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     Research Journal of Applied Sciences, Engineering and Technology


Integrated Combination of the Multi Hydrological Models by Applying the Least Square Method

Muhammad Tayyab, Jianzhong Zhou, Xiaofan Zeng, Na Zhao and Rana Adnan
School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, China
Research Journal of Applied Sciences, Engineering and Technology  2015  1:107-111
http://dx.doi.org/10.19026/rjaset.10.2561  |  © The Author(s) 2015
Received: January ‎21, ‎2015  |  Accepted: February ‎14, ‎2015  |  Published: May 10, 2015

Abstract

Different hydrological models show different outputs for specific catchment, thus combining all the models in suitable way is very important to improve the forecast. To solve the issue, researchers have applied different techniques which ranges from simple inter-comparison of different hydrological models to extended combination of hydrological models. The aim of this research is to find a suitable and applicable combination technique, by applying least square method to get more valuable flood forecasting results for the Jinshajiang River basin. The combination forecast has been compared with the results of the three models individually, based on the comparison of the simulation outputs and the Nash-Sutcliffe efficiency and Correlation coefficient. The result showed that the performance of combine system of three conceptual hydrological models including Xin’anjiang model, Antecedent Precipitation Index (API) model and Tank model is much more reliable as compared to their individual performance.

Keywords:

Combination, flood forecasting, hydrological model, least square method,


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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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