Research 

Climate change is driving an increase in the frequency and intensity of extreme weather events, with alterations to the functioning of the water cycle. Global-scale assessments of shifts in the hydrologic response to climatic perturbations (i.e. hydrologic sensitivity) are needed to identify regions where mitigation efforts will be necessary to avert detrimental changes on terrestrial water resources. 

This study introduces the crop and land cover land use (CLCLU) dataset, a 30 m resolution product providing annual maps of CLCLU across the transnational Middle Rio Grande (MRG) region, spanning both the U.S. and Mexico from 1994 to 2024. The model was trained using the Cropland Data Layer (CDL) on the US side.

This study identifies the forest types worldwide that are approaching ecological tipping points with the potential to disrupt rainfall, evapotranspiration, and the broader water-cycle dynamics.