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Cities increasingly face flood risk primarily due to extensive changes of the natural land cover to built-up areas with impervious surfaces. In urban areas, flood impacts come mainly from road interruption. This paper proposes an urban…

Floods are one of nature's most catastrophic calamities which cause irreversible and immense damage to human life, agriculture, infrastructure and socio-economic system. Several studies on flood catastrophe management and flood forecasting…

Shallow water equations are extensively considered in the domains of oceans, atmospheric modelling, and engineering research (Franca et al., 2022), which play significant roles in floods and tsunami governance. Nonetheless, the accurate…

Fluid Dynamics · Physics 2023-09-22 Ruijia Yu

Floods are the most common form of natural disaster and accurate flood forecasting is essential for early warning systems. Previous work has shown that machine learning (ML) models are a promising way to improve flood predictions when…

Machine Learning · Computer Science 2025-04-18 Emil Ryd , Grey Nearing

The use of in-situ digital sensors for water quality monitoring is becoming increasingly common worldwide. While these sensors provide near real-time data for science, the data are prone to technical anomalies that can undermine the…

Floods are increasingly frequent natural disasters causing extensive human and economic damage, highlighting the critical need for rapid and accurate flood inundation mapping. While remote sensing technologies have advanced flood monitoring…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Tomohiro Tanaka , Narumasa Tsutsumida

The operational flood forecasting system by Google was developed to provide accurate real-time flood warnings to agencies and the public, with a focus on riverine floods in large, gauged rivers. It became operational in 2018 and has since…

Rapid delineation of flash flood extents is critical to mobilize emergency resources and to manage evacuations, thereby saving lives and property. Machine learning (ML) approaches enable rapid flood delineation with reduced computational…

Information on the depth of floodwater is crucial for rapid mapping of areas affected by floods. However, previous approaches for estimating floodwater depth, including field surveys, remote sensing, and machine learning techniques, can be…

Computer Vision and Pattern Recognition · Computer Science 2024-02-27 Temitope Akinboyewa , Huan Ning , M. Naser Lessani , Zhenlong Li

Flood extent mapping plays a crucial role in disaster management and national water forecasting. In recent years, high-resolution optical imagery becomes increasingly available with the deployment of numerous small satellites and drones.…

Computer Vision and Pattern Recognition · Computer Science 2021-01-11 Zhe Jiang , Arpan Man Sainju

Flood prediction is critical for emergency planning and response to mitigate human and economic losses. Traditional physics-based hydrodynamic models generate high-resolution flood maps using numerical methods requiring fine-grid…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Sun Han Neo , Sachith Seneviratne , Herath Mudiyanselage Viraj Vidura Herath , Abhishek Saha , Sanka Rasnayaka , Lucy Amanda Marshall

The hazard of pluvial flooding is largely influenced by the spatial and temporal dependence characteristics of precipitation. When extreme precipitation possesses strong spatial dependence, the risk of flooding is amplified due to catchment…

Applications · Statistics 2020-08-03 Gregory P. Bopp , Benjamin A. Shaby , Chris E. Forest , Alfonso Mejía

The accurate prediction of precipitation is important to allow for reliable warnings of flood or drought risk in a changing climate. However, to make trust-worthy predictions of precipitation, at a local scale, is one of the most difficult…

Computation · Statistics 2021-02-26 Sherman Lo , Peter Watson , Peter Dueben , Ritabrata Dutta

An overview of current debates and contemporary research devoted to the modeling of decision making processes and their facilitation directs attention to the Analytic Hierarchy Process (AHP). At the core of the AHP are various…

Artificial Intelligence · Computer Science 2020-06-05 Paul Thaddeus Kazibudzki

With the rapid development of data-driven machine learning (ML) models in meteorology, typhoon track forecasts have become increasingly accurate. However, current ML models still face challenges, such as underestimating typhoon intensity…

Atmospheric and Oceanic Physics · Physics 2024-08-26 Zeyi Niu , Wei Huang , Lei Zhang , Lin Deng , Haibo Wang , Yuhua Yang , Dongliang Wang , Hong Li

Predictive uncertainty in hydrological modelling is quantified by using post-processing or Bayesian-based methods. The former methods are not straightforward and the latter ones are not distribution-free (i.e. assumptions on the probability…

Applications · Statistics 2021-12-09 Hristos Tyralis , Georgia Papacharalampous

Flooding can damage pavement infrastructure significantly, causing both immediate and long-term structural and functional issues. This research investigates how flooding events affect pavement deterioration, specifically focusing on…

Machine Learning · Computer Science 2025-07-03 Lidan Peng , Lu Gao , Feng Hong , Jingran Sun

Sea-levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and…

Flooding is the most devastating phenomenon occurring globally, particularly in mountainous regions, risk dramatically increases due to complex terrains and extreme climate changes. These situations are damaging livelihoods, agriculture,…

Artificial Intelligence · Computer Science 2025-05-27 Haleema Bibi , Sadia Saleem , Zakia Jalil , Muhammad Nasir , Tahani Alsubait

One measurement modality for rainfall is a fixed location rain gauge. However, extreme rainfall, flooding, and other climate extremes often occur at larger spatial scales and affect more than one location in a community. For example, in…

Methodology · Statistics 2024-05-02 Carlynn Fagnant , Julia C. Schedler , Katherine B. Ensor