A method and system for evaluating spatiotemporal decoupling of carbon emissions and grain yield in farmland irrigation

Abstract

The application provides a farmland irrigation carbon emission and grain yield space-time decoupling evaluation method and system, and belongs to the technical field of agricultural resource evaluation, which comprises the following steps: obtaining water resource data, energy consumption data, grain production data and agricultural irrigation data of a target farmland area; calculating the energy consumption of the surface water taking link, the underground water taking link and the water using link of the target farmland area based on the water resource data, the energy consumption data and the agricultural irrigation data; calculating the carbon emission per unit hectare of farmland irrigation based on the three kinds of energy consumption; calculating the Tapio decoupling index based on the carbon emission per unit hectare of farmland irrigation and the grain production data; analyzing the decoupling state of carbon emission and grain yield based on the Tapio decoupling index; and obtaining the decoupling evaluation result of farmland irrigation carbon emission and grain yield. The application eliminates the calculation deviation caused by index distortion from the source, accurately quantifies the real level of carbon-grain decoupling, and can output reliable carbon-grain decoupling evaluation results.

Description

Technical Field

[0001] This invention belongs to the field of agricultural resource assessment technology, specifically relating to a spatiotemporal decoupling assessment method and system for farmland irrigation carbon emissions and grain yield. Background Technology

[0002] With the introduction of my country's "dual carbon" goals and the implementation of the strictest water resource management system, farmland irrigation, as a major link in agricultural water use, is a core means of ensuring increased grain production. Water conservation, energy consumption control, and carbon emission reduction in farmland irrigation have become important directions for sustainable agricultural development. Each stage of farmland irrigation generates carbon emissions, naturally creating a synergistic relationship between increased grain production and carbon emissions. Therefore, a spatiotemporal decoupling assessment of farmland irrigation carbon emissions and grain yield can quantitatively evaluate the degree of decoupling between these two factors, quantify the synergistic effects of water conservation and grain protection and carbon emission reduction in different regions, identify gaps and shortcomings in low-carbon agricultural development in different areas, and formulate differentiated irrigation emission reduction and yield-increasing plans accordingly. This provides scientific and quantitative support for coordinating food security, agricultural water conservation, and the "dual carbon" goals in agriculture.

[0003] Existing research on the carbon-grain relationship in farmland irrigation is fragmented and one-sided. Carbon emission calculations are often limited to single aspects such as groundwater extraction and pressurized water-saving irrigation. These calculations combine the planted area of ​​grain to calculate carbon emissions per unit area of ​​irrigation, then match this with the grain yield per unit area in the corresponding year to perform a spatiotemporal decoupling analysis of farmland irrigation carbon emissions and grain yield. This method yields distorted carbon emission indicators per unit area, leading to systematic biases in subsequent calculations of temporal and spatial decoupling indices. The assessment of the degree of carbon-grain decoupling is inaccurate, failing to meet the timeliness and practical needs of refined agricultural irrigation management and differentiated emission reduction. Summary of the Invention

[0004] To address the issue that decoupling analysis, limited to a single dimension, fails to meet the timeliness and practical needs of refined agricultural irrigation management and differentiated emission reduction, this invention provides a spatiotemporal decoupling assessment method for farmland irrigation carbon emissions and grain yield. Specifically, it is a comprehensive method that integrates water resource data, energy consumption data, grain production data, and agricultural irrigation data to conduct precise calculations of carbon emissions across the entire irrigation chain at the provincial level, while simultaneously achieving decoupling analysis of the carbon-grain relationship across time and spatial dimensions, as well as differentiated assessments and recommendations for different regions. Specifically, it evaluates the spatiotemporal correlation between farmland irrigation carbon emissions and grain yield across the entire chain, achieving a comprehensive assessment of provincial-level farmland irrigation carbon emission calculations and water-carbon-grain relationship decoupling.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A method for spatiotemporally decoupled assessment of farmland irrigation carbon emissions and grain yield includes the following steps: Acquire water resource data, energy consumption data, grain production data, and agricultural irrigation data for the target farmland area; Based on water resource data, energy consumption data, and agricultural irrigation data, the energy consumption of surface water intake, groundwater intake, and water use in the target farmland area is calculated. Based on the energy consumption of surface water intake, groundwater intake, and water use, the carbon emissions per hectare of farmland irrigation are calculated. The Tapio decoupling index is calculated based on carbon emissions per hectare of farmland irrigation and grain production data. The decoupling status of carbon emissions and grain yield is analyzed based on the Tapio decoupling index, and the decoupling assessment results of farmland irrigation carbon emissions and grain yield are obtained.

