CN115644039B - 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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- 230000002262 irrigation Effects 0.000 title claims abstract description 116
- 238000003973 irrigation Methods 0.000 title claims abstract description 116
- 238000000034 method Methods 0.000 title claims abstract description 15
- 239000003621 irrigation water Substances 0.000 claims abstract description 114
- 239000002689 soil Substances 0.000 claims abstract description 50
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 20
- 238000013528 artificial neural network Methods 0.000 claims description 13
- 230000000694 effects Effects 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000004088 simulation Methods 0.000 claims description 3
- 239000003673 groundwater Substances 0.000 description 2
- 238000004321 preservation Methods 0.000 description 2
- 238000002791 soaking Methods 0.000 description 2
- 230000002950 deficient Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000007598 dipping method Methods 0.000 description 1
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Abstract
The application provides an irrigation decision system and method based on an agricultural system model, wherein the method comprises the following steps: grabbing farmland distribution data in the area and main channel distribution data in the area; 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 amount and soil moisture content 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 excluding weather factors; setting a scheduling time sequence based on soil moisture content data of each block and corresponding second irrigation water quantity, and dividing the water of the block into a plurality of grades based on the scheduling time sequence; scheduling of each main channel and the branch channels corresponding to each main channel is generated 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 by combining the meteorological model.
Description
Technical Field
The application relates to the technical field of agriculture, in particular to a technology for making an agricultural irrigation decision, and particularly relates to an irrigation decision system and method based on an agricultural system model.
Background
Traditional water conservancy dispatching is based on feedback of people on farmland management in seasonality, and the dispatching mode is only based on human feedback above the lower part and cannot be calculated as agricultural irrigation dispatching of the system. In China, water resources are very unevenly distributed, and generally south rivers and main channels are distributed in a plurality of ways, so that irrigation in areas can be basically met, but in north, particularly in northwest, the water resources are relatively deficient, at present, in north areas of China, two modes of main channel guiding and groundwater irrigation are basically adopted, and in the same area, such as in the same county, groundwater distribution in different places is extremely unbalanced, so that normal crop irrigation can be ensured in some places, and in other places, crop irrigation mainly depends on main channel supply. In this case, if the scheduling is inaccurate, the feedback adjustment from bottom to top is adopted, which easily causes the uneven scheduling.
Disclosure of Invention
Accordingly, a primary object of the present application is to provide an irrigation decision system and method based on an agricultural system model.
The technical scheme adopted by the application 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 the area based on the satellite images; and all main channel distribution data in the area, recording main flow lines of each main channel in the area and branch flow lines of all branch channels on each main channel;
the dividing module divides the farmland in the area into a plurality of blocks based on the distribution data of the main channels in the area, the main flow line of each main channel and the branch flow lines of all branch channels on each main channel, and at least one main channel/branch channel flow is arranged in each block or between two adjacent blocks;
the agricultural system model is used for configuring all main channel distribution, main flow lines of each main channel and branch flow lines of all branch channels on each main channel in the area based on the GIS map, and correspondingly configuring each block distribution;
the system comprises a block compensation module, a first irrigation water supply module and a second irrigation water supply module, wherein the block compensation module is used for acquiring own irrigation systems in each block, estimating irrigation capacity of the corresponding block based on the own irrigation system of each block, estimating coverage of the block based on the own irrigation system of each block, and converting the irrigation capacity of the corresponding block and the coverage of the own irrigation system to the block to obtain first irrigation water supply capacity of the own irrigation system;
a decision model, the decision model having:
the first input end is used for inputting soil moisture content data in each block based on the interface;
the second input end is used for inputting meteorological data in the area based on the interface;
a weather model for simulating an effect of weather data on each block based on the weather data;
the processing module is connected to the agricultural system model and is 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 computing units;
each block calculating unit is correspondingly connected with one block, and the block calculating unit is connected with a block compensating module, and the block deciding 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 the water consumption of the block 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 the block, the second irrigation water consumption of each block and the influence of the meteorological data on each block by combining the meteorological model simulation.
