CN115644039A - Irrigation decision-making system and method based on agricultural system model - Google Patents
Irrigation decision-making system and method based on agricultural system model Download PDFInfo
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- 239000002689 soil Substances 0.000 claims abstract description 53
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Abstract
The invention provides an irrigation decision system and method based on an agricultural system model, wherein the method comprises the following steps: capturing farmland distribution data in the region and trunk distribution data in the region; inputting soil moisture content data in each block and soil moisture content data in each block based on the interface; calculating a first irrigation water consumption of each block based on the first farmland quantity and soil moisture data in each block; calculating a second irrigation water amount for each block based on a difference between the first irrigation water amount and the first irrigation water amount for each block under exclusion of meteorological factors; setting a scheduling time sequence based on the soil moisture data of each block and the corresponding second irrigation water consumption, and dividing the water consumption of the block into a plurality of grades based on the scheduling time sequence; and generating a schedule for each main canal and the branch canal corresponding to each main canal based on the grade corresponding to the block, the second irrigation water consumption of each block and the influence of the simulated meteorological data on each block in combination with the meteorological model.
Description
Technical Field
The invention relates to the technical field of agriculture, in particular to a technology for agricultural irrigation decision-making, and particularly relates to an irrigation decision-making system and method based on an agricultural system model.
Background
Traditional water conservancy dispatching is carried out based on feedback of people on farmland management in seasonality, and the dispatching mode is only artificial feedback from the top to the bottom and cannot be calculated as systematic agricultural irrigation dispatching. In China, water resources are distributed unevenly, rivers and main canals in the south are distributed in a large number generally, and irrigation in the regions can be basically met, but water resources are scarce in the north, particularly in the northwest, at present, in the northern region of China, two modes of main canal guiding and underground water irrigation are basically adopted, and for the same region, such as the same county, the underground water distribution in different places is also extremely unbalanced, so that some places can ensure normal crop irrigation, and in other places, the crop irrigation mainly depends on main canal supply. In this case, if the scheduling is not accurate, the feedback adjustment from bottom to top is adopted, so that the scheduling imbalance is easily caused.
Disclosure of Invention
In view of the above, the main objective of the present invention is to provide an irrigation decision system and method based on an agricultural system model.
The technical scheme adopted by the invention is as follows:
an irrigation decision system based on an agricultural system model, comprising:
the data acquisition module is used for capturing farmland distribution data in an area based on the satellite image; recording main flow of each main channel in the region and branch flows of all branch channels on each main channel in the region;
the dividing module divides a farmland in the region into a plurality of blocks through a main channel and a branch channel of all branch channels on each main channel based on main channel distribution data in the region, and enables at least one main channel/branch channel to flow through in each block or between two adjacent blocks;
the agricultural system model is used for configuring all main channel distribution in an area, main flow lines of all main channels and branch flow lines of all branch channels on each main channel based on a GIS map, and correspondingly configuring each block distribution;
the block compensation module is used for acquiring the self-contained irrigation system in each block, estimating the irrigation capacity of the corresponding block based on the self-contained irrigation system of each block, estimating the coverage area of each block based on the self-contained irrigation system of each block, and converting the irrigation capacity of the corresponding block and the coverage area of the block by the self-contained irrigation system to obtain first irrigation water supply of the self-contained irrigation system;
a decision model having:
the first input end is used for inputting soil moisture content data in each block based on the interface;
a second input for inputting meteorological data within the area based on the interface;
a meteorological model for simulating the effect of meteorological data on each block based on the meteorological data;
the processing module is connected to the agricultural system model and used for calculating first irrigation water consumption of each block based on the first farmland quantity and soil moisture content data in each block;
the decision module is provided with a decision control unit, a decision neural network and a plurality of block calculation units;
each block calculation unit is correspondingly connected with one block, the block calculation unit is connected with the block compensation module, and the block decision unit is used for calculating the second irrigation water consumption of each block based on the difference value of the first irrigation water consumption and the first irrigation water supply of each block under the condition of eliminating meteorological factors;
the decision control unit is connected to the first input end and each block calculation unit, and is used for setting a scheduling time sequence based on soil moisture content data of each block and the corresponding second irrigation water consumption, and dividing water for the blocks into a plurality of grades based on the scheduling time sequence;
the decision neural network is connected with the decision control unit and the meteorological model, and the decision neural network generates scheduling of each main canal and the branch canal corresponding to each main canal based on the grade corresponding to each block, the second irrigation water consumption of each block and the influence of meteorological data simulated by the meteorological model on each block.
