Evaluation of the HYMOD model for rainfall runoff simulation using the GLUE method

被引:0
作者
Quan, Zhongxian [1 ]
Teng, Jianbiao [2 ]
Sun, Wenchao [1 ,3 ]
Cheng, Tao [1 ]
Zhang, Jie [1 ]
机构
[1] Beijing Normal Univ, Coll Water Sci, Beijing 100875, Peoples R China
[2] South China Inst Environm Sci, Guangzhou 510655, Guangdong, Peoples R China
[3] Joint Ctr Global Change Studies, Beijing 100875, Peoples R China
来源
REMOTE SENSING AND GIS FOR HYDROLOGY AND WATER RESOURCES | 2015年 / 368卷
关键词
Yalong River basin; HYMOD; GLUE; river discharge; HYDROLOGICAL MODELS; CALIBRATION;
D O I
暂无
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Yalong River is the third largest base of the 13 hydropower bases in China. Long-time series of river discharge records are essential for the design of hydropower stations and water resource management. The existing monitoring network is scarce and cannot provide sufficient hydrological information for the basin. Rainfall runoff models are popular tools for extending hydrological data in both space and time. In this paper, the feasibility of applying a conceptual rainfall runoff model, HYdrological MODel (HYMOD), to the upper Yalong River basin was evaluated. The generalized likelihood uncertainty estimation (GLUE) was employed for model calibration and uncertainty analysis. The results show that simulated discharge matches the observations satisfactorily, indicating the hydrological model performs well and the application of HYMOD to estimate long time-series of river discharge in the study area is feasible.
引用
收藏
页码:180 / 185
页数:6
相关论文
共 13 条
[1]  
Ahn C.-H., 1994, Journal of the Japan Society of Photogrammetry and Remote Sensing, V33, P12, DOI [DOI 10.4287/JSPRS.33.2_12, 10.4287/jsprs.33.2_12]
[2]   THE FUTURE OF DISTRIBUTED MODELS - MODEL CALIBRATION AND UNCERTAINTY PREDICTION [J].
BEVEN, K ;
BINLEY, A .
HYDROLOGICAL PROCESSES, 1992, 6 (03) :279-298
[3]   Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology [J].
Beven, K ;
Freer, J .
JOURNAL OF HYDROLOGY, 2001, 249 (1-4) :11-29
[4]   Uncertainty assessment of integrated distributed hydrological models using GLUE with Markov chain Monte Carlo sampling [J].
Blasone, Roberta-Serena ;
Madsen, Henrik ;
Rosbjerg, Dan .
JOURNAL OF HYDROLOGY, 2008, 353 (1-2) :18-32
[5]   THE PROBABILITY-DISTRIBUTED PRINCIPLE AND RUNOFF PRODUCTION AT POINT AND BASIN SCALES [J].
MOORE, RJ .
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES, 1985, 30 (02) :273-297
[6]   Modelling hydrologic responses in a small forested catchment (Panola Mountain, Georgia, USA): a comparison of the original and a new dynamic TOPMODEL [J].
Peters, NE ;
Freer, J ;
Beven, K .
HYDROLOGICAL PROCESSES, 2003, 17 (02) :345-362
[7]   Towards improving river discharge estimation in ungauged basins: calibration of rainfall-runoff models based on satellite observations of river flow width at basin outlet [J].
Sun, W. C. ;
Ishidaira, H. ;
Bastola, S. .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 2010, 14 (10) :2011-2022
[8]   Calibration of hydrological models in ungauged basins based on satellite radar altimetry observations of river water level [J].
Sun, Wenchao ;
Ishidaira, Hiroshi ;
Bastola, Satish .
HYDROLOGICAL PROCESSES, 2012, 26 (23) :3524-3537
[9]   Hydrologic response to climatic variability in a Great Lakes Watershed: A case study with the SWAT model [J].
Wu, Kangsheng ;
Johnston, Carol A. .
JOURNAL OF HYDROLOGY, 2007, 337 (1-2) :187-199
[10]  
Xuan Yu, 2008, J CHINA HYDROLOGY, V3, P49