Results 161 to 170 of about 4,070 (242)

Data-driven flood susceptibility assessment using hybrid machine learning and optimization techniques: case of the Sedrata Watershed, NE Algeria. [PDF]

Sci Rep
Mechentel E, Dairi S, Lefkir A, Eslamian S, Abida H, Djebbar Y.   +5 more
europepmc   +1 more source

Floods From Space: How Remote Sensing, AI, and Cloud Platforms Are Reshaping Disaster Risk Reduction

Journal of Flood Risk Management, Volume 19, Issue 3, September 2026.
ABSTRACT Flooding remains one of the most damaging climate‐related hazards globally, yet flood remote sensing has historically developed largely along sensor‐specific pathways. This review addresses the need for a systematic and decision‐oriented synthesis of how space‐borne remote sensing has evolved toward integrated flood monitoring and disaster ...
Ricky Anak Kemarau, Nurfashareena Muhamad, Aida Soraya Shamsuddin, Zulfaqar Sa'adi, Zaini Sakawi, Oliver Valentine Eboy, Nik Norliati Fitri Md Nor   +6 more
wiley   +1 more source

What defines a flood. [PDF]

Commun Earth Environ
Majszak M, Zaki A, Wani O.
europepmc   +1 more source

Diagnosing Post‐Wildfire Flood Governance Gaps Through a Values–Rules–Knowledge Lens: A Case Study From Kineta, Greece

Journal of Flood Risk Management, Volume 19, Issue 3, September 2026.
ABSTRACT Post‐wildfire flash floods are an escalating climate‐driven hazard. Advanced technical modelling can now inform impact assessments and evaluate interventions to mitigate these risks, yet such analyses are often not supported by adequate governance frameworks to facilitate the implementation of the proposed solutions.
Angelos Alamanos, Russell M. Wise, Stefanos Xenarios, George Papaioannou, Vassiliki Markogianni, George Varlas, Angelos Plataniotis, Anastasios Papadopoulos, Elias Dimitriou, Phoebe Koundouri   +9 more
wiley   +1 more source

Climate justice as a public health imperative: a perspective from Sierra Leone considering the 2025 International Court of Justice opinion. [PDF]

Infect Dis Poverty
Kamara IF, Tengbe SM, Vandi M, Ashubwe J, Hailu B, Fofanah BD, Anissette B, Osborne A, Tolhurst R, Minssen T.   +9 more
europepmc   +1 more source

Making Flood Inundation Mapping (FIM) Work for Multiple Users: Improving the Design of FIM for Decision Support

Journal of Flood Risk Management, Volume 19, Issue 3, September 2026.
ABSTRACT Visualizing and communicating flood inundation depth and extent can be valuable for informing decisions related to flood preparedness and disaster response. In the United States, several different types of flood inundation mapping (FIM) exist and a new National Water Model (NWM) FIM product is being rolled out across the country (expected to ...
Kathryn Semmens, Patrick Painter, Rachel Hogan Carr, Keri Maxfield   +3 more
wiley   +1 more source

An Integrated Framework for Flood Risk Management: Addressing Local Challenges and Resilience in Rize, Türkiye

Journal of Flood Risk Management, Volume 19, Issue 3, September 2026.
ABSTRACT In recent years, increasing flood events, driven by human activities and climate change, have caused significant loss of life and property around the globe. Consequently, effective flood risk management strategies have become crucial in response to rising flood risks.
Ayse Yildiz, Gokhan Sirmali, Rajib Shaw, Lee Bosher   +3 more
wiley   +1 more source

Mapping Climate Extremes and Infrastructure Vulnerability: A New Database for U.S. Railroads. [PDF]

Sci Data
Ghoreishi B, Staes BM, Liu C, Wang H.
europepmc   +1 more source

Enhanced Occurrence of Springtime Extreme Precipitation Associated With Mesoscale Convective Systems Over the US by Baroclinic Annular Mode

Geophysical Research Letters, Volume 53, Issue 16, 28 August 2026.
Abstract Mesoscale convective systems (MCSs) are powerful contributors to extreme precipitation, often resulting in flash floods. However, the extent to which these systems are influenced by natural modes of climate variability is still not fully understood.
Zachary Holder, Yanjun Hu, Lei Wang, Daniel Chavas, Zhe Feng, L. Ruby Leung   +5 more
wiley   +1 more source

An autoencoder driven deep learning geospatial approach to flood vulnerability analysis in the upper and middle basin of river Damodar. [PDF]

Sci Rep
Thappitla RS, Villuri VGK, Kumar S.
europepmc   +1 more source