Optimization of statistical and machine learning hybrid models for groundwater potential mapping

Yariyan, Peyman; Avand, Mohammadtaghi; Omidvar, Ebrahim; Pham, Quoc Bao; Linh, Nguyễn Thị Thùy; Tiefenbacher, John P.

doi:10.1080/10106049.2020.1870164

Cited by 37 publications

(12 citation statements)

References 91 publications

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“…Thus, areas of sand accumulation would be considered the prime zones of water accumulation as they lose sediments that hold the amount of precipitated water during rainy storms in arid regions [2,7]. Therefore, the present study classified data, by Arc GIS software (Esri, Redlands, CA, USA) packages, into four zones, viz., low (2), moderate (3), high (5), and very high (8). It is worth noting that the classes from lower to higher potentiality cover 3.91%, 21.17, 47.18, and 27.74% of the entire area (Figure 4b; Table 3).…”

Section: Radar Intensitymentioning

confidence: 98%

“…Increase in the demand for freshwater worldwide calls for revealing new water resources through applying geological, geophysical, and remote sensing techniques. It is a great challenge to secure additional source of waters as they relate to climatic, hydrologic, and topographic conditions [8]. Climate change has been noticeably realized worldwide [9,10] and it impacts the spatial distribution of rainfall intensity, as climate conditions and geomorphic and physical characteristics of the catchments [11][12][13] control the occurrence of water resources.…”

Section: Introductionmentioning

confidence: 99%

“…The areas of low elevations are positively related to infiltration, particularly depression areas [2,7]. The variation in elevations generates slope, which is an important factor in controlling the runoff, and infiltration capacity for revealing GWPZs due to its indication of the gradient in the elevations of the catchments [8,13], the speed of runoff, and infiltration capabilities [2,8]. Moreover, land surface curvature represents the morphology of the land surface, which is an important factor that is connected to accumulation, infiltration, and runoff on the slope [8,37,38].…”

Section: Introductionmentioning

confidence: 99%

“…The variation in elevations generates slope, which is an important factor in controlling the runoff, and infiltration capacity for revealing GWPZs due to its indication of the gradient in the elevations of the catchments [8,13], the speed of runoff, and infiltration capabilities [2,8]. Moreover, land surface curvature represents the morphology of the land surface, which is an important factor that is connected to accumulation, infiltration, and runoff on the slope [8,37,38]. The topographic wetness index (TWI) is also utilized to evaluate topographic influences in understanding hydrological conditions.…”

Section: Introductionmentioning

confidence: 99%

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Fusion of Remote Sensing Data Using GIS-Based AHP-Weighted Overlay Techniques for Groundwater Sustainability in Arid Regions

et al. 2022

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Remote sensing and GIS approaches have provided valuable information on modeling water resources, particularly in arid regions. The Sahara of North Africa, which is one of the driest regions on Earth, experienced several pluvial conditions in the past that could have stored significant amounts of groundwater. Thus, harvesting the stored water by revealing the groundwater prospective zones (GWPZs) is highly important to water security and the management of water resources which are necessary for sustainable development in such regions. The Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM), Advanced Land Observing Satellite (ALOS)/Phased Array type L-band Synthetic Aperture Radar (PALSAR), Tropical Rainfall Measuring Mission (TRMM), and Landsat-8 OLI data have all successfully revealed the geologic, geomorphic, climatic, and hydrologic features of Wadi El-Tarfa east of Egypt’s Nile River. The fusion of eleven predictive GIS maps including lithology, radar intensity, lineament density, altitude, slope, depressions, curvature, topographic wetness index (TWI), drainage density, runoff, and rainfall data, after being ranked and normalized through the GIS-based analytic hierarchy process (AHP) and weighted overlay methods, allowed the GWPZs to be demarcated. The resulting GWPZs map was divided into five classes: very high, high, moderate, low, and very low potentiality, which cover about 10.32, 24.98, 30.47, 24.02, and 10.20% of the entire basin area, respectively. Landsat-8 and its derived NDVI that was acquired on 15 March 2014, after the storm of 8–9 March 2014, along with existing well locations validated the GWPZs map. The overall results showed that an integrated approach of multi-criteria through a GIS-based AHP has the capability of modeling groundwater resources in arid regions. Additionally, probing areas of GWPZs is helpful to planners and decision-makers dealing with the development of arid regions.

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Section: Radar Intensitymentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fusion of Remote Sensing Data Using GIS-Based AHP-Weighted Overlay Techniques for Groundwater Sustainability in Arid Regions

et al. 2022

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“…The last decade has seen increased computational intelligence to solve problems that lack a definite solution or are difficult to solve. The human biological neural network inspires artificial neural networks (ANNs), and research on neural networks has been accompanied by an understanding and study of the human brain's structure and learning function [46]. There is no requirement for a set of special rules to solve the problem in this computational method, and the primary reliance is on the system's gradual training and learning [47].…”

Section: Multi-layer Perceptron (Mlp)mentioning

confidence: 99%

A GIS-Based Assessment of Urban Tourism Potential with a Branding Approach Utilizing Hybrid Modeling

2022

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Urban tourism has developed into one of the most efficient and effective economic and recreational activities in the modern era since the late second half of the twentieth century. Although attention to urban tourism development is increasing, this paper indicates that no comprehensive study has yet combined the two subjects of tourism development and branding for spatial modeling. Thus, for assessing urban tourism potential (AUTP), a novel hybrid modeling approach combining K-mean, fuzzy logic, and an artificial neural network (ANN) was used. The findings indicate that in Tabriz metropolis, areas 3 and 7 and the southwestern portion of region 6 have the most significant potential for urban tourism. In contrast, areas 4, 8, and 10 located within the worn-out urban fabric have the least potential for tourism. Subsequently, by examining the correlation between urban tourism conditioning factors (UTCFs) and tourism maps, it was determined that factors including distance from the catering centers, distance from the fault, quality of construction materials, distance from the historical centers, distance from the health centers, maximum temperature, and distance from the parking are the most critical in terms of increasing urban tourism's potential and branding. The analyses conducted in this study provide valuable and practical information for developing future strategies urban tourism. To this end, recommendations have been made to enhance tourism destination service delivery and management through branding.

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A Comprehensive Review on Mapping of Groundwater Potential Zones: Past, Present and Future Recommendations

et al. 2023

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Optimization of statistical and machine learning hybrid models for groundwater potential mapping

Cited by 37 publications

References 91 publications

Fusion of Remote Sensing Data Using GIS-Based AHP-Weighted Overlay Techniques for Groundwater Sustainability in Arid Regions

Fusion of Remote Sensing Data Using GIS-Based AHP-Weighted Overlay Techniques for Groundwater Sustainability in Arid Regions

A GIS-Based Assessment of Urban Tourism Potential with a Branding Approach Utilizing Hybrid Modeling

A Comprehensive Review on Mapping of Groundwater Potential Zones: Past, Present and Future Recommendations

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