Method and system for evaluating soil improvement effect of saline-alkali soil
By constructing a water-salt-carbon ternary coupled evaluation index system and dynamic evaluation method, the problems of multi-dimensionality and objectivity in the evaluation of traditional saline-alkali land improvement effects have been solved. This has enabled a scientific and systematic evaluation of the saline-alkali land improvement effects, supporting the long-term management and continuous improvement of saline-alkali land.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-05-26
- Publication Date
- 2026-07-21
AI Technical Summary
Traditional methods for evaluating the effectiveness of saline-alkali land improvement are limited by a single evaluation dimension, lack systematicity and objectivity, and fail to reflect the comprehensive benefits of improvement measures. Furthermore, they lack long-term dynamic monitoring and prediction of improvement effects, thus failing to support the long-term management of saline-alkali land.
A ternary coupled evaluation index system of water, salt, and carbon was constructed. The weights of the indexes were determined by the combined weighting method, and the index data were processed by the range standardization method. This enabled a multi-dimensional and comprehensive quantitative assessment of the improvement effect of saline-alkali land, and supported short-term, medium-term, and long-term dynamic evaluation. By constructing a prediction model for the decay of the improvement effect, support was provided for the long-term management of saline-alkali land.
It improves the accuracy and practicality of evaluating the effects of saline-alkali land improvement, provides a scientific evaluation tool, supports the promotion and application of saline-alkali land improvement technologies, and ensures the durability and stability of the improvement effects.
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Figure CN122434299A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the fields of ecological restoration of saline-alkali land and soil quality evaluation, specifically to a method and system for evaluating the effect of soil improvement in saline-alkali land. Background Technology
[0002] With increasingly scarce global land resources, the improvement and utilization of saline-alkali land, as a potential usable land resource, has become an important issue for sustainable agricultural development. Due to its high salinity and poor soil structure, saline-alkali land severely restricts crop growth and agricultural productivity.
[0003] Traditional methods for evaluating the effectiveness of saline-alkali land improvement have several shortcomings: First, they are limited to a single evaluation dimension, often focusing only on the reduction of soil salinity while neglecting changes in water-saving effects and carbon sequestration functions, thus failing to comprehensively reflect the overall benefits of improvement measures. Second, they lack a systematic evaluation index system, making the evaluation process highly subjective and difficult to guarantee the objectivity and accuracy of the evaluation results. Third, traditional methods tend to focus on static evaluation, lacking monitoring and prediction of long-term dynamic changes in improvement effects, and thus failing to provide a scientific basis for the long-term management and continuous improvement of saline-alkali land. Finally, traditional evaluation methods have relatively outdated data processing and analysis techniques, making it difficult to meet the needs of large-scale, high-precision soil data collection and processing, thus limiting the efficiency and accuracy of the evaluation work.
[0004] In view of the many shortcomings of traditional methods for evaluating the effect of saline-alkali land improvement, this invention proposes a method and system for evaluating the effect of saline-alkali land improvement, which is of particular importance. Summary of the Invention
[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a method and system for evaluating the effectiveness of saline-alkali land improvement. This method constructs a ternary coupled evaluation index system of water, salt, and carbon, determines index weights using a combined weighting method, and processes index data using a range standardization method, thereby achieving a multi-dimensional and comprehensive quantitative assessment of the improvement effect on saline-alkali land. Furthermore, this invention supports short-term, medium-term, and long-term dynamic evaluation of the improvement effect, and by constructing a prediction model for the decay of the improvement effect, it provides strong support for the long-term management and continuous improvement of saline-alkali land. This invention not only improves the accuracy and practicality of evaluation work but also provides a scientific basis and technical support for the promotion and application of saline-alkali land improvement technologies.
