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Vulnerability assessment to delineate areas that are more susceptible to contamination from anthropogenic sources has become an important element for sensible resource management and land use planning. This contribution aims at estimating aquifer vulnerability by applying the DRASTIC model as well as utilizing sensitivity analyses to evaluate the relative importance of the model parameters for aquifer vulnerability. An additional objective is to demonstrate the combined
use of the DRASTIC and geographical information system (GIS) as an effective method for groundwater pollution risk assessment. The DRASTIC model uses seven environmental parameters (Depth to water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone, and hydraulic Conductivity) to characterize the hydrogeological setting and evaluate aquifer vulnerability. Net recharge parameter inflicted the largest impact on the intrinsic
vulnerability of the aquifer followed by soil media, topography, vadose zone media, and hydraulic conductivity. Sensitivity analyses indicated that the removal of net recharge, soil media and topography causes large variation in vulnerability index. Moreover, net recharge and hydraulic conductivity were found to be more effective in assessing aquifer vulnerability than assumed by the DRASTIC model. The GIS technique has provided efficient environment for analyses and high
capabilities of handling large spatial data. moreover this study has shown that (13%) of the total area was under the low vulnerable zone, mainly due to the presence of the higher depth of water level and high elevation (Topography). And About (66 %) of the area was low vulnerable zone About (%19) of the area was moderate vulnerable zone which could be due to the reason that less depth of water level and high elevation. And about (2%) of the area was high. Final computed values for DRASTIC Index provide numerical range for vulnerability criteria and aquifer vulnerability analysis. For Bani Naim , the DRASTIC index value degree varied from 32 to 118 divided into four categories ; under low vulnerability (32- 42) , low vulnerability (42- 73) , under high vulnerability (73- 101), and high vulnerability (101- 118). |
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