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Uncertainty analysis for effluent trading planning using a Bayesian estimation-based simulation-optimization modeling
J L Zhang1, Y P Li2, G H Huang2
1MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, North China Electric Power University, Beijing 102206, China.
Water Research
|March 25, 2017
Summary
This study introduces a Bayesian estimation-based simulation-optimization modeling approach (BESMA) for effluent trading. BESMA effectively handles multiple uncertainties in water quality, aiding in optimal trading strategy identification.
Keywords:
Bayesian estimationEffluent tradingMCMCNutrient transportProbabilistic–possibilistic optimizationWater qualityMore Related Videos
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Area of Science:
- Environmental Engineering
- Water Resource Management
- Computational Modeling
Background:
- Effluent trading is crucial for managing water quality and nutrient pollution.
- Existing models often struggle to address the complex uncertainties inherent in water quality systems.
- Developing robust decision-making tools is essential for effective watershed management.
Purpose of the Study:
- To develop and apply a novel Bayesian estimation-based simulation-optimization modeling approach (BESMA) for identifying optimal effluent trading strategies.
- To integrate nutrient fate modeling (SWAT), Bayesian estimation, and fuzzy-random interval programming (PPI-FRC) to handle multiple uncertainties.
- To provide a framework for decision-making that accounts for both optimistic and pessimistic scenarios in effluent trading.
Main Methods:
- Developed the Bayesian estimation-based simulation-optimization modeling approach (BESMA).
- Integrated Soil and Water Assessment Tool (SWAT) for nutrient fate modeling and Bayesian estimation for parameter analysis.
- Employed probabilistic-possibilistic interval programming with fuzzy random coefficients (PPI-FRC) to manage interval uncertainties with fuzzy random boundaries.
- Applied the framework to a case study in the Xiangxihe watershed, China.
Main Results:
- BESMA successfully identified multiple decision alternatives for effluent trading under varying trading ratios and treatment rates.
- The approach demonstrated superior ability in handling multiple uncertainties (randomness and fuzziness) compared to conventional methods.
- Results showed that decision-maker risk preference significantly influences trading scheme selection and system benefits.
- Improved accuracy in water quality prediction by reflecting uncertainties in nutrient transport behaviors.
Conclusions:
- BESMA offers a robust and versatile framework for effluent trading planning, adept at managing complex environmental uncertainties.
- The model supports diverse decision-making preferences, from optimistic to pessimistic, enhancing the selection of effective trading schemes.
- This approach provides valuable insights into the interplay between trading parameters, risk attitudes, and overall system performance in water quality management.