A digital twin system and method for agricultural waterlogging disasters

Abstract

The present invention discloses a digital twin system and method for farmland waterlogging disasters, and relates to the technical field of data analysis and processing. The present invention obtains geographic data of a specific agricultural production area, data of existing farmland flood control and drainage projects, and observation data such as precipitation and runoff in the environment where the basin is located, integrates general hydrological and hydrodynamic models, crop waterlogging models, etc. to form a farmland waterlogging disaster analysis model, and then combines real-time environmental observation data such as rainfall and channel runoff with the analysis model; a digital twin method is used to establish a digital twin model of agricultural waterlogging disasters at the basin-field scale, and real-time environmental observation data is brought into the digital twin model of agricultural waterlogging disasters at the basin-field scale to generate agricultural flood disaster warning signals, which can minimize the impact of disasters, reduce social and economic losses, and protect people's lives and property.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a digital twin system and method for agricultural waterlogging disasters. Background Art

[0002] Digital twin technology originated from the field of industrial manufacturing. Its key significance is to achieve two-way mapping and dynamic interaction between real physical entities and network virtual entities. In recent years, the rise of digital twin technology has attracted much attention. It uses data information such as sensors and operating status to monitor, diagnose, simulate, make decisions, and control the entire life cycle of physical entities through virtual-real interactive feedback, data fusion analysis, and decision-making iterative optimization.

[0003] With the development of technologies such as 5G, Beidou, artificial intelligence, and big data, digital twin technology has gradually become practical, and using digital twin technology to promote the digital transformation and upgrading of the water conservancy industry has become a hot topic. Under the overall guidance of the Ministry of Water Resources, the construction of digital twin basins, digital twin water networks, and digital twin projects is progressing steadily. However, the existing processing system has problems with imperfect data bases and lacks a unified model platform for data processing, resulting in a long flood control business process, inability to achieve one-stop operations, and inability to meet the timeliness of flood control warning work. This leads to a lack of unified dispatching and command, resulting in the flood control department's overall control and dispatching and command capabilities for emergency events being weak.

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to form a farmland waterlogging disaster evaluation model by acquiring geographical data within the basin, existing flood control and drainage engineering data, and environmental data in the environment of the basin, integrating general hydrological and hydrodynamic models, crop waterlogging models, etc., and then combining real-time environmental observation data of rainfall and channel runoff with the evaluation model, establishing a basin-field scale agricultural waterlogging disaster digital twin model based on a digital twin method, substituting real-time environmental data into the basin-field scale agricultural waterlogging disaster digital twin model, generating an agricultural flood disaster prevention signal, selecting a disaster emergency plan corresponding to the level from a database management unit according to the level signal, and selecting one of the plans as the selected plan according to the effective value of simulation training and outputting it, which can minimize the impact of disasters, reduce social and economic losses, and protect people's lives and property.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: an agricultural waterlogging disaster digital twin system, including a data integration unit, a database management unit, a twin model establishment unit, an abnormal state analysis unit and a plan output unit, wherein:

[0007] The data integration unit obtains geographic data within the basin, existing flood control and drainage project data, and environmental data in the environment where the basin is located, and regularly updates environmental data changes, and sends the geographic data and environmental data to the database management unit for storage;

[0008] The database management unit stores emergency plans for different flood disaster levels, processes geographic data and environmental data separately, integrates common hydrological and hydrodynamic models, crop waterlogging models, etc. to form a farmland waterlogging disaster assessment model and derives the key flood disaster prevention basin sections and flood disaster prevention time periods;

[0009] The twin model building unit obtains the preview model from the database management unit, combines the real-time environmental observation data of rainfall and channel runoff with the evaluation model, couples the crop growth model and builds a digital twin model of agricultural waterlogging disasters at the watershed-field scale based on the digital twin method;

