Estimating evapotranspiration and yield of wheat and maize croplands through a remote sensing-based model

作者：Xingwang Wang, Huimin Lei, Jiadi Li, Zailin Huo, Yongqiang Zhang, Yanping Qu · 发表于：Agricultural Water Management · 年份：2023 · DOI：10.1016/j.agwat.2023.108294 · 被引用次数：34 · 研究领域：Plant Water Relations and Carbon Dynamics、Irrigation Practices and Water Management、Greenhouse Technology and Climate Control

Estimation of evapotranspiration (ET) and yield over cropland is essential for water resources management and food security. Particularly the estimation at long-term and regional scales still needs to be investigated. In this study, a remotely sensed and water-carbon coupled model was combined with a process-based crop growth simulation method to simultaneously estimate ET and yield. The developed model was tested for two of the most important crops (wheat and maize) with years of observations. Leaf area index determined by various remote sensing indices and individually calibrated parameters for wheat and maize were considered to improve crop ET and gross primary production (GPP) estimates. The parameters well reflected different physiological properties that C4 maize has a smaller stomatal conductance coefficient and a larger sensitivity in response to initial light than C3 wheat. Comparing with 20 years of measurements, the root mean square error (RMSE) of ET and GPP for winter wheat was 0.57 mm d−1 and 1.65 g C m−2 d−1, and for maize were 0.80 mm d−1 and 2.92 g C m−2 d−1, respectively. Besides, crop growth simulation including biomass accumulation and allocation agreed well with the measurements. Coefficient of determination was mostly larger than 0.66, and RMSE of yield was 554.7 and 1346.6 kg hm−2 for wheat and maize, respectively. Finally, the spatiotemporal crop water productivity (WP) of winter wheat and summer maize in the North China Plain during 2001–2018 were qua...