Urban Flood Risk Assessment and Mapping Using GIS-DEMATEL Method: Case of the Serafa River Watershed, Poland DOI Open Access

Wiktoria Natkaniec,

Izabela Godyń

Water, Journal Year: 2024, Volume and Issue: 16(18), P. 2636 - 2636

Published: Sept. 17, 2024

This paper develops a method integrating Geographic Information Systems (GIS) and the Decision-Making Trials Evaluation Laboratory (DEMATEL) for analysis of factors influencing urban flood risk identification flood-prone areas. The is based on nine selected factors: land use/land cover (LULC: ratio built-up areas, greenery areas), elevation, slope, population density, distance from river, soil, Topographic Wetness Index (TWI), Normalized Difference Vegetation (NDVI). DEMATEL used to determine cause–effect relationship between factors, allowing key criteria their weights be determined. LULC density were identified as most important floods. was applied case study—the Serafa River watershed (Poland), an urbanized catchment covering housing estates cities Kraków Wieliczka frequently affected by flooding. GIS publicly available data using QGIS with obtained vulnerable 45% total area classified areas very high or level risk. results match actual inundation incidents that occurred in recent years this area. study shows potential possibility DEMATEL-GIS significance designate

Language: Английский

Simulating and predicting future land-use/land cover trends using CA- Markov and LCM models DOI Creative Commons
Fatiha Ait El Haj, Latifa Ouadif,

Ahmed Akhssas

et al.

Case Studies in Chemical and Environmental Engineering, Journal Year: 2023, Volume and Issue: 7, P. 100342 - 100342

Published: March 29, 2023

Language: Английский

Citations

24
GIS and AHP-based flood susceptibility mapping: a case study of Bangladesh DOI

Zarjes Kader,

Md Rabiul Islam, Md. Tareq Aziz

et al.

Sustainable Water Resources Management, Journal Year: 2024, Volume and Issue: 10(5)

Published: Aug. 29, 2024

Language: Английский

Citations

10
Identifying suitable zones for integrated aquifer recharge and flood control in arid Qatar using GIS-based multi-criteria decision-making DOI Creative Commons
Sarra Aloui, Adel Zghibi, Annamaria Mazzoni

et al.

Groundwater for Sustainable Development, Journal Year: 2024, Volume and Issue: 25, P. 101137 - 101137

Published: March 13, 2024

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

Language: Английский

Citations

9
Assessment of flood susceptibility in Cachar district of Assam, India using GIS-based multi-criteria decision-making and analytical hierarchy process DOI
Preeti Barsha Borah,

Arpana Handique,

Chandra Kumar Dutta

et al.

Natural Hazards, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 7, 2025

Language: Английский

Citations

1
Evaluating Flood Susceptibility in the Brahmaputra River Basin: An Insight into Asia's Eastern Himalayan Floodplains Using Machine Learning and Multi-Criteria Decision-Making DOI Creative Commons
Jatan Debnath, Dhrubajyoti Sahariah,

Meghna Mazumdar

et al.

Earth Systems and Environment, Journal Year: 2023, Volume and Issue: 7(4), P. 733 - 760

Published: Dec. 1, 2023

Abstract Floods represent a significant threat to human life, property, and agriculture, especially in low-lying floodplains. This study assesses flood susceptibility the Brahmaputra River basin, which spans China, India, Bhutan, Bangladesh—an area notorious for frequent flooding due saturation of river water intake capacity. We developed evaluated several innovative models predicting by employing Multi-Criteria Decision Making (MCDM) Machine Learning (ML) techniques. The showed robust performance, evidenced Area Under Receiver Operating Characteristic Curve (AUC-ROC) scores exceeding 70% Mean Absolute Error (MAE), Squared (MSE), Root (RMSE) below 30%. Our findings indicate that approximately one-third studied region is categorized as moderately highly flood-prone, while over 40% classified low very flood-risk areas. Specific regions with high include Dhemaji, Dibrugarh, Lakhimpur, Majuli, Darrang, Nalbari, Barpeta, Bongaigaon, Dhubri districts Assam; Coochbihar Jalpaiguri West Bengal; Kurigram, Gaibandha, Bogra, Sirajganj, Pabna, Jamalpur, Manikganj Bangladesh. Owing their strong performance suitability training datasets, we recommend application MCDM techniques ML algorithms geographically similar holds implications policymakers, regional administrators, environmentalists, engineers informing management prevention strategies, serving climate change adaptive response within basin.

Language: Английский

Citations

22
A GIS-Based Evacuation Route Planning in Flood-Susceptible Area of Siraha Municipality, Nepal DOI Creative Commons
Gaurav Parajuli,

Shankar Neupane,

Sandeep Kunwar

et al.

ISPRS International Journal of Geo-Information, Journal Year: 2023, Volume and Issue: 12(7), P. 286 - 286

Published: July 16, 2023

Flood is one of the most frequently occurring and devastating disasters in Nepal. Several locations Nepal are at high risk flood, which requires proper guidance on early warning safe evacuation people to emergency through optimal routes minimize fatalities. However, information limited flood hazard mapping only. This study provides a comprehensive susceptibility route Siraha Municipality where lot events have occurred past liable happen future. The map was created using Geographic Information System (GIS)-based Analytical Hierarchy Process (AHP) over nine conditioning factors. It showed that 47% total area highly susceptible remaining zone. assembly points would gather for were selected within zone manual digitization while shelters such they can host maximum number people. network analysis approach used closest facility proposed optimum based walking speed evacuees reach shelter place considering effect slope pedestrian. A 12 out 22 suggested 30 min, 7 60 2 100 min walk from point. Moreover, this suggests possible areas further allocations service analysis. support authorities’ decision-making assessment system planning, helps providing an efficient plan mitigation.

