GIS-based multi-criteria decision making and entropy approaches for groundwater potential zones delineation

Forootan, E.; Seyedi, Fakhrossadat

doi:10.1007/s12145-021-00576-8

Cited by 25 publications

(11 citation statements)

References 44 publications

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“…The ability of RS and GIS to gather, manipulate, and cover vast amounts of data in a short amount of time makes it a more effective tool for identifying, analyzing, and preserving groundwater resources. As a result, multiple data sources can be incorporated into a GIS platform to build conceptual models for identifying potential groundwater zones in a given area [31,32,37,44,45].…”

Section: Introductionmentioning

confidence: 99%

“…Incorporating RS and GIS into groundwater potentiality mapping allows for data storage, manipulation, and analysis [44,47]. Integrated GIS and RS with AHP prove that it is a handy tool for delineating potential groundwater zones by reducing time and cost [4,17,32,37,41,44,45,[48][49][50]. Researchers adopt various techniques for delineation potential groundwater zones: statistical method [51], influence factor (IMF) [36,38,40,52], groundwater modelling, the combination of GIS, RS with AHP [37,41,45,49], and GIS-based machine learning [39,53,54].…”

Section: Introductionmentioning

confidence: 99%

“…Integrated GIS and RS with AHP prove that it is a handy tool for delineating potential groundwater zones by reducing time and cost [4,17,32,37,41,44,45,[48][49][50]. Researchers adopt various techniques for delineation potential groundwater zones: statistical method [51], influence factor (IMF) [36,38,40,52], groundwater modelling, the combination of GIS, RS with AHP [37,41,45,49], and GIS-based machine learning [39,53,54]. Many researchers have adopted these methods since they have been demonstrated to be reliable and effective.…”

Section: Introductionmentioning

confidence: 99%

“…AHP is recommended among these methods when there are several alternatives for a set of pairwise comparisons and a lack of adequate valid data for analysis [30,55]. Recently, remote sensing and GIS coupled with AHP techniques have been adopted as a standard methodology for delineating potential groundwater zones in semi-arid areas [37,41,45,49]. AHP is used in conjunction with RS-GIS techniques to delineate possible groundwater zones in the Kilinochchi district.…”

Section: Introductionmentioning

confidence: 99%

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An Approach to Delineate Potential Groundwater Zones in Kilinochchi District, Sri Lanka, Using GIS Techniques

Pathmanandakumar

Thasarathan

Ranagalage

2021

IJGI

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The scarcity of surface water resources in the dry season in the Kilinochchi district increases the demand for freshwater. Therefore, the main objective of this study is to delineate potential groundwater zones in Kilinochchi, Sri Lanka, using integrated remote sensing (RS), geographic information systems (GIS) and the analytical hierarchy process (AHP). Groundwater potential zones are demarcated for the Kilinochchi district by overlaying thematic layers: geology, geomorphology, land use/land cover, soil types, drainage density, slope, lineament, and rainfall. The thematic layers were integrated into a geographic information system, and a weighted overlay analysis was carried out to delineate groundwater zones. Thus the resultant map is categorized into five different potential zones: very low (59.12 km2), low (207.78 km2), moderate (309.89 km2), high (507.74 km2), and very high (111.26 km2). The groundwater potential map was validated with the existing seventy-nine wells, which indicated a good prediction accuracy of 81.8%. This suggests that the results obtained by integrating RS-GIS and AHP are well-matched with the existing well water depth. The AHP approach based on RS-GIS was a handy and efficient technique for assessing potential groundwater zones. This research will help policymakers better manage the Kilinochchi district’s groundwater resources and give scope for further research into groundwater exploration in the area.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Approach to Delineate Potential Groundwater Zones in Kilinochchi District, Sri Lanka, Using GIS Techniques

Pathmanandakumar

Thasarathan

Ranagalage

2021

IJGI

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“…Geographic information systems (GIS) and remote sensing have ushered in a new era in this area, allowing multi-parametric research [14,16,[21][22][23]. The choices of conditioning variables and the utilization of an efficient integration approach are crucial to effective modeling [10,[24][25][26][27][28]. Table 1 shows that some groundwater potentiality modelling conditioning factors, such as soil texture, groundwater level, annual rainfall, Normalized Difference Vegetation Index (NDVI), geology, land use land cover, elevation, slope, aspect, curvature, topographic wetness index (TWI), Terrain Ruggedness Index (TRI), stream power index (SPI), distance to river, and others, have been widely used [16,21,22,[29][30][31][32].…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Model for Developing Groundwater Potentiality Model Using High Resolution Digital Elevation Model (DEM) Derived Factors

Mallick

Talukdar

Kahla

et al. 2021

Water

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The present work aims to build a unique hybrid model by combining six fuzzy operator feature selection-based techniques with logistic regression (LR) for producing groundwater potential models (GPMs) utilising high resolution DEM-derived parameters in Saudi Arabia’s Bisha area. The current work focuses exclusively on the influence of DEM-derived parameters on GPMs modelling, without considering other variables. AND, OR, GAMMA 0.75, GAMMA 0.8, GAMMA 0.85, and GAMMA 0.9 are six hybrid models based on fuzzy feature selection. The GPMs were validated by using empirical and binormal receiver operating characteristic curves (ROC). An RF-based sensitivity analysis was performed in order to examine the influence of GPM settings. Six hybrid algorithms and one unique hybrid model have predicted 1835–2149 km2 as very high and 3235–4585 km2 as high groundwater potential regions. The AND model (ROCe-AUC: 0.81; ROCb-AUC: 0.804) outperformed the other models based on ROC’s area under curve (AUC). A novel hybrid model was constructed by combining six GPMs (considering as variables) with the LR model. The AUC of ROCe and ROCb revealed that the novel hybrid model outperformed existing fuzzy-based GPMs (ROCe: 0.866; ROCb: 0.892). With DEM-derived parameters, the present work will help to improve the effectiveness of GPMs for developing sustainable groundwater management plans.

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Delineation of Groundwater Potential Zones in a Tropical River Basin Using Geospatial Techniques and Analytical Hierarchy Process

Achu

Anjali

Gopinath

2022

Application of Remote Sensing and GIS in Natural Resources and Built Infrastructure Management

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GIS-based multi-criteria decision making and entropy approaches for groundwater potential zones delineation

Cited by 25 publications

References 44 publications

An Approach to Delineate Potential Groundwater Zones in Kilinochchi District, Sri Lanka, Using GIS Techniques

An Approach to Delineate Potential Groundwater Zones in Kilinochchi District, Sri Lanka, Using GIS Techniques

A Novel Hybrid Model for Developing Groundwater Potentiality Model Using High Resolution Digital Elevation Model (DEM) Derived Factors

Delineation of Groundwater Potential Zones in a Tropical River Basin Using Geospatial Techniques and Analytical Hierarchy Process

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