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

Exploring rainfall-driven climate hazards using the climate hazard index and historical data from ERA5 (study case: Indonesia) DOI

Ismail Robbani,

Joko Wiratmo,

Armi Susandi

et al.

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(3)

Published: Feb. 11, 2025

Language: Английский

Citations

1
Flood risk modelling by the synergistic approach of machine learning and best-worst method in Indus Kohistan, Western Himalaya DOI Creative Commons
Ashfaq Ahmad, Jiangang Chen, Xiaohong Chen

et al.

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

Published: Feb. 25, 2025

Language: Английский

Citations

0
The cost of flooding on housing under climate change in the Philippines: Examining projected damage at the local scale DOI Creative Commons
Isaac Besarra, Aaron Opdyke, Jerico E. Mendoza

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 124966 - 124966

Published: March 18, 2025

While the Philippines has made significant strides in proactive disaster risk reduction measures, current planning actions are undertaken primarily based on historical flood risk. There gaps understanding how escalating impacts of climate change will alter dynamics. This study examines shifting local patterns Municipality Carigara Leyte. We quantify probabilistic damage residential structures for early, mid-, and late-term scenarios under RCP4.5 RCP8.5 pathways. By utilising localised housing vulnerability functions, we assess trends at a household level, considering concrete, light material, elevated material typologies. Our results indicate 3 % decrease future damages to RCP 4.5 34 8.5 by 2100 attributable 100-year events. These shifts highlight nuances regional changes over next century. The findings provide insights into climate-risk assessments municipalities might be established as entry points inform policies projects. Through mechanisms such Local Disaster Risk Reduction Management Funds (LDRRMF) Philippines, propose methods climate-informed decision-making government units minimise scenarios.

Language: Английский

Citations

0
Evaluating the impact of gridded population datasets variability on flood exposure estimates across South Asia DOI Creative Commons

Jiahui Zhang,

Yun Xing,

Sanjit Kumar Mondal

et al.

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

Published: March 21, 2025

Language: Английский

Citations

0
Advancing flood risk assessment: Multitemporal SAR-based flood inventory generation using transfer learning and hybrid fuzzy-AHP-machine learning for flood susceptibility mapping in the Mahananda River Basin DOI Creative Commons
Chiranjit Singha, Satiprasad Sahoo,

Alireza Bahrami Mahtaj

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 124972 - 124972

Published: March 23, 2025

The Mahananda River basin, located in Eastern India, faces escalating flood risks due to its complex hydrology and geomorphology, threatening socioeconomic environmental stability. This study presents a novel approach susceptibility (FS) mapping updates the region's inventory. Multitemporal Sentinel-1 (S1) SAR images (2020-2022) were processed using U-Net transfer learning model generate water body frequency map, which was integrated with Global Flood Dataset (2000-2018) refined through grid-based classification create an updated Eleven geospatial layers, including elevation, slope, soil moisture, precipitation, type, NDVI, Land Use Cover (LULC), wind speed, drainage density, runoff, used as conditioning factors (FCFs) develop hybrid FS approach. integrates Fuzzy Analytic Hierarchy Process (FuzzyAHP) six machine (ML) algorithms models FuzzyAHP-RF, FuzzyAHP-XGB, FuzzyAHP-GBM, FuzzyAHP-avNNet, FuzzyAHP-AdaBoost, FuzzyAHP-PLS. Future trends (1990-2030) projected CMIP6 data under SSP2-4.5 SSP5-8.5 scenarios MIROC6 EC-Earth3 ensembles. SHAP algorithm identified LULC, type most influential FCFs, contributing over 60 % susceptibility. Results show that 31.10 of basin is highly susceptible flooding, western regions at greatest risk low elevation high density. projections indicate 30.69 area will remain vulnerable, slight increase SSP5-8.5. Among models, FuzzyAHP-XGB achieved highest accuracy (AUC = 0.970), outperforming FuzzyAHP-GBM 0.968) FuzzyAHP-RF 0.965). experimental results showed proposed can provide spatially well-distributed inventory derived from freely available remote sensing (RS) datasets robust framework for long-term assessment ML techniques. These findings offer critical insights improving management mitigation strategies basin.

Language: Английский

Citations

0
Dam break analysis of the Nagmati and Dhap dams using HEC-RAS DOI Creative Commons
Pratik Khanal, Sushil Paudel,

R.K. Neupane

et al.

H2Open Journal, Journal Year: 2025, Volume and Issue: 8(3), P. 139 - 156

Published: April 18, 2025

ABSTRACT This study examines the risks, vulnerability, and potential impacts of dam breaches, focusing on Dhap Nagmati dams in Kathmandu, Nepal. These are constructed to enhance river flow, but pose a risk breaching, potentially causing severe damage, loss life, inundation UNESCO World Heritage Sites. Despite these consequences, have not been comprehensively investigated no detailed scientific analysis has conducted. aimed assess effect breaches under overtopping mode failure prepare flood hazard vulnerability maps. The employs Hydrologic Engineering Center-River Analysis System simulate unsteady flow corresponding probable maximum flood, with mapping based general curves guidelines. results show peak discharges 27,835 1,064 m³/s velocities 27.2 7.27 m/s for respectively. Sites fall H6 H5 zones after breach, breach height being most sensitive parameter. finding highlights impact breaching helps land use planning, emergency response, mitigation reduce life property.

Language: Английский

Citations

0
Intelligent Methods for Estimating the Flood Susceptibility in the Danube Delta, Romania DOI Open Access
Romulus Costache, Anca Crăciun, Nicu Ciobotaru

et al.

Water, Journal Year: 2024, Volume and Issue: 16(23), P. 3511 - 3511

Published: Dec. 6, 2024

Floods, along with other natural and anthropogenic disasters, profoundly disrupt both society the environment. Populations residing in deltaic regions worldwide are particularly vulnerable to these threats. A prime example is Danube Delta (DD), located Romanian sector of Black Sea. This research paper aims identify areas within DD that highly or very susceptible flooding. To accomplish this, we employed a combination multicriteria decision-making (AHP) artificial intelligence (AI) techniques, including deep learning neural networks (DLNNs), support vector machines (SVMs), multilayer perceptron (MLP). The input data comprised previously flooded alongside eight geographical factors. All models identified high flood potential over 65% studied area. models’ performance was assessed using receiver operating characteristic (ROC) analysis, demonstrating excellent outcomes evaluated by area under curve (AUC) exceeding 0.908. study significant as it lays groundwork for implementing measures against impacts DD.

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