Freeze-thaw cycle erosion thinning risk assessment method and system for slope cropland in black soil area
By coupling a freeze-thaw cycle simulation module into the watershed hydrological model, the accuracy of risk assessment for freeze-thaw cycle erosion and thinning of sloping farmland in the black soil region was solved, and the quantitative calculation of the black soil layer thinning rate and the objective identification of degradation risk were realized.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA AGRI UNIV
- Filing Date
- 2026-03-16
- Publication Date
- 2026-04-14
Smart Images
Figure CN121860431A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of agricultural environment and ecological protection technology, and in particular to a method and system for assessing the risk of thinning due to freeze-thaw cycle erosion of sloping farmland in black soil regions. Background Technology
[0002] Black soil, as an important agricultural resource, is characterized by high organic matter content, strong structural stability, and high fertility, serving as a crucial foundation for ensuring food security. However, under sloping farmland conditions, the surface layer of black soil is highly susceptible to continuous soil erosion due to the long-term effects of precipitation runoff, tillage disturbance, and climate change. This directly leads to a gradual thinning of the black soil layer year by year, resulting in a decline in soil productivity and increasingly prominent black soil degradation problems.
[0003] To address this issue, existing research and management practices often employ watershed-scale hydrological models for soil erosion assessment. For example, soil and water assessment tools are widely used for calculating soil erosion because they can comprehensively simulate precipitation, runoff, erosion, and agricultural management processes. In practice, it is typically necessary to collect data on the watershed's topography, soil, land use, and meteorological characteristics, as well as monitoring data on river flow and sediment transport. Subsequently, based on digital elevation models, land use type, and soil type data, the study watershed is subdivided into sub-watersheds, further divided into hydrological response units to characterize hydrological and erosion processes under different slope, land use, and soil combinations. After inputting daily meteorological data into the model, the water balance module and modified general soil loss equation within the model are used, combined with parameters such as runoff, peak flow, and slope factor, to calculate and output soil erosion results for different regions, reflecting the regional soil erosion status.
[0004] While the aforementioned existing technologies can provide data on soil erosion, they still have significant technical limitations. Current evaluation indicators typically focus on surface runoff and soil erosion, which are mostly expressed in mass units. These indicators are difficult to intuitively represent the actual changes in black soil layer thickness and cannot be effectively compared with the natural formation rate of black soil, thus limiting their application in identifying and warning of black soil thinning and degradation risks. Particularly in seasonally frozen soil regions, existing models often use simplified empirical algorithms to estimate soil temperature, failing to characterize complex soil thermodynamic processes. They cannot effectively reflect the insulating effect of snow layers during freeze-thaw cycles or the phase transition between liquid water and solid ice within the soil profile. Consequently, the amplifying effect of freeze-thaw cycles on the erosion process is not accurately considered, ultimately making it difficult to accurately identify and warn of black soil thinning and degradation risks. Summary of the Invention
[0005] To address the problems existing in the prior art, this invention provides a method and system for assessing the risk of thinning due to freeze-thaw cycles in sloping farmland in black soil regions. This method can quantitatively calculate the rate of thinning of the black soil layer under freeze-thaw cycles and objectively determine the risk of degradation.
[0006] To achieve the above objectives, this invention provides a method for assessing the risk of freeze-thaw cycle erosion and thinning of sloping farmland in black soil regions, comprising: Obtain digital elevation models, land use data, soil type data, and meteorological data for the target black soil region; Based on the digital elevation model, land use data, and soil type data, the target black soil area is divided into multiple hydrological response units. Based on the meteorological data, a watershed hydrological model coupled with a freeze-thaw cycle simulation module is used to simulate the soil erosion process of each hydrological response unit under the action of freeze-thaw cycle, and the soil erosion amount of each hydrological response unit is obtained; the freeze-thaw cycle simulation module is used to simulate soil temperature changes, water-ice phase change process and snow layer insulation effect. The corresponding black soil thinning rate is calculated based on the soil erosion amount and the corresponding topsoil bulk density of each hydrological response unit; the topsoil bulk density is determined based on the soil type data. The thinning rate of each black soil layer is compared with a preset threshold for the natural soil formation rate of black soil, and the thinning risk assessment result of the target black soil area is determined based on the comparison result.
[0007] Optionally, based on the digital elevation model, land use data, and soil type data, the target black soil region is divided into multiple hydrological response units, including: Based on the digital elevation model, the target black soil area is divided into multiple sub-basins, and the slope information of each sub-basin is determined. The slope information of each sub-basin is classified according to the preset level threshold to obtain the slope classification result. By combining the land use data, the soil type data, and the slope classification results, areas within each sub-basin that have the same land use type, the same soil type, and belong to the same slope level are divided into an independent hydrological response unit.
[0008] Optionally, the freeze-thaw cycle simulation module simulates the soil temperature change, water-ice phase change process, and snow layer insulation effect based on the stratified heat conduction equation and the surface energy balance algorithm.
[0009] Optionally, the layered heat conduction equation is: In the formula, The temperature of the soil or snow layer; For time step; This refers to the depth from the Earth's surface. Soil thermal conductivity; The volumetric heat capacity of the soil; This is a latent heat term.
[0010] Optionally, the formula for calculating the thinning rate of the black soil layer is: In the formula, Indicates the rate of thinning of the topsoil; Surface runoff; To reach the peak runoff rate; To simulate the area of the unit cell; Under the influence of freeze-thaw cycles over time Dynamically updated soil erodibility factors; For coverage and management factors; To support the practical factor; For terrain factors; This is the roughness correction factor; For freeze-thaw cycles over time Dynamically updated soil bulk density.
[0011] Optionally, the thinning risk assessment result of the target black soil region is determined based on the comparison results, including: Based on the comparison results between the black soil thinning rate of each hydrological response unit and the threshold of the natural soil formation rate of the black soil, the corresponding degradation risk level is determined. Based on the degradation risk level of each hydrological response unit, a spatial distribution map of the thinning degradation risk level of the target black soil area is generated as the result of the thinning risk assessment.
[0012] Optionally, the meteorological data includes daily precipitation, temperature data, solar radiation, and relative humidity data.