[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: On one hand, a method for evaluating the soil improvement effect on saline-alkali land, the specific steps of which are as follows: S1. Baseline data collection and basic database construction of saline-alkali land to be evaluated: Collect basic geographic information of the area to be evaluated, and simultaneously collect baseline index data of soil water, salt and carbon in three dimensions before the implementation of improvement, and construct a standardized basic database of saline-alkali land baseline data. S2. Construction of a water-salt-carbon ternary coupled evaluation index system: Taking the synergistic effect of water-salt-carbon improvement on saline-alkali land as the target layer, an evaluation index system is constructed that includes three criterion layers: desalination improvement effect, water saving effect, and carbon sink gain. The index layer factors corresponding to each criterion layer are clarified, and the positive and negative attributes of the indicators are divided. S3. Determination of evaluation index weights based on the combined weighting method: The combined weighting method, which combines the analytic hierarchy process (AHP) and the improved CRITIC method, is adopted to calculate the subjective and objective weights of each factor in the index layer, and then integrate them to obtain the comprehensive weight of each index. S4. Standardization of indicator data: Collect soil water, salt and carbon corresponding indicator data for a preset period after the implementation of the improvement, and combine them with the baseline data. For positive and negative indicators, the range standardization method is used to perform dimensionless processing to obtain the standardized score of each indicator. S5. Calculation of the Water-Salt-Carbon Ternary Coupling Synergistic Enhancement Index: Based on standardized scores and comprehensive weights, the comprehensive scores of the three criteria layers of desalination improvement effect, water saving effect and carbon sink gain are calculated respectively. A ternary coupling coordination degree model is constructed, and the Water-Salt-Carbon Synergistic Enhancement Index (WSCCI) is calculated. S6. Evaluation of Improvement Effect and Screening of Adaptability of Measures: Based on the preset synergy level classification standard, the improvement effect is evaluated in a graded manner according to the WSCCI value, and the synergy performance of different improvement measures is ranked and the adaptability is screened simultaneously.
[0007] Furthermore, in S1, the basic geographic information includes the climate zoning, saline-alkali land type, land use pattern, hydrogeological conditions, annual average rainfall, and annual average evaporation of the area to be evaluated. The baseline index data of the three dimensions of water, salt, and carbon are collected separately for the 0-20cm topsoil layer, 20-40cm sub-topsoil layer, and 40-60cm deep layer. The sampling of each soil layer is repeated no less than 3 times. The sampling points are laid out using a grid method with a grid spacing of no more than 100m×100m. The GPS coordinates, sampling time, and field management measures are recorded simultaneously at each sampling point. The collected samples are tested in the laboratory within 24 hours under 4℃ cold storage conditions. The test data are entered into the basic database after outliers are removed by the Grubbs criterion. The database is standardized and archived according to soil layer, sampling time, and index category, supporting batch data retrieval and traceability.
[0008] Furthermore, in S2, the indicator layer of the desalination improvement effect criterion layer includes four positive indicators: reduction in total soil salinity, reduction in alkalinity, reduction in pH value, and reduction in sodium adsorption ratio. The indicator layer of the water-saving effect criterion layer includes four positive indicators: improvement rate of saturated hydraulic conductivity, improvement rate of field water holding capacity, improvement rate of crop water use efficiency, and improvement rate of irrigation water use coefficient. The indicator layer of the carbon sink gain criterion layer includes five positive indicators: increase in soil organic carbon, increase in active organic carbon, increase in inert organic carbon, increase in carbon pool management index, and increase in carbon sequestration rate. All indicators were screened through three rounds of Delphi method expert consultation combined with Person correlation analysis, eliminating redundant indicators with correlation coefficients greater than 0.9 to ensure the independence and representativeness of the indicator system. The positive and negative attributes of the indicators are classified according to the degree of positive impact of the indicator value improvement on the synergistic effect.
[0009] Furthermore, in S3, the comprehensive weight of the combined weighting method is calculated using the following formula: ,in For the first The overall weight of each indicator The first digit obtained by the analytic hierarchy process (AHP) The subjective weights of each indicator are derived from a judgment matrix constructed by pairwise comparisons of scores from at least 15 experts with associate senior or higher professional titles in the fields of saline-alkali land restoration, soil science, and hydrology and water resources. The judgment matrix is effective when it passes the consistency test and the consistency ratio (CR) is less than 0.1. The first number calculated using the improved CRITIC method The objective weights of each indicator are derived from the calculation results of the variability and conflict of baseline indicator data from all sampling points in the area to be evaluated. This represents the total number of indicators in the indicator layer. For the first indicator layer Item indicator.
