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The role of spatial variability of soil moisture for modelling surface runoff generation at the small catchment scale
1Potsdam Institute for Climate Impact Research, Telegraphenberg C4, P.O. Box 60 12 03, 14412 Potsdam, Germany
2Institut für Wasserbau, University of Stuttgart, 70550 Stuttgart, Germany
e-mail address for corresponding author: bronstert@pik-potsdam.de
Abstract. A Bayesian approach is described for dealing with the problem of infilling and generating stochastic flow sequences using rainfall data to guide the flow generation process, and including bounded (censored) observed flow and rainfall data to provide additional information. Solutions are obtained using a Gibbs sampling procedure. Particular problems discussed include developing new procedures for fitting transformations when bounded values are available, coping with additional information in the form of values, or bounds, for totals of flows across several sites, and developing relationships between annual flow and rainfall data. Examples are shown of both infilled values of unknown past river flows, with assessment of uncertainty, and realisations of flows representative of what might occur in the future. Several procedures for validating the model output are described and the central estimates of flows, taken as a surrogate for historical observed flows, are compared with long term regional flow and rainfall data.
Final Revised Paper (PDF, 3736 KB)
Citation: Bronstert, A. and Bárdossy, A.: The role of spatial variability of soil moisture for modelling surface runoff generation at the small catchment scale, Hydrol. Earth Syst. Sci., 3, 505-516, 1999. Bibtex EndNote Reference Manager