[0013] This invention also provides a risk assessment system for freeze-thaw cycle erosion and thinning of sloping farmland in black soil regions, comprising: The data acquisition unit is used to acquire digital elevation models, land use data, soil type data, and meteorological data for the target black soil region. Spatial division unit, used to divide the target black soil area into multiple hydrological response units based on the digital elevation model, land use data and soil type data; The erosion simulation unit is used to simulate the soil erosion process of each hydrological response unit under the action of freeze-thaw cycle based on the meteorological data and using a watershed hydrological model coupled with a freeze-thaw cycle simulation module, so as to obtain the soil erosion amount of each hydrological response unit; the freeze-thaw cycle simulation module is used to simulate soil temperature changes, water-ice phase change process and snow layer insulation effect. The thinning rate calculation unit is used to calculate the corresponding black soil layer thinning rate based on the soil erosion amount and the corresponding topsoil bulk density of each of the hydrological response units; the topsoil bulk density is determined based on the soil type data. The risk assessment unit is used to compare the thinning rate of each black soil layer with a preset threshold for the natural soil formation rate of black soil, and to determine the thinning risk assessment result of the target black soil area based on the comparison result.
[0014] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects: The method for assessing the risk of erosion and thinning of sloping farmland in black soil regions provided by this invention, by coupling a watershed hydrological model with a freeze-thaw cycle simulation module, simulates soil temperature changes, water-ice phase transition processes, and the insulating effect of snow layers through physical mechanisms. This accurately incorporates the amplifying effect of freeze-thaw cycles on erosion into the simulation system, effectively overcoming the shortcomings of existing empirical algorithms in terms of process distortion. By combining the simulated soil erosion amount with the topsoil bulk density determined based on soil type data, a quantitative conversion relationship between erosion mass and black soil layer thickness loss is established, enabling the representation of soil erosion intensity using the black soil layer thinning rate as a direct indicator. By comparing the black soil layer thinning rate with the threshold of the natural black soil formation rate, a quantitative determination is made as to whether the black soil layer consumption exceeds the natural recovery capacity, overcoming the limitation of existing technologies that can only describe the intensity of erosion but cannot identify the critical state of black soil degradation. This invention provides a technical solution with clear physical meaning and well-defined decision-making direction for the identification and early warning of degradation risks in sloping farmland in black soil regions. Attached Figure Description
[0015] The above and other objects, features and advantages of the present invention will become more apparent from the more detailed description of exemplary embodiments of the invention in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same parts in the exemplary embodiments of the invention.
[0016] Figure 1 This is a schematic diagram of the method for assessing the risk of freeze-thaw cycle erosion and thinning of sloping farmland in black soil areas, as shown in an embodiment of the present invention. Figure 2 This is a schematic diagram illustrating the thinning risk assessment technical route of an embodiment of the present invention; Figure 3 This is a schematic diagram of the watershed hydrological model structure of the coupled freeze-thaw cycle module shown in an embodiment of the present invention; Figure 4 This is a schematic diagram illustrating an improved freeze-thaw cycle simulation module according to an embodiment of the present invention; Figure 5 This is a spatial distribution map of the rate of thinning of black soil layer in a certain watershed, as shown in an embodiment of the present invention. Figure 6This is a schematic diagram of the module structure of a risk assessment system for freeze-thaw cycle erosion and thinning of sloping farmland in black soil regions, as shown in an embodiment of the present invention. Detailed Implementation
[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0018] Please see Figure 1 and Figure 2 , Figure 1 A schematic diagram illustrating the methodology for assessing the risk of thinning due to freeze-thaw cycle erosion of sloping farmland in the black soil region. Figure 2 This is a schematic diagram of the technical route for thinning risk assessment.
[0019] Methods for assessing the risk of thinning due to freeze-thaw cycle erosion of sloping farmland in black soil regions include: S101: Obtain digital elevation models, land use data, soil type data, and meteorological data for the target black soil region.
[0020] In application, the first step is to acquire basic data for the target black soil region. This data is crucial for subsequent watershed delineation, hydrological simulation, and erosion calculations. Specifically, the required data includes four categories: digital elevation models, land use data, soil type data, and meteorological data.
[0021] A Digital Elevation Model (DEM) is fundamental data characterizing the topographic features of a target black soil region. It records the elevation information of various points on the Earth's surface and can be used to extract topographic parameters such as slope, aspect, and runoff paths. In practical applications, DEMs can be obtained from authoritative data platforms such as the National Earth System Science Data Center, the Geospatial Data Cloud, or relevant natural resources departments. The spatial resolution should be appropriately selected based on the area and accuracy requirements of the target black soil region. Alternatively, high-precision local DEMs can be obtained through methods such as UAV aerial surveys, stereo image pair extraction, and field measurements.
[0022] Land use data reflects the surface cover and utilization status of the target black soil region, including types such as cultivated land, forest land, grassland, water bodies, and construction land. This data can be obtained from the National Earth System Science Data Center, the Geospatial Data Cloud, or relevant natural resources departments, or through remote sensing image interpretation. Different land use types have different surface roughness, vegetation cover, and infiltration characteristics, which significantly affect surface runoff generation and soil erosion processes.
[0023] Soil type data records the spatial distribution and physicochemical properties of soils in the target black soil region, including soil texture, organic matter content, soil layer thickness, and soil bulk density. This data can also be obtained from the National Earth System Science Data Center, the Geospatial Data Cloud, or relevant natural resources departments, or through field surveys and sampling.
[0024] For example, meteorological data may include: daily precipitation, temperature data, solar radiation, and relative humidity data. Daily precipitation data is used to calculate surface runoff and soil erosion; temperature data, including maximum and minimum temperatures, is used for evapotranspiration calculations and freeze-thaw cycle simulations in the model; solar radiation and relative humidity data are used for energy balance calculations and evaporation estimation. This meteorological data can be obtained from local meteorological departments or the National Meteorological Science Data Center. The data sequence length should cover the entire simulation period to ensure the representativeness and reliability of the simulation results. For partially missing meteorological data, observations from nearby stations can be used for interpolation, or reanalysis meteorological datasets can be used for supplementation.
[0025] Furthermore, in addition to the four basic input data types mentioned above—digital elevation model, land use data, soil type data, and meteorological data—land management data and / or hydrological data can be supplemented as input data for the model, depending on the simulation accuracy requirements of the target black soil region, thereby further improving the accuracy of the simulation results and the adaptability to the scenario.
