Groundwater vulnerability assessment in shallow aquifer of Kathmandu Valley using GIS-based DRASTIC model

Pathak, Dhundi Raj; Hiratsuka, Akira; Awata, Isao; Chen, Luonan

doi:10.1007/s00254-008-1432-8

Cited by 106 publications

(44 citation statements)

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“…This method relies heavily on the analysts' subjective judgements regarding the relevance of each of the variables for the pollution potential, by assessing its contribution to the hydrological processes that determine the fate of pollutants. Thus, the results have been questioned by some researchers who had attempted to improve the DRASTIC index system (Napolitano and Fabbri 1996, Gogu and Dassargues 2000, Di Martino et al 2005, Panagopoulos et al 2006, Mohammadi et al 2009, Pathak et al 2009). The uncertainty of the DRASTIC method mainly comes from the subjective nature of assigning weights and ratings, as shown in equation (1).…”

Section: Classic Drastic and Fuzzy-optimization Methodsmentioning

confidence: 99%

“…It has been successfully applied to many different geographical locations in the world, including the USA (Loague et al 1996, Frind et al 2006, Japan (Babiker et al 2005, Pathak et al 2009), Europe (Crema et al 1998, Di Martino et al 2005, Panagopoulos et al 2006, South Korea (Kim andHamm 1999, Lee 2003), South Africa (Lynch et al 1994), Iran (Mohammadi et al 2009) and China (Chen and Fu 2003, Wang et al 2007, Yu et al 2010.…”

Section: Introductionmentioning

confidence: 99%

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A field demonstration of the entropy-weighted fuzzy DRASTIC method for groundwater vulnerability assessment

Chen

Zhang

Yao

et al. 2012

Hydrological Sciences Journal

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., 2012. A field demonstration of the entropy-weighted fuzzy DRASTIC method for groundwater vulnerability assessment. Hydrological Sciences Journal, 57 (7), 1420-1432.Abstract Groundwater vulnerability assessment based on the DRASTIC index has been widely used since the 1980s to map potential risks of groundwater contamination. However, its applicability and usefulness are affected by two uncertain and subjective factors. One is the discretization of continuous input variables and the other is the assignment of different weights to the index variables. In this study, an entropy-weighted fuzzy-optimization approach was developed to augment and improve the classic DRASTIC method by reducing the uncertainties associated with variable discretization and weight assignment. The modified DRASTIC method was applied to a study site in Shandong, north China. The entropy-weighted fuzzy-optimization approach is shown to provide a more rigorous delineation of the relative vulnerability distribution. Meanwhile, the new approach does not require the use of more parameters. The results suggest that this approach significantly improves and enhances the ability of the classic DRASTIC method in a more systematic and rigorous way.Key words groundwater vulnerability; DRASTIC index; entropy-weighted fuzzy optimization; sensitivity analysis Une démonstration de terrain de la méthode DRASTIC floue pondérée par l'entropie pour l'évaluation de la vulnérabilité des eaux souterraines Résumé L'évaluation de la vulnérabilité des eaux souterraines sur la base de l'indice DRASTIC a été largement utilisée depuis les années 1980 pour la cartographie des risques potentiels de pollution des eaux souterraines. Son applicabilité et son utilité sont cependant affectées par les deux facteurs que sont l'incertitude et la subjectivité. Il faut d'abord discrétiser les variables d'entrée continues, puis attribuer des poids aux variables de l'indice. Dans cette étude, nous avons adopté une approche d'optimisation floue pondérée par l'entropie, afin d'élargir et d'améliorer la méthode DRASTIC classique en réduisant les incertitudes liées à la discrétisation des variables et à l'attribution des poids. La méthode DRASTIC modifiée a été appliquée à un site d'étude dans le Shandong, au Nord de la Chine. L'approche d'optimisation floue pondérée par l'entropie s'est révélée fournir une définition plus rigoureuse de la distribution relative de vulnérabilité. En même temps, la nouvelle approche ne nécessite pas d'utiliser davantage de paramètres. Les résultats suggèrent que cette approche améliore significativement et de façon systématique et rigoureuse le potentiel de la méthode DRASTIC classique.

