An integrated approach for prioritization of river water quality sampling points using modified Sanders, analytic network process, and hydrodynamic modeling

Determination of the water quality monitoring network (WQMN) is a vital stage for surveying ecosystem health. Studies have been done in determining the optimal number and location of sampling points, but seasonality of water quality, especially for heavy metals, has been rarely studied. For the firs...

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Published inEnvironmental monitoring and assessment Vol. 193; no. 8
Main Authors Asadi, Ali, Moghaddam Nia, Alireza, Bakhtiari Enayat, Bahram, Alilou, Hossein, Ahmadisharaf, Ebrahim, Kimutai Kanda, Edwin, Chessum Kipkorir, Emmanuel
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 01.08.2021
Springer Nature B.V
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Summary:Determination of the water quality monitoring network (WQMN) is a vital stage for surveying ecosystem health. Studies have been done in determining the optimal number and location of sampling points, but seasonality of water quality, especially for heavy metals, has been rarely studied. For the first time, this study proposes a framework to determine the optimal location of sampling points to monitor lead (Pb). This study was conducted for the Karoun River, located in southwestern Iran. First, hydraulic characteristics of the river were simulated by implementing of MIKE11 software as well as water quality(variation of Pb concentration). Nash‑Sutcliffe coefficient were 0.91 and 0.91 for discharge calibration and validation, respectively. Second, 16 potential sampling points were proposed using modified Sanders’ approach considering seasonality. For a better accuracy in the WQMN layout and a more efficient site selection of sampling points, a 1-km buffer is stretched along the river for determining non-point source pollution sources and prioritizing candidate points. This leads to considering different land uses in the study area, while GIS software has been employed. Seasonal changes and land use have a significant impact on the location of optimal sampling points. The presented framework can be used to improve water quality and support watershed protection efforts.
ISSN:0167-6369
1573-2959
DOI:10.1007/s10661-021-09272-y