[1] Many regions of the world are dependent on snow cover for frost protection and summer water supplies. These same regions are predominantly forested, with forests highly vulnerable to change. Here we combine a meta-analysis of observational studies across the globe with modeling to show that in regions with average December-January-February (DJF) temperatures greater than À1 C, forest cover reduces snow duration by 1-2 weeks compared to adjacent open areas. This occurs because the dominant effect of forest cover shifts from slowing snowmelt by shading the snow and blocking the wind to accelerating snowmelt from increasing longwave radiation. In many locations, midwinter melt removes forest snow before solar radiation is great enough for forest shading to matter, and with warming temperatures, midwinter melt is likely to become more widespread. This temperature-effect in forest-snow-climate interactions must be considered in representations of the combined ecohydrological system and can be used advantageously in forest management strategies.

Many plot‐scale studies have shown that snow‐cover dynamics in forest gaps are distinctly different from those in open and continuously forested areas, and forest gaps have the potential to alter the magnitude and timing of snowmelt. However, the watershed‐level impacts of canopy gap treatment on streamflows are largely unknown. Here, we present the first research that explicitly assesses the impact of canopy gaps on seasonal streamflows and particularly late‐season low flows at the watershed scale. To explicitly model forest–snow interactions in canopy gaps, we made major enhancements to a widely used distributed hydrologic model, distributed hydrology soil vegetation model, with a canopy gap component that represents physical processes of snowpack evolution in the forest gap separately from the surrounding forest on the subgrid scale (within a grid typically 10–150 m). The model predicted snow water equivalent using the enhanced distributed hydrology soil vegetation model showed good agreement (R2 > 0.9) with subhourly snow water equivalent measurements collected from open, forested, and canopy gap sites in Idaho, USA. Compared with the original model that does not account for interactions between gaps and surrounding forest, the enhanced model predicted notably later melt in small‐ to medium‐size canopy gaps (the ratio of gap radius (r) to canopy height (h) ≤ 1.2), and snow melt rates exhibited great sensitivity to changing gap size in medium‐size gaps (0.5 ≤ r/h ≤ 1.2). We demonstrated the watershed‐scale implications of canopy gaps on streamflow in the snow‐dominated Chiwawa watershed, WA, USA. With 24% of the watershed drainage area (about 446 km2) converted to gaps of 60 m diameter, the mean annual 7‐day low flow was increased by 19.4% (i.e., 0.37 m3/s), and the mean monthly 7‐day low flows were increased by 13.5% (i.e., 0.26 m3/s) to 40% (i.e., 1.76 m3/s) from late summer through fall. Lastly, in practical implementation of canopy gaps with the same total gap areas, a greater number of distributed small gaps can have greater potential for longer snow retention than a smaller number of large gaps.

Regions of complex topography and remote wilderness terrain have spatially varying patterns of temperature and streamflow, but due to inherent difficulties of access, are often very poorly sampled. Here we present a data set of distributed stream stage, streamflow, stream temperature, barometric pressure, and air temperature from the Tuolumne River Watershed in Yosemite National Park, Sierra Nevada, California, USA, for water years 2002–2015, as well as a quality‐controlled hourly meteorological forcing time series for use in hydrologic modeling. We also provide snow data and daily inflow to the Hetch Hetchy Reservoir for 1970–2015. This paper describes data collected using low‐visibility and low‐impact installations for wilderness locations and can be used alone or as a critical supplement to ancillary data sets collected by cooperating agencies, referenced herein. This data set provides a unique opportunity to understand spatial patterns and scaling of hydroclimatic processes in complex terrain and can be used to evaluate downscaling techniques or distributed modeling. The paper also provides an example methodology and lessons learned in conducting hydroclimatic monitoring in remote wilderness.

Abstract:We investigated, through hydrologic modelling, the impact of the extent and density of canopy cover on streamflow timing and on the magnitude of peak and late summer flows in the upper Tuolumne basin (2600-4000 m) of the Sierra Nevada, California, under current and warmer temperatures. We used the Distributed Hydrology Soil Vegetation Model for the hydrologic modelling of the basin, assuming four vegetation scenarios: current forest (partial cover, 80% density), all forest (uniform coverage, 80% density), all barren (no forest) and thinned forest (partial cover, 40% density) for a medium-high emissions scenario causing a 3.9 C warming over a 100-year period (2001-2100). Significant advances in streamflow timing, quantified as the centre of mass (COM) of over 1 month were projected for all vegetation scenarios. However, the COM advances faster with increased forest coverage. For example, when forest covered the entire area, the COM occurred on average 12 days earlier compared with the current forest coverage, with the rate of advance higher by about 0.06 days year À1 over 100 years and with peak and late summer flows lower by about 20% and 27%, respectively. Examination of modelled changes in energy balance components at forested and barren sites as temperatures rise indicated that increases in net longwave radiation are higher in the forest case and have a higher contribution to melting earlier in the calendar year when shortwave radiation is a smaller fraction of the energy budget. These increases contributed to increased midwinter melt under the forest at temperatures above freezing, causing decreases in total accumulation and higher winter and early spring melt rates. These results highlight the importance of carefully considering the combined impacts of changing forest cover and climate on downstream water supply and mountain ecosystems.

[1] Atmospheric moisture content is critical in hydrological modeling yet is sparsely measured in mountainous environments. We compared densely distributed measurements of dew point temperature in two study sites in the Sierra Nevada, California, against (1) simple empirical algorithms, (2) the Parameter-elevation Regressions on Independent Slopes Model (PRISM), (3) radiosonde data, and (4) the Weather Research and Forecasting (WRF) mesoscale model. Empirical algorithms that used only one sea-level measurement of dew point to extrapolate to higher elevations often did not match local dew point lapse rates and could be biased as high as 9.9 C. PRISM improved upon these methods by using local observations to determine the local average dew point lapse rate, with median bias values of À0.3 C and 3.3 C in our two study sites. Empirical algorithms that derived dew point from air temperature showed a seasonal variation in performance; summer median bias values were 0.6 C-8.2 C wetter than winter bias values. Radiosonde readings showed median biases of À6.5 C and À8.0 C from observations in our study sites. WRF improved on the radiosonde data, performing well in representing both the overall trends in the basin (with median biases of À0.9 C and À1.0 C in our study sites). One base station within the basin paired with PRISM lapse rates showed small biases from overall moisture trends. However, a physically resolved model such as WRF was better equipped to represent daily dew point variations and in basins with nonlinear trends.