Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Northeastern United States (2019)

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. These models are key inputs to drought forecasting web applications for the northeastern United states {https://usgs.maps.arcgis.com/apps/MapSeries/index.html?appid=b8c5da617a0e4d628e3e39f7dbd512da}

Data and Resources

Field Value
accessLevel public
bureauCode {010:12}
catalog_@context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
catalog_describedBy https://project-open-data.cio.gov/v1.1/schema/catalog.json
identifier USGS:5d681d5de4b0c4f70cf15c9b
metadata_type geospatial
modified 20210903
old-spatial -84.067382812719, 35.977652111331, -66.137695313435, 47.768574328315
publisher U.S. Geological Survey
publisher_hierarchy Department of the Interior > U.S. Geological Survey
resource-type Dataset
source_datajson_identifier true
source_hash c5d75e871299eb2461fe85f1f58d9df2a34b95bc
source_schema_version 1.1
spatial {"type": "Polygon", "coordinates": [[[-84.067382812719, 35.977652111331], [-84.067382812719, 47.768574328315], [ -66.137695313435, 47.768574328315], [ -66.137695313435, 35.977652111331], [-84.067382812719, 35.977652111331]]]}
theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • amerigeo
  • amerigeoss
  • ckan
  • connecticut
  • decision-support-systems
  • delaware
  • district-of-columbia
  • drought
  • forecasting
  • geo
  • geoss
  • maine
  • maryland
  • massachusetts
  • national
  • new-hampshire
  • new-jersey
  • new-york
  • north-america
  • pennsylvania
  • rhode-island
  • risk-assessment
  • streamflow
  • surface-water-hydrology
  • united-states
  • usgs-5d681d5de4b0c4f70cf15c9b
  • vermont
  • virginia
  • water-supply
  • watershed-management
  • west-virginia
isopen False
license_id notspecified
license_title License not specified
maintainer Samuel H Austin
maintainer_email saustin@usgs.gov
metadata_created 2025-11-22T03:41:31.093303
metadata_modified 2025-11-22T03:41:31.093307
notes 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. These models are key inputs to drought forecasting web applications for the northeastern United states {https://usgs.maps.arcgis.com/apps/MapSeries/index.html?appid=b8c5da617a0e4d628e3e39f7dbd512da}
num_resources 2
num_tags 31
title Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Northeastern United States (2019)