Show simple item record

Authordc.contributor.authorMendoza Zúñiga, Pablo 
Authordc.contributor.authorMusselman, Keith N. 
Authordc.contributor.authorRevuelto, Jesús 
Authordc.contributor.authorDeems, Jeffrey S. 
Authordc.contributor.authorLópez Moreno, J. Ignacio 
Authordc.contributor.authorMcPhee, James 
Admission datedc.date.accessioned2020-11-06T14:31:21Z
Available datedc.date.available2020-11-06T14:31:21Z
Publication datedc.date.issued2020
Cita de ítemdc.identifier.citationWater Resources Research, 55, e2020WR027343.es_ES
Identifierdc.identifier.other10.1029/2020WR027343
Identifierdc.identifier.urihttps://repositorio.uchile.cl/handle/2250/177586
Abstractdc.description.abstractUnderstanding and characterizing the spatial distribution of snow are critical to represent the energy balance and runoff production in mountain environments. In this study, we investigate the interannual and seasonal variability in snow depth scaling behavior at the Izas experimental catchment of the Spanish Pyrenees (2,000 to 2,300 m above sea level). We conduct variogram analyses of 24 snow depth maps derived from terrestrial light detection and ranging scans, acquired during six consecutive snow seasons (2011-2017) that span a range of hydroclimatic conditions. We complement our analyses with bare ground topography data and wind speed and direction measurements. Our results show temporal consistency in the spatial variability of snow depth, with short-range fractal behavior and scale break lengths that are similar to the optimal search distance (25 m) previously reported for the topographic position index, a terrain-based predictor of snow depth. Beyond the 25-m scale break, there is little to no fractal structure. We report a long-range scale break of the order of 185-300 m for most dates-aligned with the dominant wind direction-and patterns between anisotropies in scale break lengths of shallow snow cover and directional terrain scaling behavior. The temporal consistency of snow depth scaling patterns suggests that, in addition to guiding the spatial configuration of physically based models, fractal analysis could be used to inform the design of independent variables for statistical models used to predict snow depth and its variability.es_ES
Patrocinadordc.description.sponsorshipComisión Nacional de Investigación Científica y Tecnológica (CONICYT) CONICYT FONDECYT 3170079 CONICYT/PIA Project AFB180004es_ES
Lenguagedc.language.isoenes_ES
Publisherdc.publisherAmerican Geophysical Uniones_ES
Type of licensedc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile*
Link to Licensedc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/*
Sourcedc.sourceWater Resources Researches_ES
Keywordsdc.subjectSnow depthes_ES
Keywordsdc.subjectLidares_ES
Keywordsdc.subjectVariogrames_ES
Keywordsdc.subjectFractales_ES
Keywordsdc.subjectScale breakes_ES
Títulodc.titleInterannual and seasonal variability of snow depth scaling behavior in a subalpine catchmentes_ES
Document typedc.typeArtículo de revistaes_ES
dcterms.accessRightsdcterms.accessRightsAcceso Abierto
Catalogueruchile.catalogadorctces_ES
Indexationuchile.indexArtículo de publicación ISI
Indexationuchile.indexArtículo de publicación SCOPUS


Files in this item

Icon

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivs 3.0 Chile
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Chile