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February 12, 20260 citationsOpen Access

Comprehensive Water Quality Assessment using Ensemble Machine Learning in a Tropical Lake, Kerala, SW India

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SJSabu JosephSSS. SukanyaMVM.R. Vishnuprasad

Key Points

  • Evaluate and characterize the water quality of Vellayani Lake in Kerala using machine learning techniques.
  • Analyzed surface water samples at three different periods: post-monsoon, pre-monsoon, and monsoon.
  • Measured key physico-chemical parameters including temperature, pH, and dissolved oxygen.
  • Employed Water Quality Index (WQI) classification to assess quality.
  • Applied a Random Forest based ensemble machine learning model for validation.
  • WQI values ranged from 'Excellent' to 'Poor', indicating variable water quality.
  • General decline in water quality observed during the post-monsoon period.
  • Ensemble model achieved high accuracy (R2 = 0.96).
  • Key predictors identified include phosphate, dissolved oxygen, electrical conductivity, and total dissolved solids.

Abstract

ABSTRACT This study intends to evaluate and characterize the water quality of Vellayani Lake (VL), a tropical freshwater body in Kerala, Southwest India. Comprehensive analyses of physico-chemical parameters were conducted in surface water samples (n=13) during post-monsoon (January), pre-monsoon (May) and monsoon (July) periods. Key parameters viz., temperature, pH, Electrical Conductivity, Total Dissolved Solids, Dissolved Oxygen and nutrient concentrations were measured. The Water Quality Index (WQI) classification was employed to assess water quality. WQI values ranged from ‘Excellent’ to ‘Poor’, with a general decline of quality during post-monsoon. Additionally, a Random Forest based ensemble machine learning model was applied to validate the WQI results, achieving high accuracy (R2 = 0.96) and identified phosphate, Dissolved Oxygen, Electrical Conductivity and Total Dissolved Solids as key predictors. This integrative approach provides a comprehensive understanding of the lake’s water quality dynamics, emphasizing the need for spatially targeted interventions to reduce pollutant loads and stabilize the lake’s ecological function.

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Cite This Study

Joseph et al. (2025) studied this question.

synapsesocial.com/papers/698d6dd15be6419ac0d5313ehttps://doi.org/10.5281/zenodo.18587112
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