Multi-band SAR Interferometry for snow water equivalent estimation over Alpine mountains

Snow cover is the main component of the cryosphere and the knowledge of its properties such as thickness, water equivalent, and freeze / thaw conditions, is relevant for the study of global cycle water and the climate system. The snow water equivalent (SWE) is the water content obtained from melting a sample of snow and can be defined according to the snowpack depth and density. Compared to optical sensors and radiometers, SAR is potentially able to provide SWE estimations at high resolution, independently from daylight and in any weather conditions. The estimation of SWE can be performed by exploring both the backscattering coefficient and the interferometric phase of SAR acquisitions. The SWE estimation through differential SAR interferometry (DInSAR) [1] is based on the change of interferometric phase induced by changes on both geometrical path and propagation velocity of the SAR signal due to different SWE conditions between the two interferometric acquisitions. By assuming that dielectric inhomogeneities are much smaller than wavelength, we can neglect the volume scattering. By further assuming that snowpack is made by dry snow, the absorption of the microwave signal is negligible. Under these hypotheses, the backscattered SAR signal comes from the ground surface under the snowpack and the signal time delay related to the snowpack depends just on the snowpack depth and density. So, the DInSAR phase can be approximated as a linear function of the SWE changes [2] (due to a change in snow depth and / or density) occurred between the two interferometric acquisitions. This linear relation between DInSAR phase and SWE changes, involves also the incident angle and the wavelength, and holds for a snowpack consisting of dry snow and an arbitrary number of layers each of uniform density. Of course, due to the differential nature of the DInSAR measurements both in space and time, only SWE changes can be measured. Absolute SWE values can be inferred either by assuming that one of the two interferometric acquisitions is snow free, or by using a reference SWE value coming from independent measurements. Moreover, the SWE estimation from DInSAR phase presents some critical aspects typical of the interferometric measurements: i) phase aliasing, which limits the maximum measurable SWE variation; ii) undesirable phase components related to residual topography, atmospheric signal, and orbital errors; iii) interferometric coherence, which depends on the scattering properties of the resolution cell. Recently, this last issue has been investigated by using a multiband interferometric SAR sensor under controlled test site, observing critical DInSAR phase decorrelation conditions occurring even after few hours at shorter wavelengths. [3]. Therefore, by all above considerations, the retrieval of SWE through DInSAR is feasible only under conditions of dry snow and spatial homogeneity of snowpack properties and is hindered by phase decorrelation, aliasing, and presence of spurious signals. In particular, temporal decorrelation is due to several concurrent causes such as rain, wind, and temperature changes, and it represents a very critical issue to be faced with most of wavelengths and revisit times of nowadays spaceborne SAR sensors. That's why, this approach, despite proposed more than two decades ago, does not yet allow reliable and operational SWE monitoring at large scale. This work revises some of the issues related to the SWE estimation, and experiments the use of multifrequency SAR data for deriving SWE maps over Alpine mountains trough both DInSAR-based and SAR backscattering-based algorithms. Case studies in Val Senales and Val d'Aosta (Italy) were investigated, characterised by critical settings such as steep topography, limited size, a