This data supports the study to assess the impacts of climate change on terrestrial hydrological components and Crop Water Requirement (CWR) over the Chesapeake Bay watershed using a combination of Global Climate Models (GCMs) and a land surface model. To better understand the impacts of climate change on the hydrological cycle, long-term simulations of multiple earth system models from the Coupled Model Intercomparison Project (CMIP Phase 5) are statistically downscaled and bias-corrected using Multivariate Adaptive Constructed Analogs (MACA) scheme for use as model forcings. Precipitation indices from the twenty MACA-based GCMs are used to identify six best performing models. A mesoscale approach is developed, where CWR is estimated by accounting for the impacts of changing climate conditions and rising carbon dioxide levels. Daily grid-based crop coefficients are derived from evapotranspiration data. The findings indicate an annual increase of 18% in evapotranspiration and an annual decrease of 5% in streamflow for the RCP 8.5 scenario towards the end of the 21st century. A reduction of 13% and 17% in CWR is observed for corn and soybeans, respectively due to wetter antecedent soil moisture conditions resulting from increased total precipitation and rising carbon dioxide levels. This mesoscale approach can be scaled globally to project CWR for use in data-scarce agricultural regions and enabling better management of water resources.

This data supports the study to assess the impacts of climate change on terrestrial hydrological components and Crop Water Requirement (CWR) over the Chesapeake Bay watershed using a combination of Global Climate Models (GCMs) and a land surface model. To better understand the impacts of climate change on the hydrological cycle, long-term simulations of multiple earth system models from the Coupled Model Intercomparison Project (CMIP Phase 5) are statistically downscaled and bias-corrected using Multivariate Adaptive Constructed Analogs (MACA) scheme for use as model forcings. Precipitation indices from the twenty MACA-based GCMs are used to identify six best performing models. A mesoscale approach is developed, where CWR is estimated by accounting for the impacts of changing climate conditions and rising carbon dioxide levels. Daily grid-based crop coefficients are derived from evapotranspiration data. The findings indicate an annual increase of 18% in evapotranspiration and an annual decrease of 5% in streamflow for the RCP 8.5 scenario towards the end of the 21st century. A reduction of 13% and 17% in CWR is observed for corn and soybeans, respectively due to wetter antecedent soil moisture conditions resulting from increased total precipitation and rising carbon dioxide levels. This mesoscale approach can be scaled globally to project CWR for use in data-scarce agricultural regions and enabling better management of water resources.