Irrigation district management method

Abstract

The application relates to the technical field of irrigation district management, in particular to an irrigation district management method. A target irrigation district to be managed is acquired; the target irrigation district is divided into four-level spatial units of "target irrigation district-sub-irrigation district-administrative village-farmland block" according to corresponding administrative boundaries and hydrological boundaries of the target irrigation district; basic hydrological variables, equipment state variables and environmental characteristic variables corresponding to the spatial units at all levels in the target irrigation district are acquired; target core balance equations are constructed based on the basic hydrological variables, equipment state variables and environmental characteristic variables corresponding to the spatial units at all levels; core water account data corresponding to the spatial units at all levels in the target irrigation district are determined based on the target core balance equations; and target management measures corresponding to the target irrigation district are determined based on the core water account data corresponding to the spatial units at all levels. The measures can accurately match regions of different levels and different problem types, and the utilization efficiency of water resources in the irrigation district is maximally improved.

Description

Technical Field

[0001] This invention relates to the field of irrigation district management technology, and more specifically to irrigation district management methods. Background Technology

[0002] At present, the daily management of irrigation districts mostly relies on traditional methods such as manual flow measurement and single sensor monitoring. This not only results in low monitoring accuracy and delayed data feedback, but also has limited monitoring coverage, which cannot meet the actual needs of refined scheduling and precise water allocation in irrigation districts.

[0003] To address the monitoring challenges, general-purpose water measurement devices such as ultrasonic and electromagnetic meters have been gradually introduced and applied in irrigation areas, but they have failed to achieve the expected results. The water data collected by these devices is only used for post-event statistical accounting and paper-based record keeping. It is not deeply integrated with the actual hydrological cycle and water conveyance and consumption processes in the irrigation area. The data utilization rate is extremely low, and its value is difficult to realize. It cannot provide data support for real-time scheduling and precise management, leaving irrigation area management in a lagging state of "passive measurement" for a long time.

[0004] Due to monitoring lags and data gaps, traditional irrigation district management cannot achieve accurate water volume calculation and precise problem identification, making it even more difficult to formulate targeted control strategies. The overall management efficiency is low, water waste and leakage losses remain unresolved, ultimately hindering efficient and effective full-process management of irrigation district water resources. A scientific and feasible management method is urgently needed to solve these existing problems. Summary of the Invention

[0005] This invention provides an irrigation district management method to solve the problem of difficult and efficient full-process management of water resources in irrigation districts.

[0006] In a first aspect, the present invention provides an irrigation district management method, the method comprising: acquiring a target irrigation district to be managed; dividing the target irrigation district into four-level spatial units of "target irrigation district - sub-irrigation district - administrative village - field plot" according to the administrative and hydrological boundaries corresponding to the target irrigation district; acquiring basic hydrological variables, equipment status variables, and environmental characteristic variables corresponding to each level of spatial units in the target irrigation district; constructing a target core equilibrium equation based on the basic hydrological variables, equipment status variables, and environmental characteristic variables corresponding to each level of spatial units; determining core water account data corresponding to each level of spatial units in the target irrigation district based on the target core equilibrium equation; and determining target management measures corresponding to the target irrigation district based on the core water account data corresponding to each level of spatial units.

[0007] In one optional implementation, a target core equilibrium equation is constructed based on the basic hydrological variables, equipment state variables, and environmental characteristic variables corresponding to each level of spatial unit, including: the target core equilibrium equation for each level of spatial unit is:

[0008] Among them, I i For the water diversion volume of the channel, P i For effective rainfall, G i For groundwater recharge and discharge, ET i Crop evapotranspiration, R i For drainage volume, D i For deep leakage, For changes in soil water storage, This represents the amount of surface water infiltration.

[0009] In one optional implementation, based on the target core equilibrium equation, the core water ledger data corresponding to each level of spatial unit in the target irrigation district is determined, including: for each field spatial unit, extracting the corresponding data from the basic hydrological variables, equipment status variables, and environmental characteristics of the field spatial unit, such as the water diversion volume of the field canals, the effective rainfall of the field, the drainage volume of the field, the groundwater level depth, the field area, the soil permeability coefficient, the change in soil water storage, the crop growth stage, and the first equipment status; calculating the groundwater recharge and discharge volume of the field spatial unit based on the groundwater level depth and the field area; and calculating the crop evapotranspiration of the field spatial unit based on the crop growth stage. Based on the soil permeability coefficient, the surface water infiltration rate corresponding to the field spatial unit is calculated. Substituting the field canal water diversion, effective rainfall, groundwater recharge and discharge, crop evapotranspiration, drainage, soil water storage changes, and surface water infiltration rate into the target core equilibrium equation corresponding to the field spatial unit, the deep infiltration rate of the field spatial unit is obtained. Based on the field canal water diversion and groundwater recharge and discharge, the field canal water utilization coefficient and irrigation water utilization coefficient corresponding to the field spatial unit are calculated. Based on the field canal water diversion, effective rainfall, groundwater recharge and discharge, crop evapotranspiration, drainage, surface water infiltration, and soil water storage changes, the deep infiltration rate of the field spatial unit is calculated. By analyzing changes in water storage, surface water infiltration, deep seepage, irrigation water utilization coefficient, and irrigation water utilization coefficient, we obtain the water account data corresponding to each spatial unit of farmland. For each administrative village spatial unit, based on the corresponding basic hydrological variables, equipment status variables, environmental characteristic variables, and water account data, we obtain the corresponding data for each administrative village spatial unit, including: irrigation canal water diversion, effective rainfall, groundwater recharge and discharge, crop evapotranspiration, drainage, changes in soil water storage, surface water infiltration, deep seepage, irrigation water utilization coefficient, and irrigation water utilization coefficient. The data is obtained by analyzing the water account data of the administrative villages corresponding to the administrative village spatial units; for the sub-irrigation area spatial units, based on the basic hydrological variables, equipment status variables, environmental characteristic variables, and administrative village water account data of the sub-irrigation area, the following data are obtained: sub-irrigation area canal water diversion, effective rainfall, groundwater recharge and discharge, crop evapotranspiration, drainage, soil water storage changes, surface water infiltration, deep seepage, canal water utilization coefficient, and comprehensive irrigation efficiency of the sub-irrigation area spatial units. This yields the sub-irrigation area water account data for the sub-irrigation area spatial units. For the target irrigation area spatial unit, based on the target irrigation area spatial unit's corresponding... By analyzing the basic hydrological variables, equipment status variables, environmental characteristic variables, and water account data of the target irrigation area, we obtain the target irrigation area's canal water diversion, effective rainfall, groundwater recharge and discharge, crop evapotranspiration, drainage, soil water storage changes, surface water infiltration, deep seepage, global canal system water utilization coefficient, and global comprehensive irrigation efficiency for each spatial unit of the target irrigation area. Based on the water account data of the field, administrative village, sub-irrigation area, and target irrigation area, we generate core water account data for each level of spatial unit.

[0010] In one optional implementation, the target management measures for the target irrigation area are determined based on the core water account data corresponding to each level of spatial unit, including: generating a leakage probability heatmap for the target irrigation area based on the core water account data corresponding to each level of spatial unit; generating a time-series curve heatmap of efficiency indicators for the target irrigation area based on the core water account data corresponding to each level of spatial unit; and determining the target management measures for the target irrigation area based on the leakage probability heatmap and the time-series curve heatmap of efficiency indicators.

[0011] In one optional implementation, a heatmap of the infiltration probability corresponding to the target irrigation area is generated based on the core water account data corresponding to each level of spatial unit. This includes: extracting surface water infiltration, canal water diversion, effective rainfall, and deep infiltration from the field water account data corresponding to the core water account data; extracting surface water infiltration, effective rainfall, canal water diversion, and canal water utilization coefficient from the administrative village water account data corresponding to the core water account data; extracting surface water infiltration, canal water diversion, and effective rainfall from the sub-irrigation area water account data corresponding to the sub-irrigation area water account data; and extracting surface water infiltration, canal water diversion, and effective rainfall from the target irrigation area water account data corresponding to the target irrigation area water account data; and based on the field surface water... The infiltration rate of a field plot is calculated based on water infiltration, irrigation canal diversion, and effective rainfall in the field. The field leakage contribution is calculated based on deep seepage in the field. The administrative village canal leakage rate is calculated based on the administrative village canal system water utilization coefficient. The flow difference between the sub-irrigation area hub canals and the target irrigation area is calculated based on surface water infiltration, irrigation canal diversion, and effective rainfall in the sub-irrigation area. The global infiltration rate of the target irrigation area spatial unit is calculated based on surface water infiltration, effective rainfall, and irrigation canal diversion. A leakage probability heatmap for the target irrigation area is generated based on the field plot infiltration rate, field leakage contribution, administrative village canal leakage rate, sub-irrigation area hub canal flow difference, and global infiltration rate.

[0012] In one optional implementation, a leakage probability heatmap for the target irrigation area is generated based on field infiltration rate, field leakage contribution, administrative village canal leakage rate, sub-irrigation district hub canal flow difference, and global infiltration rate. This includes: obtaining the soil permeability coefficient, field area, and canal type corresponding to the field spatial unit; determining the leakage diffusion coefficient corresponding to the field spatial unit based on the soil permeability coefficient, field area, and canal type; calculating the risk coupling value corresponding to the field spatial unit based on the leakage diffusion coefficient, field infiltration rate, and field leakage contribution; obtaining the canal system aging degree, soil type, and irrigation frequency corresponding to the target irrigation area; and determining the leakage probability heatmap based on the canal system aging degree, soil type, and irrigation frequency. The system identifies the first weight information corresponding to the infiltration rate of fixed plots, the leakage rate of administrative village channels, the flow difference of sub-irrigation area hub channels, and the global infiltration rate. It extracts the global canal system water utilization coefficient and the global comprehensive irrigation efficiency from the target irrigation area water account data corresponding to the core water account data. For different levels of spatial units, it divides each level of spatial unit into grid units according to different sizes, generating grid units corresponding to each level. Based on the first weight information and risk coupling value corresponding to the infiltration rate of fixed plots, the leakage rate of administrative village channels, the flow difference of sub-irrigation area hub channels, and the global infiltration rate, it determines the final leakage probability corresponding to each grid unit. Finally, it generates a leakage probability heatmap based on the final leakage probability corresponding to each grid unit.

