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A sustainable irrigation water management framework coupling water-salt processes simulation and uncertain optimization in an arid area

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  • Li, Xuemin
  • Zhang, Chenglong
  • Huo, Zailin
  • Adeloye, Adebayo J.

Abstract

Field irrigation water management depends on interactions among crop yield, soil water/salt and groundwater/salt in arid irrigation area with shallow-saline groundwater. This paper presents a novel uncertainty simulation-optimization framework for irrigation water allocation and sustainable agricultural environment, which integrates simulation of physical processes of soil-groundwater water and salt balance into an uncertainty-based optimization model. The impacts of crop evapotranspiration, soil water and salt and groundwater levels are interactively involved in the simulation model. Uncertainties (economic and crop parameters, available water amount) presented as fuzzy boundary intervals and probability distribution functions are considered in the optimization model. This field irrigation water allocation framework emphasizes the role of field soil water and salt movement processes to decision-making of irrigation water allocation. Then, the proposed simulation-optimization framework was applied to a case study in the Hetao Irrigation District, an arid area of northwest China where soil salinity is a serious environmental problem induced by irrigation and shallow groundwater. Therefore, optimal irrigation water allocation solutions can be generated for providing decision makers with reliable decision options where the maximum system benefits resulting from sustainable agricultural production are desired. Furthermore, the results can support analysis of interrelationships among system benefits, water allocation planning and groundwater depth, soil salt content constraints. Scenario analysis (groundwater table depth (GTD) = 1, 1.5, 2, 2.5, 3 m and no groundwater exchange consideration) showed that the maximum net benefit could be [27469, 44818] Yuan with the groundwater table depth of 1.5 m. Also, the irrigation water allocation changed when the salt constraint was considered, which indicates that the results obtained by the developed framework can alleviate soil salinization to a certain degree. Therefore, this framework can provide more effective information for the irrigation water management and soil salinization control, which is meaningful for the sustainable development of irrigation agriculture.

