Hyper-resolution monitoring and modelling of the water budget for improving water managemen

The hydrologic regime of Alpine regions is undergoing rapid change under global warming, characterized by an alternation of wet and dry years, and even by floods and droughts within the same year. In this context, accurate catchment-scale water balance estimation is essential. To manage water withdrawals and the competing demands of hydropower, agriculture, domestic use, tourism, and industry under such variability becomes difficult and requires new tools and multiscale answers. Therefore, this work investigates scale issues in Alpine catchments and implements new modeling components. The multiscale approach is based on the GEOframe system and its space partitioning into Geomorphic Units (GU), which is mixed with a grid approach. This has practically implied writing a tool to increase the resolution of sub-catchment extraction, tools for grid information averaging over the GU, and adaptation of many existing GEOframe tools. These improvements have also affected the kriging interpolator, whose new version accommodates the possibility of varying the semivariogram to capture the temporal variability of meteorological forcing at each time step. These developments also contributed to a broader refactoring of the GEOframe system, including bug fixes, the reorganization of its Git repositories and website, and improvements to the build system. The resulting code also supported the work carried out for the AdbPo project. The tools were extensively applied to the Noce River basin, an area of particular agricultural interest. The modeling and the analysis combined ground-based observations (weather stations and cosmic-ray neutron probes) with remote sensing products (snow cover and surface soil moisture). Summarizing the methodology, hourly semivariograms were used to estimate meteorological variables on a grid, subsequently aggregated as weighted area averages over the GUs and compared to the ``centroid-based approach'' formerly used, showing interesting improvements in simulating the river discharges. Besides, the Noce River basin was modeled at various resolutions, meaning with coarser and finer GUs. The multiscale approach also shows improved validation performance not only for discharge but also for soil moisture and snow cover when GUs are smaller. The modeling infrastructure was implemented according to FAIR principles and respecting the DARTHs blueprint and is currently operational for water budget analysis.