Achieving comprehensive water productivity improvement: A multi-objective simulation-optimization model for water productivity-oriented irrigation water management

Improving water productivity (WP) from multiple perspectives is crucial for irrigated agriculture in arid areas, particularly due to challenges such as low crop WP, limited economic returns, and secondary soil salinization. In this study, a multi-objective simulation-optimization model is established for maximizing irrigation water productivity (IWP), economic water productivity (EWP), and nutritional water productivity (NWP) concurrently. Moreover, the Environmental Policy Integrated Climate (EPIC) crop growth model and water-salt balance equations are incorporated to readily simulate daily physical processes of crop growth and dynamic water and salt movement. The crop parameters required for simulating these physical processes are parameterized and calibrated based on existing studies. Subsequently, it’s implemented in a case study within the Jiefangzha Irrigation Subarea, which is divided into 44 irrigation subsystems (basic irrigation decision-making units) to reflect the spatial distribution of input data. The Non-dominated Sorting Genetic Algorithm-III (NSGA-III) and Elite Opposition-Based Learning (EOBL) strategy are used to solve the problem and enhance the diversity of the randomly generated initial population accordingly, thus optimal solutions can be generated for supporting high-efficiency irrigation water use. Results indicate that (1) Optimal objectives (mean of the 44 irrigation subsystems) for IWP, EWP, and NWP are 6.72 Yuan/m 3 , 2.36 Kg/m 3 , 20041.7 Kcal/m 3 , with IWP increasing by 32.58 % over the status-quo. (2) Irrigation subsystems 41, 42, and 44 suffer severe salt accumulation, where salt-tolerant sunflowers should be prioritized for planting. (3) Crop root growth processes, sowing time, and growing periods have a strong influence on the salt concentration of actual root zone. Moreover, the proposed model emphasizes the influence of dynamic water-salt movement processes on crop growth and WP. Therefore, the study expands the research on multifaceted crop WP concepts and applications in the arid region, offering scientifically optimal solutions for the efficient utilization of irrigation water and effective salinity control. • A multi-objective model is developed to maximize IWP, EWP and NWP concurrently. • WP is quantitatively evaluated from irrigation, economic and nutritional aspects. • The model emphasizes the influence of water-salt movement on water productivity. • The solution achieves comprehensive WP improvement in low WP and severe salinization.

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Publication Details

Journal
Agricultural Water Management
Published
2025-01-23
DOI
https://doi.org/10.1016/j.agwat.2025.109316
Citations
7
Primary Topic
Water resources management and optimization
Type
article
Field-Weighted Citation Impact
8.02

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article

Achieving comprehensive water productivity improvement: A multi-objective simulation-optimization model for water productivity-oriented irrigation water management

Zailin Huo, Chenglong Zhang, Gang Li, Yanqi Liu
7 citations
Agricultural Water Management
Water resources management and optimization
8.02
article

Achieving comprehensive water productivity improvement: A multi-objective simulation-optimization model for water productivity-oriented irrigation water management

Zailin Huo, Chenglong Zhang, Gang Li, Yanqi Liu
article en
7 citations

Abstract

Improving water productivity (WP) from multiple perspectives is crucial for irrigated agriculture in arid areas, particularly due to challenges such as low crop WP, limited economic returns, and secondary soil salinization. In this study, a multi-objective simulation-optimization model is established for maximizing irrigation water productivity (IWP), economic water productivity (EWP), and nutritional water productivity (NWP) concurrently. Moreover, the Environmental Policy Integrated Climate (EPIC) crop growth model and water-salt balance equations are incorporated to readily simulate daily physical processes of crop growth and dynamic water and salt movement. The crop parameters required for simulating these physical processes are parameterized and calibrated based on existing studies. Subsequently, it’s implemented in a case study within the Jiefangzha Irrigation Subarea, which is divided into 44 irrigation subsystems (basic irrigation decision-making units) to reflect the spatial distribution of input data. The Non-dominated Sorting Genetic Algorithm-III (NSGA-III) and Elite Opposition-Based Learning (EOBL) strategy are used to solve the problem and enhance the diversity of the randomly generated initial population accordingly, thus optimal solutions can be generated for supporting high-efficiency irrigation water use. Results indicate that (1) Optimal objectives (mean of the 44 irrigation subsystems) for IWP, EWP, and NWP are 6.72 Yuan/m 3 , 2.36 Kg/m 3 , 20041.7 Kcal/m 3 , with IWP increasing by 32.58 % over the status-quo. (2) Irrigation subsystems 41, 42, and 44 suffer severe salt accumulation, where salt-tolerant sunflowers should be prioritized for planting. (3) Crop root growth processes, sowing time, and growing periods have a strong influence on the salt concentration of actual root zone. Moreover, the proposed model emphasizes the influence of dynamic water-salt movement processes on crop growth and WP. Therefore, the study expands the research on multifaceted crop WP concepts and applications in the arid region, offering scientifically optimal solutions for the efficient utilization of irrigation water and effective salinity control. • A multi-objective model is developed to maximize IWP, EWP and NWP concurrently. • WP is quantitatively evaluated from irrigation, economic and nutritional aspects. • The model emphasizes the influence of water-salt movement on water productivity. • The solution achieves comprehensive WP improvement in low WP and severe salinization.

Agricultural Water ManagementVol. 309
China Agricultural University (CN), KU Leuven (BE)
National Natural Science Foundation of China
Clean water and sanitation
Openalex Percentile: Top 3%
Water resources management and optimization
8.02
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