An intelligent monitoring method for saline-alkali soil improvement

Abstract

The application provides a kind of saline-alkali soil improvement intelligent monitoring method, it is related to saline-alkali soil improvement technical field, the application includes the target saline-alkali soil is divided into multiple monitoring grids, obtains the soil monitoring information and groundwater level data of different depth soil layer;According to the vertical distribution gradient of soil monitoring information, the underground key structure is identified, and the groundwater salt transport model is constructed in combination with groundwater level distribution data, the water salt transport path and salt accumulation area are determined;According to this, the salt discharge engineering layout scheme is generated and the salt discharge engineering is established;In the running process, the soil salt, soil moisture content and drainage state change data are obtained in real time, the deviation between the measured data and the model prediction data is evaluated according to the salt discharge effect, and the salt discharge engineering layout scheme is adjusted when the preset optimization condition is met.The application realizes the adaptive design and continuous adjustment of salt discharge engineering from the mechanism of groundwater salt transport, so as to improve the accuracy and long-term stability of saline-alkali soil improvement.

Description

Technical Field

[0001] This invention relates to the field of saline-alkali land improvement technology, specifically to an intelligent monitoring method for saline-alkali land improvement. Background Technology

[0002] The improvement and dynamic monitoring of saline-alkali land are important technical means to enhance the utilization efficiency of saline-alkali land and ensure the sustainable development of agriculture. With the development of sensor monitoring technology, intelligent control technology, and underground salt drainage projects, the precise improvement of saline-alkali land based on monitoring data has gradually become an important research direction in the field of saline-alkali land management.

[0003] In existing technologies, such as the patent document with publication number CN121647075B, a soil improvement system and method for saline-alkali land are disclosed. This method monitors soil salinity and moisture status by constructing underground drainage units, irrigation units, and soil information monitoring units, and regulates irrigation, drainage, and soil amendment application processes based on the monitoring results. However, this method mainly regulates the improvement process based on soil salinity and moisture status parameters, lacking in-depth analysis of the underground soil structure characteristics that affect the water and salt transport process in saline-alkali land. Especially in actual saline-alkali land, due to long-term salinization and differences in soil development, special structures such as alkalization layers, water-blocking layers, and low-permeability layers often form. These structures have a significant impact on surface water infiltration paths, underground salt migration directions, and salt removal efficiency. Furthermore, when there are significant differences in underground structures in different areas, even if the same drainage or irrigation strategy is used, it may lead to problems such as poor salt removal in some areas, salt reaccumulation, or decreased improvement efficiency.

[0004] Therefore, how to identify the key underground structural features of saline-alkali land and dynamically optimize the salt drainage project based on the identified underground structural features, so as to improve the efficiency of saline-alkali land improvement and long-term governance effect, has become a technical problem that urgently needs to be solved in this field.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide an intelligent monitoring method for improving saline-alkali land, so as to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A smart monitoring method for saline-alkali land improvement includes the following steps: The target saline-alkali land is divided into multiple monitoring grids. Monitoring points are set up in each monitoring grid. At the monitoring points, soil salinity data, soil moisture content data, and soil pH data of different soil depths are obtained along the vertical direction at preset depth intervals. Groundwater level data corresponding to each monitoring grid is also obtained to construct groundwater level distribution data. Based on the salinity, moisture content, and pH data of soil layers at different depths, the vertical gradients of salinity, moisture content, and pH are calculated respectively. Based on the abrupt changes in moisture content, abrupt changes in salinity and pH gradients, and infiltration response delays, key underground structures are identified, and their depth and thickness are determined. Based on the distribution relationship of depth and thickness of underground key structures in each monitoring grid and between adjacent monitoring grids, the depth characteristics and spatial distribution characteristics of underground key structures are determined. In combination with groundwater level distribution data, a groundwater salt transport model is constructed. The spatial distribution characteristics are used as the boundary constraints of the groundwater salt transport model to determine the water and salt transport paths and salt accumulation areas in the target saline-alkali land. Based on the water and salt transport paths and salt accumulation areas, candidate areas for salt drainage shafts are determined. Within these candidate areas, the location and depth of the salt drainage shafts are determined, and the connection paths of the underground drainage ditches are generated to form a layout plan for the salt drainage project. A salt drainage project is established based on the layout plan of the salt drainage project. During the operation of the salt drainage project, data on changes in soil salinity, soil moisture content, and drainage status are acquired in real time and compared with the predicted data. When the deviation meets the preset optimization conditions, the area to be optimized is determined. Based on the magnitude of the deviation between the changed data and the predicted data within the area to be optimized, and in conjunction with the preset grading threshold, the adjustment level corresponding to the area to be optimized is determined. The layout parameters of the salt drainage shaft, the connection parameters of the drainage culvert, or the connection relationship between the two are adjusted according to the adjustment level. If the evaluation requirements are still not met after the evaluation cycle, the adjustment level is increased and adjusted again.

[0008] Furthermore, the identification of key underground structures specifically includes: When the average water content of the adjacent soil layers above a certain depth range is higher than the average water content of the adjacent soil layers below, and the difference between the two is greater than the first difference threshold, the depth range is identified as the first underground critical structure. When the vertical salt gradient within a certain depth range is greater than the first gradient threshold, and the soil pH value within that depth range is greater than the first pH threshold, that depth range is identified as the second key underground structure. When the infiltration response delay time corresponding to a certain depth interval is greater than the preset delay time threshold, and the rate of change of water content in the depth interval is less than the first change threshold, the depth interval is identified as the third underground key structure. If multiple structural criteria are met simultaneously within the same depth range, the unique structural category is determined in the order that the first underground key structure takes precedence over the second underground key structure, and the second underground key structure takes precedence over the third underground key structure.

[0009] Furthermore, the determination of the boundary constraints includes: Record the upper boundary depth, lower boundary depth, thickness, and corresponding planar position information of the underground key structure in each monitoring grid. Based on the planar position information, perform spatial interpolation on the upper boundary depth, lower boundary depth, and thickness of the underground key structure in each monitoring grid to obtain the three-dimensional continuous distribution result of the underground key structure. Based on the three-dimensional continuous distribution results, the continuous, discontinuous, and weak areas of the underground key structures are determined. The weak area is the area where the thickness of the underground key structure is less than a preset thickness threshold, and the discontinuous area is the area where there are discontinuous gaps between adjacent underground key structures. The continuous region serves as a water and salt transport hindrance region, while the discontinuous and weak regions serve as potential water and salt transport channels. Together, the water and salt transport hindrance regions and potential water and salt transport channels serve as boundary constraints for the groundwater and salt transport model.

[0010] Furthermore, the water-salt transport pathways and salt accumulation areas in the target saline-alkali land are specifically determined in the following ways: Based on the three-dimensional continuous distribution results, the target saline-alkali land is divided into multiple water and salt transport calculation units; Based on the soil salinity data, soil moisture content data, soil pH data, groundwater level data, and identification results of key underground structures corresponding to each water and salt transport calculation unit, the salinity parameters, moisture content parameters, pH parameters, groundwater level parameters, and permeability barrier parameters of each water and salt transport calculation unit are determined. The permeability barrier parameters are determined based on the water content vertical gradient, infiltration response delay time, and thickness of the underground key structure corresponding to the water-salt transport calculation unit. The water and salt transport flux between adjacent water and salt transport calculation units is calculated based on the differences in water content, salinity, and groundwater level between adjacent water and salt transport calculation units, and corrected using the permeability barrier parameters of the corresponding water and salt transport calculation units. Based on the water and salt transport flux, the direction of water and salt transport, the magnitude of the flux, and the rate of salt accumulation are determined, thereby obtaining the water and salt transport path and salt accumulation area in the target saline-alkali land. Connect multiple adjacent water and salt transport calculation units whose transport directions are continuous and whose fluxes meet the preset transport conditions to form a water and salt transport path. A water-salt transport calculation unit whose salt accumulation rate meets a preset accumulation condition is defined as a salt accumulation unit, and the area where the salt accumulation unit is located is defined as a salt accumulation area.

