Climate warming impacts on snowpack accumulation in an alpine watershed

Abstract

This paper combines a wide-area assessment of forecast changes in wintertime synoptic conditions over western North America with a meso-scale alpine hydrometeorology model to evaluate the impacts of forecast climate change on snowpack conditions in an alpine watershed. The synoptic analysis was used to generate long-term climate time series scenarios using the Canadian Centre for Climate Modelling and Analysis first-generation coupled general circulation model (GCM). The alpine hydrometeorology model SIMGRID is used to predict changes in wintertime precipitation at the watershed scale. The SNOPAC model is a simple snow model that predicts the overall snow accumulation throughout a watershed based on the output from SIMGRID. A vapour transfer model has been incorporated into the SNOPAC model to estimate snow volumes more accurately. The model is applied to a small alpine watershed in the southern Canadian Rockies. The synoptic analysis and GCM output forecasts a modest increase in both winter precipitation and temperatures in the study area. The hypothesis herein is that the increase in winter precipitation due to synoptic conditions will not compensate for regional changes in the rain-to-snow ratios. The net result will be a decline in winter accumulations of precipitation as snow, and hence an expected decline in spring runoff.

Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework

“…Biases in RH, U , and T air were often the major controls on modeled sublimation in NB, NB+RE, UB, and NB_gauge, while Q li bias controlled modeled sub-limation in NB_lab. These field results partially agree with the sensitivity analysis of Lapp et al (2005), who showed the most important forcings for sublimation in the Canadian Rockies were U and Q si . However, they did not consider Q li in their sensitivity analysis, so the experiments are not exactly comparable.…”

“…Physically based models allow researchers to test hypotheses about the role of specific processes in hydrologic systems and how changes in environment (e.g., climate, land cover) may impact key hydrologic fluxes and states (Barnett et al, 2008;Deems et al, 2013;Leavesley, 1994;Clark et al, 2011b). Due to the complexity of processes represented, these models usually require numerous meteorological forcing inputs and model parameters.…”

Flood Frequency Variability During the Past 80 Years in the Slave River Delta, NWT, as Determined from Multi-Proxy Paleolimnological Analysis

“…A shift to lower snowpacks in the Smoky River basin since the 1970s (Prowse and Conly, 1998;Romolo et al, 2006) may signify the beginning of a trend towards lower headwater discharge during the spring melt. Other evidence suggests that this trend towards lower snowpacks will continue (Lapp et al, 2005;Rood et al, 2005), suggesting further reductions in flood frequency in the SRD in the coming decades, as has also been suggested for the PAD (Wolfe et al, 2008a).…”

Multi-variable verification of hydrological processes in the upper North Saskatchewan River basin, Alberta, Canada

“…Recent studies have shown that declining streamflows are expected to reduce water availability for irrigation, industrial and domestic use, as well as hydroelectric power generation (Gan 1998, Rood et al 2005, Byrne and Kienzle 2008, Sauchyn and Kulshreshtha 2008. Expected impacts include decreased snow accumulations and associated earlier spring runoffs, increased winter and decreased summer and late fall streamflows, and decreased glacial melt contributions (Burn 1994, Gan 1998, Demuth and Pietroniro 2003, Lapp et al 2005, Sauchyn and Kulshreshtha 2008. Therefore, the understanding of watershed balances is essential for current and future water resources planning.…”