Accounting for Fine‐Scale Forest Structure is Necessary to Model Snowpack Mass and Energy Budgets in Montane Forests

Broxton, P. D.; Harpold, Adrian A.

doi:10.1029/2021wr029716

Cited by 14 publications

(11 citation statements)

References 87 publications

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“…More importantly, at the forest stand level (40 m wide) of our study, θ showed a good correlation relationship with all the snow sub-processes (interception, sublimation, and snowmelt). Similar to previous studies on the relationship between canopy closure (or LAI) and snow processes as determined using different scales and methods by Krogh et al (2020), Broxton et al (2021), andRussell et al (2021), we also found that θ was an ideal canopy index factor to explain the variations in SD, Ic, S s , S r , and SWE in the mixed forests of the Changbai Mountains.…”

Section: Influence Mechanism Of Forest Canopy Closure On the Snow Pro...supporting

confidence: 89%

“…A selection of appropriate forest structure indicators to quantify the impact is particularly critical, but the diversity of indicators and methods has instead limited research expansion. A variety of forest structure indicators have been used to reveal the impact of forests on snow processes, such as forest cover (Varhola et al, 2010;Pomeroy et al, 2012;Varhola and Coops, 2013), canopy cover (Pomeroy et al, 2002), leaf area index (Gelfan et al, 2004;Woods et al, 2006;Rutter et al, 2009;Lendzioch et al, 2019), and canopy closure (Broxton et al, 2021). In the meantime, as technology continues to progress, various methods have been applied comprehensively, such as forest snow sampling survey (Watson et al, 2006;Parajuli et al, 2020), snow model simulation (Pomeroy et al, 2007;Rutter et al, 2009;Krinner et al, 2018;Napoly et al, 2020), statistical modeling (López-Moreno andNogués-Bravo, 2006), snow remote sensing (Zhang et al, 2010;Frei et al, 2012;Hojatimalekshah et al, 2021), LiDAR technology (Harpold et al, 2014;Broxton et al, 2021;Russell et al, 2021), UAV remote sensing (Lendzioch et al, 2019), and delayed photography (Parajka et al, 2012;Dong and Menzel, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…Snow surveys need to take into account a variety of heterogeneous landscapes and survey frequency and strategy (Watson et al, 2006), and these factors can result in higher implementation costs. Snow model method has the problems of a coarse resolution and the simplification of the interaction processes between forest and snow (Broxton et al, 2021), restricting the ability of existing models to quantify effects of the forest canopy structure changes on snow processes. For example, Rutter et al (2009) and Krinner et al (2018) only focused on the accurate simulation of snow processes in specific forests and in adjacent open areas when conducting SnowMIP2 and ESM-SnowMIP studies.…”

Section: Introductionmentioning

confidence: 99%

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Impact of Forest Canopy Closure on Snow Processes in the Changbai Mountains, Northeast China

Gao

Shen

Cai

et al. 2022

Front. Environ. Sci.

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Forest canopy closure affects snow processes by changing the redistribution of snowfall, snow interception, accumulation, sublimation, and melt. However, how the forest closure impacts snow processes at different periods has not been well explored. We conducted 3-year measurements of snow density and depth and carried out snow process calculations (i.e., interception, sublimation, and snowmelt) from 2018 to 2021 in four mixed forests with different canopy closures and an open site in the Changbai Mountains, northeast China. We found that the snow density of the five study sites varied greatly (0.14–0.45 g/cm3). The snow depth (SD) at four mixed forests sites was smaller than that of the nearby open site. The SD decreased as the forest canopy closure increased. Additionally, the forest interception effect increased with the canopy closure and decreased as the snowfall intensity increased. The total interception efficiency of the four mixed forests in normal snow years changed from 34% to 73% and increased with forest canopy closure. The averaged sublimation rate (Ss) and snowmelt rate (Sr) of the four mixed forests varied during different periods of snow process. The Ss was 0.1–0.4 mm/day during the accumulation period and 0.2–1.0 mm/day during the ablation period, and the Sr was 1.5–10.5 mm/day during the ablation period. There was a good correlation between Ss, or Sr, and canopy closure, but interannual variation was observed in the correlation. The mean values of the effect of the four mixed forests on understory SWE (snow water equivalent) over the 3 years ranged from −45% to −65%. Moreover, the impact effect was correlated with the forest canopy closure and enhanced with the canopy closure. This study provided more scientific information for studies of snow cover response to forest management.

