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. The setup of a rainfall-runoff model in a river section where no streamflowmeasurements are available for its calibration is one of the key researchactivities for the Prediction in Ungauged Basins (PUB): in order to do so itis possible to estimate the model parameters based on the hydrometricinformation available in the region. The informative content of the dataset (i.e. which and how many gauged river stations are available) plays anessential role in the assessment of the best regionalisation method. Thisstudy analyses how the performances of regionalisation approaches areinfluenced by the “information richness” of the available regional dataset, i.e. the availability of potential donors, and in particular by thegauging density and by the presence of nested donor catchments, which are expected to be hydrologically very similar to the target section. The research is carried out over a densely gauged dataset covering the Austrian country, applying two rainfall-runoff models and differentregionalisation approaches. The regionalisation techniques are first implemented using all the gaugedbasins in the dataset as potential donors and then re-applied, decreasing the informative content of the dataset. The effect of excluding nested basins and the status of “nestedness” is identified based on the positionof the closing section along the river or the percentage of shared drainagearea. Moreover, the impact of reducing station density on regionalisationperformance is analysed. The results show that the predictive accuracy of parameter regionalisationtechniques strongly depends on the informative content of the dataset ofavailable donor catchments. The “output-averaging” approaches, whichexploit the information of more than one donor basin and preserve thecorrelation structure of the parameter, seem to be preferable forregionalisation purposes in both data-poor and data-rich regions. Moreover, with the use of an optimised set of catchment descriptors as a similarity measure, rather than the simple geographical distance, results are more robust tothe deterioration of the informative content of the set of donors.

hydrology and earth system sciences

Importance of the informative content in the study area when regionalising rainfall-runoff model parameters: the role of nested catchments and gauging station density