## 4 Case Study Analysis
### Analysis of Simulation Results  
Figures 8 and 9 illustrate the SOC variations of mobile energy storage and water storage vehicles under the two scheduling schemes. In Case 1, the grouped scheduling strategy based on the fast Newman algorithm ensures that the resource demands of each region are prioritized, thereby avoiding resource wastage and scheduling delays caused by cross-regional dispatching. Through efficient allocation of resources within each region, the SOC decline curve of energy storage vehicles in Case 1 is relatively smooth, demonstrating high resource utilization efficiency. In contrast, Case 2 adopts a global scheduling strategy that disregards resource balancing across regions. As a result, regions with high demand experience resource shortages during peak periods, while resources in low-demand regions remain underutilized, leading to a decline in overall resource scheduling efficiency. Regarding SOC variations, some energy storage vehicles in Case 2 deplete their energy rapidly within 24 h, whereas others remain underutilized, further diminishing the overall resource utilization efficiency. The average SOC was calculated over the entire simulation period for both scheduling strategies. As shown in the results, the grouped scheduling strategy achieves a 30. Figures 10 and 11 illustrate the variations in water storage levels. In Case 1, the scheduling paths of water storage vehicles are flexibly adjusted in real time based on demand, ensuring a stable water supply. During idle periods, water storage vehicles can promptly return to reservoirs for replenishment, ensuring that the water supply needs of each region are met in a timely manner. As a result, Case 1 is more effective in responding to fluctuations in water demand during disasters. In Case 2, the absence of regional division leads to water shortages in certain areas during peak demand periods, reducing water supply efficiency during disasters. This indicates that regional division can effectively enhance the flexibility and precision of water resource scheduling, ensuring a stable water supply during disaster scenarios. The average water storage was calculated over the entire simulation period for both scheduling strategies. As indicated by the results, the grouped scheduling strategy achieves a 31.88% higher average water storage compared to global scheduling, further demonstrating its superiority in enhancing water resource allocation and ensuring supply stability during disaster scenarios. Figures 12 and 13 illustrate the variations in user satisfaction under the two scheduling schemes. In Case 1, user satisfaction is calculated based on the resource scheduling conditions of each region and weighted according to the population proportion of each region to  
Figure 11: Comparative analysis of average freshwater in the four regions of Case 1 with the global freshwater scenario in Case 2. Figure 10: Comparative analysis of freshwater variation in of Case 1 (four regions) and Case 2 (one region). derive the overall satisfaction level. The simulation results indicate that user satisfaction in Case 1 remains relatively stable, with minor fluctuations, staying at a consistently high level within 48 h. Grouped scheduling improves user satisfaction in certain regions, demonstrating that the grouped scheduling strategy can accurately match resource demands across different regions to effectively reduce community dissatisfaction caused by insufficient resource supplies. In contrast, due to the absence of regional division and the adoption of a global scheduling approach in Case 2, resource allocation becomes unbalanced during certain periods. This issue becomes particularly evident after 24 h, where user satisfaction declines significantly and exhibits greater fluctuations. In certain regions, resource shortages lead to a noticeable deterioration in user experience, ultimately resulting in a lower user satisfaction level compared to the weighted average.