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

USGS Publications Warehouse

Stuckey, Marla H.; Koerkle, Edward H.; Ulrich, James E.

2012-01-01

BaSE uses the map correlation method and flow-duration exceedance probability regression equations to estimate baseline daily mean streamflow for an ungaged location. The output from BaSE is a Microsoft Excel® report file that summarizes the reference streamgage and ungaged location information, including basin characteristics, percent difference in basin characteristics between the two locations, any warning associated with the basin characteristics, mean and median streamflow for the ungaged location, and a daily hydrograph of streamflow for water years 1960–2008 for the ungaged location. The daily mean streamflow for the ungaged location can be exported as a text file to be used as input into other statistical software packages. BaSE estimates daily mean streamflow for baseline conditions only, and any alterations to streamflow from regulation, large water use, or substantial mining are not reflected in the estimated streamflow.

Tennessee StreamStats: A Web-Enabled Geographic Information System Application for Automating the Retrieval and Calculation of Streamflow Statistics

USGS Publications Warehouse

Ladd, David E.; Law, George S.

2007-01-01

The U.S. Geological Survey (USGS) provides streamflow and other stream-related information needed to protect people and property from floods, to plan and manage water resources, and to protect water quality in the streams. Streamflow statistics provided by the USGS, such as the 100-year flood and the 7-day 10-year low flow, frequently are used by engineers, land managers, biologists, and many others to help guide decisions in their everyday work. In addition to streamflow statistics, resource managers often need to know the physical and climatic characteristics (basin characteristics) of the drainage basins for locations of interest to help them understand the mechanisms that control water availability and water quality at these locations. StreamStats is a Web-enabled geographic information system (GIS) application that makes it easy for users to obtain streamflow statistics, basin characteristics, and other information for USGS data-collection stations and for ungaged sites of interest. If a user selects the location of a data-collection station, StreamStats will provide previously published information for the station from a database. If a user selects a location where no data are available (an ungaged site), StreamStats will run a GIS program to delineate a drainage basin boundary, measure basin characteristics, and estimate streamflow statistics based on USGS streamflow prediction methods. A user can download a GIS feature class of the drainage basin boundary with attributes including the measured basin characteristics and streamflow estimates.

August median streamflow on ungaged streams in Eastern Coastal Maine

USGS Publications Warehouse

Lombard, Pamela J.

2004-01-01

Methods for estimating August median streamflow were developed for ungaged, unregulated streams in eastern coastal Maine. The methods apply to streams with drainage areas ranging in size from 0.04 to 73.2 square miles and fraction of basin underlain by a sand and gravel aquifer ranging from 0 to 71 percent. The equations were developed with data from three long-term (greater than or equal to 10 years of record) continuous-record streamflow-gaging stations, 23 partial-record streamflow- gaging stations, and 5 short-term (less than 10 years of record) continuous-record streamflow-gaging stations. A mathematical technique for estimating a standard low-flow statistic, August median streamflow, at partial-record streamflow-gaging stations and short-term continuous-record streamflow-gaging stations was applied by relating base-flow measurements at these stations to concurrent daily streamflows at nearby long-term continuous-record streamflow-gaging stations (index stations). Generalized least-squares regression analysis (GLS) was used to relate estimates of August median streamflow at streamflow-gaging stations to basin characteristics at these same stations to develop equations that can be applied to estimate August median streamflow on ungaged streams. GLS accounts for different periods of record at the gaging stations and the cross correlation of concurrent streamflows among gaging stations. Thirty-one stations were used for the final regression equations. Two basin characteristics?drainage area and fraction of basin underlain by a sand and gravel aquifer?are used in the calculated regression equation to estimate August median streamflow for ungaged streams. The equation has an average standard error of prediction from -27 to 38 percent. A one-variable equation uses only drainage area to estimate August median streamflow when less accuracy is acceptable. This equation has an average standard error of prediction from -30 to 43 percent. Model error is larger than sampling error for both equations, indicating that additional or improved estimates of basin characteristics could be important to improved estimates of low-flow statistics. Weighted estimates of August median streamflow at partial- record or continuous-record gaging stations range from 0.003 to 31.0 cubic feet per second or from 0.1 to 0.6 cubic feet per second per square mile. Estimates of August median streamflow on ungaged streams in eastern coastal Maine, within the range of acceptable explanatory variables, range from 0.003 to 45 cubic feet per second or 0.1 to 0.6 cubic feet per second per square mile. Estimates of August median streamflow per square mile of drainage area generally increase as drainage area and fraction of basin underlain by a sand and gravel aquifer increase.

Updating estimates of low streamflow statistics to account for possible trends

NASA Astrophysics Data System (ADS)

Blum, A. G.; Archfield, S. A.; Hirsch, R. M.; Vogel, R. M.; Kiang, J. E.; Dudley, R. W.

2017-12-01

Given evidence of both increasing and decreasing trends in low flows in many streams, methods are needed to update estimators of low flow statistics used in water resources management. One such metric is the 10-year annual low-flow statistic (7Q10) calculated as the annual minimum seven-day streamflow which is exceeded in nine out of ten years on average. Historical streamflow records may not be representative of current conditions at a site if environmental conditions are changing. We present a new approach to frequency estimation under nonstationary conditions that applies a stationary nonparametric quantile estimator to a subset of the annual minimum flow record. Monte Carlo simulation experiments were used to evaluate this approach across a range of trend and no trend scenarios. Relative to the standard practice of using the entire available streamflow record, use of a nonparametric quantile estimator combined with selection of the most recent 30 or 50 years for 7Q10 estimation were found to improve accuracy and reduce bias. Benefits of data subset selection approaches were greater for higher magnitude trends annual minimum flow records with lower coefficients of variation. A nonparametric trend test approach for subset selection did not significantly improve upon always selecting the last 30 years of record. At 174 stream gages in the Chesapeake Bay region, 7Q10 estimators based on the most recent 30 years of flow record were compared to estimators based on the entire period of record. Given the availability of long records of low streamflow, using only a subset of the flow record ( 30 years) can be used to update 7Q10 estimators to better reflect current streamflow conditions.

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

USGS Publications Warehouse

Granato, Gregory E.

2009-01-01

Streamflow information is important for many planning and design activities including water-supply analysis, habitat protection, bridge and culvert design, calibration of surface and ground-water models, and water-quality assessments. Streamflow information is especially critical for water-quality assessments (Warn and Brew, 1980; Di Toro, 1984; Driscoll and others, 1989; Driscoll and others, 1990, a,b). Calculation of streamflow statistics for receiving waters is necessary to estimate the potential effects of point sources such as wastewater-treatment plants and nonpoint sources such as highway and urban-runoff discharges on receiving water. Streamflow statistics indicate the amount of flow that may be available for dilution and transport of contaminants (U.S. Environmental Protection Agency, 1986; Driscoll and others, 1990, a,b). Streamflow statistics also may be used to indicate receiving-water quality because concentrations of water-quality constituents commonly vary naturally with streamflow. For example, concentrations of suspended sediment and sediment-associated constituents (such as nutrients, trace elements, and many organic compounds) commonly increase with increasing flows, and concentrations of many dissolved constituents commonly decrease with increasing flows in streams and rivers (O'Connor, 1976; Glysson, 1987; Vogel and others, 2003, 2005). Reliable, efficient and repeatable methods are needed to access and process streamflow information and data. For example, the Nation's highway infrastructure includes an innumerable number of stream crossings and stormwater-outfall points for which estimates of stream-discharge statistics may be needed. The U.S. Geological Survey (USGS) streamflow data-collection program is designed to provide streamflow data at gaged sites and to provide information that can be used to estimate streamflows at almost any point along any stream in the United States (Benson and Carter, 1973; Wahl and others, 1995; National Research Council, 2004). The USGS maintains the National Water Information System (NWIS), a distributed network of computers and file servers used to store and retrieve hydrologic data (Mathey, 1998; U.S. Geological Survey, 2008). NWISWeb is an online version of this database that includes water data from more than 24,000 streamflow-gaging stations throughout the United States (U.S. Geological Survey, 2002, 2008). Information from NWISWeb is commonly used to characterize streamflows at gaged sites and to help predict streamflows at ungaged sites. Five computer programs were developed for obtaining and analyzing streamflow from the National Water Information System (NWISWeb). The programs were developed as part of a study by the U.S. Geological Survey, in cooperation with the Federal Highway Administration, to develop a stochastic empirical loading and dilution model. The programs were developed because reliable, efficient, and repeatable methods are needed to access and process streamflow information and data. The first program is designed to facilitate the downloading and reformatting of NWISWeb streamflow data. The second program is designed to facilitate graphical analysis of streamflow data. The third program is designed to facilitate streamflow-record extension and augmentation to help develop long-term statistical estimates for sites with limited data. The fourth program is designed to facilitate statistical analysis of streamflow data. The fifth program is a preprocessor to create batch input files for the U.S. Environmental Protection Agency DFLOW3 program for calculating low-flow statistics. These computer programs were developed to facilitate the analysis of daily mean streamflow data for planning-level water-quality analyses but also are useful for many other applications pertaining to streamflow data and statistics. These programs and the associated documentation are included on the CD-ROM accompanying this report. This report and the appendixes on the

Alternative Regression Equations for Estimation of Annual Peak-Streamflow Frequency for Undeveloped Watersheds in Texas using PRESS Minimization

USGS Publications Warehouse

Asquith, William H.; Thompson, David B.

2008-01-01

The U.S. Geological Survey, in cooperation with the Texas Department of Transportation and in partnership with Texas Tech University, investigated a refinement of the regional regression method and developed alternative equations for estimation of peak-streamflow frequency for undeveloped watersheds in Texas. A common model for estimation of peak-streamflow frequency is based on the regional regression method. The current (2008) regional regression equations for 11 regions of Texas are based on log10 transformations of all regression variables (drainage area, main-channel slope, and watershed shape). Exclusive use of log10-transformation does not fully linearize the relations between the variables. As a result, some systematic bias remains in the current equations. The bias results in overestimation of peak streamflow for both the smallest and largest watersheds. The bias increases with increasing recurrence interval. The primary source of the bias is the discernible curvilinear relation in log10 space between peak streamflow and drainage area. Bias is demonstrated by selected residual plots with superimposed LOWESS trend lines. To address the bias, a statistical framework based on minimization of the PRESS statistic through power transformation of drainage area is described and implemented, and the resulting regression equations are reported. Compared to log10-exclusive equations, the equations derived from PRESS minimization have PRESS statistics and residual standard errors less than the log10 exclusive equations. Selected residual plots for the PRESS-minimized equations are presented to demonstrate that systematic bias in regional regression equations for peak-streamflow frequency estimation in Texas can be reduced. Because the overall error is similar to the error associated with previous equations and because the bias is reduced, the PRESS-minimized equations reported here provide alternative equations for peak-streamflow frequency estimation.

Arkansas StreamStats: a U.S. Geological Survey web map application for basin characteristics and streamflow statistics

USGS Publications Warehouse

Pugh, Aaron L.

2014-01-01

Users of streamflow information often require streamflow statistics and basin characteristics at various locations along a stream. The USGS periodically calculates and publishes streamflow statistics and basin characteristics for streamflowgaging stations and partial-record stations, but these data commonly are scattered among many reports that may or may not be readily available to the public. The USGS also provides and periodically updates regional analyses of streamflow statistics that include regression equations and other prediction methods for estimating statistics for ungaged and unregulated streams across the State. Use of these regional predictions for a stream can be complex and often requires the user to determine a number of basin characteristics that may require interpretation. Basin characteristics may include drainage area, classifiers for physical properties, climatic characteristics, and other inputs. Obtaining these input values for gaged and ungaged locations traditionally has been time consuming, subjective, and can lead to inconsistent results.

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

NASA Astrophysics Data System (ADS)

Morlot, T.; Mathevet, T.; Perret, C.; Favre Pugin, A. C.

2014-12-01

Streamflow uncertainty estimation has recently received a large attention in the literature. A dynamic rating curve assessment method has been introduced (Morlot et al., 2014). This dynamic method allows to compute a rating curve for each gauging and a continuous streamflow time-series, while calculating streamflow uncertainties. Streamflow uncertainty takes into account many sources of uncertainty (water level, rating curve interpolation and extrapolation, gauging aging, etc.) and produces an estimated distribution of streamflow for each days. In order to caracterise streamflow uncertainty, a probabilistic framework has been applied on a large sample of hydrometric stations of the Division Technique Générale (DTG) of Électricité de France (EDF) hydrometric network (>250 stations) in France. A reliability diagram (Wilks, 1995) has been constructed for some stations, based on the streamflow distribution estimated for a given day and compared to a real streamflow observation estimated via a gauging. To build a reliability diagram, we computed the probability of an observed streamflow (gauging), given the streamflow distribution. Then, the reliability diagram allows to check that the distribution of probabilities of non-exceedance of the gaugings follows a uniform law (i.e., quantiles should be equipropables). Given the shape of the reliability diagram, the probabilistic calibration is caracterised (underdispersion, overdispersion, bias) (Thyer et al., 2009). In this paper, we present case studies where reliability diagrams have different statistical properties for different periods. Compared to our knowledge of river bed morphology dynamic of these hydrometric stations, we show how reliability diagram gives us invaluable information on river bed movements, like a continuous digging or backfilling of the hydraulic control due to erosion or sedimentation processes. Hence, the careful analysis of reliability diagrams allows to reconcile statistics and long-term river bed morphology processes. This knowledge improves our real-time management of hydrometric stations, given a better caracterisation of erosion/sedimentation processes and the stability of hydrometric station hydraulic control.

Trend analysis and selected summary statistics of annual mean streamflow for 38 selected long-term U.S. Geological Survey streamgages in Texas, water years 1916-2012

USGS Publications Warehouse

Asquith, William H.; Barbie, Dana L.

2014-01-01

Selected summary statistics (L-moments) and estimates of respective sampling variances were computed for the 35 streamgages lacking statistically significant trends. From the L-moments and estimated sampling variances, weighted means or regional values were computed for each L-moment. An example application is included demonstrating how the L-moments could be used to evaluate the magnitude and frequency of annual mean streamflow.

Flow Durations, Low-Flow Frequencies, and Monthly Median Flows for Selected Streams in Connecticut through 2005

USGS Publications Warehouse

Ahearn, Elizabeth A.

2008-01-01

Flow durations, low-flow frequencies, and monthly median streamflows were computed for 91 continuous-record, streamflow-gaging stations in Connecticut with 10 or more years of record. Flow durations include the 99-, 98-, 97-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 25-, 20-, 10-, 5-, and 1-percent exceedances. Low-flow frequencies include the 7-day, 10-year (7Q10) low flow; 7-day, 2-year (7Q2) low flow; and 30-day, 2-year (30Q2) low flow. Streamflow estimates were computed for each station using data for the period of record through water year 2005. Estimates of low-flow statistics for 7 short-term (operated between 3 and 10 years) streamflow-gaging stations and 31 partial-record sites were computed. Low-flow estimates were made on the basis of the relation between base flows at a short-term station or partial-record site and concurrent daily mean streamflows at a nearby index station. The relation is defined by the Maintenance of Variance Extension, type 3 (MOVE.3) method. Several short-term stations and partial-record sites had poorly defined relations with nearby index stations; therefore, no low-flow statistics were derived for these sites. The estimated low-flow statistics for the short-term stations and partial-record sites include the 99-, 98-, 97-, 95-, 90-, and 85-percent flow durations; the 7-day, 10-year (7Q10) low flow; 7-day, 2-year (7Q2) low flow; and 30-day, 2-year (30Q2) low-flow frequencies; and the August median flow. Descriptive information on location and record length, measured basin characteristics, index stations correlated to the short-term station and partial-record sites, and estimated flow statistics are provided in this report for each station. Streamflow estimates from this study are stored on USGS's World Wide Web application 'StreamStats' (http://water.usgs.gov/osw/streamstats/connecticut.html).

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

USGS Publications Warehouse

Linhart, S. Mike; Nania, Jon F.; Sanders, Curtis L.; Archfield, Stacey A.

2012-01-01

The U.S. Geological Survey (USGS) maintains approximately 148 real-time streamgages in Iowa for which daily mean streamflow information is available, but daily mean streamflow data commonly are needed at locations where no streamgages are present. Therefore, the USGS conducted a study as part of a larger project in cooperation with the Iowa Department of Natural Resources to develop methods to estimate daily mean streamflow at locations in ungaged watersheds in Iowa by using two regression-based statistical methods. The regression equations for the statistical methods were developed from historical daily mean streamflow and basin characteristics from streamgages within the study area, which includes the entire State of Iowa and adjacent areas within a 50-mile buffer of Iowa in neighboring states. Results of this study can be used with other techniques to determine the best method for application in Iowa and can be used to produce a Web-based geographic information system tool to compute streamflow estimates automatically. The Flow Anywhere statistical method is a variation of the drainage-area-ratio method, which transfers same-day streamflow information from a reference streamgage to another location by using the daily mean streamflow at the reference streamgage and the drainage-area ratio of the two locations. The Flow Anywhere method modifies the drainage-area-ratio method in order to regionalize the equations for Iowa and determine the best reference streamgage from which to transfer same-day streamflow information to an ungaged location. Data used for the Flow Anywhere method were retrieved for 123 continuous-record streamgages located in Iowa and within a 50-mile buffer of Iowa. The final regression equations were computed by using either left-censored regression techniques with a low limit threshold set at 0.1 cubic feet per second (ft3/s) and the daily mean streamflow for the 15th day of every other month, or by using an ordinary-least-squares multiple linear regression method and the daily mean streamflow for the 15th day of every other month. The Flow Duration Curve Transfer method was used to estimate unregulated daily mean streamflow from the physical and climatic characteristics of gaged basins. For the Flow Duration Curve Transfer method, daily mean streamflow quantiles at the ungaged site were estimated with the parameter-based regression model, which results in a continuous daily flow-duration curve (the relation between exceedance probability and streamflow for each day of observed streamflow) at the ungaged site. By the use of a reference streamgage, the Flow Duration Curve Transfer is converted to a time series. Data used in the Flow Duration Curve Transfer method were retrieved for 113 continuous-record streamgages in Iowa and within a 50-mile buffer of Iowa. The final statewide regression equations for Iowa were computed by using a weighted-least-squares multiple linear regression method and were computed for the 0.01-, 0.05-, 0.10-, 0.15-, 0.20-, 0.30-, 0.40-, 0.50-, 0.60-, 0.70-, 0.80-, 0.85-, 0.90-, and 0.95-exceedance probability statistics determined from the daily mean streamflow with a reporting limit set at 0.1 ft3/s. The final statewide regression equation for Iowa computed by using left-censored regression techniques was computed for the 0.99-exceedance probability statistic determined from the daily mean streamflow with a low limit threshold and a reporting limit set at 0.1 ft3/s. For the Flow Anywhere method, results of the validation study conducted by using six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 1,016 to 138 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 1,690 to 237 ft3/s. Values of the percent root-mean-square error ranged from 115 percent to 26.2 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 13.0 to 5.3 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.80 to 0.40. Percent-bias values ranged from 25.4 to 4.0 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.35. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.86 to 0.56. For the streamgage with the best agreement between observed and estimated streamflow, higher streamflows appear to be underestimated. For the streamgage with the worst agreement between observed and estimated streamflow, low flows appear to be overestimated whereas higher flows seem to be underestimated. Estimated cumulative streamflows for the period October 1, 2004, to September 30, 2009, are underestimated by -25.8 and -7.4 percent for the closest and poorest comparisons, respectively. For the Flow Duration Curve Transfer method, results of the validation study conducted by using the same six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 437 to 93.9 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 906 to 169 ft3/s. Values of the percent root-mean-square-error ranged from 67.0 to 25.6 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 12.5 to 4.4 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.79 to 0.40. Percent-bias values ranged from 22.7 to 0.94 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.38. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.89 to 0.48. For the streamgage with the closest agreement between observed and estimated streamflow, there is relatively good agreement between observed and estimated streamflows. For the streamgage with the poorest agreement between observed and estimated streamflow, streamflows appear to be substantially underestimated for much of the time period. Estimated cumulative streamflow for the period October 1, 2004, to September 30, 2009, are underestimated by -9.3 and -22.7 percent for the closest and poorest comparisons, respectively.

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.

Low-flow characteristics for streams on the Islands of Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi, State of Hawaiʻi

USGS Publications Warehouse

Cheng, Chui Ling

2016-08-03

Statistical models were developed to estimate natural streamflow under low-flow conditions for streams with existing streamflow data at measurement sites on the Islands of Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi. Streamflow statistics used to describe the low-flow characteristics are flow-duration discharges that are equaled or exceeded between 50 and 95 percent of the time during the 30-year base period 1984–2013. Record-augmentation techniques were applied to develop statistical models relating concurrent streamflow data at the measurement sites and long-term data from nearby continuous-record streamflow-gaging stations that were in operation during the base period and were selected as index stations. Existing data and subsequent low-flow analyses of the available data help to identify streams in under-represented geographic areas and hydrogeologic settings where additional data collection is suggested.Low-flow duration discharges were estimated for 107 measurement sites (including long-term and short-term continuous-record streamflow-gaging stations, and partial-record stations) and 27 index stations. The adequacy of statistical models was evaluated with correlation coefficients and modified Nash-Sutcliff coefficients of efficiency, and a majority of the low-flow duration-discharge estimates are satisfactory based on these regression statistics.Molokaʻi and Hawaiʻi have the fewest number of measurement sites (that are not located on ephemeral stream reaches) at which flow-duration discharges were estimated, which can be partially explained by the limited number of index stations available on these islands that could be used for record augmentation. At measurement sites on some tributary streams, low-flow duration discharges could not be estimated because no adequate correlations could be developed with the index stations. These measurement sites are located on streams where duration-discharge estimates are available at long-term stations at other locations on the main stream channel to provide at least some definition of low-flow characteristics on that stream. In terms of general natural streamflow data availability, data are scarce in the leeward areas for all five islands as many leeward streams are dry or have minimal flow. Other under-represented areas include central Oʻahu, central Maui, and southeastern Maui.

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 making estimates at partial-record or continuous-record gaging stations, range from 0.03 to 11.7 cubic feet per second or from 0.1 to 0.4 cubic feet per second per square mile. Estimates of August median streamflow on ungaged streams in the eastern part of Aroostook County, within the range of acceptable explanatory variables, range from 0.03 to 30 cubic feet per second or 0.1 to 0.7 cubic feet per second per square mile. Estimates of August median streamflow per square mile of drainage area generally increase as mean elevation and drainage area increase.

Methods to estimate historical daily streamflow for ungaged stream locations in Minnesota

USGS Publications Warehouse

Lorenz, David L.; Ziegeweid, Jeffrey R.

2016-03-14

Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water; however, streamgages cannot be installed at every location where streamflow information is needed. Therefore, methods for estimating streamflow at ungaged stream locations need to be developed. This report presents a statewide study to develop methods to estimate the structure of historical daily streamflow at ungaged stream locations in Minnesota. Historical daily mean streamflow at ungaged locations in Minnesota can be estimated by transferring streamflow data at streamgages to the ungaged location using the QPPQ method. The QPPQ method uses flow-duration curves at an index streamgage, relying on the assumption that exceedance probabilities are equivalent between the index streamgage and the ungaged location, and estimates the flow at the ungaged location using the estimated flow-duration curve. Flow-duration curves at ungaged locations can be estimated using recently developed regression equations that have been incorporated into StreamStats (http://streamstats.usgs.gov/), which is a U.S. Geological Survey Web-based interactive mapping tool that can be used to obtain streamflow statistics, drainage-basin characteristics, and other information for user-selected locations on streams.

Computed statistics at streamgages, and methods for estimating low-flow frequency statistics and development of regional regression equations for estimating low-flow frequency statistics at ungaged locations in Missouri

USGS Publications Warehouse

Southard, Rodney E.

2013-01-01

The weather and precipitation patterns in Missouri vary considerably from year to year. In 2008, the statewide average rainfall was 57.34 inches and in 2012, the statewide average rainfall was 30.64 inches. This variability in precipitation and resulting streamflow in Missouri underlies the necessity for water managers and users to have reliable streamflow statistics and a means to compute select statistics at ungaged locations for a better understanding of water availability. Knowledge of surface-water availability is dependent on the streamflow data that have been collected and analyzed by the U.S. Geological Survey for more than 100 years at approximately 350 streamgages throughout Missouri. The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, computed streamflow statistics at streamgages through the 2010 water year, defined periods of drought and defined methods to estimate streamflow statistics at ungaged locations, and developed regional regression equations to compute selected streamflow statistics at ungaged locations. Streamflow statistics and flow durations were computed for 532 streamgages in Missouri and in neighboring States of Missouri. For streamgages with more than 10 years of record, Kendall’s tau was computed to evaluate for trends in streamflow data. If trends were detected, the variable length method was used to define the period of no trend. Water years were removed from the dataset from the beginning of the record for a streamgage until no trend was detected. Low-flow frequency statistics were then computed for the entire period of record and for the period of no trend if 10 or more years of record were available for each analysis. Three methods are presented for computing selected streamflow statistics at ungaged locations. The first method uses power curve equations developed for 28 selected streams in Missouri and neighboring States that have multiple streamgages on the same streams. Statistical estimates on one of these streams can be calculated at an ungaged location that has a drainage area that is between 40 percent of the drainage area of the farthest upstream streamgage and within 150 percent of the drainage area of the farthest downstream streamgage along the stream of interest. The second method may be used on any stream with a streamgage that has operated for 10 years or longer and for which anthropogenic effects have not changed the low-flow characteristics at the ungaged location since collection of the streamflow data. A ratio of drainage area of the stream at the ungaged location to the drainage area of the stream at the streamgage was computed to estimate the statistic at the ungaged location. The range of applicability is between 40- and 150-percent of the drainage area of the streamgage, and the ungaged location must be located on the same stream as the streamgage. The third method uses regional regression equations to estimate selected low-flow frequency statistics for unregulated streams in Missouri. This report presents regression equations to estimate frequency statistics for the 10-year recurrence interval and for the N-day durations of 1, 2, 3, 7, 10, 30, and 60 days. Basin and climatic characteristics were computed using geographic information system software and digital geospatial data. A total of 35 characteristics were computed for use in preliminary statewide and regional regression analyses based on existing digital geospatial data and previous studies. Spatial analyses for geographical bias in the predictive accuracy of the regional regression equations defined three low-flow regions with the State representing the three major physiographic provinces in Missouri. Region 1 includes the Central Lowlands, Region 2 includes the Ozark Plateaus, and Region 3 includes the Mississippi Alluvial Plain. A total of 207 streamgages were used in the regression analyses for the regional equations. Of the 207 U.S. Geological Survey streamgages, 77 were located in Region 1, 120 were located in Region 2, and 10 were located in Region 3. Streamgages located outside of Missouri were selected to extend the range of data used for the independent variables in the regression analyses. Streamgages included in the regression analyses had 10 or more years of record and were considered to be affected minimally by anthropogenic activities or trends. Regional regression analyses identified three characteristics as statistically significant for the development of regional equations. For Region 1, drainage area, longest flow path, and streamflow-variability index were statistically significant. The range in the standard error of estimate for Region 1 is 79.6 to 94.2 percent. For Region 2, drainage area and streamflow variability index were statistically significant, and the range in the standard error of estimate is 48.2 to 72.1 percent. For Region 3, drainage area and streamflow-variability index also were statistically significant with a range in the standard error of estimate of 48.1 to 96.2 percent. Limitations on the use of estimating low-flow frequency statistics at ungaged locations are dependent on the method used. The first method outlined for use in Missouri, power curve equations, were developed to estimate the selected statistics for ungaged locations on 28 selected streams with multiple streamgages located on the same stream. A second method uses a drainage-area ratio to compute statistics at an ungaged location using data from a single streamgage on the same stream with 10 or more years of record. Ungaged locations on these streams may use the ratio of the drainage area at an ungaged location to the drainage area at a streamgage location to scale the selected statistic value from the streamgage location to the ungaged location. This method can be used if the drainage area of the ungaged location is within 40 to 150 percent of the streamgage drainage area. The third method is the use of the regional regression equations. The limits for the use of these equations are based on the ranges of the characteristics used as independent variables and that streams must be affected minimally by anthropogenic activities.

Regional regression equations for the estimation of selected monthly low-flow duration and frequency statistics at ungaged sites on streams in New Jersey

USGS Publications Warehouse

Watson, Kara M.; McHugh, Amy R.

2014-01-01

Regional regression equations were developed for estimating monthly flow-duration and monthly low-flow frequency statistics for ungaged streams in Coastal Plain and non-coastal regions of New Jersey for baseline and current land- and water-use conditions. The equations were developed to estimate 87 different streamflow statistics, which include the monthly 99-, 90-, 85-, 75-, 50-, and 25-percentile flow-durations of the minimum 1-day daily flow; the August–September 99-, 90-, and 75-percentile minimum 1-day daily flow; and the monthly 7-day, 10-year (M7D10Y) low-flow frequency. These 87 streamflow statistics were computed for 41 continuous-record streamflow-gaging stations (streamgages) with 20 or more years of record and 167 low-flow partial-record stations in New Jersey with 10 or more streamflow measurements. The regression analyses used to develop equations to estimate selected streamflow statistics were performed by testing the relation between flow-duration statistics and low-flow frequency statistics for 32 basin characteristics (physical characteristics, land use, surficial geology, and climate) at the 41 streamgages and 167 low-flow partial-record stations. The regression analyses determined drainage area, soil permeability, average April precipitation, average June precipitation, and percent storage (water bodies and wetlands) were the significant explanatory variables for estimating the selected flow-duration and low-flow frequency statistics. Streamflow estimates were computed for two land- and water-use conditions in New Jersey—land- and water-use during the baseline period of record (defined as the years a streamgage had little to no change in development and water use) and current land- and water-use conditions (1989–2008)—for each selected station using data collected through water year 2008. The baseline period of record is representative of a period when the basin was unaffected by change in development. The current period is representative of the increased development of the last 20 years (1989–2008). The two different land- and water-use conditions were used as surrogates for development to determine whether there have been changes in low-flow statistics as a result of changes in development over time. The State was divided into two low-flow regression regions, the Coastal Plain and the non-coastal region, in order to improve the accuracy of the regression equations. The left-censored parametric survival regression method was used for the analyses to account for streamgages and partial-record stations that had zero flow values for some of the statistics. The average standard error of estimate for the 348 regression equations ranged from 16 to 340 percent. These regression equations and basin characteristics are presented in the U.S. Geological Survey (USGS) StreamStats Web-based geographic information system application. This tool allows users to click on an ungaged site on a stream in New Jersey and get the estimated flow-duration and low-flow frequency statistics. Additionally, the user can click on a streamgage or partial-record station and get the “at-site” streamflow statistics. The low-flow characteristics of a stream ultimately affect the use of the stream by humans. Specific information on the low-flow characteristics of streams is essential to water managers who deal with problems related to municipal and industrial water supply, fish and wildlife conservation, and dilution of wastewater.

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

NASA Astrophysics Data System (ADS)

Farmer, W. H.; Archfield, S. A.; Over, T. M.; Kiang, J. E.

2015-12-01

In the United States and across the globe, the majority of stream reaches and rivers are substantially impacted by water use or remain ungaged. The result is large gaps in the availability of natural streamflow records from which to infer hydrologic understanding and inform water resources management. From basin-specific to continent-wide scales, many efforts have been undertaken to develop methods to estimate ungaged streamflow. This work applies and contrasts several statistical models of daily streamflow to more than 1,700 reference-quality streamgages across the conterminous United States using a cross-validation methodology. The variability of streamflow simulation performance across the country exhibits a pattern familiar to other continental scale modeling efforts performed for the United States. For portions of the West Coast and the dense, relatively homogeneous and humid regions of the eastern United States models produce reliable estimates of daily streamflow using many different prediction methods. Model performance for the middle portion of the United States, marked by more heterogeneous and arid conditions, and with larger contributing areas and sparser networks of streamgages, is consistently poor. A discussion of the difficulty of statistical interpolation and regionalization in these regions raises additional questions of data availability and quality, hydrologic process representation and dominance, and intrinsic variability.

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.

Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Red River of the North at Fargo and Grand Forks, North Dakota, 2003-12

USGS Publications Warehouse

Galloway, Joel M.

2014-01-01

The Red River of the North (hereafter referred to as “Red River”) Basin is an important hydrologic region where water is a valuable resource for the region’s economy. Continuous water-quality monitors have been operated by the U.S. Geological Survey, in cooperation with the North Dakota Department of Health, Minnesota Pollution Control Agency, City of Fargo, City of Moorhead, City of Grand Forks, and City of East Grand Forks at the Red River at Fargo, North Dakota, from 2003 through 2012 and at Grand Forks, N.Dak., from 2007 through 2012. The purpose of the monitoring was to provide a better understanding of the water-quality dynamics of the Red River and provide a way to track changes in water quality. Regression equations were developed that can be used to estimate concentrations and loads for dissolved solids, sulfate, chloride, nitrate plus nitrite, total phosphorus, and suspended sediment using explanatory variables such as streamflow, specific conductance, and turbidity. Specific conductance was determined to be a significant explanatory variable for estimating dissolved solids concentrations at the Red River at Fargo and Grand Forks. The regression equations provided good relations between dissolved solid concentrations and specific conductance for the Red River at Fargo and at Grand Forks, with adjusted coefficients of determination of 0.99 and 0.98, respectively. Specific conductance, log-transformed streamflow, and a seasonal component were statistically significant explanatory variables for estimating sulfate in the Red River at Fargo and Grand Forks. Regression equations provided good relations between sulfate concentrations and the explanatory variables, with adjusted coefficients of determination of 0.94 and 0.89, respectively. For the Red River at Fargo and Grand Forks, specific conductance, streamflow, and a seasonal component were statistically significant explanatory variables for estimating chloride. For the Red River at Grand Forks, a time component also was a statistically significant explanatory variable for estimating chloride. The regression equations for chloride at the Red River at Fargo provided a fair relation between chloride concentrations and the explanatory variables, with an adjusted coefficient of determination of 0.66 and the equation for the Red River at Grand Forks provided a relatively good relation between chloride concentrations and the explanatory variables, with an adjusted coefficient of determination of 0.77. Turbidity and streamflow were statistically significant explanatory variables for estimating nitrate plus nitrite concentrations at the Red River at Fargo and turbidity was the only statistically significant explanatory variable for estimating nitrate plus nitrite concentrations at Grand Forks. The regression equation for the Red River at Fargo provided a relatively poor relation between nitrate plus nitrite concentrations, turbidity, and streamflow, with an adjusted coefficient of determination of 0.46. The regression equation for the Red River at Grand Forks provided a fair relation between nitrate plus nitrite concentrations and turbidity, with an adjusted coefficient of determination of 0.73. Some of the variability that was not explained by the equations might be attributed to different sources contributing nitrates to the stream at different times. Turbidity, streamflow, and a seasonal component were statistically significant explanatory variables for estimating total phosphorus at the Red River at Fargo and Grand Forks. The regression equation for the Red River at Fargo provided a relatively fair relation between total phosphorus concentrations, turbidity, streamflow, and season, with an adjusted coefficient of determination of 0.74. The regression equation for the Red River at Grand Forks provided a good relation between total phosphorus concentrations, turbidity, streamflow, and season, with an adjusted coefficient of determination of 0.87. For the Red River at Fargo, turbidity and streamflow were statistically significant explanatory variables for estimating suspended-sediment concentrations. For the Red River at Grand Forks, turbidity was the only statistically significant explanatory variable for estimating suspended-sediment concentration. The regression equation at the Red River at Fargo provided a good relation between suspended-sediment concentration, turbidity, and streamflow, with an adjusted coefficient of determination of 0.95. The regression equation for the Red River at Grand Forks provided a good relation between suspended-sediment concentration and turbidity, with an adjusted coefficient of determination of 0.96.

Missouri StreamStats—A water-resources web application

USGS Publications Warehouse

Ellis, Jarrett T.

2018-01-31

The U.S. Geological Survey (USGS) maintains and operates more than 8,200 continuous streamgages nationwide. Types of data that may be collected, computed, and stored for streamgages include streamgage height (water-surface elevation), streamflow, and water quality. The streamflow data allow scientists and engineers to calculate streamflow statistics, such as the 1-percent annual exceedance probability flood (also known as the 100-year flood), the mean flow, and the 7-day, 10-year low flow, which are used by managers to make informed water resource management decisions, at each streamgage location. Researchers, regulators, and managers also commonly need physical characteristics (basin characteristics) that describe the unique properties of a basin. Common uses for streamflow statistics and basin characteristics include hydraulic design, water-supply management, water-use appropriations, and flood-plain mapping for establishing flood-insurance rates and land-use zones. The USGS periodically publishes reports that update the values of basin characteristics and streamflow statistics at selected gaged locations (locations with streamgages), but these studies usually only update a subset of streamgages, making data retrieval difficult. Additionally, streamflow statistics and basin characteristics are most often needed at ungaged locations (locations without streamgages) for which published streamflow statistics and basin characteristics do not exist. Missouri StreamStats is a web-based geographic information system that was created by the USGS in cooperation with the Missouri Department of Natural Resources to provide users with access to an assortment of tools that are useful for water-resources planning and management. StreamStats allows users to easily obtain the most recent published streamflow statistics and basin characteristics for streamgage locations and to automatically calculate selected basin characteristics and estimate streamflow statistics at ungaged locations.

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)

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.

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 basins, however, the effective lead time is significantly reduced by short basin memory and reduced skill in the single-valued QPF.

Equations for estimating selected streamflow statistics in Rhode Island

USGS Publications Warehouse

Bent, Gardner C.; Steeves, Peter A.; Waite, Andrew M.

2014-01-01

The equations, which are based on data from streams with little to no flow alterations, will provide an estimate of the natural flows for a selected site. They will not estimate flows for altered sites with dams, surface-water withdrawals, groundwater withdrawals (pumping wells), diversions, and wastewater discharges. If the equations are used to estimate streamflow statistics for altered sites, the user should adjust the flow estimates for the alterations. The regression equations should be used only for ungaged sites with drainage areas between 0.52 and 294 square miles and stream densities between 0.94 and 3.49 miles per square mile; these are the ranges of the explanatory variables in the equations.

A geographic information system tool to solve regression equations and estimate flow-frequency characteristics of Vermont Streams

USGS Publications Warehouse

Olson, Scott A.; Tasker, Gary D.; Johnston, Craig M.

2003-01-01

Estimates of the magnitude and frequency of streamflow are needed to safely and economically design bridges, culverts, and other structures in or near streams. These estimates also are used for managing floodplains, identifying flood-hazard areas, and establishing flood-insurance rates, but may be required at ungaged sites where no observed flood data are available for streamflow-frequency analysis. This report describes equations for estimating flow-frequency characteristics at ungaged, unregulated streams in Vermont. In the past, regression equations developed to estimate streamflow statistics required users to spend hours manually measuring basin characteristics for the stream site of interest. This report also describes the accompanying customized geographic information system (GIS) tool that automates the measurement of basin characteristics and calculation of corresponding flow statistics. The tool includes software that computes the accuracy of the results and adjustments for expected probability and for streamflow data of a nearby stream-gaging station that is either upstream or downstream and within 50 percent of the drainage area of the site where the flow-frequency characteristics are being estimated. The custom GIS can be linked to the National Flood Frequency program, adding the ability to plot peak-flow-frequency curves and synthetic hydrographs and to compute adjustments for urbanization.

Methods for estimating low-flow statistics for Massachusetts streams

USGS Publications Warehouse

Ries, Kernell G.; Friesz, Paul J.

2000-01-01

Methods and computer software are described in this report for determining flow duration, low-flow frequency statistics, and August median flows. These low-flow statistics can be estimated for unregulated streams in Massachusetts using different methods depending on whether the location of interest is at a streamgaging station, a low-flow partial-record station, or an ungaged site where no data are available. Low-flow statistics for streamgaging stations can be estimated using standard U.S. Geological Survey methods described in the report. The MOVE.1 mathematical method and a graphical correlation method can be used to estimate low-flow statistics for low-flow partial-record stations. The MOVE.1 method is recommended when the relation between measured flows at a partial-record station and daily mean flows at a nearby, hydrologically similar streamgaging station is linear, and the graphical method is recommended when the relation is curved. Equations are presented for computing the variance and equivalent years of record for estimates of low-flow statistics for low-flow partial-record stations when either a single or multiple index stations are used to determine the estimates. The drainage-area ratio method or regression equations can be used to estimate low-flow statistics for ungaged sites where no data are available. The drainage-area ratio method is generally as accurate as or more accurate than regression estimates when the drainage-area ratio for an ungaged site is between 0.3 and 1.5 times the drainage area of the index data-collection site. Regression equations were developed to estimate the natural, long-term 99-, 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, and 50-percent duration flows; the 7-day, 2-year and the 7-day, 10-year low flows; and the August median flow for ungaged sites in Massachusetts. Streamflow statistics and basin characteristics for 87 to 133 streamgaging stations and low-flow partial-record stations were used to develop the equations. The streamgaging stations had from 2 to 81 years of record, with a mean record length of 37 years. The low-flow partial-record stations had from 8 to 36 streamflow measurements, with a median of 14 measurements. All basin characteristics were determined from digital map data. The basin characteristics that were statistically significant in most of the final regression equations were drainage area, the area of stratified-drift deposits per unit of stream length plus 0.1, mean basin slope, and an indicator variable that was 0 in the eastern region and 1 in the western region of Massachusetts. The equations were developed by use of weighted-least-squares regression analyses, with weights assigned proportional to the years of record and inversely proportional to the variances of the streamflow statistics for the stations. Standard errors of prediction ranged from 70.7 to 17.5 percent for the equations to predict the 7-day, 10-year low flow and 50-percent duration flow, respectively. The equations are not applicable for use in the Southeast Coastal region of the State, or where basin characteristics for the selected ungaged site are outside the ranges of those for the stations used in the regression analyses. A World Wide Web application was developed that provides streamflow statistics for data collection stations from a data base and for ungaged sites by measuring the necessary basin characteristics for the site and solving the regression equations. Output provided by the Web application for ungaged sites includes a map of the drainage-basin boundary determined for the site, the measured basin characteristics, the estimated streamflow statistics, and 90-percent prediction intervals for the estimates. An equation is provided for combining regression and correlation estimates to obtain improved estimates of the streamflow statistics for low-flow partial-record stations. An equation is also provided for combining regression and drainage-area ratio estimates to obtain improved e

Testing an automated method to estimate ground-water recharge from streamflow records

USGS Publications Warehouse

Rutledge, A.T.; Daniel, C.C.

1994-01-01

The computer program, RORA, allows automated analysis of streamflow hydrographs to estimate ground-water recharge. Output from the program, which is based on the recession-curve-displacement method (often referred to as the Rorabaugh method, for whom the program is named), was compared to estimates of recharge obtained from a manual analysis of 156 years of streamflow record from 15 streamflow-gaging stations in the eastern United States. Statistical tests showed that there was no significant difference between paired estimates of annual recharge by the two methods. Tests of results produced by the four workers who performed the manual method showed that results can differ significantly between workers. Twenty-two percent of the variation between manual and automated estimates could be attributed to having different workers perform the manual method. The program RORA will produce estimates of recharge equivalent to estimates produced manually, greatly increase the speed od analysis, and reduce the subjectivity inherent in manual analysis.

Estimating annual high-flow statistics and monthly and seasonal low-flow statistics for ungaged sites on streams in Alaska and conterminous basins in Canada

USGS Publications Warehouse

Wiley, Jeffrey B.; Curran, Janet H.

2003-01-01

Methods for estimating daily mean flow-duration statistics for seven regions in Alaska and low-flow frequencies for one region, southeastern Alaska, were developed from daily mean discharges for streamflow-gaging stations in Alaska and conterminous basins in Canada. The 15-, 10-, 9-, 8-, 7-, 6-, 5-, 4-, 3-, 2-, and 1-percent duration flows were computed for the October-through-September water year for 222 stations in Alaska and conterminous basins in Canada. The 98-, 95-, 90-, 85-, 80-, 70-, 60-, and 50-percent duration flows were computed for the individual months of July, August, and September for 226 stations in Alaska and conterminous basins in Canada. The 98-, 95-, 90-, 85-, 80-, 70-, 60-, and 50-percent duration flows were computed for the season July-through-September for 65 stations in southeastern Alaska. The 7-day, 10-year and 7-day, 2-year low-flow frequencies for the season July-through-September were computed for 65 stations for most of southeastern Alaska. Low-flow analyses were limited to particular months or seasons in order to omit winter low flows, when ice effects reduce the quality of the records and validity of statistical assumptions. Regression equations for estimating the selected high-flow and low-flow statistics for the selected months and seasons for ungaged sites were developed from an ordinary-least-squares regression model using basin characteristics as independent variables. Drainage area and precipitation were significant explanatory variables for high flows, and drainage area, precipitation, mean basin elevation, and area of glaciers were significant explanatory variables for low flows. The estimating equations can be used at ungaged sites in Alaska and conterminous basins in Canada where streamflow regulation, streamflow diversion, urbanization, and natural damming and releasing of water do not affect the streamflow data for the given month or season. Standard errors of estimate ranged from 15 to 56 percent for high-duration flow statistics, 25 to greater than 500 percent for monthly low-duration flow statistics, 32 to 66 percent for seasonal low-duration flow statistics, and 53 to 64 percent for low-flow frequency statistics.

StreamStats: A water resources web application

USGS Publications Warehouse

Ries, Kernell G.; Guthrie, John G.; Rea, Alan H.; Steeves, Peter A.; Stewart, David W.

2008-01-01

Streamflow statistics, such as the 1-percent flood, the mean flow, and the 7-day 10-year low flow, are used by engineers, land managers, biologists, and many others to help guide decisions in their everyday work. For example, estimates of the 1-percent flood (the flow that is exceeded, on average, once in 100 years and has a 1-percent chance of being exceeded in any year, sometimes referred to as the 100-year flood) are used to create flood-plain maps that form the basis for setting insurance rates and land-use zoning. This and other streamflow statistics also are used for 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 the setting of minimum required streamflows to protect freshwater ecosystems. In addition, researchers, planners, regulators, and others often need to know the physical and climatic characteristics of the drainage basins (basin characteristics) and the influence of human activities, such as dams and water withdrawals, on streamflow upstream from locations of interest to understand the mechanisms that control water availability and quality at those locations. Knowledge of the streamflow network and downstream human activities also is necessary to adequately determine whether an upstream activity, such as a water withdrawal, can be allowed without adversely affecting downstream activities.Streamflow statistics could be needed at any location along a stream. Most often, streamflow statistics are needed at ungaged sites, where no streamflow data are available to compute the statistics. At U.S. Geological Survey (USGS) streamflow data-collection stations, which include streamgaging stations, partial-record stations, and miscellaneous-measurement stations, streamflow statistics can be computed from available data for the stations. Streamflow data are collected continuously at streamgaging stations. Streamflow measurements are collected systematically over a period of years at partial-record stations to estimate peak-flow or low-flow statistics. Streamflow measurements usually are collected at miscellaneous-measurement stations for specific hydrologic studies with various objectives.StreamStats is a Web-based Geographic Information System (GIS) application that was created by the USGS, in cooperation with Environmental Systems Research Institute, Inc. (ESRI)1, to provide users with access to an assortment of analytical tools that are useful for water-resources planning and management. StreamStats functionality is based on ESRI’s ArcHydro Data Model and Tools, described on the Web at http://resources.arcgis.com/en/communities/hydro/01vn0000000s000000.htm. StreamStats allows users to easily obtain streamflow statistics, basin characteristics, and descriptive information for USGS data-collection stations and user-selected ungaged sites. It also allows users to identify stream reaches that are upstream and downstream from user-selected sites, and to identify and obtain information for locations along the streams where activities that may affect streamflow conditions are occurring. This functionality can be accessed through a map-based user interface that appears in the user’s Web browser, or individual functions can be requested remotely as Web services by other Web or desktop computer applications. StreamStats can perform these analyses much faster than historically used manual techniques.StreamStats was designed so that each state would be implemented as a separate application, with a reliance on local partnerships to fund the individual applications, and a goal of eventual full national implementation. Idaho became the first state to implement StreamStats in 2003. By mid-2008, 14 states had applications available to the public, and 18 other states were in various stages of implementation.

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

USGS Publications Warehouse

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

2003-01-01

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

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 drainage area to estimate June and August median streamflows were developed for use when less accuracy is acceptable. These equations have average standard errors of prediction from -46 to 87 percent and from -57 to 133 percent, respectively.

Methods for estimating the magnitude and frequency of peak streamflows at ungaged sites in and near the Oklahoma Panhandle

USGS Publications Warehouse

Smith, S. Jerrod; Lewis, Jason M.; Graves, Grant M.

2015-09-28

Generalized-least-squares multiple-linear regression analysis was used to formulate regression relations between peak-streamflow frequency statistics and basin characteristics. Contributing drainage area was the only basin characteristic determined to be statistically significant for all percentage of annual exceedance probabilities and was the only basin characteristic used in regional regression equations for estimating peak-streamflow frequency statistics on unregulated streams in and near the Oklahoma Panhandle. The regression model pseudo-coefficient of determination, converted to percent, for the Oklahoma Panhandle regional regression equations ranged from about 38 to 63 percent. The standard errors of prediction and the standard model errors for the Oklahoma Panhandle regional regression equations ranged from about 84 to 148 percent and from about 76 to 138 percent, respectively. These errors were comparable to those reported for regional peak-streamflow frequency regression equations for the High Plains areas of Texas and Colorado. The root mean square errors for the Oklahoma Panhandle regional regression equations (ranging from 3,170 to 92,000 cubic feet per second) were less than the root mean square errors for the Oklahoma statewide regression equations (ranging from 18,900 to 412,000 cubic feet per second); therefore, the Oklahoma Panhandle regional regression equations produce more accurate peak-streamflow statistic estimates for the irrigated period of record in the Oklahoma Panhandle than do the Oklahoma statewide regression equations. The regression equations developed in this report are applicable to streams that are not substantially affected by regulation, impoundment, or surface-water withdrawals. These regression equations are intended for use for stream sites with contributing drainage areas less than or equal to about 2,060 square miles, the maximum value for the independent variable used in the regression analysis.

Obtaining Streamflow Statistics for Massachusetts Streams on the World Wide Web

USGS Publications Warehouse

Ries, Kernell G.; Steeves, Peter A.; Freeman, Aleda; Singh, Raj

2000-01-01

A World Wide Web application has been developed to make it easy to obtain streamflow statistics for user-selected locations on Massachusetts streams. The Web application, named STREAMSTATS (available at http://water.usgs.gov/osw/streamstats/massachusetts.html ), can provide peak-flow frequency, low-flow frequency, and flow-duration statistics for most streams in Massachusetts. These statistics describe the magnitude (how much), frequency (how often), and duration (how long) of flow in a stream. The U.S. Geological Survey (USGS) has published streamflow statistics, such as the 100-year peak flow, the 7-day, 10-year low flow, and flow-duration statistics, for its data-collection stations in numerous reports. Federal, State, and local agencies need these statistics to plan and manage use of water resources and to regulate activities in and around streams. Engineering and environmental consulting firms, utilities, industry, and others use the statistics to design and operate water-supply systems, hydropower facilities, industrial facilities, wastewater treatment facilities, and roads, bridges, and other structures. Until now, streamflow statistics for data-collection stations have often been difficult to obtain because they are scattered among many reports, some of which are not readily available to the public. In addition, streamflow statistics are often needed for locations where no data are available. STREAMSTATS helps solve these problems. STREAMSTATS was developed jointly by the USGS and MassGIS, the State Geographic Information Systems (GIS) agency, in cooperation with the Massachusetts Departments of Environmental Management and Environmental Protection. The application consists of three major components: (1) a user interface that displays maps and allows users to select stream locations for which they want streamflow statistics (fig. 1), (2) a data base of previously published streamflow statistics and descriptive information for 725 USGS data-collection stations, and (3) an automated procedure that determines characteristics of the land-surface area (basin) that drains to the stream and inserts those characteristics into equations that estimate the streamflow statistics. Each of these components is described and guidance for using STREAMSTATS is provided below.

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

USGS Publications Warehouse

Unthank, Michael D.; Newson, Jeremy K.; Williamson, Tanja N.; Nelson, Hugh L.

2012-01-01

Flow- and load-duration curves were constructed from the model outputs of the U.S. Geological Survey's Water Availability Tool for Environmental Resources (WATER) application for streams in Kentucky. The WATER application was designed to access multiple geospatial datasets to generate more than 60 years of statistically based streamflow data for Kentucky. The WATER application enables a user to graphically select a site on a stream and generate an estimated hydrograph and flow-duration curve for the watershed upstream of that point. The flow-duration curves are constructed by calculating the exceedance probability of the modeled daily streamflows. User-defined water-quality criteria and (or) sampling results can be loaded into the WATER application to construct load-duration curves that are based on the modeled streamflow results. Estimates of flow and streamflow statistics were derived from TOPographically Based Hydrological MODEL (TOPMODEL) simulations in the WATER application. A modified TOPMODEL code, SDP-TOPMODEL (Sinkhole Drainage Process-TOPMODEL) was used to simulate daily mean discharges over the period of record for 5 karst and 5 non-karst watersheds in Kentucky in order to verify the calibrated model. A statistical evaluation of the model's verification simulations show that calibration criteria, established by previous WATER application reports, were met thus insuring the model's ability to provide acceptably accurate estimates of discharge at gaged and ungaged sites throughout Kentucky. Flow-duration curves are constructed in the WATER application by calculating the exceedence probability of the modeled daily flow values. The flow-duration intervals are expressed as a percentage, with zero corresponding to the highest stream discharge in the streamflow record. Load-duration curves are constructed by applying the loading equation (Load = Flow*Water-quality criterion) at each flow interval.

Methods for estimating annual exceedance-probability streamflows for streams in Kansas based on data through water year 2015

USGS Publications Warehouse

Painter, Colin C.; Heimann, David C.; Lanning-Rush, Jennifer L.

2017-08-14

A study was done by the U.S. Geological Survey in cooperation with the Kansas Department of Transportation and the Federal Emergency Management Agency to develop regression models to estimate peak streamflows of annual exceedance probabilities of 50, 20, 10, 4, 2, 1, 0.5, and 0.2 percent at ungaged locations in Kansas. Peak streamflow frequency statistics from selected streamgages were related to contributing drainage area and average precipitation using generalized least-squares regression analysis. The peak streamflow statistics were derived from 151 streamgages with at least 25 years of streamflow data through 2015. The developed equations can be used to predict peak streamflow magnitude and frequency within two hydrologic regions that were defined based on the effects of irrigation. The equations developed in this report are applicable to streams in Kansas that are not substantially affected by regulation, surface-water diversions, or urbanization. The equations are intended for use for streams with contributing drainage areas ranging from 0.17 to 14,901 square miles in the nonirrigation effects region and, 1.02 to 3,555 square miles in the irrigation-affected region, corresponding to the range of drainage areas of the streamgages used in the development of the regional equations.

Evaluation of statistical and rainfall-runoff models for predicting historical daily streamflow time series in the Des Moines and Iowa River watersheds

USGS Publications Warehouse

Farmer, William H.; Knight, Rodney R.; Eash, David A.; Kasey J. Hutchinson,; Linhart, S. Mike; Christiansen, Daniel E.; Archfield, Stacey A.; Over, Thomas M.; Kiang, Julie E.

2015-08-24

Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.

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.

Streamflow and Nutrient Fluxes of the Mississippi-Atchafalaya River Basin and Subbasins for the Period of Record Through 2005

USGS Publications Warehouse

Aulenbach, Brent T.; Buxton, Herbert T.; Battaglin, William A.; Coupe, Richard H.

2007-01-01

U.S. Geological Survey has monitored streamflow and water quality systematically in the Mississippi-Atchafalaya River Basin (MARB) for more than five decades. This report provides streamflow and estimates of nutrient delivery (flux) to the Gulf of Mexico from both the Atchafalaya River and the main stem of the Mississippi River. This report provides streamflow and nutrient flux estimates for nine major subbasins of the Mississippi River. This report also provides streamflow and flux estimates for 21 selected subbasins of various sizes, hydrology, land use, and geographic location within the Basin. The information is provided at each station for the period for which sufficient water-quality data are available to make statistically based flux estimates (starting as early as water year1 1960 and going through water year 2005). Nutrient fluxes are estimated using the adjusted maximum likelihood estimate, a type of regression-model method; nutrient fluxes to the Gulf of Mexico also are estimated using the composite method. Regression models were calibrated using a 5-year moving calibration period; the model was used to estimate the last year of the calibration period. Nutrient flux estimates are provided for six water-quality constituents: dissolved nitrite plus nitrate, total organic nitrogen plus ammonia nitrogen (total Kjeldahl nitrogen), dissolved ammonia, total phosphorous, dissolved orthophosphate, and dissolved silica. Additionally, the contribution of streamflow and net nutrient flux for five large subbasins comprising the MARB were determined from streamflow and nutrient fluxes from seven of the aforementioned major subbasins. These five large subbasins are: 1. Lower Mississippi, 2. Upper Mississippi, 3. Ohio/Tennessee, 4. Missouri, and 5. Arkansas/Red.

Low-flow statistics of selected streams in Chester County, Pennsylvania

USGS Publications Warehouse

Schreffler, Curtis L.

1998-01-01

Low-flow statistics for many streams in Chester County, Pa., were determined on the basis of data from 14 continuous-record streamflow stations in Chester County and data from 1 station in Maryland and 1 station in Delaware. The stations in Maryland and Delaware are on streams that drain large areas within Chester County. Streamflow data through the 1994 water year were used in the analyses. The low-flow statistics summarized are the 1Q10, 7Q10, 30Q10, and harmonic mean. Low-flow statistics were estimated at 34 partial-record stream sites throughout Chester County.

Streamflow characteristics related to channel geometry of streams in western United States

USGS Publications Warehouse

Hedman, E.R.; Osterkamp, W.R.

1982-01-01

Assessment of surface-mining and reclamation activities generally requires extensive hydrologic data. Adequate streamflow data from instrumented gaging stations rarely are available, and estimates of surface- water discharge based on rainfall-runoff models, drainage area, and basin characteristics sometimes have proven unreliable. Channel-geometry measurements offer an alternative method of quickly and inexpensively estimating stream-flow characteristics for ungaged streams. The method uses the empirical development of equations to yield a discharge value from channel-geometry and channel-material data. The equations are developed by collecting data at numerous streamflow-gaging sites and statistically relating those data to selected discharge characteristics. Mean annual runoff and flood discharges with selected recurrence intervals can be estimated for perennial, intermittent, and ephemeral streams. The equations were developed from data collected in the western one-half of the conterminous United States. The effect of the channel-material and runoff characteristics are accounted for with the equations.

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

USGS Publications Warehouse

Smith, S. Jerrod; Esralew, Rachel A.

2010-01-01

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

Evaluation of the streamgage network for estimating streamflow statistics at ungaged sites in Pennsylvania and the Susquehanna River Basin in Pennsylvania and New York

USGS Publications Warehouse

Sloto, Ronald A.; Stuckey, Marla H.; Hoffman, Scott A.

2017-05-10

The current (2015) streamgage network in Pennsylvania and the Susquehanna River Basin in Pennsylvania and New York was evaluated in order to design a network that would meet the hydrologic needs of many partners and serve a variety of purposes and interests, including estimation of streamflow statistics at ungaged sites. This study was done by the U.S. Geological Survey, in cooperation with the Pennsylvania Department of Environmental Protection and the Susquehanna River Basin Commission. The study area includes the Commonwealth of Pennsylvania and the Susquehanna River Basin in Pennsylvania and New York. For this study, 229 streamgages were identified as reference streamgages that could be used to represent ungaged watersheds. Criteria for a reference streamgage are a minimum of 10 years of continuous record, minimally altered streamflow, and a drainage area less than 1,500 square miles. Some of the reference streamgages have been discontinued but provide historical hydrologic information valuable in the determination of streamflow characteristics of ungaged watersheds. Watersheds in the study area not adequately represented by a reference streamgage were identified by examining a range of basin characteristics, the extent of geographic coverage, and the strength of estimated streamflow correlations between gaged and ungaged sites.Basin characteristics were determined for the reference streamgage watersheds and the 1,662 12-digit hydrologic unit code (HUC12) subwatersheds in Pennsylvania and the Susquehanna River Basin using a geographic information system (GIS) spatial analysis and nationally available GIS datasets. Basin characteristics selected for this study include drainage area, mean basin elevation, mean basin slope, percentage of urbanized area, percentage of forested area, percentage of carbonate bedrock, mean annual precipitation, and soil thickness. A GIS spatial analysis was used to identify HUC12 subwatersheds outside the range of basin characteristics of the reference streamgages. There were 320 HUC12 subwatersheds, or 19 percent of the study area, with basin characteristics outside the range represented by the reference streamgage watersheds.A GIS spatial analysis was used to identify geographic gaps in the streamgage network. For each streamgage, a watershed area, called the gage statistical area (GSA), was delineated. The GSA shows the drainage area within a specific drainage-area ratio of the streamgage for transfer of streamflow statistics from that streamgage to ungaged sites on the valid statistical reach of the GSA for a streamgage. In Pennsylvania, a drainage-area ratio of 0.33–3 times the drainage area of the ungaged site was found to perform as well as, if not better than, more traditional ratios such as 0.5–1.5 (or 2) for transfer of selected streamflow statistics. A total of 1,102 HUC12 subwatersheds, or 66 percent of the study area, are outside the GSA for a reference streamgage.The USGS Baseline Streamflow Estimator (BaSE) program was used to determine how well HUC12 subwatersheds outside the streamgage GSAs are represented by the reference streamgage network in Pennsylvania, based on estimated streamflow correlation. The centroid of each HUC12 subwatershed was run through the BaSE program to determine the reference streamgage with the highest estimated streamflow correlation. There were 929 HUC12 subwatersheds in Pennsylvania, or 56 percent of the State, with an estimated correlation coefficient less than 0.96.The results from the basin characteristic, geographic, and streamflow correlation analyses were combined to identify 1,405 HUC12 subwatersheds in Pennsylvania and the Susquehanna River Basin in Pennsylvania and New York that lack a representative reference, based on at least one identified gap. Of the 1,405 HUC12 subwatersheds, 139 exhibited all three gaps, indicating a 8-percent gap in the reference streamgage network.Streamgages in areas with similar hydrologic characteristics and in close proximity to one another can potentially provide similar information (termed streamgages with high substitution potential). Streamgages were considered to have a high substitution potential with a nearby streamgage(s) if (1) the streamflow correlation coefficient was equal to or greater than 0.96, (2) the streamgages had 10 years of concurrent record, and (3) the streamgages are in the same watershed within the GSA of the streamgage. Seventy-four current (2015) streamgages with high substitution potential with at least one other streamgage were identified in the study area. Although these identified streamgages have a high substitution potential, they provide valuable streamflow information to a stakeholder. Selected primary uses of these streamgages were identified to determine the overall need for an individual streamgage.

Updated techniques for estimating monthly streamflow-duration characteristics at ungaged and partial-record sites in central Nevada

USGS Publications Warehouse

Hess, Glen W.

2002-01-01

Techniques for estimating monthly streamflow-duration characteristics at ungaged and partial-record sites in central Nevada have been updated. These techniques were developed using streamflow records at six continuous-record sites, basin physical and climatic characteristics, and concurrent streamflow measurements at four partial-record sites. Two methods, the basin-characteristic method and the concurrent-measurement method, were developed to provide estimating techniques for selected streamflow characteristics at ungaged and partial-record sites in central Nevada. In the first method, logarithmic-regression analyses were used to relate monthly mean streamflows (from all months and by month) from continuous-record gaging sites of various percent exceedence levels or monthly mean streamflows (by month) to selected basin physical and climatic variables at ungaged sites. Analyses indicate that the total drainage area and percent of drainage area at altitudes greater than 10,000 feet are the most significant variables. For the equations developed from all months of monthly mean streamflow, the coefficient of determination averaged 0.84 and the standard error of estimate of the relations for the ungaged sites averaged 72 percent. For the equations derived from monthly means by month, the coefficient of determination averaged 0.72 and the standard error of estimate of the relations averaged 78 percent. If standard errors are compared, the relations developed in this study appear generally to be less accurate than those developed in a previous study. However, the new relations are based on additional data and the slight increase in error may be due to the wider range of streamflow for a longer period of record, 1995-2000. In the second method, streamflow measurements at partial-record sites were correlated with concurrent streamflows at nearby gaged sites by the use of linear-regression techniques. Statistical measures of results using the second method typically indicated greater accuracy than for the first method. However, to make estimates for individual months, the concurrent-measurement method requires several years additional streamflow data at more partial-record sites. Thus, exceedence values for individual months are not yet available due to the low number of concurrent-streamflow-measurement data available. Reliability, limitations, and applications of both estimating methods are described herein.

Use of digital land-cover data from the Landsat satellite in estimating streamflow characteristics in the Cumberland Plateau of Tennessee

USGS Publications Warehouse

Hollyday, E.F.; Hansen, G.R.

1983-01-01

Streamflow may be estimated with regression equations that relate streamflow characteristics to characteristics of the drainage basin. A statistical experiment was performed to compare the accuracy of equations using basin characteristics derived from maps and climatological records (control group equations) with the accuracy of equations using basin characteristics derived from Landsat data as well as maps and climatological records (experimental group equations). Results show that when the equations in both groups are arranged into six flow categories, there is no substantial difference in accuracy between control group equations and experimental group equations for this particular site where drainage area accounts for more than 90 percent of the variance in all streamflow characteristics (except low flows and most annual peak logarithms). (USGS)

Progress report on daily flow-routing simulation for the Carson River, California and Nevada

USGS Publications Warehouse

Hess, G.W.

1996-01-01

A physically based flow-routing model using Hydrological Simulation Program-FORTRAN (HSPF) was constructed for modeling streamflow in the Carson River at daily time intervals as part of the Truckee-Carson Program of the U.S. Geological Survey (USGS). Daily streamflow data for water years 1978-92 for the mainstem river, tributaries, and irrigation ditches from the East Fork Carson River near Markleeville and West Fork Carson River at Woodfords down to the mainstem Carson River at Fort Churchill upstream from Lahontan Reservoir were obtained from several agencies and were compiled into a comprehensive data base. No previous physically based flow-routing model of the Carson River has incorporated multi-agency streamflow data into a single data base and simulated flow at a daily time interval. Where streamflow data were unavailable or incomplete, hydrologic techniques were used to estimate some flows. For modeling purposes, the Carson River was divided into six segments, which correspond to those used in the Alpine Decree that governs water rights along the river. Hydraulic characteristics were defined for 48 individual stream reaches based on cross-sectional survey data obtained from field surveys and previous studies. Simulation results from the model were compared with available observed and estimated streamflow data. Model testing demonstrated that hydraulic characteristics of the Carson River are adequately represented in the models for a range of flow regimes. Differences between simulated and observed streamflow result mostly from inadequate data characterizing inflow and outflow from the river. Because irrigation return flows are largely unknown, irrigation return flow percentages were used as a calibration parameter to minimize differences between observed and simulated streamflows. Observed and simulated streamflow were compared for daily periods for the full modeled length of the Carson River and for two major subreaches modeled with more detailed input data. Hydrographs and statistics presented in this report describe these differences. A sensitivity analysis of four estimated components of the hydrologic system evaluated which components were significant in the model. Estimated ungaged tributary streamflow is not a significant component of the model during low runoff, but is significant during high runoff. The sensitivity analysis indicates that changes in the estimated irrigation diversion and estimated return flow creates a noticeable change in the statistics. The modeling for this study is preliminary. Results of the model are constrained by current availability and accuracy of observed hydrologic data. Several inflows and outflows of the Carson River are not described by time-series data and therefore are not represented in the model.

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

USGS Publications Warehouse

Haj, Adel E.; Christiansen, Daniel E.; Hutchinson, Kasey J.

2015-10-14

The accuracy of Precipitation-Runoff Modeling System model streamflow estimates of nine river basins in eastern Iowa as compared to measured values at U.S. Geological Survey streamflow-gaging stations varied. The Precipitation-Runoff Modeling System models of nine river basins in eastern Iowa were satisfactory at estimating daily streamflow at 57 of the 79 calibration sites and 13 of the 14 validation sites based on statistical results. Unsatisfactory performance can be contributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) the availability and accuracy of meteorological input data. The Precipitation- Runoff Modeling System models of nine river basins in eastern Iowa will provide water-resource managers with a consistent and documented method for estimating streamflow at ungaged sites and aid in environmental studies, hydraulic design, water management, and water-quality projects.

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

The drainage-area ratio method commonly is used to estimate streamflow for sites where no streamflow data are available using data from one or more nearby streamflow-gaging stations. The method is intuitive and straightforward to implement and is in widespread use by analysts and managers of surface-water resources. The method equates the ratio of streamflow at two stream locations to the ratio of the respective drainage areas. In practice, unity often is assumed as the exponent on the drainage-area ratio, and unity also is assumed as a multiplicative bias correction. These two assumptions are evaluated in this investigation through statewide analysis of daily mean streamflow in Texas. The investigation was made by the U.S. Geological Survey in cooperation with the Texas Commission on Environmental Quality. More than 7.8 million values of daily mean streamflow for 712 U.S. Geological Survey streamflow-gaging stations in Texas were analyzed. To account for the influence of streamflow probability on the drainage-area ratio method, 34 percentile ranges were considered. The 34 ranges are the 4 quartiles (0-25, 25-50, 50-75, and 75-100 percent), the 5 intervals of the lower tail of the streamflow distribution (0-1, 1-2, 2-3, 3-4, and 4-5 percent), the 20 quintiles of the 4 quartiles (0-5, 5-10, 10-15, 15-20, 20-25, 25-30, 30-35, 35-40, 40-45, 45-50, 50-55, 55-60, 60-65, 65-70, 70-75, 75-80, 80-85, 85-90, 90-95, and 95-100 percent), and the 5 intervals of the upper tail of the streamflow distribution (95-96, 96-97, 97-98, 98-99 and 99-100 percent). For each of the 253,116 (712X711/2) unique pairings of stations and for each of the 34 percentile ranges, the concurrent daily mean streamflow values available for the two stations provided for station-pair application of the drainage-area ratio method. For each station pair, specific statistical summarization (median, mean, and standard deviation) of both the exponent and bias-correction components of the drainage-area ratio method were computed. Statewide statistics (median, mean, and standard deviation) of the station-pair specific statistics subsequently were computed and are tabulated herein. A separate analysis considered conditioning station pairs to those stations within 100 miles of each other and with the absolute value of the logarithm (base-10) of the ratio of the drainage areas greater than or equal to 0.25. Statewide statistics of the conditional station-pair specific statistics were computed and are tabulated. The conditional analysis is preferable because of the anticipation that small separation distances reflect similar hydrologic conditions and the observation of large variation in exponent estimates for similar-sized drainage areas. The conditional analysis determined that the exponent is about 0.89 for streamflow percentiles from 0 to about 50 percent, is about 0.92 for percentiles from about 50 to about 65 percent, and is about 0.93 for percentiles from about 65 to about 85 percent. The exponent decreases rapidly to about 0.70 for percentiles nearing 100 percent. The computation of the bias-correction factor is sensitive to the range analysis interval (range of streamflow percentile); however, evidence suggests that in practice the drainage-area method can be considered unbiased. Finally, for general application, suggested values of the exponent are tabulated for 54 percentiles of daily mean streamflow in Texas; when these values are used, the bias correction is unity.

Estimating Low-Flow Frequency Statistics and Hydrologic Analysis of Selected Streamflow-Gaging Stations, Nooksack River Basin, Northwestern Washington and Canada

USGS Publications Warehouse

Curran, Christopher A.; Olsen, Theresa D.

