Short-term forecasting method of farmland evapotranspiration considering dynamic changes of crop coefficient and rainfall

Abstract

The invention discloses a short-term prediction method of farmland evapotranspiration considering the dynamic change of crop coefficient and rainfall. The method includes acquiring the meteorological data of the growing environment of farmland crops; Daily crop coefficient; construct training set and test set respectively, and perform preprocessing; establish a feed-forward neural network model considering the dynamic change of crop coefficient and rainfall influence, and conduct training optimization; use the optimized feed-forward neural network model according to the test Short-term prediction of farmland crop evapotranspiration using set data. The present invention considers the influence of crop coefficient change and rainfall on farmland crop evapotranspiration, effectively constructs the nonlinear relationship between farmland reference crop evapotranspiration and its driving factors, and thus can obtain crop evapotranspiration that is more in line with the actual growth conditions of crops, Provide a scientific basis for the future water management of the underlying surface of farmland.

Description

technical field [0001] The invention belongs to the technical field of crop transpiration prediction, and in particular relates to a short-term prediction method for farmland evapotranspiration considering the dynamic change of crop coefficients and rainfall. Background technique [0002] Evapotranspiration process is an important part of terrestrial hydrological cycle, evapotranspiration (Evapotranspiration, ET c ) has important guiding significance for irrigation planning and regional water resources allocation. Accurate prediction of evapotranspiration can save irrigation water to a certain extent. Therefore, in order to better manage crop irrigation water consumption and improve crop water use efficiency, it is urgent to accurately predict crop evapotranspiration. [0003] At present, the prediction methods of evapotranspiration are mainly divided into four categories: time series method, grey model method, empirical formula method and neural network model method. Due ...

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Problems solved by technology

[0005] To sum up, many studies on evapotranspiration prediction have been carried out, but there are two main problems at present: (1) The fixed or simple difference crop coefficient recommended by FAO-56 is suitable for the prediction of evapotranspiration in a long period, while The applicability of short-term evapotranspiration prediction is low, and the basic crop coefficient curve in the crop coefficient method is only linearly differenced by three determined nodes, which simplifies the processing of the crop growth process, which will cause large deviations; ( 2) Due to the uncertainty of rainfall, there are few studies on evapotranspiration prediction models considering rainfall. Only considering deterministic meteorological factors will inevitably cause deviations in evapotranspiration prediction under typical weather, and the applicability is weak

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