期刊
ENVIRONMENTAL MODELLING & SOFTWARE
卷 23, 期 4, 页码 464-478出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2007.06.010
关键词
forecasting; parameter identification; Kalman Filter; floods; distributed modelling; stream routing; model accuracy; dominant processes concept
This paper presents a distributed model that is in operational use for forecasting flash floods in northern Austria. The main challenge in developing the model was parameter identification which was addressed by a modelling strategy that involved a model structure defined at the model element scale and multi-source model identification. The model represents runoff generation on a grid basis and lumped routing in the river reaches. Ensemble Kalman Filtering is used to update the model states (grid soil moisture) based on observed runoff. The forecast errors as a function of forecast lead time are evaluated for a number of major events in the 622 km(2) Kamp catchment and range from 10% to 30% for 4-24 h lead times, respectively. (C) 2007 Elsevier Ltd. All rights reserved.
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