Zhao, L., Q. Duan, J. Schaake, A. Ye, and J. Xia, 2011: A hydrologic post-processor for ensemble streamflow predictions. Adv. Geosci., 29, 51-59. Ye, A., Q. Duan, X. Yuan, E. F. Wood, and J. Schaake, 2014: Hydrologic post-processing of MOPEX streamflow simulations. J. Hydrol. , 508, 147-156. Ye, A., Q. Duan, J. Schaake,et al., 2015: Post‐processing of ensemble forecasts in low‐flow period. Hydrological processes, 29(10), 2438-2453.
Firstly apply normal quantile transform (NQT), then fit a general linear regression model to the multiple-day observed and simulated streamflow. Given new streamflow simulations, the conditional distribution of observations can be obtained in forms of ensemble forecasts.The method can be applied to remove the bias in raw streamflow simulations.
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LinksNational Tibetan Plateau Data Center