Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

NASA Technical Reports Server (NTRS)

Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.

2013-01-01

Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

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

Continuity vs. the Crowd-Tradeoffs Between Continuous and Intermittent Citizen Hydrology Streamflow Observations.

PubMed

Davids, Jeffrey C; van de Giesen, Nick; Rutten, Martine

2017-07-01

Hydrologic data has traditionally been collected with permanent installations of sophisticated and accurate but expensive monitoring equipment at limited numbers of sites. Consequently, observation frequency and costs are high, but spatial coverage of the data is limited. Citizen Hydrology can possibly overcome these challenges by leveraging easily scaled mobile technology and local residents to collect hydrologic data at many sites. However, understanding of how decreased observational frequency impacts the accuracy of key streamflow statistics such as minimum flow, maximum flow, and runoff is limited. To evaluate this impact, we randomly selected 50 active United States Geological Survey streamflow gauges in California. We used 7 years of historical 15-min flow data from 2008 to 2014 to develop minimum flow, maximum flow, and runoff values for each gauge. To mimic lower frequency Citizen Hydrology observations, we developed a bootstrap randomized subsampling with replacement procedure. We calculated the same statistics, and their respective distributions, from 50 subsample iterations with four different subsampling frequencies ranging from daily to monthly. Minimum flows were estimated within 10% for half of the subsample iterations at 39 (daily) and 23 (monthly) of the 50 sites. However, maximum flows were estimated within 10% at only 7 (daily) and 0 (monthly) sites. Runoff volumes were estimated within 10% for half of the iterations at 44 (daily) and 12 (monthly) sites. Watershed flashiness most strongly impacted accuracy of minimum flow, maximum flow, and runoff estimates from subsampled data. Depending on the questions being asked, lower frequency Citizen Hydrology observations can provide useful hydrologic information.

Estimated monthly streamflows for selected locations on the Kabul and Logar Rivers, Aynak copper, cobalt, and chromium area of interest, Afghanistan, 1951-2010

USGS Publications Warehouse

Vining, Kevin C.; Vecchia, Aldo V.

2014-01-01

The U.S. Geological Survey, in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, used the stochastic monthly water-balance model and existing climate data to estimate monthly streamflows for 1951–2010 for selected streamgaging stations located within the Aynak copper, cobalt, and chromium area of interest in Afghanistan. The model used physically based, nondeterministic methods to estimate the monthly volumetric water-balance components of a watershed. A comparison of estimated and recorded monthly streamflows for the streamgaging stations Kabul River at Maidan and Kabul River at Tangi-Saidan indicated that the stochastic water-balance model was able to provide satisfactory estimates of monthly streamflows for high-flow months and low-flow months even though withdrawals for irrigation likely occurred. A comparison of estimated and recorded monthly streamflows for the streamgaging stations Logar River at Shekhabad and Logar River at Sangi-Naweshta also indicated that the stochastic water-balance model was able to provide reasonable estimates of monthly streamflows for the high-flow months; however, for the upstream streamgaging station, the model overestimated monthly streamflows during periods when summer irrigation withdrawals likely occurred. Results from the stochastic water-balance model indicate that the model should be able to produce satisfactory estimates of monthly streamflows for locations along the Kabul and Logar Rivers. This information could be used by Afghanistan authorities to make decisions about surface-water resources for the Aynak copper, cobalt, and chromium area of interest.

Estimates of monthly streamflow characteristics at selected sites in the upper Missouri River basin, Montana, base period water years 1937-86

USGS Publications Warehouse

Parrett, Charles; Johnson, D.R.; Hull, J.A.

1989-01-01

Estimates of streamflow characteristics (monthly mean flow that is exceeded 90, 80, 50, and 20 percent of the time for all years of record and mean monthly flow) were made and are presented in tabular form for 312 sites in the Missouri River basin in Montana. Short-term gaged records were extended to the base period of water years 1937-86, and were used to estimate monthly streamflow characteristics at 100 sites. Data from 47 gaged sites were used in regression analysis relating the streamflow characteristics to basin characteristics and to active-channel width. The basin-characteristics equations, with standard errors of 35% to 97%, were used to estimate streamflow characteristics at 179 ungaged sites. The channel-width equations, with standard errors of 36% to 103%, were used to estimate characteristics at 138 ungaged sites. Streamflow measurements were correlated with concurrent streamflows at nearby gaged sites to estimate streamflow characteristics at 139 ungaged sites. In a test using 20 pairs of gages, the standard errors ranged from 31% to 111%. At 139 ungaged sites, the estimates from two or more of the methods were weighted and combined in accordance with the variance of individual methods. When estimates from three methods were combined the standard errors ranged from 24% to 63 %. A drainage-area-ratio adjustment method was used to estimate monthly streamflow characteristics at seven ungaged sites. The reliability of the drainage-area-ratio adjustment method was estimated to be about equal to that of the basin-characteristics method. The estimate were checked for reliability. Estimates of monthly streamflow characteristics from gaged records were considered to be most reliable, and estimates at sites with actual flow record from 1937-86 were considered to be completely reliable (zero error). Weighted-average estimates were considered to be the most reliable estimates made at ungaged sites. (USGS)

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

Water balance models in one-month-ahead streamflow forecasting

USGS Publications Warehouse

Alley, William M.

1985-01-01

Techniques are tested that incorporate information from water balance models in making 1-month-ahead streamflow forecasts in New Jersey. The results are compared to those based on simple autoregressive time series models. The relative performance of the models is dependent on the month of the year in question. The water balance models are most useful for forecasts of April and May flows. For the stations in northern New Jersey, the April and May forecasts were made in order of decreasing reliability using the water-balance-based approaches, using the historical monthly means, and using simple autoregressive models. The water balance models were useful to a lesser extent for forecasts during the fall months. For the rest of the year the improvements in forecasts over those obtained using the simpler autoregressive models were either very small or the simpler models provided better forecasts. When using the water balance models, monthly corrections for bias are found to improve minimum mean-square-error forecasts as well as to improve estimates of the forecast conditional distributions.

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.

Monthly streamflow forecasting at varying spatial scales in the Rhine basin

NASA Astrophysics Data System (ADS)

Schick, Simon; Rössler, Ole; Weingartner, Rolf

2018-02-01

Model output statistics (MOS) methods can be used to empirically relate an environmental variable of interest to predictions from earth system models (ESMs). This variable often belongs to a spatial scale not resolved by the ESM. Here, using the linear model fitted by least squares, we regress monthly mean streamflow of the Rhine River at Lobith and Basel against seasonal predictions of precipitation, surface air temperature, and runoff from the European Centre for Medium-Range Weather Forecasts. To address potential effects of a scale mismatch between the ESM's horizontal grid resolution and the hydrological application, the MOS method is further tested with an experiment conducted at the subcatchment scale. This experiment applies the MOS method to 133 additional gauging stations located within the Rhine basin and combines the forecasts from the subcatchments to predict streamflow at Lobith and Basel. In doing so, the MOS method is tested for catchments areas covering 4 orders of magnitude. Using data from the period 1981-2011, the results show that skill, with respect to climatology, is restricted on average to the first month ahead. This result holds for both the predictor combination that mimics the initial conditions and the predictor combinations that additionally include the dynamical seasonal predictions. The latter, however, reduce the mean absolute error of the former in the range of 5 to 12 %, which is consistently reproduced at the subcatchment scale. An additional experiment conducted for 5-day mean streamflow indicates that the dynamical predictions help to reduce uncertainties up to about 20 days ahead, but it also reveals some shortcomings of the present MOS method.

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.

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

Can Low Frequency Measurements Be Good Enough? - A Statistical Assessment of Citizen Hydrology Streamflow Observations

NASA Astrophysics Data System (ADS)

Davids, J. C.; Rutten, M.; Van De Giesen, N.

2016-12-01

Hydrologic data has traditionally been collected with permanent installations of sophisticated and relatively accurate but expensive monitoring equipment at limited numbers of sites. Consequently, the spatial coverage of the data is limited and costs are high. Achieving adequate maintenance of sophisticated monitoring equipment often exceeds local technical and resource capacity, and permanently deployed monitoring equipment is susceptible to vandalism, theft, and other hazards. Rather than using expensive, vulnerable installations at a few points, SmartPhones4Water (S4W), a form of Citizen Hydrology, leverages widely available mobile technology to gather hydrologic data at many sites in a manner that is repeatable and scalable. However, there is currently a limited understanding of the impact of decreased observational frequency on the accuracy of key streamflow statistics like minimum flow, maximum flow, and runoff. As a first step towards evaluating the tradeoffs between traditional continuous monitoring approaches and emerging Citizen Hydrology methods, we randomly selected 50 active U.S. Geological Survey (USGS) streamflow gauges in California. We used historical 15 minute flow data from 01/01/2008 through 12/31/2014 to develop minimum flow, maximum flow, and runoff values (7 year total) for each gauge. In order to mimic lower frequency Citizen Hydrology observations, we developed a bootstrap randomized subsampling with replacement procedure. We calculated the same statistics, along with their respective distributions, from 50 subsample iterations with four different subsampling intervals (i.e. daily, three day, weekly, and monthly). Based on our results we conclude that, depending on the types of questions being asked, and the watershed characteristics, Citizen Hydrology streamflow measurements can provide useful and accurate information. Depending on watershed characteristics, minimum flows were reasonably estimated with subsample intervals ranging from

Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models

NASA Astrophysics Data System (ADS)

Mazzoleni, Maurizio; Alfonso, Leonardo; Chacon-Hurtado, Juan; Solomatine, Dimitri

2015-09-01

Catastrophic floods cause significant socio-economical losses. Non-structural measures, such as real-time flood forecasting, can potentially reduce flood risk. To this end, data assimilation methods have been used to improve flood forecasts by integrating static ground observations, and in some cases also remote sensing observations, within water models. Current hydrologic and hydraulic research works consider assimilation of observations coming from traditional, static sensors. At the same time, low-cost, mobile sensors and mobile communication devices are becoming also increasingly available. The main goal and innovation of this study is to demonstrate the usefulness of assimilating uncertain streamflow observations that are dynamic in space and intermittent in time in the context of two different semi-distributed hydrological model structures. The developed method is applied to the Brue basin, where the dynamic observations are imitated by the synthetic observations of discharge. The results of this study show how model structures and sensors locations affect in different ways the assimilation of streamflow observations. In addition, it proves how assimilation of such uncertain observations from dynamic sensors can provide model improvements similar to those of streamflow observations coming from a non-optimal network of static physical sensors. This can be a potential application of recent efforts to build citizen observatories of water, which can make the citizens an active part in information capturing, evaluation and communication, helping simultaneously to improvement of model-based flood forecasting.

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

Summary of percentages of zero daily mean streamflow for 712 U.S. Geological Survey streamflow-gaging stations in Texas through 2003

USGS Publications Warehouse

Asquith, William H.; Vrabel, Joseph; Roussel, Meghan C.

2007-01-01

Analysts and managers of surface-water resources might have interest in the zero-flow potential for U.S.Geological Survey (USGS) streamflow-gaging stations in Texas. The USGS, in cooperation with the Texas Commission on Environmental Quality, initiated a data and reporting process to generate summaries of percentages of zero daily mean streamflow for 712 USGS streamflow-gaging stations in Texas. A summary of the percentages of zero daily mean streamflow for most active and inactive, continuous-record gaging stations in Texas provides valuable information by conveying the historical perspective for zero-flow potential for the watershed. The summaries of percentages of zero daily mean streamflow for each station are graphically depicted using two thematic perspectives: annual and monthly. The annual perspective consists of graphs of annual percentages of zero streamflow by year with the addition of lines depicting the mean and median annual percentage of zero streamflow. Monotonic trends in the percentages of zero streamflow also are identified using Kendall's T. The monthly perspective consists of graphs of the percentage of zero streamflow by month with lines added to indicate the mean and median monthly percentage of zero streamflow. One or more summaries could be used in a watershed, river basin, or other regional context by analysts and managers of surface-water resources to guide scientific, regulatory, or other inquiries of zero-flow or other low-flow conditions in Texas.

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.

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

Synthesis of monthly and annual streamflow records (water years 1950-2003) for Big Sandy, Clear, Peoples, and Beaver Creeks in the Milk River basin, Montana

USGS Publications Warehouse

Parrett, Charles

2006-01-01

To address concerns expressed by the State of Montana about the apportionment of water in the St. Mary and Milk River basins between Canada and the United States, the International Joint Commission requested information from the United States government about water that originates in the United States but does not cross the border into Canada. In response to this request, the U.S. Geological Survey synthesized monthly and annual streamflow records for Big Sandy, Clear, Peoples, and Beaver Creeks, all of which are in the Milk River basin in Montana, for water years 1950-2003. This report presents the synthesized values of monthly and annual streamflow for Big Sandy, Clear, Peoples, and Beaver Creeks in Montana. Synthesized values were derived from recorded and estimated streamflows. Statistics, including long-term medians and averages and flows for various exceedance probabilities, were computed from the synthesized data. Beaver Creek had the largest median annual discharge (19,490 acre-feet), and Clear Creek had the smallest median annual discharge (6,680 acre-feet). Big Sandy Creek, the stream with the largest drainage area, had the second smallest median annual discharge (9,640 acre-feet), whereas Peoples Creek, the stream with the second smallest drainage area, had the second largest median annual discharge (11,700 acre-feet). The combined median annual discharge for the four streams was 45,400 acre-feet. The largest combined median monthly discharge for the four creeks was 6,930 acre-feet in March, and the smallest combined median monthly discharge was 48 acre-feet in January. The combined median monthly values were substantially smaller than the average monthly values. Overall, synthesized flow records for the four creeks are considered to be reasonable given the prevailing climatic conditions in the region during the 1950-2003 base period. Individual estimates of monthly streamflow may have large errors, however. Linear regression was used to relate

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. 

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.

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.

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...

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.

Effect of year-to-year variability of leaf area index on variable infiltration capacity model performance and simulation of streamflow during drought

NASA Astrophysics Data System (ADS)

Tesemma, Z. K.; Wei, Y.; Peel, M. C.; Western, A. W.

2014-09-01

This study assessed the effect of using observed monthly leaf area index (LAI) on hydrologic model performance and the simulation of streamflow during drought using the variable infiltration capacity (VIC) hydrological model in the Goulburn-Broken catchment of Australia, which has heterogeneous vegetation, soil and climate zones. VIC was calibrated with both observed monthly LAI and long-term mean monthly LAI, which were derived from the Global Land Surface Satellite (GLASS) observed monthly LAI dataset covering the period from 1982 to 2012. The model performance under wet and dry climates for the two different LAI inputs was assessed using three criteria, the classical Nash-Sutcliffe efficiency, the logarithm transformed flow Nash-Sutcliffe efficiency and the percentage bias. Finally, the percentage deviation of the simulated monthly streamflow using the observed monthly LAI from simulated streamflow using long-term mean monthly LAI was computed. The VIC model predicted monthly streamflow in the selected sub-catchments with model efficiencies ranging from 61.5 to 95.9% during calibration (1982-1997) and 59 to 92.4% during validation (1998-2012). Our results suggest systematic improvements from 4 to 25% in the Nash-Sutcliffe efficiency in pasture dominated catchments when the VIC model was calibrated with the observed monthly LAI instead of the long-term mean monthly LAI. There was limited systematic improvement in tree dominated catchments. The results also suggest that the model overestimation or underestimation of streamflow during wet and dry periods can be reduced to some extent by including the year-to-year variability of LAI in the model, thus reflecting the responses of vegetation to fluctuations in climate and other factors. Hence, the year-to-year variability in LAI should not be neglected; rather it should be included in model calibration as well as simulation of monthly water balance.

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

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.

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.

Monthly paleostreamflow reconstruction from annual tree-ring chronologies

NASA Astrophysics Data System (ADS)

Stagge, J. H.; Rosenberg, D. E.; DeRose, R. J.; Rittenour, T. M.

2018-02-01

Paleoclimate reconstructions are increasingly used to characterize annual climate variability prior to the instrumental record, to improve estimates of climate extremes, and to provide a baseline for climate-change projections. To date, paleoclimate records have seen limited engineering use to estimate hydrologic risks because water systems models and managers usually require streamflow input at the monthly scale. This study explores the hypothesis that monthly streamflows can be adequately modeled by statistically decomposing annual flow reconstructions. To test this hypothesis, a multiple linear regression model for monthly streamflow reconstruction is presented that expands the set of predictors to include annual streamflow reconstructions, reconstructions of global circulation, and potential differences among regional tree-ring chronologies related to tree species and geographic location. This approach is used to reconstruct 600 years of monthly streamflows at two sites on the Bear and Logan rivers in northern Utah. Nash-Sutcliffe Efficiencies remain above zero (0.26-0.60) for all months except April and Pearson's correlation coefficients (R) are 0.94 and 0.88 for the Bear and Logan rivers, respectively, confirming that the model can adequately reproduce monthly flows during the reference period (10/1942 to 9/2015). Incorporating a flexible transition between the previous and concurrent annual reconstructed flows was the most important factor for model skill. Expanding the model to include global climate indices and regional tree-ring chronologies produced smaller, but still significant improvements in model fit. The model presented here is the only approach currently available to reconstruct monthly streamflows directly from tree-ring chronologies and climate reconstructions, rather than using resampling of the observed record. With reasonable estimates of monthly flow that extend back in time many centuries, water managers can challenge systems models with a

Impacts of uncertainties in weather and streamflow observations in calibration and evaluation of an elevation distributed HBV-model

NASA Astrophysics Data System (ADS)

Engeland, K.; Steinsland, I.; Petersen-Øverleir, A.; Johansen, S.

2012-04-01

The aim of this study is to assess the uncertainties in streamflow simulations when uncertainties in both observed inputs (precipitation and temperature) and streamflow observations used in the calibration of the hydrological model are explicitly accounted for. To achieve this goal we applied the elevation distributed HBV model operating on daily time steps to a small catchment in high elevation in Southern Norway where the seasonal snow cover is important. The uncertainties in precipitation inputs were quantified using conditional simulation. This procedure accounts for the uncertainty related to the density of the precipitation network, but neglects uncertainties related to measurement bias/errors and eventual elevation gradients in precipitation. The uncertainties in temperature inputs were quantified using a Bayesian temperature interpolation procedure where the temperature lapse rate is re-estimated every day. The uncertainty in the lapse rate was accounted for whereas the sampling uncertainty related to network density was neglected. For every day a random sample of precipitation and temperature inputs were drawn to be applied as inputs to the hydrologic model. The uncertainties in observed streamflow were assessed based on the uncertainties in the rating curve model. A Bayesian procedure was applied to estimate the probability for rating curve models with 1 to 3 segments and the uncertainties in their parameters. This method neglects uncertainties related to errors in observed water levels. Note that one rating curve was drawn to make one realisation of a whole time series of streamflow, thus the rating curve errors lead to a systematic bias in the streamflow observations. All these uncertainty sources were linked together in both calibration and evaluation of the hydrologic model using a DREAM based MCMC routine. Effects of having less information (e.g. missing one streamflow measurement for defining the rating curve or missing one precipitation station

Streamflow Characteristics of Streams in the Helmand Basin, Afghanistan

USGS Publications Warehouse

Williams-Sether, Tara

2008-01-01

Statistical summaries of streamflow data for all historical streamflow-gaging stations for the Helmand Basin upstream from the Sistan Wetlands are presented in this report. The summaries for each streamflow-gaging station include (1) manuscript (station description), (2) graph of the annual mean discharge for the period of record, (3) statistics of monthly and annual mean discharges, (4) graph of the annual flow duration, (5) monthly and annual flow duration, (6) probability of occurrence of annual high discharges, (7) probability of occurrence of annual low discharges, (8) probability of occurrence of seasonal low discharges, (9) annual peak discharge and corresponding gage height for the period of record, and (10) monthly and annual mean discharges for the period of record.

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.

Streamflow record extension for selected streams in the Susitna River Basin, Alaska

USGS Publications Warehouse

Curran, Janet H.

2012-01-01

Daily streamflow records for water years 1950–2010 in the Susitna River Basin range in length from 4 to 57 years, and many are distributed within that period in a way that might not adequately represent long-term streamflow conditions. Streamflow in the basin is affected by the Pacific Decadal Oscillation (PDO), a multi-decadal climate pattern that shifted from a cool phase to a warm phase in 1976. Records for many streamgages in the basin fell mostly within one phase of the PDO, such that monthly and annual statistics from observed records might not reflect streamflow conditions over a longer period. Correlations between daily discharge values sufficed for extending streamflow records at 11 of the 14 streamgages in the basin on the basis of relatively long-term records for one or more of the streamgages within the basin, or one outside the basin, that were defined as index stations. Streamflow at the index stations was hydrologically responsive to glacier melt and snowmelt, and correlated well with flow from similar high-elevation, glaciated basins, but flow in low-elevation basins without glaciers could not be correlated to flow at any of the index stations. Kendall-Theil Robust Line multi-segment regression equations developed for one or more index stations were used to extend daily discharge values to the full 61-year period for all 11 streamgages. Monthly and annual statistics prepared for the extended records show shifts in timing of breakup and freeze-up and magnitude of snowmelt peaks largely predicted by the PDO phase.

A stepwise model to predict monthly streamflow

NASA Astrophysics Data System (ADS)

Mahmood Al-Juboori, Anas; Guven, Aytac

2016-12-01

In this study, a stepwise model empowered with genetic programming is developed to predict the monthly flows of Hurman River in Turkey and Diyalah and Lesser Zab Rivers in Iraq. The model divides the monthly flow data to twelve intervals representing the number of months in a year. The flow of a month, t is considered as a function of the antecedent month's flow (t - 1) and it is predicted by multiplying the antecedent monthly flow by a constant value called K. The optimum value of K is obtained by a stepwise procedure which employs Gene Expression Programming (GEP) and Nonlinear Generalized Reduced Gradient Optimization (NGRGO) as alternative to traditional nonlinear regression technique. The degree of determination and root mean squared error are used to evaluate the performance of the proposed models. The results of the proposed model are compared with the conventional Markovian and Auto Regressive Integrated Moving Average (ARIMA) models based on observed monthly flow data. The comparison results based on five different statistic measures show that the proposed stepwise model performed better than Markovian model and ARIMA model. The R2 values of the proposed model range between 0.81 and 0.92 for the three rivers in this study.

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

Historical groundwater trends in northern New England and relations with streamflow and climatic variables

USGS Publications Warehouse

Dudley, Robert W.; Hodgkins, Glenn A.

2013-01-01

Water-level trends spanning 20, 30, 40, and 50 years were tested using month-end groundwater levels in 26, 12, 10, and 3 wells in northern New England (Maine, New Hampshire, and Vermont), respectively. Groundwater levels for 77 wells were used in interannual correlations with meteorological and hydrologic variables related to groundwater. Trends in the contemporary groundwater record (20 and 30 years) indicate increases (rises) or no substantial change in groundwater levels in all months for most wells throughout northern New England. The highest percentage of increasing 20-year trends was in February through March, May through August, and October through November. Forty-year trend results were mixed, whereas 50-year trends indicated increasing groundwater levels. Whereas most monthly groundwater levels correlate strongly with the previous month's level, monthly levels also correlate strongly with monthly streamflows in the same month; correlations of levels with monthly precipitation are less frequent and weaker than those with streamflow. Groundwater levels in May through August correlate strongly with annual (water year) streamflow. Correlations of groundwater levels with streamflow data and the relative richness of 50- to 100-year historical streamflow data suggest useful proxies for quantifying historical groundwater levels in light of the relatively short and fragmented groundwater data records presently available.

Estimation of unregulated monthly, annual, and peak streamflows in Forest City Stream and lake levels in East Grand Lake, United States-Canada border between Maine and New Brunswick

USGS Publications Warehouse

Lombard, Pamela J.

2018-04-30

The U.S. Geological Survey, in cooperation with the International Joint Commission, compiled historical data on regulated streamflows and lake levels and estimated unregulated streamflows and lake levels on Forest City Stream at Forest City, Maine, and East Grand Lake on the United States-Canada border between Maine and New Brunswick to study the effects on streamflows and lake levels if two or all three dam gates are left open. Historical regulated monthly mean streamflows in Forest City Stream at the outlet of East Grand Lake (referred to as Grand Lake by Environment Canada) fluctuated between 114 cubic feet per second (ft3 /s) (3.23 cubic meters per second [m3 /s]) in November and 318 ft3 /s (9.01 m3 /s) in September from 1975 to 2015 according to Environment Canada streamgaging data. Unregulated monthly mean streamflows at this location estimated from regression equations for unregulated sites range from 59.2 ft3 /s (1.68 m3 /s) in September to 653 ft3 /s (18.5 m3 /s) in April. Historical lake levels in East Grand Lake fluctuated between 431.3 feet (ft) (131.5 meters [m]) in October and 434.0 ft (132.3 m) in May from 1969 to 2016 according to Environment Canada lake level data for East Grand Lake. Average monthly lake levels modeled by using the estimated hydrology for unregulated flows, and an outflow rating built from a hydraulic model with all gates at the dam open, range from 427.7 ft (130.4 m) in September to 431.1 ft (131.4 m) in April. Average monthly lake levels would likely be from 1.8 to 5.4 ft (0.55 to 1.6 m) lower with the gates at the dam opened than they have been historically. The greatest lake level changes would be from June through September.

Analysis of managed aquifer recharge for retiming streamflow in an alluvial river

NASA Astrophysics Data System (ADS)

Ronayne, Michael J.; Roudebush, Jason A.; Stednick, John D.

2017-01-01

Maintenance of low flows during dry periods is critical for supporting ecosystem function in many rivers. Managed aquifer recharge is one method that can be used to augment low flows in rivers that are hydraulically connected to an alluvial groundwater system. In this study, we performed numerical modeling to evaluate a managed recharge operation designed to retime streamflow in the South Platte River, northeastern Colorado (USA). Modeling involved the simulation of spatially and temporally variable groundwater-surface water exchange, as well as streamflow routing in the river. Periodic solutions that incorporate seasonality were developed for two scenarios, a natural base case scenario and an active management scenario that included groundwater pumping and managed recharge. A framework was developed to compare the scenarios by analyzing changes in head-dependent inflows and outflows to/from the aquifer, which was used to interpret the simulated impacts on streamflow. The results clearly illustrate a retiming of streamflow. Groundwater pumping near the river during winter months causes a reduction in streamflow during those months. Delivery of the pumped water to recharge ponds, located further from the river, has the intended effect of augmenting streamflow during low-flow summer months. Higher streamflow is not limited to the target time period, however, which highlights an inefficiency of flow augmentation projects that rely on water retention in the subsurface.

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.

Streamflow statistics for selected streams in North Dakota, Minnesota, Manitoba, and Saskatchewan

USGS Publications Warehouse

Williams-Sether, Tara

2012-01-01

Statistical summaries of streamflow data for the periods of record through water year 2009 for selected active and discontinued U.S. Geological Survey streamflow-gaging stations in North Dakota, Minnesota, Manitoba, and Saskatchewan were compiled. The summaries for each streamflow-gaging station include a brief station description, a graph of the annual peak and annual mean discharge for the period of record, statistics of monthly and annual mean discharges, monthly and annual flow durations, probability of occurrence of annual high discharges, annual peak discharge and corresponding gage height for the period of record, and monthly and annual mean discharges for the period of record.

Skill of a global seasonal ensemble streamflow forecasting system

NASA Astrophysics Data System (ADS)

Candogan Yossef, Naze; Winsemius, Hessel; Weerts, Albrecht; van Beek, Rens; Bierkens, Marc

2013-04-01

Forecasting of water availability and scarcity is a prerequisite for managing the risks and opportunities caused by the inter-annual variability of streamflow. Reliable seasonal streamflow forecasts are necessary to prepare for an appropriate response in disaster relief, management of hydropower reservoirs, water supply, agriculture and navigation. Seasonal hydrological forecasting on a global scale could be valuable especially for developing regions of the world, where effective hydrological forecasting systems are scarce. In this study, we investigate the forecasting skill of the global seasonal streamflow forecasting system FEWS-World, using the global hydrological model PCR-GLOBWB. FEWS-World has been setup within the European Commission 7th Framework Programme project Global Water Scarcity Information Service (GLOWASIS). Skill is assessed in historical simulation mode as well as retroactive forecasting mode. The assessment in historical simulation mode used a meteorological forcing based on observations from the Climate Research Unit of the University of East Anglia and the ERA-40 reanalysis of the European Center for Medium-Range Weather Forecasts (ECMWF). We assessed the skill of the global hydrological model PCR-GLOBWB in reproducing past discharge extremes in 20 large rivers of the world. This preliminary assessment concluded that the prospects for seasonal forecasting with PCR-GLOBWB or comparable models are positive. However this assessment did not include actual meteorological forecasts. Thus the meteorological forcing errors were not assessed. Yet, in a forecasting setup, the predictive skill of a hydrological forecasting system is affected by errors due to uncertainty from numerical weather prediction models. For the assessment in retroactive forecasting mode, the model is forced with actual ensemble forecasts from the seasonal forecast archives of ECMWF. Skill is assessed at 78 stations on large river basins across the globe, for all the months of

Streamflow conditions along Soldier Creek, Northeast Kansas

USGS Publications Warehouse

Juracek, Kyle E.

2017-11-14

The availability of adequate water to meet the present (2017) and future needs of humans, fish, and wildlife is a fundamental issue for the Prairie Band Potawatomi Nation in northeast Kansas. Because Soldier Creek flows through the Prairie Band Potawatomi Nation Reservation, it is an important tribal resource. An understanding of historical Soldier Creek streamflow conditions is required for the effective management of tribal water resources, including drought contingency planning. Historical data for six selected U.S. Geological Survey (USGS) streamgages along Soldier Creek were used in an assessment of streamflow characteristics and trends by Juracek (2017). Streamflow data for the period of record at each streamgage were used to compute annual mean streamflow, annual mean base flow, mean monthly flow, annual peak flow, and annual minimum flow. Results of the assessment are summarized in this fact sheet.

Variability and predictability of the streamflows in Coastal and Andean Ecuador

NASA Astrophysics Data System (ADS)

Quishpe-Vásquez, César; Córdoba-Machado, Samir; Palomino-Lemus, Reiner; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

The main objective of this study is to examine the variability and the predictability in available water resources in Coastal and Andean Ecuador. For this aim, we use the streamflow data from a network of hydrological stations, provided by the National Institute of Meteorology and Hydrology of Ecuador (IHNAMI), distributed over the Ecuadorian territory and strategically located in the watersheds of its main rivers. A number of 20 stations with a continuous period of daily data covering a period of 42 years (1973-2015) were selected. To analyze the spatio-temporal variability of streamflow in Ecuador, principal component analysis (PCA) along with a study of trends have been applied to the streamflow data at monthly time scales. The significance and magnitude of trends have been analyzed using Man-Kendall test and Sen slope. Moreover, to analyze the predictability of the streamflow, the spatio-temporal effects of the ENSO phenomenon on the country have been evaluated through a correlation analysis using different lags between different El Niño indices (Niño 1+2, Niño Modoki, Trans-Niño and Niño 3.4) and the seasonal streamflow. The results show two main regions that differ in terms of variability. We found that the variations in water resources have a close relationship between the magnitude and the seasonal distribution of the streamflow and the ENSO. However, each index shows a different impact on the streamflow depending on the season and the region. In general, the higher correlations between the ENSO indices and the streamflow are observed in the stations closer to the coast. KEY WORDS: Ecuador streamflow; trends; PCA; variability; predictability; ENSO. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Monthly hydroclimatology of the continental United States

NASA Astrophysics Data System (ADS)

Petersen, Thomas; Devineni, Naresh; Sankarasubramanian, A.

2018-04-01

Physical/semi-empirical models that do not require any calibration are of paramount need for estimating hydrological fluxes for ungauged sites. We develop semi-empirical models for estimating the mean and variance of the monthly streamflow based on Taylor Series approximation of a lumped physically based water balance model. The proposed models require mean and variance of monthly precipitation and potential evapotranspiration, co-variability of precipitation and potential evapotranspiration and regionally calibrated catchment retention sensitivity, atmospheric moisture uptake sensitivity, groundwater-partitioning factor, and the maximum soil moisture holding capacity parameters. Estimates of mean and variance of monthly streamflow using the semi-empirical equations are compared with the observed estimates for 1373 catchments in the continental United States. Analyses show that the proposed models explain the spatial variability in monthly moments for basins in lower elevations. A regionalization of parameters for each water resources region show good agreement between observed moments and model estimated moments during January, February, March and April for mean and all months except May and June for variance. Thus, the proposed relationships could be employed for understanding and estimating the monthly hydroclimatology of ungauged basins using regional parameters.

Changes in seasonal streamflow extremes experienced in rivers of Northwestern South America (Colombia)

NASA Astrophysics Data System (ADS)

Pierini, J. O.; Restrepo, J. C.; Aguirre, J.; Bustamante, A. M.; Velásquez, G. J.

2017-04-01

A measure of the variability in seasonal extreme streamflow was estimated for the Colombian Caribbean coast, using monthly time series of freshwater discharge from ten watersheds. The aim was to detect modifications in the streamflow monthly distribution, seasonal trends, variance and extreme monthly values. A 20-year length time moving window, with 1-year successive shiftments, was applied to the monthly series to analyze the seasonal variability of streamflow. The seasonal-windowed data were statistically fitted through the Gamma distribution function. Scale and shape parameters were computed using the Maximum Likelihood Estimation (MLE) and the bootstrap method for 1000 resample. A trend analysis was performed for each windowed-serie, allowing to detect the window of maximum absolute values for trends. Significant temporal shifts in seasonal streamflow distribution and quantiles (QT), were obtained for different frequencies. Wet and dry extremes periods increased significantly in the last decades. Such increase did not occur simultaneously through the region. Some locations exhibited continuous increases only at minimum QT.

Climatic change projections for winter streamflow in Guadalquivir river

NASA Astrophysics Data System (ADS)

Jesús Esteban Parra, María; Hidalgo Muñoz, José Manuel; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz Fortis, Sonia; Castro Díez, Yolanda

2015-04-01

In this work we have obtained climate change projections for winter streamflow of the Guadalquivir River in the period 2071-2100 using the Principal Component Regression (PCR) method. The streamflow data base used has been provided by the Center for Studies and Experimentation of Public Works, CEDEX. Series from gauging stations and reservoirs with less than 10% of missing data (filled by regression with well correlated neighboring stations) have been considered. The homogeneity of these series has been evaluated through the Pettit test and degree of human alteration by the Common Area Index. The application of these criteria led to the selection of 13 streamflow time series homogeneously distributed over the basin, covering the period 1952-2011. For this streamflow data, winter seasonal values were obtained by averaging the monthly values from January to March. The PCR method has been applied using the Principal Components of the mean anomalies of sea level pressure (SLP) in winter (December to February averaged) as predictors of streamflow for the development of a downscaled statistical model. The SLP database is the NCEP reanalysis covering the North Atlantic region, and the calibration and validation periods used for fitting and evaluating the ability of the model are 1952-1992 and 1993-2011, respectively. In general, using four Principal Components, regression models are able to explain up to 70% of the variance of the streamflow data. Finally, the statistical model obtained for the observational data was applied to the SLP data for the period 2071-2100, using the outputs of different GCMs of the CMIP5 under the RPC8.5 scenario. The results found for the end of the century show no significant changes or moderate decrease in the streamflow of this river for most GCMs in winter, but for some of them the decrease is very strong. Keywords: Statistical downscaling, streamflow, Guadalquivir River, climate change. ACKNOWLEDGEMENTS This work has been financed by the

FLO1K, global maps of mean, maximum and minimum annual streamflow at 1 km resolution from 1960 through 2015

NASA Astrophysics Data System (ADS)

Barbarossa, Valerio; Huijbregts, Mark A. J.; Beusen, Arthur H. W.; Beck, Hylke E.; King, Henry; Schipper, Aafke M.

