A GIS-based DRASTIC model for assessing groundwater vulnerability in hard rock granitic aquifer

Shekhar, Shashank; Pandey, Arvind Chandra; Tirkey, Anamika Shalini

doi:10.1007/s12517-014-1285-2

Cited by 39 publications

(6 citation statements)

References 25 publications

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“…The DRASTIC model is flexible for modification as it allows users to define the model input and weight the importance of the model variables based on their experience and knowledge [23]. This ensures that local hydrogeological characteristics are taken into account, and therefore, the model suits better for the local case study [35,36]. In Equation ( 1), all the essential parameters are determined according to their key roles in the presence of soil water vulnerability in the study area.…”

Section: Thematic Layer Processingmentioning

confidence: 99%

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Estimating Soil Water Susceptibility to Salinization in the Mekong River Delta Using a Modified DRASTIC Model

Tran

et al. 2021

Water

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Saltwater intrusion risk assessment is a foundational step for preventing and controlling salinization in coastal regions. The Vietnamese Mekong Delta (VMD) is highly affected by drought and salinization threats, especially severe under the impacts of global climate change and the rapid development of an upstream hydropower dam system. This study aimed to apply a modified DRASTIC model, which combines the generic DRASTIC model with hydrological and anthropogenic factors (i.e., river catchment and land use), to examine seawater intrusion vulnerability in the soil-water-bearing layer in the Ben Tre province, located in the VMD. One hundred and fifty hand-auger samples for total dissolved solids (TDS) measurements, one of the reflected salinity parameters, were used to validate the results obtained with both the DRASTIC and modified DRASTIC models. The spatial analysis tools in the ArcGIS software (i.e., Kriging and data classification tools) were used to interpolate, classify, and map the input factors and salinization susceptibility in the study area. The results show that the vulnerability index values obtained from the DRASTIC and modified DRASTIC models were 36–128 and 55–163, respectively. The vulnerable indices increased from inland districts to coastal areas. The Ba Tri and Binh Dai districts were recorded as having very high vulnerability to salinization, while the Chau Thanh and Cho Lach districts were at a low vulnerability level. From the comparative analysis of the two models, it is obvious that the modified DRASTIC model with the inclusion of a river or canal network and agricultural practices factors enables better performance than the generic DRASTIC model. This enhancement is explained by the significant impact of anthropogenic activities on the salinization of soil water content. This study’s results can be used as scientific implications for planners and decision-makers in river catchment and land-use management practices.

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Section: Thematic Layer Processingmentioning

confidence: 99%

“…The aquifer media presents the aquifer's salinity attenuation capacity, which depends on the quantity and types of the grains [17,36]. Because the formation factor (F) leans on the porosity (Φ) (i.e., the grain size of aquifer media), the greater the (F), the higher the salinization possibility [4,42].…”

Section: Aquifer Media (A)mentioning

confidence: 99%

Estimating Soil Water Susceptibility to Salinization in the Mekong River Delta Using a Modified DRASTIC Model

Tran

et al. 2021

Water

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“…Topography (T): The area topography directly affects the precipitation distribution and runoff infiltration in the study area, and indirectly affects the retention time of pollutants on the soil surface [43]. For large slopes, precipitation quickly carries pollutants away, in the form of surface runoffs; thus, pollutants are retained only for a short time.…”

Section: The Drastic Methodsmentioning

confidence: 99%

Influence of Agricultural Irrigation Activity on the Potential Risk of Groundwater Pollution: A Study with Drastic Method in a Semi-Arid Agricultural Region of China

Meng

Zhang²,

Liu³

et al. 2020

Sustainability

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Agricultural irrigation strongly affects groundwater pollution in cultivated areas. Groundwater vulnerability was evaluated using the DRASTIC method by considering agricultural activities that affect water infiltration and pollutant transport to the groundwater. Three scenarios, using different water recharge sources and calculation methods, were considered for the Tongliao area of northern China. For Scenario 1, only precipitation contributed to the net recharge estimation and ~33.77% of the area was under high pollution risk. For Scenarios 2 and 3, both precipitation and irrigation return water were considered for net recharge estimations. The fractional areas of high pollution risk regions were 40.60% and 19.22% for Scenarios 2 and 3, respectively. The modified infiltration coefficients for this study area were used in Scenario 3, and the fractional area of the high-risk region was 21.38% lower than for Scenario 2. The use of empirical infiltration coefficients in Scenario 2 overestimated the water infiltration ability in the cultivated areas, which also overestimated the fractional area of high-risk regions in this study. Accurate assessment of the impact of agricultural activities on the groundwater pollution risk is essential for cultivated areas. Emphasis should be placed on the calculation method of proper parameters for DRASTIC model construction.

