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Investigating snowpack across scale in the northern Great Lakes–St. Lawrence forest region of Central Ontario, Canada
Author(s) -
Beaton Andy D.,
Metcalfe Robert A.,
Buttle James M.,
Franklin Steven E.
Publication year - 2019
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.13558
Subject(s) - transect , snowpack , snow , environmental science , scale (ratio) , physical geography , hydrology (agriculture) , variogram , spatial ecology , geology , atmospheric sciences , geography , kriging , ecology , geomorphology , statistics , cartography , oceanography , geotechnical engineering , mathematics , biology
Scaling issues in snow hydrology persist due to limitations in instrumentation and inability to measure physical properties and processes at spatiotemporal scales required for analysis. Snow depth and water equivalent (SWE) across scale estimated using time‐lapse photos, transects, and model grids (Canadian Meteorological Centre depth, GlobSnow SWE) were found to represent different physical processes and have substantially different statistical moments. Findings have implications for understanding limitations of distributing snowpack measurements, data assimilation, and validation of remotely sensed estimates.