Research Article
No access
Published Online: 7 May 2010

Evolutionary Modeling for Streamflow Forecasting with Minimal Datasets: A Case Study in the West Malian River, China

Publication: Environmental Engineering Science
Volume 27, Issue Number 5

Abstract

A large dataset is generally needed when modeling hydrological processes. However, for developing countries such as China, datasets are often unavailable in remote areas. An attempt to apply a novel genetic programming (GP) technique was made to model the relationship between streamflow of the West Malian River and the impact of climate change in the northeastern part of China. Available annual streamflow and climatic data were used for training and testing of the GP model. Data from the years between 1982 and 2002 were used for automatic selection of the model relationship. Prediction of the model was undertaken for the period 2003–2006 and the results were compared with measured data. Predicted annual streamflow of the West Malian River agreed with measured data to an acceptable degree of accuracy even with a small amount of dataset. For comparison, a multilayer perceptron method with back propagation algorithm, a gray theory model, and a multiple linear regression model were selected to conduct the prediction with the same dataset. Results showed that the performance of GP method was generally better than other statistical methods such as multilayer perceptron, gray theory model, and multiple linear regression model. Further, the results also showed that the GP method is a useful tool for water resource management, especially in developing countries, to evaluate the potential impacts of climate change on the streamflow when large datasets are unavailable.

Get full access to this article

View all available purchase options and get full access to this article.

Information & Authors

Information

Published In

cover image Environmental Engineering Science
Environmental Engineering Science
Volume 27Issue Number 5May 2010
Pages: 377 - 385

History

Published online: 7 May 2010
Published in print: May 2010
Accepted: 7 March 2010
Received: 1 March 2009

Permissions

Request permissions for this article.

Authors

Affiliations

Qingwei Ni
School of Environmental and Biological Science and Technology, Dalian University of Technology, Dalian, China.
College of Environmental & Biological Engineering, Shenyang University of Chemical Technology, Shenyang, China.
Renzhen Ye
Department of Mathematics, Agricultural University of Huazhong, Wuhan, China.
Fenglin Yang
School of Environmental and Biological Science and Technology, Dalian University of Technology, Dalian, China.
Muttucumaru Sivakumar
School of Civil, Mining, and Environmental Engineering, University of Wollongong, Wollongang, New South Wales, Australia.

Notes

*
Corresponding author: College of Environmental & Biological Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China. Phone: 86-24-81839602; Fax: 86-24-89389166; E-mail: [email protected]

Metrics & Citations

Metrics

Citations

Export citation

Select the format you want to export the citations of this publication.

View Options

Access content

To read the fulltext, please use one of the options below to sign in or purchase access.

Society Access

If you are a member of a society that has access to this content please log in via your society website and then return to this publication.

Restore your content access

Enter your email address to restore your content access:

Note: This functionality works only for purchases done as a guest. If you already have an account, log in to access the content to which you are entitled.

View options

PDF/EPUB

View PDF/EPUB

Figures

Tables

Media

Share

Share

Copy the content Link

Share on social media

Back to Top