A method for quantitatively analyzing frozen soil ice melt water runoff based on a distributed hydrological model

Abstract

The application relates to a permafrost ice melt water runoff quantitative analysis method based on a distributed hydrological model. The method comprises the following steps: dividing soil in a target region into at least one soil layer, and constructing a solid ice mass parameter corresponding to each soil layer; for any soil layer, determining a water migration path corresponding to the soil layer according to the position of the soil layer, and constructing a melt water mass parameter migration function corresponding to each water migration path according to the conversion relationship between solid ice and melt water in the soil layer and the solid ice mass parameter corresponding to the soil layer; constructing a target distributed hydrological model corresponding to the target region based on the melt water mass parameter migration functions; simulating and processing the water cycle process of the target region through the target distributed hydrological model, and determining the permafrost ice melt water runoff of the target region according to the output value of the melt water mass parameter migration function corresponding to the runoff water migration path in the simulation result. The method can reduce the calculation cost of the permafrost ice melt water runoff.

Description

Technical Field

[0001] This application relates to the field of distributed hydrological models, and in particular to a quantitative analysis method for frozen soil meltwater runoff based on a distributed hydrological model. Background Technology

[0002] Cryosphere elements such as glaciers and permafrost play an important role in the hydrological cycle and river runoff changes of watersheds. Accurately assessing the contribution of permafrost meltwater to runoff in high-altitude watersheds is crucial for predicting hydrological changes and managing water resources in high-altitude watersheds under climate change.

[0003] In related technologies, isotope labeling or synthetic aperture radar data is typically used to invert ground subsidence in permafrost regions, and empirical formulas are used to infer the amount of permafrost ice ablation and its contribution to runoff. However, these methods are difficult to extend to larger watersheds and are relatively expensive. Summary of the Invention

[0004] Therefore, it is necessary to provide a quantitative analysis method for frozen soil meltwater runoff based on a distributed hydrological model to address the aforementioned technical problems.

[0005] Firstly, this application provides a method for quantitative analysis of frozen soil meltwater runoff based on a distributed hydrological model. The method includes:

[0006] The soil in the target area is divided into at least one soil layer, and solid ice mass parameters corresponding to each soil layer are constructed.

[0007] For any of the soil layers, the water migration path corresponding to the soil layer is determined according to the location of the soil layer, and a migration function of the melt water mass parameter corresponding to each water migration path is constructed based on the conversion relationship between solid ice and melt water in the soil layer and the solid ice mass parameter corresponding to the soil layer; the water migration path includes at least the runoff water migration path.

[0008] A target distributed hydrological model corresponding to the target area is constructed based on the migration functions of each meltwater quality parameter.

[0009] The water cycle process in the target area is simulated using the target distributed hydrological model to obtain simulation results. Based on the output value of the meltwater quality parameter migration function corresponding to the runoff water migration path in the simulation results, the permafrost meltwater runoff in the target area is determined.

[0010] In one embodiment, the construction of solid ice mass parameters corresponding to each of the soil layers includes:

[0011] For any of the soil layers, determine the ice content correlation parameter corresponding to the soil layer, construct the soil ice mass of the soil layer based on the ice content correlation parameter, and use the soil ice mass of the soil layer at the target time as the solid ice mass parameter corresponding to the soil layer.

[0012] In one embodiment, using the soil ice mass corresponding to the soil layer at the target time as the solid ice mass parameter corresponding to the soil layer includes:

[0013] In the case where the soil layer contains permafrost, the mass of soil ice at the first target time is used as the solid ice mass parameter, where the first target time is the time with the deepest soil thawing depth at any time of the year.

[0014] In the case where the soil layer contains seasonally frozen soil, the soil ice mass at a second target time is used as the solid ice mass parameter, where the second target time is the time with the deepest soil freezing depth at any time of the year.

[0015] In one embodiment, the method further includes:

[0016] During the simulation of the water cycle process in the target area by the target distributed hydrological model, the surface soil temperature is obtained from the current simulation results of the target distributed hydrological model.

[0017] When the surface soil temperature indicates that the soil has begun to melt, the time when the second target time is reached is determined; when the surface soil temperature indicates that the soil has begun to freeze, the time when the first target time is reached is determined.

[0018] In one embodiment, constructing the meltwater quality parameter migration function corresponding to the runoff water migration path includes:

[0019] Determine all water migration paths corresponding to the soil layer, and construct water migration functions corresponding to each water migration path;

[0020] Based on the relationship between the meltwater quality parameters and the water that migrates in each water migration path of the soil layer, and the water migration function corresponding to each water migration path, a meltwater quality parameter migration function corresponding to each water migration path is constructed.

[0021] In one embodiment, the water migration pathway includes a surface migration pathway and a soil migration pathway, and the method further includes:

[0022] Based on the thickness of surface water, a relationship is established between the meltwater quality parameters and the water migrating along the surface migration path;

[0023] Based on soil moisture content and soil layer thickness, a relationship is established between the melt water quality parameters and the water migrating along the soil migration path.

[0024] In one embodiment, the surface migration path includes a surface runoff migration path and an infiltration migration path, and the soil migration path includes at least one of a soil runoff migration path, an evapotranspiration migration path, a soil longitudinal migration path, and a phase change migration path.

