CN114662911A - Irrigation water management method and management system based on farmland moisture monitoring - Google Patents
Irrigation water management method and management system based on farmland moisture monitoring Download PDFInfo
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Abstract
The application discloses irrigation water management method and management system based on farmland moisture monitoring, which relate to the technical field of farmland irrigation, and comprise the following steps: identifying the farmland type of a target farmland; setting a water level threshold value and an irrigation scheme based on the farmland type; irrigating a target farmland according to an irrigation scheme; acquiring water level data of a target farmland; and adjusting an irrigation scheme by combining the water level threshold and the water level data. This application has the effect that can intelligent reply bad weather such as heavy rain among the automatic irrigation process.
Description
Technical Field
The application relates to the technical field of farmland irrigation, in particular to an irrigation water management method and a management system based on farmland water monitoring.
Background
The purpose of farmland irrigation is to ensure that crops can have high quality and high yield and obtain the best economic benefit. The method is generally divided into a plurality of irrigation modes such as drip irrigation, sprinkling irrigation, flood irrigation and the like according to different types of crops in the farmland and different farmland geology. With the continuous development of society and science and technology, the irrigation mode is gradually changed from the most original manual irrigation to the automatic irrigation. Among the correlation technique, can adopt intelligent irrigation system to irrigate the farmland, and can set for the irrigation time according to farmland size, crops type before automatic irrigation, irrigate the farmland based on the irrigation time of setting for again.
With respect to the related art among the above, the inventors consider that the following drawbacks exist: the irrigation water volume of automatic irrigation is the suitable water volume of crops usually, but bad weather such as heavy rain weather can appear in the irrigation process, if not in time adjust automatic irrigation scheme, irrigation water leads to the farmland moisture too high easily and drowns crops.
Disclosure of Invention
In order to improve the defect that severe weather such as heavy rain weather easily causes the farmland to have too high moisture in the irrigation process, the application provides an irrigation water management method and a management system based on farmland moisture monitoring.
In a first aspect, the application provides a method for managing irrigation water based on farmland moisture monitoring, comprising the following steps:
identifying the farmland type of a target farmland;
setting a water level threshold value and an irrigation scheme based on the farmland type;
irrigating the target farmland according to the irrigation scheme;
acquiring water level data of the target farmland;
adjusting the irrigation regime in combination with the water level threshold and the water level data.
By adopting the technical scheme, different automatic irrigation schemes are generated according to different farmland types, and the required appropriate water quantities of crops in different farmlands are different, so that the corresponding water level threshold value can be set according to the farmland types. The water level data of the target farmland can be monitored in real time in the process of irrigating the target farmland by adopting an irrigation scheme, if heavy rain and other weather occurs, the water level of the farmland can rise according to rainfall and irrigation water, and at the moment, the water level data of the farmland can be higher than a set water level threshold value; if windy weather appears, irrigation of a sprinkling irrigation mode can be influenced, and farmland water level data can not reach a water level threshold value all the time, so that the irrigation scheme needs to be analyzed and judged in time and adjusted in time by combining the water level threshold value and the water level data, and the moisture in a target farmland is guaranteed to be at a normal level as far as possible.
Optionally, the identifying the farmland type of the target farmland comprises the following steps:
acquiring image information and positioning information of a target farmland;
acquiring timestamp information in the image information or the positioning information;
identifying current season information based on the timestamp information;
acquiring geological information of the position of the target farmland based on the positioning information through a GIS system;
carrying out image recognition on the image information to obtain crop information in the target farmland;
and identifying the farmland type of the target farmland by combining the current season information, the crop information and the geological information.
By adopting the technical scheme, the image information and the positioning information of the target farmland are obtained, the current season information can be identified according to the timestamp information in the image information or the positioning information, the crop information in the target farmland can be identified according to the image information of the target farmland based on the image identification technology, the positioning information is further guided into a GIS system to be inquired and the geological information of the position of the target farmland is obtained, and finally the farmland type of the target farmland can be analyzed and identified by combining the geological information, the crop information and the current season information.
