IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v245y2021ics0378377420321223.html
   My bibliography  Save this article

Optimizing irrigation schedule in a large agricultural region under different hydrologic scenarios

Author

Listed:
  • Guo, Daxin
  • Olesen, Jørgen Eivind
  • Manevski, Kiril
  • Ma, Xiaoyi

Abstract

Irrigation schedule is essential for improving crop production and allocating water resources in agricultural regions that heavily rely on irrigation. This study designs a framework based on the AquaCrop model to optimize the irrigation schedule of winter wheat under dry, normal and wet hydrologic scenarios over a large region in China. The model parameters were calibrated for one cultivar using observed data from three locations in the Fenwei Plain, northern China, and were shown to slightly vary spatially across this region. Regional weather data at high spatio-temporal resolution were generated by interpolation and were combined with regional soil data on a 2 × 2 km grid to drive the model. The irrigation schedule for the study area was optimized by combining a multi-objective algorithm with the exponential efficacy coefficient method. The optimization objectives included crop yield, water use efficiency (WUE), irrigation WUE and economic irrigation benefit. The results showed that the optimized irrigation schedule performed better than the current irrigation schedule applied by the farmers under studied hydrologic scenarios, resulting in increased crop yield, WUE, irrigation WUE and irrigation economic benefit by 1.1–9.7% and decreased irrigation amount by 4.2–5.7%, depending on regions within the study area. The framework developed in this study reallocated irrigation water amounts between regions, thereby improving water allocation to achieve optimal crop yield, water use and economic benefit for the Fenwei Plain. The results can also serve as a guide for local farmers and irrigation district managers.