[0010] The abnormal state analysis unit obtains real-time environmental data, makes risk judgments on the real-time environmental data, generates abnormal risk signals, substitutes the real-time environmental data into the digital twin model of agricultural waterlogging disasters at the watershed-field scale, generates agricultural flood disaster prevention signals, judges the signal level, and outputs the judgment results to the plan output unit;

[0011] After obtaining the judgment result, the plan output unit selects the disaster emergency plan corresponding to the level from the database management unit according to the level signal, including the primary emergency plan and the alternative emergency plan, and sequentially substitutes the primary emergency plan and the alternative emergency plan into the digital twin model of agricultural waterlogging disaster at the watershed-field scale for simulation training. According to the effective value of the simulation training, one of the plans is selected as the selected plan and output.

[0012] Furthermore, the data integration unit includes a geographic data acquisition module and an environmental data acquisition module. The geographic data acquisition module is used to acquire geographic data within the river basin and existing flood control and drainage project data, and the geographic data changes are updated regularly. The environmental data acquisition module is used to acquire environmental data of the river basin and the environmental data changes are updated regularly. It also includes a historical data twin model establishment module, a core data and flood disaster relationship module, and a core data regulation module.

[0013] Furthermore, the database management unit includes a flood disaster plan storage module and a data classification module, wherein:

[0014] The flood disaster plan storage module is used to store emergency plans for different flood disaster levels. There are two emergency plans for each flood disaster level, namely, a primary emergency plan and an alternative emergency plan.

[0015] The data classification unit establishes a watershed model based on the geographic database, and then analyzes the data change rules to establish a preview model. At the same time, it conducts rule analysis based on environmental data changes to derive key flood disaster prevention periods, and classifies and manages the preview model and rule analysis results to form a watershed database.

[0016] Furthermore, the specific method of establishing a digital twin model of agricultural waterlogging disasters at the basin-field scale based on digital twins is as follows:

[0017] S1. Substitute the real-time environmental data into the data processing system to remove errors and then convert it into the basic data of the digital twin;

[0018] S2. Determine the composition of twin data according to the type of basic data, and then determine the construction requirements of twin data. Based on the construction requirements of twin data, determine the preprocessing method and storage method of environmental data and geographic data;

[0019] S3. According to the watershed distribution of the preview model, the environmental data is brought into the preview model according to the watershed distribution, the environmental changes in the watershed are digitally described, and the preview model is converted into a digital twin model of agricultural waterlogging disasters at the watershed-field scale;

[0020] S4. Use the digital twin model of agricultural waterlogging disasters at the watershed-field scale to simulate flood disaster scenarios generated as environmental data changes, and continuously optimize the model simulation results based on the data level and simulation results to obtain a precise digital twin model of agricultural waterlogging disasters at the watershed-field scale.

[0021] Furthermore, the process of risk assessment for real-time environmental data is as follows:

[0022] Sa. Acquire real-time environmental data, wherein the real-time environmental data includes air humidity Bt, rainfall Qt, ambient wind speed Vt and water flow change rate θt in the watershed, wherein the air humidity Bt is monitored by multiple humidity sensors arranged in the watershed, the rainfall Qt is obtained through real-time monitoring data of the meteorological platform, the ambient wind speed Vt is monitored by multiple wind speed sensors arranged in the watershed, and the water flow change rate θt is monitored by multiple flow velocity sensors arranged in the watershed;

[0023] Sb, normalize the real-time environmental data in the key river basins of flood disasters, and calculate the risk coefficient η according to the following formula: , where e1 is the correlation coefficient of air humidity Bt, e2 is the correlation coefficient of rainfall Qt, and e3 is the correlation coefficient of ambient wind speed Vt;

[0024] Sc. Obtain a preset risk factor threshold η0, and perform a threshold judgment on the risk factor η: if η>η0, generate an abnormal risk signal;

[0025] If η≦η0, no abnormal risk signal is generated.

