As one of nature's most destructive calamities, floods cause fatalities, property destruction,
and infrastructure damage, affecting millions of people worldwide. Due to its ability to …

Machine learning (also called data-driven) methods have become popular in modeling flood
inundations across river basins. Among data-driven methods, traditional machine learning …

Accurate prediction of runoff is an important foundation for optimizing water resource
allocation and reservoir scheduling operations. However, due to its complex characteristics …

Urban pluvial floods induced by rainstorms can cause severe losses to human lives and
property. Fast and accurate simulation and prediction of urban pluvial flood are of …

Multi-hazard susceptibility prediction is an important component of disasters risk
management plan. An effective multi-hazard risk mitigation strategy includes assessing …

Climate change has led to increasing frequency of sudden extreme heavy rainfall events in
cities, resulting in great disaster losses. Therefore, in emergency management, we need to …

Study region Typical basin in semi-arid and semi humid areas in the middle reaches of the
Yellow River Study focus Floods are among the most devastating natural disasters. Timely …

Monthly runoff time-series estimation is imperative information for water resources planning
and development projects. This article aims to comparatively investigate the applicability of …

Despite rural, agricultural landscapes being exposed to pluvial flooding, prior predictive
flood modeling research has largely focused on urban areas. To improve and extend pluvial …

An accurate and rapid urban flood prediction model is essential to support decision-making
for flood management. This study developed a deep-learning-technique-based data-driven …