Assessment of Flood Disaster Risk in the Lancang–Mekong Region DOI Open Access
Qiang Sun, Wei Song, Ze Han

et al.

Water, Journal Year: 2024, Volume and Issue: 16(21), P. 3112 - 3112

Published: Oct. 30, 2024

The Lancang–Mekong Region encompasses six countries, covering an area exceeding five million square kilometers and containing a population of more than 400 million. Floods in this region may cause extremely serious losses lives property. However, due to the severe shortage flood disaster data, loss data meteorological monitoring assessment risks remains highly formidable. In view this, we systematically integrated from EM-DAT (the Emergency Events Database), Desinventar (a information management system), Reliefweb humanitarian service provided by United Nations Office for Coordination Humanitarian Affairs), ADRC Asian Disaster Reduction Center), coupled with GLDAS (Global Land Data Assimilation System) precipitation economic World Bank, comprehensively considered vulnerability, exposure, criteria assess Region. research findings are as follows: (1) From 1965 2017, total 370 floods occurred Region, among which proportion Vietnam Thailand combined was high 43.7%. contrast, number Qinghai Tibet China relatively small, only 1.89%. (2) When mild disasters occur, southern part Myanmar, western Thailand, northeastern faced large threats; when moderate central eastern Cambodia, comparatively high-loss areas mainly concentrated Vietnam. (3) Considering hazards comprehensively, high-risk distributed central–southern Vietnam, bordering Cambodia Vietnam; medium-risk Sichuan China; speaking, other have lower risk level. This can provide references regions scarce technical support prevention control well

Language: Английский

Enhancing flood susceptibility mapping in Meghna River basin by introducing ensemble Naive Bayes with stacking algorithms DOI Creative Commons
Abu Reza Md. Towfiqul Islam,

Md. Uzzal Mia,

Nílson Augusto Villa Nova

et al.

Geomatics Natural Hazards and Risk, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 13, 2025

Language: Английский

Citations

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

et al.

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 58, P. 102285 - 102285

Published: March 4, 2025

Language: Английский

Citations

0
SAR-driven flood inventory and multi-factor ensemble susceptibility modelling using machine learning frameworks DOI Creative Commons

Krishnagopal Halder,

Anitabha Ghosh,

Amit Kumar Srivastava

et al.

Geomatics Natural Hazards and Risk, Journal Year: 2024, Volume and Issue: 15(1)

Published: Oct. 16, 2024

Climate change has substantially increased both the occurrence and intensity of flood events, particularly in Indian subcontinent, exacerbating threats to human populations economic infrastructure. The present research employed novel ML models—LR, SVM, RF, XGBoost, DNN, Stacking Ensemble—developed Python environment leveraged 18 flood-influencing factors delineate flood-prone areas with precision. A comprehensive inventory, obtained from Sentinel-1 Synthetic Aperture Radar (SAR) data using Google Earth Engine (GEE) platform, provided empirical for entire model training validation. Model performance was assessed precision, recall, F1-score, accuracy, ROC-AUC metrics. results highlighted Ensemble's superior predictive ability (0.965), followed closely by, XGBoost (0.934), DNN (0.929), RF (0.925), LR (0.921), SVM (0.920) respectively, establishing feasibility applications disaster management. maps depicting susceptibility flooding generated by current provide actionable insights decision-makers, city planners, authorities responsible management, guiding infrastructural community resilience enhancements against risks.

Language: Английский

Citations

1
Flood mapping, damage assessment, and susceptibility zonation in northeastern Bangladesh in 2022 using geospatial datasets DOI Creative Commons
Mizanur Rahman, Mohammad Kamruzzaman, Limon Deb

et al.

Progress in Disaster Science, Journal Year: 2024, Volume and Issue: unknown, P. 100402 - 100402

Published: Dec. 1, 2024

Language: Английский

Citations

1
Assessment of Flood Disaster Risk in the Lancang–Mekong Region DOI Open Access
Qiang Sun, Wei Song, Ze Han

et al.

Water, Journal Year: 2024, Volume and Issue: 16(21), P. 3112 - 3112

Published: Oct. 30, 2024

The Lancang–Mekong Region encompasses six countries, covering an area exceeding five million square kilometers and containing a population of more than 400 million. Floods in this region may cause extremely serious losses lives property. However, due to the severe shortage flood disaster data, loss data meteorological monitoring assessment risks remains highly formidable. In view this, we systematically integrated from EM-DAT (the Emergency Events Database), Desinventar (a information management system), Reliefweb humanitarian service provided by United Nations Office for Coordination Humanitarian Affairs), ADRC Asian Disaster Reduction Center), coupled with GLDAS (Global Land Data Assimilation System) precipitation economic World Bank, comprehensively considered vulnerability, exposure, criteria assess Region. research findings are as follows: (1) From 1965 2017, total 370 floods occurred Region, among which proportion Vietnam Thailand combined was high 43.7%. contrast, number Qinghai Tibet China relatively small, only 1.89%. (2) When mild disasters occur, southern part Myanmar, western Thailand, northeastern faced large threats; when moderate central eastern Cambodia, comparatively high-loss areas mainly concentrated Vietnam. (3) Considering hazards comprehensively, high-risk distributed central–southern Vietnam, bordering Cambodia Vietnam; medium-risk Sichuan China; speaking, other have lower risk level. This can provide references regions scarce technical support prevention control well

Language: Английский

Citations

0