Canopy structure and topography effects on snow distribution at a catchment scale: Application of multivariate approaches

Jeníček, Michal; Pevná, Hana; Matějka, Ondřej

doi:10.1515/johh-2017-0027

Cited by 20 publications

(25 citation statements)

References 43 publications

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“…The melt factors presented in Jenicek et al (2016) are somewhat higher than in this study, especially for open areas. This might be influenced by previously mentioned fact that open area in this study is rather small and the snowpack distribution might by affected by surrounding trees.…”

Section: Vegetation Structure and Its Possible Consequences To Runoffcontrasting

confidence: 77%

“…Holko et al 2009;Jenicek et al 2015;Jost et al 2012;Pomeroy et al 2012;Šípek and Tesař 2014). The results presented by Jenicek et al (2016) who performed similar survey of snow storages at a catchment scale (same catchment as in this study) demonstrated similar differences in snow storages accumulated in open areas compared to forest sites (on average by 45% lower snow storages under healthy coniferous forest and 29% by lower snow storage in disturbed forest). On the contrary, Bartík et al (2014) reported larger decrease of SWE deposited in a disturbed forest compared to open area in the West Tatra Mountains (decrease by 53%).…”

Section: Vegetation Structure and Its Possible Consequences To Runoffsupporting

confidence: 76%

“…Many studies showed that snow accumulated in forests is by 40-50% lower than that in nearby open areas (see e.g. Bartík et al 2014;Jenicek et al 2016Jenicek et al , 2015Jost et al 2007;Stähli and Gustafsson 2006). The study performed in experimental forested mountain plots in central Europe showed that up to 60% of cumulative snowfall was intercepted and sublimated (Holko et al 2009).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Chernozem. From concept to classification: a review

Vysloužilová¹,

Ertlen²,

Schwartz³

et al. 2016

Auc Geographica

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The knowledge of water volume stored in the snowpack and its spatial distribution is important to predict the snowmelt runoff. The objective of this study was to quantify the role of different forest types on the snowpack distribution at a plot scale during snow accumulation and snow ablation periods. Special interest was put in the role of the forest affected by the bark beetle (Ips typographus). We performed repeated detailed manual field survey at selected mountain plots with different canopy structure located at the same elevation and without influence of topography and wind on the snow distribution. A snow accumulation and ablation model was set up to simulate the snow water equivalent (SWE) in plots with different vegetation cover. The model was based on degree-day approach and accounts for snow interception in different forest types.The measured SWE in the plot with healthy forest was on average by 41% lower than in open area during snow accumulation period. The disturbed forest caused the SWE reduction by 22% compared to open area indicating increasing snow storage after forest defoliation. The snow ablation in healthy forest was by 32% slower compared to open area. On the contrary, the snow ablation in disturbed forest (due to the bark beetle) was on average only by 7% slower than in open area. The relative decrease in incoming solar radiation in the forest compared to open area was much bigger compared to the relative decrease in snowmelt rates. This indicated that the decrease in snowmelt rates cannot be explained only by the decrease in incoming solar radiation. The model simulated best in open area and slightly worse in healthy forest. The model showed faster snowmelt after forest defoliation which also resulted in earlier snow melt-out in the disturbed forest.

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Section: Vegetation Structure and Its Possible Consequences To Runoffcontrasting

confidence: 77%

Section: Vegetation Structure and Its Possible Consequences To Runoffsupporting

confidence: 76%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Chernozem. From concept to classification: a review

Vysloužilová¹,

Ertlen²,

Schwartz³

et al. 2016

Auc Geographica

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“…The variable climate of the mountainous headwaters induces high inter‐ and intra‐annual variability in snowpack characteristics (i.e., distribution, depth, density and snow–water equivalent [SWE]; Fayad et al, ). The characteristics of the snowpack also depend on interactions between topography and forest cover (Huerta, Molotch, & McPhee, ; Jenicek, Pevna, & Matejka, ; Jost, Weiler, Gluns, & Alila, ). Forest cover reduces snow accumulation on the ground because the tree canopies intercept some of the snowfall (Storck, Lettenmaier, & Bolton, ).…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies have documented the different ways that snowpacks and forests interact at different altitudinal ranges in mid‐latitude mountain ranges (Huerta et al, ; Jenicek et al, ; Lundquist, Dickerson‐Lange, Lutz, & Cristea, ). However, there is uncertainty on the magnitude of these interactions among nearby areas and during different years, and this can affect the representativeness of a study site and study period that is used for research.…”

