Floods are a devastating natural calamity that may seriously harm both infrastructure and
people. Accurate flood forecasts and control are essential to lessen these effects and …

The Kalman filter (KF) is a popular state estimation technique that is utilized in a variety of
applications, including positioning and navigation, sensor networks, battery management …

Due to the stochastic nature and complexity of flow, as well as the existence of hydrological
uncertainties, predicting streamflow in dam reservoirs, especially in semi-arid and arid …

Quantifying the uncertainty of probabilistic water quality forecasting induced by missing input
data is fundamentally challenging. This study introduced a novel methodology for …

River water level usually given by nonlinear and nonstationary time series and affected by
numerous complex spatial and temporal factors. But not all input factors are positively …

Making accurate and reliable probability density forecasts of flood processes is
fundamentally challenging for machine learning techniques, especially when prediction …

Reliable and accurate regional multistep-ahead flood forecasts during extreme events are
crucial and beneficial to flood disaster management and preparedness. Hydrologic …

Flood control operation is one of the effective measures to reduce flood risks. Since flood
forecasting plays a critical role in real-time reservoir flood control operation, it is necessary to …

Accurate and timely flood forecasting, facilitated by remote sensing technology, is crucial to
mitigate the damage and loss of life caused by floods. However, despite years of research …

Extreme precipitation events can lead to the exceedance of the sewer capacity in urban
areas. To mitigate the effects of urban flooding, a model is required that is capable of …