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Related papers: Regional Flood Risk Projections under Climate Chan…

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Extreme streamflow is a key indicator of flood risk, and quantifying the changes in its distribution under non-stationary climate conditions is key to mitigating the impact of flooding events. We propose a non-stationary process mixture…

Methodology · Statistics 2024-05-08 Reetam Majumder , Brian Reich

Numerical simulation models associated with hydraulic engineering take a wide array of data into account to produce predictions: rainfall contribution to the drainage basin (characterized by soil nature, infiltration capacity and moisture),…

Computational Engineering, Finance, and Science · Computer Science 2021-03-01 Corentin J. Lapeyre , Nicolas Cazard , Pamphile T. Roy , Sophie Ricci , Fabrice Zaoui

As climate change intensifies, the urgency for accurate global-scale disaster predictions grows. This research presents a novel multimodal disaster prediction framework, combining weather statistics, satellite imagery, and textual insights.…

Machine Learning · Computer Science 2023-10-02 Gengyin Liu , Huaiyang Zhong

To improve the efficiency of flood early warning systems (FEWS), it is important to understand the interactions between natural and social systems. The high level of trust in authorities and experts is necessary to improve the likeliness of…

Geophysics · Physics 2021-10-01 Yohei Sawada , Rin Kanai , Hitomu Kotani

Understanding flood probabilities is essential to making sound decisions about flood-risk management. Many people rely on flood probability maps to inform decisions about purchasing flood insurance, buying or selling real-estate,…

Applications · Statistics 2020-12-22 Mahkameh Zarekarizi , K. Joel Roop-Eckart , Sanjib Sharma , Klaus Keller

Floods are highly uncertain events, occurring in different regions, with varying prerequisites and intensities. A highly reliable flood disaster risk map can help reduce the impact of floods for flood management, disaster decreasing, and…

Applications · Statistics 2021-07-06 Hongping Zhang , Zhenfeng Shao , Jinqi Zhao , Xiao Huang , Jie Yang , Bin Hu , Wenfu Wu

Flood risk changes in time and is influenced by both natural and socio-economic trends and interactions. In Europe, previous studies of historical flood losses corrected for demographic and economic growth ("normalized") have been limited…

This paper presents a methodology for freight traffic assignment in a large-scale road-rail intermodal network under uncertainty. Network uncertainties caused by natural disasters have dramatically increased in recent years. Several of…

Optimization and Control · Mathematics 2024-01-08 Majbah Uddin , Nathan Huynh , Fahim Ahmed

Concurrent floods and concurrent droughts in nearby catchments pose challenges to risk assessment and water management. Climate change is affecting extremely high and low discharge, but the complex interplay between changes in individual…

Applications · Statistics 2026-04-24 C. J. R. Murphy-Barltrop , J. Richards , B. Poschlod , A. Sasse , J. Zscheischler

Wildfires pose a significant threat to ecosystems, wildlife, and human communities, leading to habitat destruction, pollutant emissions, and biodiversity loss. Accurate wildfire risk prediction is crucial for mitigating these impacts and…

Machine Learning · Computer Science 2025-06-17 Zhengsen Xu , Jonathan Li , Sibo Cheng , Xue Rui , Yu Zhao , Hongjie He , Haiyan Guan , Aryan Sharma , Matthew Erxleben , Ryan Chang , Linlin Xu

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

Internal climate variability arises from the climate system's inherently chaotic dynamics. Quantifying it is essential for climate science, as it enables risk-based decision-making and differentiates between externally forced change and…

This paper presents a forecasting model designed using WSNs (Wireless Sensor Networks) to predict flood in rivers using simple and fast calculations to provide real-time results and save the lives of people who may be affected by the flood.…

Machine Learning · Computer Science 2012-03-13 Victor Seal , Arnab Raha , Shovan Maity , Souvik Kr Mitra , Amitava Mukherjee , Mrinal Kanti Naskar

Regression-based frameworks for streamflow regionalization are built around catchment attributes that traditionally originate from catchment hydrology, flood frequency analysis and their interplay. In this work, we deviated from this…

Methodology · Statistics 2022-06-22 Georgia Papacharalampous , Hristos Tyralis

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

Reliable prediction of river floods in the first 72 hours can reduce harm because emergency agencies have sufficient time to prepare and deploy for help at the scene. Such river flood prediction models already exist and perform relatively…

The prediction of streamflows and other environmental variables in unmonitored basins is a grand challenge in hydrology. Recent machine learning (ML) models can harness vast datasets for accurate predictions at large spatial scales.…

Machine Learning · Computer Science 2024-10-29 Jared D. Willard , Fabio Ciulla , Helen Weierbach , Vipin Kumar , Charuleka Varadharajan

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

Hydrodynamic flood modeling improves hydrologic and hydraulic prediction of storm events. However, the computationally intensive numerical solutions required for high-resolution hydrodynamics have historically prevented their implementation…

Machine Learning · Computer Science 2023-07-06 Francisco Haces-Garcia , Natalya Maslennikova , Craig L Glennie , Hanadi S Rifai , Vedhus Hoskere , Nima Ekhtari

The astounding success of these methods has made it imperative to obtain more explainable and trustworthy estimates from these models. In hydrology, basin characteristics can be noisy or missing, impacting streamflow prediction. For solving…

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