2009-01-01

Low-flow frequency statistics were computed at 17 continuous-record streamflow-gaging stations and 8 miscellaneous measurement sites in and near the Nooksack River basin in northwestern Washington and Canada, including the 1, 3, 7, 15, 30, and 60 consecutive-day low flows with recurrence intervals of 2 and 10 years. Using these low-flow statistics, 12 regional regression equations were developed for estimating the same low-flow statistics at ungaged sites in the Nooksack River basin using a weighted-least-squares method. Adjusted R2 (coefficient of determination) values for the equations ranged from 0.79 to 0.93 and the root-mean-squared error (RMSE) expressed as a percentage ranged from 77 to 560 percent. Streamflow records from six gaging stations located in mountain-stream or lowland-stream subbasins of the Nooksack River basin were analyzed to determine if any of the gaging stations could be removed from the network without significant loss of information. Using methods of hydrograph comparison, daily-value correlation, variable space, and flow-duration ratios, and other factors relating to individual subbasins, the six gaging stations were prioritized from most to least important as follows: Skookum Creek (12209490), Anderson Creek (12210900), Warm Creek (12207750), Fishtrap Creek (12212050), Racehorse Creek (12206900), and Clearwater Creek (12207850). The optimum streamflow-gaging station network would contain all gaging stations except Clearwater Creek, and the minimum network would include Skookum Creek and Anderson Creek.

The Application of Censored Regression Models in Low Streamflow Analyses

NASA Astrophysics Data System (ADS)

Kroll, C.; Luz, J.

2003-12-01

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

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.

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.

Regression equations for estimation of annual peak-streamflow frequency for undeveloped watersheds in Texas using an L-moment-based, PRESS-minimized, residual-adjusted approach

USGS Publications Warehouse

Asquith, William H.; Roussel, Meghan C.

2009-01-01

Annual peak-streamflow frequency estimates are needed for flood-plain management; for objective assessment of flood risk; for cost-effective design of dams, levees, and other flood-control structures; and for design of roads, bridges, and culverts. Annual peak-streamflow frequency represents the peak streamflow for nine recurrence intervals of 2, 5, 10, 25, 50, 100, 200, 250, and 500 years. Common methods for estimation of peak-streamflow frequency for ungaged or unmonitored watersheds are regression equations for each recurrence interval developed for one or more regions; such regional equations are the subject of this report. The method is based on analysis of annual peak-streamflow data from U.S. Geological Survey streamflow-gaging stations (stations). Beginning in 2007, the U.S. Geological Survey, in cooperation with the Texas Department of Transportation and in partnership with Texas Tech University, began a 3-year investigation concerning the development of regional equations to estimate annual peak-streamflow frequency for undeveloped watersheds in Texas. The investigation focuses primarily on 638 stations with 8 or more years of data from undeveloped watersheds and other criteria. The general approach is explicitly limited to the use of L-moment statistics, which are used in conjunction with a technique of multi-linear regression referred to as PRESS minimization. The approach used to develop the regional equations, which was refined during the investigation, is referred to as the 'L-moment-based, PRESS-minimized, residual-adjusted approach'. For the approach, seven unique distributions are fit to the sample L-moments of the data for each of 638 stations and trimmed means of the seven results of the distributions for each recurrence interval are used to define the station specific, peak-streamflow frequency. As a first iteration of regression, nine weighted-least-squares, PRESS-minimized, multi-linear regression equations are computed using the watershed characteristics of drainage area, dimensionless main-channel slope, and mean annual precipitation. The residuals of the nine equations are spatially mapped, and residuals for the 10-year recurrence interval are selected for generalization to 1-degree latitude and longitude quadrangles. The generalized residual is referred to as the OmegaEM parameter and represents a generalized terrain and climate index that expresses peak-streamflow potential not otherwise represented in the three watershed characteristics. The OmegaEM parameter was assigned to each station, and using OmegaEM, nine additional regression equations are computed. Because of favorable diagnostics, the OmegaEM equations are expected to be generally reliable estimators of peak-streamflow frequency for undeveloped and ungaged stream locations in Texas. The mean residual standard error, adjusted R-squared, and percentage reduction of PRESS by use of OmegaEM are 0.30log10, 0.86, and -21 percent, respectively. Inclusion of the OmegaEM parameter provides a substantial reduction in the PRESS statistic of the regression equations and removes considerable spatial dependency in regression residuals. Although the OmegaEM parameter requires interpretation on the part of analysts and the potential exists that different analysts could estimate different values for a given watershed, the authors suggest that typical uncertainty in the OmegaEM estimate might be about +or-0.1010. Finally, given the two ensembles of equations reported herein and those in previous reports, hydrologic design engineers and other analysts have several different methods, which represent different analytical tracks, to make comparisons of peak-streamflow frequency estimates for ungaged watersheds in the study area.

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.

Implementation and Evaluation of the Streamflow Statistics (StreamStats) Web Application for Computing Basin Characteristics and Flood Peaks in Illinois

USGS Publications Warehouse

Ishii, Audrey L.; Soong, David T.; Sharpe, Jennifer B.

2010-01-01

Illinois StreamStats (ILSS) is a Web-based application for computing selected basin characteristics and flood-peak quantiles based on the most recently (2010) published (Soong and others, 2004) regional flood-frequency equations at any rural stream location in Illinois. Limited streamflow statistics including general statistics, flow durations, and base flows also are available for U.S. Geological Survey (USGS) streamflow-gaging stations. ILSS can be accessed on the Web at http://streamstats.usgs.gov/ by selecting the State Applications hyperlink and choosing Illinois from the pull-down menu. ILSS was implemented for Illinois by obtaining and projecting ancillary geographic information system (GIS) coverages; populating the StreamStats database with streamflow-gaging station data; hydroprocessing the 30-meter digital elevation model (DEM) for Illinois to conform to streams represented in the National Hydrographic Dataset 1:100,000 stream coverage; and customizing the Web-based Extensible Markup Language (XML) programs for computing basin characteristics for Illinois. The basin characteristics computed by ILSS then were compared to the basin characteristics used in the published study, and adjustments were applied to the XML algorithms for slope and basin length. Testing of ILSS was accomplished by comparing flood quantiles computed by ILSS at a an approximately random sample of 170 streamflow-gaging stations computed by ILSS with the published flood quantile estimates. Differences between the log-transformed flood quantiles were not statistically significant at the 95-percent confidence level for the State as a whole, nor by the regions determined by each equation, except for region 1, in the northwest corner of the State. In region 1, the average difference in flood quantile estimates ranged from 3.76 percent for the 2-year flood quantile to 4.27 percent for the 500-year flood quantile. The total number of stations in region 1 was small (21) and the mean difference is not large (less than one-tenth of the average prediction error for the regression-equation estimates). The sensitivity of the flood-quantile estimates to differences in the computed basin characteristics are determined and presented in tables. A test of usage consistency was conducted by having at least 7 new users compute flood quantile estimates at 27 locations. The average maximum deviation of the estimate from the mode value at each site was 1.31 percent after four mislocated sites were removed. A comparison of manual 100-year flood-quantile computations with ILSS at 34 sites indicated no statistically significant difference. ILSS appears to be an accurate, reliable, and effective tool for flood-quantile estimates.

Methods for estimating flow-duration and annual mean-flow statistics for ungaged streams in Oklahoma

USGS Publications Warehouse

Esralew, Rachel A.; Smith, S. Jerrod

2010-01-01

Flow statistics can be used to provide decision makers with surface-water information needed for activities such as water-supply permitting, flow regulation, and other water rights issues. Flow statistics could be needed at any location along a stream. Most often, streamflow statistics are needed at ungaged sites, where no flow data are available to compute the statistics. Methods are presented in this report for estimating flow-duration and annual mean-flow statistics for ungaged streams in Oklahoma. Flow statistics included the (1) annual (period of record), (2) seasonal (summer-autumn and winter-spring), and (3) 12 monthly duration statistics, including the 20th, 50th, 80th, 90th, and 95th percentile flow exceedances, and the annual mean-flow (mean of daily flows for the period of record). Flow statistics were calculated from daily streamflow information collected from 235 streamflow-gaging stations throughout Oklahoma and areas in adjacent states. A drainage-area ratio method is the preferred method for estimating flow statistics at an ungaged location that is on a stream near a gage. The method generally is reliable only if the drainage-area ratio of the two sites is between 0.5 and 1.5. Regression equations that relate flow statistics to drainage-basin characteristics were developed for the purpose of estimating selected flow-duration and annual mean-flow statistics for ungaged streams that are not near gaging stations on the same stream. Regression equations were developed from flow statistics and drainage-basin characteristics for 113 unregulated gaging stations. Separate regression equations were developed by using U.S. Geological Survey streamflow-gaging stations in regions with similar drainage-basin characteristics. These equations can increase the accuracy of regression equations used for estimating flow-duration and annual mean-flow statistics at ungaged stream locations in Oklahoma. Streamflow-gaging stations were grouped by selected drainage-basin characteristics by using a k-means cluster analysis. Three regions were identified for Oklahoma on the basis of the clustering of gaging stations and a manual delineation of distinguishable hydrologic and geologic boundaries: Region 1 (western Oklahoma excluding the Oklahoma and Texas Panhandles), Region 2 (north- and south-central Oklahoma), and Region 3 (eastern and central Oklahoma). A total of 228 regression equations (225 flow-duration regressions and three annual mean-flow regressions) were developed using ordinary least-squares and left-censored (Tobit) multiple-regression techniques. These equations can be used to estimate 75 flow-duration statistics and annual mean-flow for ungaged streams in the three regions. Drainage-basin characteristics that were statistically significant independent variables in the regression analyses were (1) contributing drainage area; (2) station elevation; (3) mean drainage-basin elevation; (4) channel slope; (5) percentage of forested canopy; (6) mean drainage-basin hillslope; (7) soil permeability; and (8) mean annual, seasonal, and monthly precipitation. The accuracy of flow-duration regression equations generally decreased from high-flow exceedance (low-exceedance probability) to low-flow exceedance (high-exceedance probability) . This decrease may have happened because a greater uncertainty exists for low-flow estimates and low-flow is largely affected by localized geology that was not quantified by the drainage-basin characteristics selected. The standard errors of estimate of regression equations for Region 1 (western Oklahoma) were substantially larger than those standard errors for other regions, especially for low-flow exceedances. These errors may be a result of greater variability in low flow because of increased irrigation activities in this region. Regression equations may not be reliable for sites where the drainage-basin characteristics are outside the range of values of independent vari

Estimating Selected Streamflow Statistics Representative of 1930-2002 in West Virginia

USGS Publications Warehouse

Wiley, Jeffrey B.

2008-01-01

Regional equations and procedures were developed for estimating 1-, 3-, 7-, 14-, and 30-day 2-year; 1-, 3-, 7-, 14-, and 30-day 5-year; and 1-, 3-, 7-, 14-, and 30-day 10-year hydrologically based low-flow frequency values for unregulated streams in West Virginia. Regional equations and procedures also were developed for estimating the 1-day, 3-year and 4-day, 3-year biologically based low-flow frequency values; the U.S. Environmental Protection Agency harmonic-mean flows; and the 10-, 25-, 50-, 75-, and 90-percent flow-duration values. Regional equations were developed using ordinary least-squares regression using statistics from 117 U.S. Geological Survey continuous streamflow-gaging stations as dependent variables and basin characteristics as independent variables. Equations for three regions in West Virginia - North, South-Central, and Eastern Panhandle - were determined. Drainage area, precipitation, and longitude of the basin centroid are significant independent variables in one or more of the equations. Estimating procedures are presented for determining statistics at a gaging station, a partial-record station, and an ungaged location. Examples of some estimating procedures are presented.

Estimates of Flow Duration, Mean Flow, and Peak-Discharge Frequency Values for Kansas Stream Locations

USGS Publications Warehouse

Perry, Charles A.; Wolock, David M.; Artman, Joshua C.

2004-01-01

Streamflow statistics of flow duration and peak-discharge frequency were estimated for 4,771 individual locations on streams listed on the 1999 Kansas Surface Water Register. These statistics included the flow-duration values of 90, 75, 50, 25, and 10 percent, as well as the mean flow value. Peak-discharge frequency values were estimated for the 2-, 5-, 10-, 25-, 50-, and 100-year floods. Least-squares multiple regression techniques were used, along with Tobit analyses, to develop equations for estimating flow-duration values of 90, 75, 50, 25, and 10 percent and the mean flow for uncontrolled flow stream locations. The contributing-drainage areas of 149 U.S. Geological Survey streamflow-gaging stations in Kansas and parts of surrounding States that had flow uncontrolled by Federal reservoirs and used in the regression analyses ranged from 2.06 to 12,004 square miles. Logarithmic transformations of climatic and basin data were performed to yield the best linear relation for developing equations to compute flow durations and mean flow. In the regression analyses, the significant climatic and basin characteristics, in order of importance, were contributing-drainage area, mean annual precipitation, mean basin permeability, and mean basin slope. The analyses yielded a model standard error of prediction range of 0.43 logarithmic units for the 90-percent duration analysis to 0.15 logarithmic units for the 10-percent duration analysis. The model standard error of prediction was 0.14 logarithmic units for the mean flow. Regression equations used to estimate peak-discharge frequency values were obtained from a previous report, and estimates for the 2-, 5-, 10-, 25-, 50-, and 100-year floods were determined for this report. The regression equations and an interpolation procedure were used to compute flow durations, mean flow, and estimates of peak-discharge frequency for locations along uncontrolled flow streams on the 1999 Kansas Surface Water Register. Flow durations, mean flow, and peak-discharge frequency values determined at available gaging stations were used to interpolate the regression-estimated flows for the stream locations where available. Streamflow statistics for locations that had uncontrolled flow were interpolated using data from gaging stations weighted according to the drainage area and the bias between the regression-estimated and gaged flow information. On controlled reaches of Kansas streams, the streamflow statistics were interpolated between gaging stations using only gaged data weighted by drainage area.

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

USGS Publications Warehouse

Koltun, G.F.; Holtschlag, David J.

2010-01-01

Bootstrapping techniques employing random subsampling were used with the AFINCH (Analysis of Flows In Networks of CHannels) model to gain insights into the effects of variation in streamflow-gaging-network size and composition on the accuracy and precision of streamflow estimates at ungaged locations in the 0405 (Southeast Lake Michigan) hydrologic subregion. AFINCH uses stepwise-regression techniques to estimate monthly water yields from catchments based on geospatial-climate and land-cover data in combination with available streamflow and water-use data. Calculations are performed on a hydrologic-subregion scale for each catchment and stream reach contained in a National Hydrography Dataset Plus (NHDPlus) subregion. Water yields from contributing catchments are multiplied by catchment areas and resulting flow values are accumulated to compute streamflows in stream reaches which are referred to as flow lines. AFINCH imposes constraints on water yields to ensure that observed streamflows are conserved at gaged locations.  Data from the 0405 hydrologic subregion (referred to as Southeast Lake Michigan) were used for the analyses. Daily streamflow data were measured in the subregion for 1 or more years at a total of 75 streamflow-gaging stations during the analysis period which spanned water years 1971–2003. The number of streamflow gages in operation each year during the analysis period ranged from 42 to 56 and averaged 47. Six sets (one set for each censoring level), each composed of 30 random subsets of the 75 streamflow gages, were created by censoring (removing) approximately 10, 20, 30, 40, 50, and 75 percent of the streamflow gages (the actual percentage of operating streamflow gages censored for each set varied from year to year, and within the year from subset to subset, but averaged approximately the indicated percentages).Streamflow estimates for six flow lines each were aggregated by censoring level, and results were analyzed to assess (a) how the size and composition of the streamflow-gaging network affected the average apparent errors and variability of the estimated flows and (b) whether results for certain months were more variable than for others. The six flow lines were categorized into one of three types depending upon their network topology and position relative to operating streamflow-gaging stations.    Statistical analysis of the model results indicates that (1) less precise (that is, more variable) estimates resulted from smaller streamflow-gaging networks as compared to larger streamflow-gaging networks, (2) precision of AFINCH flow estimates at an ungaged flow line is improved by operation of one or more streamflow gages upstream and (or) downstream in the enclosing basin, (3) no consistent seasonal trend in estimate variability was evident, and (4) flow lines from ungaged basins appeared to exhibit the smallest absolute apparent percent errors (APEs) and smallest changes in average APE as a function of increasing censoring level. The counterintuitive results described in item (4) above likely reflect both the nature of the base-streamflow estimate from which the errors were computed and insensitivity in the average model-derived estimates to changes in the streamflow-gaging-network size and composition. Another analysis demonstrated that errors for flow lines in ungaged basins have the potential to be much larger than indicated by their APEs if measured relative to their true (but unknown) flows.     “Missing gage” analyses, based on examination of censoring subset results where the streamflow gage of interest was omitted from the calibration data set, were done to better understand the true error characteristics for ungaged flow lines as a function of network size. Results examined for 2 water years indicated that the probability of computing a monthly streamflow estimate within 10 percent of the true value with AFINCH decreased from greater than 0.9 at about a 10-percent network-censoring level to less than 0.6 as the censoring level approached 75 percent. In addition, estimates for typically dry months tended to be characterized by larger percent errors than typically wetter months.

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

USGS Publications Warehouse

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

2009-01-01

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

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 undeveloped, unregulated sites have not been affected by the increase in average precipitation. The ratio of instantaneous peak flow to 3-day mean flow, ratios of flow duration, ratios of high-flow/low-flow frequency, and coefficient of variation were used to define streamflow variability. Streamflow variability was significantly greater among the group of gaging stations located outside the Coastal Plain than among the group of gaging stations located in the Coastal Plain.

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

NASA Astrophysics Data System (ADS)

Huang, Q. Z.; Hsu, S. Y.; Li, M. H.

2016-12-01

The long-term streamflow prediction is important not only to estimate water-storage of a reservoir but also to the surface water intakes, which supply people's livelihood, agriculture, and industry. Climatology forecasts of streamflow have been traditionally used for calculating the exceedance probability curve of streamflow and water resource management. In this study, we proposed a stochastic approach to predict the exceedance probability curve of long-term streamflow with the seasonal weather outlook from Central Weather Bureau (CWB), Taiwan. The approach incorporates a statistical downscale weather generator and a catchment-scale hydrological model to convert the monthly outlook into daily rainfall and temperature series and to simulate the streamflow based on the outlook information. Moreover, we applied Bayes' theorem to derive a method for calculating the exceedance probability curve of the reservoir inflow based on the seasonal weather outlook and its imperfection. The results show that our approach can give the exceedance probability curves reflecting the three-month weather outlook and its accuracy. We also show how the improvement of the weather outlook affects the predicted exceedance probability curves of the streamflow. Our approach should be useful for the seasonal planning and management of water resource and their risk assessment.

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

USGS Publications Warehouse

Barbie, Dana L.; Wehmeyer, Loren L.

2012-01-01

Trends in selected streamflow statistics during 1922-2009 were evaluated at 19 long-term streamflow-gaging stations considered indicative of outflows from Texas to Arkansas, Louisiana, Galveston Bay, and the Gulf of Mexico. The U.S. Geological Survey, in cooperation with the Texas Water Development Board, evaluated streamflow data from streamflow-gaging stations with more than 50 years of record that were active as of 2009. The outflows into Arkansas and Louisiana were represented by 3 streamflow-gaging stations, and outflows into the Gulf of Mexico, including Galveston Bay, were represented by 16 streamflow-gaging stations. Monotonic trend analyses were done using the following three streamflow statistics generated from daily mean values of streamflow: (1) annual mean daily discharge, (2) annual maximum daily discharge, and (3) annual minimum daily discharge. The trend analyses were based on the nonparametric Kendall's Tau test, which is useful for the detection of monotonic upward or downward trends with time. A total of 69 trend analyses by Kendall's Tau were computed - 19 periods of streamflow multiplied by the 3 streamflow statistics plus 12 additional trend analyses because the periods of record for 2 streamflow-gaging stations were divided into periods representing pre- and post-reservoir impoundment. Unless otherwise described, each trend analysis used the entire period of record for each streamflow-gaging station. The monotonic trend analysis detected 11 statistically significant downward trends, 37 instances of no trend, and 21 statistically significant upward trends. One general region studied, which seemingly has relatively more upward trends for many of the streamflow statistics analyzed, includes the rivers and associated creeks and bayous to Galveston Bay in the Houston metropolitan area. Lastly, the most western river basins considered (the Nueces and Rio Grande) had statistically significant downward trends for many of the streamflow statistics analyzed.

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 days. In addition, the composite estimates ensure a gradual transition between periods of estimated and measured flows. Model performance among stations of differing model error magnitudes were compared by computing ratios of the mean standard deviation of the length l composite errors to the standard deviation of OLSR errors. The mean error ratio for the set of 25 selected stations was less than 1 for intervals l < 32 days. Considering the frequency characteristics of the length of intervals of estimated record in Michigan, the effective mean error ratio for intervals < 30 days was 0.52. Thus, for intervals of estimation of 1 month or less, the error of the composite estimate is substantially lower than error of the OLSR estimate.

Estimating predictive hydrological uncertainty by dressing deterministic and ensemble forecasts; a comparison, with application to Meuse and Rhine

NASA Astrophysics Data System (ADS)

Verkade, J. S.; Brown, J. D.; Davids, F.; Reggiani, P.; Weerts, A. H.

2017-12-01

Two statistical post-processing approaches for estimation of predictive hydrological uncertainty are compared: (i) 'dressing' of a deterministic forecast by adding a single, combined estimate of both hydrological and meteorological uncertainty and (ii) 'dressing' of an ensemble streamflow forecast by adding an estimate of hydrological uncertainty to each individual streamflow ensemble member. Both approaches aim to produce an estimate of the 'total uncertainty' that captures both the meteorological and hydrological uncertainties. They differ in the degree to which they make use of statistical post-processing techniques. In the 'lumped' approach, both sources of uncertainty are lumped by post-processing deterministic forecasts using their verifying observations. In the 'source-specific' approach, the meteorological uncertainties are estimated by an ensemble of weather forecasts. These ensemble members are routed through a hydrological model and a realization of the probability distribution of hydrological uncertainties (only) is then added to each ensemble member to arrive at an estimate of the total uncertainty. The techniques are applied to one location in the Meuse basin and three locations in the Rhine basin. Resulting forecasts are assessed for their reliability and sharpness, as well as compared in terms of multiple verification scores including the relative mean error, Brier Skill Score, Mean Continuous Ranked Probability Skill Score, Relative Operating Characteristic Score and Relative Economic Value. The dressed deterministic forecasts are generally more reliable than the dressed ensemble forecasts, but the latter are sharper. On balance, however, they show similar quality across a range of verification metrics, with the dressed ensembles coming out slightly better. Some additional analyses are suggested. Notably, these include statistical post-processing of the meteorological forecasts in order to increase their reliability, thus increasing the reliability of the streamflow forecasts produced with ensemble meteorological forcings.

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.

Detection, attribution, and sensitivity of trends toward earlier streamflow in the Sierra Nevada

USGS Publications Warehouse

Maurer, E.P.; Stewart, I.T.; Bonfils, Celine; Duffy, P.B.; Cayan, D.

2007-01-01

Observed changes in the timing of snowmelt dominated streamflow in the western United States are often linked to anthropogenic or other external causes. We assess whether observed streamflow timing changes can be statistically attributed to external forcing, or whether they still lie within the bounds of natural (internal) variability for four large Sierra Nevada (CA) basins, at inflow points to major reservoirs. Streamflow timing is measured by "center timing" (CT), the day when half the annual flow has passed a given point. We use a physically based hydrology model driven by meteorological input from a global climate model to quantify the natural variability in CT trends. Estimated 50-year trends in CT due to natural climate variability often exceed estimated actual CT trends from 1950 to 1999. Thus, although observed trends in CT to date may be statistically significant, they cannot yet be statistically attributed to external influences on climate. We estimate that projected CT changes at the four major reservoir inflows will, with 90% confidence, exceed those from natural variability within 1-4 decades or 4-8 decades, depending on rates of future greenhouse gas emissions. To identify areas most likely to exhibit CT changes in response to rising temperatures, we calculate changes in CT under temperature increases from 1 to 5??. We find that areas with average winter temperatures between -2??C and -4??C are most likely to respond with significant CT shifts. Correspondingly, elevations from 2000 to 2800 in are most sensitive to temperature increases, with CT changes exceeding 45 days (earlier) relative to 1961-1990. Copyright 2007 by the American Geophysical Union.

Estimating the Magnitude and Frequency of Floods in Small Urban Streams in South Carolina, 2001

USGS Publications Warehouse

Feaster, Toby D.; Guimaraes, Wladimir B.

2004-01-01

The magnitude and frequency of floods at 20 streamflowgaging stations on small, unregulated urban streams in or near South Carolina were estimated by fitting the measured wateryear peak flows to a log-Pearson Type-III distribution. The period of record (through September 30, 2001) for the measured water-year peak flows ranged from 11 to 25 years with a mean and median length of 16 years. The drainage areas of the streamflow-gaging stations ranged from 0.18 to 41 square miles. Based on the flood-frequency estimates from the 20 streamflow-gaging stations (13 in South Carolina; 4 in North Carolina; and 3 in Georgia), generalized least-squares regression was used to develop regional regression equations. These equations can be used to estimate the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence-interval flows for small urban streams in the Piedmont, upper Coastal Plain, and lower Coastal Plain physiographic provinces of South Carolina. The most significant explanatory variables from this analysis were mainchannel length, percent impervious area, and basin development factor. Mean standard errors of prediction for the regression equations ranged from -25 to 33 percent for the 10-year recurrence-interval flows and from -35 to 54 percent for the 100-year recurrence-interval flows. The U.S. Geological Survey has developed a Geographic Information System application called StreamStats that makes the process of computing streamflow statistics at ungaged sites faster and more consistent than manual methods. This application was developed in the Massachusetts District and ongoing work is being done in other districts to develop a similar application using streamflow statistics relative to those respective States. Considering the future possibility of implementing StreamStats in South Carolina, an alternative set of regional regression equations was developed using only main channel length and impervious area. This was done because no digital coverages are currently available for basin development factor and, therefore, it could not be included in the StreamStats application. The average mean standard error of prediction for the alternative equations was 2 to 5 percent larger than the standard errors for the equations that contained basin development factor. For the urban streamflow-gaging stations in South Carolina, measured water-year peak flows were compared with those from an earlier urban flood-frequency investigation. The peak flows from the earlier investigation were computed using a rainfall-runoff model. At many of the sites, graphical comparisons indicated that the variance of the measured data was much less than the variance of the simulated data. Several statistical tests were applied to compare the variances and the means of the measured and simulated data for each site. The results indicated that the variances were significantly different for 11 of the 13 South Carolina streamflow-gaging stations. For one streamflow-gaging station, the test for normality, which is one of the assumptions of the data when comparing variances, indicated that neither the measured data nor the simulated data were distributed normally; therefore, the test for differences in the variances was not used for that streamflow-gaging station. Another statistical test was used to test for statistically significant differences in the means of the measured and simulated data. The results indicated that for 5 of the 13 urban streamflowgaging stations in South Carolina there was a statistically significant difference in the means of the two data sets. For comparison purposes and to test the hypothesis that there may have been climatic differences between the period in which the measured peak-flow data were measured and the period for which historic rainfall data were used to compute the simulated peak flows, 16 rural streamflow-gaging stations with long-term records were reviewed using similar techniques as those used for the measured an

Streamflow Simulations and Percolation Estimates Using the Soil and Water Assessment Tool for Selected Basins in North-Central Nebraska, 1940-2005

USGS Publications Warehouse

Strauch, Kellan R.; Linard, Joshua I.

2009-01-01

The U.S. Geological Survey, in cooperation with the Upper Elkhorn, Lower Elkhorn, Upper Loup, Lower Loup, Middle Niobrara, Lower Niobrara, Lewis and Clark, and Lower Platte North Natural Resources Districts, used the Soil and Water Assessment Tool to simulate streamflow and estimate percolation in north-central Nebraska to aid development of long-term strategies for management of hydrologically connected ground and surface water. Although groundwater models adequately simulate subsurface hydrologic processes, they often are not designed to simulate the hydrologically complex processes occurring at or near the land surface. The use of watershed models such as the Soil and Water Assessment Tool, which are designed specifically to simulate surface and near-subsurface processes, can provide helpful insight into the effects of surface-water hydrology on the groundwater system. The Soil and Water Assessment Tool was calibrated for five stream basins in the Elkhorn-Loup Groundwater Model study area in north-central Nebraska to obtain spatially variable estimates of percolation. Six watershed models were calibrated to recorded streamflow in each subbasin by modifying the adjustment parameters. The calibrated parameter sets were then used to simulate a validation period; the validation period was half of the total streamflow period of record with a minimum requirement of 10 years. If the statistical and water-balance results for the validation period were similar to those for the calibration period, a model was considered satisfactory. Statistical measures of each watershed model's performance were variable. These objective measures included the Nash-Sutcliffe measure of efficiency, the ratio of the root-mean-square error to the standard deviation of the measured data, and an estimate of bias. The model met performance criteria for the bias statistic, but failed to meet statistical adequacy criteria for the other two performance measures when evaluated at a monthly time step. A primary cause of the poor model validation results was the inability of the model to reproduce the sustained base flow and streamflow response to precipitation that was observed in the Sand Hills region. The watershed models also were evaluated based on how well they conformed to the annual mass balance (precipitation equals the sum of evapotranspiration, streamflow/runoff, and deep percolation). The model was able to adequately simulate annual values of evapotranspiration, runoff, and precipitation in comparison to reported values, which indicates the model may provide reasonable estimates of annual percolation. Mean annual percolation estimated by the model as basin averages varied within the study area from a maximum of 12.9 inches in the Loup River Basin to a minimum of 1.5 inches in the Shell Creek Basin. Percolation also varied within the studied basins; basin headwaters tended to have greater percolation rates than downstream areas. This variance in percolation rates was mainly was because of the predominance of sandy, highly permeable soils in the upstream areas of the modeled basins.

Comparison between two statistically based methods, and two physically based models developed to compute daily mean streamflow at ungaged locations in the Cedar River Basin, Iowa

USGS Publications Warehouse

Linhart, S. Mike; Nania, Jon F.; Christiansen, Daniel E.; Hutchinson, Kasey J.; Sanders, Curtis L.; Archfield, Stacey A.

2013-01-01

A variety of individuals from water resource managers to recreational users need streamflow information for planning and decisionmaking at locations where there are no streamgages. To address this problem, two statistically based methods, the Flow Duration Curve Transfer method and the Flow Anywhere method, were developed for statewide application and the two physically based models, the Precipitation Runoff Modeling-System and the Soil and Water Assessment Tool, were only developed for application for the Cedar River Basin. Observed and estimated streamflows for the two methods and models were compared for goodness of fit at 13 streamgages modeled in the Cedar River Basin by using the Nash-Sutcliffe and the percent-bias efficiency values. Based on median and mean Nash-Sutcliffe values for the 13 streamgages the Precipitation Runoff Modeling-System and Soil and Water Assessment Tool models appear to have performed similarly and better than Flow Duration Curve Transfer and Flow Anywhere methods. Based on median and mean percent bias values, the Soil and Water Assessment Tool model appears to have generally overestimated daily mean streamflows, whereas the Precipitation Runoff Modeling-System model and statistical methods appear to have underestimated daily mean streamflows. The Flow Duration Curve Transfer method produced the lowest median and mean percent bias values and appears to perform better than the other models.

Estimation of selected seasonal streamflow statistics representative of 1930-2002 in West Virginia

USGS Publications Warehouse

Wiley, Jeffrey B.; Atkins, John T.

2010-01-01

Regional equations and procedures were developed for estimating seasonal 1-day 10-year, 7-day 10-year, and 30-day 5-year hydrologically based low-flow frequency values for unregulated streams in West Virginia. Regional equations and procedures also were developed for estimating the seasonal U.S. Environmental Protection Agency harmonic-mean flows and the 50-percent flow-duration values. The seasons were defined as winter (January 1-March 31), spring (April 1-June 30), summer (July 1-September 30), and fall (October 1-December 31). Regional equations were developed using ordinary least squares regression using statistics from 117 U.S. Geological Survey continuous streamgage stations as dependent variables and basin characteristics as independent variables. Equations for three regions in West Virginia-North, South-Central, and Eastern Panhandle Regions-were determined. Drainage area, average annual precipitation, and longitude of the basin centroid are significant independent variables in one or more of the equations. The average standard error of estimates for the equations ranged from 12.6 to 299 percent. Procedures developed to estimate the selected seasonal streamflow statistics in this study are applicable only to rural, unregulated streams within the boundaries of West Virginia that have independent variables within the limits of the stations used to develop the regional equations: drainage area from 16.3 to 1,516 square miles in the North Region, from 2.78 to 1,619 square miles in the South-Central Region, and from 8.83 to 3,041 square miles in the Eastern Panhandle Region; average annual precipitation from 42.3 to 61.4 inches in the South-Central Region and from 39.8 to 52.9 inches in the Eastern Panhandle Region; and longitude of the basin centroid from 79.618 to 82.023 decimal degrees in the North Region. All estimates of seasonal streamflow statistics are representative of the period from the 1930 to the 2002 climatic year.

Total Phosphorus Loads for Selected Tributaries to Sebago Lake, Maine

USGS Publications Warehouse

Hodgkins, Glenn A.

2001-01-01

The streamflow and water-quality datacollection networks of the Portland Water District (PWD) and the U.S. Geological Survey (USGS) as of February 2000 were analyzed in terms of their applicability for estimating total phosphorus loads for selected tributaries to Sebago Lake in southern Maine. The long-term unit-area mean annual flows for the Songo River and for small, ungaged tributaries are similar to the long-term unit-area mean annual flows for the Crooked River and other gaged tributaries to Sebago Lake, based on a regression equation that estimates mean annual streamflows in Maine. Unit-area peak streamflows of Sebago Lake tributaries can be quite different, based on a regression equation that estimates peak streamflows for Maine. Crooked River had a statistically significant positive relation (Kendall's Tau test, p=0.0004) between streamflow and total phosphorus concentration. Panther Run had a statistically significant negative relation (p=0.0015). Significant positive relations may indicate contributions from nonpoint sources or sediment resuspension, whereas significant negative relations may indicate dilution of point sources. Total phosphorus concentrations were significantly larger in the Crooked River than in the Songo River (Wilcoxon rank-sum test, p<0.0001). Evidence was insufficient, however, to indicate that phosphorus concentrations from medium-sized drainage basins, at a significance level of 0.05, were different from each other or that concentrations in small-sized drainage basins were different from each other (Kruskal-Wallis test, p= 0.0980, 0.1265). All large- and medium-sized drainage basins were sampled for total phosphorus approximately monthly. Although not all small drainage basins were sampled, they may be well represented by the small drainage basins that were sampled. If the tributaries gaged by PWD had adequate streamflow data, the current PWD tributary monitoring program would probably produce total phosphorus loading data that would represent all gaged and ungaged tributaries to Sebago Lake. Outside the PWD tributary-monitoring program, the largest ungaged tributary to Sebago Lake contains 1.5 percent of the area draining to the lake. In the absence of unique point or nonpoint sources of phosphorus, ungaged tributaries are unlikely to have total phosphorus concentrations that differ significantly from those in the small tributaries that have concentration data. The regression method, also known as the rating-curve method, was used to estimate the annual total phosphorus load for Crooked River, Northwest River, and Rich Mill Pond Outlet for water years 1996-98. The MOVE.1 method was used to estimate daily streamflows for the regression method at Northwest River and Rich Mill Pond Outlet, where streamflows were not continuously monitored. An averaging method also was used to compute annual loads at the three sites. The difference between the regression estimate and the averaging estimate for each of the three tributaries was consistent with what was expected from previous studies.

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

USGS Publications Warehouse

Waldron, Marcus C.; Archfield, Stacey A.

2006-01-01

Factors affecting reservoir firm yield, as determined by application of the Massachusetts Department of Environmental Protection's Firm Yield Estimator (FYE) model, were evaluated, modified, and tested on 46 streamflow-dominated reservoirs representing 15 Massachusetts drinking-water supplies. The model uses a mass-balance approach to determine the maximum average daily withdrawal rate that can be sustained during a period of record that includes the 1960s drought-of-record. The FYE methodology to estimate streamflow to the reservoir at an ungaged site was tested by simulating streamflow at two streamflow-gaging stations in Massachusetts and comparing the simulated streamflow to the observed streamflow. In general, the FYE-simulated flows agreed well with observed flows. There were substantial deviations from the measured values for extreme high and low flows. A sensitivity analysis determined that the model's streamflow estimates are most sensitive to input values for average annual precipitation, reservoir drainage area, and the soil-retention number-a term that describes the amount of precipitation retained by the soil in the basin. The FYE model currently provides the option of using a 1,000-year synthetic record constructed by randomly sampling 2-year blocks of concurrent streamflow and precipitation records 500 times; however, the synthetic record has the potential to generate records of precipitation and streamflow that do not reflect the worst historical drought in Massachusetts. For reservoirs that do not have periods of drawdown greater than 2 years, the bootstrap does not offer any additional information about the firm yield of a reservoir than the historical record does. For some reservoirs, the use of a synthetic record to determine firm yield resulted in as much as a 30-percent difference between firm-yield values from one simulation to the next. Furthermore, the assumption that the synthetic traces of streamflow are statistically equivalent to the historical record is not valid. For multiple-reservoir systems, the firm-yield estimate was dependent on the reservoir system's configuration. The firm yield of a system is sensitive to how the water is transferred from one reservoir to another, the capacity of the connection between the reservoirs, and how seasonal variations in demand are represented in the FYE model. Firm yields for 25 (14 single-reservoir systems and 11 multiple-reservoir systems) reservoir systems were determined by using the historical records of streamflow and precipitation. Current water-use data indicate that, on average, 20 of the 25 reservoir systems in the study were operating below their estimated firm yield; during months with peak demands, withdrawals exceeded the firm yield for 8 reservoir systems.

Selected Streamflow Statistics and Regression Equations for Predicting Statistics at Stream Locations in Monroe County, Pennsylvania

USGS Publications Warehouse

Thompson, Ronald E.; Hoffman, Scott A.

2006-01-01

A suite of 28 streamflow statistics, ranging from extreme low to high flows, was computed for 17 continuous-record streamflow-gaging stations and predicted for 20 partial-record stations in Monroe County and contiguous counties in north-eastern Pennsylvania. The predicted statistics for the partial-record stations were based on regression analyses relating inter-mittent flow measurements made at the partial-record stations indexed to concurrent daily mean flows at continuous-record stations during base-flow conditions. The same statistics also were predicted for 134 ungaged stream locations in Monroe County on the basis of regression analyses relating the statistics to GIS-determined basin characteristics for the continuous-record station drainage areas. The prediction methodology for developing the regression equations used to estimate statistics was developed for estimating low-flow frequencies. This study and a companion study found that the methodology also has application potential for predicting intermediate- and high-flow statistics. The statistics included mean monthly flows, mean annual flow, 7-day low flows for three recurrence intervals, nine flow durations, mean annual base flow, and annual mean base flows for two recurrence intervals. Low standard errors of prediction and high coefficients of determination (R2) indicated good results in using the regression equations to predict the statistics. Regression equations for the larger flow statistics tended to have lower standard errors of prediction and higher coefficients of determination (R2) than equations for the smaller flow statistics. The report discusses the methodologies used in determining the statistics and the limitations of the statistics and the equations used to predict the statistics. Caution is indicated in using the predicted statistics for small drainage area situations. Study results constitute input needed by water-resource managers in Monroe County for planning purposes and evaluation of water-resources availability.

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

USGS Publications Warehouse

Asquith, William H.; Heitmuller, Franklin T.

2008-01-01

Analysts and managers of surface-water resources have interest in annual mean and annual harmonic mean statistics of daily mean streamflow for U.S. Geological Survey (USGS) streamflow-gaging stations in Texas. The mean streamflow represents streamflow volume, whereas the harmonic mean streamflow represents an appropriate statistic for assessing constituent concentrations that might adversely affect human health. In 2008, the USGS, in cooperation with the Texas Commission on Environmental Quality, conducted a large-scale documentation of mean and harmonic mean streamflow for 620 active and inactive, continuous-record, streamflow-gaging stations using period of record data through water year 2007. About 99 stations within the Texas USGS streamflow-gaging network are part of the larger national Hydroclimatic Data Network and are identified. The graphical depictions of annual mean and annual harmonic mean statistics in this report provide a historical perspective of streamflow at each station. Each figure consists of three time-series plots, two flow-duration curves, and a statistical summary of the mean annual and annual harmonic mean streamflow statistics for available data for each station.The first time-series plot depicts daily mean streamflow for the period 1900-2007. Flow-duration curves follow and are a graphical depiction of streamflow variability. Next, the remaining two time-series plots depict annual mean and annual harmonic mean streamflow and are augmented with horizontal lines that depict mean and harmonic mean for the period of record. Monotonic trends for the annual mean streamflow and annual harmonic mean streamflow also are identified using Kendall's tau, and the slope of the trend is depicted using the nonparametric (linear) Theil-Sen line, which is only drawn for p-values less than .10 of tau. The history of annual mean and annual harmonic mean streamflow of one or more streamflow-gaging stations could be used in a watershed, river basin, or other regional context by analysts and managers of surface-water resources to guide scientific, regulatory, or other inquiries of streamflow conditions in Texas.

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

NASA Astrophysics Data System (ADS)

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

2009-05-01

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

Application of at-site peak-streamflow frequency analyses for very low annual exceedance probabilities

USGS Publications Warehouse

Asquith, William H.; Kiang, Julie E.; Cohn, Timothy A.

2017-07-17

The U.S. Geological Survey (USGS), in cooperation with the U.S. Nuclear Regulatory Commission, has investigated statistical methods for probabilistic flood hazard assessment to provide guidance on very low annual exceedance probability (AEP) estimation of peak-streamflow frequency and the quantification of corresponding uncertainties using streamgage-specific data. The term “very low AEP” implies exceptionally rare events defined as those having AEPs less than about 0.001 (or 1 × 10–3 in scientific notation or for brevity 10–3). Such low AEPs are of great interest to those involved with peak-streamflow frequency analyses for critical infrastructure, such as nuclear power plants. Flood frequency analyses at streamgages are most commonly based on annual instantaneous peak streamflow data and a probability distribution fit to these data. The fitted distribution provides a means to extrapolate to very low AEPs. Within the United States, the Pearson type III probability distribution, when fit to the base-10 logarithms of streamflow, is widely used, but other distribution choices exist. The USGS-PeakFQ software, implementing the Pearson type III within the Federal agency guidelines of Bulletin 17B (method of moments) and updates to the expected moments algorithm (EMA), was specially adapted for an “Extended Output” user option to provide estimates at selected AEPs from 10–3 to 10–6. Parameter estimation methods, in addition to product moments and EMA, include L-moments, maximum likelihood, and maximum product of spacings (maximum spacing estimation). This study comprehensively investigates multiple distributions and parameter estimation methods for two USGS streamgages (01400500 Raritan River at Manville, New Jersey, and 01638500 Potomac River at Point of Rocks, Maryland). The results of this study specifically involve the four methods for parameter estimation and up to nine probability distributions, including the generalized extreme value, generalized log-normal, generalized Pareto, and Weibull. Uncertainties in streamflow estimates for corresponding AEP are depicted and quantified as two primary forms: quantile (aleatoric [random sampling] uncertainty) and distribution-choice (epistemic [model] uncertainty). Sampling uncertainties of a given distribution are relatively straightforward to compute from analytical or Monte Carlo-based approaches. Distribution-choice uncertainty stems from choices of potentially applicable probability distributions for which divergence among the choices increases as AEP decreases. Conventional goodness-of-fit statistics, such as Cramér-von Mises, and L-moment ratio diagrams are demonstrated in order to hone distribution choice. The results generally show that distribution choice uncertainty is larger than sampling uncertainty for very low AEP values.

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.

Evaluation of long-term trends in hydrologic and water-quality conditions, and estimation of water budgets through 2013, Chester County, Pennsylvania

USGS Publications Warehouse

Sloto, Ronald A.; Reif, Andrew G.

2017-06-02

An evaluation of trends in hydrologic and water quality conditions and estimation of water budgets through 2013 was done by the U.S. Geological Survey in cooperation with the Chester County Water Resources Authority. Long-term hydrologic, meteorologic, and biologic data collected in Chester County, Pennsylvania, which included streamflow, groundwater levels, surface-water quality, biotic integrity, precipitation, and air temperature were analyzed to determine possible trends or changes in hydrologic conditions. Statistically significant trends were determined by applying the Kendall rank correlation test; the magnitudes of the trends were determined using the Sen slope estimator. Water budgets for eight selected watersheds were updated and a new water budget was developed for the Marsh Creek watershed. An average water budget for Chester County was developed using the eight selected watersheds and the new Marsh Creek water budget.Annual and monthly mean streamflow, base flow, and runoff were analyzed for trends at 10 streamgages. The periods of record at the 10 streamgages ranged from 1961‒2013 to 1988‒2013. The only statistically significant trend for annual mean streamflow was for West Branch Brandywine Creek near Honey Brook, Pa. (01480300) where annual mean streamflow increased 1.6 cubic feet per second (ft3/s) per decade. The greatest increase in monthly mean streamflow was for Brandywine Creek at Chadds Ford, Pa. (01481000) for December; the increase was 47 ft3/s per decade. No statistically significant trends in annual mean base flow or runoff were determined for the 10 streamgages. The greatest increase in monthly mean base flow was for Brandywine Creek at Chadds Ford, Pa. (01481000) for December; the increase was 26 ft3/s per decade.The magnitude of peaks greater than a base streamflow was analyzed for trends for 12 streamgages. The period of record at the 12 stream gages ranged from 1912‒2012 to 2004–11. Fifty percent of the streamgages showed a small statistically significant increase in peaks greater than the base streamflow. The greatest increase was for Brandywine Creek at Chadds Ford, Pa. (01481000) during 1962‒2012; the increase was 1.8 ft3/s per decade. There were no statistically significant trends in the number of floods equal to or greater than the 2-year recurrence interval flood flow.Twenty‒one monitoring wells were evaluated for statistically significant trends in annual mean water level, minimum annual water level, maximum annual water level, and annual range in water-level fluctuations. For four wells, a small statistically significant increase in annual mean water level was determined that ranged from 0.16 to 0.7 feet per decade. There was poor or no correlation between annual mean groundwater levels and annual mean streamflow and base flow. No correlation was determined between annual mean groundwater level and annual precipitation. Despite rapid population growth and land-use change since 1950, there appears to have been little or no detrimental effects on groundwater levels in 21 monitoring wells.Long-term precipitation and temperature data were available from the West Chester (1893‒2013) and Phoenixville, Pa. (1915‒2013) National Oceanic and Atmospheric Administration (NOAA) weather stations. No statistically significant trends in annual mean precipitation or annual mean temperature were determined for either station. Both weather stations had a significant decrease in the number of days per year with precipitation greater than or equal to 0.1 inch. Annual mean minimum and maximum temperatures from the NOAA Southeastern Piedmont Climate Division increased 0.2 degrees Fahrenheit (F) per decade between 1896 and 2014. The number of days with a maximum temperature equal to or greater than 90 degrees F increased at West Chester and decreased at Phoenixville. No statistically significant trend was determined for annual snowfall amounts.Data from 1974 to 2013 for three stream water-quality monitors in the Brandywine Creek watershed were evaluated. The monitors are on the West Branch Brandywine Creek at Modena, Pa. (01480617), East Branch Brandywine Creek below Downingtown, Pa. (01480870), and Brandywine Creek at Chadds Ford, Pa. (01481000). Statistically significant upward trends were determined for annual mean specific conductance at all three stations, indicating the total dissolved solids load has been increasing. If the current trend continues, the annual mean specific conductance could almost double from 1974 to 2050. The increase in specific conductance likely is due to increases in chloride concentrations, which have been increasing steadily over time at all three stations. No correlation was found between monthly mean specific conductance and monthly mean streamflow or base flow. Statistically significant upward trends in pH were determined for all three stations. Statistically significant upward trends in stream temperature were determined for East Branch Brandywine Creek below Downingtown, Pa. (01480870) and Brandywine Creek at Chadds Ford, Pa. (01481000). The stream water-quality data indicate substantial increases in the minimum daily dissolved oxygen concentrations in the Brandywine Creek over time.The Chester County Index of Biotic Integrity (CC-IBI) determined for 1998‒2013 was evaluated for the five biological sampling sites collocated with streamgages. CC-IBI scores are based on a 0‒100 scale with higher scores indicating better stream quality. Statistically significant upward trends in the CC-IBI were determined for West Branch Brandywine Creek at Modena, Pa. (01480617) and East Branch Brandywine Creek below Downingtown, Pa. (01480870). No correlation was found between the CC-IBI and streamflow, precipitation, or stream specific conductance, pH, temperature, or dissolved oxygen concentration.A Chester County average water budget was developed using the nine estimated watershed water budgets. Average precipitation was 48.4 inches, and average streamflow was 21.4 inches. Average runoff and base flow were 8.3 and 13.1 inches, respectively, and average evapotranspiration and estimation of errors was 27.2 inches."

Load estimator (LOADEST): a FORTRAN program for estimating constituent loads in streams and rivers

USGS Publications Warehouse

Runkel, Robert L.; Crawford, Charles G.; Cohn, Timothy A.

2004-01-01

LOAD ESTimator (LOADEST) is a FORTRAN program for estimating constituent loads in streams and rivers. Given a time series of streamflow, additional data variables, and constituent concentration, LOADEST assists the user in developing a regression model for the estimation of constituent load (calibration). Explanatory variables within the regression model include various functions of streamflow, decimal time, and additional user-specified data variables. The formulated regression model then is used to estimate loads over a user-specified time interval (estimation). Mean load estimates, standard errors, and 95 percent confidence intervals are developed on a monthly and(or) seasonal basis. The calibration and estimation procedures within LOADEST are based on three statistical estimation methods. The first two methods, Adjusted Maximum Likelihood Estimation (AMLE) and Maximum Likelihood Estimation (MLE), are appropriate when the calibration model errors (residuals) are normally distributed. Of the two, AMLE is the method of choice when the calibration data set (time series of streamflow, additional data variables, and concentration) contains censored data. The third method, Least Absolute Deviation (LAD), is an alternative to maximum likelihood estimation when the residuals are not normally distributed. LOADEST output includes diagnostic tests and warnings to assist the user in determining the appropriate estimation method and in interpreting the estimated loads. This report describes the development and application of LOADEST. Sections of the report describe estimation theory, input/output specifications, sample applications, and installation instructions.

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.

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.

Median and Low-Flow Characteristics for Streams under Natural and Diverted Conditions, Northeast Maui, Hawaii

USGS Publications Warehouse

Gingerich, Stephen B.

2005-01-01

Flow-duration statistics under natural (undiverted) and diverted flow conditions were estimated for gaged and ungaged sites on 21 streams in northeast Maui, Hawaii. The estimates were made using the optimal combination of continuous-record gaging-station data, low-flow measurements, and values determined from regression equations developed as part of this study. Estimated 50- and 95-percent flow duration statistics for streams are presented and the analyses done to develop and evaluate the methods used in estimating the statistics are described. Estimated streamflow statistics are presented for sites where various amounts of streamflow data are available as well as for locations where no data are available. Daily mean flows were used to determine flow-duration statistics for continuous-record stream-gaging stations in the study area following U.S. Geological Survey established standard methods. Duration discharges of 50- and 95-percent were determined from total flow and base flow for each continuous-record station. The index-station method was used to adjust all of the streamflow records to a common, long-term period. The gaging station on West Wailuaiki Stream (16518000) was chosen as the index station because of its record length (1914-2003) and favorable geographic location. Adjustments based on the index-station method resulted in decreases to the 50-percent duration total flow, 50-percent duration base flow, 95-percent duration total flow, and 95-percent duration base flow computed on the basis of short-term records that averaged 7, 3, 4, and 1 percent, respectively. For the drainage basin of each continuous-record gaged site and selected ungaged sites, morphometric, geologic, soil, and rainfall characteristics were quantified using Geographic Information System techniques. Regression equations relating the non-diverted streamflow statistics to basin characteristics of the gaged basins were developed using ordinary-least-squares regression analyses. Rainfall rate, maximum basin elevation, and the elongation ratio of the basin were the basin characteristics used in the final regression equations for 50-percent duration total flow and base flow. Rainfall rate and maximum basin elevation were used in the final regression equations for the 95-percent duration total flow and base flow. The relative errors between observed and estimated flows ranged from 10 to 20 percent for the 50-percent duration total flow and base flow, and from 29 to 56 percent for the 95-percent duration total flow and base flow. The regression equations developed for this study were used to determine the 50-percent duration total flow, 50-percent duration base flow, 95-percent duration total flow, and 95-percent duration base flow at selected ungaged diverted and undiverted sites. Estimated streamflow, prediction intervals, and standard errors were determined for 48 ungaged sites in the study area and for three gaged sites west of the study area. Relative errors were determined for sites where measured values of 95-percent duration discharge of total flow were available. East of Keanae Valley, the 95-percent duration discharge equation generally underestimated flow, and within and west of Keanae Valley, the equation generally overestimated flow. Reduction in 50- and 95-percent flow-duration values in stream reaches affected by diversions throughout the study area average 58 to 60 percent.

The origin and evolution of safe-yield policies in the Kansas groundwater management districts

USGS Publications Warehouse

Sophocleous, M.

2000-01-01

The management of groundwater resources in Kansas continues to evolve. Declines in the High Plains aquifer led to the establishment of groundwater management districts in the mid-1970s and reduced streamflows prompted the enactment of minimum desirable streamflow standards in the mid-1980s. Nonetheless, groundwater levels and streamflows continued to decline, although at reduced rates compared to premid-1980s rates. As a result, "safe-yield" policies were revised to take into account natural groundwater discharge in the form of stream baseflow. These policies, although a step in the right direction, are deficient in several ways. In addition to the need for more accurate recharge data, pumping-induced streamflow depletion, natural stream losses, and groundwater evapotranspiration need to be accounted for in the revised safe-yield policies. Furthermore, the choice of the 90% flow-duration statistic as a measure of baseflow needs to be reevaluated, as it significantly underestimates mean baseflow estimated from baseflow separation computer programs; moreover, baseflow estimation needs to be refined and validated. ?? 2000 International Association for Mathematical Geology.

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.

Regression model development and computational procedures to support estimation of real-time concentrations and loads of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-9

USGS Publications Warehouse

Lee, Michael T.; Asquith, William H.; Oden, Timothy D.

2012-01-01

In December 2005, the U.S. Geological Survey (USGS), in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria (Escherichia coli and total coliform), atrazine, and suspended sediment at two USGS streamflow-gaging stations that represent watersheds contributing to Lake Houston (08068500 Spring Creek near Spring, Tex., and 08070200 East Fork San Jacinto River near New Caney, Tex.). Data from the discrete water-quality samples collected during 2005–9, in conjunction with continuously monitored real-time data that included streamflow and other physical water-quality properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), were used to develop regression models for the estimation of concentrations of water-quality constituents of substantial source watersheds to Lake Houston. The potential explanatory variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, and time (to account for seasonal variations inherent in some water-quality data). The response variables (the selected constituents) at each site were nitrite plus nitrate nitrogen, total phosphorus, total organic carbon, E. coli, atrazine, and suspended sediment. The explanatory variables provide easily measured quantities to serve as potential surrogate variables to estimate concentrations of the selected constituents through statistical regression. Statistical regression also facilitates accompanying estimates of uncertainty in the form of prediction intervals. Each regression model potentially can be used to estimate concentrations of a given constituent in real time. Among other regression diagnostics, the diagnostics used as indicators of general model reliability and reported herein include the adjusted R-squared, the residual standard error, residual plots, and p-values. Adjusted R-squared values for the Spring Creek models ranged from .582–.922 (dimensionless). The residual standard errors ranged from .073–.447 (base-10 logarithm). Adjusted R-squared values for the East Fork San Jacinto River models ranged from .253–.853 (dimensionless). The residual standard errors ranged from .076–.388 (base-10 logarithm). In conjunction with estimated concentrations, constituent loads can be estimated by multiplying the estimated concentration by the corresponding streamflow and by applying the appropriate conversion factor. The regression models presented in this report are site specific, that is, they are specific to the Spring Creek and East Fork San Jacinto River streamflow-gaging stations; however, the general methods that were developed and documented could be applied to most perennial streams for the purpose of estimating real-time water quality data.

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.

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.

Low-flow characteristics of Virginia streams

USGS Publications Warehouse

Austin, Samuel H.; Krstolic, Jennifer L.; Wiegand, Ute

2011-01-01

Low-flow annual non-exceedance probabilities (ANEP), called probability-percent chance (P-percent chance) flow estimates, regional regression equations, and transfer methods are provided describing the low-flow characteristics of Virginia streams. Statistical methods are used to evaluate streamflow data. Analysis of Virginia streamflow data collected from 1895 through 2007 is summarized. Methods are provided for estimating low-flow characteristics of gaged and ungaged streams. The 1-, 4-, 7-, and 30-day average streamgaging station low-flow characteristics for 290 long-term, continuous-record, streamgaging stations are determined, adjusted for instances of zero flow using a conditional probability adjustment method, and presented for non-exceedance probabilities of 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.05, 0.02, 0.01, and 0.005. Stream basin characteristics computed using spatial data and a geographic information system are used as explanatory variables in regional regression equations to estimate annual non-exceedance probabilities at gaged and ungaged sites and are summarized for 290 long-term, continuous-record streamgaging stations, 136 short-term, continuous-record streamgaging stations, and 613 partial-record streamgaging stations. Regional regression equations for six physiographic regions use basin characteristics to estimate 1-, 4-, 7-, and 30-day average low-flow annual non-exceedance probabilities at gaged and ungaged sites. Weighted low-flow values that combine computed streamgaging station low-flow characteristics and annual non-exceedance probabilities from regional regression equations provide improved low-flow estimates. Regression equations developed using the Maintenance of Variance with Extension (MOVE.1) method describe the line of organic correlation (LOC) with an appropriate index site for low-flow characteristics at 136 short-term, continuous-record streamgaging stations and 613 partial-record streamgaging stations. Monthly streamflow statistics computed on the individual daily mean streamflows of selected continuous-record streamgaging stations and curves describing flow-duration are presented. Text, figures, and lists are provided summarizing low-flow estimates, selected low-flow sites, delineated physiographic regions, basin characteristics, regression equations, error estimates, definitions, and data sources. This study supersedes previous studies of low flows in Virginia.

Flood of June 22-24, 2006, in North-Central Ohio, With Emphasis on the Cuyahoga River Near Independence

USGS Publications Warehouse

Sherwood, James M.; Ebner, Andrew D.; Koltun, G.F.; Astifan, Brian M.

2007-01-01

Heavy rains caused severe flooding on June 22-24, 2006, and damaged approximately 4,580 homes and 48 businesses in Cuyahoga County. Damage estimates in Cuyahoga County for the two days of flooding exceed $47 million; statewide damage estimates exceed $150 million. Six counties (Cuyahoga, Erie, Huron, Lucas, Sandusky, and Stark) in northeast Ohio were declared Federal disaster areas. One death, in Lorain County, was attributed to the flooding. The peak streamflow of 25,400 cubic feet per second and corresponding peak gage height of 23.29 feet were the highest recorded at the U.S. Geological Survey (USGS) streamflow-gaging station Cuyahoga River at Independence (04208000) since the gaging station began operation in 1922, exceeding the previous peak streamflow of 24,800 cubic feet per second that occurred on January 22, 1959. An indirect calculation of the peak streamflow was made by use of a step-backwater model because all roads leading to the gaging station were inundated during the flood and field crews could not reach the station to make a direct measurement. Because of a statistically significant and persistent positive trend in the annual-peak-streamflow time series for the Cuyahoga River at Independence, a method was developed and applied to detrend the annual-peak-streamflow time series prior to the traditional log-Pearson Type III flood-frequency analysis. Based on this analysis, the recurrence interval of the computed peak streamflow was estimated to be slightly less than 100 years. Peak-gage-height data, peak-streamflow data, and recurrence-interval estimates for the June 22-24, 2006, flood are tabulated for the Cuyahoga River at Independence and 10 other USGS gaging stations in north-central Ohio. Because flooding along the Cuyahoga River near Independence and Valley View was particularly severe, a study was done to document the peak water-surface profile during the flood from approximately 2 miles downstream from the USGS streamflow-gaging station at Independence to approximately 2 miles upstream from the gaging station. High-water marks were identified and flagged in the field. Third-order-accuracy surveys were used to determine elevations of the high-water marks, and the data were tabulated and plotted.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

Methodology for Estimation of Flood Magnitude and Frequency for New Jersey Streams

USGS Publications Warehouse

Watson, Kara M.; Schopp, Robert D.

2009-01-01

Methodologies were developed for estimating flood magnitudes at the 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals for unregulated or slightly regulated streams in New Jersey. Regression equations that incorporate basin characteristics were developed to estimate flood magnitude and frequency for streams throughout the State by use of a generalized least squares regression analysis. Relations between flood-frequency estimates based on streamflow-gaging-station discharge and basin characteristics were determined by multiple regression analysis, and weighted by effective years of record. The State was divided into five hydrologically similar regions to refine the regression equations. The regression analysis indicated that flood discharge, as determined by the streamflow-gaging-station annual peak flows, is related to the drainage area, main channel slope, percentage of lake and wetland areas in the basin, population density, and the flood-frequency region, at the 95-percent confidence level. The standard errors of estimate for the various recurrence-interval floods ranged from 48.1 to 62.7 percent. Annual-maximum peak flows observed at streamflow-gaging stations through water year 2007 and basin characteristics determined using geographic information system techniques for 254 streamflow-gaging stations were used for the regression analysis. Drainage areas of the streamflow-gaging stations range from 0.18 to 779 mi2. Peak-flow data and basin characteristics for 191 streamflow-gaging stations located in New Jersey were used, along with peak-flow data for stations located in adjoining States, including 25 stations in Pennsylvania, 17 stations in New York, 16 stations in Delaware, and 5 stations in Maryland. Streamflow records for selected stations outside of New Jersey were included in the present study because hydrologic, physiographic, and geologic boundaries commonly extend beyond political boundaries. The StreamStats web application was developed cooperatively by the U.S. Geological Survey and the Environmental Systems Research Institute, Inc., and was designed for national implementation. This web application has been recently implemented for use in New Jersey. This program used in conjunction with a geographic information system provides the computation of values for selected basin characteristics, estimates of flood magnitudes and frequencies, and statistics for stream locations in New Jersey chosen by the user, whether the site is gaged or ungaged.

Flood Frequency Curves - Use of information on the likelihood of extreme floods

NASA Astrophysics Data System (ADS)

Faber, B.

2011-12-01

Investment in the infrastructure that reduces flood risk for flood-prone communities must incorporate information on the magnitude and frequency of flooding in that area. Traditionally, that information has been a probability distribution of annual maximum streamflows developed from the historical gaged record at a stream site. Practice in the United States fits a Log-Pearson type3 distribution to the annual maximum flows of an unimpaired streamflow record, using the method of moments to estimate distribution parameters. The procedure makes the assumptions that annual peak streamflow events are (1) independent, (2) identically distributed, and (3) form a representative sample of the overall probability distribution. Each of these assumptions can be challenged. We rarely have enough data to form a representative sample, and therefore must compute and display the uncertainty in the estimated flood distribution. But, is there a wet/dry cycle that makes precipitation less than independent between successive years? Are the peak flows caused by different types of events from different statistical populations? How does the watershed or climate changing over time (non-stationarity) affect the probability distribution floods? Potential approaches to avoid these assumptions vary from estimating trend and shift and removing them from early data (and so forming a homogeneous data set), to methods that estimate statistical parameters that vary with time. A further issue in estimating a probability distribution of flood magnitude (the flood frequency curve) is whether a purely statistical approach can accurately capture the range and frequency of floods that are of interest. A meteorologically-based analysis produces "probable maximum precipitation" (PMP) and subsequently a "probable maximum flood" (PMF) that attempts to describe an upper bound on flood magnitude in a particular watershed. This analysis can help constrain the upper tail of the probability distribution, well beyond the range of gaged data or even historical or paleo-flood data, which can be very important in risk analyses performed for flood risk management and dam and levee safety studies.

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 larger range of natural variability in drought and pluvial events and better evaluate extreme events with recurrence intervals longer than the observed record. Establishing this natural baseline is critical when estimating future hydrologic risks under conditions of a non-stationary climate.

Techniques for Estimating the Magnitude and Frequency of Peak Flows on Small Streams in Minnesota Based on Data through Water Year 2005

USGS Publications Warehouse

Lorenz, David L.; Sanocki, Chris A.; Kocian, Matthew J.

2010-01-01

Knowledge of the peak flow of floods of a given recurrence interval is essential for regulation and planning of water resources and for design of bridges, culverts, and dams along Minnesota's rivers and streams. Statistical techniques are needed to estimate peak flow at ungaged sites because long-term streamflow records are available at relatively few places. Because of the need to have up-to-date peak-flow frequency information in order to estimate peak flows at ungaged sites, the U.S. Geological Survey (USGS) conducted a peak-flow frequency study in cooperation with the Minnesota Department of Transportation and the Minnesota Pollution Control Agency. Estimates of peak-flow magnitudes for 1.5-, 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals are presented for 330 streamflow-gaging stations in Minnesota and adjacent areas in Iowa and South Dakota based on data through water year 2005. The peak-flow frequency information was subsequently used in regression analyses to develop equations relating peak flows for selected recurrence intervals to various basin and climatic characteristics. Two statistically derived techniques-regional regression equation and region of influence regression-can be used to estimate peak flow on ungaged streams smaller than 3,000 square miles in Minnesota. Regional regression equations were developed for selected recurrence intervals in each of six regions in Minnesota: A (northwestern), B (north central and east central), C (northeastern), D (west central and south central), E (southwestern), and F (southeastern). The regression equations can be used to estimate peak flows at ungaged sites. The region of influence regression technique dynamically selects streamflow-gaging stations with characteristics similar to a site of interest. Thus, the region of influence regression technique allows use of a potentially unique set of gaging stations for estimating peak flow at each site of interest. Two methods of selecting streamflow-gaging stations, similarity and proximity, can be used for the region of influence regression technique. The regional regression equation technique is the preferred technique as an estimate of peak flow in all six regions for ungaged sites. The region of influence regression technique is not appropriate for regions C, E, and F because the interrelations of some characteristics of those regions do not agree with the interrelations throughout the rest of the State. Both the similarity and proximity methods for the region of influence technique can be used in the other regions (A, B, and D) to provide additional estimates of peak flow. The peak-flow-frequency estimates and basin characteristics for selected streamflow-gaging stations and regional peak-flow regression equations are included in this report.

Regression method for estimating long-term mean annual ground-water recharge rates from base flow in Pennsylvania

USGS Publications Warehouse

Risser, Dennis W.; Thompson, Ronald E.; Stuckey, Marla H.

2008-01-01

A method was developed for making estimates of long-term, mean annual ground-water recharge from streamflow data at 80 streamflow-gaging stations in Pennsylvania. The method relates mean annual base-flow yield derived from the streamflow data (as a proxy for recharge) to the climatic, geologic, hydrologic, and physiographic characteristics of the basins (basin characteristics) by use of a regression equation. Base-flow yield is the base flow of a stream divided by the drainage area of the basin, expressed in inches of water basinwide. Mean annual base-flow yield was computed for the period of available streamflow record at continuous streamflow-gaging stations by use of the computer program PART, which separates base flow from direct runoff on the streamflow hydrograph. Base flow provides a reasonable estimate of recharge for basins where streamflow is mostly unaffected by upstream regulation, diversion, or mining. Twenty-eight basin characteristics were included in the exploratory regression analysis as possible predictors of base-flow yield. Basin characteristics found to be statistically significant predictors of mean annual base-flow yield during 1971-2000 at the 95-percent confidence level were (1) mean annual precipitation, (2) average maximum daily temperature, (3) percentage of sand in the soil, (4) percentage of carbonate bedrock in the basin, and (5) stream channel slope. The equation for predicting recharge was developed using ordinary least-squares regression. The standard error of prediction for the equation on log-transformed data was 9.7 percent, and the coefficient of determination was 0.80. The equation can be used to predict long-term, mean annual recharge rates for ungaged basins, providing that the explanatory basin characteristics can be determined and that the underlying assumption is accepted that base-flow yield derived from PART is a reasonable estimate of ground-water recharge rates. For example, application of the equation for 370 hydrologic units in Pennsylvania predicted a range of ground-water recharge from about 6.0 to 22 inches per year. A map of the predicted recharge illustrates the general magnitude and variability of recharge throughout Pennsylvania.

Quantitative predictions of streamflow variability in the Susquehanna River Basin

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

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.

Regression equations for estimating concentrations of selected water-quality constituents for selected gaging stations in the Red River of the North Basin, North Dakota, Minnesota, and South Dakota

USGS Publications Warehouse

Williams-Sether, Tara

2004-01-01

The Dakota Water Resources Act, passed by the U.S. Congress on December 15, 2000, authorized the Secretary of the Interior to conduct a comprehensive study of future water-quantity and quality needs of the Red River of the North Basin in North Dakota and possible options to meet those water needs. Previous Red River of the North Basin studies conducted by the Bureau of Reclamation used streamflow and water-quality data bases developed by the U.S. Geological Survey that included data for 1931-84. As a result of the recent congressional authorization and results of previous studies by the Bureau of Reclamation, redevelopment of the streamflow and water-quality data bases with current data through 1999 are needed in order to evaluate and predict the water-quantity and quality effects within the Red River of the North Basin. This report provides updated statistical summaries of selected water-quality constituents and streamflow and the regression relations between them.  Available data for 1931-99 were used to develop regression equations between 5 selected water-quality constituents and streamflow for 38 gaging stations in the Red River of the North Basin. The water-quality constituents that were regressed against streamflow were hardness (as CaCO3), sodium, chloride, sulfate, and dissolved solids. Statistical summaries of the selected water-quality constituents and streamflow for the gaging stations used in the regression equations development and the applications and limitations of the regression equations are presented in this report.

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.

Topological and canonical kriging for design flood prediction in ungauged catchments: an improvement over a traditional regional regression approach?

USGS Publications Warehouse

Archfield, Stacey A.; Pugliese, Alessio; Castellarin, Attilio; Skøien, Jon O.; Kiang, Julie E.

2013-01-01

In the United States, estimation of flood frequency quantiles at ungauged locations has been largely based on regional regression techniques that relate measurable catchment descriptors to flood quantiles. More recently, spatial interpolation techniques of point data have been shown to be effective for predicting streamflow statistics (i.e., flood flows and low-flow indices) in ungauged catchments. Literature reports successful applications of two techniques, canonical kriging, CK (or physiographical-space-based interpolation, PSBI), and topological kriging, TK (or top-kriging). CK performs the spatial interpolation of the streamflow statistic of interest in the two-dimensional space of catchment descriptors. TK predicts the streamflow statistic along river networks taking both the catchment area and nested nature of catchments into account. It is of interest to understand how these spatial interpolation methods compare with generalized least squares (GLS) regression, one of the most common approaches to estimate flood quantiles at ungauged locations. By means of a leave-one-out cross-validation procedure, the performance of CK and TK was compared to GLS regression equations developed for the prediction of 10, 50, 100 and 500 yr floods for 61 streamgauges in the southeast United States. TK substantially outperforms GLS and CK for the study area, particularly for large catchments. The performance of TK over GLS highlights an important distinction between the treatments of spatial correlation when using regression-based or spatial interpolation methods to estimate flood quantiles at ungauged locations. The analysis also shows that coupling TK with CK slightly improves the performance of TK; however, the improvement is marginal when compared to the improvement in performance over GLS.

