Real-time error correction method combined with combination flood forecasting technique for improving the accuracy of flood forecasting

Journal of Hydrology - Tập 521 - Trang 157-169 - 2015
Lu Chen1,2,3, Yongchuan Zhang1, Jianzhong Zhou1, Vijay P. Singh2,3, Shenglian Guo4, Junhong Zhang5
1College of Hydropower & Information Engineering, Huazhong University of Science & Technology, Wuhan 430074, China
2Dept. of Biological and Agricultural Engineering, Texas A&M University, 2117 TAMU, College Station, TX 77843-2117, USA
3Zachry Dept. of Civil Engineering, Texas A&M University, 2117 TAMU, College Station, TX 77843-2117, USA
4State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
5Dept. of Environmental Engineering, South-Central University for Nationalities, Wuhan 430074, China

Tài liệu tham khảo

Abrahart, 2002, Multi-model data fusion for river flow forecasting: an evaluation of six alternative methods based on two contrasting catchments, Hydrol. Earth Syst. Sci., 6, 655, 10.5194/hess-6-655-2002 Ajami, 2006, Multimodel combination techniques for analysis of hydrological simulations: application to distributed model intercomparison project results, J. Hydrometeorol., 7, 755, 10.1175/JHM519.1 Ali, 2010, Rainfall–runoff simulation using a normalized antecedent precipitation index, Hydrol. Sci. J., 55, 266, 10.1080/02626660903546175 Bogner, 2011, Multiscale error analysis, correction, and predictive uncertainty estimation in a flood forecasting system, Water Resour. Res., 47, W07524, 10.1029/2010WR009137 Broerse, 2007, Error correction of rainfall-runoff models with the ARMAsel program, IEEE Trans. Instrum. Meas., 56, 2212, 10.1109/TIM.2007.908252 Chen, 2013, Determination of input for artificial neural networks for flood forecasting using the copula entropy method, J. Hydrol. Eng. Coulibaly, 2005, Improving daily reservoir inflow forecasts with model combination, J. Hydrol. Eng., 10, 91, 10.1061/(ASCE)1084-0699(2005)10:2(91) Descroix, 2002, Evaluation of an antecedent index to model runoff yield in the western Sierra Madre (north-west Mexico), J. Hydrol., 263, 114, 10.1016/S0022-1694(02)00047-1 Fernando, 2011, Use of gene expression programing for multi-model combination of rainfall-runoff models, J. Hydraul. Eng., 17, 975 Georgakakos, 2004, Towards the characterization of streamflow simulation uncertainty through multimodel ensembles, J. Hydrol., 298, 222, 10.1016/j.jhydrol.2004.03.037 Giang, 2010, Calibration and verification of a hydrological model using event data, J. Sci., Earth Sci., 26, 64 Hsu, 2009, A sequential Bayesian approach for hydrologic model selection and prediction, Water Resour. Res., 45, 10.1029/2008WR006824 Koehler, M.A., Linsley, R.K., 1951. Predicting the runoff from storm rainfall. Research Paper no. 34, Weather Bureau, US Dept of Commerce, Washington, USA. Li, 2010, Dynamic control of flood limited water level for reservoir operation by considering inflow uncertainty, J. Hydrol., 391, 124, 10.1016/j.jhydrol.2010.07.011 Liao, W., Lei, X., 2012. Multi-model combination techniques for flood forecasting from the distributed hydrological model easy DHM. In: Li, Z., et al. (Eds.). ISICA, CCIS 316, pp. 396–402. Available at <http://link.springer.com/chapter/10.1007/978-3-642-34289-9_44>. Liu, 2007, Uncertainty in hydrologic modeling: toward an integrated data assimilation framework, Water Resour. Res., 43, W07401, 10.1029/2006WR005756 Ministry of Water Resources (MWR). 2006. Regulation for calculating design flood of water resources and hydropower projects. Chinese Shuili Shuidian Press, Beijing (In Chinese). Ngoc, 2013, Optimizing parameters for two conceptual hydrological models using a genetic algorithm: a case study in the Dau Tieng River Watershed, Vietnam, Jpn. Agric. Res., 47, 85, 10.6090/jarq.47.85 Rose, 1998, A statistical method for evaluating the effects of antecedent rainfall upon runoff: application to the coastal plain of Georgia, J. Hydrol., 211, 168, 10.1016/S0022-1694(98)00234-0 See, 2000, A hybrid multi-model approach to river level forecasting, Hydrol. Sci. J., 45, 523, 10.1080/02626660009492354 Shamseldin, 1997, Methods for combining the outputs of different rainfall runoff models, J. Hydrol., 197, 203, 10.1016/S0022-1694(96)03259-3 Shamseldin, 2007, A comparative study of three neural network forecast combination methods for simulated river flows of different rainfallrunoff models, Hydrol. Sci. J., 52, 896, 10.1623/hysj.52.5.896 Shamseldin, 1999, A real-time combination method for the outputs of different rainfall-runoff models, Hydrol. Sci. J., 44, 895, 10.1080/02626669909492288 Sittner, 1969, Continuous hydrograph synthesis with an API type hydrologic model, Water Resour. Res., 5, 1007, 10.1029/WR005i005p01007 Wu, 2012, Real-time correction of water stage forecast during rainstorm events using combination of forecast errors, Stoch. Environ. Res Risk Assess., 26, 519, 10.1007/s00477-011-0514-4 Xiong, 2001, A non-linear combination of the forecasts of rainfall-runoff models by the first-order Takagi-Sugeno fuzzy system, J. Hydrol., 245, 196, 10.1016/S0022-1694(01)00349-3 Xiong, 2002, Comparison of four updating models for real-time river flow forecasting, Hydrol. Sci. J., 47, 21, 10.1080/02626660209492964 Xu, 2013, Comparison of three global optimization algorithms for calibration of the Xinanjiang model parameters, J. Hydroinform., 15, 174, 10.2166/hydro.2012.053 Zhao, R.J., Zhang, Y.L., Fang, L.R., 1980. The Xinanjiang model. In: Paper Presented at Hydrological Forecasting Proceeding Oxford Symposium, IASH-AISH Publ. no. 129, Washington, DC, pp. 351–356. Zhao, 1992, The Xinanjiang model applied in China, J. Hydrol., 135, 371, 10.1016/0022-1694(92)90096-E