Development of a fuzzy-stochastic programming with Green Z-score criterion method for planning water resources systems with a trading mechanism.
This study developed a fuzzy-stochastic programming with Green Z-score criterion (FSGZ) method for water resources allocation and water quality management with a trading-mechanism (WAQT) under uncertainties. FSGZ can handle uncertainties expressed as probability distributions, and it can also quantify objective/subjective fuzziness in the decision-making process. Risk-averse attitudes and robustness coefficient are joined to express the relationship between the expected target and outcome under various risk preferences of decision makers and systemic robustness. The developed method is applied to a real-world case of WAQT in the Kaidu-Kongque River Basin in northwest China, where an effective mechanism (e.g., market trading) to simultaneously confront severely diminished water availability and degraded water quality is required. Results of water transaction amounts, water allocation patterns, pollution mitigation schemes, and system benefits under various scenarios are analyzed, which indicate that a trading-mechanism is a more sustainable method to manage water-environment crisis in the study region. Additionally, consideration of anthropogenic (e.g., a risk-averse attitude) and systemic factors (e.g., the robustness coefficient) can support the generation of a robust plan associated with risk control for WAQT when uncertainty is present. These findings assist local policy and decision makers to gain insights into water-environment capacity planning to balance the basin's social and economic growth with protecting the region's ecosystems.
Capital University of Economics and Business, Beijing, 10070, China.|Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, SK, S4S 0A2, Canada.
X T
XT
Zeng
Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, SK, S4S 0A2, Canada. Huang@iseis.org.|College of Environment, Beijing Normal University, Beijing, 100875, China. Huang@iseis.org.
G H
GH
Huang
Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, SK, S4S 0A2, Canada. yongping.li33@gmail.com.|College of Environment, Beijing Normal University, Beijing, 100875, China. yongping.li33@gmail.com.
Y P
YP
Li
MOE Key Laboratory of Regional Energy Systems Optimization, North China Electric Power University, Beijing, 102206, China.
J L
JL
Zhang
College of Environment, Beijing Normal University, Beijing, 100875, China.
Y P
YP
Cai
MOE Key Laboratory of Regional Energy Systems Optimization, North China Electric Power University, Beijing, 102206, China.
Z P
ZP
Liu
Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, SK, S4S 0A2, Canada.
L R
LR
Liu
D002681:China; D003657:Decision Making; D017143:Fuzzy Logic; D008962:Models, Theoretical; D011336:Probability; D012306:Risk; D035501:Uncertainty; D014876:Water Pollution; D060753:Water Quality; D062066:Water Resources; D014881:Water Supply
Arid basin; Fuzzy programming; Green Z-score criterion; Strategic analysis; Trading-mechanism; Two-stage stochastic programming
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