[0025] Secondly, this application also provides a quantitative analysis device for frozen soil meltwater runoff based on a distributed hydrological model. The device includes:

[0026] The first construction module is used to divide the soil in the target area into at least one soil layer and construct the solid ice mass parameters corresponding to each soil layer.

[0027] The second construction module is used to determine the water migration path corresponding to any soil layer based on the location of the soil layer, and to construct a water mass parameter migration function corresponding to each water migration path based on the conversion relationship between solid ice and melt water in the soil layer and the solid ice mass parameter corresponding to the soil layer; the water migration path includes at least the runoff water migration path.

[0028] The third construction module is used to construct the target distributed hydrological model corresponding to the target area based on the migration function of each meltwater quality parameter.

[0029] The simulation module is used to simulate the water cycle process of the target area using the target distributed hydrological model, obtain simulation results, and determine the permafrost meltwater runoff of the target area based on the output value of the meltwater quality parameter migration function corresponding to the runoff water migration path in the simulation results.

[0030] In one embodiment, the first building module is further configured to:

[0031] For any of the soil layers, determine the ice content correlation parameter corresponding to the soil layer, construct the soil ice mass of the soil layer based on the ice content correlation parameter, and use the soil ice mass of the soil layer at the target time as the solid ice mass parameter corresponding to the soil layer.

[0032] In one embodiment, the first building module is further configured to:

[0033] In the case where the soil layer contains permafrost, the mass of soil ice at the first target time is used as the solid ice mass parameter, where the first target time is the time with the deepest soil thawing depth at any time of the year.

[0034] In the case where the soil layer contains seasonally frozen soil, the soil ice mass at a second target time is used as the solid ice mass parameter, where the second target time is the time with the deepest soil freezing depth at any time of the year.

[0035] In one embodiment, the device further includes:

[0036] The acquisition module is used to acquire the surface soil temperature from the current simulation results of the target distributed hydrological model during the simulation of the water cycle process in the target area by the target distributed hydrological model.

[0037] The determining module is used to determine the arrival of the second target time when the surface soil temperature indicates that the soil has begun to melt, and to determine the arrival of the first target time when the surface soil temperature indicates that the soil has begun to freeze.

[0038] In one embodiment, the second building module is further configured to:

[0039] Determine all water migration paths corresponding to the soil layer, and construct water migration functions corresponding to each water migration path;

[0040] Based on the relationship between the meltwater quality parameters and the water that migrates in each water migration path of the soil layer, and the water migration function corresponding to each water migration path, a meltwater quality parameter migration function corresponding to each water migration path is constructed.

[0041] In one embodiment, the water migration path includes a surface migration path and a soil migration path, and the device further includes:

[0042] The fourth construction module is used to construct the relationship between the meltwater quality parameters and the water migrating in the surface migration path based on the thickness of the surface water.

[0043] The fifth construction module is used to construct the relationship between the melt water quality parameters and the water migrating in the soil migration path based on the soil moisture content and the thickness of the soil layer.

[0044] In one embodiment, the surface migration path includes a surface runoff migration path and an infiltration migration path, and the soil migration path includes at least one of a soil runoff migration path, an evapotranspiration migration path, a soil longitudinal migration path, and a phase change migration path.

[0045] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement any of the methods described above.

[0046] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements any of the above methods.

[0047] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements any of the above methods.

[0048] The aforementioned method and apparatus for quantitative analysis of frozen soil ice melt runoff based on a distributed hydrological model constructs solid ice mass parameters to describe solid ice in the soil layer. Then, for each soil layer, it determines the water migration path and the conversion relationship between solid ice mass parameters and melt water mass parameters. A melt water mass parameter migration function is constructed for each water migration path to describe the loss of solid ice mass parameters during the water cycle. Based on these melt water mass parameter migration functions, a target distributed hydrological model corresponding to the target area is constructed. The water cycle process is simulated using the target distributed hydrological model. Based on the output values ​​calculated by the target distributed hydrological model for the melt water mass parameter migration functions of the runoff water migration paths, the contribution of the melted solid ice in the frozen soil to the runoff in the target area is determined. This embodiment calculates frozen soil ice melt runoff through model simulation, which can adapt to various watershed ranges and reduce the computational cost of frozen soil ice melt runoff. Attached Figure Description

[0049] Figure 1 This is a flowchart illustrating a method for quantitative analysis of frozen soil meltwater runoff based on a distributed hydrological model in one embodiment.

[0050] Figure 2 This is a flowchart illustrating a quantitative analysis method for frozen soil meltwater runoff based on a distributed hydrological model, as described in another embodiment.

[0051] Figure 3 This is a schematic diagram illustrating the contribution of permafrost meltwater runoff to runoff in perennial and seasonally frozen soils in one embodiment.

[0052] Figure 4 This is a structural block diagram of a quantitative analysis device for frozen soil meltwater runoff based on a distributed hydrological model in one embodiment.

[0053] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0055] In one embodiment, such as Figure 1 As shown, a quantitative analysis method for frozen soil meltwater runoff based on a distributed hydrological model is provided. This embodiment illustrates the method using a server as an example; however, it is understood that the method can also be applied to a terminal, or to a system including both a terminal and a server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0056] Step 102: Divide the soil in the target area into at least one soil layer and construct the solid ice mass parameters corresponding to each soil layer.