[0026] Land management data refers to data related to agricultural production management and soil and water conservation measures on sloping farmland in the target black soil region. This includes, but is not limited to, tillage systems, crop rotation patterns, irrigation systems, straw return to the field, and data on the layout, spatial distribution, and implementation years of soil and water conservation measures such as contour tillage, terrace construction, no-till, and reduced-tillage. This data is used to refine the determination of cover and management factors in the revised general soil loss equation. Supporting practical factors The assignment of values allows for differentiated simulation of soil erosion processes on sloping farmland under different agricultural management models and soil and water conservation measures, making the calculated rate of black soil thinning more consistent with the actual production and management conditions of the target black soil region. Land management data can be obtained through field surveys, farmer questionnaires, and statistical data from local agricultural and rural affairs departments and natural resources departments.
[0027] The hydrological data consists of measured sequence data from typical hydrological monitoring sections within the target black soil region's watershed, including but not limited to daily runoff and monthly / daily sediment transport data. The data sequence length must cover the complete freeze-thaw and erosion cycles. This data is primarily used for parameter calibration, verification, and simulation effectiveness validation of the watershed hydrological model coupled with the freeze-thaw cycle simulation module. Iterative optimization of the model's runoff generation and erosion calculation parameters using measured hydrological data can effectively reduce model simulation errors and improve the reliability of simulation results for surface runoff and soil erosion under freeze-thaw cycles. Hydrological data can be obtained from hydrological monitoring stations within the target black soil region's watershed, local water resources authorities, or supplemented using publicly available watershed hydrological datasets.
[0028] It should be noted that the aforementioned digital elevation model, land use data, and soil type data together constitute the basic geographic information framework of the target black soil region. From this framework, topographic features (such as slope, aspect, and runoff accumulation) can be further extracted for subsequent sub-basin delineation and hydrological response unit generation. Meanwhile, land management data provides information on human intervention in surface processes, which, together with meteorological data, drives the model operation.
[0029] S102: Based on digital elevation model, land use data and soil type data, the target black soil area is divided into multiple hydrological response units.
[0030] In application, the target black soil region needs to be spatially discretized based on digital elevation models, land use data, and soil type data, dividing it into multiple hydrological response units (HRUs). The hydrological response unit is the basic spatial unit for simulating hydrological processes and calculating soil erosion in watershed hydrological models. Each hydrological response unit has relatively uniform topographic features, land use types, and soil properties, effectively characterizing the differences in hydrological and erosion processes under different conditions.
[0031] For example, S102 specifically includes: Based on the digital elevation model, the target black soil area is divided into multiple sub-basins, and the slope information of each sub-basin is determined. The slope information of each sub-basin is classified according to the preset level threshold to obtain the slope classification result. By combining land use data, soil type data, and slope classification results, areas within each sub-basin that have the same land use type, the same soil type, and belong to the same slope level are divided into an independent hydrological response unit.
[0032] Specifically, the target black soil region is first divided into sub-basins based on a digital elevation model (DEM). The DEM records the spatial distribution of surface elevation, and topographic features such as watershed boundaries, runoff paths, and sub-basin divisions can be extracted through terrain analysis. During sub-basin division, watersheds and catchment areas are identified based on topographic relief and water flow direction, dividing the entire target black soil region into several relatively independent sub-basins. Each sub-basin represents a spatial unit with independent runoff characteristics, and the hydrological processes within it share certain similarities. Simultaneously with sub-basin division, the slope information for each sub-basin also needs to be determined, as slope is a key factor influencing surface runoff generation and soil erosion intensity.
[0033] Based on the slope information of each sub-basin, the slope needs to be classified. The slope classification can be determined by combining the normal distribution of the basin slope and referring to the "Classification and Grading Standards for Soil Erosion" issued by the Ministry of Water Resources of the People's Republic of China. When inputting into the model, it needs to be converted into a slope percentage format usable by the model. The purpose of slope classification is to discretize the continuously changing slope values into several levels, facilitating the subsequent division of hydrological response units and differentiated simulation of erosion processes. Different slope levels correspond to different erosion risk levels; the steeper the slope, the faster the surface runoff velocity, and the greater the soil erosion intensity. Taking a certain basin as an example, based on the normal distribution of the basin slope and the soil erosion intensity surface erosion classification standards, the slope is divided into 3° (5.2%), 8° (14.1%), 15° (26.8%), and 25° (46.6%).
[0034] After completing the sub-basin delineation and slope classification, it is necessary to further subdivide each sub-basin into several hydrological response units by combining land use data, soil type data, and slope classification results. The delineation principle is to classify areas within a sub-basin that have the same land use type, soil type, and slope grade into an independent hydrological response unit. In this way, the topography, land use, and soil characteristics within each hydrological response unit are highly consistent, accurately reflecting the differences in hydrological response and erosion processes under different spatial conditions. For example, within the same sub-basin, a cultivated black soil area with a slope of less than five degrees and a forest meadow soil area with a slope of more than fifteen degrees will be divided into two different hydrological response units, and hydrological simulations and erosion calculations will be performed separately for each unit.
[0035] The division into hydrological response units provides a refined spatial basis for subsequent soil erosion simulations. Because different hydrological response units differ in slope, land use, and soil type, their surface runoff generation mechanisms, infiltration capacity, vegetation cover conditions, and soil erosion resistance also vary. By dividing the target black soil region into multiple hydrological response units, subsequent watershed hydrological models can calculate surface runoff and soil erosion separately for each unit's characteristics, thereby improving the accuracy and spatial resolution of the simulation results.
[0036] S103: Based on meteorological data, a watershed hydrological model coupled with a freeze-thaw cycle simulation module is used to simulate the soil erosion process of each hydrological response unit under the action of freeze-thaw cycle, and the soil erosion amount of each hydrological response unit is obtained.
[0037] Please see Figure 3 , Figure 3 This is a schematic diagram of the watershed hydrological model structure with coupled freeze-thaw cycle modules. (See diagram below.) Figure 3 As shown, this invention, based on existing hydrological models (such as SWAT, Soil and Water Assessment Tool) with climate, hydrology, crop, nutrient, and erosion modules, couples a freeze-thaw cycle module based on physical mechanisms. This freeze-thaw cycle module interacts with the hydrology and erosion modules through quantitative relationship equations, dynamically updating soil bulk density and soil erosion factors. This enables accurate simulation of soil erosion processes on sloping farmland under the influence of freeze-thaw cycles, yielding data on soil freeze-thaw erosion and the rate of black soil thinning.
