Spatio-temporal variations in snow depth and associated driving mechanisms in a temperate mesoscale mountainous watershed

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dc.contributor.authorCartwright, Kelsey
dc.contributor.authorUniversity of Lethbridge. Faculty of Arts and Science
dc.contributor.supervisorHopkinson, Christopher
dc.date.accessioned2019-06-19T20:20:27Z
dc.date.available2019-06-19T20:20:27Z
dc.date.issued2019
dc.degree.levelMastersen_US
dc.description.abstractSeasonal snow is a significant source of runoff in Western Canada. Mountainous snow depth distributions are challenging to quantify over large areas. Enhanced monitoring methods can provide the necessary data for more accurate flood and drought forecasts. Using multiple datasets, this research provides the foundation to optimize LiDAR snow depth data collection. Snow depth distribution consistency during mid-winter and melt onset was assessed and depth driver (elevation, aspect, slope, TPI and canopy cover) importance was determined. Consistent inter-annual relationships between aspect, TPI, elevation, treeline and snow depth distributions could be exploited in future sampling designs. Random forest models were utilized to predict depth over a 103 km2 area, based on high resolution (3m) watershed scale and partial datasets. Statistically significant correlations were found between parent and modelled datasets in all trials. This thesis illustrates that machine learning is a promising means of optimizing airborne LiDAR snow surveys in headwater environments.en_US
dc.embargoNoen_US
dc.identifier.urihttps://hdl.handle.net/10133/5415
dc.language.isoen_USen_US
dc.proquest.subjectAtmospheric sciences [0725]en_US
dc.proquest.subjectClimate change [0404]en_US
dc.proquest.subjectHydrologic sciences [0388]en_US
dc.proquestyesYesen_US
dc.publisherLethbridge, Alta. : University of Lethbridge, Dept. of Geographyen_US
dc.publisher.departmentDepartment of Geographyen_US
dc.publisher.facultyArts and Scienceen_US
dc.relation.ispartofseriesThesis (University of Lethbridge. Faculty of Arts and Science)
dc.subjectRemote sensingen_US
dc.subjectSnowen_US
dc.subjectSnow surveysen_US
dc.titleSpatio-temporal variations in snow depth and associated driving mechanisms in a temperate mesoscale mountainous watersheden_US
dc.typeThesisen_US
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