Optionally, the water level data includes field water level data and ground water level data, and the acquiring the water level data of the target field includes the following steps:
defining a target area based on the boundary of the target farmland;
judging whether the area of the target area exceeds a preset area threshold value or not;
if the area of the region does not exceed the area threshold, selecting a first sampling point in the target region based on a five-point sampling method;
if the area of the region exceeds the area threshold, randomly selecting a plurality of second sampling points in the target region, wherein the distance between any two second sampling points is between a preset first distance threshold and a preset second distance threshold, and the second distance threshold is greater than the first distance threshold;
and collecting the field water level data and the underground water level data based on the first sampling point or the second sampling point.
By adopting the technical scheme, the target region containing the target farmland is defined according to the boundary of the target farmland, the size of the region area of the target region is judged through the preset area threshold value, and the region surrounded by the farmland is usually rectangular, so that the target farmland with the area not exceeding the area threshold value is sampled by adopting a five-point sampling method, and more accurate sample information can be acquired by using fewer sampling points; and the target farmland with the area exceeding the area threshold value is sampled in a multi-point sampling mode, the multi-point sampling is more accurate compared with a five-point sampling method for the target farmland with the larger area, and the selected sampling point covers the whole target farmland. And finally, collecting field water level data and underground water level data according to the first sampling point selected by the five-point sampling method or the second sampling point selected by the multi-point sampling method.
Optionally, the water level threshold includes a field water level threshold and an underground water level threshold, and the adjusting the irrigation scheme by combining the water level threshold and the water level data includes the following steps:
judging whether the field water level data exceeds the field water level threshold value;
if the field water level data exceeds the field water level threshold, adjusting the irrigation scheme to reduce the irrigation water amount;
if the field water level data does not exceed the field water level threshold, acquiring environment data of a target environment where the target farmland is located;
predicting a precipitation probability of the target environment based on the environment data;
and adjusting the irrigation scheme by combining the precipitation probability, the groundwater level threshold value and the groundwater level data.
By adopting the technical scheme, the importance degree of the field water level is greater than the underground water level, so that whether field water level data exceeds the standard is judged according to a preset field water level threshold value, if the field water level data exceeds the field water level threshold value, an irrigation scheme needs to be adjusted immediately to reduce the irrigation water quantity, and excessive water of a target field is avoided; if the water level threshold value of the target farmland is not exceeded, the environmental data of the target environment where the target farmland is located can be obtained, and the precipitation probability is predicted according to the environmental data, so that the irrigation scheme can be adjusted according to the precipitation probability and the underground water condition of the target farmland.
Optionally, the adjusting the irrigation scheme by combining the precipitation probability, the groundwater level threshold and the groundwater level data includes the following steps:
judging whether the precipitation probability exceeds a preset probability threshold value or not;
if the precipitation probability exceeds the probability threshold, predicting precipitation time of the target environment based on the environment data;
generating an adjusting time according to the precipitation moment;
adjusting the irrigation schedule to reduce the amount of irrigation water after the adjustment time has elapsed;
if the precipitation probability does not exceed the probability threshold, judging whether the underground water level data exceeds the underground water level threshold;
if the underground water level data does not exceed the underground water level threshold value, the irrigation scheme is not adjusted;
and if the underground water level data exceeds the underground water level threshold value, adjusting the irrigation scheme to reduce the irrigation water quantity.
By adopting the technical scheme, the precipitation probability is judged according to the preset probability threshold, if the precipitation probability is high, the subsequent possible precipitation time needs to be continuously predicted, and the adjusting time for adjusting the irrigation scheme is generated according to the predicted precipitation time; if the precipitation probability is low, the groundwater level data needs to be further judged according to a preset groundwater level threshold value, groundwater can affect the soil seepage rate of a target farmland, groundwater is excessive, the soil seepage rate is low, the field water level data of the target farmland can be indirectly affected, and therefore when the groundwater level data exceeds the groundwater level threshold value, an irrigation scheme needs to be adjusted to reduce the irrigation water quantity.
