IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v246y2021ics0378377420322149.html
   My bibliography  Save this article

Optimal irrigation water allocation in Hetao Irrigation District considering decision makers’ preference under uncertainties

Author

Listed:
  • Zhang, Xiaoxing
  • Guo, Ping
  • Zhang, Fan
  • Liu, Xiao
  • Yue, Qiong
  • Wang, Youzhi

Abstract

In this study, a fuzzy multi-objective mλ-measure dependent-chance programming model was proposed to optimize limited irrigation water among three crops and five subareas in Hetao Irrigation District (HID) under uncertainties, with the objectives of ensuring food security and maximizing economic benefits. Three levels of droughts (100%, 85%, and 70% of annual average water diversion) that may happen in HID were set as future possible droughts scenarios. The optimization model considered the detailed physical process of soil water balance, which is necessary for irrigation districts where groundwater recharge plays a major role when available water limited. Moreover, sensitivities of crop yield to water deficit during crop growth periods were involved in model formulation to reflect the difference of crop water demand in different subareas. In optimization model, mλ-measure was introduced into the first objective to quantify optimistic and pessimistic decision attitudes of decision makers, and a series of alternatives were obtained. The obtained results indicate that: (1) the irrigation water of wheat, maize, and sunflower at rapid growth stage and middle growth stage should be preferentially guaranteed due to their high water-deficit sensitivities. The water demand at initial growth stage and late growth stage can be satisfied by soil water and groundwater recharge. (2) maize has the priority of irrigation in almost all subareas while sunflower has to face water deficit when drought occurs. (3) allocating more irrigation water to Yongji and Jiefangzha subareas can help increase food production. (4) the irrigation water allocated to grain crops increases along with the decrease of λ, representing decision makers’ more conservative preference. The optimization model and results in this study provide decision makers abundant water-allocation schemes under drought conditions.

