A kind of watershed similarity classification method and classification device

Abstract

The invention discloses a watershed similarity classification method and a classification device. The classification method comprises the following steps: collecting hydrology, meteorology and underlying surface data of a predetermined watershed, extracting meteorological and underlying surface factors, and constructing characteristic indexes; setting correlation The threshold value determines the similarity index of meteorology and underlying surface; based on the fusion algorithm of SOM and FCM, the grid-scale hydrometeorological division is carried out in the predetermined watershed; the sub-basin-scale clustering group is constructed in the meteorological homogeneous area, and the sub-basin classification is performed by using the fusion model ; According to the meteorological division of the watershed and the sub-watershed category it contains, the fuzzy membership degree of the sub-watershed is used to construct a comprehensive measure of watershed similarity, and the maximum and minimum closeness method is used to evaluate the similarity between the watersheds and identify the difference between the watersheds. similarity. The invention provides a theoretical basis for the selection and parameter transplantation of the evidence-free watershed in the data-free watershed, and promotes the in-depth development of the model parameter regionalization and hydrological early warning and forecasting in the data-free area.

Description

technical field

[0001] The invention belongs to the technical field of hydrology, in particular to a watershed similarity classification method and a classification device, which are mainly used for similar watershed discrimination and hydrological early warning and forecasting in areas without data. Background technique

[0002] In recent years, under the influence of climate change and human activities, extreme weather events have shown an increasing trend, and serious flood disasters such as mountain torrents and mudslides have occurred frequently. Especially for areas with lack of hydrological data, due to the lack of effective hydrological monitoring methods, the detection of disasters is insufficient, the disasters occur rapidly, and the losses are serious, which seriously restricts the sustainable development of the economy and society. In response to the problem of hydrological forecasting in data-free areas, the International Association of Hydrological Sciences (IA...

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