Optionally, the step of defining the target area based on the boundary of the target farmland includes the following steps:
acquiring a remote sensing image of the target farmland;
carrying out image processing on the remote sensing image to obtain a target image;
identifying a peripheral ditch and a peripheral road of the target farmland in the target image;
calculating a first identification integrity of the peripheral ditch and a second identification integrity of the peripheral road;
judging whether the first identification integrity is greater than the second identification integrity;
if the first recognition integrity is larger than the second recognition integrity, the peripheral ditch is used as the boundary of the target farmland and a target area is defined;
and if the first recognition integrity is smaller than the second recognition integrity, taking the peripheral road as the boundary of the target farmland and dividing a target area.
By adopting the technical scheme, the periphery of the farmland is usually provided with one circle of peripheral roads for walking, one circle of ditch is arranged between the peripheral roads and the farmland, and the remote sensing image is a top view of the target farmland, so that the peripheral ditch or the peripheral roads in the remote sensing image can be shielded by sundries.
Optionally, the acquiring the field water level data and the ground water level data based on the first sampling point or the second sampling point includes the following steps:
judging a sampling point as the first sampling point or the second sampling point;
if the sampling points are the first sampling points, acquiring first initial field water level data and first initial underground water level data from all the first sampling points respectively;
calculating the average value of all the first initial field water level data as the field water level data, and calculating the average value of all the first initial underground water level data as the underground water level data;
if the sampling points are the second sampling points, second initial field water level data and second initial underground water level data are collected from all the second sampling points respectively;
screening out all abnormal data in the second initial field water level data and the second initial underground water level data to obtain second field water level data and second underground water level data;
and calculating the average value of all the second field water level data as the field water level data, and calculating the average value of all the second underground water level data as the underground water level data.
By adopting the technical scheme, after the target farmland with a small area is sampled by adopting a five-point sampling method, the average value of the data acquired by five sampling points can be directly calculated, and the average value is taken as the final sampling data. If sampling is performed in a multi-point sampling mode, due to the fact that the number of sampling points is large, abnormal sampling may occur due to sampling equipment or data transmission, data collected by the second sampling point needs to be screened first, abnormal data are screened out, and then average value calculation is performed, so that sampled data are obtained finally.
In a second aspect, the present application further provides an irrigation water management system based on farmland water monitoring, including a memory, a processor, and a program stored in the memory and executable on the processor, where the program can be loaded and executed by the processor to implement the irrigation water management method based on farmland water monitoring according to the first aspect.
By adopting the technical scheme, different automatic irrigation schemes are generated according to different farmland types through calling of programs, the appropriate water quantity required by crops in different farmlands is different, and the corresponding water level threshold value can be set according to the farmland types. The water level data of the target farmland can be monitored in real time in the process of irrigating the target farmland by adopting an irrigation scheme, if heavy rain and other weather occurs, the water level of the farmland can rise according to rainfall and irrigation water, and at the moment, the water level data of the farmland can be higher than a set water level threshold value; if windy weather appears, irrigation of a sprinkling irrigation mode can be influenced, and farmland water level data can not reach a water level threshold value all the time, so that the irrigation scheme needs to be analyzed and judged in time and adjusted in time by combining the water level threshold value and the water level data, and the moisture in a target farmland is guaranteed to be at a normal level as far as possible.
In summary, the present application includes at least one of the following beneficial technical effects:
different automatic irrigation schemes are generated according to different farmland types, the appropriate water quantity required by crops in different farmlands is different, and therefore the corresponding water level threshold value can be set according to the farmland types. The water level data of the target farmland can be monitored in real time in the process of irrigating the target farmland by adopting an irrigation scheme, if heavy rain and other weather occurs, the water level of the farmland can rise according to rainfall and irrigation water, and at the moment, the water level data of the farmland can be higher than a set water level threshold value; if windy weather appears, irrigation of a sprinkling irrigation mode can be influenced, and farmland water level data can not reach a water level threshold value all the time, so that the irrigation scheme needs to be analyzed and judged in time and adjusted in time by combining the water level threshold value and the water level data, and the moisture in a target farmland is guaranteed to be at a normal level as far as possible.
