Method for predicting evaporation transpiration of lawn reference crops

A crop and prediction model technology, applied in the field of prediction of reference crop evapotranspiration, can solve problems such as difficult practical application, inaccurate prediction, and difficulty in carrying out

Inactive Publication Date: 2021-03-19
CHINA AGRI UNIV
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Problems solved by technology

The reference crop evapotranspiration of turfgrass has a strong nonlinear relationship with meteorological factors. Existing predictions require a series of empirical coefficients and complex formulas, and the parameters of many formulas need regional correction, which brings certain difficulties to practical applications. , and in the case of incomplete meteorological data, the prediction based on the weather forecast data is inaccurate o

Method used

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  • Method for predicting evaporation transpiration of lawn reference crops
  • Method for predicting evaporation transpiration of lawn reference crops
  • Method for predicting evaporation transpiration of lawn reference crops

Examples

Experimental program
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Embodiment Construction

[0032] Specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings

[0033] In order to effectively calculate the water demand of lawns in landscaping, it is often calculated by multiplying the evapotranspiration of the reference crop by the crop coefficient. One method of predicting the evapotranspiration of the reference crop is as follows:

[0034] Step 1. Determine the study area

[0035] This example takes Tongzhou District, Beijing as the research area, and the selected weather station is located in Yujiawu Huizu Township, Tongzhou District, Beijing, in the North China Plain, 39°41′N, 116°41′E, and 29.1m above sea level.

[0036] Step 2. Get weather data

[0037] Obtain the geographical information of the weather station and the daily meteorological data from 2014 to 2018 from the weather station selected in step 1, including the altitude of the weather station, the latitude and longitude of the weather s...

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Abstract

The invention discloses a method for predicting evaporation transpiration of a reference crop. The method comprises the following steps: (1) determining a research area; (2) acquiring meteorological data; (3) calculating an evaporation transpiration standard value of the reference crop; (4) analyzing the correlation between common meteorological factors and a standard value; (5) establishing a reference crop evapotranspiration prediction model of the BP neural network based on genetic algorithm optimization; and (6) verifying the model precision in the step (5). According to the invention, theprediction precision of the reference crop evaporation transpiration is higher, the actual requirements are met, and an effective method is provided for predicting the reference crop evaporation transpiration.

Description

technical field [0001] The invention relates to agricultural and landscaping water-saving irrigation projects, in particular to a method for predicting reference crop evapotranspiration. Background technique [0002] Agriculture and landscaping water-saving irrigation project is to fully improve the utilization rate of irrigation water and water productivity by adopting comprehensive technical measures such as advanced irrigation and drainage engineering measures, appropriate crop technology and water management under the condition of limited water resources. Lawn is one of the main plants in landscaping. The determination of lawn crop water demand is an important link in garden water-saving irrigation projects, and the reference crop evapotranspiration of lawn is a key factor in calculating crop water demand, and its accurate estimation plays an important role in garden water management and real-time irrigation forecast. The reference crop evapotranspiration of turfgrass h...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/02G06N3/12G06N3/04
CPCG06Q10/04G06Q50/02G06N3/126G06N3/044
Inventor 严海军谢树华李茂娜徐云成
Owner CHINA AGRI UNIV
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