## 4 Conclusions  
This study aimed to analyze the flash flood susceptibility zones by using an FR model with ten independent parameters. This was performed considering that the higher the input, the more dependable the accuracy of the results. As a result, only areas where the necessary number of flash flood locations is at least 100 points could be subject to the mapping of flash flood vulnerable zones using the FR model. In total, 147 flooded locations were collected from field and satellite data of pre- and post-flash flood events. Frequency ratio techniques as tools were used in this study to create an accurate FSM map in New Cairo City. Researchers and scientists can use this tool to gain insights about effective methods for handling massive datasets. In our study, we used ten conditioning factors (elevation, slope, aspect, LULC, lithology, stream distance, stream density, TWI, TRI, and surface runoff) that have been developed and used in the FR technique's training data as input. According to our findings, the flood susceptibility map has been categorized as having very low, low, moderate, high, and very high risk, which correspond to 40.09%, 13.14%, 14.48%, 12.97%, and 19.32% of the total area of the city, respectively. The findings of the susceptibility map showed a high flood risk in regions with low elevation, low slope and aspect, and near proximity to stream networks, urban areas as well high topographic areas, and wet areas. Decision makers could use the generated flood susceptibility map as a reference to step up preventive measures in areas that are particularly vulnerable to flash flood threats. Eventually, the AUC-ROC curve was used to perform and validate the used models, with an accuracy of 90.11% area under the curve. In order to build a deeper understanding of flash flood crisis mitigation, future studies will need to integrate models, such as logistic regression and weights of evidence. The findings reported here can act as a jumping-off point for subsequent research on flood evaluation and could give researchers a better understanding of the study area's vulnerability to flash floods.  
Conceptualization, H.A.M., A.M.A. and M.N.H.; methodology, H.A.M., A.M.A., M.A.E.A. and M.N.H.; software, H.A.M., A.M.A., M.A.E.A. and M.N.H.; validation, H.A.M., A.M.A., M.A.E.A. and M.N.H.; formal analysis, H.A.M., A.M.A. and M.N.H.; investigation, H.A.M., A.M.A., M.A.E.A. and M.N.H.; resources, H.A.M., A.M.A., M.A.E.A. and M.N.H.; data curation, H.A.M., A.M.A., A.S. and M.N.H.; writing-original draft preparation, H.A.M., A.M.A., A.S. and M.N.H.; writing-review and editing, H.A.M., A.M.A., M.A.E.A., A.S. and M.N.H.; visualization, H.A.M. and M.N.H.; supervision, H.A.M. and M.N.H.; project administration, H.A.M., A.M.A., M.A.E.A. and M.N.H.; funding acquisition, H.A.M., A.M.A., M.A.E.A., A.S. and M.N.H. All authors have read and agreed to the published version of the manuscript.  
The work received no fund.  
Not applicable.  
The data presented in this study are available upon request from the corresponding author.  
The authors are grateful for support in carrying out this work from the National Authority for Remote Sensing and Space Sciences (NARSS), Cairo 11769, Egypt and SAFE University of Basilicata, Potenza Italy. We sincerely thank the editor and all reviewers for their valuable feedback that we have permitted to improve the quality of our manuscript.  
The authors declare no conflict of interest.