Language: Английский

Citations

17
Landslide vulnerability mapping using multi-criteria decision-making approaches: in Gacho Babba District, Gamo Highlands Southern Ethiopia DOI Creative Commons
Lemma Tadesse, Abera Uncha Utallo, Thomas Toma Tora

et al.

Deleted Journal, Journal Year: 2024, Volume and Issue: 6(2)

Published: Jan. 26, 2024

Abstract The landslide has been a life-threatening natural disaster in most districts of Gamo Highlands. This study was conducted to assess the status vulnerability Gacho Baba district zone southern Ethiopia. Geographic Information System Analytical Hierarchy Process and Weighted Linear Combination multi-criteria decision-making approaches were applied. Eight causative factors landslide, namely, slope, elevation, aspect, distance from stream, drainage density, soil type, road, land use/cover considered. weight values each factor determined by previous studies, field observations, experts’ judgment. calculated is slope (23%), elevation (21%), aspect (8%), stream density (12%), type road length (9%), (6%). Moreover, Consistency Index (0.13) Ratio (0.08%) with acceptable for comparison weighted overlay analysis produce map area. result shows that vast majority (86.6%) falls within very high moderate susceptibility class only (13.4%) low susceptibility. indicates almost all 11 villages district, are found which alerts responsible community zonal risk prevention related offices take action on identified reduce occurrences hazard district.

Language: Английский

Citations

8
Enhancing the Performance of Machine Learning and Deep Learning-Based Flood Susceptibility Models by Integrating Grey Wolf Optimizer (GWO) Algorithm DOI Creative Commons
Ali Nouh Mabdeh, R. S. Ajin, Seyed Vahid Razavi-Termeh

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(14), P. 2595 - 2595

Published: July 16, 2024

Flooding is a recurrent hazard occurring worldwide, resulting in severe losses. The preparation of flood susceptibility map non-structural approach to management before its occurrence. With recent advances artificial intelligence, achieving high-accuracy model for mapping (FSM) challenging. Therefore, this study, various intelligence approaches have been utilized achieve optimal accuracy modeling address challenge. By incorporating the grey wolf optimizer (GWO) metaheuristic algorithm into models—including neural networks (RNNs), support vector regression (SVR), and extreme gradient boosting (XGBoost)—the objective generate maps evaluate variation performance. tropical Manimala River Basin India, severely battered by flooding past, has selected as test site. This 15 conditioning factors such aspect, enhanced built-up bareness index (EBBI), slope, elevation, geomorphology, normalized difference water (NDWI), plan curvature, profile soil adjusted vegetation (SAVI), stream density, texture, power (SPI), terrain ruggedness (TRI), land use/land cover (LULC) topographic wetness (TWI). Thus, six are produced applying RNN, SVR, XGBoost, RNN-GWO, SVR-GWO, XGBoost-GWO models. All models exhibited outstanding (AUC above 0.90) performance, performance ranks following order: RNN-GWO (AUC: 0.968) > 0.961) SVR-GWO 0.960) RNN 0.956) XGBoost 0.953) SVR 0.948). It was discovered that hybrid GWO optimization improved three RNN-GWO-based shows 8.05% MRB very susceptible floods. found SPI, LULC, TWI top five influential factors.

Language: Английский

Citations

7
Geospatial analysis of flood risk hazard in Zambezi Region, Namibia DOI Creative Commons
Zachariah Haruna Mshelia, Yong Sebastian Nyam, Deolfa Josè Moisès

et al.

Environmental Challenges, Journal Year: 2024, Volume and Issue: 15, P. 100915 - 100915

Published: April 1, 2024

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

Language: Английский

Citations

5
Flood Susceptibility Assessment for Improving the Resilience Capacity of Railway Infrastructure Networks DOI Open Access
Giada Varra, Renata Della Morte, Mario Tartaglia

et al.

Water, Journal Year: 2024, Volume and Issue: 16(18), P. 2592 - 2592

Published: Sept. 12, 2024

Floods often cause significant damage to transportation infrastructure such as roads, railways, and bridges. This study identifies several topographic, environmental, hydrological factors (slope, elevation, rainfall, land use cover, distance from rivers, geology, topographic wetness index, drainage density) influencing the safety of railway uses multi-criteria analysis (MCA) alongside an analytical hierarchy process (AHP) produce flood susceptibility maps within a geographic information system (GIS). The proposed methodology was applied catchment area track in southern Italy that heavily affected by destructive occurred autumn 2015. Two were obtained, one based on static geophysical another including triggering rainfall (dynamic). results showed large portions line are very highly susceptible zone. found be good agreement with post-disaster flood-induced infrastructural recorded along railway, whilst official inundation competent authorities fail supply about flooding occurring secondary tributaries direct rainfall. reliable identification sites floods may provide environmental useful for preparing disaster management action plans, risk analysis, targeted maintenance/monitoring programs, improving resilience capacity network. approach offer cost-effective strategy rapidly screening at regional/national levels could also other types linear transport infrastructures.

Language: Английский

Citations

4