Suggested Citation

  • Zhang, Xiaoxing & Guo, Ping & Zhang, Fan & Liu, Xiao & Yue, Qiong & Wang, Youzhi, 2021. "Optimal irrigation water allocation in Hetao Irrigation District considering decision makers’ preference under uncertainties," Agricultural Water Management, Elsevier, vol. 246(C).
    • Handle: RePEc:eee:agiwat:v:246:y:2021:i:c:s0378377420322149
    DOI: 10.1016/j.agwat.2020.106670
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377420322149
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2020.106670?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. Xu, Xu & Huang, Guanhua & Qu, Zhongyi & Pereira, Luis S., 2010. "Assessing the groundwater dynamics and impacts of water saving in the Hetao Irrigation District, Yellow River basin," Agricultural Water Management, Elsevier, vol. 98(2), pages 301-313, December.
    2. Igbadun, Henry E. & Tarimo, Andrew K.P.R. & Salim, Baanda A. & Mahoo, Henry F., 2007. "Evaluation of selected crop water production functions for an irrigated maize crop," Agricultural Water Management, Elsevier, vol. 94(1-3), pages 1-10, December.
    3. Saseendran, S.A. & Ahuja, Lajpat R. & Ma, Liwang & Trout, Thomas J. & McMaster, Gregory S. & Nielsen, David C. & Ham, Jay M. & Andales, Allan A. & Halvorson, Ardel D. & Chávez, José L. & Fang, Quanxia, 2015. "Developing and normalizing average corn crop water production functions across years and locations using a system model," Agricultural Water Management, Elsevier, vol. 157(C), pages 65-77.
    4. Comas, Louise H. & Trout, Thomas J. & DeJonge, Kendall C. & Zhang, Huihui & Gleason, Sean M., 2019. "Water productivity under strategic growth stage-based deficit irrigation in maize," Agricultural Water Management, Elsevier, vol. 212(C), pages 433-440.
    5. Zhang, Fan & Guo, Ping & Engel, Bernard A. & Guo, Shanshan & Zhang, Chenglong & Tang, Yikuan, 2019. "Planning seasonal irrigation water allocation based on an interval multiobjective multi-stage stochastic programming approach," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    6. Xue, Jingyuan & Guan, Huade & Huo, Zailin & Wang, Fengxin & Huang, Guanhua & Boll, Jan, 2017. "Water saving practices enhance regional efficiency of water consumption and water productivity in an arid agricultural area with shallow groundwater," Agricultural Water Management, Elsevier, vol. 194(C), pages 78-89.
    7. Dai, C. & Cai, Y.P. & Li, Y.P. & Sun, W. & Wang, X.W. & Guo, H.C., 2014. "Optimal strategies for carbon capture, utilization and storage based on an inexact mλ-measure fuzzy chance-constrained programming," Energy, Elsevier, vol. 78(C), pages 465-478.
    8. Kisekka, Isaya & Kandelous, Maziar M. & Sanden, Blake & Hopmans, Jan W., 2019. "Uncertainties in leaching assessment in micro-irrigated fields using water balance approach," Agricultural Water Management, Elsevier, vol. 213(C), pages 107-115.
    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. 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. Xu, Xianghui & Chen, Yingshan & Zhou, Yan & Liu, Wuyuan & Zhang, Xinrui & Li, Mo, 2023. "Sustainable management of agricultural water rights trading under uncertainty: An optimization-evaluation framework," Agricultural Water Management, Elsevier, vol. 280(C).
    3. Wu, Shiang-Jen & Yang, Han-Yuan & Chang, Che-Hao & Hsu, Chih-Tsung, 2023. "Modeling GA-derived optimization analysis for canal-based irrigation water allocation under variations in runoff-related and irrigation-related factors," Agricultural Water Management, Elsevier, vol. 290(C).
    4. Jiao, Fengli & Ding, Risheng & Du, Taisheng & Kang, Jian & Tong, Ling & Gao, Jia & Shao, Jie, 2024. "Multi-growth stage regulated deficit irrigation improves maize water productivity in an arid region of China," Agricultural Water Management, Elsevier, vol. 297(C).
    5. 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).
    6. Qiuli Zheng & Chunfang Yue & Shengjiang Zhang & Chengbao Yao & Qin Zhang, 2024. "Optimal Allocation of Water Resources in Canal Systems Based on the Improved Grey Wolf Algorithm," Sustainability, MDPI, vol. 16(9), pages 1-16, April.
    7. Liu, Xiuxia & Ma, Shimeng & Fang, Yu & Wang, Sufen & Guo, Ping, 2023. "A novel approach to identify crop irrigation priority," Agricultural Water Management, Elsevier, vol. 275(C).
    8. 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).
    9. Jing Tang & Xiaoyong Zhang & Zhengchao Chen & Yongqing Bai, 2022. "Crop Identification and Analysis in Typical Cultivated Areas of Inner Mongolia with Single-Phase Sentinel-2 Images," Sustainability, MDPI, vol. 14(19), pages 1-16, October.
    10. Yu Fan & Haorui Chen & Zhanyi Gao & Benyan Fang & Xiangkun Liu, 2023. "A Model Coupling Water Resource Allocation and Canal Optimization for Water Distribution," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1341-1365, February.