Preferably, in the data acquisition module, a main starting end and a main ending end of each main canal in the region are respectively recorded, and a branch starting end and a branch ending end of a branch canal on each main canal are recorded; recording the flowing depth of the main flowing line in the area through the main starting end and the main terminating end; the flow depth of the branch flow line in the area is recorded by the branch start end and the branch end.
Preferably, in the block compensation module, the irrigation capacity and coverage of the corresponding block are estimated by acquiring historical irrigation data of the own irrigation system in each block.
Preferably, a plurality of different positions of the farmland of each block are respectively provided with a moisture sensor, and soil moisture content data in each block are acquired based on the moisture sensors.
Preferably, the meteorological model is used for simulating the influence on each block in the region through meteorological data based on the solar terms and the climatic conditions in the region.
Preferably, in the block calculation unit, when a difference between the first irrigation water amount and the first irrigation water supply amount is a positive number and greater than a set initial threshold value; and representing the second irrigation water amount required by the block by using the difference, wherein when the difference between the first irrigation water amount and the first irrigation water amount is a negative number, the second irrigation water amount required by the block is represented as 0.
Preferably, the sequence in the hierarchy is expressed as a scheduling sequence of block water use.
Preferably, in the decision neural network, an irrigation strategy of the meteorological influence area is judged based on the influence, and the irrigation strategy is one of flooding irrigation, flood irrigation and quick irrigation.
The application also provides an irrigation decision-making method based on the agricultural system model, which comprises the following steps:
constructing an agricultural system model: configuring all main channel distribution in an area, main flow lines of each main channel and branch lines of all branch channels on each main channel based on a GIS map, and simultaneously configuring each block distribution correspondingly;
setting a block compensation module: the irrigation system is used for acquiring the self-contained irrigation system in each block, estimating the irrigation capacity of the corresponding block based on the self-contained irrigation system of each block, estimating the coverage area of each block based on the self-contained irrigation system of each block, and converting the irrigation capacity of the corresponding block and the coverage area of the block by the self-contained irrigation system to obtain first irrigation water supply quantity of the self-contained irrigation system;
constructing a decision model: inputting soil moisture content data in each block based on the interface and inputting soil moisture content data in each block based on the interface; calculating a first irrigation water consumption of each block based on the first farmland quantity and soil moisture data in each block; simulating the influence of the meteorological data on each block based on the meteorological data; calculating a second irrigation water amount for each block based on a difference between the first irrigation water amount and the first irrigation water amount for each block under exclusion of meteorological factors; when the difference between the first irrigation water usage and the first irrigation water usage is a positive number and greater than a set initial threshold; representing a second irrigation water amount required by the block by using the difference, wherein when the difference between the first irrigation water amount and the first irrigation water amount is a negative number, the second irrigation water amount required by the block is represented as 0; setting a scheduling time sequence based on the soil moisture content data of each block and the corresponding second irrigation water consumption, and dividing the water consumption of the block into a plurality of grades based on the scheduling time sequence; wherein, the sequence of the grades is expressed as the scheduling sequence of the block water; and generating a schedule for each main canal and the branch canal corresponding to each main canal based on the grade corresponding to the block, the second irrigation water consumption of each block and the influence of the simulated meteorological data on each block in combination with the meteorological model.
Preferentially, farmland distribution data in a region are captured based on satellite images before an agricultural system model is constructed; recording main flow of each main channel in the region and branch flows of all branch channels on each main channel in the region; dividing the farmland in the region into a plurality of blocks by the main flow path of each main channel and the branch flows of all branch channels on each main channel based on the distribution data of the main channels in the region, and enabling at least one main channel/branch channel to flow through each block or between two adjacent blocks.
