Microtopography reconstruction method for loess area power grid project

Abstract

The invention relates to the technical field of terrain reconstruction, in particular to a micro-terrain reconstruction method for a loess area power grid project, and the method comprises the steps: collecting parameters in a multi-dimensional manner; determining an undetermined area; determining a candidate area; determining a target area; constructing a structure; and optimizing and adjusting. According to the invention, through joint analysis of rainfall duration, instantaneous rainfall intensity and permeability coefficient, a synergistic change rule among soil volume moisture content, porosity and volume weight in a wetting-compacting process is utilized, and superposition effects of surface roughness and root depth distribution on water flow retardation, infiltration path extension and soil fixing capability are combined; the transformation depth is adaptively determined based on the root system depth and the regional feature matching degree, meanwhile, after a transformation structure is put into use, the infiltration threshold value and the transformation depth coefficient are periodically corrected through combined monitoring, and the transformation depth is obtained. The problems of slow vegetation recovery and unstable effect caused by insufficient utilization of soil moisture and single microtopography function are effectively solved.

Description

Technical Field

[0001] This invention relates to the field of terrain modification technology, and in particular to a micro-terrain modification method for power grid engineering in loess areas. Background Technology

[0002] With the accelerated development of ecological construction and infrastructure in the northern plateau region, the problems of insufficient soil moisture, severe erosion, and limited vegetation growth in the areas disturbed by power grid construction are becoming increasingly prominent. The poor soil, limited rainfall, and high evaporation make it difficult for plant roots to absorb water and slow their growth. At the same time, although the thick soil layer has the potential to store water, it is difficult to utilize it effectively, thus affecting the restoration of the ecological environment and the safety of the project. It is urgent to solve the challenges of water regulation and insufficient soil water storage capacity.

[0003] Chinese Patent Application Publication No. CN102405813A discloses a method for afforestation on steep slopes with micro-topography in the Loess Plateau region. The method includes: first, classifying the afforestation site conditions of the loess slope and determining the corresponding main vegetation types based on the site conditions and the difficulty of vegetation restoration and reconstruction; second, investigating the quantity and characteristics of local micro-topography within slopes with the same site conditions, and determining the corresponding woody plants within the micro-topography based on different habitat conditions; and finally, determining the proportion and location of tree or shrub species and the plant community structure configuration based on the site type and micro-topography. Tree planting is carried out in the loess slope; the micro-topography of the loess slope refers to one or more of the following local landforms on the loess slope: shallow gullies, gullies, collapses, gentle terraces, and steep embankments; shallow gullies and gullies refer to two primary states in the development process of loess erosion gullies on the loess slope, which are formed by the erosion and downcutting of concentrated streams during the convergence process of surface runoff formed by rainfall; collapses refer to the depressions or depressions formed by the headward erosion of concentrated streams on the loess slope; gentle terraces refer to the flat sections of the loess slope where the local slope is significantly less than the average slope of the entire slope; steep embankments refer to the steep sections of the loess slope where the local slope is significantly greater than the average slope of the entire slope.

[0004] Therefore, the proposed afforestation method for steep slopes with micro-topography in the Loess Plateau has the following problems: This method determines vegetation types and locations solely based on slope type and micro-topographic distribution, without systematically analyzing soil infiltration capacity, water storage potential, and root water absorption requirements. This makes it difficult to fully utilize the water storage capacity of the thick soil layer, limiting vegetation growth under drought conditions. Furthermore, the micro-topographic features defined by this method, such as shallow ditches, gullies, collapses, gentle slopes, and steep embankments, serve only as planting references and lack comprehensive regulatory effects on soil water storage, runoff control, and local water balance, failing to effectively improve soil moisture distribution and prevent erosion. Finally, this method relies heavily on empirical matching of site conditions and vegetation types, without considering rainfall, soil physical properties, and the coupling relationship between micro-topography and vegetation growth. This results in vegetation restoration failing to quickly meet acceptance standards, and long-term effects being significantly affected by rainfall fluctuations and soil characteristics. Summary of the Invention

[0005] Therefore, this invention provides a micro-topography modification method for power grid engineering in the Loess Plateau region, which overcomes the problems of slow vegetation recovery and unstable effects caused by insufficient soil moisture utilization and single micro-topography function in the prior art by optimizing soil water storage structure and adjusting micro-topography.

[0006] To achieve the above objectives, the present invention provides a micro-topography modification method for power grid engineering in loess areas, comprising: Real-time acquisition of total rainfall duration, instantaneous rainfall intensity, surface runoff, soil volumetric water content, soil bulk density, soil porosity, permeability coefficient, surface roughness, and root depth distribution of target vegetation communities within the power grid engineering disturbance area. Based on the total rainfall duration, the instantaneous rainfall intensity, and the permeability coefficient, several undetermined areas are determined from all the monitored areas based on a preset infiltration threshold; Several candidate regions are determined based on the synchronous change trends of the soil volumetric water content, soil porosity, and soil bulk density in each of the undetermined regions. Based on the distribution characteristics of the surface roughness and root depth distribution of each candidate region, several target regions are determined, and the micro-topography modification depth corresponding to each target region is determined based on the preset depth determination coefficient and the root depth distribution of each target region. Based on the micro-topography modification depth, a soil water storage structure is constructed in the target area using biodegradable materials. The preset infiltration threshold is adjusted based on the soil volumetric water content and surface runoff of each target area within a preset optimization period after the soil water storage structure is constructed, as well as the location change characteristics of all target areas. Alternatively, the preset depth determination coefficient can be adjusted.

