Tomorrow's Railway and Climate Change Adaptation Final Report

analysis was well underway. Designed to address some of the issues above, they offered
a ‘strategic’ systems level of understanding.
Further development of spatial understanding at this level will act as a good example of
how GIS can deliver informatics at operational systems level. This includes improved
granularity of issues and clearer integration of the report’s findings into a live or
interactive spatial dataset. With specific metrics to address weather and climate impacts
and incurred costs, the Baselines Capability and Extreme Weather Action Team (EWAT)
projects (see Appendix 3 of the Task 5C report) will roll out further integrated metrics
over the next 12 months.
These will show weather and environment hotspots and will be valid at operational to
socio-economic systems levels. This project will also establish a level of understanding to
assess resilience to certain weather inputs at route level. It is unclear how much
granularity of information will become available. Ideally all assets, particularly critical
ones, will have some ranking or designation to show their resilience to a range of
expected vulnerabilities.
4.20 Task 5D Geographic systems modelling, an
investigation into how GIS-based analyses are being
used and can form decision support tools
This task contributed to the assessment of GB rail system’s resilience to climate change
by demonstrating the relationships between the key scales and frequencies of natural or
anthropogenic hazard processes and the data available to assess it. This includes a
discussion about how physical dimensions of assets (and their environment) are
described by data, and the challenges and opportunities for comparing the hazard data
with asset data.
Task 5D has highlighted critical data issues. It has proposed areas where improvements
to data-resolution (or mitigation of limitations) may enhance the understanding of
processes that could affect the rail system’s resilience to climate change. It has
identified more areas where spatial analysis can be developed or implemented.
There will be some challenges concerning the understanding and identification of
thresholds for environmental data. These have been discussed at length in T1009 Phases
1 and 2. However, the scope and resolution of weather/ environmental data is a
significant factor in resolving susceptibilities of assets to potential environmental
impacts. In turn, the extent and resolution of data about assets are critical to
understanding their resilience.
In terms of data use, accuracy and purpose, the following issues should be considered:
• An appropriate resolution of data for the systems level of analysis could be defined
and aligned to industry practices/ hierarchy. The integrated metrics report and Task
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