6.1 Risk Matrix
In order to determine the level of risk resulting from different hazards a risk matrix integrates information on the likelihood of various hazard scenarios (see 2.3) with the expected severity of their impact (2.5). This can in principle be calculated using the simple equation of hazard x vulnerability (probability representing hazards and impact values representing vulnerability). For instance, based upon scales from 1-‐4 let us assume landslides were likely (value: 3) and their impact was moderate (value: 2). This would result in a risk value of 3 x 2 = 6. If earthquakes were somewhat likely (2) but their impact would be highly catastrophic (4) they would have a risk value of 2 x 4 = 8. The higher the risk the higher the value: 8 would indicate that earthquakes would be the more significant risk compared with floods (though the difference is relatively small).
A strictly quantitative interpretation of the risk equation is however not always appropriate or sufficient. In any event preliminary results from calculations should be scrutinized in workshops bringing together working group members and key stakeholders. Participants need to agree on what risks require priority attention while checking all available information (including information on capacity). Care needs to be taken that the interpretation of data is performed in an accurate and unbiased way. A risk matrix visualizes results i.e. a comparative representation of a variety of risks related to various types of hazards. Below is an example of a risk matrix (that does not use figures but colors to indicate levels of risks red indicating highest and green lowest level of risk). Matrices can be completed for a whole local government area; for particular villages or high-risk locations; and for different vulnerable groups.
Table 10: Risk Matrix Local Government Area (Example)
Impact
Probability Minor Moderate Major Catastrophic
Very likely Flood - rural
Likely Mild influenza Extreme cold Flood - urban
Somewhat
Unlikely Serious pandemic Nuclear accident
Table 11: Risks Matrix for children, village 1 (Example) Probability
Impact Minor Moderate Destructive destructive Highly
Very likely Avalanche Flood - rural Landslide
Likely Extreme cold Fire at school Earthquake
Somewhat
likely Measles
Unlikely Nuclear accident
6.2 Vulnerability and Risk Mapping
In section 2.3 we have already briefly looked at hazard and exposure maps. By adding spatial information on vulnerability to hazard information (i.e. data on expected impact or degree of losses to data on the likelihood and location of certain hazard(s)) we can identify high-‐risk areas In order to establish these maps we use data on likelihood and impact that can be spatially referenced. We may combine for instance classified data on the probability of flood hazard with information on population density, economic productivity, the relative numbers of certain vulnerable groups, the structural qualities of infrastructure: in other words selected indicators that we used to identify and classify impact and vulnerability. This can be done for each hazard (or priority hazards) individually.
Tip No 13
23 See also Shirish, Ravan “Spatial Data to complement the use of space-‐based information in disaster
management” in: UNOOSA/ Altan, Backhaus et al., “Geoinformation for Disaster and Risk Management”, Copenhagen, 2010
Figure 5: City of Boise, Oregon USA Wildfire Risk Map24
Maps can show a whole local government area or focus on one high-‐risk area such as a village or floodplain. In the image above an aerial photo has been used as background and been overlaid with electronic data from the local bureau of Land Management and data from a fire-‐ hazard and risk assessment covering a range of parameters. Risk (high risk in red, low risk in grey) has been identified in relation to individual buildings. At a larger scale risk mapping can be done in relation to individual settlements within a local government area.
Eventually data on different hazards (landslides, earthquakes, floods etc.) can be overlaid to identify “hot spots” where risks from multiple hazards overlap. The more complex and multi-‐layered the analysis gets, the more useful it is to do the mapping with the help of an electronic geographic information system. However, multi-‐ hazard and risk analysis can also be done manually by using transparencies. Maps of different themes -‐ for example, flood zones, poor neighborhoods (vulnerability), hospital and evacuations centers (capacities) are drawn onto transparent sheets. They are then all laid over a topographical map and each other, and the resulting map will indicate the locations of high and low risk for a particular geographic area.
24 http://www.boiseweekly.com/boise/98-‐percent-‐of-‐surveyed-‐east-‐foothills-‐homes-‐at-‐high-‐risk-‐
As for any analysis we need to remember that the result of risk mapping depends upon the accuracy of underlying assumptions and the quality of data.
The following are common challenges that complicate (risk) mapping in particular at the local government level:
Non-‐availability of topographical maps in sufficient resolution
Non-‐availability of general reference and thematic spatial data
(Spatial) general reference and thematic data is outdated
Base-‐line and thematic data is scattered across different organizations with non-‐uniform data-‐standards (that complicate integration in a map)
Lack of mapping and GIS capacity
UNICEF’s initial experience in working with local governments in CEE CIS has shown that mapping efforts have depended upon the support from external specialists. However preliminary results – mostly focusing on hazards and exposure – have been promising and deemed highly useful by local governments.
6.3 Writing Risk Analysis Reports
The information presented in the report is supposed to be neutral and objective. Reports need to present key findings and conclusions in a way that is transparent and facilitates the verification of data and the tracing of analysis. This means that the methodology and sources of data need to be clearly presented. This includes an explanation of key assumptions and gaps and weaknesses in collected data (i.e. data that is outdated etc.) and how these weaknesses were dealt with.
Reports should be clearly structured and key information and conclusions should be presented in an executive summary preceding the main narrative. Graphs, photos and tables that help to illustrate findings and conclusions should be included. The structure of reports will vary depending upon context. However reports should highlight:
Executive Summary
Objectives and methodology of the analysis (including duration and key benchmarks of the analysis)
General information about the reference area
Key Hazard (Scenarios) affecting the area
Risk Analysis (narrative, risk matrice(s), map(s)) including an analysis of:
o Key vulnerabilities and vulnerable groups
o Key capacities and resources
Conclusions and proposed measures to reduce vulnerabilities and risks
Annexes might include further information on the composition of the working group, stakeholders, data-‐collection process, time-‐line of the analysis, sources of information etc.
The structure of the report should be agreed with the working group. Key conclusions and recommendations should also reflect agreement with the working group (and potentially with other key stakeholders, community representatives and experts). The local government should approve the final draft of the report officially.