This child item describes R code used to determine public supply consumptive use estimates. Consumptive use was estimated by scaling an assumed fraction of deliveries used for outdoor irrigation by spatially explicit estimates of evaporative demand using estimated domestic and commercial, industrial, and institutional deliveries from the public supply delivery machine learning model child item. This method scales public supply water service area outdoor water use by the relationship between service area gross reference evapotranspiration provided by GridMET and annual continental U.S. (CONUS) growing season maximum evapotranspiration. This relationship to climate at the CONUS scale could result in over- or under-estimation of consumptive use at public supply service areas where local variations differ from national variations in climate. This method also assumes that 50% of deliveries for total domestic and commercial, industrial, and institutional deliveries is used for outdoor purposes. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. This page includes the following file: PS_ConsumptiveUse.zip - a zip file containing input datasets, scripts, and output datasets