According to the method, a decision system is constructed, and under the condition that the solar terms, the climate, the distribution of main channels and branch channels and the irrigation system in the region are fully considered, a top-down scheduling is provided, so that the scheduling balance is ensured. Specifically, farmland distribution data in an area is captured based on a satellite image; recording main stream lines of all main channels in the region and branch streams of all branch channels on each main channel in the region; dividing a farmland in a region into a plurality of blocks by a main flow path of each main channel and branch flows of all branch channels on each main channel based on main channel distribution data in the region, and enabling at least one main channel/branch channel to flow through each block or between two adjacent blocks; inputting soil moisture content data in each block based on the interface and inputting soil moisture content data in each block based on the interface; calculating a first irrigation water consumption of each block based on the first farmland quantity and soil moisture data in each block; simulating an effect of the meteorological data on each block based on the meteorological data; under the condition of eliminating meteorological factors, calculating second irrigation water supply of each block based on the difference value of the first irrigation water supply and the first irrigation water supply of each block; when the difference value between the first irrigation water supply amount and the first irrigation water supply amount is positive and is greater than a set initial threshold value; representing a second irrigation water amount required by the block by using the difference, wherein when the difference between the first irrigation water amount and the first irrigation water amount is a negative number, the second irrigation water amount required by the block is represented as 0; setting a scheduling time sequence based on the soil moisture data of each block and the corresponding second irrigation water consumption, and dividing the water consumption of the block into a plurality of grades based on the scheduling time sequence; wherein, the sequence of the grades is expressed as the scheduling sequence of the block water; and generating a schedule for each main canal and the branch canal corresponding to each main canal based on the grade corresponding to the block, the second irrigation water consumption of each block and the influence of the simulated meteorological data on each block in combination with the meteorological model.
Drawings
The invention is illustrated and described only by way of example and not by way of limitation in the scope of the invention as set forth in the following drawings, in which:
FIG. 1 is a schematic diagram of the framework of the system of the present invention;
FIG. 2 is a flow chart of the method of the present invention.
Detailed Description
In order to make the objects, technical solutions, design methods, and advantages of the present invention more apparent, the present invention will be further described in detail by specific embodiments with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
Example 1
Referring to the drawings, the present invention provides an irrigation decision system based on an agricultural system model, comprising:
the data acquisition module is used for capturing farmland distribution data in the region based on the satellite image; recording main stream lines of all main channels in the region and branch streams of all branch channels on each main channel in the region;
the dividing module divides a farmland in a region into a plurality of blocks based on main channel distribution data in the region, a main channel of each main channel and branch channels of all branch channels on each main channel, and enables at least one main channel/branch channel to flow through each block or between two adjacent blocks;
the agricultural system model is used for configuring all main channel distribution in an area, main flow lines of all main channels and branch flow lines of all branch channels on each main channel based on a GIS map, and correspondingly configuring each block distribution;
the block compensation module is used for acquiring the self-contained irrigation system in each block, estimating the irrigation capacity of the corresponding block based on the self-contained irrigation system of each block, estimating the coverage area of each block based on the self-contained irrigation system of each block, and converting the irrigation capacity of the corresponding block and the coverage area of each block by the self-contained irrigation system to obtain first irrigation water supply of the self-contained irrigation system;
a decision model having:
the first input end is used for inputting soil moisture content data in each block based on the interface;
a second input for inputting meteorological data within the area based on the interface;
a meteorological model for simulating the effect of meteorological data on each block based on the meteorological data;
a processing module connected to the agricultural system model for calculating a first irrigation water usage for each block based on the first farmland quantity and soil moisture data within each block;
the decision module is provided with a decision control unit, a decision neural network and a plurality of block calculation units;
each block calculation unit is correspondingly connected with one block, the block calculation unit is connected with the block compensation module, and the block decision unit is used for calculating the second irrigation water consumption of each block based on the difference value of the first irrigation water consumption and the first irrigation water supply of each block under the condition of eliminating meteorological factors;
the decision control unit is connected to the first input end and each block calculation unit, and is used for setting a scheduling time sequence based on soil moisture content data of each block and corresponding second irrigation water consumption, and dividing water consumption of the blocks into a plurality of grades based on the scheduling time sequence;
the decision neural network is connected with the decision control unit and the meteorological model, and the decision neural network generates scheduling of each main canal and the branch canal corresponding to each main canal based on the grade corresponding to each block, the second irrigation water consumption of each block and the influence of meteorological data simulated by the meteorological model on each block.
