Irrigation water utilization coefficient evaluation method and system based on whole-process simulation of irrigation area water consumption

Abstract

The invention discloses an irrigation water utilization coefficient evaluation method and system based on irrigation area water use whole process simulation, and relates to the technical field of agricultural water-saving irrigation. Irrigation water utilization information is obtained through multi-source data fusion; based on the irrigation water utilization information, constructing an irrigation area water utilization whole-process simulation model; the whole-process water consumption simulation model for the irrigated area comprises main canal water simulation, field canal water simulation and field crop water simulation; calculating a water delivery utilization coefficient, a water distribution utilization coefficient and a field water utilization coefficient by utilizing the irrigation area water utilization whole-process simulation model; and multiplying the obtained water delivery utilization coefficient, water distribution utilization coefficient and field water utilization coefficient to obtain an irrigation water utilization coefficient. The irrigation water utilization coefficient is accurately measured and calculated, the water utilization efficiency of crops is accurately evaluated, and fine management of water utilization in an irrigation area and water-saving benefit evaluation can be achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural water-saving irrigation, and more particularly to an irrigation water utilization coefficient evaluation method and system based on full-process simulation of water use in an irrigation area. Background Art

[0002] At present, agricultural irrigation accounts for the vast majority of total water use in arid and semi-arid areas, and improving irrigation efficiency has a significant impact on the sustainability of water resources. Water conservancy is the lifeblood of agriculture, and food production depends on irrigation. The sustainability of water resources is directly related to the stability of food supply. Climate change and population growth have made these two issues more urgent. Therefore, improving the efficiency of irrigation water use is crucial to ensuring food security and the sustainable use of water resources.

[0003] The effective irrigation water utilization coefficient (IWUC) is a core indicator for measuring irrigation water efficiency. Traditional methods for calculating the IWUC, such as the "head-to-tail method," rely solely on canal headwater inflow and measured field water consumption. These methods fail to accurately quantify losses during water distribution and fail to reflect the water-saving potential under different irrigation district conditions. Furthermore, with the rapid development of modern agricultural technologies such as remote sensing, drone monitoring, IoT sensors, and GIS spatial analysis, irrigation district water resource management is moving toward digitalization, refinement, and intelligence. Utilizing multi-source data to construct a more scientific and systematic IWUC assessment method to improve the accuracy and efficiency of irrigation district water resource management has become a hot topic of research.

[0004] Numerous researchers have explored methods for measuring irrigation water utilization coefficients based on intelligent detection methods. For example, the Pearl River Water Conservancy Commission's Pearl River Water Conservancy Research Institute proposed a remote sensing-based method for calculating the effective irrigation water utilization coefficient (ZL2019111272873). This method uses remote sensing to measure total irrigation water volume and net surface flow, ultimately calculating the irrigation water utilization coefficient using the head-to-tail method. The Jiangsu Water Conservancy Research Institute proposed an automatic method and system for calculating the effective irrigation water utilization coefficient for rice fields (ZL2024108845616). Measuring instruments are deployed throughout the rice fields, and the effective irrigation water utilization coefficient for each sampling unit is calculated using the head-to-tail method. The coefficient for each sampling unit is then weighted averaged to obtain the coefficient for the entire measurement area. Current research uses the head-to-tail method to measure water volume only at the canal head and at both ends of the field. This method fails to accurately capture water losses during each stage of the water distribution process, leading to significant deviations in the calculated results. Furthermore, existing methods for calculating the effective irrigation water utilization coefficient fail to fully consider the dynamic water demand of crops throughout their growth cycle, making it difficult to accurately assess crop water use efficiency.

[0005] Therefore, how to accurately evaluate crop water use efficiency based on the dynamic water demand process of the entire crop growth cycle is an urgent problem that technicians in this field need to solve. Summary of the Invention

[0006] In view of this, the present invention provides an irrigation water utilization coefficient evaluation method and system based on the simulation of the entire water use process in the irrigation area. Based on the measured data of the channel, the Saint-Venant equations are used to analyze the water loss in the irrigation area channel and the water distribution utilization coefficient. It is planned to use multi-source data such as remote sensing satellites, UAV monitoring, and meteorological station data to calculate the field water utilization coefficient, construct a simulation model of the entire water use process in the irrigation area, accurately measure the irrigation water utilization coefficient, and accurately evaluate the water use efficiency of crops, so as to realize the refined management of water use in the irrigation area and the evaluation of water-saving benefits.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] An irrigation water utilization coefficient evaluation method based on the simulation of the entire water use process in the irrigation area, which obtains irrigation water utilization information through multi-source data fusion;

