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IAHS 90th ANNIVERSARY |
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PUB SYMPOSIUM 2012
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Theme 4: New Approaches to Data Collection and Information Gain - Wednesday, October 24, 2012
Convener: Erwin Zehe ([email protected])
Co-conveners: Nick van de Giesen, Vincent Fortin, Theresa Blume, Uwe Ehret, Karsten Schulz ([email protected]; [email protected]; [email protected]; [email protected]; [email protected])
No prediction without understanding, no understanding without information, no information
without data. These statements are valid for any empirical science; the last two statements,
however, point to a cardinal problem in hydrological science. In recent years many new
approaches to collect data on surface and subsurface properties, states and processes have been
developed. This includes geophysical methods (geo radar, active seismic methods, ERT) to
collect proxies on subsurface patterns and dynamics; remote sensing methods, cosmic neutrons,
scintillometers to collect dynamic proxies on soil moisture, latent and sensible heat fluxes, water
stress indices for vegetation; new approaches to assess rainfall variability and variability of air
humidity (radar, attenuation of GNSS signals) as well as new smart tracers to discriminate source
areas and source volumes of runoff components. While this is a major step ahead we need a much better picture which combination of
these data sources and which metrics - to extract information form these data - are needed to
(1) Characterize the hydrological relevant architecture of landscape elements (hillslope,
catchments), especially with respect to bedrock topography, subsurface heterogeneity and flow
path connectivity; (2) Understand how structural characteristics, and distributed dynamics control integral
mass/water and integral energy flows across scales.
These insights are however the key to find out whether certain elements in the landscape exhibit
functional similarity with respect to the dominant process (which might of course change
depending on the prevailing boundary conditions). This is deemed as a key to better understand
spatio-temporal organization of the water cycle at relevant scales and specifically to design more
targeted strategies collected the right for the right reasons to maximize information gain when
gauging ungauged catchments.