Statistical blending of global-gridded climatological products: an approach to inverse hydrological model

Abstract The growing use of global-scale environmental products in hydro-climatic modeling (with different assumptions, resolutions, and precisions) has increased the variety their applications complications uncertainties evaluations. Researchers have recently turned to statistical blending (fusion) these achieve optimal while avoiding difficulties. proposed this study includes five large-scale satellite precipitation (Climate Hazards Group Infrared Precipitation with Stations (CHIRPS), ERA5-Land ECMWF (ERA), Integrated Multi-Satellite Retrievals for GPM (IMERG), Tropical Rainfall Measuring Mission (TRMM), Terra) evapotranspiration (Global Land Evaporation Amsterdam Model (GLEAM), SSEBop, Moderate Resolution Imaging Spectroradiometer (MODIS), Terra, ERA) committed three scenarios. procedures are organized using a conceptual water balance model best results production streamflow hydrological inverse modeling. Based on results, improved performance metrics. In addition, show conformity pattern behavior blended calculated moving least square method area. This happened by changing estimation based situ values, particularly cold months considering orographic/snow effects. combining provides good fusion procedure improve realistic ungagged watersheds as well.