Preferably, in the data acquisition module, a main starting end and a main ending end of each main channel in the area are recorded respectively, and a supporting starting end and a supporting ending end of a supporting channel on each main channel are recorded; recording the flow depth of a main flow line in an area through a main starting end and a main ending end; the flow depth of the branch flow path in the region is recorded by the branch start end and the branch end.
Preferably, in the block compensation module, the irrigation capacity and coverage of each block is estimated by acquiring historical irrigation data of its own irrigation system within the corresponding 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 area in the area by meteorological data based on solar terms and weather conditions in the area.
Preferably, in the block calculation unit, when the difference between the first irrigation water amount and the first irrigation water supply amount is positive and greater than a set initial threshold; the difference represents the second irrigation water volume required by the block, and when the difference between the first irrigation water volume and the first irrigation water volume is negative, the second irrigation water volume required by the block is represented as 0.
Preferably, the order at the level is expressed as a scheduling order of the block water.
Preferably, in the decision neural network, an irrigation strategy of the weather affected area is determined based on the influence, and the irrigation strategy is one of dipping irrigation, flood irrigation and fast irrigation.
The application also provides an irrigation decision method based on the agricultural system model, which comprises the following steps:
building an agricultural system model: configuring all main channel distribution, main flow lines of each main channel and branch flow lines of all branch channels on each main channel in the area based on a GIS map, and correspondingly configuring each block distribution;
setting a block compensation module: the method comprises the steps of obtaining own irrigation systems in each block, estimating irrigation capacity of a corresponding block based on the own irrigation system of each block, estimating coverage of the block based on the own irrigation system of each block, and converting the irrigation capacity of the corresponding block and the coverage of the own irrigation system to the block to obtain first irrigation water supply 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 amount and soil moisture content 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 excluding weather factors; when the difference between the first irrigation water consumption and the first irrigation water supply is positive and is greater than the set initial threshold; representing the second irrigation water consumption required by the block by the difference, wherein when the difference between the first irrigation water consumption and the first irrigation water supply is negative, the second irrigation water consumption required by the block is represented as 0; setting a scheduling time sequence based on soil moisture content data of each block and corresponding second irrigation water quantity, and dividing the water of the block into a plurality of grades based on the scheduling time sequence; the sequence of the levels is expressed as the scheduling sequence of the water for the block; scheduling of each main channel and the branch channels corresponding to each main channel is generated 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 by combining the meteorological model.
Preferably, before the agricultural system model is built, farmland distribution data in the satellite image capturing area are based; and all main channel distribution data in the area, recording main flow lines of each main channel in the area and branch flow lines of all branch channels on each main channel; based on the distribution data of the main channels in the area, the main flow line of each main channel and the branch flow lines of all branch channels on each main channel, the farmland in the area is divided into a plurality of blocks, and at least one main channel/branch channel flows in each block or between two adjacent blocks.
The application provides a top-down scheduling by constructing a decision-making system under the condition of fully considering the distribution of the regional position solar terms, climate, main channels and branch channels and the own irrigation system in the region, thereby ensuring the uniform scheduling. Specifically, based on farmland distribution data in a satellite image capturing area; and all main channel distribution data in the area, recording main flow lines of each main channel in the area and branch flow lines of all branch channels on each main channel; dividing a farmland in the area into a plurality of blocks based on the distribution data of main channels in the area, main flow lines of each main channel and branch flow lines of all branch channels on each main channel, and enabling at least one main channel/branch channel to flow in 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 amount and soil moisture content 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 excluding weather factors; when the difference between the first irrigation water consumption and the first irrigation water supply is positive and is greater than the set initial threshold; representing the second irrigation water consumption required by the block by the difference, wherein when the difference between the first irrigation water consumption and the first irrigation water supply is negative, the second irrigation water consumption required by the block is represented as 0; setting a scheduling time sequence based on soil moisture content data of each block and corresponding second irrigation water quantity, and dividing the water of the block into a plurality of grades based on the scheduling time sequence; the sequence of the levels is expressed as the scheduling sequence of the water for the block; scheduling of each main channel and the branch channels corresponding to each main channel is generated 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 by combining the meteorological model.