[0013] In one optional implementation, based on the core water account data corresponding to each level of spatial unit, a time-series curve heatmap of efficiency indicators corresponding to the target irrigation area is generated, including: extracting the field irrigation water utilization coefficient from the field water account data corresponding to the core water account data; extracting the administrative village canal system water utilization coefficient and the administrative village irrigation water utilization coefficient from the administrative water account data corresponding to the core water account data; extracting the sub-irrigation area canal system water utilization coefficient and the sub-irrigation area comprehensive irrigation efficiency from the sub-irrigation area water account data corresponding to the core water account data; extracting the global canal system water utilization coefficient and the global comprehensive irrigation efficiency from the target irrigation area water account data corresponding to the core water account data; dividing the spatial units at different levels according to different sizes for different levels of spatial units, generating grid units corresponding to each level of spatial units; and obtaining the second weight information corresponding to the field irrigation water utilization coefficient, the administrative village canal system water utilization coefficient, the administrative village irrigation water utilization coefficient, the sub-irrigation area canal system water utilization coefficient, the sub-irrigation area comprehensive irrigation efficiency, the global canal system water utilization coefficient, and the global comprehensive irrigation efficiency, respectively. Based on the second weight information, the fusion efficiency value corresponding to each grid unit is determined; a time series array of daily fusion efficiency values ​​within the irrigation cycle is established for each grid unit; based on the time series array of daily fusion efficiency values, the health level corresponding to each grid unit is determined; based on the time series array of daily fusion efficiency values ​​and the health level, a time series curve heatmap of efficiency indicators corresponding to the target irrigation area is generated.

[0014] In one optional implementation, the target management measures corresponding to the target irrigation area are determined based on the leakage probability heat map and the efficiency index time series curve heat map, including: inputting the leakage probability heat map and the efficiency index time series curve heat map into a preset problem determination model to determine the target problem corresponding to the target irrigation area; and determining the target management measures corresponding to the target irrigation area based on the target problem.

[0015] In one optional implementation, the leakage probability heatmap and the efficiency index time-series curve heatmap are input into a preset problem-solving model to determine the target problem corresponding to the target irrigation area. This includes: inputting the leakage probability heatmap and the efficiency index time-series curve heatmap into the preset problem-solving model; the preset problem-solving model identifies the leakage probability heatmap and extracts the final leakage probability, risk coupling value, leakage diffusion coefficient, canal aging degree, normalized soil permeability coefficient, and irrigation frequency corresponding to each grid cell in the leakage probability heatmap, obtaining the efficiency feature vector corresponding to each grid cell; the preset problem-solving model identifies the efficiency index time-series curve heatmap and extracts... The efficiency indicator time-series curve heatmap is used to obtain the fusion efficiency value, health level quantification value, efficiency time-series fluctuation rate, efficiency trend slope, canal water utilization coefficient, and comprehensive irrigation efficiency corresponding to each grid unit, thus obtaining the efficiency feature vector corresponding to each grid unit. Among them, each grid unit in the leakage probability heatmap corresponds one-to-one with each grid unit in the efficiency indicator time-series curve heatmap. The efficiency feature vectors corresponding to each grid unit and the efficiency feature vectors are fused to obtain the fusion feature vector corresponding to each grid unit. Based on each fusion feature vector, the target problem corresponding to at least one grid area in the target irrigation area is determined. Among them, the grid area includes at least one grid unit.

[0016] In one optional implementation, the target problem includes at least one target problem corresponding to a grid area. Based on the target problem, the target management measures corresponding to the target irrigation area are determined, including: for the target problem corresponding to each grid area, matching at least one candidate management measure in a preset measure library, and determining the measure cost and effective period corresponding to each candidate management measure; obtaining the regional average integration efficiency value and soil type code corresponding to each grid area; calculating the effect improvement rate corresponding to each candidate management measure corresponding to the grid area based on the regional average integration efficiency value and soil type code corresponding to the grid area; calculating the priority score corresponding to each candidate management measure based on the measure cost, effective period, and effect improvement rate; and determining the target management measures corresponding to each grid area based on each priority score.

[0017] The irrigation district management method provided in this application acquires the target irrigation district to be managed. It clearly defines the management object and scope, delineating boundaries for all subsequent operations and avoiding data redundancy or omissions due to ambiguous management scope, ensuring targeted processes. It divides the target irrigation district into four spatial units: "target irrigation district—sub-irrigation district—administrative village—field," achieving hierarchical and refined decomposition of the target irrigation district and addressing the pain points of traditional "extensive management" of irrigation districts. Different spatial units correspond to different management granularities (e.g., field focuses on field irrigation, sub-irrigation district focuses on main canal water conveyance), laying the spatial foundation for subsequent hierarchical water accounting and targeted policy implementation. It acquires basic hydrological, equipment status, and environmental characteristic variables for each spatial unit. It collects core basic data for target irrigation district management, covering three dimensions: "hydrological cycle—equipment operation—environmental impact," providing comprehensive and accurate input parameters for the water balance equation and avoiding model distortion due to data gaps. This study constructs a core balance equation for the target irrigation area and establishes a quantitative model based on multi-dimensional variables to achieve accurate accounting of water revenue and expenditure. It clearly depicts the "water intake-transfer-consumption-drainage" process at each spatial unit level, providing a scientific basis for generating core water account data. The study determines the core water account data for each spatial unit level, outputting detailed water balance information for each unit. This directly reflects the allocation, loss, and utilization of water resources in the irrigation area, accurately identifying key aspects of water waste and canal leakage, providing data support for subsequent problem identification. The study then determines the target management measures for the target irrigation area. Based on the quantitative analysis results of the water account data, targeted and differentiated management plans are developed. These measures can be precisely matched to areas at different levels and with different problem types (such as seepage prevention renovation in high-leakage areas and irrigation system optimization in low-efficiency areas), maximizing the efficiency of water resource utilization in the irrigation area. Attached Figure Description

[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the first process of the irrigation district management method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the framework of an irrigation district management method according to an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0022] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0023] According to an embodiment of the present invention, an embodiment of an irrigation district management method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0024] This embodiment provides a method for irrigation district management, which can be used on electronic devices such as mobile phones and tablets. Figure 1 This is a flowchart of an irrigation district management method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: Step S101: Obtain the target irrigation area to be managed.

[0025] Specifically, electronic devices can retrieve authoritative administrative boundary vector data (such as township / administrative village zoning maps published by county-level natural resources bureaus) and hydrological boundary data (such as watershed scope, main canal water conveyance range, and water source protection zone zoning). Then, through overlay analysis using GIS tools (ArcGIS / QGIS), areas within the administrative boundaries that do not belong to the irrigation area (such as mountains and construction land) are eliminated, ultimately determining the precise geographical boundaries of the target irrigation area and outputting the irrigation area's latitude and longitude range, total area, and a list of involved administrative regions. For example, the target irrigation area to be managed is "Xihe Irrigation Area of ​​XX City". Its administrative boundaries involve 2 townships and 15 administrative villages. Its hydrological boundaries cover the water conveyance range of the main canal of Xihe and 5 branch canals, with a total area of ​​8,000 hectares. The water source is Xihe surface water. The main canal is 25 km long and has 6 pumping stations. The main crops are wheat and corn. The irrigation method is mainly canal irrigation. The historical irrigation water utilization coefficient is 0.72 and the canal system leakage rate is 12%. The management goal is to "increase the water utilization coefficient to 0.78 and reduce the canal system leakage rate to 7% during the irrigation season".

[0026] Step S102: Based on the administrative and hydrological boundaries corresponding to the target irrigation area, the target irrigation area is divided into four spatial units: "target irrigation area - sub-irrigation area - administrative village - field".

[0027] Specifically, electronic devices can divide the target irrigation area into four spatial units—"target irrigation area—sub-irrigation area—administrative village—field"—based on the administrative and hydrological dual-matching principle, according to the administrative and hydrological boundaries corresponding to the target irrigation area. At the meso-level (sub-irrigation area, administrative village), administrative boundaries are prioritized to ensure that management responsibility corresponds to specific entities; at the micro-level (field), hydrological boundaries (irrigation range of branch canals / field ditches) are matched to ensure the accuracy of water volume statistics. The higher the level, the coarser the management granularity (target irrigation area → macro-level coordination); the lower the level, the finer the management granularity (field → precision irrigation). Each lower-level unit uniquely belongs to one higher-level unit, with no overlap or omissions. Table 1 illustrates an example of spatial unit division.

[0028] Table 1. Spatial Unit Division Diagram

[0029] The electronic equipment adopts a structure of "hierarchical identifier - superior code - unit serial number" to ensure the uniqueness of the code. For example, the target irrigation area is GQ-001; the sub-irrigation area is GQ-001-ZGQ-002 (the second sub-irrigation area of ​​GQ-001); the administrative village is GQ-001-ZGQ-002-XZC-008 (the eighth administrative village of ZGQ-002); and the field is GQ-001-ZGQ-002-XZC-008-TK-036 (the 36th field of XZC-008). The electronic equipment can bind basic attributes to each unit, such as binding branch canal length and pump station location to the sub-irrigation area; and binding crop type, soil permeability coefficient, and irrigated area to the field.

[0030] Step S103: Obtain the basic hydrological variables, equipment status variables, and environmental characteristic variables corresponding to each level of spatial unit in the target irrigation area.

[0031] The basic hydrological variables include: headworks water diversion, representing the total irrigation water diversion at each headworks level, with the data collection level including the target irrigation district / sub-irrigation district / administrative village; field irrigation water, representing the actual irrigation water consumption of the field, with the data collection level including the field; effective rainfall, representing the rainfall that can be absorbed by the crop roots during the crop growth period (excluding surface runoff and deep seepage), with the data collection level including all levels; crop evapotranspiration (ET), representing the total water volume of crop transpiration and soil evaporation, with the data collection level including the field / administrative village; groundwater recharge and discharge, representing the amount of groundwater recharge to the crop root zone (recharge) or the amount of groundwater level drop caused by crop water consumption (discharge), with the data collection level including the field / sub-irrigation district; canal system seepage, representing water loss during canal water conveyance, with the data collection level including the sub-irrigation district / administrative village; and surface runoff, representing the total amount of unutilized surface runoff in the field / region, with the data collection level including the field / sub-irrigation district. Equipment status variables include: the degree of aging of the canal system, which characterizes the integrity rate of the canal lining, using a score of 1-5 (5 points being extremely aged), and the data collection level includes sub-irrigation districts / administrative villages; pump station operating efficiency, which characterizes the ratio of the actual output to the rated output of the pump station, and the data collection level includes sub-irrigation districts; water measurement equipment accuracy, which characterizes the measurement error rate of flow meters / water meters, and the data collection level includes all levels; and irrigation equipment operating conditions, which characterize the clogging rate and operating pressure of drip irrigation / sprinkler irrigation equipment, and the data collection level includes fields. Environmental characteristic variables include: soil type, representing sandy loam / clay / sandy soil, etc., with a sampling level including field plots; soil permeability coefficient, representing the rate of soil water infiltration (mm / h), with a sampling level including field plots; and crop growth stage, representing sowing period / jointing period / grain-filling period / maturity period, with a sampling level including field plots / administrative villages. Temperature, humidity, and sunshine duration are key meteorological data representing the growing season, collected at levels including the target irrigation district and sub-irrigation districts. Specifically, electronic devices can collect real-time hydrological and environmental data by installing flow meters, rain gauges, lysimeters, and soil moisture sensors at canal heads and in fields. This data is transmitted via an IoT platform. The electronic devices can also collect historical water management records, equipment maintenance records, and crop planting records from the irrigation district management office to supplement non-real-time data. Furthermore, the electronic devices can receive results from on-site scoring and sampling analysis by technical personnel on canal aging, soil type, and irrigation equipment operating conditions, ensuring data accuracy. For variables that cannot be directly monitored (such as effective rainfall and crop evapotranspiration), the electronic devices use a mature formula to calculate: Effective rainfall: P effective =P total ×(1-α) (α is the runoff coefficient, which is determined according to soil type). Crop evapotranspiration can be calculated using the Penman-Monteith formula, which is suitable for different crops and growth stages.

