Literature DB >> 11447862

Calibration of the DRASTIC ground water vulnerability mapping method.

M G Rupert1.   

Abstract

Ground water vulnerability maps developed using the DRASTIC method have been produced in many parts of the world. Comparisons of those maps with actual ground water quality data have shown that the DRASTIC method is typically a poor predictor of ground water contamination. This study significantly improved the effectiveness of a modified DRASTIC ground water vulnerability map by calibrating the point rating schemes to actual ground water quality data by using nonparametric statistical techniques and a geographic information system. Calibration was performed by comparing data on nitrite plus nitrate as nitrogen (NO2 + NO3-N) concentrations in ground water to land-use, soils, and depth to first-encountered ground water data. These comparisons showed clear statistical differences between NO2 + NO3-N concentrations and the various categories. Ground water probability point ratings for NO2 + NO3-N contamination were developed from the results of these comparisons, and a probability map was produced. This ground water probability map was then correlated with an independent set of NO2 + NO3-N data to demonstrate its effectiveness in predicting elevated NO2 + NO3-N concentrations in ground water. This correlation demonstrated that the probability map was effective, but a vulnerability map produced with the uncalibrated DRASTIC method in the same area and using the same data layers was not effective. Considerable time and expense have been out-laid to develop ground water vulnerability maps with the DRASTIC method. This study demonstrates a cost-effective method to improve and verify the effectiveness of ground water vulnerability maps.

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Year:  2001        PMID: 11447862     DOI: 10.1111/j.1745-6584.2001.tb02350.x

Source DB:  PubMed          Journal:  Ground Water        ISSN: 0017-467X            Impact factor:   2.671


  6 in total

1.  Using GA-Ridge regression to select hydro-geological parameters influencing groundwater pollution vulnerability.

Authors:  Jae Joon Ahn; Young Min Kim; Keunje Yoo; Joonhong Park; Kyong Joo Oh
Journal:  Environ Monit Assess       Date:  2011-11-29       Impact factor: 2.513

2.  Application of drastic model and GIS: for assessing vulnerability in hard rock granitic aquifer.

Authors:  Ranjeet Kumar Prasad; V S Singh; S K G Krishnamacharyulu; Pallavi Banerjee
Journal:  Environ Monit Assess       Date:  2010-06-29       Impact factor: 2.513

3.  Mapping of coastal aquifer vulnerable zone in the south west coast of Kanyakumari, South India, using GIS-based DRASTIC model.

Authors:  S Kaliraj; N Chandrasekar; T Simon Peter; S Selvakumar; N S Magesh
Journal:  Environ Monit Assess       Date:  2014-11-19       Impact factor: 2.513

4.  Environmental indicators to assess the risk of diffuse Nitrogen losses from agriculture.

Authors:  Uwe Buczko; Rolf O Kuchenbuch
Journal:  Environ Manage       Date:  2010-03-20       Impact factor: 3.266

5.  Identification of dominating factors affecting vadose zone vulnerability by a simulation method.

Authors:  Juan Li; Beidou Xi; Wutian Cai; Yang Yang; Yongfeng Jia; Xiang Li; Yonggao Lv; Ningqing Lv; Huan Huan; Jinjin Yang
Journal:  Sci Rep       Date:  2017-04-07       Impact factor: 4.379

6.  Groundwater vulnerability to pollution mapping of Ranchi district using GIS.

Authors:  R Krishna; J Iqbal; A K Gorai; G Pathak; F Tuluri; P B Tchounwou
Journal:  Appl Water Sci       Date:  2014-05-17
  6 in total

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