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Schlagwörter:
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Zusammenfassung:
Sustainable water resources management needs to be based on sound process understanding. This is especially
true in a changing world, where boundary conditions change and models calibrated to the status quo are no
longer helpful. There is a general agreement in the hydrologic community that we are in need of a better process
understanding and that one of the most promising ways to achieve this is by using nested experimental designs
that cover a range of scales.
In the here presented study we argue that while we might be able to investigate a certain process at a plot
or hillslope in detail, the real power of advancing our understanding lies in site intercomparison and if possible
knowledge transfer and generalization. The experimental design of the CAOS observatory is based on sensor
clusters measuring ground-, soil and stream water, sap flow and climate variables in 45 hydrological functional
units which were chosen from a matrix of site characteristics (geology, land use, hillslope aspect, and topographic
positions). This design allows for site intercomparisons that are based on more than one member per class and
thus does not only characterize between class differences but also attempts to identify within-class variability.
These distributed plot scale investigations offer a large amount of information on plot scale processes and
their variability in space and time (e.g. water storage dynamics and patterns, vertical flow processes and vadose
zone transit times, transpiration dynamics and patterns). However, if we want to improve our understanding of
runoff generation (and thus also of nutrient and contaminant transport and export to the stream) we need to also
understand how these plots link up within hillslopes and how and when these hillslopes are connected to the
stream. And certainly, this is again most helpful if we do not focus on single sites but attempt experimental designs
that aim at intercomparison and generalization. At the same time, the investigation of hillslope-stream connectivity
is extremely challenging due to the fact that there is a high 4-dimensional variability of the involved processes
and most of them are hidden from view in the subsurface. To tackle this challenge we employed a number of
different field methods ranging from hillslope scale irrigation and flow-through experiments, to in depth analyses
of near stream piezometer responses and stream reach tracer experiments, and then moving on to the mesoscale
catchment with network wide investigations of spatial patterns of stream temperature and electric conductivity as
well as of the expansion and shrinkage of the network itself. In this presentation we will provide an overview of
the rationale, approach, experimental design and ongoing work, the challenges we encountered and a synthesis of
exemplary results.