[0011] Furthermore, the aforementioned salt drainage project layout scheme specifically includes: Multiple water-salt transport calculation units with water-salt transport fluxes greater than a preset flux threshold and pointing to the same region are defined as water-salt collection zones. Areas with a salt accumulation rate greater than a preset accumulation threshold are designated as priority salt removal zones; The area that simultaneously belongs to the water-salt collection area and the priority salt discharge area is identified as a candidate area for salt discharge shafts; Within the candidate area for salt drainage shafts, the location with the highest salt accumulation rate, the intersection of water and salt transport paths, or the center of alkali spots are selected as the location for setting up the salt drainage shafts. The installation depth of the salt drainage shaft is determined based on the lower boundary depth of the underground key structure, so that the bottom of the salt drainage shaft passes through the identified underground key structure and extends to a predetermined distance below the underground key structure. A drainage ditch connection path is generated along the dominant direction of the water and salt transport path, so that the drainage ditch connects the salt accumulation area with the salt discharge shaft, or connects two adjacent salt discharge shafts.

[0012] Furthermore, determining the region to be optimized specifically includes: The salt reduction rate is calculated based on soil salinity change data before and after the salt drainage project, the waterlogging reduction rate is calculated based on soil moisture content change data, and the drainage rate of underground ditches and salt drainage shafts is calculated based on drainage status data. Combined with the change in the area of ​​salt accumulation zone, the salt drainage effect evaluation value is calculated. When the salt drainage effect evaluation value is lower than the preset evaluation threshold, or when the deviation between the real-time acquired soil salinity change data, soil moisture content change data and the predicted data of the groundwater salt transport model is greater than the preset deviation threshold, the salt drainage project is determined to meet the preset optimization conditions, and the corresponding area is identified as the area to be optimized.

[0013] Furthermore, after satisfying the preset optimization conditions, the specific optimization includes: Based on the monitoring grid corresponding to the deviation between the real-time acquired data and the predicted data of the groundwater salt transport model, the area to be optimized is determined, and based on the soil salinity change data, soil moisture content change data and drainage status change data in the area to be optimized, the dominant deviation type is determined. Based on the relationship between the deviation magnitude corresponding to the dominant deviation type and the preset grading threshold, the adjustment level corresponding to the region to be optimized is determined, and the adjustment range of each adjustment parameter increases as the adjustment level increases, but does not exceed the corresponding preset single adjustment limit. When the dominant deviation type is salt reduction deviation, the salt collection area and the water and salt transport path in the area to be optimized are used to increase the drainage capacity of the corresponding salt discharge shaft, increase the number of salt discharge shafts, change the setting position of the salt discharge shafts and / or increase the setting depth of the salt discharge shafts. When the dominant deviation type is waterlogging reduction deviation, the length of the drainage ditch is extended, the connection path of the drainage ditch is changed, the number of drainage ditches is increased, and / or the connection relationship between the drainage ditch and the salt drainage shaft is adjusted according to the water and salt transport direction in the area to be optimized. When the dominant deviation type is drainage capacity deviation, the drainage parameters of the corresponding drainage ditch, the drainage parameters of the salt discharge shaft, and the connection relationship between the two are adjusted according to the deviation position of the drainage rate of the underground ditch and the drainage rate of the salt discharge shaft. After the layout plan of the salt drainage project was adjusted, the soil salinity change data, soil moisture content data and drainage status change data were re-acquired after a preset evaluation cycle, and the salt drainage effect evaluation value was recalculated. When the recalculated salt drainage effect evaluation value is still lower than the preset evaluation threshold, or the deviation between the re-acquired data and the predicted data of the groundwater salt transport model is still greater than the preset deviation threshold, the adjustment level is increased and the salt drainage project layout scheme is adjusted again; when the recalculated salt drainage effect evaluation value reaches the preset evaluation threshold and the deviation is not greater than the preset deviation threshold, the adjusted salt drainage project layout scheme is maintained.

[0014] Compared with the prior art, the beneficial effects of the present invention are: This invention identifies key underground structures based on abrupt changes in salinity, moisture content, and pH gradients between adjacent soil layers. This allows the obstruction zones caused by differences in soil properties during groundwater salt transport to be transformed into locatable structural information. Furthermore, it combines the spatial characteristics of these key underground structures with groundwater level data to construct a groundwater salt transport model. Based on this model, a salt drainage project layout scheme is generated, and the scheme is adjusted during the salt drainage process. This transforms the salt drainage structure from a static design based on initial monitoring results to a dynamic optimization process driven by model bias, improving the adaptability of salt drainage projects to complex saline-alkali lands and enhancing their long-term, stable treatment effects. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 A comparison chart of predicted and measured soil salinity values ​​from a groundwater salt transport model; Figure 3 Comparison of soil salinity in each monitoring grid before and after optimization of the salt drainage project layout. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0017] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0018] Example: Please see Figure 1 The present invention provides a technical solution: A smart monitoring method for saline-alkali land improvement includes the following steps: S1: Divide the target saline-alkali land into multiple monitoring grids, set up monitoring points in each monitoring grid, and obtain soil salinity data, soil moisture content data, and soil pH data at different depths along the vertical direction at preset depth intervals at the monitoring points. Also obtain the groundwater level data corresponding to each monitoring grid to construct groundwater level distribution data.

[0019] S2: Based on the salinity, moisture content, and pH data of soil layers at different depths, calculate the vertical gradients of salinity, moisture content, and pH respectively. Based on the abrupt changes in moisture content, salinity and pH gradients, and infiltration response delays, identify key underground structures and determine their depth and thickness.

[0020] S3: Based on the distribution relationship of depth and thickness of underground key structures in each monitoring grid and between adjacent monitoring grids, determine the depth characteristics and spatial distribution characteristics of underground key structures, and construct a groundwater salt transport model in combination with groundwater level distribution data. Use the spatial distribution characteristics as the boundary constraints of the groundwater salt transport model to determine the water and salt transport paths and salt accumulation areas in the target saline-alkali land.

[0021] S4: Based on the water and salt transport path and salt accumulation area, generate and determine the candidate area for salt drainage shafts, determine the location and depth of the salt drainage shafts within the candidate area, and generate the connection path of the drainage culvert to form a salt drainage project layout plan.

[0022] S5: Establish a salt drainage project based on the layout plan of the salt drainage project, and acquire data on changes in soil salinity, soil moisture content, and drainage status in real time during the operation of the salt drainage project. Compare these data with the predicted data, and determine the area to be optimized when the deviation meets the preset optimization conditions.

[0023] S6: Based on the magnitude of the deviation between the changed data and the predicted data within the area to be optimized, and in conjunction with the preset grading threshold, determine the adjustment level corresponding to the area to be optimized. Adjust the salt drainage shaft layout parameters, drainage culvert connection parameters, or the connection relationship between the two according to the adjustment level. If the evaluation requirements are still not met after the evaluation cycle, raise the adjustment level and adjust again.

[0024] In this embodiment, the target saline-alkali land is first divided into multiple monitoring grids according to a preset grid scale. The preset grid scale can be determined based on the area of ​​the target saline-alkali land, topographic conditions, and expected monitoring accuracy. For example, a larger grid scale can be used in areas with less topographic relief, while a smaller grid scale can be used in areas with greater topographic variation or where higher monitoring accuracy is required. At least one monitoring point is selected within each monitoring grid, typically located at the center of the grid. At this monitoring point, soil monitoring information is acquired vertically from the surface downwards at preset depth intervals to obtain soil monitoring data for different depths. The preset depth interval can be determined based on the thickness of the topsoil layer in the target area, the depth of the underground saline-alkali layer, and the required monitoring accuracy. For example, the preset depth interval can be set between 5cm and 50cm. In areas where higher monitoring accuracy is required, a smaller depth interval can be used.

