Groundwater vulnerability assessment in agricultural areas using a modified DRASTIC model

Sadat‐Noori, Mahmood; Ebrahimi, Kumars

doi:10.1007/s10661-015-4915-6

Cited by 44 publications

(22 citation statements)

References 36 publications

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“…chloride [Cl]) in different hydrogeologic settings to further explore their potential to establish reliable groundwater vulnerability maps. Previously, Sadat‐Noori and Ebrahimi () employed the Wilcoxon test for the modification of the DRASTIC framework in the Saveh‐Nobaran plain aquifer in Iran, using Cl concentrations. This study showed that the R 2 between the Cl concentration data and the modified vulnerability index increased significantly, from 0.52 to 0.78.…”

Section: Resultsmentioning

confidence: 99%

Modification of the DRASTIC Framework for Mapping Groundwater Vulnerability Zones

et al. 2019

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The DRASTIC technique is commonly used to assess groundwater vulnerability. The main disadvantage of the DRASTIC method is the difficulty associated with identifying appropriate ratings and weight assignments for each parameter. To mitigate this issue, ratings and weights can be approximated using different methods appropriate to the conditions of the study area. In this study, different linear (i.e., Wilcoxon test and statistical approaches) and nonlinear (Genetic algorithm [GA]) modifications for calibration of the DRASTIC framework using nitrate (NO 3 ) concentrations were compared through the preparation of groundwater vulnerability maps of the Meshqin-Shahr plain, Iran. Twenty-two groundwater samples were collected from wells in the study area, and their respective NO 3 concentrations were used to modify the ratings and weights of the DRASTIC parameters. The areas found to have the highest vulnerability were in the eastern, central, and western regions of the plain. Results showed that the modified DRASTIC frameworks performed well, compared to the unmodified DRASTIC. When measured NO 3 concentrations were correlated with the vulnerability indices produced by each method, the unmodified DRASTIC method performed most poorly, and the Wilcoxon-GA-DRASTIC method proved optimal. Compared to the unmodified DRASTIC method with an R 2 of 0.22, the Wilcoxon-GA-DRASTIC obtained a maximum R 2 value of 0.78. Modification of DRASTIC parameter ratings was found to be more efficient than the modification of the weights in establishing an accurately calibrated DRASTIC framework. However, modification of parameter ratings and weights together increased the R 2 value to the highest degree. Article impact statement: The results showed that both linear and nonlinear methods are useful in modifying the ratings and weights of the DRASTIC method for assessing the groundwater vulnerability.

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Section: Resultsmentioning

confidence: 99%

Modification of the DRASTIC Framework for Mapping Groundwater Vulnerability Zones

et al. 2019

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“…Transmissivity was obtained from the pumping tests. This approach has been applied in different studies (Saidi et al 2010;Sadat-Noori and Ebrahimi 2015).…”

Section: Structure Of Each Model For Evaluating Drastic Indicesmentioning

confidence: 99%

“…The vulnerability indices have been correlated with nitrate concentrations and/or controlled with sensitivity analysis in most of the previous studies (Rupert 2001;Huan et al 2012;Neshat et al 2014a;Pacheco et al 2014;Ahmed et al 2015;Vaezihir and Tabarmayeh 2015). Recent researchers made alteration to rating scales to adjust the model by data interpolation (kriging method) using ArcGIS® (Ahmed et al 2015;Vaezihir and Tabarmayeh 2015;Sadat-Noori and Ebrahimi 2015). In addition, modifying the model with omitting or adding layers such as land use pattern to estimate contamination risk to pollutants mostly nitrate (Panagopoulos et al 2006;Bai et al 2012;Huan et al 2012;Neshat et al 2014a;Ahmed et al 2015;Kazakis and Voudouris 2015;Vaezihir and Tabarmayeh 2015) or applying analytic hierarchy process (AHP), a multiple criteria decision-making (MCDM) technique, to adjust weights of the DRASTIC parameters to local settings have become prevalent (Sener and Davraz 2013;Neshat and Pradhan 2014;Neshat et al 2014a).…”

Section: Introductionmentioning

confidence: 99%

Groundwater risk assessment based on optimization framework using DRASTIC method

Jafari

Nikoo

2016

Arab J Geosci

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Due to anthropogenic influences and large amounts of pollutant released into the groundwater, it is vital to investigate groundwater quality and to characterize susceptible areas to contamination. In this paper, a new optimizationbased methodology is proposed for determining groundwater risk using DRASTIC model based on genetic algorithm optimization model and Wilcoxon test. The correlation coefficient between DRASTIC/modified DRASTIC indices and nitrate concentrations in monitoring wells is used as a criteria for evaluating the efficiency of the proposed models. In this regard, because of the unsatisfactory original DRASTIC's result, sensitivity analysis, genetic algorithm (GA), and Wilcoxon test (1945) are carried out to tackle the subjectivity associated with the original DRASTIC model and obtain better and reliable results. The results indicate that application of Wilcoxon test and GA optimization outperforms the others. Consequently, the correlation coefficient increased remarkably as compared to the original DRASTIC model (from 0.57 to 0.82). The proposed optimization process is adaptable to be applied in different case studies; mainly since it has the ability to optimize the weights of the model based on hydrogeological characteristics of the aquifer. Finally, the risk maps of the models are prepared using ArcGIS® to determine the most vulnerable areas.

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“…However, reliable quantitative determination of groundwater pollution risk is difficult as it depends on many factors, some of the mhardly measurable, and thus assessments of groundwater pollution risk are usually qualitative instead quantitative. Some groundwater pollution risk assessments focus on the risk stemming from only one specific source of pollution, for example nitrates derived from agricultural fertilization [11][12][13][14][15][16][17][18][19], waste disposal sites [20,21], or even biofuel-related land use [22].…”

mentioning

confidence: 99%

“…Locally measured nitrate concentrations are usually taken as an indicator of current degradation of groundwater quality, such as in [11][12][13][14][15][16][17][18][19]. In this way, a purely theoretical possibility of occurrence of an unwanted event is linked with real facts.…”

mentioning

confidence: 99%

Groundwater Pollution Risk Assessment Based on Vulnerability to Pollution and Potential Impact of Land Use Forms

Duda¹,

Klebert²,

Zdechlik³

2019

Pol. J. Environ. Stud.

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Groundwater constitutes a natural source of fresh water, mainly used for consumption and communal purposes. Groundwater pollution risk is mainly related to hydrogeological factors, that is, vulnerability of groundwater to pollution and anthropogenic factors related to the land use forms, as described by [1-6], among others. When the areas of high groundwater pollution risk are indicated, appropriate preventative measures can be undertaken, as indicated for example by [7, 8]. Risk can be defined as the probability of an unwanted event that results in negative consequences, as stated by [9], among others. High probability, that is, high risk of contamination, can be achieved only when a highly vulnerable area has a high probability of exposure to contamination [10]. Moreover, it has been indicated that

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Groundwater vulnerability assessment in agricultural areas using a modified DRASTIC model

Cited by 44 publications

References 36 publications

Modification of the DRASTIC Framework for Mapping Groundwater Vulnerability Zones

Modification of the DRASTIC Framework for Mapping Groundwater Vulnerability Zones

Groundwater risk assessment based on optimization framework using DRASTIC method

Groundwater Pollution Risk Assessment Based on Vulnerability to Pollution and Potential Impact of Land Use Forms

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