Soil and Water Research

Influence of rainfall data on the uncertainty of flood simulation

DOI:10.17221/156/2015-SWRCitation:Walega A., Ksiazek L.: (2016): Influence of rainfall data on the uncertainty of flood simulation. Soil & Water Res., 11: 277-284.
fulltext

The aim of this paper was to determine the influence of factors related to rainfall data on the uncertainty flood simulation. The calculations were based on a synthetic unit hydrograph NRCS-UH. Simulation uncertainty was determined by means of GLUE method. The calculations showed that in the case of a catchment with limited meteorological data, it is better to use rainfall data from a single station located within the catchment, than to take into account the data from higher number of stations, but located outside the catchment area. The parameters of the NRCS-UH model (curve number and initial abstraction) were found to be less variable when the input contained rainfall data from a single rainfall station. It was also manifested by a lower uncertainty of the simulation results for the variant with one rainfall station, as compared to the variant based on the use of averaged rainfall in the catchment.

References
Anctil François, Lauzon Nicolas, Andréassian Vazken, Oudin Ludovic, Perrin Charles (2006): Improvement of rainfall-runoff forecasts through mean areal rainfall optimization. Journal of Hydrology, 328, 717-725 doi:10.1016/j.jhydrol.2006.01.016
 
Bárdossy A., Das T. (2008): Influence of rainfall observation network on model calibration and application. Hydrology and Earth System Sciences, 12, 77-89 doi:10.5194/hess-12-77-2008
 
Bates Bryson C., Campbell Edward P. (2001): A Markov Chain Monte Carlo Scheme for parameter estimation and inference in conceptual rainfall-runoff modeling. Water Resources Research, 37, 937-947 doi:10.1029/2000WR900363
 
Bedient P.B., Huber W.C., Vieux B.E. (2013): Hydrology and Floodplain Analysis. Harlow, Pearson.
 
Beven Keith, Binley Andrew (1992): The future of distributed models: Model calibration and uncertainty prediction. Hydrological Processes, 6, 279-298 doi:10.1002/hyp.3360060305
 
Blasone R.-S. (2007): Parameter Estimation and Uncertainty Assessment in Hydrological Modelling. [Ph.D. Thesis.] Lyngby, Institute of Environment & Resources, Technical University of Denmark.
 
Blasone R.-S., Vrugt J.A., Madsen H., Rosbjerg D., Robinson B.A., Zyvoloski G.A. (2008): Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling. Advances in Water Resources, 31: 630−648.
 
Bormann H. (2006): Impact of spatial data resolution on simulated catchment water balances and model performance of the multi-scale TOPLATS model. Hydrology and Earth System Sciences, 10, 165-179 doi:10.5194/hess-10-165-2006
 
Butts Michael B., Payne Jeffrey T., Kristensen Michael, Madsen Henrik (2004): An evaluation of the impact of model structure on hydrological modelling uncertainty for streamflow simulation. Journal of Hydrology, 298, 242-266 doi:10.1016/j.jhydrol.2004.03.042
 
Chen Xi, Yang Tao, Wang Xiaoyan, Xu Chong-Yu, Yu Zhongbo (2013): Uncertainty Intercomparison of Different Hydrological Models in Simulating Extreme Flows. Water Resources Management, 27, 1393-1409 doi:10.1007/s11269-012-0244-5
 
Cunderlik J.M., Simonovic S.P. (2004): Calibration, Verification and Sensitivity Analysis of the HEC-HMS Hydrologic Model. Report IV. CFCAS Project: Assessment of Water Resources Risk and Volunerability to Changing Climatic Conditions. Ontario, University of Western.
 
Diaz-Ramirez Jairo N., McAnally William H., Martin James L. (2012): Sensitivity of Simulating Hydrologic Processes to Gauge and Radar Rainfall Data in Subtropical Coastal Catchments. Water Resources Management, 26, 3515-3538 doi:10.1007/s11269-012-0088-z
 
Jin Xiaoli, Xu Chong-Yu, Zhang Qi, Singh V.P. (2010): Parameter and modeling uncertainty simulated by GLUE and a formal Bayesian method for a conceptual hydrological model. Journal of Hydrology, 383, 147-155 doi:10.1016/j.jhydrol.2009.12.028
 
Kovář Pavel, Hrabalíková M., Neruda M., Neruda R., Šrejber J., Jelínková A., Bačinová H. (): Choosing an appropriate hydrological model for rainfall-runoff extremes in small catchments. Soil and Water Research, 10, 137-146 doi:10.17221/16/2015-SWR
 
Lü Haishen, Hou Ting, Horton Robert, Zhu Yonghua, Chen Xi, Jia Yangwen, Wang Wen, Fu Xiaolei (2013): The streamflow estimation using the Xinanjiang rainfall runoff model and dual state-parameter estimation method. Journal of Hydrology, 480, 102-114 doi:10.1016/j.jhydrol.2012.12.011
 
Moriasi D.N., Arnold J.G., Van Liew M.W., Bingner R.L., Harmel R.D., Veith T.L. (2007): Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. American Society of Agricultural and Biological Engineers, 50: 885–900.
 
Nash J.E., Sutcliffe J.V. (1970): River flow forecasting through conceptual models part I — A discussion of principles. Journal of Hydrology, 10, 282-290 doi:10.1016/0022-1694(70)90255-6
 
USACE (2008): Hydrologic Modelling System HEC-HMS User’s Manual. Davis, USACE.
 
USDA (1986): Urban Hydrology for Small Watershed. Technical Release 55. Washington, USDA.
 
Wu Simon, Li Jonathan, Huang G. H. (2008): Characterization and Evaluation of Elevation Data Uncertainty in Water Resources Modeling with GIS. Water Resources Management, 22, 959-972 doi:10.1007/s11269-007-9204-x
 
XIONG LIHUA, WAN MIN, WEI XIAOJING, O'CONNOR KIERAN M. (2009): Indices for assessing the prediction bounds of hydrological models and application by generalised likelihood uncertainty estimation / Indices pour évaluer les bornes de prévision de modèles hydrologiques et mise en œuvre pour une estimation d'incertitude par vraisemblance généralisée. Hydrological Sciences Journal, 54, 852-871 doi:10.1623/hysj.54.5.852
 
Xu Chong-yu, Tunemar Liselotte, Chen Yongqin David, Singh V.P. (2006): Evaluation of seasonal and spatial variations of lumped water balance model sensitivity to precipitation data errors. Journal of Hydrology, 324, 80-93 doi:10.1016/j.jhydrol.2005.09.019
 
fulltext