Flooding is a growing problem, which affects more than 10% of the UK population. The cost of damage caused by flooding correlates closely with the warning time given before a flood event, making flood monitoring and prediction critical to minimizing the cost of flood damage. This paper describes a wireless sensor network for flood warning which is not only capable of integrating with remote fix...

Extreme precipitation events can lead to the exceedance of sewer capacity in urban areas. To mitigate effects flooding, a model is required that capable predicting flood timing and volumes based on forecasts while computational times are significantly low. In this study, long short-term memory (LSTM) neural network set up predict time series at 230 manhole locations present system. For first ti...

Flood Early Warning system development is relatively new and costly area for developing countries, though it has captured attention of the respective parties since such System can avoid loss lives reduce property damages from floods. Rather than standalone early warning system, with ability to forecast or predict flood events more useful relevant stake holders where be used plan act fast. Geolo...

Flash floods are considered to be one the worst kind of hazard. They are characterized by their suddenness, rarity, small scale, heavy rain and peak discharge, unpredictable, fast and violent movement. It has severe effects on human society in the form life losses, damages to property, roads, communication and on natural settings. Advances in hydrology, meteorology, engineering, using of GIS an...

Abstract The aim of any early warning systems is to provide warning to people of an impending natural hazard so that those vulnerable are aware of the potential impact of the natural processes in order to respond appropriately and minimise damage. This paper looks at variables affecting the implementation of flood hazard early warning systems in a flood prone area of Zimbabwe. Documenting the e...

Flood forecasting is always a challenge in Taiwan, which has a subtropical climate and high mountains. This paper develops a fuzzy clustering neural network (FCNN), and implements this novel structure and reasoning process for flood forecasting. The FCNN has a hybrid learning scheme; the unsupervised learning scheme employs fuzzy min-max clustering to extract information from the input data. Th...