Flooding in London
Effects on Energy, Transport and Tourism Sectors
What do the results tell us?
The results show that the vulnerability of London's economy to flooding events, now and in the future, is affected primarily by damage to the transport system (affecting movement of labour), power and water infrastructure, the professional services sector (primarily offices) and the hotel and food industries (related primarily to the economic sectors related to tourism).
They also tell us that the amount of this loss of GDP is influenced significantly by how the city chooses to allocate recovery resources after flooding has taken place. Specifically, if recovery takes place only as there is a return of final demand for products (for example, production of televisions is repaired only as demand for new televisions returns after the flooding), both the length of the recovery period and the total loss of GDP is longer than if recovery takes place in advance of demand.
What can we do with the results?
The results can help decision-makers direct adaptation funds so they produce the greatest reduction in the vulnerability of the city's economy to extreme weather events. This can be done by adjusting the Sector Vulnerability Matrix so the production assets of an economic sector are protected prior to flooding. For example, by protecting buildings that house the most significant economic activities, or moving the locations of those buildings outside flood zones; and by allocating recovery resources to bring about repairs in those sectors that are contributing most strongly to the loss of GDP during the recovery period (allocating those resources in advance of return of demand for the products and/or services of a sector).
How are the results obtained?
Results were obtained using an Input-output model of London's economy, linked to climate projections supplied by the partners at University of East Anglia. The model was used to simulate 1-in-100 year pluvial flooding events in London in 2015, 2050 and 2100, and then to follow both the direct and indirect economic impacts of this flooding during a recovery period using the input-output model. The Sector Vulnerability Matrix was developed from information supplied by the ARCADIA project, assuming locations of production facilities of each sector are randomly distributed throughout London; this assumption can be changed as a city develops more detailed mappings of the locations of production facilities.
More specifically, the modelling took place in 7 steps:
- One of the Representative Concentration Pathways (RCPs) was selected from amoungst the RCP2.6, 4.5 and 8.5 pathways considered throughout the ToPDAd project.
- The SPEI today, in 2050 and in 2100 was obtained from the University of East Anglia climate group. SPEI is the Standardised Precipitation-Evapotranpiration Index.
- The highest SPEI value associated with a 1-in-100 year event was determined for each of the three years.
- The Sector Vulnerability Matrix for each sector was determined from the 1-in-100 year flood zone using the Drain London maps.
- This information was used to calculate the loss of production capacity in each economic sector for the present day. Values in 2050 and 2100 were adjusted upwards based on the increase in the 1-in-100 year event SPEI from Step 3.
- The indirect and direct economic losses were calculated from the input-output model for each of the three years and for each of the three RCPs.
- Adaptation strategies were then applied to repeat steps 1-6 so the effectiveness at reducing GDP loss could be produced.
Three adaptation strategies (plus one forecast with no adaptation strategy) were modelled for each RCP and year:
- Option 0: No adaptation strategy is applied.
- Option 1: Strategic application of recovery resources (capital) to reduce the overall economic impact. This requires replacement of damaged assets in key production sectors in advance of full return of final demand for the products and services of those sectors.
- Option 2: Changes in the Sector Vulnerability Matrix to reduce the vulnerability of each critical energy, transport and tourism sector (sectors 22, 23, 27, 28 and 29 in the input-output table) by half through flood defence measures.
- Option 3: Simultaneous application of the first and second adaptation measures.
What are the broader applications?
The same methodology can be applied to any community, nation or region for which the necessary input-output data are available. Since the input-output data contain all economic sectors, the methodology can be applied to any sector for which the Sector Vulnerability Matrix can be supplied. This in turn requires detailed hydrological information for the geographic area, linked to the RCP projections of SPEI.
The methodology can be improved by linking it to a detailed Transport model, which will improve the analysis of the labour loss through damage to the transport sector of the area. It can also incorporate macroeconomic projections such as are available through the GRACE and GINFORS models of ToPDAd, allowing the methodology to better reflect potential changes in the size and structure of the economy in 2050 and 2100. At present, these two factors are within the model as data entries that reflect the assumptions given above, but can be changed as the data on transport and the macroeconomy become available.