In the data acquisition module, respectively recording a main starting end and a main terminal end of each main canal in the area, and recording a branch starting end and a branch terminal end of a branch canal on each main canal; recording the flowing depth of the main flowing line in the area through the main starting end and the main terminating end; the flow depth of the branch flow line in the area is recorded through the branch start end and the branch end.
In the block compensation module, the irrigation capacity and coverage of the corresponding block are estimated by acquiring historical irrigation data of the own irrigation system in each block.
In some embodiments, the blocks should be divided according to the distribution of main channels or branch channels, and at least one main channel/branch channel flows in each block or between two adjacent blocks; the extending depth of the main canal or the branch canal in each block is critical to the effect in the block, and it should be considered that the blocks should be divided in sequence according to the trend of the main canal or the branch canal, and the area of each block should not be too large, for example, the blocks can be divided according to the unit of county and town. Of course smaller units are also possible.
In some embodiments, a plurality of different positions of the farmland of each block are respectively provided with a moisture sensor, and soil moisture content data in each block is acquired based on the moisture sensors; in order to obtain more effective data, the moisture sensors are provided in different farmlands for each block.
In some embodiments, the meteorological model is used to model the impact on each block in the region based on the solar terms and the climate conditions within the region from meteorological data. In the decision neural network, judging an irrigation strategy of the weather-affected area based on the influence, wherein the irrigation strategy is one of flooding irrigation, flooding irrigation and quick irrigation.
In some embodiments, the solar terms and climate conditions are decisive for irrigation, reflect the change state of soil moisture in the region in the future to a certain extent, for example, in spring and autumn, dew is formed at night due to early and late temperature reasons, and has a good moisture conservation effect on farmlands, so that the basic scheduling can be judged based on the solar terms and climate conditions.
In some embodiments, the weather conditions are also main factors influencing irrigation, and national weather satellites have high accuracy in weather prediction, so that according to the weather conditions, such as rainy weather in a region in the future, rainfall can be obtained according to a basic weather model, a soil moisture preservation condition can be obtained through the rainfall, whether scheduling irrigation is performed or not can be determined, and what irrigation mode is adopted, such as in the case of transient light rain, the influence on soil moisture preservation is not large, if the soil moisture content condition is serious, the modes of soaking irrigation and flood irrigation should be selected, but continuous rainy weather is met in the period when the soil moisture content is serious, the soil moisture preservation condition on soil is obtained by calculating according to the total rainfall, and if further soil moisture preservation is required, the irrigation mode should be selected to perform rapid irrigation.
In some embodiments, the own irrigation system is somewhat restrictive, such as being inside the same block, and the own irrigation system can function somewhat, leaving the block with negligible effort.
In some embodiments, in the block calculation unit, when a difference between the first irrigation water amount and the first irrigation water supply amount is a positive number and greater than a set initial threshold; and representing the second irrigation water amount required by the block by using the difference, wherein when the difference between the first irrigation water amount and the first irrigation water amount is a negative number, the second irrigation water amount required by the block is represented as 0.
In some embodiments, the agricultural system model is configured based on a GIS map, so that the start and end points of the main and branch channels captured from the satellite images and the recorded main and branch channels within the region can be calibrated by the GIS map. Simultaneously, the distribution in farmland also can snatch through the satellite image, and the farmland distributes and also can mark according to the GIS map.
Preferably, the sequence in the hierarchy is expressed as a scheduling sequence of block water usage.