[0026] The present invention also provides a flood disaster digital twin method, comprising the following steps:

[0027] Step 1: Obtain geographic data within the watershed, existing flood control and drainage engineering data, and environmental data in the environment where the watershed is located, and regularly update environmental data changes, and send the geographic data and environmental data to the database management unit and save them;

[0028] Step 2: Process the geographic data and environmental data separately, integrate the general hydrological and hydrodynamic models, crop waterlogging models, etc. to form a farmland waterlogging disaster assessment model and derive the key flood disaster prevention basin sections and flood disaster prevention time periods;

[0029] Step 3: Combine the real-time environmental observation data of rainfall and channel runoff with the evaluation model, and establish a digital twin model of agricultural waterlogging disasters at the watershed-field scale based on the digital twin method;

[0030] Step 4: After making a risk assessment on the real-time environmental data and generating an abnormal risk signal, the real-time environmental data is substituted into the digital twin model of agricultural waterlogging disasters at the watershed-field scale to generate an agricultural flood disaster prevention signal, the signal level is assessed, and the assessment result is output and sent to the plan output unit;

[0031] Step 5. After obtaining the judgment result, select the disaster emergency plan corresponding to the level from the database management unit according to the level signal, including the primary emergency plan and the alternative emergency plan, and substitute the primary emergency plan and the alternative emergency plan into the digital twin model of agricultural waterlogging disaster at the watershed-field scale for simulation training. Select one of the plans as the selected plan according to the effective value of the simulation training and output it.

[0032] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0033] The agricultural waterlogging disaster digital twin system and method obtains geographic data within the basin, existing flood control and drainage engineering data, and environmental data in the basin environment, integrates general hydrological and hydrodynamic models, crop waterlogging models, etc. to form a farmland waterlogging disaster evaluation model, then combines rainfall and channel runoff real-time environmental observation data with the evaluation model, and establishes a basin-field scale agricultural waterlogging disaster digital twin model based on the digital twin method. The real-time environmental data is substituted into the basin-field scale agricultural waterlogging disaster digital twin model to generate agricultural flood disaster prevention signals, selects disaster emergency plans corresponding to the level from the database management unit according to the level signal, and selects one of the plans as the selected plan according to the effective value of the simulation training and outputs it, which can minimize the impact of disasters, reduce social and economic losses, and protect people's lives and property. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 A schematic diagram of the system flow of the present invention is shown;

[0035] Figure 2 The schematic diagram of the output flow of the scheme for segmented watersheds of the present invention is shown;

[0036] Figure 3 A schematic flow chart of the method of the present invention is shown. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Embodiment 1:

[0038] like Figure 1-2 As shown, a digital twin system for agricultural waterlogging disasters includes a data integration unit, a database management unit, a twin model establishment unit, an abnormal state analysis unit and a plan output unit, wherein:

[0039] The data integration unit obtains geographic data within the basin, existing flood control and drainage project data, and environmental data in the environment where the basin is located, and regularly updates environmental data changes, and sends the geographic data and environmental data to the database management unit for storage;

[0040] The data integration unit includes a geographic data acquisition module and an environmental data acquisition module. The geographic data acquisition module is used to acquire geographic data within the basin and existing flood control and drainage project data, and regularly updates the geographic data changes. The environmental data acquisition module is used to acquire environmental data of the basin and regularly updates the environmental data changes. It also includes a historical data twin model establishment module, a core data and flood disaster relationship module, and a core data regulation module.

[0041] The main purpose of building a twin model of historical data is to establish a relationship model between core data and flood disasters. Based on the relationship model, the core data can be adjusted to predict flood disasters. At the same time, unit predictions can be established based on the twin model of real-time data for comparison.

[0042] The database management unit stores emergency plans for different flood disaster levels, processes geographic data and environmental data separately, integrates common hydrological and hydrodynamic models, crop waterlogging models, etc. to form a farmland waterlogging disaster assessment model and derives the key flood disaster prevention basin sections and flood disaster prevention time periods;

[0043] The database management unit includes a flood disaster plan storage module and a data classification module, among which:

[0044] The flood disaster plan storage module is used to store emergency plans for different flood disaster levels. There are two emergency plans for each flood disaster level, namely, a primary emergency plan and an alternative emergency plan.

