4.6 Article

Runoff Projection from an Alpine Watershed in Western Canada: Application of a Snowmelt Runoff Model

期刊

WATER
卷 13, 期 9, 页码 -

出版社

MDPI
DOI: 10.3390/w13091199

关键词

Snowmelt Runoff Model (SRM); climate change; degree– day; Upper Athabasca River Basin; hydrology; MODIS

资金

  1. Natural Sciences and Engineering Council of Canada (NSERC)

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The study used the degree-day Snowmelt Runoff Model (SRM) combined with MODIS to remotely sense various factors for predicting future runoff changes. The SRM simulations showed consistent patterns in historical flows and future projections, demonstrating good performance in simulating runoff.
The rising global temperature is shifting the runoff patterns of snowmelt-dominated alpine watersheds, resulting in increased cold season flows, earlier spring peak flows, and reduced summer runoff. Projections of future runoff are beneficial in preparing for the anticipated changes in streamflow regimes. This study applied the degree-day Snowmelt Runoff Model (SRM) in combination with the MODIS to remotely sense snow cover observations for modeling the snowmelt runoff response of the Upper Athabasca River Basin in western Canada. After assessing its ability to simulate the observed historical flows, the SRM was applied for projecting future runoff in the basin. The inclusion of a spatial and temporal variation in the degree-day factor (DDF) and separation of the DDF for glaciated and non-glaciated areas were found to be important for improved simulation of varying snow conditions over multiple years. The SRM simulations, driven by an ensemble of six statistically downscaled GCM runs under the RCP8.5 scenario for the future period (2070-2080), show a consistent pattern in projected runoff change, with substantial increases in May runoff, smaller increases over the winter months, and decreased runoff in the summer months (June-August). Despite the SRM's relative simplicity and requirement of only a few input variables, the model performed well in simulating historical flows, and provides runoff projections consistent with historical trends and previous modeling studies.

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