Improved Estimates of Snow Water Equivalent at NRCS Aerial Markers Using New Statistical Methodology
Title | Improved Estimates of Snow Water Equivalent at NRCS Aerial Markers Using New Statistical Methodology |
Publication Type | Conference Proceedings |
Year of Conference | 2012 |
Authors | Lea, Jon, Sturm Matthew, and Lea Jolyne |
Conference Name | 80th Annual Western Snow Conference |
Series Title | Proceedings of the Western Snow Conference |
Date Published | 2012 |
Publisher | Omnipress |
Conference Location | Anchorage, Alaska |
Keywords | aerial markers, Bayesian analysis, bulk density, climate (snow) class, NRCS, Snow water equivalent, SWE |
Abstract | Natural Resources Conservation Service (NRCS) Aerial Markers snow depth data have been measured since the late 1940s and are located in remote areas of the West. These stations would typically take hours or days of ground travel to visit, so are measured by aircraft over-flights to get a monthly depth reading. This depth reading and an estimate of the snowpack density are used to estimate snow water equivalent (SWE) for use in water supply forecasting. The NRCS historically has used an empirical method described in the agency National Engineering Handbook (Davis, R. T., et al.) to calculate densities. Using Bayesian analysis technique, Sturm et al. developed densification parameters from worldwide snow pack data. With these parameters, the accuracy of the estimates of density can be improved using only the snow depth, day of the year, and climate class of the snowpack. These parameters were applied to a subset of data from February 1, 2012, NRCS Cooperative snow surveys where measurements of SWE and depth were measured. The density of the snow pack using the observed data was compared to the modeled density. Differences between the modeled and the measured densities were about 1%. With additional refinement, this method can be applied to depth readings throughout the NRCS Aerial Marker network to calculate SWE values in a consistent and repeatable fashion. |
URL | sites/westernsnowconference.org/PDFs/2012Lea-J.pdf |