AUTOMATED WEB GIS BASED HYDROGRAPH ANALYSIS TOOL,WHAT1

The separation of the base flow component from a varying streamflow hydrograph is called “hydrograph analysis.” In this study, two digital filter based separation modules, the BFLOW and Eckhardt filters, were incorporated into the Web based Hydrograph Analysis Tool (WHAT) system. A statistical component was also developed to provide fundamental information for flow frequency analysis and time series analysis. The Web Geographic Information System (GIS) version of the WHAT system accesses and uses U.S. Geological Survey (USGS) daily streamflow data from the USGS web server. The results from the Eckhardt filter method were compared with the results from the BFLOW filter method that was previously validated, since measured base flow data were not available for this study. Following validation, the two digital filter methods in the WHAT system were run for 50 Indiana gaging stations. The Nash‐Sutcliffe coefficient values comparing the results of the two digital filter methods were over 0.91 for all 50 gaging stations, suggesting the filtered base flow using the Eckhardt filter method will typically match measured base flow. Manual separation of base flow from streamflow can lead to inconsistency in the results, while the WHAT system provides consistent results in less than a minute. Although base flow separation algorithms in the WHAT system cannot consider reservoir release and snowmelt that can affect stream hydrographs, the Web based WHAT system provides an efficient tool for hydrologic model calibration and validation. The base flow information from the WHAT system can also play an important role for sustainable ground water and surface water exploitation, including irrigation and industrial uses, and estimation of pollutant loading from both base flow and direct runoff. Thus, best management practices can be appropriately applied to reduce and intercept pollutant leaching if base flow contributes significant amounts of pollutants to the stream. This Web GIS based system also demonstrates how remote, distributed resources can be shared through the Internet using Web programming.     

BASE FLOW TRENDS IN URBANIZING WATERSHEDS OF THE DELAWARE RIVER BASIN1

Rapid land development is raising concern regarding the ability of urbanizing watersheds to sustain adequate base flow during periods of drought. Long term streamflow records from unregulated watersheds of the lower to middle Delaware River basin are examined to evaluate the impact of urbanization and imperviousness on base flow. Trends in annual base flow volumes, seven‐day low flows, and runoff ratios are determined for six urbanizing watersheds and four reference watersheds across three distinct physiographic regions. Hydrograph separation is used to determine annual base flow and stormflow volumes, and nonparametric trend tests are conducted on the resulting time series. Of the watersheds examined, the expected effects of declining base flow volumes and seven‐day low flows and increasing stormflows are seen in only one watershed that is approximately 20 percent impervious and has been subject to a net water export over the past 15 years. Both interbasin transfers and hydrologic mechanisms are invoked to explain these results. The results show that increases in impervious area may not result in measurable reductions in base flow at the watershed scale.     

Use of Streamflow Data to Estimate Base Flow/Ground‐Water Recharge For Wisconsin1

Abstract: 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.     

Estimation of Daily Streamflow of Southeastern Coastal Plain Watersheds by Combining Estimated Magnitude and Sequence

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. Magnitude is modeled using the flow duration curve (FDC), whereas sequence is modeled by transferring streamflow sequence of gauged watershed(s). This study tests the applicability of the approach on watersheds ranging in size from about 25‐7,226 km² in Southeastern Coastal Plain (U.S.) with substantial surface storage of wetlands. A 19‐point regionalized FDC is developed to estimate streamflow magnitude using the three most selected variables (drainage area, hydrologic soil index, and maximum 24‐h precipitation with a recurrence interval of 100 years) by a greedy‐heuristic search process. The results of validation on four watersheds (Trent River, North Carolina: 02092500; Satilla River, Georgia: 02226500; Black River, South Carolina: 02136000; and Coosawhatchie River, South Carolina: 02176500) yielded Nash‐Sutcliffe efficiency values of 0.86‐0.98 for the predicted magnitude and 0.09‐0.84 for the predicted daily streamflow over a simulation period of 1960‐2010. The prediction accuracy of the method on two headwater watersheds at Santee Experimental Forest in coastal South Carolina was weak, but comparable to simulations by MIKE‐SHE.     