[0057] In this embodiment, the target area is the region where the runoff from frozen ground meltwater needs to be simulated. The soil in the target area can be divided into multiple soil layers according to its properties, ensuring that the properties of the soil in each layer are similar to improve calculation accuracy. The thickness of each soil layer can vary. For example, since the water cycle process in the surface soil is more complex than in deeper soils, the soil layers closer to the surface can be made shallower during layer division to more accurately simulate the water cycle process in the surface soil.

[0058] The solid ice mass parameter can be any parameter used to describe the mass of solid ice in the soil layer that needs to be studied. The solid ice mass parameter can be set according to the relationship between the solid ice mass and the soil ice mass that needs to be studied.

[0059] For example, if it is necessary to study the contribution of soil solid ice on a specific date to runoff during the subsequent water cycle, the soil ice mass on that specific date can be used as the solid ice mass parameter. Then, during the operation of the target distributed hydrological model, the contribution of the melting of solid ice contained in the soil on that specific date to runoff can be obtained by calculating the conversion between the solid ice mass parameter and the meltwater mass parameter.

[0060] Soil ice mass can be estimated by sampling the soil in the target area, or by obtaining ice content correlation parameters related to soil ice mass and constructing a mathematical model describing the relationship between these parameters and soil ice mass. For example, ice content correlation parameters may include: temperature, soil moisture, radiation conditions, etc., of the target area.

[0061] This application does not limit the selection of which parameters to use as ice content correlation parameters. The specific selection depends on which input parameters of the target distributed hydrological model can be collected for the target area, and the parameters that the target distributed hydrological model can calculate based on these input parameters. For example, if the target area has daily average precipitation, daily average temperature, downward shortwave radiation, downward longwave radiation, and multi-year average ground temperature as input parameters for the target distributed hydrological model, and the target distributed hydrological model can further calculate soil ice mass based on these input parameters through a thermodynamic model, then the target area's daily average precipitation, daily average temperature, downward shortwave radiation, downward longwave radiation, and multi-year average ground temperature can be used as ice content correlation parameters.

[0062] This application does not specifically limit how to calculate soil ice mass based on ice content correlation parameters. For example, soil samples can be taken from the target area to obtain the distribution of solid ice in the soil layer, and then the specific values ​​of ice content correlation parameters in the target area can be collected. The correlation between ice content correlation parameters and soil ice mass can be obtained through function fitting and other methods, and the soil ice mass can be obtained through this correlation.

[0063] In one embodiment, the solid ice mass parameters corresponding to each soil layer are constructed, including:

[0064] For any of the soil layers, determine the ice content correlation parameter corresponding to the soil layer, construct the soil ice mass of the soil layer based on the ice content correlation parameter, and use the soil ice mass of the soil layer at the target time as the solid ice mass parameter corresponding to the soil layer.

[0065] In this embodiment, the ice content correlation parameters for each soil layer can be the same or different. For example, for shallower soil layers, surface temperature and radiation conditions are more strongly correlated with soil ice mass, so surface temperature and radiation conditions can be used as ice content correlation parameters. For deeper soil layers, average daily ground temperature is more strongly correlated with solid ice mass parameters, so average daily low temperature can be used as ice content correlation parameters.

[0066] After determining the ice content correlation parameters for each soil layer, the soil ice mass of the soil layer can be constructed based on these parameters. The soil ice mass at the target time can then be set as the solid ice mass parameter. Here, the target time refers to the time to be studied. If there are multiple target times, there will also be multiple solid ice mass parameters. The frozen soil meltwater runoff calculated based on each solid ice mass parameter can reflect the contribution of solid ice to the runoff at each target time.

[0067] It should be further explained that, in order to include length units in the dimensions of the solid ice mass parameter for easier subsequent runoff calculation, the volume percentage of ice in the soil layer can be first constructed using ice content correlation parameters, and then the soil ice mass can be further constructed using the following formula (I):

[0068] Formula (1)

[0069] in, This refers to the mass of soil ice in the i-th soil layer at target time t. Let be the volume percentage of ice in the i-th soil layer at the target time t (hereinafter referred to as soil ice content). Let be the thickness of the i-th soil layer. This is the density of ice.

[0070] In one embodiment, the soil ice mass corresponding to the soil layer at the target time is used as the solid ice mass parameter corresponding to the soil layer, including:

[0071] In the case where the soil layer contains permafrost, the soil ice mass corresponding to the first target time is used as the solid ice mass parameter. The first target time is the time when the soil thawing depth is the deepest at any time of the year.

[0072] In cases where the soil layer contains seasonally frozen soil, the soil ice mass at the second target time is used as the solid ice mass parameter, where the second target time is the time with the deepest soil freezing depth at any time of the year.

[0073] In this embodiment, solid ice mass parameters corresponding to permafrost and seasonally frozen soil in the soil layer can be constructed separately. This allows for the subsequent construction of a meltwater mass parameter migration function based on the solid ice mass parameters. After obtaining the output value of the meltwater mass parameter migration function through the simulation results of the target distributed hydrological model, the portions of permafrost and seasonally frozen soil in the output value can be calculated using the solid ice mass parameters corresponding to permafrost and seasonally frozen soil, respectively. This allows for the determination of the contributions of permafrost and seasonally frozen soil to the permafrost meltwater runoff.