[0045] The data classification unit establishes a watershed model based on the geographic database, and then analyzes the data change rules to establish a preview model. At the same time, it conducts rule analysis based on environmental data changes to derive key flood disaster prevention periods, and classifies and manages the preview model and rule analysis results to form a watershed database.

[0046] The twin model building unit obtains the preview model from the database management unit, combines the real-time environmental observation data of rainfall and channel runoff with the evaluation model, couples the crop growth model and builds a digital twin model of agricultural waterlogging disasters at the watershed-field scale based on the digital twin method;

[0047] The specific method of establishing a digital twin model of agricultural waterlogging disasters at the basin-field scale based on digital twins is as follows:

[0048] S1. Substitute the real-time environmental data into the data processing system to remove errors and then convert it into the basic data of the digital twin;

[0049] S2. Determine the composition of twin data according to the type of basic data, and then determine the construction requirements of twin data. Based on the construction requirements of twin data, determine the preprocessing method and storage method of environmental data and geographic data;

[0050] S3. According to the watershed distribution of the preview model, the environmental data is brought into the preview model according to the watershed distribution, the environmental changes in the watershed are digitally described, and the preview model is converted into a digital twin model of agricultural waterlogging disasters at the watershed-field scale;

[0051] S4. Use the digital twin model of agricultural waterlogging disasters at the watershed-field scale to simulate flood disaster scenarios generated as environmental data changes, and continuously optimize the model simulation results based on the data level and simulation results to obtain a precise digital twin model of agricultural waterlogging disasters at the watershed-field scale.

[0052] The abnormal state analysis unit obtains real-time environmental data, makes risk judgments on the real-time environmental data, generates abnormal risk signals, substitutes the real-time environmental data into the digital twin model of agricultural waterlogging disasters at the watershed-field scale, generates agricultural flood disaster prevention signals, judges the signal level, and outputs the judgment results to the plan output unit;

[0053] The process of risk assessment for real-time environmental data is as follows:

[0054] Sa. Acquire real-time environmental data, wherein the real-time environmental data includes air humidity Bt, rainfall Qt, ambient wind speed Vt and water flow change rate θt in the watershed, wherein the air humidity Bt is monitored by multiple humidity sensors arranged in the watershed, the rainfall Qt is obtained through real-time monitoring data of the meteorological platform, the ambient wind speed Vt is monitored by multiple wind speed sensors arranged in the watershed, and the water flow change rate θt is monitored by multiple flow velocity sensors arranged in the watershed;

[0055] Sb, normalize the real-time environmental data in the key river basins of flood disasters, and calculate the risk coefficient η according to the following formula: , where e1 is the correlation coefficient of air humidity Bt, e2 is the correlation coefficient of rainfall Qt, and e3 is the correlation coefficient of ambient wind speed Vt;

[0056] Sc. Obtain a preset risk factor threshold η0, and perform a threshold judgment on the risk factor η: if η>η0, generate an abnormal risk signal;

[0057] If η≦η0, no abnormal risk signal is generated.

[0058] After obtaining the judgment result, the plan output unit selects the disaster emergency plan corresponding to the level from the database management unit according to the level signal, including the primary emergency plan and the alternative emergency plan, and sequentially substitutes the primary emergency plan and the alternative emergency plan into the digital twin model of agricultural waterlogging disaster at the watershed-field scale for simulation training. According to the effective value of the simulation training, one of the plans is selected as the selected plan and output.