According to the method, a decision system is constructed, and under the condition that the regional position gas saving, the climate, the distribution of main canals and branch canals and the regional self-irrigation system are fully considered, a top-down scheduling is provided, so that the scheduling balance is ensured. Specifically, farmland distribution data in an area is captured based on a satellite image; recording main stream lines of all main channels in the region and branch streams of all branch channels on each main channel in the region; dividing a farmland in a region into a plurality of blocks by a main channel of each main channel and branch channels of all branch channels on each main channel based on main channel distribution data in the region, and enabling at least one main channel/branch channel to flow through each block or between two adjacent blocks; inputting soil moisture content data in each block based on the interface and inputting soil moisture content data in each block based on the interface; calculating a first irrigation water consumption of each block based on the first farmland quantity and soil moisture data in each block; simulating the influence of the meteorological data on each block based on the meteorological data; calculating a second irrigation water amount for each block based on a difference between the first irrigation water amount and the first irrigation water amount for each block under exclusion of meteorological factors; when the difference between the first irrigation water usage and the first irrigation water usage is a positive number and greater than a set initial threshold; representing a second irrigation water amount required by the block by using the difference, wherein when the difference between the first irrigation water amount and the first irrigation water amount is a negative number, the second irrigation water amount required by the block is represented as 0; setting a scheduling time sequence based on the soil moisture content data of each block and the corresponding second irrigation water consumption, and dividing the water consumption of the block into a plurality of grades based on the scheduling time sequence; wherein, the sequence of the grades is expressed as the scheduling sequence of the block water; and generating a schedule for each main canal and the branch canal corresponding to each main canal based on the grade corresponding to the block, the second irrigation water consumption of each block and the influence of the simulated meteorological data on each block in combination with the meteorological model.
Example 2
Referring to fig. 2, the present application further provides an irrigation decision method based on an agricultural system model, comprising the following steps:
constructing an agricultural system model: configuring all main channel distribution in an area, main flow main lines of each main channel and branch lines of all branch channels on each main channel on the basis of a GIS map, and correspondingly configuring each block distribution;
setting a block compensation module: the irrigation system is used for acquiring the self-contained irrigation system in each block, estimating the irrigation capacity of the corresponding block based on the self-contained irrigation system of each block, estimating the coverage area of each block based on the self-contained irrigation system of each block, and converting the irrigation capacity of the corresponding block and the coverage area of the block by the self-contained irrigation system to obtain first irrigation water supply quantity of the self-contained irrigation system;
constructing a decision model: inputting soil moisture content data in each block based on the interface and inputting soil moisture content data in each block based on the interface; calculating a first irrigation water consumption of each block based on the first farmland quantity and soil moisture data in each block; simulating the influence of the meteorological data on each block based on the meteorological data; calculating a second irrigation water amount for each block based on a difference between the first irrigation water amount and the first irrigation water amount for each block under exclusion of meteorological factors; when the difference value between the first irrigation water supply amount and the first irrigation water supply amount is positive and is greater than a set initial threshold value; representing a second irrigation water amount required by the block by using the difference, wherein when the difference between the first irrigation water amount and the first irrigation water amount is a negative number, the second irrigation water amount required by the block is represented as 0; setting a scheduling time sequence based on the soil moisture data of each block and the corresponding second irrigation water consumption, and dividing the water consumption of the block into a plurality of grades based on the scheduling time sequence; wherein, the sequence of the grades is expressed as the scheduling sequence of the block water; and generating the scheduling of each main canal and the branch canal corresponding to each main canal based on the grade corresponding to the block, the second irrigation water consumption of each block and the influence of the simulated meteorological data combined with the meteorological model on each block.
In the above, before the agricultural system model is constructed, farmland distribution data in an area is captured based on a satellite image; recording main stream lines of all main channels in the region and branch streams of all branch channels on each main channel in the region; dividing the farmland in the region into a plurality of blocks by the main flow path of each main channel and the branch flows of all branch channels on each main channel based on the distribution data of the main channels in the region, and enabling at least one main channel/branch channel to flow through each block or between two adjacent blocks.
In some embodiments, the blocks should be divided according to the distribution of main channels or branch channels, and at least one main channel/branch channel flows in each block or between two adjacent blocks; the extending depth of the main canal or branch canal in each block is very critical to the function in the block, and it should be considered that the blocks should be divided in sequence according to the trend of the main canal or branch canal, and the area of each block should not be too large, for example, the blocks can be divided according to the unit of county and town. Of course smaller units are also possible.
