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ARS Home » Plains Area » Bushland, Texas » Conservation and Production Research Laboratory » Soil and Water Management Research » Research » Publications at this Location » Publication #348805

Research Project: Precipitation and Irrigation Management to Optimize Profits from Crop Production

Location: Soil and Water Management Research

Title: Evaluation of the uncalibrated energy balance model (BAITSSS)for estimating evapotranspiration in a semiarid, advective climate

Author
item Dhungel, Ramesh - Kansas State University
item Aiken, Robert - Kansas State University
item Colaizzi, Paul
item Lin, Xiaomao - Kansas State University
item O'brien, Dan - Kansas State University Extension Center
item Baumhardt, Roland - Louis
item Brauer, David - Dave
item Marek, Gary
item Evett, Steven - Steve

Submitted to: Hydrological Processes
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/28/2019
Publication Date: N/A
Citation: N/A

Interpretive Summary: Predicting crop water use is important for conserving water and managing irrigation, and maximizing farm profits. Corn is profitable but has a high water requirement. Water use by corn can be predicted by models; however, these models are not always accurate and can be too complex for use by farmers and crop consultations. Therefore, scientists at USDA Agricultural Research Service (Bushland, Texas) and Kansas State University tested a new crop water use model that was designed to achieve accuracy across different locations without being overly complex. The model accurately predicted the water use of corn for an entire growing season in Bushland, Texas. The model did not require calibration for the windy conditions of Texas. Therefore, the new model will help farmers conserve water and increase farm profits.

Technical Abstract: An energy balance model was developed to calculate crop evapotranspiration (ETc) at point to regional scales. The model is termed the Backward-Averaged Iterative Two-Source Surface temperature and energy balance Solution (BAITSSS). The BAITSSS model is driven by micrometeorological and surface temperature measurements, and simulates the water and energy balance of the soil and canopy separately, where canopy resistance is calculated by the Jarvis model. The BAITSSS model has so far undergone limited testing in Idaho. This study conducted a blind test of the model without prior calibration using drought-tolerant corn (Zea mays L. cv. PIO 1151) in Bushland, Texas. The location is a semiarid, advective climate, and ETc calculated by the model was compared to ETc measured by a large weighing lysimeter. Early in the season when vegetation cover was sparse, BAITSSS underestimated ETc by about 2 mm d-1. Late in the season when leaves were senescing, BAITSSS overestimated ETc by up to 3 mm d-1. For the entire growing season, calculated vs. measured ETc resulted in RMSE = 0.14 mm h-1 and 1.79 mm d-1; MAE = 0.08 mm h-1 and 1.32 mm d-1, and MBE = 0.02 mm h-1 and 0.48 mm d-1. The results were comparable to other thermally-driven ETc models that required some calibration. Therefore, the BAITSSS model was deemed robust. Nonetheless, measurement of initial soil water, more site-specific soil resistance parameters, and including the fraction of green leaf area to account for late-season leaf senescence may improve the model.