Classification of Short-term Flood Events Using Stochastic Variable Selection and Gaussian Naïve Bayes Classifier: A Case Study of Sirajganj district, Bangladesh.

Heliyon, Journal Year: 2025, Volume and Issue: 11(2), P. e41941 - e41941

Published: Jan. 1, 2025

Around the world, catastrophes caused by flooding are occurring naturally that cause a great deal of fatalities and financial loss. The loss life property can be considerably reduced with precise flood forecasts. complexity many predicting techniques makes results difficult to interpret, compromising process's core goal. This study uses quick flexible Gaussian Naïve Bayes (GNB) classifier categorize eight different years as flooded or non-flooded based on predictor variables obtained via Mutual Information (MI) technique. During search, all-sky surface shortwave downward irradiance is identified optimum variable out nineteen stochastic variables, highest sensitivity for model accuracy. then validated using four iterations derived from MAPE GNB classification method Twenty-five percent mean error rates 4-fold cross-validation indicate this suitable forecasting. high rate short amount data utilized training data, requires huge records get effective results. research could aid in development evaluation hydrological projects Sirajganj district.

Language: Английский

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Research on regional economic development and natural disaster risk assessment under the goal of carbon peak and carbon neutrality: A case study in Chengdu-Chongqing economic circle

Land Use Policy, Journal Year: 2024, Volume and Issue: 143, P. 107206 - 107206

Published: May 28, 2024

Language: Английский

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Optimized green infrastructure planning at the city scale based on an interpretable machine learning model and multi-objective optimization algorithm: A case study of central Beijing, China

Landscape and Urban Planning, Journal Year: 2024, Volume and Issue: 252, P. 105191 - 105191

Published: Aug. 19, 2024

Language: Английский

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Land use assessment under dynamic evolution: Multi-objective optimization and multi-scenario simulation analysis

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 373, P. 123456 - 123456

Published: Nov. 29, 2024

Language: Английский

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Attribution analysis of urban social resilience differences under rainstorm disaster impact: Insights from interpretable spatial machine learning framework

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: unknown, P. 106029 - 106029

Published: Dec. 1, 2024

Language: Английский

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Dempster–Shafer theory-based information fusion for natural disaster emergency management: A systematic literature review

Information Fusion, Journal Year: 2024, Volume and Issue: 112, P. 102585 - 102585

Published: July 18, 2024

Language: Английский

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An integrated assessment of urban flooding risk and resilience based on spatial grids

Urban Water Journal, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 12

Published: Jan. 2, 2025

During heavy rainfall events, stormwater exceeds the drainage capacity and overflows onto urban surface, causing flooding problems. Risk resilience assess severity recovery characteristics of damage from static dynamic perspectives independently. This work proposes a spatial grid-based integrated risk-resilience assessment framework for to consider both risk aspects at detailed level. The formulates an drainage-surface coupled model simulate inundation process. A classification method is proposed identify flood-affected each grid, with values considering socio-economic step-by-step dynamics. According case results discussion, classifies all grids into four types different levels, in which 7.02% are identified as worst type high low resilience. enables detailed-level targeted management

Language: Английский

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Integrating machine learning with the Minimum Cumulative Resistance Model to assess the impact of urban land use on road waterlogging risk

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 132842 - 132842

Published: Feb. 1, 2025

Language: Английский

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Comprehensive analysis of data aggregation techniques for flood vulnerability and bivariate flood risk mapping of a coastal urban floodplain

International Journal of Disaster Risk Reduction, Journal Year: 2025, Volume and Issue: unknown, P. 105330 - 105330

Published: Feb. 1, 2025

Language: Английский

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The cost of flooding on housing under climate change in the Philippines: Examining projected damage at the local scale

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

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