Method for evaluating soil wind erosion degree in photovoltaic sand control project

Abstract

The application discloses a photovoltaic sand control engineering soil wind erosion degree evaluation method and relates to the technical field of soil wind erosion degree evaluation, and comprises the following steps: collecting second-level air pressure change curves before and after the passage of a cold front, near-ground airflow instantaneous speed data and surface fine particle starting image data, performing time alignment processing under a unified time scale, extracting an airflow jump section corresponding to air pressure sudden drop, and forming a front compression characteristic interval; around the front compression characteristic interval, extracting surface particle displacement amplitude change data in the interval, and calculating synchronous transition intensity of particle groups. The application correlates air pressure, airflow and particle image data through unified time scale, constructs a front compression characteristic interval, generates a transient scouring intensity identifier, realizes accurate identification of instantaneous scouring and particle transition, simultaneously establishes a bearing sudden drop judgment basis, carries out high-frequency tracking and early warning, and realizes early identification and control of bearing capacity mutation risk.

Description

Technical Field

[0001] This invention relates to the field of soil wind erosion assessment technology, specifically to a method for assessing soil wind erosion in photovoltaic desertification control projects. Background Technology

[0002] Soil erosion assessment in photovoltaic desertification control projects refers to the technical activity of quantitatively determining the intensity of soil loss, erosion depth, and spatial distribution differences per unit time by comprehensively analyzing factors such as changes in surface micro-topography, soil particle size distribution, surface roughness, vegetation cover changes, temporal characteristics of wind speed and direction, and the impact of the array structure on near-surface airflow disturbances under the construction and operation conditions of photovoltaic arrays. Its core lies in revealing the impact mechanism of local accelerated wind zones, eddy zones, and shading deposition zones formed after the photovoltaic array alters the surface airflow structure on soil stability. The role of this assessment is twofold: firstly, to provide parameter basis for the design of photovoltaic array spacing, support height setting, and windbreak and sand-fixing measures, reducing the risk of foundation erosion and support instability; secondly, to provide zoning control standards for vegetation restoration strategies, surface cover material selection, and subsequent ecological restoration intensity classification, thereby achieving a synergistic improvement in power generation efficiency and ecological stability, and providing quantitative support for operation and maintenance decisions and risk warnings throughout the entire project lifecycle.

[0003] The existing technology has the following shortcomings: During the operation of photovoltaic desertification control projects, when a cold front passes and causes a sharp drop in air pressure, the air at the leading edge forms a compression disturbance in a short period of time. The near-surface air velocity gradient increases rapidly, and fine particles that were originally in a critically stable state on the ground are easily propelled by the compression disturbance to migrate as a whole, exhibiting a sheet-like synchronous displacement phenomenon. This process often occurs within a very short time window, and conventional average wind speed monitoring data cannot reflect the true erosion intensity in a timely manner, easily causing the surface soil to be rapidly extracted and forming local collapse pits. As fine particles continue to be lost, the soil bearing capacity will significantly decrease within a few hours, and the support conditions around the foundation are prone to sudden changes, leading to increased foundation settlement or even the risk of tilting.

[0004] 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

[0005] The purpose of this invention is to provide a method for assessing the degree of soil wind erosion in photovoltaic desertification control projects, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for assessing the degree of soil wind erosion in photovoltaic desertification control projects, comprising the following steps: Step 1: Collect second-level air pressure change curves, near-surface airflow instantaneous velocity data, and surface fine particle initiation image data before and after the passage of the cold front. Perform time alignment processing under a unified time scale, extract the airflow leap segment corresponding to the sudden drop in air pressure, and form the pre-frontal compression characteristic interval. Step 2: Extract the displacement amplitude change data of surface particles within the compression characteristic range before the front, calculate the synchronous transition intensity of the particle population, and synchronously map the pressure drop amplitude with the synchronous transition intensity of the particle population to generate a transient scour intensity identifier. Step 3: Based on the transient scour intensity indicator, perform high-frequency unfolding analysis on the continuous change data of the micro-topography of the ground surface below the photovoltaic array to identify the period of depression formation corresponding to the rapid detachment of particles, and form the time interval of the collapse evolution. Step 4: Combine the time interval of subsidence evolution, continuously track the trend data of surface bearing capacity changes, extract the bearing capacity attenuation rate, and establish the linkage relationship between the bearing capacity attenuation rate and the transient scour intensity indicator to construct the basis for judging sudden bearing capacity drop. Step 5: Based on the criteria for judging sudden pressure drop, a high-frequency dynamic tracking process is initiated before the arrival of the subsequent cold front. The synchronization between the sudden pressure drop and the transient scour intensity indicator is compared in real time, and a risk warning is issued when the preset critical mapping condition is reached.

[0007] Preferably, the process of collecting second-level air pressure change curves, near-surface airflow instantaneous velocity data, and surface fine particle initiation image data before and after the passage of a cold front, and forming a pre-frontal compression characteristic region, includes the following steps: During the cold front impact forecast period, the continuous data collection period is from two hours before the arrival of the cold front to one hour after its passage. The air pressure is continuously recorded at second-level time intervals to form a second-level air pressure change curve. At the same time starting point, the instantaneous velocity data of the near-ground airflow and the surface fine particle initiation image data are recorded simultaneously, so that the air pressure change curve, the instantaneous velocity data of the near-ground airflow and the surface fine particle initiation image data are marked with the same time numbering method. Using the start time of the cold front's influence period as the unified zero point of the time scale, the second-level air pressure change curve, the instantaneous velocity data of near-ground airflow, and the surface fine particle initiation image data are mapped to the same continuous time axis. The air pressure value and the instantaneous velocity value of near-ground airflow corresponding to each second are arranged synchronously to form a synchronous sequence of air pressure change and instantaneous velocity change of near-ground airflow. In the synchronous sequence, we screened out continuous time intervals where the air pressure continuously decreased and the instantaneous velocity of the near-ground airflow continuously increased, and retrieved the surface fine particle initiation image data with the corresponding time number. We recorded the particle displacement direction and displacement distance within the continuous time frame to form a complete disturbance time window. The pressure drop segment and airflow rise segment within the complete disturbance time window are time-overlaid, and the overlapping intervals on the time axis, together with the corresponding surface fine particle initiation image data segments, are defined as the pre-frontal compression characteristic interval.