[0010] Furthermore, in S4, after the improvement is implemented, the sampling points, soil depth, number of repetitions, detection methods and quality control standards for the index data collection and the baseline data collection in the preset period are kept the same to ensure the comparability of the data. Before the range standardization process, the collected index data is first corrected for environmental factors. The correction factors include the cumulative rainfall, cumulative evaporation, average temperature and irrigation water volume in the sampling period to eliminate the interference of climate fluctuations and differences in field management on the index data. The corrected index data is combined with the baseline data of the corresponding sampling points to calculate the index change range, and then dimensionless processing is completed for positive and negative indicators respectively. The standardized score range after processing is fixed between 0 and 1.
[0011] Furthermore, in S4, the preset period after the improvement is implemented is divided into a short-term period of 3 months, a medium-term period of 6 months, and a long-term period of 12 months. Index data for the corresponding period are collected to complete the dynamic evaluation of the improvement effect at different time scales. For saline-alkali land in seasonal freeze-thaw zones, an additional 1-month special data collection for the salt return period after the end of the freeze-thaw cycle is added. For saline-alkali land in arid rain-fed agricultural areas, an additional 1-month special data collection for the leaching period after the end of the rainy season is added. The evaluation data of different periods are fitted according to the time series to construct a prediction model for the decay of the improvement effect, predict the long-term effectiveness of the improvement measures, and the evaluation results are simultaneously included in the basic database to complete the dynamic update and iteration of the baseline data.
[0012] Furthermore, in S5, the water-salt-carbon synergistic enhancement index (WSCCI) is calculated using the following formula: ,in This is a quantitative index for the synergistic effect of water, salt, and carbon, with a value ranging from 0 to 1. A higher value indicates a better synergistic effect of water, salt, and carbon. The overall score of the criterion layer for desalination improvement effect, The comprehensive score of the water-saving effect criterion layer, The comprehensive score of the carbon sink gain criterion layer is obtained by weighting the standardized scores of the corresponding indicators and the comprehensive weights. 0.4, 0.3 and 0.3 are the contribution coefficients of the corresponding criterion layers, which are set for the resource constraints and development needs of arid saline-alkali land.
[0013] Furthermore, in S6, the synergistic effect level classification criteria are as follows: WSCCI ≥ 0.85 is excellent synergy level, WSCCI ≥ 0.70 and < 0.85 is good synergy level, WSCCI ≥ 0.55 and < 0.70 is medium synergy level, WSCCI ≥ 0.40 and < 0.55 is barely synergy level, and WSCCI < 0.40 is imbalanced and declining level. The level classification thresholds are determined by calibration using data from more than 120 sets of field improvement experiments on different climate zones and different types of saline-alkali land across the country. During the suitability screening process, different improvement measures for the same evaluation area are sorted from high to low according to WSCCI values. The optimal suitable improvement measures are selected by combining the water resource endowment, improvement cost, planting pattern, and dual carbon target requirements of the evaluation area.
[0014] On the other hand, an evaluation system for the soil improvement effect of saline-alkali land, the system comprising: Data acquisition module: used to collect basic geographic information of the saline-alkali land to be evaluated, measured data of water-salt-carbon indicators before and after improvement, and transmit them to the basic database module; Basic database module: Used to store and manage various types of collected data, and to complete the standardized archiving and retrieval of data; Indicator system construction module: used to preset and output a water-salt-carbon ternary coupled evaluation indicator system, and to clarify the correspondence between the target layer, the criterion layer, and the indicator layer, as well as the positive and negative attributes of the indicators; Weight Calculation Module: Built-in combined weighting method calculation unit, used to calculate and output the comprehensive weight of each indicator; Standardization processing module: Built-in range standardization calculation unit, used to complete the dimensionless processing of indicator data and output standardized scores; Synergistic Efficiency Index Calculation Module: Built-in ternary coupling coordination degree model calculation unit, used to calculate and output the comprehensive score of the three criteria layers and the water-salt-carbon synergistic efficiency quantitative index WSCCI; The tiered evaluation and output module has a built-in synergy synergy grading standard, which is used to complete the tiered evaluation of improvement effects and output evaluation reports and the results of the suitability screening of improvement measures.