[0009] Based on the irrigation water utilization information, a simulation model of the entire irrigation area water use process is constructed; the simulation model of the entire irrigation area water use process includes main canal water simulation, field canal water simulation and field crop water simulation;

[0010] The water utilization coefficient of the entire irrigation area is calculated using the simulation model of the entire irrigation area water use process;

[0011] The irrigation water utilization coefficient is obtained by multiplying the obtained water delivery utilization coefficient, water distribution utilization coefficient and field water utilization coefficient.

[0012] Optionally, the process of the main canal water simulation and the field canal water simulation is the same, specifically:

[0013] Basic model construction and discretization: First, the irrigation channel network is topologically transformed into a tree structure, and the calculation units are divided into two levels: main channel and field channel. Different lining materials need to consider channel shape, initial water depth, flow velocity, and channel roughness parameters. The channel roughness is assigned based on the channel material classification.

[0014] The unsteady flow Saint-Venant equations are used to simulate water flow, seepage loss and irrigation water supply scheduling in irrigation canal systems.

[0015] Gate control coupling and boundary processing: The gate is used as the internal boundary condition and the gate flow formula is established based on the energy equation;

[0016] Calculation of water transmission and distribution utilization coefficient: Using the Preissmann implicit difference method to discretize the equation, the temporal and spatial distribution of flow and water depth is iteratively solved, and the seepage loss of each canal section is calculated to compare the water utilization efficiency of different water transmission methods; the key water volume parameters in the water transmission process are calculated in the simulated irrigation area water transmission process, and the water diversion volume of the canal head, the water transmission loss of the main canal, and the water transmission loss of the branch canal are calculated;

[0017] Based on the obtained headwater diversion volume, main canal water transmission loss, and branch canal water transmission loss, the main canal water transmission utilization coefficient and distribution water utilization coefficient are calculated.

[0018] Optionally, the unsteady flow Saint-Venant equations are specifically:

[0019]

[0020] Among them, x is the displacement of water flow, t is time, Q is flow rate, A is the cross-sectional area of ​​water flow, h is water depth, g is gravity acceleration, S0 is bottom slope, S f The friction resistance makes the slope descend.

[0021] Optionally, the gate flow formula is as follows:

[0022]

[0023] Among them, C d is the discharge coefficient, b is the gate opening, and Δh is the upstream and downstream water level difference.

[0024] Optionally, the main canal water utilization coefficient η is calculated based on the obtained headwater diversion, main canal water loss, and branch canal water loss. s and water utilization coefficient η d Specifically:

[0025]

[0026] Among them, W in is the water diversion volume at the head of the canal, W losss is the water loss of the main canal, W lossd is the water loss of the branch canal, W losss =W in -W 干渠 , W lossd =W 干渠 -W 田间 .

[0027] Optionally, the field crop water simulation is specifically as follows:

[0028] Model selection: Use crop evapotranspiration estimation model to estimate crop evapotranspiration ET c ;

[0029] Using soil moisture changes and crop evapotranspiration as input data, combined with ERA5 precipitation data, the irrigation water consumption was calibrated.

[0030] Calculate the field water utilization coefficient η based on irrigation water consumption and field water supply f .

[0031] Optional, crop evapotranspiration (ET) c The mathematical expression is:

[0032] ET c =K c ×ET0

[0033] Among them: K c is the crop coefficient, which indicates the evapotranspiration capacity of crops at different growth stages; ET0 is the net radiation and soil heat flux; it is calculated according to the following formula:

[0034]

[0035] Where: R n is the net radiation; G is the soil heat flux; T is the air temperature; u2 is the wind speed at 2m; e s and e a are the saturated water vapor pressure and actual water vapor pressure respectively; γ is the dry-wet ratio; Δ is the slope of the saturated water vapor pressure curve.

[0036] Optionally, calculate the field water utilization coefficient η f The formula is:

[0037]

[0038] Where: P is the amount of irrigation water, representing the actual use of irrigation water by crops; W 田间 The water supply to the fields includes the irrigation water entering the fields from branch canals and effective precipitation.