[0032] Step S104: Based on the basic hydrological variables, equipment state variables, and environmental characteristic variables corresponding to each level of spatial unit, construct the target core equilibrium equation.

[0033] Specifically, electronic equipment can construct the target core equilibrium equation based on the basic hydrological variables, equipment state variables, and environmental characteristic variables corresponding to each level of spatial unit, following the core logic as follows: The core logic is: Total input water volume = Total water consumption + Total output water volume + Change in stored water volume.

[0034] This step will be explained in detail below.

[0035] Step S105: Based on the target core balance equation, determine the core water account data corresponding to each level of spatial unit of the target irrigation area.

[0036] Specifically, electronic devices can first calculate field-level water account data based on the target core balance equation, and then summarize it level by level to administrative villages, sub-irrigation areas, and target irrigation areas to ensure clear data traceability.

[0037] This step will be explained in detail below.

[0038] Step S106: Based on the core water account data corresponding to each level of spatial unit, determine the target management measures corresponding to the target irrigation area.

[0039] Specifically, electronic devices determine the target problems corresponding to the target irrigation area based on the core water accounting data corresponding to each level of spatial unit. Then, based on the target problems, they determine the target management measures corresponding to the target irrigation area.

[0040] This step will be explained in detail below.

[0041] The irrigation district management method provided in this application acquires the target irrigation district to be managed. It clearly defines the management object and scope, delineating boundaries for all subsequent operations and avoiding data redundancy or omissions due to ambiguous management scope, ensuring targeted processes. It divides the target irrigation district into four spatial units: "target irrigation district—sub-irrigation district—administrative village—field," achieving hierarchical and refined decomposition of the target irrigation district and addressing the pain points of traditional "extensive management" of irrigation districts. Different spatial units correspond to different management granularities (e.g., field focuses on field irrigation, sub-irrigation district focuses on main canal water conveyance), laying the spatial foundation for subsequent hierarchical water accounting and targeted policy implementation. It acquires basic hydrological, equipment status, and environmental characteristic variables for each spatial unit. It collects core basic data for target irrigation district management, covering three dimensions: "hydrological cycle—equipment operation—environmental impact," providing comprehensive and accurate input parameters for the water balance equation and avoiding model distortion due to data gaps. This study constructs a core balance equation for the target irrigation area and establishes a quantitative model based on multi-dimensional variables to achieve accurate accounting of water revenue and expenditure. It clearly depicts the "water intake-transfer-consumption-drainage" process at each spatial unit level, providing a scientific basis for generating core water account data. The study identifies core water account data for each spatial unit level, outputting detailed water balance statements for each level. This data intuitively reflects the allocation, loss, and utilization of water resources in the irrigation area, accurately pinpointing key issues such as water waste and canal leakage, and providing data support for subsequent problem identification. The study then determines target management measures for the target irrigation area. Based on the quantitative analysis results of the water account data, targeted and differentiated management plans are developed. These measures can be precisely matched to areas at different levels and with different problem types (such as seepage prevention renovation in high-leakage areas and irrigation system optimization in low-efficiency areas), maximizing the efficiency of water resource utilization in the irrigation area.

[0042] This embodiment provides an irrigation district management method that can be used on electronic devices, such as mobile phones, tablets, etc. Figure 2 The diagram shown is a schematic representation of the framework of the irrigation district management method provided in this embodiment. The irrigation district management method of this invention includes the following steps: Step S201: Obtain the target irrigation area to be managed.

[0043] Please refer to the above description of step S101 for details on this step, which will not be repeated here.

[0044] Step S202: Based on the administrative and hydrological boundaries of the target irrigation area, the target irrigation area is divided into four spatial units: "target irrigation area - sub-irrigation area - administrative village - field".

[0045] Please refer to the above description of step S102 for details on this step, which will not be repeated here.

[0046] Step S203: Obtain the basic hydrological variables, equipment status variables, and environmental characteristic variables corresponding to each level of spatial unit in the target irrigation area; Please refer to the above description of step S103 for details on this step, which will not be repeated here.

[0047] Step S204: Based on the basic hydrological variables, equipment state variables, and environmental characteristic variables corresponding to each level of spatial unit, construct the target core equilibrium equation.

[0048] The target core equilibrium equations corresponding to each level of space unit are as follows:

[0049] Among them, I i For the water diversion volume of the channel, P i For effective rainfall, G i For groundwater recharge and discharge, ET i Crop evapotranspiration, R i For drainage volume, D i For deep leakage, For changes in soil water storage, This represents the amount of surface water infiltration.

[0050] Step S205: Based on the target core equilibrium equation, determine the core water account data corresponding to each level of spatial unit of the target irrigation area.

[0051] Specifically, step S205 above may include the following steps: Step S2051: For the field space unit, extract the following data from the basic hydrological variables, equipment status variables, and environmental characteristics variables of the corresponding field space unit: field channel water diversion volume, effective rainfall, drainage volume, groundwater level depth, field area, soil permeability coefficient, changes in soil water storage, crop growth stage, and first equipment status.

[0052] Specifically, for a field space unit, the electronic equipment extracts the following data from the basic hydrological variables, equipment status variables, and environmental characteristics variables of the corresponding field space unit: field channel water diversion volume, effective rainfall, drainage volume, groundwater level depth, field area, soil permeability coefficient, changes in soil water storage, crop growth stage, and first equipment status.

[0053] Step S2052: Calculate the groundwater recharge and discharge volume of the field corresponding to the field spatial unit based on the groundwater level depth and field area.

[0054] Specifically, electronic devices can substitute groundwater level depth and farmland area into a formula. The groundwater recharge and discharge of the farmland are calculated. Among them, μ is the soil water yield, which refers to the amount of water released or absorbed by a unit area of ​​soil when the groundwater level changes by 1m. It is determined by the soil type (e.g., sandy soil μ=0.2, clay soil μ=0.05), ΔH is the change in groundwater level during the calculation period, and A is the farmland area.

[0055] Step S2053: Calculate the evapotranspiration of the field crops corresponding to the field spatial unit based on the crop growth stage.

[0056] Specifically, electronic devices can determine the crop coefficient Kc based on the crop growth stage. For example, Kc = 0.3 for wheat seedlings and Kc = 1.2 for grain-filling stages.

[0057] Then, the electronic device substitutes the crop coefficient and field area into the formula. Calculate the evapotranspiration of the field crops corresponding to the field spatial unit. Among them, ET0 is the reference crop evapotranspiration calculated using the Penman-Monteith formula. Input meteorological data (temperature, humidity, wind speed, sunshine duration), Kc is the crop coefficient, and A is the field area.

[0058] Step S2054: Based on the soil permeability coefficient, calculate the surface water infiltration amount of the field corresponding to the field spatial unit.

[0059] Specifically, electronic devices can substitute the soil permeability coefficient into the formula. Calculate the surface water infiltration rate corresponding to the field spatial unit. Wherein, K s The soil permeability coefficient is the measured value extracted in step S2051 (unit converted to m / h). t is the field irrigation duration, extracted from the irrigation record. A is the field area. β is the equipment condition correction coefficient, which is determined by the first equipment condition score (5 points, β=1.0; 3 points, β=0.7; the worse the equipment, the lower the correction coefficient).

[0060] Step S2055: Substitute the water diversion volume of the field canals, the effective rainfall of the field, the groundwater recharge and discharge of the field, the crop evapotranspiration of the field, the drainage volume of the field, the change in soil water storage of the field, and the surface water infiltration of the field into the target core balance equation corresponding to the field spatial unit to obtain the deep infiltration volume of the field corresponding to the field spatial unit.

[0061] Specifically, the core equilibrium equation for the field-level target is: .

[0062] The formula for solving the problem by deformation is: , among which, I field For the amount of water diverted to the field canals, P field For the effective rainfall of the field, G field For the replenishment and discharge of groundwater in the field, ETfield Evapotranspiration of crops in the field, R field For field drainage, D field For the deep seepage of the field, For changes in soil water storage in the field, This represents the amount of surface water infiltration into the field.

[0063] Electronic devices can substitute data such as the amount of water diverted from farmland channels, the effective rainfall in farmland, the amount of groundwater replenishment and drainage in farmland, the amount of crop evapotranspiration in farmland, the amount of drainage in farmland, the changes in soil water storage in farmland, and the amount of surface water infiltration in farmland into a deformation solution formula to obtain the amount of deep infiltration in farmland corresponding to the farmland spatial unit.

[0064] Step S2056: Based on the water diversion volume of the field canals and the groundwater replenishment and discharge volume of the field, calculate the field canal system water utilization coefficient and the field irrigation water utilization coefficient corresponding to the field spatial unit.

[0065] Specifically, electronic equipment can calculate the water utilization coefficient of the field canal system based on the water diversion volume of the field canals and the groundwater recharge and discharge volume of the field using the following formula. .in, The field irrigation system water utilization coefficient reflects the water conveyance efficiency from the irrigation canal to the field, that is, the ratio of the actual water diversion to the field to the water diversion of the irrigation canal.

[0066] Electronic equipment can calculate the irrigation water utilization coefficient of farmland based on the water diversion volume of field channels and the recharge and discharge volume of groundwater in the field, using the following formula. .in, The field irrigation water utilization coefficient reflects the effective utilization of irrigation water in the field, which is the ratio of crop evapotranspiration to total water supply.

[0067] Step S2057: Based on the water diversion volume of field channels, effective rainfall of field, groundwater recharge and discharge of field, crop evapotranspiration of field, drainage volume of field, surface water infiltration of field, changes in soil water storage of field, surface water infiltration of field, deep seepage of field, water utilization coefficient of field canal system, and irrigation water utilization coefficient of field, obtain the field water account data corresponding to the field spatial unit.

[0068] Specifically, the water account data corresponding to the field spatial unit includes the water diversion volume of field channels, the effective rainfall of field, the replenishment and discharge of groundwater in field, the evapotranspiration of field crops, the drainage volume of field, the infiltration of surface water in field, the change of soil water storage in field, the infiltration of surface water in field, the deep leakage of field, the water utilization coefficient of field canal system, and the irrigation water utilization coefficient of field.

