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Application of a Coupled Land Surface-Hydrological Model to Flood Simulation in the Huaihe River Basin of China |
LI Min1,2, LIN Zhao-Hui1, YANG Chuan-Guo4,SHAO Quan-Xi5, |
1International Center for Climate and Environment Sciences (ICCES), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
2University of the Chinese Academy of Sciences, Beijing 100049, China
3Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China
4Hohai University, Nanjing 210098, China
5Commonweath Scientific and Industrial Research Organization (CSIRO), Computational Informatics, WA 6014, Australia |
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Abstract A hydrograph simulation in the Huaihe River Basin (HRB) was investigated using two different models: a coupled land surface hydrological model (CLHMS), and a large-scale hydrological model (LSX-HMS). The NCEP-NCAR reanalysis dataset and observed precipitation data were used as meteorological inputs. The simulation results from both models were compared in terms of flood processes forecasting during high flow periods in the summers of 2003 and 2007, and partial high flow periods in 2000. The comparison results showed that the simulated streamflow by CLHMS model agreed well with the observations with Nash-Sutcliffe coefficients larger than 0.76, in both periods of 2000 at Lutaizi and Bengbu stations in the HRB, while the skill of the LSX-HMS model was relatively poor. The simulation results for the high flow periods in 2003 and 2007 suggested that the CLHMS model can simulate both the peak time and intensity of the hydrological processes, while the LSX-HMS model provides a delayed flood peak. These results demonstrated the importance of considering the coupling between the land surface and hydrological module in achieving better predictions for hydrological processes, and CLHMS was proven to be a promising model for future applications in flood simulation and forecasting.
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Received: 13 May 2014
Revised: 17 May 2014
Accepted: 19 May 2014
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Corresponding Author:
LIN Zhao-Hui
E-mail: lzh@mail.iap.ac.cn
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