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Snowmelt and runoff modelling of an Arctic hydrological basin in west Greenland

✍ Scribed by C. E. Bøggild; C. J. Knudby; M. B. Knudsen; W. Starzer


Book ID
101283382
Publisher
John Wiley and Sons
Year
1999
Tongue
English
Weight
415 KB
Volume
13
Category
Article
ISSN
0885-6087

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✦ Synopsis


This paper compares the performance of a conceptual modelling system and several physically-based models for predicting runo in a large hydrological basin, Tasersuaq, in west Greenland. This basin, which is typical of many Greenland basins, is interesting because of the fast hydrological response to changing conditions. Due to the predominance of exposed bedrock surface and only minor occurrence of sediments and organic soils, there is little restraint to run-o, making the treatment of the snowmelt component of primary importance.

Presently a conceptual modelling system, HBV, is applied in Greenland and also in most of the arctic regions of Scandinavia for operational forecasting. A general wish to use hydrological models for other purposes, such as to improve data collection and to gain insight into the hydrological processes has promoted interest in the more physically-based hydrological models. In this paper, two degree-day models, the Danish version of the physically-based SHE distributed hydrological modelling system (MIKE SHE) and the conceptual HBV model are compared with a new model that links MIKE SHE and a distributed energy balance model developed for this study, APUT.

The HBV model performs the best overall simulation of discharge, which presently makes it most suited for general forecasting. The combination of MIKE SHE and APUT i.e. a physically based modelling system shows promising results by improving the timing of the initiation of spring ¯ood, but does not perform as well throughout the remaining part of the snowmelt season. The modelling study shows that local parameters such as the snow depletion curve, the temporal snow albedo and perhaps also melt water storage need to be more precisely determined from ®eld studies before physically-based modelling can be improved.


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