[0069] Step S2058: For the administrative village spatial unit, based on the basic hydrological variables, equipment status variables, environmental characteristic variables, and field water account data of the administrative village corresponding to the administrative village spatial unit, the following data are obtained: water diversion volume of the administrative village canals, effective rainfall, groundwater recharge and discharge, crop evapotranspiration, drainage, soil water storage changes, surface water infiltration, deep seepage, canal water utilization coefficient, and irrigation water utilization coefficient of the administrative village spatial unit.

[0070] Specifically, the water account data for administrative villages is based on the summary of water account data for all fields within the village, plus the water loss of the village-level canal system, following the principle of "summarization + correction".

[0071] Electronic devices sum the water accounting indicators of all fields within an administrative village to obtain basic water volume data at the administrative village level. For the water diversion volume of the administrative village canals, For the effective rainfall of administrative villages, To replenish groundwater in administrative villages, For the evapotranspiration of crops in administrative villages, For the drainage volume of administrative villages, For the deep seepage volume of administrative villages, For changes in soil water storage in administrative villages, This refers to the amount of surface water infiltration in administrative villages.

[0072] Among them, the water diversion volume of administrative village canals I village The measured water diversion volume at the head of the village-level irrigation canal; the leakage volume (L) of the village-level irrigation canal system. channel-village =I village -∑I field (The difference between the water diversion volume at the canal head and the total water diversion volume in the fields); the water utilization coefficient of the canal system in administrative villages is... ,in, Water diversion volume for administrative villages. Irrigation water utilization coefficient for administrative villages: ,in, Evapotranspiration of crops in administrative villages For the effective rainfall of administrative villages, It measures the replenishment and discharge of groundwater in administrative villages. Electronic devices can integrate and summarize data and calculate indicators to form water account data for administrative villages, which includes "water income and expenditure, utilization efficiency, and loss" for each spatial unit.

[0073] Step S2059: For the sub-irrigation area spatial unit, based on the sub-irrigation area basic hydrological variables, sub-irrigation area equipment status variables, sub-irrigation area environmental characteristic variables, and administrative village water account data corresponding to the sub-irrigation area spatial unit, obtain the sub-irrigation area canal water diversion volume, sub-irrigation area effective rainfall, sub-irrigation area groundwater recharge and discharge volume, sub-irrigation area crop evapotranspiration, sub-irrigation area drainage volume, sub-irrigation area soil water storage change, sub-irrigation area surface water infiltration volume, sub-irrigation area deep seepage volume, sub-irrigation area canal system water utilization coefficient, and sub-irrigation area comprehensive irrigation efficiency corresponding to the sub-irrigation area spatial unit, and obtain the sub-irrigation area water account data corresponding to the sub-irrigation area spatial unit.

[0074] Specifically, the water account of the sub-irrigation area is based on the summary of water account data of all administrative villages in the area, superimposed with variables such as the loss of the main canal of the sub-irrigation area and the operating efficiency of the pumping station, reflecting the characteristics of water volume control at the regional level.

[0075] The electronic device can sum the water account indicators for all administrative villages within the sub-irrigation district. Then, based on the collected data, the electronic device obtains the water diversion volume I of the sub-irrigation district's canals. district The water diversion volume of the sub-irrigation area canals is the water diversion volume at the head of the branch canals of the sub-irrigation area (measured value); the pump station operating efficiency η pump The pump station operating efficiency is the measured value (actual output of the pump station / rated output); the leakage rate L of the main canal in the sub-irrigation area. channel-district =I district ×η pump -∑I village , where ∑I village This refers to the amount of water diverted from the irrigation canals within the sub-irrigation area.

[0076] The water utilization coefficient of the irrigation canal system in the sub-irrigation area is: ,in, The overall irrigation efficiency of the sub-irrigation district is: .

[0077] Electronic equipment integrates and summarizes data, loss data, and comprehensive efficiency indicators to obtain water account data for the sub-irrigation area corresponding to the sub-irrigation area spatial unit.

[0078] Step S20510: For the target irrigation area spatial unit, based on the target irrigation area basic hydrological variables, target irrigation area equipment status variables, target irrigation area environmental characteristic variables, and sub-irrigation area water account data corresponding to the target irrigation area spatial unit, obtain the target irrigation area canal water diversion volume, target irrigation area effective rainfall, target irrigation area groundwater recharge and discharge volume, target irrigation area crop evapotranspiration, target irrigation area drainage volume, target irrigation area soil water storage change, target irrigation area surface water infiltration volume, target irrigation area deep seepage volume, global canal system water utilization coefficient, and global comprehensive irrigation efficiency, and obtain the target irrigation area water account data corresponding to the target irrigation area spatial unit.

[0079] Specifically, the target irrigation district water account is the highest level of water account in the entire irrigation district. It is based on the summary of water account data from all sub-irrigation districts and reflects the water balance and overall utilization efficiency of the entire irrigation district.

[0080] The electronic equipment sums the water account indicators of all sub-irrigation districts within the entire irrigation district. Then, based on the measured total water diversion volume at the head of the main irrigation canal of the irrigation district, the electronic equipment obtains the canal water diversion volume I of the target irrigation district. global Electronic equipment calculates the total leakage of the global drainage system, ∑L global =I global -∑(I district ×η pump Electronic equipment calculates the global canal system water utilization coefficient. Electronic equipment calculates the overall irrigation efficiency. .

[0081] Electronic equipment integrates the water income and expenditure, total loss, and overall efficiency indicators of the entire irrigation area to form the final target irrigation area water account data corresponding to the target irrigation area spatial unit.

[0082] Step S20511: Based on the water account data of farmland, administrative villages, sub-irrigation areas, and target irrigation areas, generate core water account data corresponding to each level of spatial unit.

[0083] Specifically, electronic devices organize the water account data of four levels—field, administrative village, sub-irrigation area, and target irrigation area—in a unified standard format, establish a four-level water account relationship, and realize that "the water account of the upper level can be traced back to the water account of the lower level," thereby generating core water account data corresponding to each level of spatial unit.

[0084] Step S206: Based on the core water account data corresponding to each level of spatial unit, determine the target management measures corresponding to the target irrigation area.

[0085] Specifically, step S206 above may include the following steps: Step S2061: Based on the core water account data corresponding to each level of spatial unit, generate a heat map of leakage probability corresponding to the target irrigation area.

[0086] Specifically, step S2061 above may include the following steps: Step a1: Extract the surface water infiltration, irrigation canal water diversion, effective rainfall, and deep water leakage from the field water ledger data corresponding to the core water ledger data.

[0087] Specifically, electronic devices can extract data such as surface water infiltration, water diversion from irrigation canals, effective rainfall, and deep water leakage from farmland from the farmland water account data corresponding to the core water account data.

[0088] Step a2: Extract the surface water infiltration volume, effective rainfall, channel water diversion volume, and channel water utilization coefficient of the administrative villages from the administrative village water account data corresponding to the core water account data.

[0089] Specifically, electronic devices can extract the surface water infiltration volume, effective rainfall, channel water diversion volume, and canal water utilization coefficient of administrative villages from the administrative village water account data corresponding to the core water account data.

[0090] Step a3: Extract the surface water infiltration volume, canal water diversion volume, and effective rainfall of the sub-irrigation area from the sub-irrigation area water account data corresponding to the core water account data.

[0091] Specifically, electronic devices can extract the surface water infiltration volume, canal water diversion volume, and effective rainfall of the sub-irrigation area from the sub-irrigation area water account data corresponding to the core water account data.

[0092] Step a4: Extract the surface water infiltration volume, canal water diversion volume, and effective rainfall of the target irrigation area from the target irrigation area water account data corresponding to the core water account data.

[0093] Specifically, electronic devices can extract the surface water infiltration volume, canal water diversion volume, and effective rainfall volume of the target irrigation area from the target irrigation area water account data corresponding to the core water account data.

[0094] Step a5: Based on the surface water infiltration, water diversion from irrigation canals, and effective rainfall in the field, calculate the field infiltration rate corresponding to the field spatial unit; based on the deep infiltration in the field, calculate the field infiltration contribution of the field spatial unit.

[0095] Specifically, electronic devices can use formulas based on the infiltration rate of surface water in the field, the water diversion volume of the field channels, and the effective rainfall in the field. Calculate the field infiltration rate corresponding to the field spatial unit. Electronic equipment can calculate the contribution of farmland to infiltration based on the amount of deep infiltration, using the following formula: ;in, This represents the total deep seepage of all fields in the administrative village to which the field belongs.

[0096] Step a6: Based on the water utilization coefficient of the canal system in the administrative village, calculate the leakage rate of the canal system corresponding to the spatial unit of the administrative village.

[0097] Specifically, the electronic device can quantify the proportion of water conveyance leakage loss in the administrative village canal system based on the water utilization coefficient of the administrative village canal system extracted in step a2, identify high-risk canal sections at the village level, characterize the proportion of leakage water during the water conveyance process of the administrative village canal system to the water intake at the canal head, and reflect the seepage prevention performance of the village-level canal system.

[0098] The calculation formula is: , where δ village The leakage rate of canals in administrative villages.

[0099] For example, if the channel leakage rate ranges from δ village If the leakage rate is less than 5%, the canal system's seepage prevention performance is excellent, and the recommended management is to maintain routine inspections; if the canal leakage rate is 5% ≤ δ village If the leakage rate is less than 15%, the canal's seepage prevention performance is considered good, and the recommended management measure is localized seepage prevention and repair of the canal section; if the canal leakage rate is 15% ≤ δ village If the leakage rate is less than 30%, the canal system's seepage prevention performance is considered poor, and the recommended management measure is comprehensive canal system lining renovation; if the canal leakage rate ranges from δ... village If the water level is ≥30%, the canal system's seepage prevention performance is rated as extremely poor. The recommended management measures are emergency seepage prevention treatment and optimization of water volume scheduling.

[0100] Step a7: Based on the surface water infiltration rate of the sub-irrigation area, the water diversion rate of the sub-irrigation area channels, and the effective rainfall of the sub-irrigation area, calculate the flow difference of the hub channels of the sub-irrigation area corresponding to the spatial unit of the sub-irrigation area.

[0101] Specifically, electronic equipment can calculate the flow difference of the key channels in the sub-irrigation area corresponding to the spatial unit of the sub-irrigation area based on the surface water infiltration, the water diversion volume of the sub-irrigation area channels, and the effective rainfall in the sub-irrigation area. The calculation formula is as follows: , among which, I district For the water diversion volume of the irrigation canals in the sub-irrigation area, G district ′ P represents the surface water infiltration rate in the sub-irrigation area. district For the effective rainfall in the sub-irrigation area; γ channel The coefficient for rainfall replenishment to the canal system is taken as an empirical value, with 0.3~0.5 for earthen canals and 0.1~0.2 for lined canals.

[0102] Where, if ΔQ district If ΔQ > 0, then the actual water delivery volume of the hub channel meets the downstream demand, and the water allocation is balanced; if ΔQ district =0, then the water conveyance of the hub channel is equal to the loss and replenishment, and the current dispatch plan needs to be maintained; if ΔQ district If the water diversion volume is less than 0, the water diversion volume of the hub channel cannot cover the leakage loss and rainfall replenishment, indicating abnormal leakage or insufficient water diversion. It is necessary to investigate the channel section or increase the water diversion volume.

