CN212009620U - A system for forecasting irrigation flow based on climate change - Google Patents

Abstract

The utility model relates to the technical field of irrigation prediction, and proposes a system for predicting irrigation flow according to climate change, comprising a historical database, a climate prediction database, an on-site acquisition sensor, and an irrigation water volume prediction and correction module. Data and climate prediction data obtained from the network, calculate the predicted irrigation water volume, and use the on-site environmental data to correct the predicted irrigation water volume, and finally obtain the actual irrigation water volume, add climate change factors to the basis of crop irrigation flow, and target Different crops, the irrigation flow prediction is carried out, and the intelligent irrigation flow prediction is designed according to the climatic factors, which can replace the disadvantages of the existing quantitative irrigation and make the water supply more rational.

Description

A system for forecasting irrigation flow based on climate change

technical field

The utility model relates to the technical field of irrigation prediction, in particular to a system for predicting irrigation flow according to climate change.

Background technique

In order to ensure the normal growth of crops and obtain high and stable yields, it is necessary to provide crops with sufficient water to promote growth. With the continuous strengthening of scientific and technological forces, automatic irrigation of crops has been realized, which improves the disadvantages of manual irrigation, saves manpower and improves irrigation efficiency.

But not all crops need the same amount of water. Some crops have too much water, which will reduce the yield, and the change of the climate environment is also inseparable from the amount of irrigation water. It is very important to give proper irrigation flow in the growing state.

Utility model content

The purpose of the utility model is to improve the deficiencies existing in the prior art, and to provide a system for predicting irrigation flow according to climate change.

In order to achieve the above purpose of the utility model, the embodiments of the present utility model provide the following technical solutions:

A system for forecasting irrigation flow based on climate change, including:

Historical database for storing historical irrigation water data;

Climate prediction database, used to access the network to obtain climate prediction data;

On-site acquisition sensors are used to collect on-site environmental data;

The irrigation water volume prediction and correction module is used to calculate the predicted irrigation water volume according to the historical irrigation water volume data and climate prediction data, and correct the predicted irrigation water volume according to the on-site environmental data to obtain the actual irrigation water volume.

Further, the climate prediction database obtains the climate prediction data through any access network in Lora, GPRS, IoT communication protocol mode.

Since the on-site acquisition sensors are located in the outdoor crop planting site, it is troublesome to use the building's WIFI, Bluetooth and other communication methods, and a new base station or router is required. Therefore, the climate prediction database described in this solution is implemented through the communication protocols of Lora, GPRS, and IoT. Any kind of access network can be used to obtain climate prediction data, without doing too much construction on communication methods, saving costs.

Further, the on-site acquisition sensors include an air temperature sensor, an air humidity sensor, a soil humidity sensor, and a wind sensor.

Furthermore, the system is connected with a power supply module, and the power supply module includes a battery and a solar charging board, the battery supplies power to the system, and the solar charging board supplies power for the battery.

A method for forecasting irrigation flow based on climate change, comprising the following steps:

Step S1: extract historical irrigation water volume data from the historical database;

Step S2: connect to the network to obtain climate prediction data;

Step S3: calculating the predicted irrigation water volume in combination with the historical irrigation water volume data and the climate prediction data;

Step S4: collecting on-site environmental data through on-site sensors;

Step S5: correcting the predicted irrigation water volume using the on-site environmental data to obtain the actual irrigation water volume.

According to the original historical irrigation water volume data and the climate prediction data obtained from the network, this scheme calculates the predicted irrigation water volume, and uses the on-site environmental data to correct the predicted irrigation water volume, and finally obtains the actual irrigation water volume, adding the factors of climate change into The basis of the irrigation flow of crops, and for different crops, the irrigation flow prediction is carried out, and the intelligent irrigation flow prediction is designed according to the climatic factors, which can replace the disadvantages of the existing quantitative irrigation and make the water supply more rational.

