Medium-and-long-term runoff ensemble forecasting method

An ensemble forecasting, medium and long-term technology, applied in forecasting, instruments, computational models, etc., can solve problems such as inability to predict unstable time series well

Active Publication Date: 2019-12-10
TSINGHUA UNIV
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Problems solved by technology

[0005] The purpose of this invention is to propose a medium and long-term runoff ensemble forecasting method in ord

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Embodiment Construction

[0036] The present invention proposes a medium and long-term runoff ensemble forecasting method, which will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0037] A medium and long-term runoff ensemble forecasting method proposed by the present invention, the principle diagram is as follows figure 1 shown. figure 1 Among them, the key part of the present invention is the selection of the set of predictors, considering the time lag effect, analyzing lag (lag=1,2,...,12, the same below) teleconnection factors before the month and the history of the forecast month based on the principle of telecorrelation The correlation of runoff data, based on the local factor correlation, analyzes the correlation between the local historical runoff data and the historical weather station data before the lag month, that is, the teleconnection factor before the lag month, the weather station factor and the runoff data of other months...

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Abstract

The invention provides a medium-and-long term runoff ensemble forecasting method, and belongs to the field of hydrological forecasting. The method comprises the following steps: firstly, respectivelyacquiring historical runoff data of a forecast object, acquiring historical meteorological data as a local correlation factor, and acquiring climate factor data as a remote correlation factor; takingthe runoff data of the first 11 months of the month to be forecasted as a time sequence autocorrelation factor; selecting the factor with the highest correlation coefficient from all the factors to form a forecasting factor set; and inputting the forecasting factor set data corresponding to the month to be forecasted into the model by utilizing the trained and verified machine learning runoff forecasting model to obtain a forecasting value of the runoff volume of the month. The method can be practically applied to month-by-month runoff calculation of hydrological station data missing regions and station sparse regions, can also be used for interpolation of missing runoff data, and provides an effective reference basis for local water resource distribution and management, especially arid region reservoir scheduling, local irrigation planning, agricultural water management and the like.

Description

technical field [0001] The invention belongs to the field of hydrological forecasting, and in particular relates to a medium and long-term runoff ensemble forecasting method. Background technique [0002] In the context of climate change, the water cycle is influenced not only by local meteorological elements, but also by global climate factors. In the arid area, the climate is harsh and the population is sparsely populated. Due to the limitations of objective conditions such as terrain and equipment, the distribution of hydrological stations and meteorological stations is sparse, and there are often problems of lack of measurement and missing data. In the case of relatively large proportions of irrigation water and agricultural water Under such circumstances, it is impossible to allocate water resources reasonably and efficiently, resulting in waste of water resources and exacerbating the shortage of water resources. The efficient use of water resources is of great signifi...

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Application Information

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IPC IPC(8): G06Q10/04G06N20/00
CPCG06Q10/04G06N20/00
Inventor 张腾王忠静张子雄
Owner TSINGHUA UNIV
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