GIS-based Multi-criteria Decision Research Articles

Mapping Vulnerability to Potential Crisis Events in Surabaya City: A GIS-Based Approach

Background This study aims to develop a vulnerability map for Surabaya using GIS-based Multi-Criteria Decision Analysis (MCDA) to assess the city’s vulnerability to COVID-19. Methods Six key factors influencing vulnerability were identified and their relative importance determined through the Analytic Hierarchy Process (AHP) pairwise comparison matrix. GIS was utilized to classify Surabaya’s vulnerability into five levels: very low, low, medium, high, and very high. Results The resulting vulnerability map provides essential insights for decision-makers, healthcare professionals, and disaster management teams. It enables strategic resource allocation, targeted interventions, and formulation of comprehensive response strategies tailored to specific needs of vulnerable districts. Conclusions Through these measures, Surabaya can enhance its resilience and preparedness, ensuring the well-being of its residents in the face of potential emergency outbreaks.

Assessment of the geothermal potential zone of India utilizing GIS-based multi-criteria decision analysis technique

India, with 80 % energy demand reliant on fossil fuels, is the world's third-largest greenhouse gas emitter, necessitating a shift from fossil fuels to renewable energy. While solar and wind production has grown, geothermal energy remains untapped despite enormous prospects in the country. In this regard, India's first regional-scale geothermal potential (GP) map has been prepared using a GIS based on a multi-criteria decision analysis technique. Five thematic layers (geology, fault, heat flow, thermal spring, and earthquake epicenter) have been used to calculate GP index, which is divided into high, moderate, and low categories. The result shows that most geothermal drilling sites are distributed in the high GP category zone, showing high efficacy. Further, a joint study of the geothermal surface and reservoir temperature with the present study shows that the northern and western parts of India have significant potential for geothermal exploration. Our result also reveals that the projected CO2 emissions are approximately 2.6 gigatons (which is lower than other energy sources) for an output of 10 GW using geothermal energy in the next 75 years. This study can enhance geothermal prospect identification, cutting exploration costs, and site selection, and contributing to multiple UN Sustainable Development Goals.

GIS-Based Multi-criteria Decision-Making Techniques and Analytical Hierarchical Process for Flash Flood Risk Assessment Due to a Possible Dam Break in Urban Arid Environment: Case Study of Biskra City, Southern Algeria

GIS-Based Multi-criteria Decision-Making Techniques and Analytical Hierarchical Process for Flash Flood Risk Assessment Due to a Possible Dam Break in Urban Arid Environment: Case Study of Biskra City, Southern Algeria

GIS-Based Multi-criteria Decision Analysis for the Optimal Location of Public Facility in Batna City, Algeria

GIS-Based Multi-criteria Decision Analysis for the Optimal Location of Public Facility in Batna City, Algeria

Spatial Prediction of Groundwater Potential of Upper Tigris Basin Mapping in the Turkey with GIS-Based Multicriteria Decision Making (MCDM) Method

The Upper Tigris region in the Middle East is in Turkey and this study shows it to be an area with significant water resources that enable agricultural activities in the region. Since the GAP irrigation project has not been completed yet, there is an extensive use of groundwater for irrigation. This situation threatens the groundwater potential of the basin in a negative manner. Therefore, determination of groundwater potential should be evaluated properly instead of approving the groundwater potential of the region with observation wells, which is a more costly method. In this study, the groundwater potential of the basin was calculated by the GIS-based Multi-Criteria Decision Making (MCDM) method via main elements affecting groundwater formation. The GIS-based-AHP method is used for identifying the groundwater potential zones of the Upper Tigris Basin as an alternative to expensive and time-consuming method of well drilling. There are 8 key criteria taken into account; Geomorphology (GM), Geology(G), Line Density (LD), Slope (SL), Drainage Density (DD), Land Use (LU), Rainfall (R), and Soil Type (ST) and the individual weight of each criterion was evaluated by the AHP technique and utilized by the “Spatial Analysis Overlay Weighted Method” obtaining the “Groundwater Potential Index (GWPI)”. The GWPI values obtained is used to classify the Upper Tigris Basin into five categories as follows: 319 km2 of the basin has very poor potential (3.8%); 2217 km2 has poor potential (26.7%); 2800 km2 has moderate potential (33.7%); 2200 km2 has good potential (26.5%); and finally, 763 km2 has very good potential (9.2%).

