Centre for Earth Systems Engineering Research

Transport Analysis for Climate Impact Assessment

Transport Analysis for Climate Impact Assessment

Transport infrastructure analysis for climate impact assessment and urban simulation.

Project Leads

Introduction

Transport modelling is a well-developed field. There are many powerful commercial models which allow simulations of traffic flows and network performance. 

These models range from micro models of individual junctions to macro models of whole transport networks. They are often expensive and complex to run. 

Sometimes a more simple solution is needed which allows rapid testing of transport scenarios and their effects on local and regional accessibility and thus population or land-use patterns. 

A number of GIS-based transport modelling tools have been developed in CESER. These are part of the Tyndall Cities Programme and the EPSRC ARCADIA project.

This work was sponsored partly by the EPSRC ARCADIA project (EP/G061254/2).

Tyndall Cities Programme

 

Transport analysis is a key component of the Tyndall Cities Urban Integrated Assessment Facility (UIAF).

A model of transport accessibility, based on generalised cost, was developed to allow decision-makers to test scenarios of future transport infrastructure investment. 

The resulting changes in accessibility across London were used as drivers in scenarios of possible population and land-use change. They allowed testing of possible climate change adaptation and mitigation policy options.

Transport by car, rail, light rail and bus was modelled across the Greater London region.  Costs between 633 census (CAS) wards were computed, including time and monetary values. 

These costs did not include measures of capacity in the networks and thus congestion. They did not include interchanges between the various modes accounted for. 

This modelling was further developed under the ARCADIA project as part of EPSRC’s ARCC programme.

ARCADIA Project

The ARCADIA project seeks to provide a better understanding of the impacts of climate change on urban areas. This allows planning of suitable and sustainable adaptations. 

As part of this project, the transport models developed for the Tyndall Cities Programme were further extended. This was to allow simulation of both direct and indirect impacts from climate events. For example, flooding, extreme heat and droughts.

One of the most important indirect effects of such climate events is disruption to the transport network. For example, flooding of transport infrastructure or speed restrictions caused by extreme temperatures. This results in an increased travel costs for commuters and goods. 

To capture these effects, representations of capacity and congestion was integrated into the network models.

ARCADIA models the transport networks as two modes:

  1. An integrated public transport network comprising rail, light rail and bus routes and allowing for interchanges between them.
  2. A road network modelled on Ordnance Survey ITN data.

Capacities on the road network are modelled using speed-flow relationships. These link the volume of traffic on a road segment with the maximum speed of travel along it. This is from the UK Department for Transport’s COBA model. 

Capacities on the public transport network are modelled using information gathered on train length, passenger capacity, and service frequency. This gives values for total carrying capacity per hour.

To model disruption to commuting journeys, passenger trips are mapped to the network. These trips are from census journey-to-work data for the current day, or spatial-interaction model outputs for future scenarios. They're assigned to the shortest route between the origin (place of residence) and destination (place of work). 

This assignment is done iteratively. The effects of congestion are computed at each iteration. The shortest route is adjusted accordingly to reflect the build-up of traffic. 

This gives the total flow on each network link and the cost of travel between locations.

This information on flows and costs can be used to understand the disruption from future extreme weather events. This is by utilising impact functions to link flooding and temperature to network performance. 

For example, when temperatures are above a given threshold a speed limit is applied to the rail network to prevent derailments from rail buckling. 

The resultant increased travel costs can be fed back to economic models, allowing indirect effects to be understood.