## 4 Conclusions  
1. The amount of rainfall runoff in the study area was monitored, and the data obtained were used to calibrate and verify the SWMM parameters. The constructed SWMM simulation is highly accurate, and the model is suitable for Wujin District.
2. By optimizing the drainage system and implementing low-impact development (LID) measures, the average duration of internal flooding in Wujin District was reduced from 7.43 h to 3.12 h, a 58% reduction. The results show that the optimized drainage system can drain floodwater more quickly, significantly reducing the impact of internal flooding on the area and improving the area's flood control capabilities and the quality of life of residents. The average depth of accumulated floodwater was also reduced from 21.27 cm to 8.65 cm, a 59.33% reduction. The data show that by constructing new stormwater mains, adding drainage branches, and building stormwater storage ponds, the depth of accumulated water has been significantly reduced, and the extent of accumulated water during internal flooding has been effectively controlled, reducing damage to buildings and farmland and protecting the infrastructure and ecological environment in the area. At the same time, drainage efficiency has increased from 58.32% before optimization to 91.46%, representing an increase of 56.82%. The drainage system failure rate has dropped from 5.15% to 1.86%, a decrease of 63.88%. These results show that the overall performance and reliability of the drainage system can be significantly improved by optimizing the drainage network layout and conducting regular maintenance. An efficient drainage system can remove rainfall runoff more quickly, reduce the risk of waterlogging, and improve the stability and reliability of the regional drainage system.  
The proposed method for SWMM calibration and optimization demonstrates strong adaptability and this approach can be applied to rapidly urbanizing regions prone to flash flooding, coastal cities facing rising sea levels, and semi-arid regions experiencing episodic intense rainfall. The combination of parameter calibration and LID measures provides a systematic framework that can be tailored to local conditions, offering a scalable solution for enhancing urban flood resilience. Future work should focus on integrating emerging technologies, such as real-time monitoring systems and machine learning algorithms, to further enhance the accuracy and efficiency of SWMM optimization. Expanding the application scope of this method to diverse urban and climatic settings will contribute to more robust and generalized flood management strategies.  
Conceptualization, Y.P. and X.L.; methodology, Y.P.; software, Y.P.; validation, Y.P. and X.L.; formal analysis, Y.P.; investigation, Y.P.; resources, Y.P.; data curation, Y.P.; writing--original draft preparation, Y.P. and X.L.; writing--review and editing, Y.P. and X.L.; visualization, Y.P.; supervision, X.L.; project administration, Y.P. and X.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
This research acquired data support from the Emergency Management Joint Innovation Technology Key Projects (Type I) of the Emergency Management Department of Guangxi Zhuang Autonomous Region (2024 GXYJ005).  
The authors declare no conflicts of interest.