[0008] Preferably, the complete disturbance time window covers the stage of continuous pressure decline, the stage of continuous increase in instantaneous velocity of near-surface airflow, and the stage of continuous particle transition in the surface fine particle initiation image data. The pre-frontal compression feature interval retains the numerical sequence of pressure change, the numerical sequence of instantaneous velocity of near-surface airflow, and the particle displacement image sequence on the corresponding time axis to reflect the temporal consistency of the compression disturbance process.

[0009] Preferably, the extraction of surface particle displacement amplitude variation data around the pre-frontal compression characteristic interval and the generation of transient scour intensity indicators include the following steps: Within the starting and ending time range of the frontal compression feature interval, the surface fine particle initiation image data is retrieved second by second. The spatial position of particles in the continuous time frame is compared frame by frame. The initial position and corresponding position changes of particles are recorded to form a particle displacement trajectory sequence. The displacement distance of all particles in each second is counted to obtain the surface particle displacement amplitude change data. The data on the variation of surface particle displacement amplitude are correlated with the data on sudden drop in air pressure and instantaneous velocity of near-surface airflow at the corresponding time number within the compression characteristic interval of the front, forming a multi-source time series set containing air pressure values, instantaneous velocity values ​​of near-surface airflow, and particle displacement amplitude values. The particle displacement direction and displacement distance within the same time node are statistically analyzed to calculate the synchronous transition intensity of the particle population. The synchronous transition intensity of the particle population and the pressure drop amplitude within the pre-frontal compression characteristic range are arranged second by second on a unified time scale. The pressure drop segment and the particle population synchronous transition intensity change segment are time-overlaid to construct the synchronous mapping relationship between the pressure drop amplitude and the particle population synchronous transition intensity. The synchronous mapping relationship is sorted out in time sequence, and the values ​​of the pressure drop range segment and the synchronous transition intensity values ​​of the particle population at the corresponding time node are integrated to form a comprehensive identifier that includes the pressure drop range value, the synchronous transition intensity value of the particle population and the duration. The comprehensive identifier is defined as the transient scour intensity identifier.

[0010] Preferably, in the synchronous mapping relationship, the overlapping section of the pressure drop amplitude and the synchronous transition intensity of the particle group on the time axis is used as the intensity determination interval, and the duration of the overlapping section is included in the comprehensive identifier to limit the formation conditions of the transient scour intensity identifier.

[0011] Preferably, the process of forming a collapse evolution time interval based on transient scour intensity indicators includes the following steps: Under a unified time scale, with the time node corresponding to the transient scour intensity as the center, the continuous time range is determined by extending to the time node of the sudden drop in air pressure and the time node of the synchronous transition intensity of the particle group falling back to the initial level. The continuous change data of the micro-topography of the ground surface below the photovoltaic array is retrieved second by second to form a time series elevation change set. Within the time series elevation change set, the elevation difference of each spatial location is recorded second by second around the peak time node of the transient scour intensity indicator. Spatial locations with continuously decreasing elevation are marked as particle detachment areas, forming a surface depression change data sequence, which is then synchronized with the transient scour intensity indicator. In the data sequence of surface depression changes, select the continuous time intervals before and after the peak of transient scour intensity, record the entire process of elevation drop at each spatial location, mark the continuous drop intervals at multiple spatial locations as the depression formation period, and overlay them with the time interval of the peak of transient scour intensity. Starting from the initial time of the depression formation period and ending at the time when the rate of surface elevation decline recovers to the pre-scour level, continuous changes in surface micro-topography and transient scour intensity values ​​are collected within the corresponding time range to form the time interval of the subsidence evolution.

[0012] Preferably, the formation period of the depression must simultaneously satisfy the following conditions: multiple spatial locations in the surface depression change data sequence show a continuous decrease in elevation, and the corresponding time period overlaps with the peak time period of the transient scour intensity indicator under a unified time scale. This overlapping time range is taken as the core judgment segment of the subsidence evolution time interval.

[0013] Preferably, the criteria for determining sudden load-bearing drop are constructed by combining the time interval of the collapse evolution, including the following steps: Starting from the beginning of the subsidence evolution time interval under a unified time scale, the bearing capacity change trend data of the surface area below the photovoltaic array is collected second by second to form a data sequence of surface bearing capacity change trend that runs through the subsidence evolution time interval. The surface bearing capacity change trend data of each time node and the corresponding transient scour intensity indicator are arranged in parallel to form a synchronous sequence. The change in load value between consecutive time nodes is recorded second by second in the synchronization sequence. The attenuation segment where the load value continues to decrease is divided, and the duration and cumulative decrease of each attenuation segment are counted to form a load attenuation rate change sequence. The sequence of bearing capacity attenuation rate changes is arranged second by second with the transient scour intensity markers within the time interval of collapse evolution. The peak time interval of the transient scour intensity markers and the peak time interval of the bearing capacity attenuation rate are time-overlaid to form a set of correspondences between the transient scour intensity markers and the bearing capacity attenuation rate. In the corresponding relationship set, select the interval where the load attenuation rate exceeds the predetermined range of change per unit time and coincides with the peak time period of the transient scour intensity indicator to determine the load drop segment. Then, construct the load drop judgment basis based on the starting time node of the load drop segment and the corresponding transient scour intensity indicator value range.

