Semi-automatic derivation of hydrographic network - Impacts of human activities on hydrographic network

The mapping of the channel network plays a fundamental role in manifold landscape management issues, such as geo-hydrological risk analysis, legal matters related to land use, technical cartography and water resources management. Human activities in mountain regions results in a wide variety of environmental impacts. Human activities that influence runoff generation and drainage pattern have reflections in the context of hydro-geological hazard and water resources management. In some cases, channel network has been modified for drainage and irrigation purposes, in other the alteration of drainage patterns is due to the presence of man-made features, such as roads and new urbanized areas. The last 40 years have seen relevant changes in land use in mountain regions, with an important increase of urbanized areas and road network, and consequent modifications of the hydrographic network. Accordingly, an up-to-date detailed recognition of the channel network is needed for landscape management purposes. The availability of high-resolution digital terrain models (HR-DTMs) of regional coverage opens interesting prospects for the analysis and the definition of the channel network. These terrain models offer an unprecedented capability to interpret surface morphology and the related geomorphic and hydrological processes. Moreover, the availability of regional HR-DTMs is increasing, thanks to technological developments and decreasing costs of data acquisition and processing. In this study, we present our experience in the derivation of channel network from regional HR-DTM for an alpine region (Autonomous Province of Trento, Northern Italy), covering an area of 6500 km2. The derivation of the channel network is conducted via a geomorphometric approach. Moreover, we analyze the interaction between human activities and the channel network by comparing the channel network derived from the HR-DTM with field evidences collected during extensive field surveys.