A novel hybrid <scp>GIS</scp>‐based multi‐criteria decision‐making approach for flood susceptibility analysis in large ungauged watersheds

Sahraei, Razieh; Kanani‐Sadat, Yousef; Homayouni, Saeid; Safari, Abdolreza; Oubennaceur, Khalid; Chokmani, Karem

doi:10.1111/jfr3.12879

Cited by 18 publications

(6 citation statements)

References 91 publications

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“…Our research findings reveal significant similarities in the calculated criteria weights between the AHP and BWM methods, with the weights nearly equal. In contrast, studies conducted by Ajrina et al [65], Sahraei et al [66], and Tan et al [67], did not observe such pronounced similarities. Both methods consistently assign notably higher weights to the first three criteria (distance from existing hospitals, distance from main roads, distance from green spaces) and considerably lower weights to the last three criteria (distance from petrol stations, distance from residential areas, and population density).…”

Section: Discussionmentioning

confidence: 76%

GIS-Enabled Multi-Criteria Assessment for Hospital Site Suitability: A Case Study of Tehran

Zandi,

Pahlavani,

Bigdeli

et al. 2024

Sustainability

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In developing countries, the interaction between rapid urban expansion and population growth brings forth a host of challenges, particularly concerning essential services like healthcare. While interest in site suitability analysis for identifying optimal hospital locations to ensure equitable and secure healthcare access is on the rise, the absence of a holistic study that encompasses social and environmental aspects in the assessment of hospital site suitability is evident. The objective of this research is to introduce a hybrid methodology that combines Geographic Information Systems (GIS) with Multi-Criteria Decision-Making (MCDM) weighting methods. This methodology aims to create hospital site suitability maps for districts 21 and 22 in Tehran, taking into account socio-environmental factors. In addition to the conventional Analytical Hierarchical Process (AHP) weighting method, this study employs two relatively less-explored methods, the Best-Worst Method (BWM) and Step-wise Weight Assessment Ratio Analysis (SWARA), to enhance the analysis of hospital site suitability. In the SWARA method, there are minimal variations in weights among criteria, indicating that all socio-environmental factors (e.g., distance from existing hospitals, distance from main roads, distance from green spaces) hold significant importance in the decision-making process. Additionally, the findings indicate that the western part of the study area is the most suitable location for the construction of a new hospital. To achieve the average hospital bed availability in Tehran, an additional 2206 beds are required in the studied area, in addition to the existing facilities. Considering the ongoing urban development, population growth, and the potential for natural disasters and epidemics, it becomes essential to enhance the healthcare system by increasing the number of hospitals and available hospital beds. The sensitivity analysis showed that GIS-based SWARA-WLC was the most suitable and stable model for determining hospital site suitability in the study area. This methodology can be adapted for use in other regions and further improved by incorporating additional criteria. In conclusion, the study recommended three specific alternative sites for establishing a new hospital in the study area.

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Section: Discussionmentioning

confidence: 76%

GIS-Enabled Multi-Criteria Assessment for Hospital Site Suitability: A Case Study of Tehran

Zandi,

Pahlavani,

Bigdeli

et al. 2024

Sustainability

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“…■ China is the most prolific country in BWM research, followed by Iran, India, and Turkey. (Wu et al, 2022;Polat et al, 2023), COCOSO (Torkayesh et al, 2021;Ali et al, 2023), MARCOS (Yadav & Kumar, 2023;Ecer et al, 2024), VIKOR (Jain et al, 2023), QFD (Chang et al, 2023), WASPAS (Tavakoli Haji Abadi & Avakh Darestani, 2023), MOORA (Riahi et al, 2023), MULTIMOORA (Koppiahraj et al, 2023), SAW (Darvazeh et al, 2022), TODIM (Kumar et al, 2023), COPRAS (Sahraei et al, 2023), GRA (Hsu et al, 2023), MABAC (Chauhan et al, 2022), DEA (Eskandari et al, 2022), ARAS (Almutairi et al, 2023), and EDAS (Liang et al, 2023), weighting-based MCDM methods, including AHP (Koppiahraj et al, 2023), ANP (Nasiri Khiavi et al, 2023), DEMATEL (Bongo & Seva, 2023), FUCOM (Fazeli & Peng, 2023), and SWARA (Karakuş, 2023), some theories, including game theory (Fard et al, 2022), grey theory (Ulutaş et al, 2022), prospect theory (Zheng et al, 2023), and zero-sum game theory (Li et al, 2021), and mathematical programming, including goal programming (Do et al, 2023), and possibilistic programming (Shaw et al, 2023).…”