[0059] Based on the digital twin method, a digital twin model of agricultural waterlogging disaster at the watershed-field scale is established, and the digital twin model of agricultural waterlogging disaster at the watershed-field scale is segmented. For each section of the digital twin model of agricultural waterlogging disaster at the watershed-field scale, an agricultural flood disaster prevention signal is generated, and a corresponding disaster emergency plan is selected. The feasibility of the disaster emergency plan of the digital twin model of agricultural waterlogging disaster at the watershed-field scale of each section is integrated and calculated to form an overall output plan for the watershed. Embodiment 2:

[0060] like Figure 3 As shown, the present invention also provides a flood disaster digital twin method, comprising the following steps:

[0061] Step 1: Obtain geographic data within the watershed, existing flood control and drainage engineering data, and environmental data in the environment where the watershed is located, and regularly update environmental data changes, and send the geographic data and environmental data to the database management unit and save them;

[0062] Step 2: Process the geographic data and environmental data separately, integrate the general hydrological and hydrodynamic models, crop waterlogging models, etc. to form a farmland waterlogging disaster assessment model and derive the key flood disaster prevention basin sections and flood disaster prevention time periods;

[0063] Step 3: Combine the real-time environmental observation data of rainfall and channel runoff with the evaluation model, couple the crop growth model and establish a digital twin model of agricultural waterlogging disasters at the watershed-field scale based on the digital twin method;

[0064] Step 4: After making a risk assessment on the real-time environmental data and generating an abnormal risk signal, the real-time environmental data is substituted into the digital twin model of agricultural waterlogging disasters at the watershed-field scale to generate an agricultural flood disaster prevention signal, the signal level is assessed, and the assessment result is output and sent to the plan output unit;

[0065] Step 5. After obtaining the judgment result, select the disaster emergency plan corresponding to the level from the database management unit according to the level signal, including the primary emergency plan and the alternative emergency plan, and substitute the primary emergency plan and the alternative emergency plan into the digital twin model of agricultural waterlogging disaster at the watershed-field scale for simulation training. Select one of the plans as the selected plan according to the effective value of the simulation training and output it.

[0066] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technical personnel in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0067] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0068] Those skilled in the art can appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware; whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution; professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application;

[0069] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways; for example, the device embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed; another point, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms;

[0070] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module;

[0071] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0072] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A digital twin system for agricultural waterlogging disasters, characterized in that: It includes data integration unit, database management unit, twin model establishment unit, abnormal state analysis unit and plan output unit, among which: The data integration unit obtains geographic data in the basin, existing flood control and drainage project data, and environmental data in the basin's environment, and regularly updates environmental data changes, and sends geographic data and environmental data to the database management unit for storage; it also includes a historical data twin model establishment module, a core data and flood disaster relationship module, and a core data control module; The database management unit stores emergency plans for different flood disaster levels, processes geographic data and environmental data separately, integrates common hydrological and hydrodynamic models and crop waterlogging models to form a farmland waterlogging disaster assessment model, and derives key flood disaster prevention basin sections and flood disaster prevention time periods; The twin model building unit obtains the preview model from the database management unit, combines the real-time environmental observation data of rainfall and channel runoff with the evaluation model, couples the crop growth model and builds a digital twin model of agricultural waterlogging disasters at the watershed-field scale based on the digital twin method; The specific method of establishing a digital twin model of agricultural waterlogging disasters at the basin-field scale based on digital twins is as follows: S1. Substitute the real-time environmental data into the data processing system to remove errors and then convert it into the basic data of the digital twin; S2. Determine the composition of twin data according to the type of basic data, and then determine the construction requirements of twin data. Based on the construction requirements of twin data, determine the preprocessing method and storage method of environmental data and geographic data; S3. According to the watershed distribution of the preview model, the environmental data is brought into the preview model according to the watershed distribution, the environmental changes in the watershed are digitally described, and the preview model is converted into a digital twin model of agricultural waterlogging disasters at the watershed-field scale; S4. Use the digital twin model of agricultural waterlogging disasters at the watershed-field scale to simulate flood disaster scenarios caused by changes in environmental data, and continuously optimize the model simulation results based on the data level and simulation results to obtain a precise digital twin model of agricultural waterlogging disasters at the watershed-field scale; The abnormal state analysis unit obtains real-time environmental data, makes risk judgments on the real-time environmental data, generates abnormal risk signals, substitutes the real-time environmental data into the digital twin model of agricultural waterlogging disasters at the watershed-field scale, generates agricultural flood disaster prevention signals, judges the signal level, and outputs the judgment results to the plan output unit; The process of risk assessment using real-time environmental data is as follows: Sa. Acquire real-time environmental data, wherein the real-time environmental data includes air humidity Bt, rainfall Qt, ambient wind speed Vt and water flow change rate θt in the watershed, wherein the air humidity Bt is monitored by multiple humidity sensors arranged in the watershed, the rainfall Qt is obtained through real-time monitoring data of the meteorological platform, the ambient wind speed Vt is monitored by multiple wind speed sensors arranged in the watershed, and the water flow change rate θt is monitored by multiple flow velocity sensors arranged in the watershed; Sb, normalize the real-time environmental data in the key river basins of flood disasters, and calculate the risk coefficient η according to the following formula: , where e1 is the correlation coefficient of air humidity Bt, e2 is the correlation coefficient of rainfall Qt, and e3 is the correlation coefficient of ambient wind speed Vt; Sc. Obtain a preset risk factor threshold η0, and perform a threshold judgment on the risk factor η: if η>η0, an abnormal risk signal is generated; If η≦η0, no abnormal risk signal is generated; After obtaining the judgment result, the plan output unit selects the disaster emergency plan corresponding to the level from the database management unit according to the level signal, including the primary emergency plan and the alternative emergency plan, and sequentially substitutes the primary emergency plan and the alternative emergency plan into the digital twin model of agricultural waterlogging disaster at the watershed-field scale for simulation training. According to the effective value of the simulation training, one of the plans is selected as the selected plan and output.

