Advances in Geosciences
www.adv-geosci.net
1680-7340
1680-7359
9
Integration of hydrological models on different spatial and temporal scales
2006
10.5194/adgeo-9-145-2006
http://www.adv-geosci.net/9/145/2006/
http://www.adv-geosci.net/9/145/2006/adgeo-9-145-2006.html
http://www.adv-geosci.net/9/145/2006/adgeo-9-145-2006.pdf
145
150
2006-09-26
Investigation of parameter uncertainty and identifiability of the hydrological model WaSiM-ETH
G. Wriedt
gunter.wriedt@jrc.it
M. Rode
UFZ Centre for Environmental Research Leipzig-Halle GmbH, Brückstrasse 3a, 39114 Magdeburg, Germany
The identification of optimum model parameters may be influenced by temporal
or event-specific changes of optimum parameter ranges and the length and
information content of calibration data. These effects were studied for the
hydrological model WaSiM-ETH in a 170 km<sup>2</sup> catchment. Based on a
Monte-Carlo simulation including seven model parameters, we investigated
temporal and state dependent changes of parameter identifiability using the
DYNIA algorithm. The effect of data length was studied using a modified
DYNIA approach based on a growing window algorithm. The DYNIA analysis
revealed temporal changes of identifiability for the snow melt runoff
parameter <i>cmelt</i>, which is only identifiable during winter runoff, and for the
drainage density parameter <i>drd</i>. The <i>drd</i> parameter was closely related to observed
discharge (or catchment moisture), when re-ordering the time series by
discharge. Such dependencies probably result from processes not included in
model equations. The growing window analysis shows that more than one year
of data did not result in improved identification of model parameters
<i>cmelt</i> and <i>drd</i>. Using the re-ordered data series, good identifiability of <i>cmelt</i> was bound
to high discharges, while identifiability of <i>drd</i> changed with the addition of
further values in descending or ascending order. The methodology revealed
structural problems with regard to the parameter <i>drd</i>, which are not yet
completely understood and require further investigation.
Beven, K. and Binley, A. M.: The future of distributed models: model calibration and uncertainmty production. Hydrol. Processes 6, 279–298, 1992.
Hornberger, G. M. and Spear, R. C.: An approach to preliminary analysis of environmental systems, J. Environ. Manag., 12, 7–18, 1981.
Schulla, J. and Jasper, K.: Model Description WaSiM-ETH. Internal report, IAC, ETH Zürich, 166 pp, 2001.
Shulla, J.: Hydrologische Modellierung von Flussgebieten zur Abschätzung der Folgen von Klimaänderungen, Diss., ETH Zürich, CH, 161 pp, 1997.
Spear, R. C. and Hornberger, G. M.: Eutrophication in Peel Inlet, II, identification of critical uncertainties via generalised sensitivity analysis, Water Res., 14, 43–49, 1980.
Wagener, T., McIntyre, N., Lees, M. J., Wheater, H. S., and Gupta, H. V.: Towards reduced uncertainty in conceptual rainfall-runoff modelling: Dynamic identifiability analysis, Hydrol. Processes, 17, 455–476, 2003.
Yapo, P. O., Gupta, H. V., and Sorooshian, S.: Automatic calibration of conceptual rainfall-runoff models: sensitivity to calibration data, J. Hydrol., 181, 23–48, 1996.