Delineation of Groundwater Potential Zones for Sustainable Development and Planning using AHP and GIS Techniques in the Coal Mining Province of Mahan River Catchment Area

The present research aims to address the drinking water crisis in the Mahan River catchment area resulting from the disruption of groundwater availability due to extensive coal mining. The study uses GIS-based Multi-Criteria Decision Analysis (MCDA) to map the groundwater potential of the area by analysing several factors that affect groundwater availability, including rainfall, water depth, geomorphology, geology, soil, land-cover/land-use, and topographic characteristics derived from DEM. The groundwater potential map created using the MCDA technique classified the area into low, moderate, and high groundwater potential zones. The map was validated and verified using water table depth and electrical conductivity values available in the region, indicating that it can be used to identify groundwater recharging sites. The study’s results show that about 30% of the area has high groundwater potential, and more than 45% of the area has moderate groundwater potential. The information derived from the study can be used for sustainable management and proper planning of groundwater resources in the Mahan River catchment area. Overall, the study presents a useful approach to address the groundwater depletion problem resulting from coal mining activities in the Mahan River catchment area.

Geospatial analysis of flood risk hazard in Zambezi Region, Namibia

The recent decade has seen an increase in frequency and intensity of flood risk globally especially in less developed countries. This has been attributed to many factors such as population growth, urbanization, climate change, increasing precipitation, and poor solid waste management among others. This study used quantitative analysis to identify and characterise flood-prone areas in Kabbe and Kaltima in the Zambezi region. We estimated major factors influencing flood events in the study area. We estimated this by incorporating the analytical hierarchy process (AHP) and GIS-based multi-criteria decision-making to map and identify flood-prone areas in Kabbe and Katima. AHP was employed to ascertain the weight of each criterion taken into consideration for the susceptibility mapping. We analysed ten factors elevation, slope, distance to river, rainfall, topographic wetness index, distance to road, drainage density, land use land cover, modified soil adjusted vegetation index, and soil which are closely associated with flood occurrence in the study area. The flood factors maps were categorized into five susceptibility levels. We used field data by interviewing key informants and community members to validate the GIS analysis. The result from the flood susceptibility map indicates that 46 % of areas in Kaltima and Kabbe have a low susceptibility to flood, 56.04 % are moderate, 43.33 % are high and 17 % are very highly susceptible to flood. The areas susceptible to flooding are mostly low-laying areas in Kabbe which are gentle slopes and are sitting at approximately 921–935 m below sea level. Speaking with stakeholders in the area, they confirmed that communities such as Ihaha, Isize, Mbalasinte, and Kalumnesa are highly susceptible to flooding. The community members confirm that they experience flooding every year with devastating impacts on their lives and livelihoods. We recommend localized flood management strategies that cater to the needs of the communities and develop strategies to improve preparedness, response, and mitigation. Increasing government funding for flood risk management in the area can increase the capacity of the community for flood risk management through training and awareness

Landslide susceptibility assessment using GIS-based multicriteria decision analysis (MCDA) along a part of National Highway-1, Kashmir- Himalayas, India

Landslide susceptibility assessment using GIS-based multicriteria decision analysis (MCDA) along a part of National Highway-1, Kashmir- Himalayas, India

Computerized constructed wetlands allocation model (based on ecosystem services demand)

Egypt’s urban communities face many threats, including, pluvial floods, heat waves, and lack of publicly accessible urban green spaces. Nature-based solutions such as constructed wetlands (CWs) present a promising solution that could offer a wide range of ecosystem services (ES). However, the adoption of CWs is challenged by the lack of local planning guides and uncertainty about potential benefits. There are various models and tools available for quantifying and valuing ES, however, many of them are either highly complex or require extensive data and expertise. The aim of this paper is to develop a GIS-based multi-criteria decision model to select CW sites based on the supply and demand of ES. The model is to operate on three main stages: (i) demand: based on the need for risk reduction or benefit provisioning, (ii) potential sites (PSs): identify and score suitable sites for establishing a CW, and (iii) supply: define the service benefiting areas (SBA). An experimental approach is used, where the model is tested on New Damietta, an Egyptian Mediterranean city, proving the model is a reliable decision-making tool during preliminary urban planning stages due to its practicality, flexibility, and reasonable data requirements.

