Monitoring and assessment of water health quality in the Tajan River, Iran using physicochemical, fish and macroinvertebrates indices.

Jaber Aazami, Abbas Esmaili-Sari, Asghar Abdoli, Hormoz Sohrabi, Paul J Van den Brink
Author Information
  1. Jaber Aazami: Department of Environment, Faculty of Natural Resources, Tarbiat Modares University, Tehran, Iran.
  2. Abbas Esmaili-Sari: Department of Environment, Faculty of Natural Resources, Tarbiat Modares University, Tehran, Iran.
  3. Asghar Abdoli: Department of Biodiversity and Ecosystem Management, Environmental Research Institute, Shahid Beheshti University, Tehran, Iran.
  4. Hormoz Sohrabi: Department of Forestry, Faculty of Natural Resources, Tarbiat Modares University, Tehran, Iran.
  5. Paul J Van den Brink: Department of Aquatic Ecology and Water Quality Management, Wageningen University, Wageningen University and Research Centre, Wageningen, The Netherlands ; Alterra, Wageningen University and Research Centre, Wageningen, The Netherlands.

Abstract

BACKGROUND: Nowadays, aquatic organisms are used as bio-indicators to assess ecological water quality in western regions, but have hardly been used in an Iranian context. We, therefore, evaluated the suitability of several indices to assess the water quality for an Iranian case study.
METHODS: Measured data on biotic (fish and macroinvertebrates) and abiotic elements (28 physicochemical and habitat parameters), were used to calculate six indices for assessment of water quality and the impact of human activities in the Tajan river, Iran. GIS, uni- and multivariate statistics were used to assess the correlations between biological and environmental endpoints.
RESULTS: The results showed that ecological condition and water quality were reduced from up- to downstream. The reduced water quality was revealed by the biotic indices better than the abiotic ones which were linked to a variety of ecological water quality scales.
CONCLUSION: The fish index showed a strong relationship with long-term database of physicochemical parameters (12 years (94%)), whereas macroinvertebrates index is more correlated with short-term data (76%). Meanwhile, the biotic and abiotic elements in this study were also classified well by PCA. Pulp and wood plants and sand mining are indicated to have the most negative effects on the river ecosystem.

Keywords

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Word Cloud

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