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

Kyle Siemens,Terry Prowse,Rajesh Shrestha,Yonas Dibike

doi:10.3390/w13091199

Kyle Siemens, Terry Prowse + Show 2 more

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https://doi.org/10.3390/w13091199

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Abstract

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.

Highlights

Streamflow forecasts are a valuable source of information for water resource management, e.g., to assess water availability for irrigation, hydroelectricity generation, and municipal or industrial use [1]
The Snowmelt Runoff Model (SRM) model for the Upper Athabasca River Basin (UARB) was calibrated with the Markov Chain Monte Carlo (MCMC) method using observed discharge data at the Hinton station for the years 2000 to 2005 and validated over the 2006 to 2010 period
The results showed that the mean annual discharge (MAD) increased for all climate change projections, with the exception of inmcm4/Bias Correction/Climate Imprint (BCCI) (Figure 9, Table 5)

Summary

Introduction

Streamflow forecasts are a valuable source of information for water resource management, e.g., to assess water availability for irrigation, hydroelectricity generation, and municipal or industrial use [1]. An ensemble of six regional climate models projected 1.5 to 2.5 ◦C of warming of the annual mean daily maximum temperature, 2.5 to 3 ◦C of warming of the annual mean daily minimum temperature, and increases in precipitation of up to 100 mm across western Canada over 2041–2070 relative to 1971–2000 [7]. Given these potential changes in precipitation and temperature, quantifying future runoff will assist water resource managers in preparing for changing runoff seasonality

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