[0014] Preferably, the criteria for determining the sudden drop in load capacity include the starting time node of the sudden drop in load capacity section and the corresponding range of transient scour intensity indicators, and the coincidence of the peak time period of the transient scour intensity indicator and the peak time period of the load capacity attenuation rate on the time axis is used as the condition for determining the sudden drop in load capacity section.

[0015] Preferably, high-frequency dynamic tracking and risk warnings are conducted based on the criteria for determining sudden load drops, including the following steps: Under a unified time scale, with reference to the time segment boundary and transient scour intensity indicator range in the criteria for determining sudden drop in load, a continuous observation period is set, and the air pressure is recorded second by second to form a second-level air pressure change curve. Simultaneously, the instantaneous velocity data of the near-ground airflow is recorded to generate the transient scour intensity indicator for the corresponding time node. The pressure drop amplitude in the second-level pressure change curve is compared with the pressure drop amplitude range in the load-bearing sudden drop judgment criteria every second. At the same time, the transient scour intensity indicator at the corresponding time node is arranged in parallel with the transient scour intensity indicator value range in the load-bearing sudden drop judgment criteria to form a real-time mapping comparison relationship. In the real-time mapping comparison relationship, select continuous time segments where the pressure drop amplitude enters the pressure drop amplitude range and the transient scour intensity indicator enters the transient scour intensity indicator value range, record the duration of the continuous time segment and the corresponding change trajectory, and form a critical mapping candidate segment. When the duration of the candidate critical mapping segment reaches a predetermined length, the trigger segment that meets the preset critical mapping conditions is determined, and a risk warning is issued at the start time node of the trigger segment.

[0016] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention constructs a pre-frontal compression characteristic interval by performing correlation processing on a unified time scale on the second-level air pressure change curves before and after the passage of a cold front, the instantaneous velocity data of near-surface airflow, and the image data of fine particles starting on the ground before and after the passage of a cold front. Furthermore, it generates a transient erosion intensity label, so that the compression disturbance process that occurs in a short period of time can be continuously characterized. This breaks through the limitation of the traditional average wind speed statistical method in responding to the lag of instantaneous erosion behavior, and realizes the accurate identification of sheet-like synchronous transition and rapid particle extraction process, thereby improving the timeliness and pertinence of wind erosion intensity assessment.

[0017] This invention establishes a basis for judging sudden drops in bearing capacity by correlating transient scour intensity indicators with the time interval of collapse evolution and the rate of bearing capacity attenuation. It also conducts high-frequency dynamic tracking before the arrival of subsequent cold fronts to achieve real-time comparison between the magnitude of sudden air pressure drop and transient scour intensity indicators. When the preset critical mapping conditions are reached, a risk warning is issued, thereby enabling early identification of sudden changes in the surface bearing capacity and improving the safety management and risk warning capabilities during the operation of photovoltaic desertification control projects. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0019] Figure 1 This is a flowchart of the method for assessing the degree of soil wind erosion in photovoltaic desertification control projects according to the present invention. Detailed Implementation

[0020] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0021] This invention provides, for example Figure 1 The method for assessing soil wind erosion in photovoltaic desertification control projects, as shown, includes the following steps: Step 1: Collect second-level air pressure change curves, near-surface airflow instantaneous velocity data, and surface fine particle initiation image data before and after the passage of the cold front. Perform time alignment processing under a unified time scale, extract the airflow leap segment corresponding to the sudden drop in air pressure, and form the pre-frontal compression characteristic interval. The specific implementation method for this step is as follows: After the photovoltaic desertification control area enters the cold front impact forecast period, the continuous data collection period is from two hours before the arrival of the cold front to one hour after its passage. The air pressure is continuously recorded at second-level time intervals to form a continuous second-level air pressure change curve. At the same time starting point, the instantaneous velocity data of the near-ground airflow is recorded synchronously, with the recording frequency controlled at no less than once per second to ensure that each air pressure recording point corresponds to an instantaneous airflow velocity recording value. At the same time, within the same collection area, the activity state of surface fine particles is continuously imaged. The timestamp of the image recording is consistent with the air pressure and airflow recording time, so that the second-level air pressure change curve, the instantaneous velocity data of the near-ground airflow, and the surface fine particle initiation image data are marked with the same time numbering method in the original recording stage. The three types of data are under a unified time series framework from the beginning of collection, thereby ensuring the temporal continuity and data correspondence of the entire process of the cold front's passage.

[0022] After completing the continuous data acquisition, using the start time of the cold front's influence period as the unified time scale zero point, all the second-level air pressure change curves, near-surface airflow instantaneous velocity data, and surface fine particle initiation image data were mapped onto the same continuous time axis. The air pressure value, airflow instantaneous velocity value, and image frame corresponding to each second were numbered and arranged to form a complete unified time series data set. On this unified time axis, the air pressure value changes were extracted second by second from the air pressure change curve, marking the sections of air pressure drop for several consecutive seconds. At the same second time node, the corresponding near-surface airflow instantaneous velocity data was read, and the change amplitude of the airflow instantaneous velocity within the continuous time period was recorded. The continuous air pressure drop sections and the change trend of the airflow instantaneous velocity within the same time period were arranged synchronously, so that the air pressure change value of each second corresponds to the airflow instantaneous velocity value of the same second, thereby constructing a synchronous sequence of air pressure change and near-surface airflow instantaneous velocity change in the time dimension.

