An approach for modelling snowcover ablation and snowmelt runoff in cold region environments
| dc.contributor.advisor | Pomeroy, John W. | en_US |
| dc.contributor.advisor | Pietroniro, Alain | en_US |
| dc.contributor.committeeMember | Si, Bing C. | en_US |
| dc.contributor.committeeMember | Martz, Lawrence W. | en_US |
| dc.contributor.committeeMember | Marsh, Philip | en_US |
| dc.contributor.committeeMember | de Boer, Dirk H. | en_US |
| dc.contributor.committeeMember | Tarboton, David G. | en_US |
| dc.creator | Dornes, Pablo F. | en_US |
| dc.date.accessioned | 2009-06-29T12:37:08Z | en_US |
| dc.date.accessioned | 2013-01-04T04:41:21Z | |
| dc.date.available | 2010-06-29T08:00:00Z | en_US |
| dc.date.available | 2013-01-04T04:41:21Z | |
| dc.date.created | 2009 | en_US |
| dc.date.issued | 2009 | en_US |
| dc.date.submitted | 2009 | en_US |
| dc.description.abstract | Reliable hydrological model simulations are the result of numerous complex interactions among hydrological inputs, landscape properties, and initial conditions. Determination of the effects of these factors is one of the main challenges in hydrological modelling. This situation becomes even more difficult in cold regions due to the ungauged nature of subarctic and arctic environments. This research work is an attempt to apply a new approach for modelling snowcover ablation and snowmelt runoff in complex subarctic environments with limited data while retaining integrity in the process representations. The modelling strategy is based on the incorporation of both detailed process understanding and inputs along with information gained from observations of basin-wide streamflow phenomenon; essentially a combination of deductive and inductive approaches. The study was conducted in the Wolf Creek Research Basin, Yukon Territory, using three models, a small-scale physically based hydrological model, a land surface scheme, and a land surface hydrological model. The spatial representation was based on previous research studies and observations, and was accomplished by incorporating landscape units, defined according to topography and vegetation, as the spatial model elements. Comparisons between distributed and aggregated modelling approaches showed that simulations incorporating distributed initial snowcover and corrected solar radiation were able to properly simulate snowcover ablation and snowmelt runoff whereas the aggregated modelling approaches were unable to represent the differential snowmelt rates and complex snowmelt runoff dynamics. Similarly, the inclusion of spatially distributed information in a land surface scheme clearly improved simulations of snowcover ablation. Application of the same modelling approach at a larger scale using the same landscape based parameterisation showed satisfactory results in simulating snowcover ablation and snowmelt runoff with minimal calibration. Verification of this approach in an arctic basin illustrated that landscape based parameters are a feasible regionalisation framework for distributed and physically based models. In summary, the proposed modelling philosophy, based on the combination of an inductive and deductive reasoning, is a suitable strategy for reliable predictions of snowcover ablation and snowmelt runoff in cold regions and complex environments. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10388/etd-06292009-123708 | en_US |
| dc.language.iso | en_US | en_US |
| dc.subject | Landscape-units | en_US |
| dc.subject | Inductive-Deductive | en_US |
| dc.subject | Modelling | en_US |
| dc.subject | Physically-based | en_US |
| dc.subject | Snowmelt | en_US |
| dc.subject | Ungauged Basins | en_US |
| dc.title | An approach for modelling snowcover ablation and snowmelt runoff in cold region environments | en_US |
| dc.type.genre | Thesis | en_US |
| dc.type.material | text | en_US |
| thesis.degree.department | Geography | en_US |
| thesis.degree.discipline | Geography | en_US |
| thesis.degree.grantor | University of Saskatchewan | en_US |
| thesis.degree.level | Doctoral | en_US |
| thesis.degree.name | Doctor of Philosophy (Ph.D.) | en_US |