Flood susceptibility mapping contributes to disaster risk reduction: A case study in Sindh, Pakistan

International Journal of Disaster Risk Reduction, Год журнала: 2024, Номер 108, С. 104503 - 104503

Опубликована: Апрель 23, 2024

Floods are a widespread and damaging natural phenomenon that causes harm to human lives, resources, property has agricultural, eco-environmental, economic impacts. Therefore, it is crucial perform flood susceptibility mapping (FSM) identify susceptible zones mitigate reduce damage. This study assessed the damage caused by 2022 flash in Sindh identified flood-susceptible based on frequency ratio (FR) analytical hierarchy process (AHP) models. Flood inventory maps were generated, containing 150 sampling points, which manually selected from Landsat imagery. The points split into 70% for training 30% validating results. Furthermore, fourteen conditioning factors considered analysis developing FSM. final FSM categorized five zones, representing levels very low high. results areas under high Ghotki (FR 4.42% AHP 5.66%), Dadu 21.40% 21.29%), Sanghar 6.81% 6.78%). Ultimately, accuracy was evaluated using receiver operating characteristics area curve method, resulting 82%, 83%), 91%, 90%), 96%, 95%). enhances scientific understanding of impacts across diverse regions emphasizes importance accurate informed decision-making. findings provide valuable insights supportive policymakers, agricultural planners, stakeholders engaged risk management adverse consequences floods.

Язык: Английский

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

Sustainable Water Resources Management, Год журнала: 2024, Номер 10(5)

Опубликована: Авг. 29, 2024

Язык: Английский

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Improving flood hazard susceptibility assessment by integrating hydrodynamic modeling with remote sensing and ensemble machine learning

Natural Hazards, Год журнала: 2025, Номер unknown

Опубликована: Янв. 11, 2025

Abstract Floods are natural disasters with significant economic and infrastructural impacts. Assessing flood susceptibility in mountainous urban regions is particularly challenging due to the complicated interaction which structures terrain affect behavior. This study employs two ensemble machine learning algorithms, Extreme Gradient Boosting (XGBoost) Random Forest (RF), develop maps for Hunza-Nagar region, has been experiencing frequent flooding past three decades. An unsteady flow simulation carried out HEC-RAS utilizing a 100-year return period hydrograph as an input boundary condition, output of provided spatial inundation extents necessary developing inventory. Ten explanatory factors, including climatic, geological, geomorphological features namely elevation, slope, curvature, topographic wetness index (TWI), normalized difference vegetation (NDVI), land use cover (LULC), rainfall, lithology, distance roads rivers considered mapping. For inventory, random sampling technique adopted create repository non-flood points, incorporating ten geo-environmental conditioning factors. The models’ accuracy assessed using area under curve (AUC) receiver operating characteristics (ROC). prediction rate AUC values 0.912 RF 0.893 XGBoost, also demonstrating superior performance accuracy, precision, recall, F1-score, kappa evaluation metrics. Consequently, model selected represent map area. resulting will assist national disaster management infrastructure development authorities identifying high susceptible zones carrying early mitigation actions future floods.

Язык: Английский

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Unveiling global flood hotspots: Optimized machine learning techniques for enhanced flood susceptibility modeling

Journal of Hydrology Regional Studies, Год журнала: 2025, Номер 58, С. 102285 - 102285

Опубликована: Март 4, 2025

Язык: Английский

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Flood Susceptibility Analysis with Integrated Geographic Information System and Analytical Hierarchy Process: A Multi-Criteria Framework for Risk Assessment and Mitigation

Water, Год журнала: 2025, Номер 17(7), С. 937 - 937

Опубликована: Март 23, 2025

Flooding is among the most destructive natural disasters globally, and it inflicts severe damage on both environments human-made structures. The frequency of floods has been increasing due to unplanned urbanization, climate change, changes in land use. Flood susceptibility maps help identify at-risk areas, supporting informed decisions disaster preparedness, risk management, mitigation. This study aims generate a flood map for Davidson County Tennessee using an integrated geographic information system (GIS) analytical hierarchical process (AHP). In this study, ten causative factors are employed flood-prone zones. AHP, form weighted multi-criteria decision analysis, applied assess relative impact weights these factors. Subsequently, into ArcGIS Pro (Version 3.3) create area overlay approach. resulting classified county five zones: very low (17.48%), (41.89%), moderate (37.53%), high (2.93%), (0.17%). FEMA hazard used validate created from Ultimately, comparison reinforced accuracy reliability assessment GIS AHP

Язык: Английский

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Flood susceptibility mapping of Cheongju, South Korea based on the integration of environmental factors using various machine learning approaches

Journal of Environmental Management, Год журнала: 2024, Номер 364, С. 121291 - 121291

Опубликована: Июнь 13, 2024

Язык: Английский

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Assessment of spatial cyclone surge susceptibility through GIS-based AHP multi-criteria analysis and frequency ratio: a case study from the Bangladesh coast

Geomatics Natural Hazards and Risk, Год журнала: 2024, Номер 15(1)

Опубликована: Июль 3, 2024

Tropical cyclones, including surge inundation, are a common event in the coastal regions of Bangladesh. The washes out area within very short period and remains flooded condition for several days. Spatial analysis to understand susceptibility level can assist cyclone management system. Surge could be one most essential parts disaster risk reduction through which vulnerability minimized. A Geographic Information Systems-based analytical hierarchy process (AHP) multi-criteria bivariate frequency ratio (FR) techniques were conducted cyclone-prone on Bangladesh coast. total 10 criteria considered influential flooding, i.e. Topographic Wetness Index, elevation, wind velocity, slope, distance from sea rivers, drainage density, Land Use Cover, Normalized Difference Vegetation precipitation, soil types. final maps categorized into five classes, low, moderate, high, high. Conferring these policymakers make decisions future land use activities. According this research, AHP showed better precision (Receiver Operating Characteristic) than FR prediction

Язык: Английский

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Assessment of flood susceptibility in Sylhet using analytical hierarchy process and geospatial technique

GEOMATICA, Год журнала: 2024, Номер 76(1), С. 100003 - 100003

Опубликована: Июль 1, 2024

Язык: Английский

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GIS-based MCDM approach for landslide hazard zonation mapping in east Gojjam zone, central Ethiopia

Quaternary Science Advances, Год журнала: 2024, Номер 15, С. 100210 - 100210

Опубликована: Июнь 24, 2024

Landslides are prevalent in the Ethiopian highlands, particularly east Gojjam zone, which is highly affected by landslide problems. This research was carried out northwestern Ethiopia. The study area part of an economically important country, and it main source water for Grand Renaissance Dam (GERD). objective this work to undertake a detailed inventory past locations prediction present future hazards, as well preparation zonation map East zone using Analytical Hierarchy Process (AHP) with GIS technique. parameters used were slope degree, aspect, land use cover, road proximity, rainfall, lithology, altitude, river proximity. various causative collected from field, suitable modifications made thematic maps. Finally, ratings basis prepare LHZ windows. susceptibility mapping produced environment. results show that driving factors hazards manmade activities. Validation revealed more than 80% landslides match within "high hazard zone" reasonably accepted rationality adopted methodology. considered parameters, their evaluation production LHZ-Map, confirmed. very urban planners, agricultural studies, environmentalists, hazardous prevention mitigation strategies.

Язык: Английский

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Flood susceptibility and flood frequency modeling for lower Kosi Basin, India using AHP and Sentinel-1 SAR data in geospatial environment

Natural Hazards, Год журнала: 2024, Номер 120(13), С. 11579 - 11610

Опубликована: Май 31, 2024

Язык: Английский

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