[0015] Compared with existing technologies, this method and system for evaluating the soil improvement effect in saline-alkali land has the following advantages: I. This invention proposes a systematic and scientific evaluation method for the improvement effect of saline-alkali land. It constructs a ternary coupled evaluation index system of water, salt, and carbon, determines the index weights using a combined weighting method, and processes the index data using a range standardization method, ultimately calculating a quantitative index for the synergistic effect of water, salt, and carbon. This method not only comprehensively considers the desalination effect, water-saving effect, and carbon sequestration gain during the saline-alkali land improvement process, but also intuitively reflects the comprehensive effect of improvement measures through a quantitative index, providing a powerful tool for scientifically evaluating the effectiveness of saline-alkali land improvement.
[0016] Second, this invention supports short-term, medium-term, and long-term dynamic evaluation of the effects of saline-alkali land improvement. By collecting indicator data at different time scales, a model for predicting the decay of improvement effects can be constructed, enabling the prediction of the long-term effectiveness of improvement measures. This function provides data support for the long-term management and continuous improvement of saline-alkali land, helping to adjust improvement strategies in a timely manner and ensuring the persistence and stability of improvement effects. Simultaneously, the evaluation results are integrated into a basic database, enabling dynamic updates and iterations of baseline data, thus improving the accuracy and practicality of the evaluation.
[0017] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description
[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.
[0019] Figure 1 A flowchart for evaluating the effectiveness of soil improvement in saline-alkali land; Figure 2 A flowchart for dynamic evaluation and attenuation prediction of a method for evaluating the effect of soil improvement in saline-alkali land. Figure 3 This is a flowchart of an evaluation system for the effectiveness of soil improvement in saline-alkali land. Detailed Implementation
[0020] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.
[0021] Example The application scenario of this embodiment is moderate sulfate-chloride type saline-alkali farmland in the Hetao Irrigation District of Inner Mongolia. This area belongs to the mid-temperate arid continental climate zone. The land use pattern is irrigated farmland with one crop of spring corn per year. The hydrogeological conditions are shallow groundwater depth of 1.8-2.2m, mineralization of 2.3-3.5g / L, average annual rainfall of 142mm, and average annual evaporation of 2200mm. It is a typical irrigated saline-alkali land distribution area in the arid northwest of my country. This evaluation conducts a full-process evaluation and suitability screening of the synergistic effect of four mainstream improvement measures in this area.
[0022] The first step involved collecting baseline data and constructing a basic database for the saline-alkali land to be evaluated. A grid-based sampling method was used to establish 36 sampling points in the evaluation area, with a grid size of 100m × 100m. At each sampling point, GPS coordinates, sampling time, and routine field management practices were recorded simultaneously. Soil samples were collected from the 0–20cm topsoil layer, 20–40cm sub-topsoil layer, and 40–60cm deep soil layer. Simultaneously, basic geographic information regarding the climate zone, saline-alkali land type, land use, hydrogeological conditions, average annual rainfall, and average annual evaporation of the evaluation area was also collected. All collected soil samples were stored at 4℃ throughout the process and underwent laboratory testing within 24 hours. After testing, outliers were removed using the Grubbs criterion. The qualified basic geographic information and baseline index data for the three dimensions of soil water, salinity, and carbon were entered into a standardized saline-alkali land baseline database. The database was standardized and archived according to soil layer, sampling time, and index category, supporting batch data retrieval and traceability.
[0023] The second step involved constructing a ternary coupled evaluation index system for water, salt, and carbon. Taking the synergistic effect of water, salt, and carbon improvement on saline-alkali land as the target layer, an evaluation index system was constructed, comprising three criterion layers: desalination improvement effect, water-saving effect, and carbon sequestration gain. The index layer factors corresponding to each criterion layer were clarified, and the positive and negative attributes of the indicators were classified. Specifically, the desalination improvement effect criterion layer included four positive indicators: reduction in total soil salinity, reduction in alkalinity, reduction in pH value, and reduction in sodium adsorption ratio. The water-saving effect criterion layer included four positive indicators: increase in saturated hydraulic conductivity, increase in field water holding capacity, increase in crop water use efficiency, and increase in irrigation water use coefficient. The carbon sequestration gain criterion layer included five positive indicators: increase in soil organic carbon, increase in active organic carbon, increase in inert organic carbon, increase in carbon pool management index, and increase in carbon sequestration rate. All indicators were screened through three rounds of Delphi method expert consultation combined with Pearson correlation analysis, eliminating redundant indicators with correlation coefficients greater than 0.9, ultimately determining the aforementioned 13 evaluation indicators.
