Assessment of airborne LIDAR for snowpack depth modeling

• Published in: Boletín de la Sociedad Geológica Mexicana Vol. 63; no. 1; pp. 95 - 107
• Main Authors: Baños, Ignacio Moreno, García, Antoni Ruiz, Marturià i Alavedra, Jordi, Oller i Figueras, Pere, Iglesias, Jordi Piña, Martínez i Figueras, Pere, López, Julià Talaya
• Format: Journal Article
• Language: English; Portuguese
• Published: Sociedad Geológica Mexicana e Instituto de Geología de la UNAM 2011; Sociedad Geológica Mexicana, A.C
• Subjects: ARTÍCULOS DEL NÚMERO ESPECIAL; Geology; Geosciences, Multidisciplinary; Global positioning systems; Hydrological modeling; LIDAR; Snow; Snowpack; Solar radiation; Spatial models; Surface areas; Watersheds; Profundidad de manto nivoso; SIG; stepwise regression tree; GIS; Pirineos; LIDAR; Snowpack depth; Pyrenees; árbol de regresión
• ISSN: 1405-3322; 1405-3322
• DOI: 10.18268/bsgm2011v63n1a8

The Institut Geològic de Catalunya (IGC) and the Institut Cartogràfic de Catalunya (ICC) have begun a joint project to model snowpack depth distribution in the Núria valley (a 38 km² basin located in the Eastern Pyrenees) in order to evaluate water reserves in mountain watersheds. The evaluation was based on a remote sensing airborne LIDAR survey and validated with field-work calculations. Previous studies have applied geostatistical techniques to extrapolate sparse point data obtained from costly field-work campaigns. Despite being a recently developed technique, LIDAR has become a useful method in snow sciences as it produces dense point data and covers wide areas. The new methodology presented here combines LIDAR data with field-work, the use of geographical information systems (GIS) and the stepwise regression tree (SRT), as an extrapolation technique. These methods have allowed us to map snowpack depth distribution in high spatial resolution. Extrapolation was necessary because raw LIDAR data was only obtained from part of the study area in order to minimise costs. Promising results show high correlation between LIDAR data and field data, validating the use of airborne laser altimetry to estimate snow depth. Moreover, differences of total snow volume calculated from modeled snowpack distribution and total volume from LIDAR data differ by only 1 %.