[0007] Furthermore, the process of determining several undetermined areas based on the total rainfall duration, the instantaneous rainfall intensity, and the permeability coefficient, using a preset infiltration threshold, includes: The impact coefficient of previous rainfall is calculated based on the sum of the total rainfall duration within the preset historical judgment period. The potential value of the runoff coefficient is calculated based on the previous rainfall impact coefficient, the instantaneous rainfall intensity in each of the monitoring areas, and the permeability coefficient; Several undetermined areas are determined based on the potential value of the runoff coefficient and the preset infiltration threshold.

[0008] Furthermore, the process of determining several undetermined areas based on the potential runoff coefficient and the preset infiltration threshold includes: When the potential value of the runoff coefficient is greater than the preset infiltration threshold, the monitoring area is determined as the undetermined area, thereby identifying several undetermined areas.

[0009] Furthermore, the process of determining several candidate regions based on the synchronous change trends of the soil volumetric water content, soil porosity, and soil bulk density in each of the undetermined regions includes: When determining several undetermined areas, the water storage conversion degree is determined based on the total soil volume moisture content and total soil porosity of each undetermined area within the next preset candidate determination time. The bulk density influence is determined based on the total volumetric moisture content and total bulk density of all soils in each candidate region within the same preset candidate determination time period. Several candidate regions are determined based on the water storage conversion degree and the bulk density influence degree.

[0010] Furthermore, the process of determining several candidate regions based on the water storage conversion degree and the bulk density influence degree includes: When the water storage conversion degree is less than or equal to a preset conversion degree threshold, or the bulk density influence degree is greater than or equal to a preset influence threshold, the corresponding undetermined region is determined as the candidate region, thereby determining several candidate regions.

[0011] Furthermore, the process of determining several target regions based on the distribution characteristics of the surface roughness and root depth distribution of each candidate region includes: Calculate the average surface roughness of all the candidate regions to obtain the average roughness; Calculate the average root depth distribution of all candidate regions to obtain the average depth distribution. The region matching degree is calculated based on the surface roughness, root depth distribution, average roughness, and average depth distribution of each candidate region. Several target regions are determined based on the region matching degree.

[0012] Furthermore, the process of determining several target regions based on the region matching degree includes: When the region matching degree is greater than a preset matching degree threshold, the candidate region is determined to be the target region, thereby identifying several target regions.

[0013] Furthermore, the process of determining the micro-topography modification depth corresponding to each target area based on the preset depth determination coefficient and the root depth distribution of each target area includes: The micro-topography modification depth is calculated based on the preset depth determination coefficient, the root system depth distribution degree, and the regional matching degree.

[0014] Furthermore, the process of adjusting the preset infiltration threshold based on the soil volumetric water content and surface runoff of each target area within a preset optimization period after the soil water storage structure is constructed, and the location change characteristics of all target areas, includes: The preset optimization cycle is divided into several time periods of equal length to obtain several adjustment judgment durations; Obtain the target region that has been identified as the target region at least a preset number of times within the preset optimization period, so as to obtain the adjustment determination region; The average values ​​of the soil volumetric water content and the surface runoff in the adjustment determination area are calculated respectively to obtain the average water content and average runoff. The trend coefficients of the mean water content and the mean flow rate within the preset optimization period are calculated by linear regression analysis to obtain the water content trend coefficient and the flow rate trend coefficient. Based on the set of target regions for all adjustment judgment durations, calculate the Jaccard distance between each pair and take the average value to obtain the spatial distribution variability; A first determination result is obtained when the water content trend coefficient is greater than a preset water content trend threshold and the flow rate trend coefficient is less than a preset flow rate trend threshold; A second determination result is obtained when the water content trend coefficient is less than or equal to a preset water content trend threshold, or when the flow rate trend coefficient is greater than or equal to a preset flow rate trend threshold. A third determination result is obtained when the spatial distribution variability is less than or equal to a preset variability threshold. When the spatial distribution variability is greater than a preset variability threshold, a fourth determination result is obtained. When the first determination result and the third determination result are obtained, the preset infiltration threshold is reduced by adjusting the preset threshold index.

[0015] Furthermore, the process of adjusting the preset depth determination coefficient includes: When obtaining the second determination result and the fourth determination result, the preset depth determination coefficient is reduced according to the relative deviation between the spatial distribution variability and the preset variability threshold.

[0016] Compared with existing technologies, the beneficial effects of this invention are as follows: by jointly analyzing rainfall duration, instantaneous rainfall intensity, and permeability coefficient, it achieves dynamic determination of surface infiltration and potential runoff formation conditions, enabling the identification of the target area to reflect the actual impact of rainfall on soil infiltration capacity; further, by utilizing the synergistic change law between soil volumetric water content, porosity, and bulk density during the wetting-compaction process, it screens out candidate areas with structures more prone to water storage attenuation or runoff surges; subsequently, by combining the superimposed effects of surface roughness and root depth distribution on water flow obstruction, infiltration path extension, and soil fixation capacity, it determines target areas more suitable for micro-topography adjustment, and adaptively determines the modification depth based on the degree of matching between root depth and regional characteristics, making the micro-topography construction more in line with the needs of vegetation soil stabilization and water redistribution; at the same time, after the modified structure is put into use, by jointly monitoring water content trends, runoff changes, and the spatial distribution stability of the target area, it periodically corrects the infiltration threshold and modification depth coefficient, enabling the system to continuously adapt to the characteristics of strong rainfall randomness, easy soil collapse, and large spatial heterogeneity in the Loess Plateau. Through the above multi-parameter progressive analysis and dynamic feedback adjustment, this invention achieves accurate identification of micro-topography transformation areas, adaptive determination of transformation scale, and continuous optimization after operation, effectively solving the problem of slow vegetation recovery and unstable results caused by insufficient soil moisture utilization and single micro-topography function.