[0023] Based on the established synchronous sequence of air pressure changes and near-surface airflow instantaneous velocity changes, a continuous time interval is selected from the synchronous sequence where the air pressure continuously decreases and the near-surface airflow instantaneous velocity continuously increases within the same time period. The start and end seconds of this time interval are clearly marked. Subsequently, surface fine particle initiation image data with corresponding time numbers are retrieved within this continuous time interval. The positional changes of fine particles in each second of the image are continuously observed, and the displacement direction and displacement distance of particles between continuous time frames are recorded. When multiple adjacent time frames in this continuous time interval show simultaneous jump migration of fine particles, the entire continuous time interval is preserved, and the interval boundary is extended forward and backward by several seconds to cover the stable state before the air pressure begins to decrease and the fall phase before the airflow recovers. This forms a complete disturbance time window that includes the air pressure decrease phase, the airflow jump phase, and the synchronous jump phase of fine particles.

[0024] After determining the complete disturbance time window, the second-level air pressure change curve within that time window is segmented. The entire process of air pressure decreasing continuously from a stable value to reaching its lowest point is defined as the air pressure drop segment. Simultaneously, near-surface airflow instantaneous velocity data within the same time window is continuously read, calibrating the entire process of airflow instantaneous velocity rapidly rising from a baseline state to reaching its peak. The air pressure drop segment and the airflow rise segment are superimposed on a unified time scale. When there is an overlapping interval between the two on the time axis, this overlapping interval, along with the corresponding surface fine particles, is used to initiate [the process]. The image data segment is defined as a pre-frontal compression feature interval. Within this pre-frontal compression feature interval, the numerical sequence of air pressure change, the numerical sequence of instantaneous airflow velocity, and the image sequence of continuous transition of fine particles are completely preserved. This allows the pre-frontal compression feature interval to simultaneously possess the characteristics of sudden air pressure drop, airflow rise, and particle initiation response. This forms a continuous time segment that can directly reflect the compression disturbance process at the leading edge of the cold front under a unified time scale. This provides a continuous time basis for subsequent extraction of particle displacement amplitude change data and construction of transient scour intensity markers around the pre-frontal compression feature interval.

[0025] Step 2: Extract the displacement amplitude change data of surface particles within the compression characteristic range before the front, calculate the synchronous transition intensity of the particle population, and synchronously map the pressure drop amplitude with the synchronous transition intensity of the particle population to generate a transient scour intensity identifier. The specific implementation method for this step is as follows: Using the start and end times of the established pre-frontal compression feature interval as boundaries, the corresponding surface fine particle initiation image data within this interval is retrieved second by second under a unified time scale. The spatial positions of particles in continuous time frames are compared frame by frame, and the initial position of identifiable particles in each frame and the positional changes of the corresponding particles in the next frame are recorded in chronological order to form a particle displacement trajectory sequence. In this particle displacement trajectory sequence, the displacement distance of all particles in each second is statistically analyzed to form surface particle displacement amplitude change data in seconds. This surface particle displacement amplitude change data is then time-correlated with the air pressure drop data and near-surface airflow instantaneous velocity data of the same time number within the pre-frontal compression feature interval, so that each time node simultaneously has air pressure value, airflow instantaneous velocity value, and particle displacement amplitude value, thereby establishing a complete multi-source time series set within the pre-frontal compression feature interval.

[0026] After obtaining the data on the changes in the displacement amplitude of surface particles at consecutive time points within the pre-frontal compression characteristic interval, the displacement direction and displacement distance of all particles at the same time point are statistically analyzed. The number of particles that displace within the same second is recorded, and the consistency of the overall displacement direction and the concentration of displacement distance within the same second are calculated. The number of particles that displace within the same second is compared with the total number of identifiable particles within that time point to obtain the group participation ratio at that time point. At the same time, combined with the particle displacement amplitude change data at that time point, a numerical sequence reflecting the group transition state is formed. This numerical sequence is arranged in chronological order to obtain the change curve of the synchronous transition intensity of the particle group throughout the entire pre-frontal compression characteristic interval. This allows the synchronous transition intensity of the particle group to reflect the changes in the overall transition behavior of particles second by second under a unified time scale, and to maintain time consistency with the sudden drop in air pressure within the pre-frontal compression characteristic interval.

[0027] After establishing the synchronous transition intensity variation curve of the particle population within the pre-frontal compression characteristic region, this curve is synchronized with the pressure drop amplitude within the same pre-frontal compression characteristic region. Pressure and particle population synchronous transition intensity values ​​are read second-by-second at a unified time scale. The entire process of pressure decreasing from its initial value to its lowest value is segmented, and the change in particle population synchronous transition intensity over time within each segment is extracted. The pressure drop amplitude variation segment and the particle population synchronous transition intensity variation segment are superimposed on the time axis. When the pressure drop phase and the synchronous transition intensity increase phase of the particle population coincide in time, the duration of this overlapping segment, the total pressure drop, and the cumulative value of the synchronous transition intensity of the particle population are recorded. By segmentally mapping the pressure drop amplitude and the synchronous transition intensity of the particle population at different time periods within the same pre-frontal compression characteristic interval, a set of data pairs with a one-to-one correspondence under a unified time scale is formed. This constructs a synchronous mapping relationship between the pressure drop amplitude and the synchronous transition intensity of the particle population, allowing the degree of linkage between pressure change and particle transition behavior to be quantitatively expressed in the time dimension.

[0028] After establishing the synchronous mapping relationship between the magnitude of the pressure drop and the synchronous transition intensity of the particle population, the mapping data within the entire pre-frontal compression characteristic interval is continuously processed. The segment values ​​of the pressure drop magnitude are integrated with the corresponding time node values ​​of the synchronous transition intensity of the particle population, forming a mapping sequence table in chronological order. The time nodes in this mapping sequence table that both the pressure drop magnitude and the synchronous transition intensity of the particle population reach their peak are marked. These time nodes serve as the core reference points for transient scour intensity. At the same time, the continuous time periods before and after the peak are included in the same intensity interval, ultimately forming a comprehensive identifier that includes the pressure drop magnitude value, the synchronous transition intensity value of the particle population, and the duration. This comprehensive identifier is defined as the transient scour intensity identifier, and it is fully preserved within the pre-frontal compression characteristic interval so that it can directly reflect the degree of synchronization and duration of the pressure drop and the synchronous transition behavior of the particle population. This provides a clear temporal and intensity basis for subsequent analysis of continuous changes in surface micro-topography and tracking of bearing capacity changes based on the transient scour intensity identifier.

