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A comparison study of DRASTIC methods with various objective methods for groundwater vulnerability assessment.
Khosravi, Khabat; Sartaj, Majid; Tsai, Frank T-C; Singh, Vijay P; Kazakis, Nerantzis; Melesse, Assefa M; Prakash, Indra; Tien Bui, Dieu; Pham, Binh Thai.
Afiliação
  • Khosravi K; Faculty of Natural Resources, Sari Agricultural Science and Natural Resources University, Sari, Iran.
  • Sartaj M; Civil Engineering Department, University of Ottawa, Ottawa, Ontario K1N6N5, Canada.
  • Tsai FT; Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, USA.
  • Singh VP; Department of Biological and Agricultural Engineering & Zachry Department of Civil Engineering, Texas A & M University, USA.
  • Kazakis N; School of Geology, Aristotle University of Thessaloniki, Greece.
  • Melesse AM; Department of Earth and Environment, AHC-5-390, Florida International University, USA.
  • Prakash I; Department of Science & Technology, Bhaskarcharya Institute for Space Applications and Geo-Informatics (BISAG), Gandhinagar, India.
  • Tien Bui D; Geographic Information System Group, Department of Business and IT, University of South-Eastern Norway, Gullbringvegen 36, N-3800 Bø i Telemark, Norway.
  • Pham BT; Geographic Information Science Research Group, Ton Duc Thang University, Ho Chi Minh City, Viet Nam; Faculty of Environment and Labour Safety, Ton Duc Thang University, Ho Chi Minh City, Viet Nam. Electronic address: phamthaibinh@tdt.edu.vn.
Sci Total Environ ; 642: 1032-1049, 2018 Nov 15.
Article em En | MEDLINE | ID: mdl-30045486
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Total Environ Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Irã

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Total Environ Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Irã