PREDICTION OF MASTER RECESSION CURVES AND BASEFLOW RECESSIONS IN THE LUQUILLO MOUNTAINS OF PUERTO RICO1

ABSTRACT: An analysis of hydrograph recessions and rainfall data was performed to estimate the recession constants for two watersheds in the Luquillo mountains of Puerto Rico. To account for seasonal rainfall patterns, the data were grouped into dry and wet seasons. Sets of three Master Recession Curves (MRC) per season for each watershed were developed: one using the Matching Strip Method (MS) and two using variations of the Correlation Method (CM). These variations were the envelope line (CME) and the least squares regression (CMR). Other regression based analytical expressions that consider the streamflow recession as an autore‐gressive or an integrated moving average process were also applied. The regression based methods performed consistently better than the graphical ones and they proved to be faster, easier, and less subjective. The recession constants from these methods were then used to estimate the time it would take the streamflow to reach the critical Q₉₉ flow duration. Based on this study, once the streamflow reaches Q₉₀, water managers have 6 to 12 days warning before streamflow reaches critical levels.     

Spatial and Temporal Patterns of Low Streamflow and Precipitation Changes in the Chesapeake Bay Watershed

Spatial and temporal patterns in low streamflows were investigated for 183 streamgages located in the Chesapeake Bay Watershed for the period 1939–2013. Metrics that represent different aspects of the frequency and magnitude of low streamflows were examined for trends: (1) the annual time series of seven‐day average minimum streamflow, (2) the scaled average deficit at or below the 2% mean daily streamflow value relative to a base period between 1939 and 1970, and (3) the annual number of days below the 2% threshold. Trends in these statistics showed spatial cohesion, with increasing low streamflow volume at streamgages located in the northern uplands of the Chesapeake Bay Watershed and decreasing low streamflow volume at streamgages in the southern part of the watershed. For a small subset of streamgages (12%), conflicting trend patterns were observed between the seven‐day average minimum streamflow and the below‐threshold time series and these appear to be related to upstream diversions or the influence of reservoir‐influenced streamflows in their contributing watersheds. Using multivariate classification techniques, mean annual precipitation and fraction of precipitation falling as snow appear to be broad controls of increasing and decreasing low‐flow trends. Further investigation of seasonal precipitation patterns shows summer rainfall patterns, driven by the Atlantic Multidecadal Oscillation, as the main driver of low streamflows in the Chesapeake Bay Watershed.     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

Revealing the Diversity of Natural Hydrologic Regimes in California with Relevance for Environmental Flows Applications

Alterations to flow regimes for water management objectives have degraded river ecosystems worldwide. These alterations are particularly profound in Mediterranean climate regions such as California with strong climatic variability and riverine species highly adapted to the resulting flooding and drought disturbances. However, defining environmental flow targets for Mediterranean rivers is complicated by extreme hydrologic variability and often intensive water management legacies. Improved understanding of the diversity of natural streamflow patterns and their spatial arrangement across Mediterranean regions is needed to support the future development of effective flow targets at appropriate scales for management applications with minimal resource and data requirements. Our study addresses this need through the development of a spatially explicit reach‐scale hydrologic classification for California. Dominant hydrologic regimes and their physio‐climatic controls are revealed, using available unimpaired and naturalized streamflow time‐series and generally publicly available geospatial datasets. This methodology identifies eight natural flow classes representing distinct flow sources, hydrologic characteristics, and catchment controls over rainfall‐runoff response. The study provides a broad‐scale hydrologic framework upon which flow‐ecology relationships could subsequently be established towards reach‐scale environmental flows applications in a complex, highly altered Mediterranean region.     

