Rationale and Efficacy of Assimilating Remotely Sensed Potential Evapotranspiration for Reduced Uncertainty of Hydrologic Models

Abstract The objective of this study is to systematically attribute sources of evapotranspiration uncertainty in a hydrologic model and accordingly propose a remote sensing‐based solution. Using Soil and Water Assessment Tool (SWAT) for three U.S. watersheds, representing different geophysical settings, this study first addresses the effects of parameter equifinality, energy‐related weather input uncertainty, and limited process representation on evapotranspiration simulation. Remotely sensed 8‐day total actual evapotranspiration (AET) from Moderate Resolution Imaging Spectroradiometer (MODIS) is used as a reference to evaluate the model outcome. Results indicate the likelihood of a pseudo‐accurate model showing high streamflow prediction skill despite severely erroneous spatiotemporal dynamics of AET. As a remedial measure, a hybrid daily potential evapotranspiration (PET) estimate, derived from MODIS, is directly ingested at each hydrologic response unit of the model to create a new configuration called SWAT‐PET. A key contribution is the modified SWAT source code that integrates the model (i.e., SWAT‐PET) with an automatic remote sensing data processor. The underlying notion is that remotely sensed PET works as a surrogate of actual vegetation dynamics, biophysical processes, and energy balance, without overruling the model's built‐in soil moisture accounting. Noticeably, increased accuracy of soil moisture, AET, and streamflow in SWAT‐PET, compared to independent sources of observations/reference estimates (i.e., field sensor, satellite, and gauge stations), approves the efficacy of the proposed approach toward improved physical consistency of hydrologic modeling. While the idea is tested for a past period, the ultimate goal is to improve near‐real‐time hydrologic forecasting once such PET estimates become available.