    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. Liu, Meihan & Paredes, Paula & Shi, Haibin & Ramos, Tiago B. & Dou, Xu & Dai, Liping & Pereira, Luis S., 2022. "Impacts of a shallow saline water table on maize evapotranspiration and groundwater contribution using static water table lysimeters and the dual Kc water balance model SIMDualKc," Agricultural Water Management, Elsevier, vol. 273(C).
    2. Wen, Yeqiang & Shang, Songhao & Rahman, Khalil Ur & Xia, Yuhong & Ren, Dongyang, 2020. "A semi-distributed drainage model for monthly drainage water and salinity simulation in a large irrigation district in arid region," Agricultural Water Management, Elsevier, vol. 230(C).
    3. Zhao, Tianxing & Zhu, Yan & Ye, Ming & Yang, Jinzhong & Jia, Biao & Mao, Wei & Wu, Jingwei, 2022. "A new approach for estimating spatial-temporal phreatic evapotranspiration at a regional scale using NDVI and water table depth measurements," Agricultural Water Management, Elsevier, vol. 264(C).
    4. Lina Mi & Juncang Tian & Jianning Si & Yuchun Chen & Yinghai Li & Xinhe Wang, 2020. "Evolution of Groundwater in Yinchuan Oasis at the Upper Reaches of the Yellow River after Water-Saving Transformation and Its Driving Factors," IJERPH, MDPI, vol. 17(4), pages 1-17, February.
    5. Liu, Xiuxia & Ma, Shimeng & Fang, Yu & Wang, Sufen & Guo, Ping, 2023. "A novel approach to identify crop irrigation priority," Agricultural Water Management, Elsevier, vol. 275(C).
    6. 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).
    7. 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.
    8. 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).
    9. Zhou, Qing & Zhang, Yali & Wu, Feng, 2021. "Evaluation of the most proper management scale on water use efficiency and water productivity: A case study of the Heihe River Basin, China," Agricultural Water Management, Elsevier, vol. 246(C).
    10. Sun, Guanfang & Zhu, Yan & Ye, Ming & Yang, Jinzhong & Qu, Zhongyi & Mao, Wei & Wu, Jingwei, 2019. "Development and application of long-term root zone salt balance model for predicting soil salinity in arid shallow water table area," Agricultural Water Management, Elsevier, vol. 213(C), pages 486-498.
    11. Zhang, Bangbang & Feng, Gary & Ahuja, Lajpat R. & Kong, Xiangbin & Ouyang, Ying & Adeli, Ardeshir & Jenkins, Johnie N., 2018. "Soybean crop-water production functions in a humid region across years and soils determined with APEX model," Agricultural Water Management, Elsevier, vol. 204(C), pages 180-191.
    12. 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).
    13. Wu, Zhangsheng & Li, Yue & Wang, Rong & Xu, Xu & Ren, Dongyang & Huang, Quanzhong & Xiong, Yunwu & Huang, Guanhua, 2023. "Evaluation of irrigation water saving and salinity control practices of maize and sunflower in the upper Yellow River basin with an agro-hydrological model based method," Agricultural Water Management, Elsevier, vol. 278(C).
    14. Sun, J. & Li, Y.P. & Suo, C. & Liu, Y.R., 2019. "Impacts of irrigation efficiency on agricultural water-land nexus system management under multiple uncertainties—A case study in Amu Darya River basin, Central Asia," Agricultural Water Management, Elsevier, vol. 216(C), pages 76-88.
    15. Motazedian, Azam & Kazemeini, Seyed Abdolreza & Bahrani, Mohammad Jafar, 2019. "Sweet corn growth and GrainYield as influenced by irrigation and wheat residue management," Agricultural Water Management, Elsevier, vol. 224(C), pages 1-1.
    16. Miodrag Tolimir & Branka Kresović & Katarina Gajić & Violeta Anđelković & Milan Brankov & Marijana Dugalić & Boško Gajić, 2024. "Integrated effect of irrigation rate and plant density on yield, yield components and water use efficiency of maize," Plant, Soil and Environment, Czech Academy of Agricultural Sciences, vol. 70(8), pages 475-482.
    17. Cao, Jingjing & Tan, Junwei & Cui, Yuanlai & Luo, Yufeng, 2019. "Irrigation scheduling of paddy rice using short-term weather forecast data," Agricultural Water Management, Elsevier, vol. 213(C), pages 714-723.
    18. Chen, Qi & Qu, Zhaoming & Ma, Guohua & Wang, Wenjing & Dai, Jiaying & Zhang, Min & Wei, Zhanbo & Liu, Zhiguang, 2022. "Humic acid modulates growth, photosynthesis, hormone and osmolytes system of maize under drought conditions," Agricultural Water Management, Elsevier, vol. 263(C).
    19. Ma, L. & Ahuja, L.R. & Islam, A. & Trout, T.J. & Saseendran, S.A. & Malone, R.W., 2017. "Modeling yield and biomass responses of maize cultivars to climate change under full and deficit irrigation," Agricultural Water Management, Elsevier, vol. 180(PA), pages 88-98.
    20. Tarkalson, David D. & King, Bradley A. & Bjorneberg, Dave L., 2022. "Maize grain yield and crop water productivity functions in the arid Northwest U.S," Agricultural Water Management, Elsevier, vol. 264(C).

    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:246:y:2021:i:c:s0378377420322149. 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.