Elsevier

Journal of Hydrology

Volume 392, Issues 3–4, 15 October 2010, Pages 219-233
Journal of Hydrology

Review Paper
Forest canopy effects on snow accumulation and ablation: An integrative review of empirical results

https://doi.org/10.1016/j.jhydrol.2010.08.009Get rights and content

Summary

The past century has seen significant research comparing snow accumulation and ablation in forested and open sites. In this review we compile and standardize the results of previous empirical studies to generate statistical relations between changes in forest cover and the associated changes in snow accumulation and ablation rate. The analysis drew upon 33 articles documenting these relationships at 65 individual sites in North America and Europe from the 1930s to present. Changes in forest cover explained 57% and 72% of the variance of relative changes in snow accumulation and ablation, respectively. The incorporation of geographic and average historic climatic information did not significantly improve the ability to predict changes in snow processes, mainly because most of the studies did not provide enough information on site characteristics such as slope and aspect or meteorological conditions taking place during the experiments. Two simple linear models using forest cover as the sole predictor of changes in snow accumulation and ablation are provided, as well as a review of the main sources of variation that prevent the elaboration of more accurate multiple regression models. Further studies should provide detailed information regarding the main sources of variation influencing snow processes including the effect of year-to-year changes in weather variables during the monitoring period.

Introduction

The effects of forest cover on snow accumulation and ablation have been subject of substantial research over the last century. Snow accumulation is most often represented by the peak snow water equivalent (SWE) (mm) on the ground before the snow starts to melt, while snow ablation rate (mm/day) is usually computed as the peak SWE divided by the number of days of the ablation period (from date of peak SWE to date of snow disappearance).1 Generally, as forest cover increases, snow accumulation on the ground is reduced because part of the snowfall intercepted in the canopies is returned to the atmosphere by sublimation (Essery et al., 2003). Although the magnitude of these combined phenomena varies according to specific conditions, it has been found that up to 60% and 40% of cumulative snowfall can be intercepted and sublimated, respectively (Hedstrom and Pomeroy, 1998, Pomeroy et al., 1998). Many studies have shown that snow accumulated in forested areas is up to 40% lower than that in nearby open reference sites (e.g. D’Eon, 2004, Winkler et al., 2005, Jost et al., 2007).

The primary driver of snow ablation is the net available energy, which can be calculated with an energy balance model that includes incoming and reflected shortwave radiation, incoming and outgoing longwave radiation, sensible and latent heat fluxes and ground heat conduction as independent variables (Brooks et al., 2003, Boon, 2007). Forest cover is critical in this equation because even though it might increase longwave radiation, reductions in the incoming shortwave radiation from the sun generally lead to net losses in the total energy budget available for melting (Essery et al., 2008). Canopies also reduce wind speed and thus the magnitudes of the sensible and latent heat fluxes. A number of empirical studies have shown that snowmelt rates in forests can be up to 70% lower than in open areas (e.g. Hendrick et al., 1971, Boon, 2007, Teti, 2008).

Snow accumulation and melt play an important role in the hydrology of montane snow-dominated regions, where water supply is highly dependent on spring melting from forested areas (Uunila et al., 2006). The sensitive connection between forest structure and snow processes has, therefore, many significant implications (Musselman et al., 2008). Although the interest in this subject is not new (e.g. Connaughton, 1933a, Meagher, 1938), climate variability has recently increased concerns about the potential magnitude of the impacts. For example, evidence is showing that over the past decades decreasing snowpacks are melting at faster rates and earlier in the spring in western North America (e.g. Mote et al., 2005, Knowles et al., 2006) and other regions (e.g. Koening and Abegg, 1997, Bavay et al., 2009), where up to 75% of the total water input comes from snow (Service, 2004). As a result, spring peak discharges are becoming larger while the summer/autumn flows are experiencing severe declines (Rood et al., 2008). These changes have generated concern about the current capacity of existing dams to handle higher peak flows, the need for more reservoirs to regulate water release for summer irrigation and the loss of farmlands and wildlife habitat (D’Eon, 2001, Service, 2004).