Drawings
The following drawings are illustrative of the application and are not intended to limit the scope of the application, in which:
FIG. 1 is a schematic diagram of a frame of a system of the present application;
fig. 2 is a flow chart of the method of the present application.
Detailed Description
The present application will be further described in detail with reference to the following specific examples, which are given by way of illustration, in order to make the objects, technical solutions, design methods and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
Example 1
Referring to the figures, the present application 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 area based on the satellite images; and all main channel distribution data in the area, recording main flow lines of each main channel in the area and branch flow lines of all branch channels on each main channel;
the dividing module divides the farmland in the area into a plurality of blocks based on the distribution data of the main channels in the area, the main flow line of each main channel and the branch flow lines of all branch channels on each main channel, and at least one main channel/branch channel flow is arranged in each block or between two adjacent blocks;
the agricultural system model is used for configuring all main channel distribution, main flow lines of each main channel and branch flow lines of all branch channels on each main channel in the area based on the GIS map, and correspondingly configuring each block distribution;
the system comprises a block compensation module, a first irrigation water supply module and a second irrigation water supply module, wherein the block compensation module is used for acquiring own irrigation systems in each block, estimating irrigation capacity of the corresponding block based on the own irrigation system of each block, estimating coverage of the block based on the own irrigation system of each block, and converting the irrigation capacity of the corresponding block and the coverage of the own irrigation system to the block to obtain first irrigation water supply capacity of the own irrigation system;
a decision model, the decision model having:
the first input end is used for inputting soil moisture content data in each block based on the interface;
the second input end is used for inputting meteorological data in the area based on the interface;
a weather model for simulating an effect of weather data on each block based on the weather data;
the processing module is connected to the agricultural system model and is 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 computing units;
each block calculating unit is correspondingly connected with one block, and the block calculating unit is connected with a block compensating module, and the block deciding 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 the water consumption of the block 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 the block, the second irrigation water consumption of each block and the influence of the meteorological data on each block by combining the meteorological model simulation.
In the data acquisition module, the main starting end and the main ending end of each main channel in the area and the supporting starting end and the supporting ending end of the supporting channel on each main channel are recorded respectively; recording the flow depth of a main flow line in an area through a main starting end and a main ending end; the flow depth of the branch flow path in the region is recorded by the branch start end and the branch end.
In the block compensation module, the irrigation capacity and coverage of each block are estimated by acquiring historical irrigation data of the own irrigation system in the corresponding block.
In some embodiments, the division of blocks should be divided according to the distribution of main channels or side channels, and such that there is at least one main channel/side channel flow within each block or between two adjacent blocks; the extending depth of the main channel or the branch channel in each block is critical to the function in the block, and it is also considered that the blocks should be divided according to the trend of the main channel or the branch channel, and the area of each block should not be too large, for example, the blocks can be divided according to village and town units. Of course, smaller units are also possible.
In some embodiments, moisture sensors are respectively arranged at a plurality of different positions of the farmland of each block, and soil moisture content data in each block are acquired based on the moisture sensors; when setting up the moisture sensor, should set up according to different crops, the even depth of moisture sensor is also crucial to the crop, in order to obtain more effective data, sets up the moisture sensor in each area in different farmland respectively.
In some embodiments, the meteorological model is used to simulate the effect on each zone within an area based on solar terms and climate conditions within the area by meteorological data. In the decision neural network, an irrigation strategy of a weather-affected zone is determined based on the impact, the irrigation strategy being one of dip irrigation, flood irrigation and fast irrigation.
In some embodiments, the conditions of the solar terms and climate have a decisive effect on irrigation, and the conditions of the solar terms and climate reflect the change state of soil moisture in the area at future time to some extent, for example, in spring and autumn, dew is formed at night due to the early and late temperature, and dew has a good soil moisture preservation effect on farmlands, so that the basic scheduling can be judged based on the conditions of the solar terms and climate.
