Accumulated snow ablation model construction method and accumulated snow ablation prediction method based on system dynamics

Abstract

The invention relates to an accumulated snow ablation model construction method and an accumulated snow ablation prediction method based on system dynamics, and the method comprises the steps: obtaining a snow surface net radiation flux, a rainfall conduction flux, a terrestrial heat flux, a sensible heat flux, and a latent heat flux according to meteorological data; according to the snow surface net radiation flux, the rainfall conduction flux, the terrestrial heat flux, the sensible heat flux and the latent heat flux, accumulated snow layer net energy is obtained; obtaining an accumulated snow melting depth model according to the accumulated snow layer net energy; and according to a rainfall type discrimination model and the accumulated snow melting depth model, constructing an accumulated snow melting model. The simulation precision of the accumulated snow ablation process can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of snow melting process monitoring, and in particular to a snow melting model construction method and a snow melting prediction method based on system dynamics. Background Art

[0002] With the impact of the continued global warming, the cryosphere, which is most sensitive to climate change, is undergoing rapid changes. Snow in the cryosphere affects the hydrological cycle and human activities at the global and regional scales in many ways. First of all, large-scale snow accumulation plays a regulatory role in global climate change, and also affects the surface energy balance and water cycle process. Secondly, at the regional or watershed scale, snow cover will change the local microclimate environment. The basin hydrological simulation considering the snow accumulation process has important guiding significance for the early warning, monitoring and assessment of snowmelt flood disasters. The prediction of runoff under future climate scenarios can understand the impact of climate change on runoff, and is of great significance to ensuring normal social production activities, ecological environmental protection, and flood prevention and disaster reduction.

[0003] The snow ablation process is affected by many factors, including meteorological conditions, terrain characteristics and snow characteristics. Existing snow ablation models often fail to fully consider these factors, resulting in inaccurate calculation results. In addition, only a single parameter can be set for the snow ablation process, and the ablation results under multiple parameters cannot be simulated, and the impact of changes in specific factors on the ablation process cannot be observed in real time. Therefore, a snow ablation model construction method based on system dynamics and a snow ablation prediction method are proposed to improve the simulation accuracy of the snow ablation process and improve the visualization of the simulation process. Summary of the invention

[0004] The purpose of the present invention is to provide a snow ablation model construction method and a snow ablation prediction method based on system dynamics, so as to improve the simulation accuracy of the snow ablation process.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] The snow melt model construction method based on system dynamics includes:

[0007] According to meteorological data, obtain the snow surface net radiation flux, precipitation conduction flux, geothermal flux, sensible heat flux, and latent heat flux;

[0008] Obtaining the net energy of the snow layer according to the snow surface net radiation flux, the precipitation conduction flux, the geothermal flux, the sensible heat flux and the latent heat flux;

[0009] Obtaining a snow melt depth model according to the net energy of the snow layer;

[0010] A snow melting model is constructed according to the precipitation type discrimination model and the snow melting depth model.

[0011] Optionally, the meteorological data include: air temperature, air pressure, humidity, snow surface temperature, wind speed, snow surface albedo, cloud coverage and incident shortwave radiation.

[0012] Optionally, obtaining the snow surface net radiation flux comprises: obtaining the snow surface net radiation flux according to the sum of net shortwave radiation, atmospheric longwave radiation and snow surface longwave radiation, wherein the net shortwave radiation is obtained according to the incident shortwave radiation and the snow surface albedo, and the atmospheric longwave radiation is obtained according to the cloud coverage rate;

[0013] Acquiring the precipitation conduction flux comprises: acquiring the precipitation conduction flux according to the density, specific heat capacity, surface temperature, precipitation amount, and snowfall amount of water and snow;

[0014] Acquiring the geothermal flux includes: acquiring the geothermal flux according to soil temperatures at different depths;

[0015] Acquiring the sensible heat flux comprises: acquiring the sensible heat flux according to aerodynamic resistance, snow surface temperature, air temperature and volume heat capacity of air, wherein the aerodynamic resistance is acquired according to the wind speed;

[0016] Acquiring the latent heat flux includes: acquiring the latent heat flux according to air vapor pressure and snow surface vapor pressure.