2018-03-01

Streamflow data is highly relevant for a variety of socio-economic as well as ecological analyses or applications, but a high-resolution global streamflow dataset is yet lacking. We created FLO1K, a consistent streamflow dataset at a resolution of 30 arc seconds (~1 km) and global coverage. FLO1K comprises mean, maximum and minimum annual flow for each year in the period 1960-2015, provided as spatially continuous gridded layers. We mapped streamflow by means of artificial neural networks (ANNs) regression. An ensemble of ANNs were fitted on monthly streamflow observations from 6600 monitoring stations worldwide, i.e., minimum and maximum annual flows represent the lowest and highest mean monthly flows for a given year. As covariates we used the upstream-catchment physiography (area, surface slope, elevation) and year-specific climatic variables (precipitation, temperature, potential evapotranspiration, aridity index and seasonality indices). Confronting the maps with independent data indicated good agreement (R2 values up to 91%). FLO1K delivers essential data for freshwater ecology and water resources analyses at a global scale and yet high spatial resolution.

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.

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

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. 

Streamflow characteristics and trends along Soldier Creek, Northeast Kansas

USGS Publications Warehouse

Juracek, Kyle E.

2017-08-16

Historical data for six selected U.S. Geological Survey streamgages along Soldier Creek in northeast Kansas were used in an assessment of streamflow characteristics and trends. This information is required by the Prairie Band Potawatomi Nation for the effective management of tribal water resources, including drought contingency planning. Streamflow data for the period of record at each streamgage were used to assess annual mean streamflow, annual mean base flow, mean monthly flow, annual peak flow, and annual minimum flow.Annual mean streamflows along Soldier Creek were characterized by substantial year-to-year variability with no pronounced long-term trends. On average, annual mean base flow accounted for about 20 percent of annual mean streamflow. Mean monthly flows followed a general seasonal pattern that included peak values in spring and low values in winter. Annual peak flows, which were characterized by considerable year-to-year variability, were most likely to occur in May and June and least likely to occur during November through February. With the exception of a weak yet statistically significant increasing trend at the Soldier Creek near Topeka, Kansas, streamgage, there were no pronounced long-term trends in annual peak flows. Annual 1-day, 30-day, and 90-day mean minimum flows were characterized by considerable year-to-year variability with no pronounced long-term trend. During an extreme drought, as was the case in the mid-1950s, there may be zero flow in Soldier Creek continuously for a period of one to several months.

Streamflow variability and classification using false nearest neighbor method

NASA Astrophysics Data System (ADS)

Vignesh, R.; Jothiprakash, V.; Sivakumar, B.

2015-12-01

Understanding regional streamflow dynamics and patterns continues to be a challenging problem. The present study introduces the false nearest neighbor (FNN) algorithm, a nonlinear dynamic-based method, to examine the spatial variability of streamflow over a region. The FNN method is a dimensionality-based approach, where the dimension of the time series represents its variability. The method uses phase space reconstruction and nearest neighbor concepts, and identifies false neighbors in the reconstructed phase space. The FNN method is applied to monthly streamflow data monitored over a period of 53 years (1950-2002) in an extensive network of 639 stations in the contiguous United States (US). Since selection of delay time in phase space reconstruction may influence the FNN outcomes, analysis is carried out for five different delay time values: monthly, seasonal, and annual separation of data as well as delay time values obtained using autocorrelation function (ACF) and average mutual information (AMI) methods. The FNN dimensions for the 639 streamflow series are generally identified to range from 4 to 12 (with very few exceptional cases), indicating a wide range of variability in the dynamics of streamflow across the contiguous US. However, the FNN dimensions for a majority of the streamflow series are found to be low (less than or equal to 6), suggesting low level of complexity in streamflow dynamics in most of the individual stations and over many sub-regions. The FNN dimension estimates also reveal that streamflow dynamics in the western parts of the US (including far west, northwestern, and southwestern parts) generally exhibit much greater variability compared to that in the eastern parts of the US (including far east, northeastern, and southeastern parts), although there are also differences among 'pockets' within these regions. These results are useful for identification of appropriate model complexity at individual stations, patterns across regions and sub

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

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

Streamflow characteristics and trends in New Jersey, water years 1897-2003

USGS Publications Warehouse

Watson, Kara M.; Reiser, Robert G.; Nieswand, Steven P.; Schopp, Robert D.

2005-01-01

Streamflow statistics were computed for 111 continuous-record streamflow-gaging stations with 20 or more years of continuous record and for 500 low-flow partial-record stations, including 66 gaging stations with less than 20 years of continuous record. Daily mean streamflow data from water year 1897 through water year 2001 were used for the computations at the gaging stations. (The water year is the 12-month period, October 1 through September 30, designated by the calendar year in which it ends). The characteristics presented for the long-term continuous-record stations are daily streamflow, harmonic mean flow, flow frequency, daily flow durations, trend analysis, and streamflow variability. Low-flow statistics for gaging stations with less than 20 years of record and for partial-record stations were estimated by correlating base-flow measurements with daily mean flows at long-term (more than 20 years) continuous-record stations. Instantaneous streamflow measurements through water year 2003 were used to estimate low-flow statistics at the partial-record stations. The characteristics presented for partial-record stations are mean annual flow; harmonic mean flow; and annual and winter low-flow frequency. The annual 1-, 7-, and 30-day low- and high-flow data sets were tested for trends. The results of trend tests for high flows indicate relations between upward trends for high flows and stream regulation, and high flows and development in the basin. The relation between development and low-flow trends does not appear to be as strong as for development and high-flow trends. Monthly, seasonal, and annual precipitation data for selected long-term meteorological stations also were tested for trends to analyze the effects of climate. A significant upward trend in precipitation in northern New Jersey, Climate Division 1 was identified. For Climate Division 2, no general increase in average precipitation was observed. Trend test results indicate that high flows at

Classification Scheme for Centuries of Reconstructed Streamflow Droughts in Water Resources Planning

NASA Astrophysics Data System (ADS)

Stagge, J.; Rosenberg, D. E.

2017-12-01

New advances in reconstructing streamflow from tree rings have permitted the reconstruction of flows back to the 1400s or earlier at a monthly, rather than annual, time scale. This is a critical step for incorporating centuries of streamflow reconstructions into water resources planning. Expanding the historical record is particularly important where the observed record contains few of these rare, but potentially disastrous extreme events. We present how a paleo-drought clustering approach was incorporated alongside more traditional water management planning in the Weber River basin, northern Utah. This study used newly developed monthly reconstructions of flow since 1430 CE and defined drought events as flow less than the 50th percentile during at least three contiguous months. Characteristics for each drought event included measures of drought duration, severity, cumulative loss, onset, seasonality, recession rate, and recovery rate. Reconstructed drought events were then clustered by hierarchical clustering to determine distinct drought "types" and the historical event that best represents the centroid of each cluster. The resulting 144 reconstructed drought events in the Weber basin clustered into nine distinct types, of which four were severe enough to potentially require drought management. Using the characteristic drought event for each of the severe drought clusters, water managers were able to estimate system reliability and the historical return frequency for each drought type. Plotting drought duration and severity from centuries of historical reconstructed events alongside observed events and climate change projections further placed recent events into a historical context. For example, the drought of record for the Weber River remains the most severe event in the record with regard to minimum flow percentile (1930, 7 years), but is far from the longest event in the longer historical record, where events beginning in 1658 and 1705 both lasted longer

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.

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.

Estimation of Streamflow Characteristics for Charles M. Russell National Wildlife Refuge, Northeastern Montana

USGS Publications Warehouse

Sando, Steven K.; Morgan, Timothy J.; Dutton, DeAnn M.; McCarthy, Peter M.

2009-01-01

Charles M. Russell National Wildlife Refuge (CMR) encompasses about 1.1 million acres (including Fort Peck Reservoir on the Missouri River) in northeastern Montana. To ensure that sufficient streamflow remains in the tributary streams to maintain the riparian corridors, the U.S. Fish and Wildlife Service is negotiating water-rights issues with the Reserved Water Rights Compact Commission of Montana. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, conducted a study to gage, for a short period, selected streams that cross CMR, and analyze data to estimate long-term streamflow characteristics for CMR. The long-term streamflow characteristics of primary interest include the monthly and annual 90-, 80-, 50-, and 20-percent exceedance streamflows and mean streamflows (Q.90, Q.80, Q.50, Q.20, and QM, respectively), and the 1.5-, 2-, and 2.33- year peak flows (PK1.5, PK2, and PK2.33, respectively). The Regional Adjustment Relationship (RAR) was investigated for estimating the monthly and annual Q.90, Q.80, Q.50, Q.20, and QM, and the PK1.5, PK2, and PK2.33 for the short-term CMR gaging stations (hereinafter referred to as CMR stations). The RAR was determined to provide acceptable results for estimating the long-term Q.90, Q.80, Q.50, Q.20, and QM on a monthly basis for the months of March through June, and also on an annual basis. For the months of September through January, the RAR regression equations did not provide acceptable results for any long-term streamflow characteristic. For the month of February, the RAR regression equations provided acceptable results for the long-term Q.50 and QM, but poor results for the long-term Q.90, Q.80, and Q.20. For the months of July and August, the RAR provided acceptable results for the long-term Q.50, Q.20, and QM, but poor results for the long-term Q.90 and Q.80. Estimation coefficients were developed for estimating the long-term streamflow characteristics for which the RAR did not provide

Possible Link Between Irrigation in the U.S. High Plains and Increased Summer Streamflow in the Midwest

NASA Technical Reports Server (NTRS)

Kustu, M. Deniz; Fan, Ying; Rodell, Matthew

2011-01-01

We have previously presented evidence that higher rates of evapotranspiration (ET) associated with irrigation in the U.S. High Plains has likely caused an increased downwind precipitation (P). July P over the Midwest increased by 20%-30% from the pre-irrigation period (1900-1950) to the post-irrigation (1950-2000) period. In this study, we test the hypothesis that the increased July P has had hydrologic consequences, possibly increasing groundwater storage and streamflow. Seasonal analyses of hydrologic variables over Illinois suggest that the water table and streamflow response lags P - ET by 1-2 months, indicating August and September as the months when the increased July P may be detected. We analyzed long-term observations of water table depth at 10 wells in Illinois and streamflow at 46 gauges in Illinois-Ohio basins. The Mann-Kendal test for trends suggests field significant increases in groundwater storage and streamflow in August-September over the period of irrigation expansion. Examination of soil moisture response to present-day above-normal July P suggests that the increased July P can reach the water table in normal to wet years. Mann-Kendall tests suggest that there has been no change in pan evaporation and atmospheric vapor pressure deficit. This implies that soil water availability is the driver of changes in ET, and the increased P may have possibly increased ET. Other studies in the literature give further evidence of increased ET due to increased P. By ruling out a reduction in ET, we suggest that the observed increase in groundwater storage and streamflow in the Midwest is linked to the increased July precipitation attributed to High Plains irrigation. We note that the increases in late summer streamflow are rather small when placed in the context of seasonal dynamics, but they are conceptually important in that they point to a different cause of change.

Statistical downscaling for winter streamflow in Douro River

NASA Astrophysics Data System (ADS)

Jesús Esteban Parra, María; Hidalgo Muñoz, José Manuel; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz Fortis, Sonia; Castro Díez, Yolanda

2015-04-01

In this paper we have obtained climate change projections for winter flow of the Douro River in the period 2071-2100 by applying the technique of Partial Regression and various General Circulation Models of CMIP5. The streamflow data base used has been provided by the Center for Studies and Experimentation of Public Works, CEDEX. Series from gauing stations and reservoirs with less than 10% of missing data (filled by regression with well correlated neighboring stations) have been considered. The homogeneity of these series has been evaluated through the Pettit test and degree of human alteration by the Common Area Index. The application of these criteria led to the selection of 42 streamflow time series homogeneously distributed over the basin, covering the period 1951-2011. For these streamflow data, winter seasonal values were obtained by averaging the monthly values from January to March. Statistical downscaling models for the streamflow have been fitted using as predictors the main atmospheric modes of variability over the North Atlantic region. These modes have been obtained using winter sea level pressure data of the NCEP reanalysis, averaged for the months from December to February. Period 1951-1995 was used for calibration, while 1996-2011 period was used in validating the adjusted models. In general, these models are able to reproduce about 70% of the variability of the winter streamflow of the Douro River. Finally, the obtained statistical models have been applied to obtain projections for 2071-2100 period, using outputs from different CMIP5 models under the RPC8.5 scenario. The results for the end of the century show modest declines of winter streamflow in this river for most of the models. Keywords: Statistical downscaling, streamflow, Douro River, climate change. ACKNOWLEDGEMENTS This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Modeling the effect of glacier recession on streamflow response using a coupled glacio-hydrological model

DOE PAGES

Frans, Chris D.; Clarke, Garry K. C.; Burns, P.; ...

2014-02-27

Here, we describe an integrated spatially distributed hydrologic and glacier dynamic model, and use it to investigate the effect of glacier recession on streamflow variations for the Upper Bow River basin, a tributary of the South Saskatchewan River. Several recent studies have suggested that observed decreases in summer flows in the South Saskatchewan River are partly due to the retreat of glaciers in the river's headwaters. Modeling the effect of glacier changes on streamflow response in river basins such as the South Saskatchewan is complicated due to the inability of most existing physically-based distributed hydrologic models to represent glacier dynamics.more » We compare predicted variations in glacier extent, snow water equivalent and streamflow discharge made with the integrated model with satellite estimates of glacier area and terminus position, observed streamflow and snow water equivalent measurements over the period of 1980 2007. Simulations with the coupled hydrology-glacier model reduce the uncertainty in streamflow predictions. Our results suggested that on average, the glacier melt contribution to the Bow River flow upstream of Lake Louise is about 30% in summer. For warm and dry years, however, the glacier melt contribution can be as large as 50% in August, whereas for cold years, it can be as small as 20% and the timing of glacier melt signature can be delayed by a month.« less

Can we use Earth Observations to improve monthly water level forecasts?

NASA Astrophysics Data System (ADS)

Slater, L. J.; Villarini, G.

2017-12-01

Dynamical-statistical hydrologic forecasting approaches benefit from different strengths in comparison with traditional hydrologic forecasting systems: they are computationally efficient, can integrate and `learn' from a broad selection of input data (e.g., General Circulation Model (GCM) forecasts, Earth Observation time series, teleconnection patterns), and can take advantage of recent progress in machine learning (e.g. multi-model blending, post-processing and ensembling techniques). Recent efforts to develop a dynamical-statistical ensemble approach for forecasting seasonal streamflow using both GCM forecasts and changing land cover have shown promising results over the U.S. Midwest. Here, we use climate forecasts from several GCMs of the North American Multi Model Ensemble (NMME) alongside 15-minute stage time series from the National River Flow Archive (NRFA) and land cover classes extracted from the European Space Agency's Climate Change Initiative 300 m annual Global Land Cover time series. With these data, we conduct systematic long-range probabilistic forecasting of monthly water levels in UK catchments over timescales ranging from one to twelve months ahead. We evaluate the improvement in model fit and model forecasting skill that comes from using land cover classes as predictors in the models. This work opens up new possibilities for combining Earth Observation time series with GCM forecasts to predict a variety of hazards from space using data science techniques.

Streamflow Changes Induced by the 1999 MW 7.6 Chi-Chi Earthquake

NASA Astrophysics Data System (ADS)

Chia, Yeeping; Liu, Ching-Yi; Chuang, Po-Yu

2016-04-01

Anomalous streamflow changes have often been observed after strong earthquakes. These changes have been used to study crustal deformation induced by earthquakes. Previous studies indicated that co-seismic groundwater-level changes, ranging from a fall of 11.1 m to a rise of 7.42 m, were recorded in 152 monitoring wells near the seismogenic fault during the 1999 MW 7.6 Chi-Chi earthquake. Here we report anomalous streamflow changes due to the earthquake in central Taiwan. There are 32 stream gauges in the vicinity of the fault, mostly in the mountainous hanging wall area. Of those, 22 recorded anomalous streamflow increases, ranging from 60% to 732%, one to four days after the earthquake. Unlike a rapid decrease in discharge after heavy rainfall, the post-seismic increase is followed by a slow decline which may last for several months. Only one gauge recorded a sudden decrease in discharge immediately after the earthquake. Besides, the decrease was preceded by a large and abrupt streamflow increase over the four days before the earthquake. We attribute the post-seismic increase to fracturing in the mountainous area due to seismic shaking, while the decrease to co-seismic pore pressure drop induced by crustal extension. However, more evidence is needed to consider the pre-seismic streamflow changes as a potential precursory indicator of earthquakes.

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.

Effects of urban best management practices on streamflow and phosphorus and suspended-sediment transport on Englesby Brook in Burlington, Vermont, 2000-2010

USGS Publications Warehouse

Medalie, Laura

2012-01-01

example, monthly loads assessed using analysis of covariance, which compensated for the effects of streamflow on loads, suggested no difference in phosphorus or suspended-sediment loads between the two periods, whereas the comparison of monthly loads without factoring in streamflow showed an increase. This result could be viewed as evidence that the ponds may have mitigated the effect of greater discharges in the period after construction by preventing a corresponding increase in loads. In another analysis used to adjust for the difference in discharge between the two comparison periods, annual and monthly load results were grouped into dry and wet years. Large (50 percent) reductions in annual loads were observed when data from dry (or wet) years before construction were compared with data from dry (or wet) years after construction. When paired monthly loads of each constituent were grouped into dry and wet years, approximately the same number of months had increases as did decreases with the magnitudes of the decreases generally larger than the magnitudes of the increases. These differences in magnitude explain the decrease in annual loads for dry and wet years. The close association of phosphorus with suspended-sediment data suggested that most of the phosphorus was in the particulate form and was controlled by suspended-sediment dynamics.

Characteristics and Classification of Least Altered Streamflows in Massachusetts

USGS Publications Warehouse

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

2008-01-01

Streamflow records from 85 streamflow-gaging stations at which streamflows were considered to be least altered were used to characterize natural streamflows within southern New England. Period-of-record streamflow data were used to determine annual hydrographs of median monthly flows. The shapes and magnitudes of annual hydrographs of median monthly flows, normalized by drainage area, differed among stations in different geographic areas of southern New England. These differences were gradational across southern New England and were attributed to differences in basin and climate characteristics. Period-of-record streamflow data were also used to analyze the statistical properties of daily streamflows at 61 stations across southern New England by using L-moment ratios. An L-moment ratio diagram of L-skewness and L-kurtosis showed a continuous gradation in these properties between stations and indicated differences between base-flow dominated and runoff-dominated rivers. Streamflow records from a concurrent period (1960-2004) for 61 stations were used in a multivariate statistical analysis to develop a hydrologic classification of rivers in southern New England. Missing records from 46 of these stations were extended by using a Maintenance of Variation Extension technique. The concurrent-period streamflows were used in the Indicators of Hydrologic Alteration and Hydrologic Index Tool programs to determine 224 hydrologic indices for the 61 stations. Principal-components analysis (PCA) was used to reduce the number of hydrologic indices to 20 that provided nonredundant information. The PCA also indicated that the major patterns of variability in the dataset are related to differences in flow variability and low-flow magnitude among the stations. Hierarchical cluster analysis was used to classify stations into groups with similar hydrologic properties. The cluster analysis classified rivers in southern New England into two broad groups: (1) base-flow dominated rivers

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.

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).

Estimates of ground-water recharge based on streamflow-hydrograph methods: Pennsylvania

USGS Publications Warehouse

Risser, Dennis W.; Conger, Randall W.; Ulrich, James E.; Asmussen, Michael P.

2005-01-01

This study, completed by the U.S. Geological Survey (USGS) in cooperation with the Pennsylvania Department of Conservation and Natural Resources, Bureau of Topographic and Geologic Survey (T&GS), provides estimates of ground-water recharge for watersheds throughout Pennsylvania computed by use of two automated streamflow-hydrograph-analysis methods--PART and RORA. The PART computer program uses a hydrograph-separation technique to divide the streamflow hydrograph into components of direct runoff and base flow. Base flow can be a useful approximation of recharge if losses and interbasin transfers of ground water are minimal. The RORA computer program uses a recession-curve displacement technique to estimate ground-water recharge from each storm period indicated on the streamflow hydrograph. Recharge estimates were made using streamflow records collected during 1885-2001 from 197 active and inactive streamflow-gaging stations in Pennsylvania where streamflow is relatively unaffected by regulation. Estimates of mean-annual recharge in Pennsylvania computed by the use of PART ranged from 5.8 to 26.6 inches; estimates from RORA ranged from 7.7 to 29.3 inches. Estimates from the RORA program were about 2 inches greater than those derived from the PART program. Mean-monthly recharge was computed from the RORA program and was reported as a percentage of mean-annual recharge. On the basis of this analysis, the major ground-water recharge period in Pennsylvania typically is November through May; the greatest monthly recharge typically occurs in March.

Streamflow sensitivity to water storage changes across Europe

NASA Astrophysics Data System (ADS)

Berghuijs, Wouter R.; Hartmann, Andreas; Woods, Ross A.

2016-03-01

Terrestrial water storage is the primary source of river flow. We introduce storage sensitivity of streamflow (ɛS), which for a given flow rate indicates the relative change in streamflow per change in catchment water storage. ɛS can be directly derived from streamflow observations. Analysis of 725 catchments in Europe reveals that ɛS is high in, e.g., parts of Spain, England, Germany, and Denmark, whereas flow regimes in parts of the Alps are more resilient (that is, less sensitive) to storage changes. A regional comparison of ɛS with observations indicates that ɛS is significantly correlated with variability of low (R2 = 0.41), median (R2 = 0.27), and high flow conditions (R2 = 0.35). Streamflow sensitivity provides new guidance for a changing hydrosphere where groundwater abstraction and climatic changes are altering water storage and flow regimes.

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.

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.

Statistical procedures for evaluating daily and monthly hydrologic model predictions

USGS Publications Warehouse

Coffey, M.E.; Workman, S.R.; Taraba, J.L.; Fogle, A.W.

2004-01-01

The overall study objective was to evaluate the applicability of different qualitative and quantitative methods for comparing daily and monthly SWAT computer model hydrologic streamflow predictions to observed data, and to recommend statistical methods for use in future model evaluations. Statistical methods were tested using daily streamflows and monthly equivalent runoff depths. The statistical techniques included linear regression, Nash-Sutcliffe efficiency, nonparametric tests, t-test, objective functions, autocorrelation, and cross-correlation. None of the methods specifically applied to the non-normal distribution and dependence between data points for the daily predicted and observed data. Of the tested methods, median objective functions, sign test, autocorrelation, and cross-correlation were most applicable for the daily data. The robust coefficient of determination (CD*) and robust modeling efficiency (EF*) objective functions were the preferred methods for daily model results due to the ease of comparing these values with a fixed ideal reference value of one. Predicted and observed monthly totals were more normally distributed, and there was less dependence between individual monthly totals than was observed for the corresponding predicted and observed daily values. More statistical methods were available for comparing SWAT model-predicted and observed monthly totals. The 1995 monthly SWAT model predictions and observed data had a regression Rr2 of 0.70, a Nash-Sutcliffe efficiency of 0.41, and the t-test failed to reject the equal data means hypothesis. The Nash-Sutcliffe coefficient and the R r2 coefficient were the preferred methods for monthly results due to the ability to compare these coefficients to a set ideal value of one.

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.

The Global Streamflow Indices and Metadata archive (G-SIM): A compilation of global streamflow time series indices and meta-data

NASA Astrophysics Data System (ADS)

Do, Hong; Gudmundsson, Lukas; Leonard, Michael; Westra, Seth; Senerivatne, Sonia

2017-04-01

In-situ observations of daily streamflow with global coverage are a crucial asset for understanding large-scale freshwater resources which are an essential component of the Earth system and a prerequisite for societal development. Here we present the Global Streamflow Indices and Metadata archive (G-SIM), a collection indices derived from more than 20,000 daily streamflow time series across the globe. These indices are designed to support global assessments of change in wet and dry extremes, and have been compiled from 12 free-to-access online databases (seven national databases and five international collections). The G-SIM archive also includes significant metadata to help support detailed understanding of streamflow dynamics, with the inclusion of drainage area shapefile and many essential catchment properties such as land cover type, soil and topographic characteristics. The automated procedure in data handling and quality control of the project makes G-SIM a reproducible, extendible archive and can be utilised for many purposes in large-scale hydrology. Some potential applications include the identification of observational trends in hydrological extremes, the assessment of climate change impacts on streamflow regimes, and the validation of global hydrological models.

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

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

. 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

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

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.

Short-term ensemble streamflow forecasting using operationally-produced single-valued streamflow forecasts - A Hydrologic Model Output Statistics (HMOS) approach

NASA Astrophysics Data System (ADS)

Regonda, Satish Kumar; Seo, Dong-Jun; Lawrence, Bill; Brown, James D.; Demargne, Julie

2013-08-01

We present a statistical procedure for generating short-term ensemble streamflow forecasts from single-valued, or deterministic, streamflow forecasts produced operationally by the U.S. National Weather Service (NWS) River Forecast Centers (RFCs). The resulting ensemble streamflow forecast provides an estimate of the predictive uncertainty associated with the single-valued forecast to support risk-based decision making by the forecasters and by the users of the forecast products, such as emergency managers. Forced by single-valued quantitative precipitation and temperature forecasts (QPF, QTF), the single-valued streamflow forecasts are produced at a 6-h time step nominally out to 5 days into the future. The single-valued streamflow forecasts reflect various run-time modifications, or "manual data assimilation", applied by the human forecasters in an attempt to reduce error from various sources in the end-to-end forecast process. The proposed procedure generates ensemble traces of streamflow from a parsimonious approximation of the conditional multivariate probability distribution of future streamflow given the single-valued streamflow forecast, QPF, and the most recent streamflow observation. For parameter estimation and evaluation, we used a multiyear archive of the single-valued river stage forecast produced operationally by the NWS Arkansas-Red River Basin River Forecast Center (ABRFC) in Tulsa, Oklahoma. As a by-product of parameter estimation, the procedure provides a categorical assessment of the effective lead time of the operational hydrologic forecasts for different QPF and forecast flow conditions. To evaluate the procedure, we carried out hindcasting experiments in dependent and cross-validation modes. The results indicate that the short-term streamflow ensemble hindcasts generated from the procedure are generally reliable within the effective lead time of the single-valued forecasts and well capture the skill of the single-valued forecasts. For smaller

Predicting Hydrological Drought: Relative Contributions of Soil Moisture and Snow Information to Seasonal Streamflow Prediction Skill

NASA Technical Reports Server (NTRS)

Koster, R.; Mahanama, S.; Livneh, B.; Lettenmaier, D.; Reichle, R.

2011-01-01

in this study we examine how knowledge of mid-winter snow accumulation and soil moisture conditions contribute to our ability to predict streamflow months in advance. A first "synthetic truth" analysis focuses on a series of numerical experiments with multiple sophisticated land surface models driven with a dataset of observations-based meteorological forcing spanning multiple decades and covering the continental United States. Snowpack information by itself obviously contributes to the skill attained in streamflow prediction, particularly in the mountainous west. The isolated contribution of soil moisture information, however, is found to be large and significant in many areas, particularly in the west but also in region surrounding the Great Lakes. The results are supported by a supplemental, observations-based analysis using (naturalized) March-July streamflow measurements covering much of the western U.S. Additional forecast experiments using start dates that span the year indicate a strong seasonality in the skill contributions; soil moisture information, for example, contributes to kill at much longer leads for forecasts issued in winter than for those issued in summer.

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

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.

Streamflow trends in the Spokane River and tributaries, Spokane Valley/Rathdrum Prairie, Idaho and Washington

USGS Publications Warehouse

Hortness, Jon E.; Covert, John J.

2005-01-01

A clear understanding of the aquifer and river dynamics within the Spokane Valley/Rathdrum Prairie is essential in making proper management decisions concerning ground-water and surface-water appropriations. Management of the Spokane Valley/Rathdrum Prairie aquifer is complicated because of interstate, multi-jurisdictional responsibilities, and by the interaction between ground water and surface water. Kendall?s tau trend analyses were completed on monthly mean (July through December) and annual 7-day low streamflow data for the period 1968?2002 from gaging stations located within the Spokane Valley/Rathdrum Prairie. The analyses detected trends of decreasing monthly mean streamflow at the following gaging stations: Spokane River near Post Falls, Idaho (August and September); Spokane River at Spokane, Washington (September); and Little Spokane River at Dartford, Washington (September and October); and decreasing annual 7-day low streamflows at the following gaging stations: Spokane River near Post Falls, Idaho and Spokane River at Spokane, Washington. Limited analyses of lake-level, precipitation, tributary inflow, temperature, and water-use data provided little insight as to the reason for the decreasing trends in streamflow. A net gain in streamflow occurs between the gaging stations Spokane River near Post Falls, Idaho and Spokane River at Spokane, Washington. Significant streamflow losses occur between the gaging stations Spokane River near Post Falls, Idaho and Spokane River at Greenacres, Washington; most, if not all, of the gains occur downstream from the Greenacres gaging station. Trends of decreasing net streamflow gains in the Spokane River between the near Post Falls and at Spokane gaging stations were detected for the months of September, October, and November.

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

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

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

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

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.

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.

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.

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

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.

Estimates of streamflow characteristics for selected small streams, Baker River basin, Washington

USGS Publications Warehouse

Williams, John R.

1987-01-01

Regression equations were used to estimate streamflow characteristics at eight ungaged sites on small streams in the Baker River basin in the North Cascade Mountains, Washington, that could be suitable for run-of-the-river hydropower development. The regression equations were obtained by relating known streamflow characteristics at 25 gaging stations in nearby basins to several physical and climatic variables that could be easily measured in gaged or ungaged basins. The known streamflow characteristics were mean annual flows, 1-, 3-, and 7-day low flows and high flows, mean monthly flows, and flow duration. Drainage area and mean annual precipitation were not the most significant variables in all the regression equations. Variance in the low flows and the summer mean monthly flows was reduced by including an index of glacierized area within the basin as a third variable. Standard errors of estimate of the regression equations ranged from 25 to 88%, and the largest errors were associated with the low flow characteristics. Discharge measurements made at the eight sites near midmonth each month during 1981 were used to estimate monthly mean flows at the sites for that period. These measurements also were correlated with concurrent daily mean flows from eight operating gaging stations. The correlations provided estimates of mean monthly flows that compared reasonably well with those estimated by the regression analyses. (Author 's abstract)

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.

Estimation of streamflow for selected sites on the Carson and Truckee rivers in California and Nevada, 1944-80

USGS Publications Warehouse

Blodgett, J.C.; Oltmann, R.N.; Poeschel, K.R.

1984-01-01

Daily mean and monthly discharges were estimated for 10 sites on the Carson and Truckee Rivers for periods of incomplete records and for tributary sites affected by reservoir regulation. On the basis of the hydrologic characteristics, stream-flow data for a water year were grouped by month or season for subsequent regression analysis. In most cases, simple linear regressions adequately defined a relation of streamflow between gaging stations, but in some instances a nonlinear relation for several months of the water year was derived. Statistical data are presented to indicate the reliability of the estimated streamflow data. Records of discharges including historical and estimated data for the gaging stations for the water years 1944-80 are presented. (USGS)

Techniques for estimating streamflow characteristics in the Eastern and Interior coal provinces of the United States

USGS Publications Warehouse

Wetzel, Kim L.; Bettandorff, J.M.

1986-01-01

Techniques are presented for estimating various streamflow characteristics, such as peak flows, mean monthly and annual flows, flow durations, and flow volumes, at ungaged sites on unregulated streams in the Eastern Coal region. Streamflow data and basin characteristics for 629 gaging stations were used to develop multiple-linear-regression equations. Separate equations were developed for the Eastern and Interior Coal Provinces. Drainage area is an independent variable common to all equations. Other variables needed, depending on the streamflow characteristic, are mean annual precipitation, mean basin elevation, main channel length, basin storage, main channel slope, and forest cover. A ratio of the observed 50- to 90-percent flow durations was used in the development of relations to estimate low-flow frequencies in the Eastern Coal Province. Relations to estimate low flows in the Interior Coal Province are not presented because the standard errors were greater than 0.7500 log units and were considered to be of poor reliability.

An environmental streamflow assessment for the Santiam River basin, Oregon

USGS Publications Warehouse

Risley, John C.; Wallick, J. Rose; Mangano, Joseph F.; Jones, Krista L.

2012-01-01

The Santiam River is a tributary of the Willamette River in northwestern Oregon and drains an area of 1,810 square miles. The U.S. Army Corps of Engineers (USACE) operates four dams in the basin, which are used primarily for flood control, hydropower production, recreation, and water-quality improvement. The Detroit and Big Cliff Dams were constructed in 1953 on the North Santiam River. The Green Peter and Foster Dams were completed in 1967 on the South Santiam River. The impacts of the structures have included a decrease in the frequency and magnitude of floods and an increase in low flows. For three North Santiam River reaches, the median of annual 1-day maximum streamflows decreased 42–50 percent because of regulated streamflow conditions. Likewise, for three reaches in the South Santiam River basin, the median of annual 1-day maximum streamflows decreased 39–52 percent because of regulation. In contrast to their effect on high flows, the dams increased low flows. The median of annual 7-day minimum flows in six of the seven study reaches increased under regulated streamflow conditions between 60 and 334 percent. On a seasonal basis, median monthly streamflows decreased from February to May and increased from September to January in all the reaches. However, the magnitude of these impacts usually decreased farther downstream from dams because of cumulative inflow from unregulated tributaries and groundwater entering the North, South, and main-stem Santiam Rivers below the dams. A Wilcox rank-sum test of monthly precipitation data from Salem, Oregon, and Waterloo, Oregon, found no significant difference between the pre-and post-dam periods, which suggests that the construction and operation of the dams since the 1950s and 1960s are a primary cause of alterations to the Santiam River basin streamflow regime. In addition to the streamflow analysis, this report provides a geomorphic characterization of the Santiam River basin and the associated conceptual

Streamflow characteristics for selected stations in and near the Grand Mesa, Uncompahgre, and Gunnison National Forests, southwestern Colorado

USGS Publications Warehouse

Kuhn, Gerhard

2002-01-01

The U.S Geological Survey, in cooperation with the Grand Mesa, Uncompahgre, and Gunnison National Forests, began a study in 2000 to develop selected streamflow characteristics for 60 streamflow-gaging stations in and near the Grand Mesa, Uncompahgre, and Gunnison National Forests. The study area is located in southwestern Colorado within the Gunnison River, Dolores River, and Plateau Creek Basins, which are tributaries of the Colorado River. In addition to presenting the compiled daily, monthly, and annual discharge data for the 60 stations, the report presents tabular and graphical results for the following computed streamflow characteristics: (1) Instantaneous peak-flow frequency; (2) flow duration for daily mean discharges on an annual (water year) basis and on a monthly basis, and flow duration for the annual and monthly mean discharges; (3) low-flow and high-flow frequency of daily mean discharges for periods of 1, 3, 7, 15, 30, 60, 120, and 183 consecutive days; and (4) annual and monthly mean and median discharges for each year and month of record, and frequency of the annual and monthly mean and median discharges. All discharge data and results from the streamflow-characteristics analyses are presented in Microsoft Excel workbooks on the enclosed CD-ROM.

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

How far downstream do dams impact streamflow?

NASA Astrophysics Data System (ADS)

Troy, T.

2017-12-01

Water infrastructure can be a double-edged sword. For example, dams can provide significant flood protection and stable water supplies, but they negatively impact river ecosystems. As the United States enters an era of dam decommissioning instead of dam building, it raises the question of how far downstream dams provide protection against flood peaks and sustaining environmental flows. This study uses USGS streamflow observations, the National Inventory of Dams, and VIC-modeled streamflow as a proxy for naturalized streamflow to evaluate the scale at which dams impact a variety of hydrologic signatures such as flood return period flows, streamflow variability, and low flows. Results over the Delaware River show that the impact of dams quickly dissipates as one moves downstream, but this is due to the basin's characteristics. This analysis is performed over the contiguous United States, quantifying the length scale of impact as a function of dam capacity, position on the river network, and the hydroclimatology.

