Abstract
Area-based measurements of snow water equivalent (SWE) are important for understanding earth system processes such as glacier mass balance, winter hydrological storage in drainage basins and ground thermal regimes. Remote sensing techniques are ideally suited for wide-scale area-based mapping with the most commonly used technique to measure SWE being passive-microwave, which is limited to coarse spatial resolutions of 25 km or greater, and to areas without significant topographic variation. Passive-microwave also has a negative bias for large SWE. Repeat-pass synthetic aperture radar interferometry (InSAR) as an alternate technique allows measurement of SWE change at much higher spatial resolution. However, it has not been widely adopted because: (1) the phase unwrapping problem has not been robustly addressed, especially for interferograms with poor coherence and; (2) SWE change maps scaled directly from repeat-pass interferograms are not an absolute measurement but contain unknown offsets for each contiguous coherent area. We develop and test a novel method for repeat-pass InSAR based dry-snow SWE estimation that exploits the sensitivity of the dry-snow refraction-induced InSAR phase to topographic variations. The method robustly estimates absolute SWE change at spatial resolutions of < 1 km, without the need for phase unwrapping. We derive a quantitative signal model for this new SWE change estimator and identify the relevant sources of bias. The method is demonstrated using both simulated SWE distributions and a 9-year RADARSAT-2 spotlight-mode dataset near Inuvik, NWT, Canada. SWE results are compared to in situ snow survey measurements and estimates from ERA5 reanalysis. Our method performs well in high-relief areas and in areas with high SWE (> 150 mm), thus providing complementary coverage to other passive- and active-microwave based SWE estimation methods. Further, our method has the advantage of requiring only a single wavelength band and thus can utilize existing spaceborne synthetic aperture radar systems. In application, a first order analysis of SWE trends within three drainage basins suggests that differences between basin-level accumulations are a function of major landcover types, and that re-vegetation following a forest-tundra fire that occurred over 50 years ago continues to affect the spatial distribution of SWE accumulation in the study area.
Highlights
Snow melt is one of the greatest sources of water in snow-affected areas, snow accumulation on glaciers is critical to their mass balance and longevity, and snow cover variation is a dominant control on ground thermal regimes in cold regions, quantification of snowpack conditions is essential to understanding the role of snow on earth system processes
We have introduced a novel spatial analysis method ‘SlopeVar’ that estimates dry-snow water equivalent (SWE) change from wrapped repeat-pass 715 interferograms by spatially correlating the InSAR phase to a digital elevation model (DEM)-derived dry-snow phase sensitivity map over a suitably sized estimation window
We investigated the role of spatial SWE change inhomogeneity as a possible bias factor by simulating an evolving snow-pack with the Snow720 Model snow transport model and found that surface morphology caused sufficient ∆SWE inhomogeneity to generate modest estimation errors whereas spatial variations in vegetation height induced much larger errors
Summary
Snow melt is one of the greatest sources of water in snow-affected areas, snow accumulation on glaciers is critical to their mass balance and longevity, and snow cover variation is a dominant control on ground thermal regimes in cold regions, quantification of snowpack conditions is essential to understanding the role of snow on earth system processes. Snow depth, used to infer SWE when integrated with snow density, has been determined using surface elevation models 40 developed using LiDAR as well as structure-from-motion (optical photogrammetry) systems, either by differential repeat-pass measurement or comparison with a pre-existing snow-free reference elevation model (Deems et al, 2013; Nolan et al, 2015). As these systems are presently only feasible on airborne platforms they have not yet been used for repeated, widescale SWE mapping, which is required to substantively improve hydrological monitoring. Despite the potential for spaceborne microwave determination of SWE, there are key limitations inherent within each of the current approaches that affect the sensitivity and uncertainty of the measurements and prevent adoption of the methods for wide-scale SWE monitoring
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