Suggested Citation

  • Li, Xuemin & Zhang, Chenglong & Huo, Zailin & Adeloye, Adebayo J., 2020. "A sustainable irrigation water management framework coupling water-salt processes simulation and uncertain optimization in an arid area," Agricultural Water Management, Elsevier, vol. 231(C).
    • Handle: RePEc:eee:agiwat:v:231:y:2020:i:c:s0378377419314106
    DOI: 10.1016/j.agwat.2019.105994
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    1. Feng, Zhao-Zhong & Wang, Xiao-Ke & Feng, Zong-Wei, 2005. "Soil N and salinity leaching after the autumn irrigation and its impact on groundwater in Hetao Irrigation District, China," Agricultural Water Management, Elsevier, vol. 71(2), pages 131-143, February.
    2. Liu, Haijun & Wang, Xuming & Zhang, Xian & Zhang, Liwei & Li, Yan & Huang, Guanhua, 2017. "Evaluation on the responses of maize (Zea mays L.) growth, yield and water use efficiency to drip irrigation water under mulch condition in the Hetao irrigation District of China," Agricultural Water Management, Elsevier, vol. 179(C), pages 144-157.
    3. Domínguez, A. & Tarjuelo, J.M. & de Juan, J.A. & López-Mata, E. & Breidy, J. & Karam, F., 2011. "Deficit irrigation under water stress and salinity conditions: The MOPECO-Salt Model," Agricultural Water Management, Elsevier, vol. 98(9), pages 1451-1461, July.
    4. David Tilman & Kenneth G. Cassman & Pamela A. Matson & Rosamond Naylor & Stephen Polasky, 2002. "Agricultural sustainability and intensive production practices," Nature, Nature, vol. 418(6898), pages 671-677, August.
    5. Li, Mo & Fu, Qiang & Singh, Vijay P. & Liu, Dong, 2018. "An interval multi-objective programming model for irrigation water allocation under uncertainty," Agricultural Water Management, Elsevier, vol. 196(C), pages 24-36.
    6. Fazlullah Akhtar & Bernhard Tischbein & Usman Awan, 2013. "Optimizing Deficit Irrigation Scheduling Under Shallow Groundwater Conditions in Lower Reaches of Amu Darya River Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 3165-3178, June.
    7. Jimenez, Mariano & Arenas, Mar & Bilbao, Amelia & Rodri'guez, M. Victoria, 2007. "Linear programming with fuzzy parameters: An interactive method resolution," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1599-1609, March.
    8. Gao, Xiaoyu & Huo, Zailin & Xu, Xu & Qu, Zhongyi & Huang, Guanhua & Tang, Pengcheng & Bai, Yining, 2018. "Shallow groundwater plays an important role in enhancing irrigation water productivity in an arid area: The perspective from a regional agricultural hydrology simulation," Agricultural Water Management, Elsevier, vol. 208(C), pages 43-58.
    9. Zhang, Chenglong & Guo, Ping, 2018. "FLFP: A fuzzy linear fractional programming approach with double-sided fuzziness for optimal irrigation water allocation," Agricultural Water Management, Elsevier, vol. 199(C), pages 105-119.
    10. Dattatray Regulwar & Jyotiba Gurav, 2011. "Irrigation Planning Under Uncertainty—A Multi Objective Fuzzy Linear Programming Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(5), pages 1387-1416, March.
    11. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
    12. Wen, Yeqiang & Shang, Songhao & Yang, Jian, 2017. "Optimization of irrigation scheduling for spring wheat with mulching and limited irrigation water in an arid climate," Agricultural Water Management, Elsevier, vol. 192(C), pages 33-44.
    13. Kang, Shaozhong & Hao, Xinmei & Du, Taisheng & Tong, Ling & Su, Xiaoling & Lu, Hongna & Li, Xiaolin & Huo, Zailin & Li, Sien & Ding, Risheng, 2017. "Improving agricultural water productivity to ensure food security in China under changing environment: From research to practice," Agricultural Water Management, Elsevier, vol. 179(C), pages 5-17.
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    1. Cao, Zhaodan & Zhu, Tingju & Cai, Ximing, 2023. "Hydro-agro-economic optimization for irrigated farming in an arid region: The Hetao Irrigation District, Inner Mongolia," Agricultural Water Management, Elsevier, vol. 277(C).
    2. Zhang, Xiaoxing & Guo, Ping & Guo, Wenxian & Gong, Juan & Luo, Biao, 2021. "Optimization towards sustainable development in shallow groundwater area and risk analysis," Agricultural Water Management, Elsevier, vol. 258(C).
    3. Li, Xuemin & Zhang, Jingwen & Cai, Ximing & Huo, Zailin & Zhang, Chenglong, 2023. "Simulation-optimization based real-time irrigation scheduling: A human-machine interactive method enhanced by data assimilation," Agricultural Water Management, Elsevier, vol. 276(C).
    4. Wang, Youzhi & Guo, Ping, 2021. "Irrigation water resources optimization with consideration of the regional agro-hydrological process of crop growth and multiple uncertainties," Agricultural Water Management, Elsevier, vol. 245(C).
    5. Zengming Ke & Xiaoli Liu & Lihui Ma & Feng Jiao & Zhanli Wang, 2023. "Spatial Distribution of Soil Water and Salt in a Slightly Salinized Farmland," Sustainability, MDPI, vol. 15(8), pages 1-15, April.
    6. Wang, Xiquan & Zhang, Hongyuan & Zhang, Zhizhong & Zhang, Chenping & Zhang, Kai & Pang, Huancheng & Bell, Stephen M. & Li, Yuyi & Chen, Ji, 2023. "Reinforced soil salinization with distance along the river: A case study of the Yellow River Basin," Agricultural Water Management, Elsevier, vol. 279(C).

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