Sensitivity Analysis and Vulnerability Mapping of the Guilan Aquifer Using Drastic Method

Hadi Modabberi (), Mir Moslem Rahbar Hashemi (), Mehdi Ashournia () and Mohammad Ali Rahimipour ()

Review of Environment and Earth Sciences, 2017, vol. 4, issue 1, 27-41

Abstract: Vulnerability of the water resources is a continuation of such trends. The first step in management of the groundwater resources is a determination of the vulnerable areas. The objective of this research was determining the vulnerability assessment of the central plain of Gilan using DRASTIC model. Principles of the model are based on overlaying of seven thematic maps of depth to water table, net recharges, aquifer media, soil media, topography, vados zone and hydraulic conductivity by considering appropriate weights and rates. The database was constructed by introducing the mentioned maps. Index of DRASTIC model for aquifer vulnerability of the central plain Gilan was ranged in 82-182. In this plain, there was not very much and very low vulnerability classes. The final map of DRASTIC model showed that %¬48.64 of the area has high vulnerability and %¬50.55 has medium vulnerability and only a small area of plain (%0.81) has low vulnerability. The statistical summary of the DRASTIC model elements shows that the element of depth to groundwater table has the greatest impact on DRASTIC model. Also based on the map remove and single element sensitivity, depth to groundwater table is identified as the effective element in the central plain of Gilan. The results of the correlation between the elements of DRASTIC model and nitrate concentrations showed that there is the highest correlation between nitrate and depth to groundwater table. The average concentration of nitrates is 8.92 mg/lit in the wells studied at the Central Plains Gilan. In all wells studied, nitrate concentration was lower than the recommended level by US Environmental Protection Agency (45 mg/lit).

Keywords: Groundwater vulnerability assessment; Drastic; Nitrate; Sensitivity Analysiss; Guilan Province (search for similar items in EconPapers)
Date: 2017
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