# Study on the Effectiveness of Multi-Dimensional Approaches to Urban Flood Risk Assessment
## 3 Result
### Comparison of FRIB-Based and Depth-Based Response Strategies  
Using FRIB-based measures instead of traditional flood-depth-based response criteria can lead to more effective and efficient disaster management. To quantify and compare these two approaches, a 500-year frequency flood map was used to evaluate buildings under each criterion. Figure 7 provides a direct visual comparison between the traditional 'flood-depth-based' risk classification method and the 'FRIB-based' risk classification method proposed in this study. This comparison demonstrates that the FRIB approach can more accurately delineate high-risk areas and reflect nuances for various situations than relying solely on flood depth. Figure 7a shows the levels derived solely from flood depth, following \begin{table}
\begin{tabular}{c c c} \hline \hline
**FRIB Level** & **Entropy** & **Variance** \\ \hline Very low & 0.423 & 1777 \\ Low & 0.608 & 1492 \\ High & 1.839 & 347 \\ Very high & 2.419 & 98 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Entropy and variance by FRIB level. the legend provided by the 'Urban Flood Map' within the Ministry of the Interior and Safety's Safety Map. In contrast, Figure 7b presents risk categories determined by the FRIB methodology. In a depth-based system, risk is linearly classified using a single indicator (flood depth), which makes it difficult to distinguish among various situations. Additionally, because the legend applies uniform depth thresholds to all areas, the resulting risk categories lack nuance. By contrast, the FRIB approach in this study incorporates multiple factors, enabling more refined differentiation of risk across different regions and facilitating the identification of truly at-risk buildings. For example, under the depth-based method, any building submerged beyond a certain flood depth is uniformly treated at the same risk level. However, with FRIB, even buildings designated as \"very high\" can be excluded from active response if their water depth is assessed to be relatively low, allowing resources to be allocated more selectively and reducing unnecessary interventions. Figure 7: Risk based on flood depth (**a**) and FRIB (**b**). Section A in (**b**) indicates deep inundation areas of 1 m or more, representing sections where Level 3 or higher risk can occur on the Urban Flood Map. Figure 8 expands on a specific area (Section A) of Figure 7, providing a detailed comparison of the quantitative resource allocation efficiency of the two approaches under the assumption of an actual urban flooding scenario. This figure visually demonstrates how FRIB reduces unnecessary interventions, optimizes resource allocation, minimizes resource wastage, and improves disaster response efficiency by showing the number of buildings where such improvements can be achieved. Based on the depth-based measurement (1 m or more), 5124 buildings were identified as requiring response measures. In contrast, when applying FRIB, buildings classified as \"low\" within that same 1 m threshold were excluded, reducing the target list by 24. If the exclusion criteria are expanded to also omit \"high\" levels, 530 buildings could be excluded, as shown in Table 5. This illustrates how a multi-factor index like FRIB can decrease the number of buildings demanding immediate action and optimize resource allocation. In a purely depth-based framework, all structures experiencing the specified flood level receive uniform emergency responses, potentially leading to an over-allocation of resources. The FRIB-based approach, however, allows buildings with lower composite risk to be excluded from full-scale responses, ensuring that resources and efforts remain concentrated on genuinely high-risk areas. Consequently, FRIB-based analysis not only enhances disaster response capacity but also provides a more tailored, efficient method for deploying personnel and equipment.