[0103] Step a8: Calculate the global infiltration rate corresponding to the spatial unit of the target irrigation area based on the surface water infiltration, effective rainfall, and canal water diversion in the target irrigation area.

[0104] Specifically, the global infiltration rate represents the proportion of the total surface water infiltration in the target irrigation area to the total water supply of the entire irrigation area, and is a macroscopic indicator for measuring the seepage prevention performance of the irrigation area's canal system.

[0105] Electronic equipment can calculate the global infiltration rate corresponding to the spatial unit of the target irrigation area based on the surface water infiltration, effective rainfall, and canal water diversion volume of the target irrigation area, using the following formula: The specific formula is as follows: Among them, G global ′ I represents the total surface water infiltration in the target irrigation area. global P represents the water diversion volume of the target irrigation district canal. global The effective rainfall in the target irrigation area.

[0106] Step a9: Based on the field infiltration rate, field leakage contribution, administrative village channel leakage rate, sub-irrigation area hub channel flow difference, and global infiltration rate, generate a leakage probability heat map corresponding to the target irrigation area.

[0107] Specifically, step a9 above may include the following steps: Step a91: Obtain the soil permeability coefficient, field area, and canal type corresponding to the field spatial unit.

[0108] Specifically, the electronic device can look up the soil permeability coefficient and field area corresponding to the field spatial unit from the field water ledger data corresponding to the field spatial unit, and receive the channel type input by the user.

[0109] The types of channels can include earthen channels, masonry channels, concrete-lined channels, and geomembrane-lined channels. Earthen channels have extremely poor seepage prevention performance, masonry channels have moderate seepage prevention performance, concrete-lined channels have excellent seepage prevention performance, and geomembrane-lined channels have excellent seepage prevention performance.

[0110] Step a92: Based on the soil permeability coefficient, field area, and channel type, determine the seepage diffusion coefficient corresponding to the field spatial unit.

[0111] Specifically, electronic devices can calculate the seepage diffusion coefficient based on soil permeability coefficient, field area, and channel type, quantifying the spatial diffusion capacity of seepage water within a field. The seepage diffusion coefficient D... leak It is a parameter that characterizes the rate at which deep seepage water in a field diffuses into the surrounding soil. The larger the value, the wider the diffusion range of seepage water and the greater its impact on the hydrological environment of the surrounding area.

[0112] The calculation formula is: , where D leak K is the leakage diffusion coefficient. s Soil permeability coefficient, This is the area conversion factor. This is the channel type correction factor. For example, for earthen channels, the channel type correction factor is 1.0, with no seepage prevention measures and no reduction in seepage diffusion; for masonry channels, the channel type correction factor is 0.6, with slight seepage prevention and a 40% reduction in seepage diffusion; for concrete-lined channels, the channel type correction factor is 0.3, with moderate seepage prevention and a 70% reduction in seepage diffusion; and for geomembrane-lined channels, the channel type correction factor is 0.1, with severe seepage prevention and a 90% reduction in seepage diffusion.

[0113] Step a93: Based on the leakage diffusion coefficient, field infiltration rate, and field leakage contribution, calculate the risk coupling value corresponding to the field spatial unit.

[0114] Specifically, electronic devices can integrate three indicators—leakage diffusion coefficient, field infiltration rate, and field leakage contribution—to calculate a risk coupling value and comprehensively assess the leakage risk level of a field. Risk coupling value R couple It is a comprehensive quantitative indicator of field seepage "diffusion capacity - infiltration efficiency - loss contribution". The higher the value, the higher the risk of field seepage.

[0115] The calculation formula is: , where D leak γ is the leakage diffusion coefficient. field θ represents the field infiltration rate. field Contribution to soil seepage.

[0116] For example, R couple <0.5 indicates extremely low risk; routine inspections are recommended. 0.5≤R couple <1.0 indicates low risk; control measures recommended are regular monitoring. 1.0≤R couple <2.0 indicates medium risk; the recommended management approach is to optimize irrigation methods. 2.0≤R couple <5.0 indicates high risk; recommended management measures include soil improvement and canal seepage prevention. couple A value of ≥5.0 indicates an extremely high risk, and the recommended management measures are emergency seepage prevention renovation and precision irrigation.

[0117] Step a94: Obtain the aging degree of the irrigation system, soil type, and irrigation frequency corresponding to the target irrigation area.

[0118] Specifically, the electronic device can receive user input regarding the aging degree of the irrigation system, soil type, and irrigation frequency corresponding to the target irrigation area.

[0119] Step a95: Based on the aging degree of the irrigation system, soil type, and irrigation frequency, determine the first weight information corresponding to the field infiltration rate, the administrative village channel leakage rate, the flow difference of the sub-irrigation area hub channel, and the overall infiltration rate.

[0120] Specifically, electronic devices can use the Analytic Hierarchy Process (AHP) to determine the weights of four indicators—field infiltration rate, administrative village channel leakage rate, sub-irrigation area hub flow difference, and global infiltration rate—based on the aging degree of the irrigation system, soil type, and irrigation frequency in the target irrigation area. These weights are then used for calculating the final leakage probability of subsequent grid units. The weight allocation must reflect the hierarchical risk differences under the guidance of macroscopic parameters. For example, the specific association rules are as follows: for the aging degree of the irrigation system, a score ≥ 4 indicates severe aging, requiring an increase in the weight of the administrative village channel leakage rate; for the soil type, code = 3 corresponds to sandy soil, which has high permeability, thus increasing the weight of the field infiltration rate; for the irrigation frequency, code = 3, meaning an irrigation frequency ≥ 3 times / week, therefore, increasing the weight of the sub-irrigation area hub flow difference.

[0121] Next, the electronic device can construct a pairwise comparison judgment matrix for the four indicators based on the values ​​of the macroscopic parameters. The judgment matrix is ​​the core input of the analytic hierarchy process (AHP), constructed by comparing the importance of the four leakage indicators pairwise. Matrix element a ij The importance of the i-th indicator relative to the j-th indicator is represented by a 1-9 scale. For example, the scale meanings are as follows: 1 indicates that indicator i and indicator j are equally important; 3 indicates that indicator i is slightly more important than indicator j; 5 indicates that indicator i is significantly more important than indicator j; 7 indicates that indicator i is strongly more important than indicator j; 9 indicates that indicator i is extremely more important than indicator j; 2, 4, 6, and 8 represent the median values ​​of the above adjacent scales (used for more refined descriptions of importance).

[0122] For example, the macroscopic parameters of a certain irrigation district are: canal system aging level 4 (severe aging), soil type 2 (loam), and irrigation frequency 2 (twice a week). According to the association rules, the weight of the canal leakage rate of administrative villages needs to be increased. Therefore, the constructed judgment matrix is ​​shown in Table 2 below.

[0123] Table 2. Schematic diagram of the judgment matrix

[0124] For example, the leakage rate of channels in administrative villages vs. the infiltration rate of fields: a 21 =2, meaning the importance of the leakage rate in administrative village channels is twice that of the field infiltration rate; Field infiltration rate vs. flow difference of sub-irrigation area hubs: a 13 =1, meaning both are equally important. Matrix satisfies reciprocity: a ij =1 / a ji , such as a 12 =0.5, then a 21 =2).

[0125] In addition, electronic devices can perform consistency checks on the judgment matrix, with the core indicator being the consistency ratio (CR).

[0126] Specifically, the electronic device can solve the characteristic equation A·W=λ·W for the judgment matrix A to obtain the largest eigenvalue λ. max Taking the example matrix above as an example, we calculate λmax = 4.0.

[0127] Then, the consistency index (CI) is calculated. Where n is the number of indicators (n=4 in this process). Example calculation: Electronic devices can look up the average random consistency index RI. RI is an empirical value calculated by randomly generating a large number of judgment matrices, corresponding to the number of indices n. For example, commonly used values ​​are as follows: when n=1, RI=0; when n=2, RI=0; when n=3, RI=0.58; when n=4, RI=0.90; when n=5, RI=1.12; when n=6, RI=1.24.

[0128] Next, the consistency ratio (CR) of the electronic equipment is calculated. If CR < 0.1, then the judgment matrix meets the consistency requirement and the weight allocation is valid; otherwise, the judgment matrix needs to be adjusted.

[0129] Electronic devices can solve for the eigenvectors of the judgment matrix using the eigenvalue method, and then normalize the eigenvectors to obtain the final weights W1, W2, W3, W4 of the four indicators, satisfying... .

[0130] Step a96: Extract the global canal system water utilization coefficient and the global comprehensive irrigation efficiency from the target irrigation area water account data corresponding to the core water account data.

[0131] Specifically, electronic devices can extract the global canal system water utilization coefficient and the global comprehensive irrigation efficiency from the target irrigation area water account data corresponding to the core water account data.

[0132] Step a97: For different levels of spatial units, divide the spatial units at each level according to different sizes to generate the corresponding grid units for each level of spatial units.

[0133] Specifically, the scale adaptation principle is that the lower the level, the smaller the grid size, ensuring that the risk details of micro-plots are not lost; the higher the level, the larger the grid size, reflecting the risk distribution trend of the macro-irrigation area; the boundary alignment principle is that the grid boundary must be aligned with the geographical boundary of each level of spatial unit to avoid the occurrence of cross-unit grids. For example, the grid size corresponding to a plot is 5m×5m or 10m×10m, which is a refined expression of the leakage risk within the plot; the grid size corresponding to an administrative village is 50m×50m, which shows the regional distribution of leakage risk at the village level; the grid size corresponding to a sub-irrigation area is 200m×200m, which is a trend analysis of leakage risk around the sub-irrigation area hub; and the grid size corresponding to the target irrigation area is 500m×500m, which presents the macro-pattern of leakage risk in the entire irrigation area.

[0134] Electronic devices can load boundary vector data of spatial units at all levels based on a GIS platform, then create a grid layer according to a preset size, trim it to the spatial unit boundaries, and retain the grid within the unit. Finally, each grid is assigned a unique code (such as "hierarchical code - grid row and column number"), and the association between the grid and the original spatial unit is established.

[0135] Step a98: Based on the first weight information and risk coupling value corresponding to the field infiltration rate, administrative village channel leakage rate, sub-irrigation area hub channel flow difference and global infiltration rate, determine the final leakage probability corresponding to each grid unit.

[0136] Specifically, electronic devices can correlate leakage indicators (field infiltration rate, village channel leakage rate, etc.), weight information, and field risk coupling values ​​of various spatial units to corresponding grid units according to their spatial location. The final leakage probability calculation formula uses a weighted summation method to calculate the final leakage probability P for different levels of grid units. leak : ; Among them, W1~W4 are the first weight information of the four indicators, γ field δvillage represents the field infiltration rate, and δvillage represents the canal leakage rate of the administrative village. γ is the normalized value of the flow difference between the sub-irrigation district hubs. global R represents the global infiltration rate. couple-n This is the normalized value of the field risk coupling value.

