Snow represents an important resource in mountainous regions. Monitoring its extent and amount is relevant for several applications, such as hydrology, ecology, avalanche monitoring, or hydropower production. However, a correct understanding of the high spatial and temporal variability of snow accumulation, redistribution and ablation processes requires its monitoring in a spatialized and detailed way. Recently, the launch of the Sentinel missions has opened the doors to new approaches that mainly exploit high resolution (HR) data having a spatial detail of few dozens of m. In this thesis, we aimed at exploiting these new sources of information to retrieve important parameters related to the snowmelt processes. In detail, we i) investigated the use of Sentinel-1 Synthetic Aperture Radar (SAR) observations to evaluate snowmelt dynamics in alpine regions, ii) developed a novel approach based on a hierarchical multi-resolution analysis of optical time-series to reconstruct the daily HR snow cover area (SCA), and iii) explored the combination of HR SCA time-series, SAR snowmelt information and other multi-source data to reconstruct a daily HR snow water equivalent (SWE) time-series. In detail, in the first work we analyzed the relationship between the snowmelt phases of a snowpack and the multi-temporal SAR backscattering. We found that the SAR is able to provide useful information about the moistening, ripening and runoff phases. In the second work, we exploited the snow pattern repetition on an inter-annual basis driven by the geomorphological features of a study area to carry out historical analyses. Thus, we took advantage of these repeated patterns to fuse low resolution and HR satellite optical data and set up a gap filling to derive daily HR snow cover area (SCA) time-series. These two research works are the pillars for the last contribution, which aims at combining all these information sources together with both in-situ data and a simple yet robust degree day model that provides an estimate of the potential melting to derive daily HR SWE time-series. These final results have an unprecedented spatial detail, that allows to sample the phenomena linked to the complex snow accumulation, redistribution and ablation processes with the required spatial and temporal resolution. The methodology and the results of each experimental work are illustrated and discussed in detail in the chapters of this thesis, with a look on further research and potential applications.
| Identifer | oai:union.ndltd.org:unitn.it/oai:iris.unitn.it:11572/356729 |
| Date | 09 November 2022 |
| Creators | Premier, Valentina |
| Contributors | Premier, Valentina, Bruzzone, Lorenzo |
| Publisher | Università degli studi di Trento, place:TRENTO |
| Source Sets | Università di Trento |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | firstpage:1, lastpage:140, numberofpages:140 |
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