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Scale effects in a distributed snow water equivalence and snowmelt model for mountain basins
Author(s) -
Cline Don,
Elder Kelly,
Bales Roger
Publication year - 1998
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/(sici)1099-1085(199808/09)12:10/11<1527::aid-hyp678>3.0.co;2-e
Subject(s) - snowmelt , snowpack , snow , environmental science , digital elevation model , drainage basin , remote sensing , image resolution , temporal resolution , elevation (ballistics) , spatial ecology , spatial variability , hydrology (agriculture) , geology , geomorphology , geography , cartography , ecology , statistics , physics , geometry , mathematics , geotechnical engineering , quantum mechanics , artificial intelligence , computer science , biology
We investigated the effect of increasing spatial and temporal resolutions on modelled distributions of snow water equivalence (SWE) and snowmelt in the Emerald Lake Watershed (ELW) of the Sierra Nevada of California, USA. We used a coupled remote sensing/distributed energy balance snowmelt model (SNODIS), and used previously validated results from a high spatial (30 m) and temporal (hourly) resolution model run in ELW as a control. We selected spatial resolutions that are commensurate with standard product DEMs (digital elevation models) or with existing or planned satellite remote sensing data, and temporal resolutions that are factors of typical operational intervals for meteorological data. We degraded the spatial resolution of the DEM from 30 m to 90, 250 and 500 m prior to computing the distributed micrometeorological data. We degraded the classified remote sensing data to the same spatial resolutions prior to computing the duration of the snow cover. Similarly, we degraded the temporal resolution of the micrometeorological data from 1 h to 3 and 6 h prior to computing the distributed energy balance and snowmelt. We compared mean basin SWE, basin snowpack water volume and the spatial patterns of SWE from each test with our previous, high resolution results. We found no significant differences between the mean basin‐wide SWE computed from the 250 m and 500 m spatial resolutions and that of our high resolution control, regardless of temporal resolution. At each temporal resolution mean basin SWE was overestimated at the 90 m resolution by 14–17%. Coarsening of the spatial resolution did result in a loss of explicit information regarding the location of SWE in the basin, as expected. We discuss these results in terms of their implications for applying the SNODIS model to larger regions. © 1998 John Wiley & Sons, Ltd.