that complex social-ecological systems are adaptive, contain feedbacks, emergent properties, cross-scale linkages, large-scale dynamics and non-linearities. Further, most analyses of SES to date have been qualitative, utilizing conceptual models to understand driver interactions. This study utilizes both qualitative and quantitative techniques to develop an innovative approach for analyzing driver interactions in the URG-SLV. Five drivers were identified for the URG-SLV social-ecological system: water (streamflow), water rights, climate, agriculture, and internal and external water policy. The drivers contained several longitudes (data aspect) relevant to the system, except water policy, for which only discreet events were present. Change point and statistical analyses were applied to the longitudes to identify quantifiable changes, to allow detection of cross-scale linkages between drivers, and presence of feedback cycles. Agricultural was identified as the driver signal. Change points for agricultural expansion defined four distinct periods: 1852--1923, 1924--1948, 1949--1978 and 1979--2007. Changes in streamflow, water allocations and water policy were observed in all agriculture periods. Cross-scale linkages were also evident between climate and streamflow; policy and water rights; and agriculture, groundwater pumping and streamflow.

Peak data for U.S. Geological Survey gaging stations, Texas network and computer program to estimate peak-streamflow frequency

USGS Publications Warehouse

Slade, R.M.; Asquith, W.H.

1996-01-01

About 23,000 annual peak streamflows and about 400 historical peak streamflows exist for about 950 stations in the surface-water data-collection network of Texas. These data are presented on a computer diskette along with the corresponding dates, gage heights, and information concerning the basin, and nature or cause for the flood. Also on the computer diskette is a U.S. Geological Survey computer program that estimates peak-streamflow frequency based on annual and historical peak streamflow. The program estimates peak streamflow for 2-, 5-, 10-, 25-, 50-, and 100-year recurrence intervals and is based on guidelines established by the Interagency Advisory Committee on Water Data. Explanations are presented for installing the program, and an example is presented with discussion of its options.

Variable Streamflow Contributions in Nested Subwatersheds of a US Midwestern Urban Watershed

DOE PAGES

Wei, Liang; Hubbart, Jason A.; Zhou, Hang

2017-09-09

Quantification of runoff is critical to estimate and control water pollution in urban regions, but variation in impervious area and land-use type can complicate the quantification of runoff. We quantified the streamflow contributions of subwatersheds and the historical changes in streamflow in a flood prone urbanizing watershed in US Midwest to guide the establishment of a future pollution-control plan. Streamflow data from five nested hydrological stations enabled accurate estimations of streamflow contribution from five subwatersheds with variable impervious areas (from 0.5% to 26.6%). We corrected the impact of Missouri river backwatering at the most downstream station by comparing its streamflowmore » with an upstream station using double-mass analysis combined with Bernaola-Galvan Heuristic Segmentation approach. We also compared the streamflow of the urbanizing watershed with seven surrounding rural watersheds to estimate the cumulative impact of urbanization on the streamflow regime. The two most urbanized subwatersheds contributed >365 mm streamflow in 2012 with 657 mm precipitation, which was more than fourfold greater than the two least urbanized subwatersheds. Runoff occurred almost exclusively over the most urbanized subwatersheds during the dry period. The frequent floods occurred and the same amount of precipitation produced ~100 mm more streamflow in 2008–2014 than 1967–1980 in the urbanizing watershed; such phenomena did not occur in surrounding rural watersheds. Our approaches provide comprehensive information for planning on runoff control and pollutant reduction in urban watersheds.« less

Improving Hydrological Simulations by Incorporating GRACE Data for Parameter Calibration

NASA Astrophysics Data System (ADS)

Bai, P.

2017-12-01

Hydrological model parameters are commonly calibrated by observed streamflow data. This calibration strategy is questioned when the modeled hydrological variables of interest are not limited to streamflow. Well-performed streamflow simulations do not guarantee the reliable reproduction of other hydrological variables. One of the reasons is that hydrological model parameters are not reasonably identified. The Gravity Recovery and Climate Experiment (GRACE) satellite-derived total water storage change (TWSC) data provide an opportunity to constrain hydrological model parameterizations in combination with streamflow observations. We constructed a multi-objective calibration scheme based on GRACE-derived TWSC and streamflow observations, with the aim of improving the parameterizations of hydrological models. The multi-objective calibration scheme was compared with the traditional single-objective calibration scheme, which is based only on streamflow observations. Two monthly hydrological models were employed on 22 Chinese catchments with different hydroclimatic conditions. The model evaluation was performed using observed streamflows, GRACE-derived TWSC, and evapotranspiraiton (ET) estimates from flux towers and from the water balance approach. Results showed that the multi-objective calibration provided more reliable TWSC and ET simulations without significant deterioration in the accuracy of streamflow simulations than the single-objective calibration. In addition, the improvements of TWSC and ET simulations were more significant in relatively dry catchments than in relatively wet catchments. This study highlights the importance of including additional constraints besides streamflow observations in the parameter estimation to improve the performances of hydrological models.