[0025] Groundwater level monitoring points are set up in each monitoring grid to obtain groundwater level data corresponding to each monitoring grid, which is used to monitor changes in groundwater depth. Groundwater level monitoring points can be implemented using groundwater level gauges, pressure level gauges, or other monitoring devices.

[0026] The soil monitoring information includes soil salinity data, soil moisture content data, and soil pH data.

[0027] According to the method given in this embodiment, the target saline-alkali land is divided into multiple monitoring grids. Monitoring points are set in each grid, and soil salinity, moisture content, pH, and groundwater level data are collected vertically at preset depth intervals (10cm to 160cm). The simulation scenario sets up 6 monitoring grids, with 8 monitoring depths in each grid, resulting in 48 sets of stratified soil monitoring data and 6 sets of corresponding groundwater level data. Table 1 lists some monitoring results for monitoring grids G01 and G03, where the groundwater level corresponding to G01 is 2.70 m and the groundwater level corresponding to G03 is 2.12 m.

[0028] Table 1 shows the soil data collection results for some monitoring grids. As shown in Table 1, in the depth range of 50-70cm, the soil salinity is 9.63-13.62 g / kg, the soil moisture content is 38.1%-43.4%, and the soil pH is 9.1-9.4, all of which are significantly higher than those of the adjacent shallow soil. This indicates that there are obvious salt enrichment, alkalization and water retention phenomena in this depth range, which can be regarded as a candidate depth range for key underground structures.

[0029] In the shallow soil layer (10–30 cm), soil salinity was 3.11–3.14 g / kg, soil moisture content was 25.1%–29.1%, and soil pH was 8.0–8.1, indicating a relatively low degree of salinization. In the soil layer at a depth of at least 100 cm, soil salinity decreased to 3.81–6.14 g / kg, soil pH was 8.1, and soil moisture content was 24.2%–33.1%. Compared to the 50–70 cm depth range, both salinity and pH showed a significant decrease. Therefore, based on the changes in salinity, moisture content, and pH at different soil depths, the 50–70 cm depth range can be preliminarily identified as the main distribution area for critical underground structures.

[0030] The vertical gradient of salinity was calculated based on soil salinity data at different soil depths, the vertical gradient of moisture content was calculated based on soil moisture content data at different soil depths, and the vertical gradient of pH was calculated based on soil pH data at different soil depths.

[0031] In one specific embodiment, the vertical gradient of salinity between adjacent soil layers is determined based on the ratio of the difference in soil salinity data at two adjacent monitoring depths to the corresponding depth interval; the vertical gradient of moisture content is determined based on the ratio of the difference in soil moisture content data at two adjacent monitoring depths to the corresponding depth interval; and the vertical gradient of pH is determined based on the ratio of the difference in soil pH data at two adjacent monitoring depths to the corresponding depth interval. It should be noted that the sign of the vertical gradient characterizes the direction of change of the corresponding soil monitoring information with increasing depth, and the absolute value of the vertical gradient characterizes the degree of change of the corresponding soil monitoring information in the vertical direction.

[0032] The key underground structures are identified based on the locations of abrupt changes in the vertical gradient. Specifically, this includes: When the average water content of the adjacent soil layers above a certain depth interval is higher than the average water content of the adjacent soil layers below, and the difference between the two is greater than a first difference threshold, it indicates that water is trapped or its infiltration is obstructed near that depth interval, and this depth interval is identified as the first critical underground structure. The first difference threshold is used to characterize the minimum value at which the difference in water content between adjacent soil layers above and below the critical underground structure reaches the degree of water trapping or obstructed infiltration. The water content difference is the absolute value of the difference between the average water content of the adjacent soil layers above and below the corresponding depth interval. The first difference threshold is determined based on the difference in water content between the depth interval where the water-blocking structure has been confirmed to exist through infiltration tests and the normal infiltration depth interval. The value corresponding to the highest accuracy in distinguishing the water content difference between the two types of samples is taken as the first difference threshold. In this embodiment, the first difference threshold is 5.0 percentage points.

[0033] When the vertical salt gradient within a certain depth range is greater than the first gradient threshold, and the absolute value of the vertical pH gradient within that depth range is greater than the first pH gradient threshold, it indicates that there is salt and alkali enrichment within that depth range, and this depth range is identified as the second key underground structure. The first gradient threshold is the minimum absolute value of the vertical salt gradient that indicates a significant abrupt change in soil salinity along the depth direction, and its unit is g / (kg·cm). The first gradient threshold is determined based on the vertical salt gradient data of salt-enriched and non-salt-enriched ranges confirmed by stratified sampling, and the gradient value with the highest accuracy in distinguishing between the two types of ranges is used as the first gradient threshold. In this embodiment, the first gradient threshold is 0.20 g / (kg·cm). The first pH gradient threshold is used to determine whether there is a significant change in soil pH along the depth direction. The pH vertical gradient is determined based on the ratio of the absolute value of the difference between the soil pH values ​​at two adjacent monitoring depths to the corresponding depth interval, and its unit is pH units / cm. It is determined based on the soil alkalization classification standard of the target area and the pre-sampling results. In this embodiment, the first pH gradient threshold is 0.06.

[0034] When the infiltration response delay time corresponding to a certain depth interval is greater than a preset delay time threshold, and the rate of change of water content within that depth interval is less than a first change threshold, it indicates that the depth interval responds slowly to external water inflow, and its water inflow and conduction capacity is weak. This depth interval is identified as a third critical underground structure. The infiltration response delay time is the time elapsed since the rate of change of water content at the monitoring point first exceeds the preset change threshold under standard water inflow conditions. The standard water inflow conditions can be a natural rainfall process or a controlled quantitative water inflow process. The preset delay time threshold is the maximum allowable normal response time from the start of standard water inflow to the first time the rate of change of water content at the corresponding monitoring depth reaches the preset change threshold. It is determined based on the statistical results of the infiltration response delay time of normally permeable soil layers, for example, taking the 95th percentile of the infiltration response delay time of normal permeable samples. In this embodiment, the preset delay time threshold is 4.0 h. The first change threshold is the maximum rate of change of water content used to determine low-permeability structures. When the rate of change of water content in the corresponding depth interval is less than the first change threshold, it indicates that its water conduction capacity is low. The first change threshold is determined based on the rate of change of water content in low-permeability soil layers and normally permeable soil layers under the same infiltration conditions. In this embodiment, the first change threshold is 0.80% / h. The preset change threshold is the minimum rate of change of water content required to determine that the water content sensor generates an effective infiltration response. Its value is higher than the upper limit of the background fluctuation of the rate of change of water content under no-infiltration conditions, and is determined based on the sensor measurement error and pre-test data. In this embodiment, the preset change threshold is 0.10% / h.

[0035] If multiple structural criteria are met simultaneously within the same depth range, the unique structural category is determined in the order that the first underground key structure takes precedence over the second underground key structure, and the second underground key structure takes precedence over the third underground key structure.

[0036] Table 2 shows the partial gradient analysis and identification results of key underground structures for the six monitoring grids in this embodiment.

[0037] Table 2. Results of partial gradient analysis and identification of key underground structures. As shown in Table 2, the following three types of key underground structures were identified in this embodiment: The first key underground structure, namely the water-blocking layer, is distributed in the depth ranges of 25–45 cm, 45–75 cm and 90–120 cm, respectively. Its vertical gradient of water content is 0.217–0.348 % / cm, indicating that the soil water content in the corresponding depth range changes significantly with depth. Water may be retained or its infiltration may be blocked near this depth range.

[0038] The second key underground structure, namely the alkalization layer, is mainly distributed in the depth range of 45–75 cm, with some monitoring grids distributed in the depth range of 25–45 cm or 90–120 cm. Its vertical salt gradient is 0.202–0.407 g / kg / cm and its vertical pH gradient is 0.069–0.116, indicating that the salt and pH in the corresponding depth ranges change significantly with depth, exhibiting characteristics of salt enrichment and vertical pH abrupt change.

