This review paper focuses on the use of ensemble neural networks (ENN) in the
development of storm surge flood models. Storm surges are a major concern in coastal …

Over the past 10 years, urban floods have increased in frequency because of extreme
rainfall events and urbanization development. To reduce the losses caused by floods …

Since the beginning of the 2000s, most of the West-African countries, particularly Benin,
have experienced an increased frequency of extreme flood events. In this study, we focus on …

The occurrence of flash floods in urban catchments within the Mediterranean climate zone
has witnessed a substantial rise due to climate change, underscoring the urgent need for …

The paper presents a hybrid approach for short-term river flood forecasting. It is based on
multi-modal data fusion from different sources (weather stations, water height sensors …

The global community is continuously working to minimize the impact of disasters through
various actions, including earth surveying. For example, flood-prone areas must be …

Flood events occurrences and frequencies in the world are of immense worry for the stability
of the economy and life safety. Africa continent is the third continent the most negatively …

Urban floods caused by extreme rainstorm events have increased in recent decades,
particularly in concave-down bridge zones. To simulate urban flooding processes …

In view of the problems related to flood forecasting and the different types of neural networks
that can be applied, this study aims to analyse which neural networks and statistical metrics …

The dimensioning of canal geometry in a surface drainage network influences the size and
functionality of canal structures, reduces flood hazard, and consequently imposes …