Fuzzy or Non-Fuzzy? A Comparison between Fuzzy Logic-Based Vulnerability Mapping and DRASTIC Approach Using a Numerical Model. A Case Study from Qatar
Vulnerability maps are useful for groundwater protection, water resources development, and land use management. The literature contains various approaches for intrinsic vulnerability assessment, and they mainly depend on hydrogeological settings and anthropogenic impacts. Most methods assign certain...
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doaj-32f8bb03af9b43388e06ec6318da89c42021-05-31T23:03:53ZengMDPI AGWater2073-44412021-05-01131288128810.3390/w13091288Fuzzy or Non-Fuzzy? A Comparison between Fuzzy Logic-Based Vulnerability Mapping and DRASTIC Approach Using a Numerical Model. A Case Study from QatarHusam Musa Baalousha0Bassam Tawabini1Thomas D. Seers2Petroleum Engineering Program, Texas A&M University at Qatar, Education City, Doha P.O. Box 23874, QatarDepartment of Geosciences, College of Petroleum Engineering and Geosciences, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi ArabiaPetroleum Engineering Program, Texas A&M University at Qatar, Education City, Doha P.O. Box 23874, QatarVulnerability maps are useful for groundwater protection, water resources development, and land use management. The literature contains various approaches for intrinsic vulnerability assessment, and they mainly depend on hydrogeological settings and anthropogenic impacts. Most methods assign certain ratings and weights to each contributing factor to groundwater vulnerability. Fuzzy logic (FL) is an alternative artificial intelligence tool for overlay analysis, where spatial properties are fuzzified. Unlike the specific rating used in the weighted overlay-based vulnerability mapping methods, FL allows more flexibility through assigning a degree of contribution without specific boundaries for various classes. This study compares the results of DRASTIC vulnerability approach with the FL approach, applying both on Qatar aquifers. The comparison was checked and validated against a numerical model developed for the same study area, and the actual anthropogenic contamination load. Results show some similarities and differences between both approaches. While the coastal areas fall in the same category of high vulnerability in both cases, the FL approach shows greater variability than the DRASTIC approach and better matches with model results and contamination load. FL is probably better suited for vulnerability assessment than the weighted overlay methods.https://www.mdpi.com/2073-4441/13/9/1288artificial intelligencefuzzy logicsolute transportgroundwater vulnerabilityDRASTICQatar |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Husam Musa Baalousha Bassam Tawabini Thomas D. Seers |
spellingShingle |
Husam Musa Baalousha Bassam Tawabini Thomas D. Seers Fuzzy or Non-Fuzzy? A Comparison between Fuzzy Logic-Based Vulnerability Mapping and DRASTIC Approach Using a Numerical Model. A Case Study from Qatar Water artificial intelligence fuzzy logic solute transport groundwater vulnerability DRASTIC Qatar |
author_facet |
Husam Musa Baalousha Bassam Tawabini Thomas D. Seers |
author_sort |
Husam Musa Baalousha |
title |
Fuzzy or Non-Fuzzy? A Comparison between Fuzzy Logic-Based Vulnerability Mapping and DRASTIC Approach Using a Numerical Model. A Case Study from Qatar |
title_short |
Fuzzy or Non-Fuzzy? A Comparison between Fuzzy Logic-Based Vulnerability Mapping and DRASTIC Approach Using a Numerical Model. A Case Study from Qatar |
title_full |
Fuzzy or Non-Fuzzy? A Comparison between Fuzzy Logic-Based Vulnerability Mapping and DRASTIC Approach Using a Numerical Model. A Case Study from Qatar |
title_fullStr |
Fuzzy or Non-Fuzzy? A Comparison between Fuzzy Logic-Based Vulnerability Mapping and DRASTIC Approach Using a Numerical Model. A Case Study from Qatar |
title_full_unstemmed |
Fuzzy or Non-Fuzzy? A Comparison between Fuzzy Logic-Based Vulnerability Mapping and DRASTIC Approach Using a Numerical Model. A Case Study from Qatar |
title_sort |
fuzzy or non-fuzzy? a comparison between fuzzy logic-based vulnerability mapping and drastic approach using a numerical model. a case study from qatar |
publisher |
MDPI AG |
series |
Water |
issn |
2073-4441 |
publishDate |
2021-05-01 |
description |
Vulnerability maps are useful for groundwater protection, water resources development, and land use management. The literature contains various approaches for intrinsic vulnerability assessment, and they mainly depend on hydrogeological settings and anthropogenic impacts. Most methods assign certain ratings and weights to each contributing factor to groundwater vulnerability. Fuzzy logic (FL) is an alternative artificial intelligence tool for overlay analysis, where spatial properties are fuzzified. Unlike the specific rating used in the weighted overlay-based vulnerability mapping methods, FL allows more flexibility through assigning a degree of contribution without specific boundaries for various classes. This study compares the results of DRASTIC vulnerability approach with the FL approach, applying both on Qatar aquifers. The comparison was checked and validated against a numerical model developed for the same study area, and the actual anthropogenic contamination load. Results show some similarities and differences between both approaches. While the coastal areas fall in the same category of high vulnerability in both cases, the FL approach shows greater variability than the DRASTIC approach and better matches with model results and contamination load. FL is probably better suited for vulnerability assessment than the weighted overlay methods. |
topic |
artificial intelligence fuzzy logic solute transport groundwater vulnerability DRASTIC Qatar |
url |
https://www.mdpi.com/2073-4441/13/9/1288 |
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