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A simulation-based bi-level multi-objective programming model for watershed water quality management under interval

Qiangqiang Rong1, Yanpeng Cai2, Meirong Su1

  • 1(a)Research Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China.

Journal of Environmental Management
|June 5, 2019
PubMed
Summary

This study introduces a novel simulation-based interval stochastic bi-level multi-objective programming (SISBLMOP) model for water quality management. The model effectively balances decision-maker objectives and uncertainties to find acceptable best management practices (BMPs).

Keywords:
Bi-level multi-objective programmingChance-constrained programmingInterval parameter programmingNutrient export from watershedsWater quality management

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Area of Science:

  • Environmental Science
  • Water Resource Management
  • Operations Research

Background:

  • Water quality management faces challenges from multiple uncertainties and complex decision-making hierarchies.
  • Existing models often struggle to integrate simulation, interval parameters, and stochastic elements within bi-level programming.
  • Effective identification of best management practices (BMPs) requires considering both upper- and lower-level decision-maker objectives.

Purpose of the Study:

  • To develop a simulation-based interval stochastic bi-level multi-objective programming (SISBLMOP) model.
  • To address uncertainties in discrete intervals and probability density functions within simulation and optimization.
  • To identify satisfactory BMP implementation levels for water quality management in a watershed.

Main Methods:

  • Integration of a global nutrient export from watersheds model with interval parameter programming and stochastic chance-constrained programming.
  • Application of a general bi-level multi-objective programming framework to handle hierarchical decision-making.
  • Utilizing simulation and optimization processes to manage multiple uncertainties.

Main Results:

  • The SISBLMOP model successfully generated multiple BMP schemes under various decision-making and risk scenarios.
  • Model outcomes reflect the cooperative and gaming dynamics between upper- and lower-level decision makers.
  • Identified BMP implementation costs were acceptable to both decision-making levels.

Conclusions:

  • The proposed SISBLMOP model is effective for water quality management under multiple uncertainties and system complexities.
  • The model provides a robust framework for balancing competing objectives and risk preferences in watershed management.
  • The approach offers a widely applicable tool for identifying cost-effective BMPs in real-world scenarios.