4.7 Article

Small scale spatial variability of snow density and depth over complex alpine terrain: Implications for estimating snow water equivalent

Journal

ADVANCES IN WATER RESOURCES
Volume 55, Issue -, Pages 40-52

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.advwatres.2012.08.010

Keywords

Snow depth and density; Snow water equivalent (SWE); Spatial variability; Pyrenees

Funding

  1. Hidrologia nival en el Pirineo central espanol: variabilidad espacial, importancia hidrologica y su respuesta a la variabilidad y cambio climatico [CGL2011-27536/HID]
  2. Spanish Commission of Science and Technology
  3. FEDER
  4. ACQWA [FP7-ENV-2008-1-212250]
  5. La nieve en el Pirineo aragones: Distribucion especial y su respuesta a las condiciones climaticas
  6. Efecto de los escenarios de cambio climatico sobre la hidrologica superficial y la gesti~n de embalses del Pirineo Aragones
  7. Obra Social La Caixa
  8. Influencia del cambio climatico en el turismo de nieve [CTTP1/10]
  9. Comunidad de Trabajo de los Pirineos, CTP

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This study analyzes spatial variability of snow depth and density from measurements made in February and April of 2010 and 2011 in three 1-2 km(2) areas within a valley of the central Spanish Pyrenees. Snow density was correlated with snow depth and different terrain characteristics. Regression models were used to predict the spatial variability of snow density, and to assess how the error in computed densities might influence estimates of snow water equivalent (SWE). The variability in snow depth was much greater than that of snow density. The average snow density was much greater in April than in February. The correlations between snow depth and density were generally statistically significant but typically not very high, and their magnitudes and signs were highly variable among sites and surveys. The correlation with other topographic variables showed the same variability in magnitude and sign, and consequently the resulting regression models were very inconsistent, and in general explained little of the variance. Antecedent climatic and snow conditions prior to each survey help highlight the main causes of the contrasting relation shown between snow depth, density and terrain. As a consequence of the moderate spatial variability of snow density relative to snow depth, the absolute error in the SWE estimated from computed densities using the regression models was generally less than 15%. The error was similar to that obtained by relating snow density measurements directly to adjacent snow depths. (C) 2012 Elsevier Ltd. All rights reserved.

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