**6. Conclusions**

Rainfall remote sensing datasets have the advantages of high temporal-spatial resolution and large coverage, which can overcome limitations such as a lack of gauge-based rainfall records. In this study, we propose a modeling framework for urban flood analysis based on short-record remote sensing rainfall and hydrologic model. The framework is largely motivated by the fact that, in spite of increased interest in urban flood analysis using high-temporal remote sensing rainfall data, the inherent limitation of a lack of long-term high-temporal rainfall data still exists. We used RainyDay and a nine-year record of hourly, 0.1◦ remotely sensed rainfall data to generate extreme rainfall events for an urban hydrologic model (SWMM). The rainfall estimates of RainyDay-based and IDF formula-based methods were compared, as well as the corresponding runoff process at 5-, 10-, 20-, 50-, 100-yr return periods for 2 h, 6 h, 12 h, and 24 h durations. In addition, the projection pursuit method was used to reflect the comprehensive characteristics of the urban flooding. A typical urban drainage basin in the south of China was selected as the case-study area. The main conclusions include the following:


**Author Contributions:** Conceptualization, Z.Z. and Y.C.; methodology, Z.Z. and Y.Y.; software, Z.Z. and Y.Y.; validation, Z.Z., Y.C., and Z.Y.; investigation, Z.Z.; resources, Y.C. and Z.Y.; writing—original draft preparation, Z.Z. and Y.Y.; writing—review and editing, Y.C. and Z.Z.; visualization, Z.Z. and Y.Y.; supervision, Z.Y.; funding acquisition, Z.Y. and Z.Z. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program (2017BT01Z176), Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (GML2019ZD0403), and National Natural Science Foundation of China (52009021).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data that support the findings of this study are available from the corresponding author upon reasonable request.

**Acknowledgments:** The authors wish to express their gratitude to all authors of the numerous technical reports used for this paper. We would also like to thank the editor as well as the reviewers whose constructive criticism contributed greatly to this paper.

**Conflicts of Interest:** The authors declare no conflict of interest.
