Spatial Distribution and Scaling Properties of Lidar‐Derived Snow Depth in the Extratropical Andes. Issue 12 (1st December 2020)
- Record Type:
- Journal Article
- Title:
- Spatial Distribution and Scaling Properties of Lidar‐Derived Snow Depth in the Extratropical Andes. Issue 12 (1st December 2020)
- Main Title:
- Spatial Distribution and Scaling Properties of Lidar‐Derived Snow Depth in the Extratropical Andes
- Authors:
- Mendoza, Pablo A.
Shaw, Thomas E.
McPhee, James
Musselman, Keith N.
Revuelto, Jesús
MacDonell, Shelley - Abstract:
- Abstract: We characterize elevational gradients, probability distributions, and scaling patterns of lidar‐derived snow depth at the hillslope scale along the extratropical Andes. Specifically, we analyze snow depth maps acquired near the date of maximum accumulation in 2018 at three experimental sites: (i) the Tascadero catchment (31.26°S, 3, 270–3, 790 m), (ii) the Las Bayas catchment (33.31°S, 3, 218–4, 022 m); and (iii) the Valle Hermoso (VH) catchment (36.91°S, 1, 449–2, 563 m). We examine two subdomains in the latter site: one with (VH West) and one without (VH East) shrub cover. The comparison across sites reveals that elevational gradients are site‐dependent, and that the gamma and normal distributions are more robust than the lognormal function to characterize the spatial variability of snow depth. Multiscale behavior in snow depth is obtained in all sites, with up to three fractal regimes, and the magnitude of primary scale breaks is found to be related to the mean separation distance between local snow depth peaks. The differences in snow depth fractal parameters between VH West—the only vegetated subdomain—and the remaining sites suggest that local topographic and land cover properties are dominant controls on the spatial structure of snow, rather than average hydroclimatic conditions. Overall, the results presented here provide, for the first time, insights into the spatial structure of snow depth along the extratropical Andes Cordillera, showing notableAbstract: We characterize elevational gradients, probability distributions, and scaling patterns of lidar‐derived snow depth at the hillslope scale along the extratropical Andes. Specifically, we analyze snow depth maps acquired near the date of maximum accumulation in 2018 at three experimental sites: (i) the Tascadero catchment (31.26°S, 3, 270–3, 790 m), (ii) the Las Bayas catchment (33.31°S, 3, 218–4, 022 m); and (iii) the Valle Hermoso (VH) catchment (36.91°S, 1, 449–2, 563 m). We examine two subdomains in the latter site: one with (VH West) and one without (VH East) shrub cover. The comparison across sites reveals that elevational gradients are site‐dependent, and that the gamma and normal distributions are more robust than the lognormal function to characterize the spatial variability of snow depth. Multiscale behavior in snow depth is obtained in all sites, with up to three fractal regimes, and the magnitude of primary scale breaks is found to be related to the mean separation distance between local snow depth peaks. The differences in snow depth fractal parameters between VH West—the only vegetated subdomain—and the remaining sites suggest that local topographic and land cover properties are dominant controls on the spatial structure of snow, rather than average hydroclimatic conditions. Overall, the results presented here provide, for the first time, insights into the spatial structure of snow depth along the extratropical Andes Cordillera, showing notable similarities with other mountain regions in the Northern Hemisphere and providing guidance for future snow studies. Key Points: We present the first analysis of snow depth distribution in the extratropical Andes using high‐resolution lidar measurements Multiscale behavior in snow depth is found, and fractal parameters depend on local topography and vegetation rather than climate The magnitudes of scale break lengths are related to the mean separation distance between local snow depth peaks … (more)
- Is Part Of:
- Water resources research. Volume 56:Issue 12(2020)
- Journal:
- Water resources research
- Issue:
- Volume 56:Issue 12(2020)
- Issue Display:
- Volume 56, Issue 12 (2020)
- Year:
- 2020
- Volume:
- 56
- Issue:
- 12
- Issue Sort Value:
- 2020-0056-0012-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2020-12-01
- Subjects:
- snow depth -- lidar -- probability distribution -- variogram -- fractal
Hydrology -- Periodicals
333.91 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1944-7973 ↗
http://www.agu.org/pubs/current/wr/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1029/2020WR028480 ↗
- Languages:
- English
- ISSNs:
- 0043-1397
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9275.150000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 22526.xml