Comparison of surface resistance‐based models for estimating maize evapotranspiration in a humid region of China

Abstract

AbstractAccurate simulation of evapotranspiration (ET) is essential to enhance efficient irrigation management in the maize field. Here, we evaluated the performance of four mathematical models for estimating the ET of maize. The four models based on surface resistance calculate ET from different vapor sources, which are Penman‐Monteith (PM) through the “big leaf” model, the Shuttleworth‐Wallace (SW) model for distinguishing between soil and canopy, the clumping (C) model for distinguishing between canopy, soils under the canopy and bare soil, and the seasonal clumping (Cj) model for dividing ET into transpiration of sunlit leaves and shaded leaves, evaporation of bare soil surface, sunlit soil surface of canopy gap fraction, and canopy shaded soil surfaces. The models were calibrated by ET measured from a weighing lysimeter, transpiration by the sap flux method, and soil evaporation by micro‐lysimeters in 2014, 2015, and 2017. Results showed that the measured daily transpiration was 3.32 mm/day during the full‐grown stage of maize, and the mean measured daily soil evaporation was 1.46 mm/day. The performance of the sap flow for transpiration plus micro‐lysimeter for soil evaporation method was consistent with the large‐weighted lysimeter method in measuring daily ET. For simulating versus measuring hourly transpiration, the Cj model performed better than the C model with a slope of 0.94, determination coefficient (R2) of 0.85, mean absolute error (MAE) of 0.08 mm/h, and modified agreement index (d) of 0.81. In simulating daily soil evaporation, the Cj model also had a higher slope and less MAE than the C and SW models. Nevertheless, the Cj model yielded increased slope and d and decreased MAE between simulated and measured daily ET. The most sensitive environmental factor in the Cj model is temperature. With a 50% increase in temperature, ET, transpiration, and evaporation increase by 45%, 36%, and 69%, respectively. In summary, the Cj model improved the accuracy for hourly and daily ET of maize and helped separate plant transpiration and soil evaporation, thus giving an available approach for precision irrigation in water management of maize planting systems.