[0017] Furthermore, by converting the sustained impact of recent cumulative rainfall on soil saturation into an impact coefficient of previous rainfall, and combining this with the proportional relationship between instantaneous rainfall intensity and permeability coefficient that determines slope runoff velocity, a potential runoff coefficient value reflecting actual runoff pressure is constructed. This allows for the early identification of runoff risk areas before infiltration capacity significantly declines. This approach not only more accurately distinguishes between rainfall intensity-dominated and soil permeability-dominated areas but also avoids misjudgments based solely on instantaneous rainfall intensity or a single permeability parameter. The identification results more closely reflect the true coupling relationship between soil moisture content, infiltration capacity, and rainfall dynamics, improving the effectiveness and foresight of area selection.

[0018] Furthermore, by comparing the potential runoff coefficient with a preset infiltration threshold, areas that may generate significant runoff under the combined effects of rainfall intensity, soil permeability, and previous rainfall accumulation can be accurately identified. When the potential runoff coefficient exceeds the threshold, it indicates that the soil infiltration capacity in that area is relatively insufficient, making it prone to surface runoff or water imbalance, and thus it is identified as a pending area. This identification process effectively links hydrological factors with soil physical properties, making the selection of micro-topography modification targets more scientific and reasonable, and improving water regulation efficiency and soil water storage potential.

[0019] Furthermore, by analyzing the synchronous variation trends of soil volumetric water content, porosity, and bulk density within the target area, the soil's water storage capacity and the impact of soil structure on water regulation can be quantified. The water conversion ratio reflects the degree of matching between soil pore structure and water changes, while the bulk density influence reveals the limiting effect of soil compaction on water infiltration and storage. By considering both indicators simultaneously, candidate areas with good water storage capacity and minimal influence from bulk density under specific rainfall conditions can be scientifically selected. This provides precise target selection for subsequent micro-topography modification, improving water use efficiency and soil moisture balance.

[0020] Furthermore, by comprehensively considering the water storage conversion degree and the influence of bulk density, this embodiment can effectively screen out areas that are prone to insufficient water accumulation or limited soil carrying capacity under the influence of rainfall and soil physical properties. These areas can then be used as candidate areas for subsequent micro-topography modification to ensure that soil moisture is maintained in accordance with the soil structure state, thereby improving the targeting of modification and the effect of water regulation.

[0021] Furthermore, by calculating the average surface roughness and root depth distribution of candidate areas, and combining this with the actual values ​​of each area to calculate the regional matching degree, the target areas most suitable for micro-topography modification based on topographic conditions and vegetation characteristics can be scientifically identified. Surface roughness affects water flow velocity and soil runoff formation, while root depth distribution reflects the vegetation's ability to absorb soil moisture. A comprehensive evaluation of both can accurately screen areas that are conducive to both water storage and suitable for vegetation growth, thereby improving the soil and water conservation effect and ecological restoration efficiency of micro-topography modification.

[0022] Furthermore, by comparing the regional matching degree with a preset matching degree threshold, candidate areas with the most coordinated surface roughness and root depth distribution can be effectively screened as target areas. This not only ensures the optimal performance of the micro-topography modification area in terms of water retention and runoff regulation, but also fully considers the combination of vegetation root system's ability to absorb soil moisture and topographic conditions, thereby improving water storage efficiency, mitigating soil erosion, and promoting the stable restoration of the ecosystem.

[0023] Furthermore, by combining the preset depth determination coefficient, the root depth distribution of the target area, and the regional matching degree, this method can accurately calculate the required micro-topography modification depth for each target area, so that the soil water storage structure can meet the root water absorption needs while also taking into account the surface water regulation, thereby improving soil water use efficiency and vegetation growth adaptability, and achieving dynamic coordination between micro-topography modification depth and vegetation characteristics and surface conditions.

[0024] Furthermore, by systematically analyzing the changes in soil volumetric water content, surface runoff, and spatial distribution in the target area after the soil water storage structure is constructed within a preset optimization period, the trends and spatial uniformity of water storage and runoff response in each region can be dynamically assessed. By calculating the trend coefficients of mean water content and mean flow rate using linear regression, and combining this with Jaccard distance between regions to measure spatial distribution variability, the actual effectiveness of water regulation in each target area can be accurately determined. Under conditions of increasing water content, decreasing flow rate, and uniform spatial distribution, the infiltration threshold is automatically and appropriately reduced to optimize the control of water infiltration, thereby ensuring the continuous accumulation and rational distribution of soil moisture after micro-topography modification, improving water storage efficiency, and preventing localized runoff excess or water loss.

[0025] Furthermore, by evaluating the relative difference between the spatial distribution variability of the target area and the preset threshold in real time during the optimization period, the depth determination coefficient is dynamically adjusted. When the distribution of the target area fluctuates significantly or deviates from the expected distribution, the depth coefficient is automatically reduced, so that the depth of micro-topography modification changes synchronously with regional conditions and distribution characteristics. This coordinates the relationship between soil moisture storage capacity, surface runoff and vegetation root growth depth, achieving a consistent match between the modification depth and soil, vegetation and hydrological characteristics, and improving the efficiency and stability of the water storage structure. Attached Figure Description

[0026] Figure 1 This is a flowchart of the micro-topography modification method used in the power grid project in the Loess Plateau region according to this embodiment; Figure 2 This embodiment defines the decision logic diagram for determining the region to be determined. Figure 3 This embodiment defines the decision logic for determining candidate regions. Figure 4 The determination logic diagram for identifying the target region in this embodiment is shown. Detailed Implementation

