Using Quantile Regression to Model Elevation/SWE Relationships in the Olympics and Central Washington Cascades
Title | Using Quantile Regression to Model Elevation/SWE Relationships in the Olympics and Central Washington Cascades |
Publication Type | Conference Proceedings |
Year of Conference | 2011 |
Authors | McDonald, S., and Barry D. |
Conference Name | 79th Annual Western Snow Conference |
Series Title | Proceedings of the 79th Annual Western Snow Conference |
Date Published | April 2011 |
Publisher | Western Snow Conference |
Conference Location | Stateline, NV |
Keywords | Washington Cascades, snow water equivalent, quartile regression, watershed elevation, least squares regression, Dungeness Watershed |
Abstract | Although ordinary least squares (OLS) regression is often used to develop initial models for elevation/snow water equivalent (SWE) relationships in watersheds, such an approach cannot account for the heterogeneous variability in SWE over elevation bands common in many coastal Pacific Northwest watersheds. This is particularly problematic in attempting to model middle-elevation SWE in watersheds affected by winter rain-on-snow events. Scatterplots of this relationship often show a distinctive fan-shaped pattern that widens as elevation increases, implying that there is not a single rate of change in SWE by elevation. Thus, the use of an OLS regression in models or trend assessment could provide severely misleading estimates of SWE in middle elevation areas where no field data are collected. We compare OLS and quantile regression-based models of SWE by elevation based on four snow seasons of field assessment for the Dungeness Watershed of western Washington State, as well as for snow courses and SNOTEL sites in the Olympic Mountains and central Washington Cascades. In both cases, quantile regression better accounts for the observed data than does the typical OLS approach. |
URL | sites/westernsnowconference.org/PDFs/2011McDonald.pdf |