Influence of microscale in snow distributed modelling in semiarid regions

This work focuses on the importance of the microscale snow distribution in the modelling of the snow dynamics in semiarid regions. Snow over these areas has particular features that further complicate its measuring, monitoring and modelling (e.g. several snowmelt cycles throughout the year and a very heterogeneous distribution). Most extended GIS-based calculation of snowmelt/accumulation models must deal with non-negligible scales effects below the cell size, which may result in unsatisfactory predictions depending on the study scale. This study proposes the joint use of physically- based distributed snowmelt-accumulation modelling and remote sensing observation datasets to study the subgrid variability of snow distribution and its effects on the snow modelling at the watershed scale. The study has been carried out in Sierra Nevada Mountains, southern Spain, where the highest submit of the Iberian Peninsula can be found close to the seaside, which results in a sharp gradient of climate conditions associated to topography. The typical Alpine climate in the mountains is modulated by the subtropical conditions at the coast, with occurrence of snowfall usually from November to April in altitudes greater than 2000 m, and successive cycles of accumulation and snowmelt during the season. Terrestrial photography data, an alternative and economical remote sensing information source whose scales can be adapted to the studied processes requirements, has been employed to study the snow dynamics at the subgrid scale (30 x 30 m). Snow cover area and snow depth datasets were obtained from terrestrial images in a pilot study area during 2009-2013. These dataset was employed to define the subgrid variability by means of depletion curves with two different approaches. As a first step, different snow depletion curves proposed by other authors were tested at the study area. The observations were included in a data assimilation scheme, an Ensemble Transform Kalman Filter, in the energy and mass balance equations of the snow model. The results identified the need for selecting a particular depletion curve parameterization depending on the succession of accumulation-melting cycles. Secondly, based on the former results, these datasets were directly employed to define parametric depletion curves at the pilot area. A flexible sigmoid function was found to satisfactorily reproduce the observed trends of the snowmelt effects on the snow cover area at the cell scale, but different values resulted for the sigmoid’s parameters depending on the different snow states found: 1) cycles with a high accumulated snow depth which came from a metamorphosed snow; 2) cycles with great snow depth preceded by short accumulation phases; 3) cycles with low accumulation that occur in the cold season; and 4) cycles with low snow depth values which take place during spring. Moreover, an unique expression for the accumulation curve was also proposed. These results confirm the need of different parameterization to represent the physical variability in the accumulation-melting cycles in semiarid regions. Furthermore, this selective curve improves the model performance when compared to the results previously obtained with the data assimilation scheme. Finally, the proposed parameterization was tested at the watershed scale, at the Guadalfeo River Basin, at the southern face of Sierra Nevada. Snow cover area distributed results from the model simulations were assessed with Landsat TM and ETM+ observations (30 x 30m spatial resolution), consisting of snow cover maps at the area from an endmembers spectral mixture analysis of the Landsat imagery. These maps had previously been validated from snow cover maps at higher spatial resolution (10m x 10m) obtained from terrestrial photography in a monitoring hillside in the area. The results showed a significant agreement between observed...Este trabajo pone de manifiesto la importancia de la microescala en el modelado distribuido de la nieve en ambientes semiáridos. En estas áreas, la nieve posee características muy específicas que dificultan su medida, monitorización y modelado (p.e. diferentes ciclos de fusión a lo largo del año y una gran variabilidad espaciotemporal). Desde este último punto de vista, los modelos distribuidos de acumulación/fusión de nieve poseen limitaciones al representar procesos que ocurren a una escala inferior a la seleccionada como tamaño de celda en la discretización para la realización de sus cálculos. Este estudio propone el uso de modelado hidrológico, físico y distribuido, junto con técnicas de teledetección para el estudio de la variabilidad a escala de celda de la nieve y sus implicaciones a escala de cuenca. El área de estudio seleccionada ha sido Sierra Nevada, sur de España, cordillera paralela a la costa del mar Mediterráneo y donde se localizan las cumbres más altas de la Península Ibérica. Su proximidad al mar hace que el típico clima alpino de montaña se vea modificado por el clima subtropical de la costa, con nevadas desde noviembre a abril en cotas superiores a los 2000 m y ciclos sucesivos de acumulación y fusión de nieve durante este periodo. La fotografía terrestre, técnica de teledetección novedosa y económica, que permite adaptar las observaciones a la escala de los procesos estudiados, ha sido empleada para el estudio de la dinámica de la nieve a escala de celda (30 x 30 m). Valores de superficie cubierta y espesor de nieve han sido obtenidos en una pequeña área experimental durante el período 2009-2013. Estas series de datos fueron empleadas para definir la variabilidad espacial dentro de la celda por medio de curvas de agotamiento utilizando dos enfoques. En primer lugar, diferentes curvas de agotamiento propuestas por otros autores fueron evaluadas en el área de estudio. Las observaciones fueron incluidas mediante un algoritmo de asimilación de datos, Ensemble Transform Kalman Filter, en el balance de masa y energía del modelo de nieve. Los resultados mostraron la necesidad de seleccionar diferentes curvas de agotamiento dependiendo de la sucesión de los ciclos de fusión-acumulación. En segundo lugar y en base a los resultados previos, estas series de datos fueron directamente empleadas para definir curvas de agotamiento paramétricas en el área experimental. Una curva sigmoide fue la utilizada para reproducir las tendencias de los diferentes ciclos de fusión, donde diferentes parámetros de ajuste fueron obtenidos para cada uno de estados encontrados: 1) ciclos con un gran espesor de nieve muy metamorfoseada; 2) ciclos son gran espesor de nieve precedidas de una fase de acumulación corta; 3) ciclos con poco espesor durante la estación de nieve; y 4) ciclos con poco espesor de nieve que tienen lugar en primavera. Una única parametrización fue propuesta para los ciclos de acumulación. Estos resultados confirmaron la necesidad de diferentes parametrizaciones para la representación de la variabilidad observada en los ciclos de acumulación-fusión en ambientes semiáridos. La elección de estas curvas mejora los resultados en el modelado si se comparan con los obtenidos utilizando el algoritmo de asimilación. Finalmente, la parametrización propuesta fue evaluada a escala de cuenca, en la cuenca del río Guadalfeo, cara sur de Sierra Nevada. Los mapas distribuidos de superficie cubierta de nieve obtenidos en el modelado fueron comparados con mapas de nieve obtenidos mediante la aplicación de un modelo de mezclas espectrales aplicado sobre imágenes Landsat TM y ETM+ (30 x 30 m). Estos mapas fueron previamente validados con mapas de nieve a mayor resolución (10 x 10 m) obtenidos gracias a imágenes terrestres in una ladera monitorizada dentro de la cuenca. Los resultados muestran una gran concordancia entre mapas medidos y simulados, lo..

Comparison between Snow Albedo Obtained from Landsat TM, ETM+ Imagery and the SPOT VEGETATION Albedo Product in a Mediterranean Mountainous Site

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 objective