DOI: 10.5194/hess-23-225-2019
论文题名: Stochastic reconstruction of spatio-Temporal rainfall patterns by inverse hydrologic modelling
作者: Grundmann J. ; Hörning S. ; Bárdossy A.
刊名: Hydrology and Earth System Sciences
ISSN: 1027-5606
出版年: 2019
卷: 23, 期: 1 起始页码: 225
结束页码: 237
语种: 英语
Scopus关键词: Catchments
; Floods
; Inverse problems
; Runoff
; Stochastic models
; Stochastic systems
; Storms
; Uncertainty analysis
; Distributed hydrologic model
; Distributed rainfall-runoff models
; Ground-based monitoring
; Hydrologic modelling
; Rainfall - Runoff modelling
; Semi-arid environments
; Spatial interpolation method
; Stochastic reconstruction
; Rain
; catchment
; flash flood
; flood
; flood wave
; gauge
; hydrological modeling
; interpolation
; methodology
; Monte Carlo analysis
; rainfall
; rainfall-runoff modeling
; rainstorm
; reconstruction
; runoff
; spatiotemporal analysis
; stochasticity
英文摘要: Knowledge of spatio-Temporal rainfall patterns is required as input for distributed hydrologic models used for tasks such as flood runoff estimation and modelling. Normally, these patterns are generated from point observations on the ground using spatial interpolation methods. However, such methods fail in reproducing the true spatio-Temporal rainfall pattern, especially in data-scarce regions with poorly gauged catchments, or for highly dynamic, small-scale rainstorms which are not well recorded by existing monitoring networks. Consequently, uncertainties arise in distributed rainfall-runoff modelling if poorly identified spatio-Temporal rainfall patterns are used, since the amount of rainfall received by a catchment as well as the dynamics of the runoff generation of flood waves is underestimated. To address this problem we propose an inverse hydrologic modelling approach for stochastic reconstruction of spatio-Temporal rainfall patterns. The methodology combines the stochastic random field simulator Random Mixing and a distributed rainfall-runoff model in a Monte Carlo framework. The simulated spatio-Temporal rainfall patterns are conditioned on point rainfall data from ground-based monitoring networks and the observed hydrograph at the catchment outlet and aim to explain measured data at best. Since we infer a three-dimensional input variable from an integral catchment response, several candidates for spatio-Temporal rainfall patterns are feasible and allow for an analysis of their uncertainty. The methodology is tested on a synthetic rainfall-runoff event on sub-daily time steps and spatial resolution of 1 km2 for a catchment partly covered by rainfall. A set of plausible spatio-Temporal rainfall patterns can be obtained by applying this inverse approach. Furthermore, results of a real-world study for a flash flood event in a mountainous arid region are presented. They underline that knowledge about the spatio-Temporal rainfall pattern is crucial for flash flood modelling even in small catchments and arid and semiarid environments. © Author(s) 2019. All rights reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/163076
Appears in Collections: 气候变化与战略
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作者单位: Grundmann, J., Technische Universität Dresden, Institute of Hydrology and Meteorology, Dresden, Germany; Hörning, S., University of Queensland, EAIT, Centre for Coal Seam Gas, Brisbane, Australia; Bárdossy, A., Universität Stuttgart, Institute for Modelling Hydraulic and Environmental Systems, Stuttgart, Germany
Recommended Citation:
Grundmann J.,Hörning S.,Bárdossy A.. Stochastic reconstruction of spatio-Temporal rainfall patterns by inverse hydrologic modelling[J]. Hydrology and Earth System Sciences,2019-01-01,23(1)