[0029] Step 3: Based on the transient scour intensity indicator, perform high-frequency unfolding analysis on the continuous change data of the micro-topography of the ground surface below the photovoltaic array to identify the period of depression formation corresponding to the rapid detachment of particles, and form the time interval of the collapse evolution. The specific implementation method for this step is as follows: Centered on the time node corresponding to the transient scour intensity marker, the time scale is extended forward to the starting time node of the sudden pressure drop and backward to the time node when the synchronous transition intensity of the particle population returns to the initial level. This determines a continuous time range covering the entire transient scour process. Within this continuous time range, the continuous change data of the surface micro-topography below the photovoltaic array is retrieved second by second. The surface elevation distribution state corresponding to each time node is continuously recorded. The elevation values ​​of the same spatial location at different time nodes are arranged in chronological order to form a time series elevation change set. In this set, the time corresponding to the peak of the transient scour intensity marker is used as the reference time point. The surface elevation distribution state several seconds before the reference time point is compared with the surface elevation distribution state several seconds after the reference time point to establish a continuous surface elevation change framework under a unified time scale, so that the transient scour intensity marker and the continuous change data of surface micro-topography form a correspondence in the time dimension.

[0030] Based on the established framework of continuous surface elevation change, the elevation change amplitude of each spatial location below the photovoltaic array is analyzed second by second around the peak time node of the transient scour intensity marker. The elevation difference between consecutive time nodes is recorded point by point. Spatial locations with continuous elevation decline are marked as particle extraction areas. The number of spatial locations with elevation decline within the same second and the corresponding total decline amplitude are counted to form a surface depression change data sequence in seconds. At the same time, this surface depression change data sequence is synchronized with the transient scour intensity marker at the same time node. By comparing the stage of the transient scour intensity marker value increase with the time segment of the surface depression change data sequence where the elevation decline rate increases, the scour intensity change process corresponding to the synchronous transition intensity of the particle population and the surface micro-topography change process are continuously correlated under a unified time scale.

[0031] After establishing the time correspondence between the transient scour intensity marker and the surface depression change data sequence, a few consecutive seconds before and after the transient scour intensity marker reaches its peak are selected as the key analysis segment. Within this segment, the elevation change trajectory of each spatial location below the photovoltaic array is continuously unfolded, and the entire process of each spatial location descending from its initial elevation value to its lowest elevation value is recorded. The start time, duration, and cumulative decline of this descent process are statistically analyzed. The intervals in which multiple spatial locations simultaneously experience continuous elevation decline are collectively labeled as the depression formation period corresponding to rapid particle extraction. This depression formation period is then superimposed with the peak time period of the transient scour intensity marker. When the two coincide on the time axis, the overlapping time period is completely preserved, thus forming the core time segment of depression formation based on the transient scour intensity marker.

[0032] After determining the core time period of the depression formation, the starting time of this core time period is taken as the starting point of the subsidence evolution time interval, and the time node when the rate of surface elevation decline recovers to the pre-scour level is taken as the ending point of the subsidence evolution time interval. All continuous changes in surface micro-topography between the starting point and the ending point are collected as a whole. The elevation change trajectory, spatial distribution changes, and corresponding transient scour intensity indicators within this continuous time period are uniformly organized to form a complete subsidence evolution time interval. This subsidence evolution time interval simultaneously includes the transient scour intensity indicator change process and the continuous change process of surface micro-topography, reflecting the entire process of subsidence formation and expansion caused by rapid particle detachment from a temporal dimension. This provides continuous time boundaries and intensity basis for subsequent data tracking of surface bearing capacity changes around the subsidence evolution time interval.

[0033] Step 4: Combine the time interval of subsidence evolution, continuously track the trend data of surface bearing capacity changes, extract the bearing capacity attenuation rate, and establish the linkage relationship between the bearing capacity attenuation rate and the transient scour intensity indicator to construct the basis for judging sudden bearing capacity drop. The specific implementation method for this step is as follows: Starting from the initial time point of the subsidence evolution time interval, continuous bearing capacity change trend data are collected on the surface area below the photovoltaic array under a unified time scale. Within the subsidence evolution time interval, the bearing capacity response status of the same spatial location at different time points is recorded at second-level time intervals, forming a data sequence of surface bearing capacity change trends spanning the entire subsidence evolution time interval. In this data sequence, the bearing capacity response value at each time point and the transient scour intensity indicator corresponding to the same time point are arranged in parallel, so that each time number simultaneously contains surface bearing capacity change trend data and transient scour intensity indicator values. This forms a synchronous sequence of bearing capacity change and scour intensity change within the subsidence evolution time interval in the time dimension, providing a continuous data foundation for subsequent extraction of bearing capacity attenuation rate.

[0034] Based on the established synchronous sequence of bearing capacity changes within the time interval of subsidence evolution, the surface bearing capacity change trend data is unfolded second by second. The change range of bearing capacity values ​​between consecutive time nodes is recorded. The entire process of the bearing capacity value continuously decreasing from the initial value to the lowest value is divided into continuous attenuation segments. Within each attenuation segment, the duration and cumulative decrease of the bearing capacity value are statistically analyzed. By arranging the cumulative decrease range with the corresponding duration, a bearing capacity attenuation rate change sequence is formed that runs through the subsidence evolution time interval. This allows the bearing capacity attenuation rate to reflect the changing trend of the surface bearing capacity decrease process second by second on a unified time scale, while maintaining consistency with the transient scour intensity on the time axis.

