New Fish-Based Multimetric Index for Appraising Shatt Al-Arab Ecological Quality

In recent years, there has been a growing need to develop biometric indicators that accurately reflect an area’s environmental quality and biological integrity. Various indicators have been developed and analyzed, focusing on functional, ecological, and organism-based indicators, particularly fish-related ones. The purpose of the current paper is to create the first fish-based multimetric index designed to evaluate the quality of water in the Shatt Al-Arab River (SAAR), known as Shatt Al-Arab Fish Index (SFI), which can also be applied to the Qarmat Ali River and other water bodies similar to the SAAR ecology. Data was collected from three stations along the river from March 2019 to February 2023 to construct and calibrate the index. Twenty-nine metrics were considered as possible parameters for the SFI, including factors such as fish composition, and food habits. Ultimately, nine metrics were included in the SFI. The SFI demonstrated high assessment efficiency because it relied on measures sensitive to temporal and spatial changes that are affected by human activities. The SFI was used to validate additional data collected during sampling conducted in 2023. As a result of these applications, the three stations in the SAAR were classified as “moderate” and “poor” status. In contrast, the Qarmat Ali River was classified as “poor” status. Therefore, the study concludes that fish are essential in biological assessment tools, which are used as a basis for monitoring and managing multiple water bodies. Thus, the health of the SAAR ecosystem can be improved in the long term.

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Publication Details

Journal
Journal of King Abdulaziz University-Marine Sciences
Published
2025-12-31
DOI
https://doi.org/10.64064/1658-4325.1020
Primary Topic
Water Quality and Pollution Assessment
Type
article
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article

New Fish-Based Multimetric Index for Appraising Shatt Al-Arab Ecological Quality

Laith Faisal Lazem
Journal of King Abdulaziz University-Marine Sciences
Water Quality and Pollution Assessment
article

New Fish-Based Multimetric Index for Appraising Shatt Al-Arab Ecological Quality

Laith Faisal Lazem
article en

Abstract

In recent years, there has been a growing need to develop biometric indicators that accurately reflect an area’s environmental quality and biological integrity. Various indicators have been developed and analyzed, focusing on functional, ecological, and organism-based indicators, particularly fish-related ones. The purpose of the current paper is to create the first fish-based multimetric index designed to evaluate the quality of water in the Shatt Al-Arab River (SAAR), known as Shatt Al-Arab Fish Index (SFI), which can also be applied to the Qarmat Ali River and other water bodies similar to the SAAR ecology. Data was collected from three stations along the river from March 2019 to February 2023 to construct and calibrate the index. Twenty-nine metrics were considered as possible parameters for the SFI, including factors such as fish composition, and food habits. Ultimately, nine metrics were included in the SFI. The SFI demonstrated high assessment efficiency because it relied on measures sensitive to temporal and spatial changes that are affected by human activities. The SFI was used to validate additional data collected during sampling conducted in 2023. As a result of these applications, the three stations in the SAAR were classified as “moderate” and “poor” status. In contrast, the Qarmat Ali River was classified as “poor” status. Therefore, the study concludes that fish are essential in biological assessment tools, which are used as a basis for monitoring and managing multiple water bodies. Thus, the health of the SAAR ecosystem can be improved in the long term.

Journal of King Abdulaziz University-Marine SciencesVol. 35(2)
Openalex Percentile: Top 33%
Water Quality and Pollution Assessment
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New Fish-Based Multimetric Index for Appraising Shatt Al-Arab Ecological Quality — Laith Faisal Lazem · Journal of King Abdulaziz University-Marine Sciences (2025) | TGRS Research Map | TGRS