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ASEAN Journal on Science and Technology for Development

Abstract

The Water Quality Index (WQI) is an essential metric for evaluating the usability of surface water resources, particularly in ecologically sensitive and high-demand areas like the Panch Prayag belt of Uttarakhand, India. This region, comprising five major pilgrimage towns—Devaprayag, Nandprayag, Vishnuprayag, Karnaprayag, and Rudraprayag—faces seasonal fluctuations in water quality due to both natural and anthropogenic pressures. In this study, water samples were collected from 2021 to 2023 across pre-monsoon, monsoon, and post-monsoon seasons, and the WQI was computed using the Canadian Water Quality Index (CWQI 1.0). Results revealed that WQI values ranged from 36 to 45 across locations and seasons, with lower values during dry seasons due to increased contaminant concentrations. Regression analysis using ANOVA identified magnesium, chloride, nitrate, and fluoride as key pollutants significantly influencing WQI (F-values > 10 in some locations, with p-values < 0.05), with location-wise R² values ranging from 75.6% (Vishnuprayag) to 93.1% (Rudraprayag). Artificial Neural Network (ANN) models were employed for predictive analysis, achieving high accuracy with R² values exceeding 0.91 and Root Mean Square Error (RMSE) below 0.6. The ANN model demonstrated a strong ability to forecast WQI trends, reinforcing its potential for real-time water quality monitoring. The study provides critical insights into pollution sources and seasonal dynamics, supporting sustainable water resource management in this culturally and environmentally vital region.

Keywords

Water Quality Index, Canadian Water Quality Index, Regression Analysis, MINITAB Software, Artificial Neural Network

Publication Date

2025

Received Date

12/04/2025

Revised Date

11/09/2025

Accepted Date

13/09/2025

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