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Titel Simulation of snow accumulation and melt in needleleaf forest environments
VerfasserIn C. R. Ellis, J. W. Pomeroy, T. Brown, J. MacDonald
Medientyp Artikel
Sprache Englisch
ISSN 1027-5606
Digitales Dokument URL
Erschienen In: Hydrology and Earth System Sciences ; 14, no. 6 ; Nr. 14, no. 6 (2010-06-14), S.925-940
Datensatznummer 250012333
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/hess-14-925-2010.pdf
 
Zusammenfassung
Drawing upon numerous field studies and modelling exercises of snow processes, the Cold Regions Hydrological Model (CRHM) was developed to simulate the four season hydrological cycle in cold regions. CRHM includes modules describing radiative, turbulent and conductive energy exchanges to snow in open and forest environments, as well as account for losses from canopy snow sublimation and rain evaporation. Due to the physical-basis and rigorous testing of each module, there is a minimal need for model calibration. To evaluate CRHM, simulations of snow accumulation and melt were compared to observations collected at paired forest and clearing sites of varying latitude, elevation, forest cover density, and climate. Overall, results show that CRHM is capable of characterising the variation in snow accumulation between forest and clearing sites, achieving a model efficiency of 0.51 for simulations at individual sites. Simulations of canopy sublimation losses slightly overestimated observed losses from a weighed cut tree, having a model efficiency of 0.41 for daily losses. Good model performance was demonstrated in simulating energy fluxes to snow at the clearings, but results were degraded from this under forest cover due to errors in simulating sub-canopy net longwave radiation. However, expressed as cumulative energy to snow over the winter, simulated values were 96% and 98% of that observed at the forest and clearing sites, respectively. Overall, the good representation of the substantial variations in mass and energy between forest and clearing sites suggests that CRHM may be useful as an analytical or predictive tool for snow processes in needleleaf forest environments.
 
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