Andrew G. Fountain

Date of Award

Summer 1-1-2012

Document Type


Degree Name

Doctor of Philosophy (Ph.D.) in Environmental Sciences and Resources


Environmental Science and Management

Physical Description

1 online resource (xv, 309 p.) : ills. (chiefly col.), col. maps + 7 geologic data sets (ods files) and 2 geologic data sets (odt files)


Hydrology -- Washington (State), Snow -- Washington (State), Runoff -- Washington (State), Cascade Range, Monte Carlo method




Rain-on-snow (ROS) occurs when warm, wet air moves into latitudes and/or elevations having vulnerable snowpacks, where it can alter water inputs to infiltration, runoff and erosion. The Pacific Northwest is particularly susceptible: winter storms off the Pacific cause locally heavy rain plus snowmelt almost annually, and disastrous flooding and landsliding intermittently. In maritime mountainous terrain, the effects seem more likely and hydrologically important where warm rains and seasonal snowpacks are liable to coincide, in middle elevations. Several questions arise: (1) In the PNW, does ROS affect the long-term frequency and magnitude of water delivery to the ground, versus total precipitation (liquid and solid), during big storms? Where and how much? (2) If so, can we determine which elevations experience maximum hydrologic effects, the peak ROS zone? Probabilistic characteristics of ROS are difficult to establish because of geographic variability and sporadic occurrence: scattered stations and short observational records make quantitative frequency analysis difficult. These problems dictate a modeling approach, combining semi-random selection of storm properties with physical rules governing snow and water behavior during events. I created a simple computer program to perform Monte Carlo simulation of large storms over 1000 "years", generating realizations of snowpack and storm-weather conditions; in each event precipitation falls, snow accumulates and/or melts, and water moves to the ground. Frequency distributions are based on data from the Washington Cascades, and the model can be applied to specific sites or generalized elevations. Many of the data sets were based on observations at Stampede Pass, where high-quality measurements of weather and snow at the Cascade crest have been made since the 1940s. These data were used to inform the model, and to test its reliability with respect to the governing data distributions. In addition, data from ROS events at Stampede, and at research sites in southwest Oregon, were used to confirm that the model's deterministic calculations of snow accumulation, snowmelt, and percolation (yielding water available for runoff) adequately simulate conditions observed in the field. The Monte Carlo model was run for elevations ranging from 200 to 1500 m, each over a hypothetical millennium. Results indicate that the presence of snow in some storms reduces the amount of water reaching the ground. This occurred more often in highlands but also at middle and lower elevations, affecting the long-term frequency-magnitude relations across the landscape. In these conditions, the rain-gauges overestimate the amount of liquid water actually reaching the ground. For many storms, however, ROS enhances water reaching the ground, most significantly at elevations between ~500-1100 m. At lower and higher elevations, the water available for runoff exceeds precipitation in ~2% of events, but this proportion rises to ~20-30% at ~800 m. Other metrics (e.g., series statistics, exponential regression coefficients, frequency-magnitude factors) also indicate that this middle-elevation band (around ~800 m) experiences ROS most often and with greatest water available for runoff. Of the west-central Washington Cascades study region, about one-third to one-half the landscape is susceptible to significant ROS influence. These results indicate areas where ROS currently has the greatest hydrologic consequence on ecosystems and human works, and possibly the greatest sensitivity to changes in land-use and climate.


Supplemental files precipitation and climate observation data require Microsoft Excel and Microsoft Word software for viewing.

Persistent Identifier