In some embodiments, weather conditions are also main factors affecting irrigation, and weather conditions such as weather conditions in the future are predicted by weather satellites in China, so that rainfall can be obtained according to a basic weather model, soil moisture conservation can be obtained according to the rainfall, at the moment, whether scheduling irrigation is performed or not can be determined, and the irrigation mode is not greatly affected, for example, under short-term small rainfall, if the soil moisture condition is serious, the irrigation mode of soaking irrigation and flooding irrigation should be selected, but continuous overcast weather is encountered during the serious soil moisture condition period, the soil moisture conservation condition is calculated according to the total rainfall, and if further soil moisture conservation is needed, the irrigation mode should be selected.
In some embodiments, the own irrigation system has certain limitations, such as being within the same block, the own irrigation system can function somewhat, leaving the block with negligible effect.
In some embodiments, in the block calculation unit, when the difference between the first irrigation water amount and the first irrigation water amount is positive and greater than a set initial threshold; the difference represents the second irrigation water volume required by the block, and when the difference between the first irrigation water volume and the first irrigation water volume is negative, the second irrigation water volume required by the block is represented as 0.
In some embodiments, the present application is configured on the basis of a GIS map in the agricultural system model, so that the starting points and ending points of the main channels and the branch channels and the recorded main channels and branch channels in the areas can be calibrated by the GIS map when the main channels and the branch channels are grabbed from the satellite images. Meanwhile, the distribution of farmlands can be grasped through satellite images, and the distribution of farmlands can be calibrated according to a GIS map.
Preferably, the order at the level is expressed as a scheduling order of the block water.
The application provides a top-down scheduling by constructing a decision-making system under the condition of fully considering the distribution of the regional position solar terms, climate, main channels and branch channels and the own irrigation system in the region, thereby ensuring the uniform scheduling. Specifically, based on farmland distribution data in a satellite image capturing area; and all main channel distribution data in the area, recording main flow lines of each main channel in the area and branch flow lines of all branch channels on each main channel; dividing a farmland in the area into a plurality of blocks based on the distribution data of main channels in the area, main flow lines of each main channel and branch flow lines of all branch channels on each main channel, and enabling at least one main channel/branch channel to flow in 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 amount and soil moisture content 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 excluding weather factors; when the difference between the first irrigation water consumption and the first irrigation water supply is positive and is greater than the set initial threshold; representing the second irrigation water consumption required by the block by the difference, wherein when the difference between the first irrigation water consumption and the first irrigation water supply is negative, the second irrigation water consumption required by the block is represented as 0; setting a scheduling time sequence based on soil moisture content data of each block and corresponding second irrigation water quantity, and dividing the water of the block into a plurality of grades based on the scheduling time sequence; the sequence of the levels is expressed as the scheduling sequence of the water for the block; scheduling of each main channel and the branch channels corresponding to each main channel is generated 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 by combining the meteorological model.
Example 2
Referring to fig. 2, the application also provides an irrigation decision method based on an agricultural system model, comprising the following steps:
building an agricultural system model: configuring all main channel distribution, main flow lines of each main channel and branch flow lines of all branch channels on each main channel in the area based on a GIS map, and correspondingly configuring each block distribution;
setting a block compensation module: the method comprises the steps of obtaining own irrigation systems in each block, estimating irrigation capacity of a corresponding block based on the own irrigation system of each block, estimating coverage of the block based on the own irrigation system of each block, and converting the irrigation capacity of the corresponding block and the coverage of the own irrigation system to the block to obtain first irrigation water supply 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 amount and soil moisture content 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 excluding weather factors; when the difference between the first irrigation water consumption and the first irrigation water supply is positive and is greater than the set initial threshold; representing the second irrigation water consumption required by the block by the difference, wherein when the difference between the first irrigation water consumption and the first irrigation water supply is negative, the second irrigation water consumption required by the block is represented as 0; setting a scheduling time sequence based on soil moisture content data of each block and corresponding second irrigation water quantity, and dividing the water of the block into a plurality of grades based on the scheduling time sequence; the sequence of the levels is expressed as the scheduling sequence of the water for the block; scheduling of each main channel and the branch channels corresponding to each main channel is generated 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 by combining the meteorological model.
