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Self-Organizing Optimization of Water Resources and Soil Moisture Content to Sustainable Agriculture

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Abstract

Hydrological phenomena have probabilistic components that affect water resource management strategies. A risk-based sustainable management scenario will create a structure that considers the role of uncertain variables in predicting water consumption. The present study aims at investigating the impact of the drought duration and severity on water resources and soil moisture supplements for agricultural activities in Huai River Basin, China. Two objective functions including minimization of the soil dryness index (SDI) and river allocation index (RAI) were formulated. The cropping pattern was simulated using AquaCrop with 12 main plants in daily time steps. Grey wolf optimizer was combined with the non-dominated sorting theory for developing a self-organizing multiobjective optimization algorithm to achieve optimal water allocation. Furthermore, water use efficiency was incorporated as a stopping criterion to improve the expected yield production. Results showed that the multiobjective optimization model decreases the existing water resource index from 0.71 to − 2.12, − 1.27 and − 0.72 for 2 years, 10 years and 50 years, respectively. Moreover, soil moisture content when air-dry had an important role in the arrangement of the Pareto front solutions.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

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  1. College of Modern Agriculture, Changchun Polytechnic, Changchun, 130504, Jilin, China

    Xuewen Sheng

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Sheng, X. Self-Organizing Optimization of Water Resources and Soil Moisture Content to Sustainable Agriculture. Iran J Sci Technol Trans Civ Eng 47, 1801–1811 (2023). https://doi.org/10.1007/s40996-022-00976-w

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