Drawings
Fig. 1 is a schematic flow diagram of a method for managing irrigation water based on field moisture monitoring according to an embodiment of the present disclosure.
Fig. 2 is a schematic flow chart of field type identification of a target farmland according to an embodiment of the present application.
Fig. 3 is a schematic flow chart of acquiring water level data of a target farmland according to an embodiment of the present application.
FIG. 4 is a schematic flow chart of adjusting an irrigation program according to an embodiment of the present disclosure.
FIG. 5 is a schematic flow diagram of an embodiment of the present application for adjusting an irrigation scheme in conjunction with precipitation probability and groundwater conditions.
FIG. 6 is a schematic flow chart illustrating the delimiting of the target area based on the boundary of the target farmland according to an embodiment of the present application.
FIG. 7 is a schematic flow chart of collecting field water level data and groundwater level data based on a sampling point according to one embodiment of the present application.
Detailed Description
The present application is described in further detail below with reference to figures 1-7.
The embodiment of the application discloses an irrigation water management method based on farmland moisture monitoring.
Referring to fig. 1, the method for managing irrigation water based on farmland moisture monitoring comprises the following steps:
101, identifying the farmland type of the target farmland.
The farmland types include terraced fields, paddy fields, dry lands and the like.
And 102, setting a water level threshold value and an irrigation scheme based on the farmland type.
The optimal irrigation schemes and the average optimal water level of different types of farmlands are retrieved through the Internet, the water level threshold value is set according to the average optimal water level, and the irrigation schemes are set according to the optimal irrigation schemes.
And 103, irrigating the target farmland according to the irrigation scheme.
And 104, acquiring water level data of the target farmland.
And 105, adjusting the irrigation scheme by combining the water level threshold value and the water level data.
The implementation principle of the embodiment is as follows:
different automatic irrigation schemes are generated according to different farmland types, the required suitable water quantities of crops in different farmlands are different, and corresponding water level thresholds can be set according to the farmland types. The water level data of the target farmland can be monitored in real time in the process of irrigating the target farmland by adopting an irrigation scheme, if heavy rain and other weather occurs, the water level of the farmland can rise according to rainfall and irrigation water, and at the moment, the water level data of the farmland can be higher than a set water level threshold value; if windy weather appears, irrigation of a sprinkling irrigation mode can be influenced, and farmland water level data can not reach a water level threshold value all the time, so that the irrigation scheme needs to be analyzed and judged in time and adjusted in time by combining the water level threshold value and the water level data, and the moisture in a target farmland is guaranteed to be at a normal level as far as possible.
In step 101 of the embodiment shown in fig. 1, current season information, geological information and crop information may be obtained according to image information and positioning information of a target farmland, and then a farmland type may be identified. This is explained in detail with reference to the embodiment shown in fig. 2.
Referring to fig. 2, identifying a field type of a target field includes the steps of:
and 201, acquiring image information and positioning information of a target farmland.
Wherein, gather the image information in target farmland through unmanned aerial vehicle to when unmanned aerial vehicle flies to directly over the target farmland central point, the GPS positioning device who carries through unmanned aerial vehicle acquires the locating information of target farmland position.
Time stamp information in the image information or the positioning information is acquired 202.
And 203, identifying current season information based on the time stamp information.
Wherein, the month information contained in the timestamp information is identified based on spring of 3-5 months, summer of 6-8 months, autumn of 9-11 months, and winter of 12 months to next year of 2 months.
And 204, acquiring geological information of the position of the target farmland through a GIS system based on the positioning information.
And 205, carrying out image recognition on the image information to obtain crop information in the target farmland.
And carrying out image recognition on crops in the image information through a preset neural network recognition model, and obtaining crop information according to a recognition result.
And 206, identifying the farmland type of the target farmland by combining the current season information, the crop information and the geological information.