[0027] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0028] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0029] Please see Figure 1The diagram shows a flowchart of a micro-topography modification method for a power grid project in the Loess Plateau region, as shown in this embodiment. This embodiment provides a micro-topography modification method for a power grid project in the Loess Plateau region, including: real-time acquisition of the total rainfall duration, instantaneous rainfall intensity, surface runoff, soil volumetric water content, soil bulk density, soil porosity, permeability coefficient, surface roughness, and root depth distribution of the target vegetation community within the disturbance zone of the power grid project; determining several undetermined areas from all the monitored areas based on the total rainfall duration, instantaneous rainfall intensity, and permeability coefficient, using a preset infiltration threshold; and determining the undetermined areas based on the soil volumetric water content and soil porosity, surface roughness, and root depth distribution of the target vegetation community. The synchronous change trend of soil bulk density determines several candidate areas; based on the distribution characteristics of surface roughness and root depth distribution of each candidate area, several target areas are determined, and the micro-topography modification depth corresponding to each target area is determined based on the preset depth determination coefficient and the root depth distribution of each target area; based on the micro-topography modification depth, biodegradable materials are used to construct soil water storage structures in the target areas, and the preset infiltration threshold or the preset depth determination coefficient is adjusted based on the soil volumetric water content and surface runoff of each target area and the location change characteristics of all target areas within the preset optimization period after the construction of the soil water storage structure.

[0030] In this embodiment, the construction and disturbance area of ​​the power grid project in the Loess Plateau refers to the surface area involved in operations such as tower foundation excavation, line construction, and construction access road laying in the Loess Plateau region, as well as the surrounding area where the soil structure is broken, compacted, or cut due to processes such as mechanical compaction, foundation pit excavation and backfilling, vegetation removal, and access road construction. This area is usually characterized by a decrease in the original vegetation coverage, weakened root fixation capacity, altered surface runoff paths, and significant fluctuations in soil porosity, permeability, and water retention capacity. It is prone to abnormal water and soil responses such as increased runoff, insufficient infiltration, local erosion, or collapse under rainfall conditions. This area is the core target for real-time monitoring and micro-topographic control in this method. Construction activities will change the original surface morphology and soil structure, causing changes in local infiltration capacity, runoff formation conditions, and the hydraulic environment of the vegetation root zone. Therefore, it is necessary to conduct real-time integrated hydrological-soil-vegetation monitoring in the disturbance area. In practice, the total rainfall duration and instantaneous rainfall intensity in each monitoring area are collected in real time by rain gauges and optical rain intensity meters deployed around the tower foundations and slope areas; surface runoff is calculated using open channel flow meters or miniature flow flumes based on pressure level sensors located at the runoff confluence; soil volumetric water content is continuously measured using soil time-domain reflectometry sensors installed at different burial depths; soil bulk density and soil porosity are estimated in real time using embedded soil mechanical property probes deployed on-site or using gravity-based undisturbed soil sampling combined with embedded micro-compaction monitoring modules; permeability coefficient is calculated using an automatic infiltration loop instrument under short-term quantitative water replenishment or a groundwater dynamic monitoring unit based on a humidity gradient inversion algorithm; surface roughness is calculated by reconstructing the surface micro-topography using a laser scanner or structured light camera and then calculating the roughness index; and the depth distribution of vegetation roots is obtained by forming depth distribution curves using resistivity-capacitance composite root growth monitoring probes deployed in the vegetation root zone or by periodic shallow scanning of ground-based radar. This embodiment achieves complete acquisition of key parameters such as rainfall process, surface runoff formation, soil moisture dynamics, soil mechanical state, and vegetation root structure in the disturbed area through the coordinated deployment and real-time acquisition of the above-mentioned multi-source sensors.

[0031] The preset infiltration threshold is a reference parameter used to determine whether there is a risk of insufficient infiltration capacity in the monitored area. It depends on the permeability coefficient range of typical soils in the Loess region, the distribution of historical rainfall intensity, and the regional average slope runoff characteristics, and is usually set between 0.6 and 1.8. Within the dimensionless interval, this embodiment sets it to 1.0, which can identify runoff-sensitive areas early and improve the accuracy of screening areas to be determined; the preset depth determination coefficient is a trade-off coefficient used to determine the micro-topography modification depth based on the root depth distribution. It depends on the root development characteristics of the target vegetation community, the structural strength of the loess layer, and the optimal burial depth requirements of the biodegradable water storage structure. It is usually set in the range of 0.4 to 0.9. In this embodiment, it is set to 0.6, which can make the modification depth more closely match the water demand layer of the root zone and improve the actual water replenishment efficiency of the water storage structure; the preset optimization period is a monitoring period used to evaluate the effect of soil water storage structure and adjust threshold parameters. It depends on the seasonal rainfall rhythm of the loess area, the root growth cycle of vegetation, and the lag characteristics of soil moisture content response. It is usually set in the range of 20 to 60 days. In this embodiment, it is set to 30 days, which can ensure data stability while timely feedback of modification effect and provide a reliable basis for threshold update.

[0032] By jointly analyzing rainfall duration, instantaneous rainfall intensity, and permeability coefficient, the system dynamically determines the conditions for surface infiltration and potential runoff formation, enabling the identification of potential areas to reflect the actual impact of rainfall processes on soil infiltration capacity. Furthermore, by utilizing the synergistic changes in soil volumetric water content, porosity, and bulk density during the wetting-compaction process, candidate areas with structures more prone to water storage depletion or runoff surges are screened. Subsequently, by combining the combined effects of surface roughness and root depth distribution on water flow obstruction, infiltration path extension, and soil fixation capacity, target areas more suitable for micro-topographic adjustment are identified. The modification depth is adaptively determined based on root depth and the degree of matching with regional characteristics, making micro-topographic construction more aligned with the needs of vegetation soil stabilization and water redistribution. Simultaneously, after the modified structure is put into use, the infiltration threshold and modification depth coefficient are periodically corrected through joint monitoring of water content trends, runoff changes, and the spatial distribution stability of the target area, enabling the system to continuously adapt to the characteristics of strong rainfall randomness, easy soil collapse, and high spatial heterogeneity in the Loess Plateau. Through the above multi-parameter progressive analysis and dynamic feedback adjustment, this invention achieves accurate identification of micro-topography transformation areas, adaptive determination of transformation scale, and continuous optimization after operation, effectively solving the problem of slow vegetation recovery and unstable results caused by insufficient soil moisture utilization and single micro-topography function.

