Method and system for quantitatively forecasting extreme rainfall

Abstract

The invention discloses a method for quantitatively forecasting extreme rainfall. The method comprises the following steps that: I, an input module (100) reads raw data of a hydrometric station from a database or an Excel file, performing abnormal detection and washing on the read data, and preprocessing the data to obtain standardized hydrometric time sequence data; II, a modeling module (200) constructs a model consisting of a first forecasting model (210), a second forecasting model (220) and a combined BP neural network (230) according to the hydrometric time sequence data in the input module (100); III, a correction module (300) performs parameter adjustment on the forecasting models constructed in the modeling module (200) according to the quality of the forecast data in the step II; and IV, an output module (400) stores an extreme rainfall forecast value in the next year into the database or the file, so that a user can check and analyze the data. By the method, a yearly average extreme rainfall amount can be modeled and forecast from a data excavation angle; and the method is high in applicability and relatively high in accuracy.

Description

technical field [0001] The invention relates to a method and system for predicting precipitation, in particular to a method for predicting annual average extreme precipitation. Background technique [0002] Extreme weather and climate events have an important impact on the human economy, society and the natural environment, and its research has become one of the frontier issues of climate change science. When the climate state of a place deviates significantly from its mean state, it can be considered as an unlikely climate event. In a statistical sense, values ​​(events) that are not likely to occur can be called extreme values ​​(events). [0003] Extremely heavy precipitation events usually have concentrated precipitation periods, very high precipitation intensity, and a wide range, which often cause floods in some areas and seriously affect industrial and agricultural production. Paralyze urban traffic, stop production of industrial and mining enterprises; not only tha...

AI Technical Summary

Problems solved by technology

Fitting analysis mainly uses global climate models or regional climate models to simulate extreme precipitation events, but it cannot be verified whether the statistical relationship established by using current climate data is applicable to the future climate state

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