[0039] An irrigation water utilization coefficient evaluation system based on the simulation of the entire irrigation area water use process includes:

[0040] Data collection module, which obtains irrigation water utilization information through multi-source data fusion;

[0041] A model building module, based on irrigation water utilization information, constructs a simulation model of the entire irrigation area water use process; the simulation model of the entire irrigation area water use process includes main canal water simulation, field canal water simulation and field crop water simulation;

[0042] The coefficient calculation module uses the whole process simulation model of irrigation area water use to calculate the water transmission utilization coefficient, water distribution utilization coefficient and field water utilization coefficient;

[0043] The result output module multiplies the obtained water transmission utilization coefficient, water distribution utilization coefficient and field water utilization coefficient to obtain the irrigation water utilization coefficient.

[0044] It can be seen from the above technical solutions that, compared with the prior art, the present invention provides an irrigation water utilization coefficient evaluation method and system based on the simulation of the entire irrigation water use process, which has the following beneficial effects:

[0045] (1) The present invention combines multi-source remote sensing images, drone monitoring, meteorological data, soil moisture monitoring and water supply and distribution statistics to construct a simulation model for the entire water use process in the irrigation area. It can accurately obtain information such as irrigation water diversion, water supply loss, field water consumption and crop evapotranspiration, realize dynamic monitoring of the irrigation area's water supply and distribution process and field water utilization, improve the accuracy of irrigation water utilization coefficient calculation, and provide a scientific basis for optimizing irrigation scheduling.

[0046] (2) The present invention constructs a numerical simulation model of irrigation channel based on the Saint-Venant equation, gate control coupling and boundary processing; proposes a CPU parallel computing method to achieve a balance between computing accuracy and computing power, and then calculates water transmission, water distribution and field water utilization coefficients in stages, refines the sources of water utilization loss, and provides scientific support for precise irrigation management.

[0047] (3) The present invention utilizes multi-source data fusion and drone monitoring and other technical means, combined with the crop water demand law model, to dynamically evaluate the field water use efficiency. At the same time, through the ET calculation during the crop growth period, it accurately reflects the water demand and irrigation utilization efficiency of different crops and different growth stages, calculates the field water utilization coefficient, and thus provides scientific support for precise irrigation management.

[0048] (4) The present invention constructs an irrigation water utilization coefficient evaluation system based on multi-source data, covering core indicators such as water transmission loss coefficient, field water utilization coefficient, and crop water consumption efficiency. It can be widely applied to different types of irrigation areas and provides a water utilization efficiency evaluation framework for water-saving transformation measures (such as channel anti-seepage, drip irrigation, sprinkler irrigation, etc.), providing technical support for regional water resource optimization, precise water-saving management, and policy formulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0050] Figure 1 The present invention provides a flow chart of the method. DETAILED DESCRIPTION

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0052] The embodiment of the present invention discloses an irrigation water utilization coefficient evaluation method based on the simulation of the entire water use process in the irrigation area. Figure 1 As shown, including:

[0053] Obtain irrigation water utilization information through multi-source data fusion;

[0054] Based on the irrigation water utilization information, a simulation model of the entire irrigation area water use process is constructed; the simulation model of the entire irrigation area water use process includes main canal water simulation, field canal water simulation and field crop water simulation;

[0055] The water utilization coefficient of the entire irrigation area is calculated using the simulation model of the entire irrigation area water use process;

[0056] The irrigation water utilization coefficient is obtained by multiplying the obtained water delivery utilization coefficient, water distribution utilization coefficient and field water utilization coefficient.

[0057] The calculation principle of the present invention is:

[0058] According to the water balance principle, the irrigation water utilization coefficient (IWUE) can be divided into the water utilization coefficient (η s ), water distribution utilization coefficient (η d ), field water utilization coefficient (η f ), the present invention is based on this solution and uses remote sensing, drone and other data for analysis.

[0059] The irrigation water use efficiency (IWUE) is defined as:

[0060] IWUE=η s ×η d ×η f

[0061] Among them, the water utilization coefficient (η s ): Water delivery efficiency from the canal head to the main canal of the irrigation area.

[0062] Water utilization coefficient (η d ): Water delivery efficiency from main canals to fields.