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

USGS Publications Warehouse

Dash, R.G.; Edelmann, P.R.

1997-01-01

Traveltime and gains and losses within a stream are important basic characteristics of streamflow. The lower Purgatoire River flows more than 160 river miles from Trinidad to the Arkansas River near Las Animas. A better knowledge of streamflow traveltime and streamflow gains and losses along the lower Purgatoire River would enable more informed management decisions about the availability of water supplies for irrigation use in southeastern Colorado. In 1994-95, the U.S.\\x11Geological Survey, in cooperation with the Purgatoire River Water Conservancy District and the Arkansas River Compact Administration, evaluated streamflow traveltime and estimated streamflow gains and losses using historical surface-water records. Traveltime analyses were used along the lower Purgatoire River to determine when streamflows would arrive at selected downstream sites. The substantial effects of diversions for irrigation and unmeasured return flows in the most upstream reach of the river prevented the tracking of streamflow through reach\\x111. Therefore, the estimation of streamflow traveltime for the 60.6 miles of river downstream from Trinidad could not be made.Hourly streamflow data from 1990 through 1994 were used to estimate traveltimes of more than 30 streamflow events for about 100 miles of the lower Purgatoire River. In the middle reach of the river, the traveltime of streamflow for the 40.1\\x11miles ranged from about 11 to about 47\\x11hours, and in the lower reach of the river, traveltime for the 58.5 miles ranged from about 6 to about 61 hours.Traveltime in the river reaches generally increased as streamflow decreased, but also varied for a specific streamflow in both reaches. Streamflow gains and losses were estimated using daily streamflow data at the upstream and downstream sites, available tributary inflow data, and daily diversion data. Differences between surface-water inflows and surface-water outflows in a reach determined the quantity of water gained or lost. In the most upstream reach of the river near Trinidad, difficulties in establishing streamflow traveltimes prevented the estimation of streamflow gains or losses. From 1984 through 1992, more than 2,900 daily estimates of streamflow gains or losses were made for the last 100\\x11miles of the lower Purgatoire River that indicated daily gains and losses in streamflow were common during all four seasons of the year. Although some large daily streamflow gains and losses were computed, most daily estimates indicated small gains and losses in streamflow. The daily median streamflow gain or loss for the middle reach of the river was close to zero during every season, whereas median values for the lower most reach of the river indicated a daily gain in streamflow during every season.

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

USGS Publications Warehouse

Williamson, Tanja N.; Odom, Kenneth R.; Newson, Jeremy K.; Downs, Aimee C.; Nelson, Hugh L.; Cinotto, Peter J.; Ayers, Mark A.

2009-01-01

The Water Availability Tool for Environmental Resources (WATER) was developed in cooperation with the Kentucky Division of Water to provide a consistent and defensible method of estimating streamflow and water availability in ungaged basins. WATER is process oriented; it is based on the TOPMODEL code and incorporates historical water-use data together with physiographic data that quantitatively describe topography and soil-water storage. The result is a user-friendly decision tool that can estimate water availability in non-karst areas of Kentucky without additional data or processing. The model runs on a daily time step, and critical source data include a historical record of daily temperature and precipitation, digital elevation models (DEMs), the Soil Survey Geographic Database (SSURGO), and historical records of water discharges and withdrawals. The model was calibrated and statistically evaluated for 12 basins by comparing the estimated discharge to that observed at U.S. Geological Survey streamflow-gaging stations. When statistically evaluated over a 2,119-day time period, the discharge estimates showed a bias of -0.29 to 0.42, a root mean square error of 1.66 to 5.06, a correlation of 0.54 to 0.85, and a Nash-Sutcliffe Efficiency of 0.26 to 0.72. The parameter and input modifications that most significantly improved the accuracy and precision of streamflow-discharge estimates were the addition of Next Generation radar (NEXRAD) precipitation data, a rooting depth of 30 centimeters, and a TOPMODEL scaling parameter (m) derived directly from SSURGO data that was multiplied by an adjustment factor of 0.10. No site-specific optimization was used.

Environmental flow allocation and statistics calculator

USGS Publications Warehouse

Konrad, Christopher P.

2011-01-01

The Environmental Flow Allocation and Statistics Calculator (EFASC) is a computer program that calculates hydrologic statistics based on a time series of daily streamflow values. EFASC will calculate statistics for daily streamflow in an input file or will generate synthetic daily flow series from an input file based on rules for allocating and protecting streamflow and then calculate statistics for the synthetic time series. The program reads dates and daily streamflow values from input files. The program writes statistics out to a series of worksheets and text files. Multiple sites can be processed in series as one run. EFASC is written in MicrosoftRegistered Visual BasicCopyright for Applications and implemented as a macro in MicrosoftOffice Excel 2007Registered. EFASC is intended as a research tool for users familiar with computer programming. The code for EFASC is provided so that it can be modified for specific applications. All users should review how output statistics are calculated and recognize that the algorithms may not comply with conventions used to calculate streamflow statistics published by the U.S. Geological Survey.

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.

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

USGS Publications Warehouse

Christiansen, Daniel E.; Haj, Adel E.; Risley, John C.

2017-10-24

The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for 12 river basins in western Iowa that drain into the Missouri River. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration periods for each basin varied depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations.A geographic information system tool was used to delineate each basin and estimate initial values for model parameters based on basin physical and geographical features. A U.S. Geological Survey automatic calibration tool that uses a shuffled complex evolution algorithm was used for initial calibration, and then manual modifications were made to parameter values to complete the calibration of each basin model. The main objective of the calibration was to match daily discharge values of simulated streamflow to measured daily discharge values. The Precipitation-Runoff Modeling System model was calibrated at 42 sites located in the 12 river basins in western Iowa.The accuracy of the simulated daily streamflow values at the 42 calibration sites varied by river and by site. The models were satisfactory at 36 of the sites based on statistical results. Unsatisfactory performance at the six other sites can be attributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) limited availability and accuracy of meteorological input data. The Precipitation-Runoff Modeling System models of 12 river basins in western Iowa will provide water-resource managers with a consistent and documented method for estimating streamflow at ungaged sites and aid in environmental studies, hydraulic design, water management, and water-quality projects.

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)

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.

Web services in the U.S. geological survey streamstats web application

USGS Publications Warehouse

Guthrie, J.D.; Dartiguenave, C.; Ries, Kernell G.

2009-01-01

StreamStats is a U.S. Geological Survey Web-based GIS application developed as a tool for waterresources planning and management, engineering design, and other applications. StreamStats' primary functionality allows users to obtain drainage-basin boundaries, basin characteristics, and streamflow statistics for gaged and ungaged sites. Recently, Web services have been developed that provide the capability to remote users and applications to access comprehensive GIS tools that are available in StreamStats, including delineating drainage-basin boundaries, computing basin characteristics, estimating streamflow statistics for user-selected locations, and determining point features that coincide with a National Hydrography Dataset (NHD) reach address. For the state of Kentucky, a web service also has been developed that provides users the ability to estimate daily time series of drainage-basin average values of daily precipitation and temperature. The use of web services allows the user to take full advantage of the datasets and processes behind the Stream Stats application without having to develop and maintain them. ?? 2009 IEEE.

21st Century Projections of High Streamflow Events in the UK and Germany

NASA Astrophysics Data System (ADS)

Cioffi, Francesco; Rosario Conticello, Federico; Lall, Upmanu; Merz, Bruno

2017-04-01

Radiative effects of anthropogenic changes in atmospheric composition are expected to enhance the hydrological cycle leading to more frequent and intense floods. To explore if there will be an increased risk of river flooding in the future, 21st century projections under global warming scenarios of High Streamflow Events (HSEs) for UK and German rivers are carried out, using a model that statistically relates large-scale atmospheric predictors - 850 hPa Geopotential Height (GPH850) and Integrated Water Vapor Transport (IVT) - to the occurrence of HSEs in one or simultaneously in several streamflow gauges. Here, HSE is defined as the streamflow exceeding the 99th percentile of daily flowrate time series measured at streamflow gauges. For the common period 1960-2012, historical data from 57 streamflow gauges in UK and 61 streamflow gauges in Germany, as well as, reanalysis data of GPH850 and IVT fields, bounded from 90W to 70E and from 20N to 80N are used. The link between GPH850 configurations and HSEs, and more precisely, identification of the GPH850 states potentially able to generate HSEs, is performed by a combined Kohonen Networks (Self Organized Map, SOM) and Event Syncronization approach. Complex network and modularity methods are used to cluster streamflow gauges that share common GPH850 configurations. Then a model based on a conditional Poisson distribution, in which the parameter of the Poisson distribution is assumed to be a nonlinear function of GPH850 and IVT, allows for the identification of GPH850 state and threshold of IVT beyond which there is the HSE highest probability. Using that model, projections of 21st century changes in frequency of HSEs occurrence in UK and Germany are estimated using the simulated fields of GPH850 and IVT from selected GCMs belonging to the Coupled Model Inter-comparison Project Phase 5 (CMIP5). Among the different GCMs, those are selected whose retrospective predictor fields have consistent statistics with the corresponding reanalysis data.

Five Centuries of Tree Ring Reconstructed Streamflow and Projections for Future Water Risk over the Upper Indus Watershed

NASA Astrophysics Data System (ADS)

Rao, M. P.; Cook, E. R.; Cook, B.; Palmer, J. G.; Uriarte, M.; Devineni, N.; Lall, U.; D'Arrigo, R.; Woodhouse, C. A.; Ahmed, M.

2017-12-01

We present tree-ring reconstructions of streamflow at seven gauges in the Upper Indus River watershed over the past five centuries (1452-2008 C.E.) using Hierarchical Bayesian Regression (HBR) with partial pooling of information across gauges. Using HBR with partial pooling we can develop reconstructions for short gauge records with interspersed missing data. This overcomes a common limitation faced when using conventional tree-ring reconstruction methods such as point-by-point regression (PPR) in remote regions in developing countries. Six of these streamflow gauge reconstructions are produced for the first time while a reconstruction at one streamflow gauge has been previously produced using PPR. These new reconstructions are used to characterize long-term flow variability and drought risk in the region. For the one gauge where a prior reconstruction exists, the reconstruction of streamflow by HBR and the more traditional PPR are nearly identical and yield comparable uncertainty estimates and reconstruction skill statistics. These results highlight that tree-ring reconstructions of streamflow are not dependent on the choice of statistical method. We find that streamflow in the region peaks between May-September, and is primarily driven by a combination of winter (January-March) precipitation and summer (May-September) temperature, with summer temperature likely guiding the rate of snow and glacial melt. Our reconstructions indicate that current flow since the 1980s are higher than mean flow for the past five centuries at five out of seven gauges in the watershed. The increased flow is likely driven by enhanced rates of snow and glacial melt and regional wetting over recent decades. These results suggest that while in the near-term streamflow is expected to increase, future water risk in the region will be dependent on changes in snowfall and glacial mass balance due to projected warming.

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.

Use of streamflow data to estimate base flowground-water recharge for Wisconsin

USGS Publications Warehouse

Gebert, W.A.; Radloff, M.J.; Considine, E.J.; Kennedy, J.L.

2007-01-01

The average annual base flow/recharge was determined for streamflow-gaging stations throughout Wisconsin by base-flow separation. A map of the State was prepared that shows the average annual base flow for the period 1970-99 for watersheds at 118 gaging stations. Trend analysis was performed on 22 of the 118 streamflow-gaging stations that had long-term records, unregulated flow, and provided aerial coverage of the State. The analysis found that a statistically significant increasing trend was occurring for watersheds where the primary land use was agriculture. Most gaging stations where the land cover was forest had no significant trend. A method to estimate the average annual base flow at ungaged sites was developed by multiple-regression analysis using basin characteristics. The equation with the lowest standard error of estimate, 9.5%, has drainage area, soil infiltration and base flow factor as independent variables. To determine the average annual base flow for smaller watersheds, estimates were made at low-flow partial-record stations in 3 of the 12 major river basins in Wisconsin. Regression equations were developed for each of the three major river basins using basin characteristics. Drainage area, soil infiltration, basin storage and base-flow factor were the independent variables in the regression equations with the lowest standard error of estimate. The standard error of estimate ranged from 17% to 52% for the three river basins. ?? 2007 American Water Resources Association.

Evaluating the applicability of four recent satellite–gauge combined precipitation estimates for extreme precipitation and streamflow predictions over the upper Yellow river basin in China

USDA-ARS?s Scientific Manuscript database

This study aimed to statistically and hydrologically assess the performance of four latest and widely used satellite–gauge combined precipitation estimates (SGPEs), namely CRT, BLD, 3B42CDR, and 3B42 for the extreme precipitation and stream'ow scenarios over the upper Yellow river basin (UYRB) in ch...

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 daily to monthly. However, maximum flows in most cases were poorly characterized, even at daily subsample intervals. In general, runoff volumes were accurately estimated from daily, three day, weekly, and even in some cases, monthly observations.

Trends in precipitation, streamflow, reservoir pool elevations, and reservoir releases in Arkansas and selected sites in Louisiana, Missouri, and Oklahoma, 1951–2011

USGS Publications Warehouse

Wagner, Daniel M.; Krieger, Joshua D.; Merriman, Katherine R.

2014-01-01

The U.S. Geological Survey (USGS) and the U.S. Army Corps of Engineers (USACE) conducted a statistical analysis of trends in precipitation, streamflow, reservoir pool elevations, and reservoir releases in Arkansas and selected sites in Louisiana, Missouri, and Oklahoma for the period 1951–2011. The Mann-Kendall test was used to test for trends in annual and seasonal precipitation, annual and seasonal streamflows of 42 continuous-record USGS streamflow-gaging stations, annual pool elevations and releases from 16 USACE reservoirs, and annual releases from 11 dams on the Arkansas River. A statistically significant (p≤0.10) upward trend was observed in annual precipitation for the State, with a Sen slope of approximately 0.10 inch per year. Autumn and winter were the only seasons that had statistically significant trends in precipitation. Five of six physiographic sections and six of seven 4-digit hydrologic unit code (HUC) regions in Arkansas had statistically significant upward trends in autumn precipitation, with Sen slopes of approximately 0.06 to 0.10 inch per year. Sixteen sites had statistically significant upward trends in the annual mean daily streamflow and were located on streams that drained regions with statistically significant upward trends in annual precipitation. Expected annual rates of change corresponding to statistically significant trends in annual mean daily streamflows, which ranged from 0.32 to 0.88 percent, were greater than those corresponding to regions with statistically significant upward trends in annual precipitation, which ranged from 0.19 to 0.28 percent, suggesting that the observed trends in regional annual precipitation do not fully account for the observed trends in annual mean daily streamflows. Trends in annual maximum daily streamflows were similar to trends in the annual mean daily streamflows but were only statistically significant at seven sites. There were more statistically significant trends (28 of 42 sites) in the annual minimum daily streamflows than in the annual means or maximums. Statistically significant trends in the annual minimum daily streamflows were upward at 18 sites and downward at 10 sites. Despite autumn being the only season that had statistically significant upward trends in seasonal precipitation, statistically significant upward trends in seasonal mean streamflows occurred in every season but spring. Trends in the annual mean, maximum, and minimum daily pool elevations of USACE reservoirs were consistent between metrics for reservoirs in the White, Arkansas, and Ouachita River watersheds, while trends varied between metrics at DeQueen Lake, Millwood Lake, and Lake Chicot. Most of the statistically significant trends in pool elevation metrics were upward and gradual—Sen slopes were less than 0.37 foot per year—and were likely the result of changes in reservoir regulation plans. Trends in the annual mean and maximum daily releases from USACE reservoirs were generally upward in all HUC regions. There were few statistically significant trends in the annual mean daily releases because the reservoirs are operated to maintain a regulation stage at a downstream site according to guidelines set forth in the regulation plans of the reservoirs. The annual number of low-flow days was both increasing and decreasing for reservoirs in northern Arkansas and southern Missouri and generally increasing for reservoirs in southern Arkansas.

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.

Marginal economic value of streamflow: A case study for the Colorado River Basin

Treesearch

Thomas C. Brown; Benjamin L. Harding; Elizabeth A. Payton

1990-01-01

The marginal economic value of streamflow leaving forested areas in the Colorado River Basin was estimated by determining the impact on water use of a small change in streamflow and then applying economic value estimates to the water use changes. The effect on water use of a change in streamflow was estimated with a network flow model that simulated salinity levels and...

Estimation of selected flow and water-quality characteristics of Alaskan streams

USGS Publications Warehouse

Parks, Bruce; Madison, R.J.

1985-01-01

Although hydrologic data are either sparse or nonexistent for large areas of Alaska, the drainage area, area of lakes, glacier and forest cover, and average precipitation in a hydrologic basin of interest can be measured or estimated from existing maps. Application of multiple linear regression techniques indicates that statistically significant correlations exist between properties of basins determined from maps and measured streamflow characteristics. This suggests that corresponding characteristics of ungaged basins can be estimated. Streamflow frequency characteristics can be estimated from regional equations developed for southeast, south-central and Yukon regions. Statewide or modified regional equations must be used, however, for the southwest, northwest, and Arctic Slope regions where there is a paucity of data. Equations developed from basin characteristics are given to estimate suspended-sediment values for glacial streams and, with less reliability, for nonglacial streams. Equations developed from available specific conductance data are given to estimate concentrations of major dissolved inorganic constituents. Suggestions are made for expanding the existing data base and thus improving the ability to estimate hydrologic characteristics for Alaskan streams. (USGS)

Improving Streamflow Simulation in Gaged and Ungaged Areas Using a Multi-Model Synthesis Combined with Remotely-Sensed Data and Estimates of Uncertainty

NASA Astrophysics Data System (ADS)

Lafontaine, J.; Hay, L.

2015-12-01

The United States Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the conterminous United States (CONUS). More than 1,700 gaged watersheds across the CONUS were modeled to test the feasibility of improving streamflow simulations in gaged and ungaged watersheds by linking statistically- and physically-based hydrologic models with remotely-sensed data products (i.e. - snow water equivalent) and estimates of uncertainty. Initially, the physically-based models were calibrated to measured streamflow data to provide a baseline for comparison. As many stream reaches in the CONUS are either not gaged, or are substantially impacted by water use or flow regulation, ancillary information must be used to determine reasonable parameter estimations for streamflow simulations. In addition, not all ancillary datasets are appropriate for application to all parts of the CONUS (e.g. - snow water equivalent in the southeastern U.S., where snow is a rarity). As it is not expected that any one data product or model simulation will be sufficient for representing hydrologic behavior across the entire CONUS, a systematic evaluation of which data products improve simulations of streamflow for various regions across the CONUS was performed. The resulting portfolio of calibration strategies can be used to guide selection of an appropriate combination of simulated and measured information for model development and calibration at a given location of interest. In addition, these calibration strategies have been developed to be flexible so that new data products or simulated information can be assimilated. This analysis provides a foundation to understand how well models work when streamflow data is either not available or is limited and could be used to further inform hydrologic model parameter development for ungaged areas.

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

USGS Publications Warehouse

Lizarraga, Joy S.; Wehmeyer, Loren L.

2012-01-01

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

Marginal Economic Value of Streamflow: A Case Study for the Colorado River Basin

NASA Astrophysics Data System (ADS)

Brown, Thomas C.; Harding, Benjamin L.; Payton, Elizabeth A.

1990-12-01

The marginal economic value of streamflow leaving forested areas in the Colorado River Basin was estimated by determining the impact on water use of a small change in streamflow and then applying economic value estimates to the water use changes. The effect on water use of a change in streamflow was estimated with a network flow model that simulated salinity levels and the routing of flow to consumptive uses and hydroelectric dams throughout the Basin. The results show that, under current water management institutions, the marginal value of streamflow in the Colorado River Basin is largely determined by nonconsumptive water uses, principally energy production, rather than by consumptive agricultural or municipal uses. The analysis demonstrates the importance of a systems framework in estimating the marginal value of streamflow.

Estimated flow-duration curves for selected ungaged sites in Kansas

USGS Publications Warehouse

Studley, S.E.

2001-01-01

Flow-duration curves for 1968-98 were estimated for 32 ungaged sites in the Missouri, Smoky Hill-Saline, Solomon, Marais des Cygnes, Walnut, Verdigris, and Neosho River Basins in Kansas. Also included from a previous report are estimated flow-duration curves for 16 ungaged sites in the Cimarron and lower Arkansas River Basins in Kansas. The method of estimation used six unique factors of flow duration: (1) mean streamflow and percentage duration of mean streamflow, (2) ratio of 1-percent-duration streamflow to mean streamflow, (3) ratio of 0.1-percent-duration streamflow to 1-percent-duration streamflow, (4) ratio of 50-percent-duration streamflow to mean streamflow, (5) percentage duration of appreciable streamflow (0.10 cubic foot per second), and (6) average slope of the flow-duration curve. These factors were previously developed from a regionalized study of flow-duration curves using streamflow data for 1921-76 from streamflow-gaging stations with drainage areas of 100 to 3,000 square miles. The method was tested on a currently (2001) measured, continuous-record streamflow-gaging station on Salt Creek near Lyndon, Kansas, with a drainage area of 111 square miles and was found to adequately estimate the computed flow-duration curve for the station. The method also was tested on a currently (2001) measured, continuous-record, streamflow-gaging station on Soldier Creek near Circleville, Kansas, with a drainage area of 49.3 square miles. The results of the test on Soldier Creek near Circleville indicated that the method could adequately estimate flow-duration curves for sites with drainage areas of less than 100 square miles. The low-flow parts of the estimated flow-duration curves were verified or revised using 137 base-flow discharge measurements made during 1999-2000 at the 32 ungaged sites that were correlated with base-flow measurements and flow-duration analyses performed at nearby, long-term, continuous-record, streamflow-gaging stations (index stations). The method did not adequately estimate the flow-duration curves for two sites in the western one-third of the State because of substantial changes in farming practices (terracing and intensive ground-water withdrawal) that were not accounted for in the two previous studies (Furness, 1959; Jordan, 1983). For these two sites, there was enough historic, continuous-streamflow record available to perform record-extension techniques correlated to their respective index stations for the development of the estimated flow-duration curves. The estimated flow-duration curves at the ungaged sites can be used for projecting future flow frequencies for assessment of total maximum daily loads (TMDLs) or other water-quality constituents, water-availability studies, and for basin-characteristic studies.

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.

Techniques for estimating monthly mean streamflow at gaged sites and monthly streamflow duration characteristics at ungaged sites in central Nevada

USGS Publications Warehouse

Hess, G.W.; Bohman, L.R.

1996-01-01

Techniques for estimating monthly mean streamflow at gaged sites and monthly streamflow duration characteristics at ungaged sites in central Nevada were developed using streamflow records at six gaged sites and basin physical and climatic characteristics. Streamflow data at gaged sites were related by regression techniques to concurrent flows at nearby gaging stations so that monthly mean streamflows for periods of missing or no record can be estimated for gaged sites in central Nevada. The standard error of estimate for relations at these sites ranged from 12 to 196 percent. Also, monthly streamflow data for selected percent exceedence levels were used in regression analyses with basin and climatic variables to determine relations for ungaged basins for annual and monthly percent exceedence levels. Analyses indicate that the drainage area and percent of drainage area at altitudes greater than 10,000 feet are the most significant variables. For the annual percent exceedence, the standard error of estimate of the relations for ungaged sites ranged from 51 to 96 percent and standard error of prediction for ungaged sites ranged from 96 to 249 percent. For the monthly percent exceedence values, the standard error of estimate of the relations ranged from 31 to 168 percent, and the standard error of prediction ranged from 115 to 3,124 percent. Reliability and limitations of the estimating methods are described.

Alternative standardization approaches to improving streamflow reconstructions with ring-width indices of riparian trees

USGS Publications Warehouse

Meko, David M.; Friedman, Jonathan M.; Touchan, Ramzi; Edmondson, Jesse R.; Griffin, Eleanor R.; Scott, Julian A.

2015-01-01

Old, multi-aged populations of riparian trees provide an opportunity to improve reconstructions of streamflow. Here, ring widths of 394 plains cottonwood (Populus deltoids, ssp. monilifera) trees in the North Unit of Theodore Roosevelt National Park, North Dakota, are used to reconstruct streamflow along the Little Missouri River (LMR), North Dakota, US. Different versions of the cottonwood chronology are developed by (1) age-curve standardization (ACS), using age-stratified samples and a single estimated curve of ring width against estimated ring age, and (2) time-curve standardization (TCS), using a subset of longer ring-width series individually detrended with cubic smoothing splines of width against year. The cottonwood chronologies are combined with the first principal component of four upland conifer chronologies developed by conventional methods to investigate the possible value of riparian tree-ring chronologies for streamflow reconstruction of the LMR. Regression modeling indicates that the statistical signal for flow is stronger in the riparian cottonwood than in the upland chronologies. The flow signal from cottonwood complements rather than repeats the signal from upland conifers and is especially strong in young trees (e.g. 5–35 years). Reconstructions using a combination of cottonwoods and upland conifers are found to explain more than 50% of the variance of LMR flow over a 1935–1990 calibration period and to yield reconstruction of flow to 1658. The low-frequency component of reconstructed flow is sensitive to the choice of standardization method for the cottonwood. In contrast to the TCS version, the ACS reconstruction features persistent low flows in the 19th century. Results demonstrate the value to streamflow reconstruction of riparian cottonwood and suggest that more studies are needed to exploit the low-frequency streamflow signal in densely sampled age-stratified stands of riparian trees.

Site-specific estimation of peak-streamflow frequency using generalized least-squares regression for natural basins in Texas

USGS Publications Warehouse

Asquith, William H.; Slade, R.M.

1999-01-01

The U.S. Geological Survey, in cooperation with the Texas Department of Transportation, has developed a computer program to estimate peak-streamflow frequency for ungaged sites in natural basins in Texas. Peak-streamflow frequency refers to the peak streamflows for recurrence intervals of 2, 5, 10, 25, 50, and 100 years. Peak-streamflow frequency estimates are needed by planners, managers, and design engineers for flood-plain management; for objective assessment of flood risk; for cost-effective design of roads and bridges; and also for the desin of culverts, dams, levees, and other flood-control structures. The program estimates peak-streamflow frequency using a site-specific approach and a multivariate generalized least-squares linear regression. A site-specific approach differs from a traditional regional regression approach by developing unique equations to estimate peak-streamflow frequency specifically for the ungaged site. The stations included in the regression are selected using an informal cluster analysis that compares the basin characteristics of the ungaged site to the basin characteristics of all the stations in the data base. The program provides several choices for selecting the stations. Selecting the stations using cluster analysis ensures that the stations included in the regression will have the most pertinent information about flooding characteristics of the ungaged site and therefore provide the basis for potentially improved peak-streamflow frequency estimation. An evaluation of the site-specific approach in estimating peak-streamflow frequency for gaged sites indicates that the site-specific approach is at least as accurate as a traditional regional regression approach.

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.

Methods for estimating selected low-flow frequency statistics for unregulated streams in Kentucky

USGS Publications Warehouse

Martin, Gary R.; Arihood, Leslie D.

2010-01-01

This report provides estimates of, and presents methods for estimating, selected low-flow frequency statistics for unregulated streams in Kentucky including the 30-day mean low flows for recurrence intervals of 2 and 5 years (30Q2 and 30Q5) and the 7-day mean low flows for recurrence intervals of 5, 10, and 20 years (7Q2, 7Q10, and 7Q20). Estimates of these statistics are provided for 121 U.S. Geological Survey streamflow-gaging stations with data through the 2006 climate year, which is the 12-month period ending March 31 of each year. Data were screened to identify the periods of homogeneous, unregulated flows for use in the analyses. Logistic-regression equations are presented for estimating the annual probability of the selected low-flow frequency statistics being equal to zero. Weighted-least-squares regression equations were developed for estimating the magnitude of the nonzero 30Q2, 30Q5, 7Q2, 7Q10, and 7Q20 low flows. Three low-flow regions were defined for estimating the 7-day low-flow frequency statistics. The explicit explanatory variables in the regression equations include total drainage area and the mapped streamflow-variability index measured from a revised statewide coverage of this characteristic. The percentage of the station low-flow statistics correctly classified as zero or nonzero by use of the logistic-regression equations ranged from 87.5 to 93.8 percent. The average standard errors of prediction of the weighted-least-squares regression equations ranged from 108 to 226 percent. The 30Q2 regression equations have the smallest standard errors of prediction, and the 7Q20 regression equations have the largest standard errors of prediction. The regression equations are applicable only to stream sites with low flows unaffected by regulation from reservoirs and local diversions of flow and to drainage basins in specified ranges of basin characteristics. Caution is advised when applying the equations for basins with characteristics near the applicable limits and for basins with karst drainage features.

Statistical summary of selected physical, chemical, and microbial characteristics, and estimates of constituent loads in urban stormwater, Maricopa County, Arizona

USGS Publications Warehouse

Lopes, T.J.; Fossum, K.D.; Phillips, J.V.; Monical, J.E.

1995-01-01

Stormwater and streamflow in the Phoenix, Arizona, area were monitored to determine the physical, chemical, and microbial characteristics of storm- water from areas having different land uses; to describe the characteristics of streamflow in a river that receives urban stormwater; and to estimate constituent loads in stormwater from unmonitored areas in Maricopa County, Arizona. Land use affects urban stormwater chemistry mostly because the percentage of impervious area controls the suspended-solids concentrations and varies with the type of land use. Urban activities also seem to concentrate cadmium, lead, and zinc in sediments. Urban stormwater had larger concentrations of chemical oxygen demand and biological oxygen demand, oil and grease, and higher counts of fecal bacteria than streamflow and could degrade the quality of the Salt River. Most regression equations for estimating constituent loads require three explanatory variables (total rainfall, drainage area, and per- centage of impervious area) and had standard errors that were from 65 to 266 percent. Localized areas that appear to contribute a large proportion of the constituent loads typically have 40 percent or more impervious area and are associated with industrial, commercial, and high-density residential land uses. The use of the mean value of the event-mean constituent concentrations measured in stormwater may be the best way of estimating constituent concentrations.

Base-flow characteristics of streams in the Valley and Ridge, Blue Ridge, and Piedmont physiographic provinces of Virginia

USGS Publications Warehouse

Nelms, D.L.; Harlow, G.E.; Hayes, Donald C.

1995-01-01

Growth within the Valley and Ridge, Blue Ridge, and Piedmont Physiographic Provinces of Virginia has focussed concern about allocation of surface-water flow and increased demands on the ground-water resources. The purpose of this report is to (1) describe the base-flow characteristics of streams, (2) identify regional differences in these flow characteristics, and (3) describe, if possible, the potential surface-water and ground-water yields of basins on the basis of the base-flow character- istics. Base-flow characteristics are presented for streams in the Valley and Ridge, Blue Ridge, and Piedmont Physiographic Provinces of Virginia. The provinces are separated into five regions: (1) Valley and Ridge, (2) Blue Ridge, (3) Piedmont/Blue Ridge transition, (4) Piedmont northern, and (5) Piedmont southern. Different flow statistics, which represent streamflows predominantly comprised of base flow, were determined for 217 continuous-record streamflow-gaging stations from historical mean daily discharge and for 192 partial-record streamflow-gaging stations by means of correlation of discharge measurements. Variability of base flow is represented by a duration ratio developed during this investigation. Effective recharge rates were also calculated. Median values for the different flow statistics range from 0.05 cubic foot per second per square mile for the 90-percent discharge on the streamflow-duration curve to 0.61 cubic foot per second per square mile for mean base flow. An excellent estimator of mean base flow for the Piedmont/Blue Ridge transition region and Piedmont southern region is the 50-percent discharge on the streamflow-duration curve, but tends to under- estimate mean base flow for the remaining regions. The base-flow variability index ranges from 0.07 to 2.27, with a median value of 0.55. Effective recharge rates range from 0.07 to 33.07 inches per year, with a median value of 8.32 inches per year. Differences in the base-flow characteristics exist between regions. The median discharges for the Valley and Ridge, Blue Ridge, and Piedmont/Blue Ridge transition regions are higher than those for the Piedmont regions. Results from statistical analysis indicate that the regions can be ranked in terms of base-flow characteristics from highest to lowest as follows: (1) Piedmont/Blue Ridge transition, (2) Valley and Ridge and Blue Ridge, (3) Piedmont southern, and (4) Piedmont northern. The flow statistics are consistently higher and the values for base-flow variability are lower for basins within the Piedmont/Blue Ridge transition region relative to those from the other regions, whereas the basins within the Piedmont northern region show the opposite pattern. The group rankings of the base-flow characteristics were used to designate the potential surface-water yield for the regions. In addition, an approach developed for this investigation assigns a rank for potential surface- water yield to a basin according to the quartiles in which the values for the base-flow character- istics are located. Both procedures indicate that the Valley and Ridge, Blue Ridge, and Piedmont/Blue Ridge transition regions have moderate-to-high potential surface-water yield and the Piedmont regions have low-to-moderate potential surface- water yield. In order to indicate potential ground-water yield from base-flow characteristics, aquifer properties for 51 streamflow-gaging stations with continuous record of streamflow data were determined by methods that use streamflow records and basin characteristics. Areal diffusivity ranges from 17,100 to 88,400 feet squared per day, with a median value of 38,400 feet squared per day. Areal transmissivity ranges from 63 to 830 feet squared per day, with a median value of 270 feet squared per day. Storage coefficients, which were estimated by dividing areal transmissivity by areal diffusivity, range from approximately 0.001 to 0.019 (dimensionless), with a median value of 0.007. The median value for areal diffus

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

USGS Publications Warehouse

Ockerman, Darwin J.

2005-01-01

The U.S. Geological Survey, in cooperation with the San Antonio Water System, constructed three watershed models using the Hydrological Simulation Program—FORTRAN (HSPF) to simulate streamflow and estimate recharge to the Edwards aquifer in the Hondo Creek, Verde Creek, and San Geronimo Creek watersheds in south-central Texas. The three models were calibrated and tested with available data collected during 1992–2003. Simulations of streamflow and recharge were done for 1951–2003. The approach to construct the models was to first calibrate the Hondo Creek model (with an hourly time step) using 1992–99 data and test the model using 2000–2003 data. The Hondo Creek model parameters then were applied to the Verde Creek and San Geronimo Creek watersheds to construct the Verde Creek and San Geronimo Creek models. The simulated streamflows for Hondo Creek are considered acceptable. Annual, monthly, and daily simulated streamflows adequately match measured values, but simulated hourly streamflows do not. The accuracy of streamflow simulations for Verde Creek is uncertain. For San Geronimo Creek, the match of measured and simulated annual and monthly streamflows is acceptable (or nearly so); but for daily and hourly streamflows, the calibration is relatively poor. Simulated average annual total streamflow for 1951–2003 to Hondo Creek, Verde Creek, and San Geronimo Creek is 45,400; 32,400; and 11,100 acre-feet, respectively. Simulated average annual streamflow at the respective watershed outlets is 13,000; 16,200; and 6,920 acre-feet. The difference between total streamflow and streamflow at the watershed outlet is streamflow lost to channel infiltration. Estimated average annual Edwards aquifer recharge for Hondo Creek, Verde Creek, and San Geronimo Creek watersheds for 1951–2003 is 37,900 acrefeet (5.04 inches), 26,000 acre-feet (3.36 inches), and 5,940 acre-feet (1.97 inches), respectively. Most of the recharge (about 77 percent for the three watersheds together) occurs as streamflow channel infiltration. Diffuse recharge (direct infiltration of rainfall to the aquifer) accounts for the remaining 23 percent of recharge. For the Hondo Creek watershed, the HSPF recharge estimates for 1992–2003 averaged about 22 percent less than those estimated by the Puente method, a method the U.S. Geological Survey has used to compute annual recharge to the Edwards aquifer since 1978. HSPF recharge estimates for the Verde Creek watershed average about 40 percent less than those estimated by the Puente method.

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.

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.

Statistical Approaches for Spatiotemporal Prediction of Low Flows

NASA Astrophysics Data System (ADS)

Fangmann, A.; Haberlandt, U.

2017-12-01

An adequate assessment of regional climate change impacts on streamflow requires the integration of various sources of information and modeling approaches. This study proposes simple statistical tools for inclusion into model ensembles, which are fast and straightforward in their application, yet able to yield accurate streamflow predictions in time and space. Target variables for all approaches are annual low flow indices derived from a data set of 51 records of average daily discharge for northwestern Germany. The models require input of climatic data in the form of meteorological drought indices, derived from observed daily climatic variables, averaged over the streamflow gauges' catchments areas. Four different modeling approaches are analyzed. Basis for all pose multiple linear regression models that estimate low flows as a function of a set of meteorological indices and/or physiographic and climatic catchment descriptors. For the first method, individual regression models are fitted at each station, predicting annual low flow values from a set of annual meteorological indices, which are subsequently regionalized using a set of catchment characteristics. The second method combines temporal and spatial prediction within a single panel data regression model, allowing estimation of annual low flow values from input of both annual meteorological indices and catchment descriptors. The third and fourth methods represent non-stationary low flow frequency analyses and require fitting of regional distribution functions. Method three is subject to a spatiotemporal prediction of an index value, method four to estimation of L-moments that adapt the regional frequency distribution to the at-site conditions. The results show that method two outperforms successive prediction in time and space. Method three also shows a high performance in the near future period, but since it relies on a stationary distribution, its application for prediction of far future changes may be problematic. Spatiotemporal prediction of L-moments appeared highly uncertain for higher-order moments resulting in unrealistic future low flow values. All in all, the results promote an inclusion of simple statistical methods in climate change impact assessment.

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.

Estimation of average annual streamflows and power potentials for Alaska and Hawaii

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

Verdin, Kristine L.

2004-05-01

This paper describes the work done to develop average annual streamflow estimates and power potential for the states of Alaska and Hawaii. The Elevation Derivatives for National Applications (EDNA) database was used, along with climatic datasets, to develop flow and power estimates for every stream reach in the EDNA database. Estimates of average annual streamflows were derived using state-specific regression equations, which were functions of average annual precipitation, precipitation intensity, drainage area, and other elevation-derived parameters. Power potential was calculated through the use of the average annual streamflow and the hydraulic head of each reach, which is calculated from themore » EDNA digital elevation model. In all, estimates of streamflow and power potential were calculated for over 170,000 stream segments in the Alaskan and Hawaiian datasets.« less

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

USGS Publications Warehouse

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

2005-01-01

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

Effects of future climate conditions on terrestrial export from coastal southern California

NASA Astrophysics Data System (ADS)

Feng, D.; Zhao, Y.; Raoufi, R.; Beighley, E.; Melack, J. M.

2015-12-01

The Santa Barbara Coastal - Long Term Ecological Research Project (SBC-LTER) is focused on investigating the relative importance of land and ocean processes in structuring giant kelp forest ecosystems. Understanding how current and future climate conditions influence terrestrial export is a central theme for the project. Here we combine the Hillslope River Routing (HRR) model and daily precipitation and temperature downscaled using statistical downscaling based on localized constructed Analogs (LOCA) to estimate recent streamflow dynamics (2000 to 2014) and future conditions (2015 to 2100). The HRR model covers the SBC-LTER watersheds from just west of the Ventura River to Point Conception; a land area of roughly 800 km2 with 179 watersheds ranging from 0.1 to 123 km2. The downscaled climate conditions have a spatial resolution of 6 km by 6 km. Here, we use the Penman-Monteith method with the Food and Agriculture Organization of the United Nations (FAO) limited climate data approximations and land surface conditions (albedo, leaf area index, land cover) measured from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites to estimate potential evapotranspiration (PET). The HRR model is calibrated for the period 2000 to 2014 using USGS and LTER streamflow. An automated calibration technique is used. For future climate scenarios, we use mean 8-day land cover conditions. Future streamflow, ET and soil moisture statistics are presented and based on downscaled P and T from ten climate model projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5).

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

NASA Astrophysics Data System (ADS)

Sauchyn, David; Ilich, Nesa

2017-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Estimation of daily stream flow of southeastern coastal plain watersheds by combining estimated magnitude and sequence

Treesearch

Herbert Ssegane; Devendra M. Amatya; E.W. Tollner; Zhaohua Dai; Jami E. Nettles

2013-01-01

Commonly used methods to predict streamflow at ungauged watersheds implicitly predict streamflow magnitude and temporal sequence concurrently. An alternative approach that has not been fully explored is the conceptualization of streamflow as a composite of two separable components of magnitude and sequence, where each component is estimated separately and then combined...

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.

Spatial interpolation schemes of daily precipitation for hydrologic modeling

USGS Publications Warehouse

Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.

2012-01-01

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

Determination of Baseline Periods of Record for Selected Streamflow-Gaging Stations in New Jersey for Determining Ecologically Relevant Hydrologic Indices (ERHI)

USGS Publications Warehouse

Esralew, Rachel A.; Baker, Ronald J.

2008-01-01

Hydrologic changes in New Jersey stream basins resulting from human activity can affect the flow and ecology of the streams. To assess future changes in streamflow resulting from human activity an understanding of the natural variability of streamflow is needed. The natural variability can be classified using Ecologically Relevant Hydrologic Indices (ERHIs). ERHIs are defined as selected streamflow statistics that characterize elements of the flow regime that substantially affect biological health and ecological sustainability. ERHIs are used to quantitatively characterize aspects of the streamflow regime, including magnitude, duration, frequency, timing, and rate of change. Changes in ERHI values can occur as a result of human activity, and changes in ERHIs over time at various stream locations can provide information about the degree of alteration in aquatic ecosystems at or near those locations. New Jersey streams can be divided into four classes (A, B, C, or D), where streams with similar ERHI values (determined from cluster analysis) are assigned the same stream class. In order to detect and quantify changes in ERHIs at selected streamflow-gaging stations, a 'baseline' period is needed. Ideally, a baseline period is a period of continuous daily streamflow record at a gaging station where human activity along the contributing stream reach or in the stream's basin is minimal. Because substantial urbanization and other development had already occurred before continuous streamflow-gaging stations were installed, it is not possible to identify baseline periods that meet this criterion for many reaches in New Jersey. Therefore, the baseline period for a considerably altered basin can be defined as a period prior to a substantial human-induced change in the drainage basin or stream reach (such as regulations or diversions), or a period during which development did not change substantially. Index stations (stations with minimal urbanization) were defined as streamflow-gaging stations in basins that contain less than 15 percent urban land use throughout the period of continuous streamflow record. A minimum baseline period of record for each stream class was determined by comparing the variability of selected ERHIs among consecutive 5-, 10-, 15-, and 20-year time increments for index stations. On the basis of this analysis, stream classes A and D were assigned a minimum of 20 years of continuous record as a baseline period and stream classes B and C, a minimum of 10 years. Baseline periods were calculated for 85 streamflow-gaging stations in New Jersey with 10 or more years of continuous daily streamflow data, and the values of 171 ERHIs also were calculated for these baseline periods for each station. Baseline periods were determined by using historical streamflow-gaging station data, estimated changes in impervious surface in the drainage basin, and statistically significant changes in annual base flow and runoff. Historical records were reviewed to identify years during which regulation, diversions, or withdrawals occurred in the drainage basins. Such years were not included in baseline periods of record. For some sites, the baseline period of record was shorter than the minimum period of record specified for the given stream class. In such cases, the baseline period was rated as 'poor'. Impervious surface was used as an indicator of urbanization and change in streamflow characteristics owing to increases in storm runoff and decreases in base flow. Percentages of impervious surface were estimated for 85 streamflow-gaging stations from available municipal population-density data by using a regression model. Where the period of record was sufficiently long, all years after the impervious surface exceeded 10 to 20 percent were excluded from the baseline period. The percentage of impervious surface also was used as a criterion in assigning qualitative ratings to baseline periods. Changes in trends of annual base fl

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

USGS Publications Warehouse

Hess, Glen W.; Stonewall, Adam J.

2014-01-01

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

Peak data for U.S. Geological Survey gaging stations, Texas network and computer program to estimate peak-streamflow frequency

USGS Publications Warehouse

Slade, R.M.; Asquith, W.H.

1996-01-01

About 23,000 annual peak streamflows and about 400 historical peak streamflows exist for about 950 stations in the surface-water data-collection network of Texas. These data are presented on a computer diskette along with the corresponding dates, gage heights, and information concerning the basin, and nature or cause for the flood. Also on the computer diskette is a U.S. Geological Survey computer program that estimates peak-streamflow frequency based on annual and historical peak streamflow. The program estimates peak streamflow for 2-, 5-, 10-, 25-, 50-, and 100-year recurrence intervals and is based on guidelines established by the Interagency Advisory Committee on Water Data. Explanations are presented for installing the program, and an example is presented with discussion of its options.

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...

Estimation of streamflow response to wildfire and salvage logging in a snow-dominated catchment using a model-based change detection approach

NASA Astrophysics Data System (ADS)

Moore, R. D.; Mahrlein, M.; Chuang, Y. C. M.

2016-12-01

Forest cover changes associated with natural disturbance and forest management can have significant influences on the magnitude and timing of streamflow. This study quantified the effect of a wildfire that burned over 60% of the catchment of Fishtrap Creek in the southern interior of British Columbia in August 2003. Fishtrap Creek has been gauged from 1970 to present. The catchment drains 158 km2 at the gauging station and has a snow-dominated hydrologic regime. In 2006, about one-third of the burned area was salvage logged. A semi-distributed hydrologic model was calibrated and tested using the pre-fire streamflow data. Simulated daily streamflow based on the "best" parameter set, and assuming pre-fire forest cover, was used as a "virtual" control in a paired-catchment analysis. Each year was divided into 73 five-day periods (pentads), and separate pre-fire regressions were fit for each of the 73 pentad time series. This approach avoids issues with autocorrelation and can address seasonally varying model bias. Statistically significant increases in streamflow were detected in late winter and through the month of April, with no evidence for increased peak flows, which is inferred to reflect a de-synchronization of snowmelt between disturbed and undisturbed areas of the catchment. The results of the model-based change detection are consistent with statistical analyses using climatic variables as covariates, but have the advantage of providing more temporal detail. However, the power of the change detection can be limited by insufficiently long records of streamflow and driving weather variables for both the pre- and post-fire periods and model structural errors (e.g., an inability to reproduce winter baseflow). An interesting side result of the study was the identification of parameter uncertainty associated with uncertainty regarding forest cover during the calibration period.

An operational GLS model for hydrologic regression

USGS Publications Warehouse

Tasker, Gary D.; Stedinger, J.R.

1989-01-01

Recent Monte Carlo studies have documented the value of generalized least squares (GLS) procedures to estimate empirical relationships between streamflow statistics and physiographic basin characteristics. This paper presents a number of extensions of the GLS method that deal with realities and complexities of regional hydrologic data sets that were not addressed in the simulation studies. These extensions include: (1) a more realistic model of the underlying model errors; (2) smoothed estimates of cross correlation of flows; (3) procedures for including historical flow data; (4) diagnostic statistics describing leverage and influence for GLS regression; and (5) the formulation of a mathematical program for evaluating future gaging activities. ?? 1989.

Long-Term Historical Rainfall-Runoff Modeling Using High-Resolution Satellite-based Precipitation Products

NASA Astrophysics Data System (ADS)

Ashouri, H.; Nguyen, P.; Thorstensen, A. R.; Hsu, K. L.; Sorooshian, S.

2014-12-01

This study evaluates the performance of a newly developed long-term high-resolution satellite-based precipitation products, named Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network - Climate Data Record (PERSIANN-CDR), in hydrological modeling. PERSIANN-CDR estimations are biased corrected using GPCP monthly climatology data. PERSIANN-CDR provides daily rainfall estimates at 0.25° x 0.25° grid boxes for 1983-2014 (delayed present). This newly released product makes it feasible to model the streamflow over the past 30 years. Three test basins from the Distributed Hydrologic Model Intercomparison Project - Phase 2 (DMIP 2) are chosen. Comparing with other satellite products, the Version 7 TRMM Multi-satellite Precipitation Analysis (TMPA) product is used. Stage IV radar data is used as a reference data for evaluating the PERSIANN-CDR and TMPA precipitation data. All products are scaled to 0.25° and daily spatiotemporal resolution. The study is performed in two phases. In the first phase, the 2003-2011 period where all the products are available is chosen. Precipitation evaluation results, presented on Taylor Diagrams, show that TMPA and PERSIANN-CDR have close performances. The National Weather Service (NWS) Office of Hydrologic Development (OHD) Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) is then forced with the PERSIANN-CDR and the TMPA precipitation products, as well as the stage IV radar data. USGS Streamflow observations at the outlet of the basins are used as the reference streamflow data. The results show that in general, in all the three DMIP 2 basins the simulated hydrographs forced with PERSIANN-CDR and TMPA show good agreement, as the statistical measures such as root mean square error, bias, and correlation coefficient are close. In addition, with respect to the streamflow peaks, PERSIANN-CDR shows better performance than Stage IV radar data in capturing the extreme streamflow magnitudes. Based on the results from the first phase of the study and given the fact that PERSIANN-CDR covers the 1983-2014, in the second phase of the study we model the streamflow for the period of 1983-2014. The results will be presented in the meeting.

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

USGS Publications Warehouse

Dudley, Robert W.; Hodgkins, Glenn A.

2005-01-01

The U.S. Geological Survey (USGS), in cooperation with the Maine Atlantic Salmon Commission (ASC), began a study in 2003 to examine the timing, magnitude, and duration of summer (June through October) and fall/early winter (September through January) seasonal streamflows of unregulated coastal river basins in Maine and to correlate them to meteorological variables and winter/spring (January through May) seasonal streamflows. This study overlapped the summer seasonal window with the fall/early winter seasonal window to completely bracket the low-streamflow period during July, August, and September between periods of high streamflows in June and October. The ASC is concerned with the impacts of potentially changing meteorological and hydrologic conditions on Atlantic salmon survival. Because winter/spring high streamflows appear to have trended toward earlier dates over the 20th century in coastal Maine, it was hypothesized that the spring/summer recession to low streamflows could have a similar trend toward earlier, and possibly lower, longer lasting, late summer/early fall low streamflows during the 20th century. There were few statistically significant trends in the timing, magnitude, or duration of summer low streamflows for coastal river basins in Maine during the 20th century. The hypothesis that earlier winter/spring high streamflows may result in earlier or lower low streamflows is not supported by the data. No statistically significant trends in the magnitude of total runoff volume during the low-streamflow months of August and September were observed. The magnitude and timing of summer low streamflows correlated with the timing of fall/winter high streamflows and the amount of summer precipitation. The magnitude and timing of summer low streamflows did not correlate with the timing of spring snowmelt runoff. There were few correlations between the magnitude and timing of summer low streamflows and monthly mean surface air temperatures. There were few statistically significant trends in the timing or duration of fall/winter high streamflows for coastal river basins in Maine during the 20th century. The timing of the bulk of fall/winter high streamflows correlated with seasonal precipitation. Earlier fall/winter center-of-volume dates correlated with higher September and October precipitation. In general, little evidence was observed of trends in the magnitude of seasonal runoff volume during fall/winter. The magnitude of fall/winter high streamflows positively correlated with November and December precipitation amounts. There were few correlations between the magnitude and timing of fall/winter high streamflows and monthly mean surface air temperatures.

Methods for estimating flow-duration curve and low-flow frequency statistics for ungaged locations on small streams in Minnesota

USGS Publications Warehouse

Ziegeweid, Jeffrey R.; Lorenz, David L.; Sanocki, Chris A.; Czuba, Christiana R.

2015-12-24

Equations developed in this study apply only to stream locations where flows are not substantially affected by regulation, diversion, or urbanization. All equations presented in this study will be incorporated into StreamStats, a web-based geographic information system tool developed by the U.S. Geological Survey. StreamStats allows users to obtain streamflow statistics, basin characteristics, and other information for user-selected locations on streams through an interactive map.

Investigation of the complexity of streamflow fluctuations in a large heterogeneous lake catchment in China

NASA Astrophysics Data System (ADS)

Ye, Xuchun; Xu, Chong-Yu; Li, Xianghu; Zhang, Qi

2018-05-01

The occurrence of flood and drought frequency is highly correlated with the temporal fluctuations of streamflow series; understanding of these fluctuations is essential for the improved modeling and statistical prediction of extreme changes in river basins. In this study, the complexity of daily streamflow fluctuations was investigated by using multifractal detrended fluctuation analysis (MF-DFA) in a large heterogeneous lake basin, the Poyang Lake basin in China, and the potential impacts of human activities were also explored. Major results indicate that the multifractality of streamflow fluctuations shows significant regional characteristics. In the study catchment, all the daily streamflow series present a strong long-range correlation with Hurst exponents bigger than 0.8. The q-order Hurst exponent h( q) of all the hydrostations can be characterized well by only two parameters: a (0.354 ≤ a ≤ 0.384) and b (0.627 ≤ b ≤ 0.677), with no pronounced differences. Singularity spectrum analysis pointed out that small fluctuations play a dominant role in all daily streamflow series. Our research also revealed that both the correlation properties and the broad probability density function (PDF) of hydrological series can be responsible for the multifractality of streamflow series that depends on watershed areas. In addition, we emphasized the relationship between watershed area and the estimated multifractal parameters, such as the Hurst exponent and fitted parameters a and b from the q-order Hurst exponent h( q). However, the relationship between the width of the singularity spectrum (Δ α) and watershed area is not clear. Further investigation revealed that increasing forest coverage and reservoir storage can effectively enhance the persistence of daily streamflow, decrease the hydrological complexity of large fluctuations, and increase the small fluctuations.

Streamflow variability and classification using false nearest neighbor method

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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.

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.

Relative effects of statistical preprocessing and postprocessing on a regional hydrological ensemble prediction system

NASA Astrophysics Data System (ADS)

Sharma, Sanjib; Siddique, Ridwan; Reed, Seann; Ahnert, Peter; Mendoza, Pablo; Mejia, Alfonso

2018-03-01

The relative roles of statistical weather preprocessing and streamflow postprocessing in hydrological ensemble forecasting at short- to medium-range forecast lead times (day 1-7) are investigated. For this purpose, a regional hydrologic ensemble prediction system (RHEPS) is developed and implemented. The RHEPS is comprised of the following components: (i) hydrometeorological observations (multisensor precipitation estimates, gridded surface temperature, and gauged streamflow); (ii) weather ensemble forecasts (precipitation and near-surface temperature) from the National Centers for Environmental Prediction 11-member Global Ensemble Forecast System Reforecast version 2 (GEFSRv2); (iii) NOAA's Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM); (iv) heteroscedastic censored logistic regression (HCLR) as the statistical preprocessor; (v) two statistical postprocessors, an autoregressive model with a single exogenous variable (ARX(1,1)) and quantile regression (QR); and (vi) a comprehensive verification strategy. To implement the RHEPS, 1 to 7 days weather forecasts from the GEFSRv2 are used to force HL-RDHM and generate raw ensemble streamflow forecasts. Forecasting experiments are conducted in four nested basins in the US Middle Atlantic region, ranging in size from 381 to 12 362 km2. Results show that the HCLR preprocessed ensemble precipitation forecasts have greater skill than the raw forecasts. These improvements are more noticeable in the warm season at the longer lead times (> 3 days). Both postprocessors, ARX(1,1) and QR, show gains in skill relative to the raw ensemble streamflow forecasts, particularly in the cool season, but QR outperforms ARX(1,1). The scenarios that implement preprocessing and postprocessing separately tend to perform similarly, although the postprocessing-alone scenario is often more effective. The scenario involving both preprocessing and postprocessing consistently outperforms the other scenarios. In some cases, however, the differences between this scenario and the scenario with postprocessing alone are not as significant. We conclude that implementing both preprocessing and postprocessing ensures the most skill improvements, but postprocessing alone can often be a competitive alternative.

Statistical summaries of selected Iowa streamflow data through September 2013.

DOT National Transportation Integrated Search

2015-01-01

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 rep...

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

USGS Publications Warehouse

Norton, Parker A.; Anderson, Mark T.; Stamm, John F.

2014-01-01

The Missouri River and its tributaries are an important resource that serve multiple uses including agriculture, energy, recreation, and municipal water supply. Understanding historical streamflow characteristics provides relevant guidance to adaptive management of these water resources. Streamflow records in the Missouri River watershed were examined for trends in time series of annual, seasonal, and monthly streamflow. A total of 227 streamgages having continuous observational records for water years 1960–2011 were examined. Kendall’s tau nonparametric test was used to determine statistical significance of trends in annual, seasonal, and monthly streamflow. A trend was considered statistically significant for a probability value less than or equal to 0.10 that the Kendall’s tau value equals zero. Significant trends in annual streamflow were indicated for 101 out of a total of 227 streamgages. The Missouri River watershed was divided into six watershed regions and trends within regions were examined. The western and the southern parts of the Missouri River watershed had downward trends in annual streamflow (56 streamgages), whereas the eastern part of the watershed had upward trends in streamflow (45 streamgages). Seasonal and monthly streamflow trends reflected prevailing annual streamflow trends within each watershed region.

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.

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.

The Massachusetts Sustainable-Yield Estimator: A decision-support tool to assess water availability at ungaged stream locations in Massachusetts

USGS Publications Warehouse

Archfield, Stacey A.; Vogel, Richard M.; Steeves, Peter A.; Brandt, Sara L.; Weiskel, Peter K.; Garabedian, Stephen P.

2010-01-01

Federal, State and local water-resource managers require a variety of data and modeling tools to better understand water resources. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a statewide, interactive decision-support tool to meet this need. The decision-support tool, referred to as the Massachusetts Sustainable-Yield Estimator (MA SYE) provides screening-level estimates of the sustainable yield of a basin, defined as the difference between the unregulated streamflow and some user-specified quantity of water that must remain in the stream to support such functions as recreational activities or aquatic habitat. The MA SYE tool was designed, in part, because the quantity of surface water available in a basin is a time-varying quantity subject to competing demands for water. To compute sustainable yield, the MA SYE tool estimates a daily time series of unregulated, daily mean streamflow for a 44-year period of record spanning October 1, 1960, through September 30, 2004. Selected streamflow quantiles from an unregulated, daily flow-duration curve are estimated by solving six regression equations that are a function of physical and climate basin characteristics at an ungaged site on a stream of interest. Streamflow is then interpolated between the estimated quantiles to obtain a continuous daily flow-duration curve. A time series of unregulated daily streamflow subsequently is created by transferring the timing of the daily streamflow at a reference streamgage to the ungaged site by equating exceedence probabilities of contemporaneous flow at the two locations. One of 66 reference streamgages is selected by kriging, a geostatistical method, which is used to map the spatial relation among correlations between the time series of the logarithm of daily streamflows at each reference streamgage and the ungaged site. Estimated unregulated, daily mean streamflows show good agreement with observed unregulated, daily mean streamflow at 18 streamgages located across southern New England. Nash-Sutcliffe efficiency goodness-of-fit values are between 0.69 and 0.98, and percent root-mean-square-error values are between 19 and 283 percent. The MA SYE tool provides an estimate of streamflow adjusted for current (2000-04) water withdrawals and discharges using a spatially referenced database of permitted groundwater and surface-water withdrawal and discharge volumes. For a user-selected basin, the database is queried to obtain the locations of water withdrawal or discharge volumes within the basin. Groundwater and surface-water withdrawals and discharges are subtracted and added, respectively, from the unregulated, daily streamflow at an ungaged site to obtain a streamflow time series that includes the effects of these withdrawals and discharges. Users also have the option of applying an analytical solution to the time-varying, groundwater withdrawal and discharge volumes that take into account the effects of the aquifer properties on the timing and magnitude of streamflow alteration. For the MA SYE tool, it is assumed that groundwater and surface-water divides are coincident. For areas of southeastern Massachusetts and Cape Cod where this assumption is known to be violated, groundwater-flow models are used to estimate average monthly streamflows at fixed locations. There are several limitations to the quality and quantity of the spatially referenced database of groundwater and surface-water withdrawals and discharges. The adjusted streamflow values do not account for the effects on streamflow of climate change, septic-system discharge, impervious area, non-public water-supply withdrawals less than 100,000 gallons per day, and impounded surface-water bodies.

CrowdWater - Can people observe what models need?

NASA Astrophysics Data System (ADS)

van Meerveld, I. H. J.; Seibert, J.; Vis, M.; Etter, S.; Strobl, B.

2017-12-01

CrowdWater (www.crowdwater.ch) is a citizen science project that explores the usefulness of crowd-sourced data for hydrological model calibration and prediction. Hydrological models are usually calibrated based on observed streamflow data but it is likely easier for people to estimate relative stream water levels, such as the water level above or below a rock, than streamflow. Relative stream water levels may, therefore, be a more suitable variable for citizen science projects than streamflow. In order to test this assumption, we held surveys near seven different sized rivers in Switzerland and asked more than 450 volunteers to estimate the water level class based on a picture with a virtual staff gauge. The results show that people can generally estimate the relative water level well, although there were also a few outliers. We also asked the volunteers to estimate streamflow based on the stick method. The median estimated streamflow was close to the observed streamflow but the spread in the streamflow estimates was large and there were very large outliers, suggesting that crowd-based streamflow data is highly uncertain. In order to determine the potential value of water level class data for model calibration, we converted streamflow time series for 100 catchments in the US to stream level class time series and used these to calibrate the HBV model. The model was then validated using the streamflow data. The results of this modeling exercise show that stream level class data are useful for constraining a simple runoff model. Time series of only two stream level classes, e.g. above or below a rock in the stream, were already informative, especially when the class boundary was chosen towards the highest stream levels. There was hardly any improvement in model performance when more than five water level classes were used. This suggests that if crowd-sourced stream level observations are available for otherwise ungauged catchments, these data can be used to constrain a simple runoff model and to generate simulated streamflow time series from the level observations.

Flooding in the Northeastern United States, 2011

USGS Publications Warehouse

Suro, Thomas P.; Roland, Mark A.; Kiah, Richard G.

2015-12-31

The annual exceedance probability (AEP) for 327 streamgages in the Northeastern United States were computed using annual peak streamflow data through 2011 and are included in this report. The 2011 peak streamflow for 129 of those streamgages was estimated to have an AEP of less than or equal to 1 percent. Almost 100 of these peak streamflows were a result of the flooding associated with Hurricane Irene in late August 2011. More extreme than the 1-percent AEP, is the 0.2-percent AEP. The USGS recorded peak streamflows at 31 streamgages that equaled or exceeded the estimated 0.2-percent AEP during 2011. Collectively, the USGS recorded peak streamflows having estimated AEPs of less than 1 percent in Connecticut, Delaware, Maine, Maryland, Massachusetts, Ohio, Pennsylvania, New Hampshire, New Jersey, New York, and Vermont and new period-of-record peak streamflows were recorded at more than 180 streamgages resulting from the floods of 2011.

Methods for estimating streamflow at mountain fronts in southern New Mexico

USGS Publications Warehouse

Waltemeyer, S.D.

1994-01-01

The infiltration of streamflow is potential recharge to alluvial-basin aquifers at or near mountain fronts in southern New Mexico. Data for 13 streamflow-gaging stations were used to determine a relation between mean annual stream- flow and basin and climatic conditions. Regression analysis was used to develop an equation that can be used to estimate mean annual streamflow on the basis of drainage areas and mean annual precipi- tation. The average standard error of estimate for this equation is 46 percent. Regression analysis also was used to develop an equation to estimate mean annual streamflow on the basis of active- channel width. Measurements of the width of active channels were determined for 6 of the 13 gaging stations. The average standard error of estimate for this relation is 29 percent. Stream- flow estimates made using a regression equation based on channel geometry are considered more reliable than estimates made from an equation based on regional relations of basin and climatic conditions. The sample size used to develop these relations was small, however, and the reported standard error of estimate may not represent that of the entire population. Active-channel-width measurements were made at 23 ungaged sites along the Rio Grande upstream from Elephant Butte Reservoir. Data for additional sites would be needed for a more comprehensive assessment of mean annual streamflow in southern New Mexico.

Temporal rainfall estimation using input data reduction and model inversion

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Predicting the natural flow regime: Models for assessing hydrological alteration in streams

USGS Publications Warehouse

Carlisle, D.M.; Falcone, J.; Wolock, D.M.; Meador, M.R.; Norris, R.H.

2009-01-01

Understanding the extent to which natural streamflow characteristics have been altered is an important consideration for ecological assessments of streams. Assessing hydrologic condition requires that we quantify the attributes of the flow regime that would be expected in the absence of anthropogenic modifications. The objective of this study was to evaluate whether selected streamflow characteristics could be predicted at regional and national scales using geospatial data. Long-term, gaged river basins distributed throughout the contiguous US that had streamflow characteristics representing least disturbed or near pristine conditions were identified. Thirteen metrics of the magnitude, frequency, duration, timing and rate of change of streamflow were calculated using a 20-50 year period of record for each site. We used random forests (RF), a robust statistical modelling approach, to develop models that predicted the value for each streamflow metric using natural watershed characteristics. We compared the performance (i.e. bias and precision) of national- and regional-scale predictive models to that of models based on landscape classifications, including major river basins, ecoregions and hydrologic landscape regions (HLR). For all hydrologic metrics, landscape stratification models produced estimates that were less biased and more precise than a null model that accounted for no natural variability. Predictive models at the national and regional scale performed equally well, and substantially improved predictions of all hydrologic metrics relative to landscape stratification models. Prediction error rates ranged from 15 to 40%, but were 25% for most metrics. We selected three gaged, non-reference sites to illustrate how predictive models could be used to assess hydrologic condition. These examples show how the models accurately estimate predisturbance conditions and are sensitive to changes in streamflow variability associated with long-term land-use change. We also demonstrate how the models can be applied to predict expected natural flow characteristics at ungaged sites. ?? 2009 John Wiley & Sons, Ltd.

Estimation of low-flow statistics at ungaged sites on streams in the Lower Hudson River Basin, New York, from data in geographic information systems

USGS Publications Warehouse

Randall, Allan D.; Freehafer, Douglas A.

2017-08-02

A variety of watershed properties available in 2015 from geographic information systems were tested in regression equations to estimate two commonly used statistical indices of the low flow of streams, namely the lowest flows averaged over 7 consecutive days that have a 1 in 10 and a 1 in 2 chance of not being exceeded in any given year (7-day, 10-year and 7-day, 2-year low flows). The equations were based on streamflow measurements in 51 watersheds in the Lower Hudson River Basin of New York during the years 1958–1978, when the number of streamflow measurement sites on unregulated streams was substantially greater than in subsequent years. These low-flow indices are chiefly a function of the area of surficial sand and gravel in the watershed; more precisely, 7-day, 10-year and 7-day, 2-year low flows both increase in proportion to the area of sand and gravel deposited by glacial meltwater, whereas 7-day, 2-year low flows also increase in proportion to the area of postglacial alluvium. Both low-flow statistics are also functions of mean annual runoff (a measure of net water input to the watershed from precipitation) and area of swamps and poorly drained soils in or adjacent to surficial sand and gravel (where groundwater recharge is unlikely and riparian water loss to evapotranspiration is substantial). Small but significant refinements in estimation accuracy resulted from the inclusion of two indices of stream geometry, channel slope and length, in the regression equations. Most of the regression analysis was undertaken with the ordinary least squares method, but four equations were replicated by using weighted least squares to provide a more realistic appraisal of the precision of low-flow estimates. The most accurate estimation equations tested in this study explain nearly 84 and 87 percent of the variation in 7-day, 10-year and 7-day, 2-year low flows, respectively, with standard errors of 0.032 and 0.050 cubic feet per second per square mile. The equations use natural values of streamflow and watershed properties; logarithmic transformations yielded less accurate equations inconsistent with some conceptualized relationships.

Statistical summary of selected physical, chemical, and toxicity characteristics and estimates of annual constituent loads in urban stormwater, Maricopa County, Arizona

USGS Publications Warehouse

Fossum, Kenneth D.; O'Day, Christie M.; Wilson, Barbara J.; Monical, Jim E.

2001-01-01

Stormwater and streamflow in Maricopa County were monitored to (1) describe the physical, chemical, and toxicity characteristics of stormwater from areas having different land uses, (2) describe the physical, chemical, and toxicity characteristics of streamflow from areas that receive urban stormwater, and (3) estimate constituent loads in stormwater. Urban stormwater and streamflow had similar ranges in most constituent concentrations. The mean concentration of dissolved solids in urban stormwater was lower than in streamflow from the Salt River and Indian Bend Wash. Urban stormwater, however, had a greater chemical oxygen demand and higher concentrations of most nutrients. Mean seasonal loads and mean annual loads of 11 constituents and volumes of runoff were estimated for municipalities in the metropolitan Phoenix area, Arizona, by adjusting regional regression equations of loads. This adjustment procedure uses the original regional regression equation and additional explanatory variables that were not included in the original equation. The adjusted equations had standard errors that ranged from 161 to 196 percent. The large standard errors of the prediction result from the large variability of the constituent concentration data used in the regression analysis. Adjustment procedures produced unsatisfactory results for nine of the regressions?suspended solids, dissolved solids, total phosphorus, dissolved phosphorus, total recoverable cadmium, total recoverable copper, total recoverable lead, total recoverable zinc, and storm runoff. These equations had no consistent direction of bias and no other additional explanatory variables correlated with the observed loads. A stepwise-multiple regression or a three-variable regression (total storm rainfall, drainage area, and impervious area) and local data were used to develop local regression equations for these nine constituents. These equations had standard errors from 15 to 183 percent.

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.

Techniques for estimating peak-streamflow frequency for unregulated streams and streams regulated by small floodwater retarding structures in Oklahoma

USGS Publications Warehouse

Tortorelli, Robert L.

1997-01-01

Statewide regression equations for Oklahoma were determined for estimating peak discharge and flood frequency for selected recurrence intervals from 2 to 500 years for ungaged sites on natural unregulated streams. The most significant independent variables required to estimate peak-streamflow frequency for natural unregulated streams in Oklahoma are contributing drainage area, main-channel slope, and mean-annual precipitation. The regression equations are applicable for watersheds with drainage areas less than 2,510 square miles that are not affected by regulation from manmade works. Limitations on the use of the regression relations and the reliability of regression estimates for natural unregulated streams are discussed. Log-Pearson Type III analysis information, basin and climatic characteristics, and the peak-stream-flow frequency estimates for 251 gaging stations in Oklahoma and adjacent states are listed. Techniques are presented to make a peak-streamflow frequency estimate for gaged sites on natural unregulated streams and to use this result to estimate a nearby ungaged site on the same stream. For ungaged sites on urban streams, an adjustment of the statewide regression equations for natural unregulated streams can be used to estimate peak-streamflow frequency. For ungaged sites on 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 frequency. The statewide regression equations are adjusted by substituting the drainage area below the floodwater retarding structures, or drainage area that represents the percentage of the unregulated basin, in the contributing drainage area parameter to obtain peak-streamflow frequency estimates.

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.

Simulation of daily streamflows at gaged and ungaged locations within the Cedar River Basin, Iowa, using a Precipitation-Runoff Modeling System model

USGS Publications Warehouse

Christiansen, Daniel E.