In some embodiments, a plurality of different positions of the farmland of each block are respectively provided with a moisture sensor, and soil moisture content data in each block is acquired based on the moisture sensors; in order to obtain more effective data, the moisture sensors are installed in different fields in each block.
In some embodiments, the meteorological model is used to simulate the effects on each block within a region based on the solar terms and the climatic conditions within the region, and from meteorological data. In the decision neural network, judging an irrigation strategy of the meteorological influence block based on the influence, wherein the irrigation strategy is one of flooding irrigation, flooding irrigation and quick irrigation.
In some embodiments, the solar terms and climate conditions are decisive for irrigation, reflect the change state of soil moisture in the region in the future to a certain extent, for example, in spring and autumn, dew is formed at night due to early and late temperature reasons, and has a good moisture conservation effect on farmlands, so that the basic scheduling can be judged based on the solar terms and climate conditions.
In some embodiments, the weather conditions are also main factors influencing irrigation, and weather satellites in China predict weather with high accuracy, so that according to the weather conditions, such as rainy weather in a region in the future, rainfall can be obtained according to a basic weather model, a soil moisture preservation condition can be obtained through the rainfall, at the moment, whether to perform scheduling irrigation or not can be determined, and what irrigation method is adopted, such as under a transient light rain condition, the influence on soil moisture preservation is not large, if the soil moisture condition is serious, a soaking irrigation and flood irrigation method should be selected, but continuous rainy weather is encountered during the serious soil moisture condition, the soil moisture preservation condition on the soil is calculated according to the total rainfall, and if further soil moisture preservation is needed, at the moment, the irrigation method should be selected for rapid irrigation.
While embodiments of the present invention have been described above, the above description is illustrative, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. An irrigation decision system based on an agricultural system model, comprising:
the data acquisition module is used for capturing farmland distribution data in the region based on the satellite image; recording main stream lines of all main channels in the region and branch streams of all branch channels on each main channel in the region;
the dividing module divides a farmland in the region into a plurality of blocks through a main channel and a branch channel of all branch channels on each main channel based on main channel distribution data in the region, and enables at least one main channel/branch channel to flow through in each block or between two adjacent blocks;
the agricultural system model is used for configuring all main channel distribution in an area, main flow channels of all main channels and branch flow channels of all branch channels on each main channel based on a GIS map, and correspondingly configuring each block distribution;
the block compensation module is used for acquiring the self-contained irrigation system in each block, estimating the irrigation capacity of the corresponding block based on the self-contained irrigation system of each block, estimating the coverage area of each block based on the self-contained irrigation system of each block, and converting the irrigation capacity of the corresponding block and the coverage area of each block by the self-contained irrigation system to obtain first irrigation water supply of the self-contained irrigation system;
a decision model having:
the first input end is used for inputting soil moisture content data in each block based on the interface;
a second input for inputting meteorological data within the area based on the interface;
a meteorological model for simulating the influence of meteorological data on each block based on the meteorological data;
the processing module is connected to the agricultural system model and used for calculating first irrigation water consumption of each block based on the first farmland quantity and soil moisture content data in each block;
the decision module is provided with a decision control unit, a decision neural network and a plurality of block calculation units;
each block calculation unit is correspondingly connected with one block, the block calculation unit is connected with the block compensation module, and the block decision unit is used for calculating the second irrigation water consumption of each block based on the difference value of the first irrigation water consumption and the first irrigation water supply of each block under the condition of eliminating meteorological factors;
the decision control unit is connected to the first input end and each block calculation unit, and is used for setting a scheduling time sequence based on soil moisture content data of each block and the corresponding second irrigation water consumption, and dividing water for the blocks into a plurality of grades based on the scheduling time sequence;
the decision neural network is connected with the decision control unit and the meteorological model, and the decision neural network generates scheduling of each main canal and the branch canal corresponding to each main canal based on the grade corresponding to each block, the second irrigation water consumption of each block and the influence of meteorological data simulated by combining the meteorological model on each block.