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

The Global Streamflow Indices and Metadata Archive (GSIM) - Part 2: Quality control, time-series indices and homogeneity assessment

NASA Astrophysics Data System (ADS)

Gudmundsson, Lukas; Do, Hong Xuan; Leonard, Michael; Westra, Seth

2018-04-01

This is Part 2 of a two-paper series presenting the Global Streamflow Indices and Metadata Archive (GSIM), which is a collection of daily streamflow observations at more than 30 000 stations around the world. While Part 1 (Do et al., 2018a) describes the data collection process as well as the generation of auxiliary catchment data (e.g. catchment boundary, land cover, mean climate), Part 2 introduces a set of quality controlled time-series indices representing (i) the water balance, (ii) the seasonal cycle, (iii) low flows and (iv) floods. To this end we first consider the quality of individual daily records using a combination of quality flags from data providers and automated screening methods. Subsequently, streamflow time-series indices are computed for yearly, seasonal and monthly resolution. The paper provides a generalized assessment of the homogeneity of all generated streamflow time-series indices, which can be used to select time series that are suitable for a specific task. The newly generated global set of streamflow time-series indices is made freely available with an digital object identifier at https://doi.pangaea.de/10.1594/PANGAEA.887470 and is expected to foster global freshwater research, by acting as a ground truth for model validation or as a basis for assessing the role of human impacts on the terrestrial water cycle. It is hoped that a renewed interest in streamflow data at the global scale will foster efforts in the systematic assessment of data quality and provide momentum to overcome administrative barriers that lead to inconsistencies in global collections of relevant hydrological observations.

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.

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.

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.

Stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural streamflow

USGS Publications Warehouse

Kolars, Kelsey A.; Vecchia, Aldo V.; Ryberg, Karen R.

2016-02-24

-balance model was developed for simulating monthly natural (unregulated) mean streamflow based on precipitation, temperature, and potential evapotranspiration at select streamflow-gaging stations. The model was calibrated using streamflow data from the U.S. Geological Survey and Environment Canada, along with natural (unregulated) streamflow data from the U.S. Army Corps of Engineers. Correlation coefficients between simulated and natural (unregulated) flows generally were high (greater than 0.8), and the seasonal means and standard deviations of the simulated flows closely matched the means and standard deviations of the natural (unregulated) flows. After calibrating the model for a monthly time step, monthly streamflow for each subbasin was disaggregated into three values per month, or an approximately 10-day time step, and a separate routing model was developed for simulating 10-day streamflow for downstream gages.The stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration was combined with the water-balance model to simulate potential future sequences of 10-day mean streamflow for each of the streamflow-gaging station locations. Flood risk, as determined by equilibrium flow-frequency distributions for the dry (1912–69) and wet (1970–2011) climate states, was considerably higher for the wet state compared to the dry state. Future flood risk will remain high until the wet climate state ends, and for several years after that, because there may be a long lag-time between the return of drier conditions and the onset of a lower soil-moisture storage equilibrium.

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.

Stream gage descriptions and streamflow statistics for sites in the Tigris River and Euphrates River Basins, Iraq

USGS Publications Warehouse

Saleh, Dina K.

2010-01-01

Statistical summaries of streamflow data for all long-term streamflow-gaging stations in the Tigris River and Euphrates River Basins in Iraq are presented in this report. The summaries for each streamflow-gaging station include (1) a station description, (2) a graph showing annual mean discharge for the period of record, (3) a table of extremes and statistics for monthly and annual mean discharge, (4) a graph showing monthly maximum, minimum, and mean discharge, (5) a table of monthly and annual mean discharges for the period of record, (6) a graph showing annual flow duration, (7) a table of monthly and annual flow duration, (8) a table of high-flow frequency data (maximum mean discharge for 3-, 7-, 15-, and 30-day periods for selected exceedance probabilities), and (9) a table of low-flow frequency data (minimum mean discharge for 3-, 7-, 15-, 30-, 60-, 90-, and 183-day periods for selected non-exceedance probabilities).

Variance analysis of forecasted streamflow maxima in a wet temperate climate

NASA Astrophysics Data System (ADS)

Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.

2018-05-01

Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.

BOREAS HYD-9 Streamflow Data

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Knapp, David E. (Editor); Kouwen, Nick; Soulis, Ric; Jenkinson, Wayne; Graham, Allyson; Neff, Todd; Smith, David E. (Technical Monitor)

2000-01-01

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-9 team collected several data sets containing precipitation and streamflow measurements over the BOREAS study areas. These streamflow data were collected by the HYD-09 science team to support its research into meltwater supply to the soil during the spring melt period. These data were also collected for HYD-09's research into the evolution of soil moisture, evaporation, and runoff from the end of the snowmelt period through freeze up. Data were collected in the BOREAS Southern Study Area (SSA) and Northern Study Area (NSA) from April until October in 1994, 1995, and 1996. Gauges southwest-1 and northwest-1 were operated year-round; however, data may not be available for both gauges for all three years. The data are available in tabular ASCII files. The HYD-09 streamflow data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

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

Interaction between stream temperature, streamflow, and groundwater exchanges in alpine streams

USGS Publications Warehouse

Constantz, James E.

1998-01-01

Four alpine streams were monitored to continuously collect stream temperature and streamflow for periods ranging from a week to a year. In a small stream in the Colorado Rockies, diurnal variations in both stream temperature and streamflow were significantly greater in losing reaches than in gaining reaches, with minimum streamflow losses occurring early in the day and maximum losses occurring early in the evening. Using measured stream temperature changes, diurnal streambed infiltration rates were predicted to increase as much as 35% during the day (based on a heat and water transport groundwater model), while the measured increase in streamflow loss was 40%. For two large streams in the Sierra Nevada Mountains, annual stream temperature variations ranged from 0° to 25°C. In summer months, diurnal stream temperature variations were 30–40% of annual stream temperature variations, owing to reduced streamflows and increased atmospheric heating. Previous reports document that one Sierra stream site generally gains groundwater during low flows, while the second Sierra stream site may lose water during low flows. For August the diurnal streamflow variation was 11% at the gaining stream site and 30% at the losing stream site. On the basis of measured diurnal stream temperature variations, streambed infiltration rates were predicted to vary diurnally as much as 20% at the losing stream site. Analysis of results suggests that evapotranspiration losses determined diurnal streamflow variations in the gaining reaches, while in the losing reaches, evapotranspiration losses were compounded by diurnal variations in streambed infiltration. Diurnal variations in stream temperature were reduced in the gaining reaches as a result of discharging groundwater of relatively constant temperature. For the Sierra sites, comparison of results with those from a small tributary demonstrated that stream temperature patterns were useful in delineating discharges of bank storage following

ESTIMATING STREAMFLOW AND ASSOCIATED HYDRAULIC GEOMETRY, THE MID-ATLANTIC REGION, USA

EPA Science Inventory

Methods to estimate streamflow and channel hydraulic geometry were developed for ungaged streams in the Mid-Atlantic Region. Observed mean annual streamflow and associated hydraulic geometry data from 75 gaging stations located in the Appalachian Plateau, the Ridge and Valley, an...

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.

Streamflow characteristics of streams in southeastern Afghanistan

USGS Publications Warehouse

Vining, Kevin C.

2010-01-01

Statistical summaries of streamflow data for all historical streamgaging stations that have available data in the southeastern Afghanistan provinces of Ghazni, Khost, Logar, Paktya, and Wardak, and a portion of Kabul Province are presented in this report. The summaries for each streamgaging station include a station desciption, table of statistics of monthly and annual mean discharges, table of monthly and annual flow duration, table of probability of occurrence of annual high discharges, table of probability of occurrence of annual low discharges, table of annual peak discharge and corresponding gage height for the period of record, and table of monthly and annual mean discharges for the period of record.

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

Benchmarking ensemble streamflow prediction skill in the UK

NASA Astrophysics Data System (ADS)

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

2018-03-01

Skilful hydrological forecasts at sub-seasonal to seasonal lead times would be extremely beneficial for decision-making in water resources management, hydropower operations, and agriculture, especially during drought conditions. Ensemble streamflow prediction (ESP) is a well-established method for generating an ensemble of streamflow forecasts in the absence of skilful future meteorological predictions, instead using initial hydrologic conditions (IHCs), such as soil moisture, groundwater, and snow, as the source of skill. We benchmark when and where the ESP method is skilful across a diverse sample of 314 catchments in the UK and explore the relationship between catchment storage and ESP skill. The GR4J hydrological model was forced with historic climate sequences to produce a 51-member ensemble of streamflow hindcasts. We evaluated forecast skill seamlessly from lead times of 1 day to 12 months initialized at the first of each month over a 50-year hindcast period from 1965 to 2015. Results showed ESP was skilful against a climatology benchmark forecast in the majority of catchments across all lead times up to a year ahead, but the degree of skill was strongly conditional on lead time, forecast initialization month, and individual catchment location and storage properties. UK-wide mean ESP skill decayed exponentially as a function of lead time with continuous ranked probability skill scores across the year of 0.75, 0.20, and 0.11 for 1-day, 1-month, and 3-month lead times, respectively. However, skill was not uniform across all initialization months. For lead times up to 1 month, ESP skill was higher than average when initialized in summer and lower in winter months, whereas for longer seasonal and annual lead times skill was higher when initialized in autumn and winter months and lowest in spring. ESP was most skilful in the south and east of the UK, where slower responding catchments with higher soil moisture and groundwater storage are mainly located

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

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.

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

A comparison of methods to predict historical daily streamflow time series in the southeastern United States

USGS Publications Warehouse

Farmer, William H.; Archfield, Stacey A.; Over, Thomas M.; Hay, Lauren E.; LaFontaine, Jacob H.; Kiang, Julie E.

2015-01-01

Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water. Streamgages cannot be installed at every location where streamflow information is needed. As part of its National Water Census, the U.S. Geological Survey is planning to provide streamflow predictions for ungaged locations. In order to predict streamflow at a useful spatial and temporal resolution throughout the Nation, efficient methods need to be selected. This report examines several methods used for streamflow prediction in ungaged basins to determine the best methods for regional and national implementation. A pilot area in the southeastern United States was selected to apply 19 different streamflow prediction methods and evaluate each method by a wide set of performance metrics. Through these comparisons, two methods emerged as the most generally accurate streamflow prediction methods: the nearest-neighbor implementations of nonlinear spatial interpolation using flow duration curves (NN-QPPQ) and standardizing logarithms of streamflow by monthly means and standard deviations (NN-SMS12L). It was nearly impossible to distinguish between these two methods in terms of performance. Furthermore, neither of these methods requires significantly more parameterization in order to be applied: NN-SMS12L requires 24 regional regressions—12 for monthly means and 12 for monthly standard deviations. NN-QPPQ, in the application described in this study, required 27 regressions of particular quantiles along the flow duration curve. Despite this finding, the results suggest that an optimal streamflow prediction method depends on the intended application. Some methods are stronger overall, while some methods may be better at predicting particular statistics. The methods of analysis presented here reflect a possible framework for continued analysis and comprehensive multiple comparisons of methods of prediction in ungaged basins (PUB

Shifts in historical streamflow extremes in the Colorado River Basin

DOE PAGES

Solander, Kurt C.; Bennett, Katrina Eleanor; Middleton, Richard Stephen

2017-07-10

The global phenomenon of climate change-induced shifts in precipitation leading to "wet regions getting wetter" and "dry regions getting drier" has been widely studied. However, the propagation of these changes in atmospheric moisture within stream channels is not a direct relationship due to differences in the timing of how changing precipitation patterns interact with various land surfaces. Streamflow is of particular interest in the Colorado River Basin (CRB) due to the region’s rapidly growing population, projected temperature increases that are expected to be higher than elsewhere in the contiguous United States, and subsequent climate-driven disturbances including drought, vegetation mortality, andmore » wildfire, which makes the region more vulnerable to changes in hydrologic extremes. Here in this study, we determine how streamflow extremes have shifted in the CRB using two statistical methods—the Mann-Kendall trend detection analysis and Generalized Extreme Value (GEV) theorem. We evaluate these changes in the context of key flow metrics that include high and low flow percentiles, maximum and minimum 7-day flows, and the center timing of streamflow using historical gage records representative of natural flows. Monthly results indicate declines of up to 41% for high and low flows during the June to July peak runoff season, while increases of up to 24% were observed earlier from March to April. Finally, our results highlight a key threshold elevation and latitude of 2300 m and 39° North, respectively, where there is a distinct shift in the trend. The spatiotemporal patterns observed are indicative of changing snowmelt patterns as a primary cause of the shifts. Identification of how this change varies spatially has consequences for improved land management strategies, as specific regions most vulnerable to threats can be prioritized for mitigation or adaptation as the climate warms.« less

Shifts in historical streamflow extremes in the Colorado River Basin

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

Solander, Kurt C.; Bennett, Katrina Eleanor; Middleton, Richard Stephen

The global phenomenon of climate change-induced shifts in precipitation leading to "wet regions getting wetter" and "dry regions getting drier" has been widely studied. However, the propagation of these changes in atmospheric moisture within stream channels is not a direct relationship due to differences in the timing of how changing precipitation patterns interact with various land surfaces. Streamflow is of particular interest in the Colorado River Basin (CRB) due to the region’s rapidly growing population, projected temperature increases that are expected to be higher than elsewhere in the contiguous United States, and subsequent climate-driven disturbances including drought, vegetation mortality, andmore » wildfire, which makes the region more vulnerable to changes in hydrologic extremes. Here in this study, we determine how streamflow extremes have shifted in the CRB using two statistical methods—the Mann-Kendall trend detection analysis and Generalized Extreme Value (GEV) theorem. We evaluate these changes in the context of key flow metrics that include high and low flow percentiles, maximum and minimum 7-day flows, and the center timing of streamflow using historical gage records representative of natural flows. Monthly results indicate declines of up to 41% for high and low flows during the June to July peak runoff season, while increases of up to 24% were observed earlier from March to April. Finally, our results highlight a key threshold elevation and latitude of 2300 m and 39° North, respectively, where there is a distinct shift in the trend. The spatiotemporal patterns observed are indicative of changing snowmelt patterns as a primary cause of the shifts. Identification of how this change varies spatially has consequences for improved land management strategies, as specific regions most vulnerable to threats can be prioritized for mitigation or adaptation as the climate warms.« less

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.

Uncertainties in Forecasting Streamflow using Entropy Theory

NASA Astrophysics Data System (ADS)

Cui, H.; Singh, V. P.

2017-12-01

Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.

HYDRORECESSION: A toolbox for streamflow recession analysis

NASA Astrophysics Data System (ADS)

Arciniega, S.

2015-12-01

Streamflow recession curves are hydrological signatures allowing to study the relationship between groundwater storage and baseflow and/or low flows at the catchment scale. Recent studies have showed that streamflow recession analysis can be quite sensitive to the combination of different models, extraction techniques and parameter estimation methods. In order to better characterize streamflow recession curves, new methodologies combining multiple approaches have been recommended. The HYDRORECESSION toolbox, presented here, is a Matlab graphical user interface developed to analyse streamflow recession time series with the support of different tools allowing to parameterize linear and nonlinear storage-outflow relationships through four of the most useful recession models (Maillet, Boussinesq, Coutagne and Wittenberg). The toolbox includes four parameter-fitting techniques (linear regression, lower envelope, data binning and mean squared error) and three different methods to extract hydrograph recessions segments (Vogel, Brutsaert and Aksoy). In addition, the toolbox has a module that separates the baseflow component from the observed hydrograph using the inverse reservoir algorithm. Potential applications provided by HYDRORECESSION include model parameter analysis, hydrological regionalization and classification, baseflow index estimates, catchment-scale recharge and low-flows modelling, among others. HYDRORECESSION is freely available for non-commercial and academic purposes.

Potential effects of climate change on streamflow, eastern and western slopes of the Sierra Nevada, California and Nevada

USGS Publications Warehouse

Jeton, A.E.; Dettinger, M.D.; Smith, J. LaRue

1996-01-01

Precipitation-runoff models of the East Fork Carson and North Fork American Rivers were developed and calibrated for use in evaluating the sensitivity of streamflow in the north-central Sierra Nevada to climate change. The East Fork Carson River drains part of the rain-shadowed, eastern slope of the Sierra Nevada and is generally higher than the North Fork American River, which drains the wetter, western slope. First, a geographic information system was developed to describe the spatial variability of basin characteristics and to help estimate model parameters. The result was a partitioning of each basin into noncontiguous, but hydrologically uniform, land units. Hydrologic descriptions of these units were developed and the Precipitation- Runoff Modeling System (PRMS) was used to simulate water and energy balances for each unit in response to daily weather conditions. The models were calibrated and verified using historical streamflows over 22-year (Carson River) and 42-year (American River) periods. Simulated annual streamflow errors average plus 10 percent of the observed flow for the East Fork Carson River basin and plus 15 percent for the North Fork American River basin. Interannual variability is well simulated overall, but, at daily scales, wet periods are simulated more accurately than drier periods. The simulated water budgets for the two basins are significantly different in seasonality of streamflow, sublimation, evapotranspiration, and snowmelt. The simulations indicate that differences in snowpack and snowmelt timing can play pervasive roles in determining the sensitivity of water resources to climate change, in terms of both resource availability and amount. The calibrated models were driven by more than 25 hypothetical climate-change scenarios, each 100 years long. The scenarios were synthesized and spatially disaggregated by methods designed to preserve realistic daily, monthly, annual, and spatial statistics. Simulated streamflow timing was not very

Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions

USGS Publications Warehouse

Austin, Samuel H.; Nelms, David L.

2017-01-01

Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5-11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best-performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid-Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.

Trends in Streamflow Characteristics at Long-Term Gaging Stations, Hawaii

USGS Publications Warehouse

Oki, Delwyn S.

2004-01-01

The surface-water resources of Hawaii have significant cultural, aesthetic, ecologic, and economic importance. Proper management of the surface-water resources of the State requires an understanding of the long- and short-term variability in streamflow characteristics that may occur. The U.S. Geological Survey maintains a network of stream-gaging stations in Hawaii, including a number of stations with long-term streamflow records that can be used to evaluate long-term trends and short-term variability in flow characteristics. The overall objective of this study is to obtain a better understanding of long-term trends and variations in streamflow on the islands of Hawaii, Maui, Molokai, Oahu, and Kauai, where long-term stream-gaging stations exist. This study includes (1) an analysis of long-term trends in flows (both total flow and estimated base flow) at 16 stream-gaging stations, (2) a description of patterns in trends within the State, and (3) discussion of possible regional factors (including rainfall) that are related to the observed trends and variations. Results of this study indicate the following: 1. From 1913 to 2002 base flows generally decreased in streams for which data are available, and this trend is consistent with the long-term downward trend in annual rainfall over much of the State during that period. 2. Monthly mean base flows generally were above the long-term average from 1913 to the early 1940s and below average after the early 1940s to 2002, and this pattern is consistent with the detected downward trends in base flows from 1913 to 2002. 3. Long-term downward trends in base flows of streams may indicate a reduction in ground-water discharge to streams caused by a long-term decrease in ground-water storage and recharge. 4. From 1973 to 2002, trends in streamflow were spatially variable (up in some streams and down in others) and, with a few exceptions, generally were not statistically significant. 5. Short-term variability in streamflow is

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)

Statistical summaries of selected Iowa streamflow data through September 2013

USGS Publications Warehouse

Eash, David A.; O'Shea, Padraic S.; Weber, Jared R.; Nguyen, Kevin T.; Montgomery, Nicholas L.; Simonson, Adrian J.

2016-01-04

Statistical summaries of streamflow data collected at 184 streamgages in Iowa are presented in this report. All streamgages included for analysis have at least 10 years of continuous record collected before or through September 2013. This report is an update to two previously published reports that presented statistical summaries of selected Iowa streamflow data through September 1988 and September 1996. The statistical summaries include (1) monthly and annual flow durations, (2) annual exceedance probabilities of instantaneous peak discharges (flood frequencies), (3) annual exceedance probabilities of high discharges, and (4) annual nonexceedance probabilities of low discharges and seasonal low discharges. Also presented for each streamgage are graphs of the annual mean discharges, mean annual mean discharges, 50-percent annual flow-duration discharges (median flows), harmonic mean flows, mean daily mean discharges, and flow-duration curves. Two sets of statistical summaries are presented for each streamgage, which include (1) long-term statistics for the entire period of streamflow record and (2) recent-term statistics for or during the 30-year period of record from 1984 to 2013. The recent-term statistics are only calculated for streamgages with streamflow records pre-dating the 1984 water year and with at least 10 years of record during 1984–2013. The streamflow statistics in this report are not adjusted for the effects of water use; although some of this water is used consumptively, most of it is returned to the streams.

Effect of reforestation on streamflow in central New York

USGS Publications Warehouse

Schneider, William Joseph; Ayer, Gordon Roundy

1961-01-01

Hydrologic data have been collected since 1932 in central New York State to determine the effect of reforestation on streamflow. Data are available for three small partly reforested areas and for one nonreforested control area. From 35 to 58 percent of the 3 areas were reforested, mostly with species of pine and spruce. The trees were allowed to grow without thinning or cutting, and by 1958 these reforested areas had developed into dense coniferous woodlots. Intensive statistical analyses of the data from the four study areas were made in 1958. Analyses were made for three hydrologic periods: the dormant season represented by the 6-month period ending April 30, the growing season represented by the 6-month period ending October 31, and the year represented by the 12-month period ending April 30. Analyses of the hydrologic data using multiple correlation with time as a variable and analyses of covariance between early and late periods of record indicated that several significant changes had occurred in the streamflow from the partly reforested study areas. Based on correlation with precipitation, total runoff for the dormant season from the 3 study areas was reduced by annual rates of 0.17 to 0.29 inches per year. Based on correlations with streamflow from a control area, total runoff from the partly reforested Shackham Brook area was reduced by average rates of 0.14 inches per growing season, 0.23 inches per dormant season, and 0.36 inches per hydrologic year. Peak discharges on Shackham Brook during the dormant season were reduced by 1958 by an average of 41 percent for the season, with reductions ranging from an average of 66 percent for November to an average of 16 percent for April. No significant changes were found in the peak discharges for the growing season, rates of base-flow recession, volumes of direct runoff, or annual low flows of streams in the three partly reforested areas. The significant reductions in total runoff are attributed to increases in

Moving Beyond Streamflow Observations: Lessons From A Multi-Objective Calibration Experiment in the Mississippi Basin

NASA Astrophysics Data System (ADS)

Koppa, A.; Gebremichael, M.; Yeh, W. W. G.

2017-12-01

Calibrating hydrologic models in large catchments using a sparse network of streamflow gauges adversely affects the spatial and temporal accuracy of other water balance components which are important for climate-change, land-use and drought studies. This study combines remote sensing data and the concept of Pareto-Optimality to address the following questions: 1) What is the impact of streamflow (SF) calibration on the spatio-temporal accuracy of Evapotranspiration (ET), near-surface Soil Moisture (SM) and Total Water Storage (TWS)? 2) What is the best combination of fluxes that can be used to calibrate complex hydrological models such that both the accuracy of streamflow and the spatio-temporal accuracy of ET, SM and TWS is preserved? The study area is the Mississippi Basin in the United States (encompassing HUC-2 regions 5,6,7,9,10 and 11). 2003 and 2004, two climatologically average years are chosen for calibration and validation of the Noah-MP hydrologic model. Remotely sensed ET data is sourced from GLEAM, SM from ESA-CCI and TWS from GRACE. Single objective calibration is carried out using DDS Algorithm. For Multi objective calibration PA-DDS is used. First, the Noah-MP model is calibrated using a single objective function (Minimize Mean Square Error) for the outflow from the 6 HUC-2 sub-basins for 2003. Spatial correlograms are used to compare the spatial structure of ET, SM and TWS between the model and the remote sensing data. Spatial maps of RMSE and Mean Error are used to quantify the impact of calibrating streamflow on the accuracy of ET, SM and TWS estimates. Next, a multi-objective calibration experiment is setup to determine the pareto optimal parameter sets (pareto front) for the following cases - 1) SF and ET, 2) SF and SM, 3) SF and TWS, 4) SF, ET and SM, 5) SF, ET and TWS, 6) SF, SM and TWS, 7) SF, ET, SM and TWS. The best combination of fluxes that provides the optimal trade-off between accurate streamflow and preserving the spatio

Paleoflood investigations to improve peak-streamflow regional-regression equations for natural streamflow in eastern Colorado, 2015

USGS Publications Warehouse

Kohn, Michael S.; Stevens, Michael R.; Harden, Tessa M.; Godaire, Jeanne E.; Klinger, Ralph E.; Mommandi, Amanullah

2016-09-09

The U.S. Geological Survey (USGS), in cooperation with the Colorado Department of Transportation, developed regional-regression equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, 0.2-percent annual exceedance-probability discharge (AEPD) for natural streamflow in eastern Colorado. A total of 188 streamgages, consisting of 6,536 years of record and a mean of approximately 35 years of record per streamgage, were used to develop the peak-streamflow regional-regression equations. The estimated AEPDs for each streamgage were computed using the USGS software program PeakFQ. The AEPDs were determined using systematic data through water year 2013. Based on previous studies conducted in Colorado and neighboring States and on the availability of data, 72 characteristics (57 basin and 15 climatic characteristics) were evaluated as candidate explanatory variables in the regression analysis. Paleoflood and non-exceedance bound ages were established based on reconnaissance-level methods. Multiple lines of evidence were used at each streamgage to arrive at a conclusion (age estimate) to add a higher degree of certainty to reconnaissance-level estimates. Paleoflood or nonexceedance bound evidence was documented at 41 streamgages, and 3 streamgages had previously collected paleoflood data.To determine the peak discharge of a paleoflood or non-exceedanc bound, two different hydraulic models were used.The mean standard error of prediction (SEP) for all 8 AEPDs was reduced approximately 25 percent compared to the previous flood-frequency study. For paleoflood data to be effective in reducing the SEP in eastern Colorado, a larger ratio than 44 of 188 (23 percent) streamgages would need paleoflood data and that paleoflood data would need to increase the record length by more than 25 years for the 1-percent AEPD. The greatest reduction in SEP for the peak-streamflow regional-regression equations was observed when additional new basin characteristics were included in the peak-streamflow

Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq

NASA Astrophysics Data System (ADS)

Yaseen, Zaher Mundher; Jaafar, Othman; Deo, Ravinesh C.; Kisi, Ozgur; Adamowski, Jan; Quilty, John; El-Shafie, Ahmed

2016-11-01

Monthly stream-flow forecasting can yield important information for hydrological applications including sustainable design of rural and urban water management systems, optimization of water resource allocations, water use, pricing and water quality assessment, and agriculture and irrigation operations. The motivation for exploring and developing expert predictive models is an ongoing endeavor for hydrological applications. In this study, the potential of a relatively new data-driven method, namely the extreme learning machine (ELM) method, was explored for forecasting monthly stream-flow discharge rates in the Tigris River, Iraq. The ELM algorithm is a single-layer feedforward neural network (SLFNs) which randomly selects the input weights, hidden layer biases and analytically determines the output weights of the SLFNs. Based on the partial autocorrelation functions of historical stream-flow data, a set of five input combinations with lagged stream-flow values are employed to establish the best forecasting model. A comparative investigation is conducted to evaluate the performance of the ELM compared to other data-driven models: support vector regression (SVR) and generalized regression neural network (GRNN). The forecasting metrics defined as the correlation coefficient (r), Nash-Sutcliffe efficiency (ENS), Willmott's Index (WI), root-mean-square error (RMSE) and mean absolute error (MAE) computed between the observed and forecasted stream-flow data are employed to assess the ELM model's effectiveness. The results revealed that the ELM model outperformed the SVR and the GRNN models across a number of statistical measures. In quantitative terms, superiority of ELM over SVR and GRNN models was exhibited by ENS = 0.578, 0.378 and 0.144, r = 0.799, 0.761 and 0.468 and WI = 0.853, 0.802 and 0.689, respectively and the ELM model attained lower RMSE value by approximately 21.3% (relative to SVR) and by approximately 44.7% (relative to GRNN). Based on the findings of this

Surface waters of the Washita River basin in Oklahoma--magnitude, distribution, and quality of streamflow

USGS Publications Warehouse

Laine, L.L.

1958-01-01

Analysis of streamflow data shows that water supply in the Washita River basin is variable, ranging from substantial amounts and almost continuous flow in the Washita River in the lower end of the basin to somewhat limited and intermittent flow in the upper part of the basin. The total yield of the basin averages 1,557,000 acre-ft per year, of which somewhat less than 1.3 percent is contributed by headwater areas in Texas. The surface waters are generally of acceptable quality for drinking purposes, excellent for irrigation uses, and suitable for many industrial purposes. In Oklahoma the high amounts of runoff tend to occur in the spring months. High runoff may occur during any month in the year but, in general, the available streamflow is relatively small in the summer. Most tributary streams have little sustained base flow and many are dry at times each year. Because of the high variability in flow, development of storage will be necessary to attain maximum utilization of the available water supplies. This report gives the average discharge at most gaging stations and at several additional sites for the 16-year period October 1938 to September 1954, used as a standard period in this report. Data are also shown on water available at several gaging stations and other sites for a given percentage of the time during the 16-year standard period. For several gaging stations data are given on minimum discharges for periods of various length during the most critical periods of record. For all gaging stations a summary of available basic data on streamflow is presented on a monthly annual basis. For other sites at which discharge measurements have been made, a tabulation of observed discharge is given. (available as photostat copy only)

Improving the performance of streamflow forecasting model using data-preprocessing technique in Dungun River Basin

NASA Astrophysics Data System (ADS)

Khai Tiu, Ervin Shan; Huang, Yuk Feng; Ling, Lloyd

2018-03-01

An accurate streamflow forecasting model is important for the development of flood mitigation plan as to ensure sustainable development for a river basin. This study adopted Variational Mode Decomposition (VMD) data-preprocessing technique to process and denoise the rainfall data before putting into the Support Vector Machine (SVM) streamflow forecasting model in order to improve the performance of the selected model. Rainfall data and river water level data for the period of 1996-2016 were used for this purpose. Homogeneity tests (Standard Normal Homogeneity Test, the Buishand Range Test, the Pettitt Test and the Von Neumann Ratio Test) and normality tests (Shapiro-Wilk Test, Anderson-Darling Test, Lilliefors Test and Jarque-Bera Test) had been carried out on the rainfall series. Homogenous and non-normally distributed data were found in all the stations, respectively. From the recorded rainfall data, it was observed that Dungun River Basin possessed higher monthly rainfall from November to February, which was during the Northeast Monsoon. Thus, the monthly and seasonal rainfall series of this monsoon would be the main focus for this research as floods usually happen during the Northeast Monsoon period. The predicted water levels from SVM model were assessed with the observed water level using non-parametric statistical tests (Biased Method, Kendall's Tau B Test and Spearman's Rho Test).

Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010

USGS Publications Warehouse

Gazoorian, Christopher L.

2015-01-01

A graphical user interface, with an integrated spreadsheet summary report, has been developed to estimate and display the daily mean streamflows and statistics and to evaluate different water management or water withdrawal scenarios with the estimated monthly data. This package of regression equations, U.S. Geological Survey streamgage data, and spreadsheet application produces an interactive tool to estimate an unaltered daily streamflow hydrograph and streamflow statistics at ungaged sites in New York. Among other uses, the New York Streamflow Estimation Tool can assist water managers with permitting water withdrawals, implementing habitat protection, estimating contaminant loads, or determining the potential affect from chemical spills.

Analysing streamflow variability and water allocation for sustainable management of water resources in the semi-arid Karkheh river basin, Iran

NASA Astrophysics Data System (ADS)

Masih, Ilyas; Ahmad, Mobin-ud-Din; Uhlenbrook, Stefan; Turral, Hugh; Karimi, Poolad

This study provides a comprehensive spatio-temporal assessment of the surface water resources of the semi-arid Karkheh basin, Iran, and consequently enables decision makers to work towards a sustainable water development in that region. The analysis is based on the examination of statistical parameters, flow duration characteristics, base flow separation and trend analysis for which data of seven key gauging stations were used for the period of 1961-2001. Additionally, basin level water accounting was carried out for the water year 1993-94. The study shows that observed daily, monthly and annual streamflows are highly variable in space and time within the basin. The streamflows have not been changed significantly at annual scale, but few months have shown significant trends, most notably a decline during May and June and an increase during December and March. The major causes were related to changes in climate, land use and reservoir operations. The study concludes that the water allocations to different sectors were lower than the totally available resources during the study period. However, looking at the high variability of streamflows, changes in climate and land use and ongoing water resources development planning, it will be extremely difficult to meet the demands of all sectors in the future, particularly during dry years.

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

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.

Quantifying the relative contribution of climate and human impacts on streamflow at seasonal scale

NASA Astrophysics Data System (ADS)

Xin, Z.; Zhang, L.; Li, Y.; Zhang, C.

2017-12-01

Both climate change and human activities have induced changes to hydrology. The quantification of their impacts on streamflow is a challenge, especially at the seasonal scale due to seasonality of climate and human impacts, i.e., water use for irrigation and water storage and release due to reservoir operation. In this study, the decomposition method based on the Budyko hypothesis is extended to the seasonal scale and is used to quantify the climate and human impacts on annual and seasonal streamflow changes. The results are further compared and verified with those simulated by the hydrological method of abcd model. Data are split into two periods (1953-1974 and 1975-2005) to quantify the change. Three seasons, including wet, dry and irrigation seasons are defined by introducing the monthly aridity index. In general, results showed a satisfactory agreement between the Budyko decomposition method and abcd model. Both climate change and human activities were found to induce a decrease in streamflow at the annual scale, with 67% of the change contributed by human activities. At the seasonal scale, the human-induced contribution to the reduced stream flow was 64% and 73% for dry and wet seasons, respectively; whereas in the irrigation season, the impact of human activities on reducing the streamflow was more pronounced (180%) since the climate contributes to increased streamflow. In addition, the quantification results were analyzed for each month in the wet season to reveal the effects of intense precipitation and reservoir operation rules during flood season.

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.

Streamflow of 2016—Water year summary

USGS Publications Warehouse

Jian, Xiaodong; Wolock, David M.; Lins, Harry F.; Brady, Steven J.

2017-09-26

The maps and graphs in this summary describe national streamflow conditions for water year 2016 (October 1, 2015, to September 30, 2016) in the context of streamflow ranks relative to the 87-year period of 1930–2016, unless otherwise noted. The illustrations are based on observed data from the U.S. Geological Survey’s (USGS) National Streamflow Network. The period of 1930–2016 was used because the number of streamgages before 1930 was too small to provide representative data for computing statistics for most regions of the country.In the summary, reference is made to the term “runoff,” which is the depth to which a river basin, State, or other geographic area would be covered with water if all the streamflow within the area during a specified period was uniformly distributed on it. Runoff quantifies the magnitude of water flowing through the Nation’s rivers and streams in measurement units that can be compared from one area to another.In all the graphics, a rank of 1 indicates the highest flow of all years analyzed and 87 indicates the lowest flow of all years. Rankings of streamflow are grouped into much below normal, below normal, normal, above normal, and much above normal based on percentiles of flow (less than 10 percent, 10–24 percent, 25–75 percent, 76–90 percent, and greater than 90 percent, respectively). Some of the data used to produce the maps and graphs are provisional and subject to change.

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.

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

Streamflow response to increasing precipitation extremes altered by forest management

NASA Astrophysics Data System (ADS)

Kelly, Charlene N.; McGuire, Kevin J.; Miniat, Chelcy Ford; Vose, James M.

2016-04-01

Increases in extreme precipitation events of floods and droughts are expected to occur worldwide. The increase in extreme events will result in changes in streamflow that are expected to affect water availability for human consumption and aquatic ecosystem function. We present an analysis that may greatly improve current streamflow models by quantifying the impact of the interaction between forest management and precipitation. We use daily long-term data from paired watersheds that have undergone forest harvest or species conversion. We find that interactive effects of climate change, represented by changes in observed precipitation trends, and forest management regime, significantly alter expected streamflow most often during extreme events, ranging from a decrease of 59% to an increase of 40% in streamflow, depending upon management. Our results suggest that vegetation might be managed to compensate for hydrologic responses due to climate change to help mitigate effects of extreme changes in precipitation.

Understanding uncertainties in future Colorado River streamflow

USGS Publications Warehouse

Julie A. Vano,; Bradley Udall,; Cayan, Daniel; Jonathan T Overpeck,; Brekke, Levi D.; Das, Tapash; Hartmann, Holly C.; Hidalgo, Hugo G.; Hoerling, Martin P; McCabe, Gregory J.; Morino, Kiyomi; Webb, Robert S.; Werner, Kevin; Lettenmaier, Dennis P.

