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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Reliable estimation of evapotranspiration on agricultural fields predicted by Priestley-Taylor model using soil moisture data from ground and remote sensing observations compared with Common Land Model

Authors
item Choi, Minha -
item Tae, Woong -
item Kustas, William

Submitted to: International Journal of Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 8, 2010
Publication Date: August 22, 2011
Citation: Choi, M., Tae, W.K., Kustas, W.P. 2011. Reliable estimation of evapotranspiration on agricultural fields predicted by Priestley-Taylor model using soil moisture data from ground and remote sensing observations compared with Common Land Model. International Journal of Remote Sensing. 32(16):4571-4587.

Interpretive Summary: Reliable evapotranspiration (ET) estimates are critical in evaluating the hydrologic cycle and water resources for watersheds and regions. In addition, ET is an important metric used in assessing environmental conditions such as drought in natural and agricultural ecosystems. Providing spatially-distributed maps of ET required for watershed and regional assessments is problematic using ground observations, so models been developed using remotely sensed inputs that range in level of complexity from empirical to physically-based approaches, fully treating soil-vegetation-atmosphere interactions. A relatively simple model, the Priestley-Taylor (P-T) approach, and the complex physically-based Common Land Model (CLM) are compared for a corn-soybean production region encompassing Ames, Iowa. ET measurements are compared to output from these two models using ground and remotely sensed soil moisture data as a constraint to potential ET computed by the P-T model. Results show that the relatively simple P-T formulation performs as well as the complex processed-based CLM scheme when the soil moisture constraint on the P-T technique is imposed, which can be derived from remote sensing. This suggests that remote sensing-based methods using relatively simple ET formulations may provide reliable estimates for agricultural crops at watershed and regional scales.

Technical Abstract: Evapotranspiration (ET) is a crucial factor in understanding the hydrologic cycle and essential to many applications in hydrology, ecology, and water resources management. However, reliable ET measurements and predictions for a range of temporal and spatial scales are difficult. This study focuses on the comparison of ET estimates using a relatively simple model, the Priestley-Taylor (P-T) approach and the physically-based Common Land Model (CLM) using ground and remotely sensed soil moisture data as input. The results from both models were directly compared with hourly eddy covariance measurements at two agricultural field sites during the Soil Moisture-Atmosphere Coupling Experiment in the corn soybean production region in the upper Midwest, United States. The P-T model showed a significant overestimation of the potential ET compared to the measurements with a root-mean square error (RMSE) between 115 and 130 Wm-2. Actual ET was better predicted by the CLM with RMSE ranging between 50 and 75 Wm-2. However, the actual ET from the P-T model constrained with a soil moisture dependency parameterization showed improved results when compared to the measurements with a significantly reduced bias and RMSE values between 60 and 65 Wm-2. This study suggests that even with a simple semi-empirical ET model similar performance in estimating actual ET for agricultural crops compared to more complex land surface-atmosphere models (i.e., CLM) can be achieved when constrained with the soil moisture function. This may imply that remote sensing soil moisture estimates from the Advanced Microwave Scanning Radiometer - Earth Observing System and others such as Soil Moisture and Ocean Salinity may be an effective alternative under certain environmental conditions for estimating actual ET of agricultural crops using a fairly simple algorithm.

Last Modified: 10/23/2014
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