[0035] After the bearing capacity attenuation rate change sequence has been formed, this sequence is arranged second-by-second with the transient scour intensity markers within the collapse evolution time interval. The bearing capacity attenuation rate values ​​at corresponding time nodes are extracted for the rising, peak, and falling phases of the transient scour intensity markers. The change process of bearing capacity attenuation rate under different scour intensity stages is compared. When the transient scour intensity marker is in a high value range, the continuous change of bearing capacity attenuation rate within that time interval is recorded. The peak time period of the transient scour intensity marker is superimposed with the time period when the bearing capacity attenuation rate reaches its peak, and the overlap length and corresponding numerical change amplitude on the time axis are statistically analyzed. By continuously recording and arranging the collapse evolution time intervals during multiple cold front processes, a set of correspondences between the transient scour intensity marker value segments and the bearing capacity attenuation rate segments is formed, so that the linkage between the change of transient scour intensity marker and the change of bearing capacity attenuation rate can be continuously expressed in the time dimension.

[0036] Based on the established linkage between transient scour intensity indicators and bearing capacity attenuation rates, the sections of rapid decline in bearing capacity values ​​within the subsidence evolution time interval are comprehensively organized. The intervals where the bearing capacity attenuation rate exceeds a predetermined range within a unit time and coincides with the peak time period of the transient scour intensity indicator are defined as bearing capacity sudden drop sections. The start time of these bearing capacity sudden drop sections is used as the trigger time node for bearing capacity sudden drop determination. At the same time, the corresponding transient scour intensity indicator value range within these sections is recorded as the intensity basis for bearing capacity sudden drop determination. This forms a bearing capacity sudden drop determination basis that includes time and intensity boundaries. This allows the bearing capacity sudden drop determination basis to directly determine the time node when the surface bearing capacity enters a sudden drop state by real-time comparison of transient scour intensity indicators and bearing capacity attenuation rates during subsequent cold front processes, providing a continuous, unified, and traceable determination basis for risk warning.

[0037] Step 5: Based on the criteria for judging sudden pressure drop, a high-frequency dynamic tracking process is initiated before the arrival of the subsequent cold front to compare the synchronization between the sudden pressure drop and the transient scour intensity indicator in real time, and issue a risk warning when the preset critical mapping condition is reached. The specific implementation method for this step is as follows: After establishing the criteria for determining sudden pressure drop, the time segment boundaries and corresponding transient scour intensity value ranges in the criteria are used as reference benchmarks for subsequent tracking. A continuous observation period is pre-set before the arrival of the subsequent cold front, and air pressure is continuously recorded at second-level time intervals during this continuous observation period to form a new second-level air pressure change curve. At the same time, near-surface airflow instantaneous velocity data is recorded synchronously at the same time scale, and transient scour intensity indicators for the corresponding time nodes are generated in real time according to the existing mapping relationship. This ensures that the new air pressure drop amplitude data and transient scour intensity indicators maintain a one-to-one correspondence on the time axis, thereby completing the synchronous generation of air pressure change data and transient scour intensity indicators before the subsequent cold front has completely passed, providing a continuous data source for the high-frequency dynamic tracking process.

[0038] During the aforementioned continuous observation period, the real-time pressure drop amplitude is time-aligned with the pressure drop segment recorded in the existing load-bearing sudden drop judgment criteria. The pressure value for each second is compared second by second with the corresponding pressure drop amplitude range in the load-bearing sudden drop judgment criteria. At the same time, the transient scour intensity indicator value generated at the same time node is read, and this value is arranged in parallel with the transient scour intensity indicator range of the corresponding time period in the load-bearing sudden drop judgment criteria. This makes the real-time pressure drop amplitude and the real-time transient scour intensity indicator form a synchronous comparison sequence under a unified time scale, thereby establishing a real-time mapping and comparison relationship in the subsequent cold front process.

[0039] Based on the established real-time mapping relationship, the synchronous changes between the pressure drop amplitude and the transient scour intensity indicator within consecutive time nodes are continuously analyzed. When the pressure drop amplitude enters the pressure drop amplitude range recorded in the load-bearing sudden drop judgment criteria within several consecutive seconds, and the transient scour intensity indicator enters the corresponding intensity range in the load-bearing sudden drop judgment criteria within the same consecutive time period, the entire consecutive time period is marked as a critical mapping candidate segment. The duration of this candidate segment and the corresponding pressure drop amplitude change trajectory and transient scour intensity indicator change trajectory are recorded. By continuously tracking the degree of overlap between the pressure drop amplitude and the transient scour intensity indicator on the time axis, time segments that meet the preset critical mapping conditions are gradually selected, so that the critical mapping conditions are continuously locked in the time dimension.

[0040] When the pressure drop amplitude and transient scour intensity indicator both fall within the mapping range defined by the load-bearing sudden drop judgment criteria within a certain continuous time interval, and the duration of this time interval reaches a predetermined length, this time interval is identified as a triggering interval that has reached the preset critical mapping condition. A risk warning is issued immediately at the start time of this triggering interval. At the same time, the pressure drop amplitude value, transient scour intensity indicator value, and corresponding time number within the triggering interval are fully recorded. This ensures that the risk warning is based on both the load-bearing sudden drop judgment criteria and the real-time synchronous comparison results. Thus, before the subsequent cold front has completed its entire process, the potential load-bearing sudden drop trend can be identified and warned in advance, realizing a high-frequency dynamic tracking and real-time risk warning process based on the load-bearing sudden drop judgment criteria.

[0041] Beneficial effect 1: This invention constructs a pre-frontal compression characteristic interval by performing correlation processing on a unified time scale on the second-level air pressure change curves before and after the passage of a cold front, the instantaneous velocity data of near-surface airflow, and the image data of fine particles starting on the ground before and after the passage of a cold front. Furthermore, it generates a transient erosion intensity label, so that the compression disturbance process that occurs in a short period of time can be continuously characterized. This breaks through the limitation of the traditional average wind speed statistical method in responding to the lag of instantaneous erosion behavior, and realizes the accurate identification of sheet-like synchronous transition and rapid particle extraction process, thereby improving the timeliness and pertinence of wind erosion intensity assessment.