The implementation principle of the embodiment is as follows:
the method comprises the steps of obtaining image information and positioning information of a target farmland, identifying current season information according to timestamp information in the image information or the positioning information, identifying crop information in the target farmland according to the image information of the target farmland based on an image identification technology, further guiding the positioning information into a GIS (geographic information system) to inquire and obtain geological information of the position of the target farmland, and finally analyzing and identifying the farmland type of the target farmland by combining the geological information, the crop information and the current season information.
In step 104 of the embodiment shown in fig. 1, the water level data includes field water level data and ground water level data, and different sampling methods are selected according to the area size of the target area including the target field. This is explained in detail with reference to the embodiment shown in fig. 3.
Referring to fig. 3, the step of acquiring the water level data of the target farmland comprises the following steps:
a target area is defined based on the boundary of the target field 301.
302, judging whether the area of the target area exceeds a preset area threshold, if not, executing a step 303; if yes, go to step 304.
303, selecting a first sampling point in the target area based on a five-point sampling method.
If the target area is rectangular, selecting first sampling points at four corners and a center of the target area; if the target area is not a rectangle, drawing a maximum rectangle in the target area, and selecting first sampling points at four corners and a center of the maximum rectangle.
And 304, randomly selecting a plurality of second sampling points in the target area.
The distance between any two second sampling points is between a preset first distance threshold and a preset second distance threshold, and the second distance threshold is larger than the first distance threshold.
And 305, collecting field water level data and underground water level data based on the first sampling point or the second sampling point.
The implementation principle of the embodiment is as follows:
the method comprises the steps that a target area containing the target farmland is drawn according to the boundary of the target farmland, the area of the target area is judged through a preset area threshold value, and the area surrounded by the farmland is generally rectangular, so that the target farmland with the area not exceeding the area threshold value is sampled by adopting a five-point sampling method, and more accurate sample information can be acquired by using fewer sampling points; and the target farmland with the area exceeding the area threshold value is sampled in a multi-point sampling mode, the multi-point sampling is more accurate compared with a five-point sampling method for the target farmland with the larger area, and the selected sampling point covers the whole target farmland. And finally, collecting field water level data and underground water level data according to the first sampling point selected by the five-point sampling method or the second sampling point selected by the multi-point sampling method.
In step 105 of the embodiment shown in fig. 1, the water level threshold includes a field water level threshold and an underground water level threshold, whether the irrigation scheme is to be adjusted currently is determined according to the field water level data and the preset field water level threshold, if adjustment is not needed currently, the precipitation probability of the target environment of the target farmland is predicted, and further analysis and determination are performed based on the precipitation probability and the underground water condition. This is explained in detail with reference to the embodiment shown in fig. 4.
Referring to fig. 4, adjusting the irrigation regime in conjunction with the water level threshold and water level data comprises the steps of:
401, judging whether the field water level data exceeds a field water level threshold value, if so, executing a step 402; if not, go to step 403.
402, adjusting the irrigation scheme to reduce the amount of irrigation water.
Wherein, irrigation mode and irrigation time in the irrigation scheme can be adjusted to reduce the amount of irrigation water.
And 403, acquiring environmental data of the target environment of the target farmland.
The environmental data includes wind power, humidity, temperature, etc.
And 404, predicting precipitation probability of the target environment based on the environment data.
And 405, adjusting an irrigation scheme by combining the precipitation probability, the groundwater level threshold value and the groundwater level data.
The implementation principle of the embodiment is as follows:
the important degree of the field water level is greater than the underground water level, so that whether field water level data exceed the standard or not is judged according to a preset field water level threshold, if the field water level data exceed the field water level threshold, an irrigation scheme needs to be adjusted immediately to reduce the irrigation water amount, and excessive water of a target farmland is avoided; if the water level threshold value of the target farmland is not exceeded, the environmental data of the target environment where the target farmland is located can be obtained, and the precipitation probability is predicted according to the environmental data, so that the irrigation scheme can be adjusted according to the precipitation probability and the underground water condition of the target farmland.
