Hydropower production in Alpine regions is greatly affected by snow accumulation and melt. However, monitoring these processes is challenging due to limited measurements at high elevations and the complex mountainous terrain. This thesis investigates the integration of satellite-derived snow products into hydrological modelling to improve the representation of snow dynamics in eight basins, each closed by a hydropower plant of the Province of Bolzano (South Tyrol, Italy). Analyses were carried out in a multi-phase workflow that combined in-situ snow depth measurements, meteorological station data, a snowfall proxy based on precipitation and temperature, Sentinel-1 C-SNOW snow depth observations, snow water equivalent (SWE) variation products, and hydrological simulations using the FEST model. Results show that satellite-derived snow depth generally reproduces the temporal evolution of the snow dynamics observed at ground stations, although errors increase with elevation. The snowfall proxy captures the timing of snowfall events but consistently produces lower intensity estimates. Comparisons between the proxy and satellite SWE changes show that Sentinel-1 effectively detects accumulation periods while reporting higher SWE increments due to the combination of multi-day snowfall and internal snowpack processes. Hydrological simulations conducted with precipitation-only input data and with precipitation combined with satellite SWE demonstrate that both setups produce similar seasonal patterns. Notably, the simulation incorporating satellite data yields higher SWE values and improves the spatial description of snow storage. Despite significant differences in magnitude between modeled and satellite SWE, the strong temporal alignment emphasizes the potential benefits of remote sensing for hydrological applications in data-limited mountainous areas. Overall, this study shows that integrating satellite SWE information can help assess snow-driven hydropower resources more reliably in the Italian Alps.
La produzione idroelettrica nelle regioni alpine è fortemente influenzata dall’accumulo e dallo scioglimento della neve. Tuttavia, il monitoraggio di questi processi risulta complesso a causa della scarsità di misure alle alte quote e della morfologia montuosa. Questa tesi analizza l’integrazione di prodotti nivologici derivati da satellite nella modellazione idrologica, con l’obiettivo di migliorare la rappresentazione della dinamica della neve in otto bacini, ciascuno associato a una centrale idroelettrica della Provincia di Bolzano (Alto Adige, Italia). Le analisi sono state condotte attraverso un workflow multi-fase che combina misure in situ di altezza del manto nevoso, dati provenienti da stazioni meteorologiche, un proxy di nevicata basato su precipitazione e temperatura, osservazioni della profondità di neve Sentinel-1 C-SNOW, prodotti di variazione della snow water equivalent (SWE) e simulazioni idrologiche tramite il modello FEST. I risultati mostrano che la profondità di neve derivata da satellite riproduce generalmente l’evoluzione temporale della dinamica nivale osservata alle stazioni a terra, sebbene le incertezze aumentino con la quota. Il proxy di nevicata cattura correttamente il timing degli eventi, ma fornisce valori di intensità sistematicamente inferiori. Il confronto tra il proxy e le variazioni di SWE da satellite evidenzia che Sentinel-1 rileva efficacemente i periodi di accumulo, riportando incrementi di SWE più elevati grazie alla combinazione di nevicate multi-giornaliere e processi interni del manto nevoso. Le simulazioni idrologiche condotte con i soli dati di precipitazione e con precipitazione combinata a SWE satellitare mostrano andamenti stagionali simili. In particolare, l’integrazione dei dati da satellite produce valori di SWE più alti e migliora la descrizione spaziale dell’accumulo nivale. Nonostante le differenze di magnitudine tra SWE modellata e SWE da satellite, la forte coerenza temporale osservata evidenzia i potenziali vantaggi dell’uso del telerilevamento per applicazioni idrologiche in aree montuose con disponibilità di dati limitata. Nel complesso, questo studio dimostra che l’integrazione delle informazioni di SWE satellitare può contribuire a valutare in modo più affidabile le risorse idroelettriche dipendenti dalla neve nelle Alpi italiane.
Optimizing high-altitude precipitation estimates using Sentinel-1 observations for hydropower assessment in the Italian Alps
Toni Caravello, Enzo
2024/2025
Abstract
Hydropower production in Alpine regions is greatly affected by snow accumulation and melt. However, monitoring these processes is challenging due to limited measurements at high elevations and the complex mountainous terrain. This thesis investigates the integration of satellite-derived snow products into hydrological modelling to improve the representation of snow dynamics in eight basins, each closed by a hydropower plant of the Province of Bolzano (South Tyrol, Italy). Analyses were carried out in a multi-phase workflow that combined in-situ snow depth measurements, meteorological station data, a snowfall proxy based on precipitation and temperature, Sentinel-1 C-SNOW snow depth observations, snow water equivalent (SWE) variation products, and hydrological simulations using the FEST model. Results show that satellite-derived snow depth generally reproduces the temporal evolution of the snow dynamics observed at ground stations, although errors increase with elevation. The snowfall proxy captures the timing of snowfall events but consistently produces lower intensity estimates. Comparisons between the proxy and satellite SWE changes show that Sentinel-1 effectively detects accumulation periods while reporting higher SWE increments due to the combination of multi-day snowfall and internal snowpack processes. Hydrological simulations conducted with precipitation-only input data and with precipitation combined with satellite SWE demonstrate that both setups produce similar seasonal patterns. Notably, the simulation incorporating satellite data yields higher SWE values and improves the spatial description of snow storage. Despite significant differences in magnitude between modeled and satellite SWE, the strong temporal alignment emphasizes the potential benefits of remote sensing for hydrological applications in data-limited mountainous areas. Overall, this study shows that integrating satellite SWE information can help assess snow-driven hydropower resources more reliably in the Italian Alps.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/247511