High‐resolution snow depth prediction using Random Forest algorithm with topographic parameters: A case study in the Greiner watershed, Nunavut

High‐resolution snow depth prediction using Random Forest algorithm with topographic parameters: A case study in the Greiner watershed, Nunavut

Increased surface temperatures (0.7°C per decade) in the Arctic affects polar ecosystems by reducing the extent and duration of annual snow cover. Monitoring of these important ecosystems needs detailed information on snow cover properties at resolutions (

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Hydrological processes 2022-03, Vol.36 (3), p.n/a
Hauptverfasser: Meloche, Julien, Langlois, Alexandre, Rutter, Nick, McLennan, Donald, Royer, Alain, Billecocq, Paul, Ponomarenko, Serguei
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Alpine environments
Arctic snow
Ecological effects
Ecosystems
Ecotypes
Machine learning
Parameters
Permafrost
Random Forest
Resolution
Snow
Snow accumulation
Snow cover
Snow depth
Surface temperature
Topography
Vegetation
Watersheds
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Increased surface temperatures (0.7°C per decade) in the Arctic affects polar ecosystems by reducing the extent and duration of annual snow cover. Monitoring of these important ecosystems needs detailed information on snow cover properties at resolutions (
ISSN:0885-6087
1099-1085
DOI:10.1002/hyp.14546