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A table is presented listing: (1) USGS Gage Station Numbers, (2) Model Identification Tags, (3) Model Term Estimates, (4) Model Term Fit Statistics, and (5) Model Performance Indices for Maximum Likelihood Logistic Regression (MLLR) Models estimating hydrological drought probabilities in the United States. Models were developed using streamflow daily values (DV) readily available from the U.S. Geological Survey National Water Information System (NWIS) and mean monthly streamflows readily computed from NWIS streamflow DV. Models were prepared for 9,144 sites throughout the United States as described in: Modeling Summer Month Hydrological Drought Probabilities In The United States Using Antecedent Flow Conditions...
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A table is presented listing: (1) monthly streamflows, (2) drought duration dates, (3) drought severity indices, (4) supporting statistics, and (5) identification tags, for analysis of hydrological droughts in the Conterminous United States (CONUS). Data were summarized from USGS streamflow daily values (DV), readily available from the U.S. Geological Survey National Water Information System (NWIS), for USGS gage stations used in SIR 2017-5099 Variability of Hydrological Droughts in the Conterminous United States, 1951 through 2014 by Samuel H. Austin, David M. Wolock, and David L. Nelms. https://doi. org/10.3133/sir20175099
    map background search result map search result map Monthly Streamflows, Drought Indices, and Supporting Statistics for USGS Gage Stations Used to Identify Variability of Hydrological Droughts in the Conterminous United States, 1951 through 2014 Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the United States (2017) Monthly Streamflows, Drought Indices, and Supporting Statistics for USGS Gage Stations Used to Identify Variability of Hydrological Droughts in the Conterminous United States, 1951 through 2014 Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the United States (2017)