Section: The Current Status Of Bwm Researchmentioning

confidence: 99%

A State-of-the-Art Review of the BWM Method and Future Research Agenda

Ecer

2024

Technological and Economic Development of Economy

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The superiority of BWM over other weighting methods for obtaining the weight values of the attributes is that it achieves high-confidence results with a reasonable number of pairwise comparisons. Although the best-worst method (BWM) is a well-known multi-criteria decision-making (MCDM) method that has been successfully utilized in almost all scientific areas to solve challenging real-life problems, no research has comprehensively examined the state-of-the-art in this regard. The present study depicts a detailed overview of publications concerned with BWM during the period 2015–2022. Based on the information obtained from the Scopus database, this work presents a big picture of current research on BWM. In other words, this paper analyzes the existing literature about BWM and identifies thematic contexts, application areas, emerging trends, and remaining research gaps to shed light on future research agendas aligning with those gaps. Further, the most recent BWM research is analyzed in the top ten scientific areas, from engineering to materials science. “Engineering”, “computer science”, and “business, management, and accounting” are the hottest fields of BWM research. China is the most active country regarding “engineering” and “computer science”, whereas India is the leader in “business, management, and accounting”. The study also reveals that there are still many research gaps in BWM research. The big picture taken in this study will not only showcase the current situation of BWM research but will also positively impact the direction and quality of new research.

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“…COPRAS is an algorithm Zavadskas et al (1994) developed for assessing options within a set of mutually exclusive parameters in the multi-criteria space. Sahraei et al (2022) have demonstrated its application in watershed management. The COPRAS model involves the following steps:…”

Section: Coprasmentioning

confidence: 99%

Coupling MCDM-Based ensemble and AHP for the sustainable management of erosion risk in a tropical Sub-Saharan basin

Raji

Akintuyi

Wunude

et al. 2023

Preprint

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One of the most pressing environmental issues of the 21st century is land degradation in fragile watersheds where acute sediment aggradation, erosion, and flooding have become everyday occurrences. Previous attempts to prioritise sub-watersheds have been plagued with uncertainty. Addressing this problem therefore requires identifying erosion-prone areas, specifically at the sub-watersheds level, and reducing the uncertainty of outcomes to a minimum. In this study, an ensemble of seven multi-criteria decision-making (MCDM) models was developed to prioritise the sub-watersheds of the Anambra Basin against erosion risk. These MCDM models, namely MOORA (multi-objective optimisation based on ratio analysis), GRA (grey relational analysis), CoCoSo (combined compromise solution), CODAS (combinative distance-based assessment), TOPSIS (a technique for order preference by similarity to ideal solution), COPRAS (complex proportional assessment), and VIKOR (VieKriterijumsko KOmpromisno Rangiranje), were coupled with the Analytical Hierarchical Process (AHP) and Geographic Information System (GIS) with 23 geomorphometric parameters to provide an integrated sub-watershed ranking. The accuracy of the models was tested using Spearman's rank correlation and geometric mean to compute a uniform sub-watershed ranking. The results indicate that sub-watershed H has the highest aggregate ranking across the MCDM models, making it the top priority for erosion mitigation projects. Furthermore, the model validation assessment shows that the MOORA and COPRAS models returned similar results with the aggregated ranks and possess the most significant rank correlation coefficients, indicating the highest predictive accuracy. This study can be utilised by decision-makers in data-sparse regions for sustainable watershed management in the face of erosion risks.

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A novel hybrid GIS‐based multi‐criteria decision‐making approach for flood susceptibility analysis in large ungauged watersheds

Cited by 18 publications

References 91 publications

GIS-Enabled Multi-Criteria Assessment for Hospital Site Suitability: A Case Study of Tehran

GIS-Enabled Multi-Criteria Assessment for Hospital Site Suitability: A Case Study of Tehran

A State-of-the-Art Review of the BWM Method and Future Research Agenda

Coupling MCDM-Based ensemble and AHP for the sustainable management of erosion risk in a tropical Sub-Saharan basin

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