Probabilistic Flood Forecasting Of Ungaged Basins In Nam Ou River Basin Considering Rainfall Uncertainty

The cycle of Hydrology is a complex phenomenon that is affected by deterministic components and random components.The process of hydrology forecasting based on hydrological model is affected by the uncertainty of input data,model structure and model parameters,and the uncertainty of input data has the greatest influence on the simulation results.It is very important to analyze the probability distribution of input data to improve the prediction accuracy of hydrological model.In this paper,the time-varying-gain model(TVGM)of two water source is used to discuss the problem of probabilistic flood forecasting considering the input uncertainty for the needs of hydrological forecasting in Nam Ou River.The main conclusions are as follows:(1)The Sobol method is used to analyze the parameter sensitivity of the TVGM model of two water source,and the sensitive parameters of the runoff simulation are selected as the main transplant parameters in the process of parameters regionalization.The TVGM model is calibrated and validated by the rainfall and runoff data of the seventh power station,Nanlian River and Namba River Basin.The efficiency coefficients of the model are above 0.7,indicating that the TVGM in the Nam Ou River is applicable.(2)Based on the analysis of the three indexes of rainfall stations density,rainfall station uniformity and annual variation of runoff coefficient in the Nanpa River and Nanya River Basin,it is found that the average rainfall process of the two basins is not on behalf of the real rainfall process,so the two basins are regarded as ungaged basins.In order to obtain the parameters of the two basins,the regional similarity method is studied,and the validity of the method is completed by cross validation.Finally,the model parameters of Nanpa River and Nanya River Basin are obtained by this method.(3)In order to analyze the influence of the uncertainty of rainfall input on the hydrological forecasting process,the average rainfall correction method based on the system dynamic response curve is used to obtain the real average rainfall of ten floods in the Nanpa River Basin and eight floods in the Nanya River Basin,and the frequency distribution of the ratio of rainfall reduction is statisticed in different sections.Finally,the probabilistic flood forecasting of Nanpa River and Nanya River Basin is implemented to consider the uncertainties of average rainfall in different intervals according to the frequency distribution of corrected proportion.the reliability and rationality of the method is analyzed by comparing the probability flood forecasting results to the results of the relative error of the rainfall in the[-1,1].This method is proved to be feasible and effective by analyzing the results of flood forecasting considering the uncertainty of rainfall input in ungaged basinsin Nam Ou River.The probabilitic flood forecasting based on the distribution of the rainfall error obtained in this paper is better than the deterministic flood forecasting and even is better than result of the uniform distribution error.A method to obtain the distribution of a priori rainfall error by comparing the real average rainfall and the measured average rainfall is presented in this paper.It can be used as a way to obtain the priori distribution of rainfall in the probabilistic flood forecasting and uncertainty analysis method.