[0006] Preferably, the decoupling state includes temporal decoupling and spatial decoupling; the temporal decoupling involves performing longitudinal time-series analysis on data from the same region over many years to quantitatively assess whether the increase in grain production and the increase in irrigation carbon emissions have been decoupled during the region's own changes over time; the spatial decoupling uses the national average level as a reference to horizontally compare the relative advantages and disadvantages of unit irrigation carbon emissions and grain production in different provinces in the same year.

[0007] Preferably, the energy consumption in the surface water intake process includes the electricity consumption for surface water pumping and the diesel consumption for surface water pumping; the electricity consumption for surface water pumping is calculated based on the surface water irrigation water consumption, pump head, pump efficiency, energy type ratio, and the carbon emission coefficients of electricity and diesel. Diesel consumption for surface water extraction ; The energy consumption of the groundwater extraction process includes the electricity consumption and diesel consumption for groundwater extraction. The electricity consumption for groundwater extraction is calculated based on groundwater irrigation water consumption, pump head, pump efficiency, energy type ratio, and the carbon emission coefficients of electricity and diesel. Diesel consumption for groundwater extraction .

[0008] Preferably, the energy consumption in the water use process includes electricity consumption and diesel consumption in the irrigation water use process. The electricity consumption in the irrigation water use process is calculated based on the flood irrigation area, energy intensity per unit area, energy type ratio, and carbon emission coefficient. Diesel consumption in irrigation water .

[0009] Preferably, the calculation of carbon emissions per hectare of farmland irrigation based on the energy consumption of surface water intake, groundwater intake, and water use specifically includes the following steps: based on , and The carbon emissions generated during electricity consumption are calculated using the following formula: ; In the formula, Indicates the first Province Carbon emissions generated during annual electricity consumption For the first Annual power grid carbon emission factor; based on , and The carbon emissions from diesel consumption are calculated using the following formula: ; In the formula, Indicates the first Province Carbon emissions generated during annual diesel consumption Carbon emission factors for diesel fuel; right and Summing up yields the total carbon emissions from farmland irrigation. The calculation formula is: ; based on Calculation of carbon emissions from farmland irrigation, with the unit of grain sown area being hectares. The calculation formula is: ; In the formula, For the first Year The province's grain planting area.

[0010] Preferably, the formula for calculating the Tapio decoupling index is: ; In the formula, The Tapio decoupling index. , These represent the carbon emissions per hectare of farmland irrigation in year t and year b, respectively. , These represent the grain yield per hectare in year t and year b, respectively. , These represent the changes in carbon emissions from irrigation per unit hectare of farmland and grain yield, respectively, between year t and year b.

[0011] Preferably, it also includes: grouping and statistically analyzing the decoupling state types of each province at different times according to the north-south region and the main grain-producing area and non-main grain-producing area; comparing the differences and trends in the distribution of decoupling states within each group to obtain the long-term dynamic relationship characteristics between farmland irrigation carbon emissions and grain yield, including time series decoupling characteristics and regional decoupling difference characteristics. Based on the total carbon emissions from farmland irrigation, time-series decoupling characteristics, and regional decoupling differences, combined with the resource endowment data of each province, the actual development of agricultural irrigation, and the positioning of grain production, differentiated strategies for coordinated development of farmland irrigation water conservation and emission reduction with grain production are formulated.

[0012] This invention also proposes a spatiotemporally decoupled assessment system for farmland irrigation carbon emissions and grain yield, comprising: The data acquisition module is used to acquire water resource data, energy consumption data, grain production data, and agricultural irrigation data for the target farmland area. The carbon emission calculation module is used to calculate the energy consumption of surface water intake, groundwater intake, and water use in a target farmland area based on water resource data, energy consumption data, and agricultural irrigation data, and to calculate the carbon emission per hectare of farmland irrigation based on the energy consumption of surface water intake, groundwater intake, and water use. The decoupling assessment module is used to calculate the Tapio decoupling index based on carbon emissions per hectare of farmland irrigation and grain production data. Based on the Tapio decoupling index, the decoupling status of carbon emissions and grain yield is analyzed to obtain the decoupling assessment results of farmland irrigation carbon emissions and grain yield.

[0013] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the steps in the spatiotemporal decoupling assessment method for farmland irrigation carbon emissions and grain yield.

[0014] The present invention also provides a computer-readable storage medium storing a computer program that, when loaded by a processor, can execute any of the steps in the method for spatiotemporal decoupling assessment of farmland irrigation carbon emissions and grain yield.