[0038] The freeze-thaw cycle simulation module is used to simulate soil temperature changes, water-ice phase transition processes, and the insulating effect of snow layers. Specifically, the freeze-thaw cycle simulation module simulates soil temperature changes, water-ice phase transition processes, and the insulating effect of snow layers based on the stratified heat conduction equation and the surface energy balance algorithm.
[0039] In the application, after the hydrological response units are divided, it is necessary to use the watershed hydrological model coupled with the freeze-thaw cycle simulation module based on the acquired meteorological data to simulate the soil erosion process of each hydrological response unit under the action of freeze-thaw cycle on a daily basis, so as to obtain the annual average soil erosion of each hydrological response unit in terms of mass units.
[0040] Existing watershed hydrological models, such as the Soil and Water Assessment Tool (SWAT), can comprehensively simulate precipitation, runoff, erosion, and agricultural management processes, and have been widely used for soil erosion assessment and scenario analysis. The SWAT model, through the combination of a water balance module and the Modified Universal Soil Loss Equation (MUSLE), can output soil erosion amounts for each hydrological response unit. However, when applied to cold regions or seasonally frozen soil areas, the original watershed hydrological models default to using simplified empirical algorithms to estimate soil temperature, making it difficult to characterize complex soil thermodynamic processes. In particular, they cannot effectively reflect the insulating effect of snow layers during freeze-thaw cycles, nor can they simulate the phase transition process between liquid water and solid ice within the soil profile. This limits their ability to accurately characterize the hydrological response and erosion processes driven by freeze-thaw cycles.
[0041] The simplified empirical algorithm formula described above is as follows: In the formula, The first of the year The depth of the sky is Soil temperature at the location (°C); This is the lag factor, used to weigh the soil temperature of the previous day. The impact; This is a depth factor used to quantify the impact of soil depth on temperature changes; The average annual temperature (°C); This represents the soil surface temperature on that day.
[0042] To address the aforementioned shortcomings, this invention couples a freeze-thaw cycle simulation module based on physical mechanisms into a watershed hydrological model, thereby achieving an accurate characterization of the freeze-thaw cycle process in seasonally frozen soil regions. Taking the SWAT model as an example, specifically, the freeze-thaw cycle module is integrated into the SWAT model, forming the SWAT-FT model. It should be noted that the improvement of this invention lies in coupling the freeze-thaw cycle simulation module based on physical mechanisms into the watershed hydrological model, rather than relying on a specific watershed hydrological model itself. Therefore, in addition to the SWAT model, the freeze-thaw cycle simulation module can also be integrated into other models or algorithms with soil and water loss calculation functions based on the same technical concept.
[0043] For example, soil erosion can also be calculated using empirical or physical erosion models such as the Universal Soil Loss Equation (USLE), the Modified Universal Soil Loss Equation (MUSLE), and the Water Erosion Prediction Model (WEPP); hydrological process simulation can also employ other watershed hydrological models such as HSPF, AGNPS, and EPIC. By integrating the aforementioned freeze-thaw cycle simulation module into the above models or algorithms, a physical simulation of the freeze-thaw erosion process in seasonally frozen soil regions can be achieved, and subsequent black soil thinning rate conversion and degradation risk assessment can be performed based on the simulation results.
[0044] To integrate the freeze-thaw cycle module with the watershed hydrological model, taking the SWAT model as an example, the application can be achieved by modifying the model's source code. Specifically, the original empirical soil temperature calculation module in the SWAT model is deleted, and the newly constructed freeze-thaw cycle simulation module based on physical mechanisms is embedded into the model's main calculation flow in source code form, replacing the original calculation logic for soil temperature and the freeze-thaw process. For example... Figure 3 As shown, the coupled model retains all the functions of the original SWAT climate, hydrology, crop, nutrient, and erosion modules. The freeze-thaw cycle simulation module interacts bidirectionally with the original modules at daily time steps. Within each calculation time step, the climate module inputs daily meteorological data such as air temperature, solar radiation, relative humidity, and wind speed into the freeze-thaw cycle simulation module. After completing the simulation calculations of soil temperature field, water-ice phase transition process, and snow layer insulation effect, the freeze-thaw cycle simulation module outputs real-time updated soil stratification temperature, soil liquid water content, soil bulk density, and saturated hydraulic conductivity parameters to the hydrology module. These parameters are used to correct key hydrological parameters such as soil infiltration capacity, surface runoff coefficient, and lateral flow path. The hydrology module outputs the calculated surface runoff and peak runoff rate to the erosion module. Simultaneously, the freeze-thaw cycle simulation module outputs dynamically updated soil erodibility factors to the erosion module. Finally, the erosion module performs quantitative calculations of soil erosion under freeze-thaw cycles.
[0045] See Figure 4 This freeze-thaw cycle simulation module simulates soil temperature changes, water-ice phase transition processes, and the insulating effect of snow cover. Its core lies in employing a layered heat conduction equation combined with a surface energy balance algorithm to comprehensively characterize the impact mechanism of freeze-thaw cycles on soil hydrothermal states. Based on the physical mechanisms of soil heat conduction and water-ice phase transition, the module uses a one-dimensional vertical layered structure as its core simulation framework, fully covering the hydrothermal coupling process of the snow-soil profile. The simulation domain is vertically divided into two main computational domains: a snow layer and a soil layer. The soil layer is discretized into multiple continuous computational layers at preset depth intervals, enabling a refined simulation of the vertical differences in the hydrothermal states of the soil profile. The boundary conditions of the simulation domain are divided into two categories: upper boundary and lower boundary. The upper boundary is the air-soil interface or the air-snow layer interface. When there is snow on the surface, the upper boundary is the air-snow layer interface, and when there is no snow, it is the air-soil interface. The lower boundary is the soil damping depth interface. This depth is the critical depth at which the soil temperature is not affected by short-term fluctuations in surface temperature, ensuring that the simulation domain can completely cover the influence range of the freeze-thaw cycle.
