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Diriba D, Karuppannan S, Takele T, Husein M. Delineation of groundwater potential zonation using geoinformatics and AHP techniques with remote sensing data. Heliyon 2024; 10:e25532. [PMID: 38371977 PMCID: PMC10873671 DOI: 10.1016/j.heliyon.2024.e25532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 01/28/2024] [Accepted: 01/29/2024] [Indexed: 02/20/2024] Open
Abstract
Among all other valuable natural resources, groundwater is crucial for global economic growth and food security. This study aimed to delineate groundwater potential zones (GWPZ) in the Gidabo watershed of the Main Ethiopian Rift. The demand for groundwater supplies for various applications has risen recently in the watershed due to rapid population upsurge. An integrated Geographical Information System, Remote Sensing, and Analytical Hierarchy Process (AHP) has been utilized. Eight groundwater regulating factors, including rainfall, elevation, drainage density, soil types, lineament density, slope, lithology, and land use/land cover, have been taken in the analysis. To assign suitable weights to each factor, AHP was employed, as each element contributes differently to groundwater occurrence. The weighted overlay analysis (WOA) technique was then used in the ArcGIS environment to integrate all thematic layers and generate a GWPZ map. The delineated GWPZ in the watershed was classified into five categories. The poor GWPZ covered 18.7 %, the low GWPZ covered 33.8 %, the moderate GWPZ covered 23.4 %, the high GWPZ covered 18.1 %, and the very high GWPZ covered 5.8 % of the area. Well and spring data were used to validate the model, and the ROC (Receiver Operating Characteristic) curve method was applied. The results showed good accuracy of 76.8 %. The result of this research can be valuable for planning and managing groundwater resources in the Gidabo watershed.
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Affiliation(s)
- Dechasa Diriba
- Department of Geology, College of Natural and Computational Science, Dilla University, P.O. Box: 419, Dilla, Ethiopia
| | - Shankar Karuppannan
- Department of Applied Geology, School of Applied Natural Science, Adama Science and Technology University, Adama, P.O. Box: 1888, Ethiopia
- Department of Research Analytics, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, 600077, Tamil Nadu, India
| | - Tariku Takele
- Department of Geology, College of Natural and Computational Science, Dilla University, P.O. Box: 419, Dilla, Ethiopia
| | - Musa Husein
- Department of Geology, College of Natural and Computational Science, Dilla University, P.O. Box: 419, Dilla, Ethiopia
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Singh R, Pathak VK, Kumar R, Dikshit M, Aherwar A, Singh V, Singh T. A historical review and analysis on MOORA and its fuzzy extensions for different applications. Heliyon 2024; 10:e25453. [PMID: 38352792 PMCID: PMC10861981 DOI: 10.1016/j.heliyon.2024.e25453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 12/10/2023] [Accepted: 01/26/2024] [Indexed: 02/16/2024] Open
Abstract
Multi-criteria decision-making (MCDM) methods have been widely used among researchers to provide a trade-off solution between best and worst, considering conflicting criteria and sets of preferences. An efficient and systematic literature review of these methods is needed to maintain their application in distinctive domains. To this end, this paper presents a comprehensive and systematic literature survey on "multi-objective optimization by ratio analysis" (MOORA) method and its fuzzy extensions developed and discussed in recent years. This review includes articles categorized based on the publication name, publishing year, journal name, type of applications, and type of fuzzy extensions. In addition, this review will enhance the understanding of practitioners and decision-makers on the MOORA method, its development, fuzzy hybridization, different application areas, and future work. The study revealed that the MOORA technique was predominantly used with the TOPSIS approach, followed by the AHP and COPRAS methods. Furthermore, 76.28 % use single and hybridization approaches among all MOORA studies, while 23.72 % use MOORA in a fuzzy environment.