[0015] The spatiotemporal decoupling assessment method for farmland irrigation carbon emissions and grain yield provided by this invention has the following beneficial effects: This invention calculates the energy consumption of the entire process, including surface water intake, groundwater intake, and water use, in the target farmland area. Based on the energy consumption of the entire irrigation process, it converts the total carbon emissions into total emissions, moving beyond the limitation to carbon emissions from a single irrigation stage. By combining the grain planting area, it obtains accurate and complete carbon emissions per hectare of irrigation, eliminating calculation biases caused by distorted indicators at the source. It accurately quantifies the true level of carbon-grain decoupling and outputs reliable carbon-grain decoupling assessment results, supporting the implementation of refined management of agricultural irrigation and regionally differentiated emission reduction strategies. Attached Figure Description

[0016] To more clearly illustrate the embodiments and design schemes of the present invention, the accompanying drawings required for this embodiment will be briefly described below. The drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of the spatiotemporal decoupling assessment method for farmland irrigation carbon emissions and grain yield according to Embodiment 1 of the present invention. Detailed Implementation

[0018] To enable those skilled in the art to better understand and implement the technical solutions of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and should not be construed as limiting the scope of protection of the present invention.

[0019] This invention addresses the shortcomings of existing agricultural irrigation and food production assessment technologies, such as their reliance on a single carbon emission measurement step, lack of decoupling analysis dimensions, insufficient consideration of regional differences, and weak guidance of assessment results. It provides an evaluation method capable of calculating carbon emissions across the entire agricultural irrigation chain, rapidly performing spatiotemporal decoupling analysis of the carbon-food relationship, and assessing the level of coordinated development in different regions. This facilitates accurate assessment of the carbon-food relationship in agricultural irrigation at the provincial level, across the entire chain, and in two dimensions, while also enabling differentiated identification of the level of coordinated development between irrigation carbon reduction and food production in different regions. The assessment method proposed in this invention can meet the needs of varying resource endowments and actual food production conditions in different regions of my country, enabling rapid, accurate, and comprehensive spatiotemporal decoupling assessment of the carbon-food relationship in agricultural irrigation.

[0020] Example 1 This invention provides a spatiotemporal decoupling assessment method for farmland irrigation carbon emissions and grain yield, specifically as follows: Figure 1 As shown, it includes the following steps: Step 1: Obtain multi-source data for the target farmland area, including water resource data, energy consumption data, food production data, and agricultural irrigation data. Water resource data includes surface water withdrawals. and groundwater extraction wait.

[0021] Step 2: Calculate the energy consumption of irrigation water intake and water use based on multi-source data, and summarize the carbon emissions of the entire farmland irrigation chain.

[0022] First, using water resource data, energy consumption data, and agricultural irrigation data, refined energy consumption calculations are conducted for both water intake and water use. For water intake, surface water and groundwater sources are differentiated, and electricity and diesel are further distinguished. For water use, water-saving irrigation (sprinkler irrigation, drip irrigation, etc.) and traditional flood irrigation are differentiated, and the energy structure of electricity and diesel is also differentiated. Through these distinctions, precise quantification of carbon emissions across the entire agricultural irrigation chain at the provincial level is achieved.

[0023] Based on this, the energy consumption calculation targets include four categories of energy consumption-related data: energy consumption in surface water intake, energy consumption in groundwater intake, energy consumption in water-saving irrigation, and energy consumption in traditional irrigation.

[0024] Specifically, the calculation methods for each energy consumption level are as follows: (0) Calculation of surface water intake energy consumption: Based on the surface water irrigation water consumption (i.e., surface water intake), pump head, pump efficiency, and energy type ratio, combined with the carbon emission coefficients of electricity and diesel, the energy consumption of the surface water intake process is calculated. The energy consumption of the surface water intake process includes the electricity consumption for surface water intake and the diesel consumption for surface water intake.

[0025] Surface water energy consumption is characterized by low head and low energy consumption. The difference in the proportion of surface water in different provinces directly affects the energy consumption level in the water intake process. Combined with provincial-level surface water irrigation data, it is easy to calculate accurately.

[0026] Energy consumption in the water intake process mainly stems from the energy required to lift water from the source. For surface water intake, the energy consumption for electric and diesel-powered operations is calculated using the following formulas:

[0027] The formula for calculating the electricity consumption for surface water extraction (i.e., the energy consumption of electric drive) is as follows: ; In the formula, Indicates the first Year Electricity consumption for surface water extraction in the province, in kWh; This represents the density of water, with a value of 1 × 10³ kg / m³. It is the acceleration due to gravity, with a value of 9.8 m / s². Indicates the first Year Provincial surface water lifting head, in meters; This indicates the efficiency of the water intake pump, with a value of 0.75. Indicates the first Year Provincial surface water intake, in m3; Indicates the first Year The proportion of electricity consumption in the energy consumption of surface water extraction in the province.