[0137] Electronic devices can reduce the final leakage probability P leak The heatmap is divided into 5 levels, corresponding to the color gradient of the heatmap. Table 3 shows the color gradient table of the heatmap.

[0138] Table 3 Color Gradient Table of Heatmap

[0139] Step a99: Generate a leakage probability heatmap based on the final leakage probability corresponding to each grid cell.

[0140] Specifically, electronic devices can use professional GIS software such as ArcGIS and QGIS, or Python's Matplotlib and Seaborn libraries for drawing. The final leakage probability data of the grid cells is imported into the GIS platform and associated with the grid layer's attributes. The "hierarchical color setting" rendering method is selected, and the corresponding color gradient is set according to the probability level in step a98. Basic geographic features of the irrigation area (such as canal systems, water sources, and administrative village boundaries) are overlaid to enhance the readability of the heat map. The heat map is exported to common formats (such as PNG, PDF, and TIFF), supporting printing and report embedding.

[0141] The red / orange areas are high-probability leakage zones and require priority for seepage prevention renovations. The color gradient of the heat map is used to analyze the diffusion trend of leakage risk from the canal system to the fields. Step S2062: Based on the core water account data corresponding to each level of spatial unit, generate a time-series curve heat map of the efficiency index corresponding to the target irrigation area.

[0142] Specifically, step S2062 above may include the following steps: Step b1: Extract the farmland irrigation water utilization coefficient from the farmland water account data corresponding to the core water account data.

[0143] Specifically, electronic devices can extract the field irrigation water utilization coefficient from the field water account data corresponding to the core water account data.

[0144] Step b2: Extract the administrative village canal water utilization coefficient and administrative village irrigation water utilization coefficient from the administrative water account data corresponding to the core water account data.

[0145] Specifically, electronic devices can extract the administrative village canal system water utilization coefficient and the administrative village irrigation water utilization coefficient from the administrative water account data corresponding to the core water account data.

[0146] Step b3: Extract the canal system water utilization coefficient and the comprehensive irrigation efficiency of the sub-irrigation area from the sub-irrigation area water account data corresponding to the core water account data.

[0147] Specifically, electronic devices can extract the water utilization coefficient of the canal system and the comprehensive irrigation efficiency of the sub-irrigation area from the sub-irrigation area water account data corresponding to the core water account data.

[0148] Step b4: Extract the global canal system water utilization coefficient and the global comprehensive irrigation efficiency from the target irrigation area water account data corresponding to the core water account data.

[0149] Specifically, electronic devices can extract the global canal system water utilization coefficient and the global comprehensive irrigation efficiency from the target irrigation area water account data corresponding to the core water account data.

[0150] Step b5: For different levels of spatial units, divide the spatial units at each level according to different sizes to generate the corresponding grid units for each level of spatial units.

[0151] Please refer to the above description of step a97 for details on this step, which will not be repeated here.

[0152] Step b6: Obtain the second weight information corresponding to the field irrigation water utilization coefficient, the administrative village canal system water utilization coefficient, the administrative village irrigation water utilization coefficient, the sub-irrigation district canal system water utilization coefficient, the sub-irrigation district comprehensive irrigation efficiency, the global canal system water utilization coefficient, and the global comprehensive irrigation efficiency.

[0153] Specifically, the electronic device can receive second weight information corresponding to the user-inputted field irrigation water utilization coefficient, administrative village canal system water utilization coefficient, administrative village irrigation water utilization coefficient, sub-irrigation district canal system water utilization coefficient, sub-irrigation district comprehensive irrigation efficiency, global canal system water utilization coefficient, and global comprehensive irrigation efficiency, respectively. The electronic device can also allocate second weights to seven indicators with the core objectives of reducing canal system leakage and improving technical efficiency. For example, the second weight corresponding to the farmland irrigation water utilization coefficient is 0.15, which is the basis of micro-level technical efficiency; the second weight corresponding to the administrative village canal system water utilization coefficient is 0.20, as village-level canals are a high-risk area for leakage; the second weight corresponding to the administrative village irrigation water utilization coefficient is 0.10, which is a reference for village-level comprehensive technical efficiency; the second weight corresponding to the sub-irrigation district canal system water utilization coefficient is 0.20, as the main canals of the sub-irrigation district are key to water conveyance; the second weight corresponding to the sub-irrigation district comprehensive irrigation efficiency (normalized) is 0.10, which is a supplementary reference for economic efficiency; the second weight corresponding to the global canal system water utilization coefficient is 0.15, which is a constraint on macro-level technical efficiency; and the second weight corresponding to the global comprehensive irrigation efficiency (normalized) is 0.10, which is a reference for macro-level economic efficiency.

[0154] Electronic devices can also refer to the above calculation process for calculating each first weight information to calculate each second weight information, which will not be elaborated here.

[0155] Step b7: Based on the second weight information, determine the fusion efficiency value corresponding to each grid cell.

[0156] Specifically, based on the second weight information, the electronic device performs weighted fusion calculations on the field irrigation water utilization coefficient, the administrative village canal system water utilization coefficient, the administrative village irrigation water utilization coefficient, the sub-irrigation district canal system water utilization coefficient, the sub-irrigation district comprehensive irrigation efficiency, the global canal system water utilization coefficient, and the global comprehensive irrigation efficiency, respectively, to obtain the fusion efficiency value corresponding to each grid unit.

[0157] Step b8: Establish a time series array of daily fusion efficiency values ​​for each grid cell within the irrigation cycle.

[0158] Specifically, for each grid cell, the electronic device can record the daily fusion efficiency value in "days" within the time range of the irrigation cycle (e.g., a 120-day crop growth period), forming a one-dimensional time-series array: E time =[E fusion-1 E fusion-2 ,...,E fusion-k ,...,E fusion-n ], where: n is the total number of days in the irrigation cycle; E fusion-k This represents the fusion efficiency value on day k. For example, here's a time series array example of a grid cell with a 10-day irrigation cycle: E tim e=[0.72,0.71,0.73,0.70,0.68,0.69,0.71,0.72,0.74,0.73].

[0159] Step b9: Based on the time series array of daily fusion efficiency values, determine the health level corresponding to each grid cell.

[0160] Specifically, electronic devices can extract the mean efficiency E, the coefficient of variation of efficiency CV, and the minimum efficiency value E from the time series array. min Three key quantitative indicators are used to comprehensively determine health status.

[0161] The formula for calculating the average efficiency E is as follows: The formula for calculating the efficiency coefficient of variation (CV) is: Where σ is the standard deviation of the time series array; and E is the minimum efficiency value. min The corresponding calculation formula is: .

[0162] Electronic devices can be calculated to obtain the mean efficiency E, the coefficient of variation of efficiency CV, and the minimum efficiency value E. min The health level of each grid cell is then determined. For example, the health level classification can be shown in Table 4 below.

[0163] Table 4 Health Level Classification Table

[0164] Step b10: Based on the time series array of daily fusion efficiency values ​​and health level, generate a time series curve heatmap of efficiency indicators corresponding to the target irrigation area.

[0165] Specifically, the electronic device can load the target irrigation district's four-level grid vector data and set the boundary styles for different grid levels (e.g., thin red lines for field grids and thick blue lines for sub-irrigation district grids). Then, it assigns colors to the grids using a "green-yellow-red" color scheme, corresponding to the fusion efficiency value (green = high efficiency, red = low efficiency), with color intensity positively correlated with efficiency value. At the center of each grid, a time-series curve of the daily fusion efficiency value for that grid is overlaid (horizontal axis = date, vertical axis = fusion efficiency value), with the curve color consistent with the grid color. Furthermore, the electronic device labels the health level (e.g., "Excellent" or "Good") in the upper right corner of the grid, using different font colors to distinguish them (Excellent = dark green, Very Poor = dark red).

[0166] The electronic device allows users to switch between efficiency heatmaps for different dates using a time slider, observing daily changes in efficiency. Hovering the mouse over the grid automatically displays the time series array, health level, and raw values ​​for seven efficiency indicators. The device also allows users to select specific sub-irrigation districts / administrative villages to view efficiency changes within that area individually. Finally, the electronic device adds a legend (color-efficiency value correspondence), a timeline, a scale bar, a north arrow, and the irrigation district name.

[0167] Step S2063: Based on the heat map of leakage probability and the heat map of efficiency index time series curve, determine the target management measures corresponding to the target irrigation area.

[0168] Specifically, step S2063 above may include the following steps: Step c1: Input the leakage probability heatmap and the efficiency index time series curve heatmap into the preset problem determination model to determine the target problem corresponding to the target irrigation area.

[0169] Specifically, step c1 above may include the following steps: Step c11: Input the leakage probability heatmap and the efficiency index time series curve heatmap into the preset problem determination model.

[0170] Specifically, the electronic device can input the heatmap of leakage probability and the heatmap of efficiency index time series curves into a preset problem determination model. This preset problem determination model can be a machine learning classification model or a rule engine model, which needs to be trained or configured in advance. If it is a machine learning model (such as Random Forest or XGBoost), the model is trained using historical irrigation district problem data (such as "high leakage, low efficiency" or "low leakage, high efficiency fluctuations") as labels. If it is a rule engine model, preset problem judgment rules are used (such as "leakage probability > 0.7 and fusion efficiency value < 0.5 → judged as high leakage, low efficiency problem").

[0171] Step c12: The preset problem determination model identifies the leakage probability heatmap, extracts the final leakage probability, risk coupling value, leakage diffusion coefficient, canal aging degree, normalized soil permeability coefficient and irrigation frequency corresponding to each grid unit in the leakage probability heatmap, and obtains the efficiency feature vector corresponding to each grid unit.

[0172] Specifically, the pre-defined problem determination model can identify the leakage probability heatmap by reading image attributes and performing data inversion. It can then extract the final leakage probability, risk coupling value, leakage diffusion coefficient, canal aging degree, normalized soil permeability coefficient, and irrigation frequency corresponding to each grid cell in the leakage probability heatmap, thereby obtaining the efficiency feature vector corresponding to each grid cell.

[0173] Step c13: The preset problem determination model identifies the efficiency index time series curve heat map, extracts the fusion efficiency value, health level quantification value, efficiency time series fluctuation rate, efficiency trend slope, canal water utilization coefficient, and comprehensive irrigation efficiency corresponding to each grid unit in the efficiency index time series curve heat map, and obtains the efficiency feature vector corresponding to each grid unit.

[0174] In the leakage probability heatmap, each grid cell corresponds one-to-one with each grid cell in the efficiency index time series curve heatmap.

[0175] Specifically, the pre-defined problem-solving model can identify the heat map of the time series curve of efficiency indicators through time series data analysis and image attribute parsing. It can extract the fusion efficiency value, health level quantification value, efficiency time series fluctuation rate, efficiency trend slope, canal water utilization coefficient, and comprehensive irrigation efficiency corresponding to each grid unit in the heat map of the time series curve of efficiency indicators, and obtain the efficiency feature vector corresponding to each grid unit.

