HR: 13:55h
AN: H53K-02    [Abstracts]
TI: Investigation of SRTM Data for Delineation of Process Relevant Response Units in Different Landscapes
AU: * Wolf, M
EM: markus.wolf@uni-jena.de
AF: Friedrich-Schiller-University Jena, Loebdergraben 32, Jena, 07743, Germany
AU: Pfennig, B
EM: bjoern.pfennig@uni-jena.de
AF: Friedrich-Schiller-University Jena, Loebdergraben 32, Jena, 07743, Germany
AB: The concept of this research is justified to the integration of landscape components for hydrological modelling within distributed models. Distributed models are based on homogenous entities which are delineated using landscape parameters such as topography, land use, soil, and geology. In ungauged basins most of these required data are only available on a coarse spatial resolution. In order to by-pass this gap the globally and freely available data from the Shuttle Radar Topography Mission (SRTM) were used to obtain model entities on a finer resolution because this data have an adequate resolution of 30m and 90m. The method relies on the assumption of a strong, process-driven feedback between the topography and further landscape components as well as runoff dynamics. It is expected that the water balance of catchments with insufficient data availability can be estimated using SRTM-based delineations of process-oriented model entities. A main goal is the investigation of the SRTM-data for delineation of process relevant response units (RU) over various scales. In order to correct geometric and radiometric errors the SRTM-data were optimized using several GIS procedures and new algorithms for void filling, vegetation reduction, hydrological oriented filter combinations and stream burning. A new developed sink fill method was implemented with the name LaSA (Landscape based Sink Algorithm). Elimination of sinks should be realized by a landscape-based optimum between filling sinks and carving of flow paths in flow barriers. In result of DEM preparation, hydrological corrected elevation data were available to establish a ruled-based framework for RU-delineation. Numerous topographic indices were applied whereas the index selection was oriented on different relief driven processes. The resulting datasets were analysed by the Cluster Analysis IVHG. Finally, different patterns of process driven RU, combing various topographic indices were delineated for three mesoscale catchments within different landscape types. These RU-sets were used as input entities in the hydrological model J2000. The analysis of the significance of the different landscape components to estimate runoff dynamics will define the potential of this approach for ungauged basins.
DE: 1640 Remote sensing (1855)
DE: 1855 Remote sensing (1640)
SC: Hydrology [H]
MN: 2007 Fall Meeting