CN212009620U - System for irrigation flow prediction is carried out according to climate change - Google Patents
System for irrigation flow prediction is carried out according to climate change Download PDFInfo
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- CN212009620U CN212009620U CN202020375959.4U CN202020375959U CN212009620U CN 212009620 U CN212009620 U CN 212009620U CN 202020375959 U CN202020375959 U CN 202020375959U CN 212009620 U CN212009620 U CN 212009620U
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- 238000003973 irrigation Methods 0.000 title claims abstract description 33
- 230000002262 irrigation Effects 0.000 title claims abstract description 33
- 239000003621 irrigation water Substances 0.000 claims abstract description 96
- 238000012937 correction Methods 0.000 claims abstract description 7
- 238000004891 communication Methods 0.000 claims description 12
- 238000000034 method Methods 0.000 claims description 9
- QVFWZNCVPCJQOP-UHFFFAOYSA-N chloralodol Chemical compound CC(O)(C)CC(C)OC(O)C(Cl)(Cl)Cl QVFWZNCVPCJQOP-UHFFFAOYSA-N 0.000 claims description 6
- 239000002689 soil Substances 0.000 claims description 6
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 abstract description 6
- 238000013461 design Methods 0.000 abstract description 2
- 230000002354 daily effect Effects 0.000 description 7
- 238000005286 illumination Methods 0.000 description 7
- 238000001556 precipitation Methods 0.000 description 7
- 230000008020 evaporation Effects 0.000 description 6
- 238000001704 evaporation Methods 0.000 description 6
- 238000004364 calculation method Methods 0.000 description 4
- 238000010276 construction Methods 0.000 description 3
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- 238000005516 engineering process Methods 0.000 description 1
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Abstract
The utility model relates to an irrigate prediction technical field, provide a system for irrigation flow prediction according to climate change, including historical database, climate prediction database, on-the-spot acquisition sensor, irrigation water volume prediction and correction module, the utility model discloses according to the climate prediction data that original historical irrigation water volume data and follow acquireed in the network, calculate out the prediction irrigation water volume to use site environment data to correct the prediction irrigation water volume, finally obtain actual irrigation water volume, add the basis of crops irrigation flow with climate change's factor, and to different crops, carry out irrigation flow's prediction to it, design intelligent irrigation flow prediction according to climate factor, can replace the drawback of current quantitative irrigation always, make the water supply rationalize more.
Description
Technical Field
The utility model relates to an irrigate prediction technical field, in particular to system for flow prediction irrigates according to climate change.
Background
In order to ensure the normal growth of crops and obtain high and stable yield, sufficient moisture needs to be supplied to the crops to promote the growth, and along with the continuous strengthening of technological strength, the automatic irrigation of the crops is realized, so that the defects of manual irrigation are overcome, the labor is saved, and the irrigation efficiency is improved.
However, not all crops require the same amount of water, some crops have too much water, the yield is reduced, and the change of the climate environment is inseparably connected with the amount of irrigation water, so that it is very important to give an appropriate irrigation flow rate according to the change of the climate environment and the growth state of the crops themselves.
SUMMERY OF THE UTILITY MODEL
An object of the utility model is to improve the not enough that exists among the prior art, provide a system that irrigates the flow prediction according to climate change.
In order to realize the purpose of the utility model, the embodiment of the utility model provides a following technical scheme:
a system for predicting irrigation flow based on climate change, comprising:
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.
Furthermore, the climate forecast database acquires climate forecast data through any access network of communication protocol modes of Lora, GPRS and IoT.
Because the field acquisition sensor is positioned at an outdoor crop planting field, communication modes such as WIFI and Bluetooth of a building are troublesome to use, and a base station or a router needs to be newly built, the climate prediction database in the scheme can acquire climate prediction data through any access network in communication protocol modes of Lora, GPRS and IoT, excessive construction is not performed on the communication modes, and the cost is saved.
Furthermore, the on-site acquisition sensor comprises an air temperature sensor, an air humidity sensor, a soil humidity sensor and a wind power sensor.
Furthermore, 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 to the system, and the solar charging panel supplies power to the storage battery.
A method for predicting irrigation flow based on climate change, comprising the steps of:
step S1: extracting historical irrigation water quantity data from a historical database;
step S2: connecting a network to obtain climate prediction data;
step S3: calculating the predicted irrigation water quantity by combining the historical irrigation water quantity data and the climate prediction data;
step S4: acquiring field environment data through a field acquisition sensor;
step S5: and correcting and predicting the irrigation water quantity by using the field environment data to obtain the actual irrigation water quantity.
According to the scheme, the predicted irrigation water amount is calculated according to original historical irrigation water amount data and climate prediction data acquired from a network, the predicted irrigation water amount is corrected by using field environment data, the actual irrigation water amount is finally obtained, the climate change factor is added into the basis of the irrigation flow of crops, the irrigation flow of different crops is predicted, intelligent irrigation flow prediction is designed according to the climate factor, the defect of the existing consistent quantitative irrigation can be replaced, and water supply is more reasonable.