In step 405 of the embodiment shown in fig. 4, the precipitation probability is determined by a preset probability threshold, and the groundwater level data may also be determined according to the preset groundwater level threshold, and whether the irrigation scheme needs to be adjusted is analyzed according to the comprehensive determination result. This is illustrated in detail by the embodiment shown in fig. 5.
Referring to fig. 5, adjusting the irrigation scheme in combination with precipitation probability and groundwater conditions comprises the steps of:
501, judging whether the precipitation probability exceeds a preset probability threshold, if so, executing a step 502; if not, go to step 505.
And 502, predicting the precipitation moment of the target environment based on the environment data.
An adjustment time is generated 503 from the precipitation time.
And subtracting the current moment from the precipitation moment to obtain the adjustment time.
Adjusting the irrigation schedule to reduce the amount of irrigation water when the adjustment time has elapsed 504.
505, judging whether the groundwater level data exceeds the groundwater level threshold value, if not, executing a step 506; if yes, go to step 507.
506, the irrigation regime is not adjusted.
507, adjusting the irrigation scheme to reduce the amount of irrigation water.
The implementation principle of the embodiment is as follows:
judging the precipitation probability according to a preset probability threshold, if the precipitation probability is high, continuing to predict the subsequent possible precipitation time, and generating the adjustment time for adjusting the irrigation scheme according to the predicted precipitation time; if the precipitation probability is low, the groundwater level data needs to be further judged according to a preset groundwater level threshold value, groundwater can affect the soil seepage rate of a target farmland, groundwater is excessive, the soil seepage rate is low, the field water level data of the target farmland can be indirectly affected, and therefore when the groundwater level data exceeds the groundwater level threshold value, an irrigation scheme needs to be adjusted to reduce the irrigation water quantity.
In step 301 of the embodiment shown in fig. 3, the boundary is determined by obtaining a remote sensing image of a target farmland, identifying a peripheral ditch and a peripheral road at the periphery of the target farmland in the remote sensing image, and comparing the identification integrity. This is explained in detail with reference to the embodiment shown in fig. 6.
Referring to fig. 6, the step of defining a target area based on the boundary of the target farmland includes the steps of:
601, obtaining a remote sensing image of a target farmland.
And acquiring a rocker image of the target farmland through a rocker satellite.
And 602, performing image processing on the remote sensing image to obtain a target image.
The image processing includes processes of denoising, sharpening and the like.
603, identifying the peripheral ditch and the peripheral road of the target farmland in the target image.
604, a first recognition integrity of the peripheral trench and a second recognition integrity of the peripheral road are calculated.
Wherein, the first recognition integrity calculation formula of the peripheral ditch is as follows: the area of the peripheral trench not covered/(the area of the peripheral trench covered + the area of the peripheral trench not covered). The second recognition integrity calculation formula of the peripheral road is as follows: the peripheral road unblocked area/(blocked area of peripheral road + unblocked area of peripheral road).
605, determining whether the first recognition integrity is greater than the second recognition integrity, if yes, executing step 606; if not, go to step 607.
And 606, taking the peripheral ditch as the boundary of the target farmland and delimiting a target area.
And 607, defining the peripheral road as the boundary of the target farmland and defining the target area.
The implementation principle of the embodiment is as follows:
the periphery of a farmland is usually provided with a circle of peripheral roads for walking, a circle of ditches are arranged between the peripheral roads and the farmland, and the remote sensing image is a top view of a target farmland, so that the peripheral ditches or the peripheral roads in the remote sensing image can be shielded by sundries.
In step 305 of the embodiment shown in fig. 3, when the sampling point is the second sampling point in the multi-point sampling method, the data collected at the second sampling point needs to be screened before the final sampling data is calculated. This is explained in detail with reference to the embodiment shown in fig. 7.
Referring to fig. 7, collecting field water level data and ground water level data based on sampling points includes the following steps:
701, judging whether the sampling point is a first sampling point or a second sampling point, and if the sampling point is the first sampling point, executing a step 702; if the second sample point is the first sample point, go to step 704.