[0074] The mass of soil ice at the moment with the deepest soil melting (the first target moment) at any time of the year can be used as the solid ice mass parameter of permafrost. At this moment, almost all the ice in the seasonal permafrost has melted, and almost all the solid ice in the soil comes from the permafrost.

[0075] The mass of soil ice at the moment with the deepest soil freezing depth (the second target moment) can also be used as the solid ice mass parameter of seasonally frozen soil. At this moment, the seasonally frozen soil is almost completely frozen, and the ice content in the seasonally frozen soil reaches its maximum.

[0076] If a soil layer contains both perennial and seasonally frozen soil, two solid ice mass parameters can be constructed based on the soil ice mass at the first target time and the soil ice mass at the second target time, respectively. Considering that the ice content in perennial frozen soil generally remains stable throughout the year, the difference between the frozen soil meltwater runoff calculated based on the solid ice mass parameter constructed based on the soil ice mass at the second target time and the frozen soil meltwater runoff calculated based on the solid ice mass parameter constructed based on the soil ice mass at the first target time can be taken as the contribution of seasonally frozen soil to the frozen soil meltwater runoff.

[0077] The first and second target times can be preset, or they can be determined in real time during the simulation of the target distributed hydrological model. For example, September 1st can be preset as the first target time, and May 1st as the second target time. When determining the first and second target times in real time during the simulation of the target distributed hydrological model, the method is as follows:

[0078] During the simulation of the water cycle process in the target area by the target distributed hydrological model, the surface soil temperature is obtained from the current simulation results of the target distributed hydrological model.

[0079] The time to reach the second target is determined when the surface soil temperature indicates that the soil has begun to melt, and the time to reach the first target is determined when the surface soil temperature indicates that the soil has begun to freeze.

[0080] In this embodiment, the target distributed hydrological model typically simulates the water cycle process using a preset time period as the simulation step size. After each simulation step is completed, the surface soil temperature in the simulation results can be determined. Based on the surface soil temperature, it can be determined whether the soil has begun to thaw or freeze, thereby determining whether the first or second target time has been reached.

[0081] This application does not limit how to determine whether the soil has begun to thaw or freeze based on the surface soil temperature. For example, if the surface soil temperature in multiple consecutive simulation results is greater than 0, it can be determined that the soil has begun to thaw. This is also the time when the soil freezing depth is the deepest at any given time of year. Therefore, the time simulated by the target distributed hydrological model at this point can be used as the second target time. The specific value of the soil ice mass in the simulation results can be obtained, and the specific value of the solid ice mass parameter can be calculated based on the specific value of the soil ice mass. Then, the water cycle process can be simulated based on this value to obtain the frozen soil meltwater runoff contributed by seasonal frozen soil.

[0082] Similarly, if the surface soil temperature is less than or equal to 0 in multiple consecutive simulation results, it can be determined that the soil has begun to freeze. This is also the time when the soil thawing depth is the deepest at any time of the year. The time simulated by the target distributed hydrological model at this point can be used as the first target time to simulate and obtain the permafrost meltwater runoff contributed by permafrost.

[0083] Step 104: For any soil layer, determine the water migration path corresponding to the soil layer based on its location, and construct the melt water mass parameter migration function corresponding to each water migration path based on the conversion relationship between solid ice and melt water in the soil layer and the solid ice mass parameter corresponding to the soil layer; the water migration path includes at least the runoff water migration path.

[0084] In this embodiment, the water migration path of a soil layer can be determined based on its location. For example, when the soil layer is in the topsoil, it can be determined that water in the soil layer will be lost through runoff, vegetation transpiration, evaporation, and water exchange with the next soil layer, and will be replenished through water exchange with adjacent soil layers or surface water. Therefore, the water migration path corresponding to this soil layer can be determined to include at least runoff, vegetation transpiration, evaporation, and water exchange with adjacent soil layers or surface water. A similar method can be used to determine the water migration paths of other soil layers. Among these water migration paths, the path guiding runoff is the runoff water migration path. Runoff water migration paths may include surface runoff migration paths, soil runoff migration paths, and groundwater runoff migration paths.

[0085] The conversion relationship between solid ice and melted water can be determined using methods such as heat conduction models. For example, for each soil layer, the amount of heat that the soil layer can receive can be determined based on its location. Then, the phase change can be calculated based on the heat received by the soil layer to obtain the conversion relationship between solid ice and melted water.

[0086] Based on the conversion relationship between solid ice and melt water, and the mass parameters of solid ice, the mass parameters of melt water corresponding to the soil layer can be calculated. By determining the specific migration paths through which all the water in the soil layer migrates, and the proportion of melt water in the water migrating through each path, a migration function for the melt water mass parameters corresponding to each migration path can be constructed. The specific steps are as follows:

[0087] Determine all water migration paths corresponding to the soil layer and construct the water migration function corresponding to each water migration path;

[0088] Based on the relationship between the meltwater quality parameters and the water that migrates in the soil layer along each water migration path, and the water migration function corresponding to each water migration path, a meltwater quality parameter migration function is constructed for each water migration path.

