Temporal Trend Analysis of Water Quality Index for Sustainable Water Resource Management

Abstract

This study aimed to explore the dynamics of water quality indices (WQIs) and their relationship with various physicochemical parameters, addressing a critical gap in understanding adaptive management's role in water quality enhancement. Utilizing a comprehensive dataset of 29,159 records and 24 variables, including key numeric parameters such as alkalinity, ammonia, BOD, chloride, and dissolved oxygen, we analyzed water quality trends over several years. The study employed robust statistical methods to assess seasonal and annual variations in WQI and its correlation with physicochemical factors.

Results showed a significant upward trend in WQI scores and dissolved oxygen levels, indicating an overall improvement in water quality. The implementation of adaptive management strategies, including pollution mitigation and regulatory measures, was linked to these positive trends. Seasonal fluctuations were observed, with peak WQI improvements during late spring and autumn, correlating with increased precipitation and runoff events. Specifically, dissolved oxygen concentrations exhibited a statistically significant increase (p < 0.05), reinforcing the effectiveness of adaptive interventions.

Our findings suggest that adaptive management strategies, which integrate real-time data and account for climatic variability, are effective in enhancing water quality. These results indicate that targeted adaptive interventions can significantly improve aquatic health and resource resilience. Policymakers and water managers are encouraged to adopt these strategies, emphasizing continuous monitoring and adaptive responses to environmental challenges. Despite limitations such as reliance on historical data, the study provides a strong foundation for future research to build upon. The insights offered here contribute valuable guidance for the development of sustainable, adaptive water quality management practices.