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Filters: Tags: Surface water hydrology (X) > partyWithName: Samuel H Austin (X)

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Tables are presented listing parameters and fit statistics for 25,453 maximum likelihood logistic regression (MLLR) models describing hydrological drought probabilities at 324 gaged locations on rivers and streams in the Delaware River Basin (DRB). Data from previous months are used to estimate chance of hydrological drought during future summer months. Models containing 1 explanatory variable use monthly mean daily streamflow data (DV) to provide hydrological drought streamflow probabilities for July, August, and September as functions of monthly mean DV from the previous 11 months. Outcomes are estimated 1 to 12 months ahead of their occurrence. Models containing 2 explanatory variables use monthly mean daily...
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Tables are presented listing parameters used in logistic regression equations describing drought streamflow probabilities in the Northeastern United States. Streamflow daily data, streamflow monthly mean data, maximum likelihood logistic regression (MLLR) equation explanatory parameters, equation goodness of fit parameters, and Receiver Operating Characteristic (ROC) AUC values identifying the utility of each relation, describe each model of the probability (chance) of a particular streamflow daily value exceeding or not exceeding an identified drought streamflow threshold.


    map background search result map search result map Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Northeastern United States (2019) Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Delaware River Basin (2020) Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Delaware River Basin (2020) Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Northeastern United States (2019)