Improving Operational Flood Forecasting Using Data Assimilation

Reliable and accurate flood early warnings are very important because they can mitigate the number of casualties and reduce economic damage. Understanding the behaviour of extreme hydrological events and the ability of hydrological modellers to improve their forecast skills are distinct challenges of applied hydrology.

Promovendus O (Olda) Rakovec MSc
Promotor R (Remko) Uijlenhoet
Copromotor AH (Albrecht) Weerts
Organisatie Wageningen University, Hydrology and Quantitative Water Management

vr 25 april 2014 11:00 tot 12:30

Locatie Auditorium, building number 362
Generaal Foulkesweg 1
6703 BG Wageningen

Since models simplify the real world complexity, hydrological forecasts are prone to many sources of uncertainties, such as in initial conditions, boundary conditions, and model input, structure and parameters.

Evaluation of local sensitivity analysis at multiple points across the parameter space of hydrological models can reveal important parameter subregions, generally undetected by popular global methods.
Oldrich Rakovec

This thesis contributes to improved understanding and quantification of hydrological model uncertainty especially related to the initial conditions of the model and to a lesser extent to the model structure and parameters.