The interval copula-measure Me based multi-objective multi-stage stochastic chance-constrained programming for seasonal water resources allocation under uncertainty

A copula-measure Me based interval multi-objective multi-stage stochastic chance-constrained programming (CMIMOMSP) model is proposed for water consumption optimization. It can conduct water allocation amid multiple users and multiple stages, and deal with the uncertainties presented as interval num...

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Bibliographic Details
Published in:Stochastic environmental research and risk assessment Vol. 35; no. 7; pp. 1463 - 1480
Main Authors: Wang, Youzhi, Guo, Ping
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2021
Springer Nature B.V
Subjects:
Agriculture
Aquatic Pollution
Aridity
Attitudes
Chemistry and Earth Sciences
Computational Intelligence
Computer Science
Distribution functions
Earth and Environmental Science
Earth Sciences
Ecological effects
Economic impact
Economics
Environment
Environmental research
Math. Appl. in Environmental Science
Mathematical programming
Multiple objective analysis
Objective function
Optimization
Original Paper
Pessimism
Physics
Probability
Probability Theory and Stochastic Processes
Resource allocation
Risk assessment
River basins
Runoff
Statistics for Engineering
Uncertainty
Variables
Waste Water Technology
Water allocation
Water consumption
Water demand
Water Management
Water Pollution Control
Water resources
Water shortages
Multi-stage stochastic programming
Interval copula function
Uncertainty
Multi-objective programming
Measure Me
Interval conditional distribution
ISSN:1436-3240, 1436-3259
Online Access:Get full text
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Summary:A copula-measure Me based interval multi-objective multi-stage stochastic chance-constrained programming (CMIMOMSP) model is proposed for water consumption optimization. It can conduct water allocation amid multiple users and multiple stages, and deal with the uncertainties presented as interval numbers, random fuzzy interval numbers, and stochastic variables. It improves upon multi-stage stochastic chance-constrained programming by introducing the multi-objective programming, and it can tradeoff the relationships amid economic benefit, full usage of water resources, and economic loss. It enhances the accuracy of copula function and conditional distribution function through proposing the interval functions. Besides, it can deal with the impact of the decision attitudes of managers on water allocation by formulating the function equation between water demand and the optimistic-pessimistic factor. The CMIMOMSP model is applied to a case study of the Heihe River Basin to verify its application. The results indicate that: (1) the optimistic-pessimistic factors have different degrees of positive influences on water allocation for industrial, domestic and ecological sectors; (2) the joint violated probability and optimistic-pessimistic factor have various range of impacts on agricultural water allocation; (3) tthe objective function values have different variation tendencies with the rise of joint violated probabilities and optimistic-pessimistic factors. Its robustness is enhanced by comparing it with the three single-objective programming models. The CMIMOMSP model can provide various water allocation schemes for managers with different risk attitudes in semi-arid and arid districts.
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ISSN:1436-3240
1436-3259
DOI:10.1007/s00477-020-01913-x