Quantifying the risks of tree failure to guide proactive management and increase the resilience of electricity distribution networks.

Lead Research Organisation: Lancaster University
Department Name: Lancaster Environment Centre


Severe storms lead to the uprooting and breakage of trees and this, in turn, can cause considerable damage to electricity supply networks. For example, over the Christmas period 2013/2014 over 500,000 customers were off supply for over five days in the East of England and this was mainly due to damage to overhead power lines caused by catastrophic tree failure in storms. This type of disruption is likely to become more common in the UK as climate change causes storms to become more frequent and severe. It is possible to reduce the impacts of storm damage on electricity networks by felling those trees that are close to power lines and are at more risk of failing in a severe storm. However, assessment of the likelihood of a tree failing is currently done by a surveyor who makes a subjective and qualitative personal judgement based on a field observation of the tree. This approach lacks consistency and scientific rigour and the number of trees that it is feasible to assess and the frequency of repeat surveys is restricted by logistical and financial constraints. This project will address these limitations by developing a new approach to evaluating the risk of failure of individual trees in severe weather. This will begin by developing computer software which can prioritise trees at greatest risk of failure across a landscape which may contain thousands of trees that are close proximity to power lines. Those trees at greatest risk will then be targeted for more detailed measurements, particularly using laser scanners, which will allow us to provide more realistic and objective assessments of the risk of failure of individual trees. We will work with our project partners Scottish Power to demonstrate how this new approach is able to help them target their resources for managing trees at greatest risk of failure, in order to increase the resilience of electricity supply networks in severe weather and minimise disruption to customers. The techniques developed in this research will be valuable for improving the management of trees that are in close proximity to other infrastructure such as roads, railways and buildings, thereby helping to reduce the likelihood that storms will cause financial losses, disruption to services and harm to humans.


10 25 50
Description The project has developed a model which is capable of evaluating the risks of tree failure. The model, TREEFALL, uses data from meteorological stations and simulates the flow air over the land surface, providing estimates of wind speed and direction at any location. Previous storm events can be simulated and different weather scenarios can be developed. The model then uses data derived from remote sensing on the location and key properties of individual trees to quantify the risk of failure of each tree given the simulated wind speed and direction. We have demonstrated how the representations of individual trees can be improved within the model using further field survey and the use of terrestrial laser scanner data. The model calculates the probability of a falling tree hitting a powerline and can display the risks of damage to powerlines in various numerical ways and visualisations.
Exploitation Route The TREEFALL model will be valuable to the operators of all electricity supply networks and the operators of other forms of infrastructure such as roads and railways. The model has been demonstrated to a number of infrastructure operators and they have become involved in developing and applying the model further.
Sectors Energy,Environment,Transport

URL http://www.treefall.co.uk
Description The TREEFALL model has been demonstrated to project partner Scottish Power and used to identify parts of their electricity supply network in Wales that are at risk due to tree failure. The model has also been demonstrated to a wider range of stakeholders including UK Power Networks and Network Rail.
First Year Of Impact 2015
Sector Energy
Impact Types Economic

Title TREEFALL model 
Description A web-based model for predicting the risks of individual tree failures across landscapes. 
Type Of Material Computer model/algorithm 
Provided To Others? No  
Impact The model has been used to predict the risks to electricity supply networks due to tree failure. 
URL http://www.treefall.co.uk
Description Collaboration with ADAS on TREEFALL 
Organisation ADAS
Country United Kingdom 
Sector Private 
PI Contribution We have worked with ADAS to develop the basis of the TREEFALL model.
Collaborator Contribution ADAS have collaborated on the project, under contract, to develop some aspects of the TREEFALL model and disseminate the finding of the project ot relevant stakeholders.
Impact The functioning model TREEFALL has resulted from this collaboration.
Start Year 2015
Description Dissemination of findings 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
Results and Impact Several presentations of the TREEFALL model to various stakeholders and research colleagues
Year(s) Of Engagement Activity 2015,2016,2017