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We explore the potential of a multi-criteria selection of\uddonor catchments in the prediction of continuous streamflow series by the\udspatial proximity method. Three criteria have been used: (1) spatial\udproximity; (2) physical similarity; (3) stream gauging network topology. An\udextensive assessment of our spatial proximity method variant is made on a\ud149 catchment-data set located in the Rhine-Meuse catchment. The\udcompetitiveness of the method is evaluated against spatial interpolation of\udcatchment model parameters with ordinary kriging. We found that the spatial\udproximity approach is more efficient than ordinary kriging. When distance to\udupstream/downstream stream gauge stations is considered as a second order\udcriterion in the selection of donor catchments, an unprecedented level of\udefficiency is reached for nested catchments. Nevertheless, the spatial\udproximity method does not take advantage from physical similarity between\uddonor catchments and receiver catchments because catchments that are the\udmost hydrologically similar to each catchment poorly match with the\udcatchments that are the most physically similar to each catchment

Added-value from a multi-criteria selection of donor catchments in the prediction of continuous streamflow series at ungauged pollution control-sites