Floods are the most frequent of natural disasters, affecting millions of people across the
globe every year. The anticipation and forecasting of floods at the global scale is crucial to …

Floods affect a large fraction of the Indian population during the monsoon (June-September)
every year. Floods disrupt all aspects of the socio-economic conditions and cause enormous …

Abstract Ensemble Forecast Operations (EFO) is a risk‐based approach of reservoir flood
control operations that incorporates ensemble streamflow predictions (ESPs) made by the …

The heavy rain event of July 2018 and Typhoon Hagibis in October 2019 caused severe
flash flood disasters in numerous parts of western and eastern Japan. Flash floods need to …

Skillful streamflow forecasts provide key support to several water‐related applications.
Because of the critical impact of initial conditions (ICs) on forecast accuracy, ever‐growing …

Many present-day statistical schemes for postprocessing weather forecasts, in particular
precipitation forecasts, rely on calibration using prescribed statistical models to relate …

Reliably quantifying uncertainty in precipitation forecasts remains a critical challenge. This
work examines the application of a deep learning (DL) architecture, Unet, for postprocessing …

Streamflow forecasting is prone to substantial uncertainty due to errors in meteorological
forecasts, hydrological model structure, and parameterization, as well as in the observed …

This study presents a high-resolution regional reforecast based on the Weather Research
and Forecasting (WRF) Model, tailored for the prediction of extreme hydrometeorological …

This study proposes an integrated hydrometeorological modelling framework approach and
methodology for flash flood Early Warning Systems in the Chugoku region of Japan …