[0042] Benefit 2: This invention establishes a basis for judging sudden drops in bearing capacity by correlating transient scour intensity indicators with the time interval of collapse evolution and the rate of bearing capacity attenuation. It also conducts high-frequency dynamic tracking before the arrival of subsequent cold fronts to achieve real-time comparison between the magnitude of sudden air pressure drop and transient scour intensity indicators. When the preset critical mapping conditions are reached, a risk warning is issued, thereby enabling early identification of sudden changes in the surface bearing capacity and improving the safety management and risk warning capabilities during the operation of photovoltaic desertification control projects.

[0043] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for assessing the degree of soil wind erosion in photovoltaic desertification control projects, characterized in that, Includes the following steps: Step 1: Collect second-level air pressure change curves, near-surface airflow instantaneous velocity data, and surface fine particle initiation image data before and after the passage of the cold front. Perform time alignment processing under a unified time scale, extract the airflow leap segment corresponding to the sudden drop in air pressure, and form the pre-frontal compression characteristic interval. Step 2: Extract the displacement amplitude change data of surface particles within the compression characteristic range before the front, calculate the synchronous transition intensity of the particle population, and synchronously map the pressure drop amplitude with the synchronous transition intensity of the particle population to generate a transient scour intensity identifier. Step 3: Based on the transient scour intensity indicator, perform high-frequency unfolding analysis on the continuous change data of the micro-topography of the ground surface below the photovoltaic array to identify the period of depression formation corresponding to the rapid detachment of particles, and form the time interval of the collapse evolution. Step 4: Combine the time interval of subsidence evolution, continuously track the trend data of surface bearing capacity changes, extract the bearing capacity attenuation rate, and establish the linkage relationship between the bearing capacity attenuation rate and the transient scour intensity indicator to construct the basis for judging sudden bearing capacity drop. Step 5: Based on the criteria for judging sudden pressure drop, a high-frequency dynamic tracking process is initiated before the arrival of the subsequent cold front. The synchronization between the sudden pressure drop and the transient scour intensity indicator is compared in real time, and a risk warning is issued when the preset critical mapping condition is reached.

2. The method for assessing the degree of soil wind erosion in photovoltaic desertification control projects according to claim 1, characterized in that, The process involves collecting second-level air pressure change curves, near-surface airflow instantaneous velocity data, and surface fine particle initiation image data before and after the passage of a cold front, and forming a pre-frontal compression characteristic region, including the following steps: During the cold front impact forecast period, the continuous data collection period is from two hours before the arrival of the cold front to one hour after its passage. The air pressure is continuously recorded at second-level time intervals to form a second-level air pressure change curve. At the same time starting point, the instantaneous velocity data of the near-ground airflow and the surface fine particle initiation image data are recorded simultaneously, so that the air pressure change curve, the instantaneous velocity data of the near-ground airflow and the surface fine particle initiation image data are marked with the same time numbering method. Using the start time of the cold front's influence period as the unified zero point of the time scale, the second-level air pressure change curve, the instantaneous velocity data of near-ground airflow, and the surface fine particle initiation image data are mapped to the same continuous time axis. The air pressure value and the instantaneous velocity value of near-ground airflow corresponding to each second are arranged synchronously to form a synchronous sequence of air pressure change and instantaneous velocity change of near-ground airflow. In the synchronous sequence, we screened out continuous time intervals where the air pressure continuously decreased and the instantaneous velocity of the near-ground airflow continuously increased, and retrieved the surface fine particle initiation image data with the corresponding time number. We recorded the particle displacement direction and displacement distance within the continuous time frame to form a complete disturbance time window. The pressure drop segment and airflow rise segment within the complete disturbance time window are time-overlaid, and the overlapping intervals on the time axis, together with the corresponding surface fine particle initiation image data segments, are defined as the pre-frontal compression characteristic interval.

3. The method for assessing the degree of soil wind erosion in photovoltaic desertification control projects according to claim 2, characterized in that, The complete disturbance time window covers the stage of continuous pressure decline, the stage of continuous increase in instantaneous velocity of near-surface airflow, and the stage of continuous particle transition in the surface fine particle initiation image data. The pre-frontal compression feature interval retains the numerical sequence of pressure change, the numerical sequence of instantaneous velocity of near-surface airflow, and the particle displacement image sequence on the corresponding time axis.

4. The method for assessing the degree of soil wind erosion in photovoltaic desertification control projects according to claim 2, characterized in that, Extracting surface particle displacement amplitude variation data around the pre-frontal compression characteristic range and generating transient scour intensity indicators includes the following steps: Within the starting and ending time range of the frontal compression feature interval, the surface fine particle initiation image data is retrieved second by second. The spatial position of particles in the continuous time frame is compared frame by frame. The initial position and corresponding position changes of particles are recorded to form a particle displacement trajectory sequence. The displacement distance of all particles in each second is counted to obtain the surface particle displacement amplitude change data. The data on the variation of surface particle displacement amplitude are correlated with the data on sudden drop in air pressure and instantaneous velocity of near-surface airflow at the corresponding time number within the compression characteristic interval of the front, forming a multi-source time series set containing air pressure values, instantaneous velocity values ​​of near-surface airflow, and particle displacement amplitude values. The particle displacement direction and displacement distance within the same time node are statistically analyzed to calculate the synchronous transition intensity of the particle population. The synchronous transition intensity of the particle population and the pressure drop amplitude within the pre-frontal compression characteristic range are arranged second by second on a unified time scale. The pressure drop segment and the particle population synchronous transition intensity change segment are time-overlaid to construct the synchronous mapping relationship between the pressure drop amplitude and the particle population synchronous transition intensity. The synchronous mapping relationship is sorted out in time sequence, and the values ​​of the pressure drop range segment and the synchronous transition intensity values ​​of the particle population at the corresponding time node are integrated to form a comprehensive identifier that includes the pressure drop range value, the synchronous transition intensity value of the particle population and the duration. The comprehensive identifier is defined as the transient scour intensity identifier.