[0046] The simulation domain of the freeze-thaw cycle simulation module extends from the air-soil interface or air-snow interface to the damping depth. The upper boundary temperature is determined by the surface energy balance algorithm, which comprehensively considers net radiation, latent heat flux, sensible heat flux, and geothermal or conductive heat flux. The lower boundary is processed using the damping depth method, thereby ensuring computational efficiency while taking into account the buffering effect of deep soil thermal storage on surface temperature changes.
[0047] In the freeze-thaw cycle simulation module, the temperature change over time at any depth within the soil or snow layer follows the following stratified heat conduction equation: In the formula, Soil or snow cover temperature (°C); Time step (days); The depth (cm) from the ground surface; Soil thermal conductivity (J cm) -1 day -1 ℃ -1 ); Soil volumetric heat capacity (J cm³) -3 ℃ -1 ); For latent heat term (J cm) -3 day -1 This freeze-thaw cycle simulation module, when solving the stratified heat conduction equation, can accurately simulate the contribution of the latent heat released when liquid water transforms into solid ice during freezing to the soil temperature field, and the heat absorbed when solid ice transforms into liquid water during melting, by explicitly handling the latent heat term. At the same time, the equation incorporates the snow layer as a special medium with low thermal conductivity into the computational domain, thus truly reflecting the heat insulation and buffering effect of the snow cover on the heat exchange between the soil and the atmosphere.
[0048] To further quantify the impact of freeze-thaw cycles on soil erosion, this invention establishes a functional equation for the dynamic updating of soil parameters before and after freeze-thaw cycles. Specifically, based on the changes in soil bulk density and soil erodibility factors before and after freeze-thaw cycles, regression analysis is used to analyze the characteristics and relationships of data before and after freeze-thaw cycles. The initial values of parameters before freezing are set as independent variables x, and the parameter values after freeze-thaw cycles are set as dependent variables y. Multiple regression models are set up and the significance coefficients (…) are used to… p -value), coefficient of determination ( R 2 ), root mean square error ( RMSE The optimal regression model was selected based on indicators such as ( ), and the final quantitative function equation was determined as follows: In the formula, The original soil erodibility factor reflects the soil type's sensitivity to erosion and is usually determined by parameters such as soil particle composition, structure, and permeability. Original soil bulk density (g / cm³) -3 ); Time step (days); The depth (cm) from the ground surface; Soil temperature (°C) calculated by the improved freeze-thaw cycle module; Soil erodibility factors that are dynamically updated over time after taking into account the effects of freeze-thaw cycles; Soil bulk density (g / cm³) dynamically updated under freeze-thaw cycles -3 ).
[0049] Within each simulation time step, the freeze-thaw cycle simulation module first calculates the surface temperature using the surface energy balance algorithm, and then solves the aforementioned heat conduction equation layer by layer along the vertical direction to obtain the soil temperature and freeze-thaw phase distribution at each depth. These results are transmitted in real time to the hydrological module of the watershed hydrological model to correct key hydrological parameters such as soil infiltration capacity, surface runoff coefficient, and lateral flow path, so that the amplification effect of the freeze-thaw cycle on the runoff generation and confluence process can be explicitly expressed.
[0050] Based on this, the erosion module in the watershed hydrological model uses the improved modified general soil loss equation to calculate the daily soil erosion of each hydrological response unit. The specific form of this equation is: In the formula, The amount of soil erosion on that day (metric tons). Surface runoff (mm ha) -1 ); To achieve the peak runoff rate (m 3 s -1 ); The simulated unit area (ha); Under the influence of freeze-thaw cycles over time Dynamically updated soil erodibility factors can accurately characterize the dynamic impact of freeze-thaw cycles on soil erosion resistance. Coverage and management factors reflect the impact of vegetation cover and land management measures on soil erosion; To support practice factors, which represent the effectiveness of supportive soil conservation measures such as contour tillage and terracing, the specific agricultural practices and conservation measures are determined. The topographic factor represents the impact of topography on soil erosion. It is a roughness correction factor used to correct the impact of surface roughness on soil erosion.
[0051] With the introduction of the freeze-thaw cycle simulation module, the surface runoff calculated by the watershed hydrological model has been improved. With peak runoff rate The equation already inherently incorporates the combined effects of freeze-thaw cycles on soil structure damage, decreased infiltration capacity, and the superposition of snowmelt runoff. Therefore, the soil erosion output based on the above equation is... It can accurately reflect the actual erosion intensity of sloping farmland in seasonally frozen soil areas under the action of freeze-thaw cycles.
[0052] By simulating and accumulating data daily, the average annual soil erosion of each hydrological response unit during the complete simulation period can be obtained, recorded and output in tons per hectare. This qualitative erosion result retains the mature technical advantages of watershed hydrological models in soil and water loss assessment, and due to the coupling of the freeze-thaw cycle simulation module, it possesses physical consistency and reliability in cold regions, especially in sloping farmland applications in black soil areas. This provides accurate input data for subsequently converting erosion into the rate of black soil thinning and further conducting degradation risk assessment.
[0053] In applications, when supplementary land management data for the target black soil region is obtained, the management information matched by the hydrological response unit can be used to adjust the above equations. Factors and Factors are assigned refined values. For each hydrological response unit, coverage and management factors are determined based on its corresponding cropping system, straw return status, and crop rotation pattern. Precise value selection; for example, lower unit matching for no-till and full straw return to the field. Factor values indicate that traditional tillage patterns have higher unit matching rates. Factor values; based on the corresponding soil and water conservation measures such as contour farming and terrace construction, determine the support practice factors for the corresponding units. Precise value selection; for example, matching lower values to sloping farmland units where terraces are laid out. Factor values indicate that units practicing downhill cultivation have higher matching rates. Factor values.
[0054] By precisely matching and associating land management data with the spatial locations of various hydrological response units, differentiated simulations of soil erosion processes on sloping farmland under different agricultural management models and soil and water conservation measures can be achieved. , The value of the factor is closer to the actual production management situation, thereby improving the accuracy and scenario applicability of the calculation results of the black soil layer thinning rate.
[0055] Furthermore, when supplementary hydrological data for the target black soil region is obtained, it can be used for parameter calibration and validation of watershed hydrological models coupled with freeze-thaw cycle simulation modules. Specifically, the complete hydrological data sequence is divided into a calibration period and a validation period. Using the measured daily runoff and monthly sediment transport data from the calibration period as a benchmark, the simulated results of runoff and sediment transport at corresponding cross-sections from the model simulation are compared with the measured data, using the coefficient of determination. R 2 Nash efficiency coefficient NSE Percentage deviation PBIAS The accuracy of the simulation is evaluated using indicators such as [list of indicators].