2014-01-01

The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamf low changes in the Colorado River all project annual declines, but the magnitude of the projected decreases range from less than 10% to 45% by the mid-twenty-first century. To understand these differences, we address the questions the management community has raised: Why is there such a wide range of projections of impacts of future climate change on Colorado River streamflow, and how should this uncertainty be interpreted? We identify four major sources of disparities among studies that arise from both methodological and model differences. In order of importance, these are differences in 1) the global climate models (GCMs) and emission scenarios used; 2) the ability of land surface and atmospheric models to simulate properly the high-elevation runoff source areas; 3) the sensitivities of land surface hydrology models to precipitation and temperature changes; and 4) the methods used to statistically downscale GCM scenarios. In accounting for these differences, there is substantial evidence across studies that future Colorado River streamflow will be reduced under the current trajectories of anthropogenic greenhouse gas emissions because of a combination of strong temperature-induced runoff curtailment and reduced annual precipitation. Reconstructions of preinstrumental streamflows provide additional insights; the greatest risk to Colorado River streamf lows is a multidecadal drought, like that observed in paleoreconstructions, exacerbated by a steady reduction in flows due to climate change. This could result in decades of sustained streamflows much lower than have been observed in the ~100 years of instrumental record.

Exploring the Link Between Streamflow Trends and Climate Change in Indiana, USA

NASA Astrophysics Data System (ADS)

Kumar, S.; Kam, J.; Thurner, K.; Merwade, V.

2007-12-01

Streamflow trends in Indiana are evaluated for 85 USGS streamflow gaging stations that have continuous unregulated streamflow records varying from 10 to 80 years. The trends are analyzed by using the non-parametric Mann-Kendall test with prior trend-free pre-whitening to remove serial correlation in the data. Bootstrap method is used to establish field significance of the results. Trends are computed for 12 streamflow statistics to include low-, medium- (median and mean flow), and high-flow conditions on annual and seasonal time step. The analysis is done for six study periods, ranging from 10 years to more than 65 years, all ending in 2003. The trends in annual average streamflow, for 50 years study period, are compared with annual average precipitation trends from 14 National Climatic Data Center (NCDC) stations in Indiana, that have 50 years of continuous daily record. The results show field significant positive trends in annual low and medium streamflow statistics at majority of gaging stations for study periods that include 40 or more years of records. In seasonal analysis, all flow statistics in summer and fall (low flow seasons), and only low flow statistics in winter and spring (high flow seasons) are showing positive trends. No field significant trends in annual and seasonal flow statistics are observed for study periods that include 25 or fewer years of records, except for northern Indiana where localized negative trends are observed in 10 and 15 years study periods. Further, stream flow trends are found to be highly correlated with precipitation trends on annual time step. No apparent climate change signal is observed in Indiana stream flow records.

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.

Streamflow simulation for continental-scale river basins

NASA Astrophysics Data System (ADS)

Nijssen, Bart; Lettenmaier, Dennis P.; Liang, Xu; Wetzel, Suzanne W.; Wood, Eric F.

1997-04-01

A grid network version of the two-layer variable infiltration capacity (VIC-2L) macroscale hydrologic model is described. VIC-2L is a hydrologically based soil- vegetation-atmosphere transfer scheme designed to represent the land surface in numerical weather prediction and climate models. The grid network scheme allows streamflow to be predicted for large continental rivers. Off-line (observed and estimated surface meteorological and radiative forcings) applications of the model to the Columbia River (1° latitude-longitude spatial resolution) and Delaware River (0.5° resolution) are described. The model performed quite well in both applications, reproducing the seasonal hydrograph and annual flow volumes to within a few percent. Difficulties in reproducing observed streamflow in the arid portion of the Snake River basin are attributed to groundwater-surface water interactions, which are not modeled by VIC-2L.

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.

Use of instantaneous streamflow measurements to improve regression estimates of index flow for the summer month of lowest streamflow in Michigan

USGS Publications Warehouse

Holtschlag, David J.

2011-01-01

In Michigan, index flow Q50 is a streamflow characteristic defined as the minimum of median flows for July, August, and September. The state of Michigan uses index flow estimates to help regulate large (greater than 100,000 gallons per day) water withdrawals to prevent adverse effects on characteristic fish populations. At sites where long-term streamgages are located, index flows are computed directly from continuous streamflow records as GageQ50. In an earlier study, a multiple-regression equation was developed to estimate index flows IndxQ50 at ungaged sites. The index equation explains about 94 percent of the variability of index flows at 147 (index) streamgages by use of six explanatory variables describing soil type, aquifer transmissivity, land cover, and precipitation characteristics. This report extends the results of the previous study, by use of Monte Carlo simulations, to evaluate alternative flow estimators, DiscQ50, IntgQ50, SiteQ50, and AugmQ50. The Monte Carlo simulations treated each of the available index streamgages, in turn, as a miscellaneous site where streamflow conditions are described by one or more instantaneous measurements of flow. In the simulations, instantaneous flows were approximated by daily mean flows at the corresponding site. All estimators use information that can be obtained from instantaneous flow measurements and contemporaneous daily mean flow data from nearby long-term streamgages. The efficacy of these estimators was evaluated over a set of measurement intensities in which the number of simulated instantaneous flow measurements ranged from 1 to 100 at a site. The discrete measurement estimator DiscQ50 is based on a simple linear regression developed between information on daily mean flows at five or more streamgages near the miscellaneous site and their corresponding GageQ50 index flows. The regression relation then was used to compute a DiscQ50 estimate at the miscellaneous site by use of the simulated instantaneous flow

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

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

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.

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.

Simulation of streamflow in small drainage basins in the southern Yampa River basin, Colorado

USGS Publications Warehouse

Parker, R.S.; Norris, J.M.

1989-01-01

Coal mining operations in northwestern Colorado commonly are located in areas that have minimal available water-resource information. Drainage-basin models can be a method for extending water-resource information to include periods for which there are no records or to transfer the information to areas that have no streamflow-gaging stations. To evaluate the magnitude and variability of the components of the water balance in the small drainage basins monitored, and to provide some method for transfer of hydrologic data, the U.S. Geological Survey 's Precipitation-Runoff Modeling System was used for small drainage basins in the southern Yampa River basin to simulate daily mean streamflow using daily precipitation and air-temperature data. The study area was divided into three hydrologic regions, and in each of these regions, three drainage basins were monitored. Two of the drainage basins in each region were used to calibrate the Precipitation-Runoff Modeling System. The model was not calibrated for the third drainage basin in each region; instead, parameter values were transferred from the model that was calibrated for the two drainage basins. For all of the drainage basins except one, period of record used for calibration and verification included water years 1976-81. Simulated annual volumes of streamflow for drainage basins used in calibration compared well with observed values; individual hydrographs indicated timing differences between the observed and simulated daily mean streamflow. Observed and simulated annual average streamflows compared well for the periods of record, but values of simulated high and low streamflows were different than observed values. Similar results were obtained when calibrated model parameter values were transferred to drainage basins that were uncalibrated. (USGS)

History of irrigation and characteristics of streamflow in Nebraska, part of the North and South Platte River basins

USGS Publications Warehouse

Shaffer, F. Butler

1976-01-01

Statistics on streamflow for selected periods of time are presented for 28 gaging sites in the Nebraska part of the North and South Platte River basins. Monthly mean discharges, monthly means in percent of annual runoff, standard deviations, coefficients of variation, and monthly extremes are given. Also tabulated are probabilities of high discharges for 1 day and for 3, 7, 15, 30, and 60 consecutive days and of low discharges for 1 day and for 3, 7, 14, 30, and 60 consecutive days. All statistics are based on records that are representative of 1973 conditions of streamflow. Brief historical data are given for 27 of the principal irrigation canals diverting from the North and South Platte Rivers. (Woodard-USGS)

Long-Term Interactions of Streamflow Generation and River Basin Morphology

NASA Astrophysics Data System (ADS)

Huang, X.; Niemann, J.

2005-12-01

It is well known that the spatial patterns and dynamics of streamflow generation processes depend on river basin topography, but the impact of streamflow generation processes on the long-term evolution of river basins has not drawn as much attention. Fluvial erosion processes are driven by streamflow, which can be produced by Horton runoff, Dunne runoff, and groundwater discharge. In this analysis, we hypothesize that the dominant streamflow generation process in a basin affects the spatial patterns of fluvial erosion and that the nature of these patterns changes for storm events with differing return periods. Furthermore, we hypothesize that differences in the erosion patterns modify the topography over the long term in a way that promotes and/or inhibits the other streamflow generation mechanisms. In order to test these hypotheses, a detailed hydrologic model is imbedded into an existing landscape evolution model. Precipitation events are simulated with a Poisson process and have random intensities and durations. The precipitation is partitioned between Horton runoff and infiltration to groundwater using a specified infiltration capacity. Groundwater flow is described by a two-dimensional Dupuit equation for a homogeneous, isotropic, unconfined aquifer with an irregular underlying impervious layer. Dunne runoff occurs when precipitation falls on locations where the water table reaches the land surface. The combined hydrologic/geomorphic model is applied to the WE-38 basin, an experimental watershed in Pennsylvania that has substantial available hydrologic data. First, the hydrologic model is calibrated to reproduce the observed streamflow for 1990 using the observed rainfall as the input. Then, the relative roles of Horton runoff, Dunne runoff, and groundwater discharge are controlled by varying the infiltration capacity of the soil. For each infiltration capacity, the hydrologic and geomorphic behavior of the current topography is analyzed and the long

Streamflow characteristics at streamgages in northern Afghanistan and selected locations

USGS Publications Warehouse

Olson, Scott A.; Williams-Sether, Tara

2010-01-01

Statistical summaries of streamflow data for 79 historical streamgages in Northern Afghanistan and other selected historical streamgages are presented in this report. The summaries for each streamgage include (1) station description, (2) graph of the annual mean discharge for the period of record, (3) statistics of monthly and annual mean discharges, (4) monthly and annual flow duration, (5) probability of occurrence of annual high discharges, (6) probability of occurrence of annual low discharges, (7) probability of occurrence of seasonal low discharges, (8) annual peak discharges for the period of record, and (9) monthly and annual mean discharges for the period of record.

Analysis of the streamflow-gaging station network in Ohio for effectiveness in providing regional streamflow information

USGS Publications Warehouse

Straub, D.E.

1998-01-01

The streamflow-gaging station network in Ohio was evaluated for its effectiveness in providing regional streamflow information. The analysis involved application of the principles of generalized least squares regression between streamflow and climatic and basin characteristics. Regression equations were developed for three flow characteristics: (1) the instantaneous peak flow with a 100-year recurrence interval (P100), (2) the mean annual flow (Qa), and (3) the 7-day, 10-year low flow (7Q10). All active and discontinued gaging stations with 5 or more years of unregulated-streamflow data with respect to each flow characteristic were used to develop the regression equations. The gaging-station network was evaluated for the current (1996) condition of the network and estimated conditions of various network strategies if an additional 5 and 20 years of streamflow data were collected. Any active or discontinued gaging station with (1) less than 5 years of unregulated-streamflow record, (2) previously defined basin and climatic characteristics, and (3) the potential for collection of more unregulated-streamflow record were included in the network strategies involving the additional 5 and 20 years of data. The network analysis involved use of the regression equations, in combination with location, period of record, and cost of operation, to determine the contribution of the data for each gaging station to regional streamflow information. The contribution of each gaging station was based on a cost-weighted reduction of the mean square error (average sampling-error variance) associated with each regional estimating equation. All gaging stations included in the network analysis were then ranked according to their contribution to the regional information for each flow characteristic. The predictive ability of the regression equations developed from the gaging station network could be improved for all three flow characteristics with the collection of additional streamflow data

Land Use Change Increases Streamflow Across the Arc of Deforestation in Brazil

NASA Astrophysics Data System (ADS)

Levy, M. C.; Lopes, A. V.; Cohn, A.; Larsen, L. G.; Thompson, S. E.

2018-04-01

Nearly half of recent decades' global forest loss occurred in the Amazon and Cerrado (tropical savanna) biomes of Brazil, known as the arc of deforestation. Despite prior analysis in individual river basins, a generalizable empirical understanding of the effect of deforestation on streamflow across this region is lacking. We frame land use change in Brazil as a natural experiment and draw on in situ and remote sensing evidence in 324 river basins covering more than 3 × 106 km2 to estimate streamflow changes caused by deforestation and agricultural development between 1950 and 2013. Deforestation increased dry season low flow by between 4 and 10 percentage points (relative to the forested condition), corresponding to a regional- and time-averaged rate of increase in specific streamflow of 1.29 mm/year2, equivalent to a 4.08 km3/year2 increase, assuming a stationary climate. In conjunction with rainfall and temperature variations, the net (observed) average increase in streamflow over the same period was 0.76 mm/year2, or 2.41 km3/year2. Thus, net increases in regional streamflow in the past half century are 58% of those that would have been experienced with deforestation given a stationary climate. This study uses a causal empirical analysis approach novel to the water sciences to verify the regional applicability of prior basin-scale studies, provides a proof of concept for the use of observational causal identification methods in the water sciences, and demonstrates that deforestation masks the streamflow-reducing effects of climate change in this region.

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.

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.

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

Potential effects of climate change on streamflow for seven watersheds in eastern and central Montana

USGS Publications Warehouse

Chase, Katherine J.; Haj, Adel E.; Regan, R. Steven; Viger, Roland J.

2016-01-01

Study regionEastern and central Montana.Study focusFish in Northern Great Plains streams tolerate extreme conditions including heat, cold, floods, and drought; however changes in streamflow associated with long-term climate change may render some prairie streams uninhabitable for current fish species. To better understand future hydrology of these prairie streams, the Precipitation-Runoff Modeling System model and output from the RegCM3 Regional Climate model were used to simulate streamflow for seven watersheds in eastern and central Montana, for a baseline period (water years 1982–1999) and three future periods: water years 2021–2038 (2030 period), 2046–2063 (2055 period), and 2071–2088 (2080 period).New hydrological insights for the regionProjected changes in mean annual and mean monthly streamflow vary by the RegCM3 model selected, by watershed, and by future period. Mean annual streamflows for all future periods are projected to increase (11–21%) for two of the four central Montana watersheds: Middle Musselshell River and Cottonwood Creek. Mean annual streamflows for all future periods are projected to decrease (changes of −24 to −75%) for Redwater River watershed in eastern Montana. Mean annual streamflows are projected to increase slightly (2–15%) for the 2030 period and decrease (changes of −16 to −44%) for the 2080 period for the four remaining watersheds.

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

The role of groundwater in streamflow in a headwater catchment with sub-humid climate

NASA Astrophysics Data System (ADS)

Liu, Yaping; Tian, Fuqiang; Hu, Hongchang; Tie, Qiang

2015-04-01

Recent studies have suggested that bedrock groundwater can exert considerable influence on streamflow in headwater catchments under humid climate. However, study of the role of bedrock groundwater is still challenged due to limited direct observation data. In this study, by utilizing observed hydrometric and hydrochemical data, we aimed at characterize the bedrock groundwater's response to rainfall at hillslope and catchment scales in a small headwater catchment with sub-humid climate. We selected Xitaizi catchment with area of 6.7 km in the earth-rock mountain region, which located in the north of Beijing, China, as study area. The catchment bedrock is mainly consist of fractured granite. Four weather stations were installed to observe the weather condition and soil volumetric water content (VWC) at depth of 10-60 cm with 10-minute interval. Five wells with depth of 10 m were drilled in two slopes to monitor the bedrock water table by pneumatic water gauge. At slope 1, the soil VWC at depth of 10-80 cm were also observed by soil moisture sensors, and surface/subsurface hillslope runoff at three different layers (0-20cm, 20-80cm, 80-300cm) was observed by three recording buckets. Field works were conducted from July 2013 to November 2014. During the period, precipitation, river, spring and groundwater were sampled nearly monthly. Water temperature, electrical conductivity (EC) and pH were measured in site with portable instruments. In addition, the precipitation, river and groundwater were also sampled intensively during two storm events. All the samples were subjected to stable isotope analysis, the samples taken monthly during the period from July 2013 to July 2014 were subjected to hydrochemistry analysis. Our results show that: (1) the bedrock groundwater is the dominant component of streamflow in the headwater catchment with sub-humid climate; (2) stream is recharged by groundwater sourcing from different mountains with different hydrochemistry characteristics

Elevated streamflows increase dam passage by juvenile coho salmon during winter: Implications of climate change in the Pacific Northwest

USGS Publications Warehouse

Kock, Tobias J.; Liedtke, Theresa L.; Rondorf, Dennis W.; Serl, John D.; Kohn, Mike; Bumbaco, Karin A.

2012-01-01

A 4-year evaluation was conducted to determine the proportion of juvenile coho salmon Oncorhynchus kisutch passing Cowlitz Falls Dam, on the Cowlitz River, Washington, during winter. River and reservoir populations of coho salmon parr were monitored using radiotelemetry to determine if streamflow increases resulted in increased downstream movement and dam passage. This was of interest because fish that pass downstream of Cowlitz Falls Dam become landlocked in Riffe Lake and are lost to the anadromous population. Higher proportions of reservoir-released fish (0.391-0.480) passed Cowlitz Falls Dam than did river-released fish (0.037-0.119). Event-time analyses demonstrated that streamflow increases were important predictors of dam passage rates during the study. The estimated effect of increasing streamflows on the risk of dam passage varied annually and ranged from 9% to 75% for every 28.3 m3/s increase in streamflow. These results have current management implications because they demonstrate the significance of dam passage by juvenile coho salmon during winter months when juvenile fish collection facilities are typically not operating. The results also have future management implications because climate change predictions suggest that peak streamflow timing for many watersheds in the Pacific Northwest will shift from late spring and early summer to winter. Increased occurrence of intense winter flood events is also expected. Our results demonstrate that juvenile coho salmon respond readily to streamflow increases and initiate downstream movements during winter months, which could result in increased passage at dams during these periods if climate change predictions are realized in the coming decades.

Climate Change Impacts to Hydro Power Reservoir Systems in British Columbia, Canada: Modelling, Validation and Projection of Historic and Future Streamflow and Snowpack

NASA Astrophysics Data System (ADS)

Bennett, K. E.; Schnorbus, M.; Werner, A. T.; Berland, A. J.

2010-12-01

The British Columbia Hydro Electric Corporation (BC Hydro) has a mandate to provide clean, renewable and reliable sources of hydro-electric power into the future, hence managing those resources in the context of climate change will be an important component of reservoir operational planning in British Columbia. The Pacific Climate Impacts Consortium (www.PacificClimate.org) has implemented the Variable Infiltration Capacity hydrologic model parameterized at 1/16th degree (~32 km2) to provide BC Hydro with future projections of changes to streamflow and snowpack to the 2050s. The headwaters of the Peace, Columbia, and Campbell River basins were selected for study; the Upper Peace River basin (101,000 km2) is a snowmelt-dominated watershed, and the Upper Columbia River Basin (104,000 km2) has a mixed snowmelt-glacier melt runoff regime, with glacier runoff contributing up to 15 to 20% of late summer discharge. The Upper Campbell River watershed (1,200 km2) has a mixed rainfall and snowmelt (hybrid) hydrologic regime. The model has been calibrated using historical streamflow observations and validated against these observations, as well as automated snow pillow measurements. Future streamflow changes are estimated based on eight Global Climate Models (GCMs) from the CMIP3 suite, downscaled using the Bias Correction Spatial Downscaling (BCSD) technique, run under three emissions scenarios (A2, A1B and B1; A1B is specifically reported on herein). Climate impacts by the 2050s in the three watersheds illustrate an increase in annual average temperature and precipitation ranging between +2.2°C to +2.8°C and +2% to +10% depending on basin, and an annual change in streamflow of -1% to +12% for the three watersheds. Changes are more profound on the seasonal time-scale and differ across basins. Summer streamflow in the Upper Campbell River watershed is projected to decline by -60%, where as the Upper Peace and Columbia systems are projected to decline by -25% and -22

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.

Observations on Sara's First Eight Months by Her Mother

ERIC Educational Resources Information Center

Fresco, Grazia Honegger

2016-01-01

Grazia Honegger Fresco gives us direct observations of her daughter from birth to eight months, grouping her observations by age even further into birth to fourth month, fifth and sixth months, and seventh and eighth months. Within each age range, she focuses on Sara's sensory life and her relationships. Her observations are detailed and gentle as…

Geologic and climatic controls on streamflow generation processes in a complex eogenetic karst basin

NASA Astrophysics Data System (ADS)

Vibhava, F.; Graham, W. D.; Maxwell, R. M.

2012-12-01

Streamflow at any given location and time is representative of surface and subsurface contributions from various sources. The ability to fully identify the factors controlling these contributions is key to successfully understanding the transport of contaminants through the system. In this study we developed a fully integrated 3D surface water-groundwater-land surface model, PARFLOW, to evaluate geologic and climatic controls on streamflow generation processes in a complex eogenetic karst basin in North Central Florida. In addition to traditional model evaluation criterion, such as comparing field observations to model simulated streamflow and groundwater elevations, we quantitatively evaluated the model's predictions of surface-groundwater interactions over space and time using a suite of binary end-member mixing models that were developed using observed specific conductivity differences among surface and groundwater sources throughout the domain. Analysis of model predictions showed that geologic heterogeneity exerts a strong control on both streamflow generation processes and land atmospheric fluxes in this watershed. In the upper basin, where the karst aquifer is overlain by a thick confining layer, approximately 92% of streamflow is "young" event flow, produced by near stream rainfall. Throughout the upper basin the confining layer produces a persistent high surficial water table which results in high evapotranspiration, low groundwater recharge and thus negligible "inter-event" streamflow. In the lower basin, where the karst aquifer is unconfined, deeper water tables result in less evapotranspiration. Thus, over 80% of the streamflow is "old" subsurface flow produced by diffuse infiltration through the epikarst throughout the lower basin, and all surface contributions to streamflow originate in the upper confined basin. Climatic variability provides a secondary control on surface-subsurface and land-atmosphere fluxes, producing significant seasonal and

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

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

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.

Trends in streamflow in the Yukon River Basin from 1944 to 2005 and the influence of the Pacific Decadal Oscillation

USGS Publications Warehouse

Brabets, T.P.; Walvoord, Michelle Ann

2009-01-01

Streamflow characteristics in the Yukon River Basin of Alaska and Canada have changed from 1944 to 2005, and some of the change can be attributed to the two most recent modes of the Pacific Decadal Oscillation (PDO). Seasonal, monthly, and annual stream discharge data from 21 stations in the Yukon River Basin were analyzed for trends over the entire period of record, generally spanning 4-6 decades, and examined for differences between the two most recent modes of the PDO: cold-PDO (1944-1975) and warm-PDO (1976-2005) subsets. Between 1944 and 2005, average winter and April flow increased at 15 sites. Observed winter flow increases during the cold-PDO phase were generally limited to sites in the Upper Yukon River Basin. Positive trends in winter flow during the warm-PDO phase broadened to include stations in the Middle and Lower Yukon River drainage basins. Increases in winter streamflow most likely result from groundwater input enhanced by permafrost thawing that promotes infiltration and deeper subsurface flow paths. Increased April flow may be attributed to a combination of greater baseflow (from groundwater increases), earlier spring snowmelt and runoff, and increased winter precipitation, depending on location. Calculated deviations from long-term mean monthly discharges indicate below-average flow in the winter months during the cold PDO and above-average flow in the winter months during the warm PDO. Although not as strong a signal, results also support the reverse response during the summer months: above-average flow during the cold PDO and below-average flow during the warm PDO. Changes in the summer flows are likely an indirect consequence of the PDO, resulting from earlier spring snowmelt runoff and also perhaps increased summer infiltration and storage in a deeper active layer. Annual discharge has remained relatively unchanged in the Yukon River Basin, but a few glacier-fed rivers demonstrate positive trends, which can be attributed to enhanced glacier

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.

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.

Statistical summaries of New Jersey streamflow records

USGS Publications Warehouse

Laskowski, Stanley L.

1970-01-01

In 1961 the U.S. Geological Survey prepared a report which was published by the State of New Jersey as Water Resources Circular 6, "New Jersey Streamflow Records analyzed with Electronic Computer" by Miller and McCall. Basic discharge data for periods of record through 1958 were analyzed for 59 stream-gaging stations in New Jersey and flow-duration, low-flow, and high-flow tables were presented.The purpose of the current report is to update and expand Circular 6 by presenting, with a few meaningful statistics and tables, the bulk of the information that may be obtained from the mass of streamflow records available. The records for 79 of approximately 110 stream-gaging stations presently or previously operated in New Jersey, plus records for three stations in Pennsylvania, and one in New York are presented in summarized form. In addition to inclusing a great number of stations in this report, more years of record and more tables are listed for each station. A description of the station, three arrangements of data summarizing the daily flow records and one table listing statistics of the monthly mean flows are provided. No data representing instantaneous extreme flows are given. Plotting positions for the three types of curves describing the characteristics of daily discharge are listed for each station. Statistical parameters are also presented so that alternate curves may be drawn.All stations included in this report have 5 or more years of record. The data presented herein are based on observed flow past the gaging station. For any station where the observed flow is affected by regulation or diversion, a "Remarks" paragraph, explaining the possible effect on the data, is included in the station description.Since any streamflow record is a sample in time, the data derived from these records can provide only a guide to expected future flows. For this reason the flow records are analyzed by statistical techniques, and the magnitude of sampling errors should be

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.

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.

Hydrometeorological model for streamflow prediction

USGS Publications Warehouse

Tangborn, Wendell V.

1979-01-01

The hydrometeorological model described in this manual was developed to predict seasonal streamflow from water in storage in a basin using streamflow and precipitation data. The model, as described, applies specifically to the Skokomish, Nisqually, and Cowlitz Rivers, in Washington State, and more generally to streams in other regions that derive seasonal runoff from melting snow. Thus the techniques demonstrated for these three drainage basins can be used as a guide for applying this method to other streams. Input to the computer program consists of daily averages of gaged runoff of these streams, and daily values of precipitation collected at Longmire, Kid Valley, and Cushman Dam. Predictions are based on estimates of the absolute storage of water, predominately as snow: storage is approximately equal to basin precipitation less observed runoff. A pre-forecast test season is used to revise the storage estimate and improve the prediction accuracy. To obtain maximum prediction accuracy for operational applications with this model , a systematic evaluation of several hydrologic and meteorologic variables is first necessary. Six input options to the computer program that control prediction accuracy are developed and demonstrated. Predictions of streamflow can be made at any time and for any length of season, although accuracy is usually poor for early-season predictions (before December 1) or for short seasons (less than 15 days). The coefficient of prediction (CP), the chief measure of accuracy used in this manual, approaches zero during the late autumn and early winter seasons and reaches a maximum of about 0.85 during the spring snowmelt season. (Kosco-USGS)

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.

Trends in snowmelt-related streamflow timing in the conterminous United States

NASA Astrophysics Data System (ADS)

Dudley, R. W.; Hodgkins, G. A.; McHale, M. R.; Kolian, M. J.; Renard, B.

2017-04-01

Changes in snowmelt-related streamflow timing have implications for water availability and use as well as ecologically relevant shifts in streamflow. Historical trends in snowmelt-related streamflow timing (winter-spring center volume date, WSCVD) were computed for minimally disturbed river basins in the conterminous United States. WSCVD was computed by summing daily streamflow for a seasonal window then calculating the day that half of the seasonal volume had flowed past the gage. We used basins where at least 30 percent of annual precipitation was received as snow, and streamflow data were restricted to regionally based winter-spring periods to focus the analyses on snowmelt-related streamflow. Trends over time in WSCVD at gages in the eastern U.S. were relatively homogenous in magnitude and direction and statistically significant; median WSCVD was earlier by 8.2 days (1.1 days/decade) and 8.6 days (1.6 days/decade) for 1940-2014 and 1960-2014 periods respectively. Fewer trends in the West were significant though most trends indicated earlier WSCVD over time. Trends at low-to-mid elevation (<1600 m) basins in the West, predominantly located in the Northwest, had median earlier WSCVD by 6.8 days (1940-2014, 0.9 days/decade) and 3.4 days (1960-2014, 0.6 days/decade). Streamflow timing at high-elevation (⩾1600 m) basins in the West had median earlier WSCVD by 4.0 days (1940-2014, 0.5 days/decade) and 5.2 days (1960-2014, 0.9 days/decade). Trends toward earlier WSCVD in the Northwest were not statistically significant, differing from previous studies that observed many large and (or) significant trends in this region. Much of this difference is likely due to the sensitivity of trend tests to the time period being tested, as well as differences in the streamflow timing metrics used among the studies. Mean February-May air temperature was significantly correlated with WSCVD at 100 percent of the study gages (field significant, p < 0.0001), demonstrating the

Modified Streamflows 1990 Level of Irrigation : Missouri, Colorado, Peace and Slave River Basin, 1928-1989.

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

A.G. Crook Company; United States. Bonneville Power Administration

1993-07-01

This report presents data for monthly mean streamflows adjusted for storage change, evaporation, and irrigation, for the years 1928-1990, for the Colorado River Basin, the Missouri River Basin, the Peace River Basin, and the Slave River Basin.

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

-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

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.

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

Spatial Correlation Of Streamflows: An Analytical Approach

NASA Astrophysics Data System (ADS)

Betterle, A.; Schirmer, M.; Botter, G.

2016-12-01

The interwoven space and time variability of climate and landscape properties results in complex and non-linear hydrological response of streamflow dynamics. Understanding how meteorologic and morphological characteristics of catchments affect similarity/dissimilarity of streamflow timeseries at their outlets represents a scientific challenge with application in water resources management, ecological studies and regionalization approaches aimed to predict streamflows in ungauged areas. In this study, we establish an analytical approach to estimate the spatial correlation of daily streamflows in two arbitrary locations within a given hydrologic district or river basin at seasonal and annual time scales. The method is based on a stochastic description of the coupled streamflow dynamics at the outlet of two catchments. The framework aims to express the correlation of daily streamflows at two locations along a river network as a function of a limited number of physical parameters characterizing the main underlying hydrological drivers, that include climate conditions, precipitation regime and catchment drainage rates. The proposed method portrays how heterogeneity of climate and landscape features affect the spatial variability of flow regimes along river systems. In particular, we show that frequency and intensity of synchronous effective rainfall events in the relevant contributing catchments are the main driver of the spatial correlation of daily discharge, whereas only pronounced differences in the drainage rate of the two basins bear a significant effect on the streamflow correlation. The topological arrangement of the two outlets also influences the underlying streamflow correlation, as we show that nested catchments tend to maximize the spatial correlation of flow regimes. The application of the method to a set of catchments in the South-Eastern US suggests the potential of the proposed tool for the characterization of spatial connections of flow regimes in the

Assessment of groundwater/surface-water interaction and simulation of potential streamflow depletion induced by groundwater withdrawal, Uinta River near Roosevelt, Utah

USGS Publications Warehouse

Lambert, P.M.; Marston, T.; Kimball, B.A.; Stolp, B.J.

2011-01-01

potential streamflow depletion that might result from future groundwater withdrawals at the Sprouse well field. The model incorporates concepts of transient groundwater flow conditions including fluctuations in groundwater levels and storage, and the distribution of and temporal variations in gains to and losses from streamflow in the West Channel of the Uinta River near the Sprouse well field. Two predictive model simulations incorporated additional future discharge from the Sprouse well field totaling 325 acre-feet annually and biennially during summer months. Results of the predictive model simulations indicate that the water withdrawn by the additional pumping was derived initially from aquifer storage and then, with time, predominantly from streamflow depletion. By the 10th year of the predictive simulation incorporating annual summer pumping from an additional public-supply well in the Sprouse well field, the simulation results indicate that 89 percent of a future annual 325 acre-feet of discharge is derived from depletion of streamflow in the West Channel of the Uinta River. A similar result was observed in a predictive model simulating the same discharge rate but with the new well being pumped every other year.

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

Potential Impact of Climate Change on Streamflow of Major Ethiopian Rivers

NASA Astrophysics Data System (ADS)

Gizaw, M. S.; Zhang, S.; Biftu, G. F.; Gan, T. Y.; Tan, X.; Moges, S. A.; Koivusalo, H.

2017-12-01

In this study, HSPF (Hydrologic Simulation Program-FORTRAN) was used to analyze the potential impact of climate change on the streamflow of four major river basins in Ethiopia: Awash, Baro, Genale and Tekeze. The calibrated and validated HSPF model was forced with daily climate data of 10 CMIP5 (Coupled Model Intercomparison Project phase 5) Global Climate Models (GCMs) for the 1971-2000 control period and the RCP4.5 and RCP8.5 climate projections of 2041-2070 (2050s) and 2071-2100 (2080s). The ensemble median of these 10 GCMs projects the temperature in the four study areas to increase by about 2.3 ˚C (3.3 ˚C) in 2050s (2080s) whereas the mean annual precipitation is projected to increase by about 6% (9%) in 2050s (2080s). This results in about 3% (6%) increase in the projected annual streamflow in Awash, Baro and Tekeze rivers whereas the annual streamflow of Genale river is projected to increase by about 18% (33%) in the 2050s (2080s). However, such projected increase in the mean annual streamflow due to increasing precipitation over Ethiopia contradicts the decreasing trends in mean annual precipitation observed in recent decades. Regional climate models of high resolutions could provide more realistic climate projections for Ethiopia's complex topography, thus reducing the uncertainties in future streamflow projections.

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.

Global maps of streamflow characteristics based on observations from several thousand catchments

NASA Astrophysics Data System (ADS)

Beck, Hylke; de Roo, Ad; van Dijk, Albert

2016-04-01

Streamflow (Q) estimation in ungauged catchments is one of the greatest challenges facing hydrologists. Observed Q from three to four thousand small-to-medium sized catchments (10--10 000~km^2) around the globe were used to train neural network ensembles to estimate Q characteristics based on climate and physiographic characteristics of the catchments. In total 17 Q characteristics were selected, including mean annual Q, baseflow index, and a number of flow percentiles. Testing coefficients of determination for the estimation of the Q characteristics ranged from 0.55 for the baseflow recession constant to 0.93 for the Q timing. Overall, climate indices dominated among the predictors. Predictors related to soils and geology were relatively unimportant, perhaps due to their data quality. The trained neural network ensembles were subsequently applied spatially over the entire ice-free land surface, resulting in global maps of the Q characteristics (0.125° resolution). These maps possess several unique features: they represent observation-driven estimates; are based on an unprecedentedly large set of catchments; and have associated uncertainty estimates. The maps can be used for various hydrological applications, including the diagnosis of macro-scale hydrological models. To demonstrate this, the produced maps were compared to equivalent maps derived from the simulated daily Q of four macro-scale hydrological models, highlighting various opportunities for improvement in model Q behavior. The produced dataset is available via http://water.jrc.ec.europa.eu.

Global maps of streamflow characteristics based on observations from several thousand catchments

NASA Astrophysics Data System (ADS)

Beck, Hylke; van Dijk, Albert; de Roo, Ad

2015-04-01

Streamflow (Q) estimation in ungauged catchments is one of the greatest challenges facing hydrologists. Observed Q from three to four thousand small-to-medium sized catchments (10-10000 km2) around the globe were used to train neural network ensembles to estimate Q characteristics based on climate and physiographic characteristics of the catchments. In total 17 Q characteristics were selected, including mean annual Q, baseflow index, and a number of flow percentiles. Testing coefficients of determination for the estimation of the Q characteristics ranged from 0.55 for the baseflow recession constant to 0.93 for the Q timing. Overall, climate indices dominated among the predictors. Predictors related to soils and geology were relatively unimportant, perhaps due to their data quality. The trained neural network ensembles were subsequently applied spatially over the entire ice-free land surface, resulting in global maps of the Q characteristics (0.125° resolution). These maps possess several unique features: they represent observation-driven estimates; are based on an unprecedentedly large set of catchments; and have associated uncertainty estimates. The maps can be used for various hydrological applications, including the diagnosis of macro-scale hydrological models. To demonstrate this, the produced maps were compared to equivalent maps derived from the simulated daily Q of four macro-scale hydrological models, highlighting various opportunities for improvement in model Q behavior. The produced dataset is available via http://water.jrc.ec.europa.eu.

How Hydroclimate Influences the Effectiveness of Particle Filter Data Assimilation of Streamflow in Initializing Short- to Medium-range Streamflow Forecasts

NASA Astrophysics Data System (ADS)

Clark, E.; Wood, A.; Nijssen, B.; Clark, M. P.

