A GIS-based DRASTIC Model and an Adjusted DRASTIC Model (DRASTICA) for Groundwater Susceptibility Assessment along the China–Pakistan Economic Corridor (CPEC) Route (original) (raw)
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Groundwater is the most economic natural source of drinking in urban and rural areas which 28 are degraded due to high population growth and increased industrial development. We applied 29 a GIS-based DRASTIC model in a populated urban area of Pakistan (Peshawar) to assess 30 groundwater vulnerability to pollution. Six input parametersdepth to phreatic/groundwater 31 level, groundwater recharge, aquifer material, soil type, slope and hydraulic conductivity -32 were used in the model to generate the groundwater vulnerable zones. Each parameter was 33 divided into different ranges or media types, and ratings = 1-10 were assigned to each factor 34 where 1 represented the very low impact on pollution potential and 10 represented very high 35 impact. Weight multipliers = 1-5 were also used to balance and enhance the importance of 36 each factor. The DRASTIC model scores obtained varied from 47 to 147, which were divided 37 into three different zones: low, moderate and high vulnerability to pollution. The final results 38 indicate that about 31.22%, 39.50%, and 29.27% of the total area are under low, moderate, and 39 high vulnerable zones, respectively. Our method presents a very simple and robust way to 40 assess groundwater vulnerability to pollution and helps the decision makers to select 41 appropriate landfill sites for waste disposals, and manage groundwater pollution problems 42 efficiently. 43 44
International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022
Groundwater intrinsic vulnerability maps are considered a promising means for forestalling groundwater resources from contamination in recent years. With the use of a Geographic Information System (GIS) and hydro-geochemical data, the DRASTIC model is used to forecast groundwater vulnerability. For which ArcGIS software is used. Lucknow, capital of Uttar Pradesh, is the study area for this study. This model is based on the seven data layers that provide the input to the modelling. It corresponds to the initials of seven layers i.e. Depth to water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone ,and Hydraulic Conductivity. Mal and Sarojani Nagar Block showed higher vulnerability (139-143). The results also suggested that the low, moderate, and high groundwater vulnerability zones cover around 30.35%, 45.02%, and 24.63 % of the study area, respectively. The results is validated using nitrate concentration in groundwater. The percentage of study area for nitrate concentrations <45 mg/l, 45-60 mg/l, 60-80 mg/l, and 80-110 mg/l are 55.5%, 34.5%, 9%, and ~1% respectively. The GIS technique has provided an efficient tool for assessing and analysing the vulnerability to groundwater pollution.
Water Supply, 2015
Pollution control and removal of pollutants from groundwater are a challenging and expensive task. The aims of this paper are to determine the aquifer vulnerability of Sefid-Dasht, in Chaharmahal and Bakhtiari province, Iran, using the DRASTIC model. In addition, the groundwater quality index (GQI) technique was applied to assess the groundwater quality and study the spatial variability of major ion concentrations using a geographic information system (GIS). The vulnerability index ranged from 65 to 132, classified into two classes: low and moderate vulnerability. In the southern part of the aquifer, the vulnerability was moderate. Furthermore, the results indicate that the magnitude of the GQI index varies from 92% to 95%. This means the water has a suitable quality. However, from the north to the south and southwest of the aquifer, the water quality has been deteriorating, and the highest concentration of major ions was found in the southwest of the Sefid-Dasht aquifer. A comparis...
Environmental Earth Sciences, 2019
Intensive use of fertilizers in the agricultural lands and a swift-flying of coal and allied industries in Korba district, India in an unprecedented manner has led to groundwater contamination. Accordingly, an integrated modified DRASTIC and risk index model combined with other statistical techniques are applied to evaluate groundwater susceptibility and pollution risk in the region. The ArcGIS based spatial distribution map of the DRASTIC vulnerability index (DVI) reveals that the high (63%) and very high (23.61%) vulnerable zones identified in DVI map are reduced to that of 57.86% and 17.74%, respectively, when compared with pollution risk map. Results of sensitivity analysis, i.e., map removal sensitivity analysis and single parameter sensitivity analysis confirms that amongst seven DRASTIC parameters the net recharge parameter is the most influencing parameter in view of the groundwater contamination. The linear correlation coefficient (r = 0.89) obtained between risk index values and NO 3 concentrations alongside nearly 75% of the study area comprises of agricultural lands and forest/tree clad area corresponds to high to very high risk contamination zones reveal the model validation in the light of the influence of anthropogenic contamination factor in these zones. Furthermore, elevated iron concentration also supports the certain influence of geogenic contamination within the study area. In essence, this study can be effectively utilized in the planning and management of precious groundwater resources in high to very high vulnerable and risk zones of the study area, for its overall sustainable development.