Section: Introductionmentioning

confidence: 99%

Variable effects of forest canopies on snow processes in a valley of the central Spanish Pyrenees

Sanmiguel‐Vallelado

López‐Moreno

Morán-Tejéda

et al. 2020

Hydrological Processes

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Snowpacks and forests have complex interactions throughout the large range of altitudes where they co-occur. However, there are no reliable data on the spatial and temporal interactions of forests with snowpacks, such as those that occur in nearby areas that have different environmental conditions and those that occur during different snow seasons. This study monitored the interactions of forests with snowpacks in four forest stands in a single valley of the central Spanish Pyrenees during three consecutive snow seasons (2015/2016, 2016/2017 and 2017/2018). Daily snow depth data from time-lapse cameras were compared with snow data from field surveys that were performed every 10-15 days. These data thus provided information on the spatial and temporal changes of snow-water equivalent (SWE). The results indicated that forest had the same general effects on snowpack in each forest stand and during each snow season. On average, forest cover reduced the duration of snowpack by 17 days, reduced the cumulative SWE of the snowpack by about 60% and increased the spatial heterogeneity of snowpack by 190%. Overall, forest cover reduced SWE total accumulation by 40% and the rate of SWE accumulation by 25%. The forest-mediated reduction of the accumulation rate, in combination with the occasional forest-mediated enhancement of melting rate, explained the reduced duration of snowpacks beneath forest canopies. However, the magnitude and timing of certain forest effects on snowpack had significant spatial and temporal variations. This variability must be considered when selecting the location of an experimental site in a mountainous area, because the study site should be representative of surrounding areas. The same considerations apply when selecting a time period for study. K E Y W O R D Smountain forest, snowpack, spatial and temporal variability, SWE

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Isotopic response of run‐off to forest disturbance in small mountain catchments

Vystavna

Holko

Hejzlar

et al. 2018

Hydrological Processes

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Stable water isotopes were applied to trace hydrological processes in an undisturbed (mature spruce forest) and a nearby disturbed (deforested from a bark beetle outbreak) lake catchments in the Czech Republic. Both catchments are situated above 1,000 m a.s.l. within the Šumava National Park and have similar environmental conditions. The isotopic compositions of precipitation, creeks, springs, and lakes were sampled at 3-week intervals over one hydrological year. Water inputs to catchments were derived from isotopically similar local precipitation, whereas run-off was found to have different isotopic signatures. Creeks in the undisturbed catchment had 1‰ and~7‰ higher δ 18 O and δ 2 H with~2‰ lower d-excess than in the disturbed catchment. The d-excess in creeks of the undisturbed catchment was more pronounced, particularly during snowmelt, and highly heterogeneous as compared with the disturbed catchment. Creeks in the undisturbed catchment were mainly fed by precipitation during the warm period (May-October), whereas creeks in the disturbed catchment were mostly fed by precipitation during the cold period (November-April).Estimated mean transit times of creeks and springs were~6 months, except for two creeks in the undisturbed catchment, which had residence times of~1 year. Although evaporation and transpiration fluxes were apparently reduced in the disturbed catchment, transpiration ratios were similar for both catchments. The difference in isotope signatures between catchments was attributed to the altered role of the forest canopy in temporal water distribution, which produced changes in the water cycle, potentially influencing important biogeochemical processes.

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Canopy structure and topography effects on snow distribution at a catchment scale: Application of multivariate approaches

Cited by 20 publications

References 43 publications

Chernozem. From concept to classification: a review

Chernozem. From concept to classification: a review

Variable effects of forest canopies on snow processes in a valley of the central Spanish Pyrenees

Isotopic response of run‐off to forest disturbance in small mountain catchments

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