Further, in order to specify the relevant parameters of the historical irrigation water data, the historical irrigation water data extracted from the historical database includes the monthly average daily irrigation water, the annual monthly average irrigation water, the annual quarterly average irrigation water, Average annual irrigation water volume.

Further, in order to specifically describe the relevant parameters of the climate prediction data, the climate prediction data obtained by the connection network includes temperature, humidity, wind, precipitation, and illumination.

Further, in order to describe in detail how to calculate the predicted irrigation water volume in combination with the historical irrigation water volume data and the climate prediction data, the step S3 specifically includes the following steps:

Step S3-1: Calculate the evaporation amount according to the temperature, humidity, wind power, and light amount in the climate prediction data;

Step S3-2: The predicted irrigation water amount is obtained by subtracting the evaporation amount from the historical irrigation water amount data in the current time period of each year, and adding the rainfall in the climate prediction data.

Further, in order to specifically describe the relevant parameters of the on-site environmental data, the on-site environmental data collected by the on-site acquisition sensors include current air temperature, air humidity, soil humidity, and wind power.

Further, in order to describe in detail how to use the on-site environmental data to correct the predicted irrigation water volume and obtain the actual irrigation water volume, the step S5 specifically includes the following steps:

Step S5-1: Compare the air temperature, air humidity, and wind power in the on-site environmental data with the temperature, humidity, and wind power in the climate prediction data, and determine whether the difference is greater than the respective standard deviation;

Step S5-2: if it is not greater than the respective standard deviations, use the predicted irrigation water volume as the actual irrigation water volume; if it is greater than the respective standard deviations, recalculate the evaporation to obtain a new predicted irrigation water volume, and use the new predicted irrigation water volume as the actual irrigation water volume. Irrigation water volume.

It also includes step S6: storing the actual irrigation water amount as historical irrigation data into a historical database.

In order to further improve the accuracy of the predicted irrigation water volume, the actual irrigation water volume of each time is stored in the historical database, and the data in the historical database is updated to improve the accuracy of the calculation and processing of the predicted irrigation water volume, reduce the correction steps, and speed up the process. Computational efficiency.

Compared with the prior art, the beneficial effects of the present utility model:

(1) the utility model calculates the predicted irrigation water according to the original historical irrigation water data and the climate prediction data obtained from the network, and uses the on-site environmental data to correct the predicted irrigation water, finally obtains the actual irrigation water, and the climate The changing factors are added to the basis of the irrigation flow of crops, and the irrigation flow is predicted for different crops, and the intelligent irrigation flow prediction is designed according to the climatic factors, which can replace the disadvantages of the existing quantitative irrigation and make the water supply more rational. .

(2) the present utility model is to further improve the accuracy of the predicted irrigation water quantity, the actual irrigation water quantity of each time is all stored in the historical database, the data in the historical database is updated, and the accuracy of the calculation processing prediction irrigation water quantity is improved more and more, Reduce the number of correction steps and speed up the calculation efficiency.

(3) Since the field acquisition sensor of the present utility model is located in the outdoor crop planting site, it is troublesome to use the communication methods such as WIFI and Bluetooth of the building, and a new base station or router needs to be built. One of the communication protocol methods of IoT can access the network to obtain climate prediction data, without doing too much construction on the communication method, which saves costs.

(4) The power supply module used in the present invention is a solar charging method. Since the system of the present utility model is located in an outdoor environment, the use of solar charging and power supply can greatly save power supply costs, and there is no need to connect to the mains power supply to avoid complicated wire rows. cloth.

Description of drawings

In order to illustrate the technical solutions of the embodiments of the present invention more clearly, the accompanying drawings that need to be used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention. Therefore, it should not be regarded as a limitation of the scope. For those of ordinary skill in the art, other related drawings can also be obtained from these drawings without any creative effort.

Fig. 1 is the module block diagram of the irrigation flow prediction system of the present utility model;

Fig. 2 is a flow chart of the irrigation flow prediction method of the present invention.