2. The agricultural waterlogging disaster digital twin system according to claim 1 is characterized in that: The database management unit includes a flood disaster plan storage module and a data classification module, wherein: The flood disaster plan storage module is used to store emergency plans for different flood disaster levels. There are two emergency plans for each flood disaster level, namely, a primary emergency plan and an alternative emergency plan. The data classification unit establishes a watershed model based on the geographic database, and then analyzes the data change rules to establish a preview model. At the same time, it conducts rule analysis based on environmental data changes to derive key flood disaster prevention periods, and classifies and manages the preview model and rule analysis results to form a watershed database.

3. A flood disaster digital twin method, applied to an agricultural waterlogging disaster digital twin system as claimed in claim 1, characterized in that: The following steps are involved: Step 1: Obtain geographic data within the watershed, existing flood control and drainage engineering data, and environmental data in the environment where the watershed is located, and regularly update environmental data changes, and send the geographic data and environmental data to the database management unit and save them; Step 2: Process the geographic data and environmental data separately, integrate the general hydrological and hydrodynamic model and crop waterlogging model to form a farmland waterlogging disaster assessment model and derive the key flood disaster prevention basin sections and flood disaster prevention time periods; Step 3: Combine the real-time environmental observation data of rainfall and channel runoff with the evaluation model, and establish a digital twin model of agricultural waterlogging disasters at the watershed-field scale based on the digital twin method; Step 4: After making a risk assessment on the real-time environmental data and generating an abnormal risk signal, the real-time environmental data is substituted into the digital twin model of agricultural waterlogging disasters at the watershed-field scale to generate an agricultural flood disaster prevention signal, the signal level is assessed, and the assessment result is output and sent to the plan output unit; Step 5. After obtaining the judgment result, select the disaster emergency plan corresponding to the level from the database management unit according to the level signal, including the primary emergency plan and the alternative emergency plan, and substitute the primary emergency plan and the alternative emergency plan into the digital twin model of agricultural waterlogging disaster at the watershed-field scale for simulation training. Select one of the plans as the selected plan according to the effective value of the simulation training and output it.

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