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<p>Wetlands are dynamic and robust ecosystems that require comprehensive monitoring and assessment to safeguard water resources for irrigation and consumption. Recently, surface water has been severely degraded by several anthropogenic activities that persistently disrupt both public health as well as ecological integrity. This study employed multivariate statistical analysis (MSA) to examine spatial heterogeneity in hydro-chemical parameters and elucidate the dominant factors controlling water quality degradation. Water samples were strategically collected from peripheral and core areas o f the Rudrasagar wetland following standard protocol. An integrated framework was utilised incorporating geospatial techniques and water quality indices such as Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) and Weighted Arithmetic Water Quality Index (WAWQI) to provide a holistic snapshot of hydro-chemical properties. Spatial variation mapping effectively demonstrated dynamics of physico-chemical fingerprints and contamination risks of the wetland ecosystem. Multidimensional assessment revealed significant spatial heterogeneity in Rudrasagar wetland. CCME WQI classified 76% of the area as having excellent and 19% as good water quality while WAWQI indicated 66% as poor quality and 11% as unsuitable for domestic utilisation. Concurrently, Comprehensive Pollution Index (CPI) specified consistent pollution levels with nominal significant variation. This study exhibited pollution levels under three distinct categories; sub-clean water, slightly polluted water and moderately polluted water. CPI exposed that 68% of the samples were slightly polluted, while 14% were approaching heavily polluted water quality. The central to south-eastern zones exhibited substantial contamination by various pollutants. Pearson correlation matrix (r) demonstrated the significance interdependence among hydro-chemical parameters. Principal Component Analysis (PCA) identified five factors accounting for 65% of the extraction sums of squared loadings indicating that both anthropogenic activities and geogenic mechanism significantly accelerated water quality deterioration. Hierarchical cluster analysis (HCA) classified the sampling sites based upon similar hydro-chemical characteristic. These findings effectively emphasized the urgent need to develop sustainable management strategies and strict land-use regulations for protecting wetland ecosystems. Furthermore, establishing integrated GIS-based monitoring systems is essential for implementing effective conservation policies and ensures long-term ecosystem integrity.</p> Graphical Abstract <p></p>

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Novel integrated framework for hydro-chemical characterization, long-term assessment of wetland ecosystem service degradation and restoration prioritization

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月6日

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  • Pradip Debnath,
  • Arpita Biswas,
  • Punarbasu Chaudhuri,
  • Saptarshi Mitra

摘要

Wetlands are dynamic and robust ecosystems that require comprehensive monitoring and assessment to safeguard water resources for irrigation and consumption. Recently, surface water has been severely degraded by several anthropogenic activities that persistently disrupt both public health as well as ecological integrity. This study employed multivariate statistical analysis (MSA) to examine spatial heterogeneity in hydro-chemical parameters and elucidate the dominant factors controlling water quality degradation. Water samples were strategically collected from peripheral and core areas o f the Rudrasagar wetland following standard protocol. An integrated framework was utilised incorporating geospatial techniques and water quality indices such as Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) and Weighted Arithmetic Water Quality Index (WAWQI) to provide a holistic snapshot of hydro-chemical properties. Spatial variation mapping effectively demonstrated dynamics of physico-chemical fingerprints and contamination risks of the wetland ecosystem. Multidimensional assessment revealed significant spatial heterogeneity in Rudrasagar wetland. CCME WQI classified 76% of the area as having excellent and 19% as good water quality while WAWQI indicated 66% as poor quality and 11% as unsuitable for domestic utilisation. Concurrently, Comprehensive Pollution Index (CPI) specified consistent pollution levels with nominal significant variation. This study exhibited pollution levels under three distinct categories; sub-clean water, slightly polluted water and moderately polluted water. CPI exposed that 68% of the samples were slightly polluted, while 14% were approaching heavily polluted water quality. The central to south-eastern zones exhibited substantial contamination by various pollutants. Pearson correlation matrix (r) demonstrated the significance interdependence among hydro-chemical parameters. Principal Component Analysis (PCA) identified five factors accounting for 65% of the extraction sums of squared loadings indicating that both anthropogenic activities and geogenic mechanism significantly accelerated water quality deterioration. Hierarchical cluster analysis (HCA) classified the sampling sites based upon similar hydro-chemical characteristic. These findings effectively emphasized the urgent need to develop sustainable management strategies and strict land-use regulations for protecting wetland ecosystems. Furthermore, establishing integrated GIS-based monitoring systems is essential for implementing effective conservation policies and ensures long-term ecosystem integrity.

Graphical Abstract