[0033] Specifically, the process of determining several undetermined areas based on the total rainfall duration, the instantaneous rainfall intensity, and the permeability coefficient, and using a preset infiltration threshold, includes: calculating the previous rainfall impact coefficient based on the sum of all the total rainfall durations within a preset historical judgment period, where λ = 1 + γ × (T' / T0), λ is the previous rainfall impact coefficient, γ is a preset empirical attenuation coefficient, T' is the sum of all the total rainfall durations within a preset historical judgment period, and T0 is the preset historical judgment period; calculating the potential value of the runoff coefficient based on the previous rainfall impact coefficient, the instantaneous rainfall intensity of each monitoring area, and the permeability coefficient, where R = λ × (P / K), R is the potential value of the runoff coefficient, P is the instantaneous rainfall intensity, and K is the permeability coefficient; and determining several undetermined areas based on the potential value of the runoff coefficient and the preset infiltration threshold.

[0034] The preset historical judgment period is a time window used to calculate the cumulative impact of previous rainfall. It depends on the soil moisture response rate and rainfall frequency in the target area and is usually set between 1 and 7 days. In this embodiment, it is set to 3 days, which can reflect the cumulative effect of recent rainfall on soil moisture content. The preset empirical attenuation coefficient is used to adjust the ratio of the attenuation of the impact of previous rainfall over time. It depends on the soil type, slope and vegetation cover and is usually set between 0.1 and 0.5. In this embodiment, it is set to 0.3, which can reasonably adjust the degree of impact of historical rainfall on the current runoff potential.

[0035] By converting the sustained impact of recent cumulative rainfall on soil saturation into an impact coefficient of previous rainfall, and combining this with the proportional relationship between instantaneous rainfall intensity and permeability coefficient that determines slope runoff velocity, a potential runoff coefficient value reflecting actual runoff pressure is constructed. This allows for the early identification of runoff risk areas before infiltration capacity significantly declines. This approach not only more accurately distinguishes between rainfall intensity-driven and soil permeability-driven areas for potential identification, but also avoids misjudgments based solely on instantaneous rainfall intensity or a single permeability parameter. The identification results more closely reflect the true coupling relationship between soil moisture state, infiltration capacity, and rainfall dynamics, improving the effectiveness and foresight of potential area screening.

[0036] Please see Figure 2 As shown, it is the determination logic diagram for determining the undetermined area in this embodiment. In this embodiment, the process of determining several undetermined areas based on the potential value of the runoff coefficient and the preset infiltration threshold includes: when the potential value of the runoff coefficient is greater than the preset infiltration threshold, the monitoring area is determined as the undetermined area, so as to determine several undetermined areas.

[0037] By comparing the potential runoff coefficient with a preset infiltration threshold, areas that may generate significant runoff under the combined effects of rainfall intensity, soil permeability, and previous rainfall accumulation can be accurately identified. When the potential runoff coefficient exceeds the threshold, it indicates that the soil infiltration capacity in that area is relatively insufficient, making it prone to surface runoff or water imbalance, and thus it is identified as a pending area. This identification process effectively links hydrological factors with soil physical properties, making the selection of micro-topography modification targets more scientific and reasonable, and improving water regulation efficiency and soil water storage potential.

[0038] Specifically, the process of determining several candidate regions based on the synchronous change trends of the soil volumetric moisture content, soil porosity, and soil bulk density of each of the candidate regions includes: when determining several candidate regions, determining the water storage conversion degree based on the total soil volumetric moisture content and total soil porosity of each candidate region within the next preset candidate determination time period, wherein the process of determining the water storage conversion degree includes: normalizing the total soil volumetric moisture content and the total soil volumetric moisture content using the maximum-minimum normalization method to obtain a normalized moisture content dataset and a normalized porosity dataset, respectively, and calculating... Calculate the Pearson correlation coefficient between the water content normalized dataset and the porosity normalized dataset to obtain the water storage conversion degree; determine the bulk density influence degree based on the total soil volumetric water content and total soil bulk density of each candidate area within the same preset candidate determination time period, wherein the process of determining the bulk density influence degree includes: normalizing the total soil bulk density using the maximum-minimum normalization method to obtain the bulk density normalized dataset, and calculating the Pearson correlation coefficient between the water content normalized dataset and the bulk density normalized dataset to obtain the bulk density influence degree; determine several candidate areas based on the water storage conversion degree and the bulk density influence degree.

[0039] The preset candidate determination time is a time window used to calculate the soil water storage conversion degree and bulk density influence degree. It depends on the changes in rainfall intensity and the soil moisture response rate, and is usually set between 1 day and 7 days. In this embodiment, it is set to 3 days, which can accurately reflect the soil moisture dynamics under short-term rainfall and provide a reliable basis for candidate area screening.

[0040] By analyzing the synchronous variation trends of soil volumetric water content, porosity, and bulk density within a designated area, the soil's water storage capacity and the impact of soil structure on water regulation can be quantified. The water conversion ratio reflects the degree of matching between soil pore structure and water changes, while the bulk density influence reveals the limiting effect of soil compaction on water infiltration and storage. By considering both indicators simultaneously, candidate areas with good water storage capacity and minimal influence from bulk density under specific rainfall conditions can be scientifically selected. This provides precise target selection for subsequent micro-topography modifications, improving water use efficiency and soil moisture balance.

[0041] Please see Figure 3 As shown, this is a logic diagram for determining candidate regions in this embodiment. In this embodiment, the process of determining several candidate regions based on the water storage conversion degree and the bulk density influence degree includes: When the water storage conversion degree is less than or equal to a preset conversion degree threshold, or the bulk density influence degree is greater than or equal to a preset influence threshold, the corresponding undetermined region is determined as the candidate region, thereby determining several candidate regions.