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Section: Classic Drastic and Fuzzy-optimization Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A field demonstration of the entropy-weighted fuzzy DRASTIC method for groundwater vulnerability assessment

Chen

Zhang

Yao

et al. 2012

Hydrological Sciences Journal

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“…For instance, we know that for vulnerability evaluation, when the water ta- Figure 8. Flow chart of methodology adopted to develop the groundwater contamination potential map using DRASTIC and fuzzy pattern recognition models in the framework of GIS (source Pathak et al, 2009). ble is shallow, the recharge rate is high, and if aquifer and soil materials are coarser, groundwater potential for pollution is higher. Also if the hydraulic conductivity, recharge rate and slope are low then the groundwater potential for pollution is low.…”

Section: Vulnerability Assessment By the Fuzzy Methodsmentioning

confidence: 99%

“…For example, membership expresses the relations between two given parameters and also the degree of truth or falseness of these relations (Pacheco et al, 2015;Madhumita et al, 2016). This technique has been used by many authors -such as Pacheco et al (2015), Madhumita et al (2016), Pathak et al (2009), Sahoo et al (2016a, Saidi et al (2011) and Sener et al (2013) -but most of these studies assessed pollution risk Van der Weijden, 2011, 2012) and did not compare intrinsic with specific vulnerability or different types of sensitivity analyses with memberships to identify parameter impact on groundwater vulnerability to pollution.…”

mentioning

confidence: 99%

A novel method of sensitivity analysis testing by applying the DRASTIC and fuzzy optimization methods to assess groundwater vulnerability to pollution: the case of the Senegal River basin in Mali

Keita

Tang

2017

Nat. Hazards Earth Syst. Sci.

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Abstract. Vulnerability to groundwater pollution in the Senegal River basin was studied by two different but complementary methods: the DRASTIC method (which evaluates the intrinsic vulnerability) and the fuzzy method (which assesses the specific vulnerability by taking into account the continuity of the parameters). The validation of this application has been tested by comparing the connection in groundwater and distribution of different established classes of vulnerabilities as well as the nitrate distribution in the study area. Three vulnerability classes (low, medium and high) have been identified by both the DRASTIC method and the fuzzy method (between which the normalized model was used). An integrated analysis reveals that high classes with 14.64 % (for the DRASTIC method), 21.68 % (for the normalized DRAS-TIC method) and 18.92 % (for the fuzzy method) are not the most dominant. In addition, a new method for sensitivity analysis was used to identify (and confirm) the main parameters which impact the vulnerability to pollution with fuzzy membership. The results showed that the vadose zone is the main parameter which impacts groundwater vulnerability to pollution while net recharge contributes least to pollution in the study area. It was also found that the fuzzy method better assesses the vulnerability to pollution with a coincidence rate of 81.13 % versus that of 77.35 % for the DRASTIC method. These results serve as a guide for policymakers to identify areas sensitive to pollution before such sites are used for socioeconomic infrastructures.

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“…However, acceptable estimate of static groundwater storage could be made with relatively fewer resources using readily available secondary data, information and geographic information system (GIS) tool(s). GIS and GIS-based tools are widely used in groundwater studies to analyze and visualize results of groundwater vulnerability (e.g., Kattaa et al 2010;Nobre et al 2007;Pathak et al 2009), groundwater storage potential (e.g., Singh and Prakash 2002;Wahyuni et al 2008), groundwater flow and contaminant transport modeling (e.g. Akbar et al 2011;Chenini and Mammou 2010), among others.…”

Section: Introductionmentioning

confidence: 99%

A GIS-based methodology to delineate potential areas for groundwater development: a case study from Kathmandu Valley, Nepal

2013

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For an effective planning of activities aimed at recovering aquifer depletion and maintaining health of groundwater ecosystem, estimates of spatial distribution in groundwater storage volume would be useful. The estimated volume, if analyzed together with other hydrogeologic characteristics, may help delineate potential areas for groundwater development. This study proposes a GIS-based ARC model to delineate potential areas for groundwater development; where 'A' stands for groundwater availability, 'R' for groundwater release potential of soil matrix, and 'C' for cost for groundwater development. The model is illustrated with a case of the Kathmandu Valley in Central Nepal, where active discussions are going on to develop and implement groundwater management strategies. The study results show that shallow aquifers have high groundwater storage potential (compared to the deep) and favorable areas for groundwater development are concentrated at some particular areas in shallow and deep aquifers. The distribution of groundwater storage and potential areas for groundwater development are then mapped using GIS.

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Groundwater vulnerability assessment in shallow aquifer of Kathmandu Valley using GIS-based DRASTIC model

Cited by 106 publications

References 4 publications

A field demonstration of the entropy-weighted fuzzy DRASTIC method for groundwater vulnerability assessment

A field demonstration of the entropy-weighted fuzzy DRASTIC method for groundwater vulnerability assessment

A novel method of sensitivity analysis testing by applying the DRASTIC and fuzzy optimization methods to assess groundwater vulnerability to pollution: the case of the Senegal River basin in Mali

A GIS-based methodology to delineate potential areas for groundwater development: a case study from Kathmandu Valley, Nepal

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