AI-enabled strategies for climate change adaptation: protecting communities, infrastructure, and businesses from the impacts of climate change

H Jain, R Dhupper, A Shrivastava, D Kumar… - Computational Urban …, 2023 - Springer
Climate change is one of the most pressing global challenges we face today. The impacts of
rising temperatures, sea levels, and extreme weather events are already being felt around …

[HTML][HTML] A hybrid of ensemble machine learning models with RFE and Boruta wrapper-based algorithms for flash flood susceptibility assessment

A Habibi, MR Delavar, MS Sadeghian, B Nazari… - International Journal of …, 2023 - Elsevier
Flash floods are among the world most destructive natural disasters, and developing
optimum hybrid Machine Learning (ML) models for flash flood susceptibility (FFS) modeling …

A systematic literature review on classification machine learning for urban flood hazard mapping

M El baida, M Hosni, F Boushaba… - Water Resources …, 2024 - Springer
The computational expensiveness of the hydrodynamic models and the complexity of the
rainfall-runoff transformation process presents a pressing need to shift to machine learning …

[HTML][HTML] An XGBoost-SHAP approach to quantifying morphological impact on urban flooding susceptibility

M Wang, Y Li, H Yuan, S Zhou, Y Wang, RMA Ikram… - Ecological …, 2023 - Elsevier
Urban flooding risks, often overlooked by conventional methods, can be profoundly affected
by city configurations. However, explainable Artificial Intelligence could provide insights into …

Enhancing flood risk assessment through integration of ensemble learning approaches and physical-based hydrological modeling

M Saber, T Boulmaiz, M Guermoui… - … , Natural Hazards and …, 2023 - Taylor & Francis
This study aims to examine three machine learning (ML) techniques, namely random forest
(RF), LightGBM, and CatBoost for flooding susceptibility maps (FSMs) in the Vietnamese Vu …

Flood susceptibility modeling of the Karnali river basin of Nepal using different machine learning approaches

S Duwal, D Liu, PM Pradhan - Geomatics, Natural Hazards and …, 2023 - Taylor & Francis
Abstract The Karnali River Basin (KRB) comprises the longest river in Nepal, located south
of the Himalayas. Despite its high susceptibility to floods, the basin lacks detailed studies …

[HTML][HTML] Flood susceptibility mapping to improve models of species distributions

E Ebrahimi, MB Araújo, B Naimi - Ecological Indicators, 2023 - Elsevier
As significant ecosystem disturbances flooding events are expected to increase in both
frequency and severity due to climate change, underscoring the critical need to understand …

Flood susceptibility prediction using MaxEnt and frequency ratio modeling for Kokcha River in Afghanistan

AB Qasimi, V Isazade, R Berndtsson - Natural Hazards, 2024 - Springer
Flooding is a natural but unavoidable disaster that occurs over time. Flooding threatens
human life, property, and resources and affects regional and national economies. Through …

Leveraging machine learning and open-source spatial datasets to enhance flood susceptibility mapping in transboundary river basin

Y Bhattarai, S Duwal, S Sharma… - International Journal of …, 2024 - Taylor & Francis
Floods pose devastating effects on the resiliency of human and natural systems. flood risk
management challenges are typically complicated in the transboundary river basin due to …

[HTML][HTML] Machine learning models for gully erosion susceptibility assessment in the Tensift catchment, Haouz plain, Morocco for sustainable development

Y Bammou, B Benzougagh, O Abdessalam… - Journal of African Earth …, 2024 - Elsevier
Gully erosion is a widespread environmental danger, threatening global socio-economic
stability and sustainable development. This study comprehensively applied seven machine …