Simulations of the influence of forest management on wind climate on a regional scale

Venäläinen, Ari; Zeng, Hong; Peltola, Heli; Talkkari, Ari; Strandman, Harri; Wang, Kaiyun; Kellomäki, Seppo

doi:10.1016/j.agrformet.2003.12.005

Cited by 32 publications

(22 citation statements)

References 13 publications

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“…By comparison, Venäläinen et al (2004) found in this same area that new clear-cuttings did increase high wind speeds at forest edges relative to the current forest structure (Case I), this being most obvious in Case II. This was because the number and size of the gaps and the length of vulnerable forest edges, and also the surface roughness (as affected by forest structure), changed following the new clear-cutting operations (Fig.…”

Section: Discussionmentioning

confidence: 92%

“…Based on a polar grid terrain representation, the orographic flow perturbations are evaluated as the sum of spectral potential flow solutions using a Fourier-Bessel expansion. Clear-cutting changes the cover of the fields and consequently reduces the roughness values, which speeds up the wind for a certain degree (Venäläinen et al, 2004). For vertical extrapolation to a new height above the surface in flat terrain with homogeneous roughness, a logarithmic wind profile is assumed, although this needs to be perturbed to account for the influence of non-neutral stratification.…”

Section: The Airflow Model Waspmentioning

confidence: 99%

“…This is because gaps, forest margins, surface roughness, and critical wind speeds all change after new clear-cutting due to the changes in gap sizes and forest structure. Since the roughness changes, local wind conditions will also be affected (Venäläinen et al, 2004). New roughness values were therefore also digitized and transferred to WAsP in order to calculate the resource grids separately for each Cases I-III.…”

Section: Topography and Surface Roughness Datamentioning

confidence: 99%

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Influence of clear-cutting on the risk of wind damage at forest edges

Zeng

Peltola

Talkkari

et al. 2004

Forest Ecology and Management

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Section: Discussionmentioning

confidence: 92%

Section: The Airflow Model Waspmentioning

confidence: 99%

Section: Topography and Surface Roughness Datamentioning

confidence: 99%

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Influence of clear-cutting on the risk of wind damage at forest edges

Zeng

Peltola

Talkkari

et al. 2004

Forest Ecology and Management

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“…its size and perimeter), as well as the presence of old stands, on the risk of wind damage at downwind stand edges of open areas (e.g. Blennow and Sallnäs 2004;Elling and Verry, 1978;Lanquaye-Opoku and Mitchell 2005;Neustein, 1965;Stacey et al, 1994;Venäläinen et al, 2004;Zeng et al, 2004;2006.…”

Section: Discussionmentioning

confidence: 99%

The effects of forest structure on the risk of wind damage at a landscape level in a boreal forest ecosystem

et al. 2010

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Keywords:critical wind speed / forest edges / mechanistic model / Monte Carlo simulation / risk of wind damage Abstract • The aim of this work was to analyze how the forest structure affects the risk of wind damage at the landscape level in a boreal forest.• This was done by employing: (i) Monte Carlo simulation technique for generating landscapes with different age class distributions, proportions of open areas (gaps), and tree species composition; and (ii) a mechanistic wind damage model, HWIND, for predicting the critical wind speeds at downwind stand edges of open areas (gaps) for risk consideration. The level of risk of wind damage observed at the landscape level was significantly affected by the presence of gaps and old stands. Even a slight increase in the proportion of gap areas or older stands had a significant impact on the total length of edges at risk. As a comparison, variation in species composition (Scots pine and/or Norway spruce) had much smaller impact on the risk of damage.• In conclusion, the effects of forest structure on the risk of wind damage should especially be considered by forest managers in day-to-day forest planning in order to reduce the risk of wind damage both at the stand and landscape level. Mots-clés :vitesse critique du vent / lisières forestières / modèle mécaniste / simulation de Monte Carlo / risque de dommages causés par le vent Résumé -Les effets de la structure de la forêt sur le risque de dommages causés par le vent au niveau du paysage dans un écosystème forestier boréal.• L'objectif de ce travail était d'analyser comment la structure forestière affecte le risque de dommages causés par le vent à l'échelle du paysage dans une forêt boréale.• C'est objectif a été atteint par l'emploi : (i) de la technique de simulation de Monte Carlo pour générer des paysages de différentes distributions de classe d'âge, de proportions des zones ouvertes (trouées), et de composition des espèces d'arbres ; et (ii) d'un modèle mécaniste de dommages causés par le vent, HWIND, pour la prédiction des vitesses de vent critiques au niveau des lisières sous le vent des zones ouvertes (trouées) en relation avec les risques. Le niveau de risque de dommages causés par le vent observé à l'échelle du paysage a été significativement affecté par la présence de trouées et de vieux peuplements. Une augmentation même légère dans la proportion de trouées ou de vieux peuplements a eu un impact significatif sur la longueur totale des lisières à risque. À titre de comparaison, la variation dans la composition des espèces (pin sylvestre et/ou épicéa) a eu beaucoup moins d'impact sur le risque de dommages.• En conclusion, les effets de la structure de la forêt sur le risque de dommages causés par le vent devraient être examinées en particulier par les gestionnaires forestiers pour une planification des opé-rations forestière au jour le jour, afin de réduire le risque de dommages causés par le vent à la fois au niveau du peuplement et au niveau du paysage.

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“…A number of studies highlighted the influence of the spatial configuration of forest stands on landscape-scale wind susceptibility. Such approaches evaluate snapshots of landscape structure (e.g., Blennow and Sallnäs, 2004;Venäläinen et al, 2004) or use growth models, sometimes in conjunction with GIS software, to project stand development (e.g., Wilson, 2004: LMS;Zeng et al, 2007: SIMA;Blennow et al, 2010: FTM) as the basis for predicting susceptibility to storm events. Zeng et al (2009: HWIND), for instance, recently corroborated the relevance of landscape configuration in their analysis based on Monte Carlo renderings of a forest landscape.…”

Section: From Events To Disturbance Regime 421 Spatio-temporal Dynmentioning

confidence: 99%