[0024] The third step is to determine the weights of the evaluation indicators based on the combined weighting method. A combined weighting method, integrating the analytic hierarchy process (AHP) and a modified CRITIC method, is employed. First, the subjective weights of each factor in the indicator layer are calculated using the AHP. Then, the objective weights of each factor in the indicator layer are calculated using the modified CRITIC method. Finally, the combined weighting method is used to calculate the comprehensive weight of each indicator using the integrated weighting formula, which is: ,in For the first The overall weight of each indicator The first digit obtained by the analytic hierarchy process (AHP) Subjective weighting of each indicator The first number calculated using the improved CRITIC method The objective weight of each indicator This represents the total number of indicators in the indicator layer. For the first indicator layer The calculation process for each indicator strictly follows the calculation logic of the combined weighting method, ensuring that the weight assignment takes into account both the experience of experts in the field of saline-alkali land improvement in arid areas and the objective characteristics of the indicator data itself.
[0025] The fourth step is to standardize the indicator data. First, the pre-set periods after the improvement implementation are divided into a short-term period of 3 months, a medium-term period of 6 months, and a long-term period of 12 months. Soil water, salt, and carbon indicators are collected for the corresponding periods. The data collection maintains the same sampling points, soil depth, number of repetitions, testing methods, and quality control standards as the baseline data collection. For the saline-alkali land in the rain-fed agricultural area of this arid region, an additional one-month leaching period data collection is added after the rainy season. Before range standardization, environmental factors are corrected for the collected index data for each period. The correction factors include cumulative rainfall, cumulative evaporation, average temperature, and irrigation water volume within the sampling period to eliminate the interference of climate fluctuations and differences in field management on the index data. The corrected index data are combined with the baseline data of the corresponding sampling points to calculate the index change range. Then, the positive and negative indicators are respectively processed by the range standardization method to make them dimensionless. The standardized scores after processing are fixed between 0 and 1. At the same time, the evaluation data of different periods are fitted according to the time series to construct a prediction model for the decay of improvement effect and predict the long-term effectiveness of improvement measures. The evaluation results are simultaneously included in the basic database to complete the dynamic update and iteration of the baseline data.
[0026] The fifth step involves calculating the water-salt-carbon ternary coupling synergistic efficiency quantitative index. Based on the standardized scores and comprehensive weights of each indicator, the comprehensive scores of the three criteria layers—desalination improvement effect, water-saving effect, and carbon sequestration gain—are calculated. Then, a ternary coupling coordination degree model is constructed. Using the water-salt-carbon synergistic efficiency quantitative index (WSCCI) calculation formula, the WSCCI corresponding to each improvement measure in the region is calculated. The formula is: ,in A quantitative index for the synergistic effect of water, salt, and carbon. The overall score of the criterion layer for desalination improvement effect, The comprehensive score of the water-saving effect criterion layer, The comprehensive score of the carbon sink gain criterion layer is 0.4, 0.3, and 0.3, which are the contribution coefficients of the corresponding criterion layers. The calculation process strictly follows the calculation logic of the ternary coupling coordination degree model, accurately reflecting the synergistic effect level among the three criterion layers.
[0027] The sixth step involves conducting a graded evaluation of the improvement effects and screening for the suitability of the measures. Based on the pre-set synergistic effect classification criteria, the improvement effects are graded and evaluated according to the calculated WSCCI values. Specifically, the classification criteria are: WSCCI ≥ 0.85 for excellent synergy, WSCCI ≥ 0.70 and < 0.85 for good synergy, WSCCI ≥ 0.55 and < 0.70 for moderate synergy, WSCCI ≥ 0.40 and < 0.55 for barely synergy, and WSCCI < 0.40 for imbalance and decline. Simultaneously, for the four different improvement measures implemented concurrently in the area to be evaluated—desulfurized gypsum improvement, organic fertilizer application, straw return to the field, and drip irrigation under mulch—the measures are ranked from highest to lowest according to their corresponding WSCCI values. Considering the area's water resource endowment, improvement costs, spring maize planting patterns, and dual-carbon target requirements, the optimal and suitable improvement measures are finally selected.
