Comparing InSAR Snow Water Equivalent Retrieval Using ALOS2 With In Situ Observations and SnowModel Over the Boreal Forest Area

Interferometric SAR (InSAR) is a promising tool for monitoring seasonal snow and for retrieving snow water equivalent (SWE) as the interferometric phase can be related to changes in SWE (<inline-formula> <tex-math notation="LaTeX">$\Delta $ </tex-math></inline-formula>SWE). The boreal forest is a challenging landscape for the InSAR retrieval of SWE since it contributes to the signal by adding an undesired component originating from the vegetation. Although the technique has been validated extensively, most of these works are limited to discrete points. For comparison, we used snowpack simulations from the SnowModel, a high-resolution spatially distributed snow evolution model. This enables a better understanding of the limitations of L-band InSAR for SWE retrieval since it allows evaluating its performance under different conditions. We analyzed the effect on coherence caused by snow melt between acquisitions and the presence of wet snow at the acquisition time. The interferometric phase was inverted and compared to the simulated <inline-formula> <tex-math notation="LaTeX">$\Delta $ </tex-math></inline-formula>SWE from the SnowModel distributions for three interferometric pairs. The results indicate a good spatial match between SnowModel and InSAR estimations. However, an increased difference was observed over densely forested areas when the air temperature was close to zero in at least one of the interferometric pairs. We hypothesize that the increase in permittivity of the forest for close to zero temperatures also increases the contribution from the canopy, consequently inducing errors in the retrieval. Both ALOS2 and SnowModel <inline-formula> <tex-math notation="LaTeX">$\Delta $ </tex-math></inline-formula>SWE estimates were compared with in situ data including a snow scale, snow depth from an automatic weather station (AWS), a snow pit, and manual courses.