2017-12-01

Short- to medium-range (1- to 7-day) streamflow forecasts are important for flood control operations and in issuing potentially life-save flood warnings. In the U.S., the National Weather Service River Forecast Centers (RFCs) issue such forecasts in real time, depending heavily on a manual data assimilation (DA) approach. Forecasters adjust model inputs, states, parameters and outputs based on experience and consideration of a range of supporting real-time information. Achieving high-quality forecasts from new automated, centralized forecast systems will depend critically on the adequacy of automated DA approaches to make analogous corrections to the forecasting system. Such approaches would further enable systematic evaluation of real-time flood forecasting methods and strategies. Toward this goal, we have implemented a real-time Sequential Importance Resampling particle filter (SIR-PF) approach to assimilate observed streamflow into simulated initial hydrologic conditions (states) for initializing ensemble flood forecasts. Assimilating streamflow alone in SIR-PF improves simulated streamflow and soil moisture during the model spin up period prior to a forecast, with consequent benefits for forecasts. Nevertheless, it only consistently limits error in simulated snow water equivalent during the snowmelt season and in basins where precipitation falls primarily as snow. We examine how the simulated initial conditions with and without SIR-PF propagate into 1- to 7-day ensemble streamflow forecasts. Forecasts are evaluated in terms of reliability and skill over a 10-year period from 2005-2015. The focus of this analysis is on how interactions between hydroclimate and SIR-PF performance impact forecast skill. To this end, we examine forecasts for 5 hydroclimatically diverse basins in the western U.S. Some of these basins receive most of their precipitation as snow, others as rain. Some freeze throughout the mid-winter while others experience significant mid-winter melt

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

Analysis of trends in climate, streamflow, and stream temperature in north coastal California

USGS Publications Warehouse

Madej, Mary Ann; Medley, C. Nicholas; Patterson, Glenn; Parker, Melanie J.

2011-01-01

As part of a broader project analyzing trends in climate, streamflow, vegetation, salmon, and ocean conditions in northern California national park units, we compiled average monthly air temperature and precipitation data from 73 climate stations, streamflow data from 21 river gaging stations, and limited stream temperature data from salmon-bearing rivers in north coastal California. Many climate stations show a statistically significant increase in both average maximum and average minimum air temperature in early fall and midwinter during the last century. Concurrently, average September precipitation has decreased. In many coastal rivers, summer low flow has decreased and summer stream temperatures have increased, which affects summer rearing habitat for salmonids. Nevertheless, because vegetative cover has also changed during this time period, we cannot ascribe streamflow changes to climate change without first assessing water budgets. Although shifts in the timing of the centroid of runoff have been documented in snowmelt-dominated watersheds in the western United States, this was not the case in lower elevation coastal rivers analyzed in this study.

Analysis of streambed temperatures in ephemeral channels to determine streamflow frequency and duration

USGS Publications Warehouse

Constantz, James E.; Stonestrom, David A.; Stewart, Amy E.; Niswonger, Richard G.; Smith, Tyson R.

2001-01-01

Spatial and temporal patterns in streamflow are rarely monitored for ephemeral streams. Flashy, erosive streamflows common in ephemeral channels create a series of operational and maintenance problems, which makes it impractical to deploy a series of gaging stations along ephemeral channels. Streambed temperature is a robust and inexpensive parameter to monitor remotely, leading to the possibility of analyzing temperature patterns to estimate streamflow frequency and duration along ephemeral channels. A simulation model was utilized to examine various atmospheric and hydrological upper boundary conditions compared with a series of hypothetical temperature‐monitoring depths within the streambed. Simulation results indicate that streamflow events were distinguished from changing atmospheric conditions with greater certainty using temperatures at shallow depths (e.g., 10–20 cm) as opposed to the streambed surface. Three ephemeral streams in the American Southwest were instrumented to monitor streambed temperature for determining the accuracy of using this approach to ascertain the long‐term temporal and spatial extent of streamflow along each stream channel. Streambed temperature data were collected at the surface or at shallow depth along each stream channel, using thermistors encased in waterproof, single‐channel data loggers tethered to anchors in the channel. On the basis of comparisons with site information, such as direct field observations and upstream flow records, diurnal temperature variations successfully detected the presence and duration of streamflow for all sites.

Simulation of streamflow and water quality in the Leon Creek watershed, Bexar County, Texas, 1997-2004

USGS Publications Warehouse

Ockerman, Darwin J.; Roussel, Meghan C.

2009-01-01

The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers and the San Antonio River Authority, configured, calibrated, and tested a Hydrological Simulation Program ? FORTRAN watershed model for the approximately 238-square-mile Leon Creek watershed in Bexar County, Texas, and used the model to simulate streamflow and water quality (focusing on loads and yields of selected constituents). Streamflow in the model was calibrated and tested with available data from five U.S. Geological Survey streamflow-gaging stations for 1997-2004. Simulated streamflow volumes closely matched measured streamflow volumes at all streamflow-gaging stations. Total simulated streamflow volumes were within 10 percent of measured values. Streamflow volumes are greatly influenced by large storms. Two months that included major floods accounted for about 50 percent of all the streamflow measured at the most downstream gaging station during 1997-2004. Water-quality properties and constituents (water temperature, dissolved oxygen, suspended sediment, dissolved ammonia nitrogen, dissolved nitrate nitrogen, and dissolved and total lead and zinc) in the model were calibrated using available data from 13 sites in and near the Leon Creek watershed for varying periods of record during 1992-2005. Average simulated daily mean water temperature and dissolved oxygen at the most downstream gaging station during 1997-2000 were within 1 percent of average measured daily mean water temperature and dissolved oxygen. Simulated suspended-sediment load at the most downstream gaging station during 2001-04 (excluding July 2002 because of major storms) was 77,700 tons compared with 74,600 tons estimated from a streamflow-load regression relation (coefficient of determination = .869). Simulated concentrations of dissolved ammonia nitrogen and dissolved nitrate nitrogen closely matched measured concentrations after calibration. At the most downstream gaging station, average simulated monthly

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.

Real-time streamflow conditions

USGS Publications Warehouse

Graczyk, David J.; Gebert, Warren A.

1996-01-01

Would you like to know streamflow conditions before you go fishing in Wisconsin or in more distant locations? Real-time streamflow data throughout Wisconsin and the United States are available on the Internet from the U.S. Geological Survey. You can see if the stream you are interested in fishing is high due to recent rain or low because of an extended dry spell. Flow conditions at more than 100 stream-gaging stations located throughout Wisconsin can be viewed by accessing the Wisconsin District Home Page at: http://wwwdwimdn.er.usgs.gov

Statistical downscaling of GCM simulations to streamflow using relevance vector machine

NASA Astrophysics Data System (ADS)

Ghosh, Subimal; Mujumdar, P. P.

2008-01-01

General circulation models (GCMs), the climate models often used in assessing the impact of climate change, operate on a coarse scale and thus the simulation results obtained from GCMs are not particularly useful in a comparatively smaller river basin scale hydrology. The article presents a methodology of statistical downscaling based on sparse Bayesian learning and Relevance Vector Machine (RVM) to model streamflow at river basin scale for monsoon period (June, July, August, September) using GCM simulated climatic variables. NCEP/NCAR reanalysis data have been used for training the model to establish a statistical relationship between streamflow and climatic variables. The relationship thus obtained is used to project the future streamflow from GCM simulations. The statistical methodology involves principal component analysis, fuzzy clustering and RVM. Different kernel functions are used for comparison purpose. The model is applied to Mahanadi river basin in India. The results obtained using RVM are compared with those of state-of-the-art Support Vector Machine (SVM) to present the advantages of RVMs over SVMs. A decreasing trend is observed for monsoon streamflow of Mahanadi due to high surface warming in future, with the CCSR/NIES GCM and B2 scenario.

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

USDA-ARS?s Scientific Manuscript database

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....

Monitoring Supraglacial Streams over Three Months in Southwest Greenland

NASA Astrophysics Data System (ADS)

Muthyala, R.; Rennermalm, A.; Leidman, S. Z.; Cooper, M. G.; Cooley, S. W.; Smith, L. C.; van As, D.

2017-12-01

Supraglacial river networks are the most efficient conduits for evacuation of meltwater runoff produced on Greenland ice sheet. These rivers are prominent features on the ablation zone of southwest Greenland. However, little is known about the transport of meltwater through supraglacial stream network and most of the in-situ observations only capture a few days of streamflow. Here we report three months of observations of water level and discharge collected during summer of 2016, in two small supraglacial streams near the ice sheet margin in southwest Greenland. We also compare streamflow observations with meteorological data from a nearby automatic weather station. The two sites are very different, with the lower basin relatively steep, smooth and dark while the upper basin has rugged terrain and deeply incised stream channels. These catchment characteristics propagate to different relationships with meteorological parameters. For example, upper basin stream water levels show a strong covariance with surface temperature while the lower basin water levels do not. We also find differences in temporal variation of supraglacial stream water level, with the upper basin having two distinct peaks, in mid-June and mid-July, while the lower basin shows gradual decrease from June to August. Long-term supraglacial stream observations such as these will ultimately help assess how well surface mass balance models can simulate ice sheet runoff.

Improving Alpine Streamflow Simulations by Incorporation of Evapotranspiration and Soil Moisture Data

NASA Astrophysics Data System (ADS)

Tobin, K. J.; Bennett, M. E.

2017-12-01

Over the last decade autocalibration routines have become commonplace in watershed modeling. This approach is most often used to simulate a streamflow at a basin's outlet. In alpine settings spring/early summer snowmelt is by far the dominant signal in this system. Therefore, there is great potential for a modeled watershed to underperform during other times of the year. This tendency has been noted in many prior studies. In this work, the Soil and Water Assessment Tool (SWAT) model was autocalibrated with the SUFI-2 routine. Two mountainous watersheds from Idaho and Utah were examined. In this study, the basins were calibrated on a monthly satellite based on the MODIS 16A2 product. The gridded MODIS product was ideally suited to derive an estimate of ET on a subbasin basis. Soil moisture data was derived from extrapolation of in situ sites from the SNOwpack TELemetry (SNOTEL) network. Previous work has indicated that in situ soil moisture can be applied to derive an estimate at a significant distance (>30 km) away from the in situ site. Optimized ET and soil moisture parameter values were then applied to streamflow simulations. Preliminary results indicate improved streamflow performance both during calibration (2005-2011) and validation (2012-2014) periods. Streamflow performance was monitored with not only standard objective metrics (bias and Nash Sutcliffe coefficients) but also improved baseflow accuracy, demonstrating the utility of this approach in improving watershed modeling fidelity outside the main snowmelt season.

Evaluation of the streamflow-gaging network of Alaska in providing regional streamflow information

USGS Publications Warehouse

Brabets, Timothy P.

1996-01-01

In 1906, the U.S. Geological Survey (USGS) began operating a network of streamflow-gaging stations in Alaska. The primary purpose of the streamflow- gaging network has been to provide peak flow, average flow, and low-flow characteristics to a variety of users. In 1993, the USGS began a study to evaluate the current network of 78 stations. The objectives of this study were to determine the adequacy of the existing network in predicting selected regional flow characteristics and to determine if providing additional streamflow-gaging stations could improve the network's ability to predict these characteristics. Alaska was divided into six distinct hydrologic regions: Arctic, Northwest, Southcentral, Southeast, Southwest, and Yukon. For each region, historical and current streamflow data were compiled. In Arctic, Northwest, and Southwest Alaska, insufficient data were available to develop regional regression equations. In these areas, proposed locations of streamflow-gaging stations were selected by using clustering techniques to define similar areas within a region and by spatial visual analysis using the precipitation, physiographic, and hydrologic unit maps of Alaska. Sufficient data existed in Southcentral and Southeast Alaska to use generalized least squares (GLS) procedures to develop regional regression equations to estimate the 50-year peak flow, annual average flow, and a low-flow statistic. GLS procedures were also used for Yukon Alaska but the results should be used with caution because the data do not have an adequate spatial distribution. Network analysis procedures were used for the Southcentral, Southeast, and Yukon regions. Network analysis indicates the reduction in the sampling error of the regional regression equation that can be obtained given different scenarios. For Alaska, a 10-year planning period was used. One scenario showed the results of continuing the current network with no additional gaging stations and another scenario showed the results

A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites

NASA Astrophysics Data System (ADS)

Wang, Q. J.; Robertson, D. E.; Chiew, F. H. S.

2009-05-01

Seasonal forecasting of streamflows can be highly valuable for water resources management. In this paper, a Bayesian joint probability (BJP) modeling approach for seasonal forecasting of streamflows at multiple sites is presented. A Box-Cox transformed multivariate normal distribution is proposed to model the joint distribution of future streamflows and their predictors such as antecedent streamflows and El Niño-Southern Oscillation indices and other climate indicators. Bayesian inference of model parameters and uncertainties is implemented using Markov chain Monte Carlo sampling, leading to joint probabilistic forecasts of streamflows at multiple sites. The model provides a parametric structure for quantifying relationships between variables, including intersite correlations. The Box-Cox transformed multivariate normal distribution has considerable flexibility for modeling a wide range of predictors and predictands. The Bayesian inference formulated allows the use of data that contain nonconcurrent and missing records. The model flexibility and data-handling ability means that the BJP modeling approach is potentially of wide practical application. The paper also presents a number of statistical measures and graphical methods for verification of probabilistic forecasts of continuous variables. Results for streamflows at three river gauges in the Murrumbidgee River catchment in southeast Australia show that the BJP modeling approach has good forecast quality and that the fitted model is consistent with observed data.

Hydrology of the North Cascades region, Washington: 2. A proposed hydrometeorological streamflow prediction method

USGS Publications Warehouse

Tangborn, Wendell V.; Rasmussen, Lowell A.

1976-01-01

On the basis of a linear relationship between winter (October-April) precipitation and annual runoff from a drainage basin (Rasmussen and Tangborn, 1976) a physically reasonable model for predicting summer (May-September) streamflow from drainages in the North Cascades region was developed. This hydrometeorological prediction method relates streamflow for a season beginning on the day of prediction to the storage (including snow, ice, soil moisture, and groundwater) on that day. The spring storage is inferred from an input-output relationship based on the principle of conservation of mass: spring storage equals winter precipitation on the basin less winter runoff from the basin and less winter evapotranspiration, which is presumed to be small. The method of prediction is based on data only from the years previous to the one for which the prediction is made, and the system is revised each year as data for the previous year become available. To improve the basin storage estimate made in late winter or early spring, a short-season runoff prediction is made. The errors resulting from this short-term prediction are used to revise the storage estimate and improve the later prediction. This considerably improves the accuracy of the later prediction, especially for periods early in the summer runoff season. The optimum length for the test period appears to be generally less than a month for east side basins and between 1 and 2 months for those on the west side of the Cascade Range. The time distribution of the total summer runoff can be predicted when this test season is used so that on May 1 monthly streamflow for the May-September season can be predicted. It was found that summer precipitation and the time of minimum storage are two error sources that were amenable to analysis. For streamflow predictions in seasons beginning in early spring the deviation of the subsequent summer precipitation from a long-period average will contribute up to 53% of the prediction error

A proposed streamflow-data program for Utah

USGS Publications Warehouse

Whitaker, G.L.

1970-01-01

An evaluation of the streamflow data available in Utah was made to provide guidelines for planning future programs. The basic steps in the evaluation procedure were (1) definition of the long- term goals of the streamflow-data program in quantitative form, (2) examination and analysis of all available data to determine which goals have already been met, and (3) consideration of alternate programs and techniques to meet the remaining objectives. The principal goals are (1) to provide current streamflow data where needed for water management and (2) to define streamflow characteristics at any point on any stream within a specified accuracy. It was found that the first goal generally is being satisfied but that flow characteristics at ungaged sites cannot be estimated within the specified accuracy by regression analysis with the existing data and model now available. This latter finding indicates the need for some changes in the present data program so that the accuracy goals can be approached by alternate methods. The regression method may be more successful at a future time if a more suitable model can be developed, and if an adequate sample of streamflow records can be obtained in all areas. In the meantime, methods of transferring flow characteristics which require some information at the ungaged site may be used. A modified streamflow-data program based on this study is proposed.

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.

National Streamflow Information Program: Implementation Status Report

USGS Publications Warehouse

Norris, J. Michael

2009-01-01

The U.S. Geological Survey (USGS) operates and maintains a nationwide network of about 7,500 streamgages designed to provide and interpret long-term, accurate, and unbiased streamflow information to meet the multiple needs of many diverse national, regional, state, and local users. The National Streamflow Information Program (NSIP) was initiated in 2003 in response to Congressional and stakeholder concerns about (1) the decrease in the number of operating streamgages, including a disproportionate loss of streamgages with a long period of record; (2) the inability of the USGS to continue operating high-priority streamgages in an environment of reduced funding through partnerships; and (3) the increasing demand for streamflow information due to emerging resource-management issues and new data-delivery capabilities. The NSIP's mission is to provide the streamflow information and understanding required to meet national, regional, state, and local needs. Most of the existing streamgages are funded through partnerships with more than 850 other Federal, state, tribal, and local agencies. Currently, about 90 percent of the streamgages send data to the World Wide Web in near-real time (some information is transmitted within 15 minutes, whereas some lags by about 4 hours). The streamflow information collected at USGS streamgages is used for many purposes: *In water-resource appraisals and allocations - to determine how much water is available and how it is being allocated; *To provide streamflow information required by interstate agreements, compacts, and court decrees; *For engineering design of reservoirs, bridges, roads, culverts, and treatment plants; *For the operation of reservoirs, the operation of locks and dams for navigation purposes, and power production; *To identify changes in streamflow resulting from changes in land use, water use, and climate; *For streamflow forecasting, flood planning, and flood forecasting; *To support water-quality programs by allowing

Estimating ice-affected streamflow by extended Kalman filtering

USGS Publications Warehouse

Holtschlag, D.J.; Grewal, M.S.

1998-01-01

An extended Kalman filter was developed to automate the real-time estimation of ice-affected streamflow on the basis of routine measurements of stream stage and air temperature and on the relation between stage and streamflow during open-water (ice-free) conditions. The filter accommodates three dynamic modes of ice effects: sudden formation/ablation, stable ice conditions, and eventual elimination. The utility of the filter was evaluated by applying it to historical data from two long-term streamflow-gauging stations, St. John River at Dickey, Maine and Platte River at North Bend, Nebr. Results indicate that the filter was stable and that parameters converged for both stations, producing streamflow estimates that are highly correlated with published values. For the Maine station, logarithms of estimated streamflows are within 8% of the logarithms of published values 87.2% of the time during periods of ice effects and within 15% 96.6% of the time. Similarly, for the Nebraska station, logarithms of estimated streamflows are within 8% of the logarithms of published values 90.7% of the time and within 15% 97.7% of the time. In addition, the correlation between temporal updates and published streamflows on days of direct measurements at the Maine station was 0.777 and 0.998 for ice-affected and open-water periods, respectively; for the Nebraska station, corresponding correlations were 0.864 and 0.997.

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

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.

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

Artificial Neural Network Models for Long Lead Streamflow Forecasts using Climate Information

NASA Astrophysics Data System (ADS)

Kumar, J.; Devineni, N.

2007-12-01

Information on season ahead stream flow forecasts is very beneficial for the operation and management of water supply systems. Daily streamflow conditions at any particular reservoir primarily depend on atmospheric and land surface conditions including the soil moisture and snow pack. On the other hand recent studies suggest that developing long lead streamflow forecasts (3 months ahead) typically depends on exogenous climatic conditions particularly Sea Surface Temperature conditions (SST) in the tropical oceans. Examples of some oceanic variables are El Nino Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Identification of such conditions that influence the moisture transport into a given basin poses many challenges given the nonlinear dependency between the predictors (SST) and predictand (stream flows). In this study, we apply both linear and nonlinear dependency measures to identify the predictors that influence the winter flows into the Neuse basin. The predictor identification approach here adopted uses simple correlation coefficients to spearman rank correlation measures for detecting nonlinear dependency. All these dependency measures are employed with a lag 3 time series of the high flow season (January - February - March) using 75 years (1928-2002) of stream flows recorded in to the Falls Lake, Neuse River Basin. Developing streamflow forecasts contingent on these exogenous predictors will play an important role towards improved water supply planning and management. Recently, the soft computing techniques, such as artificial neural networks (ANNs) have provided an alternative method to solve complex problems efficiently. ANNs are data driven models which trains on the examples given to it. The ANNs functions as universal approximators and are non linear in nature. This paper presents a study aiming towards using climatic predictors for 3 month lead time streamflow forecast. ANN models representing the physical process of the system are

Streamflow gain/loss in the Republican River basin, Nebraska, March 1989

USGS Publications Warehouse

Johnson, Michaela R.; Stanton, Jennifer S.; Cornwall, James F.; Landon, Matthew K.

2002-01-01

This arc and point data set contains streamflow measurement sites and reaches indicating streamflow gain or loss under base-flow conditions along the Republican River and tributaries in Nebraska during March 21 to 22, 1989 (Boohar and others, 1990). These measurements were made to obtain data on ground-water/surface-water interaction. Flow was visually observed to be zero, was measured, or was estimated at 136 sites. The measurements were made on the main stem of the Republican River and all flowing tributaries that enter the Republican River above Swanson Reservoir and parts of the Frenchman, Red Willow, and Medicine Creek drainages in the Nebraska part of the Republican River Basin. Tributaries were followed upstream until the first road crossing where zero flow was encountered. For selected streams, points of zero flow upstream of the first zero flow site were also checked. Streamflow gain or loss for each stream reach was calculated by subtracting the streamflow values measured at the upstream end of the reach and values for contributing tributaries from the downstream value. The data obtained reflected base-flow conditions suitable for estimating streamflow gains and losses for stream reaches between sites. This digital data set was created by manually plotting locations of streamflow measurements. These points were used to designate stream-reach segments to calculate gain/loss per river mile. Reach segments were created by manually splitting the lines from a 1:250,000 hydrography data set (Soenksen and others, 1999) at every location where the streams were measured. Each stream-reach segment between streamflow-measurement sites was assigned a unique reach number. All other lines in the hydrography data set without reach numbers were omitted. This data set was created to archive the calculated streamflow gains and losses of selected streams in part of the Republican River Basin, Nebraska in March 1989, and make the data available for use with geographic

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.

Estimated monthly percentile discharges at ungaged sites in the Upper Yellowstone River Basin in Montana

USGS Publications Warehouse

Parrett, Charles; Hull, J.A.

1986-01-01

Once-monthly streamflow measurements were used to estimate selected percentile discharges on flow-duration curves of monthly mean discharge for 40 ungaged stream sites in the upper Yellowstone River basin in Montana. The estimation technique was a modification of the concurrent-discharge method previously described and used by H.C. Riggs to estimate annual mean discharge. The modified technique is based on the relationship of various mean seasonal discharges to the required discharges on the flow-duration curves. The mean seasonal discharges are estimated from the monthly streamflow measurements, and the percentile discharges are calculated from regression equations. The regression equations, developed from streamflow record at nine gaging stations, indicated a significant log-linear relationship between mean seasonal discharge and various percentile discharges. The technique was tested at two discontinued streamflow-gaging stations; the differences between estimated monthly discharges and those determined from the discharge record ranged from -31 to +27 percent at one site and from -14 to +85 percent at the other. The estimates at one site were unbiased, and the estimates at the other site were consistently larger than the recorded values. Based on the test results, the probable average error of the technique was + or - 30 percent for the 21 sites measured during the first year of the program and + or - 50 percent for the 19 sites measured during the second year. (USGS)

Statistical analysis of water-level, springflow, and streamflow data for the Edwards Aquifer in south-central Texas

USGS Publications Warehouse

Puente, Celso

1976-01-01

Water-level, springflow, and streamflow data were used to develop simple and multiple linear-regression equations for use in estimating water levels in wells and the flow of three major springs in the Edwards aquifer in the eastern San Antonio area. The equations provide daily, monthly, and annual estimates that compare very favorably with observed data. Analyses of geologic and hydrologic data indicate that the water discharged by the major springs is supplied primarily by regional underflow from the west and southwest and by local recharge in the infiltration area in northern Bexar, Comal, and Hays Counties.

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

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

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...

New Jersey StreamStats: A web application for streamflow statistics and basin characteristics

USGS Publications Warehouse

Watson, Kara M.; Janowicz, Jon A.

2017-08-02

StreamStats is an interactive, map-based web application from the U.S. Geological Survey (USGS) that allows users to easily obtain streamflow statistics and watershed characteristics for both gaged and ungaged sites on streams throughout New Jersey. Users can determine flood magnitude and frequency, monthly flow-duration, monthly low-flow frequency statistics, and watershed characteristics for ungaged sites by selecting a point along a stream, or they can obtain this information for streamgages by selecting a streamgage location on the map. StreamStats provides several additional tools useful for water-resources planning and management, as well as for engineering purposes. StreamStats is available for most states and some river basins through a single web portal.Streamflow statistics for water resources professionals include the 1-percent annual chance flood flow (100-year peak flow) used to define flood plain areas and the monthly 7-day, 10-year low flow (M7D10Y) used in water supply management and studies of recreation, wildlife conservation, and wastewater dilution. Additionally, watershed or basin characteristics, including drainage area, percent area forested, and average percent of impervious areas, are commonly used in land-use planning and environmental assessments. These characteristics are easily derived through StreamStats.

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

Streamflow characteristics at hydrologic bench-mark stations

USGS Publications Warehouse

Lawrence, C.L.

1987-01-01

The Hydrologic Bench-Mark Network was established in the 1960's. Its objectives were to document the hydrologic characteristics of representative undeveloped watersheds nationwide and to provide a comparative base for studying the effects of man on the hydrologic environment. The network, which consists of 57 streamflow gaging stations and one lake-stage station in 39 States, is planned for permanent operation. This interim report describes streamflow characteristics at each bench-mark site and identifies time trends in annual streamflow that have occurred during the data-collection period. The streamflow characteristics presented for each streamflow station are (1) flood and low-flow frequencies, (2) flow duration, (3) annual mean flow, and (4) the serial correlation coefficient for annual mean discharge. In addition, Kendall's tau is computed as an indicator of time trend in annual discharges. The period of record for most stations was 13 to 17 years, although several stations had longer periods of record. The longest period was 65 years for Merced River near Yosemite, Calif. Records of flow at 6 of 57 streamflow sites in the network showed a statistically significant change in annual mean discharge over the period of record, based on computations of Kendall's tau. The values of Kendall's tau ranged from -0.533 to 0.648. An examination of climatological records showed that changes in precipitation were most likely the cause for the change in annual mean discharge.

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.

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

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.

Assessment of an ensemble seasonal streamflow forecasting system for Australia

NASA Astrophysics Data System (ADS)

Bennett, James C.; Wang, Quan J.; Robertson, David E.; Schepen, Andrew; Li, Ming; Michael, Kelvin

2017-11-01

Despite an increasing availability of skilful long-range streamflow forecasts, many water agencies still rely on simple resampled historical inflow sequences (stochastic scenarios) to plan operations over the coming year. We assess a recently developed forecasting system called forecast guided stochastic scenarios (FoGSS) as a skilful alternative to standard stochastic scenarios for the Australian continent. FoGSS uses climate forecasts from a coupled ocean-land-atmosphere prediction system, post-processed with the method of calibration, bridging and merging. Ensemble rainfall forecasts force a monthly rainfall-runoff model, while a staged hydrological error model quantifies and propagates hydrological forecast uncertainty through forecast lead times. FoGSS is able to generate ensemble streamflow forecasts in the form of monthly time series to a 12-month forecast horizon. FoGSS is tested on 63 Australian catchments that cover a wide range of climates, including 21 ephemeral rivers. In all perennial and many ephemeral catchments, FoGSS provides an effective alternative to resampled historical inflow sequences. FoGSS generally produces skilful forecasts at shorter lead times ( < 4 months), and transits to climatology-like forecasts at longer lead times. Forecasts are generally reliable and unbiased. However, FoGSS does not perform well in very dry catchments (catchments that experience zero flows more than half the time in some months), sometimes producing strongly negative forecast skill and poor reliability. We attempt to improve forecasts through the use of (i) ESP rainfall forcings, (ii) different rainfall-runoff models, and (iii) a Bayesian prior to encourage the error model to return climatology forecasts in months when the rainfall-runoff model performs poorly. Of these, the use of the prior offers the clearest benefit in very dry catchments, where it moderates strongly negative forecast skill and reduces bias in some instances. However, the prior does

Streamflow of 2015—Water year national summary

USGS Publications Warehouse

Jian, Xiaodong; Wolock, David M.; Lins, Harry F.; Brady, Steve

2016-08-30

IntroductionThe maps and graphs in this summary describe national streamflow conditions for water year 2015 (October 1, 2014, to September 30, 2015) in the context of the 86-year period 1930–2015, unless otherwise noted. The illustrations are based on observed data from the U.S. Geological Survey’s (USGS) National Streamflow Information Program http://water.usgs.gov/nsip). The period 1930–2015 was used because prior to 1930, the number of streamgages was too small to provide representative data for computing statistics for most regions of the country.In the summary, reference is made to the term “runoff,” which is the depth to which a river basin, State, or other geographic area would be covered with water if all the streamflow within the area during a specified time period was uniformly distributed upon it. Runoff quantifies the magnitude of water flowing through the Nation's rivers and streams in measurement units that can be compared from one area to another.Each of the maps and graphs can be expanded to a larger view by clicking on the image. In all of the graphics, a rank of 1 indicates the highest flow of all years analyzed. Rankings of streamflow are grouped into much-below normal, below normal, normal, above normal, and much-above normal, based on percentiles of flow (greater than 90 percent, 76–90 percent, 25–75 percent, 10–24 percent, and less than 10 percent, respectively) (http://waterwatch.usgs.gov/?id=ww_current). Some data used to produce maps and graphs are provisional and subject to change.

Multidecadal change in streamflow associated with anthropogenic disturbances in the tropical Andes

NASA Astrophysics Data System (ADS)

Molina, A.; Vanacker, V.; Brisson, E.; Mora, D.; Balthazar, V.

2015-10-01

Andean headwater catchments are an important source of freshwater for downstream water users. However, few long-term studies exist on the relative importance of climate change and direct anthropogenic perturbations on flow regimes in these catchments. In this paper, we assess change in streamflow based on long time series of hydrometeorological data (1974-2008) and land cover reconstructions (1963-2009) in the Pangor catchment (282 km2) located in the tropical Andes. Three main land cover change trajectories can be distinguished during the period 1963-2009: (1) expansion of agricultural land by an area equal to 14 % of the catchment area (or 39 km2) in 46 years' time, (2) deforestation of native forests by 11 % (or -31 km2) corresponding to a mean rate of 67 ha yr-1, and (3) afforestation with exotic species in recent years by about 5 % (or 15 km2). Over the time period 1963-2009, about 50 % of the 64 km2 of native forests was cleared and converted to agricultural land. Given the strong temporal variability of precipitation and streamflow data related to El Niño-Southern Oscillation, we use empirical mode decomposition techniques to detrend the time series. The long-term increasing trend in rainfall is remarkably different from the observed changes in streamflow, which exhibit a decreasing trend. Hence, observed changes in streamflow are not the result of long-term change in precipitation but very likely result from anthropogenic disturbances associated with land cover change.

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

The efficacy of calibrating hydrologic model using remotely sensed evapotranspiration and soil moisture for streamflow prediction

NASA Astrophysics Data System (ADS)

Kunnath-Poovakka, A.; Ryu, D.; Renzullo, L. J.; George, B.

2016-04-01

Calibration of spatially distributed hydrologic models is frequently limited by the availability of ground observations. Remotely sensed (RS) hydrologic information provides an alternative source of observations to inform models and extend modelling capability beyond the limits of ground observations. This study examines the capability of RS evapotranspiration (ET) and soil moisture (SM) in calibrating a hydrologic model and its efficacy to improve streamflow predictions. SM retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and daily ET estimates from the CSIRO MODIS ReScaled potential ET (CMRSET) are used to calibrate a simplified Australian Water Resource Assessment - Landscape model (AWRA-L) for a selection of parameters. The Shuffled Complex Evolution Uncertainty Algorithm (SCE-UA) is employed for parameter estimation at eleven catchments in eastern Australia. A subset of parameters for calibration is selected based on the variance-based Sobol' sensitivity analysis. The efficacy of 15 objective functions for calibration is assessed based on streamflow predictions relative to control cases, and relative merits of each are discussed. Synthetic experiments were conducted to examine the effect of bias in RS ET observations on calibration. The objective function containing the root mean square deviation (RMSD) of ET result in best streamflow predictions and the efficacy is superior for catchments with medium to high average runoff. Synthetic experiments revealed that accurate ET product can improve the streamflow predictions in catchments with low average runoff.

Regionalization of harmonic-mean streamflows in Kentucky

USGS Publications Warehouse

Martin, Gary R.; Ruhl, Kevin J.

1993-01-01

Harmonic-mean streamflow (Qh), defined as the reciprocal of the arithmetic mean of the reciprocal daily streamflow values, was determined for selected stream sites in Kentucky. Daily mean discharges for the available period of record through the 1989 water year at 230 continuous record streamflow-gaging stations located in and adjacent to Kentucky were used in the analysis. Periods of record affected by regulation were identified and analyzed separately from periods of record unaffected by regulation. Record-extension procedures were applied to short-term stations to reducetime-sampling error and, thus, improve estimates of the long-term Qh. Techniques to estimate the Qh at ungaged stream sites in Kentucky were developed. A regression model relating Qh to total drainage area and streamflow-variability index was presented with example applications. The regression model has a standard error of estimate of 76 percent and a standard error of prediction of 78 percent.

The contribution of glacier melt to streamflow

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

Schaner, Neil; Voisin, Nathalie; Nijssen, Bart

2012-09-13

Ongoing and projected future changes in glacier extent and water storage globally have lead to concerns about the implications for water supplies. However, the current magnitude of glacier contributions to river runoff is not well known, nor is the population at risk to future glacier changes. We estimate an upper bound on glacier melt contribution to seasonal streamflow by computing the energy balance of glaciers globally. Melt water quantities are computed as a fraction of total streamflow simulated using a hydrology model and the melt fraction is tracked down the stream network. In general, our estimates of the glacier meltmore » contribution to streamflow are lower than previously published values. Nonetheless, we find that globally an estimated 225 (36) million people live in river basins where maximum seasonal glacier melt contributes at least 10% (25%) of streamflow, mostly in the High Asia region.« less

Streamflow measurements, basin characteristics, and streamflow statistics for low-flow partial-record stations operated in Massachusetts from 1989 through 1996

USGS Publications Warehouse

Ries, Kernell G.

1999-01-01

A network of 148 low-flow partial-record stations was operated on streams in Massachusetts during the summers of 1989 through 1996. Streamflow measurements (including historical measurements), measured basin characteristics, and estimated streamflow statistics are provided in the report for each low-flow partial-record station. Also included for each station are location information, streamflow-gaging stations for which flows were correlated to those at the low-flowpartial-record station, years of operation, and remarks indicating human influences of stream-flowsat the station. Three or four streamflow measurements were made each year for three years during times of low flow to obtain nine or ten measurements for each station. Measured flows at the low-flow partial-record stations were correlated with same-day mean flows at a nearby gaging station to estimate streamflow statistics for the low-flow partial-record stations. The estimated streamflow statistics include the 99-, 98-, 97-, 95-, 93-, 90-, 85-, 80-, 75-, 70-, 65-, 60-, 55-, and 50-percent duration flows; the 7-day, 10- and 2-year low flows; and the August median flow. Characteristics of the drainage basins for the stations that theoretically relate to the response of the station to climatic variations were measured from digital map data by use of an automated geographic information system procedure. Basin characteristics measured include drainage area; total stream length; mean basin slope; area of surficial stratified drift; area of wetlands; area of water bodies; and mean, maximum, and minimum basin elevation.Station descriptions and calculated streamflow statistics are also included in the report for the 50 continuous gaging stations used in correlations with the low-flow partial-record stations.