[0017] Optionally, obtaining a snow melt depth model according to the snow layer net energy includes:

[0018]

[0019] Where h is the snowmelt depth, Q NET is the net energy of the snow layer, S is the melting heat of snow, ρ S is the snow density, Q LE is the latent heat flux, λ V is the latent heat of evaporation, ρ W is the density of water.

[0020] Optionally, obtaining the precipitation type discrimination model includes:

[0021] Get the median of the range of wet-bulb temperatures where the transition from rain to snow occurs, based on relative humidity and altitude;

[0022] According to the ratio of the temperature range of sleet occurrence to the temperature range of rain-snow transition, the maximum temperature threshold and the minimum temperature threshold are obtained;

[0023] The precipitation type discrimination model is obtained according to the maximum temperature threshold, the minimum temperature threshold and the median of the wet-bulb temperature range in which rain-snow conversion occurs, wherein the precipitation type discrimination model is used to obtain the precipitation type and obtain the depth of different precipitation types.

[0024] Optionally, the snow ablation model includes:

[0025] Snow depth = H 雨夹雪 / 2+H 降雪 -h

[0026] Among them, H 雨夹雪 is the amount of sleet, H 降雪 is the snowfall, and h is the snowmelt depth.

[0027] The present invention also provides a snow ablation prediction method based on system dynamics, including: obtaining the air temperature, humidity, air pressure, wind speed, snow surface temperature, initial snow depth, incident shortwave radiation, cloud coverage, snow surface albedo and the total amount of each type of precipitation in the corresponding time period of the target area and inputting them into a snow ablation model to obtain the snow depth after snow ablation, wherein the snow ablation model is constructed according to a snow ablation model construction method.

[0028] The beneficial effects of the present invention are as follows: (1) Based on the simulation of snow depth based on the traditional snow ablation model, the prior conditions for distinguishing precipitation types are added, providing more accurate input variables for the subsequent snow ablation model. (2) The snow ablation model is constructed by using system dynamics, which can not only add feedback loops that affect snow ablation factors according to needs, but also use the model characteristics to intuitively compare the differences in simulation results under different simulation conditions. (3) The present invention has wide applicability and can be promoted and applied to other high-cold mountainous areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0030] Figure 1 A flowchart of a method for constructing a snow ablation model based on system dynamics according to an embodiment of the present invention;

[0031] Figure 2 A flow stock diagram of a snowmelt model according to an embodiment of the present invention;

[0032] Figure 3 A simulated snow layer net energy diagram according to an embodiment of the present invention;

[0033] Figure 4 A simulated snow melting depth map according to an embodiment of the present invention;

[0034] Figure 5 A schematic diagram of simulated snow depth variation according to an embodiment of the present invention;

[0035] Figure 6 This is a comparison diagram of the simulated snow depth and the measured snow depth according to an embodiment of the present invention. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0038] like Figure 1 As shown, this embodiment provides a method for constructing a snow melting model based on system dynamics, including:

[0039] According to meteorological data, obtain the snow surface net radiation flux, precipitation conduction flux, geothermal flux, sensible heat flux, and latent heat flux;

[0040] The net energy of the snow layer is obtained based on the net radiation flux of the snow surface, the conduction flux of precipitation, the geothermal flux, the sensible heat flux and the latent heat flux;

[0041] Obtain snow melt depth model based on the net energy of snow layer;

[0042] A snow melt model is constructed based on the precipitation type discrimination model and the snow melt depth model.

[0043] Furthermore, meteorological data include: air temperature, air pressure, humidity, snow surface temperature, wind speed, snow surface albedo, cloud cover and incident shortwave radiation.

[0044] Further, obtaining the snow surface net radiation flux includes: obtaining the snow surface net radiation flux according to the sum of the net shortwave radiation, the atmospheric longwave radiation and the snow surface longwave radiation, wherein the net shortwave radiation is obtained according to the incident shortwave radiation and the snow surface albedo, and the atmospheric longwave radiation is obtained according to the cloud coverage rate;

[0045] Obtaining the precipitation conduction flux includes: obtaining the precipitation conduction flux according to the density, specific heat capacity, surface temperature, precipitation amount and snowfall amount of water and snow;

[0046] Obtaining geothermal flux includes: obtaining geothermal flux according to soil temperature at different depths;

[0047] The sensible heat flux is obtained by: aerodynamic drag, snow surface temperature, air temperature and volumetric heat capacity of air. Aerodynamic drag is obtained by wind speed.

