Case Studies
Aug 17, 2015

New Multisite Cascading Calibration Approach for Hydrological Models: Case Study in the Red River Basin Using the VIC Model

Publication: Journal of Hydrologic Engineering
Volume 21, Issue 2

Abstract

A novel multisite cascading calibration (MSCC) approach using the shuffled complex evolution–University of Arizona (SCE-UA) optimization method, developed at the University of Arizona, was employed to calibrate the variable infiltration capacity (VIC) model in the Red River Basin. Model simulations were conducted at 35 nested gauging stations. Compared with simulated results using a priori parameters, single-site calibration can improve VIC model performance at specific calibration sites; however, improvement is still limited in upstream locations. The newly developed MSCC approach overcomes this limitation. Simulations using MSCC not only utilize all of the available streamflow observations but also better represent spatial heterogeneities in the model parameters. Results indicate that MSCC largely improves model performance by decreasing the number of stations with negative Nash-Sutcliffe coefficient of efficiency (NSCE) values from 69% (66%) for a priori parameters to 37% (34%) for single-site calibration to 3% (3%) for MSCC, and by increasing the number of stations with NSCE values larger than 0.5 from 9% (9%), to 23% (23%) to 34% (29%) during calibration (and validation) periods across all sites.

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Acknowledgments

This study was supported by the USGS South Central Climate Science Center at the University of Oklahoma through Grant #G13AC00386, “Impacts of Climate Change on Flows in the Red River Basin.” Partial support for the second author was provided by the Disaster Relief Appropriations Act of 2013 (P.L. 113-2), which funded NOAA research grant NA14OAR4830100. The authors also appreciate Mr. Cody Hudson of INTERA for sharing the script to download the USGS observed streamflow data and Mr. Manabendra Saharia and Mr. Humberto Vergara for peak flow qualification of USGS streamflow stations. The authors gratefully acknowledge the editor, associate editor, and anonymous reviewers for their valuable and constructive comments on this manuscript.

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Journal of Hydrologic Engineering
Volume 21Issue 2February 2016

History

Received: Dec 23, 2014
Accepted: Jun 26, 2015
Published online: Aug 17, 2015
Discussion open until: Jan 17, 2016
Published in print: Feb 1, 2016

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Xianwu Xue, Ph.D. [email protected]
Postdoctoral Research Fellow, School of Civil Engineering and Environmental Sciences, Univ. of Oklahoma, Norman, OK 73019; and Hydrometeorology and Remote Sensing Laboratory and Advanced Radar Research Center, National Weather Center, Norman, OK 73072 (corresponding author). E-mail: [email protected]
Ke Zhang, Ph.D.
Research Scientist, Cooperative Institute for Mesoscale Meteorological Studies, Univ. of Oklahoma, Norman, OK 73072.
Yang Hong, Ph.D. [email protected]
Professor, School of Civil Engineering and Environmental Sciences, Univ. of Oklahoma, Norman, OK 73019; and Dept. of Hydraulic Engineering, Tsinghua Univ., Beijing 100084, China. E-mail: [email protected]
Jonathan J. Gourley, Ph.D.
Research Hydrometeorologist, NOAA/National Severe Storms Laboratory, Norman, OK 73072.
Wayne Kellogg
Environmental Engineer, Chickasaw Nation Division of Commerce, Ada, OK 74820.
Renee A. McPherson, Ph.D.
Associate Professor, Dept. of Geography and Environmental Sustainability, Univ. of Oklahoma, Norman, OK 73019; and University Co-director, South Central Climate Science Center, Norman, OK 73072.
Zhanming Wan
Ph.D. Candidate, School of Civil Engineering and Environmental Sciences, Univ. of Oklahoma, Norman, OK 73019; and Hydrometeorology and Remote Sensing Laboratory and Advanced Radar Research Center, National Weather Center, Norman, OK 73072.
Barney N. Austin, Ph.D.
Aqua Strategies, Dripping Springs, TX 78620.

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