Ecotoxicology and Environmental Safety, 2021
This study employed a modified DRASTIC model (AHP-DRASTIC model) and GALDIT model to evaluate the inherent vulnerability of shallow groundwater in Weibei Plain in Shandong Province of China and its vulnerability to seawater intrusion. The AHP-DRASTIC model uses the analytic hierarchy process (AHP) to determine the weight of each parameter and reduces the subjectivity of evaluation. The vulnerability map generated by the AHP-DRASTIC model shows four types of vulnerability: high (25.0%), higher (28.0%), moderate (29.7%), and low (17.3%), and the high-vulnerability areas are mainly distributed in the area north of Qingxiang Town and south of Changyi County. The distribution of high-vulnerability areas mainly related to the depth of groundwater table is 4-8 m, and the recharge of rainfall is 100-175 mm/year. The vulnerability map generated by the GALDIT model shows four types of vulnerability: high (33.5%), higher (23.4%), moderate (22.1%), and low (21.0%), and the high-vulnerability areas are mainly distributed in the coastal areas of Hanting District-Zhuli Town, the areas north of Linqu County, and the areas south of Shouguang County. The distribution of high-vulnerability areas mainly related to the distance between these areas and the coast is < 2.5 km, with aquifer thickness > 15 m. Total dissolved solid, NO 3 − , Cl − , and SO 4 2− are used to verify the accuracy of the DRASTIC model, the AHP-DRASTIC model, and the GALDIT model. The results show that the AHP-DRASTIC model is more suitable for the assessment of inherent vulnerability of shallow groundwater in the study area than the DRASTIC model, and human activities have a major impact on the verification of vulnerability and should be considered when conducting groundwater vulnerability verification. The results of this study can provide grounds for groundwater management and protection and land use planning in the study area and provide new ideas for groundwater vulnerability assessment in coastal areas.
GIS-based assessment of aquifer vulnerability using DRASTIC Model: A case study on Kodaganar basin
Earth Sciences Research Journal, 2016
Groundwater is vulnerable and more susceptible to contamination from various anthropogenic elements. Various steps are taken to measure the groundwater vulnerability for a sustainable groundwater development. The present study estimates the aquifer vulnerability by applying DRASTIC model in the Geographic Information System (GIS) environment. The DRASTIC model uses seven hydrological parameters which include depth to water level, net recharge, aquifer media, soil media, topography, the impact of vadose zone and hydraulic conductivity. DRASTIC index was calculated from DRASTIC model that ranged from 31 to 154. All these parameters characterize the hydrological setting for evaluating aquifer vulnerability. Sensitivity analyses have also been performed to determine the sensitivity of every individual DRASTIC parameter towards the aquifer vulnerability. Sensitivity analysis indicated that all the parameters have an almost similar influence on vulnerability index. Depth to water paramete...
2005
Assessment of groundwater pollution vulnerability using the DRASTIC model in a GIS environment has become more widespread for effective groundwater planning and management. Groundwater vulnerability is based on the assumption that the physical environment may provide some degree of protection to groundwater against contamination entering the subsurface environment. Groundwater pollution vulnerability maps are useful for groundwater quality monitoring, and to identify areas that need more detailed analysis for land use planning. The DRASTIC standardized system for evaluating groundwater pollution potential is based on different parameters, such as depth to water, net recharge, aquifer media, soil media, topography, impact of vadose zone and hydraulic conductivity. The thematic layers of each parameter have been prepared and integrated through the DRASTIC model within a GIS environment to demarcate vulnerable zones. DRASTIC indices for both normal and agricultural pollutants have been derived to prepare groundwater vulnerability maps.