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Affiliation(s)
- Ramanpreet Singh
- Department of Mechanical Engineering, Manipal University Jaipur, Jaipur, Rajasthan, 303007, India
| | - Vimal Kumar Pathak
- Department of Mechanical Engineering, Manipal University Jaipur, Jaipur, Rajasthan, 303007, India
| | - Rakesh Kumar
- Department of Mechanical Engineering, Manipal University Jaipur, Jaipur, Rajasthan, 303007, India
| | - Mithilesh Dikshit
- Department of Mechanical & Aero-Space Engineering, Institute of Infrastructure, Technology, Research and Management, Ahmedabad, Gujarat, 380026, India
| | - Amit Aherwar
- Department of Mechanical Engineering, Madhav Institute of Technology and Science, Gwalior, 474005, India
| | - Vedant Singh
- Amrita School of Business, Amrita Vishwa Vidyapeetham, Bengaluru, 560035, India
| | - Tej Singh
- Savaria Institute of Technology, Faculty of Informatics, ELTE Eötvös Loránd University, Budapest 1117, Hungary
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Singha C, Swain KC, Pradhan B, Rusia DK, Moghimi A, Ranjgar B. Mapping groundwater potential zone in the subarnarekha basin, India, using a novel hybrid multi-criteria approach in Google earth Engine. Heliyon 2024; 10:e24308. [PMID: 38293330 PMCID: PMC10825493 DOI: 10.1016/j.heliyon.2024.e24308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/28/2023] [Accepted: 01/05/2024] [Indexed: 02/01/2024] Open
Abstract
Assessing groundwater potential for sustainable resource management is critically important. In addressing this concern, this study aims to advance the field by developing an innovative approach for Groundwater potential zone (GWPZ) mapping using advanced techniques, such as FuzzyAHP, FuzzyDEMATEL, and Logistic regression (LR) models. GWPZ was carried out by integrating various primary factors, such as hydrologic, soil permeability, morphometric, terrain distribution, and anthropogenic influences, incorporating twenty-seven individual criteria using multi-criteria decision models along with a hybrid approach for the Subarnarekha River basin, India, in Google earth engine (GEE). The predictive capability of the model was evaluated using a Multi-Collinearity test (VIF <10.0), followed by applying a random forest model, considering the weighted impact of the five primary factors. The hybrid model for GWPZ classification showed that 21.97 % (4256.3 km2) of the area exhibited very high potential, while 11.37 % (2202.1 km2) indicated very low potential for GW in this area. Validation of the groundwater level data from 72 observation wells, performed by the Area under receiver operating characteristic (AUROC) curve technique, yielded values ranging between 75 % and 78 % for different models, underscoring the robust predictability of GWPZ. The hybrid and LR-FuzzyAHP models demonstrated remarkable effectiveness in GWPZ mapping, indicating that the downstream and southern regions boast substantial groundwater potential attributed to alluvial soil and favorable recharge conditions. Conversely, the central part grapples with a scarcity of groundwater. It holds the potential to assist planners and managers in formulating strategies for managing groundwater levels and alleviating the impacts of future droughts.
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Affiliation(s)
- Chiranjit Singha
- Department of Agricultural Engineering, Institute of Agriculture, Visva-Bharati (A Central University), Sriniketan, 731236, West Bengal, India
| | - Kishore Chandra Swain
- Department of Agricultural Engineering, Institute of Agriculture, Visva-Bharati (A Central University), Sriniketan, 731236, West Bengal, India
| | - Biswajeet Pradhan
- Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Civil and Environmental Engineering, Faculty of Engineering and IT, University of Technology Sydney, Sydney, NSW 2007, Australia
- Earth Observation Centre, Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi 43600 UKM, Selangor, Malaysia
| | - Dinesh Kumar Rusia
- Department of Agricultural Engineering, Institute of Agriculture, Visva-Bharati (A Central University), Sriniketan, 731236, West Bengal, India
| | - Armin Moghimi
- Ludwig-Franzius-Institute for Hydraulic, Estuarine and Coastal Engineering, Leibniz University Hannover, Nienburger Str. 4, 30167 Hanover, Germany
| | - Babak Ranjgar
- Department of Energy, Politecnico di Milano, Via Privata Giuseppe La Masa, 34, 20156, Milan, Italy
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