Adaptation of the Integrated Catchment System to On-line Assimilation of ECMWF Forecasts View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

Adam Kiczko , Renata J. Romanowicz , Marzena Osuch , Florian Pappenberger

ABSTRACT

Floods and low flows in rivers are seasonal phenomena that may cause several problems to society. Flow forecasts are crucial to anticipate high and low flow events. The forecasted flow is commonly given as one value, even though it is uncertain. There is an increasing interest to account for uncertainty in flood early warning and decision support systems. In response to that demand, ensemble flood forecasting has been developed using ensembles of numerical weather predictions (NWP) as a driving force for rainfall-runoff models. However, NWPs require bias correction in order to correspond to observations. This study focuses on comparison of two hydrological models and two error reduction techniques of the European Centre for Medium-Range Weather Forecasts (ECMWF). Namely, we compare an application of the conceptual HBV and a data-based mechanistic (DBM) grey-box rainfall-runoff model and two statistical methods of error correction, based on Quantile Mapping (QM), with and without seasonal adjustment. The Biała Tarnowska catchment (southern Poland) is used as a case study. The study shows that a simple, DBM model has similar prediction capabilities as the more complex conceptual HBV model. The use of QM downscaling techniques improves significantly the prediction skills, but seasonality can be neglected. More... »

PAGES

173-186

References to SciGraph publications

Book

TITLE

Stochastic Flood Forecasting System

ISBN

978-3-319-18853-9
978-3-319-18854-6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-18854-6_11

DOI

http://dx.doi.org/10.1007/978-3-319-18854-6_11

DIMENSIONS

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