Multi-source rainfall product fusion method based on dynamic heuristic algorithm

Abstract

The invention provides a multi-source rainfall product fusion method based on a dynamic heuristic algorithm. The method comprises the following steps: collecting limited site observation data of a scarce data region, and carrying out satellite inversion and reanalysis on a rainfall data set; correcting each data set by adopting a local magnitude scaling method and an equal-rate correction method, and obtaining a correction coefficient of each site; describing the capturing capability of each data source on the rainfall event through a division function, and deducing a state weight with a space-time dynamic attribute; considering the simulation capability of each data source on the rainfall level, and deducing a dynamic magnitude weight based on a cuckoo algorithm; and adopting a common Kriging interpolation method to dynamically map correction coefficients, state weights and magnitude weights of all stations to the same spatial resolution, and obtaining a long series of grid quantitative rainfall productsthrough correction and data fusion. According to the method, the advantages of the rainfall data sources are effectively fused, the system deviation of the rainfall data sources is corrected, and a reference basis is provided for basin hydrological simulation and water resource planning.

Description

technical field [0001] The invention belongs to the technical field of multi-source data fusion, and in particular relates to a multi-source precipitation product fusion method based on a dynamic heuristic algorithm. Background technique [0002] High-quality quantitative precipitation data are important basic data for disaster prevention and early warning, agricultural production management, ecological protection, hydrological simulation of river basins, and planning and design of water conservancy projects. Traditional precipitation data mainly rely on station observations, but the meteorological station network is usually small in density and uneven in space, which makes it difficult to accurately reflect the temporal and spatial variation characteristics of precipitation, and cannot meet the needs of high-precision hydrological simulation and other engineering applications. [0003] In recent years, satellite telemetry technology and data inversion algorithms have develo...

AI Technical Summary

Problems solved by technology

However, the following problems generally exist in the existing research: (1) the temporal and spatial heterogeneity of precipitation is generally ignored, and the dynamic characteristics of fusion parameters are less considered; (2) the systematic bias of each precipitation data source cannot be corrected, especially the simultaneous Correcting the frequency and magnitude of precipitation

In general, the existing research fails to effectively integrate the advantages of various precipitation data sources, which restricts the planning, management and operation scheduling of water conservancy projects.

Images