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June 6, 2026Discover EnvironmentOpen Access

A multidimensional approach to pollution risk assessment in surface water using statistical and regression techniques

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Authors

ADAbhijeet DasKBKrishna Pada BauriBTBhagirathi Tripathy

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Overview

Randomized trial assesses water quality variations in surface water, indicating urgent need for corrective actions.

Key Points

  • The aim is to evaluate seasonal variations in water quality and pollution risks using statistical and regression techniques.
  • Systematic field investigations at 20 sampling sites over a 5-year period (2020–2025)
  • Analysis of nine key water quality parameters using the Water Quality Index (WQI) and machine learning approaches
  • Utilization of principal component analysis and cluster analysis for data interpretation.
  • Approximately 45% of sampled locations showed poor to unsuitable water quality, with WQI values ranging from 35 to 355
  • Five sites (25%) met water quality standards for drinking and irrigation use, while ten sites (50%) were categorized as very poor to extremely poor
  • The proposed EWQI-driven regression model achieved an adjusted R2 value of 0.994, indicating high predictive accuracy.

Cite This Study

Das et al. (2026) studied this question.

synapsesocial.com/papers/6a23bc2a71a5da9775e779b6https://doi.org/10.1007/s44274-026-00774-5
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