Research project of Lancaster University funded by NERC and Scottish Power
23 and 24 December 2013, The storm caused extensive power cuts, with around 50,000 homes remaining without power through the Christmas period. Rail services were cancelled due to fallen trees.
5 December 2013, Scotland's rail network shut down, 100,000 homes without power.
3 January 2012, Fallen trees blocked roads and rail lines and damaged power lines. More than 100,000 Scottish homes and businesses were left without electricity and some buildings were damaged.
8 December 2011, By far the most significant impacts were felt across Scotland. Network Rail imposed a speed restriction because of the risk of trees and other debris on rail lines. Thousands of people were left without electricity; an estimated 150,000 homes lost power during the 8th, mainly as a result of trees and other debris blown on to overhead power lines. The overall cost of disruption to Scotland's economy has been estimated at around £100 million.
10 March 2008, A deep area of low pressure moved east across southern Ireland, central Wales and Lincolnshire. Cross-Channel ferry crossings were cancelled and 30,000 homes suffered a loss of power.
7 January 2005, Northern England took a battering, with transport and power supplies disrupted. By late on the 7th 80,000 customers had lost power in NE England and 20,000 houses in Yorkshire and Humberside remained without electricity for most of the 8th. because of damage to overhead power lines.
With the prospect of increasingly severe and more frequent storms due to climate change disruption to electricity networks and subsequent loss of supply to consumers will become more common unless there is a step-change in the methodologies used to assess the risk to infrastructure.
The aim of the project is to develop a scientifically based, robust and objective method to predict tree failure in severe weather conditions and create web based GIS application embedding the prediction model and delivering the results to the users in intuitive and interactive map format.
Phase 1 is about predicting tree failure based on complex treatment of wind but (relatively) simple treatment of trees and can be applied at a regional scale to give an indication of areas where failure is likely. Phase 2 will be more about incorporating specific parameters into models of trees at much more local scales.
You can open the application by clicking the "See it work" botton at the top of this page. When you first open the application it shows a public view of the map zoomed to maximum resolution. The public view limits the resolution so that it can use cached map tiles and work faster.
The map shows results of model simulation.
You can toggle the legend on and off by clicking the "L" button close to the zoom buttons. The legend explains color coding of the trees, power lines and other features in the map. Some of the features are restricted to admin view.
Three simple classes (red, yellow, green) give first impression of tree failure risk. The map can be also viewd on mobile devices through a web browser.
You can zoom out and zoom in by clicking "-" and "+" buttons at the upper left corner of the map or by scrolling mouse wheel. Click and drag to pan the map.
The wind speeds and directions are loaded from weather database. The map shows animated wind particles traveling over the landscape in real speed and direction.
Trees are stored in a database with number of attributes. Tree crown width is displayed as circle for each tree. In order to see the height of the tree, you can hover over the tree crown. Blue circle is displayed to show height of the tree. Height of the tree is important for assessing the tree susceptibility to failure, but also to assess the proximity to power line or other infrastructure.
Model works on individual tree level. Risk is calculated for each tree. Trees can be viewed, sorted and selected in the table.
Having the model as web application makes it easy to use. There is no need for installation and synchronization of data and trees are stored on server in central database.
Model can be parametrized for varius scenarios and run manually. The database at this moment contains past observations of weather data, i.e. hourly wind speeds and directions for all weather stations since 1969. The simulation runs can be based on existing data but the inputs can also be changed to create scenarios. E.g. you can see what would happen if the winds in 5th. December 2013 storm were two times faster and traveled from oposite direction.
Principal Investigator Alan Blackburn has developed a research team that has exploited emerging sensing technologies and modelling tools in order to elucidate the spatial and temporal dynamics of forest disturbance and understand the key abiotic and biotic controls on tree failure.
Co-Investigator Duncan Whyatt has over 20 years of experience in developing and applying spatio-temporal models of environmental processes. His work has focussed on the interactions between anthropogenic influences and natural environmental processes. Duncan has extensive experience in delivering science that has impact in the real world.
Research Associate Petr Vopenka has experience from various projects developing GIS applications, managing data and working for public and private companies. Petr works on technical aspects of the project.
Lancaster Environment Centre | Lancaster University | Bailrigg | Lancaster | United Kingdom | LA1 4YW