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<p>This study presents a new index, namely the hesitant fuzzy water quality index (Ή𝔉𝒲𝒬Ι), to assess water quality (𝒲𝒬A) in the Gomati River, Tripura (North East India), and its impacts on aquatic ecosystems. River water quality evaluation is considered in terms of diverse parameters and the inherent uncertainty introduced in the multi-criteria decision-making (ϺϹDϺ) process. A robust metric, the Ή𝔉𝒲𝒬Ι score, is proposed that may reliably rate pollution in the river. The Gomati River, the largest river in Tripura, which is used for drinking water, agriculture, and fisheries, is contaminated by a variety of sources, including household wastewater and agricultural runoff. Ten key water quality parameters (𝒲𝒬𝒫𝓈) such as pH, total dissolved solids, electrical conductivity, total hardness, chlorides, total alkalinity, total coliform, biochemical oxygen demand, dissolved oxygen, and total suspended solids were assessed across six strategically selected sites. River water samples were collected from March to December 2024 across multiple seasons. The Ή𝔉𝒲𝒬Ι-scores revealed consistently “poor” water quality (ranging from 0.734 to 0.866), degrading downstream due to untreated wastewater and agricultural runoff. To contextualize the scientific findings, traditional ecological knowledge (𝚃𝙴𝙺) was collected from four dependent tribal communities in 2025. The documentation covered local water sources, community perceptions of long-term water degradation, and their traditional conservation practices. Critically, community observations of contaminated water and health issues strongly aligned with the model’s identification of severe organic and bacterial pollution. Comparative analysis demonstrated that the Ή𝔉𝒲𝒬Ι outperformed conventional models in precision and reliability. This study demonstrates the severe impact of water pollution on both aquatic ecosystems and human health. This study bridges the gap between modern fuzzy tools and 𝚃𝙴𝙺. Its findings call for urgent action, improved sanitation, sustainable farming practices, and local conservation efforts informed by both science and culture.</p>

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An innovative hesitant fuzzy and traditional-ecological approach to water quality assessment and sustainable management of the Gomati River (the largest river in Tripura, India)

  • 期刊论文

  • 发表日期：

    2026年2月2日

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  • Nandini Gupta,
  • Ajoy Kanti Das,
  • Suman Patra,
  • Carlos Granados

摘要

This study presents a new index, namely the hesitant fuzzy water quality index (Ή𝔉𝒲𝒬Ι), to assess water quality (𝒲𝒬A) in the Gomati River, Tripura (North East India), and its impacts on aquatic ecosystems. River water quality evaluation is considered in terms of diverse parameters and the inherent uncertainty introduced in the multi-criteria decision-making (ϺϹDϺ) process. A robust metric, the Ή𝔉𝒲𝒬Ι score, is proposed that may reliably rate pollution in the river. The Gomati River, the largest river in Tripura, which is used for drinking water, agriculture, and fisheries, is contaminated by a variety of sources, including household wastewater and agricultural runoff. Ten key water quality parameters (𝒲𝒬𝒫𝓈) such as pH, total dissolved solids, electrical conductivity, total hardness, chlorides, total alkalinity, total coliform, biochemical oxygen demand, dissolved oxygen, and total suspended solids were assessed across six strategically selected sites. River water samples were collected from March to December 2024 across multiple seasons. The Ή𝔉𝒲𝒬Ι-scores revealed consistently “poor” water quality (ranging from 0.734 to 0.866), degrading downstream due to untreated wastewater and agricultural runoff. To contextualize the scientific findings, traditional ecological knowledge (𝚃𝙴𝙺) was collected from four dependent tribal communities in 2025. The documentation covered local water sources, community perceptions of long-term water degradation, and their traditional conservation practices. Critically, community observations of contaminated water and health issues strongly aligned with the model’s identification of severe organic and bacterial pollution. Comparative analysis demonstrated that the Ή𝔉𝒲𝒬Ι outperformed conventional models in precision and reliability. This study demonstrates the severe impact of water pollution on both aquatic ecosystems and human health. This study bridges the gap between modern fuzzy tools and 𝚃𝙴𝙺. Its findings call for urgent action, improved sanitation, sustainable farming practices, and local conservation efforts informed by both science and culture.