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Modeling River Runoff Temporal Behavior through a Hybrid Causal–Hydrological (HCH) Method
Open AccessArticle

An Ensemble Flow Forecast Method Based on Autoregressive Model and Hydrological Uncertainty Processer

School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
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Water 2020, 12(11), 3138; https://doi.org/10.3390/w12113138
Received: 7 October 2020 / Revised: 31 October 2020 / Accepted: 4 November 2020 / Published: 9 November 2020
(This article belongs to the Section Hydrology and Hydrogeology)
In the process of hydrological forecasting, there are uncertainties in data input, model parameters, and model structure, which cause a deterministic forecasting to fail to provide useful risk information to decision-makers. Therefore, the study of ensemble forecasting and the analysis of hydrological uncertainty are of great significance to guide the actual operation of reservoirs in the flood season. This study proposed a Bayesian ensemble forecast method, comprising of a Gaussian mixture model (GMM), a hydrological uncertainty processer (HUP), and an Autoregressive (AR) model. First, the GMM is selected as the marginal distribution function to estimate the uncertainty of observed and modelled data. Next, the AR model is used to correct the forecast rainfall data. Then, a modified HUP is used to deal with the uncertainty of hydrological model structure and rainfall input data. In the end, the ensemble flow forecast results are composed of the expected values of the posterior distribution obtained by HUP under different rainfall conditions. Taking the Three Gorges Reservoir (TGR) as a case study, the ensemble flow prediction in the forecast period is calculated by using the above method. Results show that the method proposed in this paper can improve the accuracy of runoff forecasts and reduce the uncertainty of the hydrological forecast. View Full-Text
Keywords: ensemble flow forecast; autoregressive model; hydrological uncertainty processer; Three Gorges Reservoir ensemble flow forecast; autoregressive model; hydrological uncertainty processer; Three Gorges Reservoir
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MDPI and ACS Style

Yang, X.; Zhou, J.; Fang, W.; Wang, Y. An Ensemble Flow Forecast Method Based on Autoregressive Model and Hydrological Uncertainty Processer. Water 2020, 12, 3138. https://doi.org/10.3390/w12113138

AMA Style

Yang X, Zhou J, Fang W, Wang Y. An Ensemble Flow Forecast Method Based on Autoregressive Model and Hydrological Uncertainty Processer. Water. 2020; 12(11):3138. https://doi.org/10.3390/w12113138

Chicago/Turabian Style

Yang, Xin; Zhou, Jianzhong; Fang, Wei; Wang, Yurong. 2020. "An Ensemble Flow Forecast Method Based on Autoregressive Model and Hydrological Uncertainty Processer" Water 12, no. 11: 3138. https://doi.org/10.3390/w12113138

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