Dynamic control of upper limit for rainfall storing and effective use in rice paddies based on improved AquaCrop model

Increasing the upper limit of rainfall storage to enhance rainfall utilization is an important approach for conserving irrigation water in rice production while also avoiding yield losses caused by excessive flooding depth and prolonged inundation. However, traditional static water level control met...

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Bibliographic Details
Main Authors: En Lin, Rangjian Qiu, Xinxin Li, Mengting Chen, Shizong Zheng, Fei Ren, Xiaoming Xiang, Chenglong Ji, Yuanlai Cui, Yufeng Luo
Format: Article
Language:English
Published: Elsevier 2025-07-01
Series:Agricultural Water Management
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Online Access:http://www.sciencedirect.com/science/article/pii/S0378377425002835
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Summary:Increasing the upper limit of rainfall storage to enhance rainfall utilization is an important approach for conserving irrigation water in rice production while also avoiding yield losses caused by excessive flooding depth and prolonged inundation. However, traditional static water level control methods, which apply fixed storage limits at different growth stages, often fail to align with the dynamic nature of rainfall and crop water demand, leading to inefficiencies and increased waterlogging risk. This study proposed a dynamic rainfall storage control strategy based on 1–7-day weather forecasts. To evaluate its effectiveness, the AquaCrop model was modified by incorporating a waterlogging stress coefficient, resulting in the ACOP-FRice model. The model accurately simulated rice yield under various waterlogging conditions and demonstrated strong stability across growth stages. During the validation period, the late tillering stage showed the best performance of yield simulation accuracy, with a normalized root mean square error (NRMSE) of 7.39 %, and both the coefficient of determination (R2) and nash-sutcliffe efficiency (NSE) coefficient values reaching 0.83. Although the heading–flowering stage was the most sensitive to flooding, the model still achieved reasonable accuracy, with an NRMSE of 11.61 % and R² and NSE values of 0.81, indicating its ability to capture yield variations under complex stress conditions. Compared to static control, the dynamic strategies HP1, HP2, and HP3 increased rainfall use efficiency by 10.90–17.84 % and reduced drainage by 3.90–19.30 % for early rice, 3.10–12.00 % for mid-season rice, and 21.91–25.44 % for late rice. Yield losses across all scenarios remained below 3.00 %, confirming the strategy’s potential to optimize water management while minimizing adverse impacts on yield.
ISSN:1873-2283