Further, to specify the parameters related to the historical irrigation water quantity data, the historical irrigation water quantity data extracted from the historical database includes monthly daily average irrigation water quantity, yearly monthly average irrigation water quantity, yearly seasonal average irrigation water quantity, and yearly average irrigation water quantity.
Furthermore, in order to specify relevant parameters of the climate forecast data, the climate forecast data acquired by the connection network includes temperature, humidity, wind power, precipitation and illumination.
Further, in order to specify how to calculate the predicted irrigation water amount by combining the historical irrigation water amount data and the climate prediction data, the step S3 specifically includes the following steps:
step S3-1: calculating evaporation capacity according to temperature, humidity, wind power and illumination capacity in the climate prediction data;
step S3-2: and subtracting the evaporation capacity from the historical irrigation water quantity data of the current time period every year, and adding the rainfall capacity in the climate prediction data to obtain the predicted irrigation water quantity.
Further, to specify relevant parameters of the field environment data, the field environment data collected by the field collection sensor includes current air temperature, air humidity, soil humidity, and wind power.
Further, in order to specify how to correct the predicted irrigation water amount by using the field environment data to obtain the actual irrigation water amount, the step S5 specifically includes the following steps:
step S5-1: comparing the air temperature, the air humidity and the wind power in the field environment data with the temperature, the humidity and the wind power in the climate prediction data, and judging whether the difference values are greater than respective standard deviations;
step S5-2: if the standard deviation is not greater than the standard deviation, the predicted irrigation water quantity is used as the actual irrigation water quantity; if the difference is larger than the standard deviation, recalculating the evaporation capacity to obtain a new predicted irrigation water quantity, and using the new predicted irrigation water quantity as the actual irrigation water quantity.
Further comprising step S6: and storing the actual irrigation water quantity as historical irrigation data into a historical database.
In order to further improve the accuracy of predicting the irrigation water quantity, the actual irrigation water quantity in each time is stored in the historical database, the data in the historical database are updated, the accuracy of calculating and processing the predicted irrigation water quantity is improved more and more, the correction steps are reduced, and the calculation efficiency is improved.
Compared with the prior art, the beneficial effects of the utility model are that:
(1) the utility model discloses according to original historical irrigation water volume data and the weather prediction data who acquires from the network, calculate and obtain the prediction irrigation water volume, and use site environment data to correct the prediction irrigation water volume, finally obtain actual irrigation water volume, add the basis of crops irrigation flow with the factor of climate change, and to different crops, carry out the prediction of irrigation flow to it, according to the intelligent irrigation flow prediction of climate factor design, can replace the drawback of the quantitative irrigation of keeping one's time now, make the water supply rationalize more.
(2) The utility model discloses a further accuracy of prediction irrigation water yield is improved, all deposits the actual irrigation water yield of every time in historical database, updates the data in the historical database, more and more improves the accuracy of calculating the prediction irrigation water yield, reduces the step of correcting for calculation efficiency.
(3) Because the utility model discloses a scene acquisition sensor is located open air crops planting field, and communication methods such as WIFI, the bluetooth that use the building are more troublesome, still need newly-built basic station or router, consequently in this scheme any kind of access network in the communication protocol mode of weather prediction database through Lora, GPRS, IoT acquire weather prediction data can, do not do too much construction, practice thrift the cost on communication mode.
(4) The utility model discloses a power supply module is solar charging's mode, because the utility model discloses a system is in outdoor environment, consequently uses solar charging power supply energy to save the power supply cost greatly, need not to insert the commercial power supply, avoids complicated electric wire to arrange.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a block diagram of an irrigation flow prediction system according to the present invention;
fig. 2 is a flow chart of the irrigation flow prediction method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. The components of embodiments of the present invention, as generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented 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 embodiment of the present invention, all other embodiments obtained by the person skilled in the art without creative work belong to the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Example (b):
the utility model discloses a following technical scheme realizes, as shown in fig. 2, a method for carrying out irrigation flow prediction according to climate change, includes following step:
step S1: and extracting historical irrigation water quantity data from a historical database.
Because the automatic irrigation system used in the agricultural field at present irrigates crops according to preset irrigation water, historical irrigation water data in recent years, such as daily average irrigation water, monthly average irrigation water, annual season average irrigation water and annual average irrigation water in nearly five years, can be acquired from the automatic irrigation system for a certain crop. Some species are only planted in a certain season, so the irrigation water amount of the species in the rest seasons can be zero, and the day-average, month-average, quarter-average and year-average irrigation water amount of the species needs to be acquired, so that the subsequent steps can have bases in calculating and processing the predicted irrigation water amount.
Step S2: the connecting network obtains climate forecast data.
The climate prediction is a mature technology, for example, the climate predicted by the weather station can be published on the network for people to refer to, the scheme is directly connected with the network to obtain the climate prediction data, and the communication protocol mode connected with the network can be any one of Lora, GPRS, IoT and the like. The weather prediction data of acquireing include temperature, humidity, wind-force, precipitation, the illumination volume of each day of future week or even future month, wherein the temperature of each day be the average temperature of day, or the temperature of the fixed point time of each day, for example the temperature of twelve noon every day, all the other humidity, wind-force, precipitation, the illumination volume of acquireing also are like temperature data, the utility model discloses acquire daily average temperature, humidity, wind-force, precipitation, illumination volume.
