## 2 Materials and Methods
### Methodology  
#### 2.3.1 Scenario-Based Flood Risk Analysis Framework  
The conceptual procedure used in this study is shown in Figure 2. Two scenario series representative of the historical (solid arrows) and future (dashed arrows) are associated, as the former depicts the baseline risk and the latter estimates the risk evolution. A risk analysis is performed by integrating two critical zone types, named flood inundation-prone zone and high-risk zone, which generates 3 ranks for management response (specific definitions can be found in the paragraphs below). By incorporating the differentiated rank characteristics and the driving factors of risk change, adaptive management strategies customized for different ranks can be devised. Then, through the validation pipeline (dotted arrows), the reliability of future estimations and the potential scalability of the framework for other catchments are certified. Eventually, a hierarchical panel summarizing the recommended response strategies scheduled for various social entities is produced to help address risk management uncertainty. Figure 3 shows the technical procedure, which consists of six steps, where the case study of the PLEEZ from 2015 to 2021 is considered for illustrative purposes. First, in the historical flood scenario step (Figure 3a), annual inundation and rainfall intensity are extracted to measure the hazardous of flood risk. Then, various natural and socioeconomic factors reflecting environmental sensitivity and vulnerability are jointly considered in the risk baseline model based on the multicriteria decision analysis (MCDA) approach (Figure 3b). Figure 3c maps the baseline situation and analyzes the risk at the county level. Then, with the prediction of future assessment factors based on the projection datasets (Figure 3d), the model is used to reassess future flood risk (Figure 3e). Further, the  
Figure 2: A conceptual flowchart of the flood risk analysis framework. The solid arrows represent historical scenarios, the dashed ones the projections and the dotted ones the validation pipeline. The numbering indicates the processing order. risk tendency can be determined and the key factors contributing to risk increase identified by performing attribution analysis. The last step (Figure 3f) of the key risk analysis framework aims at enhancing decision robustness and considers two components: a flood inundation-prone zone and a high-risk zone. The former is defined as the hotspot area derived from multiyear inundation frequency obtained in the first step (see Figure 3a) by using the Optimized Hot Spot Analysis tool of the ArcMap Spatial Statistics toolbox (version: 10.6; copyright: ESRI (2018) [66]). This component depicts the most statistically significant flooding-susceptible areas in recent history and thus provides a probabilistic result that aggregates the commonalities of inundation events over the years, rather than a simple intersection of inundation grids or the extent of all inundations. The other component, the flood high-risk zone, refers to areas classified as being at very high and high risk in the baseline map in Figure 3c. Clearly, these two zone types are partially correlated but imply different risk perception information. Specifically, the flood inundation-prone zone provides valuable lessons based on historical events, especially extreme cases, while the high-risk zone reveals potential damage and loss degrees. Their spatial overlap yields 3 different assessment perspectives, and 3 categories are defined accordingly based on priority, represented in the figure as a red intersecting part (Rank 1: high-risk and inundation-prone), a cream-colored upper part (Rank 2: high-risk but non-inundation-prone) and a green lower part (Rank 3: non-high-risk but inundation-prone). Combined with the causal factors of risk increase in step (e), more robust management strategies for flood prevention can be developed. Specific descriptions and usage guidance relative to the above steps are described in the following sub-sections.