Extreme hydrological events have become more frequent, as evidenced by the European floods of July 2021, which affected the southern provinces of the Netherlands. The need for improved discharge predictions to be used in operational water management to avoid potential adverse effects of flooding has encouraged researchers to employ several ways to improve hydrological model estimates, including data assimilation. This thesis explores the data assimilation effects in the discharge predictions of the wflow_sbm distributed hydrological model of the Vecht river basin. Additionally, effects on other hydrological states and fluxes like subsurface flow, saturated water depth, and soil moisture were explored spatially. This work presents a methodology for applying data assimilation in a model where water is routed from the surface and subsurface. In contrast, previous studies used a model in which water is routed only via surface water. Ensemble Kalman Filter is used to update the model’s discharge predictions by assimilating external discharge observations. This methodology also explores how the data assimilation effect is influenced by the uncertainty characterization considered in the assimilation framework and other factors like the length of the assimilation window and the number of assimilation locations. A preliminary study of the rainfall data is performed to determine the uncertainties of the chosen rainfall product. A benchmark simulation scenario is then selected after the review of deterministic and ensemble model predictions. Finally, data assimilation experiments are developed after discussing the characterization of the uncertainty model. The results of the model output analysis indicate that streamflow assimilation typically has a positive effect on improving model discharge estimations. Additionally, the Ensemble Kalman Filter update effectively captures the system’s spatial state dynamics for subsurface states and fluxes, such as saturated water depth, soil moisture, etc. Two alternative experimental ...