Abstract
In this paper, a new hybrid DRASTIC-based fuzzy C-means (FCM) clustering technique is utilized to find the real relation among the affecting parameters of each hydrogeological point resulting in vulnerability and the fuzzy membership degree of each point to the “most-vulnerable class”. This procedure can be done instead of holding a summation through all affecting parameters to form vulnerability index as implemented in the ordinary DRASTIC method. In DRASTIC, any changes in one point’s parameter value may cause that point to move to another vulnerability class or points which have obviously different parameter values may belong to the same vulnerability class. While in fuzzy logic, each point partly belongs to each vulnerability class and does not necessarily belong to a specific one. This is the main motivation to use FCM clustering technique. In this paper, the vulnerability map of Damaneh-Daran aquifer, located in Isfahan province in central Iran, is prepared using DRASTIC and hybridizing DRASTIC and FCM. The analytical-experimental investigations reveal the weighting power of 1.75 is the best value among 1.25, 1.5, 1.75 and 2. In this weighting power, there are approximately 51%, 21% and 1% decreases in the area percentages covered by low, medium and high vulnerability clusters, respectively, while the area percentages covered by very low and very high clusters increases 8 and 5 times than those of the ordinary DRASTIC, respectively, mainly due to partial membership of the hydrogeological points in the fuzzy clusters, making the areas covered much more evenly distributed among different vulnerability classes. To validate the proposed model, the final vulnerability indices were compared with the nitrate concentration of the aquifer assuming four fuzzy intensity levels. The results indicate the FCM-DRASTIC-based vulnerability zoning have more correlation with the nitrate concentration zoning of the aquifer than the ordinary DRASTIC model.
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Notes
- 1.
Universal Transverse Mercator; UTMx and UTMy give the transversal and longitudinal (x,y) coordinates of each point.
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Abedi Koupai, J., Zamani, N., Rezaei, F. (2022). A DRASTIC-Based Fuzzy C-means Clustering Technique for Evaluating Groundwater Vulnerability Under Uncertainty. In: Shaban, A. (eds) Satellite Monitoring of Water Resources in the Middle East. Springer Water. Springer, Cham. https://doi.org/10.1007/978-3-031-15549-9_19
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