Real-time flood forecasting intelligent model forecasting method for medium and small rivers

Abstract

The invention discloses a real-time flood forecasting intelligent model forecasting method for medium and small rivers. The method comprises the steps: firstly collecting historical hydrological dataof all stations of a research basin, and storing the historical hydrological data into a hydrological historical database; secondly, performing data cleaning, data conversion and data set division onhydrological history data; thirdly, constructing a three-stage real-time flood forecasting model. In the first stage, a data driving model based on a support vector machine is used for forecasting flood. In the second stage, a Markov method is adopted to intelligently adjust the state of the initial forecasting model. In the third stage, a historical flood flow mode the same as the historical flood flow mode in the real-time flood process is searched in a flood mode library. After that, the overall form of the flood hydrograph forecasted in real time is adjusted. The performance of the intelligent model is evaluated by using the test set data. Finally, real-time forecasts are made. The method has the advantages that the flood peak precision and the flood trend can be effectively forecasted, and the method is an effective tool for real-time forecasting of flood of medium and small rivers.

Description

technical field [0001] The invention relates to the technical field of data-driven water flow forecasting, in particular to an intelligent model forecasting method for real-time flood forecasting of small and medium-sized rivers. Background technique [0002] Floods in small and medium-sized watersheds have the characteristics of strong suddenness, fast confluence time, and short forecast period. Timely and effective flood warning and forecasting of small and medium rivers can help humans effectively defend against floods and reduce flood losses, and is one of the important non-engineering measures for disaster prevention and mitigation. At present, flood forecasting generally adopts two methods: a hydrological model based on the runoff process and a data-driven intelligent model, and the two models complement each other in actual forecasting. Data-driven modeling basically does not consider the physical mechanism of the hydrological process, and is a black box method aimed...

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Problems solved by technology

[0004] In view of the lack of adaptability and accuracy of existing intelligent flood forecasting models in real-time forecasting of small and medium-sized rivers, the purpose of the present invention is to propose a real-time flood forecasting method based on "three stages", which can effectively forecast flood peak accuracy and flood trends. An effective tool for real-time flood forecasting

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