Workshop on the Mathematical Modelling of the Risk of Wind Damage to Forests

Background

Wind is a major disturbance agent in forests and a key part of the dynamics of many forest ecosystems and although this has long been recognised in boreal and temperate forests there is now increasing evidence of its importance in tropical forests. In addition, the high levels of damage that can occur during storms have important economic and social impacts, particularly for managed forests. For example, in European forests wind is responsible for more than 50 % of all damage by volume and the cost of such damage can be very high (e.g. € 6 billion in France from storms Lothar and Martin in 1999, and €2.4 billion in Sweden after storm Gudrun in 2005). There is clear evidence that damage levels to forests have been increasing over the past century due to a mixture of changing climate and forest management practice, and damage levels are predicted to continue to increase. To understand the influence of wind damage on forest ecosystems or to manage forests in order to mitigate the risk of wind damage, it is necessary to have methods for predicting the levels of damage at different wind speeds and the risk of such wind speed occurrence.

Normally mathematical models are used to make assessments of wind damage risk to forests and such modelling has been active for approximately 15 years following two main approaches:

  1. 1:  Statistical models developed from observations of damage in well monitored forests with information on soil, tree size, elevation, forest management, etc.
  2. 2:  Mechanistic models that use methods from civil/mechanical engineering to directly predict the wind loading on trees and the wind speed at which they will fail.

Statistical models generally make good predictions within the locale for which they were developed but do not always translate well to other locations or conditions. Mechanistic models are usually not as accurate as statistical models for a specific area but are easier to transfer to other situations. They also the possibility of providing wind risk evaluations at all scales from individual trees to forest, regional, national and potentially global scales. However, it is becoming clear from the literature and conference discussions (e.g. IUFRO Wind and Trees Conference, August 2014, Brazil) that current mechanistic models have reached a limit in their capability (spatially and temporarily) and a re-evaluation of the approach is required to make progress. Therefore it was recommended by Prof. Steve Mitchell, chairman of the IUFRO working group 8.03.06, that a workshop focussed on mechanistic wind risk modelling would be of value in starting the discussion on the best ways to develop such models in the future.

Goals

The planned outputs of the workshop are:

  1. A report providing recommendations for the future of forest wind damage modelling, with a list of available tools/model and data, together with a discussion of the most appropriate methodologies for different temporal and spatial scales. The report will also contain an assessment of barriers to the development of new mechanistic modelling approaches and the major gaps in our knowledge.
  2. A review article on methods for modelling forest wind risk, from the single tree to national scale, for submission to Environmental Modelling and Software

Overview

The workshop was organised by ROLL collaborator Prof. Barry Gardiner and took place in Arcachon (near Bordeaux, France) from 28-30th October and brought together forest wind risk modellers from around the world along with experts in subjects required to improve the models (e.g. meso-scale airflow modellers, wind climate scientists, risk analysis engineers, etc.), but who have to date not always been actively involved in forest wind damage risk modelling.  Professor Emma Hart gave a talk on the opportunities for using Machine Learning techniques within the industry, and posed the question of whether novel optimisation methods might be developed given that potential solutions can be easily evaluated by replacing expensive simulations with tools like neural networks that approximate solutions. Slides from her talk are available here : WindDamageForests

(photograph courtesy of Barry Gardiner)