Simulation of Surface Water for Un‐Gauged Areas with Storage‐Attenuation Wetlands1

Abstract: A nontraditional application of the Hydrological Simulation Program – FORTRAN (HSPF) model to simulate freshwater discharge to upper Charlotte Harbor along Florida’s west coast was performed. This application was different from traditional HSPF applications in three ways. First, the domain of the model was defined based on the hydraulic characteristics of the landforms using small distributed parameter discretization. Second, broad wetland land forms, representing more than 20% of this area, were simulated as reaches with storage‐attenuation characteristics and not as pervious land segments (PERLNDs). Finally, the reach flow‐tables (F‐Tables) were configured in a unique way to be calibrated representing the uncertainty of the storage‐attenuation process. Characterizing wetlands as hydrography elements allows flow from the wetlands to be treated as a stage‐dependent flux. The study was conducted for the un‐gauged portion of the Peace and Myakka rivers in west‐central Florida. Due to low gradient tidal influences, a large portion of the basin is un‐gauged. The objective of this study was to simulate stream flow discharges and to estimate freshwater inflow from these un‐gauged areas to upper Charlotte Harbor. Two local gauging stations were located within the model domain and were used for calibration. Another gauge with a shorter period of record was used for verification. A set of global hydrologic parameters were selected and tested using the parameter optimization software (PEST) during the calibration. Model results were evaluated using PEST and well‐known statistical indices. The correlation coefficients were very high (0.899 and 0.825) for the two calibration stations. Further testing of this approach appears warranted for watersheds with significant wetlands coverage.     

Evidence for Changing Flood Risk in New England Since the Late 20th Century1

Abstract: Long‐term flow records for watersheds with minimal human influence have shown trends in recent decades toward increasing streamflow at regional and national scales, especially for low flow quantiles like the annual minimum and annual median flows. Trends for high flow quantiles are less clear, despite recent research showing increased precipitation in the conterminous United States over the last century that has been brought about primarily by an increased frequency and intensity of events in the upper 10th percentile of the daily precipitation distribution – particularly in the Northeast. This study investigates trends in 28 long‐term annual flood series for New England watersheds with dominantly natural streamflow. The flood series are an average of 75 years in length and are continuous through 2006. Twenty‐five series show upward trends via the nonparametric Mann‐Kendall test, 40% (10) of which are statistically significant (p < 0.1). Moreover, an average standardized departures series for 23 of the study gages indicates that increasing flood magnitudes in New England occurred as a step change around 1970. The timing of this is broadly synchronous with a phase change in the low frequency variability of the North Atlantic Oscillation, a prominent upper atmospheric circulation pattern that is known to effect climate variability along the United States east coast. Identifiable hydroclimatic shifts should be considered when the affected flow records are used for flood frequency analyses. Special treatment of the flood series can improve the analyses and provide better estimates of flood magnitudes and frequencies under the prevailing hydroclimatic condition.     

IDENTIFICATION OF CHANGES IN STREAMFLOW CHARACTERISTICS1

ABSTRACT: A set of procedures for identifying changes in selected streamflow characteristics at sites having long‐term continuous streamflow records is illustrated by using streamflow data from the Waccamaw River at Freeland, North Carolina for the 55‐year period of 1940–1994. Data were evaluated and compared to streamflow in the adjacent Lumber River Basin to determine if changes in streamflow characteristics in the Waccamaw River were localized and possibly the result of some human activity, or consistent with regional variations. Following 1963, droughts in the Waccamaw Basin seem to have been less severe than in the Lumber Basin, and the annual one‐, seven‐, and 30‐day low flows exhibited a slightly increasing trend in the Waccamaw River. Mean daily flows in the Waccamaw River at the 90 percent exceedance level (low flows) during 1985–194, a relatively dry period, were very nearly equal to flows at the same exceedance level for 1970–1979, which represents the 10‐year period between 1940 and 1994 with the highest flows. Prior to the 1980s, flows per unit drainage area in the Waccamaw Basin were generally less than those in the Lumber Basin, but after 1980, the opposite was true. The ratio of base flow to runoff in the Waccamaw River may have changed relative to that in the Lumber River in the late 1970s. There was greater variability in Waccamaw River streamflow than in Lumber River flow, and flow variability in the Waccamaw River may have increased slightly during 1985–1994.     

