[HTML][HTML] Flood susceptibility mapping: Integrating machine learning and GIS for enhanced risk assessment

Z Demissie, P Rimal, WM Seyoum, A Dutta… - Applied Computing and …, 2024 - Elsevier
Flooding presents a formidable challenge in the United States, endangering lives and
causing substantial economic damage, averaging around $5 billion annually. Addressing …

[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 …

Comparison of hydrological modeling, artificial neural networks and multi-criteria decision making approaches for determining flood source areas

E Mahmoodi, M Azari, MT Dastorani… - Water Resources …, 2024 - Springer
Flood risk management is a critical task which necessitates flood forecasting and identifying
flood source areas for implementation of prevention measures. Hydrological models, multi …

[HTML][HTML] Integrated evaluation and attribution of urban flood risk mitigation capacity: A case of Zhengzhou, China

K Dai, S Shen, C Cheng, Y Song - Journal of Hydrology: Regional Studies, 2023 - Elsevier
Abstract Study region The Zhengzhou City in China Study focus Urban flood risk mitigation
(UFRM) refers to the runoff retention capacity of land surface in urban regions. Previous …

Novel optimized deep learning algorithms and explainable artificial intelligence for storm surge susceptibility modeling and management in a flood-prone island

MJ Alshayeb, HT Hang, AAA Shohan, AA Bindajam - Natural Hazards, 2024 - Springer
Sagar Island, located in the Indian Sundarbans Delta, is extremely vulnerable to storm surge
flooding. Therefore, there is a need for a precise model to assess its susceptibility to storm …

Assessing critical flood-prone districts and optimal shelter zones in the Brahmaputra Valley: Strategies for effective flood risk management

J Debnath, D Sahariah, G Meraj, K Chand… - … of the Earth, Parts A/B/C, 2024 - Elsevier
Frequent flooding has become a persistent issue in floodplain regions, causing significant
disasters during each rainy season due to insufficient disaster management planning. This …

Flood susceptibility mapping using ANNs: a case study in model generalization and accuracy from Ontario, Canada

R Khalid, UT Khan - Geocarto International, 2024 - Taylor & Francis
Accurate flood susceptibility mapping (FSM) is critical for mitigating the environmental, social
and economic consequences of floods. The influence of model generalizability onto new …

Enhancing real-time flood forecasting and warning system by integrating ensemble techniques and hydrologic model simulations

A Patel, SM Yadav, R Teegavarapu - Journal of Water and Climate …, 2024 - iwaponline.com
Flooding poses a severe threat to communities and infrastructure worldwide, which requires
advanced flood forecasting warning systems. In this research paper, a real-time flood …

Assessment of Flash Flood Risk Using Random Forest Regression Model Integrated with Binary Statistics

X Fang, M Liao, L Yang, X Jiang, J Jin… - IGARSS 2024-2024 …, 2024 - ieeexplore.ieee.org
Flash floods are one of natural disasters that result in significant economic losses and
human casualties. Previous studies on flash flood assessment generally applied binary or …

Predicting flood-prone areas using generalized linear and maximum entropy machine learning models

A Hanifinia, H Abghari - Journal of Natural Environmental Hazards, 2024 - jneh.usb.ac.ir
The purpose of this study is to identify the effective factors, prepare flood risk prediction
maps using machine learning models, and finally evaluate the efficiency of these models in …