[0028] The formula for calculating diesel consumption for surface water extraction (i.e., diesel-powered energy consumption) is as follows: ; In the formula, Indicates the first Year Diesel consumption for surface water extraction in the province, in J; This is the calorific value of diesel fuel, taken as 3.53 × 10⁻⁶. 7J / L ; This indicates the efficiency of the diesel pump used for water intake, with a value of 0.4. Indicates the first Year The proportion of diesel consumption in the energy consumption of surface water extraction in the province.

[0029] (2) Calculation of energy consumption for groundwater extraction: The groundwater level is not less than a certain value, and the pumping head is significantly higher than that of surface water, which affects energy consumption and energy consumption level. Based on the groundwater irrigation water consumption, pumping head, pump efficiency, and energy type ratio, combined with the carbon emission coefficients of electricity and diesel, the energy consumption of groundwater extraction is calculated, which is the main source of energy consumption in farmland irrigation water extraction.

[0030] When extracting groundwater, the energy consumption for electric and diesel-powered extraction is as follows: The formula for calculating the electricity consumption (i.e., the energy consumption of electric drive) for groundwater extraction is as follows: ; In the formula, Indicates the first Year Electricity consumption for groundwater extraction in the province, in kWh; Indicates the first Year Provincial groundwater lifting head, in meters; Indicates the first Year Provincial groundwater extraction volume, in m3; Indicates the first Year The proportion of electricity consumption in the energy consumption of groundwater extraction in the province.

[0031] The formula for calculating diesel consumption for groundwater extraction (i.e., diesel-powered energy consumption) is as follows: ; In the formula, Indicates the first Year Diesel consumption for groundwater extraction in the province, in J; Indicates the first Year The proportion of diesel consumption in the energy consumption of groundwater extraction in the province.

[0032] (3) Energy consumption calculation in water use: Energy consumption in water use mainly comes from irrigation pressurization, including energy consumption in water-saving irrigation and traditional irrigation. Water-saving irrigation requires pressurized water delivery, while traditional flood irrigation can achieve near-zero energy consumption in plain areas.

[0033] The formula for calculating the electricity consumption (i.e., the energy consumption of electric drive) in the irrigation water process is as follows: ; In the formula, Indicates the first Year Electricity consumption in the province's irrigation water use process, in kWh; Indicates the first Year Provincial water-saving irrigation area, unit: hm² 2 ; Indicates the first Year Energy consumption per unit area for water-saving irrigation in the province, in kWh / hm 2 ; Indicates the first Year The proportion of electricity in the energy consumption of the water-saving irrigation pressurization process in the province; Indicates the first Year Provincial (flood irrigation) irrigated area, unit: hm² 2 ; Indicates the first Year Energy consumption per unit area for provincial flood irrigation, unit: kWh / hm 2 ; Indicates the first Year The proportion of electricity in the energy consumption of the provincial flood irrigation pressurization process.

[0034] The formula for calculating diesel consumption (diesel-powered energy consumption) in irrigation water use is as follows: ; In the formula, Indicates the first Year Diesel consumption in the province's irrigation water usage process, in J; Indicates the first Year The proportion of diesel fuel in the energy consumption of water-saving irrigation pressurization processes in the province; Indicates the first Year The proportion of electricity in the energy consumption of the provincial flood irrigation pressurization process.

[0035] (4) Carbon emission conversion and summarization: Using electricity and diesel energy consumption in water intake and water use as input items, the carbon emission coefficients of electricity and diesel are matched and converted into carbon emission amounts, with the unit being kgCO2. The carbon emissions in water intake and water use are superimposed to obtain the total carbon emissions of farmland irrigation at the provincial scale, and the carbon emissions per hectare of farmland irrigation are calculated simultaneously to complete the full-process data production of the carbon emission measurement unit.

[0036] After obtaining the energy consumption at each stage, the electricity and diesel energy consumption are multiplied by their respective carbon emission factors to obtain the carbon emissions: ① Carbon emissions during electricity consumption: ; In the formula, Indicates the first Province Carbon emissions (kgCO2) generated during annual electricity consumption. For the first Annual grid carbon emission factor (kgCO2 / kWh).

[0037] ② Carbon emissions during diesel consumption: ; In the formula, Indicates the first Province Carbon emissions (kgCO2) generated from annual diesel consumption. The carbon emission factor for diesel fuel (kgCO2 / L).

[0038] ③ Add the carbon emissions generated by the electricity consumption process to the carbon emissions generated by the diesel consumption process to obtain the total carbon emissions from farmland irrigation.

[0039] ; ④ Carbon emissions per hectare of farmland irrigation : ; In the formula, For the first Year The province's grain sown area (hm²).

[0040] Based on the carbon emission calculation results of the above water intake and water use links, the total carbon emission of farmland irrigation is finally obtained, and the carbon emission per hectare of farmland irrigation is calculated simultaneously, which serves as the core basic indicator for subsequent time decoupling and spatial decoupling analysis.