Detailed ways

The technical solutions in the embodiments of the present utility model will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present utility model. Obviously, the described embodiments are only a part of the embodiments of the present utility model, rather than all the embodiments. . The components of the embodiments of the invention generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations. Accordingly, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but is merely representative of selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the present invention.

It should be noted that like numerals and letters refer to like items in the following figures, so once an item is defined in one figure, it does not require further definition and explanation in subsequent figures.

Example:

The utility model is realized through the following technical solutions, as shown in Figure 2, a method for predicting irrigation flow according to climate change, comprising the following steps:

Step S1: Extract historical irrigation water quantity data from the historical database.

Since the automatic irrigation system currently used in the agricultural field irrigates crops according to the preset irrigation water volume, for a certain crop, historical irrigation water volume data in recent years can be obtained from the automatic irrigation system. The monthly average irrigation water volume, the annual average monthly irrigation water volume, the annual quarterly average irrigation water volume, and the annual average irrigation water volume. Some species are only planted in a certain season, so the amount of irrigation water for the remaining seasons may be zero. Therefore, it is necessary to obtain the detailed daily, monthly, seasonal, and average irrigation water in order to predict irrigation in the subsequent steps. There is a basis for the amount of water.

Step S2: Connect to the network to obtain climate prediction data.

Climate prediction is a mature technology. For example, the weather predicted by the weather station will be published on the Internet for people's reference. This solution can directly connect to the network to obtain the climate prediction data. The communication protocol for connecting to the network can be Lora, GPRS, IoT, etc. any of the. The obtained climate forecast data includes the daily temperature, humidity, wind, precipitation, and light amount for the next week or even the next month, where the daily temperature is the daily average temperature, or the temperature at a fixed time every day, such as The temperature at 12:00 noon, the other acquired humidity, wind power, precipitation, and illumination are also the same as temperature data, and the utility model acquires the daily average temperature, humidity, wind, precipitation, and illumination.

Step S3: Calculate the predicted irrigation water volume in combination with the historical irrigation water volume data and the climate prediction data.

For the convenience of explaining the working principle of the present utility model, the present embodiment assumes that the second day of the first five years is obtained (for example, today is January 1, 2020, then the second day of the first five years is January 2 of the first five years). The historical irrigation water volume (X1, X2, X3, X4, X5), that is, the average daily irrigation water volume on the second day of the previous five years, and the climate on the second day of the current year (ie, January 2, 2020) has been obtained. Forecast data, including the average daily temperature, humidity, wind, precipitation, and sunlight for the next day.

使用平均值

减去蒸发量再加上降水量即为预测灌溉水量。According to the daily average temperature, humidity, wind, and light amount of the next day, the evaporation can be calculated. The evaporated water will rise into the air and be taken away, and the precipitation will enter the soil. Compared with the natural irrigation water, then Average the daily average irrigation water volume (X1, X2, X3, X4, X5) on the second day of the previous five years

use average

Subtracting evaporation and adding precipitation is the predicted irrigation water volume.

Step S4: collecting on-site environmental data through on-site collecting sensors.

Since the predicted irrigation water volume is calculated based on historical irrigation water volume and climate prediction data, wherein the climate prediction data is uncertain, it is necessary to correct the predicted irrigation water volume through the current on-site environmental data, and a relatively appropriate irrigation water volume has been obtained. amount of water for irrigation. The on-site environmental data collected using on-site acquisition sensors include current air temperature, air humidity, soil moisture, and wind power.