In the above, before constructing the agricultural system model, the farmland distribution data in the region is grabbed based on satellite images; and all main channel distribution data in the area, recording main flow lines of each main channel in the area and branch flow lines of all branch channels on each main channel; based on the distribution data of the main channels in the area, the main flow line of each main channel and the branch flow lines of all branch channels on each main channel, the farmland in the area is divided into a plurality of blocks, and at least one main channel/branch channel flows in each block or between two adjacent blocks.
In some embodiments, the division of blocks should be divided according to the distribution of main channels or side channels, and such that there is at least one main channel/side channel flow within each block or between two adjacent blocks; the extending depth of the main channel or the branch channel in each block is critical to the function in the block, and it is also considered that the blocks should be divided according to the trend of the main channel or the branch channel, and the area of each block should not be too large, for example, the blocks can be divided according to village and town units. Of course, smaller units are also possible.
In some embodiments, moisture sensors are respectively arranged at a plurality of different positions of the farmland of each block, and soil moisture content data in each block are acquired based on the moisture sensors; when setting up the moisture sensor, should set up according to different crops, the even depth of moisture sensor is also crucial to the crop, in order to obtain more effective data, sets up the moisture sensor in each area in different farmland respectively.
In some embodiments, the meteorological model is used to simulate the effect on each zone within an area based on solar terms and climate conditions within the area by meteorological data. In the decision neural network, an irrigation strategy of a weather-affected zone is determined based on the impact, the irrigation strategy being one of dip irrigation, flood irrigation and fast irrigation.
In some embodiments, the conditions of the solar terms and climate have a decisive effect on irrigation, and the conditions of the solar terms and climate reflect the change state of soil moisture in the area at future time to some extent, for example, in spring and autumn, dew is formed at night due to the early and late temperature, and dew has a good soil moisture preservation effect on farmlands, so that the basic scheduling can be judged based on the conditions of the solar terms and climate.
In some embodiments, weather conditions are also main factors affecting irrigation, and weather conditions such as weather conditions in the future are predicted by weather satellites in China, so that rainfall can be obtained according to a basic weather model, soil moisture conservation can be obtained according to the rainfall, at the moment, whether scheduling irrigation is performed or not can be determined, and the irrigation mode is not greatly affected, for example, under short-term small rainfall, if the soil moisture condition is serious, the irrigation mode of soaking irrigation and flooding irrigation should be selected, but continuous overcast weather is encountered during the serious soil moisture condition period, the soil moisture conservation condition is calculated according to the total rainfall, and if further soil moisture conservation is needed, the irrigation mode should be selected.
The foregoing description of embodiments of the application has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the technical improvements 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-making system based on an agricultural system model, comprising:
the data acquisition module is used for capturing farmland distribution data in the area based on the satellite images; and all main channel distribution data in the area, recording main flow lines of each main channel in the area and branch flow lines of all branch channels on each main channel;
the dividing module divides the farmland in the area into a plurality of blocks based on the distribution data of the main channels in the area, the main flow line of each main channel and the branch flow lines of all branch channels on each main channel, and at least one main channel/branch channel flow is arranged in each block or between two adjacent blocks;
the agricultural system model is used for configuring all main channel distribution, main flow lines of each main channel and branch flow lines of all branch channels on each main channel in the area based on the GIS map, and correspondingly configuring each block distribution;
the system comprises a block compensation module, a first irrigation water supply module and a second irrigation water supply module, wherein the block compensation module is used for acquiring own irrigation systems in each block, estimating irrigation capacity of the corresponding block based on the own irrigation system of each block, estimating coverage of the block based on the own irrigation system of each block, and converting the irrigation capacity of the corresponding block and the coverage of the own irrigation system to the block to obtain first irrigation water supply capacity of the own irrigation system;
a decision model, the decision model having:
the first input end is used for inputting soil moisture content data in each block based on the interface;
the second input end is used for inputting meteorological data in the area based on the interface;
a weather model for simulating an effect of weather data on each block based on the weather data;
the processing module is connected to the agricultural system model and is 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 computing units;
each block calculating unit is correspondingly connected with one block, and the block calculating unit is connected with a block compensating module, and the block deciding 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 the water consumption of the block 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 the block, the second irrigation water consumption of each block and the influence of the meteorological data on each block by combining the meteorological model simulation.
