What question did this study set out to answer?

Multi-criteria decision analysis and linear programming for optimal resource allocation in water quality monitoring networks: a case study of California’s EPA monitoring stations

View Full Paper

Ask AI

Bookmark

Authors

Randomized trial analyzes resource allocation in monitoring networks, suggesting an integrated planning framework.

This research aims to optimize resource allocation in water quality monitoring networks using multiple analytical frameworks.
Developed an integrated multi-criteria decision analysis framework with CRITIC, TOPSIS, and VIKOR.
Utilized linear programming for efficient allocation of resources based on data from 347 monitoring stations.
Applied statistical filters to ensure data integrity, using Spearman’s rank correlation for parameter analysis.
Achieved a 36.9% improvement in resource allocation efficiency over uniform distribution (Z* = 0.9749 vs. C̄i = 0.712).
Identified top-performing monitoring stations with closeness coefficients ranging 0.9813 to 0.3799, mean 0.712.
Confirmed consistent rankings between TOPSIS and VIKOR with a Spearman correlation of 0.912 (p < 0.001).

Tavares et al. (2026) studied this question.

View Full Paper

Ask AI

Bookmark