And 702, collecting first initial field water level data and first initial underground water level data from all the first sampling points respectively.
703, calculating the average value of all the first initial field water level data as field water level data, and calculating the average value of all the first initial underground water level data as underground water level data.
And 704, respectively collecting second initial field water level data and second initial underground water level data from all second sampling points.
705, screening out all abnormal data in the second initial field water level data and the second initial underground water level data to obtain second field water level data and second underground water level data.
And 706, calculating the average value of all the second field water level data as field water level data, and calculating the average value of all the second underground water level data as underground water level data.
The implementation principle of the embodiment is as follows:
after a target farmland with a small area is sampled by adopting a five-point sampling method, the average value of data acquired by five sampling points can be directly calculated, and the average value is used as final sampling data. If sampling is performed in a multi-point sampling mode, due to the fact that a plurality of sampling points are available, abnormal sampling may occur due to sampling equipment or data transmission, and therefore data acquired by the second sampling point needs to be screened first, and after abnormal data are screened out, average value calculation is performed, and finally sampling data are obtained.
The embodiment of the application also discloses an irrigation water management system based on farmland moisture monitoring, which comprises a memory, a processor and a program which is stored on the memory and can run on the processor, wherein the program can be loaded and executed by the processor to realize the irrigation water management method based on farmland moisture monitoring as shown in figures 1-7.
The implementation principle of the embodiment is as follows:
through the calling of the program, different automatic irrigation schemes are generated according to different farmland types, the appropriate water quantity required by crops in different farmlands is different, and therefore the corresponding water level threshold value can be set according to the farmland types. The water level data of the target farmland can be monitored in real time in the process of irrigating the target farmland by adopting an irrigation scheme, if heavy rain and other weather occurs, the water level of the farmland can rise according to rainfall and irrigation water, and at the moment, the water level data of the farmland can be higher than a set water level threshold value; if windy weather appears, irrigation of a sprinkling irrigation mode can be influenced, and farmland water level data can not reach a water level threshold value all the time, so that the irrigation scheme needs to be analyzed and judged in time and adjusted in time by combining the water level threshold value and the water level data, and the moisture in a target farmland is guaranteed to be at a normal level as far as possible.
The above are preferred embodiments of the present application, and the scope of protection of the present application is not limited thereto, so: all equivalent changes made according to the structure, shape and principle of the present application shall be covered by the protection scope of the present application.
Claims (8)
1. An irrigation water management method based on farmland moisture monitoring is characterized by comprising the following steps:
identifying the farmland type of a target farmland;
setting a water level threshold value and an irrigation scheme based on the farmland type;
irrigating the target farmland according to the irrigation scheme;
acquiring water level data of the target farmland;
adjusting the irrigation regime in combination with the water level threshold and the water level data.
2. The method of claim 1, wherein the step of identifying the field type of the target field comprises the steps of:
acquiring image information and positioning information of a target farmland;
acquiring timestamp information in the image information or the positioning information;
identifying current season information based on the timestamp information;
acquiring geological information of the position of the target farmland based on the positioning information through a GIS system;
carrying out image recognition on the image information to obtain crop information in the target farmland;
and identifying the farmland type of the target farmland by combining the current season information, the crop information and the geological information.
3. The method of claim 1, wherein the water level data comprises field water level data and ground water level data, and the step of obtaining the water level data of the target field comprises the following steps:
defining a target area based on the boundary of the target farmland;
judging whether the area of the target area exceeds a preset area threshold value or not;
if the area of the region does not exceed the area threshold, selecting a first sampling point in the target region based on a five-point sampling method;
if the area of the region exceeds the area threshold, randomly selecting a plurality of second sampling points in the target region, wherein the distance between any two second sampling points is between a preset first distance threshold and a preset second distance threshold, and the second distance threshold is greater than the first distance threshold;
and collecting the field water level data and the underground water level data based on the first sampling point or the second sampling point.