[0176] Step c14: The efficiency feature vectors and efficiency feature vectors corresponding to each grid cell are fused to obtain the fused feature vectors corresponding to each grid cell.

[0177] Optionally, the pre-defined problem-solving model can be based on a direct concatenation method, where efficiency feature vectors are concatenated sequentially to obtain the fused feature vector corresponding to each grid cell. The formula is: F fusion =[F leak ,F eff ]=[f1,f2,f3,f4,f5,f6,g1,g2,g3,g4,g5,g6].

[0178] Optionally, the electronic device can assign weights α and β to the efficiency feature vector, where α + β = 1. Then, the weighted sum is calculated according to the corresponding dimensions, as shown in the formula: f fusion-i =α·f i +β·g i, i=1~6, to obtain the fused feature vector.

[0179] Optionally, the pre-defined problem-solving model can calculate the interaction term between the efficiency eigenvector and the efficiency eigenvector: f cross-i =f i ·g i Then, the cross term is concatenated with the original two vectors to form a fused feature vector.

[0180] Step c15: Based on each fused feature vector, determine the target problem corresponding to at least one grid region in the target irrigation area.

[0181] The grid region includes at least one grid cell.

[0182] Optionally, the preset problem determination model can preset five types of typical target problems and judgment conditions. Based on each fused feature vector, it determines the target problem corresponding to at least one grid area in the target irrigation area. For example, Table 5 below shows the preset five types of typical target problems and judgment conditions.

[0183] Table 5 Typical Target Problems and Judgment Criteria

[0184] Specifically, the preset problem determination model can directly match the above "feature threshold - problem type". Grids that meet a certain condition are determined to be the corresponding problem. The logic is simple and highly interpretable.

[0185] Optionally, the electronic device uses historical irrigation area problem data as labels and trains a classification pre-defined problem determination model (such as random forest) using fused feature vectors. The pre-defined problem determination model outputs the probability of each grid belonging to each type of problem, and the category with the highest probability is taken as the judgment result, which is more accurate and adaptable to complex irrigation areas.

[0186] Then, the electronic device can merge consecutive grid cells that are identified as having the same problem type into a "problem area," avoiding the fragmentation of individual grid identification. The electronic device adds labels to each problem area, including "problem type, area, and average core feature index," generating a distribution map of target problems in the irrigation area. It then marks the location, extent, and type of each problem area on the GIS base map, visually displaying the spatial pattern of problems in the irrigation area.

[0187] Step c2: Based on the target problem, determine the target management measures corresponding to the target irrigation area.

[0188] Specifically, step c2 above may include the following steps: Step c21: For the target problem corresponding to each grid area, match at least one candidate management measure in the preset measure library, and determine the measure cost and effective period of each candidate management measure.

[0189] Specifically, for each grid area's corresponding target problem, the electronic device can match at least one suitable candidate management measure from a pre-set measure library and extract core attributes such as cost and time to effectiveness for each measure, providing basic data for subsequent priority calculation. The pre-set measure library is constructed based on common irrigation district problem types, covering three main categories: engineering measures, agronomic measures, and management measures, clearly defining the applicable problem type, cost, and time to effectiveness for each measure. A typical measure library example is shown in Table 6 below.

[0190] Table 6 Example Table of Measures Library

[0191] Electronic devices can use a direct matching method based on "problem type - applicable scope of measures" to ensure that candidate measures are highly consistent with the target problem. For example, if the grid area is of the high leakage-low efficiency type, then "canal seepage prevention lining, drip irrigation transformation, soil improvement" will be matched; if it is of the low leakage-efficiency fluctuation type, then "straw mulching for moisture retention, irrigation system optimization" will be matched; if it is of the medium leakage-efficiency decline type, then "sprinkler irrigation transformation, canal inspection and maintenance" will be matched.

[0192] For each target problem, at least two candidate measures are matched to the corresponding grid area. The electronic device calculates the cost and effective period of each candidate management measure. The cost includes "one-time investment cost" and "annual operation and maintenance cost," uniformly converted to unit area (yuan / hm²). 2 Cost; the effective period refers to the time it takes for irrigation efficiency or leakage risk to significantly improve after the measures are implemented, and is counted in "weeks / months".

[0193] Step c22: Obtain the regional average fusion efficiency value and soil type code for each grid region.

[0194] Specifically, the electronic device can extract the regional average fusion efficiency value and soil type code corresponding to the grid area. The average fusion efficiency value is the arithmetic mean of the fusion efficiency values ​​of all grid cells within the target problem area, i.e., the E calculated in step b7. fusion The mean reflects the overall level of regional irrigation efficiency. The soil type code is the dominant soil type code for the grid area corresponding to the target problem (1=clay, 2=loam, 3=sandy).

[0195] Step c23: Calculate the effect improvement rate of each candidate management measure corresponding to the grid area based on the average fusion efficiency value of the grid area and the soil type code.

[0196] Specifically, the electronic device can determine the soil type correction coefficient K based on the soil type code. soilsuch as clay K soil =0.8, soil K soil =1.0, sandy soil K soil =1.2. Electronic equipment can extract the baseline leakage reduction rate corresponding to candidate management measures from a preset measures library, such as R for canal system seepage prevention lining. base =40%.

[0197] Electronic devices can calculate the leakage risk reduction rate R based on the soil type correction factor corresponding to the candidate management measures and the baseline leakage reduction rate. leak R leak =R base ×K soil , where: R base K represents the baseline leakage reduction rate for candidate management measures. soil This is the soil type correction factor.

[0198] Electronic devices can extract the baseline efficiency improvement rate R corresponding to candidate management measures from a preset measure library. base ′, such as R for drip irrigation transformation base =30%. Then, the electronic device calculates the irrigation efficiency improvement rate R based on the baseline efficiency improvement rate and the regional average fusion efficiency value. eff The formula is: ,in, This represents the average fusion efficiency value for the region.

[0199] Finally, the electronic equipment uses a weighted summation method to calculate the overall improvement rate, and the weight allocation needs to be combined with the irrigation district management objectives. The fusion formula is: .

[0200] For example, if the irrigation district takes "reducing seepage" as its core objective, then γ = 0.6; if it takes "improving efficiency" as its core objective, then γ = 0.4; and if it has a balanced objective, then γ = 0.5.

[0201] Step c24: Calculate the priority score for each candidate management measure based on the measure cost, time to effectiveness, and effect improvement rate.

[0202] Specifically, electronic devices can perform weighted calculations on the cost of measures, the time to effectiveness, and the improvement of effects to obtain the priority score corresponding to each candidate management measure.

[0203] Step c25: Determine the target management measures corresponding to each grid area based on the priority scores.

[0204] Specifically, the electronic device can compare the scores of each priority level and determine the candidate management measure with the highest priority score as the target management measure corresponding to the grid area.

[0205] The irrigation district management method provided in this application constructs a four-level spatial unit target core balance equation to generate water account data at each level. Using field plots as the basic unit, the method accurately calculates key indicators such as deep seepage and canal system water utilization coefficients through the water balance equation. This data is then aggregated level by level to generate water account data for administrative villages, sub-irrigation districts, and the target irrigation district, forming a hierarchical and refined water revenue and expenditure ledger. This solves the problem of traditional irrigation district water accounts being "overall-oriented but neglecting local aspects," accurately locating water loss links at each level (such as deep seepage in field plots and canal system seepage in administrative villages). Based on the core water account data, seepage-related indicators are calculated, generating a seepage probability heatmap.

[0206] Data such as infiltration and water diversion are extracted from water ledgers at all levels to calculate indicators such as field infiltration rate, leakage contribution, and village canal leakage rate, ultimately generating a spatially visualized leakage probability heatmap. This intuitively presents the spatial distribution characteristics of leakage risk in the irrigation area, quickly identifies high-risk leakage areas, and provides precise spatial targets for seepage prevention and mitigation. Efficiency indicators are extracted based on core water ledger data to generate time-series curve heatmaps of efficiency indicators.

[0207] Irrigation efficiency-related indicators are extracted from four-level spatial units. Through weighted fusion, the fused efficiency value of each grid unit is obtained. Combined with time-series analysis and health grading, a dual-dimensional efficiency heatmap ("spatial + temporal") is generated. This not only displays spatial differences in efficiency but also depicts the dynamic changes in efficiency within the irrigation cycle, clearly reflecting the time nodes and spatial locations of efficiency fluctuations. The dual heatmaps are input into a pre-defined model, and feature vectors are extracted and fused. Multi-dimensional feature vectors are extracted from both the leakage and efficiency heatmaps, ensuring one-to-one correspondence between grid units before fusion to form a coupled feature vector of "leakage risk + irrigation efficiency." This achieves deep integration of dual-dimensional data, avoiding misjudgments caused by single-dimensional analysis and improving the comprehensiveness and accuracy of problem identification. The target problems in the target irrigation area are determined based on the fused feature vectors. The model is used to analyze the fused feature vectors to accurately determine the typical problem types in the grid area (e.g., high leakage-low efficiency, low leakage-efficiency fluctuation, etc.). The output target problems possess both spatial accuracy and typicality, providing a direct basis for subsequent targeted management measures.

[0208] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for managing irrigation districts, characterized in that, The method includes: Obtain the target irrigation district to be managed; Based on the administrative and hydrological boundaries corresponding to the target irrigation area, the target irrigation area is divided into four spatial units: "target irrigation area - sub-irrigation area - administrative village - field". Acquire the basic hydrological variables, equipment status variables, and environmental characteristic variables corresponding to each level of spatial unit in the target irrigation area; Based on the basic hydrological variables, equipment status variables, and environmental characteristic variables corresponding to each level of spatial unit, the target core equilibrium equation is constructed. Based on the target core balance equation, determine the core water account data corresponding to each level of spatial unit of the target irrigation district; Based on the core water volume data corresponding to each level of spatial unit, the target management measures corresponding to the target irrigation area are determined.

2. The method according to claim 1, characterized in that, The target core equilibrium equation is constructed based on the basic hydrological variables, equipment state variables, and environmental characteristic variables corresponding to each level of spatial unit, including: The target core equilibrium equations corresponding to each level of space unit are: ； Among them, I i For the water diversion volume of the channel, P i For effective rainfall, G i For groundwater recharge and discharge, ET i Crop evapotranspiration, R i For drainage volume, D i For deep leakage, For changes in soil water storage, This represents the amount of surface water infiltration.