Environmental Engineering Research
The present study deals with the management of groundwater resources of an important agriculture track of northwestern part of Saudi Arabia. Due to strategic importance of the area efforts have been made to estimate aquifer proneness to attenuate contamination. This includes determining hydrodynamic behavior of the groundwater system. The important parameters of any vulnerability model are geological formations in the region, depth to water levels, soil, rainfall, topography, vadose zone, the drainage network and hydraulic conductivity, land use, hydrochemical data, water discharge, etc. All these parameters have greater control and helps determining response of groundwater system to a possible contaminant threat. A widely used DRASTIC model helps integrate these data layers to estimate vulnerability indices using GIS environment. DRASTIC parameters were assigned appropriate ratings depending upon existing data range and a constant weight factor. Further, land-use pattern map of study area was integrated with vulnerability map to produce pollution risk map. A comparison of DRASTIC model was done with GOD and AVI vulnerability models. Model validation was done with NO3, SO4 and Cl concentrations. These maps help to assess the zones of potential risk of contamination to the groundwater resources.
Arabian Journal of Geosciences, 2020
In recent years, one of the major concerns is groundwater contamination by industrial wastewater. Consecutive monitoring/ mapping of aquifer water quality is an expensive and hectic job in relatively large areas. Therefore, groundwater vulnerability maps are becoming more crucial to identify regional aquifer contamination potential. The present study area is focused to the largest industrial and metropolitan city of Pakistan, i.e. Faisalabad. The study is aimed to explore groundwater vulnerability potential zones and to identify most influencing hydrogeological characteristics. In this regard, a GIS-based DRASTIC model is used to delineate vulnerability to agricultural applications. Inputs of the model are based on seven different layers and the model is compared with groundwater samples. Results showed that the model accurately identifies the vulnerability with the prediction efficiency of~73%. The results revealed that more than 30% of the study area has high vulnerability potential, located in the middle and upper part of district Faisalabad. It has been found that the causation of high vulnerability in the surrounding of various cities is due to shallow groundwater table, high recharge, gradual slope, sandy aquifer media, and soil media that consist of medium sand. In some of the cities, dominating factors are shallow groundwater table, gradual slope, vadose zone that consists of course sand and high hydraulic conductivity. Therefore, it is recommended that the site-specific solutions according to their influencing hydrogeological features to pollution must be adopted. In this aspect, rainwater harvesting, aquifer storage, and recovery wells (ASR) could be adopted to reduce water salinity in medium and high vulnerability areas.
Central European Journal of Engineering, 2014
Amman-Zerqa Basin (AZB) is the second largest groundwater basin in Jordan with the highest abstraction rate, where more than 28% of total abstractions in Jordan come from this basin. In view of the extensive reliance on this basin, contamination of AZB groundwater became an alarming issue. This paper develops a Modified DRASTIC model by combining the generic DRASTIC model with land use activities and lineament density for the study area with a new model map that evaluates pollution potential of groundwater resources in AZB to various types of pollution. It involves the comparison of modified DRASTIC model that integrates nitrate loading along with other DRASTIC parameters. In addition, parameters to account for differences in land use and lineaments density were added to the DRASTIC model to reflect their influences on groundwater pollution potential. The DRASTIC model showed only 0.08% (3 km 2 ) of the AZB is situated in the high vulnerability area and about 30% of the basin is located in the moderately vulnerable zone (mainly in central basin). After modifying the DRASTIC to account for lineament density, about 87% of the area was classified as having low pollution potential and no vulnerability class accounts for about 5.01% of the AZB area. The moderately susceptible zone covers 7.83% of the basin's total area and the high vulnerability area constitutes 0.13%. The vulnerability map based on land use revealed that about 71% of the study area has low pollution potential and no vulnerability area accounts for about 0.55%, whereas moderate pollution potential zone covers an area of 28.35% and the high vulnerability class constitutes 0.11% of AZB. The final DRASTIC model which combined all DRASTIC models shows that slightly more than 89% of the study area falls under low pollution risk and about 6% is considered areas with no vulnerability. The moderate pollution risk potential covers an area of about 4% of AZB and the high vulnerability class constitutes 0.21% of the basin. The results also showed that an area of about 1761 km 2 of bare soils is of low vulnerability, whereas about 28 km 2 is moderately vulnerable. For agriculture and the urban sector, approximately 1472 km 2 are located within the low vulnerability zone and about 144 km 2 are moderately vulnerable, which together account for about 8% of the total agriculture and urban area. These areas are contaminated with human activities, particularly from the agriculture. Management of land use must be considered when changing human or agricultural activity patterns in the study area, to reduce groundwater vulnerability in the basin. The results also showed that the wells with the highest nitrate levels (81-107 mg/l) were located in high vulnerable areas and are attributed to leakage from old sewage water.