GIS-based multi-criteria decision-making techniques and analytical hierarchical process for delineation of groundwater potential

Farhat, Boutheina; Souissi, Dhekra; Mahfoudhi, Rabeb; Chrigui, Ranya; Sebei, Abdelaziz; Mammou, Abdallah Ben

doi:10.1007/s10661-022-10845-8

Cited by 16 publications

(14 citation statements)

References 56 publications

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“…In this study, in the exploration of groundwater potential zones, two distinct methodologies have been employed: the AHP and FOA method. The delineation of groundwater potential zones often relies on the AHP method, a structured decisionmaking technique (Farhat et al, 2023). Beginning with the identi cation of key parameters, ten parameters were utilized and compared within this framework, the AHP method organizes these criteria hierarchically, assigning weights based on their perceived importance.…”

Section: Groundwater Potential Zone Evaluation and Comparisonmentioning

confidence: 99%

Comparative Assessment of Analytical Hierarchy Process (AHP) and Fuzzy Overlay Analysis (FOA) Models in Groundwater Potential Zone Mapping Using Sensitive Analysis: A GIS-RS Integrated Approach

Gandhi,

Songara,

Prakash

et al. 2024

Preprint

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This study addresses the pressing need for assessing groundwater potential in diverse regions worldwide, emphasizing the challenges posed by industrialization and urban expansion. Leveraging remote sensing (RS) data within an ArcGIS framework, a comparison was conducted on the effectiveness of the Analytical Hierarchy Process (AHP) and Fuzzy Overlay Analysis (FOA) models in delineating groundwater potential zones. Ten influencing factors underwent rigorous multicollinearity checks to ensure independent analysis. Both methodologies categorized the output into five classification zones, revealing variations between methods. The sensitivity analysis identified specific influential layers for each method, showcasing heightened sensitivity in assessing groundwater potential zones. Notably, AHP emphasized factors such as NDWI, Lineament density, and Land Use Land Cover (LULC), while FOA prioritized Soil Texture, Lineament Density, and NDWI. Evaluating the reliability of groundwater potential assessments, AHP demonstrated fair agreement (59.18%), while FOA exhibited substantial agreement (77.5%). FOA emerged as superior, offering a more nuanced and precise representation of spatial relationships and uncertainties. The promising performance of FOA in our study suggests its potential applicability in accurate groundwater potential assessment beyond the study area (India) to other countries regions with heterogeneous hydrogeological conditions.

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Section: Groundwater Potential Zone Evaluation and Comparisonmentioning

confidence: 99%

Comparative Assessment of Analytical Hierarchy Process (AHP) and Fuzzy Overlay Analysis (FOA) Models in Groundwater Potential Zone Mapping Using Sensitive Analysis: A GIS-RS Integrated Approach

Gandhi,

Songara,

Prakash

et al. 2024

Preprint

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“…The average temperature across this locale is recorded at 19.5 °C, with fluctuations observed from a low of 17.8 °C to a high of 22.7 °C. The annual rainfall varies significantly, from a minimum of 300 mm to a maximum of 800 mm, with an average of 550 mm (Farhat et al, 2023;Hfaiedh, 2021)(Fig. 1).…”

Section: 1study Areamentioning

confidence: 99%

Employing Machine Learning Approaches and Multivariate Analysis to Assess Groundwater Quality for Irrigation in the Mornag Plain, Tunisia