2. The agricultural system model-based irrigation decision-making system according to claim 1, wherein in the data acquisition module, a main starting end and a main ending end of each main canal in the area and a branch starting end and a branch ending end of a branch canal on each main canal are respectively recorded; recording the flowing depth of a main flowing line in the area through a main starting end and a main terminal; the flow depth of the branch flow line in the area is recorded through the branch start end and the branch end.
3. The agricultural system model-based irrigation decision system of claim 1, wherein in the block compensation module, the irrigation capacity and coverage for the corresponding block are estimated by obtaining historical irrigation data of the own irrigation system within each block.
4. The model-based irrigation decision system of claim 1 wherein a moisture sensor is provided at each of a plurality of different locations of the agricultural field of each of the blocks, and soil moisture data is obtained within each block based on the moisture sensors.
5. The agricultural system model-based irrigation decision system of claim 1, wherein the meteorological model is configured to simulate the effect on each block in the area based on solar terms and climate conditions within the area from meteorological data.
6. The agricultural system model-based irrigation decision system of claim 1, wherein in the block calculation unit, when a difference between the first irrigation water usage and the first irrigation water supply is a positive number and greater than a set initial threshold; and representing the second irrigation water amount required by the block by using the difference, wherein when the difference between the first irrigation water amount and the first irrigation water amount is a negative number, the second irrigation water amount required by the block is represented as 0.
7. The agricultural system model-based irrigation decision system of claim 1, wherein the precedence order at the levels is expressed as a block water usage scheduling order.
8. The agricultural system model-based irrigation decision system of claim 1, wherein in the decision neural network, an irrigation strategy for weather-affected blocks is determined based on the impact, the irrigation strategy being one of flooding, flooding and fast irrigation.
9. An irrigation decision method based on an agricultural system model is characterized by comprising the following steps:
constructing an agricultural system model: configuring all main channel distribution in an area, main flow main lines of each main channel and branch lines of all branch channels on each main channel on the basis of a GIS map, and correspondingly configuring each block distribution;
setting a block compensation module: the irrigation system management system is used for acquiring the own irrigation system in each block, estimating the irrigation capacity of the corresponding block based on the own irrigation system of each block, estimating the coverage of each block based on the own irrigation system of each block, and converting the irrigation capacity of the corresponding block and the coverage of the block by the own irrigation system to obtain a first irrigation water supply amount of the own irrigation system;
constructing a decision model: inputting soil moisture content data in each block based on the interface and inputting soil moisture content data in each block based on the interface; calculating a first irrigation water consumption of each block based on the first farmland quantity and soil moisture data in each block; simulating an effect of the meteorological data on each block based on the meteorological data; under the condition of eliminating meteorological factors, calculating second irrigation water supply of each block based on the difference value of the first irrigation water supply and the first irrigation water supply of each block; when the difference between the first irrigation water usage and the first irrigation water usage is a positive number and greater than a set initial threshold; representing a second irrigation water amount required by the block by using the difference, wherein when the difference between the first irrigation water amount and the first irrigation water amount is a negative number, the second irrigation water amount required by the block is represented as 0; setting a scheduling time sequence based on the soil moisture content data of each block and the corresponding second irrigation water consumption, and dividing the water consumption of the block into a plurality of grades based on the scheduling time sequence; wherein, the sequence of the grades is expressed as the scheduling sequence of the block water consumption; and generating the scheduling of each main canal and the branch canal corresponding to each main canal based on the grade corresponding to the block, the second irrigation water consumption of each block and the influence of the simulated meteorological data combined with the meteorological model on each block.
10. The agricultural system model-based irrigation decision-making method according to claim 9, wherein prior to building the agricultural system model, farmland distribution data within the area is captured based on satellite images; recording main stream lines of all main channels in the region and branch streams of all branch channels on each main channel in the region; dividing the farmland in the region into a plurality of blocks by the main flow path of each main channel and the branch flows of all branch channels on each main channel based on the distribution data of the main channels in the region, and enabling at least one main channel/branch channel to flow through each block or between two adjacent blocks.
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