Volume 9, Issue 2 (Autumn & Winter 2024)                   KJES 2024, 9(2): 277-306 | Back to browse issues page


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1- Sahel Omid Iranian Consulting Engineers
2- Shahid Chamran University of Ahvaz , a.saberinasr@scu.ac.ir
3- Kharazmi University
Abstract:   (319 Views)
Spatial distribution of groundwater quality data and a reasonable monitoring network, which are usually collected from monitoring wells, are required for the management of groundwater resources. However, since the maintenance cost of groundwater monitoring networks is extremely high, an optimal design of those is necessary. This study aimed to find a qualitatively optimal monitoring network with a minimum number of wells in the Rafsanjan aquifer so that it could provide sufficient spatial distribution in terms of groundwater quality. For this purpose, electrical conductivity (EC) was selected as a quality parameter in the design of the monitoring network in this study. In the first step, to identify the risk and assess the vulnerability of the aquifer, the DRASTIC method was used. Then, the average Kriging standard deviation was used as a criterion for the determination of network density, and the GIS-based approach was analyzed. In this step, semi-variograms were tested to ascertain the best-fitted model accuracy measures, average standard error, root mean square error, and root mean square standardized error. The results showed that the spherical model is more reliable than other models due to the root mean square standardized error (RMSSE) being close to one, the average standard error (ASE) being close to the root mean square error (RMSE), and the less RMSE than other models. Also, based on cross-validation of data and a quality monitoring map resulting from the overlap of prediction and standard error maps with the DRASTIC map, 60 wells were sufficient as groundwater quality monitoring stations for the Rafsanjan aquifer. Removing 10 wells in different parts of the aquifer and adding 6 wells in the northwest of the aquifer will help to complete the quality monitoring network.
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Type of Study: Original Research | Subject: Geohydrology
Received: 2024/02/24 | Accepted: 2024/03/4 | Published: 2024/03/10

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