[0063] Field water utilization coefficient (η f ):Efficiency of crops in utilizing available water in the field.

[0064] In a specific embodiment, irrigation water utilization information is obtained through multi-source data fusion, which mainly covers four key links: data acquisition, water utilization simulation, parameter optimization, and indicator evaluation. The main process is as follows:

[0065] (1) Data acquisition and processing

[0066] 1) Remote sensing image selection and interpretation

[0067] Sentinel-2A (10-60m resolution, 10-day recurrence) and Landsat 8 (30m resolution, 16-day recurrence) were selected as the primary remote sensing imagery for high spatial resolution. Their high spatial resolution enables accurate identification of crop planting structure, land surface, and vegetation cover. Furthermore, long-term dynamic monitoring based on MODIS satellites (250m resolution, 1-day recurrence), AMSR2 microwave remote sensing satellites, and ERA5 meteorological data was used to analyze regional temporal variations in crop growth and long-term trends in irrigation water use.

[0068] During the data processing phase, advanced machine learning methods such as random forests (RF), support vector machines (SVM), and convolutional neural networks (CNN) are used to interpret remote sensing imagery to identify regional-scale land use types and major crop planting structures, accurately identifying the spatial distribution of different crop types. Classification accuracy is then verified using field survey data. Furthermore, by calculating vegetation indices such as NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index), crop coverage, growth potential, and irrigated area are extracted to further improve the accuracy of crop growth assessments.

[0069] 2) Field water utilization monitoring based on multi-source data fusion

[0070] UAV remote sensing technology is used to obtain high-resolution data for detailed monitoring of soil moisture, crop growth, and irrigation conditions at the field scale. The data sources mainly include multispectral and hyperspectral remote sensing images. By calculating vegetation indices such as NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index), the health status of crops, leaf area index (LAI), and biomass changes are accurately assessed. At the same time, thermal infrared images are used to extract land surface temperature (LST), and the energy balance method is combined to calculate the crop coefficient of major crops at the regional scale. In addition, visible light images are used to monitor the distribution of field irrigation, and combined with farmland management information, the efficiency of different irrigation methods and their impact on crop growth are evaluated.

[0071] In terms of data processing, high-resolution (centimeter-level) drone imagery is used to monitor key parameters such as soil moisture, crop water stress, and vegetation growth at the field scale, and ground sensor data is combined for calibration to improve data accuracy. For crop water consumption calculations, thermal infrared imagery plus the energy balance method are used to estimate evapotranspiration (ETc) at the field scale. Based on SEBAL (surface energy balance algorithm) or METRIC (modified SEBAL method), energy components such as net radiation, surface heat flux, and sensible heat flux are calculated to obtain evapotranspiration for different crop types and different growth stages. For irrigation water consumption calculations, the SM2RAIN algorithm is used to invert irrigation water consumption, and the irrigation pattern and irrigation water consumption are determined by the dynamic changes in soil moisture. Through this refined multi-source data fusion monitoring system, the spatiotemporal accuracy of crop water use monitoring can be improved, providing high-resolution, multi-temporal data support for the evaluation of irrigation water use coefficients, and providing a scientific basis for precise irrigation scheduling.

[0072] 3) Ground monitoring data

[0073] By comprehensively utilizing soil moisture monitoring, water supply and distribution data, and meteorological data, a dynamic monitoring system for the entire irrigation area water resources process is constructed to improve the accuracy of irrigation water utilization coefficient calculation and support precise irrigation scheduling.

[0074] Soil moisture monitoring: To monitor field soil moisture changes in real time, soil moisture sensors such as TDR (time domain reflectometry) and FDR (frequency domain reflectometry) are deployed at monitoring points across typical plots to obtain data on soil moisture content, soil temperature, and soil water potential at various depths. Sentinel-1 radar remote sensing data is also incorporated, combined with microwave inversion methods to estimate regional-scale soil moisture distribution. This improves the accuracy of large-scale soil moisture monitoring and compensates for the limited spatial coverage of traditional ground-based monitoring data. Furthermore, geostatistical methods are used to spatially interpolate sensor point data, optimizing the spatial distribution accuracy of soil moisture data and providing high-precision data support for irrigation management at both field and regional scales.