Variable Streamflow Contributions in Nested Subwatersheds of a US Midwestern Urban Watershed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Liang; Hubbart, Jason A.; Zhou, Hang

Quantification of runoff is critical to estimate and control water pollution in urban regions, but variation in impervious area and land-use type can complicate the quantification of runoff. We quantified the streamflow contributions of subwatersheds and the historical changes in streamflow in a flood prone urbanizing watershed in US Midwest to guide the establishment of a future pollution-control plan. Streamflow data from five nested hydrological stations enabled accurate estimations of streamflow contribution from five subwatersheds with variable impervious areas (from 0.5% to 26.6%). We corrected the impact of Missouri river backwatering at the most downstream station by comparing its streamflowmore » with an upstream station using double-mass analysis combined with Bernaola-Galvan Heuristic Segmentation approach. We also compared the streamflow of the urbanizing watershed with seven surrounding rural watersheds to estimate the cumulative impact of urbanization on the streamflow regime. The two most urbanized subwatersheds contributed >365 mm streamflow in 2012 with 657 mm precipitation, which was more than fourfold greater than the two least urbanized subwatersheds. Runoff occurred almost exclusively over the most urbanized subwatersheds during the dry period. The frequent floods occurred and the same amount of precipitation produced ~100 mm more streamflow in 2008–2014 than 1967–1980 in the urbanizing watershed; such phenomena did not occur in surrounding rural watersheds. Our approaches provide comprehensive information for planning on runoff control and pollutant reduction in urban watersheds.« less

Estimating predictive hydrological uncertainty by dressing deterministic and ensemble forecasts; a comparison, with application to Meuse and Rhine

NASA Astrophysics Data System (ADS)

Verkade, J. S.; Brown, J. D.; Davids, F.; Reggiani, P.; Weerts, A. H.

2017-12-01

Two statistical post-processing approaches for estimation of predictive hydrological uncertainty are compared: (i) 'dressing' of a deterministic forecast by adding a single, combined estimate of both hydrological and meteorological uncertainty and (ii) 'dressing' of an ensemble streamflow forecast by adding an estimate of hydrological uncertainty to each individual streamflow ensemble member. Both approaches aim to produce an estimate of the 'total uncertainty' that captures both the meteorological and hydrological uncertainties. They differ in the degree to which they make use of statistical post-processing techniques. In the 'lumped' approach, both sources of uncertainty are lumped by post-processing deterministic forecasts using their verifying observations. In the 'source-specific' approach, the meteorological uncertainties are estimated by an ensemble of weather forecasts. These ensemble members are routed through a hydrological model and a realization of the probability distribution of hydrological uncertainties (only) is then added to each ensemble member to arrive at an estimate of the total uncertainty. The techniques are applied to one location in the Meuse basin and three locations in the Rhine basin. Resulting forecasts are assessed for their reliability and sharpness, as well as compared in terms of multiple verification scores including the relative mean error, Brier Skill Score, Mean Continuous Ranked Probability Skill Score, Relative Operating Characteristic Score and Relative Economic Value. The dressed deterministic forecasts are generally more reliable than the dressed ensemble forecasts, but the latter are sharper. On balance, however, they show similar quality across a range of verification metrics, with the dressed ensembles coming out slightly better. Some additional analyses are suggested. Notably, these include statistical post-processing of the meteorological forecasts in order to increase their reliability, thus increasing the reliability of the streamflow forecasts produced with ensemble meteorological forcings.

Sociohydrological Impacts of Water Conservation Under Anthropogenic Drought in Austin, TX (USA)

NASA Astrophysics Data System (ADS)

Breyer, Betsy; Zipper, Samuel C.; Qiu, Jiangxiao

2018-04-01

Municipal water providers increasingly respond to drought by implementing outdoor water use restrictions to reduce urban water withdrawals and maintain water availability. However, restricting urban outdoor water use to support watershed-scale drought resilience may generate unanticipated cross-scale interactions, for example, by altering drought response and recovery in urban vegetation or urban streamflow. Despite this, urban water conservation is rarely conceptualized or modeled as endogenous to the water cycle. Here we investigate cross-scale interactions among urban water conservation and water availability, water use, and sociohydrological response in Austin, TX (USA) during a recent anthropogenic (human-influenced) drought. Multiscalar statistical analyses demonstrated that outdoor water conservation for reservoir management at the municipal scale produced responses that can cascade both "upward" from the city to the watershed (e.g., decoupling streamflow patterns upstream and downstream of Austin at the watershed scale) and "downward" to exert heterogeneous effects within the city (e.g., redistributing water along a socioeconomic gradient at submunicipal scales, with effects on terrestrial and aquatic ecosystems). We suggest that adapting to anthropogenic drought through irrigation curtailment requires sustained engagement between hydrology and social sciences to integrate socioeconomic status and political feedbacks within and among irrigator groups into the water cycle. Findings from this cross-disciplinary study highlight the importance of a multiscalar and spatially explicit perspectives in urban sociohydrology research to uncover how water conservation as adaptation to anthropogenic drought links hydrological processes with issues of socioeconomic inequality and spatiotemporal scale in the Anthropocene.

