Modelling Climate Change Impacts on Spring Runoff for the Rocky Mountains of Montana and Alberta I: Model Development, Calibration and Historical Analysis

• Published in: Canadian water resources journal Vol. 36; no. 1; pp. 17 - 34
• Main Authors: Larson, Robert P., Byrne, James M., Johnson, Daniel L., Letts, Matthew G., Kienzie, Stefan W.
• Format: Journal Article
• Language: English
• Published: Taylor & Francis Group 22-03-2011; Taylor & Francis Group LLC; Canadian Water Resources Assn
• Subjects: Canada; Climate change; Climatic changes; Environmental impact; Hydrology; Management; Methods; Mountains; Runoff; Studies; Water supply; Watershed management; Canada; Rocky Mountains; Montana; Alberta Canada; United States > US
• ISSN: 0701-1784; 1918-1817
• DOI: 10.4296/cwrj3601017

Water supply from mountain snowmelt is a key resource on the Great Plains. Hydrologists recognize that water yields could be significantly reduced in a warmer climate, with negative impacts upon regional water supplies. Weather data availability is usually sparse in alpine watersheds. Consequently, distributed alpine snow hydrology models are generally limited to small instrumented watersheds. Such models are unable to simulate the timing and magnitude of spring streamflow at a sufficient spatial scale for watershed management. In this study, the Simulated Grid microclimate model (SIMGRID) was refined and applied to the simulation of snow water equivalent (SWE) and spring streamflow volume in the headwaters of the St. Mary basin of northern Montana. Relationships between winter precipitation and elevation were derived from snow survey data. The SWE mass balance algorithm was enhanced to include the effect of rain-on-snow conditions, and to differentiate between snowmelt and rainfall runoff. Multiple regression analysis was used to relate predicted SWE and rainfall runoff to observed stream discharge (QS) at Babb, MT, for the 1961-1990 period. The refined SIMGRID model was then applied to the 1991-2004 period, and accurately simulated spring discharge (linear regression, r2 = 0.67). The refined SIMGRID model is capable of simulating spring runoff in poorly-instrumented complex terrain, at a scale of relevance to water resource managers. This paper presents the results of Part I of a two-part study, which assesses the impacts of climate change on spring runoff for the study watershed.