Abstract
Albedo plays an important role in snow evolution modeling quantifying the amount of solar radiation absorbed and reflected by the snowpack, especially in mid-latitude regions with semiarid conditions. Satellite remote sensing is the most extensive technique to determine the variability of snow albedo over medium to large areas; however, scale effects from the pixel size of the sensor source may affect the results of snow models, with different impacts depending on the spatial resolution. This work presents the evaluation of snow albedo values retrieved from (1) Landsat images, L (16-day frequency with 30 × 30 m pixel size) and (2) SPOT VEGETATION albedo products, SV (10-day frequency with 1 × 1 km pixel size) in the Sierra Nevada mountain range in South Spain, a Mediterranean site representative of highly heterogeneous conditions. Daily snow albedo map series were derived from both sources, and used as input for the snow module in the WiMMed (Watershed Integrated Management in Mediterranean Environment) hydrological model, which was operational at the study area for snow monitoring for two hydrological years, 2011–2012 and 2012–2013, in the Guadalfeo river basin in Sierra Nevada. The results showed similar albedo trends in both data sources, but with different values, the shift between both sources being distributed in space according to the altitude. This difference resulted in lower snow cover fraction values in the SV-simulations that affected the rest of snow variables included in the simulation. This underestimation, mainly due to the effects of mixed pixels composed by both snow and snow-free areas, produced higher divergences from both sources during the melting periods when the evapo-sublimation and melting fluxes are more relevant. Therefore, the selection of the albedo data source in these areas, where snow evapo-sublimation plays a very important role and the presence of snow-free patches is very frequent, can condition the final accuracy of the simulations of operational models; Landsat is the recommended source if the monitoring of the snowpack is the final goal of the modeling, whereas the SV product may be advantageous when water resource planning in the medium and long term is intended. Applications of large pixel size albedo sources need further assessment for short-term operational objectives.
Highlights
Albedo plays in important role in the energy and water balance in areas with the presence of snow, since it affects the shortwave radiative flux (0.3–2.5 μm), quantifying the amount of solar radiation reflected and absorbed by the snowpack
The two remote sensing sources analyzed, Landsat and SPOT VEGETATION, with significantly different sensor pixel sizes, were used to retrieve daily maps of snow albedo, which served as inputs for the operational snow model available at the study site, the Sierra Nevada Range in southern Spain
The results have shown a mean increase in the averaged retrieved snow albedo series from SPOT
Summary
Albedo plays in important role in the energy and water balance in areas with the presence of snow, since it affects the shortwave radiative flux (0.3–2.5 μm), quantifying the amount of solar radiation reflected and absorbed by the snowpack It is one of the main factors involved in the melting processes due to the dominant importance of the radiation components during these periods [1,2]. The use of energy and water balance models to characterize and predict the snowpack dynamics is the most recommended approach under the highly variable conditions dominant in these regions [5,6,7], together with the adoption of a spatial resolution high enough to represent the hydrological response of the watershed [8] This is especially highlighted during the snowmelt periods to be capable of predicting the snow contribution to runoff and, potentially, to spring floods
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