Disaster Preparedness at the Municipality Level: A Scenario-Based Multistage Measurement Methodology

Abstract

This study aims to develop a methodology in the disaster management field to assist policy-makers in the evaluation of the state of disaster preparedness of a municipality considering possible disaster types and corresponding scenarios. The paper first provides an overview of selected past disaster preparedness studies and identifies the main dimensions of preparedness. Then, it integrates them into a comprehensive framework for disaster preparedness measurement. The framework considers multistage aspects of disaster preparedness by integrating the pre- and post-disaster status. Preparedness at the municipality level is evaluated with respect to the following four areas: hazard assessment, mitigation capabilities, resource preparedness, and management performance. Implementing the methodology can provide insights to governments concerning their level of disaster preparedness. By highlighting areas of weakness, it can contribute to strengthening their readiness.

Appendices

Appendices

1.1 Appendix A: Steps of the Weighted Sum Approach

In Fig. 3, we provided a radar diagram to show the extent to which the normal situation (initial status) is going to change after each disaster scenario. The values for each dimension in Fig. 3 are calculated using the weighted sum approach. In this section, we provide an illustrative numerical example of calculating final weighted sum values for the transportation dimension. Values of other dimensions are calculated similarly. To yield the final value of each dimension in the radar diagram, the following steps are taken. Note that this procedure is repeated separately for each scenario:

• 1. First, for each dimension, we assign the weights of each level, i.e., component level, aspect level, and indicator level. Note that the summation of weights at each level (node) must be 1.

• 2. For each indicator, the percentage ratio of post-disaster value to pre-disaster value is calculated. These percentage ratio values are used for weighted sum calculations.

• 3. The weighted sum calculation is done from right to left, i.e., i) for each aspect, the weighted sum of its corresponding indicator values is computed, ii) then for each component the weighted sum of its corresponding aspect values is calculated, and iii) for each dimension the weighted sum of its corresponding component values is calculated.

In Table 7, we provided only indicators for one aspect (i.e., highway). For other aspects we only provided the aggregated values. The numbers below each indicator, aspect, component, and dimension are the weighted sum values for scenarios 1, 2, and 3, respectively. In this illustrative example, we only consider a limited number of indicators for the highway aspect; however, policy-makers in practice may define a wider range of indicators. The final values for transportation are calculated as 75.73 for scenario 1, 64.72 for scenario 2, and 53.38 for scenario3. This can be interpreted as 25 percent of transportation capacities of the municipality are affected in scenario 1.

Table 7 An illustrative example of weighted sum calculations for the transportation dimension

Note that for Hazard Knowledge and Management, other scoring methods can be used since they are more qualitative.

1.2 Appendix B: Weighted Sum Calculations for Preparedness Measurement

In Fig. 5, we provided a radar diagram specifying the final disaster preparedness for a possible disaster. The values of each preparedness area (i.e., P1, P2, P3, and P4) are calculated using the weighted sum approach which is explained earlier in Appendix A. In Table 8, we provided the final values of each preparedness area aggregated into its dimension level. The final values of P1, P2, P3, and P4 are calculated as a weighted average of their corresponding dimension values for each scenario.

Table 8 An illustrative example of weighted sum calculations for the final four areas of preparedness measurement