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Observations of distributed snow depth and snow duration within diverse forest structures in a maritime mountain watershed
Author(s) -
DickersonLange Susan E.,
Lutz James A.,
Gersonde Rolf,
Martin Kael A.,
Forsyth Jenna E.,
Lundquist Jessica D.
Publication year - 2015
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2015wr017873
Subject(s) - snow , watershed , environmental science , elevation (ballistics) , hydrology (agriculture) , lidar , snowmelt , forest cover , tree canopy , physical geography , canopy , remote sensing , geology , geography , meteorology , ecology , geometry , mathematics , geotechnical engineering , archaeology , machine learning , computer science , biology
Abstract Spatially distributed snow depth and snow duration data were collected over two to four snow seasons during water years 2011–2014 in experimental forest plots within the Cedar River Municipal Watershed, 50 km east of Seattle, Washington, USA. These 40 × 40 m forest plots, situated on the western slope of the Cascade Range, include unthinned second‐growth coniferous forests, variable density thinned forests, forest gaps in which a 20 m diameter (approximately equivalent to one tree height) gap was cut in the middle of each plot, and old‐growth forest. Together, this publicly available data set includes snow depth and density observations from manual snow surveys, distributed snow duration observations from ground temperature sensors and time‐lapse cameras, meteorological data collected at two open locations and three forested locations, and forest canopy data from airborne light detection and ranging (LiDAR) data and hemispherical photographs. These colocated snow, meteorological, and forest data have the potential to improve understanding of forest influences on snow processes, and provide a unique model‐testing data set for hydrological analyses in a forested, maritime watershed. We present empirical snow depletion curves within forests to illustrate an application of these data to improve subgrid representation of snow cover in distributed modeling.