Articles | Volume 22, issue 9
Research article
06 Sep 2018
Research article |  | 06 Sep 2018

A geostatistical data-assimilation technique for enhancing macro-scale rainfall–runoff simulations

Alessio Pugliese, Simone Persiano, Stefano Bagli, Paolo Mazzoli, Juraj Parajka, Berit Arheimer, René Capell, Alberto Montanari, Günter Blöschl, and Attilio Castellarin

Data sets

Geostatistical Enhancement of European Hydrological Predictions (GEEHP): a SWITCH-ON experiment protocol A. Pugliese, S. Persiano, S. Bagli, P. Mazzoli, J. Parajka, B. Arheimer, R. Capell, A. Montanari, G. Blöschl, G., and A. Castellarin

Short summary
This research work focuses on the development of an innovative method for enhancing the predictive capability of macro-scale rainfall–runoff models by means of a geostatistical apporach. In our method, one can get enhanced streamflow simulations without any further model calibration. Indeed, this method is neither computational nor data-intensive and is implemented only using observed streamflow data and a GIS vector layer with catchment boundaries. Assessments are performed in the Tyrol region.