气候变化领域集成服务门户

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.