[0028] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.
Claims
1. A method for evaluating the effect of soil improvement on saline-alkali land, characterized in that, The specific steps of this method are as follows: S1. Baseline data collection and basic database construction of saline-alkali land to be evaluated: Collect basic geographic information of the area to be evaluated, and simultaneously collect baseline index data of soil water, salt and carbon in three dimensions before the implementation of improvement, and construct a standardized basic database of saline-alkali land baseline data. S2. Construction of a water-salt-carbon ternary coupled evaluation index system: Taking the synergistic effect of water-salt-carbon improvement on saline-alkali land as the target layer, an evaluation index system is constructed that includes three criterion layers: desalination improvement effect, water saving effect, and carbon sink gain. The index layer factors corresponding to each criterion layer are clarified, and the positive and negative attributes of the indicators are divided. S3. Determination of evaluation index weights based on the combined weighting method: The combined weighting method, which combines the analytic hierarchy process (AHP) and the improved CRITIC method, is adopted to calculate the subjective and objective weights of each factor in the index layer, and then integrate them to obtain the comprehensive weight of each index. S4. Standardization of indicator data: Collect soil water, salt and carbon corresponding indicator data for a preset period after the implementation of the improvement, and combine them with the baseline data. For positive and negative indicators, the range standardization method is used to perform dimensionless processing to obtain the standardized score of each indicator. S5. Calculation of the Water-Salt-Carbon Ternary Coupling Synergistic Enhancement Index: Based on standardized scores and comprehensive weights, the comprehensive scores of the three criteria layers of desalination improvement effect, water saving effect and carbon sink gain are calculated respectively. A ternary coupling coordination degree model is constructed, and the Water-Salt-Carbon Synergistic Enhancement Index (WSCCI) is calculated. S6. Evaluation of Improvement Effect and Screening of Adaptability of Measures: Based on the preset synergy level classification standard, the improvement effect is evaluated in a graded manner according to the WSCCI value, and the synergy performance of different improvement measures is ranked and the adaptability is screened simultaneously.
2. The method for evaluating the effect of saline-alkali land soil improvement according to claim 1, characterized in that, In S1, the basic geographic information includes the climate zoning, saline-alkali land type, land use pattern, hydrogeological conditions, annual average rainfall, and annual average evaporation of the area to be evaluated. The baseline index data of water, salt, and carbon in three dimensions are collected separately for the 0-20cm topsoil layer, 20-40cm sub-topsoil layer, and 40-60cm deep layer. The sampling points are laid out using a grid method. Each sampling point records GPS coordinates, sampling time, and field management measures simultaneously. The collected samples are tested in the laboratory within 24 hours under 4℃ refrigeration conditions. The test data are entered into the basic database after outliers are removed by the Grubbs criterion. The database is standardized and archived according to soil layer, sampling time, and index category, supporting batch data retrieval and traceability.
3. The method for evaluating the effect of saline-alkali land soil improvement according to claim 1, characterized in that, In S2, the indicator layer of the desalination improvement effect criterion layer includes four positive indicators: reduction in total soil salinity, reduction in alkalinity, reduction in pH value, and reduction in sodium adsorption ratio. The indicator layer of the water-saving effect criterion layer includes four positive indicators: improvement rate of saturated hydraulic conductivity, improvement rate of field water holding capacity, improvement rate of crop water use efficiency, and improvement rate of irrigation water use coefficient. The indicator layer of the carbon sink gain criterion layer includes five positive indicators: increase in soil organic carbon, increase in active organic carbon, increase in inert organic carbon, increase in carbon pool management index, and increase in carbon sequestration rate. All indicators were screened through three rounds of Delphi method expert consultation combined with Person correlation analysis, and redundant indicators with correlation coefficients greater than 0.9 were removed.
4. The method for evaluating the effect of saline-alkali land soil improvement according to claim 1, characterized in that, In S3, the comprehensive weight of the combined weighting method is calculated using the following formula: ,in For the first The overall weight of each indicator The first digit obtained by the analytic hierarchy process (AHP) Subjective weighting of each indicator The first number calculated using the improved CRITIC method The objective weight of each indicator This represents the total number of indicators in the indicator layer. For the first indicator layer Item indicator.
