HR: 13:30h
AN: H13D-01 INVITED     [Abstracts]
TI: Integrated process studies and dynamical upscaling from the observation scale to the catchment scale
AU: * Zehe, E
EM: ezehe@rz.uni-potsdam.de
AF: Institute of Geoecology, University of Potsdam Karl-Liebknecht-Str. 24-25, Potsdam, 14476 Germany
AU: Schr”der, B
EM: boschroe@rz.uni-potsdam.de
AF: Institute of Geoecology, University of Potsdam Karl-Liebknecht-Str. 24-25, Potsdam, 14476 Germany
AU: Lee, H
EM: hakus@cwr.uwa.edu.au
AF: Centre of Water Research, The University of Wester 35 Stirling Highway,,Crawley, WA 6009 Australia
AU: Sivapalan, M
EM: sivapalan@cwr.uwa.edu.au
AF: Centre of Water Research, The University of Wester 35 Stirling Highway,,Crawley, WA 6009 Australia
AB: A cardinal problem in hydrology is what we call the "scale gap" in understanding. We urgently need representative data on dynamics of surface and subsurface state variables at the catchment scale, for e.g., as additional performance measures for validating meso-scale models. However, due to the known shortcomings of geophysical measurement techniques such as time domain reflectometry (TDR), ground penetrating radar (GPR) or geo electrics, our observations, and therefore also our process understanding, are restricted to the point or small field scale. Common ways to assess e.g. information on the space-time pattern of soil moisture at larger scales is to perform a distributed set of point observations either using mobile sensors, such as the "green machine", or a fixed set of TDR stations distributed in a catchment. The first approach is restricted to field campaigns and does not yield continuous information in time. The latter suffers from the fact that the correlation structure of soil moisture depends on the saturation state of the catchment. Hence, especially in dry states the network might be too coarse for explaining spatial variability of soil moisture in a geo-statistical sense. Whatever measurement approach is employed, there is no easy way to scale the information from the distributed set of small scale observations to the catchment scale because of non-linear process dynamics and strong sub-catchment heterogeneity of soils and vegetation. Geostatistical interpolation including updating approaches suffer from the fact that they either assume stationary relations between drift parameters and soil moisture or the sampling is not sufficient to obtain useful posterior probability distributions of soil moisture within different classes of available soft information. In this study we present an approach for integrated process studies in catchments by comparing principles from landscape ecology such as the pattern process paradigm with physical reasoning/modelling. The first is used to optimise a distributed network small scale hydrological observation network e.g. for soil moisture based on the dominating patterns of soils, topography and plant communities. The process model is used for something we call "dynamic" upscaling of local observations to the catchment scale. The proposed concept of integrated process studies and dynamical upscaling is discussed for a catchment in the Austrian alps and a catchment in South West of Germany.
DE: 1851 Plant ecology
DE: 1866 Soil moisture
DE: 1875 Unsaturated zone
SC: Hydrology [H]
MN: 2005 Joint Assembly