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Section: Influence Mechanism Of Forest Canopy Closure On the Snow Pro...supporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Impact of Forest Canopy Closure on Snow Processes in the Changbai Mountains, Northeast China

Gao

Shen

Cai

et al. 2022

Front. Environ. Sci.

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“…Both hydrologic models and ESMs lack certain snowalbedo feedbacks such as black carbon and litter deposition on snow and the gradient of canopy alterations following fire [71,78,89]. The multiyear post-fire changes in soil and vegetation properties have a key influence on water and energy budgets that vary with burn severity [84,85,90,91] and may lead to underestimation of actual melt rates [92] and post-fire water yield [79]. Additional uncertainties in ESMs pertain to mountain precipitation phase partitioning and energy budgets potentially resulting in biased snow accumulation, persistence, and melt [7,8,93]).…”

Section: Discussionmentioning

confidence: 99%

Decline in Seasonal Snow During a Projected 20-Year Dry Spell

Hatchett¹,

Rhoades²,

McEvoy³

2022

Preprint

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Snowpack loss in midlatitude mountains is ubiquitously projected by Earth system models, though the magnitudes, persistence and time horizons of decline vary. Using daily downscaled hydroclimate and snow projections we examine changes in snow seasonality across the U.S. Pacific Southwest region during a simulated severe 20-year dry spell in the 21st century (2051–2070) developed as part of the 4th California Climate Change Assessment to provide a "stress test" for water resources. Across California’s mountains, substantial declines (30–100% loss) in median peak annual snow water equivalent accompany changes in snow seasonality throughout the region compared to the historic period. We find 80% of historic seasonal snowpacks transition to ephemeral conditions. Subsetting empirical-statistical wildfire projections for California by snow seasonality transition regions indicates a two-to-four-fold increase in burned area, consistent with recent observations of high elevation wildfires following extended drought conditions. By analyzing six of the major California snow-fed river systems we demonstrate snowpack reductions and seasonality transitions result in concomitant declines in annual runoff (47-58% of historic values). The negative impacts to statewide water supply reliability by the projected dry spell will likely be magnified by changes in snowpack seasonality and increased wildfire activity.

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“…Due to the spatial variability of snow distribution, knowledge of the watershed scale snow distribution is critical to predicting streamflow for environmental and societal water use. Understanding the processes controlling snow accumulation and snowmelt rate and timing at fine scales is important for improving model predictions of snow water resources (Broxton et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Forest impacts on snow accumulation and melt in a semi-arid mountain environment

et al. 2022

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Snowmelt is complex under heterogeneous forest cover due to spatially variable snow surface energy and mass balances and snow accumulation. Forest canopies influence the under-canopy snowpack net total radiation energy balance by enhancing longwave radiation, shading the surface from shortwave radiation, in addition to intercepting snow, and protecting the snow surface from the wind. Despite the importance of predicting snowmelt timing for water resources, there are limited observations of snowmelt timing in heterogeneous forest cover across the Intermountain West. This research seeks to evaluate the processes that control snowmelt timing and magnitude at two paired forested and open sites in semi-arid southern Idaho, USA. Snow accumulation, snowmelt, and snow energy balance components were measured at a marginal snowpack and seasonal snowpack location in the forest, sparse vegetation, forest edge, and open environments. At both locations, the snow disappeared either later in the forest or relatively uniformly in the open and forest. At the upper elevation location, a later peak in maximum snow depth resulted in more variable snow disappearance timing between the open and forest sites with later snow disappearance in the forest. Snow disappearance timing at the marginal snowpack location was controlled by the magnitude and duration of a late season storm increasing snow depth variability and reducing the shortwave radiation energy input. Here, a shorter duration spring storm resulted in more uniform snowmelt in the forest and open. At both locations, the low-density forests shaded the snow surface into the melt period slowing the melt rate in the forest. However, the forest site had less cold content to overcome before melting started, partially canceling out the forest shading effect. Our results highlight the regional similarities and differences of snow surface energy balance controls on the timing and duration of snowmelt.

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Accounting for Fine‐Scale Forest Structure is Necessary to Model Snowpack Mass and Energy Budgets in Montane Forests

Cited by 14 publications

References 87 publications

Impact of Forest Canopy Closure on Snow Processes in the Changbai Mountains, Northeast China

Impact of Forest Canopy Closure on Snow Processes in the Changbai Mountains, Northeast China

Decline in Seasonal Snow During a Projected 20-Year Dry Spell

Forest impacts on snow accumulation and melt in a semi-arid mountain environment

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