## 9 Summary and Conclusions  
We collaborated closely with partners in the HKH to develop HydroSAR, an SAR data processing and analysis service focused on the automatic, year-round, and near real-time generation of flood information products for this region. To meet end user needs, HydroSAR was designed with a broad product suite in mind, which enables the simultaneous assessment of several flood-related parameters as events unfold and progress. The service uses Sentinel-1 SAR data as its input and is fully cloud-based to enable rapid product generation at scale. A tight integration with ASF's cloud-based Sentinel-1 SAR archives ensures that data do not have to be migrated out of the cloud, maximizing the throughput and minimizing processing costs. The service was successfully transitioned to ICIMOD, a regional organization in the HKH who continue to operate HydroSAR and provide its data to end users through a dedicated web portal. An application of HydroSAR to analyze the 2023 southeast Asia monsoon season showcased one of many potential use cases of HydroSAR and demonstrated the amount of information which can be extracted from the available data. The HydroSAR team has been monitoring the performance of its service since operational data production started in 2022. These analyses have revealed a number of strengths and limitations of the service. The service has demonstrated rapid and fully automatic data production capabilities, resulting in the consistent, weather-independent, and continuous delivery of low-latency flood hazard information to the region. Regular spot checks of the data quality and positive feedback from end users indicated improved capabilities in monitoring monsoon-related flood hazards, especially for the regions of Bangladesh, northern India, southern Nepal, and southern Bhutan. The temporal sampling provided by the service was found to be sufficient to monitor the emergence and recession of monsoon-related waters on a regional scale. Some limitations of the service were found to be related to the side-looking geometry of SAR, which has resulted in limited visibility for some of the narrower mountain valleys of Nepal. The 30 m resolution of HydroSAR data products has also resulted in occasional missed detections in areas where rivers are narrower than the 30 m pixel size. Finally, while the temporal sampling of our Sentinel-1-backed service has been sufficient for monitoring slowly evolving monsoon floods, it has not been a reliable resource for the assessment of flash flooding events in the region. These rapidly unfolding events are a growing risk in the HKH [61] but often evade detection from spaceborne sensors. The team continues to work with its partners to address these identified challenges and improve the service. We are currently evaluating the benefits of moving to a 20 m product for areas in Nepal where 30 m data revealed challenges with monitoring narrow rivers. We are also preparing for the integration of data from the highly anticipated NASA-ISRO SAR (NISAR) mission, which is currently scheduled for launch in early 2025. Finally, we are investigating machine learning algorithms, which would combine SAR data with river discharge forecasts to enable daily flood water extent forecasting. Conceptualization, F.J.M. and R.B.T. ; methodology, F.J.M., B.O., M.J., J.H.K., J.R.B., B.K. and L.A.S. ; software, F.J.M., B.O., M.J., J.H.K., J.R.B., T.J.M. and J.S. ; validation, F.J.M., M.S., T.J.M. and L.A.S. ; formal analysis, F.J.M. and B.O. ; investigation, F.J.M. ; resources, F.J.M. ; data curation, J.H.K., H.K. and S.P. ; writing--original draft preparation, F.J.M. ; writing--review and editing, B.O., M.J., R.B.T., J.H.K. and L.A.S. ; visualization, F.J.M., M.J., H.K., M.S. and R.B.T. ; supervision, F.J.M., B.O. and L.A.S. ; project administration, F.J.M. ; funding acquisition, F.J.M. All authors have read and agreed to the published version of the manuscript. This research was funded by the NASA Science Mission Directorate under grant numbers 80 NSSC20K0164 and 80 NSSC19K1109.