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Analysis of the Saltwater Wedge in a Coastal Karst Aquifer with a Double Conduit Network, Numerical Simulations and Sensitivity Analysis
Article

Mapping of Groundwater Spring Potential in Karst Aquifer System Using Novel Ensemble Bivariate and Multivariate Models

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Geographic Information Science Research Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam
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Faculty of Environment and Labour Safety, Ton Duc Thang University, Ho Chi Minh City, Vietnam
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Soil Conservation and Watershed Management Research Department, Kurdistan Agricultural and Natural Resources Research and Education center, AREEO, Sanandaj 6616936311, Iran
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Department of Watershed Management, Faculty of Agriculture and Natural Resources, Lorestan University, Lorestan 68151-44316, Iran
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Young Researchers and Elite Club, Zahedan branch, Islamic Azad University, Zahedan 9816743545, Iran
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Department of Civil, Environmental and Natural Resources Engineering, Lulea University of Technology, 971 87 Lulea, Sweden
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Department of Geomorphology, Faculty of Natural Resources, University of Kurdistan, Sanandaj 66177-15175, Iran
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Board Member of Department of Zrebar Lake Environmental Research, Kurdistan Studies Institute, University of Kurdistan, Sanandaj 66177-15175, Iran
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Department of Rangeland and Watershed Management, Faculty of Natural Resources, University of Kurdistan, Sanandaj 66177-15175, Iran
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Faculty of Mechanical Engineering, Kazimierz Pulaski University of Technology and Humanities in Radom, Chrobrego 45 Street, 26-200 Radom, Poland
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Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
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Department of Geoinformation, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Malaysia
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Authors to whom correspondence should be addressed.
Water 2020, 12(4), 985; https://doi.org/10.3390/w12040985
Received: 3 March 2020 / Revised: 26 March 2020 / Accepted: 27 March 2020 / Published: 31 March 2020
(This article belongs to the Special Issue Groundwater Modelling in Karst Areas)
Groundwater is an important natural resource in arid and semi-arid environments, where discharge from karst springs is utilized as the principal water supply for human use. The occurrence of karst springs over large areas is often poorly documented, and interpolation strategies are often utilized to map the distribution and discharge potential of springs. This study develops a novel method to delineate karst spring zones on the basis of various hydrogeological factors. A case study of the Bojnourd Region, Iran, where spring discharge measurements are available for 359 sites, is used to demonstrate application of the new approach. Spatial mapping is achieved using ensemble modelling, which is based on certainty factors (CF) and logistic regression (LR). Maps of the CF and LR components of groundwater potential were generated individually, and then, combined to prepare an ensemble map of the study area. The accuracy (A) of the ensemble map was then assessed using area under the receiver operating characteristic curve. Results of this analysis show that LR (A = 78%) outperformed CF (A = 67%) in terms of the comparison between model predictions and known occurrences of karst springs (i.e., calibration data). However, combining the CF and LR results through ensemble modelling produced superior accuracy (A = 85%) in terms of spring potential mapping. By combining CF and LR statistical models through ensemble modelling, weaknesses in CF and LR methods are offset, and therefore, we recommend this ensemble approach for similar karst mapping projects. The methodology developed here offers an efficient method for assessing spring discharge and karst spring potentials over regional scales. View Full-Text
Keywords: ensemble model; karst springs; certainty factor; logistic regression; GIS ensemble model; karst springs; certainty factor; logistic regression; GIS
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MDPI and ACS Style

Nhu, V.-H.; Rahmati, O.; Falah, F.; Shojaei, S.; Al-Ansari, N.; Shahabi, H.; Shirzadi, A.; Górski, K.; Nguyen, H.; Ahmad, B.B. Mapping of Groundwater Spring Potential in Karst Aquifer System Using Novel Ensemble Bivariate and Multivariate Models. Water 2020, 12, 985. https://doi.org/10.3390/w12040985

AMA Style

Nhu V-H, Rahmati O, Falah F, Shojaei S, Al-Ansari N, Shahabi H, Shirzadi A, Górski K, Nguyen H, Ahmad BB. Mapping of Groundwater Spring Potential in Karst Aquifer System Using Novel Ensemble Bivariate and Multivariate Models. Water. 2020; 12(4):985. https://doi.org/10.3390/w12040985

Chicago/Turabian Style

Nhu, Viet-Ha, Omid Rahmati, Fatemeh Falah, Saeed Shojaei, Nadhir Al-Ansari, Himan Shahabi, Ataollah Shirzadi, Krzysztof Górski, Hoang Nguyen, and Baharin B. Ahmad 2020. "Mapping of Groundwater Spring Potential in Karst Aquifer System Using Novel Ensemble Bivariate and Multivariate Models" Water 12, no. 4: 985. https://doi.org/10.3390/w12040985

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