Technological and methodological progress is essential to improve our understanding of
fundamental processes in natural and engineering sciences. In this paper, we will address …

Climate change, air quality, and environmental degradation are important societal
challenges for the Twenty-first Century. These challenges require an intelligent response …

The last twenty years have brought significant advances in hydrology and hydrogeology,
especially in the area of data availability and predictive modeling capabilities. Remote …

Fluvial flooding is one of the most catastrophic natural disasters threatening people's lives
and possessions. Flood forecasting systems, which simulate runoff generation and …

The reliable estimation of hydrological variables in space and time is of fundamental
importance in operational hydrology to improve the flood predictions and hydrological cycle …

This paper describes the design and use of a recursive ensemble Kalman filter (REnKF) to
assimilate streamflow data in an operational flow forecasting system of seven catchments in …

This paper presents multiple parameter estimation using multivariate observations via the
ensemble Kalman filter (EnKF) for a physically based land surface hydrologic model. A data …

This paper reviews the conceptual problems limiting our current knowledge of the
hydrological cycle over land. We start from the premise that to understand the hydrological …

For operational flood forecasting, discharge observations may be assimilated into a
hydrologic model to improve forecasts. However, the performance of conventional filtering …

Data assimilation has recently been the focus of much attention for integrated surface–
subsurface hydrological models, whereby joint assimilation of water table, soil moisture, and …