2012-01-01

The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, conducted a study to examine techniques for estimation of daily streamflows using hydrological models and statistical methods. This report focuses on the use of a hydrologic model, the U.S. Geological Survey's Precipitation-Runoff Modeling System, to estimate daily streamflows at gaged and ungaged locations. The Precipitation-Runoff Modeling System is a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The Cedar River Basin was selected to construct a Precipitation-Runoff Modeling System model that simulates the period from January 1, 2000, to December 31, 2010. The calibration period was from January 1, 2000, to December 31, 2004, and the validation periods were from January 1, 2005, to December 31, 2010 and January 1, 2000 to December 31, 2010. A Geographic Information System tool was used to delineate the Cedar River Basin and subbasins for the Precipitation-Runoff Modeling System model and to derive parameters based on the physical geographical features. Calibration of the Precipitation-Runoff Modeling System model was completed using a U.S. Geological Survey calibration software tool. The main objective of the calibration was to match the daily streamflow simulated by the Precipitation-Runoff Modeling System model with streamflow measured at U.S. Geological Survey streamflow gages. The Cedar River Basin daily streamflow model performed with a Nash-Sutcliffe efficiency ranged from 0.82 to 0.33 during the calibration period, and a Nash-Sutcliffe efficiency ranged from 0.77 to -0.04 during the validation period. The Cedar River Basin model is meeting the criteria of greater than 0.50 Nash-Sutcliffe and is a good fit for streamflow conditions for the calibration period at all but one location, Austin, Minnesota. The Precipitation-Runoff Modeling System model accurately simulated streamflow at four of six uncalibrated sites within the basin. Overall, there was good agreement between simulated and measured seasonal and annual volumes throughout the basin for calibration and validation sites. The calibration period ranged from 0.2 to 20.8 percent difference, and the validation period ranged from 0.0 to 19.5 percent difference across all seasons and total annual runoff. The Precipitation-Runoff Modeling System model tended to underestimate lower streamflows compared to the observed streamflow values. This is an indication that the Precipitation-Runoff Modeling model needs more detailed groundwater and storage information to properly model the low-flow conditions in the Cedar River Basin.

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

NASA Astrophysics Data System (ADS)

Renner, M.; Bernhofer, C.

2012-08-01

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. (2012) introduced the climate change impact hypothesis (CCUW), 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 (the Budyko approach of Roderick and Farquhar, 2011, and the CCUW) with data of more than 400 basins distributed over the continental United States. We first estimate the sensitivity of streamflow to changes in precipitation using long-term average data of the period 1949 to 2003. This provides a hydro-climatic status of the respective basins as well as their expected proportional effect to changes in climate. Next, we test the ability of both approaches to predict climate impacts on streamflow by splitting the data into two periods. We (i) analyse the long-term average changes in hydro-climatology and (ii) derive a statistical classification of potential climate and basin change impacts based on the significance of observed changes in runoff, precipitation and potential evapotranspiration. Then we (iii) use the different climate sensitivity methods to predict the change in streamflow given the observed changes in water and energy supply and (iv) evaluate the predictions by (v) using the statistical classification scheme and (vi) a conceptual approach to separate the impacts of changes in climate from basin characteristics change on streamflow. This allows us to evaluate the observed changes in streamflow as well as to assess the impact of basin changes on the validity of climate sensitivity approaches. The apparent increase of streamflow of the majority of basins in the US is dominated by an increase in precipitation. It is further evident that impacts of changes in basin characteristics appear simultaneously with climate changes. There are coherent spatial patterns with catchments where basin changes compensate for climatic changes being dominant in the western and central parts of the US. A hot spot of basin changes leading to excessive runoff is found within the US Midwest. The impact of basin changes on the prediction is large and can be twice as much as the observed change signal. Although the CCUW and the Budyko approach yield similar predictions for most basins, the data of water-limited basins support the Budyko framework rather than the CCUW approach, which is known to be invalid under limiting climatic conditions.

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 logarithms of combined annual streamflow to water years 1950-2003. The results of the regression analysis indicated a significant downward trend (regression line slope was -0.00977) for combined annual streamflow. A regression analysis using data from 1956-2003 indicated a slight, but not significant, downward trend for combined annual streamflow.

Annual peak streamflow and ancillary data for small watersheds in central and western Texas

USGS Publications Warehouse

Harwell, Glenn R.; Asquith, William H.

2011-01-01

Estimates of annual peak-streamflow frequency are needed for flood-plain management, assessment of flood risk, and design of structures, such as roads, bridges, culverts, dams, and levees. Regional regression equations have been developed and are used extensively to estimate annual peak-streamflow frequency for ungaged sites in natural (unregulated and rural or nonurbanized) watersheds in Texas (Asquith and Slade, 1997; Asquith and Thompson, 2008; Asquith and Roussel, 2009). The most recent regional regression equations were developed by using data from 638 Texas streamflow-gaging stations throughout the State with eight or more years of data by using drainage area, channel slope, and mean annual precipitation as predictor variables (Asquith and Roussel, 2009). However, because of a lack of sufficient historical streamflow data from small, rural watersheds in certain parts of the State (central and western), substantial uncertainity exists when using the regional regression equations for the purpose of estimating annual peak-streamflow frequency.

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.

A method for estimating peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area

USGS Publications Warehouse

Asquith, William H.; Cleveland, Theodore G.; Roussel, Meghan C.

2011-01-01

Estimates of peak and time of peak streamflow for small watersheds (less than about 640 acres) in a suburban to urban, low-slope setting are needed for drainage design that is cost-effective and risk-mitigated. During 2007-10, the U.S. Geological Survey (USGS), in cooperation with the Harris County Flood Control District and the Texas Department of Transportation, developed a method to estimate peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area. To develop the method, 24 watersheds in the study area with drainage areas less than about 3.5 square miles (2,240 acres) and with concomitant rainfall and runoff data were selected. The method is based on conjunctive analysis of rainfall and runoff data in the context of the unit hydrograph method and the rational method. For the unit hydrograph analysis, a gamma distribution model of unit hydrograph shape (a gamma unit hydrograph) was chosen and parameters estimated through matching of modeled peak and time of peak streamflow to observed values on a storm-by-storm basis. Watershed mean or watershed-specific values of peak and time to peak ("time to peak" is a parameter of the gamma unit hydrograph and is distinct from "time of peak") of the gamma unit hydrograph were computed. Two regression equations to estimate peak and time to peak of the gamma unit hydrograph that are based on watershed characteristics of drainage area and basin-development factor (BDF) were developed. For the rational method analysis, a lag time (time-R), volumetric runoff coefficient, and runoff coefficient were computed on a storm-by-storm basis. Watershed-specific values of these three metrics were computed. A regression equation to estimate time-R based on drainage area and BDF was developed. Overall arithmetic means of volumetric runoff coefficient (0.41 dimensionless) and runoff coefficient (0.25 dimensionless) for the 24 watersheds were used to express the rational method in terms of excess rainfall (the excess rational method). Both the unit hydrograph method and excess rational method are shown to provide similar estimates of peak and time of peak streamflow. The results from the two methods can be combined by using arithmetic means. A nomograph is provided that shows the respective relations between the arithmetic-mean peak and time of peak streamflow to drainage areas ranging from 10 to 640 acres. The nomograph also shows the respective relations for selected BDF ranging from undeveloped to fully developed conditions. The nomograph represents the peak streamflow for 1 inch of excess rainfall based on drainage area and BDF; the peak streamflow for design storms from the nomograph can be multiplied by the excess rainfall to estimate peak streamflow. Time of peak streamflow is readily obtained from the nomograph. Therefore, given excess rainfall values derived from watershed-loss models, which are beyond the scope of this report, the nomograph represents a method for estimating peak and time of peak streamflow for applicable watersheds in the Houston metropolitan area. Lastly, analysis of the relative influence of BDF on peak streamflow is provided, and the results indicate a 0:04log10 cubic feet per second change of peak streamflow per positive unit of change in BDF. This relative change can be used to adjust peak streamflow from the method or other hydrologic methods for a given BDF to other BDF values; example computations are provided.

Regionalization of winter low-flow characteristics of Tennessee streams

USGS Publications Warehouse

Bingham, R.H.

1986-01-01

Procedures were developed for estimating winter (December-April) low flows at ungaged stream sites in Tennessee based on surface geology and drainage area size. One set of equations applies to West Tennessee streams, and another set applies to Middle and East Tennessee streams. The equations do not apply to streams where flow is significantly altered by the activities of man. Standard errors of estimate of equations for West Tennessee are 22% - 35% and for middle and East Tennessee 31% - 36%. Statistical analyses indicate that summer low-flow characteristics are the same as annual low-flow characteristics, and that winter low flows are larger than annual low flows. Streamflow-recession indexes, in days per log cycle of decrease in discharge, were used to account for effects of geology on low flow of streams. The indexes in Tennessee range from 32 days/log cycle for clay and shale to 350 days/log cycle for gravel and sand, indicating different aquifer characteristics of the geologic units that contribute to streamflows during periods of no surface runoff. Streamflow-recession rate depends primarily on transmissivity and storage characteristics of the aquifers, and the average distance from stream channels to basin divides. Geology and drainage basin size are the most significant variables affecting low flow in Tennessee streams according to regression analyses. (Author 's abstract)

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

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.

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).

THE WATER BALANCE OF THE SUSQUEHANNA RIVER BASIN AND ITS RESPONSE TO CLIMATE CHANGE. (R824995)

EPA Science Inventory

Abstract

Historical precipitation, temperature and streamflow data for the Susquehanna River Basin (SRB) are analyzed with the objective of developing simple statistical and water balance models of streamflow at the watershed's outlet. Annual streamflow is highly corre...

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.

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.

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 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.

Estimating Basin-Scale Water Budgets with SMAP Level 2 Soil Moisture Data

NASA Technical Reports Server (NTRS)

Koster, Randal; Crow, Wade; Reichle, Rolf; Mahanama, Sarith P.

2018-01-01

The SMAP estimates of rainfall and streamflow are not perfect, but they do contain relevant information. At the very least, they should prove useful for constraining, or otherwise contributing to, rainfall and streamflow estimates obtained with more conventional approaches.

Streamflow distribution maps for the Cannon River drainage basin, southeast Minnesota, and the St. Louis River drainage basin, northeast Minnesota

USGS Publications Warehouse

Smith, Erik A.; Sanocki, Chris A.; Lorenz, David L.; Jacobsen, Katrin E.

2017-12-27

Streamflow distribution maps for the Cannon River and St. Louis River drainage basins were developed by the U.S. Geological Survey, in cooperation with the Legislative-Citizen Commission on Minnesota Resources, to illustrate relative and cumulative streamflow distributions. The Cannon River was selected to provide baseline data to assess the effects of potential surficial sand mining, and the St. Louis River was selected to determine the effects of ongoing Mesabi Iron Range mining. Each drainage basin (Cannon, St. Louis) was subdivided into nested drainage basins: the Cannon River was subdivided into 152 nested drainage basins, and the St. Louis River was subdivided into 353 nested drainage basins. For each smaller drainage basin, the estimated volumes of groundwater discharge (as base flow) and surface runoff flowing into all surface-water features were displayed under the following conditions: (1) extreme low-flow conditions, comparable to an exceedance-probability quantile of 0.95; (2) low-flow conditions, comparable to an exceedance-probability quantile of 0.90; (3) a median condition, comparable to an exceedance-probability quantile of 0.50; and (4) a high-flow condition, comparable to an exceedance-probability quantile of 0.02.Streamflow distribution maps were developed using flow-duration curve exceedance-probability quantiles in conjunction with Soil-Water-Balance model outputs; both the flow-duration curve and Soil-Water-Balance models were built upon previously published U.S. Geological Survey reports. The selected streamflow distribution maps provide a proactive water management tool for State cooperators by illustrating flow rates during a range of hydraulic conditions. Furthermore, after the nested drainage basins are highlighted in terms of surface-water flows, the streamflows can be evaluated in the context of meeting specific ecological flows under different flow regimes and potentially assist with decisions regarding groundwater and surface-water appropriations. Presented streamflow distribution maps are foundational work intended to support the development of additional streamflow distribution maps that include statistical constraints on the selected flow conditions.

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

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 acceptable results. The RAR also was determined to provide acceptable results for estimating the PK1.5., PK2, and PK2.33 for the three CMR stations that lacked suitable peak-flow records. Methods for estimating streamflow characteristics at ungaged sites also were derived. Regression analyses that relate individual streamflow characteristics to various basin and climatic characteristics for gaging stations were performed to develop regression equations to estimate streamflow characteristics at ungaged sites. Final equations for the annual Q.50, Q.20, and QM are reported. Acceptable equations also were developed for estimating QM for the months of February, March, April, June, and July, and Q.50, Q.20, and QM on an annual basis. However, equations for QM for the months of February, March, April, June, and July were determined to be less consistent and reliable than the use of estimation coefficients applied to the regression equation results for the annual QM. Acceptable regression equations also were developed for the PK1.5, PK2, and PK2.33.

Regression models for estimating salinity and selenium concentrations at selected sites in the Upper Colorado River Basin, Colorado, 2009-2012

USGS Publications Warehouse

Linard, Joshua I.; Schaffrath, Keelin R.

2014-01-01

Elevated concentrations of salinity and selenium in the tributaries and main-stem reaches of the Colorado River are a water-quality concern and have been the focus of remediation efforts for many years. Land-management practices with the objective of limiting the amount of salt and selenium that reaches the stream have focused on improving the methods by which irrigation water is conveyed and distributed. Federal land managers implement improvements in accordance with the Colorado River Basin Salinity Control Act of 1974, which directs Federal land managers to enhance and protect the quality of water available in the Colorado River. In an effort to assist in evaluating and mitigating the detrimental effects of salinity and selenium, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, the Colorado River Water Resources District, and the Bureau of Land Management, analyzed salinity and selenium data collected at sites to develop regression models. The study area and sites are on the Colorado River or in one of three small basins in Western Colorado: the White River Basin, the Lower Gunnison River Basin, and the Dolores River Basin. By using data collected from water years 2009 through 2011, regression models able to estimate concentrations were developed for salinity at six sites and selenium at six sites. At a minimum, data from discrete measurement of salinity or selenium concentration, streamflow, and specific conductance at each of the sites were needed for model development. Comparison of the Adjusted R2 and standard error statistics of the two salinity models developed at each site indicated the models using specific conductance as the explanatory variable performed better than those using streamflow. The addition of multiple explanatory variables improved the ability to estimate selenium concentration at several sites compared with use of solely streamflow or specific conductance. The error associated with the log-transformed salinity and selenium estimates is consistent in log space; however, when the estimates are transformed into non-log values, the error increases as the estimates decrease. Continuous streamflow and specific conductance data collected at study sites provide the means to examine temporal variability in constituent concentration and load. The regression models can estimate continuous concentrations or loads on the basis of continuous specific conductance or streamflow data. Similar estimates are available for other sites at the USGS National Real-Time Water Quality Web page (http://nrtwq.usgs.gov) and provide water-resource managers with a means of improving their general understanding of how constituent concentration or load can change annually, seasonally, or in real time.

Comparison of Peak-Flow Estimation Methods for Small Drainage Basins in Maine

USGS Publications Warehouse

Hodgkins, Glenn A.; Hebson, Charles; Lombard, Pamela J.; Mann, Alexander

2007-01-01

Understanding the accuracy of commonly used methods for estimating peak streamflows is important because the designs of bridges, culverts, and other river structures are based on these flows. Different methods for estimating peak streamflows were analyzed for small drainage basins in Maine. For the smallest basins, with drainage areas of 0.2 to 1.0 square mile, nine peak streamflows from actual rainfall events at four crest-stage gaging stations were modeled by the Rational Method and the Natural Resource Conservation Service TR-20 method and compared to observed peak flows. The Rational Method had a root mean square error (RMSE) of -69.7 to 230 percent (which means that approximately two thirds of the modeled flows were within -69.7 to 230 percent of the observed flows). The TR-20 method had an RMSE of -98.0 to 5,010 percent. Both the Rational Method and TR-20 underestimated the observed flows in most cases. For small basins, with drainage areas of 1.0 to 10 square miles, modeled peak flows were compared to observed statistical peak flows with return periods of 2, 50, and 100 years for 17 streams in Maine and adjoining parts of New Hampshire. Peak flows were modeled by the Rational Method, the Natural Resources Conservation Service TR-20 method, U.S. Geological Survey regression equations, and the Probabilistic Rational Method. The regression equations were the most accurate method of computing peak flows in Maine for streams with drainage areas of 1.0 to 10 square miles with an RMSE of -34.3 to 52.2 percent for 50-year peak flows. The Probabilistic Rational Method was the next most accurate method (-38.5 to 62.6 percent). The Rational Method (-56.1 to 128 percent) and particularly the TR-20 method (-76.4 to 323 percent) had much larger errors. Both the TR-20 and regression methods had similar numbers of underpredictions and overpredictions. The Rational Method overpredicted most peak flows and the Probabilistic Rational Method tended to overpredict peak flows from the smaller (less than 5 square miles) drainage basins and underpredict peak flows from larger drainage basins. The results of this study are consistent with the most comprehensive analysis of observed and modeled peak streamflows in the United States, which analyzed statistical peak flows from 70 drainage basins in the Midwest and the Northwest.

On Lack of Robustness in Hydrological Model Development Due to Absence of Guidelines for Selecting Calibration and Evaluation Data: Demonstration for Data-Driven Models

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Maier, Holger R.; Wu, Wenyan; Dandy, Graeme C.; Gupta, Hoshin V.; Zhang, Tuqiao

2018-02-01

Hydrological models are used for a wide variety of engineering purposes, including streamflow forecasting and flood-risk estimation. To develop such models, it is common to allocate the available data to calibration and evaluation data subsets. Surprisingly, the issue of how this allocation can affect model evaluation performance has been largely ignored in the research literature. This paper discusses the evaluation performance bias that can arise from how available data are allocated to calibration and evaluation subsets. As a first step to assessing this issue in a statistically rigorous fashion, we present a comprehensive investigation of the influence of data allocation on the development of data-driven artificial neural network (ANN) models of streamflow. Four well-known formal data splitting methods are applied to 754 catchments from Australia and the U.S. to develop 902,483 ANN models. Results clearly show that the choice of the method used for data allocation has a significant impact on model performance, particularly for runoff data that are more highly skewed, highlighting the importance of considering the impact of data splitting when developing hydrological models. The statistical behavior of the data splitting methods investigated is discussed and guidance is offered on the selection of the most appropriate data splitting methods to achieve representative evaluation performance for streamflow data with different statistical properties. Although our results are obtained for data-driven models, they highlight the fact that this issue is likely to have a significant impact on all types of hydrological models, especially conceptual rainfall-runoff models.

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

USGS Publications Warehouse

van Heeswijk, Marijke

2006-01-01

Surface water has been diverted from the Salmon Creek Basin for irrigation purposes since the early 1900s, when the Bureau of Reclamation built the Okanogan Project. Spring snowmelt runoff is stored in two reservoirs, Conconully Reservoir and Salmon Lake Reservoir, and gradually released during the growing season. As a result of the out-of-basin streamflow diversions, the lower 4.3 miles of Salmon Creek typically has been a dry creek bed for almost 100 years, except during the spring snowmelt season during years of high runoff. To continue meeting the water needs of irrigators but also leave water in lower Salmon Creek for fish passage and to help restore the natural ecosystem, changes are being considered in how the Okanogan Project is operated. This report documents development of a precipitation-runoff model for the Salmon Creek Basin that can be used to simulate daily unregulated streamflows. The precipitation-runoff model is a component of a Decision Support System (DSS) that includes a water-operations model the Bureau of Reclamation plans to develop to study the water resources of the Salmon Creek Basin. The DSS will be similar to the DSS that the Bureau of Reclamation and the U.S. Geological Survey developed previously for the Yakima River Basin in central southern Washington. The precipitation-runoff model was calibrated for water years 1950-89 and tested for water years 1990-96. The model was used to simulate daily streamflows that were aggregated on a monthly basis and calibrated against historical monthly streamflows for Salmon Creek at Conconully Dam. Additional calibration data were provided by the snowpack water-equivalent record for a SNOTEL station in the basin. Model input time series of daily precipitation and minimum and maximum air temperatures were based on data from climate stations in the study area. Historical records of unregulated streamflow for Salmon Creek at Conconully Dam do not exist for water years 1950-96. Instead, estimates of historical monthly mean unregulated streamflow based on reservoir outflows and storage changes were used as a surrogate for the missing data and to calibrate and test the model. The estimated unregulated streamflows were corrected for evaporative losses from Conconully Reservoir (about 1 ft3/s) and ground-water losses from the basin (about 2 ft3/s). The total of the corrections was about 9 percent of the mean uncorrected streamflow of 32.2 ft3/s (23,300 acre-ft/yr) for water years 1949-96. For the calibration period, the basinwide mean annual evapotranspiration was simulated to be 19.1 inches, or about 83 percent of the mean annual precipitation of 23.1 inches. Model calibration and testing indicated that the daily streamflows simulated using the precipitation-runoff model should be used only to analyze historical and forecasted annual mean and April-July mean streamflows for Salmon Creek at Conconully Dam. Because of the paucity of model input data and uncertainty in the estimated unregulated streamflows, the model is not adequately calibrated and tested to estimate monthly mean streamflows for individual months, such as during low-flow periods, or for shorter periods such as during peak flows. No data were available to test the accuracy of simulated streamflows for lower Salmon Creek. As a result, simulated streamflows for lower Salmon Creek should be used with caution. For the calibration period (water years 1950-89), both the simulated mean annual streamflow and the simulated mean April-July streamflow compared well with the estimated uncorrected unregulated streamflow (UUS) and corrected unregulated streamflow (CUS). The simulated mean annual streamflow exceeded UUS by 5.9 percent and was less than CUS by 2.7 percent. Similarly, the simulated mean April-July streamflow exceeded UUS by 1.8 percent and was less than CUS by 3.1 percent. However, streamflow was significantly undersimulated during the low-flow, baseflow-dominated months of November through F

Changes in Streamflow and the Flux of Nutrients in the Mississippi-Atchafalaya River Basin, USA, 1980-2007

USGS Publications Warehouse

Battaglin, William A.; Aulenbach, Brent T.; Vecchia, Aldo; Buxton, Herbert T.

2010-01-01

Nutrients and freshwater delivered by the Mississippi and Atchafalaya Rivers drive algal production in the northern Gulf of Mexico, which eventually results in the widespread occurrence of hypoxic bottom waters along the Louisiana and Texas coast. Researchers have demonstrated a relation between the extent of the hypoxic zone and the magnitude of streamflow, nutrient fluxes, and nutrient concentrations in the Mississippi River, with springtime streamflows and fluxes being the most predictive. In 1999 the U.S. Geological Survey (USGS) estimated the flux of nitrogen, phosphorus, and silica at selected sites in the Mississippi Basin and to the Gulf of Mexico for 1980-1996. These flux estimates provided the baseline information used by the Mississippi River/Gulf of Mexico Watershed Nutrient Task Force to develop an Action Plan for reducing hypoxia in the northern Gulf of Mexico. The primary goal of the Action Plan was to achieve a reduction in the size (areal extent) of the hypoxic zone from an average of approximately 14,000 square kilometers in 1996-2000 to a 5-year moving average of less than 5,000 square kilometers by 2015. Improved statistical models and adjusted maximum likelihood estimation using USGS Load Estimator (LOADEST) software were used to estimate annual and seasonal nutrient fluxes for 1980-2007 at selected sites on the Mississippi River and its tributaries. These data provide a means to evaluate the influence of natural and anthropogenic effects on delivery of water and nutrients to the Gulf of Mexico; to define subbasins that are the most important contributors of nutrients to the gulf; and to investigate the relations among streamflow, nutrient fluxes, and the size and duration of the Gulf of Mexico hypoxic zone. A comparative analysis between the baseline period of 1980-1996 and 5-year moving averages thereafter indicate that the average annual streamflow and fluxes of total nitrogen, nitrate, orthophosphate, and silica to the Gulf of Mexico have decreased. However, the flux of total phosphorus between the baseline period and subsequent 5-year periods has increased. The average spring (April, May, and June) streamflow and fluxes of silica, total nitrogen, nitrate, and orthophosphate to the Gulf of Mexico also decreased, whereas the spring flux of total phosphorus has increased. Similar changes in streamflow and nutrient flux were observed at many sites Buxtonwithin the basin. The inputs of water, total nitrogen, and total phosphorus from the major subbasins of the Mississippi-Atchafalaya River Basin as a percentage of the to-the-gulf totals have increased from the Ohio River Basin, decreased from the Missouri River Basin, and remained relatively unchanged from the Upper Mississippi, Red, and Arkansas River Basins. Changes in streamflow and nutrient fluxes are related, but short-term variations in sources of streamflow and nutrients complicate the interpretation of factors that affect nutrient delivery to the Gulf of Mexico. Parametric time-series models are used to try and separate natural variability in nutrient flux from changes due to other causes. Results indicate that the decrease in annual nutrient fluxes that has occurred between the 1980-1996 baseline period and more recent years can be largely attributed to natural causes (climate and streamflow) and not management actions or other human controlled activities in the Mississippi-Atchafalaya River Basin. The downward trends in total nitrogen, nitrate, ammonium, and orthophosphate that were detected at either the Mississippi River near St. Francisville, La., or the Atchafalaya River at Melville, La., occurred prior to 1995. In spite of the general decrease in nutrient flux, the average size of the Gulf of Mexico hypoxic zone has increased between 1997 and 2007. The reasons for this are not clear but could be due to the type or nature of nutrient delivery. Whereas the annual flux of total nitrogen to the Gulf of Mexico has decreased, the proporti

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).

Method for estimating potential wetland extent by utilizing streamflow statistics and flood-inundation mapping techniques: Pilot study for land along the Wabash River near Terre Haute, Indiana

USGS Publications Warehouse

Kim, Moon H.; Ritz, Christian T.; Arvin, Donald V.

2012-01-01

Potential wetland extents were estimated for a 14-mile reach of the Wabash River near Terre Haute, Indiana. This pilot study was completed by the U.S. Geological Survey in cooperation with the U.S. Department of Agriculture, Natural Resources Conservation Service (NRCS). The study showed that potential wetland extents can be estimated by analyzing streamflow statistics with the available streamgage data, calculating the approximate water-surface elevation along the river, and generating maps by use of flood-inundation mapping techniques. Planning successful restorations for Wetland Reserve Program (WRP) easements requires a determination of areas that show evidence of being in a zone prone to sustained or frequent flooding. Zone determinations of this type are used by WRP planners to define the actively inundated area and make decisions on restoration-practice installation. According to WRP planning guidelines, a site needs to show evidence of being in an "inundation zone" that is prone to sustained or frequent flooding for a period of 7 consecutive days at least once every 2 years on average in order to meet the planning criteria for determining a wetland for a restoration in agricultural land. By calculating the annual highest 7-consecutive-day mean discharge with a 2-year recurrence interval (7MQ2) at a streamgage on the basis of available streamflow data, one can determine the water-surface elevation corresponding to the calculated flow that defines the estimated inundation zone along the river. By using the estimated water-surface elevation ("inundation elevation") along the river, an approximate extent of potential wetland for a restoration in agricultural land can be mapped. As part of the pilot study, a set of maps representing the estimated potential wetland extents was generated in a geographic information system (GIS) application by combining (1) a digital water-surface plane representing the surface of inundation elevation that sloped in the downstream direction of flow and (2) land-surface elevation data. These map products from the pilot study will aid the NRCS and its partners with the onsite inundation-zone verification in agricultural land for a potential restoration and will assist in determining at what elevation to plant hardwood trees for increased survivability on ground above frequently flooded terraces.

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.

Methods for estimating selected low-flow frequency statistics and mean annual flow for ungaged locations on streams in North Georgia

USGS Publications Warehouse

Gotvald, Anthony J.

2017-01-13

The U.S. Geological Survey, in cooperation with the Georgia Department of Natural Resources, Environmental Protection Division, developed regional regression equations for estimating selected low-flow frequency and mean annual flow statistics for ungaged streams in north Georgia that are not substantially affected by regulation, diversions, or urbanization. Selected low-flow frequency statistics and basin characteristics for 56 streamgage locations within north Georgia and 75 miles beyond the State’s borders in Alabama, Tennessee, North Carolina, and South Carolina were combined to form the final dataset used in the regional regression analysis. Because some of the streamgages in the study recorded zero flow, the final regression equations were developed using weighted left-censored regression analysis to analyze the flow data in an unbiased manner, with weights based on the number of years of record. The set of equations includes the annual minimum 1- and 7-day average streamflow with the 10-year recurrence interval (referred to as 1Q10 and 7Q10), monthly 7Q10, and mean annual flow. The final regional regression equations are functions of drainage area, mean annual precipitation, and relief ratio for the selected low-flow frequency statistics and drainage area and mean annual precipitation for mean annual flow. The average standard error of estimate was 13.7 percent for the mean annual flow regression equation and ranged from 26.1 to 91.6 percent for the selected low-flow frequency equations.The equations, which are based on data from streams with little to no flow alterations, can be used to provide estimates of the natural flows for selected ungaged stream locations in the area of Georgia north of the Fall Line. The regression equations are not to be used to estimate flows for streams that have been altered by the effects of major dams, surface-water withdrawals, groundwater withdrawals (pumping wells), diversions, or wastewater discharges. The regression equations should be used only for ungaged sites with drainage areas between 1.67 and 576 square miles, mean annual precipitation between 47.6 and 81.6 inches, and relief ratios between 0.146 and 0.607; these are the ranges of the explanatory variables used to develop the equations. An attempt was made to develop regional regression equations for the area of Georgia south of the Fall Line by using the same approach used during this study for north Georgia; however, the equations resulted with high average standard errors of estimates and poorly predicted flows below 0.5 cubic foot per second, which may be attributed to the karst topography common in that area.The final regression equations developed from this study are planned to be incorporated into the U.S. Geological Survey StreamStats program. StreamStats is a Web-based geographic information system that provides users with access to an assortment of analytical tools useful for water-resources planning and management, and for engineering design applications, such as the design of bridges. The StreamStats program provides streamflow statistics and basin characteristics for U.S. Geological Survey streamgage locations and ungaged sites of interest. StreamStats also can compute basin characteristics and provide estimates of streamflow statistics for ungaged sites when users select the location of a site along any stream in Georgia.

Making climate change projections relevant to water management: opportunities and challenges in the Colorado River basin (Invited)

NASA Astrophysics Data System (ADS)

Vano, J. A.

2013-12-01

By 2007, motivated by the ongoing drought and release of new climate model projections associated with the IPCC AR4 report, multiple independent studies had made estimates of future Colorado River streamflow. Each study had a unique approach, and unique estimate for the magnitude for mid-21st century streamflow change ranging from declines of only 6% to declines of as much as 45%. The differences among studies provided for interesting scientific debates, but to many practitioners this appeared to be just a tangle of conflicting predictions, leading to the question '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?' In response, a group of scientists from academic and federal agencies, brought together through a NOAA cross-RISA project, set forth to identify the major sources of disparities and provide actionable science and guidance for water managers and decision makers. Through this project, four major sources of disparities among modeling studies were identified that arise from both methodological and model differences. These differences, in order of importance, are: (1) the Global Climate Models (GCMs) and emission scenarios used; (2) the ability of land surface hydrology 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. Additionally, reconstructions of pre-instrumental streamflows provided further insights about the greatest risk to Colorado River streamflow of a multi-decadal drought, like those observed in paleo reconstructions, exacerbated by a steady reduction in flows due to climate change. Within this talk I will provide an overview of these findings and insights into the opportunities and challenges encountered in the process of striving to make climate change projections more useful to water managers and decision makers.

Annual and average estimates of water-budget components based on hydrograph separation and PRISM precipitation for gaged basins in the Appalachian Plateaus Region, 1900-2011

USGS Publications Warehouse

Nelms, David L.; Messinger, Terence; McCoy, Kurt J.

2015-07-14

As part of the U.S. Geological Survey’s Groundwater Resources Program study of the Appalachian Plateaus aquifers, annual and average estimates of water-budget components based on hydrograph separation and precipitation data from parameter-elevation regressions on independent slopes model (PRISM) were determined at 849 continuous-record streamflow-gaging stations from Mississippi to New York and covered the period of 1900 to 2011. Only complete calendar years (January to December) of streamflow record at each gage were used to determine estimates of base flow, which is that part of streamflow attributed to groundwater discharge; such estimates can serve as a proxy for annual recharge. For each year, estimates of annual base flow, runoff, and base-flow index were determined using computer programs—PART, HYSEP, and BFI—that have automated the separation procedures. These streamflow-hydrograph analysis methods are provided with version 1.0 of the U.S. Geological Survey Groundwater Toolbox, which is a new program that provides graphing, mapping, and analysis capabilities in a Windows environment. Annual values of precipitation were estimated by calculating the average of cell values intercepted by basin boundaries where previously defined in the GAGES–II dataset. Estimates of annual evapotranspiration were then calculated from the difference between precipitation and streamflow.

Assessing uncertainties in superficial water provision by different bootstrap-based techniques

NASA Astrophysics Data System (ADS)

Rodrigues, Dulce B. B.; Gupta, Hoshin V.; Mendiondo, Eduardo Mario

2014-05-01

An assessment of water security can incorporate several water-related concepts, characterizing the interactions between societal needs, ecosystem functioning, and hydro-climatic conditions. The superficial freshwater provision level depends on the methods chosen for 'Environmental Flow Requirement' estimations, which integrate the sources of uncertainty in the understanding of how water-related threats to aquatic ecosystem security arise. Here, we develop an uncertainty assessment of superficial freshwater provision based on different bootstrap techniques (non-parametric resampling with replacement). To illustrate this approach, we use an agricultural basin (291 km2) within the Cantareira water supply system in Brazil monitored by one daily streamflow gage (24-year period). The original streamflow time series has been randomly resampled for different times or sample sizes (N = 500; ...; 1000), then applied to the conventional bootstrap approach and variations of this method, such as: 'nearest neighbor bootstrap'; and 'moving blocks bootstrap'. We have analyzed the impact of the sampling uncertainty on five Environmental Flow Requirement methods, based on: flow duration curves or probability of exceedance (Q90%, Q75% and Q50%); 7-day 10-year low-flow statistic (Q7,10); and presumptive standard (80% of the natural monthly mean ?ow). The bootstrap technique has been also used to compare those 'Environmental Flow Requirement' (EFR) methods among themselves, considering the difference between the bootstrap estimates and the "true" EFR characteristic, which has been computed averaging the EFR values of the five methods and using the entire streamflow record at monitoring station. This study evaluates the bootstrapping strategies, the representativeness of streamflow series for EFR estimates and their confidence intervals, in addition to overview of the performance differences between the EFR methods. The uncertainties arisen during EFR methods assessment will be propagated through water security indicators referring to water scarcity and vulnerability, seeking to provide meaningful support to end-users and water managers facing the incorporation of uncertainties in the decision making process.

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

NASA Astrophysics Data System (ADS)

Wright, Ashley J.; Walker, Jeffrey P.; Pauwels, Valentijn R. N.

2017-08-01

Floods are devastating natural hazards. To provide accurate, precise, and timely flood forecasts, there is a need to understand the uncertainties associated within an entire rainfall time series, even when rainfall was not observed. The estimation of an entire rainfall time series and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of entire rainfall input time series to be considered when estimating model parameters, and provides the ability to improve rainfall estimates from poorly gauged catchments. Current methods to estimate entire rainfall time series from streamflow records are unable to adequately invert complex nonlinear hydrologic systems. This study aims to explore the use of wavelets in the estimation of rainfall time series from streamflow records. Using the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia, it is shown that model parameter distributions and an entire rainfall time series can be estimated. Including rainfall in the estimation process improves streamflow simulations by a factor of up to 1.78. This is achieved while estimating an entire rainfall time series, inclusive of days when none was observed. It is shown that the choice of wavelet can have a considerable impact on the robustness of the inversion. Combining the use of a likelihood function that considers rainfall and streamflow errors with the use of the DWT as a model data reduction technique allows the joint inference of hydrologic model parameters along with rainfall.

Contribution of Soil Moisture Information to Streamflow Prediction in the Snowmelt Season: A Continental-Scale Analysis

NASA Technical Reports Server (NTRS)

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

2009-01-01

In areas dominated by winter snowcover, the prediction of streamflow during the snowmelt season may benefit from three pieces of information: (i) the accurate prediction of weather variability (precipitation, etc.) leading up to and during the snowmelt season, (ii) estimates of the amount of snow present during the winter season, and (iii) estimates of the amount of soil moisture underlying the snowpack during the winter season. The importance of accurate meteorological predictions and wintertime snow estimates is obvious. The contribution of soil moisture to streamflow prediction is more subtle yet potentially very important. If the soil is dry below the snowpack, a significant fraction of the snowmelt may be lost to streamflow and potential reservoir storage, since it may infiltrate the soil instead for later evaporation. Such evaporative losses are presumably smaller if the soil below the snowpack is wet. In this paper, we use a state-of-the-art land surface model to quantify the contribution of wintertime snow and soil moisture information -- both together and separately -- to skill in forecasting springtime streamflow. We find that soil moisture information indeed contributes significantly to streamflow prediction skill.

Selected nutrients and pesticides in streams of the eastern Iowa basins, 1970-95

USGS Publications Warehouse

Schnoebelen, Douglas J.; Becher, Kent D.; Bobier, Matthew W.; Wilton, Thomas

1999-01-01

 The statistical analysis of the nutrient data typically indicated a strong positive correlation of nitrate with streamflow. Total phosphorus concentrations with streamflow showed greater variability than nitrate, perhaps reflecting the greater potential of transport of phosphorus on sediment rather than in the dissolved phase as with nitrate. Ammonia and ammonia plus organic nitrogen showed no correlation with streamflow or a weak positive correlation. Seasonal variations and the relations of nutrients and pesticides to streamflow generally corresponded with nonpoint‑source loadings, although possible point sources for nutrients were indicated by the data at selected monitoring sites. Statistical trend tests for concentrations and loads were computed for nitrate, ammonia, and total phosphorus. Trend analysis indicated decreases for ammonia and total phosphorus concentrations at several sites and increases for nitrate concentrations at other sites in the study unit.

Estimation of sediment inflows to Lake Tuscaloosa, Alabama, 2009-11

USGS Publications Warehouse

Lee, K.G.

2013-01-01

The U.S. Geological Survey, in cooperation with the City of Tuscaloosa, evaluated the concentrations, loads, and yields of suspended sediment in the tributaries to Lake Tuscaloosa in west-central Alabama, from October 1, 2008, to January 31, 2012. The collection and analysis of these data will facilitate the comparison with historical data, serve as a baseline for future sediment-collection efforts, and help to identify areas of concern. Lake Tuscaloosa, at the reservoir dam, receives runoff from a drainage area of 423 square miles (mi2). Basinwide in 2006, forested land was the primary land cover (68 percent). Comparison of historical imagery with the National Land Cover Database (2001 and 2006) indicated that the greatest temporal land-use change was timber harvest. The land cover in 2006 was indicative of this change, with shrub/scrub land (12 percent) being the secondary land use in the basin. Agricultural land use (10 percent) was represented predominantly by hay and pasture or grasslands. Urban land use was minimal, accounting for 4 percent of the entire basin. The remaining 6 percent of the basin has a land use of open water or wetlands. Storm and monthly suspended-sediment samples were collected from seven tributaries to Lake Tuscaloosa: North River, Turkey Creek, Binion Creek, Pole Bridge Creek, Tierce Creek, Carroll Creek, and Brush Creek. Suspended-sediment concentrations and streamflow measurements were statistically analyzed to estimate annual suspended-sediment loads and yields from each of these contributing watersheds. Estimated annual suspended-sediment yields in 2009 were 360, 540, and 840 tons per square mile (tons/mi2) at the North River, Turkey Creek, and Carroll Creek streamflow-gaging stations, respectively. Estimated annual suspended-sediment yields in 2010 were 120 and 86 tons/mi2 at the Binion Creek and Pole Bridge Creek streamflow-gaging stations, respectively. Estimated annual suspended-sediment yields in 2011 were 190 and 300 tons/mi2 at the Tierce Creek and Brush Creek streamflow-gaging stations, respectively. The North River watershed at the streamflow-gaging station contributes 53 percent of the drainage area for Lake Tuscaloosa. A previous study in the 1970s analyzed streamflow and historical suspended-sediment samples to estimate a long-term average suspended-sediment yield of 300 tons per year per square mile in the North River watershed. Analysis of data collected in the North River watershed during the 2009 water year (October 2008 to September 2009) estimated a sediment yield of 360 tons/mi2. The North River watershed, a major portion of the Lake Tuscaloosa drainage basin, has not experienced a substantial increase in sedimentation rates. During the 2009 water year, the Turkey Creek watershed (6.16 mi2) and the Carroll Creek watershed (20.9 mi2) produced greater suspended-sediment yields than the North River watershed but contribute a much smaller drainage area to Lake Tuscaloosa. Aerial photography and bathymetric surveys indicate that Carroll Creek has experienced increased sediment deposition in the upstream portions of the channel. Carroll Creek is also the only watershed in the current study that has a substantial percentage (11 percent) of urban

Gazetteer of hydrologic characteristics of streams in Massachusetts; Housatonic River basin

USGS Publications Warehouse

Wandle, S.W.; Lippert, R.G.

1984-01-01

The Housatonic River basin includes streams that drain 504 square miles in western Massachusetts and 30.5 square miles in eastern New York. Drainage areas, using the latest available 1:24,000 scale topographic maps, were computed for the first time for streams draining more than 3 square miles and were recomputed for data-collection sites. Streamflow characteristics for four gaged streams were calculated using a new data base with daily flow records through 1981. These characteristics include annual and monthly flow statistics, duration of daily flow values, and the annual 7-day mean low flow at the 2-year and 10-year recurrence intervals. Seven-day low-flow statistics are presented for 52 partial-record sites, and the procedures used to determine the hydrologic characteristics of the basin are summarized. Basin characteristics representing 14 commonly used indices to estimate various streamflows are provided for selected gaging stations. This gazetteer will aid in the planning and siting of water-resources related activities and will provide a common data base for governmental agencies and the engineering and planning communities. (USGS)

Groundwater recharge in Wisconsin--Annual estimates for 1970-99 using streamflow data

USGS Publications Warehouse

Gebert, Warren A.; Walker, John F.; Hunt, Randall J.

2011-01-01

The groundwater component of streamflow is important because it is indicative of the sustained flow of a stream during dry periods, is often of better quality, and has a smaller range of temperatures, than surface contributions to streamflow. All three of these characteristics are important to the health of aquatic life in a stream. If recharge to the aquifers is to be preserved or enhanced, it is important to understand the present partitioning of total streamflow into base flow and stormflow. Additionally, an estimate of groundwater recharge is important for understanding the flows within a groundwater system-information important for water availability/sustainability or other assessments. The U.S. Geological Survey operates numerous continuous-record streamflow-gaging stations (Hirsch and Norris, 2001), which can be used to provide estimates of average annual base flow. In addition to these continuous record sites, Gebert and others (2007) showed that having a few streamflow measurements in a basin can appreciably reduce the error in a base-flow estimate for that basin. Therefore, in addition to the continuous-record gaging stations, a substantial number of low-flow partial-record sites (6 to 15 discharge measurements) and miscellaneous-measurement sites (1 to 3 discharge measurements) that were operated during 1964-90 throughout the State were included in this work to provide additional insight into spatial distribution of annual base flow and, in turn, groundwater recharge.

Computer programs for describing the recession of ground-water discharge and for estimating mean ground-water recharge and discharge from streamflow records-update

USGS Publications Warehouse

Rutledge, A.T.

1998-01-01

The computer programs included in this report can be used to develop a mathematical expression for recession of ground-water discharge and estimate mean ground-water recharge and discharge. The programs are intended for analysis of the daily streamflow record of a basin where one can reasonably assume that all, or nearly all, ground water discharges to the stream except for that which is lost to riparian evapotranspiration, and where regulation and diversion of flow can be considered to be negligible. The program RECESS determines the master reces-sion curve of streamflow recession during times when all flow can be considered to be ground-water discharge and when the profile of the ground-water-head distribution is nearly stable. The method uses a repetitive interactive procedure for selecting several periods of continuous recession, and it allows for nonlinearity in the relation between time and the logarithm of flow. The program RORA uses the recession-curve displacement method to estimate the recharge for each peak in the streamflow record. The method is based on the change in the total potential ground-water discharge that is caused by an event. Program RORA is applied to a long period of record to obtain an estimate of the mean rate of ground-water recharge. The program PART uses streamflow partitioning to estimate a daily record of base flow under the streamflow record. The method designates base flow to be equal to streamflow on days that fit a requirement of antecedent recession, linearly interpolates base flow for other days, and is applied to a long period of record to obtain an estimate of the mean rate of ground-water discharge. The results of programs RORA and PART correlate well with each other and compare reasonably with results of the corresponding manual method.

Preliminary flood-duration frequency estimates using naturalized streamflow records for the Willamette River Basin, Oregon

USGS Publications Warehouse

Lind, Greg D.; Stonewall, Adam J.

2018-02-13

In this study, “naturalized” daily streamflow records, created by the U.S. Army Corps of Engineers and the Bureau of Reclamation, were used to compute 1-, 3-, 7-, 10-, 15-, 30-, and 60-day annual maximum streamflow durations, which are running averages of daily streamflow for the number of days in each duration. Once the annual maximum durations were computed, the floodduration frequencies could be estimated. The estimated flood-duration frequencies correspond to the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent probabilities of their occurring or being exceeded each year. For this report, the focus was on the Willamette River Basin in Oregon, which is a subbasin of the Columbia River Basin. This study is part of a larger one encompassing the entire Columbia Basin.

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

USGS Publications Warehouse

McCarthy, Peter M.; Dutton, DeAnn M.; Sando, Steven K.; Sando, Roy

2016-04-05

The U.S. Geological Survey (USGS) provides streamflow characteristics and other related information needed by water-resource managers to protect people and property from floods, plan and manage water-resource activities, and protect water quality. Streamflow characteristics provided by the USGS, such as peak-flow and low-flow frequencies for streamflow-gaging stations, are frequently used by engineers, flood forecasters, land managers, biologists, and others to guide their everyday decisions. In addition to providing streamflow characteristics at streamflow-gaging stations, the USGS also develops regional regression equations and drainage area-adjustment methods for estimating streamflow characteristics at locations on ungaged streams. Regional regression equations can be complex and often require users to determine several basin characteristics, which are physical and climatic characteristics of the stream and its drainage basin. Obtaining these basin characteristics for streamflow-gaging stations and ungaged sites traditionally has been time consuming and subjective, and led to inconsistent results.StreamStats is a Web-based geographic information system application that was created by the USGS to provide users with access to an assortment of analytical tools that are useful for water-resource planning and management. StreamStats allows users to easily obtain streamflow and basin characteristics for USGS streamflow-gaging stations and user-selected locations on ungaged streams. The USGS, in cooperation with Montana Department of Transportation, Montana Department of Environmental Quality, and Montana Department of Natural Resources and Conservation, completed a study to develop a StreamStats application for Montana, compute streamflow characteristics at streamflow-gaging stations, and develop regional regression equations to estimate streamflow characteristics at ungaged sites. Chapter A of this Scientific Investigations Report describes the Montana StreamStats application and the datasets, streamflow-gaging stations, streamflow characteristics, and regression equations (as described fully in Chapters B through G of this report) that are used for development of the StreamStats application for Montana.

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

USGS Publications Warehouse

Chang, Heejun; Jung, Il-Won; Steele, Madeline; Gannett, Marshall

2012-01-01

Summer streamflow is a vital water resource for municipal and domestic water supplies, irrigation, salmonid habitat, recreation, and water-related ecosystem services in the Pacific Northwest (PNW) in the United States. This study detects significant negative trends in September absolute streamflow in a majority of 68 stream-gauging stations located on unregulated streams in the PNW from 1958 to 2008. The proportion of March streamflow to annual streamflow increases in most stations over 1,000 m elevation, with a baseflow index of less than 50, while absolute March streamflow does not increase in most stations. The declining trends of September absolute streamflow are strongly associated with seven-day low flow, January–March maximum temperature trends, and the size of the basin (19–7,260 km2), while the increasing trends of the fraction of March streamflow are associated with elevation, April 1 snow water equivalent, March precipitation, center timing of streamflow, and October–December minimum temperature trends. Compared with ordinary least squares (OLS) estimated regression models, spatial error regression and geographically weighted regression (GWR) models effectively remove spatial autocorrelation in residuals. The GWR model results show spatial gradients of local R 2 values with consistently higher local R 2 values in the northern Cascades. This finding illustrates that different hydrologic landscape factors, such as geology and seasonal distribution of precipitation, also influence streamflow trends in the PNW. In addition, our spatial analysis model results show that considering various geographic factors help clarify the dynamics of streamflow trends over a large geographical area, supporting a spatial analysis approach over aspatial OLS-estimated regression models for predicting streamflow trends. Results indicate that transitional rain–snow surface water-dominated basins are likely to have reduced summer streamflow under warming scenarios. Consequently, a better understanding of the relationships among summer streamflow, precipitation, snowmelt, elevation, and geology can help water managers predict the response of regional summer streamflow to global warming.

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....

Technical Brief for the final report presentation for Statistical summaries of selected Iowa streamflow data through September 2013, U.S. Geological Survey Open-File Report 2015-1214, Iowa DOT Research Project TR-669.

DOT National Transportation Integrated Search

2015-01-01

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 a...

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 projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

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.

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.

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, whose statistical properties indicated less flow variability and high magnitudes of low flow, and (2) runoff-dominated rivers, whose statistical properties indicated greater flow variability and lower magnitudes of low flow. A four-cluster classification further classified the runoff-dominated streams into three groups that varied in gradient, elevation, and differences in winter streamflow conditions: high-gradient runoff-dominated rivers, northern runoff-dominated rivers, and southern runoff-dominated rivers. A nine-cluster division indicated that basin size also becomes a distinguishing factor among basins at finer levels of classification. Smaller basins (less than 10 square miles) were classified into different groups than larger basins. A comparison of station classifications indicated that a classification based on multiple hydrologic indices that represent different aspects of the flow regime did not result in the same classification of stations as a classification based on a single type of statistic such as a monthly median. River basins identified by the cluster analysis as having similar hydrologic properties tended to have similar basin and climate characteristics and to be in close proximity to one another. Stations were not classified in the same cluster on the basis of geographic location alone; as a result, boundaries cannot be drawn between geographic regions with similar streamflow characteristics. Rivers with different basin and climate characteristics were classified in different clusters, even if they were in adjacent basins or upstream and downstream within the same basin.

Estimating Flow-Duration and Low-Flow Frequency Statistics for Unregulated Streams in Oregon

USGS Publications Warehouse

Risley, John; Stonewall, Adam J.; Haluska, Tana

2008-01-01

Flow statistical datasets, basin-characteristic datasets, and regression equations were developed to provide decision makers with surface-water information needed for activities such as water-quality regulation, water-rights adjudication, biological habitat assessment, infrastructure design, and water-supply planning and management. The flow statistics, which included annual and monthly period of record flow durations (5th, 10th, 25th, 50th, and 95th percent exceedances) and annual and monthly 7-day, 10-year (7Q10) and 7-day, 2-year (7Q2) low flows, were computed at 466 streamflow-gaging stations at sites with unregulated flow conditions throughout Oregon and adjacent areas of neighboring States. Regression equations, created from the flow statistics and basin characteristics of the stations, can be used to estimate flow statistics at ungaged stream sites in Oregon. The study area was divided into 10 regression modeling regions based on ecological, topographic, geologic, hydrologic, and climatic criteria. In total, 910 annual and monthly regression equations were created to predict the 7 flow statistics in the 10 regions. Equations to predict the five flow-duration exceedance percentages and the two low-flow frequency statistics were created with Ordinary Least Squares and Generalized Least Squares regression, respectively. The standard errors of estimate of the equations created to predict the 5th and 95th percent exceedances had medians of 42.4 and 64.4 percent, respectively. The standard errors of prediction of the equations created to predict the 7Q2 and 7Q10 low-flow statistics had medians of 51.7 and 61.2 percent, respectively. Standard errors for regression equations for sites in western Oregon were smaller than those in eastern Oregon partly because of a greater density of available streamflow-gaging stations in western Oregon than eastern Oregon. High-flow regression equations (such as the 5th and 10th percent exceedances) also generally were more accurate than the low-flow regression equations (such as the 95th percent exceedance and 7Q10 low-flow statistic). The regression equations predict unregulated flow conditions in Oregon. Flow estimates need to be adjusted if they are used at ungaged sites that are regulated by reservoirs or affected by water-supply and agricultural withdrawals if actual flow conditions are of interest. The regression equations are installed in the USGS StreamStats Web-based tool (http://water.usgs.gov/osw/streamstats/index.html, accessed July 16, 2008). StreamStats provides users with a set of annual and monthly flow-duration and low-flow frequency estimates for ungaged sites in Oregon in addition to the basin characteristics for the sites. Prediction intervals at the 90-percent confidence level also are automatically computed.

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.

A stream-gaging network analysis for the 7-day, 10-year annual low flow in New Hampshire streams

USGS Publications Warehouse

Flynn, Robert H.

2003-01-01

The 7-day, 10-year (7Q10) low-flow-frequency statistic is a widely used measure of surface-water availability in New Hampshire. Regression equations and basin-characteristic digital data sets were developed to help water-resource managers determine surface-water resources during periods of low flow in New Hampshire streams. These regression equations and data sets were developed to estimate streamflow statistics for the annual and seasonal low-flow-frequency, and period-of-record and seasonal period-of-record flow durations. generalized-least-squares (GLS) regression methods were used to develop the annual 7Q10 low-flow-frequency regression equation from 60 continuous-record stream-gaging stations in New Hampshire and in neighboring States. In the regression equation, the dependent variables were the annual 7Q10 flows at the 60 stream-gaging stations. The independent (or predictor) variables were objectively selected characteristics of the drainage basins that contribute flow to those stations. In contrast to ordinary-least-squares (OLS) regression analysis, GLS-developed estimating equations account for differences in length of record and spatial correlations among the flow-frequency statistics at the various stations.A total of 93 measurable drainage-basin characteristics were candidate independent variables. On the basis of several statistical parameters that were used to evaluate which combination of basin characteristics contribute the most to the predictive power of the equations, three drainage-basin characteristics were determined to be statistically significant predictors of the annual 7Q10: (1) total drainage area, (2) mean summer stream-gaging station precipitation from 1961 to 90, and (3) average mean annual basinwide temperature from 1961 to 1990.To evaluate the effectiveness of the stream-gaging network in providing regional streamflow data for the annual 7Q10, the computer program GLSNET (generalized-least-squares NETwork) was used to analyze the network by application of GLS regression between streamflow and the climatic and basin characteristics of the drainage basin upstream from each stream-gaging station. Improvement to the predictive ability of the regression equations developed for the network analyses is measured by the reduction in the average sampling-error variance, and can be achieved by collecting additional streamflow data at existing stations. The predictive ability of the regression equations is enhanced even further with the addition of new stations to the network. Continued data collection at unregulated stream-gaging stations with less than 14 years of record resulted in the greatest cost-weighted reduction to the average sampling-error variance of the annual 7Q10 regional regression equation. The addition of new stations in basins with underrepresented values for the independent variables of the total drainage area, average mean annual basinwide temperature, or mean summer stream-gaging station precipitation in the annual 7Q10 regression equation yielded a much greater cost-weighted reduction to the average sampling-error variance than when more data were collected at existing unregulated stations. To maximize the regional information obtained from the stream-gaging network for the annual 7Q10, ranking of the streamflow data can be used to determine whether an active station should be continued or if a new or discontinued station should be activated for streamflow data collection. Thus, this network analysis can help determine the costs and benefits of continuing the operation of a particular station or activating a new station at another location to predict the 7Q10 at ungaged stream reaches. The decision to discontinue an existing station or activate a new station, however, must also consider its contribution to other water-resource analyses such as flood management, water quality, or trends in land use or climatic change.

Evaluation of selected methods for determining streamflow during periods of ice effect

USGS Publications Warehouse

Melcher, Norwood B.; Walker, J.F.

1992-01-01

Seventeen methods for estimating ice-affected streamflow are evaluated for potential use with the U.S. Geological Survey streamflow-gaging station network. The methods evaluated were identified by written responses from U.S. Geological Survey field offices and by a comprehensive literature search. The methods selected and techniques used for applying the methods are described in this report. The methods are evaluated by comparing estimated results with data collected at three streamflow-gaging stations in Iowa during the winter of 1987-88. Discharge measurements were obtained at 1- to 5-day intervals during the ice-affected periods at the three stations to define an accurate baseline record. Discharge records were compiled for each method based on data available, assuming a 6-week field schedule. The methods are classified into two general categories-subjective and analytical--depending on whether individual judgment is necessary for method application. On the basis of results of the evaluation for the three Iowa stations, two of the subjective methods (discharge ratio and hydrographic-and-climatic comparison) were more accurate than the other subjective methods and approximately as accurate as the best analytical method. Three of the analytical methods (index velocity, adjusted rating curve, and uniform flow) could potentially be used at streamflow-gaging stations, where the need for accurate ice-affected discharge estimates justifies the expense of collecting additional field data. One analytical method (ice-adjustment factor) may be appropriate for use at stations with extremely stable stage-discharge ratings and measuring sections. Further research is needed to refine the analytical methods. The discharge-ratio and multiple-regression methods produce estimates of streamflow for varying ice conditions using information obtained from the existing U.S. Geological Survey streamflow-gaging network.

Flood frequency estimates and documented and potential extreme peak discharges in Oklahoma

USGS Publications Warehouse

Tortorelli, Robert L.; McCabe, Lan P.

2001-01-01

Knowledge of the magnitude and frequency of floods is required for the safe and economical design of highway bridges, culverts, dams, levees, and other structures on or near streams; and for flood plain management programs. Flood frequency estimates for gaged streamflow sites were updated, documented extreme peak discharges for gaged and miscellaneous measurement sites were tabulated, and potential extreme peak discharges for Oklahoma streamflow sites were estimated. Potential extreme peak discharges, derived from the relation between documented extreme peak discharges and contributing drainage areas, can provide valuable information concerning the maximum peak discharge that could be expected at a stream site. Potential extreme peak discharge is useful in conjunction with flood frequency analysis to give the best evaluation of flood risk at a site. Peak discharge and flood frequency for selected recurrence intervals from 2 to 500 years were estimated for 352 gaged streamflow sites. Data through 1999 water year were used from streamflow-gaging stations with at least 8 years of record within Oklahoma or about 25 kilometers into the bordering states of Arkansas, Kansas, Missouri, New Mexico, and Texas. These sites were in unregulated basins, and basins affected by regulation, urbanization, and irrigation. Documented extreme peak discharges and associated data were compiled for 514 sites in and near Oklahoma, 352 with streamflow-gaging stations and 162 at miscellaneous measurements sites or streamflow-gaging stations with short record, with a total of 671 measurements.The sites are fairly well distributed statewide, however many streams, large and small, have never been monitored. Potential extreme peak-discharge curves were developed for streamflow sites in hydrologic regions of the state based on documented extreme peak discharges and the contributing drainage areas. Two hydrologic regions, east and west, were defined using 98 degrees 15 minutes longitude as the dividing line.

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.

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.

Sediment transport and evaluation of sediment surrogate ratings in the Kootenai River near Bonners Ferry, Idaho, Water Years 2011–14

USGS Publications Warehouse

Wood, Molly S.; Fosness, Ryan L.; Etheridge, Alexandra B.

2015-12-14

Acoustic surrogate ratings were developed between backscatter data collected using acoustic Doppler velocity meters (ADVMs) and results of suspended-sediment samples. Ratings were successfully fit to various sediment size classes (total, fines, and sands) using ADVMs of different frequencies (1.5 and 3 megahertz). Surrogate ratings also were developed using variations of streamflow and seasonal explanatory variables. The streamflow surrogate ratings produced average annual sediment load estimates that were 8–32 percent higher, depending on site and sediment type, than estimates produced using the acoustic surrogate ratings. The streamflow surrogate ratings tended to overestimate suspended-sediment concentrations and loads during periods of elevated releases from Libby Dam as well as on the falling limb of the streamflow hydrograph. Estimates from the acoustic surrogate ratings more closely matched suspended-sediment sample results than did estimates from the streamflow surrogate ratings during these periods as well as for rating validation samples collected in water year 2014. Acoustic surrogate technologies are an effective means to obtain continuous, accurate estimates of suspended-sediment concentrations and loads for general monitoring and sediment-transport modeling. In the Kootenai River, continued operation of the acoustic surrogate sites and use of the acoustic surrogate ratings to calculate continuous suspended-sediment concentrations and loads will allow for tracking changes in sediment transport over time.

2011 Souris River flood—Will it happen again?

USGS Publications Warehouse

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

2016-09-29

The Souris River Basin is a 61,000 square kilometer basin in the provinces of Saskatchewan and Manitoba and the state of North Dakota. Record setting rains in May and June of 2011 led to record flooding with peak annual streamflow values (762 cubic meters per second [m3/s]) more than twice that of any previously recorded peak streamflow and more than five times the estimated 100 year postregulation streamflow (142 m3/s) at the U.S. Geological Survey (USGS) streamflow-gaging station above Minot, North Dakota. Upstream from Minot, N. Dak., the Souris River is regulated by three reservoirs in Saskatchewan (Rafferty, Boundary, and Alameda) and Lake Darling in North Dakota. During the 2011 flood, the city of Minot, N. Dak., experienced devastating damages with more than 4,000 homes flooded and 11,000 evacuated. As a result, the Souris River Basin Task Force recommended the U.S. Geological Survey (in cooperation with the North Dakota State Water Commission) develop a model for estimating the probabilities of future flooding and drought. The model that was developed took on four parts: (1) looking at past climate, (2) predicting future climate, (3) developing a streamflow model in response to certain climatic variables, and (4) combining future climate estimates with the streamflow model to predict future streamflow events. By taking into consideration historical climate record and trends in basin response to various climatic conditions, it was determined flood risk will remain high in the Souris River Basin until the wet climate state ends.

An intercomparison of approaches for improving operational seasonal streamflow forecasts

NASA Astrophysics Data System (ADS)

Mendoza, Pablo A.; Wood, Andrew W.; Clark, Elizabeth; Rothwell, Eric; Clark, Martyn P.; Nijssen, Bart; Brekke, Levi D.; Arnold, Jeffrey R.

2017-07-01

For much of the last century, forecasting centers around the world have offered seasonal streamflow predictions to support water management. Recent work suggests that the two major avenues to advance seasonal predictability are improvements in the estimation of initial hydrologic conditions (IHCs) and the incorporation of climate information. This study investigates the marginal benefits of a variety of methods using IHCs and/or climate information, focusing on seasonal water supply forecasts (WSFs) in five case study watersheds located in the US Pacific Northwest region. We specify two benchmark methods that mimic standard operational approaches - statistical regression against IHCs and model-based ensemble streamflow prediction (ESP) - and then systematically intercompare WSFs across a range of lead times. Additional methods include (i) statistical techniques using climate information either from standard indices or from climate reanalysis variables and (ii) several hybrid/hierarchical approaches harnessing both land surface and climate predictability. In basins where atmospheric teleconnection signals are strong, and when watershed predictability is low, climate information alone provides considerable improvements. For those basins showing weak teleconnections, custom predictors from reanalysis fields were more effective in forecast skill than standard climate indices. ESP predictions tended to have high correlation skill but greater bias compared to other methods, and climate predictors failed to substantially improve these deficiencies within a trace weighting framework. Lower complexity techniques were competitive with more complex methods, and the hierarchical expert regression approach introduced here (hierarchical ensemble streamflow prediction - HESP) provided a robust alternative for skillful and reliable water supply forecasts at all initialization times. Three key findings from this effort are (1) objective approaches supporting methodologically consistent hindcasts open the door to a broad range of beneficial forecasting strategies; (2) the use of climate predictors can add to the seasonal forecast skill available from IHCs; and (3) sample size limitations must be handled rigorously to avoid over-trained forecast solutions. Overall, the results suggest that despite a rich, long heritage of operational use, there remain a number of compelling opportunities to improve the skill and value of seasonal streamflow predictions.

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

NASA Astrophysics Data System (ADS)

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

2013-10-01

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

Temporal and spatial changes of rainfall and streamflow in the Upper Tekezē-Atbara river basin, Ethiopia

NASA Astrophysics Data System (ADS)

Gebremicael, Tesfay G.; Mohamed, Yasir A.; Zaag, Pieter v.; Hagos, Eyasu Y.

2017-04-01

The Upper Tekezē-Atbara river sub-basin, part of the Nile Basin, is characterized by high temporal and spatial variability of rainfall and streamflow. In spite of its importance for sustainable water use and food security, the changing patterns of streamflow and its association with climate change is not well understood. This study aims to improve the understanding of the linkages between rainfall and streamflow trends and identify possible drivers of streamflow variabilities in the basin. Trend analyses and change-point detections of rainfall and streamflow were analysed using Mann-Kendall and Pettitt tests, respectively, using data records for 21 rainfall and 9 streamflow stations. The nature of changes and linkages between rainfall and streamflow were carefully examined for monthly, seasonal and annual flows, as well as indicators of hydrologic alteration (IHA). The trend and change-point analyses found that 19 of the tested 21 rainfall stations did not show statistically significant changes. In contrast, trend analyses on the streamflow showed both significant increasing and decreasing patterns. A decreasing trend in the dry season (October to February), short season (March to May), main rainy season (June to September) and annual totals is dominant in six out of the nine stations. Only one out of nine gauging stations experienced significant increasing flow in the dry and short rainy seasons, attributed to the construction of Tekezē hydropower dam upstream this station in 2009. Overall, streamflow trends and change-point timings were found to be inconsistent among the stations. Changes in streamflow without significant change in rainfall suggests factors other than rainfall drive the change. Most likely the observed changes in streamflow regimes could be due to changes in catchment characteristics of the basin. Further studies are needed to verify and quantify the hydrological changes shown in statistical tests by identifying the physical mechanisms behind those changes. The findings from this study are useful as a prerequisite for studying the effects of catchment management dynamics on the hydrological variabilities in the basin.

Nitrate in the Mississippi River and its tributaries, 1980 to 2008: Are we making progress?

USGS Publications Warehouse

Sprague, Lori A.; Hirsch, Robert M.; Aulenbach, Brent T.

2011-01-01

Changes in nitrate concentration and flux between 1980 and 2008 at eight sites in the Mississippi River basin were determined using a new statistical method that accommodates evolving nitrate behavior over time and produces flow-normalized estimates of nitrate concentration and flux that are independent of random variations in streamflow. The results show that little consistent progress has been made in reducing riverine nitrate since 1980, and that flow-normalized concentration and flux are increasing in some areas. Flow-normalized nitrate concentration and flux increased between 9 and 76% at four sites on the Mississippi River and a tributary site on the Missouri River, but changed very little at tributary sites on the Ohio, Iowa, and Illinois Rivers. Increases in flow-normalized concentration and flux at the Mississippi River at Clinton and Missouri River at Hermann were more than three times larger than at any other site. The increases at these two sites contributed much of the 9% increase in flow-normalized nitrate flux leaving the Mississippi River basin. At most sites, concentrations increased more at low and moderate streamflows than at high streamflows, suggesting that increasing groundwater concentrations are having an effect on river concentrations.

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

USGS Publications Warehouse

Stogner, Sr., Robert W.

2000-01-01

The Fountain Creek watershed, located in and along the eastern slope of the Front Range section of the southern Rocky Mountains, drains approximately 930 square miles of parts of Teller, El Paso, and Pueblo Counties in eastern Colorado. Streamflow in the watershed is dominated by spring snowmelt runoff and storm runoff during the summer monsoon season. Flooding during the 1990?s has resulted in increased streambank erosion. Property loss and damage associated with flooding and bank erosion has cost area residents, businesses, utilities, municipalities, and State and Federal agencies millions of dollars. Precipitation (4 stations) and streamflow (6 stations) data, aerial photographs, and channel reconnaissance were used to evaluate trends in precipitation and streamflow and changes in channel morphology. Trends were evaluated for pre-1977, post-1976, and period-of-record time periods. Analysis revealed the lack of trend in total annual and seasonal precipitation during the pre-1977 time period. In general, the analysis also revealed the lack of trend in seasonal precipitation for all except the spring season during the post-1976 time period. Trend analysis revealed a significant upward trend in long-term (period of record) total annual and spring precipitation data, apparently due to a change in total annual precipitation throughout the Fountain Creek watershed. During the pre-1977 time period, precipitation was generally below average; during the post- 1976 time period, total annual precipitation was generally above average. During the post- 1976 time period, an upward trend in total annual and spring precipitation was indicated at two stations. Because two of four stations evaluated had upward trends for the post-1976 period and storms that produce the most precipitation are isolated convection storms, it is plausible that other parts of the watershed had upward precipitation trends that could affect trends in streamflow. Also, because of the isolated nature of convection storms that hit some areas of the watershed and not others, it is difficult to draw strong conclusions on relations between streamflow and precipitation. Trends in annual instantaneous peak streamflow, 70th percentile, 90th percentile, maximum daily-mean streamflow (100th percentile), 7-, 14-, and 30-day high daily-mean stream- flow duration, minimum daily-mean streamflow (0th percentile), 10th percentile, 30th percentile, and 7-, 14-, 30-day low daily-mean streamflow duration were evaluated. In general, instantaneous peak streamflow has not changed significantly at most of the stations evaluated. Trend analysis revealed the lack of a significant upward trend in streamflow at all stations for the pre-1977 time period. Trend tests indicated a significant upward trend in high and low daily-mean streamflow statistics for the post-1976 period. Upward trends in high daily-mean streamflow statistics may be an indication that changes in land use within the watershed have increased the rate and magnitude of runoff. Upward trends in low daily-mean 2 Trends in Precipitation and Streamflow and Changes in Stream Morphology in the Fountain Creek Watershed, Colorado, 1939-99 streamflow statistics may be related to changes in water use and management. An analysis of the relation between streamflow and precipitation indicated that changes in water management have had a marked effect on streamflow. Observable change in channel morphology and changes in distribution and density of vegetation varied with magnitude, duration, and frequency of large streamflow events, and increases in the magnitude and duration of low streamflows. Although more subtle, low stream- flows were an important component of day-to-day channel erosion. Substantial changes in channel morphology were most often associated with infrequent large or catastrophic streamflow events that erode streambed and banks, alter stream course, and deposit large amounts of sediment in the flood plain.

Digital-map grids of mean-annual precipitation for 1961-90, and generalized skew coefficients of annual maximum streamflow for Oklahoma

USGS Publications Warehouse

Rea, A.H.; Tortorelli, R.L.

1997-01-01

This digital report contains two digital-map grids of data that were used to develop peak-flow regression equations in Tortorelli, 1997, 'Techniques for estimating peak-streamflow frequency for unregulated streams and streams regulated by small floodwater retarding structures in Oklahoma,' U.S. Geological Survey Water-Resources Investigations Report 97-4202. One data set is a grid of mean annual precipitation, in inches, based on the period 1961-90, for Oklahoma. The data set was derived from the PRISM (Parameter-elevation Regressions on Independent Slopes Model) mean annual precipitation grid for the United States, developed by Daly, Neilson, and Phillips (1994, 'A statistical-topographic model for mapping climatological precipitation over mountainous terrain:' Journal of Applied Meteorology, v. 33, no. 2, p. 140-158). The second data set is a grid of generalized skew coefficients of logarithms of annual maximum streamflow for Oklahoma streams less than or equal to 2,510 square miles in drainage area. This grid of skew coefficients is taken from figure 11 of Tortorelli and Bergman, 1985, 'Techniques for estimating flood peak discharges for unregulated streams and streams regulated by small floodwater retarding structures in Oklahoma,' U.S. Geological Survey Water-Resources Investigations Report 84-4358. To save disk space, the skew coefficient values have been multiplied by 100 and rounded to integers with two significant digits. The data sets are provided in an ASCII grid format.

