Groundwater vulnerability mapping of Jordanian phosphate mining area based on phosphate concentration and GIS: Al-Abiad mine as a case study

2019 ◽  
Vol 9 (6) ◽  
pp. 627
Author(s):  
Adnan Al Harahsheh ◽  
Majed Ibrahim ◽  
Noureddine Elboughdiri ◽  
Mohammad Al Harahsheh ◽  
Salah Aljbour
Keyword(s):  
Groundwater Vulnerability ◽  
Mining Area ◽  
Phosphate Concentration ◽  
Vulnerability Mapping ◽  
Phosphate Mining ◽  
Groundwater Vulnerability Mapping

Groundwater vulnerability mapping using the Susceptibility Index (SI) method: Case study of Takelsa aquifer, Northeastern Tunisia

2021 ◽  
Vol 173 ◽  
pp. 104035
Author(s):  
Nesrine Ghouili ◽  
Faten Jarraya-Horriche ◽  
Fadoua Hamzaoui-Azaza ◽  
Mohamed Faouzi Zaghrarni ◽  
Luís Ribeiro ◽  
...  
Keyword(s):  
Groundwater Vulnerability ◽  
Vulnerability Mapping ◽  
Susceptibility Index ◽  
Groundwater Vulnerability Mapping ◽  
Northeastern Tunisia

scholarly journals 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 ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1288
Author(s):  
Husam Musa Baalousha ◽  
Bassam Tawabini ◽  
Thomas D. Seers
Keyword(s):  
Fuzzy Logic ◽  
Numerical Model ◽  
Vulnerability Assessment ◽  
Anthropogenic Impacts ◽  
Groundwater Vulnerability ◽  
Vulnerability Mapping ◽  
Anthropogenic Contamination ◽  
Weighted Overlay ◽  
Vulnerability Maps

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.

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