Suggested Citation

  • Guo, Daxin & Olesen, Jørgen Eivind & Manevski, Kiril & Ma, Xiaoyi, 2021. "Optimizing irrigation schedule in a large agricultural region under different hydrologic scenarios," Agricultural Water Management, Elsevier, vol. 245(C).
  • Handle: RePEc:eee:agiwat:v:245:y:2021:i:c:s0378377420321223
    DOI: 10.1016/j.agwat.2020.106575
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377420321223
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2020.106575?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Han, Congying & Zhang, Baozhong & Chen, He & Wei, Zheng & Liu, Yu, 2019. "Spatially distributed crop model based on remote sensing," Agricultural Water Management, Elsevier, vol. 218(C), pages 165-173.
    2. M. Tabari & Jaber Soltani, 2013. "Multi-Objective Optimal Model for Conjunctive Use Management Using SGAs and NSGA-II Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(1), pages 37-53, January.
    3. H. Wang & Y. Dong & Y. Wang & Q. Liu, 2008. "Water Right Institution and Strategies of the Yellow River Valley," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(10), pages 1499-1519, October.
    4. Yang, Gaiqiang & Guo, Ping & Huo, Lijuan & Ren, Chongfeng, 2015. "Optimization of the irrigation water resources for Shijin irrigation district in north China," Agricultural Water Management, Elsevier, vol. 158(C), pages 82-98.
    5. Li, Jiang & Song, Jian & Li, Mo & Shang, Songhao & Mao, Xiaomin & Yang, Jian & Adeloye, Adebayo J., 2018. "Optimization of irrigation scheduling for spring wheat based on simulation-optimization model under uncertainty," Agricultural Water Management, Elsevier, vol. 208(C), pages 245-260.
    6. Kang, Shaozhong & Zhang, Lu & Liang, Yinli & Hu, Xiaotao & Cai, Huanjie & Gu, Binjie, 2002. "Effects of limited irrigation on yield and water use efficiency of winter wheat in the Loess Plateau of China," Agricultural Water Management, Elsevier, vol. 55(3), pages 203-216, June.
    7. Abdul Rehman & Luan Jingdong, 2017. "An econometric analysis of major Chinese food crops: An empirical study," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1323372-132, January.
    8. Xiangxiang, Wang & Quanjiu, Wang & Jun, Fan & Qiuping, Fu, 2013. "Evaluation of the AquaCrop model for simulating the impact of water deficits and different irrigation regimes on the biomass and yield of winter wheat grown on China's Loess Plateau," Agricultural Water Management, Elsevier, vol. 129(C), pages 95-104.
    9. Li, Mo & Guo, Ping & Singh, Vijay P., 2016. "An efficient irrigation water allocation model under uncertainty," Agricultural Systems, Elsevier, vol. 144(C), pages 46-57.
    10. Linker, Raphael & Ioslovich, Ilya & Sylaios, Georgios & Plauborg, Finn & Battilani, Adriano, 2016. "Optimal model-based deficit irrigation scheduling using AquaCrop: A simulation study with cotton, potato and tomato," Agricultural Water Management, Elsevier, vol. 163(C), pages 236-243.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Li, Mo & Li, Haiyan & Fu, Qiang & Liu, Dong & Yu, Lei & Li, Tianxiao, 2021. "Approach for optimizing the water-land-food-energy nexus in agroforestry systems under climate change," Agricultural Systems, Elsevier, vol. 192(C).
    3. 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).
    4. Wang, Yongqiang & Huang, Donghua & Sun, Kexin & Shen, Hongzheng & Xing, Xuguang & Liu, Xiao & Ma, Xiaoyi, 2023. "Multiobjective optimization of regional irrigation and nitrogen schedules by using the CERES-Maize model with crop parameters determined from the remotely sensed leaf area index," Agricultural Water Management, Elsevier, vol. 286(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chongfeng Ren & Jiantao Yang & Hongbo Zhang, 2019. "An inexact fractional programming model for irrigation water resources optimal allocation under multiple uncertainties," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-17, June.
    2. Zhang, Chao & Xie, Ziang & Wang, Qiaojuan & Tang, Min & Feng, Shaoyuan & Cai, Huanjie, 2022. "AquaCrop modeling to explore optimal irrigation of winter wheat for improving grain yield and water productivity," Agricultural Water Management, Elsevier, vol. 266(C).
    3. Xike Guan & Zengchuan Dong & Yun Luo & Dunyu Zhong, 2021. "Multi-Objective Optimal Allocation of River Basin Water Resources under Full Probability Scenarios Considering Wet–Dry Encounters: A Case Study of Yellow River Basin," IJERPH, MDPI, vol. 18(21), pages 1-19, November.
    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).
    5. Wang, Youzhi & Guo, Shanshan & Yue, Qing & Mao, Xiaomin & Guo, Ping, 2021. "Distributed AquaCrop simulation-nonlinear multi-objective dependent-chance programming for irrigation water resources management under uncertainty," Agricultural Water Management, Elsevier, vol. 247(C).
    6. Zhang, Chenglong & Engel, Bernard A. & Guo, Ping, 2018. "An Interval-based Fuzzy Chance-constrained Irrigation Water Allocation model with double-sided fuzziness," Agricultural Water Management, Elsevier, vol. 210(C), pages 22-31.
    7. Knowling, Matthew J. & Walker, Rob R. & Pellegrino, Anne & Edwards, Everard J. & Westra, Seth & Collins, Cassandra & Ostendorf, Bertram & Bennett, Bree, 2023. "Generalized water production relations through process-based modeling: A viticulture example," Agricultural Water Management, Elsevier, vol. 280(C).
    8. Zhao, Jie & Han, Tong & Wang, Chong & Jia, Hao & Worqlul, Abeyou W. & Norelli, Nicole & Zeng, Zhaohai & Chu, Qingquan, 2020. "Optimizing irrigation strategies to synchronously improve the yield and water productivity of winter wheat under interannual precipitation variability in the North China Plain," Agricultural Water Management, Elsevier, vol. 240(C).
    9. Mandal, Uday & Dhar, Anirban & Panda, Sudhindra N., 2021. "Enhancement of sustainable agricultural production system by integrated natural resources management framework under climatic and operational uncertainty," Agricultural Water Management, Elsevier, vol. 252(C).
    10. Wenjie Geng & Xiaohui Jiang & Yuxin Lei & Jinyan Zhang & Huan Zhao, 2021. "The Allocation of Water Resources in the Midstream of Heihe River for the “97 Water Diversion Scheme” and the “Three Red Lines”," IJERPH, MDPI, vol. 18(4), pages 1-19, February.
    11. Gong, Xinghui & Zhang, Hongbo & Ren, Chongfeng & Sun, Dongyong & Yang, Jiantao, 2020. "Optimization allocation of irrigation water resources based on crop water requirement under considering effective precipitation and uncertainty," Agricultural Water Management, Elsevier, vol. 239(C).
    12. Li, Jiang & Shang, Songhao & Jiang, Hongzhe & Song, Jian & Rahman, Khalil Ur & Adeloye, Adebayo J., 2021. "Simulation-based optimization for spatiotemporal allocation of irrigation water in arid region," Agricultural Water Management, Elsevier, vol. 254(C).
    13. 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).
    14. Zhang, Chenglong & Li, Xuemin & Guo, Ping & Huo, Zailin, 2020. "An improved interval-based fuzzy credibility-constrained programming approach for supporting optimal irrigation water management under uncertainty," Agricultural Water Management, Elsevier, vol. 238(C).
    15. 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).
    16. Meena, Raj Pal & Karnam, Venkatesh & R, Sendhil & Rinki, & Sharma, R.K. & Tripathi, S.C. & Singh, Gyanendra Pratap, 2019. "Identification of water use efficient wheat genotypes with high yield for regions of depleting water resources in India," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    17. Wang, Haidong & Cheng, Minghui & Liao, Zhenqi & Guo, Jinjin & Zhang, Fucang & Fan, Junliang & Feng, Hao & Yang, Qiliang & Wu, Lifeng & Wang, Xiukang, 2023. "Performance evaluation of AquaCrop and DSSAT-SUBSTOR-Potato models in simulating potato growth, yield and water productivity under various drip fertigation regimes," Agricultural Water Management, Elsevier, vol. 276(C).
    18. Kelly, T.D. & Foster, T. & Schultz, David M., 2023. "Assessing the value of adapting irrigation strategies within the season," Agricultural Water Management, Elsevier, vol. 275(C).
    19. T. Fowe & I. Nouiri & B. Ibrahim & H. Karambiri & J. Paturel, 2015. "OPTIWAM: An Intelligent Tool for Optimizing Irrigation Water Management in Coupled Reservoir–Groundwater Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3841-3861, August.
    20. Zhang, Buchong & Li, Feng-Min & Huang, Gaobao & Cheng, Zi-Yong & Zhang, Yanhong, 2006. "Yield performance of spring wheat improved by regulated deficit irrigation in an arid area," Agricultural Water Management, Elsevier, vol. 79(1), pages 28-42, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:245:y:2021:i:c:s0378377420321223. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.