A time-space varying distributed unit hydrograph (TS-DUH) for operational flash flood forecasting using publicly-available datasets

• Published in: Journal of hydrology (Amsterdam) Vol. 642; p. 131785
• Main Authors: Hu, Ying, Wu, Huan, Alfieri, Lorenzo, Gu, Guojun, Yilmaz, Koray K., Li, Chaoqun, Jiang, Lulu, Huang, Zhijun, Chen, Weitian, Wu, Wei, Han, Qinzhe
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.10.2024
• Subjects: Flash flood; Geomorphic unit hydrograph; GFMS; Global flash flood monitoring; Hydrological response; Hydrological response; Flash flood; Global flash flood monitoring; GFMS; Geomorphic unit hydrograph
• ISSN: 0022-1694
• DOI: 10.1016/j.jhydrol.2024.131785

•A TS-DUH is proposed to integrate with a distributed hydrological model (DRIVE) for flash flood forecasting.•DRIVE-Runoff driven TS-DUH outperforms SCS-CN models in simulating streamflow and flash flood event detection.•The Global Flood Monitoring System (GFMS)-driven TS-DUH outperforms the original GFMS. Although flash floods originate in upstream (headwater) catchments causing hazards locally, they often occur at short time scales and affect widely while relatively small size catchments respond to intense rainfall systems. Due to the heavy cost of computing and parameterization, high resolution spatially distributed hydrological models are not effectively deployed for global or large-scale flash flood forecasting. This research proposes a Time-Space varying Distributed Unit Hydrograph (TS-DUH) based on publicly-available data for efficient global scale flash flood forecasting. TS-DUH estimates the runoff travel time (and flow velocity) from each location to the catchment outlet based on topographic and hydroclimatic characteristics, while it delineates the runoff-drainage process by emphasizing the heterogeneous and dynamic runoff contribution corresponding to rainfall and soil moisture variations. The excess rainfall is estimated by two methods: the Soil Conservation Service’s (SCS) curve (CN-Runoff), and the widely used Global Flood Monitoring System (GFMS) which provides both long-term (2000-present) well-archived and real-time online global runoff (GFMS-Runoff) prediction based on a distributed hydrological model. TS-DUH is first validated based on 6,324 flash flood events from 281 small-to-medium-sized catchments broadly distributed across the CONUS, using “perfect” precipitation input (i.e., NLDAS-2 for this study). TS-DUH calibrated with GFMS-Runoff shows better performance than using CN-Runoff, with a probability of detection (POD) value of 0.9 for all the events and 71% of them having a KGE metric above 0.5. More importantly, with the real-time satellite rainfall-driven GFMS-Runoff, the long-term (2003–2020) TS-DUH simulation shows better performance than GFMS, indicating promising value in global flash flood prediction of the TS-DUH-integrated GFMS.