[0075] Water transmission and distribution monitoring: To comprehensively assess water volume changes and losses during irrigation district water transmission and distribution, historical water flow and irrigation volume statistics provided by irrigation district water resources management departments are collected, and water resource transmission and distribution characteristics under different years and climatic conditions are analyzed. At the same time, flow meters and water level gauges are deployed at key water transmission nodes (such as canal heads, main canals, branch canals, and field water inlets) to monitor water flow in the irrigation district in real time and calculate water transmission losses at different levels of canal systems. Combined with hydrodynamic models (such as MIKE HYDRO and SWAT), water losses and influencing factors along different water transmission routes are simulated to optimize water transmission scheduling and improve water resource utilization efficiency.

[0076] Meteorological data monitoring: Meteorological conditions directly affect crop evapotranspiration (ET), soil evaporation, precipitation infiltration, and irrigation demand. Therefore, this method uses real-time monitoring of key meteorological parameters such as temperature, precipitation, wind speed, humidity, and net radiation from ground-based meteorological stations. This is supplemented by global reanalysis data such as ERA5 and GLDAS to ensure the continuity and spatiotemporal integrity of meteorological data. By integrating ground-based data with satellite remote sensing data, the spatial applicability of meteorological data is improved, the accuracy of evapotranspiration (ET) estimation is optimized, and a scientific basis is provided for irrigation water use coefficient assessment and precise irrigation scheduling.

[0077] Simulation of the entire irrigation process

[0078] 1) Water distribution process simulation

[0079] Basic model construction and discretization: First, the irrigation area channel network is topologically transformed into a tree structure, and the calculation units are divided into two levels: main channel and field channel (branch channel + ditches + agricultural channels). Different lining materials need to consider parameters such as channel shape, initial water depth, flow velocity, and channel roughness. The channel roughness is assigned a value (0.012-0.035) based on the channel material classification (concrete / earth channel).

[0080] The unsteady flow Saint-Venant equations are used to accurately simulate the water flow, seepage loss, and irrigation water supply scheduling of the irrigation canal system. The specific control equations are shown below, which characterize the losses of different canal systems.

[0081]

[0082]

[0083] Among them, x is the displacement of water flow, t is time, Q is flow rate, A is the cross-sectional area of ​​water flow, h is water depth, g is gravity acceleration, S0 is bottom slope, S f The friction resistance makes the slope descend.

[0084] Gate control coupling and boundary processing: Use the gate as an internal boundary condition and establish the gate flow formula based on the energy equation

[0085]

[0086] Among them, C d is the discharge coefficient, b is the gate opening, and Δh is the upstream and downstream water level difference.

[0087] Basic Model Construction and Discretization: Based on the channel network topology (tree / mesh), the computational subdomains are divided using a domain decomposition method. A hybrid parallel architecture combining the Message Passing Interface (MPI) and the shared memory parallel programming model (Open Multi-Processing, OpenMP) achieves multi-level cross-node and intra-node parallelism. MPI synchronizes global boundary information between subdomains (e.g., gate-coupled node fluxes), while OpenMP accelerates intra-subdomain grid computations. A dynamic load balancing strategy (based on grid density and gate distribution weights) optimizes core task allocation, while asynchronous communication and delayed update techniques are employed to reduce communication overhead between non-adjacent subdomains. Furthermore, a global mass-momentum residual synchronization correction mechanism and local flux conservation enforcement (e.g., Harten-Lax-van Leer-Contact, HLLC Riemann solver) are introduced at each time step to ensure a synergistic improvement in physical conservation errors (total mass error <0.1%) and computational efficiency (speedup ≥ 85% linearity with 32 cores) during parallel computation.

[0088] Calculation of water utilization coefficient: Preissmann implicit difference method is used to discretize the equation, iteratively solve the spatiotemporal distribution of flow and water depth, calculate the leakage loss of each channel section, and use it to compare the water utilization efficiency of different water delivery methods (such as open channel, pipeline water delivery, channel anti-seepage, etc.). Calculate the key water parameters in the water delivery process. In the simulated irrigation area water delivery process, calculate the water diversion volume W at the head of the channel. in , Main canal water loss W losss , branch canal water loss W lossd :

[0089] W losss =W in -W 干渠

[0090] W lossd =W 干渠 -W 田间

[0091] Calculation of water transfer utilization coefficient The water transfer utilization coefficient reflects the effective utilization of water in the water transfer process and can be defined as follows: The main canal water transfer utilization coefficient (η s ), water distribution utilization coefficient (η d ):