[0089] In this embodiment of the application, the water migration function corresponding to each water migration path can be constructed by a corresponding mathematical model. For example, for vegetation transpiration, the relationship between meteorological parameters such as temperature, light, wind speed, and humidity, vegetation characteristic parameters such as leaf area index and biomass, and vegetation transpiration can be determined by existing empirical models of vegetation transpiration. Then, the water migration function can be constructed by this relationship.

[0090] The relationship between the meltwater quality parameter and the water transported by the soil layer along each water migration path can be characterized by the ratio between the meltwater quality parameter and the corresponding water quality parameter of the soil layer along that path. The dimensions of the water quality parameter should be the same as those of the solid ice quality parameter and the meltwater quality parameter, so that the ratio between the meltwater quality parameter and the corresponding water quality parameter of the soil layer can represent the proportion of meltwater in the total water content of the soil layer.

[0091] In one embodiment, the water migration pathway includes a surface migration pathway and a soil migration pathway. The relationship between meltwater quality parameters and water content in each migration pathway can be constructed by referring to the following steps:

[0092] Based on the thickness of surface water, the relationship between meltwater quality parameters and water migrating along the surface migration path is constructed.

[0093] Based on soil moisture content and soil layer thickness, the relationship between meltwater quality parameters and water migrating along soil migration paths was constructed.

[0094] In this embodiment of the application, the surface migration path includes the surface runoff migration path and the infiltration migration path. The proportion of meltwater in the water migrating through the surface runoff migration path and the infiltration migration path can be determined according to the thickness of the surface water, as shown in formula (II):

[0095] Formula (II)

[0096] in, This refers to the proportion of meltwater in the total water volume along the surface runoff migration path. The meltwater quality parameter corresponding to surface water can be obtained by multiplying the proportion of surface water in the total water content of the soil layer in which it is located by the total meltwater quality parameter in the soil layer. The thickness of the surface water. This is the density of water.

[0097] The migration function of meltwater quality parameters corresponding to the surface runoff migration path can be further constructed using formula (III):

[0098] Formula (3)

[0099] in, These are the quality parameters of meltwater that migrate through surface runoff migration paths. It is surface runoff.

[0100] Soil migration pathways include at least one of the following: soil runoff migration pathways, evapotranspiration migration pathways, soil longitudinal migration pathways, and phase change migration pathways. Evapotranspiration migration pathways represent water transported via vegetation transpiration or evaporation; soil longitudinal migration pathways represent water exchanged between the soil layer and the soil layers above or below it; and phase change migration pathways represent water transported via freezing or thawing. The relationship between the meltwater mass parameter and total water content within the soil migration pathways can be calculated using formula (iv):

[0101] Formula (IV)

[0102] in, This refers to the proportion of melted water in the total water content of the i-th soil layer. Let be the mass parameter of the melt water in the i-th soil layer. Let be the soil moisture content in the i-th soil layer. Let be the thickness of the i-th soil layer. This is the density of water.

[0103] The migration function of meltwater quality parameters corresponding to the soil migration path can be further constructed using formula (5):

[0104] Formula (5)

[0105] in, Let be the mass parameter of meltwater that migrates from the i-th soil layer through the soil migration path. This represents soil runoff, which is also the water migration function corresponding to the soil runoff migration path. It represents the water output from the i-th soil layer to the (i+1)-th soil layer. It is the water output from the (i-1)th soil layer to the ith soil layer. Water transport function corresponding to soil vertical migration path This represents evapotranspiration, which is the water migration function corresponding to the evapotranspiration migration path. This is the water migration function corresponding to the phase change migration path.

[0106] It can be further written in the form of formula (VI):

[0107] Formula (VI)

[0108] in, It represents the total mass of water undergoing a phase change. During the freezing phase, liquid water transforms into solid ice, causing water loss. During the melting phase, solid ice transforms into liquid water, causing water gain. The formula is calculated as follows: The product of the remaining solid ice mass parameter in the i-th soil layer (i.e., the solid ice mass parameter that has not been converted into melt water mass parameter) and the product of the soil ice content, the soil layer thickness, and the ice density is used as the ratio, as shown in Formula (VII):

[0109] Formula (VII)

[0110] in, These are the current solid ice mass parameters. It is the ice content of the i-th soil layer. Let be the thickness of the i-th soil layer. This is the density of ice.

[0111] Step 106: Construct the target distributed hydrological model corresponding to the target area based on the migration function of each meltwater quality parameter.

[0112] In this embodiment, based on the principle of mass conservation, for the entire target area, the sum of the output values ​​of the migration functions of all meltwater mass parameters in all soil layers, plus the sum of the remaining meltwater mass parameters and solid ice mass parameters in all soil layers, should be equal to the sum of the solid ice mass parameters originally constructed for all soil layers. Based on this constraint and the migration functions of the meltwater mass parameters of each soil layer, a target distributed hydrological model for simulating the water cycle process can be constructed. Taking the meltwater mass parameter migration function as containing the contents of formulas (II) to (VII) in the aforementioned embodiment as an example, the process of constructing a target distributed hydrological model for simulating the water cycle process is as follows: First, determine which input parameters can be obtained for the target area, and then construct a model based on the input parameters that can calculate the contents of formulas (II) to (VII) mentioned above. , , , , , , , , A mathematical model is obtained by considering all unknowns and taking into account the conservation of energy and mass in the target area, thus obtaining the target distributed hydrological model.

