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Assessment of groundwater quality using DEA and AHP: a case study in the Sereflikochisar region in Turkey

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Abstract

This study investigated the spatial distribution of groundwater quality in Sereflikochisar Basin, in the Central Anatolian region of Turkey using different hydrochemical, statistical, and geostatistical methods. A total of 51 groundwater samples were collected from the observation wells in the study area to evaluate the characteristics of the groundwater quality. As a relatively simple and practical method, a groundwater quality index (GWQI) was developed to evaluate the overall groundwater quality. In this process, complex decision-making techniques such as analytic hierarchy process (AHP) and data envelopment analysis (DEA) were used. Based on these models, two new indices (A-GWQI and D-GWQI) were proposed. According to the D-GWQI score (from 0.6 to 1), water quality was classified in four categories as unsuitable (0.6–0.7), permissible (0.7–0.8), good (0.8–0.9), and excellent (0.9–1). The spatial distribution maps of the groundwater quality were created using the Kriging method. For each map, seven different semivariogram models were tested and the best-fitted model was chosen based on their root mean square standardized error. These maps showed that the areas with high groundwater quality were in the eastern and southern parts of the study area where the D-GWQI scores were greater than 0.8. Depending on the distance from the Salt Lake, the characteristics of groundwater changed from NaCl to NaHCO3 and CaHCO3 facies. This study shows how to determine the spatial distribution of the groundwater quality and identify the impact of salt lakes on the groundwater quality in inland aquifers. The findings of this study can be applied to ensure the quality of groundwater used for drinking and irrigation purposes in the study area.

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Correspondence to Murat Kavurmaci.

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Kavurmaci, M., Üstün, A.K. Assessment of groundwater quality using DEA and AHP: a case study in the Sereflikochisar region in Turkey. Environ Monit Assess 188, 258 (2016). https://doi.org/10.1007/s10661-016-5259-6

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