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“…permeation and control pathways). Thus, the availability of precipitation is considered to be the main underpinning of recharge (Shekhar et al, 2015). Precipitation has a strong impact on groundwater potential and the effectiveness of Multi-Criteria Decision Analysis (MCDA) (Adiat et al, 2012).…”

Section: Rainfallmentioning

confidence: 99%

Groundwater Availability and Suitability Evaluation for Irrigated Agriculture in Mbale District

2023

IJFMR

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The purpose of this study was to evaluate the availability and suitability of groundwater in Mbale district basing on potential, quality and vulnerability to support irrigated agriculture. Groundwater potential was assessed using geospatial technique through AHP model. Thematic layers were prepared namely: land use and land cover, slope, soil, rainfall, lineament density, lithology, geomorphology and drainage density. All layers were integrated using the MLC technique. Ranking of each parameter was performed using WOIA. Weights were assigned to each subject class basing on AHP results. The consistency of the outputs was tested by computation of CR and was at a reasonable acceptable level (0.029 < 0.1). Groundwater potential was delineated basing on the values of groundwater potential index. Groundwater quality was determined using IWQI method. Thirty-three water samples were collected. Five chemical parameters were tested in the laboratory: chloride, electrical conductivity, bicarbonate, sodium and SAR to generate the water quality database using Kriging interpolation technique. Computation of IWQI values for each source was made and was used to generate the IWQI map using the weighted summation. DRATIC method was used to delineate vulnerability of groundwater. Layers were generated using the following parameters: depth to groundwater, net recharge, aquifer media, topography, vadose zone impacts, and hydraulic conductivity. The aquifer vulnerability map was prepared by overlaying layers. Three different vulnerability zones were determined according to DRASTIC scores low (<100), medium (100-140) and high (>140). Integration of maps of quality, vulnerability and potential of groundwater was made using an unsupervised MLC classification method. Groundwater potential was in three zones: very good zone was 26.99 km2 (12.98%), the good zone was 126.22 km2 (60.71%) and the poor zone was 54.69 km2 (26.31%). The average annual exploitable groundwater reserves are estimated at 0.026 (MCM/km2) in the zone of “very good”, 0.024 MCM/km2 in the zone of “good” and 0.018 MCM/km2 in the zone of “poor”. Groundwater quality was in two use restrictions: High Restriction of 90.90% with the IWQI value from 40 to 55 on the area of 188.98 km2 of the study area and Severe Restriction of 9.10% with IWQI values from 32 to 40 covering of 18.92 km2. The study area had a high probability of contamination. Low vulnerability covers an area of 11.23km2 (5.40%), 77.83km2 (37.44%) for medium and 118.83km2 (57.16%) for high. The resulting clustered map was classified into five categories with their respective regions: 17.58% very poor (36.56km2), 13.84% poor (28.77km2), 12.69% good (26.39km2), 31.46% very good (65.39km2) and 24.43 % excellent (50.78km2). The sub counties in Mbale district that have inadequate and unsuitable groundwater for irrigated agriculture are Budwale, Wanale, Busano, Bubyangu, Bufumbo and Nyondo since they belong to the zones of very poor and poor. The remaining sub counties have available and suitable groundwater for irrigated agriculture since they belong to the zones of good, very good and excellent.

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A GIS-based DRASTIC model for assessing groundwater vulnerability in hard rock granitic aquifer

Cited by 39 publications

References 25 publications

Estimating Soil Water Susceptibility to Salinization in the Mekong River Delta Using a Modified DRASTIC Model

Estimating Soil Water Susceptibility to Salinization in the Mekong River Delta Using a Modified DRASTIC Model

Influence of Agricultural Irrigation Activity on the Potential Risk of Groundwater Pollution: A Study with Drastic Method in a Semi-Arid Agricultural Region of China

Groundwater Availability and Suitability Evaluation for Irrigated Agriculture in Mbale District

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