C41F-06
Constraining Annual Water Balance Estimates with Basin-Scale Observations from the Airborne Snow Observatory during the Current Californian Drought
Thursday, 17 December 2015: 09:15
3005 (Moscone West)
Kat Bormann1, Thomas H Painter1, Danny G Marks2, Andrew R Hedrick3, Jeffrey S Deems4, Victoria Patterson5 and Bruce J McGurk6, (1)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (2)USDA Agriculture Research Serv, Boise, ID, United States, (3)USDA Agricultural Research Service New England Plant, Soil and Water Research Laboratory, East Wareham, MA, United States, (4)National Snow and Ice Data Center, Boulder, CO, United States, (5)Jet Propulsion Laboratory, Pasadena, CA, United States, (6)Self Employed, McGurk Hydrologic, Washington, DC, United States
Abstract:
One of the great unknowns in mountain hydrology is how much water is stored within a seasonal snowpack at the basin scale. Quantifying mountain water resources is critical for assisting with water resource management, but has proven elusive due to high spatial and temporal variability of mountain snow cover, complex terrain, accessibility constraints and limited in-situ networks. The Airborne Snow Observatory (ASO, aso.jpl.nasa.gov) uses coupled airborne LiDAR and spectrometer instruments for high resolution snow depth retrievals which are used to derive unprecedented basin-wide estimates of snow water mass (snow water equivalent, SWE). ASO has been operational over key basins in the Sierra Nevada Mountains in California since 2013. Each operational year has been very dry, with precipitation in 2013 at 75% of average, 2014 at 50% of average and 2015 – the lowest snow year on record for the region. With vastly improved estimates of the snowpack water content from ASO, we can now for the first time conduct observation-based mass balance accounting of surface water in snow-dominated basins, and reconcile these estimates with observed reservoir inflows. In this study we use ASO SWE data to constrain mass balance accounting of basin annual water storages to quantify the water contained within the snowpack above the Hetch Hetchy water supply reservoir (Tuolumne River basin, California). The analysis compares and contrasts annual snow water volumes from observed reservoir inflows, snow water volume estimates from ASO, a physically based model that simulates the snowpack from meteorological inputs and a semi-distributed hydrological model. The study provides invaluable insight to the overall volume of water contained within a seasonal snowpack during a severe drought and how these quantities are simulated in our modelling systems. We envisage that this research will be of great interest to snowpack modellers, hydrologists, dam operators and water managers worldwide.