An Optimization Method for Estimating Constituent Mean Concentrations in Base Flow‐Dominated Flow

Pollutant coefficients have been widely used to assess runoff nonpoint source pollution from individual land uses (e.g., agricultural, residential) of a watershed. Pollutant coefficients, known as event mean concentrations (EMCs), were developed by the U.S. Environmental Protection Agency's Nationwide Urban Runoff Program (NURP) to serve as a national measure for characterizing pollutant loading in a receiving water body. The term “baseflow pollutant coefficient (BPC)” is used in this study as a surrogate for EMC to describe mean concentration of pollutants in base flow‐dominated flow. A method for characterizing base flow quantity and quality for different land uses was explored using inverse modeling with two optimization techniques (a least square method and a genetic algorithm [GA] optimization), land use information, and streamflow quantity and quality data. The inverse model was formulated as a constrained minimization problem and demonstrated with data for 15 watersheds in Indiana. Results showed that estimated pollutant coefficients are comparable to the published literature. This indicates that the proposed method has the potential to effectively estimate constituent mean concentrations for pollutant load determination in gauged and ungauged watersheds, albeit more analysis with larger and more robust datasets is desirable to further refine and validate the accuracy of the approach.     

ESTIMATION OF STREAMFLOW,BASE FLOW,AND NITRATE‐NITROGEN LOADS IN IOWA USING MULTIPLE LINEAR REGRESSION MODELS1

Nineteen variables, including precipitation, soils and geology, land use, and basin morphologic characteristics, were evaluated to develop Iowa regression models to predict total streamflow (Q), base flow (Qb), storm flow (Qs) and base flow percentage (%Qb) in gauged and ungauged watersheds in the state. Discharge records from a set of 33 watersheds across the state for the 1980 to 2000 period were separated into Qb and Qs. Multiple linear regression found that 75.5 percent of long term average Q was explained by rainfall, sand content, and row crop percentage variables, whereas 88.5 percent of Qb was explained by these three variables plus permeability and floodplain area variables. Qs was explained by average rainfall and %Qb was a function of row crop percentage, permeability, and basin slope variables. Regional regression models developed for long term average Q and Qb were adapted to annual rainfall and showed good correlation between measured and predicted values. Combining the regression model for Q with an estimate of mean annual nitrate concentration, a map of potential nitrate loads in the state was produced. Results from this study have important implications for understanding geomorphic and land use controls on streamflow and base flow in Iowa watersheds and similar agriculture dominated watersheds in the glaciated Midwest.     

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

Hydrologic Landscape Classification to Estimate Bristol Bay,Alaska Watershed Hydrology

Hydrologic landscapes (HLs) have proven to be a useful tool for broad scale assessment and classification of landscapes across the United States as they help organize larger geographical areas into areas of similar hydrologic characteristics. We developed a HL classification for the Bristol Bay watershed of southwest Alaska that incorporates indices of annual climate and seasonality, terrain, geology, and the influences of large lakes and glaciers. A HL classification is particularly useful in this large watershed because of its hydrologic and landscape variability, important salmon fishery, variety of environmental and potential anthropogenic stressors, and lack of widespread hydrologic data. Following creation of Bristol Bay basin‐wide HL classes, we compared the HL distributions within watersheds grouped by two calculated runoff parameters derived from available long‐term streamflow records and found HL distributions within these groups provided predictive insight on hydrologic behavior. Using these developed runoff groups, we estimated expected hydrologic behavior in watersheds across the larger Bristol Bay watershed that lacked gauged streamflow records. The HL approach provides a scientific basis for estimating the first‐order hydrologic behavior of watersheds and landscapes that lack detailed hydrologic information.     

The Effects of Changing Land Cover on Streamflow Simulation in Puerto Rico

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

Hydrograph Separation by Incorporating Climatological Factors: Application to Small Experimental Watersheds 1