[0042] The preset conversion degree threshold is a parameter used to determine whether the soil water storage capacity meets the standard. It depends on the soil type and historical moisture change characteristics, and is usually set between 0.3 and 0.7. In this embodiment, it is set to 0.5, which can effectively screen out areas with insufficient moisture accumulation. The preset influence degree threshold is a parameter used to determine the degree of influence of soil bulk density on moisture change. It depends on the soil density and structural characteristics, and is usually set between 0.3 and 0.8. In this embodiment, it is set to 0.6, which can accurately identify areas limited by bulk density for candidate area determination.

[0043] By comprehensively considering the water storage conversion degree and the influence of bulk density, this embodiment can effectively screen out areas that are prone to insufficient water accumulation or limited soil carrying capacity under the influence of rainfall and soil physical properties. These areas are then used as candidate areas for subsequent micro-topography modification to ensure that soil moisture is maintained in accordance with the soil structure, thereby improving the targeting of modification and the effect of water regulation.

[0044] Specifically, the process of determining several target regions based on the distribution characteristics of the surface roughness and root depth distribution of each candidate region includes: calculating the average surface roughness of all candidate regions to obtain the average roughness; calculating the average root depth distribution of all candidate regions to obtain the average depth distribution; calculating the region matching degree based on the surface roughness, root depth distribution, average roughness, and average depth distribution of each candidate region, where M = (E / E') × (D / D'), M is the region matching degree, E is the surface roughness, E' is the average roughness, D is the root depth distribution, and D' is the average depth distribution; and determining several target regions based on the region matching degree.

[0045] By calculating the average values ​​of surface roughness and root depth distribution in candidate areas, and combining these with actual values ​​for each area to calculate the regional matching degree, target areas most suitable for micro-topography modification can be scientifically identified based on their topographical conditions and vegetation characteristics. Surface roughness affects water flow velocity and soil runoff formation, while root depth distribution reflects the vegetation's ability to absorb soil moisture. A comprehensive evaluation of both can accurately screen areas that are conducive to both water storage and vegetation growth, thereby improving the soil and water conservation effect and ecological restoration efficiency of micro-topography modification.

[0046] Please see Figure 4 As shown, it is a logic diagram for determining the target region in this embodiment. In this embodiment, the process of determining several target regions based on the region matching degree includes: when the region matching degree is greater than a preset matching degree threshold, determining the candidate region as the target region, thereby determining several target regions.

[0047] The preset matching degree threshold is a value used to determine whether a candidate area meets the conditions to become a target area. It depends on the overall distribution characteristics of the surface roughness and root depth distribution of the candidate area. It is usually set between 0.8 and 1.2. In this embodiment, it is set to 1.0, which can effectively screen out the best micro-topography modification area that takes into account both water retention and vegetation adaptability.

[0048] By comparing the regional matching degree with a preset matching degree threshold, candidate areas with the most coordinated surface roughness and root depth distribution can be effectively screened as target areas. This not only ensures the optimal performance of the micro-topography modification area in terms of water retention and runoff regulation, but also fully considers the combination of vegetation root system's ability to absorb soil moisture and topographic conditions, thereby improving water storage efficiency, mitigating soil erosion, and promoting the stable restoration of the ecosystem.

[0049] Specifically, the process of determining the micro-topography modification depth corresponding to each target area based on the preset depth determination coefficient and the root depth distribution degree of each target area includes: calculating the micro-topography modification depth based on the preset depth determination coefficient, the root depth distribution degree and the area matching degree, where H=α×D×[1+i×(M-M')], H is the micro-topography modification depth, α is the preset depth determination coefficient, i is the preset adjustment coefficient and M' is the preset matching degree threshold.

[0050] The preset adjustment coefficient is a parameter used to adjust the sensitivity of the micro-topography modification depth to the regional matching degree deviation. It depends on the vegetation root system adaptability and soil moisture response characteristics of the target area. It is usually set between 0.1 and 0.5. In this embodiment, it is set to 0.2, which can maintain the water control effect while avoiding excessive or insufficient modification due to local matching degree fluctuations.

[0051] By combining the preset depth determination coefficient, the root depth distribution of the target area, and the regional matching degree, this method can accurately calculate the required micro-topography modification depth for each target area, so that the soil water storage structure can meet the root water absorption needs while also taking into account the surface water regulation, thereby improving soil water use efficiency and vegetation growth adaptability, and achieving dynamic coordination between micro-topography modification depth and vegetation characteristics and surface conditions.

[0052] Specifically, the process of adjusting the preset infiltration threshold based on the soil volumetric water content and surface runoff of each target area within a preset optimization period after the soil water storage structure is constructed, and the location change characteristics of all target areas, includes: dividing the preset optimization period into several equal-length time periods to obtain several adjustment judgment durations; obtaining target areas that have been judged as target areas at least a preset number of times within the preset optimization period to obtain adjustment judgment areas; calculating the average values ​​of the soil volumetric water content and surface runoff of the adjustment judgment areas to obtain the average water content and average flow rate; calculating the trend coefficients of the average water content and average flow rate within the preset optimization period through linear regression analysis to obtain the water content trend coefficient and flow rate trend coefficient; calculating the Jaccard distance between each pair of target areas based on the set of all adjustment judgment durations and taking the average value to obtain the spatial distribution variability, wherein the calculation process of the spatial distribution variability is as follows: F=[Σ(1-| Ti∩Tj| / |Ti∪Tj|)] / N, where Ti is the set of target regions for the i-th adjustment judgment duration, Tj is the set of target regions for the j-th adjustment judgment duration, and N is the total number of pairwise combinations; a first judgment result is obtained when the water content trend coefficient is greater than the preset water content trend threshold and the flow trend coefficient is less than the preset flow trend threshold; a second judgment result is obtained when the water content trend coefficient is less than or equal to the preset water content trend threshold, or the flow trend coefficient is greater than or equal to the preset flow trend threshold; a third judgment result is obtained when the spatial distribution variability is less than or equal to the preset variability threshold; a fourth judgment result is obtained when the spatial distribution variability is greater than the preset variability threshold; when obtaining the first judgment result and the third judgment result, the preset infiltration threshold is reduced according to the preset threshold adjustment index, where Y'=Y×(1-g), Y' is the adjusted preset infiltration threshold, Y is the original preset infiltration threshold, and g is the preset threshold adjustment index.