[0041] Step 3: Based on the carbon emissions per hectare of farmland irrigation obtained in Step 2 and the grain production data (specifically, grain yield per hectare) obtained from the statistical data in Step 1, calculate the decoupling index and determine the state of the time series. This includes three steps: calculating the Tapio decoupling index, determining the spatiotemporal decoupling state, and analyzing the decoupling characteristics of the time series. Temporal decoupling involves longitudinal time-series analysis of data from the same region over many years to quantitatively assess whether the increase in grain production and the increase in irrigation carbon emissions have become decoupled over time. Spatial decoupling uses the national average level as a reference to horizontally compare the relative advantages and disadvantages of carbon emissions per unit of irrigation and grain yield in different provinces in the same year.

[0042] Specifically, the Tapio decoupling index is calculated as follows: based on the carbon emissions per unit hectare of farmland irrigation and the grain yield per unit hectare in the time series, the Tapio decoupling index for different time periods is calculated. The core calculation formula is: ; In the formula, The Tapio decoupling index. , These represent the carbon emissions per hectare of farmland irrigation in year t and year b, respectively. , These represent the grain yield per hectare in year t and year b, respectively. , These represent the changes in carbon emissions from irrigation per unit hectare of farmland and grain yield, respectively, between years t and b. Wherein, grain yield per unit hectare... PF Carbon emissions per hectare of farmland irrigation are obtained by dividing total grain output by the sown area of ​​grain. PC Δ is obtained by dividing the total carbon emissions from farmland irrigation by the grain sown area. PF and Δ PC That is, between different years PF and PC The difference. Tapio decoupling index. Composed of the ratio of the relative change rates between the two periods, it serves as the quantitative basis for determining the subsequent state and directly determines the decoupling type.

[0043] Time decoupling state determination: based on Tapio decoupling index The numerical range and , The positive and negative directions are used to determine different time-dependent decoupling states. Here, the positive and negative directions refer to the change in carbon emissions per hectare, Δ. PCᵗ and the change in grain yield per unit hectare Δ PFᵗ These are either positive (increase) or negative (decrease).

[0044] Spatial decoupling states include seven types, such as strong spatial decoupling, weak spatial decoupling, and strong negative spatial decoupling. The decision logic is the same as for temporal decoupling: when Δ PC <0 and Δ PF When >0, Dᵢ ≤ 0, indicating strong spatial decoupling (ideal); when Δ PC >0 and Δ PF When <0, Dᵢ ≤ 0 indicates strong negative spatial decoupling (extremely undesirable); other states are determined according to the exponent range and positive / negative combinations, following the aforementioned rules. Strong spatial decoupling means that the assessment area has lower carbon emissions and higher grain yields compared to the reference area, indicating a better level of carbon-grain coordinated development; strong negative spatial decoupling is the opposite.

[0045] ; In the formula, i is the evaluation area and j is the reference area; and These represent the carbon emissions per hectare of farmland irrigation in regions i and j, respectively. and These represent the grain yield per hectare in cities i and j, respectively. and These represent the changes in carbon emissions per unit hectare of farmland irrigation and the changes in grain yield per unit hectare, respectively, for regions i and j.

[0046] Based on the most widely used Tapio elastic decoupling index, the spatiotemporal decoupling state is defined (see Table 1).

[0047] Table 1. Spatiotemporal decoupling state results Strong (spatial) decoupling (SSD) The most ideal Weak Negative (Spatial) Decoupling (WNSD) Not ideal Decaying Spatial Coupling (RSC) Not ideal Decaying (Spatial) Decoupling (RSD) Extremely unsatisfactory Strong Negative (Spatial) Decoupling (SNSD) Extremely unsatisfactory Weak (spatial) decoupling (WSD) More ideal Extended Spatial Coupling (ESC) General Ideal #imgpt188# #imgpt189# #imgpt190# #imgpt191# Extended Negative (Space) Decoupling (ENSD) Not ideal As shown in the table above, based on the time-series decoupling status of each province and region, we further explored the evolution patterns over time. The specific analysis method is as follows: First, we statistically analyzed the types of decoupling status for each province at different times; second, we grouped the data by north-south region and major grain-producing areas versus non-major grain-producing areas, comparing the differences and trends in the distribution of decoupling status within each group. This allowed us to summarize the long-term dynamic relationship characteristics between farmland irrigation carbon emissions and grain yield. These long-term dynamic relationship characteristics include time-series decoupling characteristics and regional decoupling difference characteristics, providing time-dimensional support for subsequent regional assessment and decision-making. (Table explanation follows.)