[0113] Alternatively, a pre-built distributed hydrological model for the target area can be obtained, and the migration functions of the meltwater quality parameters of each soil layer can be integrated with the pre-built distributed hydrological model to obtain the target distributed hydrological model. After the target distributed hydrological model runs according to the logic of the original distributed hydrological model to obtain the simulation results, the unknowns required in the aforementioned formulas can be obtained from the simulation results, and the output values ​​of the migration functions of each meltwater quality parameter can be calculated.

[0114] Step 108: Simulate the water cycle process in the target area using the target distributed hydrological model to obtain simulation results. Based on the output value of the meltwater quality parameter migration function corresponding to the runoff water migration path in the simulation results, determine the permafrost meltwater runoff in the target area.

[0115] In this embodiment, the target distributed hydrological model simulates the water cycle process in the target area to obtain simulation results. The simulation results refer to the output values ​​of various parameters related to the water cycle process in the target area and the migration functions of various meltwater quality parameters. By summing the output values ​​of the meltwater quality parameter migration functions corresponding to the runoff water migration paths (including surface runoff migration paths and soil runoff migration paths) of each soil layer, the permafrost meltwater runoff in the target area can be obtained.

[0116] The above process is described below with a practical example. For example... Figure 2 The diagram shows a flowchart of a quantitative analysis method for frozen soil meltwater runoff based on a distributed hydrological model in one embodiment, including:

[0117] S1, Construct a distributed hydrological model.

[0118] In this embodiment, before tracking solid ice in permafrost, a distributed hydrological model capable of describing the water cycle process in the target area is first constructed. The Yangtze River source region is selected as the target area in this application.

[0119] The parameters required to construct a distributed hydrological model are shown in Table 1:

[0120] Table 1

[0121]

[0122] The aforementioned parameters serve to construct a distributed hydrological model describing the water cycle process based on meteorological and underlying surface data. The input to the distributed hydrological model is the time-resolution data shown in the table above, and the output consists of various parameters involved in the water cycle process, such as the runoff of rivers in the target area, soil moisture content, surface water thickness, etc. The model is then periodically calibrated using validation data. This application does not limit the specific method for constructing the distributed hydrological model; any model capable of simulating soil water movement, soil freeze-thaw cycles, evapotranspiration, surface runoff, soil runoff, and groundwater runoff, or some of these processes, is applicable to this application.

[0123] In the distributed hydrological model finally constructed in this application embodiment, the target area is divided into multiple grid cells, and each grid cell is further divided into multiple soil layers for calculation. The model divides the soil from 0 to 49 meters into 39 layers, with the thickness of each layer increasing with depth. The model employs the energy balance method, using net surface radiation and geothermal flux as boundary conditions to calculate soil heat conduction, convection, and soil moisture phase change. The initial soil temperature of the model is calculated based on the multi-year average ground temperature obtained from measured boreholes in existing studies, combined with actual observed soil profile temperatures. The initial soil ice content of the model is given by data provided in existing studies.

[0124] S2 calculates the solid ice mass parameters for permafrost and seasonally frozen soil.

[0125] In this embodiment, since permafrost generally exists in deeper soil layers and receives less external replenishment, the solid ice mass parameter of the permafrost can be calculated in the first year of the simulation and then not updated thereafter. The calculation method is to sample the soil ice content in the target area on September 1st, and use the soil ice content in each soil layer obtained from the sampling as the soil ice content of the i-th soil layer at a specific time in the aforementioned formula (I). Then, the solid ice mass parameter of the permafrost is calculated using formula (I).

[0126] For seasonally frozen soil, the solid ice mass parameter needs to be updated every year during model operation to reflect the exogenous replenishment received by the seasonally frozen soil. Before the model starts running, the soil ice content in the target area is sampled on January 1st. The soil ice content in each sampled soil layer is used as the soil ice content of the i-th soil layer at a specific time in the aforementioned formula (I). Then, the solid ice mass parameter of the seasonally frozen soil is calculated using formula (I). After the model starts running, the update date for the solid ice mass parameter is set as follows: During the model operation, the daily average temperature of the surface soil of each grid in the model is statistically analyzed. When the daily average temperature reaches above 0℃ for two consecutive days throughout the year, it means that the soil will begin to thaw and the freezing depth will reach its maximum. On that day, the solid ice mass parameter of all soil layers in the grid is updated using formula (I). For grids where the temperature is below 0℃ throughout the year, the solid ice mass parameter of all soil layers in the grid is updated on June 1st of each year using formula (I).

[0127] S3, preheat the model until the solid ice mass parameters of the permafrost stabilize.

[0128] In this embodiment of the application, a distributed hydrological model is run, and during the run, the solid ice mass parameters in permafrost are continuously calculated according to formula (I). When the solid ice mass parameters reach a stable state, the model is considered to have completed preheating.

[0129] S4. Construct the meltwater quality parameter transfer function and integrate it with the distributed hydrological model.

