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<p>The Hetao Irrigation District (HID) is one of the three major irrigation districts in China, and the accurate estimation of the reference crop evapotranspiration (ETo) for effective water resource allocation and crop irrigation planning. In this study, the slime mould algorithm (SMA) was improved (named ISMA) by incorporating good point set initialization and reverse differential evolution methods. Daily meteorological data from five stations in the HID (2000–2014) were used to train and validate the ISMA model for ETo estimation. ISMA’s optimization performance was benchmarked against SMA, particle swarm optimization (PSO), salp swarm algorithm (SSA), and honey badger algorithm (HBA) using 23 test functions, with results demonstrating ISMA’s advantages in fast convergence, stability, and robustness. Six combinations of meteorological parameters (C1-C6) were evaluated, with the C6 combination (T<sub>max</sub>, T<sub>mean</sub>, T<sub>min</sub>, RH, R<sub>s</sub>, u<sub>2</sub>) achieving the best performance at all five stations, including lower MAE (0.085–0.098&#xa0;mm d<sup>−1</sup>), MSE (0.015–0.019), RMSE (0.019–0.134&#xa0;mm d<sup>−1</sup>), MAPE (4.14–5.11%), and the highest R<sup>2</sup> (0.998). Additionally, the C4 combination (T<sub>max</sub>, T<sub>mean</sub>, RH, R<sub>s</sub>) also provided satisfactory estimation accuracy. The results highlighted the critical role of solar radiation as a key input for ETo modeling in HID. In conclusion, ISMA demonstrated high accuracy and adaptability in estimating daily ETo with limited meteorological data, offering valuable data support for water resource management and promoting the development of precision agriculture in the HID.</p>

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Estimation of daily reference evapotranspiration based on an improved Slime Mould Algorithm (SMA) for the Hetao irrigation district in northwest China

  • 期刊论文

  • 发表日期：

    2025年1月15日

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  • Huaijie He,
  • Zhengqian Wang,
  • Zhenchen Wang,
  • Desheng Liu,
  • Li Ouyang,
  • Mingzhi Zhao,
  • Lei He,
  • Pingnan Ma

摘要

The Hetao Irrigation District (HID) is one of the three major irrigation districts in China, and the accurate estimation of the reference crop evapotranspiration (ETo) for effective water resource allocation and crop irrigation planning. In this study, the slime mould algorithm (SMA) was improved (named ISMA) by incorporating good point set initialization and reverse differential evolution methods. Daily meteorological data from five stations in the HID (2000–2014) were used to train and validate the ISMA model for ETo estimation. ISMA’s optimization performance was benchmarked against SMA, particle swarm optimization (PSO), salp swarm algorithm (SSA), and honey badger algorithm (HBA) using 23 test functions, with results demonstrating ISMA’s advantages in fast convergence, stability, and robustness. Six combinations of meteorological parameters (C1-C6) were evaluated, with the C6 combination (Tmax, Tmean, Tmin, RH, Rs, u2) achieving the best performance at all five stations, including lower MAE (0.085–0.098 mm d−1), MSE (0.015–0.019), RMSE (0.019–0.134 mm d−1), MAPE (4.14–5.11%), and the highest R2 (0.998). Additionally, the C4 combination (Tmax, Tmean, RH, Rs) also provided satisfactory estimation accuracy. The results highlighted the critical role of solar radiation as a key input for ETo modeling in HID. In conclusion, ISMA demonstrated high accuracy and adaptability in estimating daily ETo with limited meteorological data, offering valuable data support for water resource management and promoting the development of precision agriculture in the HID.