Step S3: and calculating the predicted irrigation water quantity by combining the historical irrigation water quantity data and the climate prediction data.
For convenience of explaining the working principle of the present invention, the present embodiment assumes that the historical irrigation water amounts (X1, X2, X3, X4, X5) of the second day of the previous five years (for example, the current day is 1 month and 1 day of 2020, and the second day of the previous five years is 1 month and 2 days of the previous five years), that is, the daily average irrigation water amount of the second day of the previous five years, are obtained, and the climate prediction data of the second day of the current year (that is, 1 month and 2 days of 2020) including the daily average temperature, humidity, wind power, precipitation, and illumination of the second day are obtained.
Calculating evaporation capacity according to the average daily temperature, humidity, wind power and illumination quantity of the next day, wherein the evaporated water rises into the air and is taken away, precipitation enters the soil, and the average value of the average daily irrigation water quantity (X1, X2, X3, X4 and X5) of the next day of the previous five years is obtained compared with the natural irrigation water quantity
Using average values
The evaporation amount is subtracted and the precipitation amount is added to obtain the predicted irrigation water amount.
Step S4: and acquiring field environment data through a field acquisition sensor.
Since the predicted irrigation water amount is calculated according to the historical irrigation water amount and the climate prediction data, wherein the climate prediction data has uncertainty, the predicted irrigation water amount is corrected through the current field environment data, and the irrigation water with relatively proper irrigation water amount is obtained. The field environment data collected using the field collection sensor includes current air temperature, air humidity, soil humidity, wind power.
Step S5: correcting and predicting irrigation water quantity by using field environment data to obtain actual irrigation water quantity
Assuming that field environment data collected in 1/2020 is G (G1, g2... gn), and climate prediction data in 31/12/2019 to 1/2020/1/2020 is H (H1, h2... hn), a standard deviation corresponding to each data can be calculated by a variance calculation method, for example, a standard deviation of an air temperature G1 in the collected field environment data to a temperature H1 in the climate prediction data is G1
Similarly, the standard deviation of the humidity g2 in the field environment data to the humidity h2 in the climate forecast data is
The standard deviation of the wind force g3 in the site environment data to the wind force h3 in the climate forecast data is
Comparing the air temperature, air humidity and wind power in the field environment data with the corresponding temperature, humidity and wind power in the climate prediction data, and judging whether the difference values are greater than respective standard deviations, for example, when | g1-h1| ≦ gh1, | g2-h2| ≦ gh2, | g3-h3| ≦ gh3 are simultaneously satisfied, using the predicted irrigation water amount as the actual irrigation water amount; and if the absolute value of G1-H1 is more than gh1 or absolute value of G1-H1 is more than gh1 or absolute value of G1-H1 is more than gh1, recalculating the evaporation amount by using the average value of G (G1, g2... gn) and H (H1, h2... hn) to obtain a new predicted irrigation water amount, and using the new predicted irrigation water amount as the actual irrigation water amount.
Step S6: and storing the actual irrigation water quantity as historical irrigation data into a historical database.
In order to further improve the accuracy of predicting the irrigation water quantity, the actual irrigation water quantity in each time is stored in the historical database, the data in the historical database are updated, the accuracy of calculating and processing the predicted irrigation water quantity is improved more and more, the correction steps are reduced, and the calculation efficiency is improved.
Based on the above method, the utility model discloses still provide a system for carry out irrigation flow prediction according to climate change, as shown in fig. 1, include:
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.
In detail, because the field acquisition sensor is located at an outdoor crop planting field, it is troublesome to use communication modes such as WIFI and bluetooth of a building, and a new base station or a new router is required, so that the climate prediction database in the scheme can acquire climate prediction data through any one of communication protocol modes of Lora, GPRS and IoT, excessive construction is not performed on the communication modes, and the cost is saved.
The field acquisition sensor comprises an air temperature sensor, an air humidity sensor, a soil humidity sensor and a wind power sensor, and transmits acquired field environment data to the irrigation water quantity prediction and correction module for correcting and predicting irrigation water quantity.
The system is connected with the power supply module, the power supply module includes battery, solar charging panel, the battery is the system power supply, and solar charging panel is the battery power supply, and the technique that the technique of solar charging is that technical staff in the electricity field is familiar with the technique of using, uses this kind of mode to anticipate saving the power supply cost, need not to insert the commercial power supply in addition, avoids complicated electric wire to arrange.
The above description is only for the specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art can easily think of the changes or substitutions within the technical scope of the present invention, and all should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to 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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| CN111401649A (en) * | 2020-03-23 | 2020-07-10 | 成都信息工程大学 | Method and system for predicting irrigation flow according to climate change |
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| CN111401649A (en) * | 2020-03-23 | 2020-07-10 | 成都信息工程大学 | Method and system for predicting irrigation flow according to climate change |
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