[0048] Step 4: Based on the total carbon emissions from farmland irrigation, time-series decoupling characteristics, and regional decoupling differences, combined with the resource endowment data of each province, the actual development of agricultural irrigation, and the positioning of grain production, conduct regional differentiated assessments and decision-making. This includes three steps: integration of spatiotemporal decoupling characteristics, classification of regional types, and formulation of differentiated strategies.

[0049] Spatiotemporal decoupling feature fusion: This method integrates the temporal and spatial decoupling features of each province to summarize the comprehensive spatiotemporal decoupling characteristics of the carbon-grain relationship in each province. This includes the evolution trend of decoupling in the temporal dimension and the relative level of decoupling in the spatial dimension. Temporal decoupling features refer to the decoupling status and evolution trend of time series, while spatial decoupling features refer to the spatial decoupling status and relative level between provinces.

[0050] Regional Classification: Based on the aforementioned temporal and spatial decoupling characteristics, multiple provinces and municipalities across the country are classified into different development types, including: **Temporally and Spatially Excellent (strong temporal and spatial decoupling), **Temporally Excellent but Spatially Weak (ideal temporal decoupling but lower than the reference level), **Spatially Excellent but Temporally Weak (high spatial decoupling but unfavorable temporal evolution trend), and **Temporally and Spatially Weak (both temporally and spatially decoupling are unsatisfactory).** Furthermore, by combining the classification of major grain-producing areas with non-major grain-producing areas, and north-south regions, the regional types are further refined, clarifying the development positioning and core issues of different types of regions.

[0051] Differentiated Strategy Formulation: Targeting the spatiotemporal decoupling characteristics, resource endowments, and core issues of different regional types, differentiated strategies for coordinated development of farmland irrigation water conservation and emission reduction with grain production are formulated. For example, for provinces with "superior spatiotemporal advantages," the strategy focuses on consolidating advantages and promoting best practices; for provinces with "superior time but weak space," the focus is on benchmarking against advanced regions with high levels of spatial decoupling, optimizing energy structures, or promoting more efficient irrigation technologies; for provinces with "superior space but weak time," the focus is on strengthening continuous improvement in the time dimension to prevent carbon emission rebound; for provinces with "weak spatiotemporal advantages," comprehensive measures are needed, prioritizing the improvement of irrigation water utilization efficiency and adjusting grain production layout. Finally, data from administrative regions and grain-producing areas are overlaid to complete the formulation of regional and type-specific decision-making schemes. Specific strategy formulation revolves around core directions such as improving the effective utilization efficiency of farmland irrigation water, optimizing irrigation energy structure, promoting water-saving irrigation technologies, agricultural water price reform, and adjusting grain production layout, combining regional realities to form implementable recommendations.

[0052] The spatiotemporal decoupling assessment method for farmland irrigation carbon emissions and grain yield of the present invention achieves a full-process assessment through the above four steps, from basic data production and refined carbon emission calculation to time-space dual-dimensional decoupling analysis and regional differentiated decision-making, and finally generates multi-dimensional and multi-level assessment results output, specifically outputting a spatiotemporal decoupling analysis report and regional differentiated strategy schemes.

[0053] The assessment method of this invention can achieve dynamic updates and assessments at different time scales such as annual and five-year periods. When new water resources, energy, and food production data are added, the carbon emission calculation and decoupled analysis results can be updated quickly, realizing dynamic adjustment of the assessment results and providing continuous technical support for refined management of agricultural irrigation and long-term emission reduction.

[0054] Meanwhile, the method of this invention can be integrated with technologies such as remote sensing monitoring and geographic information systems (GIS) to achieve spatial visualization of carbon emission data and decoupled results, improve the intuitiveness and dissemination of assessment results, and provide clearer and more scientific basis for decision-making in agriculture, water conservancy, environmental protection and other departments.

[0055] The spatiotemporal decoupling assessment method for farmland irrigation carbon emissions and grain yield of this invention solves the technical defects of existing technologies, such as a single carbon emission measurement link, lack of decoupling analysis dimensions, insufficient consideration of regional differences, and weak guidance of assessment results. It realizes accurate assessment of carbon-grain relationship at the provincial scale, across the entire chain, and in two dimensions. It provides a complete, scientific, and practical technical method for my country to achieve its agricultural "dual carbon" goals, ensure food security, and promote the conservation and utilization of water resources. It has important theoretical and practical application value.

[0056] Compared with the prior art, the present invention has the following characteristics: a) To address the monitoring needs of multiple objectives in agricultural irrigation—"water conservation, emission reduction, and food security"—a refined carbon emission measurement method focusing on the entire agricultural irrigation chain (water intake-use) has been developed. This invention not only distinguishes between surface water and groundwater sources, and between electromechanical pumps and diesel pumps, but also differentiates between different water use methods such as water-saving irrigation (sprinkler irrigation, drip irrigation) and traditional flood irrigation. This enables precise identification and quantification of carbon emissions in the specific link of agricultural irrigation, providing a more targeted data foundation for subsequent decoupled analysis.

