Literature DB >> 30045486

A comparison study of DRASTIC methods with various objective methods for groundwater vulnerability assessment.

Khabat Khosravi1, Majid Sartaj2, Frank T-C Tsai3, Vijay P Singh4, Nerantzis Kazakis5, Assefa M Melesse6, Indra Prakash7, Dieu Tien Bui8, Binh Thai Pham9.   

Abstract

Groundwater vulnerability assessment is a measure of potential groundwater contamination for areas of interest. The main objective of this study is to modify original DRASTIC model using four objective methods, Weights-of-Evidence (WOE), Shannon Entropy (SE), Logistic Model Tree (LMT), and Bootstrap Aggregating (BA) to create a map of groundwater vulnerability for the Sari-Behshahr plain, Iran. The study also investigated impact of addition of eight additional factors (distance to fault, fault density, distance to river, river density, land-use, soil order, geological time scale, and altitude) to improve groundwater vulnerability assessment. A total of 109 nitrate concentration data points were used for modeling and validation purposes. The efficacy of the four methods was evaluated quantitatively using the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC). AUC value for original DRASTIC model without any modification of weights and rates was 0.50. Modification of weights and rates resulted in better performance with AUC values of 0.64, 0.65, 0.75, and 0.81 for BA, SE, LMT, and WOE methods, respectively. This indicates that performance of WOE is the best in assessing groundwater vulnerability for DRASTIC model with 7 factors. The results also show more improvement in predictability of the WOE model by introducing 8 additional factors to the DRASTIC as AUC value increased to 0.91. The most effective contributing factor for ground water vulnerability in the study area is the net recharge. The least effective factors are the impact of vadose zone and hydraulic conductivity.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Bootstrap Aggregating; DRASTIC; Groundwater vulnerability; Logistic Model Tree; Shannon Entropy; Weights-of-Evidence

Year:  2018        PMID: 30045486     DOI: 10.1016/j.scitotenv.2018.06.130

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  4 in total

1.  Vulnerability Assessment of Farmland Groundwater Pollution around Traditional Industrial Parks Based on the Improved DRASTIC Model-A Case Study in Shifang City, Sichuan Province, China.

Authors:  Yibo Zhang; Hao Qin; Guanping An; Tao Huang
Journal:  Int J Environ Res Public Health       Date:  2022-06-21       Impact factor: 4.614

2.  Groundwater Potential Mapping Combining Artificial Neural Network and Real AdaBoost Ensemble Technique: The DakNong Province Case-study, Vietnam.

Authors:  Phong Tung Nguyen; Duong Hai Ha; Abolfazl Jaafari; Huu Duy Nguyen; Tran Van Phong; Nadhir Al-Ansari; Indra Prakash; Hiep Van Le; Binh Thai Pham
Journal:  Int J Environ Res Public Health       Date:  2020-04-04       Impact factor: 3.390

3.  CEPS: An Open Access MATLAB Graphical User Interface (GUI) for the Analysis of Complexity and Entropy in Physiological Signals.

Authors:  David Mayor; Deepak Panday; Hari Kala Kandel; Tony Steffert; Duncan Banks
Journal:  Entropy (Basel)       Date:  2021-03-08       Impact factor: 2.524

4.  The Role of Plant Growth Promoting Rhizosphere Microbiome as Alternative Biofertilizer in Boosting Solanum melongena L. Adaptation to Salinity Stress.

Authors:  Souhair Mokabel; Zakia Olama; Safaa Ali; Rehab El-Dakak
Journal:  Plants (Basel)       Date:  2022-02-28
  4 in total

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