User's manual for SEDCALC, a computer program for computation of suspended-sediment discharge

USGS Publications Warehouse

Koltun, G.F.; Gray, John R.; McElhone, T.J.

1994-01-01

Sediment-Record Calculations (SEDCALC), a menu-driven set of interactive computer programs, was developed to facilitate computation of suspended-sediment records. The programs comprising SEDCALC were developed independently in several District offices of the U.S. Geological Survey (USGS) to minimize the intensive labor associated with various aspects of sediment-record computations. SEDCALC operates on suspended-sediment-concentration data stored in American Standard Code for Information Interchange (ASCII) files in a predefined card-image format. Program options within SEDCALC can be used to assist in creating and editing the card-image files, as well as to reformat card-image files to and from formats used by the USGS Water-Quality System. SEDCALC provides options for creating card-image files containing time series of equal-interval suspended-sediment concentrations from 1. digitized suspended-sediment-concentration traces, 2. linear interpolation between log-transformed instantaneous suspended-sediment-concentration data stored at unequal time intervals, and 3. nonlinear interpolation between log-transformed instantaneous suspended-sediment-concentration data stored at unequal time intervals. Suspended-sediment discharge can be computed from the streamflow and suspended-sediment-concentration data or by application of transport relations derived by regressing log-transformed instantaneous streamflows on log-transformed instantaneous suspended-sediment concentrations or discharges. The computed suspended-sediment discharge data are stored in card-image files that can be either directly imported to the USGS Automated Data Processing System or used to generate plots by means of other SEDCALC options.

Identification of the effective water availability from streamflows in the Zerafshan river basin, Central Asia

NASA Astrophysics Data System (ADS)

Olsson, Oliver; Gassmann, Matthias; Wegerich, Kai; Bauer, Melanie

2010-09-01

SummaryQuantitative estimates of the hydrologic effects of climate change are essential for understanding and solving potential transboundary water conflicts in the Zerafshan river basin, Central Asia. This paper introduces an identification of runoff generation processes and a detection of changes in hydrological regimes supporting Mann-Kendall trend analysis for streamflows. By this, the effective available and future water resources are identified for the Zerafshan. The results for the subbasins in the upper Zerafshan and for the reference station at the upper catchment outlet indicate that glacier melt is the most significant component of river runoff. The Mann-Kendall trend analysis confirms the regime analysis with the shift in the seasonality of the discharge. Furthermore, the results of the Kendall-Theil Robust Line for predicted long-term discharge trends show a decreasing annual discharge. The experience gained during this study emphasizes the fact that the summer flood, urgently required for the large irrigation projects downstream in Uzbekistan, is reduced and more water will be available in spring. Additionally, following the estimation of future discharges in 50 and 100 years the hydrological changes are affecting the seasonal water availability for irrigation. This analysis highlighted that water availability is decreasing and the timing of availability is changing. Hence, there will be more competition between upstream Tajikistan and downstream Uzbekistan. Planned projects within the basin might have to be reconsidered and the changed scenario of water availability needs to be properly taken into account for long-term basin scale water management.

Recent Improvements to the U.S. Geological Survey Streamgaging Program...from the National Streamflow Information Program

USGS Publications Warehouse

Blanchard, Stephen F.

2007-01-01

INTRODUCTION The U.S. Geological Survey (USGS) established its first streamgage in 1889 on the Rio Grande River at Embudo, N.M. As the need for streamflow information increased, the USGS streamgaging network expanded to its current (2007) size of approximately 7,400 streamgages nationwide. The USGS streamgaging network, for most of its history, required mechanical measuring and recording devices to collect station data. Time-consuming and labor-intensive site visits were required to gather the recorded data for processing in the office. Eventually the data were published in paper reports. The USGS has progressively improved the streamgaging program by incorporating new technologies and techniques that streamline data collection, data delivery, and records processing while increasing the number and quality of product types that can be derived from the data. Improvements in recent decades that have expanded and broadened the streamgaging program are included the fact sheet.

A Combined Atmospheric Rivers and Geopotential Height Analysis for the Detection of High Streamflow Event Probability Occurrence in UK and Germany

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.

Sensitivity and Uncertainty Analysis for Streamflow Prediction Using Different Objective Functions and Optimization Algorithms: San Joaquin California

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).

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.

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.