Abstract: Evaluating the relative amounts of water moving through the different components of the hydrological cycle is required for precise management and planning of water resources. An important aspect of this evaluation is the partitioning of streamflow into surface (quick flow) and base‐flow components. A prior study evaluated 40 different approaches for hydrograph‐partitioning on a field scale watershed in the Coastal Plain of the Southeastern United States and concluded that the Boughton’s method produced the most consistent and accurate results. However, its accuracy depends upon the proper estimation of: (1) the end of surface runoff, and (2) the fraction factor (α) that is function of many physical and hydrologic characteristics of a watershed. Proper identification of the end of surface runoff was accomplished by using a second derivative approach. Applying this approach to 12 years of separately measured surface and subsurface flow data from a field scale watershed (study area) proved to be accurate for 87% of the time. Estimation of the α value was accomplished in this study using two steps: (1) alpha was fitted to individual hydrographs: and, (2) a regression equation that determines these alpha values based on climatological factors (e.g., rainfall, evapotranspiration) was developed. Using these strategies improved the streamflow partitioning method’s performance significantly.     

Effects of Rainfall and Ground‐Water Pumping on Streamflow in Mākaha,O’ahu,Hawai’i1

Abstract: Land‐use/land‐cover changes in Mākaha valley have included the development of agriculture, residential dwellings, golf courses, potable water supply facilities, and the introduction of alien species. The impact of these changes on surface water and ground water resources in the valley is of concern. In this study, streamflow, rainfall, and ground‐water pumping data for the upper part of the Mākaha valley watershed were evaluated to identify corresponding trends and relationships. The results of this study indicate that streamflow declined during the ground‐water pumping period. Mean and median annual streamflow have declined by 42% (135 mm) and 56% (175 mm), respectively, and the mean number of dry stream days per year has increased from 8 to 125. Rainfall across the study area appears to have also declined though it is not clear whether the reduction in rainfall is responsible for all or part of the observed streamflow decline. Mean annual rainfall at one location in the study area declined by 14% (179 mm) and increased by 2% (48 mm) at a second location. Further study is needed to assess the effect of ground‐water pumping and to characterize the hydrologic cycle with respect to rainfall, infiltration, ground‐water recharge and flow in the study area, and stream base flow and storm flow.     

CLASSIFICATION OF ENVIRONMENTAL HYDROLOGIC BEHAVIORS IN THE NORTHEASTERN UNITED STATES1

ABSTRACT: Environmental response to acidic deposition results from movement of water through the ecosystem. As a part of the environmental studies for acidic deposition sponsored by the U.S. Environmental Protection Agency (EPA), hydrologic classification based on regional baseflow properties was done. To obtain the amount of baseflow, a flow separation method was developed based on the division of streamflows into “baseflow” and “other” runoff sources. Because of the differences in the flow paths and exposure duration, the two components were assumed to be associated with distinct geo-chemical responses. Individual annual hydrographs were analyzed using 31 separation slopes to determine the amount of baseflow. A total of 1575 streamflow stations in the Northeastern U.S. were analyzed through the access of a long-term daily stream-flow data base. An interactive computer program was developed to obtain baseflow properties and other hydrologic characteristics of each station. The output from this analysis was used to perform cluster analysis to classify streamflow behaviors. The clustering output showed different regional boundaries than those currently used by the EPA for water quality studies.     

Observed Changes in Climate and Streamflow in the Upper Rio Grande Basin

Observed streamflow and climate data are used to test the hypothesis that climate change is already affecting Rio Grande streamflow volume derived from snowmelt runoff in ways consistent with model‐based projections of 21st‐Century streamflow. Annual and monthly changes in streamflow volume and surface climate variables on the Upper Rio Grande, near its headwaters in southern Colorado, are assessed for water years 1958–2015. Results indicate winter and spring season temperatures in the basin have increased significantly, April 1 snow water equivalent (SWE) has decreased by approximately 25%, and streamflow has declined slightly in the April–July snowmelt runoff season. Small increases in precipitation have reduced the impact of declining snowpack on trends in streamflow. Changes in the snowpack–runoff relationship are noticeable in hydrographs of mean monthly streamflow, but are most apparent in the changing ratios of precipitation (rain + snow, and SWE) to streamflow and in the declining fraction of runoff attributable to snowpack or winter precipitation. The observed changes provide observational confirmation for model projections of decreasing runoff attributable to snowpack, and demonstrate the decreasing utility of snowpack for predicting subsequent streamflow on a seasonal basis in the Upper Rio Grande Basin.