Flood Susceptibility Mapping and Accuracy Assesment of a River Floodplain Using Bivariate Statistical Methods and AHP Approach DOI
Prashant N. Pusdekar, Sanjay V. Dudul

2021 International Conference on Emerging Smart Computing and Informatics (ESCI), Год журнала: 2024, Номер unknown, С. 1 - 8

Опубликована: Март 5, 2024

Over the recent decades, world has witnessed frequent and devastating flood events with loss of life property. The focus this present study is Panchaganga River basin (PRB) in state Maharashtra, India, chosen as site for susceptibility mapping (FSM). Various models, including frequency ratio (FR), weight evidence (WoE), Analytical Hierarchy Process (AHP), an FA model (ensemble FR & AHP), were employed purpose. To facilitate study, a comprehensive inventory comprising 200 historical locations was prepared. 75 % samples selected training 25 testing model. FSM generated categorized into five zones namely, very high, moderate, low, no risk through application ArcGIS software. ROC curves plotted validation purpose AUC values 93.6 %, 91.6 95.5 FR, WoE respectively. This provides valuable insights residents living near River, aiding them relocating to safer areas during flooding events. Additionally, farmers PRB can employ information mitigate various losses resulting from disasters.

Язык: Английский

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

Shoukat Ali Shah,

Songtao Ai

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

Процитировано

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

Zarjes Kader,

Md Rabiul Islam, Md. Tareq Aziz

и другие.

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

Опубликована: Авг. 29, 2024

Язык: Английский

Процитировано

11
Improving flood hazard susceptibility assessment by integrating hydrodynamic modeling with remote sensing and ensemble machine learning DOI Creative Commons

Izhar Ahmad,

Rashid Farooq, Muhammad Ashraf

и другие.

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

Процитировано

1
Unveiling global flood hotspots: Optimized machine learning techniques for enhanced flood susceptibility modeling DOI Creative Commons
Mahdi Panahi, Khabat Khosravi, Fatemeh Rezaie

и другие.

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

Опубликована: Март 4, 2025

Язык: Английский

Процитировано

1
Flood Susceptibility Analysis with Integrated Geographic Information System and Analytical Hierarchy Process: A Multi-Criteria Framework for Risk Assessment and Mitigation DOI Open Access
Sujan Shrestha, Devendra Dahal, Bishal Poudel

и другие.

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

Процитировано

1
Flood susceptibility assessment and mapping using GIS-based analytical hierarchy process and frequency ratio models DOI Creative Commons
Saad Ashfaq, Muhammad Tufail, Abrar Niaz

и другие.

Global and Planetary Change, Год журнала: 2025, Номер unknown, С. 104831 - 104831

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

1
Flood susceptibility mapping of Cheongju, South Korea based on the integration of environmental factors using various machine learning approaches DOI
Liadira Kusuma Widya, Fatemeh Rezaie, Woojin Lee

и другие.

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

Опубликована: Июнь 13, 2024

Язык: Английский

Процитировано

9
Assessment of spatial cyclone surge susceptibility through GIS-based AHP multi-criteria analysis and frequency ratio: a case study from the Bangladesh coast DOI Creative Commons
Abdullah Al Mamun, Li Zhang, Bowei Chen

и другие.

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

Процитировано

6
Assessment of flood susceptibility in Sylhet using analytical hierarchy process and geospatial technique DOI Creative Commons
Md. Saalim Shadmaan,

K.M. Hassan

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

Опубликована: Июль 1, 2024

Язык: Английский

Процитировано

5
GIS-based MCDM approach for landslide hazard zonation mapping in east Gojjam zone, central Ethiopia DOI Creative Commons
Chalachew Tesfa,

Demeke Sewnet

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

Процитировано

5