Underground water level change medium and long term forecasting method based on support vector machine binary data assimilation

Abstract

The invention discloses an underground water level change medium and long term forecasting method based on support vector machine binary data assimilation, and belongs to the field of underground water forecasting of hydrology and water resource discipline, and the method comprises the following steps: selecting a research area, and obtaining an effective underground water level and meteorologicalelement data sequence; adopting a support vector machine nonlinear regression method to construct an underground water level change prediction model; inputting forecast moment driving elements, and forecasting underground water level change at the moment; assimilating the correction drive and output element set and constructing a metadata assimilation model when the underground water level observation data exists at the forecast moment; updating and inputting forecast moment driving elements, and outputting a metadata assimilation forecast value; and performing data assimilation correction onthe unary data assimilation forecast value again to obtain a binary data assimilation forecast value. The method is based on a machine learning theory, adopts a data assimilation technology to fuse big data to forecast groundwater level changes, and can be directly applied to medium and long term forecast and optimal configuration of groundwater resources.

Description

technical field [0001] The invention belongs to the field of groundwater forecasting in the discipline of hydrology and water resources, and in particular relates to a medium- and long-term forecasting method for groundwater level changes based on support vector machine binary data assimilation. Background technique [0002] As the world's largest freshwater resource [Shiklomanov and Rodda, 2003], groundwater resources occupy an important position in the global water cycle [Taylor et al., 2013]. As the main source of drinking water, groundwater maintains the sustainable development of the ecological environment [IPCC, 2014]. With population increase and climate change, the demand for groundwater increases dramatically [Konikow, 2011; Wada et al., 2011; Wada et al., 2012]. With the exploitation of groundwater, groundwater aquifers are facing a crisis of contraction [Sun, 2013]. Understanding the spatio-temporal distribution of groundwater and making medium- and long-term fo...

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Problems solved by technology

At present, there is no relevant research on the use of binary data assimilation technology based on support vector machines in the medium and long-term forecasting of groundwater level changes

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