A real -time preferred method of a flood forecasting solution based on machine learning

A technology of flood forecasting and machine learning, applied in the field of flood forecasting and hydraulic engineering, to improve the forecasting accuracy

Active Publication Date: 2020-07-03
CHINA INST OF WATER RESOURCES & HYDROPOWER RES
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, how to construct multiple schemes for the same forecast section and how to quickly select an appropriate scheme in real-time forecasting are problems that have not been well solved in practical applications

Method used

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  • A real -time preferred method of a flood forecasting solution based on machine learning
  • A real -time preferred method of a flood forecasting solution based on machine learning
  • A real -time preferred method of a flood forecasting solution based on machine learning

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Embodiment 1

[0042] A real-time optimal method for flood forecasting scheme based on machine learning, comprising the following steps:

[0043] 1) Collection and processing of watershed hydrological data

[0044] For the target watershed, it is necessary to collect rainfall and runoff data of not less than 30 years, and process the rainfall and runoff data into an equal-period time series. If there are multiple rainfall gauge stations within the watershed, it is necessary to use the data of multiple rainfall stations to calculate the areal rainfall of the watershed, and the Thiessen polygon method or the mean method can be used to convert the station rainfall time series into the areal rainfall time series of the watershed. Through the collection and processing of hydrological data in the basin, the time series of areal rainfall in the equal period is obtained {R 1 , R 2 , R 3 ,...,R t} and time series of watershed outlet runoff {Q 1 , Q 2 , Q 3 ,...,Q t}, where t is the time index...

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Abstract

The invention discloses a real-time optimization method of a flood forecasting scheme based on machine learning, comprising the following steps: 1) collection and processing of watershed hydrological data; 2) division and association of rainfall and flood events; 3) generation of a sample set of rainfall and flood events; 4 ) Flood classification; 5) Construction of flood forecasting scheme; 6) Classifier training based on machine learning; 7) Real-time optimization of forecasting scheme based on previous rainfall. The invention divides the sample set into subsets based on the flood level, compiles the flood forecast schemes respectively, and associates them with the previous rainfall process through the machine learning method, realizes the optimization of the flood forecast scheme during real-time forecasting, and can effectively improve the real-time flood of the basin. forecast accuracy.

Description

technical field [0001] The invention belongs to the technical field of water conservancy engineering, in particular to the technical field of flood forecasting, and specifically relates to a machine learning-based real-time optimization method for a flood forecasting scheme. Background technique [0002] As an important part of non-engineering measures, flood forecasting can effectively improve the disaster prevention and mitigation capabilities of river basins and regions. At present, more than 1,700 national basic hydrological stations have achieved normalized forecasting work, more than 200 control sections of large rivers and lakes and more than 700 medium-sized reservoirs have realized routine flood forecasting, and the national hydrological system produces and releases floods of important river, lake and reservoir sections every day during the flood season More than 5,800 stations have been forecasted, and flood forecasts with different forecast periods and accuracy ha...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/26G06K9/62G06N20/00
CPCG06Q10/04G06Q10/0637G06Q50/26G06N20/00G06F18/24323Y02A10/40
Inventor 王帆喻海军张洪斌张大伟姜晓明朴希桐
Owner CHINA INST OF WATER RESOURCES & HYDROPOWER RES
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