2. The agricultural system model-based irrigation decision system of claim 1, wherein in the data acquisition module, a main start end and a main end of each main canal in the area are recorded, and a branch start end and a branch end of a branch canal on each main canal are recorded, respectively; recording the flow depth of a main flow line in an area through a main starting end and a main ending end; the flow depth of the branch flow path in the region is recorded by 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, irrigation capacity and coverage of each block is estimated by obtaining historical irrigation data of its own irrigation system within the corresponding block.
4. The agricultural system model-based irrigation decision system of claim 1, wherein moisture sensors are respectively provided at a plurality of different positions of the farmland of each of the blocks, and soil moisture content data in each of the blocks is acquired 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 zone of the area based on solar terms and climate conditions within the area by meteorological data.
6. The agricultural system model-based irrigation decision system according to claim 1, wherein in the block calculation unit, when a difference between the first irrigation water amount and the first irrigation water amount is a positive number and is greater than a set initial threshold; the difference represents the second irrigation water volume required by the block, and when the difference between the first irrigation water volume and the first irrigation water volume is negative, the second irrigation water volume required by the block is represented as 0.
7. The agricultural system model based irrigation decision system of claim 1 wherein the order at the level is expressed as a scheduling order for block water.
8. The agricultural system model-based irrigation decision system of claim 1, wherein in the decision neural network, an irrigation strategy of a weather affected zone is determined based on the impact, the irrigation strategy being one of dip irrigation, flood irrigation, and fast irrigation.
9. The irrigation decision method based on the agricultural system model is characterized by comprising the following steps of:
building an agricultural system model: configuring all main channel distribution, main flow lines of each main channel and branch flow lines of all branch channels on each main channel in the area based on a GIS map, and correspondingly configuring each block distribution;
setting a block compensation module: the method comprises the steps of obtaining own irrigation systems in each block, estimating irrigation capacity of a corresponding block based on the own irrigation system of each block, estimating coverage of the block based on the own irrigation system of each block, and converting the irrigation capacity of the corresponding block and the coverage of the own irrigation system to the block to obtain first irrigation water supply 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 amount and soil moisture content 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 excluding weather factors; when the difference between the first irrigation water consumption and the first irrigation water supply is positive and is greater than the set initial threshold; representing the second irrigation water consumption required by the block by the difference, wherein when the difference between the first irrigation water consumption and the first irrigation water supply is negative, the second irrigation water consumption required by the block is represented as 0; setting a scheduling time sequence based on soil moisture content data of each block and corresponding second irrigation water quantity, and dividing the water of the block into a plurality of grades based on the scheduling time sequence; the sequence of the levels is expressed as the scheduling sequence of the water for the block; scheduling of each main channel and the branch channels corresponding to each main channel is generated 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 by combining the meteorological model.
10. The agricultural system model-based irrigation decision method of claim 9, wherein prior to constructing the agricultural system model, the agricultural system model is based on farmland distribution data in the satellite image capture area; and all main channel distribution data in the area, recording main flow lines of each main channel in the area and branch flow lines of all branch channels on each main channel; based on the distribution data of the main channels in the area, the main flow line of each main channel and the branch flow lines of all branch channels on each main channel, the farmland in the area is divided into a plurality of blocks, and at least one main channel/branch channel flows in each block or between two adjacent blocks.
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