Low-flow characteristics and flow-duration statistics for selected USGS continuous-record streamgaging stations in North Carolina through 2012

USGS Publications Warehouse

Weaver, J. Curtis

2015-03-12

In 2013, the U.S. Geological Survey, in cooperation with the North Carolina Division of Water Resources, compiled updated low-flow characteristics and flow-duration statistics for selected continuous-record streamgages in North Carolina. The compilation of updated streamflow statistics provides regulators and planners with relevant hydrologic information reflective of the recent droughts, which can be used to better manage the quantity and quality of streams in North Carolina. Streamflow records available through the 2012 water year1 were used to determine the annual (based on climatic year2) and winter 7-day, 10-year (7Q10, W7Q10) low-flow discharges, the 30-day, 2-year (30Q2) low-flow discharge, and the 7-day, 2-year (7Q2) low-flow discharge. Consequently, streamflow records available through March 31, 2012 (or the 2011 climatic year) were used to determine the updated low-flow characteristics. Low-flow characteristics were published for 177 unregulated sites, 56 regulated sites, and 33 sites known or considered to be affected by varying degrees of minor regulation and (or) diversions upstream from the streamgages (266 sites total). The updated 7Q10 discharges were compared for 63 streamgages across North Carolina where (1) long-term streamflow record consisted of 30 or more climatic years of data available as of the 1998 climatic year, and (2) streamflows were not known to be regulated. The 7Q10 discharges did not change for 3 sites, whereas increases and decreases were noted at 5 and 55 sites, respectively. Positive changes (increases) ranged from 4.3 percent (site 362) to 34.1 percent (site 112) with a median of 13.2 percent. Negative percentage changes (decreases) ranged from –3.3 percent (site 514) to –80.0 percent (site 308) with a median of –22.2 percent. The median percentage change for all 63 streamgages was –18.4 percent. Streamflow statistics determined as a part of this compilation included minimum, mean, maximum, and flow-duration statistics of daily mean discharges for categorical periods. Flow-duration statistics based on the daily mean discharge records were compiled in this study for the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles. Flow-duration statistics were determined for each complete water year of record at a streamgage as well as the available period of record (or selected periods if flows were regulated) and selected seasonal, monthly, and calendar day periods. In addition to the streamflow statistics compiled for each of the water years, the number of days the daily mean discharge was at or below the 10th percentile was summed for each water year as well as the number of events during the water year when streamflow was consistently at or below the 10th percentile. All low-flow characteristics for the streamgages were added into the StreamStatsDB, which is a database accessible to users through the recently released USGS StreamStats application for North Carolina. The minimum, mean, maximum, and flow-duration statistics of daily mean discharges based on the available (or selected if regulated flows) period of record were updated in the North Carolina StreamStatsDB. However, for the selected seasonal, monthly, calendar day, and annual water year periods, tab-delimited American Standard Code for Information Interchange (ASCII) tables of the streamflow statistics are available online to users from a link provided in the StreamStats application. 1The annual period from October 1 through September 30, designated by the year in which the period ends. 2The annual period from April 1 through March 31, designated by the year in which the period begins.

Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system

USGS Publications Warehouse

Bera, Maitreyee; Ortel, Terry W.

2018-01-12

The U.S. Geological Survey, in cooperation with DuPage County Stormwater Management Department, is testing a near real-time streamflow simulation system that assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek and West Branch DuPage River drainage basins in DuPage County, Illinois. As part of this effort, the U.S. Geological Survey maintains a database of hourly meteorological and hydrologic data for use in this near real-time streamflow simulation system. Among these data are next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data, which are retrieved from the North Central River Forecasting Center of the National Weather Service. The DuPage County streamflow simulation system uses these quantitative precipitation forecast data to create streamflow predictions for the two simulated drainage basins. This report discusses in detail how these data are processed for inclusion in the Watershed Data Management files used in the streamflow simulation system for the Salt Creek and West Branch DuPage River drainage basins.

Improving Hydrological Simulations by Incorporating GRACE Data for Parameter Calibration

NASA Astrophysics Data System (ADS)

Bai, P.

2017-12-01

Hydrological model parameters are commonly calibrated by observed streamflow data. This calibration strategy is questioned when the modeled hydrological variables of interest are not limited to streamflow. Well-performed streamflow simulations do not guarantee the reliable reproduction of other hydrological variables. One of the reasons is that hydrological model parameters are not reasonably identified. The Gravity Recovery and Climate Experiment (GRACE) satellite-derived total water storage change (TWSC) data provide an opportunity to constrain hydrological model parameterizations in combination with streamflow observations. We constructed a multi-objective calibration scheme based on GRACE-derived TWSC and streamflow observations, with the aim of improving the parameterizations of hydrological models. The multi-objective calibration scheme was compared with the traditional single-objective calibration scheme, which is based only on streamflow observations. Two monthly hydrological models were employed on 22 Chinese catchments with different hydroclimatic conditions. The model evaluation was performed using observed streamflows, GRACE-derived TWSC, and evapotranspiraiton (ET) estimates from flux towers and from the water balance approach. Results showed that the multi-objective calibration provided more reliable TWSC and ET simulations without significant deterioration in the accuracy of streamflow simulations than the single-objective calibration. In addition, the improvements of TWSC and ET simulations were more significant in relatively dry catchments than in relatively wet catchments. This study highlights the importance of including additional constraints besides streamflow observations in the parameter estimation to improve the performances of hydrological models.

A Hydrological Modeling Framework for Flood Risk Assessment for Japan

NASA Astrophysics Data System (ADS)

Ashouri, H.; Chinnayakanahalli, K.; Chowdhary, H.; Sen Gupta, A.

2016-12-01

Flooding has been the most frequent natural disaster that claims lives and imposes significant economic losses to human societies worldwide. Japan, with an annual rainfall of up to approximately 4000 mm is extremely vulnerable to flooding. The focus of this research is to develop a macroscale hydrologic model for simulating flooding toward an improved understanding and assessment of flood risk across Japan. The framework employs a conceptual hydrological model, known as the Probability Distributed Model (PDM), as well as the Muskingum-Cunge flood routing procedure for simulating streamflow. In addition, a Temperature-Index model is incorporated to account for snowmelt and its contribution to streamflow. For an efficient calibration of the model, in terms of computational timing and convergence of the parameters, a set of A Priori parameters is obtained based on the relationships between the model parameters and the physical properties of watersheds. In this regard, we have implemented a particle tracking algorithm and a statistical model which use high resolution Digital Terrain Models to estimate different time related parameters of the model such as time to peak of the unit hydrograph. In addition, global soil moisture and depth data are used to generate A Priori estimation of maximum soil moisture capacity, an important parameter of the PDM model. Once the model is calibrated, its performance is examined during the Typhoon Nabi which struck Japan in September 2005 and caused severe flooding throughout the country. The model is also validated for the extreme precipitation event in 2012 which affected Kyushu. In both cases, quantitative measures show that simulated streamflow depicts good agreement with gauge-based observations. The model is employed to simulate thousands of possible flood events for the entire Japan which makes a basis for a comprehensive flood risk assessment and loss estimation for the flood insurance industry.

Estimating natural monthly streamflows in California and the likelihood of anthropogenic modification

USGS Publications Warehouse

Carlisle, Daren M.; Wolock, David M.; Howard, Jeannette K.; Grantham, Theodore E.; Fesenmyer, Kurt; Wieczorek, Michael

2016-12-12

Because natural patterns of streamflow are a fundamental property of the health of streams, there is a critical need to quantify the degree to which human activities have modified natural streamflows. A requirement for assessing streamflow modification in a given stream is a reliable estimate of flows expected in the absence of human influences. Although there are many techniques to predict streamflows in specific river basins, there is a lack of approaches for making predictions of natural conditions across large regions and over many decades. In this study conducted by the U.S. Geological Survey, in cooperation with The Nature Conservancy and Trout Unlimited, the primary objective was to develop empirical models that predict natural (that is, unaffected by land use or water management) monthly streamflows from 1950 to 2012 for all stream segments in California. Models were developed using measured streamflow data from the existing network of streams where daily flow monitoring occurs, but where the drainage basins have minimal human influences. Widely available data on monthly weather conditions and the physical attributes of river basins were used as predictor variables. Performance of regional-scale models was comparable to that of published mechanistic models for specific river basins, indicating the models can be reliably used to estimate natural monthly flows in most California streams. A second objective was to develop a model that predicts the likelihood that streams experience modified hydrology. New models were developed to predict modified streamflows at 558 streamflow monitoring sites in California where human activities affect the hydrology, using basin-scale geospatial indicators of land use and water management. Performance of these models was less reliable than that for the natural-flow models, but results indicate the models could be used to provide a simple screening tool for identifying, across the State of California, which streams may be experiencing anthropogenic flow modification.

Hydrogeological framework, numerical simulation of groundwater flow, and effects of projected water use and drought for the Beaver-North Canadian River alluvial aquifer, northwestern Oklahoma

USGS Publications Warehouse

Ryter, Derek W.; Correll, Jessica S.

2016-01-14

A hypothetical severe drought was simulated by using aquifer recharge flow rates during the drought year of 2011 for a period of 10 years. All other flows including evapotranspiration and groundwater pumping were set at estimated 2011 rates. The hypothetical drought caused a decrease in water in aquifer storage by about 7 percent in Reach I and 7 percent in Reach II. Another analysis of the effects of hypothetical drought estimated the effects of drought on streamflow and lake storage. The hypothetical drought was simulated by decreasing recharge by 75 percent for a selected 10-year period (1994–2004) during the 1980–2011 simulation. In Reach I, the amounts of water stored in Canton Lake and streamflow at the Seiling, Okla., streamflow-gaging station were analyzed. Streamflow at the Seiling station decreased by a mean of 75 percent and was still diminished by 10 percent after 2011. In Reach II, the effect of drought on the streamflow at the Yukon, Okla., streamflow-gaging station was examined. The greatest mean streamflow decrease was approximately 60 percent during the simulated drought, and after 2011, the mean decrease in streamflow was still about 5 percent. Canton Lake storage decreased by as much as 83 percent during the simulated drought and did not recover by 2011.

Streamflow characteristics from modelled runoff time series: Importance of calibration criteria selection

USGS Publications Warehouse

Poole, Sandra; Vis, Marc; Knight, Rodney; Seibert, Jan

2017-01-01

Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models that were originally calibrated on gauged catchments. However, SFC estimates of the gauged donor catchments and subsequently the ungauged catchments can be substantially uncertain when models are calibrated using traditional approaches based on optimization of statistical performance metrics (e.g., Nash–Sutcliffe model efficiency). An improved calibration strategy for gauged catchments is therefore crucial to help reduce the uncertainties of estimated SFCs for ungauged catchments. The aim of this study was to improve SFC estimates from modeled runoff time series in gauged catchments by explicitly including one or several SFCs in the calibration process. Different types of objective functions were defined consisting of the Nash–Sutcliffe model efficiency, single SFCs, or combinations thereof. We calibrated a bucket-type runoff model (HBV – Hydrologiska Byråns Vattenavdelning – model) for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 ecologically relevant SFCs representing major flow regime components and different flow conditions. While the model generally tended to underestimate the tested SFCs related to mean and high-flow conditions, SFCs related to low flow were generally overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional model efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration, and modeled estimates need to be carefully interpreted.

An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri

USGS Publications Warehouse

Huizinga, Richard J.

2014-01-01

The rainfall-runoff pairs from the storm-specific GUH analysis were further analyzed against various basin and rainfall characteristics to develop equations to estimate the peak streamflow and flood volume based on a quantity of rainfall on the basin.

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)

Bromide, Chloride, and Sulfate Concentrations and Loads at U.S. Geological Survey Streamflow-Gaging Stations 07331600 Red River at Denison Dam, 07335500 Red River at Arthur City, and 07336820 Red River near DeKalb, Texas, 2007-09

USGS Publications Warehouse

Baldys, Stanley; Churchill, Christopher J.; Mobley, Craig A.; Coffman, David K.

2010-01-01

The U.S. Geological Survey, in cooperation with the City of Dallas Water Utilities Division, did a study to characterize bromide, chloride, and sulfate concentrations and loads at three U.S. Geological Survey streamflow-gaging stations on the reach of the Red River from Denison Dam, which impounds Lake Texoma, to the U.S. Highway 259 bridge near DeKalb, Texas. Bromide, chloride, and sulfate concentrations and loads were computed for streamflow-gaging stations on the study reach of the Red River. Continuous streamflow and specific conductance data and discrete samples for bromide, chloride, sulfate, and specific conductance were collected at three main-stem streamflow-gaging stations on the Red River: 07331600 Red River at Denison Dam near Denison, Texas (Denison Dam gage), 07335500 Red River at Arthur City, Texas (Arthur City gage), and 07336820 Red River near DeKalb, Texas (DeKalb gage). At each of these streamflow-gaging stations, discrete water-quality data were collected during January 2007-February 2009; continuous water-quality data were collected during March 2007-February 2009. Two periods of high flow resulted from floods during the study; floods during June-July 2007 resulted in elevated flow during June-September 2007 and smaller floods during March-April 2008 resulted in elevated flow during March-April 2008. Bromide, chloride, and sulfate concentrations in samples collected at the three gages decreased downstream. Median bromide concentrations ranged from 0.32 milligram per liter at the Denison Dam gage to 0.19 milligram per liter at the DeKalb gage. Median chloride concentrations ranged from 176 milligrams per liter at the Denison Dam gage to 108 milligrams per liter at the DeKalb gage, less than the 300-milligrams per liter secondary maximum contaminant level established by the Texas Commission on Environmental Quality. Median sulfate concentrations ranged from 213 milligrams per liter at the Denison Dam gage to 117 milligrams per liter at the DeKalb gage, also less than the 300-milligrams per liter secondary maximum contaminant level. Kruskal-Wallis analyses indicated statistically significant differences among bromide, chloride, and sulfate concentrations at the three gages. Regression equations to estimate bromide, chloride, and sulfate loads were developed for each of the three gages. The largest loads were estimated for a period of relatively large streamflow, June-September 2007, when about 50 percent of the load for the study period occurred at each gage. Adjusted R-squared values were largest for regression equations for the DeKalb gage, ranging from .957 for sulfate to .976 for chloride. Adjusted R-squared values for all regression equations developed to estimate loads of bromide, chloride, and sulfate at the three gages were .899 or larger.

Importance of record length with respect to estimating the 1-percent chance flood

USGS Publications Warehouse

Feaster, Toby D.

2010-01-01

U.S. Geological Survey (USGS) streamflow gages have been established in every State in the Nation, Puerto Rico, and the Trust Territory of the Pacific Islands. From these st reamflow records, estimates of the magnitude and frequency of floods are often developed and used to design transportation and water- conveyance structures to protect lives and property, and to determine flood-insurance rates. Probably the most recognizable flood statistic computed from USGS stream gaging records is the 1- percent (%) chance flood; better known has the 100-year flood. By definition, this is a flood that has a 1% chance of occurring in any given year. The 1% chance flood is a statistical estimate that can be significantly influenced by length of record and extreme flood events captured in that record. Consequently, it is typically recommended that flood statistics be updated on some regular interval such as every 10 years. This paper examines the influence of record length on the 1% chance flood for the Broad River in Georgia and the substantial difference that can occur in the estimate based on record length and the hydrologic conditions under which that record was collected. 

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. The addition of new gaging stations to the network would result in an even greater improvement of the accuracy of the regional regression equations. Typically, continued data collection at stations with unregulated streamflow for all flow conditions that had less than 11 years of record with drainage areas smaller than 200 square miles contributed the largest cost-weighted reduction to the average sampling-error variance of the regional estimating equations. The results of the network analyses can be used to prioritize the continued operation of active gaging stations or the reactivation of discontinued gaging stations if the objective is to maximize the regional information content in the streamflow-gaging station network.

Technique for estimating the 2- to 500-year flood discharges on unregulated streams in rural Missouri

USGS Publications Warehouse

Alexander, Terry W.; Wilson, Gary L.

1995-01-01

A generalized least-squares regression technique was used to relate the 2- to 500-year flood discharges from 278 selected streamflow-gaging stations to statistically significant basin characteristics. The regression relations (estimating equations) were defined for three hydrologic regions (I, II, and III) in rural Missouri. Ordinary least-squares regression analyses indicate that drainage area (Regions I, II, and III) and main-channel slope (Regions I and II) are the only basin characteristics needed for computing the 2- to 500-year design-flood discharges at gaged or ungaged stream locations. The resulting generalized least-squares regression equations provide a technique for estimating the 2-, 5-, 10-, 25-, 50-, 100-, and 500-year flood discharges on unregulated streams in rural Missouri. The regression equations for Regions I and II were developed from stream-flow-gaging stations with drainage areas ranging from 0.13 to 11,500 square miles and 0.13 to 14,000 square miles, and main-channel slopes ranging from 1.35 to 150 feet per mile and 1.20 to 279 feet per mile. The regression equations for Region III were developed from streamflow-gaging stations with drainage areas ranging from 0.48 to 1,040 square miles. Standard errors of estimate for the generalized least-squares regression equations in Regions I, II, and m ranged from 30 to 49 percent.

A national streamflow network gap analysis

USGS Publications Warehouse

Kiang, Julie E.; Stewart, David W.; Archfield, Stacey A.; Osborne, Emily B.; Eng, Ken

2013-01-01

The U.S. Geological Survey (USGS) conducted a gap analysis to evaluate how well the USGS streamgage network meets a variety of needs, focusing on the ability to calculate various statistics at locations that have streamgages (gaged) and that do not have streamgages (ungaged). This report presents the results of analysis to determine where there are gaps in the network of gaged locations, how accurately desired statistics can be calculated with a given length of record, and whether the current network allows for estimation of these statistics at ungaged locations. The analysis indicated that there is variability across the Nation’s streamflow data-collection network in terms of the spatial and temporal coverage of streamgages. In general, the Eastern United States has better coverage than the Western United States. The arid Southwestern United States, Alaska, and Hawaii were observed to have the poorest spatial coverage, using the dataset assembled for this study. Except in Hawaii, these areas also tended to have short streamflow records. Differences in hydrology lead to differences in the uncertainty of statistics calculated in different regions of the country. Arid and semiarid areas of the Central and Southwestern United States generally exhibited the highest levels of interannual variability in flow, leading to larger uncertainty in flow statistics. At ungaged locations, information can be transferred from nearby streamgages if there is sufficient similarity between the gaged watersheds and the ungaged watersheds of interest. Areas where streamgages exhibit high correlation are most likely to be suitable for this type of information transfer. The areas with the most highly correlated streamgages appear to coincide with mountainous areas of the United States. Lower correlations are found in the Central United States and coastal areas of the Southeastern United States. Information transfer from gaged basins to ungaged basins is also most likely to be successful when basin attributes show high similarity. At the scale of the analysis completed in this study, the attributes of basins upstream of USGS streamgages cover the full range of basin attributes observed at potential locations of interest fairly well. Some exceptions included very high or very low elevation areas and very arid areas.

Estimates of Median Flows for Streams on the 1999 Kansas Surface Water Register

USGS Publications Warehouse

Perry, Charles A.; Wolock, David M.; Artman, Joshua C.

2004-01-01

The Kansas State Legislature, by enacting Kansas Statute KSA 82a?2001 et. seq., mandated the criteria for determining which Kansas stream segments would be subject to classification by the State. One criterion for the selection as a classified stream segment is based on the statistic of median flow being equal to or greater than 1 cubic foot per second. As specified by KSA 82a?2001 et. seq., median flows were determined from U.S. Geological Survey streamflow-gaging-station data by using the most-recent 10 years of gaged data (KSA) for each streamflow-gaging station. Median flows also were determined by using gaged data from the entire period of record (all-available hydrology, AAH). Least-squares multiple regression techniques were used, along with Tobit analyses, to develop equations for estimating median flows for uncontrolled stream segments. The drainage area of the gaging stations on uncontrolled stream segments used in the regression analyses ranged from 2.06 to 12,004 square miles. A logarithmic transformation of the data was needed to develop the best linear relation for computing median flows. In the regression analyses, the significant climatic and basin characteristics, in order of importance, were drainage area, mean annual precipitation, mean basin permeability, and mean basin slope. Tobit analyses of KSA data yielded a model standard error of prediction of 0.285 logarithmic units, and the best equations using Tobit analyses of AAH data had a model standard error of prediction of 0.250 logarithmic units. These regression equations and an interpolation procedure were used to compute median flows for the uncontrolled stream segments on the 1999 Kansas Surface Water Register. Measured median flows from gaging stations were incorporated into the regression-estimated median flows along the stream segments where available. The segments that were uncontrolled were interpolated using gaged data weighted according to the drainage area and the bias between the regression-estimated and gaged flow information. On controlled segments of Kansas streams, the median flow information was interpolated between gaging stations using only gaged data weighted by drainage area. Of the 2,232 total stream segments on the Kansas Surface Water Register, 34.5 percent of the segments had an estimated median streamflow of less than 1 cubic foot per second when the KSA analysis was used. When the AAH analysis was used, 36.2 percent of the segments had an estimated median streamflow of less than 1 cubic foot per second. This report supercedes U.S. Geological Survey Water-Resources Investigations Report 02?4292.

Estimating discharge measurement uncertainty using the interpolated variance estimator

USGS Publications Warehouse

Cohn, T.; Kiang, J.; Mason, R.

2012-01-01

Methods for quantifying the uncertainty in discharge measurements typically identify various sources of uncertainty and then estimate the uncertainty from each of these sources by applying the results of empirical or laboratory studies. If actual measurement conditions are not consistent with those encountered in the empirical or laboratory studies, these methods may give poor estimates of discharge uncertainty. This paper presents an alternative method for estimating discharge measurement uncertainty that uses statistical techniques and at-site observations. This Interpolated Variance Estimator (IVE) estimates uncertainty based on the data collected during the streamflow measurement and therefore reflects the conditions encountered at the site. The IVE has the additional advantage of capturing all sources of random uncertainty in the velocity and depth measurements. It can be applied to velocity-area discharge measurements that use a velocity meter to measure point velocities at multiple vertical sections in a channel cross section.

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.

Results of streamflow gain-loss studies in Texas, with emphasis on gains from and losses to major and minor aquifers, Texas, 2000

USGS Publications Warehouse

Slade, Raymond M.; Bentley, J. Taylor; Michaud, Dana

2002-01-01

Data for all 366 known streamflow gain-loss studies conducted by the U.S. Geological Survey in Texas were aggregated. A water-budget equation that includes discharges for main channels, tributaries, return flows, and withdrawals was used to document the channel gain or loss for each of 2,872 subreaches for the studies. The channel gain or loss represents discharge from or recharge to aquifers crossed by the streams. Where applicable, the major or minor aquifer outcrop traversed by each subreach was identified, as was the length and location for each subreach. These data will be used to estimate recharge or discharge for major and minor aquifers in Texas, as needed by the Ground-Water Availability Modeling Program being conducted by the Texas Water Development Board. The data also can be used, along with current flow rates for streamflow-gaging stations, to estimate streamflow at sites remote from gaging stations, including sites where streamflow availability is needed for permitted withdrawals.

Methods used to compute low-flow frequency characteristics for continuous-record streamflow stations in Minnesota, 2006

USGS Publications Warehouse

Winterstein, Thomas A.; Arntson, Allan D.; Mitton, Gregory B.

2007-01-01

The 1-, 7-, and 30-day low-flow series were determined for 120 continuous-record streamflow stations in Minnesota having at least 20 years of continuous record. The 2-, 5-, 10-, 50-, and 100-year statistics were determined for each series by fitting a log Pearson type III distribution to the data. The methods used to determine the low-flow statistics and to construct the plots of the low-flow frequency curves are described. The low-flow series and the low-flow statistics are presented in tables and graphs.

Hawaii StreamStats; a web application for defining drainage-basin characteristics and estimating peak-streamflow statistics

USGS Publications Warehouse

Rosa, Sarah N.; Oki, Delwyn S.

2010-01-01

Reliable estimates of the magnitude and frequency of floods are necessary for the safe and efficient design of roads, bridges, water-conveyance structures, and flood-control projects and for the management of flood plains and flood-prone areas. StreamStats provides a simple, fast, and reproducible method to define drainage-basin characteristics and estimate the frequency and magnitude of peak discharges in Hawaii?s streams using recently developed regional regression equations. StreamStats allows the user to estimate the magnitude of floods for streams where data from stream-gaging stations do not exist. Existing estimates of the magnitude and frequency of peak discharges in Hawaii can be improved with continued operation of existing stream-gaging stations and installation of additional gaging stations for areas where limited stream-gaging data are available.

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 function for the signatures is derived from the likelihood for streamflow (rather than using an "ad-hoc" likelihood for the signatures as done in previous approaches). This likelihood is not easily tractable analytically and we therefore cannot apply "simple" MCMC methods. This numerical problem is solved using Approximate Bayesian Computation (ABC). Our result indicate that the proposed approach is suitable for producing reliable streamflow predictive distributions based on calibration to signature data. Moreover, our results provide indications on which signatures are more appropriate to represent the information content of the hydrograph.

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.

Reduced streamflow lowers dry-season growth of rainbow trout in a small stream

Treesearch

Bret C. Harvey; Rodney J. Nakamoto; Jason L. White

2006-01-01

A wide variety of resource management activities can affect surface discharge in small streams. Often, the effects of variation in streamflow on fish survival and growth can be difficult to estimate because of possible confounding with the effects of other variables, such as water temperature and fish density. We measured the effect of streamflow on survival and growth...

Ordinary kriging as a tool to estimate historical daily streamflow records

USGS Publications Warehouse

Farmer, William H.

2016-01-01

Efficient and responsible management of water resources relies on accurate streamflow records. However, many watersheds are ungaged, limiting the ability to assess and understand local hydrology. Several tools have been developed to alleviate this data scarcity, but few provide continuous daily streamflow records at individual streamgages within an entire region. Building on the history of hydrologic mapping, ordinary kriging was extended to predict daily streamflow time series on a regional basis. Pooling parameters to estimate a single, time-invariant characterization of spatial semivariance structure is shown to produce accurate reproduction of streamflow. This approach is contrasted with a time-varying series of variograms, representing the temporal evolution and behavior of the spatial semivariance structure. Furthermore, the ordinary kriging approach is shown to produce more accurate time series than more common, single-index hydrologic transfers. A comparison between topological kriging and ordinary kriging is less definitive, showing the ordinary kriging approach to be significantly inferior in terms of Nash–Sutcliffe model efficiencies while maintaining significantly superior performance measured by root mean squared errors. Given the similarity of performance and the computational efficiency of ordinary kriging, it is concluded that ordinary kriging is useful for first-order approximation of daily streamflow time series in ungaged watersheds.

Questa baseline and pre-mining ground-water quality investigation. 21. Hydrology and water balance of the Red River basin, New Mexico 1930-2004

USGS Publications Warehouse

Naus, Cheryl A.; McAda, Douglas P.; Myers, Nathan C.

2006-01-01

A study of the hydrology of the Red River Basin of northern New Mexico, including development of a pre- mining water balance, contributes to a greater understanding of processes affecting the flow and chemistry of water in the Red River and its alluvial aquifer. Estimates of mean annual precipitation for the Red River Basin ranged from 22.32 to 25.19 inches. Estimates of evapotranspiration for the Red River Basin ranged from 15.02 to 22.45 inches or 63.23 to 94.49 percent of mean annual precipitation. Mean annual yield from the Red River Basin estimated using regression equations ranged from 45.26 to 51.57 cubic feet per second. Mean annual yield from the Red River Basin estimated by subtracting evapotranspiration from mean annual precipitation ranged from 55.58 to 93.15 cubic feet per second. In comparison, naturalized 1930-2004 mean annual streamflow at the Red River near Questa gage was 48.9 cubic feet per second. Although estimates developed using regression equations appear to be a good representation of yield from the Red River Basin as a whole, the methods that consider evapotranspiration may more accurately represent yield from smaller basins that have a substantial amount of sparsely vegetated scar area. Hydrograph separation using the HYSEP computer program indicated that subsurface flow for 1930-2004 ranged from 76 to 94 percent of streamflow for individual years with a mean of 87 percent of streamflow. By using a chloride mass-balance method, ground-water recharge was estimated to range from 7 to 17 percent of mean annual precipitation for water samples from wells in Capulin Canyon and the Hansen, Hottentot, La Bobita, and Straight Creek Basins and was 21 percent of mean annual precipitation for water samples from the Red River. Comparisons of mean annual basin yield and measured streamflow indicate that streamflow does not consistently increase as cumulative estimated mean annual basin yield increases. Comparisons of estimated mean annual yield and measured streamflow profiles indicates that, in general, the river is gaining ground water from the alluvium in the reach from the town of Red River to between Hottentot and Straight Creeks, and from Columbine Creek to near Thunder Bridge. The river is losing water to the alluvium from upstream of the mill area to Columbine Creek. Interpretations of ground- and surface-water interactions based on comparisons of mean annual basin yield and measured streamflow are supported further with water-level data from piezometers, wells, and the Red River.

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 of adding gaging stations to the network. With the exception of the annual average discharge equation for Southeast Alaska, by adding gaging stations in all three regions, the sampling error was reduced to a greater extent than by not adding gaging stations. The proposed streamflow-gaging network for Alaska consists of 308 gaging stations, of which 32 are designated as index stations. If the proposed network can not be implemented in its entirety, then a lesser cost alternative would be to establish the index stations and to implement the network for a particular region.

Merging Satellite Precipitation Products for Improved Streamflow Simulations

NASA Astrophysics Data System (ADS)

Maggioni, V.; Massari, C.; Barbetta, S.; Camici, S.; Brocca, L.

2017-12-01

Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. Therefore, we propose to merge SM2RAIN and the widely used TMPA 3B42RT product across Italy for a 6-year period (2010-2015) at daily/0.25deg temporal/spatial scale. Two conceptually different merging techniques are compared to each other and evaluated in terms of different statistical metrics, including hit bias, threat score, false alarm rates, and missed rainfall volumes. The first is based on the maximization of the temporal correlation with a reference dataset, while the second is based on a Bayesian approach, which provides a probabilistic satellite precipitation estimate derived from the joint probability distribution of observations and satellite estimates. The merged precipitation products show a better performance with respect to the parental satellite-based products in terms of categorical statistics, as well as bias reduction and correlation coefficient, with the Bayesian approach being superior to other methods. A study case in the Tiber river basin is also presented to discuss the performance of forcing a hydrological model with the merged satellite precipitation product to simulate streamflow time series.

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.

On-line estimation of nonlinear physical systems

USGS Publications Warehouse

Christakos, G.

1988-01-01

Recursive algorithms for estimating states of nonlinear physical systems are presented. Orthogonality properties are rediscovered and the associated polynomials are used to linearize state and observation models of the underlying random processes. This requires some key hypotheses regarding the structure of these processes, which may then take account of a wide range of applications. The latter include streamflow forecasting, flood estimation, environmental protection, earthquake engineering, and mine planning. The proposed estimation algorithm may be compared favorably to Taylor series-type filters, nonlinear filters which approximate the probability density by Edgeworth or Gram-Charlier series, as well as to conventional statistical linearization-type estimators. Moreover, the method has several advantages over nonrecursive estimators like disjunctive kriging. To link theory with practice, some numerical results for a simulated system are presented, in which responses from the proposed and extended Kalman algorithms are compared. ?? 1988 International Association for Mathematical Geology.

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.

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)

Estimates of Glacier Mass Loss and Contribution to Streamflow in the Wind River Range in Wyoming: Case Study

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

Marks, Jeffrey; Piburn, Jesse; Tootle, Glenn

2014-09-11

The Wind River Range is a continuous mountain range, approximately 160 km in length, in west-central Wyoming. The presence of glaciers results in meltwater contributions to streamflow during the late summer (July, August, and September: JAS) when snowmelt is decreasing; temperatures are high; precipitation is low; evaporation rates are high; and municipal, industrial, and irrigation water are at peak demands. Therefore, the quantification of glacier meltwater (e.g., volume and mass) contributions to late summer/early fall streamflow is important, given that this resource is dwindling owing to glacier recession. The current research expands upon previous research efforts and identifies two glaciatedmore » watersheds, one on the east slope (Bull Lake Creek) and one on the west slope (Green River) of the Wind River Range, in which unimpaired streamflow is available from 1966 to 2006. Glaciers were delineated within each watershed and area estimates (with error) were obtained for the years 1966, 1989, and 2006. Glacier volume (mass) loss (with error) was estimated by using empirically based volume-area scaling relationships. For 1966 to 2006, glacier mass contributions to JAS streamflow on the east slope were approximately 8%, whereas those on the west slope were approximately 2%. Furthermore, the volume-area scaling glacier mass estimates compared favorably with measured (stereo pair remote sensed data) estimates of glacier mass change for three glaciers (Teton, Middle Teton, and Teepe) in the nearby Teton Range and one glacier (Dinwoody) in the Wind River Range.« less

Annual trace-metal load estimates and flow-weighted concentrations of cadmium, lead, and zinc in the Spokane River basin, Idaho and Washington, 1999-2004

USGS Publications Warehouse

Donato, Mary M.

2006-01-01

Streamflow and trace-metal concentration data collected at 10 locations in the Spokane River basin of northern Idaho and eastern Washington during 1999-2004 were used as input for the U.S. Geological Survey software, LOADEST, to estimate annual loads and mean flow-weighted concentrations of total and dissolved cadmium, lead, and zinc. Cadmium composed less than 1 percent of the total metal load at all stations; lead constituted from 6 to 42 percent of the total load at stations upstream from Coeur d'Alene Lake and from 2 to 4 percent at stations downstream of the lake. Zinc composed more than 90 percent of the total metal load at 6 of the 10 stations examined in this study. Trace-metal loads were lowest at the station on Pine Creek below Amy Gulch, where the mean annual total cadmium load for 1999-2004 was 39 kilograms per year (kg/yr), the mean estimated total lead load was about 1,700 kg/yr, and the mean annual total zinc load was 14,000 kg/yr. The trace-metal loads at stations on North Fork Coeur d'Alene River at Enaville, Ninemile Creek, and Canyon Creek also were relatively low. Trace-metal loads were highest at the station at Coeur d'Alene River near Harrison. The mean annual total cadmium load was 3,400 kg/yr, the mean total lead load was 240,000 kg/yr, and the mean total zinc load was 510,000 kg/yr for 1999-2004. Trace-metal loads at the station at South Fork Coeur d'Alene River near Pinehurst and the three stations on the Spokane River downstream of Coeur d'Alene Lake also were relatively high. Differences in metal loads, particularly lead, between stations upstream and downstream of Coeur d'Alene Lake likely are due to trapping and retention of metals in lakebed sediments. LOADEST software was used to estimate loads for water years 1999-2001 for many of the same sites discussed in this report. Overall, results from this study and those from a previous study are in good agreement. Observed differences between the two studies are attributable to streamflow differences in the two regression models, 1999-2001 and 1999-2004. Flow-weighted concentrations (FWCs) calculated from the estimated loads for 1999-2004 were examined to aid interpretation of metal load estimates, which were influenced by large spatial and temporal variations in streamflow. FWCs of total cadmium ranged from 0.04 micrograms per liter (?g/L) at Enaville to 14 ?g/L at Ninemile Creek. Total lead FWCs were lowest at Long Lake (1.3 ?g/L) and highest at Ninemile Creek (120 ?g/L). Elevated total lead FWCs at Harrison confirmed that the high total lead loads at this station were not simply due to higher streamflow. Conversely, relatively low total lead loads combined with high total lead FWCs at Ninemile and Canyon Creeks reflected low streamflow but high concentrations of total lead. Very low total lead FWCs (1.3 to 2.7 ?g/L) at the stations downstream of Coeur d'Alene Lake are a result both of deposition of lead-laden sediments in the lake and dilution by additional streamflow. Total zinc FWCs also demonstrated the effect of streamflow on load calculations, and highlighted source areas for zinc in the basin. Total zinc FWCs at Canyon and Ninemile Creeks, 1,600 ?g/L and 2,200 ?g/L, respectively, were by far the highest in the basin but contributed among the lowest total zinc loads due to their relatively low streamflow. Total zinc FWCs ranged from 38 to 67 ?g/L at stations downstream of Coeur d'Alene Lake, but total zinc load estimates at these stations were relatively high because of high mean streamflow compared to other stations in the basin. Long-term regression models for 1991 to 2003 or 2004 were developed and annual trace-metal loads and FWCs were estimated for Pinehurst, Enaville, Harrison, and Post Falls to better understand the variability of metal loading with time. Long-term load estimates are similar to the results for 1999-2004 in terms of spatial distribution of metal loads throughout the basin. LOADEST results for 1991-2004 indicated that statistically significant downward temporal trends for dissolved and total cadmium, dissolved zinc, and total lead were occurring at Pinehurst, Enaville, Harrison, and Post Falls. Additionally, data for Enaville and Post Falls showed significant downward trends for dissolved lead and total zinc loads; Harrison total zinc loads also decreased with time. The Mann-Kendall trend test results agreed with the LOADEST trend results in most cases, but gave contradictory results for total zinc at Pinehurst and at Post Falls. Long- and short-term load and flow-weighted concentration estimates yielded valuable information about metal storage and transport processes, and demonstrated that water quality data are a great aid in understanding these processes.

Methods and equations for estimating peak streamflow per square mile in Virginia’s urban basins

USGS Publications Warehouse

Austin, Samuel H.

2014-01-01

Models are presented that describe Virginia urban area annual peak streamflow per square mile based on basin percent urban area and basin drainage area. Equations are provided to estimate Virginia urban peak flow per square mile of basin drainage area in each of the following annual exceedance probability categories: 0.995, 0.99, 0.95, 0.9, 0.8, 0.67, 0.5, 0.43, 0.2, 0.1, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 1.005, 1.01, 1.05, 1.11, 1.25, 1.49, 2.0, 2.3, 5, 10, 25, 50, 100, 200, and 500 years, respectively). Equations apply to Virginia drainage basins ranging in size from no less than 1.2 mi2 to no more than 2,400 mi2 containing at least 10 percent urban area, and not more than 96 percent urban area. A total of 115 Virginia drainage basins were analyzed. Actual-by-predicted plots and leverage plots for response variables and explanatory variables in each peak-flow annual exceedance probability category indicate robust model fits and significant explanatory power. Equations for 8 of 15 urban peak-flow response surface models yield R-square values greater than 0.8. Relations identified in statistical models, describing significant increases in urban peak stream discharges as basin urban area increases, affirm empirical relations reported in past studies of change in stream discharge, lag times, and physical streamflow processes, most notably those detailed for urban areas in northern Virginia.

Streambed stability and scour potential at selected bridge sites in Michigan

USGS Publications Warehouse

Holtschlag, D.J.; Miller, R.L.

1998-01-01

Contraction scour in the main stream channel at a bridge and local scour near piers and abutments can result in bridge failure. Estimates of contraction-scour and local-scour potentials associated with the 100-year flood were computed for 13 bridge sites in Michigan by use of semi-theoretical equations and procedures recommended by the Federal Highway Administration. These potentials were compared with measures of Streambed stability obtained by use of data from 773 historical streamflow measurements, documenting 20,741 individual Streambed soundings between 1959 and 1995. Analysis of these data indicate small, but statistically significant, monotonic trends in Streambed elevation at 10 sites. No consistent patterns in relations between changes in Streambed elevations and streamflow, flow velocity, or flow depth were evident. Also, estimates of contraction-scour potential were not correlated with measures of Streambed stability, and no differences were detected between measures of Streambed stability in the main channel and stability adjacent to piers. Despite the inconsistencies between measures of Streambed stability and scour potential, data from a single, large flood (greater than a 100-year event) provided field evidence that the relation between scour and streamflow is highly nonlinear. This nonlinearity and the limited availability of measurements of extreme flood events may have reduced the utility of the empirical measures for confirming the nonlinear scour-potential equations and procedures. Results of field surveys using ground-penetrating radar and tuned transducers showed limited ability to aid interpretation of historical scour conditions at four bridge sites. Additional research is needed to confirm the applicability of scour-potential equations for hydrogeologic conditions in Michigan.

Estimates of ground-water recharge, base flow, and stream reach gains and losses in the Willamette River basin, Oregon

USGS Publications Warehouse

Lee, Karl K.; Risley, John C.

2002-03-19

Precipitation-runoff models, base-flow-separation techniques, and stream gain-loss measurements were used to study recharge and ground-water surface-water interaction as part of a study of the ground-water resources of the Willamette River Basin. The study was a cooperative effort between the U.S. Geological Survey and the State of Oregon Water Resources Department. Precipitation-runoff models were used to estimate the water budget of 216 subbasins in the Willamette River Basin. The models were also used to compute long-term average recharge and base flow. Recharge and base-flow estimates will be used as input to a regional ground-water flow model, within the same study. Recharge and base-flow estimates were made using daily streamflow records. Recharge estimates were made at 16 streamflow-gaging-station locations and were compared to recharge estimates from the precipitation-runoff models. Base-flow separation methods were used to identify the base-flow component of streamflow at 52 currently operated and discontinued streamflow-gaging-station locations. Stream gain-loss measurements were made on the Middle Fork Willamette, Willamette, South Yamhill, Pudding, and South Santiam Rivers, and were used to identify and quantify gaining and losing stream reaches both spatially and temporally. These measurements provide further understanding of ground-water/surface-water interactions.

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)

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

USGS Publications Warehouse

Kiah, Richard G.; Stasulis, Nicholas W.

2018-03-08

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

The relationship between groundwater ages, streamflow ages, and storage selection functions under stationary conditions

NASA Astrophysics Data System (ADS)

Berghuijs, W.; Kirchner, J. W.

2017-12-01

Waters in aquifers are often much older than the streamwaters that drain them. Simple physically based reasoning suggests that these age contrasts should be expected wherever catchments are heterogeneous. However, a general quantitative catchment-scale explanation of these age contrasts remains elusive. We show that under stationary conditions conservation of mass and age dictate that the age distribution of water stored in a catchment can be directly estimated from the age distribution of its outflows, and vice versa. This in turn implies that the catchment's preference for the release or retention of waters of different ages can be estimated directly from the age distribution of outflow under stationary conditions. Using simple models of transit times, we show that the mean age of stored water can range from half as old as the mean age of streamflow (for plug flow conditions) to almost infinitely older (for strongly preferential flow). Streamflow age distributions reported in the literature often have long upper tails, consistent with preferential flow and implying that storage ages are substantially older than streamflow ages. Mean streamflow ages reported in the literature imply that most streamflow originates from a thin veneer of total groundwater storage. This preferential release of young streamflow implies that most groundwater is exchanged only slowly with the surface, and consequently must be very old. Where information is available for both storage ages and streamflow ages, our analysis establishes consistency relationships through which each could be used to better constrain the other. By quantifying the relationship between groundwater and streamflow ages, our analysis provides tools to jointly assess both of these important catchment properties.

Methods for estimating streamflow characteristics at ungaged sites in western Montana based on data through water year 2009: Chapter G in Montana StreamStats

USGS Publications Warehouse

McCarthy, Peter M.; Sando, Roy; Sando, Steven K.; Dutton, DeAnn M.

2016-04-05

All of the data used to calculate basin characteristics were derived from publicly available data sources and are available through the U.S. Geological Survey Streamstats program (http://water.usgs.gov/osw/streamstats/) for Montana. The primary purpose of the Montana StreamStats application is to provide estimates of basin characteristics and streamflow characteristics for user-selected ungaged sites on Montana streams. The regional regression equations presented in this report have been loaded to the Montana StreamStats application and can be used to derive streamflow characteristics for ungaged sites.

Simulation of streamflow, evapotranspiration, and groundwater recharge in the lower San Antonio River Watershed, South-Central Texas, 2000-2007

USGS Publications Warehouse

Lizarraga, Joy S.; Ockerman, Darwin J.

2010-01-01

The U.S. Geological Survey (USGS), in cooperation with the San Antonio River Authority, the Evergreen Underground Water Conservation District, and the Goliad County Groundwater Conservation District, configured, calibrated, and tested a watershed model for a study area consisting of about 2,150 square miles of the lower San Antonio River watershed in Bexar, Guadalupe, Wilson, Karnes, DeWitt, Goliad, Victoria, and Refugio Counties in south-central Texas. The model simulates streamflow, evapotranspiration (ET), and groundwater recharge using rainfall, potential ET, and upstream discharge data obtained from National Weather Service meteorological stations and USGS streamflow-gaging stations. Additional time-series inputs to the model include wastewater treatment-plant discharges, withdrawals for cropland irrigation, and estimated inflows from springs. Model simulations of streamflow, ET, and groundwater recharge were done for 2000-2007. Because of the complexity of the study area, the lower San Antonio River watershed was divided into four subwatersheds; separate HSPF models were developed for each subwatershed. Simulation of the overall study area involved running simulations of the three upstream models, then running the downstream model. The surficial geology was simplified as nine contiguous water-budget zones to meet model computational limitations and also to define zones for which ET, recharge, and other water-budget information would be output by the model. The model was calibrated and tested using streamflow data from 10 streamflow-gaging stations; additionally, simulated ET was compared with measured ET from a meteorological station west of the study area. The model calibration is considered very good; streamflow volumes were calibrated to within 10 percent of measured streamflow volumes. During 2000-2007, the estimated annual mean rainfall for the water-budget zones ranged from 33.7 to 38.5 inches per year; the estimated annual mean rainfall for the entire watershed was 34.3 inches. Using the HSPF model it was estimated that for 2000-2007, less than 10 percent of the annual mean rainfall on the study watershed exited the watershed as streamflow, whereas about 82 percent, or an average of 28.2 inches per year, exited the watershed as ET. Estimated annual mean groundwater recharge for the entire study area was 3.0 inches, or about 9 percent of annual mean rainfall. Estimated annual mean recharge was largest in water-budget zone 3, the zone where the Carrizo Sand outcrops. In water-budget zone 3, the estimated annual mean recharge was 5.1 inches or about 15 percent of annual mean rainfall. Estimated annual mean recharge was smallest in water-budget zone 6, about 1.1 inches or about 3 percent of annual mean rainfall. The Cibolo Creek subwatershed and the subwatershed of the San Antonio River upstream from Cibolo Creek had the largest and smallest basin yields, about 4.8 inches and 1.2 inches, respectively. Estimated annual ET and annual recharge generally increased with increasing annual rainfall. Also, ET was larger in zones 8 and 9, the most downstream zones in the watershed. Model limitations include possible errors related to model conceptualization and parameter variability, lack of data to quantify certain model inputs, and measurement errors. Uncertainty regarding the degree to which available rainfall data represent actual rainfall is potentially the most serious source of measurement error.

Statistical Comparisons of watershed scale response to climate change in selected basins across the United States

USGS Publications Warehouse

Risley, John; Moradkhani, Hamid; Hay, Lauren E.; Markstrom, Steve

2011-01-01

In an earlier global climate-change study, air temperature and precipitation data for the entire twenty-first century simulated from five general circulation models were used as input to precalibrated watershed models for 14 selected basins across the United States. Simulated daily streamflow and energy output from the watershed models were used to compute a range of statistics. With a side-by-side comparison of the statistical analyses for the 14 basins, regional climatic and hydrologic trends over the twenty-first century could be qualitatively identified. Low-flow statistics (95% exceedance, 7-day mean annual minimum, and summer mean monthly streamflow) decreased for almost all basins. Annual maximum daily streamflow also decreased in all the basins, except for all four basins in California and the Pacific Northwest. An analysis of the supply of available energy and water for the basins indicated that ratios of evaporation to precipitation and potential evapotranspiration to precipitation for most of the basins will increase. Probability density functions (PDFs) were developed to assess the uncertainty and multimodality in the impact of climate change on mean annual streamflow variability. Kolmogorov?Smirnov tests showed significant differences between the beginning and ending twenty-first-century PDFs for most of the basins, with the exception of four basins that are located in the western United States. Almost none of the basin PDFs were normally distributed, and two basins in the upper Midwest had PDFs that were extremely dispersed and skewed.

Application of ANN and fuzzy logic algorithms for streamflow modelling of Savitri catchment

NASA Astrophysics Data System (ADS)

Kothari, Mahesh; Gharde, K. D.

2015-07-01

The streamflow prediction is an essentially important aspect of any watershed modelling. The black box models (soft computing techniques) have proven to be an efficient alternative to physical (traditional) methods for simulating streamflow and sediment yield of the catchments. The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years (1992-2011) rainfall and other hydrological data were considered, of which 13 years (1992-2004) was for training and rest 7 years (2005-2011) for validation of the models. The mode performance was evaluated by R, RMSE, EV, CE, and MAD statistical parameters. It was found that, ANN model performance improved with increasing input vectors. The results with fuzzy logic models predict the streamflow with single input as rainfall better in comparison to multiple input vectors. While comparing both ANN and FL algorithms for prediction of streamflow, ANN model performance is quite superior.

Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Red River of the North, Fargo, North Dakota, 2003-05

USGS Publications Warehouse

Ryberg, Karen R.

2006-01-01

This report presents the results of a study by the U.S. Geological Survey, done in cooperation with the Bureau of Reclamation, U.S. Department of the Interior, to estimate water-quality constituent concentrations in the Red River of the North at Fargo, North Dakota. Regression analysis of water-quality data collected in 2003-05 was used to estimate concentrations and loads for alkalinity, dissolved solids, sulfate, chloride, total nitrite plus nitrate, total nitrogen, total phosphorus, and suspended sediment. The explanatory variables examined for regression relation were continuously monitored physical properties of water-streamflow, specific conductance, pH, water temperature, turbidity, and dissolved oxygen. For the conditions observed in 2003-05, streamflow was a significant explanatory variable for all estimated constituents except dissolved solids. pH, water temperature, and dissolved oxygen were not statistically significant explanatory variables for any of the constituents in this study. Specific conductance was a significant explanatory variable for alkalinity, dissolved solids, sulfate, and chloride. Turbidity was a significant explanatory variable for total phosphorus and suspended sediment. For the nutrients, total nitrite plus nitrate, total nitrogen, and total phosphorus, cosine and sine functions of time also were used to explain the seasonality in constituent concentrations. The regression equations were evaluated using common measures of variability, including R2, or the proportion of variability in the estimated constituent explained by the regression equation. R2 values ranged from 0.703 for total nitrogen concentration to 0.990 for dissolved-solids concentration. The regression equations also were evaluated by calculating the median relative percentage difference (RPD) between measured constituent concentration and the constituent concentration estimated by the regression equations. Median RPDs ranged from 1.1 for dissolved solids to 35.2 for total nitrite plus nitrate. Regression equations also were used to estimate daily constituent loads. Load estimates can be used by water-quality managers for comparison of current water-quality conditions to water-quality standards expressed as total maximum daily loads (TMDLs). TMDLs are a measure of the maximum amount of chemical constituents that a water body can receive and still meet established water-quality standards. The peak loads generally occurred in June and July when streamflow also peaked.

Flood of March 1997 in southern Ohio

USGS Publications Warehouse

Jackson, K.S.; Vivian, S.A.; Diam, F.J.; Crecelius, C.J.

1997-01-01

Rainfall amounts of up to 12 inches produced by thunderstorms during March 1-2, 1997 resulted in severe flooding throughout much of southern Ohio. Eighteen counties were declared Federal and State disaster areas. Cost estimates of damage in Ohio from the flooding are nearly $180 million. About 6,500 residences and more than 800 businesses were affected by flooding. Nearly 20,000 persons were evacuated, and 5 deaths were attributed to the flooding. Record peak stage and streamflow were recorded at U.S. Geological Survey (USGS) streamflow-gaging stations on Ohio Brush Creek near West Union and Shade River near Chester. The peak streamflow at these two locations exceeded the estimate of the 100-year-recurrence- interval peak streamflow. The recurrence intervals of peak stream flow at selected USGS streamflow gaging stations throughout southern Ohio ranged from less than 2 years to greater than 100 years. The most severe flooding in the State was generally confined to areas within 50 to 70 miles of the Ohio River. Many communities along the Ohio River experienced the worst flooding in more than 30 years.

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.

Method for estimating spatially variable seepage loss and hydraulic conductivity in intermittent and ephemeral streams

USGS Publications Warehouse

Niswonger, R.G.; Prudic, David E.; Fogg, G.E.; Stonestrom, David A.; Buckland, E.M.

2008-01-01

A method is presented for estimating seepage loss and streambed hydraulic conductivity along intermittent and ephemeral streams using streamflow front velocities in initially dry channels. The method uses the kinematic wave equation for routing streamflow in channels coupled to Philip's equation for infiltration. The coupled model considers variations in seepage loss both across and along the channel. Water redistribution in the unsaturated zone is also represented in the model. Sensitivity of the streamflow front velocity to parameters used for calculating seepage loss and for routing streamflow shows that the streambed hydraulic conductivity has the greatest sensitivity for moderate to large seepage loss rates. Channel roughness, geometry, and slope are most important for low seepage loss rates; however, streambed hydraulic conductivity is still important for values greater than 0.008 m/d. Two example applications are presented to demonstrate the utility of the method.

Travel Times, Streamflow Velocities, and Dispersion Rates in the Yellowstone River, Montana

USGS Publications Warehouse

McCarthy, Peter M.

2009-01-01

The Yellowstone River is a vital natural resource to the residents of southeastern Montana and is a primary source of water for irrigation and recreation and the primary source of municipal water for several cities. The Yellowstone River valley is the primary east-west transportation corridor through southern Montana. This complex of infrastructure makes the Yellowstone River especially vulnerable to accidental spills from various sources such as tanker cars and trucks. In 2008, the U.S. Geological Survey (USGS), in cooperation with the Montana Department of Environmental Quality, initiated a dye-tracer study to determine instream travel times, streamflow velocities, and dispersion rates for the Yellowstone River from Lockwood to Glendive, Montana. The purpose of this report is to describe the results of this study and summarize data collected at each of the measurement sites between Lockwood and Glendive. This report also compares the results of this study to estimated travel times from a transport model developed by the USGS for a previous study. For this study, Rhodamine WT dye was injected at four locations in late September and early October 2008 during reasonably steady streamflow conditions. Streamflows ranged from 3,490 to 3,770 cubic feet per second upstream from the confluence of the Bighorn River and ranged from 6,520 to 7,570 cubic feet per second downstream from the confluence of the Bighorn River. Mean velocities were calculated for each subreach between measurement sites for the leading edge, peak concentration, centroid, and trailing edge at 10 percent of the peak concentration. Calculated velocities for the centroid of the dye plume for subreaches that were completely laterally mixed ranged from 1.83 to 3.18 ft/s within the study reach from Lockwood Bridge to Glendive Bridge. The mean of the completely mixed centroid velocity for the entire study reach, excluding the subreach between Forsyth Bridge and Cartersville Dam, was 2.80 ft/s. Longitudinal dispersion rates of the dye plume for this study ranged from 0.06 ft/s for the subreach upstream from Forsyth Bridge to 2.25 ft/s for the subreach upstream from Calyspo Bridge for subreaches where the dye was completely laterally mixed. A relation was determined between travel time of the peak concentration and time for the dye plume to pass a site (duration). This relation can be used to estimate when the receding concentration of a potential contaminant reaches 10 percent of its peak concentration for accidental spills into the Yellowstone River. Data from this dye-tracer study were used to evaluate velocity and concentration estimates from a transport model developed as part of an earlier USGS study. Comparison of the estimated and calculated velocities for the study reach indicate that the transport model estimates the velocities of the Yellowstone River between Huntley Bridge and Glendive Bridge with reasonable accuracy. Velocities of the peak concentration of the dye plume calculated for this study averaged 10 percent faster than the most probable velocities and averaged 12 percent slower than the maximum probable velocities estimated from the transport model. Peak Rhodamine WT dye concentrations were consistently lower than the transport model estimates except for the most upstream subreach of each dye injection. The most upstream subreach of each dye injection is expected to have a higher concentration because of incomplete lateral mixing. Lower measured peak concentrations for all other sites were expected because Rhodamine WT dye deteriorates when exposed to sunlight and will sorb onto the streambanks and stream bottom. Velocity-streamflow relations developed by using routine streamflow measurements at USGS gaging stations and the transport model can be used to estimate mean streamflow velocities throughout a range of streamflows. The variation in these velocity-streamflow relations emphasizes the uncertainty in estimating the mean streamflow veloc

Evaluating the performance of real-time streamflow forecasting using multi-satellite precipitation products in the Upper Zambezi, Africa

NASA Astrophysics Data System (ADS)

Demaria, E. M.; Valdes, J. B.; Wi, S.; Serrat-Capdevila, A.; Valdés-Pineda, R.; Durcik, M.

2016-12-01

In under-instrumented basins around the world, accurate and timely forecasts of river streamflows have the potential of assisting water and natural resource managers in their management decisions. The Upper Zambezi river basin is the largest basin in southern Africa and its water resources are critical to sustainable economic growth and poverty reduction in eight riparian countries. We present a real-time streamflow forecast for the basin using a multi-model-multi-satellite approach that allows accounting for model and input uncertainties. Three distributed hydrologic models with different levels of complexity: VIC, HYMOD_DS, and HBV_DS are setup at a daily time step and a 0.25 degree spatial resolution for the basin. The hydrologic models are calibrated against daily observed streamflows at the Katima-Mulilo station using a Genetic Algorithm. Three real-time satellite products: Climate Prediction Center's morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Tropical Rainfall Measuring Mission (TRMM-3B42RT) are bias-corrected with daily CHIRPS estimates. Uncertainty bounds for predicted flows are estimated with the Inverse Variance Weighting method. Because concentration times in the basin range from a few days to more than a week, we include the use of precipitation forecasts from the Global Forecasting System (GFS) to predict daily streamflows in the basin with a 10-days lead time. The skill of GFS-predicted streamflows is evaluated and the usefulness of the forecasts for short term water allocations is presented.

Comparison of base flows to selected streamflow statistics representative of 1930-2002 in West Virginia

USGS Publications Warehouse

Wiley, Jeffrey B.

2012-01-01

Base flows were compared with published streamflow statistics to assess climate variability and to determine the published statistics that can be substituted for annual and seasonal base flows of unregulated streams in West Virginia. The comparison study was done by the U.S. Geological Survey, in cooperation with the West Virginia Department of Environmental Protection, Division of Water and Waste Management. The seasons were defined as winter (January 1-March 31), spring (April 1-June 30), summer (July 1-September 30), and fall (October 1-December 31). Differences in mean annual base flows for five record sub-periods (1930-42, 1943-62, 1963-69, 1970-79, and 1980-2002) range from -14.9 to 14.6 percent when compared to the values for the period 1930-2002. Differences between mean seasonal base flows and values for the period 1930-2002 are less variable for winter and spring, -11.2 to 11.0 percent, than for summer and fall, -47.0 to 43.6 percent. Mean summer base flows (July-September) and mean monthly base flows for July, August, September, and October are approximately equal, within 7.4 percentage points of mean annual base flow. The mean of each of annual, spring, summer, fall, and winter base flows are approximately equal to the annual 50-percent (standard error of 10.3 percent), 45-percent (error of 14.6 percent), 75-percent (error of 11.8 percent), 55-percent (error of 11.2 percent), and 35-percent duration flows (error of 11.1 percent), respectively. The mean seasonal base flows for spring, summer, fall, and winter are approximately equal to the spring 50- to 55-percent (standard error of 6.8 percent), summer 45- to 50-percent (error of 6.7 percent), fall 45-percent (error of 15.2 percent), and winter 60-percent duration flows (error of 8.5 percent), respectively. Annual and seasonal base flows representative of the period 1930-2002 at unregulated streamflow-gaging stations and ungaged locations in West Virginia can be estimated using previously published values of statistics and procedures.

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 methods applied here advance the understanding of the mechanisms and timing responsible for moisture transport to the Elqui Valley and provide a unique application of streamflow forecasting in the prediction of water right allocations.

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 regional-regression equations and when eastern Colorado was divided into two separate hydrologic regions. To make further reductions in the uncertainties of the peak-streamflow regional-regression equations in the Foothills and Plains hydrologic regions, additional streamgages or crest-stage gages are needed to collect peak-streamflow data on natural streams in eastern Colorado.Generalized-Least Squares regression was used to compute the final peak-streamflow regional-regression equations for peak-streamflow. Dividing eastern Colorado into two new individual regions at –104° longitude resulted in peak-streamflow regional-regression equations with the smallest SEP. The new hydrologic region located between –104° longitude and the Kansas-Nebraska State line will be designated the Plains hydrologic region and the hydrologic region comprising the rest of eastern Colorado located west of the –104° longitude and east of the Rocky Mountains and below 7,500 feet in the South Platte River Basin and below 9,000 feet in the Arkansas River Basin will be designated the Foothills hydrologic region.

Using water-quality profiles to characterize seasonal water quality and loading in the upper Animas River basin, southwestern Colorado

USGS Publications Warehouse

Leib, Kenneth J.; Mast, M. Alisa; Wright, Winfield G.

2003-01-01

One of the important types of information needed to characterize water quality in streams affected by historical mining is the seasonal pattern of toxic trace-metal concentrations and loads. Seasonal patterns in water quality are estimated in this report using a technique called water-quality profiling. Water-quality profiling allows land managers and scientists to assess priority areas to be targeted for characterization and(or) remediation by quantifying the timing and magnitude of contaminant occurrence. Streamflow and water-quality data collected at 15 sites in the upper Animas River Basin during water years 1991?99 were used to develop water-quality profiles. Data collected at each sampling site were used to develop ordinary least-squares regression models for streamflow and constituent concentrations. Streamflow was estimated by correlating instantaneous streamflow measured at ungaged sites with continuous streamflow records from streamflow-gaging stations in the subbasin. Water-quality regression models were developed to estimate hardness and dissolved cadmium, copper, and zinc concentrations based on streamflow and seasonal terms. Results from the regression models were used to calculate water-quality profiles for streamflow, constituent concentrations, and loads. Quantification of cadmium, copper, and zinc loads in a stream segment in Mineral Creek (sites M27 to M34) was presented as an example application of water-quality profiling. The application used a method of mass accounting to quantify the portion of metal loading in the segment derived from uncharacterized sources during different seasonal periods. During May, uncharacterized sources contributed nearly 95 percent of the cadmium load, 0 percent of the copper load (or uncharacterized sources also are attenuated), and about 85 percent of the zinc load at M34. During September, uncharacterized sources contributed about 86 percent of the cadmium load, 0 percent of the copper load (or uncharacterized sources also are attenuated), and about 52 percent of the zinc load at M34. Characterized sources accounted for more of the loading gains estimated in the example reach during September, possibly indicating the presence of diffuse inputs during snowmelt runoff. The results indicate that metal sources in the upper Animas River Basin may change substantially with season, regardless of the source.

Daily Streamflow Predictions in an Ungauged Watershed in Northern California Using the Precipitation-Runoff Modeling System (PRMS): Calibration Challenges when nearby Gauged Watersheds are Hydrologically Dissimilar

NASA Astrophysics Data System (ADS)

Dhakal, A. S.; Adera, S.

2017-12-01

Accurate daily streamflow prediction in ungauged watersheds with sparse information is challenging. The ability of a hydrologic model calibrated using nearby gauged watersheds to predict streamflow accurately depends on hydrologic similarities between the gauged and ungauged watersheds. This study examines daily streamflow predictions using the Precipitation-Runoff Modeling System (PRMS) for the largely ungauged San Antonio Creek watershed, a 96 km2 sub-watershed of the Alameda Creek watershed in Northern California. The process-based PRMS model is being used to improve the accuracy of recent San Antonio Creek streamflow predictions generated by two empirical methods. Although San Antonio Creek watershed is largely ungauged, daily streamflow data exists for hydrologic years (HY) 1913 - 1930. PRMS was calibrated for HY 1913 - 1930 using streamflow data, modern-day land use and PRISM precipitation distribution, and gauged precipitation and temperature data from a nearby watershed. The PRMS model was then used to generate daily streamflows for HY 1996-2013, during which the watershed was ungauged, and hydrologic responses were compared to two nearby gauged sub-watersheds of Alameda Creek. Finally, the PRMS-predicted daily flows between HY 1996-2013 were compared to the two empirically-predicted streamflow time series: (1) the reservoir mass balance method and (2) correlation of historical streamflows from 80 - 100 years ago between San Antonio Creek and a nearby sub-watershed located in Alameda Creek. While the mass balance approach using reservoir storage and transfers is helpful for estimating inflows to the reservoir, large discrepancies in daily streamflow estimation can arise. Similarly, correlation-based predicted daily flows which rely on a relationship from flows collected 80-100 years ago may not represent current watershed hydrologic conditions. This study aims to develop a method of streamflow prediction in the San Antonio Creek watershed by examining PRMS's model outputs as well as empirically generated flow data for their use in water resources management decisions. PRMS is also being used to better understand the streamflow patterns in the San Antonio Creek watershed for a variety of antecedent soil moisture conditions as the creek is generally dry between late Spring and early Fall.

STREAMFLOW LOSSES IN THE SANTA CRUZ RIVER, ARIZONA.

USGS Publications Warehouse

Aldridge, B.N.

1985-01-01

The discharge and volume of flow in a peak decrease as the peak moves through an 89-mile (143 km) reach of the Santa Cruz River. An average of three peaks per year flow the length of the reach. Of 17,500 acre-ft (21,600 dam**3) that entered the upstream end of the reach, 2300 acre-ft (2,840 dam**3), 13 percent of the inflow, left the reach as streamflow. The remainder was lost through infiltration. Losses in a reach of channel were estimated by relating losses to the discharge at the upstream end of the reach. Tributary inflow was estimated through the use of synthesized duration curves. Streamflow losses along mountain fronts were estimated through the use of an electric analog model and by relating losses shown by the model to the median altitude of the contributing area.

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)

Water-quality data for the Clark Fork and selected tributaries from Deer Lodge to Milltown, Montana, March 1985 through June 1986

USGS Publications Warehouse

Lambing, J.H.

1987-01-01

A sampling program was conducted at six stream sites. The purpose of the study was to collect baseline data on concentrations of suspended sediment and selected trace metals in streamflow. Included in this report are tables of daily data for mean streamflow, suspended sediment concentration, and suspended sediment discharge at two streamflow gaging stations on the Clark Fork; periodic data for instantaneous streamflow, onsite water quality, and trace metal and suspended sediment concentrations in the Clark Fork and tributaries; and summary statistics for all the water quality data. Also included are graphs for each site showing median concentrations of trace metals, relationship of concentrations of trace metals to suspended sediment, and median concentrations of trace metals in suspended sediments. Hydrographs for two sites on the main stem show daily mean streamflow, suspended sediment concentration, and suspended sediment discharge for the period of study. (Author 's abstract)

Methods for estimating selected spring and fall low-flow frequency statistics for ungaged stream sites in Iowa, based on data through June 2014

USGS Publications Warehouse

Eash, David A.; Barnes, Kimberlee K.; O'Shea, Padraic S.

2016-09-19

A statewide study was led to develop regression equations for estimating three selected spring and three selected fall low-flow frequency statistics for ungaged stream sites in Iowa. The estimation equations developed for the six low-flow frequency statistics include spring (April through June) 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years and fall (October through December) 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years. Estimates of the three selected spring statistics are provided for 241 U.S. Geological Survey continuous-record streamgages, and estimates of the three selected fall statistics are provided for 238 of these streamgages, using data through June 2014. Because only 9 years of fall streamflow record were available, three streamgages included in the development of the spring regression equations were not included in the development of the fall regression equations. Because of regulation, diversion, or urbanization, 30 of the 241 streamgages were not included in the development of the regression equations. The study area includes Iowa and adjacent areas within 50 miles of the Iowa border. Because trend analyses indicated statistically significant positive trends when considering the period of record for most of the streamgages, the longest, most recent period of record without a significant trend was determined for each streamgage for use in the study. Geographic information system software was used to measure 63 selected basin characteristics for each of the 211streamgages used to develop the regional regression equations. The study area was divided into three low-flow regions that were defined in a previous study for the development of regional regression equations.Because several streamgages included in the development of regional regression equations have estimates of zero flow calculated from observed streamflow for selected spring and fall low-flow frequency statistics, the final equations for the three low-flow regions were developed using two types of regression analyses—left-censored and generalized-least-squares regression analyses. A total of 211 streamgages were included in the development of nine spring regression equations—three equations for each of the three low-flow regions. A total of 208 streamgages were included in the development of nine fall regression equations—three equations for each of the three low-flow regions. A censoring threshold was used to develop 15 left-censored regression equations to estimate the three fall low-flow frequency statistics for each of the three low-flow regions and to estimate the three spring low-flow frequency statistics for the southern and northwest regions. For the northeast region, generalized-least-squares regression was used to develop three equations to estimate the three spring low-flow frequency statistics. For the northeast region, average standard errors of prediction range from 32.4 to 48.4 percent for the spring equations and average standard errors of estimate range from 56.4 to 73.8 percent for the fall equations. For the northwest region, average standard errors of estimate range from 58.9 to 62.1 percent for the spring equations and from 83.2 to 109.4 percent for the fall equations. For the southern region, average standard errors of estimate range from 43.2 to 64.0 percent for the spring equations and from 78.1 to 78.7 percent for the fall equations.The regression equations are applicable only to stream sites in Iowa with low flows not substantially affected by regulation, diversion, or urbanization and with basin characteristics within the range of those used to develop the equations. The regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system application. StreamStats allows users to click on any ungaged stream site and compute estimates of the six selected spring and fall low-flow statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged site are provided. StreamStats also allows users to click on any Iowa streamgage to obtain computed estimates for the six selected spring and fall low-flow statistics.

Application of a stream-aquifer model to Monument Creek for development of a method to estimate transit losses for reusable water, El Paso County, Colorado

USGS Publications Warehouse

Kuhn, Gerhard; Arnold, L. Rick

2006-01-01

The U.S. Geological Survey, in cooperation with Colorado Springs Utilities, the Colorado Water Conservation Board, and the El Paso County Water Authority, began a study in 2004 to (1) apply a stream-aquifer model to Monument Creek, (2) use the results of the modeling to develop a transit-loss accounting program for Monument Creek, (3) revise the existing transit-loss accounting program for Fountain Creek to incorporate new water-management strategies and allow for incorporation of future changes in water-management strategies, and (4) integrate the two accounting programs into a single program with a Web-based user interface. The purpose of this report is to present the results of applying a stream-aquifer model to the Monument Creek study reach.Transit losses were estimated for reusable-water flows in Monument Creek that ranged from 1 to 200 cubic feet per second (ft3/s) and for native streamflows that ranged from 0 to 1,000 ft3/s. Transit losses were estimated for bank-storage, channel-storage, and evaporative losses. The same stream-aquifer model used in the previously completed (1988) Fountain Creek study was used in the Monument Creek study.Sixteen model nodes were established for the Monument Creek study reach, defining 15 subreaches. Channel length, aquifer length, and aquifer width for the subreaches were estimated from available topographic and geologic maps. Thickness of alluvial deposits and saturated thickness were estimated using lithologic and water-level data from about 100 wells and test holes in or near the Monument Creek study reach. Estimated average transmissivities for the subreaches ranged from 2,000 to 12,000 feet squared per day, and a uniform value of 0.20 was used for storage coefficient.Qualitative comparison of recorded and simulated streamflow at the downstream node for the calibration and verification simulations indicated that the two streamflows compared reasonably well. No adjustments were made to the model parameters. Differences between recorded and simulated streamflow volumes for all calibration and verification simulations ranged from about –8.8 to 7.5 percent; the total error for all simulations was about –0.7 percent.The model was used to estimate bank-storage losses for 10 to 15 native streamflows for each reusable-water flow of 1, 3, 5, 7, 10, 15, 20, 30, 40, 50, 100, and 200 ft3/s. Then the 10 to 15 bank-storage loss values were used in least-squares linear regression to estimate a relation between bank-storage loss and native streamflow for each of the 12 reusable-water flow rates. The 12 regression relations then were used to develop “look-up” tables of bank-storage loss for reusable-water flows ranging from 1 to 200 ft3/s (in 1-ft3/s increments). Additional model simulations indicated that (1) when the ratio of downstream native streamflow to upstream native streamflow was less than 1, bank-storage loss generally increased and (2) when the ratio of downstream native streamflow to upstream native streamflow was larger than 1, bank-storage loss generally decreased. These results were used to develop a bank-storage loss adjustment factor based on the ratio of native streamflow at the downstream node to native streamflow at the upstream node. The model also was used to estimate a recovery period, which is the length of time needed for the bank-storage loss to return to the stream. The recovery period was 1 day for six subreaches; 2 days for four subreaches; between 3 and 12 days for four subreaches; and 28 days for one subreach.Channel-storage losses are about 10 percent of the reusable-water flow for most of the subreaches, except for two subreaches, where the channel-storage losses are about 20 percent, and one subreach, where the losses are about 30 percent, owing to the greater channel lengths. Evaporative losses were estimated by the use of monthly pan-evaporation data and the incremental increase in stream width resulting from any reusable-water flows. Monthly pan-evaporation data were converted to a daily rate. The daily rate, when multiplied by the stream-width increase (in feet) that results from reusable-water flow and by the subreach length (in miles) gives the daily evaporative loss in cubic feet per second.

