Regionalisation of catchment model parameters

We simulate the water balance dynamics of 308 catchments in Austria using a lumped conceptual model involving I I calibration parameters. We calibrate and verify the model for two non-overlapping I I-year periods of daily runoff data. A comparison of the calibrated parameter values of the two periods suggests that all parameters are associated with some uncertainty although the degree of uncertainty differs between the parameters. The regional patterns of the calibrated parameters can be interpreted based on hydrological process reasoning indicating that they are able to represent the regional or large-scale differences in the hydrological conditions. Catchment attributes explain some of the spatial parameter variability with coefficients of determination of up to R-2 = 0.27, but usually the R-2 values are lower. Parameter uncertainty does not seem to cloud the relationship between calibrated parameters and catchment attributes to a significant extent as suggested by an optimised correlation analysis. The median Nash-Sutcliffe efficiencies of simulating streamflow decrease from 0.67 to 0.63 when moving from the calibration to the verification period. This is a small decrease, which suggests that problems with overparameterisation of the model are unlikely. We then compare regionalisation methods for estimating the model parameters in ungauged catchments, in terms of the model performance. The best regionalisation methods are the use of the average parameters of immediate upstream and downstream (nested) neighbours and regionalisation by kriging. For the calibration period, the average decrease in the Nash-Sutcliffe model efficiency, as a result of the regionalisation, is 0.10 which is about twice the decrease of moving from the calibration to the verification period. The methods based on multiple regressions with catchment attributes perform significantly poorer. Apparently, spatial proximity is a better surrogate of unknown controls on runoff dynamics than catchment attributes. (C) 2004 Elsevier B.V. All rights reserved.