[0130] In this embodiment, the meltwater quality parameter migration function is constructed in accordance with the manner described in the foregoing embodiments. The meltwater quality parameter migration function is integrated with the distributed hydrological model, so that the distributed hydrological model can synchronously output the output value of each meltwater quality parameter migration function during operation.

[0131] S5, output values ​​of the migration function of meltwater quality parameters corresponding to the runoff water migration path, to determine the permafrost meltwater runoff in the target area.

[0132] In this embodiment of the application, the output values ​​of the meltwater quality parameter migration function corresponding to the runoff water migration paths of all soil layers in all grids are added together to obtain the permafrost meltwater runoff of the target area.

[0133] Using the above method, the runoff process in the Yangtze River source region in 1991 was simulated, and the contributions of solid ice melt water in permafrost and seasonally frozen soil to the runoff in the Yangtze River source region in 1991 were calculated. The total runoff in the Yangtze River source region in 1991 was 77.9 mm. The contributions of permafrost and seasonally frozen soil to the runoff were 1.4 mm and 30.0 mm, respectively. The contributions of solid ice melt water in permafrost and seasonally frozen soil to the runoff were 1.8% and 38.5%, respectively. Their intra-annual distribution is shown below. Figure 3 As shown, the contribution of solid ice melt water in permafrost and seasonally frozen soil to runoff is mainly distributed from July to October.

[0134] The method for quantitative analysis of frozen soil ice melt runoff based on a distributed hydrological model provided in this application constructs solid ice mass parameters to describe solid ice in the soil layer. Then, for each soil layer, it determines the water migration path and the conversion relationship between solid ice mass parameters and melt water mass parameters. A melt water mass parameter migration function is constructed for each water migration path to describe the loss of solid ice mass parameters during the water cycle. Based on these melt water mass parameter migration functions, a target distributed hydrological model corresponding to the target area is constructed. The water cycle process is simulated using this target distributed hydrological model. Based on the output values ​​calculated by the target distributed hydrological model for the melt water mass parameter migration functions of the runoff water migration paths, the contribution of frozen soil ice melt in the target area to the runoff in the target area is determined. This application's method of calculating frozen soil ice melt runoff through model simulation is adaptable to various watershed ranges and reduces the computational cost of frozen soil ice melt runoff calculation.

[0135] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0136] Based on the same inventive concept, this application also provides a device for quantitative analysis of frozen soil meltwater runoff based on a distributed hydrological model, used to implement the aforementioned method for quantitative analysis of frozen soil meltwater runoff based on a distributed hydrological model. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the device for quantitative analysis of frozen soil meltwater runoff based on a distributed hydrological model provided below can be found in the limitations of the method for quantitative analysis of frozen soil meltwater runoff based on a distributed hydrological model described above, and will not be repeated here.

[0137] In one embodiment, such as Figure 4 As shown, a quantitative analysis device 400 for frozen soil meltwater runoff based on a distributed hydrological model is provided, comprising: a first construction module 402, a second construction module 404, a third construction module 406, and a simulation module 408, wherein:

[0138] The first construction module 402 is used to divide the soil in the target area into at least one soil layer and construct the solid ice mass parameters corresponding to each soil layer.

[0139] The second construction module 404 is used to determine the water migration path corresponding to any soil layer based on the location of the soil layer, and to construct a water mass parameter migration function corresponding to each water migration path based on the conversion relationship between solid ice and melt water in the soil layer and the solid ice mass parameter corresponding to the soil layer; the water migration path includes at least the runoff water migration path.

[0140] The third construction module 406 is used to construct the target distributed hydrological model corresponding to the target area based on the migration function of each meltwater quality parameter.

[0141] The simulation module 408 is used to simulate the water cycle process of the target area through the target distributed hydrological model, obtain simulation results, and determine the permafrost meltwater runoff of the target area based on the output value of the meltwater quality parameter migration function corresponding to the runoff water migration path in the simulation results.

[0142] In one embodiment, the first building module 402 is further configured to:

[0143] For any of the soil layers, determine the ice content correlation parameter corresponding to the soil layer, construct the soil ice mass of the soil layer based on the ice content correlation parameter, and use the soil ice mass of the soil layer at the target time as the solid ice mass parameter corresponding to the soil layer.

[0144] In one embodiment, the first building module 402 is further configured to:

[0145] In the case where the soil layer contains permafrost, the mass of soil ice at the first target time is used as the solid ice mass parameter, where the first target time is the time with the deepest soil thawing depth at any time of the year.

[0146] In the case where the soil layer contains seasonally frozen soil, the soil ice mass at a second target time is used as the solid ice mass parameter, where the second target time is the time with the deepest soil freezing depth at any time of the year.

[0147] In one embodiment, the device further includes:

[0148] The acquisition module is used to acquire the surface soil temperature from the current simulation results of the target distributed hydrological model during the simulation of the water cycle process in the target area by the target distributed hydrological model.

[0149] The determining module is used to determine the arrival of the second target time when the surface soil temperature indicates that the soil has begun to melt, and to determine the arrival of the first target time when the surface soil temperature indicates that the soil has begun to freeze.

[0150] In one embodiment, the second building module 404 is further configured to:

[0151] Determine all water migration paths corresponding to the soil layer, and construct water migration functions corresponding to each water migration path;

[0152] Based on the relationship between the meltwater quality parameters and the water that migrates in each water migration path of the soil layer, and the water migration function corresponding to each water migration path, a meltwater quality parameter migration function corresponding to each water migration path is constructed.