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.

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.

IOD and ENSO impacts on the extreme stream-flows of Citarum river in Indonesia

NASA Astrophysics Data System (ADS)

Sahu, Netrananda; Behera, Swadhin K.; Yamashiki, Yosuke; Takara, Kaoru; Yamagata, Toshio

2012-10-01

Extreme stream-flow events of Citarum River are derived from the daily stream-flows at the Nanjung gauge station. Those events are identified based on their persistently extreme flows for 6 or more days during boreal fall when the seasonal mean stream-flow starts peaking-up from the lowest seasonal flows of June-August. Most of the extreme events of high-streamflows were related to La Niña conditions of tropical Pacific. A few of them were also associated with the negative phases of IOD and the newly identified El Niño Modoki. Unlike the cases of extreme high streamflows, extreme low streamflow events are seen to be associated with the positive IODs. Nevertheless, it was also found that the low-stream-flow events related to positive IOD events were also associated with El Niño events except for one independent event of 1977. Because the occurrence season coincides the peak season of IOD, not only the picked extreme events are seen to fall under the IOD seasons but also there exists a statistically significant correlation of 0.51 between the seasonal IOD index and the seasonal streamflows. There also exists a significant lag correlation when IOD of June-August season leads the streamflows of September-November. A significant but lower correlation coefficient (0.39) is also found between the seasonal streamflow and El Niño for September-November season only.

Geo-social media as a proxy for hydrometeorological data for streamflow estimation and to improve flood monitoring

NASA Astrophysics Data System (ADS)

Restrepo-Estrada, Camilo; de Andrade, Sidgley Camargo; Abe, Narumi; Fava, Maria Clara; Mendiondo, Eduardo Mario; de Albuquerque, João Porto

2018-02-01

Floods are one of the most devastating types of worldwide disasters in terms of human, economic, and social losses. If authoritative data is scarce, or unavailable for some periods, other sources of information are required to improve streamflow estimation and early flood warnings. Georeferenced social media messages are increasingly being regarded as an alternative source of information for coping with flood risks. However, existing studies have mostly concentrated on the links between geo-social media activity and flooded areas. Thus, there is still a gap in research with regard to the use of social media as a proxy for rainfall-runoff estimations and flood forecasting. To address this, we propose using a transformation function that creates a proxy variable for rainfall by analysing geo-social media messages and rainfall measurements from authoritative sources, which are later incorporated within a hydrological model for streamflow estimation. We found that the combined use of official rainfall values with the social media proxy variable as input for the Probability Distributed Model (PDM), improved streamflow simulations for flood monitoring. The combination of authoritative sources and transformed geo-social media data during flood events achieved a 71% degree of accuracy and a 29% underestimation rate in a comparison made with real streamflow measurements. This is a significant improvement on the respective values of 39% and 58%, achieved when only authoritative data were used for the modelling. This result is clear evidence of the potential use of derived geo-social media data as a proxy for environmental variables for improving flood early-warning systems.

A real-time evaluation and demonstration of strategies for 'Over-The-Loop' ensemble streamflow forecasting in US watersheds

NASA Astrophysics Data System (ADS)

Wood, Andy; Clark, Elizabeth; Mendoza, Pablo; Nijssen, Bart; Newman, Andy; Clark, Martyn; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

Many if not most national operational streamflow prediction systems rely on a forecaster-in-the-loop approach that require the hands-on-effort of an experienced human forecaster. This approach evolved from the need to correct for long-standing deficiencies in the models and datasets used in forecasting, and the practice often leads to skillful flow predictions despite the use of relatively simple, conceptual models. Yet the 'in-the-loop' forecast process is not reproducible, which limits opportunities to assess and incorporate new techniques systematically, and the effort required to make forecasts in this way is an obstacle to expanding forecast services - e.g., though adding new forecast locations or more frequent forecast updates, running more complex models, or producing forecast and hindcasts that can support verification. In the last decade, the hydrologic forecasting community has begun develop more centralized, 'over-the-loop' systems. The quality of these new forecast products will depend on their ability to leverage research in areas including earth system modeling, parameter estimation, data assimilation, statistical post-processing, weather and climate prediction, verification, and uncertainty estimation through the use of ensembles. Currently, many national operational streamflow forecasting and water management communities have little experience with the strengths and weaknesses of over-the-loop approaches, even as such systems are beginning to be deployed operationally in centers such as ECMWF. There is thus a need both to evaluate these forecasting advances and to demonstrate their potential in a public arena, raising awareness in forecast user communities and development programs alike. To address this need, the US National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the US Army Corps of Engineers, using the NCAR 'System for Hydromet Analysis Research and Prediction Applications' (SHARP) to implement, assess and demonstrate real-time over-the-loop ensemble flow forecasts in a range of US watersheds. The system relies on fully ensemble techniques, including: an 100-member ensemble of meteorological model forcings and an ensemble particle filter data assimilation for initializing watershed states; analog/regression-based downscaling of ensemble weather forecasts from GEFS; and statistical post-processing of ensemble forecast outputs, all of which run in real-time within a workflow managed by ECWMF's ecFlow libraries over large US regional domains. We describe SHARP and present early hindcast and verification results for short to seasonal range streamflow forecasts in a number of US case study watersheds.

Trends and shifts in streamflow in Hawaii, 1913-2008

USGS Publications Warehouse

Bassiouni, Maoya; Oki, Delwyn S.

2013-01-01

This study addresses a need to document changes in streamflow and base flow (groundwater discharge to streams) in Hawai'i during the past century. Statistically significant long-term (1913-2008) downward trends were detected (using the nonparametric Mann-Kendall test) in low-streamflow and base-flow records. These long-term downward trends are likely related to a statistically significant downward shift around 1943 detected (using the nonparametric Pettitt test) in index records of streamflow and base flow. The downward shift corresponds to a decrease of 22% in median streamflow and a decrease of 23% in median base flow between the periods 1913-1943 and 1943-2008. The shift coincides with other local and regional factors, including a change from a positive to a negative phase in the Pacific Decadal Oscillation, shifts in the direction of the trade winds over Hawai'i, and a reforestation programme. The detected shift and long-term trends reflect region-wide changes in climatic and land-cover factors. A weak pattern of downward trends in base flows during the period 1943-2008 may indicate a continued decrease in base flows after the 1943 shift. Downward trends were detected more commonly in base-flow records than in high-streamflow, peak-flow, and rainfall records. The decrease in base flow is likely related to a decrease in groundwater storage and recharge and therefore is a valuable indicator of decreasing water availability and watershed vulnerability to hydrologic changes. Whether the downward trends will continue is largely uncertain given the uncertainty in climate-change projections and watershed responses to changes.

Statistical Attribution of Changes in Streamflow in the U.S. Midwest over the 20th and 21st Centuries

NASA Astrophysics Data System (ADS)

Slater, L. J.; Villarini, G.

2016-12-01

Streamflows have increased notably across the Midwest over the past century. These changes have largely been attributed to the influence of upward trends in heavy precipitation and agricultural increases in row crop production. However, attempts to understand the specific causes of the changes in streamflow timing, magnitude, frequency, and seasonality have led to much debate in recent years, particularly regarding the influence of changing agricultural practices. Separating the different - climatic or land use/land cover - drivers of changing streamflow from a statistical perspective is not straightforward, and different methods have been implemented in the literature. Here, we develop statistical models in 476 U.S. Midwest river basins with long-term USGS discharge records to investigate the influence of the main drivers of changing streamflows: urbanization (using basin-averaged population per square kilometer), agricultural land cover (total corn and soybean harvested acreage), basin-averaged temperature, basin-averaged precipitation, and antecedent soil moisture (using precipitation from the month preceding each season as a proxy). We model the changes in the seasonal discharge quantiles from low to high flows as a function of these drivers (separately and combined), to evaluate which set of predictors is the best in each river basin. Results indicate that precipitation is indeed the most widespread driver in regions that are neither predominantly agricultural nor heavily urbanized. Elsewhere, we find strong regional patterns in terms of the best-fitting drivers, depending on climate, agricultural land cover and urbanization. Using these models, we then examine the sensitivity of discharge to different scenarios based on potential changes in each of the predictors. The projected changes have profound implications for water resources management across the Midwest.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

USGS Publications Warehouse

Chase, Katherine J.; Caldwell, Rodney R.; Stanley, Andrea K.

2014-01-01

This report documents the construction of a precipitation-runoff model for simulating natural streamflow in the Smith River watershed, Montana. This Precipitation-Runoff Modeling System model, constructed in cooperation with the Meagher County Conservation District, can be used to examine the general hydrologic framework of the Smith River watershed, including quantification of precipitation, evapotranspiration, and streamflow; partitioning of streamflow between surface runoff and subsurface flow; and quantifying contributions to streamflow from several parts of the watershed. The model was constructed by using spatial datasets describing watershed topography, the streams, and the hydrologic characteristics of the basin soils and vegetation. Time-series data (daily total precipitation, and daily minimum and maximum temperature) were input to the model to simulate daily streamflow. The model was calibrated for water years 2002–2007 and evaluated for water years 1996–2001. Though water year 2008 was included in the study period to evaluate water-budget components, calibration and evaluation data were unavailable for that year. During the calibration and evaluation periods, simulated-natural flow values were compared to reconstructed-natural streamflow data. These reconstructed-natural streamflow data were calculated by adding Bureau of Reclamation’s depletions data to the observed streamflows. Reconstructed-natural streamflows represent estimates of streamflows for water years 1996–2007 assuming there was no agricultural water-resources development in the watershed. Additional calibration targets were basin mean monthly solar radiation and potential evapotranspiration. The model estimated the hydrologic processes in the Smith River watershed during the calibration and evaluation periods. Simulated-natural mean annual and mean monthly flows generally were the same or higher than the reconstructed-natural streamflow values during the calibration period, whereas they were lower during the evaluation period. The shape of the annual hydrographs for the simulated-natural daily streamflow values matched the shape of the hydrographs for the reconstructed-natural values for most of the calibration period, but daily streamflow values were underestimated during the evaluation period for water years 1996–1998. The model enabled a detailed evaluation of the components of the water budget within the Smith River watershed during the water year 1996–2008 study period. During this study period, simulated mean annual precipitation across the Smith River watershed was 16 inches, out of which 14 inches evaporated or transpired and 2 inches left the basin as streamflow. Per the precipitation-runoff model simulations, during most of the year, surface runoff rarely (less than 2 percent of the time during water years 2002–2008) makes up more than 10 percent of the total streamflow. Subsurface flow (the combination of interflow and groundwater flow) makes up most of the total streamflow (99 or more percent of total streamflow for 71 percent of the time during water years 2002–2008).

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

USGS Publications Warehouse

Thomas, Blakemore E.; Pool, Don R.

2006-01-01

This study was done to improve the understanding of trends in streamflow of the San Pedro River in southeastern Arizona. Annual streamflow of the river at Charleston, Arizona, has decreased by more than 50 percent during the 20th century. The San Pedro River is one of the few remaining free-flowing perennial streams in the arid Southwestern United States, and the riparian forest along the river supports several endangered species and is an important habitat for migratory birds. Trends in seasonal and annual precipitation and streamflow were evaluated for surrounding areas in southeastern Arizona and southwestern New Mexico to provide a regional perspective for the trends of the San Pedro River. Seasonal and annual streamflow trends and the relation between precipitation and streamflow in the San Pedro River Basin were evaluated to improve the understanding of the causes of trends. There were few significant trends in seasonal and annual precipitation or streamflow for the regional study area. Precipitation and streamflow records were analyzed for 11 time periods ranging from 1930 to 2002; no significant trends were found in 92 percent of the trend tests for precipitation, and no significant trends were found in 79 percent of the trend tests for streamflow. For the trends in precipitation that were significant, 90 percent were positive and most of those positive trends were in records of winter, spring, or annual precipitation that started during the mid-century drought in 1945-60. For the trends in streamflow that were significant, about half were positive and half were negative. Trends in precipitation in the San Pedro River Basin were similar to regional precipitation trends for spring and fall values and were different for summer and annual values. The largest difference was in annual precipitation, for which no trend tests were significant in the San Pedro River Basin, and 23 percent of the trend tests were significantly positive in the rest of the study area. Streamflow trends for the San Pedro River were different from regional streamflow trends. All seasonal flows for the San Pedro River, except winter flows, had significant decreasing trends, and seasonal flows for most streams in the rest of the study area had either no trend or a significant increasing trend. Two streams adjacent to the San Pedro River Basin (Whitewater Draw and Santa Cruz River), however, had significant decreasing trends in summer streamflow. Factors that caused the decreasing trends in streamflow of the San Pedro River at Charleston were investigated. Possible factors were fluctuations in precipitation and air temperature, changes in watershed characteristics, human activities, or changes in seasonal distribution of bank storage. This study statistically removed or accounted for the variation in streamflow caused by fluctuations in precipitation. Thus, the remaining variation or trend in streamflow was caused by factors other than precipitation. Two methods were used to partition the variation in streamflow and to determine trends in the partitioned variation: (1) regression analysis between precipitation and streamflow using all years in the record and evaluation of time trends in regression residuals, and (2) development of regression equations between precipitation and streamflow for three time periods (early, middle, and late parts of the record) and testing to determine if the three regression equations were significantly different. The methods were applied to monthly values of total flow (average flow) and storm runoff (maximum daily mean flow) for 1913-2002, and to monthly values of low flow (3-day low flow) for 1931-2002. Statistical tests provide strong evidence that factors other than precipitation caused a decrease in streamflow of the San Pedro River. Factors other than precipitation caused significant decreasing trends in streamflows for late spring through early winter and did not cause significant trends f

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.

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.

LFSTAT - An R-Package for Low-Flow Analysis

NASA Astrophysics Data System (ADS)

Koffler, D.; Laaha, G.

2012-04-01

When analysing daily streamflow data focusing on low flow and drought, the state of the art is well documented in the Manual on Low-Flow Estimation and Prediction [1] published by the WMO. While it is clear what has to be done, it is not so clear how to preform the analysis and make the calculation as reproducible as possible. Our software solution expands the high preforming statistical open source software package R to analyse daily stream flow data focusing on low-flows. As command-line based programs are not everyone's preference, we also offer a plug-in for the R-Commander, an easy to use graphical user interface (GUI) to analyse data in R. Functionality includes estimation of the most important low-flow indices. Beside standardly used flow indices also BFI and Recession constants can be computed. The main applications of L-moment based Extreme value analysis and regional frequency analysis (RFA) are available. Calculation of streamflow deficits is another important feature. The most common graphics are prepared and can easily be modified according to the users preferences. Graphics include hydrographs for different periods, flexible streamflow deficit plots, baseflow visualisation, flow duration curves as well as double mass curves just to name a few. The package uses a S3-class called lfobj (low-flow objects). Once this objects are created, analysis can be preformed by mouse-click, and a script can be saved to make the analysis easy reproducible. At the moment we are offering implementation of all major methods proposed in the WMO manual on Low-flow Estimation and Predictions. Future plans include e.g. report export in odt-file using odf-weave. We hope to offer a tool to ease and structure the analysis of stream flow data focusing on low-flows and to make analysis transparent and communicable. The package is designed for hydrological research and water management practice, but can also be used in teaching students the first steps in low-flow hydrology.

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 sensitive to changes in mean precipitation, but was sensitive to changes in mean temperatures. Changes in annual streamflow amounts were amplified reflections of imposed mean precipitation changes, with especially large responses to wetter climates. In contrast, streamflow amount was surprisingly insensitive to mean temperature changes as a result of temporal links between peak snowmelt and the beginning of warm-season evapotranspiration. Comparisons of simulations driven by temporally detailed climate-model changes in which mean temperature changes vary from month to month and simulations in which uniform climate changes were imposed throughout the year indicate that the snowpack accumulates the influences of short-term conditions so that season average climate changes were more important than shorter term changes.

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.

Summertime Minimum Streamflow Elasticity to Antecendent Winter Precipitation, Peak Snow Water Equivalent and Summertime Evaporative Demand in the Western US Maritime Mountains

NASA Astrophysics Data System (ADS)

Schaperow, J.; Cooper, M. G.; Cooley, S. W.; Alam, S.; Smith, L. C.; Lettenmaier, D. P.

2017-12-01

As climate regimes shift, streamflows and our ability to predict them will change, as well. Elasticity of summer minimum streamflow is estimated for 138 unimpaired headwater river basins across the maritime western US mountains to better understand how climatologic variables and geologic characteristics interact to determine the response of summer low flows to winter precipitation (PPT), spring snow water equivalent (SWE), and summertime potential evapotranspiration (PET). Elasticities are calculated using log log linear regression, and linear reservoir storage coefficients are used to represent basin geology. Storage coefficients are estimated using baseflow recession analysis. On average, SWE, PET, and PPT explain about 1/3 of the summertime low flow variance. Snow-dominated basins with long timescales of baseflow recession are least sensitive to changes in SWE, PPT, and PET, while rainfall-dominated, faster draining basins are most sensitive. There are also implications for the predictability of summer low flows. The R2 between streamflow and SWE drops from 0.62 to 0.47 from snow-dominated to rain-dominated basins, while there is no corresponding increase in R2 between streamflow and PPT.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Selected low-flow frequency statistics for continuous-record streamgage locations in Maryland, 2010

USGS Publications Warehouse

Doheny, Edward J.; Banks, William S.L.

2010-01-01

According to a 2008 report by the Governor's Advisory Committee on the Management and Protection of the State's Water Resources, Maryland's population grew by 35 percent between 1970 and 2000, and is expected to increase by an additional 27 percent between 2000 and 2030. Because domestic water demand generally increases in proportion to population growth, Maryland will be facing increased pressure on water resources over the next 20 years. Water-resources decisions should be based on sound, comprehensive, long-term data and low-flow frequency statistics from all available streamgage locations with unregulated streamflow and adequate record lengths. To provide the Maryland Department of the Environment with tools for making future water-resources decisions, the U.S. Geological Survey initiated a study in October 2009 to compute low-flow frequency statistics for selected streamgage locations in Maryland with 10 or more years of continuous streamflow records. This report presents low-flow frequency statistics for 114 continuous-record streamgage locations in Maryland. The computed statistics presented for each streamgage location include the mean 7-, 14-, and 30-consecutive day minimum daily low-flow dischages for recurrence intervals of 2, 10, and 20 years, and are based on approved streamflow records that include a minimum of 10 complete climatic years of record as of June 2010. Descriptive information for each of these streamgage locations, including the station number, station name, latitude, longitude, county, physiographic province, and drainage area, also is presented. The statistics are planned for incorporation into StreamStats, which is a U.S. Geological Survey Web application for obtaining stream information, and is being used by water-resource managers and decision makers in Maryland to address water-supply planning and management, water-use appropriation and permitting, wastewater and industrial discharge permitting, and setting minimum required streamflows to protect freshwater biota and ecosystems.

Surface-water/ground-water interaction along reaches of the Snake River and Henrys Fork, Idaho

USGS Publications Warehouse

Hortness, Jon E.; Vidmar, Peter

2005-01-01

Declining water levels in the eastern Snake River Plain aquifer and decreases in spring discharges from the aquifer to the Snake River have spurred studies to improve understanding of the surface-water/ground-water interaction on the plain. This study was done to estimate streamflow gains and losses along specific reaches of the Snake River and Henrys Fork and to compare changes in gain and loss estimates to changes in ground-water levels over time. Data collected during this study will be used to enhance the conceptual model of the hydrologic system and to refine computer models of ground-water flow and surface-water/ground-water interactions. Estimates of streamflow gains and losses along specific subreaches of the Snake River and Henrys Fork, based on the results of five seepage studies completed during 2001?02, varied greatly across the study area, ranging from a loss estimate of 606 ft3/s in a subreach of the upper Snake River near Heise to a gain estimate of 3,450 ft3/s in a subreach of the Snake River that includes Thousand Springs. Some variations over time also were apparent in specific subreaches. Surface spring flow accounted for much of the inflow to subreaches having large gain estimates. Several subreaches alternately gained and lost streamflow during the study. Changes in estimates of streamflow gains and losses along some of the subreaches were compared with changes in water levels, measured at three different times during 2001?02, in adjacent wells. In some instances, a strong relation between changes in estimates of gains or losses and changes in ground-water levels was apparent.

Estimating distribution parameters of annual maximum streamflows in Johor, Malaysia using TL-moments approach

NASA Astrophysics Data System (ADS)

Mat Jan, Nur Amalina; Shabri, Ani

2017-01-01

TL-moments approach has been used in an analysis to identify the best-fitting distributions to represent the annual series of maximum streamflow data over seven stations in Johor, Malaysia. The TL-moments with different trimming values are used to estimate the parameter of the selected distributions namely: Three-parameter lognormal (LN3) and Pearson Type III (P3) distribution. The main objective of this study is to derive the TL-moments ( t 1,0), t 1 = 1,2,3,4 methods for LN3 and P3 distributions. The performance of TL-moments ( t 1,0), t 1 = 1,2,3,4 was compared with L-moments through Monte Carlo simulation and streamflow data over a station in Johor, Malaysia. The absolute error is used to test the influence of TL-moments methods on estimated probability distribution functions. From the cases in this study, the results show that TL-moments with four trimmed smallest values from the conceptual sample (TL-moments [4, 0]) of LN3 distribution was the most appropriate in most of the stations of the annual maximum streamflow series in Johor, Malaysia.

Estimating 1970-99 average annual groundwater recharge in Wisconsin using streamflow data

USGS Publications Warehouse

Gebert, Warren A.; Walker, John F.; Kennedy, James L.

2011-01-01

Average annual recharge in Wisconsin for the period 1970-99 was estimated using streamflow data from U.S. Geological Survey continuous-record streamflow-gaging stations and partial-record sites. Partial-record sites have discharge measurements collected during low-flow conditions. The average annual base flow of a stream divided by the drainage area is a good approximation of the recharge rate; therefore, once average annual base flow is determined recharge can be calculated. Estimates of recharge for nearly 72 percent of the surface area of the State are provided. The results illustrate substantial spatial variability of recharge across the State, ranging from less than 1 inch to more than 12 inches per year. The average basin size for partial-record sites (50 square miles) was less than the average basin size for the gaging stations (305 square miles). Including results for smaller basins reveals a spatial variability that otherwise would be smoothed out using only estimates for larger basins. An error analysis indicates that the techniques used provide base flow estimates with standard errors ranging from 5.4 to 14 percent.

Towards reliable ET estimates in the semi-arid Júcar region in Spain.

NASA Astrophysics Data System (ADS)

Brenner, Johannes; Zink, Matthias; Schrön, Martin; Thober, Stephan; Rakovec, Oldrich; Cuntz, Matthias; Merz, Ralf; Samaniego, Luis

2017-04-01

Current research indicated the potential for improving evapotranspiration (ET) estimates in state-of-the-art hydrologic models such as the mesoscale Hydrological Model (mHM, www.ufz.de/mhm). Most models exhibit deficiencies to estimate the ET flux in semi-arid regions. Possible reasons for poor performance may be related to the low resolution of the forcings, the estimation of the PET, which is in most cases based on temperature only, the joint estimation of the transpiration and evaporation through the Feddes equation, poor process parameterizations, among others. In this study, we aim at sequential hypothesis-based experiments to uncover the main reasons of these deficiencies at the Júcar basin in Spain. We plan the following experiments: 1) Use the high resolution meteorological forcing (P and T) provided by local authorities to estimate its effects on ET and streamflow. 2) Use local ET measurements at seven eddy covariance stations to estimate evaporation related parameters. 3) Test the influence of the PET formulations (Hargreaves-Samani, Priestley-Taylor, Penman-Montheith). 4) Estimate evaporation and transpiration separately based on equations proposed by Bohn and Vivoni (2016) 5) Incorporate local soil moisture measurements to re-estimate ET and soil moisture related parameters. We set-up mHM for seven eddy-covariance sites at the local scale (100 × 100 m2). This resolution was chosen because it is representative for the footprint of the latent heat estimation at the eddy-covariance station. In the second experiment, for example, a parameter set is to be found as a compromised solution between ET measured at local stations and the streamflow observations at eight sub-basins of the Júcar river. Preliminary results indicate that higher model performance regarding streamflow can be achieved using local high-resolution meteorology. ET performance is, however, still deficient. On the contrary, using ET site calibrations alone increase performance in ET but yields in poor performance in streamflow. Results suggest the need of multi-variable, simultaneous calibration schemes to reliable estimate ET and streamflow in the Júcar basin. Penman-Montheith appears to be the best performing PET formulation. Experiments 4 and 5 should reveal the benefits of separating evaporation from bare soil and transpiration in semi-arid regions using mHM. Further research in this direction is foreseen by incorporating neutron counts from Cosmic Ray Neutron Sensing technology in the calibration/validation procedure of mHM.

Peak-flow characteristics of Wyoming streams

USGS Publications Warehouse

Miller, Kirk A.

2003-01-01

Peak-flow characteristics for unregulated streams in Wyoming are described in this report. Frequency relations for annual peak flows through water year 2000 at 364 streamflow-gaging stations in and near Wyoming were evaluated and revised or updated as needed. Analyses of historical floods, temporal trends, and generalized skew were included in the evaluation. Physical and climatic basin characteristics were determined for each gaging station using a geographic information system. Gaging stations with similar peak-flow and basin characteristics were grouped into six hydrologic regions. Regional statistical relations between peak-flow and basin characteristics were explored using multiple-regression techniques. Generalized least squares regression equations for estimating magnitudes of annual peak flows with selected recurrence intervals from 1.5 to 500 years were developed for each region. Average standard errors of estimate range from 34 to 131 percent. Average standard errors of prediction range from 35 to 135 percent. Several statistics for evaluating and comparing the errors in these estimates are described. Limitations of the equations are described. Methods for applying the regional equations for various circumstances are listed and examples are given.

Evaluation of selected methods for determining streamflow during periods of ice effect

USGS Publications Warehouse

Melcher, N.B.; Walker, J.F.

1990-01-01

The methods are classified into two general categories, subjective and analytical, depending on whether individual judgement is necessary for method application. On the basis of results of the evaluation for the three Iowa stations, two of the subjective methods (discharge ratio and hydrographic-and-climatic comparison) were more accurate than the other subjective methods, and approximately as accurate as the best analytical method. Three of the analytical methods (index velocity, adjusted rating curve, and uniform flow) could potentially be used for streamflow-gaging stations where the need for accurate ice-affected discharge estimates justifies the expense of collecting additional field data. One analytical method (ice adjustment factor) may be appropriate for use for stations with extremely stable stage-discharge ratings and measuring sections. Further research is needed to refine the analytical methods. The discharge ratio and multiple regression methods produce estimates of streamflow for varying ice conditions using information obtained from the existing U.S. Geological Survey streamflow-gaging network.

Estimation of tile drainage contribution to streamflow and nutrient loads at the watershed scale based on continuously monitored data.

PubMed

Arenas Amado, A; Schilling, K E; Jones, C S; Thomas, N; Weber, L J

2017-09-01

Nitrogen losses from artificially drained watersheds degrade water quality at local and regional scales. In this study, we used an end-member mixing analysis (EMMA) together with high temporal resolution water quality and streamflow data collected in the 122 km 2 Otter Creek watershed located in northeast Iowa. We estimated the contribution of three end-members (groundwater, tile drainage, and quick flow) to streamflow and nitrogen loads and tested several combinations of possible nitrate concentrations for the end-members. Results indicated that subsurface tile drainage is responsible for at least 50% of the watershed nitrogen load between April 15 and November 1, 2015. Tiles delivered up to 80% of the stream N load while providing only 15-43% of the streamflow, whereas quick flows only marginally contributed to N loading. Data collected offer guidance about areas of the watershed that should be targeted for nitrogen export mitigation strategies.

Towards a systematic approach to comparing distributions used in flood frequency analysis

NASA Astrophysics Data System (ADS)

Bobée, B.; Cavadias, G.; Ashkar, F.; Bernier, J.; Rasmussen, P.

1993-02-01

The estimation of flood quantiles from available streamflow records has been a topic of extensive research in this century. However, the large number of distributions and estimation methods proposed in the scientific literature has led to a state of confusion, and a gap prevails between theory and practice. This concerns both at-site and regional flood frequency estimation. To facilitate the work of "hydrologists, designers of hydraulic structures, irrigation engineers and planners of water resources", the World Meteorological Organization recently published a report which surveys and compares current methodologies, and recommends a number of statistical distributions and estimation procedures. This report is an important step towards the clarification of this difficult topic, but we think that it does not effectively satisfy the needs of practitioners as intended, because it contains some statements which are not statistically justified and which require further discussion. In the present paper we review commonly used procedures for flood frequency estimation, point out some of the reasons for the present state of confusion concerning the advantages and disadvantages of the various methods, and propose the broad lines of a possible comparison strategy. We recommend that the results of such comparisons be discussed in an international forum of experts, with the purpose of attaining a more coherent and broadly accepted strategy for estimating floods.

Suspended sediment and bedload in the First Broad River Basin in Cleveland County, North Carolina, 2008-2009

USGS Publications Warehouse

Hazell, William F.; Huffman, Brad A.

2011-01-01

A study was conducted to characterize sediment transport upstream and downstream from a proposed dam on the First Broad River near the town of Lawndale in Cleveland County, North Carolina. Streamflow was measured continuously, and 381 suspended-sediment samples were collected between late March 2008 and September 2009 at two monitoring stations on the First Broad River to determine the suspended-sediment load at each site for the period April 2008-September 2009. In addition, 22 bedload samples were collected at the two sites to describe the relative contribution of bedload to total sediment load during selected events. Instantaneous streamflow, suspended-sediment, and bedload samples were collected at Knob Creek near Lawndale, North Carolina, to describe general suspended-sediment and bedload characteristics at this tributary to the First Broad River. Suspended- and bedload-sediment samples were collected at all three sites during a variety of flow conditions. Streamflow and suspended-sediment measurements were compared with historical data from a long-term (1959-2009) streamflow station located upstream from Lawndale. The mean streamflow at the long-term streamflow station was approximately 60 percent less during the study period than the long-term annual mean streamflow for the site. Suspended-sediment concentrations and continuous records of streamflow were used to estimate suspended-sediment loads and yields at the two monitoring stations on the First Broad River for the period April 2008-September 2009 and for a complete annual cycle (October 2008-September 2009), also known as a water year. Total suspended-sediment loads during water year 2009 were 18,700 and 36,500 tons at the two sites. High-flow events accounted for a large percentage of the total load, suggesting that the bulk of the total suspended-sediment load was transported during these events. Suspended-sediment yields during water year 2009 were 145 and 192 tons per square mile at the two monitoring stations. Historically, the estimated mean annual suspended-sediment yield at the long-term streamflow station during the period 1970-1979 was 250 tons per square mile, with an estimated mean annual suspended-sediment load of 15,000 tons. Drought conditions throughout most of the study period were a potential factor in the smaller yields at the monitoring stations compared to the yields estimated at the long-term streamflow station in the 1970s. During an extreme runoff event on January 7, 2009, bedload was 0.4 percent, 0.8 percent, and 0.1 percent of the total load at the three study sites, which indicates that during extreme runoff conditions the percentage of the total load that is bedload is not significant. The percentages of the total load that is bedload during low-flow conditions ranged from 0.1 to 90.8, which indicate that the bedload is variable both spatially and temporally.

Synthesis of natural flows at selected sites in the upper Missouri River basin, Montana, 1928-89

USGS Publications Warehouse

Cary, L.E.; Parrett, Charles

1996-01-01

Natural monthly streamflows were synthesized for the years 1928-89 for 43 sites in the upper Missouri River Basin upstream from Fort Peck Lake in Montana. The sites are represented as nodes in a streamflow accounting model being developed by the Bureau of Reclamation. Recorded and historical flows at most sites have been affected by human activities including reservoir storage, diversions for irrigation, and municipal use. Natural flows at the sites were synthesized by eliminating the effects of these activities. Recorded data at some sites do not include the entire study period. The missing flows at these sites were estimated using a statistical procedure. The methods of synthesis varied, depending on upstream activities and information available. Recorded flows were transferred to nodes that did not have streamflow-gaging stations from the nearest station with a sufficient length of record. The flows at one node were computed as the sum of flows from three upstream tributaries. Monthly changes in reservoir storage were computed from monthend contents. The changes in storage were corrected for the effects of evaporation and precipitation using pan-evaporation and precipitation data from climate stations. Irrigation depletions and consumptive use by the three largest municipalities were computed. Synthesized natural flow at most nodes was computed by adding algebraically the upstream depletions and changes in reservoir storage to recorded or historical flow at the nodes.

Estimated Loads of Suspended Sediment and Selected Trace Elements Transported through the Milltown Reservoir Project Area Before and After the Breaching of Milltown Dam in the Upper Clark Fork Basin, Montana, Water Year 2008

USGS Publications Warehouse

Lambing, John H.; Sando, Steven K.

2009-01-01

This report presents estimated daily and cumulative loads of suspended sediment and selected trace elements transported during water year 2008 at three streamflow-gaging stations that bracket the Milltown Reservoir project area in the upper Clark Fork basin of western Montana. Milltown Reservoir is a National Priorities List Superfund site where sediments enriched in trace elements from historical mining and ore processing have been deposited since the construction of Milltown Dam in 1907. Milltown Dam was breached on March 28, 2008, as part of Superfund remedial activities to remove the dam and contaminated sediment that had accumulated in Milltown Reservoir. The estimated loads transported through the project area during the periods before and after the breaching of Milltown Dam, and for the entire water year 2008, were used to quantify the net gain or loss (mass balance) of suspended sediment and trace elements within the project area during the transition from a reservoir environment to a free-flowing river. This study was done in cooperation with the U.S. Environmental Protection Agency. Streamflow during water year 2008 compared to long-term streamflow, as represented by the record for Clark Fork above Missoula (water years 1930-2008), generally was below normal (long-term median) from about October 2007 through April 2008. Sustained runoff started in mid-April, which increased flows to near normal by mid-May. After mid-May, flows sharply increased to above normal, reaching a maximum daily mean streamflow of 16,800 cubic feet per second (ft3/s) on May 21, which essentially equaled the long-term 10th-exceedance percentile for that date. Flows substantially above normal were sustained through June, then decreased through the summer and reached near-normal by August. Annual mean streamflow during water year 2008 (3,040 ft3/s) was 105 percent of the long-term mean annual streamflow (2,900 ft3/s). The annual peak flow (17,500 ft3/s) occurred on May 21 and was 112 percent of the long-term mean annual peak flow (15,600 ft3/s). About 81 percent of the annual flow volume was discharged during the post-breach period. Daily loads of suspended sediment were estimated directly by using high-frequency sampling of the daily sediment monitoring. Daily loads of unfiltered-recoverable arsenic, cadmium, copper, iron, lead, manganese, and zinc were estimated by using regression equations relating trace-element discharge to either streamflow or suspended-sediment discharge. Regression equations for estimating trace-element discharge in water year 2008 were developed from instantaneous streamflow and concentration data for periodic water-quality samples collected during all or part of water years 2004-08. The equations were applied to records of daily mean streamflow or daily suspended-sediment loads to produce estimated daily trace-element loads. Variations in daily suspended-sediment and trace-element loads generally coincided with variations in streamflow. Relatively small to moderately large daily net losses from the project area were common during the pre-breach period when low-flow conditions were prevalent. Outflow loads from the project area sharply increased immediately after the breaching of Milltown Dam and during the rising limb and peak flow of the annual hydrograph. Net losses of suspended sediment and trace elements from the project area decreased as streamflow decreased during the summer, eventually becoming small or reaching an approximate net balance between inflow and outflow. Estimated daily loads of suspended sediment and trace elements for all three stations were summed to determine cumulative inflow and outflow loads for the pre-breach and post-breach periods, as well as for the entire water year 2008. Overall, the mass balance between the combined inflow loads from two upstream source areas (upper Clark Fork and Blackfoot River basins) and the outflow loads at Clark Fork above Missoula indicates net losses

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

NASA Astrophysics Data System (ADS)

Engeland, Kolbjorn; Steinsland, Ingelin

2016-04-01

The aim of this study is to investigate how the inclusion of uncertainties in inputs and observed streamflow influence the parameter estimation, streamflow predictions and model evaluation. In particular we wanted to answer the following research questions: • What is the effect of including a random error in the precipitation and temperature inputs? • What is the effect of decreased information about precipitation by excluding the nearest precipitation station? • What is the effect of the uncertainty in streamflow observations? • What is the effect of reduced information about the true streamflow by using a rating curve where the measurement of the highest and lowest streamflow is excluded when estimating the rating curve? To answer these questions, we designed a set of calibration experiments and evaluation strategies. We used the elevation distributed HBV model operating on daily time steps combined with a Bayesian formulation and the MCMC routine Dream for parameter inference. The uncertainties in inputs was represented by creating ensembles of precipitation and temperature. The precipitation ensemble were created using a meta-gaussian random field approach. The temperature ensembles were created using a 3D Bayesian kriging with random sampling of the temperature laps rate. The streamflow ensembles were generated by a Bayesian multi-segment rating curve model. Precipitation and temperatures were randomly sampled for every day, whereas the streamflow ensembles were generated from rating curve ensembles, and the same rating curve was always used for the whole time series in a calibration or evaluation run. We chose a catchment with a meteorological station measuring precipitation and temperature, and a rating curve of relatively high quality. This allowed us to investigate and further test the effect of having less information on precipitation and streamflow during model calibration, predictions and evaluation. The results showed that including uncertainty in the precipitation and temperature input has a negligible effect on the posterior distribution of parameters and for the Nash-Sutcliffe (NS) efficiency for the predicted flows, while the reliability and the continuous rank probability score (CRPS) improves. Reduced information in precipitation input resulted in a and a shift in the water balance parameter Pcorr, a model producing smoother streamflow predictions giving poorer NS and CRPS, but higher reliability. The effect of calibrating the hydrological model using wrong rating curves is mainly seen as variability in the water balance parameter Pcorr. When evaluating predictions obtained using a wrong rating curve, the evaluation scores varies depending on the true rating curve. Generally, the best evaluation scores were not achieved for the rating curve used for calibration, but for a rating curves giving low variance in streamflow observations. Reduced information in streamflow influenced the water balance parameter Pcorr, and increased the spread in evaluation scores giving both better and worse scores. This case study shows that estimating the water balance is challenging since both precipitation inputs and streamflow observations have pronounced systematic component in their uncertainties.

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

USGS Publications Warehouse

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-01-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

NASA Astrophysics Data System (ADS)

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-12-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

U.S. Geological Survey groundwater toolbox, a graphical and mapping interface for analysis of hydrologic data (version 1.0): user guide for estimation of base flow, runoff, and groundwater recharge from streamflow data

USGS Publications Warehouse

Barlow, Paul M.; Cunningham, William L.; Zhai, Tong; Gray, Mark

2015-01-01

This report is a user guide for the streamflow-hydrograph analysis methods provided with version 1.0 of the U.S. Geological Survey (USGS) Groundwater Toolbox computer program. These include six hydrograph-separation methods to determine the groundwater-discharge (base-flow) and surface-runoff components of streamflow—the Base-Flow Index (BFI; Standard and Modified), HYSEP (Fixed Interval, Sliding Interval, and Local Minimum), and PART methods—and the RORA recession-curve displacement method and associated RECESS program to estimate groundwater recharge from streamflow data. The Groundwater Toolbox is a customized interface built on the nonproprietary, open source MapWindow geographic information system software. The program provides graphing, mapping, and analysis capabilities in a Microsoft Windows computing environment. In addition to the four hydrograph-analysis methods, the Groundwater Toolbox allows for the retrieval of hydrologic time-series data (streamflow, groundwater levels, and precipitation) from the USGS National Water Information System, downloading of a suite of preprocessed geographic information system coverages and meteorological data from the National Oceanic and Atmospheric Administration National Climatic Data Center, and analysis of data with several preprocessing and postprocessing utilities. With its data retrieval and analysis tools, the Groundwater Toolbox provides methods to estimate many of the components of the water budget for a hydrologic basin, including precipitation; streamflow; base flow; runoff; groundwater recharge; and total, groundwater, and near-surface evapotranspiration.

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

NASA Astrophysics Data System (ADS)

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

2006-02-01

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

Methods for estimating monthly mean concentrations of selected water-quality constituents for stream sites in the Red River of the North basin, North Dakota and Minnesota

USGS Publications Warehouse

Guenthner, R.S.

1991-01-01

Future development of the Garrison Diversion Unit may divert water from the Missouri River into the Sheyenne River and the Red River of the North for municipal and industrial use. The U.S. Bureau of Reclamation's Canals, Rivers, and Reservoirs Salinity Accounting Procedures model can be used to predict the effect various operating plans could have on water quality in the Sheyenne River and the Red River of the North. The model uses, as Input, monthly means of streamflow and selected water-quality constituents for a 54-year period at 28 nodes on the Sheyenne River and the Red River of the North. This report provides methods for estimating monthly mean concentrations of selected water-quality constituents that can be used for input to and calibration of the salinity model.Mater-quality data for 32 gaging stations can be used to define selected water-quality characteristics at the 28 model nodes. Materquality data were retrieved from the U.S. Geological Survey's National Mater Data Storage and Retrieval System data base and statistical summaries were prepared. The frequency of water-quality data collection at the gaging stations is inadequate to define monthly mean concentrations of the individual water-quality constituents for all months for the 54-year period; therefore, methods for estimating monthly mean concentrations were developed. Relations between selected water-quality constituents [dissolved solids, hardness (as CaCO3), sodium, sulfate, and chloride] and streamflow were developed as the primary method to estimate monthly mean concentrations. Relations between specific conductance and streamflow and relations between selected water-quality constituents [dissolved solids, hardness (as CaCO3), sodium, sulfate, and chloride] and specific conductance were developed so that a cascaded-regression relation could be developed as a second method of estimating monthly mean concentrations and, thus, utilize a large specific-conductance data base. Information about the quantity and the quality of ground water discharging to the Sheyenne River is needed for model input for reaches of the river where ground water accounts for a substantial part of streamflow during periods of low flow. Ground-water discharge was identified for two reaches of the Sheyenne River. Ground-water discharge to the Sheyenne River in the vicinity of Warwick, N.Dak., was about 14.8 cubic feet per second and the estimated dissolved-solids concentration was about 441 milligrams per liter during October 15 and 16, 1986. Ground-water discharge to the Sheyenne River in a reach between Lisbon and Kindred, N.Dak., ranged from an average of 25.3 cubic feet per second during September 13 to November 19, 1963, to about 45.0 cubic feet per second during October 21 and 22, 1986. Dissolved-solids concentration was estimated at about 442 milligrams per liter during October 21 and 22, 1986.

Flood of June 7-9, 2008, in Central and Southern Indiana

USGS Publications Warehouse

Morlock, Scott E.; Menke, Chad D.; Arvin, Donald V.; Kim, Moon H.

2008-01-01

On June 6-7, 2008, heavy rainfall of 2 to more than 10 inches fell upon saturated soils and added to already high streamflows from a wetter than normal spring in central and southern Indiana. The heavy rainfall resulted in severe flooding on many streams within the White River Basin during June 7-9, causing three deaths, evacuation of thousands of residents, and hundreds of millions of dollars of damage to residences, businesses, infrastructure, and agricultural lands. In all, 39 Indiana counties were declared Federal disaster areas. U.S. Geological Survey (USGS) streamgages at nine locations recorded new record peak streamflows for the respective periods of record as a result of the heavy rainfall. Recurrence intervals of flood-peak streamflows were estimated to be greater than 100 years at five streamgages and 50-100 years at two streamgages. Peak-gage-height data, peak-streamflow data, and recurrence intervals are tabulated for 19 USGS streamgages in central and southern Indiana. Peak-streamflow estimates are tabulated for four ungaged locations, and estimated recurrence intervals are tabulated for three ungaged locations. The estimated recurrence interval for an ungaged location on Haw Creek in Columbus was greater than 100 years and for an ungaged location on Hurricane Creek in Franklin was 50-100 years. Because flooding was particularly severe in the communities of Columbus, Edinburgh, Franklin, Paragon, Seymour, Spencer, Martinsville, Newberry, and Worthington, high-water-mark data collected after the flood were tabulated for those communities. Flood peak inundation maps and water-surface profiles for selected streams were made in a geographic information system by combining the high-water-mark data with the highest-resolution digital elevation model data available.

Evaluation of a new satellite-based precipitation dataset for climate studies in the Xiang River basin, Southern China

NASA Astrophysics Data System (ADS)

Zhu, Q.; Xu, Y. P.; Hsu, K. L.

2017-12-01

A new satellite-based precipitation dataset, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) with long-term time series dating back to 1983 can be one valuable dataset for climate studies. This study investigates the feasibility of using PERSIANN-CDR as a reference dataset for climate studies. Sixteen CMIP5 models are evaluated over the Xiang River basin, southern China, by comparing their performance on precipitation projection and streamflow simulation, particularly on extreme precipitation and streamflow events. The results show PERSIANN-CDR is a valuable dataset for climate studies, even on extreme precipitation events. The precipitation estimates and their extreme events from CMIP5 models are improved significantly compared with rain gauge observations after bias-correction by the PERSIANN-CDR precipitation estimates. Given streamflows simulated with raw and bias-corrected precipitation estimates from 16 CMIP5 models, 10 out of 16 are improved after bias-correction. The impact of bias-correction on extreme events for streamflow simulations are unstable, with eight out of 16 models can be clearly claimed they are improved after the bias-correction. Concerning the performance of raw CMIP5 models on precipitation, IPSL-CM5A-MR excels the other CMIP5 models, while MRI-CGCM3 outperforms on extreme events with its better performance on six extreme precipitation metrics. Case studies also show that raw CCSM4, CESM1-CAM5, and MRI-CGCM3 outperform other models on streamflow simulation, while MIROC5-ESM-CHEM, MIROC5-ESM and IPSL-CM5A-MR behaves better than the other models after bias-correction.

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.

Regression models to estimate real-time concentrations of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-07

USGS Publications Warehouse

Oden, Timothy D.; Asquith, William H.; Milburn, Matthew S.

2009-01-01

In December 2005, the U.S. Geological Survey in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria (total coliform and Escherichia coli), atrazine, and suspended sediment at two U.S. Geological Survey streamflow-gaging stations upstream from Lake Houston near Houston (08068500 Spring Creek near Spring, Texas, and 08070200 East Fork San Jacinto River near New Caney, Texas). The data from the discrete water-quality samples collected during 2005-07, in conjunction with monitored real-time data already being collected - physical properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), streamflow, and rainfall - were used to develop regression models for predicting water-quality constituent concentrations for inflows to Lake Houston. Rainfall data were obtained from a rain gage monitored by Harris County Homeland Security and Emergency Management and colocated with the Spring Creek station. The leaps and bounds algorithm was used to find the best subsets of possible regression models (minimum residual sum of squares for a given number of variables). The potential explanatory or predictive variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, rainfall, and time (to account for seasonal variations inherent in some water-quality data). The response variables at each site were nitrite plus nitrate nitrogen, total phosphorus, organic carbon, Escherichia coli, atrazine, and suspended sediment. The explanatory variables provide easily measured quantities as a means to estimate concentrations of the various constituents under investigation, with accompanying estimates of measurement uncertainty. Each regression equation can be used to estimate concentrations of a given constituent in real time. In conjunction with estimated concentrations, constituent loads were estimated by multiplying the estimated concentration by the corresponding streamflow and applying the appropriate conversion factor. By computing loads from estimated constituent concentrations, a continuous record of estimated loads can be available for comparison to total maximum daily loads. The regression equations presented in this report are site specific to the Spring Creek and East Fork San Jacinto River streamflow-gaging stations; however, the methods that were developed and documented could be applied to other tributaries to Lake Houston for estimating real-time water-quality data for streams entering Lake Houston.

Effects of Surface-Water Diversions on Habitat Availability for Native Macrofauna, Northeast Maui, Hawaii

USGS Publications Warehouse

Gingerich, Stephen B.; Wolff, Reuben H.

2005-01-01

Effects of surface-water diversions on habitat availability for native stream fauna (fish, shrimp, and snails) are described for 21 streams in northeast Maui, Hawaii. Five streams (Waikamoi, Honomanu, Wailuanui, Kopiliula, and Hanawi Streams) were chosen as representative streams for intensive study. On each of the five streams, three representative reaches were selected: (1) immediately upstream of major surface-water diversions, (2) midway to the coast, and (3) near the coast. This study focused on five amphidromous native aquatic species (alamoo, nopili, nakea, opae, and hihiwai) that are abundant in the study area. The Physical Habitat Simulation (PHABSIM) System, which incorporates hydrology, stream morphology and microhabitat preferences to explore relations between streamflow and habitat availability, was used to simulate habitat/discharge relations for various species and life stages, and to provide quantitative habitat comparisons at different streamflows of interest. Hydrologic data, collected over a range of low-flow discharges, were used to calibrate hydraulic models of selected transects across the streams. The models were then used to predict water depth and velocity (expressed as a Froude number) over a range of discharges up to estimates of natural median streamflow. The biological importance of the stream hydraulic attributes was then assessed with the statistically derived suitability criteria for each native species and life stage that were developed as part of this study to produce a relation between discharge and habitat availability. The final output was expressed as a weighted habitat area of streambed for a representative stream reach. PHABSIM model results are presented to show the area of estimated usable bed habitat over a range of streamflows relative to natural conditions. In general, the models show a continuous decrease in habitat for all modeled species as streamflow is decreased from natural conditions. The PHABSIM modeling results from the intensively studied streams were normalized to develop relations between the relative amount of diversion from a stream and the resulting relative change in habitat in the stream. These relations can be used to estimate changes in habitat for diverted streams in the study area that were not intensively studied. The relations indicate that the addition of even a small amount of water to a dry stream has a significant effect on the amount of habitat available. Equations relating stream base-flow changes to habitat changes can be used to provide an estimate of the relative habitat change in the study area streams for which estimates of diverted and natural median base flow have been determined but for which detailed habitat models were not developed. Stream water temperatures, which could have an effect on stream ecology and taro cultivation, were measured in five streams in the study area. In general, the stream temperatures measured at any of the monitoring sites were not elevated enough, based on currently available information, to adversely effect the growth or mortality of native aquatic macrofauna or to cause wetland taro to be susceptible to fungi and associated rotting diseases.

Soil Moisture Initialization Error and Subgrid Variability of Precipitation in Seasonal Streamflow Forecasting

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Walker, Gregory K.; Mahanama, Sarith P.; Reichle, Rolf H.

2013-01-01

Offline simulations over the conterminous United States (CONUS) with a land surface model are used to address two issues relevant to 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 a realistic increase in the spatial resolution of forecasted precipitation would improve streamflow forecasts. The addition of error to a soil moisture initialization field is found to lead to a nearly proportional reduction in streamflow forecast skill. The linearity of the response allows the determination of a lower bound for the increase in streamflow forecast skill achievable through improved soil moisture estimation, e.g., through satellite-based soil moisture measurements. An increase in the resolution of precipitation is found to have an impact on large-scale streamflow forecasts only when evaporation variance is significant relative to the precipitation variance. This condition is met only in the western half of the CONUS domain. Taken together, the two studies demonstrate the utility of a continental-scale land surface modeling system as a tool for addressing the science of hydrological prediction.

Flood of June 11, 2010, in the Upper Little Missouri River watershed, Arkansas

USGS Publications Warehouse

Holmes, Robert R.; Wagner, Daniel M.

2011-01-01

Catastrophic flash flooding occurred in the early morning hours of June 11, 2010, in the upper Little Missouri River and tributary streams in southwest Arkansas. The flooding, which resulted in 20 fatalities and substantial property damage, was caused by as much as 4.7 inches of rain falling in the upper Little Missouri River watershed in 3 hours. The 4.7 inches of rain in 3 hours corresponds to estimated annual exceedance probability of approximately 2 percent for a 3-hour duration storm. The maximum total estimated rainfall in the upper Missouri River watershed was 5.3 inches in 6 hours. Peak streamflows and other hydraulic properties were determined at five ungaged locations and one gaged location in the upper Little Missouri River watershed.The peak streamflow for the Little Missouri River at Albert Pike, Arkansas was 40,100 cubic feet per second, estimated to have occurred between 4:00 AM and 4:30 AM the morning of June 11, 2010. The peak streamflow resulted in average water depths in the nearby floodplain (Area C of the Albert Pike Campground) of 7 feet flowing at velocities potentially as great as 11 feet per second. Peak streamflow 9.1 miles downstream on the Little Missouri at the U.S. Geological Survey streamgage near Langley, Arkansas was 70,800 cubic feet per second, which corresponds to an estimated annual exceedance probability of less than 1 percent.

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.

Simulation of streamflow in the Pleasant, Narraguagus, Sheepscot, and Royal Rivers, Maine, using watershed models

USGS Publications Warehouse

Dudley, Robert W.; Nielsen, Martha G.

2011-01-01

The U.S. Geological Survey (USGS) began a study in 2008 to investigate anticipated changes in summer streamflows and stream temperatures in four coastal Maine river basins and the potential effects of those changes on populations of endangered Atlantic salmon. To achieve this purpose, it was necessary to characterize the quantity and timing of streamflow in these rivers by developing and evaluating a distributed-parameter watershed model for a part of each river basin by using the USGS Precipitation-Runoff Modeling System (PRMS). The GIS (geographic information system) Weasel, a USGS software application, was used to delineate the four study basins and their many subbasins, and to derive parameters for their geographic features. The models were calibrated using a four-step optimization procedure in which model output was evaluated against four datasets for calibrating solar radiation, potential evapotranspiration, annual and seasonal water balances, and daily streamflows. The calibration procedure involved thousands of model runs that used the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The calibrated watershed models performed satisfactorily, in that Nash-Sutcliffe efficiency (NSE) statistic values for the calibration periods ranged from 0.59 to 0.75 (on a scale of negative infinity to 1) and NSE statistic values for the evaluation periods ranged from 0.55 to 0.73. The calibrated watershed models simulate daily streamflow at many locations in each study basin. These models enable natural resources managers to characterize the timing and amount of streamflow in order to support a variety of water-resources efforts including water-quality calculations, assessments of water use, modeling of population dynamics and migration of Atlantic salmon, modeling and assessment of habitat, and simulation of anticipated changes to streamflow and water temperature resulting from changes forecast for air temperature and precipitation.

Floods in Central Texas, September 7-14, 2010

USGS Publications Warehouse

Winters, Karl E.

2012-01-01

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

Assessing the viability of `over-the-loop' real-time short-to-medium range ensemble streamflow forecasts

NASA Astrophysics Data System (ADS)

Wood, A. W.; Clark, E.; Mendoza, P. A.; Nijssen, B.; Newman, A. J.; Clark, M. P.; Arnold, J.; Nowak, K. C.

2016-12-01

Many if not most national operational short-to-medium range streamflow prediction systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow are automated, but others require the hands-on-effort of an experienced human forecaster. This approach evolved out of the need to correct for deficiencies in the models and datasets that were available for forecasting, and often leads to skillful predictions despite the use of relatively simple, conceptual models. On the other hand, the process is not reproducible, which limits opportunities to assess and incorporate process variations, and the effort required to make forecasts in this way is an obstacle to expanding forecast services - e.g., though adding new forecast locations or more frequent forecast updates, running more complex models, or producing forecast ensembles and hindcasts that can support verification. In the last decade, the hydrologic forecasting community has begun to develop more centralized, `over-the-loop' systems. The quality of these new forecast products will depend on their ability to leverage research in areas including earth system modeling, parameter estimation, data assimilation, statistical post-processing, weather and climate prediction, verification, and uncertainty estimation through the use of ensembles. Currently, the operational streamflow forecasting and water management communities have little experience with the strengths and weaknesses of over-the-loop approaches, even as the systems are being rolled out in major operational forecasting centers. There is thus a need both to evaluate these forecasting advances and to demonstrate their potential in a public arena, raising awareness in forecast user communities and development programs alike. To address this need, the National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the US Army Corps of Engineers, using the NCAR 'System for Hydromet Analysis, Research, and Prediction' (SHARP) to implement, assess and demonstrate real-time over-the-loop forecasts. We present early hindcast and verification results from SHARP for short to medium range streamflow forecasts in a number of US case study watersheds.

Evaluation on uncertainty sources in projecting hydrological changes over the Xijiang River basin in South China

NASA Astrophysics Data System (ADS)

Yuan, Fei; Zhao, Chongxu; Jiang, Yong; Ren, Liliang; Shan, Hongcui; Zhang, Limin; Zhu, Yonghua; Chen, Tao; Jiang, Shanhu; Yang, Xiaoli; Shen, Hongren

2017-11-01

Projections of hydrological changes are associated with large uncertainties from different sources, which should be quantified for an effective implementation of water management policies adaptive to future climate change. In this study, a modeling chain framework to project future hydrological changes and the associated uncertainties in the Xijiang River basin, South China, was established. The framework consists of three emission scenarios (ESs), four climate models (CMs), four statistical downscaling (SD) methods, four hydrological modeling (HM) schemes, and four probability distributions (PDs) for extreme flow frequency analyses. Direct variance method was adopted to analyze the manner by which uncertainty sources such as ES, CM, SD, and HM affect the estimates of future evapotranspiration (ET) and streamflow, and to quantify the uncertainties of PDs in future flood and drought risk assessment. Results show that ES is one of the least important uncertainty sources in most situations. CM, in general, is the dominant uncertainty source for the projections of monthly ET and monthly streamflow during most of the annual cycle, daily streamflow below the 99.6% quantile level, and extreme low flow. SD is the most predominant uncertainty source in the projections of extreme high flow, and has a considerable percentage of uncertainty contribution in monthly streamflow projections in July-September. The effects of SD in other cases are negligible. HM is a non-ignorable uncertainty source that has the potential to produce much larger uncertainties for the projections of low flow and ET in warm and wet seasons than for the projections of high flow. PD contributes a larger percentage of uncertainty in extreme flood projections than it does in extreme low flow estimates. Despite the large uncertainties in hydrological projections, this work found that future extreme low flow would undergo a considerable reduction, and a noticeable increase in drought risk in the Xijiang River basin would be expected. Thus, the necessity of employing effective water-saving techniques and adaptive water resources management strategies for drought disaster mitigation should be addressed.

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

NASA Astrophysics Data System (ADS)

Müller, M. F.; Thompson, S. E.

2015-09-01

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

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

NASA Astrophysics Data System (ADS)

Müller, M. F.; Thompson, S. E.

2016-02-01

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

Summary of hydrologic modeling for the Delaware River Basin using the Water Availability Tool for Environmental Resources (WATER)

USGS Publications Warehouse

Williamson, Tanja N.; Lant, Jeremiah G.; Claggett, Peter; Nystrom, Elizabeth A.; Milly, Paul C.D.; Nelson, Hugh L.; Hoffman, Scott A.; Colarullo, Susan J.; Fischer, Jeffrey M.

2015-11-18

The Water Availability Tool for Environmental Resources (WATER) is a decision support system for the nontidal part of the Delaware River Basin that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions. In order to quantify the uncertainty associated with these simulations, however, streamflow and the associated hydroclimatic variables of potential evapotranspiration, actual evapotranspiration, and snow accumulation and snowmelt must be simulated and compared to long-term, daily observations from sites. This report details model development and optimization, statistical evaluation of simulations for 57 basins ranging from 2 to 930 km2 and 11.0 to 99.5 percent forested cover, and how this statistical evaluation of daily streamflow relates to simulating environmental changes and management decisions that are best examined at monthly time steps normalized over multiple decades. The decision support system provides a database of historical spatial and climatic data for simulating streamflow for 2001–11, in addition to land-cover and general circulation model forecasts that focus on 2030 and 2060. WATER integrates geospatial sampling of landscape characteristics, including topographic and soil properties, with a regionally calibrated hillslope-hydrology model, an impervious-surface model, and hydroclimatic models that were parameterized by using three hydrologic response units: forested, agricultural, and developed land cover. This integration enables the regional hydrologic modeling approach used in WATER without requiring site-specific optimization or those stationary conditions inferred when using a statistical model.

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, Horse Lake Creek, and Willow Creek watersheds, which are underlain mostly by Cretaceous-aged marine shale, was compositionally similar and had large concentrations of sulfate relative to the other streams in the study area, though the water from the Navajo River had lower specific-conductance values than did the water from Horse Lake Creek above Heron Reservoir and Willow Creek above Azotea Creek. Generally, surface-water quality varied with streamflow conditions throughout the year. Streamflow in spring and summer is generally a mixture of base flow (the component of streamflow derived from groundwater discharged to the stream channel) diluted with runoff from snowmelt and precipitation events, whereas streamflow in fall and winter is generally solely base flow. Major- and trace-element concentrations in the streams sampled were lower than U.S. Environmental Protection Agency primary and secondary drinking-water standards and New Mexico Environment Department surface-water standards for the streams. In general, years with increased annual discharge, compared to years with decreased annual discharge, had a smaller percentage of discharge in March, a larger percentage of discharge in June, an interval of discharge derived from snowmelt runoff that occurred later in the year, and a larger discharge in June. Additionally, years with increased annual discharge generally had a longer duration of runoff, and the streamflow indicators occurred at dates later in the year than the years with less snowmelt runoff. Additionally, the seasonal distribution of streamflow was more strongly controlled by the change in the amount of annual discharge than by changes in streamflow over time. The variation of streamflow conditions over time at one streamflow-gaging station in the study area, Navajo River at Banded Peak Ranch, was not significantly monotonic over the period of record with a Kendall’s tau of 0.0426 and with a p-value of 0.5938 for 1937 to 2009 (a trend was considered statistically significant at a p-value ≤ 0.05). There was a relation, however, such that annual discharge was generally lower than the median during a negative Pacific Decadal Oscillation interval and higher than the median during a positive Pacific Decadal Oscillation interval. Streamflow conditions at Navajo River at Banded Peak Ranch varied nonmonotonically over time and were likely a function of complex climate pattern interactions. Similarly, the monthly distribution of streamflow varied nonmonotonically over time and was likely a function of complex climate pattern interactions that cause variation over time. Study results indicated that the median of the sum of the streamflow available above the minimum monthly bypass requirement from Rio Blanco, Little Navajo River, and Navajo River was 126,240 acre-feet. The results also indicated that diversion of water for the San Juan–Chama Project has been possible for most months of most years.

Estimates of natural streamflow at two streamgages on the Esopus Creek, New York, water years 1932 to 2012

USGS Publications Warehouse

Burns, Douglas A.; Gazoorian, Christopher L.

2015-01-01

Natural discharge at the Mount Marion streamgage was estimated by summing the natural discharge estimated for the Coldbrook streamgage and the discharge estimated for the intervening basin area through application of the New York Streamflow Estimation Tool, recently developed for estimating unaltered streamflow at ungaged locations in the State. Estimates of natural daily discharge at the Mount Marion streamgage were about three times greater than gaged daily discharge throughout the moderate- to low-flow range from October 1, 1970, to September 30, 2012, the period of record for full water years at this streamgage. The relative difference between the two discharge time series declined as flow increased beyond the moderate range, but gaged daily discharge was still 25 to 43 percent less than estimated natural daily discharge for the high-flow metrics calculated in this analysis, and the mean relative difference was 43 percent for the annual 1-day maximum discharge. Overall, these estimates of natural discharge reflect the absence of effects of the Shandaken Tunnel and Ashokan Reservoir on flows in the Esopus Creek over broad time frames. However, caution is warranted if one is attempting to apply the natural estimates at short time scales because the regression prediction intervals indicate that uncertainty at a daily time step ranges from about 40 to 80 percent.

Wavelet-linear genetic programming: A new approach for modeling monthly streamflow

NASA Astrophysics Data System (ADS)

Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur

2017-06-01

The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.

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.

A technique to minimize uncertainties in load duration curves (LDCs) for water quality-impaired ungauged sites

EPA Science Inventory

For many water quality-impaired stream segments, streamflow and water quality monitoring sites are not available. Lack of available streamflow data at impaired ungauged sites leads to uncertainties in total maximum daily load (TMDL) estimation. We developed a technique to minimiz...

Low-flow characteristics of streams in South Carolina

USGS Publications Warehouse

Feaster, Toby D.; Guimaraes, Wladmir B.

2017-09-22

An ongoing understanding of streamflow characteristics of the rivers and streams in South Carolina is important for the protection and preservation of the State’s water resources. Information concerning the low-flow characteristics of streams is especially important during critical flow periods, such as during the historic droughts that South Carolina has experienced in the past few decades.Between 2008 and 2016, the U.S. Geological Survey, in cooperation with the South Carolina Department of Health and Environmental Control, updated low-flow statistics at 106 continuous-record streamgages operated by the U.S. Geological Survey for the eight major river basins in South Carolina. The low-flow frequency statistics included the annual minimum 1-, 3-, 7-, 14-, 30-, 60-, and 90-day mean flows with recurrence intervals of 2, 5, 10, 20, 30, and 50 years, depending on the length of record available at the streamflow-gaging station. Computations of daily mean flow durations for the 5-, 10-, 25-, 50-, 75-, 90-, and 95-percent probability of exceedance also were included.This report summarizes the findings from publications generated during the 2008 to 2016 investigations. Trend analyses for the annual minimum 7-day average flows are provided as well as trend assessments of long-term annual precipitation data. Statewide variability in the annual minimum 7-day average flow is assessed at eight long-term (record lengths from 55 to 78 years) streamgages. If previous low-flow statistics were available, comparisons with the updated annual minimum 7-day average flow, having a 10-year recurrence interval, were made. In addition, methods for estimating low-flow statistics at ungaged locations near a gaged location are described.

Methods for determining magnitude and frequency of floods in California, based on data through water year 2006

USGS Publications Warehouse

Gotvald, Anthony J.; Barth, Nancy A.; Veilleux, Andrea G.; Parrett, Charles

2012-01-01

Methods for estimating the magnitude and frequency of floods in California that are not substantially affected by regulation or diversions have been updated. Annual peak-flow data through water year 2006 were analyzed for 771 streamflow-gaging stations (streamgages) in California having 10 or more years of data. Flood-frequency estimates were computed for the streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to logarithms of annual peak flows for each streamgage. Low-outlier and historic information were incorporated into the flood-frequency analysis, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low outliers. Special methods for fitting the distribution were developed for streamgages in the desert region in southeastern California. Additionally, basin characteristics for the streamgages were computed by using a geographical information system. Regional regression analysis, using generalized least squares regression, was used to develop a set of equations for estimating flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for ungaged basins in California that are outside of the southeastern desert region. Flood-frequency estimates and basin characteristics for 630 streamgages were combined to form the final database used in the regional regression analysis. Five hydrologic regions were developed for the area of California outside of the desert region. The final regional regression equations are functions of drainage area and mean annual precipitation for four of the five regions. In one region, the Sierra Nevada region, the final equations are functions of drainage area, mean basin elevation, and mean annual precipitation. Average standard errors of prediction for the regression equations in all five regions range from 42.7 to 161.9 percent. For the desert region of California, an analysis of 33 streamgages was used to develop regional estimates of all three parameters (mean, standard deviation, and skew) of the log-Pearson Type III distribution. The regional estimates were then used to develop a set of equations for estimating flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for ungaged basins. The final regional regression equations are functions of drainage area. Average standard errors of prediction for these regression equations range from 214.2 to 856.2 percent. Annual peak-flow data through water year 2006 were analyzed for eight streamgages in California having 10 or more years of data considered to be affected by urbanization. Flood-frequency estimates were computed for the urban streamgages by fitting a Pearson Type III distribution to logarithms of annual peak flows for each streamgage. Regression analysis could not be used to develop flood-frequency estimation equations for urban streams because of the limited number of sites. Flood-frequency estimates for the eight urban sites were graphically compared to flood-frequency estimates for 630 non-urban sites. The regression equations developed from this study will be incorporated into the U.S. Geological Survey (USGS) StreamStats program. The StreamStats program is a Web-based application that provides streamflow statistics and basin characteristics for USGS streamgages and ungaged sites of interest. StreamStats can also compute basin characteristics and provide estimates of streamflow statistics for ungaged sites when users select the location of a site along any stream in California.

Entropy of hydrological systems under small samples: Uncertainty and variability

NASA Astrophysics Data System (ADS)

Liu, Dengfeng; Wang, Dong; Wang, Yuankun; Wu, Jichun; Singh, Vijay P.; Zeng, Xiankui; Wang, Lachun; Chen, Yuanfang; Chen, Xi; Zhang, Liyuan; Gu, Shenghua

2016-01-01

Entropy theory has been increasingly applied in hydrology in both descriptive and inferential ways. However, little attention has been given to the small-sample condition widespread in hydrological practice, where either hydrological measurements are limited or are even nonexistent. Accordingly, entropy estimated under this condition may incur considerable bias. In this study, small-sample condition is considered and two innovative entropy estimators, the Chao-Shen (CS) estimator and the James-Stein-type shrinkage (JSS) estimator, are introduced. Simulation tests are conducted with common distributions in hydrology, that lead to the best-performing JSS estimator. Then, multi-scale moving entropy-based hydrological analyses (MM-EHA) are applied to indicate the changing patterns of uncertainty of streamflow data collected from the Yangtze River and the Yellow River, China. For further investigation into the intrinsic property of entropy applied in hydrological uncertainty analyses, correlations of entropy and other statistics at different time-scales are also calculated, which show connections between the concept of uncertainty and variability.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Use of a forest sapwood area index to explain long-term variability in mean annual evapotranspiration and streamflow in moist eucalypt forests

NASA Astrophysics Data System (ADS)

Benyon, Richard G.; Lane, Patrick N. J.; Jaskierniak, Dominik; Kuczera, George; Haydon, Shane R.

