Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

HydroSAR: A Cloud-Based Service for the Monitoring of Inundation Events in the Hindu Kush Himalaya

Version 1 : Received: 22 June 2024 / Approved: 22 June 2024 / Online: 24 June 2024 (10:55:02 CEST)

How to cite: Meyer, F. J.; Schultz, L. A.; Osmanoglu, B.; Kennedy, J. H.; Jo, M.; Thapa, R. B.; Bell, J. R.; Pradhan, S.; Shrestha, M.; Smale, J.; Kristenson, H.; Kubby, B.; Meyer, T. J. HydroSAR: A Cloud-Based Service for the Monitoring of Inundation Events in the Hindu Kush Himalaya. Preprints 2024, 2024061640. https://doi.org/10.20944/preprints202406.1640.v1 Meyer, F. J.; Schultz, L. A.; Osmanoglu, B.; Kennedy, J. H.; Jo, M.; Thapa, R. B.; Bell, J. R.; Pradhan, S.; Shrestha, M.; Smale, J.; Kristenson, H.; Kubby, B.; Meyer, T. J. HydroSAR: A Cloud-Based Service for the Monitoring of Inundation Events in the Hindu Kush Himalaya. Preprints 2024, 2024061640. https://doi.org/10.20944/preprints202406.1640.v1

Abstract

The Hindu Kush Himalaya (HKH) is one of the most flood-prone regions in the world, yet heavy cloud cover and limited in-situ observations have hampered efforts to monitor the impact of heavy rainfall, flooding, and inundation during severe weather events. This paper introduces HydroSAR, a Sentinel-1 SAR-based hazard monitoring service that was co-developed with in-region partners to provide year-round, low-latency weather-hazards information across the HKH. The paper describes the end-user focused concept and overall design of the HydroSAR service. It introduces the main processing algorithms behind HydroSAR’s broad product portfolio, which includes qualitative visual layers as well as quantitative products measuring surface water extent and water depth. We summarize the cloud-based implementation of the developed service, which is providing capability to scale automatically with event size. A performance assessment of our quantitative algorithms is described, demonstrating capabilities to map flood extent and water depth at an accuracy of >90% and

Keywords

SAR; hazard monitoring; cloud computing; Sentinel-1; flooding; Hindu Kush Himalaya

Subject

Environmental and Earth Sciences, Remote Sensing

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