Application of DRASTIC and Modified DRASTIC Models for Modeling Groundwater Vulnerability of Malda District in West Bengal

Sarkar, Manasree; Pal, Subodh Chandra

doi:10.1007/s12524-020-01176-7

Cited by 31 publications

(13 citation statements)

References 69 publications

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“…The main strength of the DRASTIC method is the possibility of including or eliminating parameters or factors from the model to adapt to different problems, such as the conditions in the area of study and availability of data [45,75,82]. Alternatively, the weight and rate scores can be modified depending on the field measurement data, whereas susceptibility and risk maps can be combined to provide better results using DRASTIC [51].…”

Section: Advantagesmentioning

confidence: 99%

DRASTIC, GOD, and SI approaches for assessing groundwater vulnerability to pollution: a review

Fannakh

Farsang

2022

Environ Sci Eur

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Over the last three to four decades, several methods for assessing groundwater vulnerability to anthropogenic pollution have been developed. Researchers and policymakers have widely used these methods for preventing groundwater pollution through knowledge about particularly vulnerable areas. This systematic review presents different and significant methods for assessing the vulnerability of aquifers for the protection of the resource. Previous studies mentioned that formulating a single technique for assessing groundwater vulnerability is difficult; thus, different methods and techniques have been proposed. Therefore, this paper presents three methods, namely, DRASTIC, GOD, and susceptibility index (SI), which will be discussed in detail, and highlights their advantages and limitations. In doing so, the study introduces the concept of aquifer vulnerability, and further discussion will be devoted to the three methods. Lastly, the study outlines the major challenges to the assessment of aquifer vulnerability. The review concludes the importance of groundwater vulnerability and strategies for preserving its quality.

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Section: Advantagesmentioning

confidence: 99%

DRASTIC, GOD, and SI approaches for assessing groundwater vulnerability to pollution: a review

Fannakh

Farsang

2022

Environ Sci Eur

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“…Finally, the globally optimized model can be regarded as the ground state of the atom. e random matrix model uses the singular value decomposition based on the least squares to obtain the local minimum value of the objective function, and obtains the excited state of the atom [11]. e target energy level corresponding to each excited state transitions according to the energy level transition probability until it reaches the ground state of the atom.…”

Section: Eigenvalue Distribution Of the Random Matrix Ofmentioning

confidence: 99%

Construction and Application of Groundwater Impact Analysis Model Based on Random Matrix Model

Fang

Tan

2022

Mathematical Problems in Engineering

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Traditional groundwater models do not consider the influence of random factors, so their results of simulation and prediction cannot reflect the actual dynamics of ongoing groundwater changes. By comparing the statistical properties of random multidimensional time series, the random matrix theory can reflect the degree of deviation from randomness in actual data and reveal the behavioral characteristics of the overall correlation in actual data. On the basis of summarizing and analyzing the previous literature, this study expounded the research status and significance of groundwater impact analysis models, elaborated on the development background, current status, and future challenges of the random matrix model, introduced the methods and principles of the finite isometric properties and observation feature dimension, conducted the spectral analysis of the random matrix of groundwater impact analysis data, analyzed the eigenvalue and the eigenvector distribution of the random matrix of the groundwater impact analysis data, constructed a groundwater impact analysis model based on the random matrix model, designed the hydrodynamic model for the groundwater impact analysis, discussed the parameter variation mechanism of the groundwater impact analysis, and finally carried out a case application and its result analysis. The study results show that in the membership calculation formula of the random matrix model, it is found that there is an inverse relationship between the expected value of the target index and its membership value. According to the initial fuzzy membership function value, the random matrix model uses the normalization formula and evaluation criteria of the catastrophe model to carry out a comprehensive quantitative recursive operation and finally determines the concept, characteristics, influencing factors, evaluation content, purpose, and scope of the groundwater impact analysis model. The random matrix model can not only reflect the spatial and temporal differences of groundwater-influencing factors but also reflect the dynamic mechanism of aquifer or groundwater system or the inherent law of groundwater movement, so it is more applicable and convenient to evaluate groundwater resources.

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“…Different models, such as the GOD model, were used by different scholars to assess aquifer vulnerability (Ebrahimi, 2015;Musálem, 2015); SINTACS (Raipur, 2016); DRASTIC (Aller et al, 1987 Singh et al, 2015). As a result of integrating anthropogenic factors with hydrogeological parameters to examine groundwater vulnerability, the modi ed DRASTIC model is currently the most commonly and widely used model for groundwater assessment (Sarkar & Chandra, 2021). The drastic model includes seven hydrogeological parameters that in uence the occurrence and movement of groundwater into the system.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Groundwater Suceptiability to Nitrate Contamination Using GIS-Based Modified DRASTIC Model in the Rib Watershed, upper Abay Basin, Ethiopia

Fentie,

Gedefaw

2024

Preprint

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Groundwater is one of the most important sources of freshwater, contributing significantly to domestic, drinking, and irrigation needs around the world. However, its quality is deteriorating over time due to overexploitation and anthropogenic activities. The Rib watershed, located in the Tana sub-basin (Ethiopia), is a heavily cultivated and urbanising area. Therefore, this study attempted to assess groundwater vulnerability to pollution using the GIS-based Modified DRASTIC Model. Hydrogeological parameters and anthropogenic factors (land use/land cover) were used for assessment. The necessary data were collected from the field, downloaded from websites, concerned organizations, and laboratory experiments. The results showed that more than 73.24% of the watershed is under medium to high vulnerability, and highly vulnerable areas (22.48%) were confined to the Southern parts of the watershed (under built-up and cultivated areas. The vulnerability of groundwater in the watershed is highly influenced by aquifer media (24.1%), net recharge (21.75%), land use/land cover (15.1%), and depth of groundwater table (13.6%). Based on the observed data of groundwater quality parameters (turbidity, pH, and nitrate), high-vulnerable areas were more contaminated than medium and low-vulnerable areas. Therefore, the result indicated that the area is vulnerable to contamination calling for appropriate groundwater management. Hence, this finding helps to plan and minimize future contamination of groundwater by considering its vulnerability before high-risk activities are allowed. The investigators recommended that the overall quality of groundwater be investigated and that appropriate groundwater management be designed to reduce groundwater contamination.

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Application of DRASTIC and Modified DRASTIC Models for Modeling Groundwater Vulnerability of Malda District in West Bengal

Cited by 31 publications

References 69 publications

DRASTIC, GOD, and SI approaches for assessing groundwater vulnerability to pollution: a review

DRASTIC, GOD, and SI approaches for assessing groundwater vulnerability to pollution: a review

Construction and Application of Groundwater Impact Analysis Model Based on Random Matrix Model

Assessment of Groundwater Suceptiability to Nitrate Contamination Using GIS-Based Modified DRASTIC Model in the Rib Watershed, upper Abay Basin, Ethiopia

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