[0053] In this embodiment, dividing the preset optimization period into several equal-length time periods depends on the frequency of rainfall intensity changes, soil moisture response speed, and construction management requirements. Typically, it can be divided by day, week, or consecutive rainfall events. In this embodiment, the optimization period is 30 days, divided into 6 equal-length time periods, each lasting 5 days. These periods are used to separately calculate the soil volumetric water content and surface runoff in the target area, in order to dynamically adjust the infiltration threshold and the depth of micro-topography modification.

[0054] In this embodiment, for each target area within an adjustment judgment period, the average water content and average flow rate of all target areas within that time period are first calculated. Then, the entire preset optimization cycle is divided into time series of average water content and average flow rate for equal time intervals. For this time series, linear regression is used to fit the average water content with time and the average flow rate with time, respectively. The slope of the regression line is used as a trend coefficient, where the water content trend coefficient reflects the rise and fall of soil moisture in the target area over time, and the flow rate trend coefficient reflects the change in surface runoff over time. This method allows for a quantitative assessment of the dynamic changes in water content in each target area within the optimization cycle, providing a basis for adjusting the infiltration threshold and the depth of micro-topography modification.

[0055] The preset number of times refers to the minimum number of times the target area is determined as a valid target within a preset optimization period. It depends on the number of time periods divided in the optimization period and the stability of the target area, and is usually set to half to all of the total number of time periods. In this embodiment, it is set to 3 times (30 days divided into 5 segments, each segment lasting 6 days), ensuring that optimization is only performed on areas that show stability for most of the time periods. The preset water content trend threshold is a threshold used to determine the trend of soil volumetric water content changes. It depends on the soil type and rainfall characteristics, and is usually set between 0 and 0.05 / day. In this embodiment, it is set to 0.02 / day, which can identify areas with a significant increase in soil water content. The preset flow trend threshold is a threshold used to determine the trend of surface runoff changes. The threshold value depends on the surface slope and soil permeability, and is usually set between 0 and 0.05 / day. In this embodiment, it is set to 0.015 / day, which can identify areas with significant runoff reduction. The preset variability threshold is a threshold used to judge the spatial uniformity of the target area. It depends on the terrain complexity and the micro-topography modification target, and is usually set between 0.1 and 0.5. In this embodiment, it is set to 0.25, which can exclude areas with overly dispersed distribution. The preset threshold adjustment index is a proportional coefficient for adjusting the infiltration threshold. It depends on the soil water storage capacity and engineering control sensitivity, and is usually set between 0.01 and 0.2. In this embodiment, it is set to 0.1, which can moderately reduce the infiltration threshold and achieve precise control of the micro-topography modification effect.

[0056] By systematically analyzing the changes in soil volumetric water content, surface runoff, and spatial distribution in the target area after the construction of soil water storage structures within a preset optimization period, the trends and spatial uniformity of water storage and runoff response in each region can be dynamically assessed. By calculating the trend coefficients of mean water content and mean runoff using linear regression, and combining this with Jaccard distance between regions to measure spatial distribution variability, the actual effectiveness of water regulation in each target area can be accurately determined. Under conditions of increasing water content, decreasing runoff, and uniform spatial distribution, the infiltration threshold is automatically and appropriately lowered to optimize the control of water infiltration, thereby ensuring the continuous accumulation and rational distribution of soil moisture after micro-topography modification, improving water storage efficiency, and preventing localized runoff excess or water loss.

[0057] Specifically, the process of adjusting the preset depth determination coefficient includes: when obtaining the second determination result and the fourth determination result, reducing the preset depth determination coefficient according to the relative deviation between the spatial distribution variability and the preset variability threshold, where α'=α×(1-s×︱F-F0︱ / F0), α' is the adjusted depth determination coefficient, s is the preset coefficient adjustment index, and F0 is the preset variability threshold.

[0058] The preset coefficient adjustment index is a parameter used to control the adjustment range of the depth of micro-topography modification. It depends on the sensitivity of the spatial distribution of the target area to the expected deviation. It is usually set between 0.01 and 0.5. In this embodiment, it is set to 0.1, which can ensure the soil water storage and runoff regulation effect while avoiding structural instability or uneven water distribution caused by excessive depth adjustment.

[0059] By evaluating the relative difference between the spatial distribution variability of the target area and the preset threshold in real time during the optimization period, the depth determination coefficient is dynamically adjusted. When the distribution of the target area fluctuates significantly or deviates from the expected distribution, the depth coefficient is automatically reduced, so that the depth of micro-topography modification changes synchronously with regional conditions and distribution characteristics. This coordinates the relationship between soil moisture storage capacity, surface runoff and vegetation root growth depth, and achieves a consistent match between the modification depth and soil, vegetation and hydrological characteristics, thereby improving the efficiency and stability of the water storage structure.