[0092]

[0093] 2) Field water utilization simulation

[0094] Model selection: In order to accurately calculate the water demand of crops and field water use, the crop evapotranspiration estimation model is used to estimate crop evapotranspiration (ET c), its mathematical expression is:

[0095] ET c =K c ×ET0

[0096] Among them: K c = is the crop coefficient, which represents the evapotranspiration capacity of crops at different growth stages. This coefficient can be inverted and calculated based on drone hyperspectral remote sensing data (vegetation indices such as NDVI and EVI). ET0 is the net radiation and soil heat flux calculated based on remote sensing data. Temperature, wind speed, saturated vapor pressure, actual vapor pressure, and dry-wet ratio are calculated using meteorological data according to the following formula:

[0097]

[0098] Where: R n is the net radiation (MJ / m 2 / day); G is soil heat flux (MJ / m 2 / day); T is the air temperature (℃); u2 is the wind speed at 2m (m / s); e s and e a are the saturated water vapor pressure and actual water vapor pressure (kPa), respectively; γ is the dry-wet ratio (kPa / ℃); Δ is the slope of the saturated water vapor pressure curve (kPa / ℃)

[0099] The SM2RAIN algorithm uses soil moisture changes as input data and calibrates it with ERA5 precipitation data to derive irrigation water use. The formula is as follows:

[0100]

[0101] Where: S(t) is the soil moisture at the current moment, S(t-1) is the soil moisture at the previous moment, Δt is the time interval, and k is the comprehensive coefficient, which represents the combined effect of crop evapotranspiration and deep infiltration.

[0102] Calculate the field water utilization coefficient η based on irrigation water consumption and field water supply f The field water utilization coefficient is used to measure the effective utilization of field water. The calculation formula is as follows:

[0103]

[0104] Where: P: irrigation water consumption, representing the actual use of irrigation water by crops; W 田间 : Field water supply, including irrigation water entering the field from branch canals and effective precipitation

[0105] (3) Model coupling and verification

[0106] Model coupling: The water output W calculated at the canal head is干渠 As the initial water diversion volume of the main canal, the calculated water output of the main canal is used as the field water diversion volume W 田间 , field module feedback crop evapotranspiration (ET c ) to the index layer and calculate the water utilization coefficient.

[0107] Model Validation: ① Canal model validation. Comparing simulated canal flow with measured flow and correcting canal water loss parameters. ② Field model validation. Soil moisture validation. Comparing simulated values ​​with TDR sensor measurements. ET validation. Comparing ET with eddy covariance (EC) measurements and correcting the corresponding model to within 5% of the deviation.

[0108] (4) Calculation of irrigation water utilization coefficient

[0109] The calculation results of water transmission, water distribution and field water use are integrated to finally calculate IWUE:

[0110] IWUE=η s ×η d ×η f

[0111] Among them, the water utilization coefficient (η s ): Water delivery efficiency from the canal head to the main canal of the irrigation area.

[0112] Water utilization coefficient (η d ): Water delivery efficiency from main canals to fields.

[0113] Field water utilization coefficient (η f ):Efficiency of crops in utilizing available water in the field.

[0114] A specific embodiment is introduced below to further illustrate the method of the present invention.

[0115] Case: Taking a certain irrigation district as an example, with an area of ​​100,000 mu, the irrigation water utilization coefficient of this irrigation district is determined.

[0116] Canal system modeling and water distribution process simulation

[0117] This example first digitally models the irrigation district's water channel system based on geographic information data such as remote sensing images, basic topographic maps, and engineering design drawings. Using a GIS platform, the canal network structure was topologically transformed into a tree-like network, and hydraulic units were divided into two levels: main canals and field channels (including branch canals, ditches, and agricultural channels). The main canals were concrete-lined channels with a roughness ratio of 0.012, according to the standard design value. The field channels were unlined earthen channels with a roughness ratio of 0.035, and spatial correction was performed to account for differences in soil permeability.

