Articles | Volume 20, issue 7
Hydrol. Earth Syst. Sci., 20, 2649–2667, 2016
https://doi.org/10.5194/hess-20-2649-2016
Hydrol. Earth Syst. Sci., 20, 2649–2667, 2016
https://doi.org/10.5194/hess-20-2649-2016

Research article 08 Jul 2016

Research article | 08 Jul 2016

A retrospective streamflow ensemble forecast for an extreme hydrologic event: a case study of Hurricane Irene and on the Hudson River basin

Firas Saleh et al.

Data sets

North American Regional Reanalysis (NARR) F. Mesinger, G. DiMego, E. Kalnay, K. Mitchell, P. C. Shafran, W. Ebisuzaki, D. Jović, J. Woollen, E. Rogers, E. H. Berbery, M. B. Ek, Y. Fan, R. Grumbine, W. Higgins, H. Li, Y. Lin, G. Manikin, D> Parrish, and W. Shi http://nomads.ncdc.noaa.gov/data.php?name=access#narr_datasets

Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) W. Scharffenberg http://www.hec.usace.army.mil/software/hec-hms/downloads.aspx

HEC-GeoHMS M. Fleming and J. Doan http://www.hec.usace.army.mil/software/hec-geohms/downloads.aspx

USGS National Elevation Dataset (NED) D. Gesch, M. Oimoen, S. Greenlee, C. Nelson, M. Steuck, and D. Tyler http://www.ned.usgs.gov/

Land surface cover from US Department of Agriculture National Resource Conservation Service (NRCS) USDA https://gdg.sc.egov.usda.gov/

Soil data from the State Soil Geographic Database (STATSGO) D. A. Miller and R. A. White http://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcs142p2_053629

Land use from USGS National Land Cover Dataset (NLCD) C. H. Homer, J. A. Fry, and C. A. Barnes http://www.mrlc.gov/finddata.php

R dataRetrieval package R. M. Hirsch and L. A. De Cicco https://github.com/USGS-R/dataRetrieval

R lfstat package D. Koffler and G. Laaha https://cran.r-project.org/web/packages/lfstat/index.html

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Short summary
An operational framework was implemented to generate retrospective ensemble streamflow forecasts for an extreme hydrological event, Hurricane Irene. The implications of this work benefit streamflow forecast efforts and can be used for numerous applications, such as forecasting the water resources variability, predicting fate of water quality and climate change scenarios. Socio-economic analysis may be used to weigh on how improved forecasts prevent life loss and minimize property damage.