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Evaluating Multi-Scale Flow Predictions for the Connecticut River Basin | OMICS International | Abstract
ISSN: 2157-7587

Hydrology: Current Research
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Research Article

Evaluating Multi-Scale Flow Predictions for the Connecticut River Basin

Muhammet Omer Dis1, Emmanouil Anagnostou1,*, Flamig Zac2, Humberto Vergara2 and Yang Hong2
1Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut, USA
2School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, Oklahoma, USA
Corresponding Author : Emmanouil Anagnostou
Civil and Environmental Engineering
Tel: 860-486-6806
E-mail: [email protected]
Received June 09, 2015; Accepted June 29, 2015; Published July 03, 2015
Citation: Omer Dis M, Anagnostou E, Zac F, Vergara H, Hong Y (2015) Evaluating Multi-Scale Flow Predictions for the Connecticut River Basin. Hydrol Current Res 6:208. doi:10.4172/2157-7587.1000208
Copyright: © 2015 Omer Dis M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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This case study evaluates a computationally efficient distributed hydrological model, named Coupled Routing and Excess Storage (CREST), for flood modeling of basins in the Connecticut River Basin (CRB). Simulation of discharges is performed by forcing CREST with a long record (eight years) of high resolution radar-rainfall data and potential evapotranspiration maps derived from the North American Regional Reanalysis. The model performance is evaluated against observed streamflows obtained from United States Geological Survey gauging stations at outlet and interior points of various CRB sub-basins. CREST parameters were calibrated based on a three year record (2005-2007) and validated for the remaining data period (2003-2004 and 2008-2009). The model performance evaluation is based on different metrics, including the Nash-Sutchliffe Coefficient of Efficiency (NSCE), Mean Relative Error (MRE), Root Mean Square Error (RMSE), and Pearson Correlation Coefficient (PCC). The analysis shows that CREST slightly underestimated the peak flows, but exhibited a generally good capability in simulating the stream flow variability for the CRB basins. Specifically, NSCE, MRE, RMSE, and PCC values of hourly flow simulations varied from 0.31 to 0.58, -0.06 to 0.13, 61 to 121 (mm) and 0.60 to 0.83, respectively. At daily time scale the performance metrics exhibited improved values indicating that CREST has sufficient accuracy for long term multi-scale hydrologic simulations.


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