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Related papers: The FLOod Probability Interpolation Tool (FLOPIT):…

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Physically-based overland flow models are computationally demanding, hindering their use for real-time applications. Therefore, the development of fast (and reasonably accurate) overland flow models is needed if they are to be used to…

Computers and Society · Computer Science 2018-10-08 Joao P. Leitao , Mohamed Zaghloul , Vahid Moosavi

Flood forecasts are crucial for effective individual and governmental protective action. The vast majority of flood-related casualties occur in developing countries, where providing spatially accurate forecasts is a challenge due to…

Machine Learning · Computer Science 2019-10-31 Zvika Ben-Haim , Vladimir Anisimov , Aaron Yonas , Varun Gulshan , Yusef Shafi , Stephan Hoyer , Sella Nevo

Visualization is an essential operation when assessing the risk of rare events such as coastal or river floodings. The goal is to display a few prototype events that best represent the probability law of the observed phenomenon, a task…

Homeowners around the world elevate houses to manage flood risks. Deciding how high to elevate a house poses a nontrivial decision problem. The U.S. Federal Emergency Management Agency (FEMA) recommends elevating existing houses to the Base…

Applications · Statistics 2021-01-27 Mahkameh Zarekarizi , Vivek Srikrishnan , Klaus Keller

Data-driven flood forecasting methods are useful, especially for the rivers that lack hydrological information to build physical models. Although these former methods can forecast river stages using only past water levels and rainfall data,…

Geophysics · Physics 2021-04-07 Shunya Okuno , Koji Ikeuchi , Kazuyuki Aihara

In an era of escalating climate change, urban flooding has emerged as a critical challenge for sustainable cities, threatening lives, infrastructure, and ecosystems. Traditional flood detection methods are constrained by their reliance on…

Computer Vision and Pattern Recognition · Computer Science 2025-09-11 Shahid Shafi Dar , Bharat Kaurav , Arnav Jain , Chandravardhan Singh Raghaw , Mohammad Zia Ur Rehman , Nagendra Kumar

Timely, accurate, and reliable information is essential for decision-makers, emergency managers, and infrastructure operators during flood events. This study demonstrates a proposed machine learning model, MaxFloodCast, trained on…

Machine Learning · Computer Science 2023-08-14 Cheng-Chun Lee , Lipai Huang , Federico Antolini , Matthew Garcia , Andrew Juanb , Samuel D. Brody , Ali Mostafavi

With the escalating frequency of floods posing persistent threats to human life and property, satellite remote sensing has emerged as an indispensable tool for monitoring flood hazards. SpaceNet8 offers a unique opportunity to leverage…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Yanbing Bai , Zihao Yang , Jinze Yu , Rui-Yang Ju , Bin Yang , Erick Mas , Shunichi Koshimura

Flooding remains a major global challenge, worsened by climate change and urbanization, demanding advanced solutions for effective disaster management. While traditional 2D flood mapping techniques provide limited insights, 3D flood…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Wenfeng Jia , Bin Liang , Yuxi Liu , Muhammad Arif Khan , Lihong Zheng

Identifying flood affected areas in remote sensing data is a critical problem in earth observation to analyze flood impact and drive responses. While a number of methods have been proposed in the literature, there are two main limitations…

Computer Vision and Pattern Recognition · Computer Science 2024-03-07 Xavier Bou , Thibaud Ehret , Rafael Grompone von Gioi , Jeremy Anger

Flood frequency analysis is usually based on the fitting of an extreme value distribution to the local streamflow series. However, when the local data series is short, frequency analysis results become unreliable. Regional frequency…

Applications · Statistics 2008-02-05 Mathieu Ribatet , Eric Sauquet , Jean-Michel Grésillon , Taha B. M. J. Ouarda

Flooding is a destructive and dangerous hazard and climate change appears to be increasing the frequency of catastrophic flooding events around the world. Physics-based flood models are costly to calibrate and are rarely generalizable…

Machine Learning · Computer Science 2019-10-16 Chelsea Sidrane , Dylan J Fitzpatrick , Andrew Annex , Diane O'Donoghue , Yarin Gal , Piotr Biliński

Modeling continuous-time dynamics from sparse and irregularly-sampled time series remains a fundamental challenge. Neural controlled differential equations provide a principled framework for such tasks, yet their performance is highly…

Machine Learning · Computer Science 2026-04-03 YongKyung Oh , Dong-Young Lim , Sungil Kim

Flood simulation and forecast capability have been greatly improved thanks to advances in data assimilation. Such an approach combines in-situ gauge measurements with numerical hydrodynamic models to correct the hydraulic states and reduce…

Image and Video Processing · Electrical Eng. & Systems 2022-02-07 Thanh Huy Nguyen , Sophie Ricci , Christophe Fatras , Andrea Piacentini , Anthéa Delmotte , Emeric Lavergne , Peter Kettig

Prior literature has argued that flood insurance maps may not capture the extent of flood risk. This paper performs a granular assessment of coastal flood risk in the mortgage market by using physical simulations of hurricane storm surge…

General Economics · Economics 2020-06-11 Amine Ouazad

Floods are the most common and among the most severe natural disasters in many countries around the world. As global warming continues to exacerbate sea level rise and extreme weather, governmental authorities and environmental agencies are…

Applications · Statistics 2021-10-07 Lauren Ansell , Luciana Dalla Valle

Floods are among the most common and deadly natural disasters in the world, and flood warning systems have been shown to be effective in reducing harm. Yet the majority of the world's vulnerable population does not have access to reliable…

Atmospheric and Oceanic Physics · Physics 2020-12-08 Sella Nevo , Gal Elidan , Avinatan Hassidim , Guy Shalev , Oren Gilon , Grey Nearing , Yossi Matias

Floods can be very destructive causing heavy damage to life, property, and livelihoods. Global climate change and the consequent sea-level rise have increased the occurrence of extreme weather events, resulting in elevated and frequent…

Machine Learning · Computer Science 2023-10-12 Jimeng Shi , Vitalii Stebliankin , Zhaonan Wang , Shaowen Wang , Giri Narasimhan

Risk communication seeks to develop a shared understanding of disaster among stakeholders, thereby amplifying public awareness and empowering them to respond more effectively to emergencies. However, existing studies have overemphasized…

Computational Engineering, Finance, and Science · Computer Science 2025-12-04 Weilian Li , Jun Zhu , Saied Pirasteh , Qing Zhu , Yukun Guo , Lan Luo , Youness Dehbi

Floods are among the most destructive natural disasters, which are highly complex to model. The research on the advancement of flood prediction models contributed to risk reduction, policy suggestion, minimization of the loss of human life,…

Machine Learning · Computer Science 2020-08-10 Amir Mosavi , Pinar Ozturk , Kwok-wing Chau