DOI: 10.5194/hess-20-2649-2016
Scopus记录号: 2-s2.0-84978284925
论文题名: A retrospective streamflow ensemble forecast for an extreme hydrologic event: A case study of Hurricane Irene and on the Hudson River basin
作者: Saleh F ; , Ramaswamy V ; , Georgas N ; , Blumberg A ; F ; , Pullen J
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2016
卷: 20, 期: 7 起始页码: 2649
结束页码: 2667
语种: 英语
Scopus关键词: Climate models
; Floods
; Hurricanes
; Hydrology
; Risk assessment
; Rivers
; Stream flow
; Watersheds
; Atmospheric reanalysis
; Deterministic forecasts
; Ensemble forecast systems
; Extreme hydrological events
; Hydrologic prediction
; Hydrological modeling
; National centers for environmental predictions
; Weather prediction model
; Forecasting
; discharge
; ensemble forecasting
; flood damage
; flooding
; GIS
; hazard assessment
; Hurricane Irene 2011
; hydrological hazard
; hydrological modeling
; hydrological response
; risk assessment
; streamflow
; weather forecasting
; Hudson Basin
; United States
英文摘要: This paper investigates the uncertainties in hourly streamflow ensemble forecasts for an extreme hydrological event using a hydrological model forced with short-range ensemble weather prediction models. A state-of-the art, automated, short-term hydrologic prediction framework was implemented using GIS and a regional scale hydrological model (HEC-HMS). The hydrologic framework was applied to the Hudson River basin ( ~ 36 000 km2) in the United States using gridded precipitation data from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) and was validated against streamflow observations from the United States Geologic Survey (USGS). Finally, 21 precipitation ensemble members of the latest Global Ensemble Forecast System (GEFS/R) were forced into HEC-HMS to generate a retrospective streamflow ensemble forecast for an extreme hydrological event, Hurricane Irene. The work shows that ensemble stream discharge forecasts provide improved predictions and useful information about associated uncertainties, thus improving the assessment of risks when compared with deterministic forecasts. The uncertainties in weather inputs may result in false warnings and missed river flooding events, reducing the potential to effectively mitigate flood damage. The findings demonstrate how errors in the ensemble median streamflow forecast and time of peak, as well as the ensemble spread (uncertainty) are reduced 48 h pre-event by utilizing the ensemble framework. The methodology and implications of this work benefit efforts of short-term streamflow forecasts at regional scales, notably regarding the peak timing of an extreme hydrologic event when combined with a flood threshold exceedance diagram. Although the modeling framework was implemented on the Hudson River basin, it is flexible and applicable in other parts of the world where atmospheric reanalysis products and streamflow data are available. © Author(s) 2016.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78801
Appears in Collections: 气候变化事实与影响
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作者单位: Stevens Institute of Technology, Davidson Laboratory, Department of Civil, Environmental and Ocean Engineering, Hoboken, NJ, United States
Recommended Citation:
Saleh F,, Ramaswamy V,, Georgas N,et al. A retrospective streamflow ensemble forecast for an extreme hydrologic event: A case study of Hurricane Irene and on the Hudson River basin[J]. Hydrology and Earth System Sciences,2016-01-01,20(7)