Using Commercial Satellite Imagery to Reconstruct 3 m and Daily Spring
Snow Water Equivalent
Abstract
Snow water equivalent (SWE) distribution at fine spatial scales (≤ 10 m)
is difficult to estimate due to modeling and observational constraints.
However, the distribution of SWE throughout the spring snowmelt season
is often correlated to the timing of snow disappearance. Here, we show
that snow cover maps generated from PlanetScope’s constellation of Dove
Satellites can resolve the 3 m date of snow disappearance across seven
alpine domains in California and Colorado. Across a 5-year period (2019
– 2023), the average uncertainty in the date of snow disappearance, or
the period of time between the last date of observed snow cover and the
first date of observed snow absence, was 3 days. Using a simple
shortwave-based snowmelt model calibrated at nearby snow pillows, the
PlanetScope date of snow disappearance could be used to reconstruct
spring snow water equivalent (SWE). Relative to lidar SWE estimates, the
SWE reconstruction had a spatial coefficient of correlation of 0.75, and
SWE spatial variability that was biased by 9%, on average. SWE
reconstruction biases were then improved to within 0.04 m, on average,
by calibrating snowmelt rates to track the spring temporal evolution of
fractional snow cover observed by PlanetScope, including fractional snow
cover over the full modeling domain, and across domain subsections where
snowmelt rates may differ. This study demonstrates the utility of
fine-scale and high-frequency optical observations of snow cover, and
the simple and annually repeatable connections between snow cover and
spring snow water resources in regions with seasonal snowpack.