Step S5: Correct the predicted irrigation water volume using the on-site environmental data to obtain the actual irrigation water volume

同理，现场环境数据中的空气湿度g2对应气候预测数据中的湿度h2的标准差为

现场环境数据中的风力g3对应气候预测数据中的风力h3的标准差为

Assume that the field environmental data collected on January 1, 2020 is G(g1, g2...gn), and the climate forecast data for January 1, 2020 on December 31, 2019 is H(h1, h2. ..hn), then the standard deviation corresponding to each data can be calculated by calculating the variance. For example, the standard deviation of the air temperature g1 in the collected field environmental data corresponding to the temperature h1 in the climate prediction data is:

Similarly, the standard deviation of the air humidity g2 in the field environmental data corresponding to the humidity h2 in the climate prediction data is:

The standard deviation of the wind force g3 in the field environmental data corresponding to the wind force h3 in the climate prediction data is:

Then, compare the air temperature, air humidity, and wind power in the on-site environmental data with the corresponding temperature, humidity, and wind power in the climate prediction data, and judge whether the difference is greater than their respective standard deviations. For example, when |g1-h1|≤gh1, When |g2-h2|≤gh2, |g3-h3|≤gh3, the predicted irrigation water amount is used as the actual irrigation water amount; if |g1-h1|>gh1 or |g1-h1|>gh1 or |g1-h1| When >gh1, the mean value of G(g1, g2...gn) and H(h1, h2...hn) is used to recalculate the evaporation to obtain a new predicted irrigation water amount, and use the new predicted irrigation water amount as the actual Irrigation water volume.

Step S6: the actual irrigation water amount is stored in the historical database as historical irrigation data.

In order to further improve the accuracy of the predicted irrigation water volume, the actual irrigation water volume of each time is stored in the historical database, and the data in the historical database is updated to improve the accuracy of the calculation and processing of the predicted irrigation water volume, reduce the correction steps, and speed up the process. Computational efficiency.

Based on the above method, the present invention also proposes a system for predicting irrigation flow according to climate change, as shown in Figure 1, including:

Historical database for storing historical irrigation water data;

Climate prediction database, used to access the network to obtain climate prediction data;

On-site acquisition sensors are used to collect on-site environmental data;

The irrigation water volume prediction and correction module is used to calculate the predicted irrigation water volume according to the historical irrigation water volume data and climate prediction data, and correct the predicted irrigation water volume according to the on-site environmental data to obtain the actual irrigation water volume.

In detail, since the on-site acquisition sensors are located at the outdoor crop planting site, it is cumbersome to use the building's WIFI, Bluetooth and other communication methods, and a new base station or router is required. Any one of the communication protocol methods can access the network to obtain the climate prediction data, without doing too much construction on the communication method, which saves the cost.

The on-site acquisition sensors include air temperature sensors, air humidity sensors, soil humidity sensors, and wind sensors, and send the collected on-site environmental data to the irrigation water volume prediction and correction module for correcting and predicting the irrigation water volume.

The system is connected with a power supply module, the power supply module includes a battery and a solar charging board, the battery supplies power to the system, and the solar charging board supplies power for the battery, and the technology of solar charging is familiar to those skilled in the electrical field. , the use of this method is intended to save power supply costs, without the need for additional access to the mains power supply, to avoid complex wire arrangements.

The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited to this. Replacement should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims (4)

1. A system for predicting irrigation flow based on climate change, comprising: the method comprises the following steps:

the historical database is used for storing historical irrigation water quantity data;

the climate prediction database is used for accessing a network to obtain climate prediction data;

the field acquisition sensor is used for acquiring field environment data;

and the irrigation water quantity prediction and correction module is used for calculating according to the historical irrigation water quantity data and the climate prediction data to obtain the predicted irrigation water quantity, correcting the predicted irrigation water quantity according to the field environment data, and obtaining the actual irrigation water quantity.

2. A system for climate change based prediction of irrigation flow according to claim 1, wherein: the climate forecast database is accessed to the network through any one of communication protocol modes of Lora, GPRS and IoT to obtain climate forecast data.

3. A system for climate change based prediction of irrigation flow according to claim 1, wherein: the on-site acquisition sensor comprises an air temperature sensor, an air humidity sensor, a soil humidity sensor and a wind power sensor.

4. A system for climate change based prediction of irrigation flow according to any of claims 1-3, wherein: the system is connected with a power supply module, the power supply module comprises a storage battery and a solar charging panel, the storage battery supplies power for the system, and the solar charging panel supplies power for the storage battery.

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