How to delineate urban gravitational zones? GIS-based multicriteria decision analysis and Huff’s model in urban hierarchy modeling

Urban gravitational zones (UGZ) are related to cities' functions and population size. In strategic regional territorial planning adequate tools and detailed data are rarely used. This issue is not foreign to Croatia and other countries. How should the UGZ be accurately delineated for each city? A combination of Huff's model and GIS-based multicriteria decision analysis (GIS-MCDA) was used to delineate UGZ. In total, 95 criteria grouped into ten functions were used. The research resulted in a new methodological framework for deriving the urban hierarchy model, a tool that allows automation and simplification of the GIS-MCDA, and an urban hierarchy model of 20 major cities in Croatia.

A risk-based multi-criteria decision-making framework for offshore green hydrogen system developments: Pathways for utilizing existing and new infrastructure

Unlocking the potential of offshore renewables for green hydrogen (GH2) production can be a game-changer, empowering economies with their visionary clean energy policies, amplifying energy security, and promoting economic growth. However, their novelty entails uncertainty and risk, necessitating a robust framework for facility deployment and infrastructure planning. To optimize offshore GH2 infrastructure placement, this work proposes a novel and robust GIS-based multi-criteria decision-making (MCDM) framework. Encompassing thirty-two techno-socio-economic-safety factors and ocean environmental impact analysis this methodology facilitates informed decision-making for sustainable and safe GH2 development. Utilizing the synergies between offshore wind and solar resources, this study investigates the potential of hybrid ocean technologies to enhance space utilization and optimize efficiency. To illustrate the practical application of the proposed framework, a case study examining a GH2 system in Australia's marine region and its potential nexus with nearby offshore industries has been conducted. The performed life cycle assessment (LCA) explored various configurations of GH2 production, storage, and transportation technologies. A Bayesian objective weight integrating technique has been introduced and contrasted statistically with the hybrid CRITIC, Entropy, MEREC and MARCOS-based MCDM approaches. Various locations are ranked based on the net present value of life cycle cost, GH2 production capacity, risk, availability, and environment sustainability factors, illustrating their compatibility. A sensitivity analysis is conducted to confirm that a Bayesian approach improves the decision-making outcomes through identifying optimal criteria weights and alternative ranks more effectively. Empowering strategic GH2 decisions globally, the proposed approach optimizes system performances, cost, sustainability, and safety, excelling in harsh environments.

Identifying suitable zones for integrated aquifer recharge and flood control in arid Qatar using GIS-based multi-criteria decision-making

Groundwater resources in arid regions play a vital role in meeting water demands; however, they are facing rapid depletion due to unsustainable exploitation practices, exacerbated by climate change. Floods can present a unique opportunity for restoring groundwater levels and mitigating saltwater intrusion into aquifers. The use of properly managed floodwater for aquifer recharge offers a dual advantage by maximizing the potential of floods as a valuable water resource, while minimizing their negative impacts. In this work, we applied a GIS-based Multi-Criteria Decision-Making (MCDM) method, namely the Analytic Hierarchy Process (AHP), to delineate flood susceptible zones and groundwater recharge zones in Qatar, considering several influential topographical, hydrological, environmental, and anthropological criteria. The maps of flood susceptibility and groundwater recharge potential were validated using recent flooding events and existing recharge wells data, respectively. Sensitivity analysis was conducted on both variables to further assess their accuracy. The overlay analysis of the two validated maps suggests that approximately 64% of the Qatar peninsula presents medium to excellent suitability for aquifer recharge using floodwater. The areas best suited for floodwater-based recharge intervention are the northern and coastal regions of the peninsula, while the urban areas and southwestern area are less suitable. This study provides decision-makers with spatially explicit information on areas in Qatar that can be targeted for aquifer recharge projects using floodwater as well as recommendations on technical, economic, and regulatory considerations that require additional investigation. The approach employed can be effectively applied in similar flood-prone arid regions and is adaptable to diverse contexts.

Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GIS

Floods are a widespread natural disaster with substantial economic implications and far-reaching consequences. In Northern Pakistan, the Hunza-Nagar valley faces vulnerability to floods, posing significant challenges to its sustainable development. This study aimed to evaluate flood risk in the region by employing a GIS-based Multi-Criteria Decision Analysis (MCDA) approach and big climate data records. By using a comprehensive flood risk assessment model, a flood hazard map was developed by considering nine influential factors: rainfall, regional temperature variation, distance to the river, elevation, slope, Normalized difference vegetation index (NDVI), Topographic wetness index (TWI), land use/land cover (LULC), curvature, and soil type. The analytical hierarchy process (AHP) analysis assigned weights to each factor and integrated with geospatial data using a GIS to generate flood risk maps, classifying hazard levels into five categories. The study assigned higher importance to rainfall, distance to the river, elevation, and slope compared to NDVI, TWI, LULC, curvature, and soil type. The weighted overlay flood risk map obtained from the reclassified maps of nine influencing factors identified 6% of the total area as very high, 36% as high, 41% as moderate, 16% as low, and 1% as very low flood risk. The accuracy of the flood risk model was demonstrated through the Receiver Operating Characteristics-Area Under the Curve (ROC-AUC) analysis, yielding a commendable prediction accuracy of 0.773. This MCDA approach offers an efficient and direct means of flood risk modeling, utilizing fundamental GIS data. The model serves as a valuable tool for decision-makers, enhancing flood risk awareness and providing vital insights for disaster management authorities in the Hunza-Nagar Valley. As future developments unfold, this study remains an indispensable resource for disaster preparedness and management in the Hunza-Nagar Valley region.

A pathway to 25% reduction in greenhouse gas emission by 2030 using GIS-Based multi-criteria decision making for renewables, date palm (phoenix dactylifera), and carbon credits: a case for Qatar

Qatar is making concerted efforts at the national level to decrease anthropogenic greenhouse gas emissions. The country has set its National Determined Contribution (NDC) in line with the Paris Agreement to reduce its overall emissions by 25% by the year 2030. This study identifies several pathways, which Qatar can explore to achieve its set goals. It explores Qatar’s potential for renewable energy generation (solar and wind), carbon offset through planting trees, and the purchase of carbon offset credits. The study starts by investigating the available wind and solar energy potential in the country, by considering physical and legal restrictions, which limit the available land to be utilized for RE generation. Multi-criteria Decision is carried out utilizing the Analytic Hierarchy Process (AHP) for variable percentage estimation in ArcMap Geographic Information Systems software. Next, a review based on Qatar’s climate is performed to identify suitable tree species that would promote atmospheric CO2 sequestration in the country. Finally, the cost implication of offsetting emissions using verified carbon credits is considered and compared with other options. Results indicated that while a considerable area is available for both wind (37%) and solar (53%) energy generation, only 6.2% and 13.8% of Qatar are highly suitable for wind and solar energy installations, respectively. Also, while Qatar has the potential to meet 20% of its energy demand by 2030 from renewable sources by using solar PV and wind, this will only account for a 14.28% reduction in overall emissions. Additionally, planting date palm trees (Phoenix dactylifera) would significantly benefit the nation in the area of carbon sequestration and revenue generation as compared to purchasing carbon offset credits.

Groundwater delineation for sustainable improvement and development aided by GIS, AHP, and MIF techniques

Exploration of groundwater is an integral part of viable resource growth for society, economy, and irrigation. However, uncontrolled utilization is mainly reported in urban and industries due to the increasing demand for water in semi-arid and arid regions of the world. In the background, groundwater demarcation for potential areas is vital in meeting necessary demand. The current study applied an integrated method comprising the analytical hierarchy process (AHP), multiple influence factors (MIF), combined with a linear regression curve and observatory well data for groundwater prospects mapping. Thematic maps such as flow direction, flow accumulation, elevation map, land use land cover, slope, soil texture, hill shade, geomorphology, normalized vegetation index, and groundwater depth map were generated utilizing remote sensing techniques. The relative weight of each parameter was estimated and then assigned to major and minor parameters. Potential zones for groundwater were classified into five classes, namely very good, good, moderate, poor, and very poor, based on AHP and MIF methods. A spatially explicit sensitivity and uncertainty analysis method to a GIS-based multi-criteria groundwater potential zone model is presented in this research. The study addressed a flaw in the way groundwater potential mapping results are typically presented in GIS-based multi-criteria decision analysis studies, where discrete class outputs are used without any assessment of their certainty with respect to variations in criteria weighting, which is one of the main contributors to output uncertainty. The study region is categorized based on inferred results as very poor, poor, marginal, and very good in potential ground quality 3.04 km2 is considered extremely poor, 3.33 km2 is considered poor, 64.42 km2 is considered very good, and 85.84 km2 is considered marginal zones, which shows reliable and potential implementation. The outcomes of AHP and MIF were validated by linear regression curve and actual water table in a study area. The study results help to formulate the potential demarcation of groundwater zones for future sustainable planning and development of groundwater sources. This study may be helpful to provide a cost-effective solution to water resources crises. The current study finding may be helpful for decision-makers and administrative professionals for sustainable management of groundwater resources for present and future demands.

