Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the United States (2017)

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 by Samuel H. Austin and David L. Nelms, JAWRA 1-14, https://doi.org/10.1111/1752-1688.12562.

[
  "010:12"
]

[
  "geospatial"
]