Abstract. The systematic underestimation observed in debris flow early warning thresholds has been associated with the use of sparse rain gauge networks to represent highly non-stationary rainfall fields. Remote sensing products permit concurrent estimates of debris-flow-triggering rainfall for areas poorly covered by rain gauges, but the impact of using coarse spatial resolutions to represent such rainfall fields is still to be assessed. This study uses fine-resolution radar data for ∼ 100 debris flows in the eastern Italian Alps to (i) quantify the effect of spatial aggregation (1-20 km grid size) on the estimation of debris-flow-triggering rainfall and on the identification of early warning thresholds and (ii) compare thresholds derived from aggregated estimates and rain gauge networks of different densities. The impact of spatial aggregation is influenced by the spatial organization of rainfall and by its dependence on the severity of the triggering rainfall. Thresholds from aggregated estimates show 8-21 % variation in the parameters whereas 10-25 % systematic variation results from the use of rain gauge networks, even for densities as high as 1/10 km −2 .

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An empirical method aimed at generating maps of potential of geothermal energy exchange for shal-low vertical closed-loop systems is proposed here. The method uses both geological and technologicalinformation. In particular, the ground parameters that mainly influence the heat transfer in borehole heatexchangers, the energetic parameters driving efficient operations of geothermal systems and heating andcooling requirements of a typical residential building are taken into account. Spatial modeling is carriedout in a Geographic Information System leading to an effective and easy-to-use digital cartographic tool.An application of the method to four regions of southern Italy is also shown