Summary The use of Artificial Intelligence (AI) has increased since the middle of the 20th
century as seen in its application in a wide range of engineering and science problems. The …

Runoff plays an essential part in the hydrological cycle, as it regulates the quantity of water
which flows into streams and returns surplus water into the oceans. Runoff modelling may …

Ensemble forecasting applied to the field of hydrology is currently an established area of
research embracing a broad spectrum of operational situations. This work catalogs the …

Monthly stream-flow forecasting can yield important information for hydrological applications
including sustainable design of rural and urban water management systems, optimization of …

The growing menace of global warming and restrictions on access to water in each region is
a huge threat to global hydrological sustainability. Hence, the perspective at which …

In recent years, fuzzy logic has emerged as a powerful technique in the analysis of
hydrologic components and decision making in water resources. Problems related to …

Flood prediction has gained prominence world over due to the calamitous socio-economic
impacts this hazard has and the anticipated increase of its incidence in the near future …

A reliable river water level model to forecast the changes in different lead times is vital for
flood warning systems, especially in countries like Malaysia, where flood is considered the …

Eight data-driven models and five data pre-processing methods were summarized; the
multiple linear regression (MLR), artificial neural network (ANN) and wavelet decomposition …

Providing a robust and reliable prediction model for suspended sediment concentration
(SSC) is an essential task for several environmental and geomorphology prospective …