[0039] The third key underground structure, namely the low-permeability layer, is mainly distributed in the 90-120 cm depth range, with some monitoring grids distributed in the 25-45 cm depth range. Its infiltration response delay time is 4.3-6.4 h, and the water content change rate is 0.25-0.77 % / h, indicating that the corresponding depth range responds slowly to external water inflow and has a weak ability to allow water to enter and conduct.

[0040] The thickness of the underground critical structure within each monitoring grid is determined based on the span of the depth interval. Specifically, after determining the abrupt change location of the vertical gradient, the depth interval corresponding to the underground critical structure is determined based on adjacent abrupt change locations or depth ranges that continuously meet preset abrupt change conditions. The side of the depth interval closer to the ground surface is determined as the upper boundary of the underground critical structure, and the side farther from the ground surface is determined as the lower boundary of the underground critical structure. The difference between the depth of the lower boundary and the depth of the upper boundary is determined as the thickness of the underground critical structure.

[0041] When multiple adjacent depth intervals consecutively meet a preset abrupt change condition, these adjacent depth intervals are merged into a single continuous depth interval, and the thickness of the underground critical structure is determined based on the merged continuous depth interval. When the interval between adjacent abnormal depth intervals is greater than a preset merging interval, they are identified as different underground critical structures. The preset merging interval is used to determine whether adjacent abnormal depth intervals belong to the same underground critical structure. When the normal interval thickness between two abnormal depth intervals is not greater than the preset merging interval, the two abnormal intervals are merged; otherwise, they are identified as different underground critical structures. The preset merging interval is not less than the monitoring depth interval and is determined based on drilling verification results. In this embodiment, the preset merging interval is 10 cm.

[0042] After identifying the key underground structures of the target saline-alkali land, the depth and spatial distribution characteristics of the key underground structures are determined based on the distribution relationship of depth and thickness of the key underground structures in each monitoring grid and between adjacent monitoring grids. In conjunction with the groundwater level distribution data, a groundwater-salt transport model is constructed. The spatial distribution characteristics are used as the boundary constraints of the groundwater-salt transport model to determine the water-salt transport paths and salt accumulation areas in the target saline-alkali land.

[0043] The depth features include the upper and lower boundary depths and thickness of the underground key structure and its variation between adjacent monitoring grids; the spatial distribution features include the planar location, continuous distribution, discontinuous distribution, and weak points of the underground key structure.

[0044] Specifically, the upper boundary depth, lower boundary depth, thickness, and corresponding planar position information of the underground key structure in each monitoring grid are recorded. The planar position information can be represented by the coordinates of the monitoring point or the center coordinates of the monitoring grid, which is used to characterize the horizontal position of the underground key structure in the target saline-alkali land.

[0045] Based on the planar location information, spatial interpolation is performed on the upper boundary depth, lower boundary depth, and thickness of the underground key structures within each monitoring grid to obtain the continuous spatial distribution of the upper boundary, lower boundary, and thickness, thereby forming a three-dimensional continuous distribution result of the underground key structures. The spatial interpolation can employ methods such as inverse distance weighted interpolation, kriging interpolation, or spline interpolation.

[0046] Based on the three-dimensional continuous distribution results, continuous, discontinuous, and weak areas of the underground critical structure are determined. Continuous areas refer to regions where the underground critical structure is continuously distributed among multiple adjacent monitoring grids; discontinuous areas refer to regions where there are gaps in the discontinuous distribution between adjacent underground critical structures; and weak areas refer to regions where the thickness of the underground critical structure is less than a preset thickness threshold. The preset thickness threshold is the minimum thickness required for the underground critical structure to form a significant water-salt blocking effect. Quantitative infiltration tests are conducted on regions with different structural thicknesses to determine the relationship between structural thickness and the infiltration flux attenuation ratio. The structural thickness corresponding to the infiltration flux attenuation reaching the preset blocking ratio is used as the preset thickness threshold. In this embodiment, the preset thickness threshold is 15 cm.

[0047] The continuous regions are designated as water-salt transport hindrance regions, while the discontinuous and weak regions are designated as potential water-salt transport channels. These hindrance regions and potential channels are collectively used as boundary constraints for the groundwater-salt transport model. The depth characteristics of key underground structures are used to determine the vertical boundaries of the model and the degree of hindrance in each region. Groundwater level distribution data are used to characterize the hydraulic driving conditions for water-salt migration.

[0048] Based on the aforementioned three-dimensional continuous distribution results, the target saline-alkali land is divided into multiple water-salt transport calculation units. According to the soil salinity data, soil moisture content data, soil pH data, groundwater level data, and identification results of key underground structures corresponding to each water-salt transport calculation unit, the salinity parameters, moisture content parameters, pH parameters, groundwater level parameters, and permeability barrier parameters of each water-salt transport calculation unit are determined. Specifically, the salinity parameter characterizes the salinity content or concentration level within the calculation unit; the moisture content parameter characterizes the soil moisture state within the calculation unit; the pH parameter characterizes the degree of soil alkalization within the calculation unit; the groundwater level parameter characterizes the groundwater depth or changes in groundwater level; and the permeability barrier parameter characterizes the degree to which the calculation unit hinders the migration of water and salt.

[0049] The permeability barrier parameters are determined based on the vertical water content gradient, infiltration response delay time, and thickness of the key underground structure corresponding to the water-salt transport calculation unit. For example, in a specific embodiment, the formula for calculating the permeability barrier coefficient is as follows: in, Let be the osmotic barrier coefficient of the i-th water-salt transport calculation unit. The vertical gradient of water content corresponding to the i-th water-salt transport calculation unit. Let be the infiltration response delay time corresponding to the i-th water-salt transport calculation unit. Let be the thickness of the underground critical structure within the i-th water-salt transport calculation unit. , , These are the normalized baseline values ​​for the vertical gradient of water content, the infiltration response delay time, and the thickness of the critical underground structure, respectively. , , The weights representing the contributions of the vertical gradient of water content, the infiltration response delay time, and the thickness of the key underground structure to the degree of seepage barrier are dimensionless non-negative coefficients, and their sum is 1. Multiple monitoring grids with measured infiltration flux are selected as calibration samples. The three weights are determined using constrained least squares method, with the objective of minimizing the sum of squared errors between the seepage barrier coefficient and the degree of attenuation of measured infiltration flux. In this embodiment, , , The values ​​are 0.3, 0.4, and 0.3, respectively. Through the above normalization process, the permeation barrier parameters... This is a dimensionless parameter. The larger the value, the stronger the resistance of the corresponding water and salt transport calculation unit to the transport of water and salt.

[0050] The water and salt transport flux between adjacent water and salt transport calculation units is calculated based on the differences in water content, salinity, and groundwater level between adjacent water and salt transport calculation units, and after correction using the permeability barrier parameters of the corresponding water and salt transport calculation units.

[0051] In one embodiment, before calculating the water-salt transport flux between adjacent water-salt transport calculation units, initial migration driving parameters can be calculated based on the differences in water content, salinity, and groundwater level between adjacent calculation units. In another embodiment, the initial migration driving parameters can be further corrected using the pH difference between adjacent calculation units. The specific calculation formula is as follows: in, Let be the initial migration driving parameters between the i-th water-salt transport calculation unit and the j-th water-salt transport calculation unit. and These represent the water content parameters of the i-th and j-th water-salt transport calculation units, respectively. and These represent the salinity parameters of the i-th and j-th water-salt transport calculation units, respectively. and These represent the pH parameters of the i-th and j-th water-salt transport calculation units, respectively. and These represent the groundwater level parameters of the i-th and j-th water-salt transport calculation units, respectively. , , , These are the contribution weights corresponding to the differences in moisture content, salinity, pH, and groundwater level, respectively. The moisture content, salinity, pH, and groundwater level parameters used in the calculation have all been pre-normalized; therefore, the weights are dimensionless non-negative coefficients, and their sum is 1. The weights are determined using constrained least squares, with the objective of minimizing the sum of squared errors between the predicted and measured soil salinity values ​​at the next monitoring time. In this embodiment, , , , The values ​​are 0.25, 0.35, 0.15, and 0.25, respectively. The direction of water and salt transport is determined by the sign of the groundwater level difference between adjacent calculation units; when the groundwater levels are the same, it is determined by the sign of the water content difference.

[0052] Furthermore, the initial migration driving parameters are corrected using the osmotic barrier parameters to obtain the water-salt transport flux between adjacent water-salt transport calculation units. The specific calculation method is as follows: in, Let be the water-salt transport flux between the i-th water-salt transport calculation unit and the j-th water-salt transport calculation unit. This is the average value of the permeation barrier parameter between the i-th and j-th computational units, i.e. , This is the barrier correction factor, used to adjust the degree to which the permeation barrier parameter attenuates the initial migration driving parameter. Under the same circumstances, The larger the value, the smaller the calculated water-salt transport flux. Infiltration or test drainage experiments were conducted on samples with different thicknesses of key underground structures and infiltration response delay times to obtain the measured water-salt transport flux between adjacent monitoring locations; different candidate... Substituting into the water-salt transport flux formula, and aiming to minimize the sum of squared errors between the calculated and measured fluxes, a one-dimensional search is used to determine... In this embodiment, The search range is [0,1], and the actual value is 0.8.

[0053] Based on the water and salt transport flux, the direction of water and salt transport, the magnitude of the flux, and the rate of salt accumulation are determined, thereby obtaining the water and salt transport path and salt accumulation area in the target saline-alkali land.

[0054] The specific calculation method for the salt accumulation rate is as follows: in, Let be the salt accumulation rate of the i-th computational unit. This represents the sum of salt fluxes flowing into computational unit i, where k represents all adjacent units flowing into i. This represents the sum of the salt flux flowing out of computing unit i. , The pH parameter is for the corresponding unit. This is the pH correction coefficient, used to characterize the degree to which the pH parameter corrects for the salt migration and accumulation process. Both the salt parameter and the pH parameter in the formula are normalized dimensionless parameters, therefore... These are dimensionless, nonnegative coefficients. Different candidates... Substituting into the salt accumulation rate formula, and aiming to minimize the sum of squared errors between the model-predicted salt level and the measured salt level at the next monitoring time, a one-dimensional search is used to determine the optimal rate. In this embodiment, The search range is [0,1], and the value is 0.2.

[0055] In this embodiment, the permeation barrier coefficient Initial migration driving parameters Water and salt transport flux Salt accumulation rate Together with the predicted soil salinity, they constitute the groundwater salt transport model. The measured soil salinity values ​​of each water-salt transport calculation unit in the initial calculation formula of the model are used as the initial salinity values, i.e.: ,in, The measured value of soil salinity is calculated for the i-th water-salt transport calculation unit at the start time.

[0056] According to the preset time step, the predicted soil salinity value of the i-th water-salt transport calculation unit is updated based on the salt accumulation rate at the n-th calculation time: ,in, This represents the predicted soil salinity value at the (n+1)th calculation time. Let n be the soil salinity value at the nth calculation time. Let be the rate of salt accumulation at the nth calculation time. This represents the time interval between two adjacent calculation moments. During model solving, the osmotic barrier parameters are first calculated based on the monitoring data from each water-salt transport calculation unit. Then calculate the initial migration driving parameters between adjacent computing units. and water-salt transport flux Then, the salt accumulation rate of each computational unit is calculated. The system calculates the soil salinity prediction value step-by-step according to the aforementioned soil salinity prediction formula until a preset prediction time is reached. The soil salinity prediction value of each calculation unit at the prediction time is then used as the prediction data for the groundwater salt transport model. When a monitoring point is located within a water and salt transport calculation unit, the soil salinity prediction value of that calculation unit is used as the corresponding soil salinity prediction value for the monitoring point. When a monitoring grid contains multiple water and salt transport calculation units, the prediction value of the calculation unit containing the monitoring point is used as the corresponding prediction value.

[0057] In one specific embodiment, to ensure stable model output and meet engineering application requirements, a convergence criterion is set as follows: when the maximum change in the predicted soil salinity value of each calculation unit between two adjacent calculation times is less than a preset convergence threshold, iteration stops and the prediction result is output; if the convergence condition is not met, iteration continues according to a preset time step until the preset prediction time is reached. This allows obtaining the predicted soil salinity value of each water-salt transport calculation unit in the target saline-alkali land, and further determining the water-salt transport path based on the direction and magnitude of the water-salt transport flux, and determining the salt accumulation area based on the salt accumulation rate.

[0058] Multiple adjacent water-salt transport computational units with continuous water-salt transport directions and fluxes meeting preset transport conditions are connected to form a water-salt transport path. In this embodiment, the preset transport condition can be that the water-salt transport flux is greater than a preset flux threshold. The preset flux threshold is the minimum water-salt transport flux required to determine whether there is effective water-salt transport between adjacent water-salt transport computational units. Based on the confirmed water-salt transport flux distribution inside and outside the transport path in the model validation data, the flux value that can distinguish between effective and ineffective transport edges is used as the preset flux threshold. In this embodiment, the preset flux threshold is set to 0.2.

[0059] A water-salt transport calculation unit whose salt accumulation rate meets a preset accumulation condition is defined as a salt accumulation unit, and the area where the salt accumulation unit is located is defined as a salt accumulation region. When multiple adjacent salt accumulation units all meet the preset accumulation condition, their connected regions are merged into the same salt accumulation region. In this embodiment, the preset accumulation condition can be that the salt accumulation rate is greater than a preset accumulation threshold. The preset accumulation threshold is the minimum salt accumulation rate at which a calculation unit is deemed to have achieved effective salt accumulation. It is determined based on the accumulation rate distribution of calculation units with continuously increasing salt concentration and those with continuously decreasing salt concentration during a continuous monitoring period. In this embodiment, the preset accumulation threshold is set to 0.1.

[0060] To verify the predictive accuracy of the constructed groundwater salt transport model, the predicted soil salinity values ​​output by the model were compared with the measured soil salinity values ​​at the corresponding monitoring points. The results are as follows: Figure 2 As shown. Figure 2 In the graph, the horizontal axis represents the measured soil salinity, the vertical axis represents the predicted soil salinity output by the groundwater salt transport model, and the dashed line represents the 1:1 reference line when the predicted value and the measured value are completely consistent. Figure 2 It can be seen that the sample points are generally distributed near the 1:1 reference line, and the coefficient of determination R² between the predicted and measured values ​​is 0.980, indicating that the constructed groundwater salt transport model can reflect the actual changes in soil salinity in the target saline-alkali land well, and can be used to determine the water and salt transport path and salt accumulation area.

[0061] After determining the water and salt transport paths and salt accumulation areas in the target saline-alkali land, a salt drainage project layout plan is generated based on the water and salt transport paths and salt accumulation areas, and the salt drainage project is established according to the salt drainage project layout plan.

[0062] The process of generating a salt drainage project layout scheme based on water and salt transport paths and salt accumulation areas specifically includes: determining the convergence trend of water and salt in the target saline-alkali land based on the direction and magnitude of water and salt transport flux in each water and salt transport calculation unit; when the water and salt transport flux of several water and salt transport calculation units is greater than a preset flux threshold, and the water and salt transport flux points to the same area, it indicates that the area has a significant water and salt accumulation trend, and the area is identified as a water and salt accumulation zone.

[0063] Furthermore, based on the salt accumulation rate of each water-salt transport calculation unit, areas in the target saline-alkali land where salt and alkali are prone to accumulate are determined. When the salt accumulation rate of a certain area is greater than the preset accumulation threshold, the area is determined as a priority salt drainage area. When the salt accumulation rate of multiple adjacent water-salt transport calculation units is greater than the preset accumulation threshold, their connected areas can be merged into the same priority salt drainage area.

[0064] Areas that simultaneously fall within water-salt accumulation zones and priority salt discharge zones are identified as candidate areas for salt discharge shafts. These shafts are then preferentially located in areas where water-salt migration is concentrated and salt accumulation is continuous.