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

Reconstructed streamflow for Citarum River, Java, Indonesia: linkages to tropical climate dynamics

NASA Astrophysics Data System (ADS)

D'Arrigo, Rosanne; Abram, Nerilie; Ummenhofer, Caroline; Palmer, Jonathan; Mudelsee, Manfred

2011-02-01

The Citarum river basin of western Java, Indonesia, which supplies water to 10 million residents in Jakarta, has become increasingly vulnerable to anthropogenic change. Citarum's streamflow record, only ~45 years in length (1963-present), is too short for understanding the full range of hydrometeorological variability in this important region. Here we present a tree-ring based reconstruction of September-November Citarum streamflow (AD 1759-2006), one of the first such records available for monsoon Asia. Close coupling is observed between decreased tree growth and low streamflow levels, which in turn are associated with drought caused by ENSO warm events in the tropical Pacific and Indian Ocean positive dipole-type variability. Over the full length of record, reconstructed variance was at its weakest during the interval from ~1905-1960, overlapping with a period of unusually-low variability (1920-1960) in the ENSO-Indian Ocean dipole systems. In subsequent decades, increased variance in both the streamflow anomalies and a coral-based SST reconstruction of the Indian Ocean Dipole Mode signal the potential for intensified drought activity and related consequences for water supply and crop productivity in western Java, where much of the country's rice is grown.

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

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

Increasing streamflow and baseflow in Mississippi River since the 1940 s: Effect of land use change

USGS Publications Warehouse

Zhang, Y.-K.; Schilling, K.E.

2006-01-01

A trend of increasing streamflow has been observed in the Mississippi River (MR) basin since the 1940 s as a result of increased precipitation. Herein we show that increasing MR flow is mainly in its baseflow as a result of land use change and accompanying agricultural activities that occurred in the MR basin during the last 60 years. Agricultural land use change in the MR basin has affected the basin-scale hydrology: more precipitation is being routed into streams as baseflow than stormflow since 1940 s. We explain that the conversion of perennial vegetation to seasonal row crops, especially soybeans, in the basin since 1940 s may have reduced evapotranspiration, increased groundwater recharge, and thus increased baseflow and streamflow. This explanation is supported with a data analysis of the annually and monthly flow rates at various river stations in the MR basin. Results from this study will help to direct our effort in managing land use and in reducing nutrient levels in MR and other major rivers since nutrient concentrations and loads carried by storm water and baseflow are different. ?? 2005 Elsevier B.V. All rights reserved.

Statistical models for estimating daily streamflow in Michigan

USGS Publications Warehouse

Holtschlag, D.J.; Salehi, Habib

1992-01-01

Statistical models for estimating daily streamflow were analyzed for 25 pairs of streamflow-gaging stations in Michigan. Stations were paired by randomly choosing a station operated in 1989 at which 10 or more years of continuous flow data had been collected and at which flow is virtually unregulated; a nearby station was chosen where flow characteristics are similar. Streamflow data from the 25 randomly selected stations were used as the response variables; streamflow data at the nearby stations were used to generate a set of explanatory variables. Ordinary-least squares regression (OLSR) equations, autoregressive integrated moving-average (ARIMA) equations, and transfer function-noise (TFN) equations were developed to estimate the log transform of flow for the 25 randomly selected stations. The precision of each type of equation was evaluated on the basis of the standard deviation of the estimation errors. OLSR equations produce one set of estimation errors; ARIMA and TFN models each produce l sets of estimation errors corresponding to the forecast lead. The lead-l forecast is the estimate of flow l days ahead of the most recent streamflow used as a response variable in the estimation. In this analysis, the standard deviation of lead l ARIMA and TFN forecast errors were generally lower than the standard deviation of OLSR errors for l < 2 days and l < 9 days, respectively. Composite estimates were computed as a weighted average of forecasts based on TFN equations and backcasts (forecasts of the reverse-ordered series) based on ARIMA equations. The standard deviation of composite errors varied throughout the length of the estimation interval and generally was at maximum near the center of the interval. For comparison with OLSR errors, the mean standard deviation of composite errors were computed for intervals of length 1 to 40 days. The mean standard deviation of length-l composite errors were generally less than the standard deviation of the OLSR errors for l < 32

On the sensitivity of annual streamflow to air temperature

USGS Publications Warehouse

Milly, Paul C.D.; Kam, Jonghun; Dunne, Krista A.

2018-01-01

Although interannual streamflow variability is primarily a result of precipitation variability, temperature also plays a role. The relative weakness of the temperature effect at the annual time scale hinders understanding, but may belie substantial importance on climatic time scales. Here we develop and evaluate a simple theory relating variations of streamflow and evapotranspiration (E) to those of precipitation (P) and temperature. The theory is based on extensions of the Budyko water‐balance hypothesis, the Priestley‐Taylor theory for potential evapotranspiration ( ), and a linear model of interannual basin storage. The theory implies that the temperature affects streamflow by modifying evapotranspiration through a Clausius‐Clapeyron‐like relation and through the sensitivity of net radiation to temperature. We apply and test (1) a previously introduced “strong” extension of the Budyko hypothesis, which requires that the function linking temporal variations of the evapotranspiration ratio (E/P) and the index of dryness ( /P) at an annual time scale is identical to that linking interbasin variations of the corresponding long‐term means, and (2) a “weak” extension, which requires only that the annual evapotranspiration ratio depends uniquely on the annual index of dryness, and that the form of that dependence need not be known a priori nor be identical across basins. In application of the weak extension, the readily observed sensitivity of streamflow to precipitation contains crucial information about the sensitivity to potential evapotranspiration and, thence, to temperature. Implementation of the strong extension is problematic, whereas the weak extension appears to capture essential controls of the temperature effect efficiently.

Selective Tree-ring Models: A Novel Method for Reconstructing Streamflow Using Tree Rings

NASA Astrophysics Data System (ADS)

Foard, M. B.; Nelson, A. S.; Harley, G. L.

2017-12-01

Surface water is among the most instrumental and vulnerable resources in the Northwest United States (NW). Recent observations show that overall water quantity is declining in streams across the region, while extreme flooding events occur more frequently. Historical streamflow models inform probabilities of extreme flow events (flood or drought) by describing frequency and duration of past events. There are numerous examples of tree-rings being utilized to reconstruct streamflow in the NW. These models confirm that tree-rings are highly accurate at predicting streamflow, however there are many nuances that limit their applicability through time and space. For example, most models predict streamflow from hydrologically altered rivers (e.g. dammed, channelized) which may hinder our ability to predict natural prehistoric flow. They also have a tendency to over/under-predict extreme flow events. Moreover, they often neglect to capture the changing relationships between tree-growth and streamflow over time and space. To address these limitations, we utilized national tree-ring and streamflow archives to investigate the relationships between the growth of multiple coniferous species and free-flowing streams across the NW using novel species-and site-specific streamflow models - a term we coined"selective tree-ring models." Correlation function analysis and regression modeling were used to evaluate the strengths and directions of the flow-growth relationships. Species with significant relationships in the same direction were identified as strong candidates for selective models. Temporal and spatial patterns of these relationships were examined using running correlations and inverse distance weighting interpolation, respectively. Our early results indicate that (1) species adapted to extreme climates (e.g. hot-dry, cold-wet) exhibit the most consistent relationships across space, (2) these relationships weaken in locations with mild climatic variability, and (3) some

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.

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

Comparison of methods for determining streamflow requirements for aquatic habitat protection at selected sites on the Assabet and Charles Rivers, Eastern Massachusetts, 2000-02

USGS Publications Warehouse

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

2004-01-01

streamflow requirements than would result if the methods were applied to riffles on natural channels with unaltered streamflows. The R2Cross 2-of-3 criteria and the Wetted-Perimeter streamflow requirements for the Assabet and Charles River sites show narrower interquartile ranges and lower median streamflow requirements than for 10 index streamflow-gaging stations in southern New England. This is especially evident for the R2Cross 2-of-3 criteria and Wetted-Perimeter results that were close to half of the flow requirements determined at the 10 southern New England stations. The R2Cross and Wetted-Perimeter methods were also compared to the Range of Variability Approach analysis and the Tennant Method. The median R2Cross 3-of-3 criteria streamflow requirement for the nine riffles is close to the 75th percentile of the monthly mean flows during the summer low-flow period from six streamflow-gaging stations near the Assabet and Charles River Basins having mostly unaltered flow. This streamflow requirement is close to the median Tennant 40-percent-flow requirement for good habitat condi-tion for the same six nearby stations. The R2Cross 2-of-3 criteria and Wetted-Perimeter results were less than the 25th-percentile of monthly mean flows during the summer months for the six stations. These streamflow requirements are in the poor habitat range as indicated by a Tennant analysis of the same six stations. These comparisons indicate that the R2Cross and Wetted-Perimeter methods underestimate streamflow requirements when applied to sites in smaller drainage areas and channels that are runs at higher flows.

Global Maps of Temporal Streamflow Characteristics Based on Observations from Many Small Catchments

NASA Astrophysics Data System (ADS)

Beck, H.; van Dijk, A.; de Roo, A.

2014-12-01

Streamflow (Q) estimation in ungauged catchments is one of the greatest challenges facing hydrologists. We used observed Q from approximately 7500 small catchments (<10,000 km2) around the globe to train neural network ensembles to estimate temporal Q distribution characteristics from climate and physiographic characteristics of the catchments. In total 17 Q characteristics were selected, including mean annual Q, baseflow index, and a number of flow percentiles. Training coefficients of determination for the estimation of the Q characteristics ranged from 0.56 for the baseflow recession constant to 0.93 for the Q timing. Overall, climate indices dominated among the predictors. Predictors related to soils and geology were the least important, perhaps due to data quality. The trained neural network ensembles were subsequently applied spatially over the ice-free land surface including ungauged regions, resulting in global maps of the Q characteristics (0.125° spatial resolution). These maps possess several unique features: 1) they represent purely observation-driven estimates; 2) are based on an unprecedentedly large set of catchments; and 3) have associated uncertainty estimates. The maps can be used for various hydrological applications, including the diagnosis of macro-scale hydrological models. To demonstrate this, the produced maps were compared to equivalent maps derived from the simulated daily Q of five macro-scale hydrological models, highlighting various opportunities for improvement in model Q behavior. The produced dataset is available for download.

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

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.

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.

The Global Streamflow Indices and Metadata Archive (GSIM) - Part 1: The production of a daily streamflow archive and metadata

NASA Astrophysics Data System (ADS)

Do, Hong Xuan; Gudmundsson, Lukas; Leonard, Michael; Westra, Seth

2018-04-01

This is the first part of a two-paper series presenting the Global Streamflow Indices and Metadata archive (GSIM), a worldwide collection of metadata and indices derived from more than 35 000 daily streamflow time series. This paper focuses on the compilation of the daily streamflow time series based on 12 free-to-access streamflow databases (seven national databases and five international collections). It also describes the development of three metadata products (freely available at https://doi.pangaea.de/10.1594/PANGAEA.887477): (1) a GSIM catalogue collating basic metadata associated with each time series, (2) catchment boundaries for the contributing area of each gauge, and (3) catchment metadata extracted from 12 gridded global data products representing essential properties such as land cover type, soil type, and climate and topographic characteristics. The quality of the delineated catchment boundary is also made available and should be consulted in GSIM application. The second paper in the series then explores production and analysis of streamflow indices. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.

The U.S. Geological Survey streamflow and observation-well network in Massachusetts and Rhode Island

USGS Publications Warehouse

Zarriello, Phillip J.; Socolow, Roy S.

2003-01-01

The U.S. Geological Survey began systematic streamflow monitoring in Massachusetts nearly 100 years ago (1904) on the Connecticut River at Montague City. Since that time, hydrologic data collection has evolved into a monitoring network of 103 streamgage stations and 200 ground-water observation wells in Massachusetts and Rhode Island (2000 water year). Data from this network provide critical information for a variety of purposes to Federal, State, and local government agencies, engineering consultants, and the public. The uses of this information have been enhanced by the fact that about 70 percent of the streamgage stations and a small but increasing number of observation wells in Massachusetts and Rhode Island have been equipped with digital collection platforms that transmit data by satellite every 4 hours. Twenty-one of the telemetered streamgage stations are also equipped with precipitation recorders. The near real-time data provided by these stations, along with historical data collected at all stations, are available over the Internet at no charge. The monitoring network operated during the 2000 water year was summarized and evaluated with respect to spatial distribution, the current uses of the data, and the physical characteristics associated with the monitoring sites. This report provides maps that show locations and summary tables for active continuous record streamgage stations, discontinued streamgage stations, and observation wells in each of the 28 major basins identified by the Massachusetts Executive Office of Environmental Affairs and five of the major Rhode Island basins. Metrics of record length, regulation, physiographic region and physical and land-cover characteristics indicate that the streamflow-monitoring network represents a wide range of drainage-area sizes, physiographic regions, and basin characteristics. Most streamgage stations are affected by regulation, which provides information for specific water-management purposes, but

Rainfall and streamflow from small tree-covered and fern-covered and burned watersheds in Hawaii

Treesearch

H. W. Anderson; P. D. Duffy; Teruo Yamamoto

1966-01-01

Streamflow from two 30-acre watersheds near Honolulu was studied by using principal components regression analysis. Models using data on monthly, storm, and peak discharges were tested against several variables expressing amount and intensity of rainfall, and against variables expressing antecedent rainfall. Explained variation ranged from 78 to 94 percent. The...

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.

Evaluation of Strategies for Balancing Water Use and Streamflow Reductions in the Upper Charles River Basin, Eastern Massachusetts

USGS Publications Warehouse

Eggleston, Jack R.

2004-01-01

The upper Charles River basin, located 30 miles southwest of Boston, Massachusetts, is experiencing water shortages during the summer. Towns in the basin have instituted water-conservation programs and water-use bans to reduce summertime water use. During July through October, streamflow in the Charles River and its tributaries regularly falls below 0.50 cubic foot per second per square mile, the minimum streamflow used by the U.S. Fish and Wildlife Service as its Aquatic Base Flow standard for maintaining healthy freshwater ecosystems. To examine how human water use could be changed to mitigate these water shortages, a numerical ground-water flow model was modified and used in conjunction with response coefficients and optimization techniques. Streamflows at 10 locations on the Charles River and its tributaries were determined under various water-use scenarios and climatic conditions. A variety of engineered solutions to the water shortages were examined for their ability to increase water supplies and summertime streamflows. Results indicate that although human water use contributes to the problem of low summertime streamflows, human water use is not the only, or even the primary, cause of low flows in the basin. The lowest summertime streamflows increase by 12 percent but remain below the Aquatic Base Flow standard when all public water-supply pumpage and wastewater flows in the basin are eliminated in a simulation under average climatic conditions. Under dry climatic conditions, the same measures increase the lowest average monthly streamflow by 95 percent but do not increase it above the Aquatic Base Flow standard. The most promising water-management strategies to increase streamflows and water supplies, based on the study results, include wastewater recharge to the aquifer, altered management of pumping well schedules, regional water-supply sharing, and water conservation. In a scenario that simulated towns sharing water supplies, streamflow in the Charles

Improving estimates of streamflow characteristics using LANDSAT-1 (ERTS-1) imagery. [Delmarva Peninsula

NASA Technical Reports Server (NTRS)

Hollyday, E. F. (Principal Investigator)

1975-01-01

The author has identified the following significant results. Streamflow characteristics in the Delmarva Peninsula derived from the records of daily discharge of 20 gaged basins are representative of the full range in flow conditions and include all of those commonly used for design or planning purposes. They include annual flood peaks with recurrence intervals of 2, 5, 10, 25, and 50 years, mean annual discharge, standard deviation of the mean annual discharge, mean monthly discharges, standard deviation of the mean monthly discharges, low-flow characteristics, flood volume characteristics, and the discharge equalled or exceeded 50 percent of the time. Streamflow and basin characteristics were related by a technique of multiple regression using a digital computer. A control group of equations was computed using basin characteristics derived from maps and climatological records. An experimental group of equations was computed using basin characteristics derived from LANDSAT imagery as well as from maps and climatological records. Based on a reduction in standard error of estimate equal to or greater than 10 percent, the equations for 12 stream flow characteristics were substantially improved by adding to the analyses basin characteristics derived from LANDSAT imagery.

Increased evaporation following widespread tree mortality limits streamflow response

NASA Astrophysics Data System (ADS)

Biederman, J. A.; Harpold, A. A.; Gochis, D. J.; Ewers, B. E.; Reed, D. E.; Papuga, S. A.; Brooks, P. D.

2014-07-01

A North American epidemic of mountain pine beetle (MPB) has disturbed over 5 million ha of forest containing headwater catchments crucial to water resources. However, there are limited observations of MPB effects on partitioning of precipitation between vapor loss and streamflow, and to our knowledge these fluxes have not been observed simultaneously following disturbance. We combined eddy covariance vapor loss (V), catchment streamflow (Q), and stable isotope indicators of evaporation (E) to quantify hydrologic partitioning over 3 years in MPB-impacted and control sites. Annual control V was conservative, varying only from 573 to 623 mm, while MPB site V varied more widely from 570 to 700 mm. During wet periods, MPB site V was greater than control V in spite of similar above-canopy potential evapotranspiration (PET). During a wet year, annual MPB V was greater and annual Q was lower as compared to an average year, while in a dry year, essentially all water was partitioned to V. Ratios of 2H and 18O in stream and soil water showed no kinetic evaporation at the control site, while MPB isotope ratios fell below the local meteoric water line, indicating greater E and snowpack sublimation (Ss) counteracted reductions in transpiration (T) and sublimation of canopy-intercepted snow (Sc). Increased E was possibly driven by reduced canopy shading of shortwave radiation, which averaged 21 W m-2 during summer under control forest as compared to 66 W m-2 under MPB forest. These results show that abiotic vapor losses may limit widely expected streamflow increases.

Long-term (in)stability of the climate-streamflow relationship

NASA Astrophysics Data System (ADS)

Saft, Margarita; Peel, Murray; Coxon, Gemma; Freer, Jim; Parajka, Juraj; Woods, Ross

2017-04-01

Land use changes have long been known to alter streamflow production for a given climatic input. Recently, extended shifts in climate were also shown to be capable of altering catchment internal functioning and streamflow production for a given climatic input. This study investigates the stability of climate-streamflow relationships in natural catchments in different regions of the world for the first time, using datasets of natural/reference catchments from Europe, US, and Australia. Changes in climate-streamflow relationships are investigated statistically on the interannual to interdecadal timescale and related to interdecadal climate variability. We compare the frequency and magnitude of shifts in climate-streamflow relationship between different regions, and discuss what any differences in shift frequency and magnitude might be related to. This study draws attention to the issues of catchment vulnerability to changes in external factors, catchment-climate co-evolution, and long-term catchment memory.

MODFLOW-LGR-Modifications to the streamflow-routing package (SFR2) to route streamflow through locally refined grids

USGS Publications Warehouse

Mehl, Steffen W.; Hill, Mary C.

2011-01-01

This report documents modifications to the Streamflow-Routing Package (SFR2) to route streamflow through grids constructed using the multiple-refined-areas capability of shared node Local Grid Refinement (LGR) of MODFLOW-2005. MODFLOW-2005 is the U.S. Geological Survey modular, three-dimensional, finite-difference groundwater-flow model. LGR provides the capability to simulate groundwater flow by using one or more block-shaped, higher resolution local grids (child model) within a coarser grid (parent model). LGR accomplishes this by iteratively coupling separate MODFLOW-2005 models such that heads and fluxes are balanced across the shared interfacing boundaries. Compatibility with SFR2 allows for streamflow routing across grids. LGR can be used in two- and three-dimensional, steady-state and transient simulations and for simulations of confined and unconfined groundwater systems.

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

Summary of annual mean, maximum, minimum, and L-scale statistics of daily mean streamflow for 712 U.S. Geological Survey streamflow-gaging Stations in Texas Through 2003

USGS Publications Warehouse

Asquith, William H.; Vrabel, Joseph; Roussel, Meghan C.

2007-01-01

Analysts and managers of surface-water resources might have interest in selected statistics of daily mean streamflow for U.S. Geological Survey (USGS) streamflow-gaging stations in Texas. The selected statistics are the annual mean, maximum, minimum, and L-scale of daily meanstreamflow. Annual L-scale of streamflow is a robust measure of the variability of the daily mean streamflow for a given year. The USGS, in cooperation with the Texas Commission on Environmental Quality, initiated in 2006a data and reporting process to generate annual statistics for 712 USGS streamflow-gaging stations in Texas. A graphical depiction of the history of the annual statistics for most active and inactive, continuous-record gaging stations in Texas provides valuable information by conveying the historical perspective of streamflow for the watershed. Each figure consists off our time-series plots of the annual statistics of daily mean streamflow for each streamflow-gaging station. Each of the four plots is augmented with horizontal lines that depict the mean and median annual values of the corresponding statistic for the period of record. Monotonic trends for each of the four annual statistics also are identified using Kendall's T. The history of one or more streamflow-gaging stations could be used in a watershed, river basin, or other regional context by analysts and managers of surface-water resources to guide scientific, regulatory, or other inquiries of streamflow conditions in Texas.

Long-term variation analysis of a tropical river's annual streamflow regime over a 50-year period

NASA Astrophysics Data System (ADS)

Seyam, Mohammed; Othman, Faridah

2015-07-01

Studying the long-term changes of streamflow is an important tool for enhancing water resource and river system planning, design, and management. The aim of this work is to identify the long-term variations in annual streamflow regime over a 50-year period from 1961 to 2010 in the Selangor River, which is one of the main tropical rivers in Malaysia. Initially, the data underwent preliminary independence, normality, and homogeneity testing using the Pearson correlation coefficient and Shapiro-Wilk and Pettitt's tests, respectively. The work includes a study and analysis of the changes through nine variables describing the annual streamflow and variations in the yearly duration of high and low streamflows. The analyses were conducted via two time scales: yearly and sub-periodic. The sub-periods were obtained by segmenting the 50 years into seven sub-periods by two techniques, namely the change-point test and direct method. Even though analysis revealed nearly negligible changes in mean annual flow over the study period, the maximum annual flow generally increased while the minimum annual flow significantly decreased with respect to time. It was also observed that the variables describing the dispersion in streamflow continually increased with respect to time. An obvious increase was detected in the yearly duration of danger level of streamflow, a slight increase was noted in the yearly duration of warning and alert levels, and a slight decrease in the yearly duration of low streamflow was found. The perceived changes validate the existence of long-term changes in annual streamflow regime, which increase the probability of floods and droughts occurring in future. In light of the results, attention should be drawn to developing water resource management and flood protection plans in order to avert the harmful effects potentially resulting from the expected changes in annual streamflow regime.

Runoff generation processes and fraction of young water for streamflow and groundwater in a pre-alpine forested catchment

NASA Astrophysics Data System (ADS)

Zuecco, Giulia; Penna, Daniele; van Meerveld, Ilja; Borga, Marco

2017-04-01

Understanding of runoff generation mechanisms and storage dynamics is needed for sustainable management of water resources, particularly in catchments characterized by marked seasonality in rainfall. However, temporal and spatial variability of hydrological processes can hinder a detailed comprehension of catchment functioning. In this study, we use hydrometric data and stable isotope data from a 2-ha forested catchment in the Italian pre-Alps to i) identify seasonal changes in runoff generation, ii) determine the factors that affect the hysteretic relations between streamflow and soil moisture and between streamflow and shallow groundwater, and iii) estimate the fraction of young water in stream water and shallow groundwater. Streamflow, soil moisture and groundwater levels were measured continuously between August 2012 and December 2015. Soil moisture was measured at 0-30 cm depth by four time domain reflectometers installed at different locations along a riparian-hillslope transect. Depth to water table was measured in two piezometers installed at a depth of 2.0 and 1.8 m in the riparian zone. Water samples for isotopic analysis were taken monthly from bulk precipitation and approximately biweekly from stream water and groundwater. The relations between streamflow (independent variable), soil moisture and depth to water table (dependent variables) were analyzed by computing a hysteresis index that provides information on the direction, the extent and the shape of the loops for 103 rainfall-runoff events. The temporal variability of the hysteresis index was related to event characteristics (mean and maximum rainfall intensity, rainfall amount and total stormflow) and antecedent soil moisture conditions. We observed threshold-like relations between stormflow and the sum of rainfall and the antecedent soil moisture index and an exponential relation between the change in groundwater level and stormflow. Clockwise hysteretic relations were common between streamflow

Streamflow Modification Through Management of Eastern Forests

Treesearch

James E. Douglass; Wayne T. Swank

1972-01-01

Protection of the water resource was a primary objective in establishing the National Forest System in America, and improving quantity, quality, and timing of streamflow is an important objective of forest management in certain regions of the United States.Effective management of the forest for increased streamflow presupposes that impact of various management...

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.

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

Assessing the Snow Advance Index as potential predictor of winter streamflow of the Iberian Peninsula Rivers

NASA Astrophysics Data System (ADS)

Hidalgo-Muñoz, José Manuel; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2015-04-01

This study examines the ability of the Eurasian snow cover increase during the previous October as potential predictor of winter streamflow in the Iberian Peninsula Rivers. The streamflow data base used has been provided by the Center for Studies and Experimentation of Public Works, CEDEX. Series from gauging stations and reservoirs with less than 10% of missing data (filled by regression with well correlated neighboring stations) have been considered. The homogeneity of these series has been evaluated through the Pettit test and degree of human alteration by the Common Area Index. The application of these criteria led to the selection of 382 streamflow time series homogeneously distributed over the Iberian Peninsula, covering the period 1975-2008. For this streamflow data, winter seasonal values were obtained by averaging the monthly values from January to March. The recently proposed Snow Advance Index (SAI) was employed to monitor the snow cover increase during previous October. The stability of the correlations was the criterion followed to establish if SAI could be considered as potential predictor of winter streamflow at each gauging station. Winter streamflow is predicted using a linear regression model. A leave-one-out cross validation approach was adopted to create calibration and validations subsets. The correlation coefficient (RHO), Root Mean Square Error Skill Score (RMSESS) and the Gerrity Skill Score (GSS) were used to evaluate the forecasting skill. From the 382 stations evaluated, significant and stable correlations with SAI were found in 238 stations, covering most of the IP (except for the Cantabrian and Mediterranean slopes). Some forecasting skill was found in 223 of them, being this skill moderate (RHO>0.44, RMSESS>10%, GSS>0.2) in 141 of them, and particularly good (RHO>0.5, RMSESS>20%, GSS>0.4) in 23. This study shows that the SAI of previous October is a reliable predictor of following winter streamflow for the Iberian Peninsula Rivers

Streamflow Impacts of Biofuel Policy-Driven Landscape Change

PubMed Central

Khanal, Sami; Anex, Robert P.; Anderson, Christopher J.; Herzmann, Daryl E.

2014-01-01

Likely changes in precipitation (P) and potential evapotranspiration (PET) resulting from policy-driven expansion of bioenergy crops in the United States are shown to create significant changes in streamflow volumes and increase water stress in the High Plains. Regional climate simulations for current and biofuel cropping system scenarios are evaluated using the same atmospheric forcing data over the period 1979–2004 using the Weather Research Forecast (WRF) model coupled to the NOAH land surface model. PET is projected to increase under the biofuel crop production scenario. The magnitude of the mean annual increase in PET is larger than the inter-annual variability of change in PET, indicating that PET increase is a forced response to the biofuel cropping system land use. Across the conterminous U.S., the change in mean streamflow volume under the biofuel scenario is estimated to range from negative 56% to positive 20% relative to a business-as-usual baseline scenario. In Kansas and Oklahoma, annual streamflow volume is reduced by an average of 20%, and this reduction in streamflow volume is due primarily to increased PET. Predicted increase in mean annual P under the biofuel crop production scenario is lower than its inter-annual variability, indicating that additional simulations would be necessary to determine conclusively whether predicted change in P is a response to biofuel crop production. Although estimated changes in streamflow volume include the influence of P change, sensitivity results show that PET change is the significantly dominant factor causing streamflow change. Higher PET and lower streamflow due to biofuel feedstock production are likely to increase water stress in the High Plains. When pursuing sustainable biofuels policy, decision-makers should consider the impacts of feedstock production on water scarcity. PMID:25289698

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.

Using a predictive model to evaluate spatiotemporal variability in streamflow permanence across the Pacific Northwest region

NASA Astrophysics Data System (ADS)

Jaeger, K. L.

2017-12-01

The U.S. Geological Survey (USGS) has developed the PRObability Of Streamflow PERmanence (PROSPER) model, a GIS-based empirical model that provides predictions of the annual probability of a stream channel having year-round flow (Streamflow permanence probability; SPP) for any unregulated and minimally-impaired stream channel in the Pacific Northwest (Washington, Oregon, Idaho, western Montana). The model provides annual predictions for 2004-2016 at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions, and static physiographic variables associated with the upstream basin. Prediction locations correspond to the channel network consistent with the National Hydrography Dataset stream grid and are publicly available through the USGS StreamStats platform (https://water.usgs.gov/osw/streamstats/). In snowmelt-driven systems, the most informative predictor variable was mean upstream snow water equivalent on May 1, which highlights the influence of late spring snow cover for supporting streamflow in mountain river networks. In non-snowmelt-driven systems, the most informative variable was mean annual precipitation. Streamflow permanence probabilities varied across the study area by geography and from year-to-year. Notably lower SPP corresponded to the climatically drier subregions of the study area. Higher SPP were concentrated in coastal and higher elevation mountain regions. In addition, SPP appeared to trend with average hydroclimatic conditions, which were also geographically coherent. The year-to-year variability lends support for the growing recognition of the spatiotemporal dynamism of streamflow permanence. An analysis of three focus basins located in contrasting geographical and hydroclimatic settings demonstrates differences in the sensitivity of streamflow permanence to antecedent climate conditions as a function of geography. Consequently, results suggest that PROSPER model can be a useful tool to evaluate regions of the

Water quality, streamflow conditions, and annual flow-duration curves for streams of the San Juan–Chama Project, southern Colorado and northern New Mexico, 1935-2010

USGS Publications Warehouse

Falk, Sarah E.; Anderholm, Scott K.; Hafich, Katya A.

2013-01-01

The Albuquerque–Bernalillo County Water Utility Authority supplements the municipal water supply for the Albuquerque metropolitan area, in central New Mexico, with water diverted from the Rio Grande. Water diverted from the Rio Grande for municipal use is derived from the San Juan–Chama Project, which delivers water from streams in the southern San Juan Mountains in the Colorado River Basin in southern Colorado to the Rio Chama watershed and the Rio Grande Basin in northern New Mexico. The U.S. Geological Survey, in cooperation with Albuquerque–Bernalillo County Water Utility Authority, has compiled historical streamflow and water-quality data and collected new water-quality data to characterize the water quality and streamflow conditions and annual flow variability, as characterized by annual flow-duration curves, of streams of the San Juan–Chama Project. Nonparametric statistical methods were applied to calculate annual and monthly summary statistics of streamflow, trends in streamflow conditions were evaluated with the Mann–Kendall trend test, and annual variation in streamflow conditions was evaluated with annual flow-duration curves. The study area is located in northern New Mexico and southern Colorado and includes the Rio Blanco, Little Navajo River, and Navajo River, tributaries of the San Juan River in the Colorado River Basin located in the southern San Juan Mountains, and Willow Creek and Horse Lake Creek, tributaries of the Rio Chama in the Rio Grande Basin. The quality of water in the streams in the study area generally varied by watershed on the basis of the underlying geology and the volume and source of the streamflow. Water from the Rio Blanco and Little Navajo River watersheds, primarily underlain by volcanic deposits, volcaniclastic sediments and landslide deposits derived from these materials, was compositionally similar and had low specific-conductance values relative to the other streams in the study area. Water from the Navajo River

Using diurnal streamflow and conductivity data to monitor and forecast runoff in a snowmelt dominated watershed

NASA Astrophysics Data System (ADS)

Miller, S.; Miller, S. N.

2016-12-01

Natural diurnal fluctuations in streamflow are common in many types of streams and scales for different reasons (i.e. snowmelt, evapotranspiration, infiltration, precipitation). Scientific literature has placed little consideration on the role diurnal cycles as they may appear insignificant from a water management point of view; however, recent insights into the timing and shape of the diurnal cycle have led to new methods for eco-hydrologic characterization of a given watershed. The diurnal effect is usually not detectible from visual investigation of a stream, but requires a minimum of hourly continuous measurement. In the 1990s the United States Geological Survey began collecting hourly river stage measurements for thousands of stream gauge stations across the US, ushering in new methods of analysis and comparison. A nested watershed study with ten stream gauging stations recording sub-hourly river stage was deployed in a snowmelt-dominated region of the Medicine Bow National Forest in southeastern Wyoming in 2013. In addition, at each stream gauging station sub-hourly conductivity and temperature data was recorded to aid in eco-hydrologic characterization of the different watersheds. Early summer results show asymmetry in the diurnal cycle during snowmelt, with a steeper rising and a flatter falling limb. As snowmelt becomes a less contributing component of streamflow later in the season, the asymmetry shifts to a flatter rising limb and steeper falling limb. Stream conductivity is low during snowmelt and begins to gradually increase as baseflow becomes a larger portion of total streamflow. The study region is recovering from a mountain pine beetle epidemic that peaked in 2008. Prior research suggests the bark beetle epidemic has had little effect on annual streamflow patterns; however, several results show an earlier shift in the day of year in which peak annual streamflow is observed. The diurnal cycle is likely to comprise a larger percentage of daily

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.

HEC-4 Monthly Streamflow Simulation (User’s Manual)

DTIC Science & Technology

1971-02-01

adding this product to the uroduct of the complement of this multiplier and the value of the ele - ment in the inconsistent matrix. The averaged or...the month pre- ceding the first month specified (by input data) to be generated. The var-’ ele M.1A is comnutel f’or the subscript o" ; that conforms...1-4 .f’o .Td74 r m 1i4 tf’t 0atQ P PkPkk4 el %04 k04 fl 0 -41. ----- 4-4-4 a-4 -44 44-4- - -4 *fF_4Q cacao---1 00 0404- -4 Cb 0 0-r-o .0. 4

SWAT-based streamflow and embayment modeling of Karst-affected Chapel branch watershed, South Carolina

Treesearch

Devendra Amatya; M. Jha; A.E. Edwards; T.M. Williams; D.R. Hitchcock

2011-01-01

SWAT is a GIS-based basin-scale model widely used for the characterization of hydrology and water quality of large, complex watersheds; however, SWAT has not been fully tested in watersheds with karst geomorphology and downstream reservoir-like embayment. In this study, SWAT was applied to test its ability to predict monthly streamflow dynamics for a 1,555 ha karst...

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.

Temporal variability in the suspended sediment load and streamflow of the Doce River

NASA Astrophysics Data System (ADS)

Oliveira, Kyssyanne Samihra Santos; Quaresma, Valéria da Silva

2017-10-01

Long-term records of streamflow and suspended sediment load provide a better understanding of the evolution of a river mouth, and its adjacent waters and a support for mitigation programs associated with extreme events and engineering projects. The aim of this study is to investigate the temporal variability in the suspended sediment load and streamflow of the Doce River to the Atlantic Ocean, between 1990 and 2013. Streamflow and suspended sediment load were analyzed at the daily, seasonal, and interannual scales. The results showed that at the daily scale, Doce River flood events are due to high intensity and short duration rainfalls, which means that there is a flashy response to rainfall. At the monthly and season scales, approximately 94% of the suspended sediment supply occurs during the wet season. Extreme hydrological events are important for the interannual scale for Doce River sediment supply to the Atlantic Ocean. The results suggest that a summation of anthropogenic interferences (deforestation, urbanization and soil degradation) led to an increase of extreme hydrological events. The findings of this study shows the importance of understanding the typical behavior of the Doce River, allowing the detection of extreme hydrological conditions, its causes and possible environmental and social consequences.

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

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.

Potential Utility of the Real-Time TMPA-RT Precipitation Estimates in Streamflow Prediction

NASA Technical Reports Server (NTRS)

Su, Fengge; Gao, Huilin; Huffman, George J.; Lettenmaier, Dennis P.