[0056] If the simulation accuracy does not reach the preset threshold (e.g.) R 2 ≥0.60 NSE ≥0.5、 PBIAS If the absolute value of the runoff is ≤15%, then the model's key parameters for runoff generation and runoff, such as the number of runoff curves, effective soil water content, and saturated hydraulic conductivity, as well as key erosion parameters, such as the correction coefficient for soil erodibility factors, are adjusted through iterative optimization. The model is then re-simulated until its simulation accuracy meets the preset accuracy requirements. After calibration, hydrological data from the validation period are used to verify the model's simulation performance, ensuring reliable accuracy in runoff generation and runoff and erosion simulations during freeze-thaw cycles. This provides a calibrated model parameter basis for subsequent full-region soil erosion simulations. This calibration and validation process effectively reduces model uncertainty and ensures high reliability of the simulated surface runoff, soil erosion, and black soil thinning rate under freeze-thaw cycles.
[0057] S104: The corresponding rate of thinning of the black soil layer is calculated based on the soil erosion and the corresponding topsoil bulk density of each hydrological response unit.
[0058] The bulk density of the topsoil is determined based on soil type data.
[0059] After obtaining the soil erosion amount for each hydrological response unit, this qualitative index needs to be converted into a physical index that can intuitively characterize the changes in the thickness of the black soil layer. Existing technologies mainly use soil erosion amount as an evaluation index, typically expressed in tons per hectare (t / hectare). The technical logic behind this is to reflect the intensity of soil erosion by comparing the magnitude of erosion. However, since soil erosion amount is a qualitative index, it cannot directly characterize the actual change process of the black soil layer thickness, nor can it be effectively compared with the natural formation rate of black soil, thus limiting its application in the identification and early warning of black soil thinning and degradation risks. To address this problem, this invention establishes a quantitative conversion method from soil erosion amount to the rate of black soil thinning by combining soil erosion amount with the bulk density of the topsoil.
[0060] Specifically, for each hydrological response unit, the annual average soil erosion per unit area is divided by its corresponding topsoil bulk density to obtain the annual average thinning rate of the black soil layer in that unit. In this invention, due to the introduction of the freeze-thaw cycle simulation module, the soil erodibility factor... and soil bulk density All of these parameters change dynamically over time; therefore, the formula for calculating the thinning rate should use dynamically updated parameters, as follows: In the formula, Indicates the rate of thinning of the topsoil; Surface runoff; To reach the peak runoff rate; To simulate the area of the unit cell; To account for the effects of freeze-thaw cycles over time Dynamically updated soil erodibility factors; For coverage and management factors; To support the practical factor; For terrain factors; This is the roughness correction factor; For freeze-thaw cycles over time Dynamically updated soil bulk density.
[0061] Topsoil bulk density is the core parameter for performing the above conversion, and its value is determined based on soil type data. In practice, the corresponding topsoil bulk density parameter is determined from soil type data according to the soil type of each hydrological response unit. This parameter can be obtained through soil survey data or determined by referring to relevant soil databases or literature. Since soil bulk density reflects the compaction and porosity of the soil, its value directly affects the conversion of soil erosion into thickness change rate. Therefore, accurately determining the topsoil bulk density of each hydrological response unit is crucial for ensuring calculation accuracy.
[0062] The above calculations yield the black soil layer thinning rate for each hydrological response unit. This index characterizes the degree of black soil layer depletion in the form of thickness change rate, breaking through the traditional technical approach that uses soil erosion as the sole evaluation indicator. Figure 4 As shown, Figure 4 This study demonstrates the spatial distribution of the black soil thinning rate in a certain watershed. The black soil thinning rate can intuitively reflect the actual change process of the black soil layer thickness, facilitating comparison with the natural formation rate of black soil. This provides a technical benchmark and scientific basis for the subsequent quantitative identification and assessment of the risk of black soil thinning and degradation.
[0063] S105: Compare the thinning rate of each black soil layer with the preset threshold for the natural soil formation rate of black soil, and determine the thinning risk assessment result of the target black soil area based on the comparison results.
[0064] After obtaining the black soil thinning rate of each hydrological response unit, it is necessary to compare the rate with the preset black soil natural soil formation rate threshold to quantitatively determine whether the black soil layer is in an unsustainable consumption state, and to determine the thinning risk assessment result of the target black soil area accordingly.
[0065] The natural soil formation rate threshold for black soil is a risk assessment benchmark constructed based on long-term observations and epistemological studies of the natural soil formation process. Existing research indicates that under different climatic conditions and parent material backgrounds, it typically takes approximately 100 to 300 years to form 1 cm of topsoil naturally. For black soil regions with high organic matter content, vigorous biological activity, and relatively slow soil formation processes, the time required to form 1 cm of topsoil is even longer, typically requiring approximately 200 to 400 years. For example, the average annual soil formation rate corresponding to 200 years to form 1 cm of topsoil, i.e., 0.05 mm / year, can be used as a representative maximum tolerable erosion risk threshold. The physical significance of this threshold is that when the rate of thinning of the black soil layer due to soil erosion does not exceed 0.05 mm / year, the rate of black soil layer depletion is still within the range that can be compensated for by the natural soil formation process; once the thinning rate exceeds this threshold, it indicates that the loss of the black soil layer has exceeded its natural recovery capacity, and the degradation process has entered an unsustainable state.
[0066] In the specific implementation process, the rate of black soil thinning in each hydrological response unit is compared with a threshold of 0.05 mm / year. If the rate of black soil thinning in a certain hydrological response unit is less than or equal to the threshold, it is determined that the black soil consumption in that unit is within a sustainable range, and its degradation risk is low or negligible; if the rate of black soil thinning is greater than the threshold, it is determined that the black soil in that unit has entered an unsustainable consumption state, is under significant erosion pressure, and is at clear risk of erosion and degradation.
[0067] By sequentially performing the above comparisons and judgments on all hydrological response units within the target black soil region, a binary risk discrimination result for each unit can be obtained, which can then be used to comprehensively form a thinning risk assessment result covering the entire region. This assessment result, with the existence of unsustainable degradation risk in each unit as its basic output, intuitively reveals the spatial distribution pattern of net loss of black soil layer thickness under the current erosion intensity.
