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Using previously published (Robinson and others, 2019) no-flow fractions and L-moments of nonzero streamflow from decadal streamflow flow-duration analysis (daily mean streamflow), probability distributions were fit to provide 27 estimated quantiles of decadal flow-duration curves, and hence the probability distributions are a form of parametric modeling that ensures monotonicity of the quantiles by non-exceedance probability (NEP). For both U.S. Geological Survey streamflow-gaging stations (streamgages) and level-12 hydrologic unit code (HUC12) catchments, as defined by Crowley-Ornelas and others (2019), the 27 quantiles were estimated and tabulated in this data release. Three probability distributions were used...
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Using previously published (Robinson and others, 2019) no-flow fractions and L-moments of nonzero streamflow from decadal streamflow flow-duration analysis (daily mean streamflow), probability distributions were fit to provide 27 estimated quantiles of decadal flow-duration curves, and hence the probability distributions are a form of parametric modeling that ensures monotonicity of the quantiles by non-exceedance probability (NEP). For both U.S. Geological Survey streamflow-gaging stations (streamgages) and level-12 hydrologic unit code (HUC12) catchments, as defined by Crowley-Ornelas and others (2019), the 27 quantiles were estimated and tabulated in this data release. Three probability distributions were used...
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In 2016, non-interpretive streamflow statistics were compiled for streamgages located throughout the Nation and stored in the StreamStatsDB database 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) and “QSTATS” (Streamflow (Q) Statistics). 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...
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Using previously published (Robinson and others, 2019) no-flow fractions and L-moments of nonzero streamflow from decadal streamflow flow-duration analysis (daily mean streamflow), probability distributions were fit to provide 27 estimated quantiles of decadal flow-duration curves, and hence the probability distributions are a form of parametric modeling that ensures monotonicity of the quantiles by non-exceedance probability (NEP). For both U.S. Geological Survey streamflow-gaging stations (streamgages) and level-12 hydrologic unit code (HUC12) catchments, as defined by Crowley-Ornelas and others (2019), the 27 quantiles were estimated and tabulated in this data release. Three probability distributions were used...


    map background search result map search result map Streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages Estimated quantiles of decadal flow-duration curves using selected probability distributions fit to no-flow fractions and L-moments predicted for streamgages and for pour points of level-12 hydrologic unit codes in the southeastern United States, 1950–2010 Distribution Models of Flow-Duration Quantiles for Streamgages Distribution Models of Flow-Duration Quantiles for HUC12s Estimated quantiles of decadal flow-duration curves using selected probability distributions fit to no-flow fractions and L-moments predicted for streamgages and for pour points of level-12 hydrologic unit codes in the southeastern United States, 1950–2010 Distribution Models of Flow-Duration Quantiles for Streamgages Distribution Models of Flow-Duration Quantiles for HUC12s Streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages