Snow water equivalent retrieval over Idaho - Part 2: Using L-band UAVSAR repeat-pass interferometry

Abstract

This study evaluates using interferometry on low-frequency synthetic aperture radar (SAR) images to monitor snow water equivalent (SWE) over seasonal and synoptic scales. We retrieved SWE changes from nine pairs of SAR images, mean 8d temporal baseline, captured by an L-band aerial platform, NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), over central Idaho as part of the NASA SnowEx 2020 and 2021 campaigns. The retrieved SWE changes were compared against coincident in situ measurements (SNOTEL and snow pits from the SnowEx field campaign) and to 100m gridded SnowModel modeled SWE changes. The comparison of in situ to retrieved measurements shows a strong Pearson correlation (RCombining double low line0.80) and low RMSE (0.1m, nCombining double low line64) for snow depth change and similar results for SWE change (RMSECombining double low line0.04m, RCombining double low line0.52, nCombining double low line57). The comparison between retrieved SWE changes to SnowModel SWE change also showed good correlation (RCombining double low line0.60, RMSDCombining double low line0.023m, nCombining double low line3.2×106) and especially high correlation for a subset of pixels with no modeled melt and low tree coverage (RCombining double low line0.72, RMSDCombining double low line0.013m, nCombining double low line6.5×104). Finally, we bin the retrievals for a variety of factors and show decreasing correlation between the modeled and retrieved values for lower elevations, higher incidence angles, higher tree percentages and heights, and greater cumulative melt. This study builds on previous interferometry work by using a full winter season time series of L-band SAR images over a large spatial extent to evaluate the accuracy of SWE change retrievals against both in situ and modeled results and the controlling factors of the retrieval accuracy.