[0068] It should be noted that in practical applications, the threshold for the natural soil formation rate of black soil is not limited to a single fixed value. It can be set in zones according to the differences in soil types, climate zones, or land use conditions within the target black soil area. For example, for black soil subtypes with high organic matter content, vigorous biological activity, and relatively fast natural soil formation rates, a threshold slightly higher than 0.05 mm / year can be used; while for soil types with high sand content and relatively slow soil formation processes, a more stringent threshold standard should be adopted. In climate zones with significant differences in annual average temperature or precipitation gradients, the corresponding threshold values can also be determined based on existing research results on soil formation rates in that region. In addition, an interval threshold method can be used to classify and distinguish degradation risks, that is, to set multiple threshold intervals, for example, less than 0.05 mm / year, 0.05 to 0.10 mm / year, and greater than 0.10 mm / year can be corresponding to low risk, medium risk, and high risk levels, respectively, so that units with black soil thinning rates falling into different intervals can obtain corresponding risk level classifications. The threshold setting method based on zoning or grading described above can be combined with the steps of the present invention to achieve differentiated assessment of the degradation risk of sloping farmland in black soil areas under different soil types, climate conditions and management needs.
[0069] Compared with existing technologies, this invention introduces the parameter of natural soil formation rate of black soil into a watershed-scale degradation risk assessment system for the first time. Traditional methods can only describe the intensity of soil erosion based on the magnitude of erosion, but cannot answer the core question of whether erosion has exceeded the self-restoration capacity of black soil. This invention achieves quantitative discrimination of whether black soil degradation has occurred by comparing the simulated black soil thinning rate with a threshold with clear soil formation significance, thereby improving the scientific rigor of the assessment results and the directionality of management decisions. This threshold can not only be directly applied as a fixed discrimination standard, but can also be adaptively adjusted according to different black soil sub-regions, different parent material conditions, or the latest soil formation rate research results, providing an objective and quantifiable technical benchmark for the refined identification and early warning of degradation risk of sloping farmland in black soil areas.
[0070] In one embodiment, the above-mentioned determination of the thinning risk assessment result of the target black soil region based on the comparison results specifically includes: Based on the comparison results of the black soil thinning rate and the black soil natural soil formation rate threshold of each hydrological response unit, the corresponding degradation risk level is determined. Based on the degradation risk level of each hydrological response unit, a spatial distribution map of the thinning degradation risk level of the target black soil area is generated as the result of the thinning risk assessment.
[0071] In application, when determining the thinning risk assessment results of the target black soil area, the comparison results of the black soil thinning rate and the natural soil formation rate threshold of each hydrological response unit can be further processed. It is not only limited to the binary risk discrimination, but the comparison results are mapped to multiple continuous degradation risk levels, thereby generating a spatial distribution map of thinning degradation risk levels with spatial explicit expression capabilities, which serves as the final presentation form of the risk assessment results.
[0072] Specifically, when the rate of black soil thinning in a hydrological response unit exceeds a preset threshold for the natural soil formation rate (e.g., 0.05 mm / year), it indicates that the rate of black soil consumption in that unit has exceeded the replenishment capacity of the natural soil formation process, and the black soil layer is in an unsustainable net loss state. The unit is therefore deemed to be at risk of erosion and degradation. Based on this, the risk can be further classified into several progressive levels according to the specific extent to which the black soil thinning rate exceeds the threshold. The smaller the exceedance, the more critical the degradation level; the larger the exceedance, the higher the degradation intensity, the more severe the black soil consumption, and the greater the urgency of taking protective measures. If the black soil thinning rate is below or equal to the threshold, the black soil consumption in that unit is considered to be within the range that the natural recovery capacity can bear, and its degradation risk level is correspondingly at the lowest level. The above classification rules can be implemented using a fixed multiple or fixed threshold at equal intervals, or can be adaptively adjusted according to different slope grades, soil types, or protection targets in the target black soil area.
[0073] After assigning degradation risk levels to each hydrological response unit, the risk level determination results of each unit are correlated with its spatial location to generate a spatial distribution map of thinning degradation risk levels covering the entire target black soil region. This map uses hydrological response units as the basic mapping units and represents different risk intensities through differentiated color scales, fill styles, or symbol systems. This transforms the numerical discrimination results of comparing each unit with a threshold into an intuitive and shareable spatial information product. The map can be simultaneously overlaid with auxiliary geographic elements such as sub-basin boundaries, sloping farmland extent, slope grading layers, and administrative divisions, making it not only a risk level rendering map but also a data reference for watershed-scale black soil protection decisions.
[0074] This distribution map clearly identifies which areas have entered an unsustainable degradation state, which areas are particularly severely degraded, and which areas are still within the safe threshold. This provides a directly applicable technical basis for the classified management of sloping farmland, the precise implementation of differentiated prevention and control measures, and the prioritization of key soil and water conservation projects. Compared with existing technologies that can only describe the intensity of soil erosion based on erosion volume, this invention introduces a risk level system linked to the natural soil formation rate and its spatial expression, achieving a dual quantitative determination of whether black soil degradation has occurred and to what extent. This enhances the practical application value of the evaluation results in degradation status identification and protection priority classification.
[0075] Corresponding to the aforementioned application function implementation method embodiments, the present invention also provides a risk assessment system for freeze-thaw cycle erosion and thinning of sloping farmland in black soil areas and corresponding embodiments.
[0076] Please see Figure 6 , Figure 6 A schematic diagram of the module structure of a risk assessment system for freeze-thaw cycle erosion and thinning of sloping farmland in the black soil region.
[0077] A risk assessment system for freeze-thaw cycle erosion and thinning of sloping farmland in black soil regions includes: Data acquisition unit 61 is used to acquire digital elevation models, land use data, soil type data and meteorological data of the target black soil area; Spatial division unit 62 is used to divide the target black soil area into multiple hydrological response units based on digital elevation model, land use data and soil type data; Erosion simulation unit 63 is used to simulate the soil erosion process of each hydrological response unit under the action of freeze-thaw cycle based on meteorological data and using a watershed hydrological model coupled with a freeze-thaw cycle simulation module, so as to obtain the soil erosion amount of each hydrological response unit; the freeze-thaw cycle simulation module is used to simulate soil temperature changes, water-ice phase change process and snow layer insulation effect. Thinning rate calculation unit 64 is used to calculate the corresponding black soil thinning rate based on the soil erosion amount and corresponding topsoil bulk density of each hydrological response unit; the topsoil bulk density is determined based on soil type data. Risk assessment unit 65 is used to compare the thinning rate of each black soil layer with the preset threshold of the natural soil formation rate of black soil, and to determine the thinning risk assessment result of the target black soil area based on the comparison result.