2010-01-01

We investigate the potential utility of the real-time Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA-RT) data for streamflow prediction, both through direct comparisons of TMPA-RT estimates with a gridded gauge product, and through evaluation of streamflow simulations over four tributaries of La Plata Basin (LPB) in South America using the two precipitation products. Our assessments indicate that the relative accuracy and the hydrologic performance of TMPA-RT-based streamflow simulations generally improved after February 2005. The improvements in TMPA-RT since 2005 are closely related to upgrades in the TMPA-RT algorithm in early February, 2005 which include use of additional microwave sensors (AMSR-E and AMSU-B) and implementation of different calibration schemes. Our work suggests considerable potential for hydrologic prediction using purely satellite-derived precipitation estimates (no adjustments by in situ gauges) in parts of the globe where in situ observations are sparse.

Ensemble Data Assimilation for Streamflow Forecasting: Experiments with Ensemble Kalman Filter and Particle Filter

NASA Astrophysics Data System (ADS)

Hirpa, F. A.; Gebremichael, M.; Hopson, T. M.; Wojick, R.

2011-12-01

We present results of data assimilation of ground discharge observation and remotely sensed soil moisture observations into Sacramento Soil Moisture Accounting (SACSMA) model in a small watershed (1593 km2) in Minnesota, the Unites States. Specifically, we perform assimilation experiments with Ensemble Kalman Filter (EnKF) and Particle Filter (PF) in order to improve streamflow forecast accuracy at six hourly time step. The EnKF updates the soil moisture states in the SACSMA from the relative errors of the model and observations, while the PF adjust the weights of the state ensemble members based on the likelihood of the forecast. Results of the improvements of each filter over the reference model (without data assimilation) will be presented. Finally, the EnKF and PF are coupled together to further improve the streamflow forecast accuracy.

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

Hydro-Climatic Data Network (HCDN) Streamflow Data Set, 1874-1988

USGS Publications Warehouse

Slack, James Richard; Lumb, Alan M.; Landwehr, Jurate Maciunas

1993-01-01

records of 'natural flow' were permitted, nor was any record extended or had missing values 'filled in' using computational algorithms. If the streamflow at a station was judged to be free of controls for only a part of the entire period of record that is available for the station, then only that part was included in the HCDN, but only if it was of sufficient length (generally 20 years) to warrant inclusion. In addition to the daily mean discharge values, complete station identification information and basin characteristics were retrieved from WATSTORE for inclusion in the HCDN. Statistical characteristics, including the monthly mean discharge, as well as the annual mean, minimum and maximum discharge values, were derived for the records in the HCDN data set. For a full description of the development and content of the Hydro-Climatic Data Network, please take a look at the HCDN Report.

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

Hydrological responses to climatic changes in the Yellow River basin, China: Climatic elasticity and streamflow prediction

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Liu, Jianyu; Singh, Vijay P.; Shi, Peijun; Sun, Peng

2017-11-01

Prediction of streamflow of the Yellow River basin was done using downscaled precipitation and temperature based on outputs of 12 GCMs under RCP2.6 and RCP8.5 scenarios. Streamflow changes of 37 tributaries of the Yellow River basin during 2070-2099 were predicted related to different GCMs and climatic scenarios using Budyko framework. The results indicated that: (1) When compared to precipitation and temperature during 1960-1979, increasing precipitation and temperature are dominant during 2070-2099. Particularly, under RCP8.5, increase of 10% and 30% can be detected for precipitation and temperature respectively; (2) Precipitation changes have larger fractional contribution to streamflow changes than temperature changes, being the major driver for spatial and temporal patterns of water resources across the Yellow River basin; (3) 2070-2099 period will witness increased streamflow depth and decreased streamflow can be found mainly in the semi-humid regions and headwater regions of the Yellow River basin, which can be attributed to more significant increase of temperature than precipitation in these regions; (4) Distinctly different picture of streamflow changes can be observed with consideration of different outputs of GCMs which can be attributed to different outputs of GCMs under different scenarios. Even so, under RCP2.6 and RCP8.5 scenarios, 36.8% and 71.1% of the tributaries of the Yellow River basin are dominated by increasing streamflow. The results of this study are of theoretical and practical merits in terms of management of water resources and also irrigated agriculture under influences of changing climate.

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.

Post-processing of multi-hydrologic model simulations for improved streamflow projections

NASA Astrophysics Data System (ADS)

khajehei, sepideh; Ahmadalipour, Ali; Moradkhani, Hamid

2016-04-01

Hydrologic model outputs are prone to bias and uncertainty due to knowledge deficiency in model and data. Uncertainty in hydroclimatic projections arises due to uncertainty in hydrologic model as well as the epistemic or aleatory uncertainties in GCM parameterization and development. This study is conducted to: 1) evaluate the recently developed multi-variate post-processing method for historical simulations and 2) assess the effect of post-processing on uncertainty and reliability of future streamflow projections in both high-flow and low-flow conditions. The first objective is performed for historical period of 1970-1999. Future streamflow projections are generated for 10 statistically downscaled GCMs from two widely used downscaling methods: Bias Corrected Statistically Downscaled (BCSD) and Multivariate Adaptive Constructed Analogs (MACA), over the period of 2010-2099 for two representative concentration pathways of RCP4.5 and RCP8.5. Three semi-distributed hydrologic models were employed and calibrated at 1/16 degree latitude-longitude resolution for over 100 points across the Columbia River Basin (CRB) in the pacific northwest USA. Streamflow outputs are post-processed through a Bayesian framework based on copula functions. The post-processing approach is relying on a transfer function developed based on bivariate joint distribution between the observation and simulation in historical period. Results show that application of post-processing technique leads to considerably higher accuracy in historical simulations and also reducing model uncertainty in future streamflow projections.

Rainfall-runoff characteristics and effects of increased urban density on streamflow and infiltration in the eastern part of the San Jacinto River basin, Riverside County, California

USGS Publications Warehouse

Guay, Joel R.

2002-01-01

To better understand the rainfall-runoff characteristics of the eastern part of the San Jacinto River Basin and to estimate the effects of increased urbanization on streamflow, channel infiltration, and land-surface infiltration, a long-term (1950?98) time series of monthly flows in and out of the channels and land surfaces were simulated using the Hydrologic Simulation Program- FORTRAN (HSPF) rainfall-runoff model. Channel and land-surface infiltration includes rainfall or runoff that infiltrates past the zone of evapotranspiration and may become ground-water recharge. The study area encompasses about 256 square miles of the San Jacinto River drainage basin in Riverside County, California. Daily streamflow (for periods with available data between 1950 and 1998), and daily rainfall and evaporation (1950?98) data; monthly reservoir storage data (1961?98); and estimated mean annual reservoir inflow data (for 1974 conditions) were used to calibrate the rainfall-runoff model. Measured and simulated mean annual streamflows for the San Jacinto River near San Jacinto streamflow-gaging station (North-South Fork subbasin) for 1950?91 and 1997?98 were 14,000 and 14,200 acre-feet, respectively, a difference of 1.4 percent. The standard error of the mean for measured and simulated annual streamflow in the North-South Fork subbasin was 3,520 and 3,160 acre-feet, respectively. Measured and simulated mean annual streamflows for the Bautista Creek streamflow-gaging station (Bautista Creek subbasin) for 1950?98 were 980 acre-feet and 991 acre-feet, respectively, a difference of 1.1 percent. The standard error of the mean for measured and simulated annual streamflow in the Bautista Creek subbasin was 299 and 217 acre-feet, respectively. Measured and simulated annual streamflows for the San Jacinto River above State Street near San Jacinto streamflow-gaging station (Poppet subbasin) for 1998 were 23,400 and 23,500 acre-feet, respectively, a difference of 0.4 percent. The simulated

Muted responses of streamflow and suspended sediment flux in a wildfire-affected watershed

NASA Astrophysics Data System (ADS)

Owens, P. N.; Giles, T. R.; Petticrew, E. L.; Leggat, M. S.; Moore, R. D.; Eaton, B. C.

2013-11-01

In August 2003 a severe wildfire burnt 62% of Fishtrap Creek, a 158 km2 watershed in central British Columbia, Canada. Streamflows were obtained for the period 1980-2010 and suspended sediment fluxes were determined for the period 2004-2010 for Fishtrap Creek and these were compared to data for nearby Jamieson Creek, which was not affected by the wildfire. Peak streamflows in Fishtrap Creek after the wildfire were not significantly higher than before the wildfire, although total annual runoff had increased. Perhaps the most important change in streamflows following the wildfire was that peak flows associated with the annual freshet occurred earlier in the year (by ca. 2 weeks). Following the wildfire, monthly total suspended sediment fluxes peaked in April in Fishtrap Creek and May in Jamieson Creek, which reflects the change in timing of peak streamflows in Fishtrap. Specific suspended sediment yields were low in the first year following the wildfire (2004), and peak values for the 2004-2010 monitoring period occurred in 2006. Average specific suspended sediment yields over the monitoring period were similar for both watersheds at 2.8 and 2.9 t km- 2 year- 1 for Fishtrap and Jamieson watersheds, respectively. The muted responses of streamflows and suspended sediment fluxes following this severe wildfire are due to the lack of winter precipitation and the low intensities of summer rainfall events in the first year following the wildfire. Greater winter precipitation and associated snowmelt in subsequent years coincided with vegetation recovery. The major changes in the wildfire-affected watershed were increased bank erosion and channel migration due to a loss of root strength and cohesion, which occurred 3-5 years after the fire. This work demonstrates that the hydrological and geomorphological responses of watersheds to wildfires are a function of the severity of the wildfire and the timing and nature of driving forces (i.e. rainfall intensity, winter

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

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

Assessing glacier melt contribution to streamflow at Universidad Glacier, central Andes of Chile

NASA Astrophysics Data System (ADS)

Bravo, Claudio; Loriaux, Thomas; Rivera, Andrés; Brock, Ben W.

2017-07-01

Glacier melt is an important source of water for high Andean rivers in central Chile, especially in dry years, when it can be an important contributor to flows during late summer and autumn. However, few studies have quantified glacier melt contribution to streamflow in this region. To address this shortcoming, we present an analysis of meteorological conditions and ablation for Universidad Glacier, one of the largest valley glaciers in the central Andes of Chile at the head of the Tinguiririca River, for the 2009-2010 ablation season. We used meteorological measurements from two automatic weather stations installed on the glacier to drive a distributed temperature-index and runoff routing model. The temperature-index model was calibrated at the lower weather station site and showed good agreement with melt estimates from an ablation stake and sonic ranger, and with a physically based energy balance model. Total modelled glacier melt is compared with river flow measurements at three sites located between 0.5 and 50 km downstream. Universidad Glacier shows extremely high melt rates over the ablation season which may exceed 10 m water equivalent in the lower ablation area, representing between 10 and 13 % of the mean monthly streamflow at the outlet of the Tinguiririca River Basin between December 2009 and March 2010. This contribution rises to a monthly maximum of almost 20 % in March 2010, demonstrating the importance of glacier runoff to streamflow, particularly in dry years such as 2009-2010. The temperature-index approach benefits from the availability of on-glacier meteorological data, enabling the calculation of the local hourly variable lapse rate, and is suited to high melt regimes, but would not be easily applicable to glaciers further north in Chile where sublimation is more significant.

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

Predicting the likelihood of altered streamflows at ungauged rivers across the conterminous United States

USGS Publications Warehouse

Eng, Kenny; Carlisle, Daren M.; Wolock, David M.; Falcone, James A.

2013-01-01

An approach is presented in this study to aid water-resource managers in characterizing streamflow alteration at ungauged rivers. Such approaches can be used to take advantage of the substantial amounts of biological data collected at ungauged rivers to evaluate the potential ecological consequences of altered streamflows. National-scale random forest statistical models are developed to predict the likelihood that ungauged rivers have altered streamflows (relative to expected natural condition) for five hydrologic metrics (HMs) representing different aspects of the streamflow regime. The models use human disturbance variables, such as number of dams and road density, to predict the likelihood of streamflow alteration. For each HM, separate models are derived to predict the likelihood that the observed metric is greater than (‘inflated’) or less than (‘diminished’) natural conditions. The utility of these models is demonstrated by applying them to all river segments in the South Platte River in Colorado, USA, and for all 10-digit hydrologic units in the conterminous United States. In general, the models successfully predicted the likelihood of alteration to the five HMs at the national scale as well as in the South Platte River basin. However, the models predicting the likelihood of diminished HMs consistently outperformed models predicting inflated HMs, possibly because of fewer sites across the conterminous United States where HMs are inflated. The results of these analyses suggest that the primary predictors of altered streamflow regimes across the Nation are (i) the residence time of annual runoff held in storage in reservoirs, (ii) the degree of urbanization measured by road density and (iii) the extent of agricultural land cover in the river basin.

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.

Climate, water use, and land surface transformation in an irrigation intensive watershed - streamflow responses from 1950 through 2010

USGS Publications Warehouse

Dale, Joseph; Zou, Chris B.; Andrews, William J.; Long, James M.; Liang, Ye; Qiao, Lei

2015-01-01

Climatic variability and land surface change have a wide range of effects on streamflow and are often difficult to separate. We analyzed long-term records of climate, land use and land cover, and re-constructed the water budget based on precipitation, groundwater levels, and water use from 1950 through 2010 in the Cimarron–Skeleton watershed and a portion of the Cimarron–Eagle Chief watershed in Oklahoma, an irrigation-intensive agricultural watershed in the Southern Great Plains, USA. Our results show that intensive irrigation through alluvial aquifer withdrawal modifies climatic feedback and alters streamflow response to precipitation. Increase in consumptive water use was associated with decreases in annual streamflow, while returning croplands to non-irrigated grasslands was associated with increases in streamflow. Along with groundwater withdrawal, anthropogenic-induced factors and activities contributed nearly half to the observed variability of annual streamflow. Streamflow was more responsive to precipitation during the period of intensive irrigation between 1965 and 1984 than the period of relatively lower water use between 1985 and 2010. The Cimarron River is transitioning from a historically flashy river to one that is more stable with a lower frequency of both high and low flow pulses, a higher baseflow, and an increased median flow due in part to the return of cropland to grassland. These results demonstrated the interrelationship among climate, land use, groundwater withdrawal and streamflow regime and the potential to design agricultural production systems and adjust irrigation to mitigate impact of increasing climate variability on streamflow in irrigation intensive agricultural watershed.

Basin characteristics, history of stream gaging, and statistical summary of selected streamflow records for the Rapid Creek basin, western South Dakota

USGS Publications Warehouse

Driscoll, Daniel G.; Zogorski, John S.

1990-01-01

The report presents a summary of basin characteristics affecting streamflow, a history of the U.S. Geological Survey 's stream-gaging program, and a compilation of discharge records and statistical summaries for selected sites within the Rapid Creek basin. It is the first in a series which will investigate surface-water/groundwater relations along Rapid Creek. The summary of basin characteristics includes descriptions of the geology and hydrogeology, physiography and climate, land use and vegetation, reservoirs, and water use within the basin. A recounting of the U.S. Geological Survey 's stream-gaging program and a tabulation of historic stream-gaging stations within the basin are furnished. A compilation of monthly and annual mean discharge values for nine currently operated, long-term, continuous-record, streamflow-gaging stations on Rapid Creek is presented. The statistical summary for each site includes summary statistics on monthly and annual mean values, correlation matrix for monthly values, serial correlation for 1 year lag for monthly values, percentile rankings for monthly and annual mean values, low and high value tables, duration curves, and peak-discharge tables. Records of monthend contents for two reservoirs within the basin also are presented. (USGS)

Exploring the link between meteorological drought and streamflow to inform water resource management

NASA Astrophysics Data System (ADS)

Lennard, Amy; Macdonald, Neil; Hooke, Janet

2015-04-01

Drought indicators are an under-used metric in UK drought management. Standardised drought indicators offer a potential monitoring and management tool for operational water resource management. However, the use of these metrics needs further investigation. This work uses statistical analysis of the climatological drought signal based on meteorological drought indicators and observed streamflow data to explore the link between meteorological drought and hydrological drought to inform water resource management for a single water resource region. The region, covering 21,000 km2 of the English Midlands and central Wales, includes a variety of landscapes and climatological conditions. Analysis of the links between meteorological drought and hydrological drought performed using streamflow data from 'natural' catchments indicates a close positive relationship between meteorological drought indicators and streamflow, enhancing confidence in the application of drought indicators for monitoring and management. However, many of the catchments in the region are subject to modification through impoundments, abstractions and discharge. Therefore, it is beneficial to explore how climatological drought signal propagates into managed hydrological systems. Using a longitudinal study of catchments and sub-catchments that include natural and modified river reaches the relationship between meteorological and hydrological drought is explored. Initial statistical analysis of meteorological drought indicators and streamflow data from modified catchments shows a significantly weakened statistical relationship and reveals how anthropogenic activities may alter hydrological drought characteristics in modified catchments. Exploring how meteorological drought indicators link to streamflow across the water supply region helps build an understanding of their utility for operational water resource management.

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.

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

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

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

Validation of streamflow measurements made with acoustic doppler current profilers

USGS Publications Warehouse

Oberg, K.; Mueller, D.S.

2007-01-01

The U.S. Geological Survey and other international agencies have collaborated to conduct laboratory and field validations of acoustic Doppler current profiler (ADCP) measurements of streamflow. Laboratory validations made in a large towing basin show that the mean differences between tow cart velocity and ADCP bottom-track and water-track velocities were -0.51 and -1.10%, respectively. Field validations of commercially available ADCPs were conducted by comparing streamflow measurements made with ADCPs to reference streamflow measurements obtained from concurrent mechanical current-meter measurements, stable rating curves, salt-dilution measurements, or acoustic velocity meters. Data from 1,032 transects, comprising 100 discharge measurements, were analyzed from 22 sites in the United States, Canada, Sweden, and The Netherlands. Results of these analyses show that broadband ADCP streamflow measurements are unbiased when compared to the reference discharges regardless of the water mode used for making the measurement. Measurement duration is more important than the number of transects for reducing the uncertainty of the ADCP streamflow measurement. ?? 2007 ASCE.

Streamflow Observations From Cameras: Large-Scale Particle Image Velocimetry or Particle Tracking Velocimetry?

NASA Astrophysics Data System (ADS)

Tauro, F.; Piscopia, R.; Grimaldi, S.

2017-12-01

Image-based methodologies, such as large scale particle image velocimetry (LSPIV) and particle tracking velocimetry (PTV), have increased our ability to noninvasively conduct streamflow measurements by affording spatially distributed observations at high temporal resolution. However, progress in optical methodologies has not been paralleled by the implementation of image-based approaches in environmental monitoring practice. We attribute this fact to the sensitivity of LSPIV, by far the most frequently adopted algorithm, to visibility conditions and to the occurrence of visible surface features. In this work, we test both LSPIV and PTV on a data set of 12 videos captured in a natural stream wherein artificial floaters are homogeneously and continuously deployed. Further, we apply both algorithms to a video of a high flow event on the Tiber River, Rome, Italy. In our application, we propose a modified PTV approach that only takes into account realistic trajectories. Based on our findings, LSPIV largely underestimates surface velocities with respect to PTV in both favorable (12 videos in a natural stream) and adverse (high flow event in the Tiber River) conditions. On the other hand, PTV is in closer agreement than LSPIV with benchmark velocities in both experimental settings. In addition, the accuracy of PTV estimations can be directly related to the transit of physical objects in the field of view, thus providing tangible data for uncertainty evaluation.

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.

Geospatial tools effectively estimate nonexceedance probabilities of daily streamflow at ungauged and intermittently gauged locations in Ohio

USGS Publications Warehouse

Farmer, William H.; Koltun, Greg

2017-01-01

Study regionThe state of Ohio in the United States, a humid, continental climate.Study focusThe estimation of nonexceedance probabilities of daily streamflows as an alternative means of establishing the relative magnitudes of streamflows associated with hydrologic and water-quality observations.New hydrological insights for the regionSeveral methods for estimating nonexceedance probabilities of daily mean streamflows are explored, including single-index methodologies (nearest-neighboring index) and geospatial tools (kriging and topological kriging). These methods were evaluated by conducting leave-one-out cross-validations based on analyses of nearly 7 years of daily streamflow data from 79 unregulated streamgages in Ohio and neighboring states. The pooled, ordinary kriging model, with a median Nash–Sutcliffe performance of 0.87, was superior to the single-site index methods, though there was some bias in the tails of the probability distribution. Incorporating network structure through topological kriging did not improve performance. The pooled, ordinary kriging model was applied to 118 locations without systematic streamgaging across Ohio where instantaneous streamflow measurements had been made concurrent with water-quality sampling on at least 3 separate days. Spearman rank correlations between estimated nonexceedance probabilities and measured streamflows were high, with a median value of 0.76. In consideration of application, the degree of regulation in a set of sample sites helped to specify the streamgages required to implement kriging approaches successfully.

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

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.

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

Reconstructions of Columbia River streamflow from tree-ring chronologies in the Pacific Northwest, USA

USGS Publications Warehouse

Littell, Jeremy; Pederson, Gregory T.; Gray, Stephen T.; Tjoelker, Michael; Hamlet, Alan F.; Woodhouse, Connie A.

2016-01-01

We developed Columbia River streamflow reconstructions using a network of existing, new, and updated tree-ring records sensitive to the main climatic factors governing discharge. Reconstruction quality is enhanced by incorporating tree-ring chronologies where high snowpack limits growth, which better represent the contribution of cool-season precipitation to flow than chronologies from trees positively sensitive to hydroclimate alone. The best performing reconstruction (back to 1609 CE) explains 59% of the historical variability and the longest reconstruction (back to 1502 CE) explains 52% of the variability. Droughts similar to the high-intensity, long-duration low flows observed during the 1920s and 1940s are rare, but occurred in the early 1500s and 1630s-1640s. The lowest Columbia flow events appear to be reflected in chronologies both positively and negatively related to streamflow, implying low snowpack and possibly low warm-season precipitation. High flows of magnitudes observed in the instrumental record appear to have been relatively common, and high flows from the 1680s to 1740s exceeded the magnitude and duration of observed wet periods in the late-19th and 20th Century. Comparisons between the Columbia River reconstructions and future projections of streamflow derived from global climate and hydrologic models show the potential for increased hydrologic variability, which could present challenges for managing water in the face of competing demands

Streamflow Measurements in North-Central Nebraska, November 2006

USGS Publications Warehouse

Peterson, Steven M.; Strauch, Kellan R.

2007-01-01

Streamflow measurements were made during November of 2006 in the Elkhorn and Loup River basins and selected streams in the Niobrara and Platte River basins in north-central Nebraska. At these 531 sites, flows ranging from no flow to 2,600 ft3/s were measured or observed. The data are presented in a table along with the quality of measurement and the method that was used. Maps show the location of the study area and the sites.

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.

Simulation of streamflow in the McTier Creek watershed, South Carolina

USGS Publications Warehouse

Feaster, Toby D.; Golden, Heather E.; Odom, Kenneth R.; Lowery, Mark A.; Conrads, Paul; Bradley, Paul M.

2010-01-01

The McTier Creek watershed is located in the Sand Hills ecoregion of South Carolina and is a small catchment within the Edisto River Basin. Two watershed hydrology models were applied to the McTier Creek watershed as part of a larger scientific investigation to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River Basin. The two models are the topography-based hydrological model (TOPMODEL) and the grid-based mercury model (GBMM). TOPMODEL uses the variable-source area concept for simulating streamflow, and GBMM uses a spatially explicit modified curve-number approach for simulating streamflow. The hydrologic output from TOPMODEL can be used explicitly to simulate the transport of mercury in separate applications, whereas the hydrology output from GBMM is used implicitly in the simulation of mercury fate and transport in GBMM. The modeling efforts were a collaboration between the U.S. Geological Survey and the U.S. Environmental Protection Agency, National Exposure Research Laboratory. Calibrations of TOPMODEL and GBMM were done independently while using the same meteorological data and the same period of record of observed data. Two U.S. Geological Survey streamflow-gaging stations were available for comparison of observed daily mean flow with simulated daily mean flow-station 02172300, McTier Creek near Monetta, South Carolina, and station 02172305, McTier Creek near New Holland, South Carolina. The period of record at the Monetta gage covers a broad range of hydrologic conditions, including a drought and a significant wet period. Calibrating the models under these extreme conditions along with the normal flow conditions included in the record enhances the robustness of the two models. Several quantitative assessments of the goodness of fit between model simulations and the observed daily mean flows were done. These included the Nash-Sutcliffe coefficient

Georgia's Surface-Water Resources and Streamflow Monitoring Network, 2006

USGS Publications Warehouse

Nobles, Patricia L.; ,

2006-01-01

The U.S. Geological Survey (USGS) network of 223 real-time monitoring stations, the 'Georgia HydroWatch,' provides real-time water-stage data, with streamflow computed at 198 locations, and rainfall recorded at 187 stations. These sites continuously record data on 15-minute intervals and transmit the data via satellite to be incorporated into the USGS National Water Information System database. These data are automatically posted to the USGS Web site for public dissemination (http://waterdata.usgs.gov/ga/nwis/nwis). The real-time capability of this network provides information to help emergency-management officials protect human life and property during floods, and mitigate the effects of prolonged drought. The map at right shows the USGS streamflow monitoring network for Georgia and major watersheds. Streamflow is monitored at 198 sites statewide, more than 80 percent of which include precipitation gages. Various Federal, State, and local agencies fund these streamflow monitoring stations.

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.

Regional analyses of streamflow characteristics

USGS Publications Warehouse

Riggs, H.C.

1973-01-01

This manual describes various ways of generalizing streamflow characteristics and evaluates the applicability and reliability of each under various hydrologic conditions. Several alternatives to regionalization are briefly described.

ECOLOGICALLY-RELEVANT QUANTIFICATION OF STREAMFLOW REGIMES IN WESTERN STREAMS

EPA Science Inventory

This report describes the rationale for and application of a protocol for estimation of ecologically-relevant streamflow metrics that quantify streamflow regime for ungaged sites subject to a range of human impact. The analysis presented here is focused on sites sampled by the U....

Forecasting daily streamflow using online sequential extreme learning machines

NASA Astrophysics Data System (ADS)

Lima, Aranildo R.; Cannon, Alex J.; Hsieh, William W.

2016-06-01

While nonlinear machine methods have been widely used in environmental forecasting, in situations where new data arrive continually, the need to make frequent model updates can become cumbersome and computationally costly. To alleviate this problem, an online sequential learning algorithm for single hidden layer feedforward neural networks - the online sequential extreme learning machine (OSELM) - is automatically updated inexpensively as new data arrive (and the new data can then be discarded). OSELM was applied to forecast daily streamflow at two small watersheds in British Columbia, Canada, at lead times of 1-3 days. Predictors used were weather forecast data generated by the NOAA Global Ensemble Forecasting System (GEFS), and local hydro-meteorological observations. OSELM forecasts were tested with daily, monthly or yearly model updates. More frequent updating gave smaller forecast errors, including errors for data above the 90th percentile. Larger datasets used in the initial training of OSELM helped to find better parameters (number of hidden nodes) for the model, yielding better predictions. With the online sequential multiple linear regression (OSMLR) as benchmark, we concluded that OSELM is an attractive approach as it easily outperformed OSMLR in forecast accuracy.

August Median Streamflow on Ungaged Streams in Eastern Aroostook County, Maine

USGS Publications Warehouse

Lombard, Pamela J.; Tasker, Gary D.; Nielsen, Martha G.

2003-01-01

Methods for estimating August median streamflow were developed for ungaged, unregulated streams in the eastern part of Aroostook County, Maine, with drainage areas from 0.38 to 43 square miles and mean basin elevations from 437 to 1,024 feet. Few long-term, continuous-record streamflow-gaging stations with small drainage areas were available from which to develop the equations; therefore, 24 partial-record gaging stations were established in this investigation. A mathematical technique for estimating a standard low-flow statistic, August median streamflow, at partial-record stations was applied by relating base-flow measurements at these stations to concurrent daily flows at nearby long-term, continuous-record streamflow- gaging stations (index stations). Generalized least-squares regression analysis (GLS) was used to relate estimates of August median streamflow at gaging stations to basin characteristics at these same stations to develop equations that can be applied to estimate August median streamflow on ungaged streams. GLS accounts for varying periods of record at the gaging stations and the cross correlation of concurrent streamflows among gaging stations. Twenty-three partial-record stations and one continuous-record station were used for the final regression equations. The basin characteristics of drainage area and mean basin elevation are used in the calculated regression equation for ungaged streams to estimate August median flow. The equation has an average standard error of prediction from -38 to 62 percent. A one-variable equation uses only drainage area to estimate August median streamflow when less accuracy is acceptable. This equation has an average standard error of prediction from -40 to 67 percent. Model error is larger than sampling error for both equations, indicating that additional basin characteristics could be important to improved estimates of low-flow statistics. Weighted estimates of August median streamflow, which can be used when

Accuracy of selected techniques for estimating ice-affected streamflow

USGS Publications Warehouse

Walker, John F.

1991-01-01

This paper compares the accuracy of selected techniques for estimating streamflow during ice-affected periods. The techniques are classified into two categories - subjective and analytical - depending on the degree of judgment required. Discharge measurements have been made at three streamflow-gauging sites in Iowa during the 1987-88 winter and used to established a baseline streamflow record for each site. Using data based on a simulated six-week field-tip schedule, selected techniques are used to estimate discharge during the ice-affected periods. For the subjective techniques, three hydrographers have independently compiled each record. Three measures of performance are used to compare the estimated streamflow records with the baseline streamflow records: the average discharge for the ice-affected period, and the mean and standard deviation of the daily errors. Based on average ranks for three performance measures and the three sites, the analytical and subjective techniques are essentially comparable. For two of the three sites, Kruskal-Wallis one-way analysis of variance detects significant differences among the three hydrographers for the subjective methods, indicating that the subjective techniques are less consistent than the analytical techniques. The results suggest analytical techniques may be viable tools for estimating discharge during periods of ice effect, and should be developed further and evaluated for sites across the United States.

Streamflow gain and loss of selected streams in northern Arkansas

USGS Publications Warehouse

Freiwald, David A.

1987-01-01

This map shows streamflow gain and loss measurements (seepage runs) on the Crooked, Osage, and Spavinaw Creeks, and Illinois, Kings, Mulberry, Spring, and Strawberry Rivers during the low-flow conditions from September 1982 to October 1984. Data indicated that streamflow gains and losses resulted from differences in lithology of the predominately carbonate rocks and from the presence of faults. The Kings and Strawberry Rivers and Osage Creek were gaining streams throughout their length, however wastewater discharges precluded an accurate determination on Osage Creek. Crooked and Spavinaw Creeks and the Illinois, Spring, and Mulberry Rivers generally were gaining streams throughout most of their lengths although short losing reaches were identified. The largest gains in streamflow generally occurred were Mississippian formation predominated near the streams. Faults that intersected the stream channels primarily were responsible for streamflow losses. The specific conductance of water increased in the stream reaches that had the most significant streamflow gains. The specific conductance of water in tributaries was generally higher than that in larger streams. (Author 's abstract)

Uses, funding, and availability of continuous streamflow data in Montana

USGS Publications Warehouse

Shields, R.R.; White, M.K.

1984-01-01

This report documents the results of a study of the uses, funding, and availability of continuous streamflow data collected and published by the U.S. Geological Survey in Montana. Data uses and funding sources are identified for the 218 continuous streamflow gages currently (1984) being operated. These stations are supported by 18 different funding sources at a budget for the 1984 water year of $1,065,000. The streamflow-gaging program in Montana has evolved through the years as Federal, State, and local needs for surface-water data have increased. Continuous streamflow records for periods ranging from less than 1 year to more than 90 years have been collected. This report describes phase 1 of a cost-effectiveness study of the streamflow-gaging program in Montana. Evaluation of the program indicates that numerous agencies use the data for studies involving regional hydrology, hydrologic systems, and planning and design. They also use the data for operations of existing hydroelectric and irrigation dams, forecasting flood and seasonal flows, water-quality monitoring, research studies for fish habitat, and other uses such as recreational management. (USGS)

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.

A time-corrector device for adjusting streamflow records

Treesearch

Raymond W. Lavigne

1960-01-01

The first job in compiling streamflow data from streamflow charts is to mark storm rises and storm peaks, make corrections as necessary for time and stage height, and account for irregularities on the chart. Errors in the time scale can result from faulty clock operation, irregularities in chart take-up by the drum, or expansion of the paper. This note suggests a...

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.

An investigation of the role of winter and spring precipitation as drivers of streamflow in the Missouri River Headwaters using tree-ring reconstructions

NASA Astrophysics Data System (ADS)

Frederick, S. E.; Woodhouse, C. A.; Martin, J. T.; Pederson, G. T.

2017-12-01

The Missouri River supplies water to over 3 million basin residents and is a driving force for the nation's agricultural and energy sectors. However, with changing climate and declining snowpack in western North America, seasonal water yields are becoming less predictable, revealing a gap in our understanding of regional hydroclimate and drivers of streamflow within the basin. By analyzing the relationship between seasonal precipitation and streamflow in the Missouri River Headwaters sub-basin, this study seeks to expand our knowledge based on the instrumental record alone. Here we present the first annually-resolved tree-ring reconstruction of spring precipitation for the Missouri River Headwaters. This reconstruction along with existing tree-ring reconstructions of April 1 snow-water equivalence (SWE) (Pederson et al. 2011) and natural streamflow (Martin, J.T. & Pederson, G.T., personal communication, June 2017) are used to test the feasibility of detecting a variable influence of winter and spring precipitation on streamflow over past centuries, and relative to the modern period. Initial analyses indicate that April 1 SWE is a significant control on streamflow, however, the April 1 SWE record does not fully account for anomalies observed in the streamflow record. This study therefore seeks to determine whether spring precipitation can account for some of this asynchronous variability observed between the April 1 SWE and streamflow records. Aside from improved understanding of the relationship between hydroclimate and streamflow in the headwaters of the Missouri River, our findings offer insights relating to changing contributions from snowmelt and spring precipitation, and long-term hydrologic variability and trends relevant to water resource management and planning efforts.

Statewide analysis of the drainage-area ratio method for 34 streamflow percentile ranges in Texas

USGS Publications Warehouse

Asquith, William H.; Roussel, Meghan C.; Vrabel, Joseph

2006-01-01

method were computed. Statewide statistics (median, mean, and standard deviation) of the station-pair specific statistics subsequently were computed and are tabulated herein. A separate analysis considered conditioning station pairs to those stations within 100 miles of each other and with the absolute value of the logarithm (base-10) of the ratio of the drainage areas greater than or equal to 0.25. Statewide statistics of the conditional station-pair specific statistics were computed and are tabulated. The conditional analysis is preferable because of the anticipation that small separation distances reflect similar hydrologic conditions and the observation of large variation in exponent estimates for similar-sized drainage areas. The conditional analysis determined that the exponent is about 0.89 for streamflow percentiles from 0 to about 50 percent, is about 0.92 for percentiles from about 50 to about 65 percent, and is about 0.93 for percentiles from about 65 to about 85 percent. The exponent decreases rapidly to about 0.70 for percentiles nearing 100 percent. The computation of the bias-correction factor is sensitive to the range analysis interval (range of streamflow percentile); however, evidence suggests that in practice the drainage-area method can be considered unbiased. Finally, for general application, suggested values of the exponent are tabulated for 54 percentiles of daily mean streamflow in Texas; when these values are used, the bias correction is unity.

Climate controls on streamflow variability in the Missouri River Basin

NASA Astrophysics Data System (ADS)

Wise, E.; Woodhouse, C. A.; McCabe, G. J., Jr.; Pederson, G. T.; St-Jacques, J. M.

2017-12-01

The Missouri River's hydroclimatic variability presents a challenge for water managers, who must balance many competing demands on the system. Water resources in the Missouri River Basin (MRB) have increasingly been challenged by the droughts and floods that have occurred over the past several decades and the potential future exacerbation of these extremes by climate change. Here, we use observed and modeled hydroclimatic data and estimated natural flow records to describe the climatic controls on streamflow in the upper and lower portions of the MRB, examine atmospheric and oceanic patterns associated with high- and low-flow years, and investigate trends in climate and streamflow over the instrumental period. Results indicate that the two main source regions for total outflow, in the uppermost and lowermost parts of the basin, are under the influence of very different sets of climatic controls. Winter precipitation, impacted by changes in zonal versus meridional flow from the Pacific Ocean, as well as spring precipitation and temperature, play a key role in surface water supply variability in the upper basin. Lower basin flow is significantly correlated with precipitation in late spring and early summer, indicative of Atlantic-influenced circulation variability affecting the flow of moisture from the Gulf of Mexico. The upper basin, with decreasing snowpack and streamflow and warming spring temperatures, will be less likely to provide important flow supplements to the lower basin in the future.

