Hybrid hydroclimatic forecasting systems employ data-driven (statistical or machine
learning) methods to harness and integrate a broad variety of predictions from dynamical …

Ensemble flood forecasting has gained significant momentum over the past decade due to
the growth of ensemble numerical weather and climate prediction, expansion in high …

Hydrological drought forecasts outperform meteorological ones, which is anticipated coming
from catchment memory. Yet, the importance of catchment memory in explaining …

In this paper, we review the use of satellite-based remote sensing in combination with in situ
data to inform Earth surface modelling. This involves verification and optimization methods …

Predictive performance is one of the most important issues for practical applications of
ensemble hydroclimatic forecasts. While different forecasting studies tend to use different …

Skilful hydrological forecasts at sub-seasonal to seasonal lead times would be extremely
beneficial for decision-making in water resources management, hydropower operations, and …

Global overviews of upcoming flood and drought events are key for many applications,
including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early …

Hydrological Forecasts and Projections for Improved Decision-Making in the Water Sector in
Europe in: Bulletin of the American Meteorological Society Volume 100 Issue 12 (2019) Jump …

Hybrid hydroclimatic forecasting systems employ data-driven (statistical or machine
learning) methods to harness and integrate a broad variety of predictions from dynamical …

Recent technological advances in representation of processes in numerical climate models
have led to skillful predictions, which can consequently increase the confidence of …