Analysis of hydrological parameter of Rio Cucco catchment (FVG) supported by multi-source and multi-temporal Digital Elevation Models.

Flood risk assessment in mountainous regions presents significant challenges due to complex topography, variable hydrological responses, and the increasing impact of climate change. This study focuses on the Rio Cucco catchment, located in the northeastern Italian Alps, a region prone to extreme rainfall events and catastrophic floods. The research aims to enhance flood hazard mapping by integrating high-resolution geospatial data, including Digital Elevation Models (DEMs), land cover classifications, and hydrometeorological records, using geomatic tools such as GIS, remote sensing, and Google Earth Engine (GEE). A comparative analysis of DEM 2018 (1m resolution) and DEM 2024 (50cm resolution) was conducted to evaluate the influence of terrain representation on hydrological modeling. The study further integrates rain gauge data, land cover maps, and soil characteristics to improve runoff estimations using the Soil Conservation Service (SCS) Curve Number method. Special attention is given to the role of temperature in hydrological response, particularly its effect on rainfall intensity, snowmelt, and infiltration rates, utilizing the T₀ Method for temperature normalization. Results reveal that DEM resolution significantly affects flood prediction accuracy, with higher-resolution datasets capturing finer hydrological and morphometric details. Land cover changes and slope variations between 2018 and 2024 have influenced flood-prone zones, emphasizing the necessity of high-quality data integration. The analysis of the 2003 flash flood event in Rio Cucco highlights the importance of localized hydrometeorological data in refining flood risk models. This research underscores the necessity of multi-source geospatial data integration for accurate flood hazard mapping and disaster risk management. The findings contribute to improving early warning systems, flood mitigation strategies, and resilient infrastructure planning in mountainous environments susceptible to extreme hydrological events.