[0057] (b) This invention emphasizes the provincial scale and regional heterogeneity, making the decoupled evaluation of farmland irrigation carbon emissions and grain yield more suitable for the agricultural development realities of different regions in China with varying resource endowments. The invention uses the provincial scale as the basic analytical unit and groups and compares data according to standards such as north-south regions, major grain-producing areas and non-major grain-producing areas, and six major geographical divisions, providing a scientific basis for differentiated regional management.

[0058] (c) Overcoming the shortcomings of existing assessment techniques that rely on a single dimension for decoupling analysis, this invention innovatively constructs a time-space dual-dimensional decoupling assessment system. Building upon Tapio's time-series decoupling analysis, this invention constructs an extended Tapio spatial decoupling index to achieve horizontal comparison and quantitative determination of the coordinated development level of carbon emissions and grain output between provinces and regions, overcoming the limitation of traditional methods that can only analyze the temporal evolution trend of the same region.

[0059] d) This invention integrates multi-factor correlation analysis of water, energy, carbon, and grain, combining carbon emission assessment with actual grain production to transform assessment results into regional development strategies. Based on the decoupled assessment results of spatiotemporal dimensions, this invention combines data on water resource endowment, irrigation methods, and grain production positioning of each province to construct regional type classification standards (such as spatiotemporally superior type, time-superior and space-weak type, etc.), and formulates differentiated strategies for coordinated development of farmland irrigation water conservation and emission reduction with grain production, thereby enhancing the practical guiding value of the assessment results.

[0060] Based on the same inventive concept, this invention also provides a spatiotemporal decoupling assessment system for farmland irrigation carbon emissions and grain yield, comprising: The data acquisition module is used to acquire water resource data, energy consumption data, grain production data, and agricultural irrigation data for the target farmland area.

[0061] The carbon emission calculation module is used to calculate the energy consumption of surface water intake, groundwater intake, and water use in a target farmland area based on water resource data, energy consumption data, and agricultural irrigation data. It also calculates the carbon emissions per hectare of farmland irrigation based on the energy consumption of surface water intake, groundwater intake, and water use.

[0062] The decoupling assessment module is used to calculate the Tapio decoupling index based on carbon emissions per hectare of farmland irrigation and grain production data. Based on the Tapio decoupling index, the decoupling status of carbon emissions and grain yield is analyzed to obtain the decoupling assessment results of farmland irrigation carbon emissions and grain yield.

[0063] The modules in the aforementioned spatiotemporally decoupled assessment system for farmland irrigation carbon emissions and grain yield can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0064] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the steps in the embodiment of the method for spatiotemporal decoupling assessment of farmland irrigation carbon emissions and grain yield. Specific implementation methods can be found in the method embodiments, and will not be repeated here.

[0065] Furthermore, the present invention also provides a non-transitory computer-readable storage medium containing instructions, on which a computer program is stored. When executed by a processor, this computer program can implement the steps in the embodiments of the method for spatiotemporal decoupling assessment of farmland irrigation carbon emissions and grain yield. Specific implementation methods can be found in the method embodiments, and will not be repeated here.

[0066] Those skilled in the art will understand that embodiments of the present invention can provide methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0067] It should be noted that the specific embodiments described above enable those skilled in the art to more fully understand the present invention, but do not limit the present invention in any way. Therefore, although the present invention has been described in detail in this specification and embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the present invention; and all technical solutions and improvements that do not depart from the spirit and scope of the present invention are covered within the protection scope of the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims. Any simple variations or equivalent substitutions of technical solutions that can be readily obtained by those skilled in the art within the scope of the technology disclosed in the present invention are within the protection scope of the present invention.

Claims

1. A method for spatiotemporally decoupled assessment of farmland irrigation carbon emissions and grain yield, characterized in that, Includes the following steps: Acquire water resource data, energy consumption data, grain production data, and agricultural irrigation data for the target farmland area; Based on water resource data, energy consumption data, and agricultural irrigation data, the energy consumption of surface water intake, groundwater intake, and water use in the target farmland area is calculated. Based on the energy consumption of surface water intake, groundwater intake, and water use, the carbon emissions per hectare of farmland irrigation are calculated. The Tapio decoupling index is calculated based on carbon emissions per hectare of farmland irrigation and grain production data. The decoupling status of carbon emissions and grain yield is analyzed based on the Tapio decoupling index, and the decoupling assessment results of farmland irrigation carbon emissions and grain yield are obtained.

