Flood crises are the consequence of climate change and global warming, which lead to an
increase in the frequency and intensity of heavy rainfall. Floods are, and remain, natural …

The utilisation of modelling tools in hydrology has been effective in predicting future floods
by analysing historical rainfall and inflow data, due to the association between climate …

Energy storage systems enable balancing supply and demand and facilitate the integration
of intermittent renewable energy sources. In particular, latent heat thermal energy storage …

Rainfall is crucial for agricultural practices, and climate change has significantly altered
rainfall patterns. Understanding the dynamic nature of rainfall in the context of climate …

Rainfall forecasting is a challenging task due to the time-dependencies of the variables and
the stochastic behavior of the process. The difficulty increases when the zone of interest is …

Machine learning has been deemed to be a powerful approach in forecasting hydrological
events such as flood using time-series historical data. A flood can be forecast in a manner of …

Flash floods are among the most immediate and destructive natural hazards. To issue
warnings on time, various attempts were made to extend the forecast horizon of flash floods …

Extreme weather occurrences provide issues that necessitate the development of
technology capable of accurate analysis and exact prediction in order to successfully reduce …

The advancement of the machine learning model has widely been adopted to provide flood
forecasts. However, the model must deal with the challenges of determining the most …

Precipitation prediction is the main feature to be considered to run any planning-based
activities such as agriculture, logistic management and any sort of business. Rainfall is …