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<p>This study assessed water quality variations in the Hulan River Estuary Wetland Nature Reserve, using physicochemical properties and pollution indices. Twelve water samples showed spatial variations in temperature, pH, dissolved oxygen (DO), electrical conductivity (EC), turbidity, inorganic salts and organic matter. Results indicated excellent: heavy metal pollution index (<i>HPI</i>, 2.83 to 14.2), heavy metal evaluation index (<i>HEI</i>, 0.5 to 2.1), pollution index (<i>PI</i>, 2.38 to 6.0), contamination degree (<i>C</i><sub><i>d</i></sub>, − 8.5 to − 5.90), and water quality index (<i>WQI</i>, 26.12 to 44.02). Heavy metal analysis showed elevated iron (Fe) and sodium (Na) concentrations at certain sites suggested localized agricultural influence, though overall contamination was minimal. Spatial patterns of pollution indices aligned with land use changes, suggesting that agricultural expansion and urbanization may contribute to future risks. A VMD-CNN-LSTM model yielded high prediction accuracy (R<sup>2</sup>: 0.9788, 0.9452, 0.9171; MSE: 0.0561, 0.1298, 0.2136 for training, validation and test sets), and long-term forecasting indicated potential water quality decline, underscoring the need for ongoing monitoring. These findings provide essential insights for sustainable water management and conservation strategies in the region, emphasizing the importance of mitigating potential pollution risks associated with anthropogenic activities.</p>

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A holistic assessment and prediction of water quality in Hulan River Estuary Wetland Nature Reserve: parameters, pollution indices and modeling

  • 期刊论文

  • 发表日期：

    2025年7月12日

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  • Jia Liu,
  • Pengyu Wu,
  • Mengping Qin,
  • Nan Xu,
  • Chuanqi Shi,
  • Cong Du

摘要

This study assessed water quality variations in the Hulan River Estuary Wetland Nature Reserve, using physicochemical properties and pollution indices. Twelve water samples showed spatial variations in temperature, pH, dissolved oxygen (DO), electrical conductivity (EC), turbidity, inorganic salts and organic matter. Results indicated excellent: heavy metal pollution index (HPI, 2.83 to 14.2), heavy metal evaluation index (HEI, 0.5 to 2.1), pollution index (PI, 2.38 to 6.0), contamination degree (Cd, − 8.5 to − 5.90), and water quality index (WQI, 26.12 to 44.02). Heavy metal analysis showed elevated iron (Fe) and sodium (Na) concentrations at certain sites suggested localized agricultural influence, though overall contamination was minimal. Spatial patterns of pollution indices aligned with land use changes, suggesting that agricultural expansion and urbanization may contribute to future risks. A VMD-CNN-LSTM model yielded high prediction accuracy (R2: 0.9788, 0.9452, 0.9171; MSE: 0.0561, 0.1298, 0.2136 for training, validation and test sets), and long-term forecasting indicated potential water quality decline, underscoring the need for ongoing monitoring. These findings provide essential insights for sustainable water management and conservation strategies in the region, emphasizing the importance of mitigating potential pollution risks associated with anthropogenic activities.