2. The method for spatiotemporal decoupling assessment of farmland irrigation carbon emissions and grain yield according to claim 1, characterized in that, The decoupling states include temporal decoupling and spatial decoupling. Temporal decoupling involves longitudinal time-series analysis of data from the same region over many years to quantitatively assess whether the increase in grain production and the increase in irrigation carbon emissions have become decoupled during the region's own changes over time. Spatial decoupling uses the national average level as a reference to horizontally compare the relative advantages and disadvantages of unit irrigation carbon emissions and grain yields in different provinces in the same year.

3. The method for spatiotemporal decoupling assessment of farmland irrigation carbon emissions and grain yield according to claim 1, characterized in that, The energy consumption in the surface water intake process includes the electricity consumption and diesel consumption for surface water pumping. The electricity consumption for surface water pumping is calculated based on surface water irrigation water consumption, pump head, pump efficiency, energy type proportion, and the carbon emission coefficients of electricity and diesel. Diesel consumption for surface water extraction ; The energy consumption of the groundwater extraction process includes the electricity consumption and diesel consumption for groundwater extraction. The electricity consumption for groundwater extraction is calculated based on groundwater irrigation water consumption, pump head, pump efficiency, energy type ratio, and the carbon emission coefficients of electricity and diesel. Diesel consumption for groundwater extraction .

4. The method for spatiotemporal decoupling assessment of farmland irrigation carbon emissions and grain yield according to claim 3, characterized in that, The energy consumption in the water use process includes electricity consumption and diesel consumption in the irrigation water use process. The electricity consumption in the irrigation water use process is calculated based on the flood irrigation area, energy intensity per unit area, energy type proportion, and carbon emission coefficient. Diesel consumption in irrigation water .

5. The method for spatiotemporal decoupling assessment of farmland irrigation carbon emissions and grain yield according to claim 4, characterized in that, The calculation of carbon emissions per hectare of farmland irrigation based on the energy consumption of surface water intake, groundwater intake, and water use includes the following steps: based on , and The carbon emissions generated during electricity consumption are calculated using the following formula: ； In the formula, Indicates the first Province Carbon emissions generated during annual electricity consumption For the first Annual power grid carbon emission factor; based on , and The carbon emissions from diesel consumption are calculated using the following formula: ； In the formula, Indicates the first Province Carbon emissions generated during annual diesel consumption Carbon emission factors for diesel fuel; right and Summing up yields the total carbon emissions from farmland irrigation. The calculation formula is: ； based on Calculation of carbon emissions from farmland irrigation, with the unit of grain sown area being hectares. The calculation formula is: ； In the formula, For the first Year The province's grain planting area.

6. The method for spatiotemporal decoupling assessment of farmland irrigation carbon emissions and grain yield according to claim 5, characterized in that, The formula for calculating the Tapio decoupling index is as follows: ； In the formula, The Tapio decoupling index. , These represent the carbon emissions per hectare of farmland irrigation in year t and year b, respectively. , These represent the grain yield per hectare in year t and year b, respectively. , These represent the changes in carbon emissions from irrigation per unit hectare of farmland and grain yield, respectively, between year t and year b.

7. The method for spatiotemporal decoupling assessment of farmland irrigation carbon emissions and grain yield according to claim 5, characterized in that, Also includes: The data is grouped by north and south regions, and major grain-producing areas and non-major grain-producing areas to analyze the decoupling status of each province at different times. By comparing the differences and trends in the distribution of decoupling states within each group, the long-term dynamic relationship characteristics between farmland irrigation carbon emissions and grain yield were obtained. These long-term dynamic relationship characteristics include time series decoupling characteristics and regional decoupling difference characteristics. Based on the total carbon emissions from farmland irrigation, time-series decoupling characteristics, and regional decoupling differences, combined with the resource endowment data of each province, the actual development of agricultural irrigation, and the positioning of grain production, differentiated strategies for coordinated development of farmland irrigation water conservation and emission reduction with grain production are formulated.

8. A spatiotemporal decoupling assessment system for farmland irrigation carbon emissions and grain yield, characterized in that, include: The data acquisition module is used to acquire water resource data, energy consumption data, grain production data, and agricultural irrigation data for the target farmland area. The carbon emission calculation module is used to calculate the energy consumption of surface water intake, groundwater intake, and water use in a target farmland area based on water resource data, energy consumption data, and agricultural irrigation data, and to calculate the carbon emission per hectare of farmland irrigation based on the energy consumption of surface water intake, groundwater intake, and water use. The decoupling assessment module is used to calculate the Tapio decoupling index based on carbon emissions per hectare of farmland irrigation and grain production data. Based on the Tapio decoupling index, the decoupling status of carbon emissions and grain yield is analyzed to obtain the decoupling assessment results of farmland irrigation carbon emissions and grain yield.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is loaded by the processor, it is able to perform the steps of the method according to any one of claims 1 to 7.

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