Research Article | OPEN ACCESS
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
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,
References
-
Abbott, M.B., J.C. Bathurst, J.A. Cunge, P.E. O’Connell and J. Rasmussen, 1986a. An introduction to the European hydrological system-système hydrologique Européen ‘‘SHE’’. 1: History and philosophy of a physically based distributed modelling system. J. Hydrol., 87: 45-59.
CrossRef -
Abbott, M.B., J.C. Bathurst, J.A. Cunge, P.E. O’Connell and J. Rasmussen, 1986b. An introduction to European hydrological system-système hydrologique Européen ‘‘SHE’’, 2: Structure of a physically based distributed modelling system. J. Hydrol., 87: 61-77.
CrossRef -
Bates, J.M. and C.W.J. Granger, 1969. The combination of forecasts. J. Oper. Res. Soc., 20: 451-468.
CrossRef -
Benkhaled, A., B. Remini and M. Mhaiguene, 2004. Influence of antecedent precipitation index on hydrograph shape. In: Webb, B., N. Arnell, C. Onof, N. MacIntyre, R. Gurney and C. Kirby (Eds.), Hydrology: Science and Practice for the 21st Century, Proceeding of the British Hydrological Society International Conference. Imperial College, London, pp: 81-87.
-
Burnash, R.J.C., R.L. Ferrel and R.A. McGuire, 1973. A general streamflow simulation system conceptual modelling for digital computers. Report by the Joint Federal State River Forecasting Center. Sacramento, California, USA.
-
Crawford, N.H. and R.K. Linsley, 1966. Digital simulation in hydrology'stanford watershed model IV. Transportation Research Board of National Academies, Technical Report 39, Department of Civil Engineering, Stanford University. Palo Alto, CA.
-
Descroix, L., J.F. Nouvelot and M. Vauclin, 2002. Evaluation of an antecedent precipitation index to model runoff yield in the western Sierra Madre (north-west Mexico). J. Hydrol., 263(1): 114-130.
CrossRef -
Dickinson, J.P., 1975. Some comments on the combination of forecasts. Oper. Res. Quart., 26(1): 205-210.
CrossRef -
Elhassan, A.M., A. Goto and M. Mizutani, 2001. Combining a tank model with a groundwater model for simulating regional groundwater flow in an alluvial fan. Trans. Jpn. Soc. Irrig. Drain. Reclam. Eng., 215: 21-29.
-
Franchini, M. and G. Galeati, 1997. Comparing several genetic algorithm schemes for the calibration of conceptual rainfall-runoff models. Hydrolog. Sci. J., 42(3): 357-379.
CrossRef -
Galton, F., 1886. Regression towards mediocrity in hereditary stature. J. Anthropol. Inst. Great Britain Ireland, 15: 246-263.
CrossRef -
Kohler, M.A. and R.K. Linsley, 1951. Predicting the Runoff from Storm Rainfall. Department of Commerce, National Oceanic and Atmospheric Administration Weather Bureau, US Weather Bureau Research Paper No. 34, Washington, USA.
-
Newbold, P. and C.W.J. Granger, 1974. J. R. Stat. Soc. Ser. A-G., 137(2): 131-165.
-
Shamseldin, A.Y., K.M. O'Connor and G.C. Liang, 1997. Methods for combining the outputs of different rainfall-runoff models. J. Hydrol., 197: 203-229.
CrossRef -
Sherman, L.K., 1932. Stream flow from rainfall by the unit-graph method. Eng. News-Rec., 108: 501-505.
-
Sugawara, M., I. Watanabe, E. Ozaki and Y. Katsuyama, 1984. Tank model with snow component. Research Notes No. 65, National Research Center for Disaster Prevention, Japan, pp: 1-293.
-
Thompson, P.D., 1977. How to improve accuracy by combining independent forecasts. Mon. Weather Rev., 105(2): 228-229.
CrossRef -
World Meteorological Organization (WMO), 1975. Intercomparison of conceptual models used in operational hydrological forecasting. Operational Hydrological Report No. 7, WMO No. 429.
-
World Meteorological Organization (WMO), 1992. Simulated real-time intercomparison of hydrological models. Operational Hydrological Report No.38, WMO No. 779.
-
Zhao, R.J., 1992. The Xinanjiang model applied in China. J. Hydrol., 135: 371-381.
CrossRef -
Zhao, R.J., Y.L. Zhang and L.R. Fang, 1980. The Xinanjiang model, Hydrological Forecasting. Proceeding of the Oxford Symposium IASH, 129: 351-356.
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.
|
|
![](http://www.maxwellsci.com/images/RJASET-maxw.jpg) |
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
![Submit Manuscript](../images/sub.jpg) |
Information |
|
|
|
Sales & Services |
|
|
|