We present Top-kriging, or topological kriging, as a method forestimating streamflow-related variables in ungauged catchments. Ittakes both the area and the nested nature of catchments intoaccount. The main appeal of the method is that it is a best linearunbiased estimator (BLUE) adapted for the case of stream networkswithout any additional assumptions. The concept is built on the workof Sauquet et al. (2000) and extends it in a number of ways. We testthe method for the case of the specific 100-year flood for twoAustrian regions. The method provides more plausible and, indeed,more accurate estimates than Ordinary Kriging. For the variable ofinterest, Top-kriging also provides estimates of the uncertainty. Onthe main stream the estimated uncertainties are smallest and theygradually increase as one moves towards the headwaters. The methodas presented here is able to exploit the information contained inshort records by accounting for the uncertainty of each gauge. Wesuggest that Top-kriging can be used for spatially interpolating arange of streamflow-related variables including mean annualdischarge, flood characteristics, low flow characteristics,concentrations, turbidity and stream temperature.
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