Data assimilation plays a dual role in advancing the “scientific” understanding and serving
as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has …

Data Assimilation (DA) is an important step for improving prediction accuracy and real-time
correction of hydrological models for operational forecasting purposes. The Ensemble …

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 …

Land surface models (LSMs) use a large cohort of parameters and state variables to
simulate the water and energy balance at the soil–atmosphere interface. Many of these …

The crucial role of root-zone soil moisture is widely recognized in land–atmosphere
interaction, with direct practical use in hydrology, agriculture and meteorology. But it is …

Data assimilation has been widely tested for flood forecasting, although its use in
operational systems is mainly limited to a simple statistical error correction. This can be due …

Accurate flood inundation forecasts have the potential to minimize socioeconomic losses,
but uncertainties in inflows propagated from the precipitation forecasts result in large …

Flood inundation forecasts from hydrodynamic models can help with flood preparedness,
but uncertainty in the inputs and parameters can lead to erroneous flood inundation …

The concept of sustainability is assumed for this research from a temporal perspective.
Rivers represent natural systems with an inherent internal memory on their runoff and, by …

Crop growth simulation models are important components in agricultural management. Such
models include parameters that should be calibrated locally, which can be achieved by …