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Mathematical Problems in Engineering
Volume 2017, Article ID 7919324, 19 pages
https://doi.org/10.1155/2017/7919324
Research Article

Automatic Calibration of an Unsteady River Flow Model by Using Dynamically Dimensioned Search Algorithm

1Department of Civil Engineering, National Taiwan University, Taipei City 10617, Taiwan
2Department of Civil and Water Resources Engineering, National Chiayi University, Chiayi City 60004, Taiwan
3MWH Americas Incorporated, Taiwan Branch, Taipei City 10549, Taiwan

Correspondence should be addressed to Nan-Jing Wu; wt.ude.uycn.liam@uwjn

Received 7 July 2016; Revised 19 October 2016; Accepted 18 December 2016; Published 1 February 2017

Academic Editor: Paolo Lonetti

Copyright © 2017 Fu-Ru Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Dynamically dimensioned search (DDS) algorithm is a new-type heuristic algorithm which was originally developed by Tolson and Shoemaker in 2007. In this study, the DDS algorithm is applied to automate the calibration process of an unsteady river flow model in the Tamsui River basin, which was developed by Wu et al. (2007). Data observed during 2012 and 2013 are collected in this study. They are divided into three groups, one for the test case, one for calibration, and one for the validation. To prove that the DDS algorithm is capable of solving this research problem and the convergence property, a test simulation is first performed. In the studied area, the whole river systems are divided into 20 reaches, and each reach has two parameters ( and ) to be determined. These two parameters represent resistance coefficients for low- and high-water conditions. Comparing with another algorithm, it is shown that the DDS algorithm has not only improved on the efficiency but also increased the stability of calibrated results.