[0060] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A micro-topography modification method for power grid engineering in loess areas, characterized in that, include: Real-time acquisition of total rainfall duration, instantaneous rainfall intensity, surface runoff, soil volumetric water content, soil bulk density, soil porosity, permeability coefficient, surface roughness, and root depth distribution of target vegetation communities within the power grid engineering disturbance area. Based on the total rainfall duration, the instantaneous rainfall intensity, and the permeability coefficient, several undetermined areas are determined from all the monitored areas based on a preset infiltration threshold; Several candidate regions are determined based on the synchronous change trends of the soil volumetric water content, soil porosity, and soil bulk density in each of the undetermined regions. Based on the distribution characteristics of the surface roughness and root depth distribution of each candidate region, several target regions are determined, and the micro-topography modification depth corresponding to each target region is determined based on the preset depth determination coefficient and the root depth distribution of each target region. Based on the micro-topography modification depth, a soil water storage structure is constructed in the target area using biodegradable materials. The preset infiltration threshold is adjusted based on the soil volumetric water content and surface runoff of each target area within a preset optimization period after the soil water storage structure is constructed, as well as the location change characteristics of all target areas. Alternatively, the preset depth determination coefficient can be adjusted.

2. The micro-topography modification method for power grid engineering in loess areas according to claim 1, characterized in that, The process of determining several undetermined areas based on the total rainfall duration, the instantaneous rainfall intensity, and the permeability coefficient, and using a preset infiltration threshold, includes: The impact coefficient of previous rainfall is calculated based on the sum of the total rainfall duration within the preset historical judgment period. The potential value of the runoff coefficient is calculated based on the previous rainfall impact coefficient, the instantaneous rainfall intensity in each of the monitoring areas, and the permeability coefficient; Several undetermined areas are determined based on the potential value of the runoff coefficient and the preset infiltration threshold.

3. The micro-topography modification method for power grid engineering in loess areas according to claim 2, characterized in that, The process of determining several undetermined areas based on the potential value of the runoff coefficient and the preset infiltration threshold includes: When the potential value of the runoff coefficient is greater than the preset infiltration threshold, the monitoring area is determined as the undetermined area, thereby identifying several undetermined areas.

4. The micro-topography modification method for power grid engineering in loess areas according to claim 3, characterized in that, The process of determining several candidate regions based on the synchronous change trends of the soil volumetric water content, soil porosity, and soil bulk density of each of the undetermined regions includes: When determining several undetermined areas, the water storage conversion degree is determined based on the total soil volume moisture content and total soil porosity of each undetermined area within the next preset candidate determination time. The bulk density influence is determined based on the total volumetric moisture content and total bulk density of all soils in each candidate region within the same preset candidate determination time period. Several candidate regions are determined based on the water storage conversion degree and the bulk density influence degree.

5. The micro-topography modification method for power grid engineering in loess areas according to claim 4, characterized in that, The process of determining several candidate regions based on the water storage conversion degree and the bulk density influence degree includes: When the water storage conversion degree is less than or equal to a preset conversion degree threshold, or the bulk density influence degree is greater than or equal to a preset influence threshold, the corresponding undetermined region is determined as the candidate region, thereby determining several candidate regions.

6. The micro-topography modification method for power grid engineering in loess areas according to claim 5, characterized in that, The process of determining several target regions based on the distribution characteristics of the surface roughness and root depth of each candidate region includes: Calculate the average surface roughness of all the candidate regions to obtain the average roughness; Calculate the average root depth distribution of all candidate regions to obtain the average depth distribution. The region matching degree is calculated based on the surface roughness, root depth distribution, average roughness, and average depth distribution of each candidate region. Several target regions are determined based on the region matching degree.

7. The micro-topography modification method for power grid engineering in loess areas according to claim 6, characterized in that, The process of determining several target regions based on the region matching degree includes: When the region matching degree is greater than a preset matching degree threshold, the candidate region is determined to be the target region, thereby identifying several target regions.

8. The micro-topography modification method for power grid engineering in loess areas according to claim 7, characterized in that, The process of determining the micro-topography modification depth for each target area based on the preset depth determination coefficient and the root depth distribution of each target area includes: The micro-topography modification depth is calculated based on the preset depth determination coefficient, the root system depth distribution degree, and the regional matching degree.

9. The micro-topography modification method for power grid engineering in loess areas according to claim 8, characterized in that, The process of adjusting the preset infiltration threshold based on the soil volumetric water content and surface runoff of each target area within a preset optimization period after the soil water storage structure is constructed, and the location change characteristics of all target areas, includes: The preset optimization cycle is divided into several time periods of equal length to obtain several adjustment judgment durations; Obtain the target region that has been identified as the target region at least a preset number of times within the preset optimization period, so as to obtain the adjustment determination region; The average values ​​of the soil volumetric water content and the surface runoff in the adjustment determination area are calculated respectively to obtain the average water content and average runoff. The trend coefficients of the mean water content and the mean flow rate within the preset optimization period are calculated by linear regression analysis to obtain the water content trend coefficient and the flow rate trend coefficient. Based on the set of target regions for all adjustment judgment durations, calculate the Jaccard distance between each pair and take the average value to obtain the spatial distribution variability; A first determination result is obtained when the water content trend coefficient is greater than a preset water content trend threshold and the flow rate trend coefficient is less than a preset flow rate trend threshold; A second determination result is obtained when the water content trend coefficient is less than or equal to a preset water content trend threshold, or when the flow rate trend coefficient is greater than or equal to a preset flow rate trend threshold. A third determination result is obtained when the spatial distribution variability is less than or equal to a preset variability threshold. When the spatial distribution variability is greater than a preset variability threshold, a fourth determination result is obtained. When the first determination result and the third determination result are obtained, the preset infiltration threshold is reduced by adjusting the preset threshold index.

10. The micro-topography modification method for power grid engineering in loess areas according to claim 9, characterized in that, The process of adjusting the preset depth determination coefficient includes: When obtaining the second determination result and the fourth determination result, the preset depth determination coefficient is reduced according to the relative deviation between the spatial distribution variability and the preset variability threshold.

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