Abstract. Streamflow generation and deep groundwater recharge may be vulnerable to loss of snow, making it important to quantify how snowmelt is partitioned between soil storage, deep drainage, evapotranspiration, and runoff. Based on previous findings, we hypothesize that snowmelt produces greater streamflow and deep drainage than rainfall and that this effect is greatest in dry climates. To test this hypothesis we examine how snowmelt and rainfall partitioning vary with climate and soil properties using a physically based variably saturated subsurface flow model, HYDRUS-1D. We developed model experiments using observed climate from mountain regions and artificial climate inputs that convert all precipitation to rain, and then evaluated how climate variability affects partitioning in soils with different hydraulic properties and depths. Results indicate that event-scale runoff is higher for snowmelt than for rainfall due to higher antecedent moisture and input rates in both wet and dry climates. Annual runoff also increases with snowmelt fraction, whereas deep drainage is not correlated with snowmelt fraction. Deep drainage is less affected by changes from snowmelt to rainfall because it is controlled by deep soil moisture changes over longer timescales. Soil texture modifies daily wetting and drying patterns but has limited effect on annual water budget partitioning, whereas increases in soil depth lead to lower runoff and greater deep drainage. Overall these results indicate that runoff may be substantially reduced with seasonal snowpack decline in all climates, whereas the effects of snowpack decline on deep drainage are less consistent. These mechanisms help explain recent observations of streamflow sensitivity to changing snowpack and highlight the importance of developing strategies to plan for changes in water budgets in areas most at risk for shifts from snow to rain.

Abstract. Streamflow generation and deep groundwater recharge in high elevation and high latitude locations may be vulnerable to loss of snow, making it important to quantify how snowmelt is partitioned between soil storage, deep drainage, evapotranspiration, and runoff. Based on previous findings, we hypothesize that snowmelt produces greater streamflow and deep drainage than rainfall and that this effect is greatest in dry climates. To test this hypothesis we examine how snowmelt and rainfall partitioning vary with climate and soil properties using a physically based variably saturated subsurface flow model, HYDRUS-1D. To represent climate variability we use historical inputs from five SNOTEL sites in each of three mountain regions with humid to semiarid climates: Northern Cascades, Sierra Nevada, and Uinta. Each input scenario is run with three soil profiles of varying hydraulic conductivity, soil texture, and bulk density. We also create artificial input scenarios to test how the concentration of input in time, conversion of snow to rain input, and soil profile depth affect partitioning of input into deep drainage and runoff. Results indicate that event-scale runoff is higher for snowmelt than for rainfall due to higher antecedent moisture and input rates in both wet and dry climates. At the annual scale, surface runoff also increases with snowmelt fraction, whereas deep drainage is not correlated with snowmelt fraction. Deep drainage is less affected by changes from snowmelt to rainfall because it is controlled by deep soil moisture changes over longer time scales. However, extreme scenarios with input highly concentrated in time, such as during melt of a deep snowpack, yield greater deep drainage below the root zone than intermittent input. Soil texture modifies daily wetting and drying patterns but has limited effect on annual scale partitioning of rain and snowmelt, whereas increases in soil depth decrease runoff and increase deep drainage. Overall these results indicate that runoff may be substantially reduced with seasonal snowpack decline in all climates. These mechanisms help explain recent observations of streamflow sensitivity to changing snowpack and emphasize the need to develop strategies to mitigate impacts of reduced streamflow generation in places most at risk for shifts from snow to rain.

Supplementary material Model Calibration We developed simulations using two rounds of historical climate inputs, the first as a spin up period, and the second for calibration. Calibration consisted of adjusting the hydraulic conductivity of the bottom layer, which controlled how much water was retained in the soil profile. Rather than force-fitting, our goal was to produce simulations with similar timing of wetting and drying to observations. This approach is consistent with other studies using