[0065] After determining the candidate areas for salt drainage shafts, the locations within these areas—such as the location with the highest salt accumulation rate, the intersection of water-salt transport paths, or the center of an alkaline patch—are selected as the locations for the drainage shafts. Specifically, the location with the highest salt accumulation rate indicates a high degree of net salt accumulation; the intersection of water-salt transport paths indicates the location where water-salt mixtures from multiple directions converge; and the center of an alkaline patch indicates a location with significant surface salinization. These locations can be used individually or in combination as site selection criteria.

[0066] The installation depth of the salt drainage shaft is determined based on the lower boundary depth of the underground key structure at the location of the salt drainage shaft. The bottom of the salt drainage shaft passes through the identified underground key structure and extends to a predetermined distance below the underground key structure, so that the water and salt mixture retained above the underground key structure can be drained through the salt drainage shaft.

[0067] Furthermore, a drainage ditch connection path is generated along the dominant direction of the water-salt transport path. This dominant direction can be determined based on the continuity of flux directions between multiple adjacent water-salt transport calculation units. The drainage ditch is used to connect salt accumulation areas with salt drainage shafts, or to connect two adjacent salt drainage shafts, to guide shallow water-salt mixtures to the drainage shafts. When multiple optional drainage ditch connection paths exist, the final connection path can be determined based on path length, water-salt transport flux, and the underground critical structures traversed by the path. For example, paths with shorter lengths, larger water-salt transport fluxes, or fewer underground critical structures are preferentially selected.

[0068] During the operation of the salt drainage project, real-time data on changes in soil salinity, soil moisture content, and drainage status are acquired. The salt drainage effect is evaluated based on the deviation between the real-time acquired data and the predicted data of the groundwater salt transport model. When the deviation meets the preset optimization conditions, the area to be optimized is determined.

[0069] The salt content reduction rate is calculated based on the soil salinity change data before and after the salt drainage project is put into operation. The waterlogging reduction rate is calculated based on the soil moisture content change data. The drainage rate of the underground ditch and the drainage rate of the salt drainage shaft are calculated based on the drainage status change data. The drainage status change data may include at least one of the following: cumulative drainage volume of the underground ditch, cumulative drainage volume of the salt drainage shaft, drainage flow rate, water level change, and drainage pressure.

[0070] The specific calculation method for the salt content reduction rate is as follows: in, The rate of salt reduction, The soil salinity parameters of the target area before the operation of the salt drainage project. The soil salinity parameters of the target area at time t when the salt drainage project is running are given. These soil salinity parameters can be obtained by collecting data from soil salinity sensors or by averaging soil salinity data from multiple monitoring points.

[0071] The specific calculation method for waterlogging reduction rate is as follows: in, The waterlogging reduction rate, The soil moisture content parameters for the target area before the salt drainage project is put into operation. The soil moisture content parameter of the target area at time t when the salt removal project is running is given. The soil moisture content parameter can be obtained by collecting soil moisture sensors or by averaging the moisture content data of multiple monitoring depths or multiple monitoring points in the same target area.

[0072] The specific calculation methods for the drainage rate of underground ditches and the drainage rate of salt discharge shafts are as follows: in, For the drainage rate of the culvert, Let t be the cumulative drainage volume of the culvert at time t. This represents the cumulative drainage volume of the underground ditch at the initial stage of the salt drainage project's operation. To guide the discharge rate of the salt drainage shaft, Let t be the cumulative drainage volume of the salt discharge shaft. The cumulative drainage volume of the salt discharge shaft at the initial moment of operation of the salt discharge project; This represents the time interval from the initial moment of operation to time t. The cumulative drainage volume of the underground ditch and the cumulative drainage volume of the salt discharge shaft can be obtained through flow monitoring devices, water level change calculations, or drainage outlet metering devices.

[0073] Based on the salinity reduction rate, waterlogging reduction rate, underground ditch drainage rate, salt drainage shaft discharge rate, and change in the area of ​​salinity accumulation zone, the salt drainage effect evaluation value is calculated: in, This is the evaluation value for the salt removal effect. The rate of salt reduction, The waterlogging reduction rate, For the drainage rate of the culvert, To guide the discharge rate of the salt drainage shaft, and These are the normalized baseline values ​​for the drainage rate of the underground ditch and the drainage rate of the salt discharge shaft, respectively. This represents the rate of reduction in the area of ​​salt accumulation. , , , , The evaluation weights for salinity reduction rate, waterlogging reduction rate, underground ditch drainage rate, salt drainage shaft drainage rate, and salinity accumulation area reduction rate are respectively, all of which are dimensionless non-negative coefficients, and the sum of the five is 1. All of the above evaluation indicators are ratios or dimensionless indicators after normalization. This embodiment sets the weights according to the priority order of salinity reduction, waterlogging reduction, and drainage capacity in the treatment objectives. , , , , The values ​​are 0.35, 0.2, 0.15, 0.15, and 0.15, respectively. The normalized reference value... and It can be determined based on the expected drainage rate of the underground ditch and the salt discharge shaft under the design conditions, the average drainage rate measured during the trial operation, or historical engineering operation data. It is used to convert the drainage rate of the underground ditch and the discharge rate of the salt discharge shaft into a dimensionless index that can be calculated together with other evaluation indicators.

[0074] The reduction rate of the salt accumulation area can be expressed as: in, This represents the rate of reduction in the area of ​​salt accumulation. This represents the area of ​​salt accumulation before the salt drainage project was put into operation. This refers to the area of ​​the salt accumulation zone at time t during the operation of the salt drainage project. The area of ​​the salt accumulation zone can be determined based on the salt accumulation rate distribution calculated from a groundwater salt transport model, or it can be determined based on the area of ​​the monitoring grid where soil salinity data exceeds a preset salinity threshold. The preset salinity threshold is the minimum soil salinity content required to classify the monitoring grid as a salt accumulation zone. It is determined according to the target saline-alkali land soil salinization classification standard or remediation target. In this embodiment, the preset salinity threshold is 8.0 g / kg.

[0075] When the salt removal effect evaluation value is lower than the preset evaluation threshold, or the deviation between the real-time acquired soil salinity change data, soil moisture content change data and the predicted data of the groundwater salt transport model is greater than the corresponding preset deviation threshold, the salt removal project is determined to meet the preset optimization conditions. The preset evaluation threshold is the minimum value required for the salt removal effect evaluation value to reach a qualified treatment state. Historical project samples are divided into valid and invalid samples according to whether the soil salinity and moisture content treatment targets were achieved at the end of the evaluation period. Salt removal effect evaluation values ​​are calculated for each type of sample, and the evaluation value corresponding to the highest discrimination accuracy between the two types of samples is used as the preset evaluation threshold. In this embodiment, the preset evaluation threshold is 0.6. The preset deviation threshold is the maximum allowable relative deviation between the model prediction result and the measured result. It is determined based on the distribution of the predicted relative deviation in the model validation samples, for example, taking the 95th percentile of the relative deviation of the validation samples. In this embodiment, the preset deviation threshold corresponding to the soil salinity change data is 0.2.

[0076] When the preset optimization conditions are met, the area to be optimized is determined based on the monitoring grid corresponding to the deviation between the real-time acquired data and the predicted data of the groundwater salt transport model, and the dominant deviation type is determined based on the soil salinity change data, soil moisture content change data and drainage status change data in the area to be optimized.

[0077] Specifically, the salt reduction deviation can be determined based on the relative difference between the measured and predicted salt changes; the waterlogging reduction deviation can be determined based on the relative difference between the measured and predicted moisture content changes; and the drainage capacity deviation can be determined based on the relative differences between the measured and predicted values ​​of the drainage rates of the underground drainage ditches and the drainage rates of the salt drainage shafts. For example, various deviations can be determined according to the following formula: in, , and These are, respectively, the deviation in salt reduction, the deviation in waterlogging reduction, and the deviation in drainage capacity; and These represent the measured change in salinity and the predicted change in salinity, respectively. and These represent the measured change in moisture content and the predicted change in moisture content, respectively. and These are the measured and predicted values ​​of the drainage rate of the underground drainage ditch, respectively. and These are the measured and predicted values ​​of the salt drainage rate of the vertical well, respectively. and These represent the contribution weights of the drainage rate deviations of the underground drainage ditch and the salt drainage shaft to the overall drainage capacity deviation, respectively. Both are dimensionless, non-negative coefficients, and their sum is 1. The deviations are determined based on the designed drainage rates of the underground drainage ditch and the salt drainage shaft. , ,in, This indicates the design drainage rate of the underground drainage ditch. This indicates the design discharge rate of the salt drainage shaft. In this embodiment, , They are 0.5 and 0.5 respectively. A preset positive number is set to avoid the predicted value being zero.

[0078] The deviations in salt reduction, waterlogging reduction, and drainage capacity are compared, and the type with the largest deviation is determined as the dominant deviation type. When the difference between two or more deviations is less than a preset type difference threshold, the corresponding deviations can be collectively determined as the dominant deviation type, and corresponding adjustment measures are implemented accordingly. The preset type difference threshold is the minimum deviation difference required to determine whether two types of deviations have a significant difference. The threshold is determined based on the background fluctuation range of various deviations under repeated measurement conditions. In this embodiment, the preset type difference threshold is set to 0.05.

[0079] Based on the relationship between the magnitude of the deviation corresponding to the dominant deviation type and the preset grading threshold, the adjustment level corresponding to the region to be optimized is determined. The preset grading threshold includes multiple deviation thresholds that increase sequentially. When the deviation is between two adjacent deviation thresholds, the corresponding adjustment level is determined. Different adjustment levels correspond to different parameter adjustment ranges. For any parameter to be adjusted, its adjustment amount can be determined according to the following formula: in, For parameter adjustment amount, To adjust the level, The preset unit adjustment amount corresponding to this parameter. This is the preset single-adjustment upper limit for the parameter. Therefore, as the adjustment level increases, the parameter adjustment amount increases accordingly, but does not exceed the preset single-adjustment upper limit. The preset unit adjustment amount is the basic adjustment amount that increases or decreases for each adjustment level of the corresponding engineering parameter, determined according to the design specifications of the salt drainage shafts and drainage ditches. The preset single-adjustment upper limit is the maximum allowable adjustment range for the corresponding engineering parameter during one optimization process, determined based on construction safety, engineering bearing capacity, and the requirement to avoid excessive model correction. Corresponding single-adjustment upper limits are set for the depth, number of shafts, drainage capacity, length, number of ditches, and drainage capacity of the salt drainage shafts. For example, level one adjustment corresponds to one preset unit adjustment amount, and level ten adjustment corresponds to ten preset unit adjustment amounts; when ten preset unit adjustment amounts exceed the single-adjustment upper limit, adjustment is performed according to the single-adjustment upper limit.

[0080] When the dominant deviation type is salt reduction deviation, based on the location of the salt accumulation area and the water-salt transport path within the area to be optimized, the drainage capacity of the corresponding salt discharge shafts can be increased, the number of salt discharge shafts can be increased, the location of the salt discharge shafts can be changed, and / or the installation depth of the salt discharge shafts can be increased. Specifically, increasing the drainage capacity of the salt discharge shafts can be achieved by adjusting the drainage channels within the shafts, the pore state of the packing material, or the operating drainage rate.

[0081] When the dominant deviation type is waterlogging reduction deviation, according to the water and salt transport direction in the area to be optimized, the length of the drainage ditch is extended, the connection path of the drainage ditch is changed, the number of drainage ditches is increased, and / or the connection relationship between the drainage ditch and the salt drainage shaft is adjusted, so that the water and salt mixture in the area to be optimized can flow into the salt drainage shaft along the drainage ditch.

[0082] When the dominant deviation type is drainage capacity deviation, the drainage parameters of the corresponding drainage ditch, the drainage parameters of the drainage shaft, and the connectivity between them are adjusted according to the deviation positions of the drainage rate of the underground ditch and the drainage rate of the salt discharge shaft. The drainage parameters of the underground ditch may include the ditch slope, water flow cross-section, or unobstructed status, and the drainage parameters of the salt discharge shaft may include the drainage channel status, packing pore status, or operating drainage volume.

[0083] After the layout plan for the salt drainage project was adjusted, soil salinity change data, soil moisture content data, and drainage status change data were reacquired after a preset evaluation period, and the salt drainage effect evaluation value was recalculated.

[0084] When the recalculated salt drainage effect evaluation value is still lower than the preset evaluation threshold, or the deviation between the re-acquired data and the predicted data of the groundwater salt transport model is still greater than the preset deviation threshold, the adjustment level is increased and the salt drainage project layout scheme is adjusted again; when the recalculated salt drainage effect evaluation value reaches the preset evaluation threshold and the deviation is not greater than the preset deviation threshold, the adjusted salt drainage project layout scheme is maintained.

[0085] To verify the salt drainage effect after the adjustment of the salt drainage project layout, soil salinity data for each monitoring grid was acquired after a preset evaluation period following the completion of one adjustment. The adjusted soil salinity data was then compared with the corresponding monitoring grid's soil salinity data before the adjustment. The results are as follows: Figure 3 As shown.

[0086] Depend on Figure 3 It can be seen that the soil salinity of monitoring grids G01 to G10 after the optimization of the salt drainage project layout scheme is lower than that before optimization. Before optimization, the soil salinity of each monitoring grid was approximately 8.0–12.8 g / kg; after the preset evaluation period, the optimized soil salinity was approximately 5.2–9.2 g / kg. This indicates that adjusting the salt drainage shafts and drainage ditches according to the dominant deviation type and adjustment level can promote the drainage and reduction of salt in the area to be optimized.

[0087] For monitoring grids where soil salinity remains relatively high after optimization, such as G02, G06, and G08, further assessment is conducted based on the recalculated salt drainage effect evaluation values ​​and the deviation between measured data and groundwater salt transport model predictions to determine whether the preset optimization conditions are still met. If the preset optimization conditions are still met, the adjustment level for the corresponding area to be optimized is increased, and the drainage capacity, number, location, or depth of the salt drainage shafts are adjusted again, and / or the length, number, connection path, and connectivity of the drainage ditches with the salt drainage shafts are adjusted. If the preset optimization conditions are no longer met, the adjusted salt drainage engineering layout scheme is maintained.

[0088] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0089] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0090] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0091] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A smart monitoring method for improving saline-alkali land, characterized in that, The specific steps include: The target saline-alkali land is divided into multiple monitoring grids. Monitoring points are set up in each monitoring grid. At the monitoring points, soil salinity data, soil moisture content data, and soil pH data of different soil depths are obtained along the vertical direction at preset depth intervals. Groundwater level data corresponding to each monitoring grid is also obtained to construct groundwater level distribution data. Based on the salinity, moisture content, and pH data of soil layers at different depths, the vertical gradients of salinity, moisture content, and pH are calculated respectively. Based on the abrupt changes in moisture content, abrupt changes in salinity and pH gradients, and infiltration response delays, key underground structures are identified, and their depth and thickness are determined. Based on the distribution relationship of depth and thickness of underground key structures in each monitoring grid and between adjacent monitoring grids, the depth characteristics and spatial distribution characteristics of underground key structures are determined. In combination with groundwater level distribution data, a groundwater salt transport model is constructed. The spatial distribution characteristics are used as the boundary constraints of the groundwater salt transport model to determine the water and salt transport paths and salt accumulation areas in the target saline-alkali land. Based on the water and salt transport paths and salt accumulation areas, candidate areas for salt drainage shafts are determined. Within these candidate areas, the location and depth of the salt drainage shafts are determined, and the connection paths of the underground drainage ditches are generated to form a layout plan for the salt drainage project. A salt drainage project is established based on the layout plan of the salt drainage project. During the operation of the salt drainage project, data on changes in soil salinity, soil moisture content, and drainage status are acquired in real time and compared with the predicted data. When the deviation meets the preset optimization conditions, the area to be optimized is determined. Based on the magnitude of the deviation between the changed data and the predicted data within the area to be optimized, and in conjunction with the preset grading threshold, the adjustment level corresponding to the area to be optimized is determined. The layout parameters of the salt drainage shaft, the connection parameters of the drainage culvert, or the connection relationship between the two are adjusted according to the adjustment level. If the evaluation requirements are still not met after the evaluation cycle, the adjustment level is increased and adjusted again.