2015-07-01

Mean sapwood thickness, measured in fifteen 73 year old Eucalyptus regnans and E. delegatensis stands, correlated strongly with forest overstorey stocking density (R2 0.72). This curvilinear relationship was used with routine forest stocking density and basal area measurements to estimate sapwood area of the forest overstorey at various times in 15 research catchments in undisturbed and disturbed forests located in the Great Dividing Range, Victoria, Australia. Up to 45 years of annual precipitation and streamflow data available from the 15 catchments were used to examine relationships between mean annual loss (evapotranspiration estimated as mean annual precipitation minus mean annual streamflow), and sapwood area. Catchment mean sapwood area correlated strongly (R2 0.88) with catchment mean annual loss. Variation in sapwood area accounted for 68% more variation in mean annual streamflow than precipitation alone (R2 0.90 compared with R2 0.22). Changes in sapwood area accounted for 96% of the changes in mean annual loss observed after forest thinning or clear-cutting and regeneration. We conclude that forest inventory data can be used reliably to predict spatial and temporal variation in catchment annual losses and streamflow in response to natural and imposed disturbances in even-aged forests. Consequently, recent advances in mapping of sapwood area using airborne light detection and ranging will enable high resolution spatial and temporal mapping of mean annual loss and mean annual streamflow over large areas of forested catchment. This will be particularly beneficial in management of water resources from forested catchments subject to disturbance but lacking reliable long-term (years to decades) streamflow records.

Model calibration criteria for estimating ecological flow characteristics

USGS Publications Warehouse

Vis, Marc; Knight, Rodney; Poole, Sandra; Wolfe, William J.; Seibert, Jan; Breuer, Lutz; Kraft, Philipp

2016-01-01

Quantification of streamflow characteristics in ungauged catchments remains a challenge. Hydrological modeling is often used to derive flow time series and to calculate streamflow characteristics for subsequent applications that may differ from those envisioned by the modelers. While the estimation of model parameters for ungauged catchments is a challenging research task in itself, it is important to evaluate whether simulated time series preserve critical aspects of the streamflow hydrograph. To address this question, seven calibration objective functions were evaluated for their ability to preserve ecologically relevant streamflow characteristics of the average annual hydrograph using a runoff model, HBV-light, at 27 catchments in the southeastern United States. Calibration trials were repeated 100 times to reduce parameter uncertainty effects on the results, and 12 ecological flow characteristics were computed for comparison. Our results showed that the most suitable calibration strategy varied according to streamflow characteristic. Combined objective functions generally gave the best results, though a clear underprediction bias was observed. The occurrence of low prediction errors for certain combinations of objective function and flow characteristic suggests that (1) incorporating multiple ecological flow characteristics into a single objective function would increase model accuracy, potentially benefitting decision-making processes; and (2) there may be a need to have different objective functions available to address specific applications of the predicted time series.

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.

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.

Hydrology and trout populations of cold-water rivers of Michigan and Wisconsin

USGS Publications Warehouse

Hendrickson, G.E.; Knutilla, R.L.

1974-01-01

Statistical multiple-regression analyses showed significant relationships between trout populations and hydrologic parameters. Parameters showing the higher levels of significance were temperature, hardness of water, percentage of gravel bottom, percentage of bottom vegetation, variability of streamflow, and discharge per unit drainage area. Trout populations increase with lower levels of annual maximum water temperatures, with increase in water hardness, and with increase in percentage of gravel and bottom vegetation. Trout populations also increase with decrease in variability of streamflow, and with increase in discharge per unit drainage area. Most hydrologic parameters were significant when evaluated collectively, but no parameter, by itself, showed a high degree of correlation with trout populations in regression analyses that included all the streams sampled. Regression analyses of stream segments that were restricted to certain limits of hardness, temperature, or percentage of gravel bottom showed improvements in correlation. Analyses of trout populations, in pounds per acre and pounds per mile and hydrologic parameters resulted in regression equations from which trout populations could be estimated with standard errors of 89 and 84 per cent, respectively.

Gazetteer of hydrologic characteristics of streams in Massachusetts; Blackstone River basin

USGS Publications Warehouse

Wandle, S.W.; Phipps, A.F.

1984-01-01

The Blackstone River basin encompasses 335 square miles in south-central Massachusetts, including parts of Bristol, Middlesex, Norfolk, and Worcester Counties. Drainage areas, using the latest available 1:24,000 scale topographic maps, were computed for the first time for streams draining more than 3 square miles and were recomputed for data-collection sites. Streamflow characteristics, were calculated using a new data base with records through 1980. These characteristics include annual and monthly flow statistics, duration of daily flow values, and the annual 7-day mean low flow at the 2-year and 10-year recurrence intervals. The 7-day, 10-year low-flow values are presented for 31 partial-record sites and the procedures used to determine the hydrologic characteristics of the basin are summarized. Basin characteristics representing 14 commonly used indices to estimate various streamflows are presented for the six gaged streams in the Blackstone River basin. This gazetteer will aid in the planning and siting of water-resources-related activities and will provide a common data base for governmental agencies and the engineering and planning communities. (USGS)

Escherichia coli bacteria density in relation to turbidity, streamflow characteristics, and season in the Chattahoochee River near Atlanta, Georgia, October 2000 through September 2008—Description, statistical analysis, and predictive modeling

USGS Publications Warehouse

Lawrence, Stephen J.

2012-01-01

Regression analyses show that E. coli density in samples was strongly related to turbidity, streamflow characteristics, and season at both sites. The regression equation chosen for the Norcross data showed that 78 percent of the variability in E. coli density (in log base 10 units) was explained by the variability in turbidity values (in log base 10 units), streamflow event (dry-weather flow or stormflow), season (cool or warm), and an interaction term that is the cross product of streamflow event and turbidity. The regression equation chosen for the Atlanta data showed that 76 percent of the variability in E. coli density (in log base 10 units) was explained by the variability in turbidity values (in log base 10 units), water temperature, streamflow event, and an interaction term that is the cross product of streamflow event and turbidity. Residual analysis and model confirmation using new data indicated the regression equations selected at both sites predicted E. coli density within the 90 percent prediction intervals of the equations and could be used to predict E. coli density in real time at both sites.

Methods for estimating magnitude and frequency of peak flows for natural streams in Utah

USGS Publications Warehouse

Kenney, Terry A.; Wilkowske, Chris D.; Wright, Shane J.

2007-01-01

Estimates of the magnitude and frequency of peak streamflows is critical for the safe and cost-effective design of hydraulic structures and stream crossings, and accurate delineation of flood plains. Engineers, planners, resource managers, and scientists need accurate estimates of peak-flow return frequencies for locations on streams with and without streamflow-gaging stations. The 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence-interval flows were estimated for 344 unregulated U.S. Geological Survey streamflow-gaging stations in Utah and nearby in bordering states. These data along with 23 basin and climatic characteristics computed for each station were used to develop regional peak-flow frequency and magnitude regression equations for 7 geohydrologic regions of Utah. These regression equations can be used to estimate the magnitude and frequency of peak flows for natural streams in Utah within the presented range of predictor variables. Uncertainty, presented as the average standard error of prediction, was computed for each developed equation. Equations developed using data from more than 35 gaging stations had standard errors of prediction that ranged from 35 to 108 percent, and errors for equations developed using data from less than 35 gaging stations ranged from 50 to 357 percent.

Regional regression of flood characteristics employing historical information

USGS Publications Warehouse

Tasker, Gary D.; Stedinger, J.R.

1987-01-01

Streamflow gauging networks provide hydrologic information for use in estimating the parameters of regional regression models. The regional regression models can be used to estimate flood statistics, such as the 100 yr peak, at ungauged sites as functions of drainage basin characteristics. A recent innovation in regional regression is the use of a generalized least squares (GLS) estimator that accounts for unequal station record lengths and sample cross correlation among the flows. However, this technique does not account for historical flood information. A method is proposed here to adjust this generalized least squares estimator to account for possible information about historical floods available at some stations in a region. The historical information is assumed to be in the form of observations of all peaks above a threshold during a long period outside the systematic record period. A Monte Carlo simulation experiment was performed to compare the GLS estimator adjusted for historical floods with the unadjusted GLS estimator and the ordinary least squares estimator. Results indicate that using the GLS estimator adjusted for historical information significantly improves the regression model. ?? 1987.

Hydrologic Drought Decision Support System (HyDroDSS)

USGS Publications Warehouse

Granato, Gregory E.

2014-01-01

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

Analysis of temperature profiles for investigating stream losses beneath ephemeral channels

USGS Publications Warehouse

Constantz, Jim; Stewart, Amy E.; Niswonger, Richard G.; Sarma, Lisa

2002-01-01

Continuous estimates of streamflow are challenging in ephemeral channels. The extremely transient nature of ephemeral streamflows results in shifting channel geometry and degradation in the calibration of streamflow stations. Earlier work suggests that analysis of streambed temperature profiles is a promising technique for estimating streamflow patterns in ephemeral channels. The present work provides a detailed examination of the basis for using heat as a tracer of stream/groundwater exchanges, followed by a description of an appropriate heat and water transport simulation code for ephemeral channels, as well as discussion of several types of temperature analysis techniques to determine streambed percolation rates. Temperature‐based percolation rates for three ephemeral stream sites are compared with available surface water estimates of channel loss for these sites. These results are combined with published results to develop conclusions regarding the accuracy of using vertical temperature profiles in estimating channel losses. Comparisons of temperature‐based streambed percolation rates with surface water‐based channel losses indicate that percolation rates represented 30% to 50% of the total channel loss. The difference is reasonable since channel losses include both vertical and nonvertical component of channel loss as well as potential evapotranspiration losses. The most significant advantage of the use of sediment‐temperature profiles is their robust and continuous nature, leading to a long‐term record of the timing and duration of channel losses and continuous estimates of streambed percolation. The primary disadvantage is that temperature profiles represent the continuous percolation rate at a single point in an ephemeral channel rather than an average seepage loss from the entire channel.

Assessing the controls and uncertainties on mean transit times in contrasting headwater catchments

NASA Astrophysics Data System (ADS)

Cartwright, Ian; Irvine, Dylan; Burton, Chad; Morgenstern, Uwe

2018-02-01

Estimating the time required for water to travel through headwater catchments from where it recharges to where it discharges into streams (the transit time) is important for understanding catchment behaviour. This study uses tritium (3H) activities of stream water to estimate the mean transit times of water in the upper Latrobe and Yarra catchments, southeast Australia, at different flow conditions. The 3H activities of the stream water were between 1.26 and 1.99 TU, which are lower than those of local rainfall (2.6 to 3.0 TU). 3H activities in individual subcatchments are almost invariably lowest at low streamflows. Mean transit times calculated from the 3H activities using a range of lumped parameter models are between 7 and 62 years and are longest during low streamflows. Uncertainties in the estimated mean transit times result from uncertainties in the geometry of the flow systems, uncertainties in the 3H input, and macroscopic mixing. In addition, simulation of 3H activities in FEFLOW indicates that heterogeneous hydraulic conductivities increase the range of mean transit times corresponding to a specific 3H activity. The absolute uncertainties in the mean transit times may be up to ±30 years. However, differences between mean transit times at different streamflows in the same catchment or between different subcatchments in the same area are more reliably estimated. Despite the uncertainties, the conclusions that the mean transit times are years to decades and decrease with increasing streamflow are robust. The seasonal variation in major ion geochemistry and 3H activities indicate that the higher general streamflows in winter are sustained by water displaced from shallower younger stores (e.g., soils or regolith). Poor correlations between 3H activities and catchment area, drainage density, mean slope, distance to stream, and landuse, imply that mean transit times are controlled by a variety of factors including the hydraulic properties of the soils and aquifers that are difficult to characterise spatially. The long mean transit times imply that there are long-lived stores of water in these catchments that may sustain streamflow over drought periods. Additionally, there may be considerable delay in contaminants reaching the stream.

ESTIMATING LOW-FLOW FREQUENCIES OF UNGAGED STREAMS IN NEW ENGLAND.

USGS Publications Warehouse

Wandle, S. William

1987-01-01

Equations to estimate low flows were developed using multiple-regression analysis with a sample of 48 river basins, which were selected from the U. S. Geological Survey's network of gaged river basins in Massachusetts, New Hampshire, Rhode Island, Vermont, and southwestern Maine. Low-flow characteristics are represented by the 7Q2 and 7Q10 (the annual minimum 7-day mean low flow at the 2- and 10-year recurrence intervals). These statistics for each of the 48 basins were determined from a low-flow frequency analysis of streamflow records for 1942-71, or from a graphical or mathematical relationship if the record did not cover this 30-year period. Estimators for the mean and variance of the 7-day low flows at the index and short-term sites were used for two stations where discharge measurements of base flow were available and for two sites where the graphical technique was unsatisfactory.

An analysis of annual maximum streamflows in Terengganu, Malaysia using TL-moments approach

NASA Astrophysics Data System (ADS)

Ahmad, Ummi Nadiah; Shabri, Ani; Zakaria, Zahrahtul Amani

2013-02-01

TL-moments approach has been used in an analysis to determine the best-fitting distributions to represent the annual series of maximum streamflow data over 12 stations in Terengganu, Malaysia. The TL-moments with different trimming values are used to estimate the parameter of the selected distributions namely: generalized pareto (GPA), generalized logistic, and generalized extreme value distribution. The influence of TL-moments on estimated probability distribution functions are examined by evaluating the relative root mean square error and relative bias of quantile estimates through Monte Carlo simulations. The boxplot is used to show the location of the median and the dispersion of the data, which helps in reaching the decisive conclusions. For most of the cases, the results show that TL-moments with one smallest value was trimmed from the conceptual sample (TL-moments (1,0)), of GPA distribution was the most appropriate in majority of the stations for describing the annual maximum streamflow series in Terengganu, Malaysia.

An integrated uncertainty analysis and data assimilation approach for improved streamflow predictions

NASA Astrophysics Data System (ADS)

Hogue, T. S.; He, M.; Franz, K. J.; Margulis, S. A.; Vrugt, J. A.

2010-12-01

The current study presents an integrated uncertainty analysis and data assimilation approach to improve streamflow predictions while simultaneously providing meaningful estimates of the associated uncertainty. Study models include the National Weather Service (NWS) operational snow model (SNOW17) and rainfall-runoff model (SAC-SMA). The proposed approach uses the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) to simultaneously estimate uncertainties in model parameters, forcing, and observations. An ensemble Kalman filter (EnKF) is configured with the DREAM-identified uncertainty structure and applied to assimilating snow water equivalent data into the SNOW17 model for improved snowmelt simulations. Snowmelt estimates then serves as an input to the SAC-SMA model to provide streamflow predictions at the basin outlet. The robustness and usefulness of the approach is evaluated for a snow-dominated watershed in the northern Sierra Mountains. This presentation describes the implementation of DREAM and EnKF into the coupled SNOW17 and SAC-SMA models and summarizes study results and findings.

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.

Controlling suspended samplers by programmable calculator and interface circuitry

Treesearch

Rand E. Eads; Mark R. Boolootian

1985-01-01

A programmable calculator connected to an interface circuit can control automatic samplers and record streamflow data. The circuit converts a voltage representing water stage to a digital signal. The sampling program logs streamflow data when there is a predefined deviation from a linear trend in the water elevation. The calculator estimates suspended sediment...

Controlling suspended sediment samplers by programmable calculator and interface circuitry

Treesearch

Rand E. Eads; Mark R. Boolootian

1985-01-01

A programmable calculator connected to an interface circuit can control automatic samplers and record streamflow data. The circuit converts a voltage representing water stage to a digital signal. The sampling program logs streamflow data when there is a predefined deviation from a linear trend in the water elevation. The calculator estimates suspended sediment...

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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 information systems (GIS). If measurement sites are used separately from reaches, the maximum scale of 1:100,000 should not be exceeded. When used in conjunction with the reach segments, the maximum scale should not exceed 1:250,000.

Low-flow analysis and selected flow statistics representative of 1930-2002 for streamflow-gaging stations in or near West Virginia

USGS Publications Warehouse

Wiley, Jeffrey B.

2006-01-01

Five time periods between 1930 and 2002 are identified as having distinct patterns of annual minimum daily mean flows (minimum flows). Average minimum flows increased around 1970 at many streamflow-gaging stations in West Virginia. Before 1930, however, there might have been a period of minimum flows greater than any period identified between 1930 and 2002. The effects of climate variability are probably the principal causes of the differences among the five time periods. Comparisons of selected streamflow statistics are made between values computed for the five identified time periods and values computed for the 1930-2002 interval for 15 streamflow-gaging stations. The average difference between statistics computed for the five time periods and the 1930-2002 interval decreases with increasing magnitude of the low-flow statistic. The greatest individual-station absolute difference was 582.5 percent greater for the 7-day 10-year low flow computed for 1970-1979 compared to the value computed for 1930-2002. The hydrologically based low flows indicate approximately equal or smaller absolute differences than biologically based low flows. The average 1-day 3-year biologically based low flow (1B3) and 4-day 3-year biologically based low flow (4B3) are less than the average 1-day 10-year hydrologically based low flow (1Q10) and 7-day 10-year hydrologic-based low flow (7Q10) respectively, and range between 28.5 percent less and 13.6 percent greater. Seasonally, the average difference between low-flow statistics computed for the five time periods and 1930-2002 is not consistent between magnitudes of low-flow statistics, and the greatest difference is for the summer (July 1-September 30) and fall (October 1-December 31) for the same time period as the greatest difference determined in the annual analysis. The greatest average difference between 1B3 and 4B3 compared to 1Q10 and 7Q10, respectively, is in the spring (April 1-June 30), ranging between 11.6 and 102.3 percent greater. Statistics computed for the individual station's record period may not represent the statistics computed for the period 1930 to 2002 because (1) station records are available predominantly after about 1970 when minimum flows were greater than the average between 1930 and 2002 and (2) some short-term station records are mostly during dry periods, whereas others are mostly during wet periods. A criterion-based sampling of the individual station's record periods at stations was taken to reduce the effects of statistics computed for the entire record periods not representing the statistics computed for 1930-2002. The criterion used to sample the entire record periods is based on a comparison between the regional minimum flows and the minimum flows at the stations. Criterion-based sampling of the available record periods was superior to record-extension techniques for this study because more stations were selected and areal distribution of stations was more widespread. Principal component and correlation analyses of the minimum flows at 20 stations in or near West Virginia identify three regions of the State encompassing stations with similar patterns of minimum flows: the Lower Appalachian Plateaus, the Upper Appalachian Plateaus, and the Eastern Panhandle. All record periods of 10 years or greater between 1930 and 2002 where the average of the regional minimum flows are nearly equal to the average for 1930-2002 are determined as representative of 1930-2002. Selected statistics are presented for the longest representative record period that matches the record period for 77 stations in West Virginia and 40 stations near West Virginia. These statistics can be used to develop equations for estimating flow in ungaged stream locations.

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 measurement. This process was repeated to develop a set of DiscQ50 estimates for all simulated instantaneous measurements, a weighted DiscQ50 estimate was formed from this set. Results indicated that the expected value of this weighted estimate was more precise than the IndxQ50 estimate for all measurement intensities evaluated. The integrated index-flow estimator, IntgQ50, was formed by computing a weighted average of the index estimate IndxQ50 and the DiscQ50 estimate. Results indicated that the IntgQ50 estimator was more precise than the DiscQ50 estimator at low measurement intensities of one to two measurements. At greater measurement intensities, the precision of the IntgQ50 estimator converges to the DiscQ50 estimator. Neither the DiscQ50 nor the IntgQ50 estimators provided site-specific estimates. In particular, although expected values of DiscQ50 and IntgQ50 estimates converge with increasing measurement intensity, they do not necessarily converge to the site-specific value of Q50. The site estimator of flow, SiteQ50, was developed to facilitate this convergence at higher measurement intensities. This is accomplished by use of the median of simulated instantaneous flow values for each measurement intensity level. A weighted estimate of the median and information associated with the IntgQ50 estimate was used to form the SiteQ50 estimate. Initial simulations indicate that the SiteQ50 estimator generally has greater precision than the IntgQ50 estimator at measurement intensities greater than 3, however, additional analysis is needed to identify streamflow conditions under which instantaneous measurements will produce estimates that generally converge to the index flows. A preliminary augmented index regression equation was developed, which contains the index regression estimate and two additional variables associated with base-flow recession characteristics. When these recession variables were estimated as the medians of recession parameters compute

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

USGS Publications Warehouse

Moore, Stephanie J.; Stonestrom, David A.; Constantz, Jim; Ferré, Ty P.A.; Leake, Stanley A.

2007-01-01

Infiltration events in channels that flow only sporadically produce focused recharge to the Tesuque aquifer in the Española Basin. The current study examined the quantity and timing of streamflow and associated infiltration in Arroyo Hondo, an unregulated mountain-front stream that enters the basin from the western slope of the Sangre de Cristo Mountains. Traditional methods of stream gaging were combined with environmental-tracer based methods to provide the estimates. The study was conducted during a three-year period, October 1999–October 2002. The period was characterized by generally low precipitation and runoff. Summer monsoonal rains produced four brief periods of streamflow in water year 2000, only three of which extended beyond the mountain front, and negligible runoff in subsequent years. The largest peak flow during summer monsoon events was 0.59 cubic meters per second. Snowmelt was the main contributor to annual streamflow. Snowmelt produced more cumulative flow downstream from the mountain front during the study period than summer monsoonal rains.The presence or absence of streamflow downstream of the mountain front was determined by interpretation of streambed thermographs. Infiltration rates were estimated by numerical modeling of transient vertical streambed temperature profiles. Snowmelt extended throughout the instrumented reach during the spring of 2001. Flow was recorded at a station two kilometers downstream from the mountain front for six consecutive days in March. Inverse modeling of this event indicated an average infiltration rate of 1.4 meters per day at this location. For the entire study reach, the estimated total annual volume of infiltration ranged from 17,100 to 246,000 m3 during water years 2000 and 2001. During water year 2002, due to severe drought, streamflow and streambed infiltration in the study reach were both zero.

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

USGS Publications Warehouse

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

2002-01-01

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

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.

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

USGS Publications Warehouse

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

2003-01-01

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

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

USGS Publications Warehouse

Gotvald, Anthony J.; Oberg, Kevin A.

2009-01-01

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

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

USGS Publications Warehouse

Ruddy, Barbara C.; Williams, Cory A.

2007-01-01

In 2007, the U.S. Geological Survey, in cooperation with Bowie Mining Company, initiated a study to characterize the streamflow and streamflow gain-loss in a reach of Hubbard Creek in Delta County, Colorado, in the vicinity of a mine-permit area planned for future coal mining. Premining streamflow characteristics and streamflow gain-loss variation were determined so that pre- and postmining gain-loss characteristics could be compared. This report describes the methods used in this study and the results of two streamflow-measurement sets collected during low-flow conditions. Streamflow gain-loss measurements were collected using rhodamine WT and sodium bromide tracers at four sites spanning the mine-permit area on June 26-28, 2007. Streamflows were estimated and compared between four measurement sites within three stream subreaches of the study reach. Data from two streamflow-gaging stations on Hubbard Creek upstream and downstream from the mine-permit area were evaluated. Streamflows at the stations were continuous, and flow at the upstream station nearly always exceeded the streamflow at the downstream station. Furthermore, streamflow at both stations showed similar diurnal patterns with traveltime offsets. On June 26, streamflow from the gain-loss measurements was greater at site 1 (most upstream site) than at site 4 (most downstream site); on June 27, streamflow was greater at site 4 than at site 2; and on June 27, there was no difference in streamflow between sites 2 and 3. Data from streamflow-gaging stations 09132940 and 09132960 showed diurnal variations and overall decreasing streamflow over time. The data indicate a dynamic system, and streamflow can increase or decrease depending on hydrologic conditions. The streamflow within the study reach was greater than the streamflows at either the upstream or downstream stations. A second set of gain-loss measurements was collected at sites 2 and 4 on November 8-9, 2007. On November 8, streamflow was greater at site 4 than at site 2, and on the following day, November 9, streamflow was greater at site 2 than at site 4. Data collection on November 8 occurred while the streamflow was increasing due to contributions from stream ice melting throughout different parts of the basin. Data collection on November 9 occurred earlier in the day with less stream ice melting and more steady-state conditions, so the indication that streamflow decreased between sites 2 and 4 may be more accurate. Diurnal variations in streamflow are common at both the upper and the lower streamflow-gaging stations. The upper streamflow-gaging station shows a melt-freeze influence from tributaries to Hubbard Creek during the winter season. Downstream from the study reach, observed diurnal variation is likely due to evapotranspiration associated with dense flood-plain vegetation, which consumes water from the creek during the middle of the day. Varying diurnal patterns in streamflow, combined with possible variations in tributary inflows to Hubbard Creek in the study reach, probably account for the observed variations in streamflow at the tracer measurement sites. During both sampling periods in June and November 2007, conditions were less than ideal and not steady state. The June 27 sampling indicates that the streamflow was increasing between measurement sites 2 and 4, and the November 9 sampling indicates that the streamflow was decreasing between measurement sites 2 and 4. The data collected during the diurnal and day-to-day variations in streamflow indicated that the streamflow reach is dynamic and can be gaining, losing, or constant.

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.

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.

Effects of water use and land use on streamflow and aquatic habitat in the Sudbury and Assabet River Basins, Massachusetts

USGS Publications Warehouse

Zarriello, Phillip J.; Parker, Gene W.; Armstrong, David S.; Carlson, Carl S.

2010-01-01

Water withdrawals from surface-water reservoirs and groundwater have affected streamflow in the Sudbury and Assabet River Basins. These effects are particularly evident in the upper Sudbury River Basin, which prompted the need to improve the understanding of water resources and aquatic habitat in these basins. In 2004, the U.S. Geological Survey, in cooperation with the Massachusetts Department of Conservation and Recreation, developed a precipitation-runoff model that uses Hydrologic Simulation Program-FORTRAN (HSPF) to evaluate the effects of water use and projected future water-use and land-use change on streamflow. As part of this study, the aquatic habitat in the basins and the effects of streamflow alteration also were evaluated. Chapter 1 of the report covers the development of the HSPF model that focuses on the upper Sudbury River Basin (106 square miles) but covers the entire Sudbury and Assabet River Basins (339 square miles). The model was calibrated to an 11-year period (1993-2003) using observed or estimated streamflow at four streamgages. The model was then used to simulate long-term (1960-2004) streamflows to evaluate the effects of average 1993-2003 water use and projected 2030 water-use and land-use change over long-term climatic conditions. Simulations indicate that the average 1993-2003 withdrawals most altered streamflow relative to no withdrawals in small headwater subbasins where the ratios of mean annual withdrawals to mean annual streamflow are the highest. The effects of withdrawals are also appreciable in other parts of the upper Sudbury River Basin as a result of the perpetuation of the effects of large withdrawals in upstream reaches or in subbasins that also have a high ratio of withdrawal to streamflow. The simulated effects of potential 2030 water-use and land-use change indicate small decreases in flows as a result of increased water demands, but these flow alterations were offset as a result of decreased evapotranspiration associated with the loss of deep-rooted vegetation. Simulations of reactivating production wells near the north end of Lake Cochituate indicate pumping could substantially affect lake levels and flows at the lake outlet or in nearby reaches in the Sudbury River during periods of low flow, but the effects vary depending on the source of the water to the wells, which is largely unknown. Chapter 2 of the report covers the fish-community assessment and comparison of streamflow-setting standards for protecting aquatic habitat. The fish-community assessment indicates the main stems of the Sudbury and Assabet Rivers are dominated by macrohabitat generalists. Water temperatures recorded in seven free-flowing reaches in the upper Sudbury River Basin at three sites unaffected by withdrawals or impoundments are generally suitable for cold-water fish; however, summer temperatures often rose to a level considered critical to long-term survival of brook trout. At four sites downstream from withdrawals or reservoirs, or both, summer water temperatures were often in the upper critical range for brook trout survival. Physically and statistically based methods for determining streamflows for protecting aquatic habitat were applied at 10 selected riffle sites in the Sudbury and Assabet River Basins. Physically based methods, R2Cross and Wetted-Perimeter, use site-specific physical and hydraulic information and a one-dimensional hydraulics model, HEC-RAS, to determine flows that meet the criteria set forth by the method. The median flow that meets 2-of-3 of the R2Cross hydraulic criteria (percentage of bankfull wetted perimeter, average velocity, and mean depth) ranged from about 0.07 to 0.72 cubic feet per second per square mile (ft3/s/mi2) with an overall median of about 0.24 ft3/s/mi2; the median Wetted-Perimeter target flow ranged from about 0.10 to 0.51 ft3/s/mi2 with an overall median of about 0.25 ft3/s/mi2. Statistically based methods?Tennant, New England Aquatic Base Flow (ABF)

Assessing changes in failure probability of dams in a changing climate

NASA Astrophysics Data System (ADS)

Mallakpour, I.; AghaKouchak, A.; Moftakhari, H.; Ragno, E.

2017-12-01

Dams are crucial infrastructures and provide resilience against hydrometeorological extremes (e.g., droughts and floods). In 2017, California experienced series of flooding events terminating a 5-year drought, and leading to incidents such as structural failure of Oroville Dam's spillway. Because of large socioeconomic repercussions of such incidents, it is of paramount importance to evaluate dam failure risks associated with projected shifts in the streamflow regime. This becomes even more important as the current procedures for design of hydraulic structures (e.g., dams, bridges, spillways) are based on the so-called stationary assumption. Yet, changes in climate are anticipated to result in changes in statistics of river flow (e.g., more extreme floods) and possibly increasing the failure probability of already aging dams. Here, we examine changes in discharge under two representative concentration pathways (RCPs): RCP4.5 and RCP8.5. In this study, we used routed daily streamflow data from ten global climate models (GCMs) in order to investigate possible climate-induced changes in streamflow in northern California. Our results show that while the average flow does not show a significant change, extreme floods are projected to increase in the future. Using the extreme value theory, we estimate changes in the return periods of 50-year and 100-year floods in the current and future climates. Finally, we use the historical and future return periods to quantify changes in failure probability of dams in a warming climate.

NASA-modified precipitation products to improve USEPA nonpoint source water quality modeling for the Chesapeake Bay.

PubMed

Nigro, Joseph; Toll, David; Partington, Ed; Ni-Meister, Wenge; Lee, Shihyan; Gutierrez-Magness, Angelica; Engman, Ted; Arsenault, Kristi

2010-01-01

The USEPA has estimated that over 20,000 water bodies within the United States do not meet water quality standards. One of the regulations in the Clean Water Act of 1972 requires states to monitor the total maximum daily load, or the amount of pollution that can be carried by a water body before it is determined to be "polluted," for any watershed in the United States (Copeland, 2005). In response to this mandate, the USEPA developed Better Assessment Science Integrating Nonpoint Sources (BASINS) as a decision support tool for assessing pollution and to guide the decision-making process for improving water quality. One of the models in BASINS, the Hydrological Simulation Program-Fortran (HSPF), computes continuous streamflow rates and pollutant concentration at each basin outlet. By design, precipitation and other meteorological data from weather stations serve as standard model input. In practice, these stations may be unable to capture the spatial heterogeneity of precipitation events, especially if they are few and far between. An attempt was made to resolve this issue by substituting station data with NASA-modified/NOAA precipitation data. Using these data within HSPF, streamflow was calculated for seven watersheds in the Chesapeake Bay Basin during low flow periods, convective storm periods, and annual flows. In almost every case, the modeling performance of HSPF increased when using the NASA-modified precipitation data, resulting in better streamflow statistics and, potentially, in improved water quality assessment.

Montana StreamStats

USGS Publications Warehouse

2016-04-05

About this volumeMontana StreamStats is a Web-based geographic information system (http://water.usgs.gov/osw/streamstats/) application that provides users with access to basin and streamflow characteristics for gaged and ungaged streams in Montana. Montana StreamStats was developed by the U.S. Geological Survey (USGS) in cooperation with the Montana Departments of Transportation, Environmental Quality, and Natural Resources and Conservation. The USGS Scientific Investigations Report consists of seven independent but complementary chapters dealing with various aspects of this effort.Chapter A describes the Montana StreamStats application, the basin and streamflow datasets, and provides a brief overview of the streamflow characteristics and regression equations used in the study. Chapters B through E document the datasets, methods, and results of analyses to determine streamflow characteristics, such as peak-flow frequencies, low-flow frequencies, and monthly and annual characteristics, for USGS streamflow-gaging stations in and near Montana. The StreamStats analytical toolsets that allow users to delineate drainage basins and solve regression equations to estimate streamflow characteristics at ungaged sites in Montana are described in Chapters F and G.

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

USGS Publications Warehouse

Ortel, Terry W.; Spies, Ryan R.

2015-11-19

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

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

USGS Publications Warehouse

Wilby, Robert L.; Dettinger, Michael D.

2000-01-01

Simulations of future climate using general circulation models (GCMs) suggest that rising concentrations of greenhouse gases may have significant consequences for the global climate. Of less certainty is the extent to which regional scale (i.e., sub-GCM grid) environmental processes will be affected. In this chapter, a range of downscaling techniques are critiqued. Then a relatively simple (yet robust) statistical downscaling technique and its use in the modelling of future runoff scenarios for three river basins in the Sierra Nevada, California, is described. This region was selected because GCM experiments driven by combined greenhouse-gas and sulphate-aerosol forcings consistently show major changes in the hydro-climate of the southwest United States by the end of the 21st century. The regression-based downscaling method was used to simulate daily rainfall and temperature series for streamflow modelling in three Californian river basins under current-and future-climate conditions. The downscaling involved just three predictor variables (specific humidity, zonal velocity component of airflow, and 500 hPa geopotential heights) supplied by the U.K. Meteorological Office couple ocean-atmosphere model (HadCM2) for the grid point nearest the target basins. When evaluated using independent data, the model showed reasonable skill at reproducing observed area-average precipitation, temperature, and concomitant streamflow variations. Overall, the downscaled data resulted in slight underestimates of mean annual streamflow due to underestimates of precipitation in spring and positive temperature biases in winter. Differences in the skill of simulated streamflows amongst the three basins were attributed to the smoothing effects of snowpack on streamflow responses to climate forcing. The Merced and American River basins drain the western, windward slope of the Sierra Nevada and are snowmelt dominated, whereas the Carson River drains the eastern, leeward slope and is a mix of rainfall runoff and snowmelt runoff. Simulated streamflow in the American River responds rapidly and sensitively to daily-scale temperature and precipitation fluctuations and errors; in the Merced and Carson Rivers, the response to the same short-term influences is much less. Consequently, the skill of simulated flows was significantly lower in the American River model than in the Carson and Merced. The physiography of the three basins also accounts for differences in their sensitivities to future climate change. Increases in winter precipitation exceeding +100% coupled with mean temperature rises greater than +2°C result in increased winter streamflows in all three basins. In the Merced and Carson basins, these streamflow increases reflect large changes in winter snowpack, whereas the streamflow changes in the lower elevation American basin are driven primarily by rainfall runoff. Furthermore, reductions in winter snowpack in the American River basin, owing to less precipitation falling as snow and earlier melting of snow at middle elevations, lead to less spring and summer streamflow. Taken collectively, the downscaling results suggest significant changes to both the timing and magnitude of streamflows in the Sierra Nevada by the end of the 21st Century. In the higher elevation basins, the HadCM2 scenario implies more annual streamflow and more streamflow during the spring and summer months that are critical for water-resources management in California. Depending on the relative significance of rainfall runoff and snowmelt, each basin responds in its own way to regional climate forcing. Generally, then, climate scenarios need to be specified — by whatever means — with sufficient temporal and spatial resolution to capture subtle orographic influences if projections of climate-change responses are to be useful and reproducible.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

Thermal effects of dams in the Willamette River basin, Oregon

USGS Publications Warehouse

Rounds, Stewart A.

2010-01-01

Methods were developed to assess the effects of dams on streamflow and water temperature in the Willamette River and its major tributaries. These methods were used to estimate the flows and temperatures that would occur at 14 dam sites in the absence of upstream dams, and river models were applied to simulate downstream flows and temperatures under a no-dams scenario. The dams selected for this study include 13 dams built and operated by the U.S. Army Corps of Engineers (USACE) as part of the Willamette Project, and 1 dam on the Clackamas River owned and operated by Portland General Electric (PGE). Streamflows in the absence of upstream dams for 2001-02 were estimated for USACE sites on the basis of measured releases, changes in reservoir storage, a correction for evaporative losses, and an accounting of flow effects from upstream dams. For the PGE dam, no-project streamflows were derived from a previous modeling effort that was part of a dam-relicensing process. Without-dam streamflows were characterized by higher peak flows in winter and spring and much lower flows in late summer, as compared to with-dam measured flows. Without-dam water temperatures were estimated from measured temperatures upstream of the reservoirs (the USACE sites) or derived from no-project model results (the PGE site). When using upstream data to estimate without-dam temperatures at dam sites, a typical downstream warming rate based on historical data and downstream river models was applied over the distance from the measurement point to the dam site, but only for conditions when the temperature data indicated that warming might be expected. Regressions with measured temperatures from nearby or similar sites were used to extend the without-dam temperature estimates to the entire 2001-02 time period. Without-dam temperature estimates were characterized by a more natural seasonal pattern, with a maximum in July or August, in contrast to the measured patterns at many of the tall dam sites where the annual maximum temperature typically occurred in September or October. Without-dam temperatures also tended to have more daily variation than with-dam temperatures. Examination of the without-dam temperature estimates indicated that dam sites could be grouped according to the amount of streamflow derived from high-elevation, spring-fed, and snowmelt-driven areas high in the Cascade Mountains (Cougar, Big Cliff/Detroit, River Mill, and Hills Creek Dams: Group A), as opposed to flow primarily derived from lower-elevation rainfall-driven drainages (Group B). Annual maximum temperatures for Group A ranged from 15 to 20 degree(s)C, expressed as the 7-day average of the daily maximum (7dADM), whereas annual maximum 7dADM temperatures for Group B ranged from 21 to 25 degrees C. Because summertime stream temperature is at least somewhat dependent on the upstream water source, it was important when estimating without-dam temperatures to use correlations to sites with similar upstream characteristics. For that reason, it also is important to maintain long-term, year-round temperature measurement stations at representative sites in each of the Willamette River basin's physiographic regions. Streamflow and temperature estimates downstream of the major dam sites and throughout the Willamette River were generated using existing CE-QUAL-W2 flow and temperature models. These models, originally developed for the Willamette River water-temperature Total Maximum Daily Load process, required only a few modifications to allow them to run under the greatly reduced without-dam flow conditions. Model scenarios both with and without upstream dams were run. Results showed that Willamette River streamflow without upstream dams was reduced to levels much closer to historical pre-dam conditions, with annual minimum streamflows approximately one-half or less of dam-augmented levels. Thermal effects of the dams varied according to the time of year, from cooling in mid-summer to warm

Streamflow statistical summaries for Colorado streams through September 30, 1975; Volume 2, Colorado River basin

USGS Publications Warehouse

Petsch, Harold E.

1979-01-01

Statistical summaries of daily streamflow data for 189 stations west of the Continental Divide in Colorado are presented in this report. Duration tables, high-flow sequence tables, and low-flow sequence tables provide information about daily mean discharge. The mean, variance, standard deviation, skewness, and coefficient of variation are provided for monthly and annual flows. Percentages of average flow are provided for monthly flows and first-order serial-correlation coefficients are provided for annual flows. The text explain the nature and derivation of the data and illustrates applications of the tabulated information by examples. The data may be used by agencies and individuals engaged in water studies. (USGS)

Impacts of land use change on watershed streamflow and sediment yield: An assessment using hydrologic modelling and partial least squares regression

NASA Astrophysics Data System (ADS)

Yan, B.; Fang, N. F.; Zhang, P. C.; Shi, Z. H.

2013-03-01

SummaryUnderstanding how changes in individual land use types influence the dynamics of streamflow and sediment yield would greatly improve the predictability of the hydrological consequences of land use changes and could thus help stakeholders to make better decisions. Multivariate statistics are commonly used to compare individual land use types to control the dynamics of streamflow or sediment yields. However, one issue with the use of conventional statistical methods to address relationships between land use types and streamflow or sediment yield is multicollinearity. In this study, an integrated approach involving hydrological modelling and partial least squares regression (PLSR) was used to quantify the contributions of changes in individual land use types to changes in streamflow and sediment yield. In a case study, hydrological modelling was conducted using land use maps from four time periods (1978, 1987, 1999, and 2007) for the Upper Du watershed (8973 km2) in China using the Soil and Water Assessment Tool (SWAT). Changes in streamflow and sediment yield across the two simulations conducted using the land use maps from 2007 to 1978 were found to be related to land use changes according to a PLSR, which was used to quantify the effect of this influence at the sub-basin scale. The major land use changes that affected streamflow in the studied catchment areas were related to changes in the farmland, forest and urban areas between 1978 and 2007; the corresponding regression coefficients were 0.232, -0.147 and 1.256, respectively, and the Variable Influence on Projection (VIP) was greater than 1. The dominant first-order factors affecting the changes in sediment yield in our study were: farmland (the VIP and regression coefficient were 1.762 and 14.343, respectively) and forest (the VIP and regression coefficient were 1.517 and -7.746, respectively). The PLSR methodology presented in this paper is beneficial and novel, as it partially eliminates the co-dependency of the variables and facilitates a more unbiased view of the contribution of the changes in individual land use types to changes in streamflow and sediment yield. This practicable and simple approach could be applied to a variety of other watersheds for which time-sequenced digital land use maps are available.

Fusing enhanced radar precipitation, in-situ hydrometeorological measurements and airborne LIDAR snowpack estimates in a hyper-resolution hydrologic model to improve seasonal water supply forecasts

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Busto, J.; Howard, K.; Mickey, J.; Deems, J. S.; Painter, T. H.; Richardson, M.; Dugger, A. L.; Karsten, L. R.; Tang, L.

2015-12-01

Scarcity of spatially- and temporally-continuous observations of precipitation and snowpack conditions in remote mountain watersheds results in fundamental limitations in water supply forecasting. These limitationsin observational capabilities can result in strong biases in total snowmelt-driven runoff amount, the elevational distribution of runoff, river basin tributary contributions to total basin runoff and, equally important for water management, the timing of runoff. The Upper Rio Grande River basin in Colorado and New Mexico is one basin where observational deficiencies are hypothesized to have significant adverse impacts on estimates of snowpack melt-out rates and on water supply forecasts. We present findings from a coordinated observational-modeling study within Upper Rio Grande River basin whose aim was to quanitfy the impact enhanced precipitation, meteorological and snowpack measurements on the simulation and prediction of snowmelt driven streamflow. The Rio Grande SNOwpack and streamFLOW (RIO-SNO-FLOW) Prediction Project conducted enhanced observing activities during the 2014-2015 water year. Measurements from a gap-filling, polarimetric radar (NOXP) and in-situ meteorological and snowpack measurement stations were assimilated into the WRF-Hydro modeling framework to provide continuous analyses of snowpack and streamflow conditions. Airborne lidar estimates of snowpack conditions from the NASA Airborne Snow Observatory during mid-April and mid-May were used as additional independent validations against the various model simulations and forecasts of snowpack conditions during the melt-out season. Uncalibrated WRF-Hydro model performance from simulations and forecasts driven by enhanced observational analyses were compared against results driven by currently operational data inputs. Precipitation estimates from the NOXP research radar validate significantly better against independent in situ observations of precipitation and snow-pack increases. Correcting the operational NLDAS2 forcing data with the experimental observations led to significant improvements in the seasonal accumulation and ablation of mountain snowpack and ultimately led to marked improvement in model simulated streamflow as compared with streamflow observations.

Statistical analysis of surface-water-quality data in and near the coal-mining region of southwestern Indiana, 1957-80

USGS Publications Warehouse

Martin, Jeffrey D.; Crawford, Charles G.

1987-01-01

The Surface Mining Control and Reclamation Act of 1977 requires that applications for coal-mining permits contain information about the water quality of streams at and near a proposed mine. To meet this need for information, streamflow, specific conductance, pH, and concentrations of total alkalinity, sulfate, dissolved solids, suspended solids, total iron, and total manganese at 37 stations were analyzed to determine the spatial and seasonal variations in water quality and to develop equations for predicting water quality. The season of lowest median streamflow was related to the size of the drainage area. Median streamflow was least during fall at 15 of 16 stations having drainage areas greater than 1,000 square miles but was least during summer at 17 of 21 stations having drainage areas less than 1,000 square miles. In general, the season of lowest median specific conductance occurred during the season of highest streamflow except at stations on the Wabash River. Median specific conductance was least during summer at 9 of 9 stations on the Wabash River, but was least during winter or spring (the seasons of highest streamflow) at 27 of the remaining 28 stations. Linear, inverse, semilog, log-log, and hyperbolic regression models were used to investigate the functional relations between water-quality characteristics and streamflow. Of 186 relations investigated, 143 were statistically significant. Specific conductance and concentrations of total alkalinity and sulfate were negatively related to streamflow at all stations except for a positive relation between total alkalinity concentration and streamflow at Patoka River near Princeton. Concentrations of total alkalinity and sulfate were positively related to specific conductance at all stations except for a negative relation at Patoka River near Princeton and for a positive and negative relation at Patoka River at Jasper. Most of these relations are good, have small confidence intervals, and will give reliable predictions of the water-quality variables listed above. The poorest relations are typically at stations in the Patoka River watershed. Suspended-solids concentration was positively related to streamflow at all but two stations on the Patoka River. These relations are poor, have large confidence intervals, and will give less reliable predictions of suspended-solids concentration. Predictive equations for the regional relations between dissolved-solids concentration and specific conductance and between sulfate concentration and specific conductance, and the seasonal patterns of water quality, are probably valid for the coal-mining regions of Illinois and western Kentucky.

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing and Stream Power in the Wind River Range, Wyoming

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Foster, James L.; DiGirolamo, Nicolo E.; Riggs, George A.

2010-01-01

Earlier onset of springtime weather including earlier snowmelt has been documented in the western United States over at least the last 50 years. Because the majority (>70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for streamflow management. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud- gap-filled (CGF) map products and 30 years of discharge and meteorological station data are studied. Streamflow data from six streams in the WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed using MODIS snow-cover maps within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period. MODIS-derived snow cover (percent of basin covered) measured on 30 April explains over 89% of the variance in discharge for maximum monthly streamflow in the decade of the 2000s using Spearman rank correlation analysis. We also investigated stream power for Bull Lake Creek Above Bull Lake from 1970 to 2009; a statistically-significant end toward reduced stream power was found (significant at the 90% confidence level). Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature measured during the 40-year study period. The strong relationship between percent of basin covered and streamflow indicates that MODIS data is useful for predicting streamflow, leading to improved reservoir management

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing and Stream Power in the Wind River Range, Wyoming

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Foster, James L.; Riggs, George A.; DiGirolano, Nocolo E.

2010-01-01

Earlier onset of springtime weather including earlier snowmelt has been documented in the western United States over at least the last 50 years. Because the majority (>70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for streamflow management. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud- gap-filled (CGF) map products and 30 years of discharge and meteorological station a are studied. Streamflow data from six streams in the WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed using MODIS snow-cover maps within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period. MODIS- derived snow cover (percent of basin covered) measured on 30 April explains over 89% of the variance in discharge for maximum monthly streamflow in the decade of the 2000s using Spearman rank correlation analysis. We also investigated stream power for Bull Lake Creek Above Bull Lake from 1970 to 2009; a statistically-significant trend toward reduced stream power was found (significant at the 90% confidence level). Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature measured during the 40-year study period. The strong relationship between percent of basin covered and streamflow indicates that MODIS data is useful for predicting streamflow, leading to improved reservoir management.

Estimating Watershed-Averaged Precipitation and Evapotranspiration Fluxes using Streamflow Measurements in a Semi-Arid, High Altitude Montane Catchment

NASA Astrophysics Data System (ADS)

Herrington, C.; Gonzalez-Pinzon, R.

2014-12-01

Streamflow through the Middle Rio Grande Valley is largely driven by snowmelt pulses and monsoonal precipitation events originating in the mountain highlands of New Mexico (NM) and Colorado. Water managers rely on results from storage/runoff models to distribute this resource statewide and to allocate compact deliveries to Texas under the Rio Grande Compact agreement. Prevalent drought conditions and the added uncertainty of climate change effects in the American southwest have led to a greater call for accuracy in storage model parameter inputs. While precipitation and evapotranspiration measurements are subject to scaling and representativeness errors, streamflow readings remain relatively dependable and allow watershed-average water budget estimates. Our study seeks to show that by "Doing Hydrology Backwards" we can effectively estimate watershed-average precipitation and evapotranspiration fluxes in semi-arid landscapes of NM using fluctuations in streamflow data alone. We tested this method in the Valles Caldera National Preserve (VCNP) in the Jemez Mountains of central NM. This method will be further verified by using existing weather stations and eddy-covariance towers within the VCNP to obtain measured values to compare against our model results. This study contributes to further validate this technique as being successful in humid and semi-arid catchments as the method has already been verified as effective in the former setting.

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.

Quantifying mountain block recharge by means of catchment-scale storage-discharge relationships

NASA Astrophysics Data System (ADS)

Ajami, Hoori; Troch, Peter A.; Maddock, Thomas, III; Meixner, Thomas; Eastoe, Chris

2011-04-01

Despite the importance of mountainous catchments for providing freshwater resources, especially in semi-arid regions, little is known about key hydrological processes such as mountain block recharge (MBR). Here we implement a data-based method informed by isotopic data to quantify MBR rates using recession flow analysis. We applied our hybrid method in a semi-arid sky island catchment in southern Arizona, United States. Sabino Creek is a 91 km2 catchment with its sources near the summit of the Santa Catalina Mountains northeast of Tucson. Southern Arizona's climate has two distinct wet seasons separated by prolonged dry periods. Winter frontal storms (November-March) provide about 50% of annual precipitation, and summers are dominated by monsoon convective storms from July to September. Isotope analyses of springs and surface water in the Sabino Creek catchment indicate that streamflow during dry periods is derived from groundwater storage in fractured bedrock. Storage-discharge relationships are derived from recession flow analysis to estimate changes in storage during wet periods. To provide reliable estimates, several corrections and improvements to classic base flow recession analysis are considered. These corrections and improvements include adaptive time stepping, data binning, and the choice of storage-discharge functions. Our analysis shows that (1) incorporating adaptive time steps to correct for streamflow measurement errors improves the coefficient of determination, (2) the quantile method is best for streamflow data binning, (3) the choice of the regression model is critical when the stage-discharge function is used to predict changes in bedrock storage beyond the maximum observed flow in the catchment, and (4) the use of daily or night-time hourly streamflow does not affect the form of the storage-discharge relationship but will impact MBR estimates because of differences in the observed range of streamflow in each series.

Estimated effects on water quality of Lake Houston from interbasin transfer of water from the Trinity River, Texas

USGS Publications Warehouse

Liscum, Fred; East, Jeffery W.

2000-01-01

The City of Houston is considering the transfer of water from the Trinity River to Lake Houston (on the San Jacinto River) to alleviate concerns about adequate water supplies for future water demands. The U.S. Geological Survey, in cooperation with the City of Houston, conducted a study to estimate the effects on the water quality of Lake Houston from the transfer of Trinity River water. A water-quality model, CE–QUAL–W2, was used to simulate six water-quality properties and constituents for scenarios of interbasin transfer of Trinity River water. Three scenarios involved the transferred Trinity River water augmenting streamflow in the East Fork of Lake Houston, and three scenarios involved the transferred water replacing streamflow from the West Fork of the San Jacinto River.The estimated effects on Lake Houston were determined by comparing volume-weighted daily mean water temperature, phosphorus, ammonia nitrogen, nitrite plus nitrate nitrogen, algal biomass, and dissolved oxygen simulated for each of the transfer scenarios to simulations for a base dataset. The effects of the interbasin transfer on Lake Houston do not appear to be detrimental to water temperature, ammonia nitrogen, or dissolved oxygen. Phosphorus and nitrite plus nitrate nitrogen showed fairly large changes when Trinity River water was transferred to replace West Fork San Jacinto River streamflow. Algal biomass showed large decreases when Trinity River water was transferred to augment East Fork Lake Houston streamflow and large increases when Trinity River water was transferred to replace West Fork San Jacinto River streamflow. Regardless of the scenario simulated, the model indicated that light was the limiting factor for algal biomass growth.

Simulation of groundwater and surface-water resources and evaluation of water-management alternatives for the Chamokane Creek basin, Stevens County, Washington

USGS Publications Warehouse

Ely, D. Matthew; Kahle, Sue C.

2012-01-01

A three-dimensional, transient numerical model of groundwater and surface-water flow was constructed for Chamokane Creek basin to better understand the groundwater-flow system and its relation to surface-water resources. The model described in this report can be used as a tool by water-management agencies and other stakeholders to quantitatively evaluate the effects of potential increases in groundwater pumping on groundwater and surface-water resources in the basin. The Chamokane Creek model was constructed using the U.S. Geological Survey (USGS) integrated model, GSFLOW. GSFLOW was developed to simulate coupled groundwater and surface-water resources. The model uses 1,000-foot grid cells that subdivide the model domain by 102 rows and 106 columns. Six hydrogeologic units in the model are represented using eight model layers. Daily precipitation and temperature were spatially distributed and subsequent groundwater recharge was computed within GSFLOW. Streamflows in Chamokane Creek and its major tributaries are simulated in the model by routing streamflow within a stream network that is coupled to the groundwater-flow system. Groundwater pumpage and surface-water diversions and returns specified in the model were derived from monthly and annual pumpage values previously estimated from another component of this study and new data reported by study partners. The model simulation period is water years 1980-2010 (October 1, 1979, to September 30, 2010), but the model was calibrated to the transient conditions for water years 1999-2010 (October 1, 1998, to September 30, 2010). Calibration was completed by using traditional trial-and-error methods and automated parameter-estimation techniques. The model adequately reproduces the measured time-series groundwater levels and daily streamflows. At well observation points, the mean difference between simulated and measured hydraulic heads is 7 feet with a root-mean-square error divided by the total difference in water levels of 4.7 percent. Simulated streamflow was compared to measured streamflow at the USGS streamflow-gaging station-Chamokane Creek below Falls, near Long Lake (12433200). Annual differences between measured and simulated streamflow for the site ranged from -63 to 22 percent. Calibrated model output includes a 31-year estimate of monthly water budget components for the hydrologic system. Five model applications (scenarios) were completed to obtain a better understanding of the relation between groundwater pumping and surface-water resources. The calibrated transient model was used to evaluate: (1) the connection between the upper- and middle-basin groundwater systems, (2) the effect of surface-water and groundwater uses in the middle basin, (3) the cumulative impacts of claims registry use and permit-exempt wells on Chamokane Creek streamflow, (4) the frequency of regulation due to impacted streamflow, and (5) the levels of domestic and stockwater use that can be regulated. The simulation results indicated that streamflow is affected by existing groundwater pumping in the upper and middle basins. Simulated water-management scenarios show streamflow increased relative to historical conditions as groundwater and surface-water withdrawals decreased.

Trend analysis of hydro-climatic variables in the north of Iran

NASA Astrophysics Data System (ADS)

Nikzad Tehrani, E.; Sahour, H.; Booij, M. J.

2018-04-01

Trend analysis of climate variables such as streamflow, precipitation, and temperature provides useful information for understanding the hydrological changes associated with climate change. In this study, a nonparametric Mann-Kendall test was employed to evaluate annual, seasonal, and monthly trends of precipitation and streamflow for the Neka basin in the north of Iran over a 44-year period (1972 to 2015). In addition, the Inverse Distance Weight (IDW) method was used for annual seasonal, monthly, and daily precipitation trends in order to investigate the spatial correlation between precipitation and streamflow trends in the study area. Results showed a downward trend in annual and winter precipitation (Z < -1.96) and an upward trend in annual maximum daily precipitation. Annual and monthly mean flows for most of the months in the Neka basin decreased by 14% significantly, but the annual maximum daily flow increased by 118%. Results for the trend analysis of streamflow and climatic variables showed that there are statistically significant relationships between precipitation and streamflow (p value < 0.05). Correlation coefficients for Kendall, Spearman's rank and linear regression are 0.43, 0.61, and 0.67, respectively. The spatial presentation of the detected precipitation and streamflow trends showed a downward trend for the mean annual precipitation observed in the upstream part of the study area which is consistent with the streamflow trend. Also, there is a good correlation between monthly and seasonal precipitation and streamflow for all sub-basins (Sefidchah, Gelvard, Abelu). In general, from a hydro-climatic point of view, the results showed that the study area is moving towards a situation with more severe drought events.

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.

Precipitation-runoff and streamflow-routing models for the Willamette River basin, Oregon

USGS Publications Warehouse

Laenen, Antonius; Risley, John C.

1997-01-01

With an input of current streamflow, precipitation, and air temperature data the combined runoff and routing models can provide current estimates of streamflow at almost 500 locations on the main stem and major tributaries of the Willamette River with a high degree of accuracy. Relative contributions of surface runoff, subsurface flow, and ground-water flow can be assessed for 1 to 10 HRU classes in each of 253 subbasins identified for precipitation-runoff modeling. Model outputs were used with a water-quality model to simulate the movement of dye in the Pudding River as an example

Consistent and efficient processing of ADCP streamflow measurements

USGS Publications Warehouse

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

2016-01-01

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

Flood regionalization: A hybrid geographic and predictor-variable region-of-influence regression method

USGS Publications Warehouse

Eng, K.; Milly, P.C.D.; Tasker, Gary D.

2007-01-01

To facilitate estimation of streamflow characteristics at an ungauged site, hydrologists often define a region of influence containing gauged sites hydrologically similar to the estimation site. This region can be defined either in geographic space or in the space of the variables that are used to predict streamflow (predictor variables). These approaches are complementary, and a combination of the two may be superior to either. Here we propose a hybrid region-of-influence (HRoI) regression method that combines the two approaches. The new method was applied with streamflow records from 1,091 gauges in the southeastern United States to estimate the 50-year peak flow (Q50). The HRoI approach yielded lower root-mean-square estimation errors and produced fewer extreme errors than either the predictor-variable or geographic region-of-influence approaches. It is concluded, for Q50 in the study region, that similarity with respect to the basin characteristics considered (area, slope, and annual precipitation) is important, but incomplete, and that the consideration of geographic proximity of stations provides a useful surrogate for characteristics that are not included in the analysis. ?? 2007 ASCE.

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

USGS Publications Warehouse

Robertson, Dale M.; Roerish, Eric D.

1999-01-01

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

Natural streamflow simulation for two largest river basins in Poland: a baseline for identification of flow alterations

NASA Astrophysics Data System (ADS)

Piniewski, Mikołaj

2016-05-01

The objective of this study was to apply a previously developed large-scale and high-resolution SWAT model of the Vistula and the Odra basins, calibrated with the focus of natural flow simulation, in order to assess the impact of three different dam reservoirs on streamflow using the Indicators of Hydrologic Alteration (IHA). A tailored spatial calibration approach was designed, in which calibration was focused on a large set of relatively small non-nested sub-catchments with semi-natural flow regime. These were classified into calibration clusters based on the flow statistics similarity. After performing calibration and validation that gave overall positive results, the calibrated parameter values were transferred to the remaining part of the basins using an approach based on hydrological similarity of donor and target catchments. The calibrated model was applied in three case studies with the purpose of assessing the effect of dam reservoirs (Włocławek, Siemianówka and Czorsztyn Reservoirs) on streamflow alteration. Both the assessment based on gauged streamflow (Before-After design) and the one based on simulated natural streamflow showed large alterations in selected flow statistics related to magnitude, duration, high and low flow pulses and rate of change. Some benefits of using a large-scale and high-resolution hydrological model for the assessment of streamflow alteration include: (1) providing an alternative or complementary approach to the classical Before-After designs, (2) isolating the climate variability effect from the dam (or any other source of alteration) effect, (3) providing a practical tool that can be applied at a range of spatial scales over large area such as a country, in a uniform way. Thus, presented approach can be applied for designing more natural flow regimes, which is crucial for river and floodplain ecosystem restoration in the context of the European Union's policy on environmental flows.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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 Cajina. "Real-time variational assimilation of hydrologic and hydrometeorological data into operational hydrologic forecasting." J Hydromet (2003). Steiner, Matthias, JA Smith, SJ Burges, CV Alonso, and RW Darden. "Effect of bias adjustment and rain gauge data quality control on radar rainfall estimation." WRR (1999).

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

Streamflow dynamics strongly influence anthropogenic activities and the ecological functions of riverine and riparian habitats. However, the widespread lack of direct discharge measurements often challenges the set-up of conscious and effective decision-making processes, including droughts and floods protection, water resources management and river restoration practices. By characterizing the spatial correlation of daily streamflow timeseries at two arbitrary locations, this study provides a method to evaluate how spatially variable catchment-scale hydrological process affects the resulting streamflow dynamics along and across river systems. In particular, streamflow spatial correlation is described analytically as a function of morphological, climatic and vegetation properties in the contributing catchments, building on a joint probabilistic description of flow dynamics at pairs of outlets. The approach enables an explicit linkage between similarities of flow dynamics and spatial patterns of hydrologically relevant features of climate and landscape. Therefore, the method is suited to explore spatial patterns of streamflow dynamics across geomorphoclimatic gradients. In particular, we show how the streamflow correlation can be used at the continental scale to individuate catchment pairs with similar hydrological dynamics, thereby providing a useful tool for the estimate of flow duration curves in poorly gauged areas.

Streamflow gains and losses along San Francisquito Creek and characterization of surface-water and ground-water quality, southern San Mateo and northern Santa Clara counties, California, 1996-97

USGS Publications Warehouse

Metzger, Loren F.

2002-01-01

San Francisquito Creek is an important source of recharge to the 22-square-mile San Francisquito Creek alluvial fan ground-water subbasin in the southern San Mateo and northern Santa Clara Counties of California. Ground water supplies as much as 20 percent of the water to some area communities. Local residents are concerned that infiltration and consequently ground-water recharge would be reduced if additional flood-control measures are implemented along San Francisquito Creek. To improve the understanding of the surface-water/ground-water interaction between San Francisquito Creek and the San Francisquito Creek alluvial fan, the U.S. Geological Survey (USGS) estimated streamflow gains and losses along San Francisquito Creek and determined the chemical quality and isotopic composition of surface and ground water in the study area.Streamflow was measured at 13 temporary streamflow-measurement stations to determine streamflow gains and losses along a 8.4-mile section of San Francisquito Creek. A series of five seepage runs between April 1996 and May 1997 indicate that losses in San Francisquito Creek were negligible until it crossed the Pulgas Fault at Sand Hill Road. Streamflow losses increased between Sand Hill Road and Middlefield Road where the alluvial deposits are predominantly coarse-grained and the water table is below the bottom of the channel. The greatest streamflow losses were measured along a 1.8-mile section of the creek between the San Mateo Drive bike bridge and Middlefield Road; average losses between San Mateo Drive and Alma Street and from there to Middlefield Road were 3.1 and 2.5 acre-feet per day, respectively.Downstream from Middlefield Road, streamflow gains and losses owing to seepage may be masked by urban runoff, changes in bank storage, and tidal effects from San Francisco Bay. Streamflow gains measured between Middlefield Road and the 1200 block of Woodland Avenue may be attributable to urban runoff and (or) ground-water inflow. Water-level measurements from nearby wells indicate that the regional water table may coincide with the channel bottom along this reach of San Francisquito Creek, particularly during the winter and early spring when water levels usually reach their maximum. Streamflow losses resumed below the 1200 block of Woodland Avenue, extending downstream to Newell Road. Discharge from a large storm drain between Newell Road and East Bayshore Road may account for the streamflow gains measured between these sites. Streamflow gains were measured between East Bayshore Road and the Palo Alto Municipal Golf Course, but this reach is difficult to characterize because of the probable influence of high tides.Estimated average streamflow losses totaled approximately 1,050 acre-feet per year for the reaches between USGS stream gage 11164500 at Stanford University (upstream of Junipero Serra Boulevard) and the Palo Alto Municipal Golf Course, including approximately 595 acre-feet per year for the 1.8-mile section between San Mateo Drive and Middlefield Road. Approximately 58 percent, or 550 acre-feet, of the total estimated average annual recharge from San Francisquito Creek occurs between the San Mateo Drive and Middlefield Road sites.The chemical composition of San Francisquito Creek water varies as a function of seasonal changes in hydrologic conditions. Measurements of specific conductance indicate that during dry weather and low flow, the dissolved-solids concentrations tends to be high, and during wet weather, the concentration tends to be low owing to dilution by surface water. Compared with water samples from upstream sites at USGS stream gage 11164500 and San Mateo Drive, the samples from the downstream sites at Alma Street and Woodland Avenue had low specific conductance; low concentrations of magnesium, sodium, sulfate, chloride, boron, and total dissolved solids; high nutrient concentrations; and light isotopic compositions indicating that urban runoff constitutes most of the streamflow

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

NASA Astrophysics Data System (ADS)

Wei, Xiaohua; Zhang, Mingfang

2010-12-01

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

Treating pre-instrumental data as "missing" data: using a tree-ring-based paleoclimate record and imputations to reconstruct streamflow in the Missouri River Basin

NASA Astrophysics Data System (ADS)

Ho, M. W.; Lall, U.; Cook, E. R.

2015-12-01

Advances in paleoclimatology in the past few decades have provided opportunities to expand the temporal perspective of the hydrological and climatological variability across the world. The North American region is particularly fortunate in this respect where a relatively dense network of high resolution paleoclimate proxy records have been assembled. One such network is the annually-resolved Living Blended Drought Atlas (LBDA): a paleoclimate reconstruction of the Palmer Drought Severity Index (PDSI) that covers North America on a 0.5° × 0.5° grid based on tree-ring chronologies. However, the use of the LBDA to assess North American streamflow variability requires a model by which streamflow may be reconstructed. Paleoclimate reconstructions have typically used models that first seek to quantify the relationship between the paleoclimate variable and the environmental variable of interest before extrapolating the relationship back in time. In contrast, the pre-instrumental streamflow is here considered as "missing" data. A method of imputing the "missing" streamflow data, prior to the instrumental record, is applied through multiple imputation using chained equations for streamflow in the Missouri River Basin. In this method, the distribution of the instrumental streamflow and LBDA is used to estimate sets of plausible values for the "missing" streamflow data resulting in a ~600 year-long streamflow reconstruction. Past research into external climate forcings, oceanic-atmospheric variability and its teleconnections, and assessments of rare multi-centennial instrumental records demonstrate that large temporal oscillations in hydrological conditions are unlikely to be captured in most instrumental records. The reconstruction of multi-centennial records of streamflow will enable comprehensive assessments of current and future water resource infrastructure and operations under the existing scope of natural climate variability.

Simulating the impacts of groundwater pumping on stream aquifer dynamics in semiarid northwestern Oklahoma, USA

NASA Astrophysics Data System (ADS)

Zume, Joseph; Tarhule, Aondover

2008-06-01

Visual MODFLOW, a numerical groundwater flow model, was used to evaluate the impacts of groundwater exploitation on streamflow depletion in the Alluvium and Terrace aquifer of the Beaver-North Canadian River (BNCR) in northwestern Oklahoma, USA. Water demand in semi-arid northwestern Oklahoma is projected to increase by 53% during the next five decades, driven primarily by irrigation, public water supply, and agricultural demand. Using MODFLOW’s streamflow routing package, pumping-induced changes in baseflow and stream leakage were analyzed to estimate streamflow depletion in the BNCR system. Simulation results indicate groundwater pumping has reduced baseflow to streams by approximately 29% and has also increased stream leakage into the aquifer by 18% for a net streamflow loss of 47%. The magnitude and intensity of streamflow depletion, however, varies for different stream segments, ranging from 0 to 20,804 m3/d. The method provides a framework for isolating and quantifying impacts of aquifer pumping on stream function in semiarid alluvial environments.

Numerical simulation of groundwater flow for the Yakima River basin aquifer system, Washington

USGS Publications Warehouse

Ely, D.M.; Bachmann, M.P.; Vaccaro, J.J.

2011-01-01

Five applications (scenarios) of the model were completed to obtain a better understanding of the relation between pumpage and surface-water resources and groundwater levels. For the first three scenarios, the calibrated transient model was used to simulate conditions without: (1) pumpage from all hydrogeologic units, (2) pumpage from basalt hydrogeologic units, and (3) exempt-well pumpage. The simulation results indicated potential streamflow capture by the existing pumpage from 1960 through 2001. The quantity of streamflow capture generally was inversely related to the total quantity of pumpage eliminated in the model scenarios. For the fourth scenario, the model simulated 1994 through 2001 under existing conditions with additional pumpage estimated for pending groundwater applications. The differences between the calibrated model streamflow and this scenario indicated additional decreases in streamflow of 91 cubic feet per second in the model domain. Existing conditions representing 1994 through 2001 were projected through 2025 for the fifth scenario and indicated additional streamflow decreases of 38 cubic feet per second and groundwater-level declines.

StreamStats in North Carolina: a water-resources Web application

USGS Publications Warehouse

Weaver, J. Curtis; Terziotti, Silvia; Kolb, Katharine R.; Wagner, Chad R.

2012-01-01

A statewide StreamStats application for North Carolina was developed in cooperation with the North Carolina Department of Transportation following completion of a pilot application for the upper French Broad River basin in western North Carolina (Wagner and others, 2009). StreamStats for North Carolina, available at http://water.usgs.gov/osw/streamstats/north_carolina.html, is a Web-based Geographic Information System (GIS) application developed by the U.S. Geological Survey (USGS) in consultation with Environmental Systems Research Institute, Inc. (Esri) to provide access to an assortment of analytical tools that are useful for water-resources planning and management (Ries and others, 2008). The StreamStats application provides an accurate and consistent process that allows users to easily obtain streamflow statistics, basin characteristics, and descriptive information for USGS data-collection sites and user-selected ungaged sites. In the North Carolina application, users can compute 47 basin characteristics and peak-flow frequency statistics (Weaver and others, 2009; Robbins and Pope, 1996) for a delineated drainage basin. Selected streamflow statistics and basin characteristics for data-collection sites have been compiled from published reports and also are immediately accessible by querying individual sites from the web interface. Examples of basin characteristics that can be computed in StreamStats include drainage area, stream slope, mean annual precipitation, and percentage of forested area (Ries and others, 2008). Examples of streamflow statistics that were previously available only through published documents include peak-flow frequency, flow-duration, and precipitation data. These data are valuable for making decisions related to bridge design, floodplain delineation, water-supply permitting, and sustainable stream quality and ecology. The StreamStats application also allows users to identify stream reaches upstream and downstream from user-selected sites and obtain information for locations along streams where activities occur that may affect streamflow conditions. This functionality can be accessed through a map-based interface with the user’s Web browser, or individual functions can be requested remotely through Web services (Ries and others, 2008).

Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Sheyenne River, North Dakota, 1980-2006

USGS Publications Warehouse

Ryberg, Karen R.

2007-01-01

This report presents the results of a study by the U.S. Geological Survey, done in cooperation with the North Dakota State Water Commission, to estimate water-quality constituent concentrations at seven sites on the Sheyenne River, N. Dak. Regression analysis of water-quality data collected in 1980-2006 was used to estimate concentrations for hardness, dissolved solids, calcium, magnesium, sodium, and sulfate. The explanatory variables examined for the regression relations were continuously monitored streamflow, specific conductance, and water temperature. For the conditions observed in 1980-2006, streamflow was a significant explanatory variable for some constituents. Specific conductance was a significant explanatory variable for all of the constituents, and water temperature was not a statistically significant explanatory variable for any of the constituents in this study. The regression relations were evaluated using common measures of variability, including R2, the proportion of variability in the estimated constituent concentration explained by the explanatory variables and regression equation. R2 values ranged from 0.784 for calcium to 0.997 for dissolved solids. The regression relations also were evaluated by calculating the median relative percentage difference (RPD) between measured constituent concentration and the constituent concentration estimated by the regression equations. Median RPDs ranged from 1.7 for dissolved solids to 11.5 for sulfate. The regression relations also may be used to estimate daily constituent loads. The relations should be monitored for change over time, especially at sites 2 and 3 which have a short period of record. In addition, caution should be used when the Sheyenne River is affected by ice or when upstream sites are affected by isolated storm runoff. Almost all of the outliers and highly influential samples removed from the analysis were made during periods when the Sheyenne River might be affected by ice.

