Deep reinforcement learning (DRL) has been applied to real-time control (RTC) of urban drainage systems (UDSs), with impressive performance and efficiency in reducing urban flooding and combined sewer overflows (CSO). However, for complex UDSs, learn...
Inundation maps with spatial and temporal distribution of the water depths are essential for protecting the population in case of pluvial flood events. Creating these maps in operational forecasting is currently not possible with traditional physical...
The real-time forecasting of flood dynamics is a long-standing challenge traditionally addressed through numerical solutions of the Shallow Water Equations (SWEs). Numerical solutions of realistic flow problems using numerical schemes are often hinde...
Water science and technology : a journal of the International Association on Water Pollution Research
May 16, 2025
The imperviousness of urban surfaces is an important parameter in simulating urban hydrological responses, but quantifying imperviousness can be challenging and time-consuming. In response, this study presents a new framework to efficiently estimate ...
Flooding has increasingly significant adverse effects on global food security, and there is a lack of a framework to effectively integrate remote sensing with survey data for accurate damage and recovery assessment. Also, optical satellite images for...
Urban flood control and drainage systems often face significant challenges in coordinating municipal drainage with river-lake flood prevention during flood seasons. Rising river levels can create backwater effects, which substantially increase urban ...
Flood forecasting exhibits rapid fluctuations, water level forecasting shows great uncertainty and inaccuracy in small watersheds, and the reliability and accuracy performance of traditional probability forecasting is often unbalanced. This study com...
Real-time control (RTC) is an effective method used in urban drainage systems (UDS) for reducing flooding and combined sewer overflows. Recently, RTC based on Deep Reinforcement Learning (DRL) has been proven to have various advantages compared to tr...
The Mahananda River basin, located in Eastern India, faces escalating flood risks due to its complex hydrology and geomorphology, threatening socioeconomic and environmental stability. This study presents a novel approach to flood susceptibility (FS)...
The escalating impacts of climate change have intensified extreme rainfall events, placing urban drainage systems under unprecedented pressure and increasing flood risks. Addressing these challenges requires advanced flood mitigation strategies, opti...
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