Predictions
in Ungauged Basins: Promise and Progress (Proceedings of symposium S7 held during the
Seventh IAHS Scientific Assembly at Foz do Iguaçu, Brazil, April 2005). IAHS
Publ. 303, 2006, 108-115.
Identification of a river
water quality model and assessment of data information content
Michael Rode &
Gunter Wriedt
Department of Hydrological
Modelling, UFZ Centre for Environmental Research Leipzig Halle, Brückstraße 3a,
D-39114 Magdeburg, Germany
Abstract
Substantial uncertainties exist in the identification of river water quality
models, which partially depend on the information content of the calibration
data. To evaluate the dependencies between available calibration data and model
predictions investigations were conducted based on a 536 km
free-flowing reach of the German part of the River Elbe. Five extensive
flowtime related longitudinal surveys with 14 sampling locations were used. The
multi-objective calibration of the deterministic river water quality model QSIM
of the BfG (Germany) was carried out with the nonlinear parameter estimator
PEST. The Elbe case
study showed that calibration with less than two survey data sets leads to
substantial errors if these parameters are applied to deviating boundary
conditions. These uncertainties can be reduced with an increased calibration database. The results of this study will help model users to define appropriate
data collections and monitoring schemes.
Key words
calibration; data information content; QSIM; river water quality model