[A-CC25] Glaciology

[ACC25-P12] Possibility to detect spatiotemporal distribution of snow amount within a continental river watershed using optical sensors onboard polar orbiting satellites

*Masahiro Hori¹, Kosei Miyamoto¹, Konosuke Sugiura¹ (1.University of Toyama, School of Sustainable Design)

Keywords:snow depth, snow cover extent, river watershed, satellite optical sensor, Remote Sensing

The extent and depth of snow cover is a key variable to be observed from space for assessing hydrological cycle within river watershed. Satellite-derived snow cover extent (SCE) in the Northern Hemisphere (NH) exhibits significant decreasing trends during the past nearly 40 years (1982-2015) (Hori et al., 2017). On the other hand, snow depth another key variable to be monitored has not been measured accurately within river watershed in Siberia due to the existence of vegetation covers which make satellite remote sensing of snow depth or snow water equivalent from space unreliable. In 2018, space-borne lidar was launched onboard the ICESat-2 satellite. We examined the possibility to use the data of ICESat-2-derived terrain height for measuring snow depth on the Lena River watershed. Preliminary analysis results showed that the height difference between snow covered and non-snow covered surface, which corresponds to snow depth, can be measured within the accuracy of less than 10 cm although the accuracy varied depending on land cover types. In addition, the river water level measured using the ICESat-2 data exhibits significant seasonal variation, which could be used for monitoring river water discharge. By combining snow depth from ICESat-2 with SCE derived from passive optical sensors such as SGLI, the variation of snow water equivalent within the watershed might be evaluated on monthly basis.

Reference:
Hori, M. et al., 2017: A 38-year (1978-2015) Northern Hemisphere daily snow cover extent product derived using consistent objective criteria from satellite-borne optical sensors. Remote Sens. Environ., 191, 402-418.