Systematic change in global patterns of streamflow following volcanic eruptions.

PubMed

Iles, Carley E; Hegerl, Gabriele C

2015-11-01

Following large explosive volcanic eruptions precipitation decreases over much of the globe1-6, particularly in climatologically wet regions4,5. Stratospheric volcanic aerosols reflect sunlight, which reduces evaporation, whilst surface cooling stabilises the atmosphere and reduces its water-holding capacity7. Circulation changes modulate this global precipitation reduction on regional scales1,8-10. Despite the importance of rivers to people, it has been unclear whether volcanism causes detectable changes in streamflow given large natural variability. Here we analyse observational records of streamflow volume for fifty large rivers from around the world which cover between two and 6 major volcanic eruptions in the 20 th and late 19 th century. We find statistically significant reductions in flow following eruptions for the Amazon, Congo, Nile, Orange, Ob, Yenisey and Kolyma amongst others. When data from neighbouring rivers are combined - based on the areas where climate models simulate either an increase or a decrease in precipitation following eruptions - a significant (p<0.1) decrease in streamflow following eruptions is detected in northern South American, central African and high-latitude Asian rivers, and on average across wet tropical and subtropical regions. We also detect a significant increase in southern South American and SW North American rivers. This suggests that future volcanic eruptions could substantially affect global water availability.

Systematic change in global patterns of streamflow following volcanic eruptions

PubMed Central

Iles, Carley E.; Hegerl, Gabriele C.

2016-01-01

Following large explosive volcanic eruptions precipitation decreases over much of the globe1–6, particularly in climatologically wet regions4,5. Stratospheric volcanic aerosols reflect sunlight, which reduces evaporation, whilst surface cooling stabilises the atmosphere and reduces its water-holding capacity7. Circulation changes modulate this global precipitation reduction on regional scales1,8–10. Despite the importance of rivers to people, it has been unclear whether volcanism causes detectable changes in streamflow given large natural variability. Here we analyse observational records of streamflow volume for fifty large rivers from around the world which cover between two and 6 major volcanic eruptions in the 20th and late 19th century. We find statistically significant reductions in flow following eruptions for the Amazon, Congo, Nile, Orange, Ob, Yenisey and Kolyma amongst others. When data from neighbouring rivers are combined - based on the areas where climate models simulate either an increase or a decrease in precipitation following eruptions – a significant (p<0.1) decrease in streamflow following eruptions is detected in northern South American, central African and high-latitude Asian rivers, and on average across wet tropical and subtropical regions. We also detect a significant increase in southern South American and SW North American rivers. This suggests that future volcanic eruptions could substantially affect global water availability. PMID:27279897

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

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.

Effects of water-supply reservoirs on streamflow in Massachusetts

USGS Publications Warehouse

Levin, Sara B.

2016-10-06

reservoir simulation tool was used to simulate 35 single- and multiple-reservoir systems in Massachusetts over a 44-year period (water years 1961 to 2004) under two water-use scenarios. The no-pumping scenario assumes no water withdrawal pumping, and the pumping scenario incorporates average annual pumping rates from 2000 to 2004. By comparing the results of the two scenarios, the total streamflow alteration can be parsed into the portion of streamflow alteration caused by the presence of a reservoir and the additional streamflow alteration caused by the level of water use of the system.For each reservoir system, the following metrics were computed to characterize the frequency, duration, and magnitude of reservoir outflow volumes compared with unaltered streamflow conditions: (1) the median number of days per year in which the reservoir did not spill, (2) the median duration of the longest consecutive period of no-spill days per year, and (3) the lowest annual flow duration exceedance probability at which the outflows are significantly different from estimated unaltered streamflow at the 95-percent confidence level. Most reservoirs in the study do not spill during the summer months even under no-pumping conditions. The median number of days during which there was no spillage was less than 365 for all reservoirs in the study, indicating that, even under reported pumping conditions, the reservoirs refill to full volume and spill at least once during nondrought years, typically in the spring.Thirteen multiple-reservoir systems consisting of two or three hydrologically connected reservoirs were included in the study. Because operating rules used to manage multiple-reservoir systems are not available, these systems were simulated under two pumping scenarios, one in which water transfers between reservoirs are minimal and one in which reservoirs continually transferred water to intermediate or terminal reservoirs. These two scenarios provided upper and lower estimates of

Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin

USGS Publications Warehouse

Shrestha, M.S.; Artan, Guleid A.; Bajracharya, S.R.; Sharma, R. R.

2008-01-01

In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.

Improving estimates of streamflow characteristics by using Landsat-1 imagery

USGS Publications Warehouse

Hollyday, Este F.

1976-01-01

Imagery from the first Earth Resources Technology Satellite (renamed Landsat-1) was used to discriminate physical features of drainage basins in an effort to improve equations used to estimate streamflow characteristics at gaged and ungaged sites. Records of 20 gaged basins in the Delmarva Peninsula of Maryland, Delaware, and Virginia were analyzed for 40 statistical streamflow characteristics. Equations relating these characteristics to basin characteristics were obtained by a technique of multiple linear regression. A control group of equations contains basin characteristics derived from maps. An experimental group of equations contains basin characteristics derived from maps and imagery. Characteristics from imagery were forest, riparian (streambank) vegetation, water, and combined agricultural and urban land use. These basin characteristics were isolated photographically by techniques of film-density discrimination. The area of each characteristic in each basin was measured photometrically. Comparison of equations in the control group with corresponding equations in the experimental group reveals that for 12 out of 40 equations the standard error of estimate was reduced by more than 10 percent. As an example, the standard error of estimate of the equation for the 5-year recurrence-interval flood peak was reduced from 46 to 32 percent. Similarly, the standard error of the equation for the mean monthly flow for September was reduced from 32 to 24 percent, the standard error for the 7-day, 2-year recurrence low flow was reduced from 136 to 102 percent, and the standard error for the 3-day, 2-year flood volume was reduced from 30 to 12 percent. It is concluded that data from Landsat imagery can substantially improve the accuracy of estimates of some streamflow characteristics at sites in the Delmarva Peninsula.

Synthesis of streamflow recession curves in dry environments

NASA Astrophysics Data System (ADS)

Arciniega, Saul; Breña-Naranjo, Agustín; Pedrozo-Acuña, Adrían

2015-04-01

The elucidation and predictability of hydrological systems can largely benefit by extracting observed patterns in processes, data and models. Such type of research framework in hydrology, also known as synthesis has gained significant attention over the last decade. For instance, hydrological synthesis implies that the identification of patterns in catchment behavior can enhance the extrapolation of hydrological signatures over large spatial and temporal scales. Hydrological signatures during dry periods such as streamflow recession curves (SRC) are of special interest in regions coping with water scarcity. Indeed, the study of SRCs from observed hydrographs allows to extract information about the storage-discharge relationship of a specific catchment and some of their groundwater hydraulic properties. This work aims at performing a synthesis work of SRCs in semi-arid & arid environments across Northern Mexico. Our dataset consisted in observed daily SRCs in 63 catchments with minima human interferences. Three streamflow recession extraction methods (Vogel, Brutsaert and Aksoy-Wittenberg) along with four recession models (Maillet, Boussinesq, Coutagne y Wittenberg) and three parameter estimation techniques (regressions, lower envelope y data binning) were used to determine the combination among different possible methods, processes and models that better describes SRCs in our study sites. Our results show that the extraction method proposed by Aksoy-Wittenberg along with Coutagne's nonlinear recession model provides a better approximation of SRCs across Northern Mexico, whereas regression was found to be the most adequate parameter estimation method. This study suggests that hydrological synthesis turned out to be an useful framework to identify similar patterns and model parameters during dry periods across Mexico's water-limited environments.

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

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

A statistical data assimilation method for seasonal streamflow forecasting to optimize hydropower reservoir management in data-scarce regions

NASA Astrophysics Data System (ADS)

Arsenault, R.; Mai, J.; Latraverse, M.; Tolson, B.

2017-12-01

Probabilistic ensemble forecasts generated by the ensemble streamflow prediction (ESP) methodology are subject to biases due to errors in the hydrological model's initial states. In day-to-day operations, hydrologists must compensate for discrepancies between observed and simulated states such as streamflow. However, in data-scarce regions, little to no information is available to guide the streamflow assimilation process. The manual assimilation process can then lead to more uncertainty due to the numerous options available to the forecaster. Furthermore, the model's mass balance may be compromised and could affect future forecasts. In this study we propose a data-driven approach in which specific variables that may be adjusted during assimilation are defined. The underlying principle was to identify key variables that would be the most appropriate to modify during streamflow assimilation depending on the initial conditions such as the time period of the assimilation, the snow water equivalent of the snowpack and meteorological conditions. The variables to adjust were determined by performing an automatic variational data assimilation on individual (or combinations of) model state variables and meteorological forcing. The assimilation aimed to simultaneously optimize: (1) the error between the observed and simulated streamflow at the timepoint where the forecasts starts and (2) the bias between medium to long-term observed and simulated flows, which were simulated by running the model with the observed meteorological data on a hindcast period. The optimal variables were then classified according to the initial conditions at the time period where the forecast is initiated. The proposed method was evaluated by measuring the average electricity generation of a hydropower complex in Québec, Canada driven by this method. A test-bed which simulates the real-world assimilation, forecasting, water release optimization and decision-making of a hydropower cascade was

A proposed streamflow-data program for North Dakota

USGS Publications Warehouse

Crosby, O.A.

1970-01-01

An evaluation of the streamflow data available in North Dakota was made to provide guidelines for planning future programs. The basic steps in the evaluation procedure were (1) definition of the long-term goals of the streamflow data program in quantitative form, (2) examination and analysis of all available data to determine which goals have already been met, and (3) consideration of alternate programs and techniques to meet the remaining objectives. None of the goals could be met by generalization of the data for gaged basins by regression analysis. This fact indicates that significant changes should be made in the present data program to obtain better areal coverage to achieve the goals set. A streamflow data program based on the guidelines developed in this study is proposed for the future.

Causes of systematic over- or underestimation of low streamflows by use of index-streamgage approaches in the United States

USGS Publications Warehouse

Eng, K.; Kiang, J.E.; Chen, Y.-Y.; Carlisle, D.M.; Granato, G.E.

2011-01-01

Low-flow characteristics can be estimated by multiple linear regressions or the index-streamgage approach. The latter transfers streamflow information from a hydrologically similar, continuously gaged basin ('index streamgage') to one with a very limited streamflow record, but often results in biased estimates. The application of the index-streamgage approach can be generalized into three steps: (1) selection of streamflow information of interest, (2) definition of hydrologic similarity and selection of index streamgage, and (3) application of an information-transfer approach. Here, we explore the effects of (1) the range of streamflow values, (2) the areal density of streamgages, and (3) index-streamgage selection criteria on the bias of three information-transfer approaches on estimates of the 7-day, 10-year minimum streamflow (Q7, 10). The three information-transfer approaches considered are maintenance of variance extension, base-flow correlation, and ratio of measured to concurrent gaged streamflow (Q-ratio invariance). Our results for 1120 streamgages throughout the United States suggest that only a small portion of the total bias in estimated streamflow values is explained by the areal density of the streamgages and the hydrologic similarity between the two basins. However, restricting the range of streamflow values used in the index-streamgage approach reduces the bias of estimated Q7, 10 values substantially. Importantly, estimated Q7, 10 values are heavily biased when the observed Q7, 10 values are near zero. Results of the analysis also showed that Q7, 10 estimates from two of the three index-streamgage approaches have lower root-mean-square error values than estimates derived from multiple regressions for the large regions considered in this study.

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.

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.

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.

Streamflow variability over the 1881–2011 period in northern Quebec: comparison of hydrological reconstructions based on tree rings and geopotential height field reanalysis

DOE PAGES

Brigode, Pierre; Brissette, Francois; Nicault, Antoine; ...

2016-09-06

Over the last decades, different methods have been used by hydrologists to extend observed hydro-climatic time series, based on other data sources, such as tree rings or sedimentological datasets. For example, tree ring multi-proxies have been studied for the Caniapiscau Reservoir in northern Québec (Canada), leading to the reconstruction of flow time series for the last 150 years. In this paper, we applied a new hydro-climatic reconstruction method on the Caniapiscau Reservoir and compare the obtained streamflow time series against time series derived from dendrohydrology by other authors on the same catchment and study the natural streamflow variability over themore » 1881–2011 period in that region. This new reconstruction is based not on natural proxies but on a historical reanalysis of global geopotential height fields, and aims firstly to produce daily climatic time series, which are then used as inputs to a rainfall–runoff model in order to obtain daily streamflow time series. The performances of the hydro-climatic reconstruction were quantified over the observed period, and showed good performances, in terms of both monthly regimes and interannual variability. The streamflow reconstructions were then compared to two different reconstructions performed on the same catchment by using tree ring data series, one being focused on mean annual flows and the other on spring floods. In terms of mean annual flows, the interannual variability in the reconstructed flows was similar (except for the 1930–1940 decade), with noteworthy changes seen in wetter and drier years. For spring floods, the reconstructed interannual variabilities were quite similar for the 1955–2011 period, but strongly different between 1880 and 1940. Here, the results emphasize the need to apply different reconstruction methods on the same catchments. Indeed, comparisons such as those above highlight potential differences between available reconstructions and, finally, allow a

Streamflow variability over the 1881–2011 period in northern Quebec: comparison of hydrological reconstructions based on tree rings and geopotential height field reanalysis

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

Brigode, Pierre; Brissette, Francois; Nicault, Antoine

Over the last decades, different methods have been used by hydrologists to extend observed hydro-climatic time series, based on other data sources, such as tree rings or sedimentological datasets. For example, tree ring multi-proxies have been studied for the Caniapiscau Reservoir in northern Québec (Canada), leading to the reconstruction of flow time series for the last 150 years. In this paper, we applied a new hydro-climatic reconstruction method on the Caniapiscau Reservoir and compare the obtained streamflow time series against time series derived from dendrohydrology by other authors on the same catchment and study the natural streamflow variability over themore » 1881–2011 period in that region. This new reconstruction is based not on natural proxies but on a historical reanalysis of global geopotential height fields, and aims firstly to produce daily climatic time series, which are then used as inputs to a rainfall–runoff model in order to obtain daily streamflow time series. The performances of the hydro-climatic reconstruction were quantified over the observed period, and showed good performances, in terms of both monthly regimes and interannual variability. The streamflow reconstructions were then compared to two different reconstructions performed on the same catchment by using tree ring data series, one being focused on mean annual flows and the other on spring floods. In terms of mean annual flows, the interannual variability in the reconstructed flows was similar (except for the 1930–1940 decade), with noteworthy changes seen in wetter and drier years. For spring floods, the reconstructed interannual variabilities were quite similar for the 1955–2011 period, but strongly different between 1880 and 1940. Here, the results emphasize the need to apply different reconstruction methods on the same catchments. Indeed, comparisons such as those above highlight potential differences between available reconstructions and, finally, allow a

OSSE Observations of Centaurus A Over 18 Months

DTIC Science & Technology

1994-01-01

OSSE OBSERVATIONS OF CENTAURUS A OVER 18 MONTHS R.L. Kinzer, W.N. Johnson, J.D. Kurfess, M.S. Strickman, J.E. Grove, R.A. Kroeger E. O. Hulburt...D.C. 20375-5320 ABSTRACT OSSE observed Centaurus A at energies between 0.05 and 10 MeV in 1991, 1992, and in 1993. During each observation, this...radio galaxy Centaurus A (NGC 5128) on three occasions in 1991, 1992, and 1993. This source is among the brightest extragalactic objects above 100 keV

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

Streamflow statistics for unregulated and regulated conditions for selected locations on the Upper Yellowstone and Bighorn Rivers, Montana and Wyoming, 1928-2002

USGS Publications Warehouse

Chase, Katherine J.

2014-01-01

Major floods in 1996 and 1997 intensified public debate about 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 carry out 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 within the watershed. Streamflow statistics, such as flow-frequency 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 low-flow frequency data and general monthly and annual statistics for unregulated and regulated streamflow conditions for the Upper Yellowstone and Bighorn Rivers for the 1928–2002 study period; these data are presented in this report. Unregulated streamflow represents flow conditions 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.

Quantifying uncertainties in streamflow predictions through signature based inference of hydrological model parameters

NASA Astrophysics Data System (ADS)

Fenicia, Fabrizio; Reichert, Peter; Kavetski, Dmitri; Albert, Calro

2016-04-01

The calibration of hydrological models based on signatures (e.g. Flow Duration Curves - FDCs) is often advocated as an alternative to model calibration based on the full time series of system responses (e.g. hydrographs). Signature based calibration is motivated by various arguments. From a conceptual perspective, calibration on signatures is a way to filter out errors that are difficult to represent when calibrating on the full time series. Such errors may for example occur when observed and simulated hydrographs are shifted, either on the "time" axis (i.e. left or right), or on the "streamflow" axis (i.e. above or below). These shifts may be due to errors in the precipitation input (time or amount), and if not properly accounted in the likelihood function, may cause biased parameter estimates (e.g. estimated model parameters that do not reproduce the recession characteristics of a hydrograph). From a practical perspective, signature based calibration is seen as a possible solution for making predictions in ungauged basins. Where streamflow data are not available, it may in fact be possible to reliably estimate streamflow signatures. Previous research has for example shown how FDCs can be reliably estimated at ungauged locations based on climatic and physiographic influence factors. Typically, the goal of signature based calibration is not the prediction of the signatures themselves, but the prediction of the system responses. Ideally, the prediction of system responses should be accompanied by a reliable quantification of the associated uncertainties. Previous approaches for signature based calibration, however, do not allow reliable estimates of streamflow predictive distributions. Here, we illustrate how the Bayesian approach can be employed to obtain reliable streamflow predictive distributions based on signatures. A case study is presented, where a hydrological model is calibrated on FDCs and additional signatures. We propose an approach where the likelihood

How does spatial variability of climate affect catchment streamflow predictions?

EPA Science Inventory

Spatial variability of climate can negatively affect catchment streamflow predictions if it is not explicitly accounted for in hydrologic models. In this paper, we examine the changes in streamflow predictability when a hydrologic model is run with spatially variable (distribute...

On the Performance of Alternate Conceptual Ecohydrological Models for Streamflow Prediction

NASA Astrophysics Data System (ADS)

Naseem, Bushra; Ajami, Hoori; Cordery, Ian; Sharma, Ashish

2016-04-01

A merging of a lumped conceptual hydrological model with two conceptual dynamic vegetation models is presented to assess the performance of these models for simultaneous simulations of streamflow and leaf area index (LAI). Two conceptual dynamic vegetation models with differing representation of ecological processes are merged with a lumped conceptual hydrological model (HYMOD) to predict catchment scale streamflow and LAI. The merged RR-LAI-I model computes relative leaf biomass based on transpiration rates while the RR-LAI-II model computes above ground green and dead biomass based on net primary productivity and water use efficiency in response to soil moisture dynamics. To assess the performance of these models, daily discharge and 8-day MODIS LAI product for 27 catchments of 90 - 1600km2 in size located in the Murray - Darling Basin in Australia are used. Our results illustrate that when single-objective optimisation was focussed on maximizing the objective function for streamflow or LAI, the other un-calibrated predicted outcome (LAI if streamflow is the focus) was consistently compromised. Thus, single-objective optimization cannot take into account the essence of all processes in the conceptual ecohydrological models. However, multi-objective optimisation showed great strength for streamflow and LAI predictions. Both response outputs were better simulated by RR-LAI-II than RR-LAI-I due to better representation of physical processes such as net primary productivity (NPP) in RR-LAI-II. Our results highlight that simultaneous calibration of streamflow and LAI using a multi-objective algorithm proves to be an attractive tool for improved streamflow predictions.

Effects of land cover change on evapotranspiration and streamflow of small catchments in the Upper Xingu River Basin, Central Brazi

NASA Astrophysics Data System (ADS)

Costa, M. H.; Dias, L. C. P.; Macedo, M.; Coe, M. T.; Neill, C.

2014-12-01

This study assess the influence of land cover changes on evapotranspiration and streamflow in small catchments in the Upper Xingu River Basin (Mato Grosso state, Brazil). Streamflow was measured in catchments with uniform land use for September 1, 2008 to August 31, 2010. We used models to simulate evapotranspiration and streamflow for the four most common land cover types found in the Upper Xingu: tropical forest, cerrado (savanna), pasture, and soybean croplands. We used INLAND to perform single point simulations considering tropical rainforest, cerrado and pasturelands, and AgroIBIS for croplands. Converting natural vegetation to agriculture substantially modifies evapotranspiration and streamflow in small catchments. Measured mean streamflow in soy catchments was about three times greater than that of forest catchments, while the mean annual amplitude of flow in soy catchments was more than twice that of forest catchments. Simulated mean annual evapotranspiration was 39% lower in agricultural ecosystems (pasture and soybean cropland) than in natural ecosystems (tropical rainforest and cerrado). Observed and simulated mean annual streamflows in agricultural ecosystems were more than 100% higher than in natural ecosystems. The accuracy of the simulations is improved by using field-measured soil hydraulic properties. The inclusion of local measurements of key soil parameters is likely to improve hydrological simulations in other tropical regions.

Effects of land cover change on evapotranspiration and streamflow of small catchments in the Upper Xingu River Basin, Central Brazi

NASA Astrophysics Data System (ADS)

Costa, M. H.; Dias, L. C. P.; Macedo, M.; Coe, M. T.; Neill, C.

2015-12-01

This study assess the influence of land cover changes on evapotranspiration and streamflow in small catchments in the Upper Xingu River Basin (Mato Grosso state, Brazil). Streamflow was measured in catchments with uniform land use for September 1, 2008 to August 31, 2010. We used models to simulate evapotranspiration and streamflow for the four most common land cover types found in the Upper Xingu: tropical forest, cerrado (savanna), pasture, and soybean croplands. We used INLAND to perform single point simulations considering tropical rainforest, cerrado and pasturelands, and AgroIBIS for croplands. Converting natural vegetation to agriculture substantially modifies evapotranspiration and streamflow in small catchments. Measured mean streamflow in soy catchments was about three times greater than that of forest catchments, while the mean annual amplitude of flow in soy catchments was more than twice that of forest catchments. Simulated mean annual evapotranspiration was 39% lower in agricultural ecosystems (pasture and soybean cropland) than in natural ecosystems (tropical rainforest and cerrado). Observed and simulated mean annual streamflows in agricultural ecosystems were more than 100% higher than in natural ecosystems. The accuracy of the simulations is improved by using field-measured soil hydraulic properties. The inclusion of local measurements of key soil parameters is likely to improve hydrological simulations in other tropical regions.

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

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.

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

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.

Applying a simple water-energy balance framework to predict the climate sensitivity of streamflow over the continental United States

NASA Astrophysics Data System (ADS)

Renner, M.; Bernhofer, C.

2011-12-01

The prediction of climate effects on terrestrial ecosystems and water resources is one of the major research questions in hydrology. Conceptual water-energy balance models can be used to gain a first order estimate of how long-term average streamflow is changing with a change in water and energy supply. A common framework for investigation of this question is based on the Budyko hypothesis, which links hydrological response to aridity. Recently, Renner et al. (2011) introduced the CCUW hypothesis, which is based on the assumption that the total efficiency of the catchment ecosystem to use the available water and energy for actual evapotranspiration remains constant even under climate changes. Here, we confront the climate sensitivity approaches (including several versions of Budyko's approach and the CCUW) with data of more than 400 basins distributed over the continental United States. We first map an estimate of the sensitivity of streamflow to changes in precipitation using long-term average data of the period 1949-2003. This provides a hydro-climatic status of the respective basins as well as their expected proportional effect on changes in climate. Next, by splitting the data in two periods, we (i) analyse the long-term average changes in hydro-climatolgy, we (ii) use the different climate sensitivity methods to predict the change in streamflow given the observed changes in water and energy supply and (iii) we apply a quantitative approach to separate the impacts of changes in the long-term average climate from basin characteristics change on streamflow. This allows us to evaluate the observed changes in streamflow as well as to evaluate the impact of basin changes on the validity of climate sensitivity approaches. The apparent increase of streamflow in the majority of basins in the US is dominated by a climate trend towards increased humidity. It is further evident that impacts of changes in basin characteristics appear in parallel with climate changes. There

Past and future changes in streamflow in the U.S. Midwest: Bridging across time scales

NASA Astrophysics Data System (ADS)

Villarini, G.; Slater, L. J.; Salvi, K. A.

2017-12-01

Streamflows have increased notably across the U.S. Midwest over the past century, principally due to changes in precipitation and land use / land cover. Improving our understanding of the physical drivers that are responsible for the observed changes in discharge may enhance our capability of predicting and projecting these changes, and may have large implications for water resources management over this area. This study will highlight our efforts towards the statistical attribution of changes in discharge across the U.S. Midwest, with analyses performed at the seasonal scale from low to high flows. The main drivers of changing streamflows that we focus on are: urbanization, agricultural land cover, basin-averaged temperature, basin-averaged precipitation, and antecedent soil moisture. Building on the insights from this attribution, we will examine the potential predictability of streamflow across different time scales, with lead times ranging from seasonal to decadal, and discuss a potential path forward for engineering design for future conditions.

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.

Evaluation of model-based seasonal streamflow and water allocation forecasts for the Elqui Valley, Chile

NASA Astrophysics Data System (ADS)

Delorit, Justin; Cristian Gonzalez Ortuya, Edmundo; Block, Paul

2017-09-01

In many semi-arid regions, multisectoral demands often stress available water supplies. Such is the case in the Elqui River valley of northern Chile, which draws on a limited-capacity reservoir to allocate 25 000 water rights. Delayed infrastructure investment forces water managers to address demand-based allocation strategies, particularly in dry years, which are realized through reductions in the volume associated with each water right. Skillful season-ahead streamflow forecasts have the potential to inform managers with an indication of future conditions to guide reservoir allocations. This work evaluates season-ahead statistical prediction models of October-January (growing season) streamflow at multiple lead times associated with manager and user decision points, and links predictions with a reservoir allocation tool. Skillful results (streamflow forecasts outperform climatology) are produced for short lead times (1 September: ranked probability skill score (RPSS) of 0.31, categorical hit skill score of 61 %). At longer lead times, climatological skill exceeds forecast skill due to fewer observations of precipitation. However, coupling the 1 September statistical forecast model with a sea surface temperature phase and strength statistical model allows for equally skillful categorical streamflow forecasts to be produced for a 1 May lead, triggered for 60 % of years (1950-2015), suggesting forecasts need not be strictly deterministic to be useful for water rights holders. An early (1 May) categorical indication of expected conditions is reinforced with a deterministic forecast (1 September) as more observations of local variables become available. The reservoir allocation model is skillful at the 1 September lead (categorical hit skill score of 53 %); skill improves to 79 % when categorical allocation prediction certainty exceeds 80 %. This result implies that allocation efficiency may improve when forecasts are integrated into reservoir decision frameworks. The

Simulated Effects of Year 2030 Water-Use and Land-Use Changes on Streamflow near the Interstate-495 Corridor, Assabet and Upper Charles River Basins, Eastern Massachusetts

USGS Publications Warehouse

Carlson, Carl S.; Desimone, Leslie A.; Weiskel, Peter K.

2008-01-01

Continued population growth and land development for commercial, industrial, and residential uses have created concerns regarding the future supply of potable water and the quantity of ground water discharging to streams in the area of Interstate 495 in eastern Massachusetts. Two ground-water models developed in 2002-2004 for the Assabet and Upper Charles River Basins were used to simulate water supply and land-use scenarios relevant for the entire Interstate-495 corridor. Future population growth, water demands, and commercial and residential growth were projected for year 2030 by the Metropolitan Area Planning Council. To assess the effects of future development on subbasin streamflows, seven scenarios were simulated by using existing computer-based ground-water-flow models with the data projected for year 2030. The scenarios incorporate three categories of projected 2030 water- and land-use data: (1) 2030 water use, (2) 2030 land use, and (3) a combination of 2030 water use and 2030 land use. Hydrologic, land-use, and water-use data from 1997 through 2001 for the Assabet River Basin study and 1989 through 1998 for the Upper Charles River Basin study were used to represent current conditions - referred to as 'basecase' conditions - in each basin to which each 2030 scenario was compared. The effects of projected 2030 land- and water-use change on streamflows in the Assabet River Basin depended upon the time of year, the hydrologic position of the subbasin in the larger basin, and the relative areas of new commercial and residential development projected for a subbasin. Effects of water use and land use on streamflow were evaluated by comparing average monthly nonstorm streamflow (base flow) for March and September simulated by using the models. The greatest decreases in streamflow (up to 76 percent in one subbasin), compared to the basecase, occurred in September, when streamflows are naturally at their lowest level. By contrast, simulated March streamflows

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.

Streamflow forecasting and data assimilation: bias in precipitation, soil moisture states, and groundwater fluxes.

NASA Astrophysics Data System (ADS)

McCreight, J. L.; Gochis, D. J.; Hoar, T.; Dugger, A. L.; Yu, W.

2014-12-01

Uncertainty in precipitation forcing, soil moisture states, and model groundwater fluxes are first-order sources of error in streamflow forecasting. While near-surface estimates of soil moisture are now available from satellite, very few soil moisture observations below 5 cm depth or groundwater discharge estimates are available for operational forecasting. Radar precipitation estimates are subject to large biases, particularly during extreme events (e.g. Steiner et al., 2010) and their correction is not typically available in real-time. Streamflow data, however, are readily available in near-real-time and can be assimilated operationally to help constrain uncertainty in these uncertain states and improve streamflow forecasts. We examine the ability of streamflow observations to diagnose bias in the three most uncertain variables: precipitation forcing, soil moisture states, and groundwater fluxes. We investigate strategies for their subsequent bias correction. These include spinup and calibration strategies with and without the use of data assimilation and the determination of the proper spinup timescales. Global and spatially distributed multipliers on the uncertain states included in the assimilation state vector (e.g. Seo et al., 2003) will also be evaluated. We examine real cases and observing system simulation experiments for both normal and extreme rainfall events. One of our test cases considers the Colorado Front Range flood of September 2013 where the range of disagreement amongst five precipitation estimates spanned a factor of five with only one exhibiting appreciable positive bias (Gochis et al, submitted). Our experiments are conducted using the WRF-Hydro model with the NoahMP land surface component and the data assimilation research testbed (DART). A variety of ensemble data assimilation approaches (filters) are considered. ReferencesGochis, DJ, et al. "The Great Colorado Flood of September 2013" BAMS (Submitted 4-7-14). Seo, DJ, V Koren, and N

Continuous tidal streamflow, water level, and specific conductance data for Union Creek and the Little Back, Middle, and Front Rivers, Savannah River Estuary, November 2008 to March 2009

USGS Publications Warehouse

Lanier, Timothy H.; Conrads, Paul

2010-01-01

In the Water Resource Development Act of 1999, the U.S. Congress authorized the deepening of the Savannah Harbor. Additional studies were then identified by the Georgia Ports Authority and other local and regional stakeholders to determine and fully describe the potential environmental effects of deepening the channel. One need that was identified was the validation of a three-dimensional hydrodynamic model developed to evaluate mitigation scenarios for a potential harbor deepening and the effects on the Savannah River estuary. The streamflow in the estuary is very complex due to reversing tidal flows, interconnections of streams and tidal creeks, and the daily flooding and draining of the marshes. The model was calibrated using very limited streamflow data and no continuous streamflow measurements. To better characterize the streamflow dynamics and mass transport of the estuary, two index-velocity sites were instrumented with continuous acoustic velocity, water level, and specific conductance sensors on the Little Back and Middle Rivers for the 5-month period of November 2008 through March 2009. During the same period, a third acoustic velocity meter was installed on the Front River just downstream from U.S. Geological Survey streamgaging station 02198920 (Savannah River at GA 25, at Port Wentworth, Georgia) where water level and specific conductance data were being collected. A fourth index-velocity site was instrumented with continuous acoustic velocity, water level, and specific conductance sensors on Union Creek for a 2-month period starting in November 2008. In addition to monitoring the tidal cycles, streamflow measurements were made at the four index-velocity sites to develop ratings to compute continuous discharge for each site. The maximum flood (incoming) and ebb (outgoing) tides measured on Little Back River were –4,570 and 7,990 cubic feet per second, respectively. On Middle River, the maximum flood and ebb tides measured were –9,630 and 13

A multiple wavelet coherency method for temporal streamflow-precipitation-temperature relationships in 17 small catchments on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Yang, Y.; Liu, B.

2017-12-01

Climate change and human activities are two critical factors causing the dramatical variations of streamflow in the Yellow River Basin of China during the last several decades. More and more attention has been paid to the temporal relationships of streamflow with precipitation and temperature recently. The objective of the current study was to explore the contributions of precipitation and temperature to the temporal variations of streamflow on the Loess Plateau using a multiple wavelet coherency method. Annual streamflow during 1961-2013 for 17 small catchments were collected from the Yellow River Conservancy Commission and annual precipitation and temperature for each catchment were derived from the meteorological data at the national weather stations across the Loess Plateau through the China Meteorological Data Sharing Service System. An abrupt decrease was observed in the annual streamflow around year 2000 for any of the 17 catchments investigated, which was believed to be related with the extensive Grain for Green Project. According to bivariate wavelet coherences, however, annual streamflow showed strong temporal variations with annual precipitation at 8 out of the 17 catchments, where the percentage area of significant coherency (PASC) exceeded 50%. Especially in Weihe and Yiluohe catchments, the corresponding PASC were close to 100%, suggesting that annual precipitation change accounted for almost all the temporal streamflow variations. Compared to annual precipitation, the temporal correlation of temperature with streamflow was relatively small, as implied in the lower mean wavelet coherence (MWC) and PASC. Moreover, including temperature in addition to precipitation in the multiple wavelet coherency analysis failed to increase either MWC or PASC in any of the 17 catchments except for Qingjianhe and Qiushuihe catchments. It was indicated that for most catchments on the Loess Plateau, annual temperature was not significantly different from the red noise in

Seeing the climate through the trees: observing climate and forestry impacts on streamflow using a 60-year record

Treesearch

T. P. Burt; N. J. K. Howden; J. J. McDonnell; J. A. Jones; G. R. Hancock

2014-01-01

Paired watershed experiments involving the removal or manipulation of forest cover in one of the watersheds have been conducted for more than a century to quantify the impact of forestry operations on streamflow. Because climate variability is expected to be large, forestry treatment effects would be undetectable without the treatment–control comparison. New...

June and August median streamflows estimated for ungaged streams in southern Maine

USGS Publications Warehouse

Lombard, Pamela J.

2010-01-01

Methods for estimating June and August median streamflows were developed for ungaged, unregulated streams in southern Maine. The methods apply to streams with drainage areas ranging in size from 0.4 to 74 square miles, with percentage of basin underlain by a sand and gravel aquifer ranging from 0 to 84 percent, and with distance from the centroid of the basin to a Gulf of Maine line paralleling the coast ranging from 14 to 94 miles. Equations were developed with data from 4 long-term continuous-record streamgage stations and 27 partial-record streamgage stations. Estimates of median streamflows at the continuous-record and partial-record stations are presented. A mathematical technique for estimating standard low-flow statistics, such as June and August median streamflows, at partial-record streamgage stations was applied by relating base-flow measurements at these stations to concurrent daily streamflows at nearby long-term (at least 10 years of record) continuous-record streamgage stations (index stations). Weighted least-squares regression analysis (WLS) was used to relate estimates of June and August median streamflows at streamgage stations to basin characteristics at these same stations to develop equations that can be used to estimate June and August median streamflows on ungaged streams. WLS accounts for different periods of record at the gaging stations. Three basin characteristics-drainage area, percentage of basin underlain by a sand and gravel aquifer, and distance from the centroid of the basin to a Gulf of Maine line paralleling the coast-are used in the final regression equation to estimate June and August median streamflows for ungaged streams. The three-variable equation to estimate June median streamflow has an average standard error of prediction from -35 to 54 percent. The three-variable equation to estimate August median streamflow has an average standard error of prediction from -45 to 83 percent. Simpler one-variable equations that use only