[0048] Obtaining the latent heat flux includes: obtaining the latent heat flux according to the air vapor pressure and the snow surface vapor pressure.

[0049] Specifically, the net radiation flux of the snow surface is: Q R =R ns +L a -L t ;

[0050] Net shortwave radiation: R ns =Q s (1-A);

[0051] Among them, Q S is the incident shortwave radiation (KJm -2 day -1 ), A is the albedo of the snow surface, and its maximum value is 0.95 when there is snow on the ground.

[0052] Atmospheric longwave radiation: L a =ε ac σ(T a +273.15) 4 ;

[0053] Where σ is the Stefan-Bohzman constant 5.67×10 -8 W·m -2 K -4 ; ε ac is the atmospheric emissivity under cloud cover, according to the method proposed by Bristow and Campbell to calculate the atmospheric emissivity from the cloud cover ratio:

[0054] ε ac =(0.72+0.005T a )(1-0.84C)+0.84C

[0055] Where C is the cloud coverage. This method believes that the cloud coverage is closely related to precipitation. When the precipitation exceeds 5 mm, C = 100%; if there is no precipitation, C = 0%.

[0056] Snow surface longwave radiation: L t =ε s σ(T s +273.15) 4 ;

[0057] Where, σ is the Stefan-Bohzman constant 5.67×10 -8 W·m -2 K -4 ; T s is the snow surface temperature ℃; ε s is the long-wave emissivity of snow, which is taken as 0.97.

[0058] Precipitation conduction flux: Q P =ρ w c w T a P r +ρ w c s T s P s ;

[0059] In the formula, ρ w is the density of water, take 1.0×10 3 kg / m 3 ;c w represents the specific heat capacity of water, taking 4.18×10 3 (J / kg) / ℃; c s Represents the specific heat capacity of snow and ice, generally taken as 2.09×10 3 (J / kg) / ℃; P r is the rainfall; P s is the snowfall, in mm; when Q P A negative value indicates that heat is absorbed from the snow layer, T a is the air temperature.

[0060] Geothermal flux: Q G =K G (T1-T2) / (z1-z2)

[0061] In the formula, K G represents the soil thermal conductivity, T1 is the temperature at the soil depth z1, and T2 is the temperature at the depth z2. In the absence of observations, it can be considered as a stable small constant or even negligible.

[0062] Sensible heat flux:

[0063] Where, T s is the snow surface temperature, ρc p is the volume heat capacity of air, taking the constant as 1205 Jm -3 k -1 ; r as is the aerodynamic drag between the surface of the snow layer and the nearby reference height, calculated by the following formula:

[0064]

[0065] In the formula, z μ is the reference height for wind speed, usually 2m; x is the reference height for temperature, usually 1.2m; μ is the wind speed at the reference height; z m and z h are the dynamic impedance coefficient and the water vapor impedance coefficient, respectively, which are 0.001m and 0.0002m for the snow surface respectively: k1 is the VonKaman constant, which is 0.4 in this embodiment. μ2 is the wind speed at 2m above the ground (m / s), and the conversion method for the wind speed at any other height y is as follows:

[0066]

[0067] Latent heat flux:

[0068] In the formula, λ V is the latent heat of evaporation, take 2.834×10 6 J / kg, R d is the dry air constant, 287 J·kg -1 K -1 ; e(T a ) and e(T s ) are respectively the air vapor pressure and the snow surface vapor pressure. It is usually considered that the snow surface is a saturated surface. The snow surface vapor pressure is the saturated vapor pressure at the snow surface temperature. The air vapor pressure is the product of the saturated vapor pressure at the air temperature and the relative humidity:

[0069] e(T a )=e svp (T a )×Rh

[0070] e svp (T a ) represents the saturated water vapor pressure, which is a function of temperature and is calculated using the Teten formula:

[0071]

[0072] Furthermore, according to the net energy of the snow layer, the snow melting depth model is obtained including:

[0073]

[0074] Where h is the snowmelt depth, Q NET is the net energy of the snow layer, S is the melting heat of snow, ρ S is the snow density, Q LE is the latent heat flux, λ V is the latent heat of evaporation, ρ W is the density of water.

