Comparison and validation of three versions of a forest wind risk model
GARDINER, Barry
Interactions Sol Plante Atmosphère [UMR ISPA]
Forest Research, Northern Research Station
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Interactions Sol Plante Atmosphère [UMR ISPA]
Forest Research, Northern Research Station
GARDINER, Barry
Interactions Sol Plante Atmosphère [UMR ISPA]
Forest Research, Northern Research Station
Interactions Sol Plante Atmosphère [UMR ISPA]
Forest Research, Northern Research Station
TAYLOR, Philip
Forest Research, Northern Research Station
Natural Environment Research Council [NERC]
Forest Research, Northern Research Station
Natural Environment Research Council [NERC]
PIZZIRANI, Stefania
Forest Research, Northern Research Station
New Zealand Forest Research Institute
< Reduce
Forest Research, Northern Research Station
New Zealand Forest Research Institute
Language
en
Article de revue
This item was published in
Environmental Modelling and Software. 2015, vol. 68, p. 27-41
Elsevier
English Abstract
Predicting the probability of wind damage in both natural and managed forests is important for understanding forest ecosystem functioning, the environmental impact of storms and for forest risk management. We undertook a ...Read more >
Predicting the probability of wind damage in both natural and managed forests is important for understanding forest ecosystem functioning, the environmental impact of storms and for forest risk management. We undertook a thorough validation of three versions of the hybrid-mechanistic wind risk model, ForestGALES, and a statistical logistic regression model, against observed damage in a Scottish upland conifer forest following a major storm. Statistical analysis demonstrated that increasing tree height and local wind speed during the storm were the main factors associated with increased damage levels. All models provided acceptable discrimination between damaged and undamaged forest stands but there were trade-offs between the accuracy of the mechanistic models and model bias. The two versions of the mechanistic model with the lowest bias gave very comparable overall results at the forest scale and could form part of a decision support system for managing forest wind damage risk.Read less <
English Keywords
risk modelling
decision support system
wind damage
forest disturbance
mechanistic modelling
validation
Origin
Hal imported