A flexible and inexpensive remote sensing tool for albedo estimation using conventional terrestrial photography and its validation on an Alpine glacier are described. The proposed technique involves georeferencing oblique photographs to a digital elevation model (DEM), defining a mapping function between the information contained on a given pixel of the image and the corresponding cell of the DEM. This is attained by performing a perspective projection of the DEM after a viewing transformation into the camera coordinate system. Once the image is georeferenced, the reflectance values recorded by the film or digital camera are corrected for topographic and atmospheric influences and for the effect of the photographic process (lens-film-developing-scanning). Atmospheric transmittance is evaluated using the MODTRAN radiative transfer model. Diffuse and direct irradiation are estimated using a parametric solar irradiation model. The solar-ground geometry, anisotropy of reflected radiation, the effect of surrounding topography and the portion of visible sky are evaluated using terrain algorithms applied to the DEM. The response of the camera-film-scanner system is evaluated using an empirical approach. The result is a geographically correct map of normalized reflectance values. By comparing these to a surface of known albedo, the spatial distribution of albedos is calculated. Comparisons to in situ measurements on the Mer de Glace glacier, French Alps, show good agreement. Sources of error are identified and ways of improvement addressed. The georeferencing algorithm, implemented into the Interactive Data Language (IDL) is available from the author and at the user contributed IDL library at www.rsinc.com.

Tidewater calving glaciers can undergo large fluctuations not necessarily in direct response to climate, but rather owing to complex ice–water interactions at the glacier termini. One example of this process in Chilean Patagonia is Glaciar Jorge Montt, where two cameras were installed in February 2010, collecting up to four glacier photographs per day, until they were recovered on 22 January 2011. Ice velocities were derived from feature tracking of the geo-referenced photos, yielding a mean value of 13 ±4 md^–1 for the whole lower part of the glacier. These velocities were compared to satellite-imagery-derived feature tracking obtained in February 2010, resulting in similar values. During the operational period of the cameras, the glacier continued to retreat (1 km), experiencing one of the highest calving fluxes ever recorded in Patagonia (2.4 km³ a^–1). Comparison with previous data also revealed ice acceleration in recent years. These very high velocities are clearly a response to enhanced glacier calving activity into a deep water fjord.

From 18 to 19 June 2013, the Ésera river in the Pyrenees, Northern Spain, caused widespread damage due to flooding as a result of torrential rains and sustained snowmelt. We estimate the contribution of snow melt to total discharge applying a snow energy balance to the catchment. Precipitation is derived from sparse local measurements and the WRF-ARW model over three nested domains, down to a grid cell size of 2 km. Temperature profiles, precipitation and precipitation gradient are well simulated, although with a possible displacement regarding the observations. Snowpack melting was correctly reproduced and verified in three instrumented sites, and according to satellite images. We found that the hydrological simulations agree well with measured discharge. Snowmelt represented 33% of total runoff during the main flood event and 23% at peak flow. The snow energy balance model indicates that most of the energy for snow melt during the day of maximum precipitation came from turbulent fluxes. This approach forecast correctly peak flow and discharge during normal conditions at least 24 h in advance and could give an early warning of the extreme event 2.5 days before.

Terrestrial photography is a cost-effective and easy-to-use method for measuring and monitoring spatially distributed land surface variables. It can be used to continuously investigate remote and often inaccessible terrain. We focus on the observation of snow cover patterns in high mountainous areas. The high temporal and spatial resolution of the photographs have various applications, for example validating spatially distributed snow hydrological models. However, the analysis of a photograph requires a preceding georectification of the digital camera image. To accelerate and simplify the analysis, we have developed the "Photo Rectification And ClassificaTIon SoftwarE" (PRACTISE) that is available as a Matlab code. The routine requires a digital camera image, the camera location and its orientation, as well as a digital elevation model (DEM) as input. If the viewing orientation and position of the camera are not precisely known, an optional optimisation routine using ground control points (GCPs) helps to identify the missing parameters. PRACTISE also calculates a viewshed using the DEM and the camera position. The visible DEM pixels are utilised to georeference the photograph which is subsequently classified. The resulting georeferenced and classified image can be directly compared to other georeferenced data and can be used within any geoinformation system. The Matlab routine was tested using observations of the north-eastern slope of the Schneefernerkopf, Zugspitze, Germany. The results obtained show that PRACTISE is a fast and user-friendly tool, able to derive the microscale variability of snow cover extent in high alpine terrain, but can also easily be adapted to other land surface applications.