Estimating daily kiwifruit evapotranspiration under regulated deficit irrigation strategy using optimized surface resistance based model

文献类型： 外文期刊

第一作者： Xing, Liwen

作者： Xing, Liwen;Cui, Ningbo;Guo, Li;Wu, Zongjun;Wen, Shenglin;Zhao, Lu;Liu, Chunwei;Zhao, Long;Jiang, Xuelian;Gong, Daozhi

作者机构：

关键词： Water consumption; Jarvis model; Clumping model; Soil water deficit coefficient; Whale Optimization Algorithm

期刊名称：AGRICULTURAL WATER MANAGEMENT （ 影响因子：6.7； 五年影响因子：6.6 ）

ISSN： 0378-3774

年卷期： 2024 年 295 卷

页码：

收录情况： SCI

摘要： Accurate evapotranspiration (ET) estimation is paramount for effective agricultural water management. As the key parameter of surface resistance (rs)-based ET models, the direct acquisition of canopy resistance (rc) remains challenge. Moreover, the applicability of rc models and rs-based ET models has not been fully validated on kiwifruit. To address above problems, this study investigates tree growth patterns, water consumption change, and soil water content (SWC) dynamics under different irrigation strategies based on a two-year experiment in Northwest China. Subsequently, the Whale Algorithm (WOA), Quantum Whale Algorithm (QWOA), and Differential Whale Algorithm (DWOA) were employed to optimize Jarvis-type rc models (JA) constructed by different constraint functions of SWC. After internal comparison within Jarvis-type models and external comparison with Kelliher-Perrier (KP), Faria (FA), and Stannard (ST) model, the recommended rc model was integrated into Penman-Monteith (PM), Shuttleworth-Wallace (SW), and Clumping (CL) to select most suitable kiwifruit ET model. The results indicated that the water stress coefficient is suitable for JA model as a constraint function of SWC, achieving R2, NSE, RMSE, and MAPE of 0.782-0.805, 0.672-0.737, 654.191-3396.594 s m-1, and 0.102-0.183 under sufficient irrigation strategy, respectively. Under deficit irrigation strategies, the corresponding R2, NSE, RMSE, and MAPE ranged 0.886-0.917, 0.828-0.885, 325.736-3251.434 s m-1, and 0.111-0.166, respectively. Besides, DWOA is the best algorithm during whole growth period, which improved original JA by 13.2-32.9% for R2, 23.0-60.2% for NSE, 26.8-36.8% for RMSE, and 17.5-36.2%, respectively. Regarding rs-based ET models, the CL performed best under various irrigation conditions, with values of R2, NSE, RMSE, and MAPE ranging 0.908-0.961, 0.842-0.947, 0.311-0.808 mm, and 0.088-0.197, respectively. Overall, the CL integrated with DWOA-JA3 is most recommended for estimating kiwifruit ET under different irrigation strategies, which is helpful for orchardists to enhance agricultural water utilization efficiency and promote sustainable kiwifruit production.

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