GIS-Based Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP) Techniques to Derive Flood Risks Management on Rice Productivity in Gishari Marshland

GIS-Based Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP) Techniques to Derive Flood Risks Management on Rice Productivity in Gishari Marshland

Assessment of groundwater potential zones in data-scarce regions using GIS-based multicriteria decision making approach

Groundwater is an essential natural resource that sustains numerous ecological systems and human lifestyles. The Jhargram district is facing persistent groundwater development issues, requiring comprehensive monitoring and planning, as most farmers heavily rely on groundwater for crop production. The groundwater potential zone of the Jhargram district was classified into five classes, viz., very high (5.82%), high (50.81%), moderate (30.33%), low (13.01%), and very low (0.03%), zones, respectively. The results were assessed for validity using ROC curves, which demonstrated an accuracy rate of 80.4%. The calculation of the AUC was performed in order to assess the overall accuracy of the predicted GWPZ. The GWPZ map is crucial for implementing artificial recharge structures like percolation ponds, bunds and trenching in semi-arid regions. It aids in developing sustainable groundwater management policies, mitigating drought, climate change, and water scarcity, and aiding farmers, regional planners, policy-makers, climate change experts, and local governments.

Integrating multi-criteria decision analysis (MCDA) with kriging and entropy methods for optimising streamflow measurement in a scantly monitored river basin

ABSTRACT Streamflow data is one of the most important inputs for the management of water resources in river basins. In this study, a GIS-based multi-criteria decision analysis (MCDA) was integrated with kriging and entropy methods for optimising a streamflow monitoring network in the upper Tekeze River basin, north-western Ethiopia. An initial evaluation based on the WMO (2008) guideline showed that the density of existing streamflow monitoring network for the upper Tekeze River basin was inadequate. Hence, 41 new streamflow monitoring stations were needed. The most important criteria for identifying suitable streamflow monitoring sites in the upper Tekeze River basin were stream order, accessibility (distance to roads), slope gradient, land use/cover and soil texture. The required number of new streamflow monitoring stations for the upper Tekeze River basin was reduced from 41 to 33 after an optimisation using ordinary kriging and entropy. The optimal number of monitoring stations for the upper Tekeze River basin including the existing ones was therefore 47. An integrated application of MCDA, kriging and entropy methods aids to optimise the location and number of streamflow monitoring stations in a catchment. The use of optimisation techniques for designing streamflow monitoring network is essential for collecting adequate streamflow data in scantly monitored basins.

Climate change-derived environmental and physical factors influencing the socioeconomic development in the Himalayan region

Spatio-temporal fluctuation of climatic variables with the terrain characteristics and their inter-relationship is a priority for predicting flash-flood-induced landslide hazards over the fragile Himalayas. The present study addressed this anxiety by assimilating satellite data products and auxiliary datasets in the Bhagirathi River basin of the Indian Himalayas. Snow Covered Area (SCA) is a critical indicator of the ecosystem that influenced the flash flood along different terrain features such as Altitude, Hill-Gradient, and Aspect. GIS-based multi-criteria decision analysis (GIS-MCDA) technique is used to analyze the possible landslide zones and flood extent along the river basin, and MODIS Terra (MOD10A2) data products derived annual SCA is 4278 km2 for the year 2021, the analysis of geospatial maps at 25° intervals of Altitude, hill-gradient, and Aspect. The SCA distribution reveals that apart from the Altitude, the Aspect of the hill gradient significantly impacts snow accumulation. Hill-Gradient, ranging from 13.06 to 19.52, occupies 24.7% of the total area, and 45.3 to 51.83 are found without snow. The highest variation of SCA is along the Western direction (9.19%), followed by North-East (8.79%), while the least (3.78%) variance is in the Southwest direction. Additionally, it was found that many bridges, roads, and other properties are under threat in this study area, even with a moderate flash flood. Findings from this study provide the spatiotemporal status of SCA in various geological stress conditions during the last decades and probable landslide zones. This will be a preliminary pathway to policymakers in rehabilitation and early evacuation of human lives due to flash flood occurrence.

Evaluation of Flood Risk Map Development through GIS-Based Multi-Criteria Decision Analysis in Maran District, Pahang - Malaysia

Evaluation of Flood Risk Map Development through GIS-Based Multi-Criteria Decision Analysis in Maran District, Pahang - Malaysia