pyCropWat: A Python Package for Computing Effective Precipitation Using Google Earth Engine Climate Data

pyCropWat is a Python package for computing effective precipitation (the portion of rainfall that is actually available for crop use) using climate data from Google Earth Engine (GEE; https://earthengine.google.com/) and the GEE community catalog (https://gee-community-catalog.org/). It implements multiple established methods including the USDA Soil Conservation Service (SCS) formula, FAO/AGLW empirical approach, and the classical CROPWAT methodology, enabling users to select the most appropriate technique for their region and application. The package seamlessly integrates with global (ERA5-Land, TerraClimate) and U.S.-specific (GridMET, PRISM) climate datasets, supporting flexible temporal ranges and custom geographic boundaries. Beyond core calculations, pyCropWat provides comprehensive analysis tools for temporal aggregation, climatological statistics, anomaly detection, and trend analysis, along with publication-ready visualization capabilities. Designed for agricultural water management, hydrological modeling, and water footprint assessments, the package offers both a Python API for programmatic workflows and a command-line interface for rapid data processing.