Medium and long term runoff ensemble forecasting method based on multi-model combination

Abstract

The invention discloses a medium and long term runoff ensemble forecasting method based on multi-model combination, and relates to the technical field of hydrological prediction. According to the method, multiple machine learning algorithms are adopted to construct a medium-and-long-term runoff forecasting model, the medium-and-long-term runoff forecasting model is used as a weak learner, and an integrated model construction method based on multi-model combination is provided on the basis. Meanwhile, equivalent forecast is searched through parameter disturbance to construct a forecast set, andensemble forecast is carried out. Compared with an existing common deterministic forecasting method, the method has the advantages that part of defects existing in the method are improved, and the precision and generalization capacity of medium-and-long-term forecasting are improved. Meanwhile, the uncertainty of forecasting is quantitatively described through probability forecasting, and the accuracy and reference value of forecasting are improved.

Description

technical field [0001] The invention relates to the technical field of hydrological forecasting, in particular to a medium- and long-term runoff ensemble forecasting method based on multi-model combination. Background technique [0002] Affected by climate, meteorology, underlying surface, human activities and many other factors, the mid- and long-term runoff forecasting process has certain temporal and spatial uncertainties. Traditional mid- and long-term runoff forecasting methods such as physical genesis method, mathematical statistics method, regression analysis method and modern emerging forecasting methods such as fuzzy analysis method, gray system method, neural network and other methods often use meteorological factors as alternative factors, from which specific The watershed selects the appropriate predictors to learn the relationship between the predictors and the runoff of the watershed. The traditional runoff forecasting method is affected by the forecasting mod...

AI Technical Summary

Problems solved by technology

The traditional runoff forecasting method is affected by the forecasting model and data, and it is often difficult to solve the problem that the single deterministic forecasting is seriously limited due to the highly nonlinear forecasting model and the chaotic nature of the runoff process. There are still some deficiencies

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