5. The method for evaluating the soil improvement effect on saline-alkali land according to claim 1, characterized in that, In S4, after the improvement is implemented, the sampling points, soil depth, number of repetitions, detection methods and quality control standards for the index data collection and the baseline data collection are kept the same. Before the range standardization process, the collected index data is first corrected for environmental factors. The correction factors include the cumulative rainfall, cumulative evaporation, average temperature and irrigation water volume in the sampling period to eliminate the interference of climate fluctuations and differences in field management on the index data. The corrected index data is combined with the baseline data of the corresponding sampling points to calculate the index change range. Then, dimensionless processing is completed for positive and negative indicators respectively. The standardized score range after processing is fixed between 0 and 1.
6. The method for evaluating the effect of saline-alkali land soil improvement according to claim 1, characterized in that, In S4, the preset period after the improvement is implemented is divided into a short-term period of 3 months, a medium-term period of 6 months, and a long-term period of 12 months. Index data are collected for the corresponding period to complete the dynamic evaluation of the improvement effect at different time scales. For saline-alkali land in seasonal freeze-thaw zones, an additional 1-month special data collection for the salt return period after the end of the freeze-thaw cycle is added. For saline-alkali land in arid rain-fed agricultural areas, an additional 1-month special data collection for the leaching period after the end of the rainy season is added. The evaluation data of different periods are fitted according to the time series to construct a prediction model for the decay of the improvement effect, predict the long-term effectiveness of the improvement measures, and the evaluation results are simultaneously included in the basic database to complete the dynamic update and iteration of the baseline data.
7. The method for evaluating the effect of saline-alkali land soil improvement according to claim 1, characterized in that, In S5, the water-salt-carbon synergistic enhancement index (WSCCI) is calculated using the following formula: ,in A quantitative index for the synergistic effect of water, salt, and carbon. The overall score of the criterion layer for desalination improvement effect, The comprehensive score of the water-saving effect criterion layer, The score represents the overall score of the carbon sink gain criterion layer, and 0.4, 0.3, and 0.3 are the contribution coefficients of the corresponding criterion layers.
8. The method for evaluating the soil improvement effect on saline-alkali land according to claim 1, characterized in that, In S6, the synergistic effect level classification criteria are as follows: WSCCI ≥ 0.85 is excellent synergy level, WSCCI ≥ 0.70 and < 0.85 is good synergy level, WSCCI ≥ 0.55 and < 0.70 is medium synergy level, WSCCI ≥ 0.40 and < 0.55 is barely synergy level, and WSCCI < 0.40 is imbalanced and declining level. In the suitability screening process, for different improvement measures in the same evaluation area, they are sorted from high to low according to WSCCI value. Combined with the water resource endowment, improvement cost, planting pattern, and dual carbon target requirements of the evaluation area, the optimal suitable improvement measure is selected.
9. An evaluation system for the effect of improving saline-alkali land soil, applicable to the evaluation method for the effect of improving saline-alkali land soil as described in any one of claims 1-8, characterized in that, The system includes: Data acquisition module: used to collect basic geographic information of the saline-alkali land to be evaluated, measured data of water-salt-carbon indicators before and after improvement, and transmit them to the basic database module; Basic database module: Used to store and manage various types of collected data, and to complete the standardized archiving and retrieval of data; Indicator system construction module: used to preset and output a water-salt-carbon ternary coupled evaluation indicator system, and to clarify the correspondence between the target layer, the criterion layer, and the indicator layer, as well as the positive and negative attributes of the indicators; Weight Calculation Module: Built-in combined weighting method calculation unit, used to calculate and output the comprehensive weight of each indicator; Standardization processing module: Built-in range standardization calculation unit, used to complete the dimensionless processing of indicator data and output standardized scores; Synergistic Efficiency Index Calculation Module: Built-in ternary coupling coordination degree model calculation unit, used to calculate and output the comprehensive score of the three criteria layers and the water-salt-carbon synergistic efficiency quantitative index WSCCI; The tiered evaluation and output module has a built-in synergy synergy grading standard, which is used to complete the tiered evaluation of improvement effects and output evaluation reports and the results of the suitability screening of improvement measures.