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Predicting alpine headwater stream intermittency: a case study in the northern Rocky Mountains

June 1, 2015

This investigation used climatic, geological, and environmental data coupled with observational stream intermittency data to predict alpine headwater stream intermittency. Prediction was made using a random forest classification model. Results showed that the most important variables in the prediction model were snowpack persistence, represented by average snow extent from March through July, mean annual mean monthly minimum temperature, and surface geology types. For stream catchments with intermittent headwater streams, snowpack, on average, persisted until early June, whereas for stream catchments with perennial headwater streams, snowpack, on average, persisted until early July. Additionally, on average, stream catchments with intermittent headwater streams were about 0.7 °C warmer than stream catchments with perennial headwater streams. Finally, headwater stream catchments primarily underlain by coarse, permeable sediment are significantly more likely to have intermittent headwater streams than those primarily underlain by impermeable bedrock. Comparison of the predicted streamflow classification with observed stream status indicated a four percent classification error for first-order streams and a 21 percent classification error for all stream orders in the study area.

Publication Year 2015
Title Predicting alpine headwater stream intermittency: a case study in the northern Rocky Mountains
DOI 10.1016/j.ecohyd.2015.04.002
Authors Roy Sando, Kyle W. Blasch
Publication Type Article
Publication Subtype Journal Article
Series Title Ecohydrology & Hydrobiology
Index ID 70148564
Record Source USGS Publications Warehouse
USGS Organization WY-MT Water Science Center