[0118] On this basis, a non-steady flow simulation model was constructed, using the Saint-Venant equations to solve the hydraulic processes at all levels of the irrigation canal. The simulation included: fluctuations in water diversion at the headwaters; the evolution and hysteresis of water volume during canal water delivery; seepage losses such as lateral seepage and deep seepage; and the allocation and control of irrigation scheduling. After running the model and calibrating and correcting it with historical irrigation data, the following results were obtained:

[0119] After running the model and calibrating and correcting the historical irrigation data, we can obtain the following: s ) is 0.95; the field channel water utilization coefficient (η d ) is 0.85.

[0120] The above coefficients reflect the water utilization efficiency of the canal system under existing conditions. The water loss in the main canal is relatively small, while there is still significant leakage and ineffective loss in the field canal.

[0121] Crop water demand simulation and field water utilization coefficient calculation

[0122] For the main irrigated crops (such as wheat and corn) in this example, the crop evapotranspiration simulation method proposed in this invention is used to integrate the vegetation indices (NDVI, EVI) and crop coverage obtained by drone remote sensing to dynamically estimate the evapotranspiration (ETc) of crops at different growth stages. The crop coefficient (Kc) used in different stages is set as follows: Kc is selected as 0.20 in the initial growth period, 0.45 in the rapid development period, and 0.30 in the maturity period. According to the formula, the field water utilization coefficient (η f ) is 0.85.

[0123] Model Validation

[0124] To ensure the scientificity and usability of the above-mentioned whole-process simulation results, the present invention implements the following two-level verification mechanism:

[0125] (1) Channel system model verification

[0126] By setting up flow meters on site, we obtain measured flow data for the main canal and typical branch canal sections; perform error analysis between the simulated flow and the measured data; and correct the channel leakage rate parameters until the model output flow error is controlled within 5%.

[0127] (2) Field model verification

[0128] Soil moisture verification: An array of TDR sensors was deployed in a typical crop field to record soil moisture dynamics at different depths in real time and compare them with the model's simulated output. For evapotranspiration verification, an eddy covariance (EC) system was deployed to obtain actual crop ET values. The deviations between the model results and the calculated ET were analyzed on daily and weekly scales. The results showed that the average deviation between the model-calculated ET and the measured ET was 4.5%, meeting the accuracy requirements for engineering applications.

[0129] Therefore, the final calculated IWUE was 0.686 based on the calculation results of water transmission, water distribution and field water use processes.

[0130] An irrigation water utilization coefficient evaluation system based on the simulation of the entire irrigation area water use process includes:

[0131] Data collection module, which obtains irrigation water utilization information through multi-source data fusion;

[0132] A model building module, based on irrigation water utilization information, constructs a simulation model of the entire irrigation area water use process; the simulation model of the entire irrigation area water use process includes main canal water simulation, field canal water simulation and field crop water simulation;

[0133] The coefficient calculation module uses the whole process simulation model of irrigation area water use to calculate the water transmission utilization coefficient, water distribution utilization coefficient and field water utilization coefficient;

[0134] The result output module multiplies the obtained water transmission utilization coefficient, water distribution utilization coefficient and field water utilization coefficient to obtain the irrigation water utilization coefficient.

[0135] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0136] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating irrigation water utilization coefficient based on simulation of the entire water use process in an irrigation area, characterized in that: include: Obtain irrigation water utilization information through multi-source data fusion; Based on irrigation water utilization information, a simulation model of the entire irrigation area water use process is constructed; The whole process simulation model of irrigation area water use includes main canal water simulation, field canal water simulation and field crop water simulation; The water utilization coefficient of the entire irrigation area is calculated using the simulation model of the entire irrigation area water use process; The irrigation water utilization coefficient is obtained by multiplying the obtained water delivery utilization coefficient, water distribution utilization coefficient and field water utilization coefficient.

