A multi-stage fuzzy stochastic programming method for water resources management with the consideration of ecological water demand

被引:42
作者
Li, Congcong [1 ,3 ]
Cai, Yanpeng [1 ,2 ,3 ]
Qian, Jinping [4 ]
机构
[1] Beijing Normal Univ, State Key Lab Water Environm Simulat, Sch Environm, Beijing 100875, Peoples R China
[2] Univ Regina, Inst Energy Environm & Sustainable Communities, 120,2 Res Dr, Regina, SK S4S 7H9, Canada
[3] Beijing Normal Univ, Sch Environm, Beijing Engn Res Ctr Watershed Environm Restorat, Beijing 100875, Peoples R China
[4] Hebei Normal Univ, Coll Resource & Environm Sci, Hebei Key Lab Environm Change & Ecol Construct, Shyiazhuang 050016, Hebei, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-stage; Stochastic programming; Fuzzy sets; Uncertainty; Ecological water demand; Water resources; MODEL; RIVER; OPTIMIZATION; FRAMEWORK;
D O I
10.1016/j.ecolind.2018.07.029
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
In this paper, a multi-stage fuzzy stochastic programming (MFSP) method is introduced to deal with uncertainties presented as fuzzy sets and probability distributions. Moreover, it is able to reflect dynamics of uncertainties and the related decision processes through constructing a series of representative scenarios within a multi-stage context under a set of fuzzy a-cut levels. A management problem about long-term planning of water resources system has been studied to illustrate applicability of the proposed approach. With ecological water demand being considered, the framework solves the complex problems that can hardly be solved in previous individual model research and promotes sustainable development. The results indicate that the dynamic and complexity of water resources allocation can be reflected through the multilayer discrete context tree. Moreover, real-time correction for reducing the risk of water shortage and low economic penalty can be presented. They can also help identify satisfaction degree of the goal and feasibility degree of constraints in an interactive way, enabling decision makers to generate a series of alternatives under various system conditions. Overall, it can not only contribute to decision makers for in-depth analysis, but also for sustainable development of ecosystem.
引用
收藏
页码:930 / 938
页数:9
相关论文
共 42 条
  • [1] Sustainable water demand management in the face of rapid urbanization and ground water depletion for social-ecological resilience building
    Arfanuzzaman, Md.
    Rahman, A. Atiq
    [J]. GLOBAL ECOLOGY AND CONSERVATION, 2017, 10 : 9 - 22
  • [2] Benthic foraminifera to assess Ecological Quality Statuses in Italian transitional waters
    Bouchet, Vincent M. P.
    Goberville, Eric
    Frontalini, Fabrizio
    [J]. ECOLOGICAL INDICATORS, 2018, 84 : 130 - 139
  • [3] An inexact programming approach for supporting ecologically sustainable water supply with the consideration of uncertain water demand by ecosystems
    Cai, Y. P.
    Huang, G. H.
    Wang, X.
    Li, G. C.
    Tan, Q.
    [J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2011, 25 (05) : 721 - 735
  • [4] Sustainable water resources management under uncertainty
    Chang, NB
    [J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2005, 19 (02) : 97 - 98
  • [5] CHANCE-CONSTRAINED PROGRAMMING
    CHARNES, A
    COOPER, WW
    [J]. MANAGEMENT SCIENCE, 1959, 6 (01) : 73 - 79
  • [6] Chen L, 2014, B SOIL WATER CONSERV, V34, P327
  • [7] Contamination, ecological risk and source apportionment of heavy metals in sediments and water of a contaminated river in Taiwan
    Chi Thanh Vu
    Lin, Chitsan
    Shern, Chien-Chuan
    Yeh, Gavin
    Le, Van Giang
    Huu Tuan Tran
    [J]. ECOLOGICAL INDICATORS, 2017, 82 : 32 - 42
  • [8] Multi-scale assessment of forest cover in an agricultural landscape of Southeastern Brazil: Implications for management and conservation of stream habitat and water quality
    de Paula, Felipe Rossetti
    Gerhard, Pedro
    de Barros Ferraz, Silvio Frosini
    Wenger, Seth J.
    [J]. ECOLOGICAL INDICATORS, 2018, 85 : 1181 - 1191
  • [9] [董雯 DONG Wen], 2009, [新疆农业科学, Xinjiang Agricultural Sciences], V46, P306
  • [10] VERTEX METHOD FOR COMPUTING FUNCTIONS OF FUZZY VARIABLES
    DONG, WM
    SHAH, HC
    [J]. FUZZY SETS AND SYSTEMS, 1987, 24 (01) : 65 - 78