[0153] In one embodiment, the water migration path includes a surface migration path and a soil migration path, and the device further includes:

[0154] The fourth construction module is used to construct the relationship between the meltwater quality parameters and the water migrating in the surface migration path based on the thickness of the surface water.

[0155] The fifth construction module is used to construct the relationship between the melt water quality parameters and the water migrating in the soil migration path based on the soil moisture content and the thickness of the soil layer.

[0156] In one embodiment, the surface migration path includes a surface runoff migration path and an infiltration migration path, and the soil migration path includes at least one of a soil runoff migration path, an evapotranspiration migration path, a soil longitudinal migration path, and a phase change migration path.

[0157] Each module in the above-mentioned device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0158] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a quantitative analysis method for frozen soil meltwater runoff based on a distributed hydrological model.

[0159] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0160] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0161] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0162] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0163] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0164] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0165] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0166] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A quantitative analysis method for frozen soil meltwater runoff based on a distributed hydrological model, characterized in that, The method includes: The soil in the target area is divided into at least one soil layer, and solid ice mass parameters corresponding to each soil layer are constructed. For any of the soil layers, all water migration paths corresponding to the soil layer are determined based on the location of the soil layer, and a water migration function corresponding to each water migration path is constructed; based on the relationship between the meltwater quality parameter and the water migrated by the soil layer in each water migration path, and the water migration function corresponding to each water migration path, a meltwater quality parameter migration function corresponding to each water migration path is constructed; the water migration path includes at least the runoff water migration path. A target distributed hydrological model corresponding to the target area is constructed based on the migration functions of each meltwater quality parameter. The water cycle process in the target area is simulated using the target distributed hydrological model to obtain simulation results. Based on the output value of the meltwater quality parameter migration function corresponding to the runoff water migration path in the simulation results, the permafrost meltwater runoff in the target area is determined.

2. The method according to claim 1, characterized in that, The solid ice mass parameters corresponding to each of the soil layers are as follows: For any of the soil layers, determine the ice content correlation parameter corresponding to the soil layer, construct the soil ice mass of the soil layer based on the ice content correlation parameter, and use the soil ice mass of the soil layer at the target time as the solid ice mass parameter corresponding to the soil layer.

3. The method according to claim 2, characterized in that, The step of using the soil ice mass corresponding to the soil layer at the target time as the solid ice mass parameter corresponding to the soil layer includes: In the case where the soil layer contains permafrost, the mass of soil ice at the first target time is used as the solid ice mass parameter, where the first target time is the time with the deepest soil thawing depth at any time of the year. In the case where the soil layer contains seasonally frozen soil, the soil ice mass at a second target time is used as the solid ice mass parameter, where the second target time is the time with the deepest soil freezing depth at any time of the year.

4. The method according to claim 3, characterized in that, The method further includes: During the simulation of the water cycle process in the target area by the target distributed hydrological model, the surface soil temperature is obtained from the current simulation results of the target distributed hydrological model. When the surface soil temperature indicates that the soil has begun to melt, the time when the second target time is reached is determined; when the surface soil temperature indicates that the soil has begun to freeze, the time when the first target time is reached is determined.

5. The method according to claim 1, characterized in that, The water migration pathways include surface migration pathways and soil migration pathways, and the method further includes: Based on the thickness of surface water, a relationship is established between the meltwater quality parameters and the water migrating along the surface migration path; Based on soil moisture content and soil layer thickness, a relationship is established between the melt water quality parameters and the water migrating along the soil migration path.

6. The method according to claim 5, characterized in that, The surface migration pathways include surface runoff migration pathways and infiltration migration pathways, and the soil migration pathways include at least one of soil runoff migration pathways, evapotranspiration migration pathways, soil longitudinal migration pathways, and phase change migration pathways.

7. A quantitative analysis device for frozen soil meltwater runoff based on a distributed hydrological model, characterized in that, The device includes: The first construction module is used to divide the soil in the target area into at least one soil layer and construct the solid ice mass parameters corresponding to each soil layer. The second construction module is used to determine all water migration paths corresponding to any given soil layer based on the location of the soil layer, and to construct a water migration function corresponding to each water migration path; based on the relationship between the meltwater quality parameter and the water migrated by the soil layer in each water migration path, and the water migration function corresponding to each water migration path, to construct a meltwater quality parameter migration function corresponding to each water migration path; the water migration path includes at least a runoff water migration path. The third construction module is used to construct the target distributed hydrological model corresponding to the target area based on the migration function of each meltwater quality parameter. The simulation module is used to simulate the water cycle process of the target area using the target distributed hydrological model, obtain simulation results, and determine the permafrost meltwater runoff of the target area based on the output value of the meltwater quality parameter migration function corresponding to the runoff water migration path in the simulation results.

8. The apparatus according to claim 7, characterized in that, The first building module is also used for: For any of the soil layers, determine the ice content correlation parameter corresponding to the soil layer, construct the soil ice mass of the soil layer based on the ice content correlation parameter, and use the soil ice mass of the soil layer at the target time as the solid ice mass parameter corresponding to the soil layer.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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