Vine copula and cloud model-based programming approach for agricultural water allocation under uncertainty

被引:0
|
作者
Baoying Shan
Shanshan Guo
Youzhi Wang
Hao Li
Ping Guo
机构
[1] China Agricultural University,Centre for Agricultural Water Research in China
[2] Ministry of Agriculture and Rural Affairs,Wuwei Experimental Station for Efficient Water Use in Agriculture
关键词
C-vine copula; Cloud model; Dependence structure; Self-correlation; Agricultural water optimization;
D O I
暂无
中图分类号
学科分类号
摘要
In the existing agricultural water management models under uncertainty, the mutual-correlation and their self-correlation of random variables (like precipitation (P), runoff (R), reference evapotranspiration (ET0), etc.) are often ignored. When expressing the fuzziness of socio-economic factors, fuzzy membership function is usually determined by the experience of decision-makers, which often brings some confusions. To solve the above questions, first, C-vine copula is introduced in this study to depict the multiple interdependence structures. Two kinds of three-dimensional copulas is constructed: CV1(Rt,Pt,Rt-1)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${CV}_{1}({R}_{t}, {P}_{t}, {R}_{t-1})$$\end{document} and CV2(ET0t,Pt,ET0(t-1))\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${CV}_{2}({ET}_{0t}, {P}_{t}, {ET}_{0(t-1)})$$\end{document}, where t is at t-th month. Second, the cloud model, as a novel qualitative and quantitative transformation model, is chosen to describe the uncertainty of crop prices. Combining these two uncertainty-expressing methods, an agricultural water resources optimization model is built to gain maximum net benefit by allocating limited surface water and groundwater. Then this model was applied to a case study in northwestern China. Results show that the developed model could provide the decision-makers with not only the best or the optimum range of system net benefits but also the probability of obtaining a given benefit under complex uncertainties. For comparison, the ordinary models without consideration of dependence of variables as an independent were also built. When overlooking the mutual-correlation and self-correlation, the optimal water allocation and system net benefits would be higher in dry years with total water allocation higher by 4.5%. This unreasonable allocation results may cause excessive agricultural irrigation to squeeze water for other industries in dry years, which would exacerbate water shortages. The discussion and comparison results prove the necessity and effectiveness of this research.
引用
收藏
页码:1895 / 1915
页数:20
相关论文
共 50 条
  • [1] Vine copula and cloud model-based programming approach for agricultural water allocation under uncertainty
    Shan, Baoying
    Guo, Shanshan
    Wang, Youzhi
    Li, Hao
    Guo, Ping
    [J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2021, 35 (09) : 1895 - 1915
  • [2] A Copula-based interval linear programming model for water resources allocation under uncertainty
    Yue, Wencong
    Yu, Shujie
    Xu, Meng
    Rong, Qiangqiang
    Xu, Chao
    Su, Meirong
    [J]. JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2022, 317
  • [3] A copula-based interval-bistochastic programming method for regional water allocation under uncertainty
    Chen, Shu
    Xu, Jijun
    Li, Qingqing
    Tan, Xuezhi
    Nong, Xizhi
    [J]. AGRICULTURAL WATER MANAGEMENT, 2019, 217 : 154 - 164
  • [4] Risk aversion based interval stochastic programming approach for agricultural water management under uncertainty
    Li, Q. Q.
    Li, Y. P.
    Huang, G. H.
    Wang, C. X.
    [J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2018, 32 (03) : 715 - 732
  • [5] Risk aversion based interval stochastic programming approach for agricultural water management under uncertainty
    Q. Q. Li
    Y. P. Li
    G. H. Huang
    C. X. Wang
    [J]. Stochastic Environmental Research and Risk Assessment, 2018, 32 : 715 - 732
  • [6] Agricultural Multi-Water Source Allocation Model Based on Interval Two-Stage Stochastic Robust Programming under Uncertainty
    Fu, Qiang
    Li, Tianxiao
    Cui, Song
    Liu, Dong
    Lu, Xueping
    [J]. WATER RESOURCES MANAGEMENT, 2018, 32 (04) : 1261 - 1274
  • [7] Agricultural Multi-Water Source Allocation Model Based on Interval Two-Stage Stochastic Robust Programming under Uncertainty
    Qiang Fu
    Tianxiao Li
    Song Cui
    Dong Liu
    Xueping Lu
    [J]. Water Resources Management, 2018, 32 : 1261 - 1274
  • [8] A cloud model-based approach for water quality assessment
    Wang, Dong
    Liu, Dengfeng
    Ding, Hao
    Singh, Vijay P.
    Wang, Yuankun
    Zeng, Xiankui
    Wu, Jichun
    Wang, Lachun
    [J]. ENVIRONMENTAL RESEARCH, 2016, 148 : 24 - 35
  • [9] NEW APPROACH TO WATER ALLOCATION UNDER UNCERTAINTY
    THOMAS, G
    WRIGHT, G
    WHINSTON, A
    [J]. WATER RESOURCES RESEARCH, 1972, 8 (05) : 1151 - &
  • [10] A multidimension cloud model-based approach for water quality assessment
    Wang, Dong
    Zeng, Debiao
    Singh, Vijay P.
    Xu, Pengcheng
    Liu, Dengfeng
    Wang, Yuankun
    Zeng, Xiankui
    Wu, Jichun
    Wang, Lachun
    [J]. ENVIRONMENTAL RESEARCH, 2016, 149 : 113 - 121