Additional evidence also suggests that the changes in forest structure associated with alterations in wildfire, disease and insect infestation regimes could exacerbate the anomalies in the patterns of snow accumulation and melting (Musselman et al., 2008). Disturbed canopies over extensive areas might counteract the apparent snowpack decline observed in the past decades and result in larger snowpacks melting faster, with the potential to increase the magnitude–frequency of flooding events in rural as well as populated areas (Schnorbus, 2007). For example, the current mountain pine beetle (MPB) outbreak in British Columbia (BC) has infested 135,000 km2 of lodgepole pine forests as of 2008 (BC Ministry of Forests, 2008), with uncertain impacts on water resources (Winkler, 2001, Uunila et al., 2006, Bewley et al., 2010). On the other hand, forest fire suppression policies could lead to changes in canopy cover and water resources in western North America (Matheussen et al., 2000) by creating large areas of overstocked stands with higher snow interception rates (Sampson, 1997).

The need to quantify the relationship between forest structure and snow accumulation and melting has motivated the development of several modelling approaches. Methods have ranged from local-scale empirical studies comparing forested and non-forested areas (e.g. Winkler et al., 2005, Woods et al., 2006, Boon, 2009) to the application of process-based simulation models (e.g. Hendrick et al., 1971, Hedstrom and Pomeroy, 1998, Essery et al., 2008). The latter are, in principle, applicable to a wide range of conditions but require input data that are not readily available in operational contexts. Empirical models such as the ones developed by Kuz’min (1960) or Woods et al. (2006) have been derived from a wide range of studies to provide first-order estimates of the effects of forest cover changes on snow processes. However, they do not explicitly account for the governing processes, which vary in both space and time, and therefore cannot be relied upon to generate precise predictions at different sites or different years.

To develop a better understanding of, and ability to, predict the interaction between forest structure and snow accumulation and melting, it is necessary to identify the additional factors that explain the spatial and temporal distribution patterns of snow. Forest cover is not the only variable influencing snow accumulation processes, nor the most important under certain conditions (Gary, 1975, Pomeroy et al., 1997). Other sources of variation that expose the complexity of the interaction between cover and snow process include snowfall magnitude (Anderson, 1956), year to year variations (Berndt, 1965), elevation (Daugharty and Dickinson, 1982), aspect and slope (Anderson et al., 1958a, Moore and Wondzell, 2005), size of the clearcut used as a reference (Golding and Swanson, 1986), wind speed (Woods et al., 2006), specific weather conditions (Lundquist et al., 2004, Lundquist and Flint, 2006), spatial distribution of trees (Dunford and Niederhof, 1944, Veatch et al., 2009), and canopy geometry (Essery et al., 2008).

This study has two objectives. The first is to review the results of empirical studies to identify the magnitudes of the effects that different factors have on snow accumulation and ablation. The second is to use the compiled data in a meta-analysis to generate empirical models that could be used to predict the effects of forest cover change on snow processes, along with an estimate of the uncertainty associated with the prediction. Such a model could be a useful operational tool for generating first-order estimates of forest-snow interactions, particularly over large areas with sparse weather data, where the application of process-based models may involve significant uncertainty.

Section snippets

Sources of variability affecting the interaction between forest cover and snow

A variety of factors can influence the interactions between snow accumulation and melting and forest cover. In addition, errors in measuring snow accumulation, ablation and forest cover can add to the variability of observations around a statistical model. Each of these sources of variability, errors and bias is described in detail below.

Empirical data review and compilation

Empirical studies have traditionally evaluated the effects of canopy cover on snow accumulation and melting using a paired-plot approach. Open areas adjacent to the studied forest stands are the most common reference controls (e.g. Hendrick et al., 1971, Winkler and Roach, 2005), while fully stocked stands are usually the baseline for the evaluation of the effects of thinning or harvesting (e.g. Wilm and Dunford, 1948, Woods et al., 2006). Some studies include measurements of forest cover or

Conclusions

An extensive literature review was conducted to explore the relationship between forest cover and snow accumulation and melting. Generally, studies confirm that as forest cover increases, the interception of snow in the canopies reduces the amount of snow that accumulates the ground. Forest cover also provides shelter and shading to the snow and thus reduces snow ablation rates when compared to an open area. However, the interaction of forest cover and snow accumulation and melting is subject

Acknowledgements

We thank Dr. Valerie LeMay and Christopher Bater for their support in the statistical analysis, Dr. Georg Jost for his valuable comments on this review, Dr. Mark Johnson for providing relevant references, and Sally Taylor for helping to find old publications. The following authors of some of the studies cited in this review kindly provided additional information that allowed a better understanding of their data: Craig Murray, Esko Kuusisto, Rita Winkler, Dan Bewley and William Veatch. Special

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