Evaluating water quality investments using cost utility analysis

Area of Science:

• Environmental Economics
• Water Resource Management
• Decision Science

Background:

• Water quality enhancement projects require careful investment selection.
• Traditional methods struggle to quantify intangible benefits of environmental projects.
• Optimizing resource allocation under budget constraints is crucial for effective water management.

Purpose of the Study:

• To develop and apply a novel methodology for selecting an optimal portfolio of water quality enhancement projects.
• To integrate cost utility analysis (CUA) with optimization algorithms for robust decision-making.
• To maximize the aggregate utility score of water quality projects within a defined budget.

Main Methods:

• Cost utility analysis (CUA) was employed, incorporating discounted cash flow for costs.
• A binary combinatorial optimization solver (knapsack algorithm) was utilized to identify the optimal project mix.
• Compromise programming (CP) was applied within CUA to measure multi-attribute utility scores.

Main Results:

• The study demonstrates a method to select water quality projects that maximize aggregate utility.
• The approach effectively manages intangible benefits by assigning utility scores.
• The knapsack algorithm efficiently identified optimal project portfolios under budget constraints.

Conclusions:

• Cost utility analysis provides a transparent and analytically robust framework for water quality investment decisions.
• The combined CUA and knapsack algorithm approach offers an effective strategy for maximizing benefits from water remediation investments.
• This methodology supports informed decision-making for water resource management under financial limitations.