2. The intelligent monitoring method for saline-alkali land improvement according to claim 1, characterized in that: The identification of key underground structures specifically includes: When the average water content of the adjacent soil layers above a certain depth range is higher than the average water content of the adjacent soil layers below, and the difference between the two is greater than the first difference threshold, the depth range is identified as the first underground critical structure. When the vertical salt gradient within a certain depth range is greater than the first gradient threshold, and the absolute value of the vertical pH gradient within that depth range is greater than the first pH gradient threshold, that depth range is identified as the second key underground structure. When the infiltration response delay time corresponding to a certain depth interval is greater than the preset delay time threshold, and the rate of change of water content in the depth interval is less than the first change threshold, the depth interval is identified as the third underground key structure. If multiple structural criteria are met simultaneously within the same depth range, the unique structural category is determined in the order that the first underground key structure takes precedence over the second underground key structure, and the second underground key structure takes precedence over the third underground key structure.

3. The intelligent monitoring method for saline-alkali land improvement according to claim 1, characterized in that: The determination of the boundary constraints includes: Record the upper boundary depth, lower boundary depth, thickness, and corresponding planar position information of the underground key structure in each monitoring grid. Based on the planar position information, perform spatial interpolation on the upper boundary depth, lower boundary depth, and thickness of the underground key structure in each monitoring grid to obtain the three-dimensional continuous distribution result of the underground key structure. Based on the three-dimensional continuous distribution results, the continuous, discontinuous, and weak areas of the underground key structures are determined. The weak area is the area where the thickness of the underground key structure is less than a preset thickness threshold, and the discontinuous area is the area where there are discontinuous gaps between adjacent underground key structures. The continuous region serves as a water and salt transport hindrance region, while the discontinuous and weak regions serve as potential water and salt transport channels. Together, the water and salt transport hindrance regions and potential water and salt transport channels serve as boundary constraints for the groundwater and salt transport model.

4. The intelligent monitoring method for saline-alkali land improvement according to claim 3, characterized in that: The specific methods for determining the water-salt transport pathways and salt accumulation areas in the target saline-alkali land include: Based on the three-dimensional continuous distribution results, the target saline-alkali land is divided into multiple water and salt transport calculation units; Based on the soil salinity data, soil moisture content data, soil pH data, groundwater level data, and identification results of key underground structures corresponding to each water and salt transport calculation unit, the salinity parameters, moisture content parameters, pH parameters, groundwater level parameters, and permeability barrier parameters of each water and salt transport calculation unit are determined. The permeability barrier parameters are determined based on the water content vertical gradient, infiltration response delay time, and thickness of the underground key structure corresponding to the water-salt transport calculation unit. The water and salt transport flux between adjacent water and salt transport calculation units is calculated based on the differences in water content, salinity, and groundwater level between adjacent water and salt transport calculation units, and corrected using the permeability barrier parameters of the corresponding water and salt transport calculation units. Based on the water and salt transport flux, the direction of water and salt transport, the magnitude of the flux, and the rate of salt accumulation are determined, thereby obtaining the water and salt transport path and salt accumulation area in the target saline-alkali land. Connect multiple adjacent water and salt transport calculation units whose transport directions are continuous and whose fluxes meet the preset transport conditions to form a water and salt transport path. A water-salt transport calculation unit whose salt accumulation rate meets a preset accumulation condition is defined as a salt accumulation unit, and the area where the salt accumulation unit is located is defined as a salt accumulation area.

5. The intelligent monitoring method for improving saline-alkali land according to claim 4, characterized in that: The proposed layout scheme for the salt drainage project specifically includes: Multiple water-salt transport calculation units with water-salt transport fluxes greater than a preset flux threshold and pointing to the same region are defined as water-salt collection zones. Areas with a salt accumulation rate greater than a preset accumulation threshold are designated as priority salt removal zones; The area that simultaneously belongs to the water-salt collection area and the priority salt discharge area is identified as a candidate area for salt discharge shafts; Within the candidate area for salt drainage shafts, the location with the highest salt accumulation rate, the intersection of water and salt transport paths, or the center of alkali spots are selected as the location for setting up the salt drainage shafts. The installation depth of the salt drainage shaft is determined based on the lower boundary depth of the underground key structure, so that the bottom of the salt drainage shaft passes through the identified underground key structure and extends to a predetermined distance below the underground key structure. A drainage ditch connection path is generated along the dominant direction of the water and salt transport path, so that the drainage ditch connects the salt accumulation area with the salt discharge shaft, or connects two adjacent salt discharge shafts.

6. The intelligent monitoring method for improving saline-alkali land according to claim 1, characterized in that: The determination of the region to be optimized specifically includes: The salt reduction rate is calculated based on soil salinity change data before and after the salt drainage project, the waterlogging reduction rate is calculated based on soil moisture content change data, and the drainage rate of underground ditches and salt drainage shafts is calculated based on drainage status data. Combined with the change in the area of ​​salt accumulation zone, the salt drainage effect evaluation value is calculated. When the salt drainage effect evaluation value is lower than the preset evaluation threshold, or when the deviation between the real-time acquired soil salinity change data, soil moisture content change data and the predicted data of the groundwater salt transport model is greater than the preset deviation threshold, the salt drainage project is determined to meet the preset optimization conditions, and the corresponding area is identified as the area to be optimized.

7. The intelligent monitoring method for saline-alkali land improvement according to claim 6, characterized in that: After meeting the preset optimization conditions, specifically including: Based on the monitoring grid corresponding to the deviation between the real-time acquired data and the predicted data of the groundwater salt transport model, the area to be optimized is determined, and based on the soil salinity change data, soil moisture content change data and drainage status change data in the area to be optimized, the dominant deviation type is determined. Based on the relationship between the deviation magnitude corresponding to the dominant deviation type and the preset grading threshold, the adjustment level corresponding to the region to be optimized is determined, and the adjustment range of each adjustment parameter increases as the adjustment level increases, but does not exceed the corresponding preset single adjustment limit. When the dominant deviation type is salt reduction deviation, the salt collection area and the water and salt transport path in the area to be optimized are used to increase the drainage capacity of the corresponding salt discharge shaft, increase the number of salt discharge shafts, change the setting position of the salt discharge shafts and / or increase the setting depth of the salt discharge shafts. When the dominant deviation type is waterlogging reduction deviation, the length of the drainage ditch is extended, the connection path of the drainage ditch is changed, the number of drainage ditches is increased, and / or the connection relationship between the drainage ditch and the salt drainage shaft is adjusted according to the water and salt transport direction in the area to be optimized. When the dominant deviation type is drainage capacity deviation, the drainage parameters of the corresponding drainage ditch, the drainage parameters of the salt discharge shaft, and the connection relationship between the two are adjusted according to the deviation position of the drainage rate of the underground ditch and the drainage rate of the salt discharge shaft. After the layout plan of the salt drainage project was adjusted, the soil salinity change data, soil moisture content data and drainage status change data were re-acquired after a preset evaluation cycle, and the salt drainage effect evaluation value was recalculated. When the recalculated salt drainage effect evaluation value is still lower than the preset evaluation threshold, or the deviation between the re-acquired data and the predicted data of the groundwater salt transport model is still greater than the preset deviation threshold, the adjustment level is increased and the salt drainage project layout scheme is adjusted again; when the recalculated salt drainage effect evaluation value reaches the preset evaluation threshold and the deviation is not greater than the preset deviation threshold, the adjusted salt drainage project layout scheme is maintained.

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