Forest cover and topography regulate the thin, ephemeral snowpacks of the semiarid Southwest United States

Abstract

In the Southwest United States, water resources depend heavily on snowpacks, which are temporally and spatially limited in this warm, semiarid region. Snow accumulation and ablation in the Southwest are heavily influenced by forest structure.Therefore, water resource managers urgently need to understand the future impacts of unprecedented forest changes now occurring from drought, insect infestation, and forest management. Here, we present state-of-the-art maps and time series of snow water equivalent (SWE), which account for spatial variability of snow depth and snow density over a large range of forest structure and topographies in the highlands of central Arizona. We show that the degree of forest cover and its geometry largely determine which areas have more/less snow accumulation and faster/slower ablation. Compared with under-canopy areas, open areas can have 20-30% more accumulation and ablation rates can vary by 15-30% in sunny areas versus shaded areas.Although SWE response to forest cover is widely variable, depending on how much shading the trees provide versus how much snow is intercepted and lost through canopy sublimation, dense forests generally have less SWE than sparser forests. In general, SWE is optimized at intermediate levels of forest cover (~30-50%) on flat and north-facing slopes. Somewhat counterintuitively, increasing forest cover generally causes a reduction of SWE on south-facing slopes, where trees are less effective at reducing radiative forcing at the snow surface due to less efficient shading and increased enhancement of longwave radiation from the warm canopy.

Streamflow Response to Wildfire Differs With Season and Elevation in Adjacent Headwaters of the Lower Colorado River Basin

“…While adding high‐severity fire to regression models did not improve streamflow prediction (Section 4.4), the post‐fire decline in winter streamflow is consistent with the idea that widespread, severe fire reduced canopy cover well below 30% in many places (Table 2), increasing net snow sublimation and reducing snowmelt volumes at all elevations. Because increased snow sublimation is expected with canopy reduction in the high‐elevation White Mountains (Broxton et al., 2020), the lack of winter streamflow reduction in the White Mountains headwaters suggests a counteracting biophysical response that differs with elevation (H1).…”

“…Therefore, peak snowpack may be optimized at intermediate forest density (Veatch et al, 2009). In the Salt River Basin, Broxton et al (2020) previously showed peak SWE is optimized at 30%-50% forest cover. While adding high-severity fire to regression models did not improve streamflow prediction (Section 4.4), the post-fire decline in winter streamflow is consistent with the idea that widespread, severe fire reduced canopy cover well below 30% in many places (Table 2), increasing net snow sublimation and reducing snowmelt volumes at all elevations.…”

Structure from Motion of Multi-Angle RPAS Imagery Complements Larger-Scale Airborne Lidar Data for Cost-Effective Snow Monitoring in Mountain Forests

“…One thing that is likely to lead to greater difficulties when using the pre-existing lidar observations of snow distributions is land cover change (such as forest thinning, wildfire, or normal forest growth) because these changes are known to alter the snow depth patterns [4,6,9,78]. We showed in Figure 6 that the observed and predicted snow depth distributions were different following forest thinning treatments at the forest thinning comparison site.…”

“…These surveys should capture snow variability related to the important physiographic characteristics and snow processes for a given field site. For our area, snow depth variability was primarily influenced by the tradeoff between shading (from both terrain and vegetation and terrain influences) and interception [6]. Therefore, it was ideal to have transects spanning gradients of vegetation cover and tree shading (e.g., across forest gaps and into forest edges) and on opposing aspects.…”

“…Snowpack in mountain forests is a major source of water for reservoirs that provide water and hydropower for many urban and agricultural communities [1][2][3]. Mountain snowpacks are affected by many climatic, topographic and ecological variables, and are sensitive to forest disturbance such as thinning, prescribed fires, wildfire, and tree die-off [4][5][6][7][8][9][10][11][12][13]. It is important to monitor how snowpacks in these areas respond to changing environmental conditions in order to understand and forecast available water resources for both natural and human consumption.…”