Assessment of Climate Change and Agricultural Land Use Change on Streamflow Input to Devils Lake: A Case Study of the Mauvais Coulee Sub-basin

NASA Astrophysics Data System (ADS)

Jackson, C.; Todhunter, P. E.

2017-12-01

Since 1993, Devils Lake in North Dakota has experienced a prolonged rise in lake level and flooding of the lake's neighboring areas within the closed basin system. Understanding the relative contribution of climate change and land use change is needed to explain the historical rise in lake level, and to evaluate the potential impact of anthropogenic climate change upon future lake conditions and management. Four methodologies were considered to examine the relative contribution of climatic and human landscape drivers to streamflow variations: statistical, ecohydrologic, physically-based modeling, and elasticity of streamflow; for this study, ecohydrologic and climate elasticity were selected. Agricultural statistics determined that Towner and Ramsey counties underwent a crop conversion from small grains to row crops within the last 30 years. Through the Topographic Wetness Index (TWI), a 10 meter resolution DEM confirmed the presence of innumerable wetland depressions within the non-contributing area of the Mauvais Coulee Sub-basin. Although the ecohydrologic and climate elasticity methodologies are the most commonly used in literature, they make assumptions that are not applicable to basin conditions. A modified and more informed approach to the use of these methods was applied to account for these unique sub-basin characteristics. Ultimately, hydroclimatic variability was determined as the largest driver to streamflow variation in Mauvais Coulee and Devils Lake.

Space, time, and the third dimension (model error)

USGS Publications Warehouse

Moss, Marshall E.

1979-01-01

The space-time tradeoff of hydrologic data collection (the ability to substitute spatial coverage for temporal extension of records or vice versa) is controlled jointly by the statistical properties of the phenomena that are being measured and by the model that is used to meld the information sources. The control exerted on the space-time tradeoff by the model and its accompanying errors has seldom been studied explicitly. The technique, known as Network Analyses for Regional Information (NARI), permits such a study of the regional regression model that is used to relate streamflow parameters to the physical and climatic characteristics of the drainage basin.The NARI technique shows that model improvement is a viable and sometimes necessary means of improving regional data collection systems. Model improvement provides an immediate increase in the accuracy of regional parameter estimation and also increases the information potential of future data collection. Model improvement, which can only be measured in a statistical sense, cannot be quantitatively estimated prior to its achievement; thus an attempt to upgrade a particular model entails a certain degree of risk on the part of the hydrologist.

Low-flow characteristics of streams in Ohio through water year 1997

USGS Publications Warehouse

Straub, David E.

2001-01-01

This report presents selected low-flow and flow-duration characteristics for 386 sites throughout Ohio. These sites include 195 long-term continuous-record stations with streamflow data through water year 1997 (October 1 to September 30) and for 191 low-flow partial-record stations with measurements into water year 1999. The characteristics presented for the long-term continuous-record stations are minimum daily streamflow; average daily streamflow; harmonic mean flow; 1-, 7-, 30-, and 90-day minimum average low flow with 2-, 5-, 10-, 20-, and 50-year recurrence intervals; and 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 20-, and 10-percent daily duration flows. The characteristics presented for the low-flow partial-record stations are minimum observed streamflow; estimated 1-, 7-, 30-, and 90-day minimum average low flow with 2-, 10-, and 20-year recurrence intervals; and estimated 98-, 95-, 90-, 85- and 80-percent daily duration flows. The low-flow frequency and duration analyses were done for three seasonal periods (warm weather, May 1 to November 30; winter, December 1 to February 28/29; and autumn, September 1 to November 30), plus the annual period based on the climatic year (April 1 to March 31).

Estimation of traveltime and longitudinal dispersion in streams in West Virginia

USGS Publications Warehouse

Wiley, Jeffrey B.; Messinger, Terence

2013-01-01

Traveltime and dispersion data are important for understanding and responding to spills of contaminants in waterways. The U.S. Geological Survey (USGS), in cooperation with West Virginia Bureau for Public Health, Office of Environmental Health Services, compiled and evaluated traveltime and longitudinal dispersion data representative of many West Virginia waterways. Traveltime and dispersion data were not available for streams in the northwestern part of the State. Compiled data were compared with estimates determined from national equations previously published by the USGS. The evaluation summarized procedures and examples for estimating traveltime and dispersion on streams in West Virginia. National equations developed by the USGS can be used to predict traveltime and dispersion for streams located in West Virginia, but the predictions will be less accurate than those made with graphical interpolation between measurements. National equations for peak concentration, velocity of the peak concentration, and traveltime of the leading edge had root mean square errors (RMSE) of 0.426 log units (127 percent), 0.505 feet per second (ft/s), and 3.78 hours (h). West Virginia data fit the national equations for peak concentration, velocity of the peak concentration, and traveltime of the leading edge with RMSE of 0.139 log units (38 percent), 0.630 ft/s, and 3.38 h, respectively. The national equation for maximum possible velocity of the peak concentration exceeded 99 percent and 100 percent of observed values from the national data set and West Virginia-only data set, respectively. No RMSE was reported for time of passage of a dye cloud, as estimated using the national equation; however, the estimates made using the national equations had a root mean square error of 3.82 h when compared to data gathered for this study. Traveltime and dispersion estimates can be made from the plots of traveltime as a function of streamflow and location for streams with plots available, but estimates can be made using the national equations for streams without plots. The estimating procedures are not valid for regulated stream reaches that were not individually studied or streamflows outside the limits studied. Rapidly changing streamflow and inadequate mixing across the stream channel affect traveltime and dispersion, and reduce the accuracy of estimates. Increases in streamflow typically result in decreases in the peak concentration and traveltime of the peak concentration. Decreases in streamflow typically result in increases in the peak concentration and traveltime of the peak concentration. Traveltimes will likely be less than those determined using the estimating equations and procedures if the spill is in the center of the stream, and traveltimes will likely be greater than those determined using the estimating equations and procedures if the spill is near the streambank.

Estimating Precipitation Input to a Watershed by Combining Gauge and Radar Derived Observations

NASA Astrophysics Data System (ADS)

Ercan, M. B.; Goodall, J. L.

2011-12-01

One challenge in creating an accurate watershed model is obtaining estimates of precipitation intensity over the watershed area. While precipitation measurements are generally available from gauging stations and radar instruments, both of these approaches for measuring precipitation have strengths and weakness. A typical way of addressing this challenge is to use gauged precipitation estimates to calibrate radar based estimates, however this study proposes a slightly different approach in which the optimal daily precipitation value is selected from either the gauged or the radar estimates based on the observed streamflow for that day. Our proposed approach is perhaps most relevant for cases of modeling watersheds that do not have a nearby precipitation gauge, or for regions that experience convective storms that are often highly spatially variable. Using the Eno River watershed located in Orange County, NC, three different precipitation datasets were created to predict streamflow at the watershed outlet for the time period 2005-2010 using the Soil and Water Assessment Tool (SWAT): (1) estimates based on only precipitation gauging stations, (2) estimates based only on gauged-corrected radar observations, and (3) the combination of precipitation estimates from the gauge and radar data determined using our proposed approach. The results show that the combined precipitation approach significantly improves streamflow predictions (Nash-Sutcliffe Coefficient, E = 0.66) when compared to the gauged estimates alone (E = 0.47) and the radar based estimates alone (E = 0.45). Our study was limited to one watershed, therefore additional studies are needed to control for factors such as climate, ecology, and hydrogeology that will likely influence the results of the analysis.

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) was also investigated.

Comparison of two methods for estimating base flow in selected reaches of the South Platte River, Colorado

USGS Publications Warehouse

Capesius, Joseph P.; Arnold, L. Rick

2012-01-01

The Mass Balance results were quite variable over time such that they appeared suspect with respect to the concept of groundwater flow as being gradual and slow. The large degree of variability in the day-to-day and month-to-month Mass Balance results is likely the result of many factors. These factors could include ungaged stream inflows or outflows, short-term streamflow losses to and gains from temporary bank storage, and any lag in streamflow accounting owing to streamflow lag time of flow within a reach. The Pilot Point time series results were much less variable than the Mass Balance results and extreme values were effectively constrained. Less day-to-day variability, smaller magnitude extreme values, and smoother transitions in base-flow estimates provided by the Pilot Point method are more consistent with a conceptual model of groundwater flow being gradual and slow. The Pilot Point method provided a better fit to the conceptual model of groundwater flow and appeared to provide reasonable estimates of base flow.

Simulation of streamflow and estimation of ground-water recharge in the Upper Cibolo Creek Watershed, south-central Texas, 1992-2004

USGS Publications Warehouse

Ockerman, Darwin J.

2007-01-01

A watershed model (Hydrological Simulation Program?FORTRAN) was developed, calibrated, and tested by the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, San Antonio River Authority, San Antonio Water System, and Guadalupe-Blanco River Authority, to simulate streamflow and estimate ground-water recharge in the upper Cibolo Creek watershed in south-central Texas. Rainfall, evapotranspiration, and streamflow data were collected during 1992?2004 for model calibrations and simulations. Estimates of average ground-water recharge during 1992?2004 from simulation were 79,800 acre-feet (5.47 inches) per year or about 15 percent of rainfall. Most of the recharge (about 74 percent) occurred as infiltration of streamflow in Cibolo Creek. The remaining recharge occurred as diffuse infiltration of rainfall through the soil and rock layers and karst features. Most recharge (about 77 percent) occurred in the Trinity aquifer outcrop. The remaining 23 percent occurred in the downstream part of the watershed that includes the Edwards aquifer recharge zone (outcrop). Streamflow and recharge in the study area are greatly influenced by large storms. Storms during June 1997, October 1998, and July 2002 accounted for about 11 percent of study-area rainfall, 61 percent of streamflow, and 16 percent of the total ground-water recharge during 1992?2004. Annual streamflow and recharge also were highly variable. During 1999, a dry year with about 16 inches of rain and no measurable runoff at the watershed outlet, recharge in the watershed amounted to only 0.99 inch compared with 13.43 inches during 1992, a relatively wet year with about 54 inches of rainfall. Simulation of flood-control/recharge-enhancement structures showed that certain structures might reduce flood peaks and increase recharge. Simulation of individual structures on tributaries showed relatively little effect. Larger structures on the main stem of Cibolo Creek were more effective than structures on tributaries, both in terms of flood-peak reduction and recharge enhancement. One simulated scenario that incorporated two main-stem structures resulted in a 37-percent reduction of peak flow at the watershed outlet and increases in stream-channel recharge of 6.6 percent in the Trinity aquifer outcrop and 12.6 percent in the Edwards aquifer (recharge zone) outcrop.

Estimating monthly streamflow values by cokriging

USGS Publications Warehouse

Solow, A.R.; Gorelick, S.M.

1986-01-01

Cokriging is applied to estimation of missing monthly streamflow values in three records from gaging stations in west central Virginia. Missing values are estimated from optimal consideration of the pattern of auto- and cross-correlation among standardized residual log-flow records. Investigation of the sensitivity of estimation to data configuration showed that when observations are available within two months of a missing value, estimation is improved by accounting for correlation. Concurrent and lag-one observations tend to screen the influence of other available observations. Three models of covariance structure in residual log-flow records are compared using cross-validation. Models differ in how much monthly variation they allow in covariance. Precision of estimation, reflected in mean squared error (MSE), proved to be insensitive to this choice. Cross-validation is suggested as a tool for choosing an inverse transformation when an initial nonlinear transformation is applied to flow values. ?? 1986 Plenum Publishing Corporation.

Moving beyond the cost-loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker

NASA Astrophysics Data System (ADS)

Matte, Simon; Boucher, Marie-Amélie; Boucher, Vincent; Fortier Filion, Thomas-Charles

2017-06-01

A large effort has been made over the past 10 years to promote the operational use of probabilistic or ensemble streamflow forecasts. Numerous studies have shown that ensemble forecasts are of higher quality than deterministic ones. Many studies also conclude that decisions based on ensemble rather than deterministic forecasts lead to better decisions in the context of flood mitigation. Hence, it is believed that ensemble forecasts possess a greater economic and social value for both decision makers and the general population. However, the vast majority of, if not all, existing hydro-economic studies rely on a cost-loss ratio framework that assumes a risk-neutral decision maker. To overcome this important flaw, this study borrows from economics and evaluates the economic value of early warning flood systems using the well-known Constant Absolute Risk Aversion (CARA) utility function, which explicitly accounts for the level of risk aversion of the decision maker. This new framework allows for the full exploitation of the information related to a forecasts' uncertainty, making it especially suited for the economic assessment of ensemble or probabilistic forecasts. Rather than comparing deterministic and ensemble forecasts, this study focuses on comparing different types of ensemble forecasts. There are multiple ways of assessing and representing forecast uncertainty. Consequently, there exist many different means of building an ensemble forecasting system for future streamflow. One such possibility is to dress deterministic forecasts using the statistics of past error forecasts. Such dressing methods are popular among operational agencies because of their simplicity and intuitiveness. Another approach is the use of ensemble meteorological forecasts for precipitation and temperature, which are then provided as inputs to one or many hydrological model(s). In this study, three concurrent ensemble streamflow forecasting systems are compared: simple statistically dressed deterministic forecasts, forecasts based on meteorological ensembles, and a variant of the latter that also includes an estimation of state variable uncertainty. This comparison takes place for the Montmorency River, a small flood-prone watershed in southern central Quebec, Canada. The assessment of forecasts is performed for lead times of 1 to 5 days, both in terms of forecasts' quality (relative to the corresponding record of observations) and in terms of economic value, using the new proposed framework based on the CARA utility function. It is found that the economic value of a forecast for a risk-averse decision maker is closely linked to the forecast reliability in predicting the upper tail of the streamflow distribution. Hence, post-processing forecasts to avoid over-forecasting could help improve both the quality and the value of forecasts.

SWToolbox: A surface-water tool-box for statistical analysis of streamflow time series

USGS Publications Warehouse

Kiang, Julie E.; Flynn, Kate; Zhai, Tong; Hummel, Paul; Granato, Gregory

2018-03-07

This report is a user guide for the low-flow analysis methods provided with version 1.0 of the Surface Water Toolbox (SWToolbox) computer program. The software combines functionality from two software programs—U.S. Geological Survey (USGS) SWSTAT and U.S. Environmental Protection Agency (EPA) DFLOW. Both of these programs have been used primarily for computation of critical low-flow statistics. The main analysis methods are the computation of hydrologic frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10), computation of design flows including biologically based flows, and computation of flow-duration curves and duration hydrographs. Other annual, monthly, and seasonal statistics can also be computed. The interface facilitates retrieval of streamflow discharge data from the USGS National Water Information System and outputs text reports for a record of the analysis. Tools for graphing data and screening tests are available to assist the analyst in conducting the analysis.

Hydro-economic performances of streamflow withdrawal strategies: the case of small run-of-river power plants

NASA Astrophysics Data System (ADS)

Basso, Stefano; Lazzaro, Gianluca; Schirmer, Mario; Botter, Gianluca

2014-05-01

River flows withdrawals to supply small run-of-river hydropower plants have been increasing significantly in recent years - particularly in the Alpine area - as a consequence of public incentives aimed at enhancing energy production from renewable sources. This growth further raised the anthropic pressure in areas traditionally characterized by an intense exploitation of water resources, thereby triggering social conflicts among local communities, hydropower investors and public authorities. This brought to the attention of scientists and population the urgency for novel and quantitative tools for assessing the hydrologic impact of these type of plants, and trading between economic interests and ecologic concerns. In this contribution we propose an analytical framework that allows for the estimate of the streamflow availability for hydropower production and the selection of the run-of-river plant capacity, as well as the assessment of the related profitability and environmental impacts. The method highlights the key role of the streamflow variability in the design process, by showing the significance control of the coefficient of variation of daily flows on the duration of the optimal capacity of small run-of-river plants. Moreover, the analysis evidences a gap between energy and economic optimizations, which may result in the under-exploitation of the available hydropower potential at large scales. The disturbances to the natural flow regime produced between the intake and the outflow of run-of-river power plants are also estimated within the proposed framework. The altered hydrologic regime, described through the probability distribution and the correlation function of streamflows, is analytically expressed as a function of the natural regime for different management strategies. The deviations from pristine conditions of a set of hydrologic statistics are used, jointly with an economic index, to compare environmental and economic outcomes of alternative plant setups and management strategies. Benefits connected to ecosystem services provided by unimpaired riverine environments can be also included in the analysis, possibly accounting for the disruptive effect of multiple run-of-river power plants built in cascade along the same river. The application to case studies in the Alpine region shows the potential of the tool to assess different management strategies and design solution, and to evaluate local and catchment scale impacts of small run-of-river hydropower development.

Compilation of hydrologic data for White Sands pupfish habitat and nonhabitat areas, northern Tularosa Basin, White Sands Missile Range and Holloman Air Force Base, New Mexico, 1911-2008

USGS Publications Warehouse

Naus, C.A.; Myers, R.G.; Saleh, D.K.; Myers, N.C.

2014-01-01

The White Sands pupfish (Cyprinodon tularosa), listed as threatened by the State of New Mexico and as a Federal species of concern, is endemic to the Tularosa Basin, New Mexico. Because water quality can affect pupfish and the environmental conditions of their habitat, a comprehensive compilation of hydrologic data for pupfish habitat and nonhabitat areas in the northern Tularosa Basin was undertaken by the U.S. Geological Survey in cooperation with White Sands Missile Range. The four locations within the Tularosa Basin that are known pupfish habitat areas are the Salt Creek, Malpais Spring and Malpais Salt Marsh, Main Mound Spring, and Lost River habitat areas. Streamflow data from the Salt Creek near Tularosa streamflow-gaging station indicated that the average annual mean streamflow and average annual total streamflow for water years 1995–2008 were 1.35 cubic feet per second (ft3/s) and 983 acre-feet, respectively. Periods of no flow were observed in water years 2002 through 2006. Dissolved-solids concentrations in Salt Creek samples collected from 1911 through 2007 ranged from 2,290 to 66,700 milligrams per liter (mg/L). The average annual mean streamflow and average annual total streamflow at the Malpais Spring near Oscura streamflow-gaging station for water years 2003–8 were 6.81 ft3/s and 584 acre-feet, respectively. Dissolved-solids concentrations for 16 Malpais Spring samples ranged from 3,882 to 5,500 mg/L. Isotopic data for a Malpais Spring near Oscura water sample collected in 1982 indicated that the water was more than 27,900 years old. Streamflow from Main Mound Spring was estimated at 0.007 ft3/s in 1955 and 1957 and ranged from 0.02 to 0.07 ft3/s from 1996 to 2001. Dissolved-solids concentrations in samples collected between 1955 and 2007 ranged from an estimated 3,760 to 4,240 mg/L in the upper pond and 4,840 to 5,120 mg/L in the lower pond. Isotopic data for a Main Mound Spring water sample collected in 1982 indicated that the water was about 19,600 years old. Dissolved-solids concentrations of Lost River samples collected from 1984 to 1999 ranged from 8,930 to 118,000 (estimated) mg/L. Dissolved-solids concentrations in samples from nonhabitat area sites ranged from 1,740 to 54,200 (estimated) mg/L. In general, water collected from pupfish nonhabitat area sites tends to have larger proportions of calcium, magnesium, and sulfate than water from pupfish habitat area sites. Water from springs associated with mounds in pupfish nonhabitat areas was of a similar type (calcium-sulfate) to water associated with mounds in pupfish habitat areas. Alkali Spring had a sodium-chloride water type, but the proportions of sodium-chloride and magnesium-sulfate are unique as compared to samples from other sites.

Water-quality data (October 1988 through September 1989) and statistical summaries (March 1985 through September 1989) for the Clark Fork and selected tributaries from Galen to Missoula, Montana

USGS Publications Warehouse

Lambing, J.H.

1990-01-01

Water quality sampling was conducted at eight sites on the Clark Fork and selected tributaries from Galen to Missoula, from October 1988 through September 1989. This report presents tabulations and statistical summaries of the water quality data. Included are tabulations of streamflow, onsite water quality, and concentrations of trace elements and suspended sediment for periodic samples. Also included are tables and hydrographs of daily mean values for streamflow, suspended-sediment concentration, and suspended-sediment discharge at three mainstem stations and one tributary. Statistical summaries are presented for periodic water quality data collected from March 1985 through September 1989. Selected data are illustrated by graphs showing median concentrations of trace elements in water, relation of trace-element concentrations to suspended-sediment concentrations, and median concentrations of trace elements in suspended sediment. (USGS)

Water-quality data (October 1987 through September 1988) and statistical summaries (March 1985 through September 1988) for the Clark Fork and selected tributaries from Galen to Missoula, Montana

USGS Publications Warehouse

Lambing, John H.

1989-01-01

Water quality sampling was conducted at eight sites on the Clark Fork and selected tributaries from Galen to Missoula, Mont., from October 1987 through September 1988. This report presents tabulations and statistical summaries of the water quality data. Included in this report are tabulations of streamflow, onsite water quality, and concentrations of trace elements and suspended sediment for periodic samples. Also included are tables and hydrographs of daily mean values for streamflow, suspended-sediment concentration, and suspended-sediment discharge at three mainstream stations and one tributary. Statistical summaries are presented for periodic water quality data collected from March 1985 through September 1988. Selected data are illustrated by graphs showing median concentrations of trace elements in water, relation of trace element concentrations to suspended-sediment concentrations, and median concentrations of trace elements in suspended sediments. (USGS)

Peak streamflow on selected streams in Arkansas, December 2015

USGS Publications Warehouse

Breaker, Brian K.

2017-01-11

Heavy rainfall during December 2015 resulted in flooding across parts of Arkansas; rainfall amounts were as high as 12 inches over a period from December 27, 2015, to December 29, 2015. Although precipitation accumulations were highest in northwestern Arkansas, significant flooding occurred in other parts of the State. Flood damage occurred in several counties as water levels rose in streams, and disaster declarations were declared in 32 of the 75 counties in Arkansas.Given the severity of the December 2015 flooding, the U.S. Geological Survey (USGS), in cooperation with the Federal Emergency Management Agency (FEMA), conducted a study to document the meteorological and hydrological conditions prior to and during the flood; compiled flood-peak gage heights, streamflows, and flood probabilities at USGS streamflow-gaging stations; and estimated streamflows and flood probabilities at selected ungaged locations.

Streamflow statistical summaries for Colorado streams through September 30, 1975: Volume 1: Missouri River, Arkansas River, and Rio Grande Basins

USGS Publications Warehouse

Petsch, Harold E.

1979-01-01

Statistical summaries of daily streamflow data for 246 stations east of the Continental Divide in Colorado and adjacent States are presented in this report. Duration tables, high-flow sequence tables, and low-flow sequence tables provide information about daily mean discharge. The mean, variance, standard deviation, skewness, and coefficient of variation are provided for monthly and annual flows. Percentages of average flow are provided for monthly flows and first-order serial-correlation coefficients are provided for annual flows. The text explains the nature and derivation of the data and illustrates applications of the tabulated information by examples. The data may be used by agencies and individuals engaged in water studies. (USGS)

Estimation of Tile Drainage Contribution to Streamflow and Nutrient Export Loads

NASA Astrophysics Data System (ADS)

Schilling, K. E.; Arenas Amado, A.; Jones, C. S.; Weber, L. J.

2015-12-01

Subsurface drainage is a very common practice in the agricultural U.S. Midwest. It is typically installed in poorly drained soils in order to enhance crop yields. The presence of tile drains creates a route for agrichemicals to travel and therefore negatively impacts stream water quality. This study estimated through end-member analyses the contributions of tile drainage, groundwater, and surface runoff to streamflow at the watershed scale based on continuously monitored data. Especial attention was devoted to quantifying tile drainage impact on watershed streamflow and nutrient export loads. Data analyzed includes streamflow, rainfall, soil moisture, shallow groundwater levels, in-stream nitrate+nitrite concentrations and specific conductance. Data were collected at a HUC12 watershed located in Northeast Iowa, USA. Approximately 60% of the total watershed area is devoted to agricultural activities and forest and grassland are the other two predominant land uses. Results show that approximately 20% of total annual streamflow comes from tile drainage and during rainfall events tile drainage contribution can go up to 30%. Furthermore, for most of the analyzed rainfall events groundwater responded faster and in a more dramatic fashion than tile drainage. The State of Iowa is currently carrying out a plan to reduce nutrients in Iowa waters and the Gulf of Mexico (Iowa Nutrient Reduction Strategy). The outcome of this investigation has the potential to assist in Best Management Practice (BMP) scenario selection and therefore help the state achieve water quality goals.

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.

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

USGS Publications Warehouse

Pool, D.R.; Dickinson, Jesse

2007-01-01

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

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.

Diverse multi-decadal changes in streamflow within a rapidly urbanizing region

NASA Astrophysics Data System (ADS)

Diem, Jeremy E.; Hill, T. Chee; Milligan, Richard A.

2018-01-01

The impact of urbanization on streamflow depends on a variety of factors (e.g., climate, initial land cover, inter-basin transfers, water withdrawals, wastewater effluent, etc.). The purpose of this study is to examine trends in streamflow from 1986 to 2015 in a range of watersheds within the rapidly urbanizing Atlanta, GA metropolitan area. This study compares eight watersheds over three decades, while minimizing the influence of inter-annual precipitation variability. Population and land-cover data were used to analyze changes over approximately twenty years within the watersheds. Precipitation totals for the watersheds were estimated using precipitation totals at nearby weather stations. Multiple streamflow variables, such as annual streamflow, frequencies of high-flow days (HFDs), flashiness, and precipitation-adjusted streamflow, for the eight streams were calculated using daily streamflow data. Variables were tested for significant trends from 1986 to 2015 and significant differences between 1986-2000 and 2001-2015. Flashiness increased for all streams without municipal water withdrawals, and the four watersheds with the largest increase in developed land had significant increases in flashiness. Significant positive trends in precipitation-adjusted mean annual streamflow and HFDs occurred for the two watersheds (Big Creek and Suwanee Creek) that experienced the largest increases in development, and these were the only watersheds that went from majority forest land in 1986 to majority developed land in 2015. With a disproportionate increase in HFD occurrence during summer, Big Creek and Suwannee Creek also had a reduction in intra-annual variability of HFD occurrence. Watersheds that were already substantially developed at the beginning of the period and did not have wastewater discharge had declining streamflow. The most urbanized watershed (Peachtree Creek) had a significant decrease in streamflow, and a possible cause of the decrease was increasing groundwater infiltration into sewers. The impacts of urbanization on streamflow within the metropolitan area have undoubtedly been felt by a wide of range of communities.

Interactive effects of water diversion and climate change for juvenile chinook salmon in the lemhi river basin (USA.).

PubMed

Walters, Annika W; Bartz, Krista K; McClure, Michelle M

2013-12-01

The combined effects of water diversion and climate change are a major conservation challenge for freshwater ecosystems. In the Lemhi Basin, Idaho (U.S.A.), water diversion causes changes in streamflow, and climate change will further affect streamflow and temperature. Shifts in streamflow and temperature regimes can affect juvenile salmon growth, movement, and survival. We examined the potential effects of water diversion and climate change on juvenile Chinook salmon (Oncorhynchus tshawytscha), a species listed as threatened under the U.S. Endangered Species Act (ESA). To examine the effects for juvenile survival, we created a model relating 19 years of juvenile survival data to streamflow and temperature and found spring streamflow and summer temperature were good predictors of juvenile survival. We used these models to project juvenile survival for 15 diversion and climate-change scenarios. Projected survival was 42-58% lower when streamflows were diverted than when streamflows were undiverted. For diverted streamflows, 2040 climate-change scenarios (ECHO-G and CGCM3.1 T47) resulted in an additional 11-39% decrease in survival. We also created models relating habitat carrying capacity to streamflow and made projections for diversion and climate-change scenarios. Habitat carrying capacity estimated for diverted streamflows was 17-58% lower than for undiverted streamflows. Climate-change scenarios resulted in additional decreases in carrying capacity for the dry (ECHO-G) climate model. Our results indicate climate change will likely pose an additional stressor that should be considered when evaluating the effects of anthropogenic actions on salmon population status. Thus, this type of analysis will be especially important for evaluating effects of specific actions on a particular species. Efectos Interactivos de la Desviación del Agua y el Cambio Climático en Individuos Juveniles de Salmón Chinook en la Cuenca del Río Lemhi (E.U.A.). Conservation Biology © 2013 Society for Conservation Biology No claim to original US government works.

Trends in Streamflow Characteristics of Selected Sites in the Elkhorn River, Salt Creek, and Lower Platte River Basins, Eastern Nebraska, 1928-2004, and Evaluation of Streamflows in Relation to Instream-Flow Criteria, 1953-2004

USGS Publications Warehouse

Dietsch, Benjamin J.; Godberson, Julie A.; Steele, Gregory V.

2009-01-01

The Nebraska Department of Natural Resources approved instream-flow appropriations on the Platte River to maintain fish communities, whooping crane roost habitat, and wet meadows used by several wild bird species. In the lower Platte River region, the Nebraska Game and Parks Commission owns an appropriation filed to maintain streamflow for fish communities between the Platte River confluence with the Elkhorn River and the mouth of the Platte River. Because Elkhorn River flow is an integral part of the flow in the reach addressed by this appropriation, the Upper Elkhorn and Lower Elkhorn Natural Resources Districts are involved in overall management of anthropogenic effects on the availability of surface water for instream requirements. The Physical Habitat Simulation System (PHABSIM) and other estimation methodologies were used previously to determine instream requirements for Platte River biota, which led to the filing of five water appropriations applications with the Nebraska Department of Natural Resources in 1993 by the Nebraska Game and Parks Commission. One of these requested instream-flow appropriations of 3,700 cubic feet per second was for the reach from the Elkhorn River to the mouth of the Platte River. Four appropriations were granted with modifications in 1998, by the Nebraska Department of Natural Resources. Daily streamflow data for the periods of record were summarized for 17 streamflow-gaging stations in Nebraska to evaluate streamflow characteristics, including low-flow intervals for consecutive durations of 1, 3, 7, 14, 30, 60, and 183 days. Temporal trends in selected streamflow statistics were not adjusted for variability in precipitation. Results indicated significant positive temporal trends in annual flow for the period of record at eight streamflow-gaging stations - Platte River near Duncan (06774000), Platte River at North Bend (06796000), Elkhorn River at Neligh (06798500), Logan Creek near Uehling (06799500), Maple Creek near Nickerson (06800000), Elkhorn River at Waterloo (06800500), Salt Creek at Greenwood (06803555), and Platte River at Louisville (06805500). In general, sites in the Elkhorn River Basin upstream from Norfolk showed fewer significant trends than did sites downstream from Norfolk and sites in the Platte River and Salt Creek basins, where trends in low flows also were positive. Historical Platte River streamflow records for the streamflow-gaging station at Louisville, Nebraska, were used to determine the number of days per water year (Sept. 30 to Oct. 1) when flows failed to satisfy the minimum criteria of the instream-flow appropriation prior to its filing in 1993. Before 1993, the median number of days the criteria were not satisfied was about 120 days per water year. During 1993 through 2004, daily mean flows at Louisville, Nebraska, have failed to satisfy the criteria for 638 days total (median value equals 21.5 days per year). Most of these low-flow intervals occurred in summer through early fall. For water years 1953 through 2004, of the discrete intervals when flow was less that the criteria levels, 61 percent were 3 days or greater in duration, and 38 percent were 7 days or greater in duration. The median duration of intervals of flow less than the criteria levels was 4 consecutive days during 1953 through 2004.

A Precipitation-Runoff Model for the Blackstone River Basin, Massachusetts and Rhode Island

USGS Publications Warehouse

Barbaro, Jeffrey R.; Zarriello, Phillip J.

2007-01-01

A Hydrological Simulation Program-FORTRAN (HSPF) precipitation-runoff model of the Blackstone River Basin was developed and calibrated to study the effects of changing land- and water-use patterns on water resources. The 474.5 mi2 Blackstone River Basin in southeastern Massachusetts and northern Rhode Island is experiencing rapid population and commercial growth throughout much of its area. This growth and the corresponding changes in land-use patterns are increasing stress on water resources and raising concerns about the future availability of water to meet residential and commercial needs. Increased withdrawals and wastewater-return flows also could adversely affect aquatic habitat, water quality, and the recreational value of the streams in the basin. The Blackstone River Basin was represented by 19 hydrologic response units (HRUs): 17 types of pervious areas (PERLNDs) established from combinations of surficial geology, land-use categories, and the distribution of public water and public sewer systems, and two types of impervious areas (IMPLNDs). Wetlands were combined with open water and simulated as stream reaches that receive runoff from surrounding pervious and impervious areas. This approach was taken to achieve greater flexibility in calibrating evapotranspiration losses from wetlands during the growing season. The basin was segmented into 50 reaches (RCHRES) to represent junctions at tributaries, major lakes and reservoirs, and drainage areas to streamflow-gaging stations. Climatological, streamflow, water-withdrawal, and wastewater-return data were collected during the study to develop the HSPF model. Climatological data collected at Worcester Regional Airport in Worcester, Massachusetts and T.F. Green Airport in Warwick, Rhode Island, were used for model calibration. A total of 15 streamflow-gaging stations were used in the calibration. Streamflow was measured at eight continuous-record streamflow-gaging stations that are part of the U.S. Geological Survey cooperative streamflow-gaging network, and at seven partial-record stations installed in 2004 for this study. Because the model-calibration period preceded data collection at the partial-record stations, a continuous streamflow record was estimated at these stations by correlation with flows at nearby continuous-record stations to provide additional streamflow data for model calibration. Water-use information was compiled for 1996-2001 and included municipal and commercial/industrial withdrawals, private residential withdrawals, golf-course withdrawals, municipal wastewater-return flows, and on-site septic effluent return flows. Streamflow depletion was computed for all time-varying ground-water withdrawals prior to simulation. Water-use data were included in the model to represent the net effect of water use on simulated hydrographs. Consequently, the calibrated values of the hydrologic parameters better represent the hydrologic response of the basin to precipitation. The model was calibrated for 1997-2001 to coincide with the land-use and water-use data compiled for the study. Four long-term stations (Nipmuc River near Harrisville, Rhode Island; Quinsigamond River at North Grafton, Massachusetts; Branch River at Forestdale, Rhode Island; and Blackstone River at Woonsocket, Rhode Island) that monitor flow at 3.3, 5.4, 19, and 88 percent of the total basin area, respectively, provided the primary model-calibration points. Hydrographs, scatter plots, and flow-duration curves of observed and simulated discharges, along with various model-fit statistics, indicated that the model performed well over a range of hydrologic conditions. For example, the total runoff volume for the calibration period simulated at the Nipmuc River near Harrisville, Rhode Island; Quinsigamond River at North Grafton, Massachusetts; Branch River at Forestdale, Rhode Island; and Blackstone River at Woonsocket, Rhode Island streamflow-gaging stations differed from the observed runoff v

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

USGS Publications Warehouse

Williams, Cory A.; Leib, Kenneth J.

2005-01-01

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

A comparison of four streamflow record extension techniques

USGS Publications Warehouse

Hirsch, Robert M.

1982-01-01

One approach to developing time series of streamflow, which may be used for simulation and optimization studies of water resources development activities, is to extend an existing gage record in time by exploiting the interstation correlation between the station of interest and some nearby (long-term) base station. Four methods of extension are described, and their properties are explored. The methods are regression (REG), regression plus noise (RPN), and two new methods, maintenance of variance extension types 1 and 2 (MOVE.l, MOVE.2). MOVE.l is equivalent to a method which is widely used in psychology, biometrics, and geomorphology and which has been called by various names, e.g., ‘line of organic correlation,’ ‘reduced major axis,’ ‘unique solution,’ and ‘equivalence line.’ The methods are examined for bias and standard error of estimate of moments and order statistics, and an empirical examination is made of the preservation of historic low-flow characteristics using 50-year-long monthly records from seven streams. The REG and RPN methods are shown to have serious deficiencies as record extension techniques. MOVE.2 is shown to be marginally better than MOVE.l, according to the various comparisons of bias and accuracy.

A Comparison of Four Streamflow Record Extension Techniques

NASA Astrophysics Data System (ADS)

Hirsch, Robert M.

1982-08-01

One approach to developing time series of streamflow, which may be used for simulation and optimization studies of water resources development activities, is to extend an existing gage record in time by exploiting the interstation correlation between the station of interest and some nearby (long-term) base station. Four methods of extension are described, and their properties are explored. The methods are regression (REG), regression plus noise (RPN), and two new methods, maintenance of variance extension types 1 and 2 (MOVE.l, MOVE.2). MOVE.l is equivalent to a method which is widely used in psychology, biometrics, and geomorphology and which has been called by various names, e.g., `line of organic correlation,' `reduced major axis,' `unique solution,' and `equivalence line.' The methods are examined for bias and standard error of estimate of moments and order statistics, and an empirical examination is made of the preservation of historic low-flow characteristics using 50-year-long monthly records from seven streams. The REG and RPN methods are shown to have serious deficiencies as record extension techniques. MOVE.2 is shown to be marginally better than MOVE.l, according to the various comparisons of bias and accuracy.

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.

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.

Application of acoustic doppler velocimeters for streamflow measurements

USGS Publications Warehouse

Rehmel, M.

2007-01-01

The U.S. Geological Survey (USGS) principally has used Price AA and Price pygmy mechanical current meters for measurement of discharge. New technologies have resulted in the introduction of alternatives to the Price meters. One alternative, the FlowTracker acoustic Doppler velocimeter, was designed by SonTek/YSI to make streamflow measurements in wadeable conditions. The device measures a point velocity and can be used with standard midsection method algorithms to compute streamflow. The USGS collected 55 quality-assurance measurements with the FlowTracker at 43 different USGS streamflow-gaging stations across the United States, with mean depths from 0.05to0.67m, mean velocities from 13 to 60 cm/s, and discharges from 0.02 to 12.4m3/s. These measurements were compared with Price mechanical current meter measurements. Analysis of the comparisons shows that the FlowTracker discharges were not statistically different from the Price meter discharges at a 95% confidence level. ?? 2007 ASCE.

Present-day and future contributions of glacier runoff to summertime flows in a Pacific Northwest watershed: implications for water resources

Treesearch

Anne W. Nolin; Jeff Phillippe; Anne Jefferson; Sarah L. Lewis

2010-01-01

While the impacts of long-term climate change trends on glacier hydrology have received much attention, little has been done to quantify direct glacier runoff contributions to streamflow. This paper presents an approach for determining glacier runoff contributions to streamflow and estimating the effects of increased temperature and decreased glacier area on future...

A computer program (MODFLOWP) for estimating parameters of a transient, three-dimensional ground-water flow model using nonlinear regression

USGS Publications Warehouse

Hill, Mary Catherine

1992-01-01

This report documents a new version of the U.S. Geological Survey modular, three-dimensional, finite-difference, ground-water flow model (MODFLOW) which, with the new Parameter-Estimation Package that also is documented in this report, can be used to estimate parameters by nonlinear regression. The new version of MODFLOW is called MODFLOWP (pronounced MOD-FLOW*P), and functions nearly identically to MODFLOW when the ParameterEstimation Package is not used. Parameters are estimated by minimizing a weighted least-squares objective function by the modified Gauss-Newton method or by a conjugate-direction method. Parameters used to calculate the following MODFLOW model inputs can be estimated: Transmissivity and storage coefficient of confined layers; hydraulic conductivity and specific yield of unconfined layers; vertical leakance; vertical anisotropy (used to calculate vertical leakance); horizontal anisotropy; hydraulic conductance of the River, Streamflow-Routing, General-Head Boundary, and Drain Packages; areal recharge rates; maximum evapotranspiration; pumpage rates; and the hydraulic head at constant-head boundaries. Any spatial variation in parameters can be defined by the user. Data used to estimate parameters can include existing independent estimates of parameter values, observed hydraulic heads or temporal changes in hydraulic heads, and observed gains and losses along head-dependent boundaries (such as streams). Model output includes statistics for analyzing the parameter estimates and the model; these statistics can be used to quantify the reliability of the resulting model, to suggest changes in model construction, and to compare results of models constructed in different ways.

Cool-Season Moisture Delivery and Multi-Basin Streamflow Anomalies in the Western United States

NASA Astrophysics Data System (ADS)

Malevich, Steven B.

Widespread droughts can have a significant impact on western United States streamflow, but the causes of these events are not fully understood. This dissertation examines streamflow from multiple western US basins and establishes the robust, leading modes of variability in interannual streamflow throughout the past century. I show that approximately 50% of this variability is associated with spatially widespread streamflow anomalies that are statistically independent from streamflow's response to the El Nino-Southern Oscillation (ENSO). The ENSO-teleconnection accounts for approximately 25% of the interannual variability in streamflow, across this network. These atmospheric circulation anomalies associated with the most spatially widespread variability are associated with the Aleutian low and the persistent coastal atmospheric ridge in the Pacific Northwest. I use a watershed segmentation algorithm to explicitly track the position and intensity of these features and compare their variability to the multi-basin streamflow variability. Results show that latitudinal shifts in the coastal atmospheric ridge are more strongly associated with streamflow's north-south dipole response to ENSO variability while more spatially widespread anomalies in streamflow most strongly relate to seasonal changes in the coastal ridge intensity. This likely reflects persistent coastal ridge blocking of cool-season precipitation into western US river basins. I utilize the 35 model runs of the Community Earth System Model Large Ensemble (CESMLE) to determine whether the model ensemble simulates the anomalously strong coastal ridges and extreme widespread wintertime precipitation anomalies found in the observation record. Though there is considerable bias in the CESMLE, the CESMLE runs simulate extremely widespread dry precipitation anomalies with a frequency of approximately one extreme event per century during the historical simulations (1920 - 2005). These extremely widespread dry events correspond significantly with anomalously intense coastal atmospheric ridges. The results from these three papers connect widespread interannual streamflow anomalies in the western US--and especially extremely widespread streamflow droughts--with semi-permanent atmospheric ridge anomalies near the coastal Pacific Northwest. This is important to western US water managers because these widespread events appear to have been a robust feature of the past century. The semi-permanent atmospheric features associated with these widespread dry streamflow anomalies are projected to change position significantly in the next century as a response to global climate change. This may change widespread streamflow anomaly characteristic in the western US, though my results do not show evidence of these changes within the instrument record of last century.

Cost effectiveness of the stream-gaging program in South Carolina

USGS Publications Warehouse

Barker, A.C.; Wright, B.C.; Bennett, C.S.

1985-01-01

The cost effectiveness of the stream-gaging program in South Carolina was documented for the 1983 water yr. Data uses and funding sources were identified for the 76 continuous stream gages currently being operated in South Carolina. The budget of $422,200 for collecting and analyzing streamflow data also includes the cost of operating stage-only and crest-stage stations. The streamflow records for one stream gage can be determined by alternate, less costly methods, and should be discontinued. The remaining 75 stations should be maintained in the program for the foreseeable future. The current policy for the operation of the 75 stations including the crest-stage and stage-only stations would require a budget of $417,200/yr. The average standard error of estimation of streamflow records is 16.9% for the present budget with missing record included. However, the standard error of estimation would decrease to 8.5% if complete streamflow records could be obtained. It was shown that the average standard error of estimation of 16.9% could be obtained at the 75 sites with a budget of approximately $395,000 if the gaging resources were redistributed among the gages. A minimum budget of $383,500 is required to operate the program; a budget less than this does not permit proper service and maintenance of the gages and recorders. At the minimum budget, the average standard error is 18.6%. The maximum budget analyzed was $850,000, which resulted in an average standard error of 7.6 %. (Author 's abstract)

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

USGS Publications Warehouse

McKean, Sarah E.; Anderholm, Scott K.

2014-01-01

The Albuquerque Bernalillo County Water Utility Authority supplements the municipal water supply for the Albuquerque metropolitan area, in central New Mexico, with surface water diverted from the Rio Grande. The U.S. Geological Survey, in cooperation with the Albuquerque Bernalillo County Water Utility Authority, undertook this study in which water-chemistry data and historical streamflow were compiled and new water-chemistry data were collected to characterize the water chemistry and streamflow of the San Juan-Chama Project (SJCP). Characterization of streamflow included analysis of the variability of annual streamflow and comparison of the theoretical amount of water that could have been diverted into the SJCP to the actual amount of water that was diverted for the SJCP. Additionally, a seepage investigation was conducted along the channel between Azotea Tunnel Outlet and the streamflow-gaging station at Willow Creek above Heron Reservoir to estimate the magnitude of the gain or loss in streamflow resulting from groundwater interaction over the approximately 10-mile reach. Generally, surface-water chemistry varied with streamflow throughout the year. Streamflow ranged from high flow to low flow on the basis of the quantity of water diverted from the Rio Blanco, Little Navajo River, and Navajo River for the SJCP. Vertical profiles of the water temperature over the depth of the water column at Heron Reservoir indicated that the reservoir is seasonally stratified. The results from the seepage investigations indicated a small amount of loss of streamflow along the channel. Annual variability in streamflow for the SJCP was an indication of the variation in the climate parameters that interact to contribute to streamflow in the Rio Blanco, Little Navajo River, Navajo River, and Willow Creek watersheds. For most years, streamflow at Azotea Tunnel Outlet started in March and continued for approximately 3 months until the middle of July. The majority of annual streamflow at Azotea Tunnel Outlet occurred from May through June, with a median duration of slightly longer than a month. Years with higher maximum daily streamflow generally are associated with higher annual streamflow than years with lower maximum daily streamflow. The amount of water that can be diverted for the SJCP is controlled by the availability of streamflow and is limited by several factors including legal limits for diversion, limits from the SJCP infrastructure including the size of the diversion dams and tunnels, the capacity of Heron Reservoir, and operational constraints that limit when water can be diverted. The average annual streamflow at Azotea Tunnel Outlet was 94,710 acre-feet, and the annual streamflow at Azotea Tunnel Outlet was approximately 75 percent of the annual streamflow available for the SJCP. The average annual percentage of available streamflow not diverted for the SJCP was 14 percent because of structural limitations of the capacity of infrastructure, 1 percent because of limitations of the reservoir storage capacity, and 29 percent because of the limitations from operations. For most years, the annual available streamflow not diverted for unknown reasons exceeded the sum of the water not diverted because of structural, capacity, and operational limitations.

Impact of Deforestation and Recovery on Streamflow Recession Statistics

NASA Astrophysics Data System (ADS)

Krapu, C.; Kumar, M.

2016-12-01

Deforestation is known to influence streamflow and baseflow in particular in sub-humid environments. Baseflow contributions to the recession limb of a flood hydrograph convey information about subsurface stores from which trees also draw water. Recent works based on the assumptions outlined by Brutsaert and Nieber (1977) have proposed analyzing streamflow recession curves on a per-event basis. In this framework, each event's recession curve is governed by a power law relation with per-event scale and shape coefficients. As streamflow recession depends in part upon evapotranspiration demand from trees, these coefficients are hypothesized to contain useful information about catchment vegetation. Analysis was conducted of 13 small experimental catchments in the eastern United States with known forest treatment histories to determine whether or not streamflow recession behavior as observed from daily discharge records could serve as an indicator of deforestation in the drainage basin. Power-law scale coefficients were calculated for each major stormflow event at each test site and a statistical comparison of distribution of fitted coefficients was made between pre-treatment and post-treatment events as well as between pre-treatment and post-recovery events. A second method using these fitted coefficients in conjunction with Gaussian process regression was employed to track the change in the scale coefficient in the 13 catchments described previously as well as two medium-sized catchments in the North Carolina portion of the American Piedmont which did not have extensive records of forest cover. A linear trend analysis of precipitation was performed to determine whether nonstationarity in rainfall could be a confounding cause of changes in event scale coefficients. These results show a statistically significant difference in scale coefficient values in 5/8 treatment catchments and 0/5 control catchments. This suggests that lesser alterations to forest cover may not be detectable but that this method is robust against changes in precipitation. Additionally, we found clear evidence that forest regrowth in the Piedmont sites continued from 1940-1970. As a proof-of-concept, this work suggests that major alterations to forest cover can be inferred from daily data of stream discharge.

Design of surface-water data networks for regional information

USGS Publications Warehouse

Moss, Marshall E.; Gilroy, E.J.; Tasker, Gary D.; Karlinger, M.R.

1982-01-01

This report describes a technique, Network Analysis of Regional Information (NARI), and the existing computer procedures that have been developed for the specification of the regional information-cost relation for several statistical parameters of streamflow. The measure of information used is the true standard error of estimate of a regional logarithmic regression. The cost is a function of the number of stations at which hydrologic data are collected and the number of years for which the data are collected. The technique can be used to obtain either (1) a minimum cost network that will attain a prespecified accuracy and reliability or (2) a network that maximizes information given a set of budgetary and time constraints.

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.

Streamflow and water-quality properties in the West Fork San Jacinto River Basin and regression models to estimate real-time suspended-sediment and total suspended-solids concentrations and loads in the West Fork San Jacinto River in the vicinity of Conroe, Texas, July 2008-August 2009

USGS Publications Warehouse

Bodkin, Lee J.; Oden, Jeannette H.

2010-01-01

To better understand the hydrology (streamflow and water quality) of the West Fork San Jacinto River Basin downstream from Lake Conroe near Conroe, Texas, including spatial and temporal variation in suspended-sediment (SS) and total suspended-solids (TSS) concentrations and loads, the U.S. Geological Survey, in cooperation with the Houston-Galveston Area Council and the Texas Commission on Environmental Quality, measured streamflow and collected continuous and discrete water-quality data during July 2008-August 2009 in the West Fork San Jacinto River Basin downstream from Lake Conroe. During July 2008-August 2009, discrete samples were collected and streamflow measurements were made over the range of flow conditions at two streamflow-gaging stations on the West Fork San Jacinto River: West Fork San Jacinto River below Lake Conroe near Conroe, Texas (station 08067650) and West Fork San Jacinto River near Conroe, Texas (station 08068000). In addition to samples collected at these two main monitoring sites, discrete sediment samples were also collected at five additional monitoring sites to help characterize water quality in the West Fork San Jacinto River Basin. Discrete samples were collected semimonthly, regardless of flow conditions, and during periods of high flow resulting from storms or releases from Lake Conroe. Because the period of data collection was relatively short (14 months) and low flow was prevalent during much of the study, relatively few samples collected were representative of the middle and upper ranges of historical daily mean streamflows. The largest streamflows tended to occur in response to large rainfall events and generally were associated with the largest SS and TSS concentrations. The maximum SS and TSS concentrations at station 08067650 (180 and 133 milligrams per liter [mg/L], respectively) were on April 19, 2009, when the instantaneous streamflow was the third largest associated with a discrete sample at the station. SS concentrations were 25 mg/L or less in 26 of 29 environmental samples and TSS concentrations were 25 mg/L or less in 25 of 28 environmental samples. Median SS and TSS concentrations were 7.0 and 7.6 mg/L, respectively. At station 08068000, the maximum SS concentration (1,270 mg/L) was on April 19, 2009, and the maximum TSS concentration (268 mg/L) was on September 18, 2008. SS concentrations were 25 mg/L or less in 16 of 27 of environmental samples and TSS concentrations were 25 mg/L or less in 18 of 26 environmental samples at the station. Median SS and TSS concentrations were 18.0 and 14.0 mg/L, respectively. The maximum SS and TSS concentrations for all five additional monitoring sites were 3,110 and 390 mg/L, respectively, and the minimum SS and TSS concentrations were 5.0 and 1.0 mg/L, respectively. Median concentrations ranged from 14.0 to 54.0 mg/L for SS and from 11.0 to 14.0 mg/L for TSS. Continuous measurements of streamflow and selected water-quality properties at stations 08067650 and 08068000 were evaluated as possible variables in regression equations developed to estimate SS and TSS concentrations and loads. Surrogate regression equations were developed to estimate SS and TSS loads by using real-time turbidity and streamflow data; turbidity and streamflow resulted in the best regression models for estimating near real-time SS and TSS concentrations for stations 08097650 and 08068000. Relatively large errors are associated with the regression-computed SS and TSS concentrations; the 90-percent prediction intervals for SS and TSS concentrations were (+/-)48.9 and (+/-)43.2 percent, respectively, for station 08067650 and (+/-)47.7 and (+/-)43.2 percent, respectively, for station 08068000. Regression-computed SS and TSS concentrations were corrected for bias before being used to compute SS and TSS loads. The total estimated SS and TSS loads during July 2008-August 2009 were about 3,540 and 1,900 tons, respectively, at station 08067650 and about 156,000 an

Water resources of the Tulalip Indian Reservation and adjacent area, Snohomish County, Washington, 2001-03

USGS Publications Warehouse

Frans, Lonna M.; Kresch, David L.

2004-01-01

This study was undertaken to improve the understanding of water resources of the Tulalip Plateau area, with a primary emphasis on the Tulalip Indian Reservation, in order to address concerns of the Tulalip Tribes about the effects of current and future development, both on and off the Reservation, on their water resources. The drinking-water supply for the Reservation comes almost entirely from ground water, so increasing population will continue to put more pressure on this resource. The study evaluated the current state of ground- and surface-water resources and comparing results with those of studies in the 1970s and 1980s. The study included updating descriptions of the hydrologic framework and ground-water system, determining if discharge and base flow in streams and lake stage have changed significantly since the 1970s, and preparing new estimates of the water budget. The hydrogeologic framework was described using data collected from 255 wells, including their location and lithology. Data collected for the Reservation water budget included continuous and periodic streamflow measurements, micrometeorological data including daily precipitation, temperature, and solar radiation, water-use data, and atmospheric chloride deposition collected under both wet- and dry-deposition conditions to estimate ground-water recharge. The Tulalip Plateau is composed of unconsolidated sediments of Quaternary age that are mostly of glacial origin. There are three aquifers and two confining units as well as two smaller units that are only localized in extent. The Vashon recessional outwash (Qvr) is the smallest of the three aquifers and lies in the Marysville Trough on the eastern part of the study area. The primary aquifer in terms of use is the Vashon advance outwash (Qva). The Vashon till (Qvt) and the transitional beds (Qtb) act as confining units. The Vashon till overlies Qva and the transitional beds underlie Qva and separate it from the undifferentiated sediments (Qu), which are also a principal aquifer of the plateau. The undifferentiated-sediments aquifer is present throughout the entire study area, but is not well defined because few wells penetrate it. Ground water flows radially outward from the center of the Plateau in the Vashon advance outwash aquifer. Water levels fluctuate seasonally in all hydrogeologic units in response to changes in precipitation over the course of the year. However, water levels do not appear to have changed significantly over the long term. There was no statistically significant change between water levels measured in 72 wells in the early 1990s and 2001. Additionally, when a rank sum test was used to compare monthly water levels measured in 18 wells for this study with monthly water levels from the 1970s and 1980s, water levels increased in some wells, decreased in some, and did not change significantly in others. Ground water in the study area is recharged from precipitation that percolates down from the land surface. Average annual recharge, estimated using the chloride-mass-balance method, was 10.4 inches per year. Current streamflow conditions on the Reservation were defined by four continuous-record streamflow-gaging stations operated from April 2001 through March 2003 and monthly measurements of discharge at 12 periodic-measurement sites. Two continuous-record gaging stations (12157250 and 12158040) near the mouths of Mission and Tulalip Creeks, respectively, also were operated during water years 1975-77. Correlations of streamflow for Mission and Tulalip Creeks with the long-term record of streamflow at Mercer Creek (station 12120000) indicate no significant change in streamflow between the mid-1970s and 2001?03 in Mission and Tulalip Creeks. However, comparisons between the percentage of change in precipitation at the Everett precipitation station and percentages of change in streamflow at the Mercer, Mission, and Tulalip Creek gaging stations from the mid-1970s through 2001

A seasonal hydrologic ensemble prediction system for water resource management

NASA Astrophysics Data System (ADS)

Luo, L.; Wood, E. F.

2006-12-01

A seasonal hydrologic ensemble prediction system, developed for the Ohio River basin, has been improved and expanded to several other regions including the Eastern U.S., Africa and East Asia. The prediction system adopts the traditional Extended Streamflow Prediction (ESP) approach, utilizing the VIC (Variable Infiltration Capacity) hydrological model as the central tool for producing ensemble prediction of soil moisture, snow and streamflow with lead times up to 6-month. VIC is forced by observed meteorology to estimate the hydrological initial condition prior to the forecast, but during the forecast period the atmospheric forcing comes from statistically downscaled, seasonal forecast from dynamic climate models. The seasonal hydrologic ensemble prediction system is currently producing realtime seasonal hydrologic forecast for these regions on a monthly basis. Using hindcasts from a 19-year period (1981-1999), during which seasonal hindcasts from NCEP Climate Forecast System (CFS) and European Union DEMETER project are available, we evaluate the performance of the forecast system over our forecast regions. The evaluation shows that the prediction system using the current forecast approach is able to produce reliable and accurate precipitation, soil moisture and streamflow predictions. The overall skill is much higher then the traditional ESP. In particular, forecasts based on multiple climate model forecast are more skillful than single model-based forecast. This emphasizes the significant need for producing seasonal climate forecast with multiple climate models for hydrologic applications. Forecast from this system is expected to provide very valuable information about future hydrologic states and associated risks for end users, including water resource management and financial sectors.

Feasibility of Acoustic Doppler Velocity Meters for the Production of Discharge Records from U.S. Geological Survey Streamflow-Gaging Stations

USGS Publications Warehouse

Morlock, Scott E.; Nguyen, Hieu T.; Ross, Jerry H.

2002-01-01

It is feasible to use acoustic Doppler velocity meters (ADVM's) installed at U.S. Geological Survey (USGS) streamflow-gaging stations to compute records of river discharge. ADVM's are small acoustic current meters that use the Doppler principle to measure water velocities in a two-dimensional plane. Records of river discharge can be computed from stage and ADVM velocity data using the 'index velocity' method. The ADVM-measured velocities are used as an estimator or 'index' of the mean velocity in the channel. In evaluations of ADVM's for the computation of records of river discharge, the USGS installed ADVM's at three streamflow-gaging stations in Indiana: Kankakee River at Davis, Fall Creek at Millersville, and Iroquois River near Foresman. The ADVM evaluation study period was from June 1999 to February 2001. Discharge records were computed, using ADVM data from each station. Discharge records also were computed using conventional stage-discharge methods of the USGS. The records produced from ADVM and conventional methods were compared with discharge record hydrographs and statistics. Overall, the records compared closely from the Kankakee River and Fall Creek stations. For the Iroquois River station, variable backwater was present and affected the comparison; because the ADVM record compensates for backwater, the ADVM record may be superior to the conventional record. For the three stations, the ADVM records were judged to be of a quality acceptable to USGS standards for publications and near realtime ADVM-computed discharges are served on USGS real-time data World Wide Web pages.

Advanced investigation on the change in the streamflow into the water source of the middle route of China's water diversion project

NASA Astrophysics Data System (ADS)

She, Dunxian; Xia, Jun; Shao, Quanxi; Taylor, John A.; Zhang, Liping; Zhang, Xiang; Zhang, Yanjun; Gu, Huanghe

2017-07-01

To alleviate water shortage in northern China, the middle route of the South to North Water Diversion Project (MRP) was constructed by the Chinese government. A dramatic reduction in the annual streamflow into Danjiangkou Reservoir (ASDR), the water source of MRP, during 1990 has raised some concerns on the MRP's operation. This paper employed an advanced segmented regression model with more recent data to have a clear picture and understand the changing pattern of the ASDR. Our study first revealed a zigzag changing pattern (decreasing-increasing-decreasing-increasing) of ASDR during 1960-2013, which was supported by statistical criteria compared with a monotonic or single abrupt change. Particularly, the significantly decreasing trend from 1990s was reversed after 2000, and such change may relieve the concern about the water availability in the future. Sensitivity analysis showed that changes in streamflow were largely influenced by the combined effects of precipitation (P) and potential evapotranspiration (ET0) and were more sensitive to P than ET0. As ET0 is estimated from other primary variables, further analysis was conducted to understand the sensitivities of ET0 to its primary driving variables (wind speed, actual vapor pressure, temperature, and sunshine duration) and indicated that ET0 is mostly sensitive to actual vapor pressure during 1960-2013. The findings will assist the MRP's operation and management. Moreover, the results in this study also indicate that an adaptive water diversion plan, rather than the current plan with a constant annual amount of diversion water, might be a better option in the MRP's operation.

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

USGS Publications Warehouse

Medalie, Laura; Hirsch, Robert M.; Archfield, Stacey A.

2012-01-01

The U.S. Geological Survey evaluated 20 years of total phosphorus (P) and total nitrogen (N) concentration data for 18 Lake Champlain tributaries using a new statistical method based on weighted regressions to estimate daily concentration and flux histories based on discharge, season, and trend as explanatory variables. The use of all the streamflow discharge values for a given date in the record, in a process called "flow-normalization," removed the year-to-year variation due to streamflow and generated a smooth time series from which trends were calculated. This approach to data analysis can be of great value to evaluations of the success of restoration efforts because it filters out the large random fluctuations in the flux that are due to the temporal variability in streamflow. Results for the full 20 years of record showed a mixture of upward and downward trends for concentrations and yields of P and N. When the record was broken into two 10-year periods, for many tributaries, the more recent period showed a reversal in N from upward to downward trends and a similar reversal or reduction in magnitude of upward trends for P. Some measures of P and N concentrations and yields appear to be related to intensity of agricultural activities, point-source loads of P, or population density. Total flow-normalized P flux aggregated from the monitored tributaries showed a decrease of 30 metric tons per year from 1991 to 2009, which is about 15% of the targeted reduction established by the operational management plan for the Lake Champlain Basin.

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.

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.

ModABa Model: Annual Flow Duration Curves Assessment in Ephemeral Basins

NASA Astrophysics Data System (ADS)

Pumo, Dario; Viola, Francesco; Noto, Leonardo V.

2013-04-01

A representation of the streamflow regime for a river basin is required for a variety of hydrological analyses and engineering applications, from the water resource allocation and utilization to the environmental flow management. The flow duration curve (FDC) represents a comprehensive signature of temporal runoff variability often used to synthesize catchment rainfall-runoff responses. Several models aimed to the theoretical reconstruction of the FDC have been recently developed under different approaches, and a relevant scientific knowledge specific to this topic has been already acquired. In this work, a new model for the probabilistic characterization of the daily streamflows in perennial and ephemeral catchments is introduced. The ModABa model (MODel for Annual flow duration curves assessment in intermittent BAsins) can be thought as a wide mosaic whose tesserae are frameworks, models or conceptual schemes separately developed in different recent studies. Such tesserae are harmoniously placed and interconnected, concurring together towards a unique final aim that is the reproduction of the FDC of daily streamflows in a river basin. Two separated periods within the year are firstly identified: a non-zero period, typically characterized by significant streamflows, and a dry period, that, in the cases of ephemeral basins, is the period typically characterized by absence of streamflow. The proportion of time the river is dry, providing an estimation of the probability of zero flow occurring, is empirically estimated. Then, an analysis concerning the non-zero period is performed, considering the streamflow disaggregated into a slow subsuperficial component and a fast superficial component. A recent analytical model is adopted to derive the non zero FDC relative to the subsuperficial component; this last is considered to be generated by the soil water excess over the field capacity in the permeable portion of the basin. The non zero FDC relative to the fast streamflow component is directly derived from the precipitation duration curve through a simple filter model. The fast component of streamflow is considered to be formed by two contributions that are the entire amount of rainfall falling onto the impervious portion of the basin and the excess of rainfall over a fixed threshold, defining heavy rain events, falling onto the permeable portion. The two obtained FDCs are then overlapped, providing a unique non-zero FDC relative to the total streamflow. Finally, once the probability that the river is dry and the non zero FDC are known, the annual FDC of the daily total streamflow is derived applying the theory of total probability. The model is calibrated on a small catchment with ephemeral streamflows using a long period of daily precipitation, temperature and streamflow measurements, and it is successively validated in the same basin using two different time periods. The high model performances obtained in both the validation periods, demonstrate how the model, once calibrated, is able to accurately reproduce the empirical FDC starting from easily derivable parameters arising from a basic ecohydrological knowledge of the basin and commonly available climatic data such as daily precipitation and temperatures. In this sense, the model reveals itself as a valid tool for streamflow predictions in ungauged basins.

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 mean annual streamflow for the State Street gaging station at the outlet of the study basin and the simulated mean annual basin infiltration (combined infiltration from all the channels and land surfaces) were 8,720 and 41,600 acre-feet, respectively, for water years 1950-98. Simulated annual streamflow at the State Street gaging station ranged from 16.8 acre-feet in water year 1961 to 70,400 acre-feet in water year 1993, and simulated basin infiltration ranged from 2,770 acre-feet in water year 1961 to 149,000 acre-feet in water year 1983.The effects of increased urbanization on the hydrology of the study basin were evaluated by increasing the size of the effective impervious and non-effective impervious urban areas simulated in the calibrated rainfall-runoff model by 50 and 100 percent, respectively. The rainfall-runoff model simulated a long-term time series of monthly flows in and out of the channels and land surfaces using daily rainfall and potential evaporation data for water years 1950?98. Increasing the effective impervious and non-effective impervious urban areas by 100 percent resulted in a 5-percent increase in simulated mean annual streamflow at the State Street gaging station, and a 2.2-percent increase in simulated basin infiltration. Results of a frequency analysis of the simulated annual streamflow at the State Street gaging station showed that when effective impervious and non-effective impervious areas were increased 100 percent, simulated annual streamflow increased about 100 percent for low-flow conditions and was unchanged for high-flow conditions. The simulated increase in streamflow at the State Street gaging station potentially could infiltrate along the stream channel further downstream, outside of the model area.

Estimated infiltration, percolation, and recharge rates at the Rillito Creek focused recharge investigation site, Pima County, Arizona: Chapter H in Ground-water recharge in the arid and semiarid southwestern United States (Professional Paper 1703)

USGS Publications Warehouse

Hoffmann, John P.; Blasch, Kyle W.; Pool, Don R.; Bailey, Matthew A.; Callegary, James B.; Stonestrom, David A.; Constantz, Jim; Ferré, Ty P.A.; Leake, Stanley A.

2007-01-01

A large fraction of ground water stored in the alluvial aquifers in the Southwest is recharged by water that percolates through ephemeral stream-channel deposits. The amount of water currently recharging many of these aquifers is insufficient to meet current and future demands. Improving the understanding of streambed infiltration and the subsequent redistribution of water within the unsaturated zone is fundamental to quantifying and forming an accurate description of streambed recharge. In addition, improved estimates of recharge from ephemeral-stream channels will reduce uncertainties in water-budget components used in current ground-water models.This chapter presents a summary of findings related to a focused recharge investigation along Rillito Creek in Tucson, Arizona. A variety of approaches used to estimate infiltration, percolation, and recharge fluxes are presented that provide a wide range of temporal- and spatial-scale measurements of recharge beneath Rillito Creek. The approaches discussed include analyses of (1) cores and cuttings for hydraulic and textural properties, (2) environmental tracers from the water extracted from the cores and cuttings, (3) seepage measurements made during sustained streamflow, (4) heat as a tracer and numerical simulations of the movement of heat through the streambed sediments, (5) water-content variations, (6) water-level responses to streamflow in piezometers within the stream channel, and (7) gravity changes in response to recharge events. Hydraulic properties of the materials underlying Rillito Creek were used to estimate long-term potential recharge rates. Seepage measurements and analyses of temperature and water content were used to estimate infiltration rates, and environmental tracers were used to estimate percolation rates through the thick unsaturated zone. The presence or lack of tritium in the water was used to determine whether or not water in the unsaturated zone infiltrated within the past 40 years. Analysis of water-level and temporal-gravity data were used to estimate recharge volumes. Data presented in this chapter were collected from 1999 though 2002. Precipitation and streamflow during this period were less than the long-term average; however, two periods of significant streamflow resulted in recharge—one in the summer of 1999 and the other in the fall/winter of 2000.Flux estimates of infiltration and recharge vary from less than 0.1 to 1.0 cubic meter per second per kilometer of streamflow. Recharge-flux estimates are larger than infiltration estimates. Larger recharge fluxes than infiltration fluxes are explained by the scale of measurements. Methods used to estimate recharge rates incorporate the largest volumetric and temporal scales and are likely to have fluxes from other nearby sources, such as unmeasured tributaries, whereas the methods used to estimate infiltration incorporate the smallest scales, reflecting infiltration rates at individual measurement sites.

Spatial Correlation Of Streamflows: An Analytical Approach

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Effects of uncertainties in hydrological modelling. A case study of a mountainous catchment in Southern Norway

NASA Astrophysics Data System (ADS)

Engeland, Kolbjørn; Steinsland, Ingelin; Johansen, Stian Solvang; Petersen-Øverleir, Asgeir; Kolberg, Sjur

2016-05-01

In this study, we explore the effect of uncertainty and poor observation quality on hydrological model calibration and predictions. The Osali catchment in Western Norway was selected as case study and an elevation distributed HBV-model was used. We systematically evaluated the effect of accounting for uncertainty in parameters, precipitation input, temperature input and streamflow observations. For precipitation and temperature we accounted for the interpolation uncertainty, and for streamflow we accounted for rating curve uncertainty. Further, the effects of poorer quality of precipitation input and streamflow observations were explored. Less information about precipitation was obtained by excluding the nearest precipitation station from the analysis, while reduced information about the streamflow was obtained by omitting the highest and lowest streamflow observations when estimating the rating curve. The results showed that including uncertainty in the precipitation and temperature inputs has a negligible effect on the posterior distribution of parameters and for the Nash-Sutcliffe (NS) efficiency for the predicted flows, while the reliability and the continuous rank probability score (CRPS) improves. Less information in precipitation input resulted in a shift in the water balance parameter Pcorr, a model producing smoother streamflow predictions, giving poorer NS and CRPS, but higher reliability. The effect of calibrating the hydrological model using streamflow observations based on different rating curves is mainly seen as variability in the water balance parameter Pcorr. When evaluating predictions, the best evaluation scores were not achieved for the rating curve used for calibration, but for rating curves giving smoother streamflow observations. Less information in streamflow influenced the water balance parameter Pcorr, and increased the spread in evaluation scores by giving both better and worse scores.

A worldwide analysis of trends in water-balance evapotranspiration

NASA Astrophysics Data System (ADS)

Ukkola, A. M.; Prentice, I. C.

2013-10-01

Climate change is expected to alter the global hydrological cycle, with inevitable consequences for freshwater availability to people and ecosystems. But the attribution of recent trends in the terrestrial water balance remains disputed. This study attempts to account statistically for both trends and interannual variability in water-balance evapotranspiration (ET), estimated from the annual observed streamflow in 109 river basins during "water years" 1961-1999 and two gridded precipitation data sets. The basins were chosen based on the availability of streamflow time-series data in the Dai et al. (2009) synthesis. They were divided into water-limited "dry" and energy-limited "wet" basins following the Budyko framework. We investigated the potential roles of precipitation, aerosol-corrected solar radiation, land use change, wind speed, air temperature, and atmospheric CO2. Both trends and variability in ET show strong control by precipitation. There is some additional control of ET trends by vegetation processes, but little evidence for control by other factors. Interannual variability in ET was overwhelmingly dominated by precipitation, which accounted on average for 54-55% of the variation in wet basins (ranging from 0 to 100%) and 94-95% in dry basins (ranging from 69 to 100%). Precipitation accounted for 45-46% of ET trends in wet basins and 80-84% in dry basins. Net atmospheric CO2 effects on transpiration, estimated using the Land-surface Processes and eXchanges (LPX) model, did not contribute to observed trends in ET because declining stomatal conductance was counteracted by slightly but significantly increasing foliage cover.