Snow water equivalent (SWE) and its heterogeneity are two essential variables in the hydrologic cycle of a mountain environment. The first chapter explores two different modeling approaches to quantify a basin's snow pack: (1) forward modeling with the snow energy balance model Isnobal, and (2) reconstruction based on potential melt from Isnobal combined with fractional snow covered area from MODIS imagery, carried on the Terra and Aqua satellites. Basin-wide SWE and its heterogeneity were modelled for four water years in the Marble Fork of the Kaweah River, a 152 km2 basin in the Sierra Nevada. Two components of the heterogeneity of SWE were examined: that owing to accumulation and that resulting from snowmelt. Heterogeneity caused by accumulation is represented by reconstructed SWE before the onset of melt. It is highest above the timberline, where wind causes redistribution and sublimation.

Reconstruction accounts for the heterogeneity of wind-redistributed snow at the beginning of the melt season, even though it does not model the actual distribution processes. Thus it provides an independent method of measuring the spatial distribution of snow, which is useful to validate models of snow accumulation, either owing to redistribution or to precipitation itself. Heterogeneity caused by melt emerges from the calculations in Isnobal. Throughout spring it stays low above the timberline, while an increase occurs at the lowest snow-covered elevations as well as at the transition between forested and open areas. The spatial distribution of these trends persists in all four years of the study, but in the wettest year, 2006, the delayed onset of melt muted the heterogeneity. Forest cover is the dominating factor, with intermediate canopy cover causing the highest heterogeneity in melt.

As input to the reconstruction model, fractional snow covered area from MODIS (fSCA) is corrected for missing data, periodic fluctuations caused by the satellite orbit, clouds, and vegetation cover. These uncertainties propagate into the reconstruction, and their effects on modeled SWE are treated in chapter 2. Two potential uncertainties are analyzed: a bias in fSCA that scales with vegetation cover and an offset in final melt-out date. While a positive bias in fSCA has little effect, a negative bias alters reconstructed SWE. Prolonging the melt season increases SWE more than shortening decreases it (4%-12% increase per day versus 3%-6% decrease per day). Chapter 3 presents an analysis of the spatial distribution of precipitation in the densely monitored Reynolds Creek Experimental watershed in Southwest Idaho.

Elevation-detrended kriging yields interpolation surfaces similar to the PRISM precipitation model but is able to capture local anomalies such as rain shadow and topographic exposure. A comparison between summed hourly and daily precipitation surfaces illustrates the importance of interpolating precipitation at high temporal resolution in regions spanning the rain-snow transition. Otherwise, errors in the partitioning between rain and snow contaminate the daily interpolation results, when the elevation of phase transition varied frequently.