4. The method of claim 3, wherein the water level thresholds comprise field water level thresholds and ground water level thresholds, and wherein the step of adjusting the irrigation schedule in combination with the water level thresholds and the water level data comprises the steps of:
judging whether the field water level data exceeds the field water level threshold value;
if the field water level data exceeds the field water level threshold, adjusting the irrigation scheme to reduce the irrigation water amount;
if the field water level data does not exceed the field water level threshold, acquiring environment data of a target environment where the target farmland is located;
predicting a precipitation probability of the target environment based on the environment data;
and adjusting the irrigation scheme by combining the precipitation probability, the groundwater level threshold value and the groundwater level data.
5. The method of claim 4, wherein the step of adjusting the irrigation schedule in combination with the precipitation probability, the groundwater level threshold and the groundwater level data comprises the steps of:
judging whether the precipitation probability exceeds a preset probability threshold value or not;
if the precipitation probability exceeds the probability threshold, predicting precipitation time of the target environment based on the environment data;
generating an adjusting time according to the precipitation moment;
adjusting the irrigation schedule to reduce the amount of irrigation water after the adjustment time has elapsed;
if the precipitation probability does not exceed the probability threshold, judging whether the underground water level data exceeds the underground water level threshold;
if the underground water level data does not exceed the underground water level threshold value, the irrigation scheme is not adjusted;
and if the underground water level data exceeds the underground water level threshold value, adjusting the irrigation scheme to reduce the irrigation water quantity.
6. The method of claim 3, wherein the step of defining a target area based on the boundary of the target farmland comprises the steps of:
obtaining a remote sensing image of the target farmland;
carrying out image processing on the remote sensing image to obtain a target image;
identifying a peripheral ditch and a peripheral road of the target farmland in the target image;
calculating a first identification integrity of the peripheral ditch and a second identification integrity of the peripheral road;
judging whether the first identification integrity is greater than the second identification integrity;
if the first recognition integrity is larger than the second recognition integrity, the peripheral ditch is used as the boundary of the target farmland and a target area is defined;
and if the first recognition integrity is smaller than the second recognition integrity, taking the peripheral road as the boundary of the target farmland and dividing a target area.
7. The method of claim 3, wherein the step of collecting the field water level data and the ground water level data based on the first sampling point or the second sampling point comprises the steps of:
judging whether the sampling point is the first sampling point or the second sampling point;
if the sampling points are the first sampling points, acquiring first initial field water level data and first initial underground water level data from all the first sampling points respectively;
calculating the average value of all the first initial field water level data as the field water level data, and calculating the average value of all the first initial underground water level data as the underground water level data;
if the sampling points are the second sampling points, second initial field water level data and second initial underground water level data are collected from all the second sampling points respectively;
screening out all abnormal data in the second initial field water level data and the second initial underground water level data to obtain second field water level data and second underground water level data;
and calculating the average value of all the second field water level data as the field water level data, and calculating the average value of all the second underground water level data as the underground water level data.
8. An irrigation water management system based on farmland water monitoring, which comprises a memory, a processor and a program stored on the memory and capable of running on the processor, wherein the program can be loaded and executed by the processor to realize the irrigation water management method based on farmland water monitoring as claimed in any one of claims 1-7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116243745A (en) * | 2023-02-01 | 2023-06-09 | 湖南华中苗木云科技有限公司 | Intelligent control system for growth environment and intelligent nursery management platform |
| JP7398833B1 (en) | 2022-07-06 | 2023-12-15 | 株式会社笑農和 | Information processing device, information processing method, and program |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JP7398833B1 (en) | 2022-07-06 | 2023-12-15 | 株式会社笑農和 | Information processing device, information processing method, and program |
| JP2024008767A (en) * | 2022-07-06 | 2024-01-19 | 株式会社笑農和 | Information processing device, information processing method, and program |
| CN116243745A (en) * | 2023-02-01 | 2023-06-09 | 湖南华中苗木云科技有限公司 | Intelligent control system for growth environment and intelligent nursery management platform |
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