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Irrigation schedule analysis and optimization under the different combination of P and ET0 using a spatially distributed crop model

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  • Liu, Xiao
  • Yang, Dawen

Abstract

In recent years, as drought intensifies and agricultural water consumption increases, it is of great significance to optimize the irrigation schedule to ensure regional food security. This paper constructs the distributed AquaCrop model and multi-objective genetic algorithm (NSGA - Ⅱ) simulation - optimization (MGSO) model to facilitate the development of a rational irrigation schedule. The distributed AquaCrop model considers the spatial variability of soil, climate, crops, and management practices, which can be batch calibrated using the XGBoost method. The MGSO model is for irrigation schedules under the combination of different Precipitation and ET0. In this paper, crop yield, ET, and water use efficiency (WUE) were simulated and analyzed in 13 irrigation zones in Northeast China, where the existing irrigation schedules were analyzed and optimized. The results showed that the distributed AquaCrop model could simulate regional crops well. Crop yields in the study area ranged from 3 to 10ton/hm2. The western part of Heilongjiang province and the northern part of Jilin province has a higher yield. The simulation results of Heilongjiang Province are more accurate, and the relative error is minor. The joint distribution model constructed by the Frank Copula function can describe the joint probability distribution characteristics of precipitation and ET0. According to the simulation results, each typical station has a different performance under the existing irrigation schedule under different situations. The crop yield and WUE of some stations changed significantly. The maximum and minimum yield difference was 22% for Harbin, 32% for Heihe, and 21% for Dunhua. It is mainly due to the irrigation amount in some scenarios that do not meet crop water requirements. Under the optimized irrigation schedule, the crop yield and WUE in different scenarios have been improved by the MGSO model in the Harbin station

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  • Liu, Xiao & Yang, Dawen, 2021. "Irrigation schedule analysis and optimization under the different combination of P and ET0 using a spatially distributed crop model," Agricultural Water Management, Elsevier, vol. 256(C).
    • Handle: RePEc:eee:agiwat:v:256:y:2021:i:c:s0378377421003498
    DOI: 10.1016/j.agwat.2021.107084
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    1. Wang, Yue & Jiang, Kongtao & Shen, Hongzheng & Wang, Nan & Liu, Ruizhe & Wu, Jiujiang & Ma, Xiaoyi, 2023. "Decision-making method for maize irrigation in supplementary irrigation areas based on the DSSAT model and a genetic algorithm," Agricultural Water Management, Elsevier, vol. 280(C).
    2. Chen, Mengting & Linker, Raphael & Wu, Conglin & Xie, Hua & Cui, Yuanlai & Luo, Yufeng & Lv, Xinwei & Zheng, Shizong, 2022. "Multi-objective optimization of rice irrigation modes using ACOP-Rice model and historical meteorological data," Agricultural Water Management, Elsevier, vol. 272(C).
    3. Zhang, Fan & Cui, Ningbo & Guo, Shanshan & Yue, Qiong & Jiang, Shouzheng & Zhu, Bin & Yu, Xiuyun, 2023. "Irrigation strategy optimization in irrigation districts with seasonal agricultural drought in southwest China: A copula-based stochastic multiobjective approach," Agricultural Water Management, Elsevier, vol. 282(C).
    4. Wu, Hui & Yue, Qiong & Guo, Ping & Xu, Xiaoyu & Huang, Xi, 2022. "Improving the AquaCrop model to achieve direct simulation of evapotranspiration under nitrogen stress and joint simulation-optimization of irrigation and fertilizer schedules," Agricultural Water Management, Elsevier, vol. 266(C).

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