[0078] In one embodiment, regarding the division of the target black soil region into multiple hydrological response units based on digital elevation models, land use data, and soil type data, the aforementioned spatial division unit 62 is specifically used for: Based on the digital elevation model, the target black soil area is divided into multiple sub-basins, and the slope information of each sub-basin is determined. The slope information of each sub-basin is classified according to the preset level threshold to obtain the slope classification result. By combining land use data, soil type data, and slope classification results, areas within each sub-basin that have the same land use type, the same soil type, and belong to the same slope level are divided into an independent hydrological response unit.
[0079] In one embodiment, in determining the thinning risk assessment result of the target black soil region based on the comparison results, the aforementioned risk assessment unit 65 is specifically used for: Based on the comparison results of the black soil thinning rate and the black soil natural soil formation rate threshold of each hydrological response unit, the corresponding degradation risk level is determined. Based on the degradation risk level of each hydrological response unit, a spatial distribution map of the thinning degradation risk level of the target black soil area is generated as the result of the thinning risk assessment.
[0080] Regarding the system in the above embodiments, the specific manner in which each unit module performs operations has been described in detail in the embodiments related to the method, and will not be elaborated further here.
[0081] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.
Claims
1. A method for assessing the risk of freeze-thaw cycle erosion thinning of sloping farmland in a black soil region, characterized in that, include: Obtain digital elevation models, land use data, soil type data, and meteorological data for the target black soil region; Based on the digital elevation model, land use data, and soil type data, the target black soil area is divided into multiple hydrological response units. Based on the meteorological data, a watershed hydrological model coupled with a freeze-thaw cycle simulation module is used to simulate the soil erosion process of each hydrological response unit under the action of freeze-thaw cycle, and the soil erosion amount of each hydrological response unit is obtained; the freeze-thaw cycle simulation module is used to simulate soil temperature changes, water-ice phase change process and snow layer insulation effect. The corresponding black soil thinning rate is calculated based on the soil erosion amount and the corresponding topsoil bulk density of each hydrological response unit; the topsoil bulk density is determined based on the soil type data. The thinning rate of each black soil layer is compared with a preset threshold for the natural soil formation rate of black soil, and the thinning risk assessment result of the target black soil area is determined based on the comparison result.
2. The method according to claim 1, wherein, Based on the aforementioned digital elevation model, land use data, and soil type data, the target black soil region is divided into multiple hydrological response units, including: Based on the digital elevation model, the target black soil area is divided into multiple sub-basins, and the slope information of each sub-basin is determined. The slope information of each sub-basin is classified according to the preset level threshold to obtain the slope classification result. By combining the land use data, the soil type data, and the slope classification results, areas within each sub-basin that have the same land use type, the same soil type, and belong to the same slope level are divided into an independent hydrological response unit.
3. The method according to claim 1, wherein, The freeze-thaw cycle simulation module simulates soil temperature changes, water-ice phase transition processes, and the heat insulation effect of snow layers based on the stratified heat conduction equation and the surface energy balance algorithm.
4. The method for assessing the risk of thinning due to freeze-thaw cycle erosion of sloping farmland in black soil areas according to claim 3, characterized in that, The layered heat conduction equation is: In the formula, The temperature of the soil or snow layer; For time step; This refers to the depth from the Earth's surface. Soil thermal conductivity; The volumetric heat capacity of the soil; This is a latent heat term.
5. The method for assessing the risk of thinning due to freeze-thaw cycle erosion of sloping farmland in black soil areas according to claim 1, characterized in that, The formula for calculating the thinning rate of the black soil layer is: In the formula, Indicates the rate of thinning of the topsoil; Surface runoff; To reach the peak runoff rate; To simulate the area of the unit cell; Under the influence of freeze-thaw cycles over time Dynamically updated soil erodibility factors; For coverage and management factors; To support the practical factor; For terrain factors; This is the roughness correction factor; For freeze-thaw cycles over time Dynamically updated soil bulk density.
6. The method for assessing the risk of freeze-thaw cycle erosion and thinning of sloping farmland in black soil areas according to claim 1, characterized in that, The thinning risk assessment results of the target black soil region are determined based on the comparison results, including: Based on the comparison results between the black soil thinning rate of each hydrological response unit and the threshold of the natural soil formation rate of the black soil, the corresponding degradation risk level is determined. Based on the degradation risk level of each hydrological response unit, a spatial distribution map of the thinning degradation risk level of the target black soil area is generated as the result of the thinning risk assessment.
7. The method for assessing the risk of thinning due to freeze-thaw cycle erosion of sloping farmland in black soil regions according to claim 1, characterized in that, The meteorological data includes daily precipitation, temperature data, solar radiation, and relative humidity data.
8. A risk assessment system for freeze-thaw cycle erosion and thinning of sloping farmland in black soil regions, characterized in that, include: The data acquisition unit is used to acquire digital elevation models, land use data, soil type data, and meteorological data for the target black soil region. Spatial division unit, used to divide the target black soil area into multiple hydrological response units based on the digital elevation model, land use data and soil type data; The erosion simulation unit is used to simulate the soil erosion process of each hydrological response unit under the action of freeze-thaw cycle based on the meteorological data and using a watershed hydrological model coupled with a freeze-thaw cycle simulation module, so as to obtain the soil erosion amount of each hydrological response unit; the freeze-thaw cycle simulation module is used to simulate soil temperature changes, water-ice phase change process and snow layer insulation effect. The thinning rate calculation unit is used to calculate the corresponding black soil layer thinning rate based on the soil erosion amount and the corresponding topsoil bulk density of each of the hydrological response units; the topsoil bulk density is determined based on the soil type data. The risk assessment unit is used to compare the thinning rate of each black soil layer with a preset threshold for the natural soil formation rate of black soil, and to determine the thinning risk assessment result of the target black soil area based on the comparison result.