Flood prediction using machine learning models: Literature review
Floods are among the most destructive natural disasters, which are highly complex to model.
The research on the advancement of flood prediction models contributed to risk reduction …
The research on the advancement of flood prediction models contributed to risk reduction …
Flood risk in urban areas: Modelling, management and adaptation to climate change. A review
L Cea, P Costabile - Hydrology, 2022 - mdpi.com
The modelling and management of flood risk in urban areas are increasingly recognized as
global challenges. The complexity of these issues is a consequence of the existence of …
global challenges. The complexity of these issues is a consequence of the existence of …
Fast simulation and prediction of urban pluvial floods using a deep convolutional neural network model
Y Liao, Z Wang, X Chen, C Lai - Journal of Hydrology, 2023 - Elsevier
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 …
property. Fast and accurate simulation and prediction of urban pluvial flood are of …
Toward street‐level nowcasting of flash floods impacts based on HPC hydrodynamic modeling at the watershed scale and high‐resolution weather radar data
In our era, the rapid increase of parallel programming coupled with high‐performance
computing (HPC) facilities allows for the use of two‐dimensional shallow water equation (2D …
computing (HPC) facilities allows for the use of two‐dimensional shallow water equation (2D …
Performances of the new HEC-RAS version 5 for 2-D hydrodynamic-based rainfall-runoff simulations at basin scale: Comparison with a state-of-the art model
The Hydrologic Engineering Centre-River Analysis System (HEC-RAS), developed by the
US Army Corps of Engineers, is one of the most known, analyzed and used model for flood …
US Army Corps of Engineers, is one of the most known, analyzed and used model for flood …
Exploring temporal dynamics of river discharge using univariate long short-term memory (LSTM) recurrent neural network at East Branch of Delaware River
River flow prediction is a pivotal task in the field of water resource management during the
era of rapid climate change. The highly dynamic and evolving nature of the climatic …
era of rapid climate change. The highly dynamic and evolving nature of the climatic …
[HTML][HTML] Urban pluvial flooding prediction by machine learning approaches–a case study of Shenzhen city, China
Urban pluvial flooding is a threatening natural hazard in urban areas all over the world,
especially in recent years given its increasing frequency of occurrence. In order to prevent …
especially in recent years given its increasing frequency of occurrence. In order to prevent …
Water level forecasting using deep learning time-series analysis: A case study of red river of the north
The Red River of the North is vulnerable to floods, which have caused significant damage
and economic loss to inhabitants. A better capability in flood-event prediction is essential to …
and economic loss to inhabitants. A better capability in flood-event prediction is essential to …
Is local flood hazard assessment in urban areas significantly influenced by the physical complexity of the hydrodynamic inundation model?
P Costabile, C Costanzo, G De Lorenzo… - Journal of Hydrology, 2020 - Elsevier
Flood hazard in urban areas is usually assessed by the estimations of parameters like flood
extent, water depths, flow velocities and other related quantities. These hydrodynamic …
extent, water depths, flow velocities and other related quantities. These hydrodynamic …
An operational method for flood directive implementation in ungauged urban areas
An operational framework for flood risk assessment in ungauged urban areas is developed
within the implementation of the EU Floods Directive in Greece, and demonstrated for Volos …
within the implementation of the EU Floods Directive in Greece, and demonstrated for Volos …