3. The method according to claim 2, characterized in that, The determination of core water account data for each level of spatial unit corresponding to the target irrigation district based on the target core balance equation includes: For each field space unit, the following data are extracted from the basic hydrological variables, equipment status variables, and environmental characteristics variables of the corresponding field space unit: field channel water diversion volume, effective rainfall, drainage volume, groundwater level depth, field area, soil permeability coefficient, changes in soil water storage, crop growth stage, and first equipment status. The groundwater recharge and discharge volume corresponding to the field spatial unit is calculated based on the groundwater level depth and the field area. Based on the crop growth stage, calculate the crop evapotranspiration of the field corresponding to the field spatial unit; Based on the soil permeability coefficient, calculate the surface water infiltration amount of the field corresponding to the field spatial unit; Substituting the water diversion volume of the field channels, the effective rainfall of the field, the groundwater recharge and discharge of the field, the crop evapotranspiration of the field, the drainage volume of the field, the change in soil water storage of the field, and the surface water infiltration of the field into the target core balance equation corresponding to the field spatial unit, we can obtain the deep infiltration volume of the field corresponding to the field spatial unit. Based on the water diversion volume of the field canals and the groundwater replenishment and discharge volume of the field, calculate the field canal water utilization coefficient and the field irrigation water utilization coefficient corresponding to the field spatial unit; Based on the water diversion volume of the field canals, the effective rainfall of the field, the groundwater recharge and discharge of the field, the crop evapotranspiration of the field, the drainage volume of the field, the change in soil water storage of the field, the surface water infiltration of the field, the deep seepage of the field, the water utilization coefficient of the field canal system, and the irrigation water utilization coefficient of the field, the field water account data corresponding to the field spatial unit is obtained. For each administrative village spatial unit, based on the basic hydrological variables, equipment status variables, environmental characteristic variables, and field water account data of the administrative village corresponding to the administrative village spatial unit, the following data are obtained: water diversion volume of the administrative village canals, effective rainfall, groundwater recharge and discharge, crop evapotranspiration, drainage, soil water storage changes, surface water infiltration, deep seepage, canal water utilization coefficient, and irrigation water utilization coefficient of the administrative village spatial unit. For each sub-irrigation area spatial unit, based on the sub-irrigation area's basic hydrological variables, equipment status variables, environmental characteristic variables, and water account data of the administrative village, the following data are obtained: sub-irrigation area canal water diversion, effective rainfall, groundwater recharge and discharge, crop evapotranspiration, drainage, soil water storage changes, surface water infiltration, deep seepage, canal system water utilization coefficient, and comprehensive irrigation efficiency. For a target irrigation area spatial unit, based on the target irrigation area's basic hydrological variables, equipment status variables, environmental characteristic variables, and sub-irrigation area water account data, the target irrigation area's canal water diversion, effective rainfall, groundwater recharge and discharge, crop evapotranspiration, drainage, soil water storage changes, surface water infiltration, deep seepage, global canal system water utilization coefficient, and global comprehensive irrigation efficiency are obtained, thus yielding the target irrigation area water account data corresponding to the target irrigation area spatial unit. Based on the water account data of the farmland, the water account data of the administrative villages, the water account data of the sub-irrigation areas, and the water account data of the target irrigation area, the core water account data corresponding to each level of spatial unit is generated.

4. The method according to claim 1, characterized in that, The determination of target management measures for the target irrigation district based on the core water volume data corresponding to each level of spatial unit includes: Based on the core water account data corresponding to each level of spatial unit, a heat map of leakage probability corresponding to the target irrigation area is generated. Based on the core water account data corresponding to each level of spatial unit, a time-series heat map of efficiency indicators corresponding to the target irrigation area is generated. Based on the leakage probability heatmap and the efficiency index time-series curve heatmap, the target management measures corresponding to the target irrigation area are determined.

5. The method according to claim 4, characterized in that, The process of generating a heatmap of leakage probability for the target irrigation area based on the core water volume data corresponding to each level of spatial unit includes: Extract the following data from the field water ledger data corresponding to the core water ledger data: surface water infiltration, water diversion from field channels, effective rainfall, and deep seepage from the field. Extract the surface water infiltration volume, effective rainfall, canal water diversion volume, and canal water utilization coefficient of the administrative villages from the administrative village water account data corresponding to the core water account data. Extract the surface water infiltration volume, canal water diversion volume, and effective rainfall of the sub-irrigation area from the sub-irrigation area water account data corresponding to the core water account data; Extract the surface water infiltration volume, canal water diversion volume, and effective rainfall of the target irrigation area from the target irrigation area water account data corresponding to the core water account data; Based on the surface water infiltration rate, the water diversion rate of the field channels, and the effective rainfall of the field, the field infiltration rate corresponding to the field spatial unit is calculated; based on the deep infiltration rate of the field, the field infiltration contribution rate corresponding to the field spatial unit is calculated. Based on the water utilization coefficient of the canal system of the administrative village, calculate the canal leakage rate of the administrative village corresponding to the spatial unit of the administrative village; Based on the surface water infiltration rate of the sub-irrigation area, the water diversion rate of the sub-irrigation area canals, and the effective rainfall of the sub-irrigation area, calculate the flow difference of the hub canals of the sub-irrigation area corresponding to the spatial unit of the sub-irrigation area; Based on the surface water infiltration rate of the target irrigation area, the effective rainfall of the target irrigation area, and the water diversion volume of the target irrigation area canals, calculate the global infiltration rate corresponding to the spatial unit of the target irrigation area; Based on the field infiltration rate, the field leakage contribution, the administrative village channel leakage rate, the sub-irrigation area hub channel flow difference, and the global infiltration rate, a leakage probability heat map corresponding to the target irrigation area is generated.

6. The method according to claim 5, characterized in that, The process of generating a leakage probability heatmap for the target irrigation district based on the field infiltration rate, the field leakage contribution, the administrative village canal leakage rate, the sub-irrigation district hub canal flow difference, and the global infiltration rate includes: Obtain the soil permeability coefficient, field area, and canal type corresponding to the field spatial unit; Based on the soil permeability coefficient, the field area, and the channel type, the seepage diffusion coefficient corresponding to the field spatial unit is determined; Based on the leakage diffusion coefficient, the field infiltration rate, and the field leakage contribution, the risk coupling value corresponding to the field spatial unit is calculated. Obtain the aging degree of the irrigation system, soil type, and irrigation frequency corresponding to the target irrigation area; Based on the degree of aging of the canal system, the soil type, and the irrigation frequency, determine the first weight information corresponding to the field infiltration rate, the administrative village canal leakage rate, the flow difference of the sub-irrigation area hub canal, and the global infiltration rate, respectively. Extract the global canal system water utilization coefficient and the global comprehensive irrigation efficiency from the target irrigation area water account data corresponding to the core water account data; For different levels of spatial units, the spatial units at each level are divided according to different sizes, and the corresponding grid units for each level of spatial units are generated; Based on the first weight information corresponding to the field infiltration rate, the administrative village channel leakage rate, the sub-irrigation area hub channel flow difference, and the global infiltration rate, as well as the risk coupling value, the final leakage probability corresponding to each grid unit is determined. The leakage probability heatmap is generated based on the final leakage probability corresponding to each of the grid cells.

7. The method according to claim 4, characterized in that, The process of generating a time-series heatmap of efficiency indicators for the target irrigation district based on the core water volume data corresponding to each level of spatial unit includes: Extract the farmland irrigation water utilization coefficient from the farmland water account data corresponding to the core water account data; Extract the administrative village canal water utilization coefficient and administrative village irrigation water utilization coefficient from the administrative water account data corresponding to the core water account data; Extract the canal system water utilization coefficient and the comprehensive irrigation efficiency of the sub-irrigation area from the sub-irrigation area water account data corresponding to the core water account data; Extract the global canal system water utilization coefficient and the global comprehensive irrigation efficiency from the target irrigation area water account data corresponding to the core water account data; For different levels of spatial units, the spatial units at each level are divided according to different sizes, and the corresponding grid units for each level of spatial units are generated; Obtain the second weight information corresponding to the farmland irrigation water utilization coefficient, the administrative village canal system water utilization coefficient, the administrative village irrigation water utilization coefficient, the sub-irrigation district canal system water utilization coefficient, the sub-irrigation district comprehensive irrigation efficiency, the global canal system water utilization coefficient, and the global comprehensive irrigation efficiency, respectively; Based on the second weight information, the fusion efficiency value corresponding to each of the grid cells is determined; A time-series array of daily fusion efficiency values ​​within the irrigation cycle is established for each of the aforementioned grid cells; Based on the time-series array of the daily fusion efficiency values, the health level of each grid cell is determined. Based on the time series array of the daily fusion efficiency values ​​and the health level, a time series curve heatmap of the efficiency index corresponding to the target irrigation area is generated.

8. The method according to claim 4, characterized in that, The determination of target management measures corresponding to the target irrigation area based on the leakage probability heatmap and the efficiency index time-series curve heatmap includes: The leakage probability heatmap and the efficiency index time series curve heatmap are input into a preset problem determination model to determine the target problem corresponding to the target irrigation area; Based on the target problem, determine the target management measures corresponding to the target irrigation area.

9. The method according to claim 8, characterized in that, The step of inputting the leakage probability heatmap and the efficiency index time-series curve heatmap into a preset problem determination model to determine the target problem corresponding to the target irrigation area includes: Input the leakage probability heatmap and the efficiency index time series curve heatmap into the preset problem determination model; The preset problem determination model identifies the leakage probability heatmap, extracts the final leakage probability, risk coupling value, leakage diffusion coefficient, canal aging degree, normalized value of soil permeability coefficient and irrigation frequency corresponding to each grid unit in the leakage probability heatmap, and obtains the leakage feature vector corresponding to each grid unit. The preset problem determination model identifies the efficiency index time-series curve heatmap, extracts the fusion efficiency value, health level quantification value, efficiency time-series fluctuation rate, efficiency trend slope, canal water utilization coefficient, and comprehensive irrigation efficiency corresponding to each grid unit in the efficiency index time-series curve heatmap, and obtains the efficiency feature vector corresponding to each grid unit; wherein, each grid unit in the leakage probability heatmap corresponds one-to-one with each grid unit in the efficiency index time-series curve heatmap. The leakage feature vector and the efficiency feature vector corresponding to each grid cell are fused to obtain the fused feature vector corresponding to each grid cell. Based on the fused feature vectors, the target problem corresponding to at least one grid region in the target irrigation area is determined; wherein, the grid region includes at least one grid cell.

10. The method according to claim 8, characterized in that, The target problem includes at least one target problem corresponding to a grid area. Determining the target management measures corresponding to the target irrigation district based on the target problem includes: For each of the target problems corresponding to the grid areas, at least one candidate management measure is matched in the preset measure library, and the measure cost and effective period corresponding to each candidate management measure are determined; Obtain the regional average fusion efficiency value and soil type code corresponding to each grid region; Based on the average fusion efficiency value of the grid area and the soil type code, the effect improvement rate of each candidate management measure corresponding to the grid area is calculated. Based on the cost of the measures, the time to achieve results, and the rate of improvement in effectiveness, calculate the priority score for each of the candidate management measures. Based on the priority scores, the target management measures corresponding to each grid area are determined.

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