Hfaiedh,

Gaagai,

Moussa

et al. 2024

Preprint

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The crucial assessment of water quality in the Mornag Plain, Tunisia, is fundamental for reservoir management, ensuring suitability for consumption, and preserving environmental integrity. Employing a diverse range of methodologies, such as water quality indices (WQIs), statistical analyses, geographic information systems (GIS), and decision tree (DT) model, provided a nuanced understanding of the compositional attributes of groundwater designated for irrigation. Detected categories of water, for instance Na-Cl, Ca-Mg-SO4, and a combination of Ca-Mg-Cl/SO4, displayed unique chemical signatures. These patterns were shaped by diverse processes including interactions between water and rock, the breakdown of dolomite, the concentration of minerals through evaporation, the swapping of ions, and human impact. Evaluating groundwater's suitability for irrigation purposes by employing measures like Na%, SAR, SSP, and MH, demonstrated that a significant portion of the samples conformed to approved norms. However, the analysis revealing 65.6% of the IWQI and every instance of PS falling within the spectrum of high to severe constraints, as well as ranging from detrimental to unsatisfactory classes, underscores the obstacles in sustaining superior irrigation water standards. The predictive model, DT, demonstrated robust results in forecasting all water quality indices. The DT-HyC-9 model stood out as the top performer in prediction accuracy, demonstrating a robust correlation with prime factors affecting IWQI, as shown by substantial R2 metrics in both the training and evaluation phases. Likewise, the DT-HyC-3 approach showcased remarkable precision in forecasting IWQI, highlighting the critical role of three essential factors. These results provide crucial guidance for policymakers engaged in managing water quality, laying the groundwork for the sustainable management of water resources within the Mornag Plain. The integration of advanced methodologies and predictive models enhances the understanding of groundwater dynamics, facilitating informed decision-making for the region's water sustainability.

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“…In this stage, stakeholders or decision-makers are asked about their preferences, and all evaluation numbers for all alternatives generate an overall value. Eventually, Choose the best alternative [53,54].…”

Section: Gis and Support Decision-makermentioning

confidence: 99%

Enhancing Urban Sustainability by Integrating MCDM and Model of GIS Spatial Analysis in Al-Nasiriyah Heritage Center‎ Development

Al-Timimy,

Bedewy

2023

IJSDP

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Various countries of the world endeavor to achieve a new paradigm of sustainability by preserving their heritage and history and avoid the risk of old process preservation. Therefore, this article adopts several concepts for investigating heritage areas and then builds a model based on spatial analysis using GIS. So, the main problem this article addresses is that planning does not rely on appropriate mechanisms for preserving the heritage area of Al-Nasiriyah in Dhi-Qar Governorate, Iraq, which has resulted in erosion and destruction of that area. Consequently, the article aims to determine the optimal process for the rehabilitation to the heritage city center, using spatial analysis mechanisms and to achieve urban sustainability. To do this, the article first discusses various countries' experiences in the field of heritage conservation to understand successful principles for implementing the new sustainable paradigm. Subsequently, the Analytical Hierarchy Process (AHP) is used to calibrate and assign weights to the analysis mechanism. This process is based on the most prominent elements that depend on land uses and necessary services in the spatial analysis. After analyzing eight indicators, a consistency ratio of 0.47 was obtained, which is the acceptable excitation range in AHP standards. Finally, the study built a model in GIS to determine the most suitable area for the development of any city with the same condition. Therefore, the spatial analysis and model process identified Zones 2 and 3 as the most suitable for development, with Zone 4 being the optimal choice according to the MCDM analysis to be selected as the first area for development. Thus, this can limit the process of erosion of the urban heritage fabric due to the encroachment of commercial use and the rise in the value of achieving cultural sustainability.

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GIS-based multi-criteria decision-making techniques and analytical hierarchical process for delineation of groundwater potential

Cited by 16 publications

References 56 publications

Comparative Assessment of Analytical Hierarchy Process (AHP) and Fuzzy Overlay Analysis (FOA) Models in Groundwater Potential Zone Mapping Using Sensitive Analysis: A GIS-RS Integrated Approach

Comparative Assessment of Analytical Hierarchy Process (AHP) and Fuzzy Overlay Analysis (FOA) Models in Groundwater Potential Zone Mapping Using Sensitive Analysis: A GIS-RS Integrated Approach

Employing Machine Learning Approaches and Multivariate Analysis to Assess Groundwater Quality for Irrigation in the Mornag Plain, Tunisia

Enhancing Urban Sustainability by Integrating MCDM and Model of GIS Spatial Analysis in Al-Nasiriyah Heritage Center‎ Development

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