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and results to other sites. However, if the goal of
a study is the spatial interpolation of the simulation
results and the comparison of the results
of less intensivly monitored sites, a contrary
approach has to be chosen. Then, the model will
not be calibrated site-specifi c, but rather most
consistently (z.B. FALK et al. 2008, SCHULTZE und
SCHERZER 2011).
At the plot scale the only available soil hydrologic
measurements are usually the soil suction
and/or the soil water content, which are state
variables of the soil and not components of the
water balance. Therefore one can assume that
simulated state variables of the soil, like drought-
or oxygen stress, can be better validated than
e.g. deep percolation. An upscaling of the results
with catchment models like SWAT (NEITSCH et al.
2002) or WaSiM-ETH (SCHULLA und JASPER 1998,
2007) could help to improve the validation. On
this scale simulated discharge could be evaluated
against discharge measured by gauges (e.g.
PÖHLER et al. 2010).
The calibration and validation of water balance
models against soil suction is on the other
hand restricted by the measurement range of
tensiometers (< 800 hPa): During long lasting,
pronounced drought periods usually no measured
values are available. Therefore, the validation
of the simulation results against measured soil
suction is restricted during drought periods. This
problem can be solved by a depth differentiated
measurement of the soil water content which
then can be used to calculate the soil water
storage (SCHERZER et al. 2003), like it was done at
the Level II - sites Merzalben (chapter 3.1.3) and
Leisel (chapter 3.1.9).
If possible, the bulk precipitation should be used
as driving input-variable in processbased water
balance models. The other components of water
balance (e.g. evapotranspiration and discharge)
will then be simulated by the model. Results of
the long-lasting (1988 - 2009) experiments at
the Level II–sites in Rhineland-Palatinate showed
however that the interception modul usually
can not be unitary parametrisized for such a
long duration while at the same time differences
between simulated and measured throughfall are
kept at a minimum. Reasons for the discrepancy
are for example inhomogeneous climate time series
due to relocation of the measurement site or
errors in measured throughfall. As a consequence
the model usually was driven with the throughfall
as input variable. This has the positiv effect that
the simulated water amount reaching the soil
surface better represents reality. On the other
hand, the simulation period is then restricted
to the available period of measured throughfall.
Due to the increasing importance of climate and
water balance projections for the 21st century,
the relevance of the simulation of interception
has increased during the last years. In case of climate
change simulations at the Level II-sites (e.g.
KARL et al. 2012) the interception modul must be
activated and separately calibrated.