2. The irrigation water utilization coefficient evaluation method based on the whole process simulation of irrigation area water use according to claim 1 is characterized in that: The process of the main canal water simulation and the field canal water simulation is the same, specifically: Basic model construction and discretization: First, the irrigation channel network is topologically transformed into a tree structure, and the calculation units are divided into two levels: main channel and field channel. Different lining materials need to consider channel shape, initial water depth, flow velocity, and channel roughness parameters. The channel roughness is assigned based on the channel material classification. The unsteady flow Saint-Venant equations are used to simulate water flow, seepage loss and irrigation water supply scheduling in irrigation canal systems. Gate control coupling and boundary processing: The gate is used as the internal boundary condition and the gate flow formula is established based on the energy equation; Calculation of water transmission and distribution utilization coefficient: Using the Preissmann implicit difference method to discretize the equation, the temporal and spatial distribution of flow and water depth is iteratively solved, and the seepage loss of each canal section is calculated to compare the water utilization efficiency of different water transmission methods; the key water volume parameters in the water transmission process are calculated in the simulated irrigation area water transmission process, and the water diversion volume of the canal head, the water transmission loss of the main canal, and the water transmission loss of the branch canal are calculated; Based on the obtained headwater diversion volume, main canal water transmission loss, and branch canal water transmission loss, the main canal water transmission utilization coefficient and distribution water utilization coefficient are calculated.

3. The irrigation water utilization coefficient evaluation method based on the whole process simulation of irrigation area water use according to claim 1 is characterized in that: The Saint-Venant equations for unsteady flow are specifically: Among them, x is the displacement of water flow, t is time, Q is flow rate, A is the cross-sectional area of ​​water flow, h is water depth, g is gravity acceleration, S0 is bottom slope, S f The friction resistance makes the slope descend.

4. The irrigation water utilization coefficient evaluation method based on the whole process simulation of irrigation area water use according to claim 3 is characterized in that: The gate flow formula is as follows: Among them, C d is the discharge coefficient, b is the gate opening, and Δh is the upstream and downstream water level difference.

5. The irrigation water utilization coefficient evaluation method based on the whole process simulation of irrigation area water use according to claim 2 is characterized in that: Based on the obtained headwater diversion, main canal water loss, and branch canal water loss, calculate the main canal water utilization coefficient η s and water utilization coefficient η d Specifically: Among them, W in is the water diversion volume at the head of the canal, W losss is the water loss of the main canal, W lossd is the water loss of the branch canal, W losss =W in -W 干渠 , W lossd =W 干渠 -W 田间 .

6. The irrigation water utilization coefficient evaluation method based on the whole process simulation of irrigation area water use according to claim 1 is characterized in that: The field crop water simulation is specifically as follows: Model selection: Use crop evapotranspiration estimation model to estimate crop evapotranspiration ET c ; Using soil moisture changes and crop evapotranspiration as input data, combined with ERA5 precipitation data, the irrigation water consumption was calibrated. Calculate the field water utilization coefficient η based on irrigation water consumption and field water supply f .

7. The irrigation water utilization coefficient evaluation method based on the whole process simulation of irrigation area water use according to claim 6 is characterized in that: Crop evapotranspiration (ET) c The mathematical expression is: AND c =K c ×ET0 Among them: K c is the crop coefficient, which indicates the evapotranspiration capacity of crops at different growth stages; ET0 is the net radiation and soil heat flux; it is calculated according to the following formula: Where: R n is the net radiation; G is the soil heat flux; T is the air temperature; u2 is the wind speed at 2m; e s and e a are the saturated water vapor pressure and actual water vapor pressure respectively; γ is the dry-wet ratio; Δ is the slope of the saturated water vapor pressure curve.

8. The irrigation water utilization coefficient evaluation method based on the whole process simulation of irrigation area water use according to claim 6 is characterized in that: Calculate the field water utilization coefficient η f The formula is: Where: P is the amount of irrigation water, representing the actual use of irrigation water by crops; W 田间 The water supply to the fields includes the irrigation water entering the fields from branch canals and effective precipitation.

9. An irrigation water utilization coefficient evaluation system based on the simulation of the entire water use process in the irrigation area, characterized in that: The method for evaluating the irrigation water utilization coefficient based on the whole process simulation of irrigation area water use according to any one of claims 1 to 8 comprises: Data collection module, which obtains irrigation water utilization information through multi-source data fusion; A model building module, based on irrigation water utilization information, constructs a simulation model of the entire irrigation area water use process; the simulation model of the entire irrigation area water use process includes main canal water simulation, field canal water simulation and field crop water simulation; The coefficient calculation module uses the whole process simulation model of irrigation area water use to calculate the water transmission utilization coefficient, water distribution utilization coefficient and field water utilization coefficient; The result output module multiplies the obtained water transmission utilization coefficient, water distribution utilization coefficient and field water utilization coefficient to obtain the irrigation water utilization coefficient.

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