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Updated: Sep 21, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

A Copula-based interval linear programming model for water resources allocation under uncertainty.

Wencong Yue¹, Shujie Yu², Meng Xu³

¹Research Center for Eco-Environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China; Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, 510006, Guangzhou, China.

Journal of Environmental Management

|May 27, 2022

Summary

This study introduces a Copula-based interval linear programming model to address water scarcity by analyzing non-stationary water demand influenced by socio-economic factors. The model optimizes water resources allocation (WRA) under varying risk tolerances.

Keywords:

Copula functions Dalian city Interval linear programming Water resources allocation Water shortage risk

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Area of Science:

Environmental Science
Water Resource Management
Operations Research

Background:

Increasing water demand due to socio-economic development exacerbates water scarcity.
Non-stationary characteristics of water demand require advanced methods for effective water resources allocation (WRA).
Existing WRA models may not adequately capture the complex interactions between socio-economic factors and water demand variability.

Purpose of the Study:

To develop and validate a novel Copula-based interval linear programming model for regional water resources allocation.
To identify and quantify the interactions between water demand and socio-economic development indicators.
To explore water shortage variations under different decision-maker risk tolerance levels and optimize WRA strategies.

Main Methods:

Correlation analysis combined with Copula functions (Clayton and Gaussian) to model interdependencies.
Copula sampling to simulate water demand variations and explore risk tolerance scenarios (S1-S3: 20%, 40%, 60%).
Interval linear programming to derive optimal water resources allocation strategies for diverse water users.

Main Results:

Established correlations between water demand and socio-economic indicators using specified Copula functions.
Projected a 2.06%-2.65% increase in Dalian's total water supply by 2030 compared to 2025.
Demonstrated that water allocation is influenced by demand, energy consumption, and risk tolerance, with transferred water contributions varying significantly across scenarios.

Conclusions:

The Copula-based interval linear programming model effectively addresses non-stationary water demand in WRA.
Decision-maker risk tolerance significantly impacts water supply strategies, with higher tolerance leading to decreased supply.
The model provides a robust framework for optimizing water resources allocation in regions facing water scarcity and socio-economic development pressures.