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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

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Adapted optimization model for planning regional wastewater systems: case study.

J A Zeferino¹, M C Cunha¹, A P Antunes²

¹MARE, Department of Civil Engineering, University of Coimbra, Polo II, Coimbra 3030-788, Portugal

Water Science and Technology : a Journal of the International Association on Water Pollution Research

|September 7, 2017

Summary

Integrated regional wastewater system planning minimizes costs and maximizes benefits. This approach optimizes infrastructure like sewers and treatment plants for better environmental performance and water quality.

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Area of Science:

Environmental Engineering
Operations Research
Sustainable Development

Background:

Wastewater systems are vital for sustainable development.
Regional planning offers economies of scale and improved environmental outcomes.
Effective planning is needed to balance costs and benefits.

Purpose of the Study:

To present a decision support approach for regional wastewater system planning.
To optimize the configuration of wastewater infrastructure.
To evaluate solutions based on economic and environmental factors.

Main Methods:

Utilized optimization models to determine infrastructure location, type, and size.
Assessed solutions by cost (installation, operation, maintenance) and river water quality.
Employed a simulated annealing algorithm with local improvement for model solving.

Main Results:

Identified optimal configurations for sewers, pump stations, and wastewater treatment plants.
Demonstrated trade-offs between infrastructure costs and river water quality.
Case study application in the Una river basin, Brazil, provided practical insights.

Conclusions:

Integrated regional planning effectively supports sustainable wastewater management.
The decision support approach provides a framework for cost-effective and environmentally sound infrastructure development.
Optimization models are valuable tools for complex environmental system planning.