5. The method for assessing soil wind erosion in photovoltaic desertification control projects according to claim 4, characterized in that, In the synchronous mapping relationship, the overlapping section of the pressure drop amplitude and the synchronous transition intensity of the particle population on the time axis is used as the intensity determination interval, and the duration of the overlapping section is included in the comprehensive identifier.

6. The method for assessing the degree of soil wind erosion in photovoltaic desertification control projects according to claim 4, characterized in that, The time interval for collapse evolution is determined based on transient scour intensity indicators, including the following steps: Under a unified time scale, with the time node corresponding to the transient scour intensity as the center, the continuous time range is determined by extending to the time node of the sudden drop in air pressure and the time node of the synchronous transition intensity of the particle group falling back to the initial level. The continuous change data of the micro-topography of the ground surface below the photovoltaic array is retrieved second by second to form a time series elevation change set. Within the time series elevation change set, the elevation difference of each spatial location is recorded second by second around the peak time node of the transient scour intensity indicator. Spatial locations with continuously decreasing elevation are marked as particle detachment areas, forming a surface depression change data sequence, which is then synchronized with the transient scour intensity indicator. In the data sequence of surface depression changes, select the continuous time intervals before and after the peak of transient scour intensity, record the entire process of elevation drop at each spatial location, mark the continuous drop intervals at multiple spatial locations as the depression formation period, and overlay them with the time interval of the peak of transient scour intensity. Starting from the initial time of the depression formation period and ending at the time when the rate of surface elevation decline recovers to the pre-scour level, continuous changes in surface micro-topography and transient scour intensity values ​​are collected within the corresponding time range to form the time interval of the subsidence evolution.

7. The method for assessing the degree of soil wind erosion in photovoltaic desertification control projects according to claim 6, characterized in that, The formation period of a depression must simultaneously meet the following conditions: multiple spatial locations in the surface depression change data sequence show a continuous decrease in elevation, and the corresponding time period overlaps with the peak time period of the transient scour intensity indicator on a unified time scale. This overlapping time range is taken as the core judgment segment of the time interval of the subsidence evolution.

8. The method for assessing the degree of soil wind erosion in photovoltaic desertification control projects according to claim 6, characterized in that, The criteria for determining sudden load-bearing capacity reduction are constructed by combining the time interval of the collapse evolution, including the following steps: Starting from the beginning of the subsidence evolution time interval under a unified time scale, the bearing capacity change trend data of the surface area below the photovoltaic array is collected second by second to form a data sequence of surface bearing capacity change trend that runs through the subsidence evolution time interval. The surface bearing capacity change trend data of each time node and the corresponding transient scour intensity indicator are arranged in parallel to form a synchronous sequence. The change in load value between consecutive time nodes is recorded second by second in the synchronization sequence. The attenuation segment where the load value continues to decrease is divided, and the duration and cumulative decrease of each attenuation segment are counted to form a load attenuation rate change sequence. The sequence of bearing capacity attenuation rate changes is arranged second by second with the transient scour intensity markers within the time interval of collapse evolution. The peak time interval of the transient scour intensity markers and the peak time interval of the bearing capacity attenuation rate are time-overlaid to form a set of correspondences between the transient scour intensity markers and the bearing capacity attenuation rate. In the corresponding relationship set, select the interval where the load attenuation rate exceeds the predetermined range of change per unit time and coincides with the peak time period of the transient scour intensity indicator to determine the load drop segment. Then, construct the load drop judgment basis based on the starting time node of the load drop segment and the corresponding transient scour intensity indicator value range.

9. The method for assessing the degree of soil wind erosion in photovoltaic desertification control projects according to claim 8, characterized in that, The criteria for determining the sudden drop in load capacity include the starting time of the sudden drop section and the corresponding range of transient scour intensity indicators. The coincidence of the peak time period of the transient scour intensity indicator and the peak time period of the load attenuation rate on the time axis is used as the condition for determining the sudden drop section in load capacity.

10. The method for assessing the degree of soil wind erosion in photovoltaic desertification control projects according to claim 8, characterized in that, To determine the criteria for sudden load drops, high-frequency dynamic tracking and risk warnings will be conducted, including the following steps: Under a unified time scale, with reference to the time segment boundary and transient scour intensity indicator range in the criteria for determining sudden drop in load, a continuous observation period is set, and the air pressure is recorded second by second to form a second-level air pressure change curve. Simultaneously, the instantaneous velocity data of the near-ground airflow is recorded to generate the transient scour intensity indicator for the corresponding time node. The pressure drop amplitude in the second-level pressure change curve is compared with the pressure drop amplitude range in the load-bearing sudden drop judgment criteria every second. At the same time, the transient scour intensity indicator at the corresponding time node is arranged in parallel with the transient scour intensity indicator value range in the load-bearing sudden drop judgment criteria to form a real-time mapping comparison relationship. In the real-time mapping comparison relationship, select continuous time segments where the pressure drop amplitude enters the pressure drop amplitude range and the transient scour intensity indicator enters the transient scour intensity indicator value range, record the duration of the continuous time segment and the corresponding change trajectory, and form a critical mapping candidate segment. When the duration of the candidate critical mapping segment reaches a predetermined length, the trigger segment that meets the preset critical mapping conditions is determined, and a risk warning is issued at the start time node of the trigger segment.

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