Spatial interpolation and conditional simulation of short time step rainfall for hydrological modelling

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Objective of the proposed research is the investigation of spatial interpolation and spatiotemporal conditional simulation of precipitation for mesoscale hydrological modelling focussing on highly dynamic processes like floods. In the first part of the study multivariate geostatistical methods will be applied and further developed for interpolation of short time step precipitation using additional information, especially weather radar data. The interpolation methods give an unbiased estimation but have the problem of smoothing the precipitation distribution, especially when radar data are absent. This will lead to high uncertainties for the reproduction of hydrological extremes. The second part of the research project addresses this problem using conditional spatiotemporal simulation of precipitation which allows preserving the rainfall variance structure. When radar data are available conditional simulations will be used for the quantification of the uncertainty of the Z-R relationship. Validation of the methods will be carried out using cross validation of precipitation and hydrological modelling at different levels of complexity. As study area the ¿Greater Harz Region¿ in the northern part of Germany will be used.