Combined riverway water level forecasting method based on high-dimensional probability distribution function

Abstract

The invention relates to the technical field of hydrological forecasting, in particular to a combined riverway water level forecasting method based on a high-dimensional probability distribution function, which comprises the following steps: selecting a time sequence of riverway water levels in a certain period; utilizing the t-1 moment and the edge distribution functions F (Xt-1) and F (Xt) of the water level data series at the t moment to construct a joint distribution probability function of water level variables, and screening three Copula models with minimum AIC values; inputting a waterlevel variable data series Xt-1 at a known t-1 moment by utilizing the joint distribution probability function, and solving a conditional distribution probability of the water level variable data series at the t moment; converting the conditional distribution probability function into an inverse function form of the conditional distribution probability function, and obtaining a fitting water leveldata series Xt at the moment t by taking Xt-1 as an input variable; obtaining three optimal Copula model prediction values, setting the weight of each Copula function prediction value according to the AIC value, calculating the weighted average value of the three Copula function prediction values, and the weighted average value is the final prediction value. The invention can accurately forecastthe river channel water level variable and other hydrological variables, and has important application value.

Description

technical field [0001] The invention relates to the technical field of hydrological forecasting, and more specifically, relates to a combined river water level forecasting method based on a high-dimensional probability distribution function. Background technique [0002] Hydrological forecasting is to predict the hydrological situation in a certain period of time in the future based on the laws of the formation and movement of various hydrological processes in nature, combined with the currently acquired hydrometeorological data. The results of hydrological forecasting provide services for rational utilization and protection of water resources, flood control and rescue, water conservancy project construction and operation management, and industrial and agricultural safety production. The hydrological theory is based on the physical hydrological process, because the physical process can scientifically and reasonably reflect the actual hydrological process. Therefore, many ph...

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Problems solved by technology

However, due to too many uncertain factors in nature, it is difficult for the physical model to fully reflect the influence relationship between variables, resulting in unsatisfactory effects of the physical model

In addition, physical models usually require a large number of underlying surface and climate data types, and in practice, these data are often difficult to obtain, thus limiting the application of physical models

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