Modellierung des Wasserhaushalts des Unteren und ... - Espace

IAWG Ottobrunn Seite 42
Modellierung des Wasserhaushalts des Mittleren und Unteren Maingebietes Oktober 2005
10. Summary (english)
The present report describes the calibration, validation and application of the model ASGi /
WASIM to compute the water balance in the catchment area of the middle and lower Main.
The investigation area is subdivided into a total of 42 sub basins with catchment areas be-
tween 78 km² and 930 km².
For those model components that are not to be calibrated, the default values of ASGi/WASIM
were used. An exception to it arises by modifying the land use parameters. From our point of
view the default values in this module are more adapted to alpine regions and not sufficent
suitable for the area under investigation.
About one third of the area is influenced by karst formations. This complicates the modelling,
because the mainly physically based description of the individual model compartments is not
possible in karst formations. Therefore the module of the delayed base flow is introduced to
describe the water seepage in a conceptual way.
Calibrating the ten soil parameters of the model is carried out by comparisons of measured
and simulated hydrographs for a total of 41 gauges. Because an exclusively manual calibra-
tion can hardly be performed within the available time frame, two support tools are used for a
more effective investigation of the optimal parameters. These are namely the supervised,
systematic parameter variation as well as the parameter optimisation.
The supervised parameter variation basically serves the definition of suitable start values and
ranges for the following parameter optimisation. The optimisation procedure (SCE) has es-
pecially been developed within the scope of hydrologic optimisation questions and is based
on the so-called evolution strategy. The sum of linear and logarithmic Nash Sutcliff efficiency
serves as the objective function of the optimisation procedure.
The results of the calibration (chapter 5.2.2, figure 6) and validation (chapter 6.1.1, figure 7)
show that the choosen parameter retrieval strategy is suitable for the calibration of the
model: Thus 80% of the sub basins show Nash Sutcliff efficiencies higher than 0.7 and 57%
of the areas show efficiencies over 0.8. With the validation there are 70% over 0.7 and 54%
higher than 0.8. About 8000 model runs in total have been carried out to achieve these re-
sults. From our point of view further improvements of the optimisation results can be ob-
tained by additional investigation to define the objective function.