[0075] Furthermore, obtaining the precipitation type discrimination model includes:

[0076] Get the median of the range of wet-bulb temperatures where the transition from rain to snow occurs, based on relative humidity and altitude;

[0077] According to the ratio of the temperature range of sleet occurrence to the temperature range of rain-snow transition, the maximum temperature threshold and the minimum temperature threshold are obtained;

[0078] The precipitation type is determined based on the maximum temperature threshold, the minimum temperature threshold and the median of the wet-bulb temperature range at which rain-snow conversion occurs.

[0079] Specifically,

[0080]

[0081] ΔT=0.215-0.099*Rh+1.018×Rh 2

[0082] ΔS=2.374-1.634*Rh

[0083] T0=-5.87-0.1024*H+0.0885*H 2 +16.06*Rh-9.614*Rh

[0084]

[0085] Where Rh is relative humidity, H is altitude, Pr s is the air pressure, T w is the wet bulb temperature, ΔT is the temperature range where sleet mainly occurs, ΔS is the temperature range where rain and snow transition occurs, and T0 is the temperature at which the transition from rain to snow occurs. w The center of the range.

[0086] Furthermore, the snow melt model includes:

[0087] Snow depth = H 雨夹雪 / 2+H 降雪 -h

[0088] Among them, H 雨夹雪 is the amount of sleet, H 降雪 is the snowfall, and h is the snowmelt depth.

[0089] The present invention is further described below with the Tianshan region of China as an example, the region is at a higher altitude, and the precipitation type is mainly snowfall. The data of the present embodiment are derived from the meteorological observation station in the region, and these data are included in the National Meteorological Center (CMA), and the photosynthetically active radiation daily mean value data set (1951-2010) of 716 meteorological stations in China is also used in addition, and this part of data comes from the National Tibetan Plateau Data Center. Through the work such as data quality verification and resampling, the meteorological data with continuous time series is obtained.

[0090] 1. First, the precipitation types are divided according to the precipitation type discrimination system (model). Here, the Ding method, which is currently considered to have a good precipitation discrimination accuracy in high mountain cold areas, is used to separate the original precipitation types. Specifically:

[0091]

[0092] ΔT=0.215-0.099*Rh+1.018×Rh2

[0093] ΔS=2.374-1.634*Rh

[0094] T0=-5.87-0.1024*H+0.0885*H 2 +16.06*Rh-9.614*Rh 2

[0095]

[0096] Where Rh is relative humidity, H is altitude, T w is the wet bulb temperature, ΔT is the temperature range where sleet mainly occurs, ΔS is the temperature range where rain and snow transition occurs, and T0 is the temperature at which the transition from rain to snow occurs. w The center of the range corresponds to T w Median of the range, T min is the minimum temperature threshold, T max is the maximum temperature threshold, Indicates T when humidity Rh is 78% min and T max If Rh>78%, T min and T max The values ​​are different, otherwise T min and T max The precipitation types are classified according to the precipitation type identification system, and then the depths corresponding to different precipitation types are obtained.

[0097] 2. Determine the net radiation flux of the snow surface, net short-wave radiation, atmospheric long-wave radiation, snow surface long-wave radiation, precipitation conduction flux, geothermal flux, sensible heat flux, and latent heat flux according to meteorological conditions, such as Figure 2shown.

[0098] Specific:

[0099] 2.1 The formula for the net radiation flux of the snow surface is: Q R =R ns +L a -L t ;

[0100] Among them, R ns is the net shortwave radiation, L a is the atmospheric long-wave radiation, L t is the long-wave radiation of the snow surface. The calculation formulas for these three energies are as follows:

[0101] Net shortwave radiation: R ns =Q s (1-A);

[0102] Among them, Q S is the incident shortwave radiation (KJm -2 day -1 ), A is the albedo of the snow surface, and its maximum value is 0.95 when there is snow on the ground;

[0103] Atmospheric longwave radiation: L a =ε ac σ(T a +273.15) 4 ;

[0104] Where σ is the Stefan-Bohzman constant 5.67×10 -8 W·m -2 K -4 ; ε ac is the atmospheric emissivity under cloud cover, according to the method proposed by Bristow and Campbell to calculate the atmospheric emissivity from the cloud cover ratio:

[0105] ε ac =(0.72+0.005T a )(1-0.84C)+0.84C;

[0106] Where C is the cloud coverage. This method believes that the cloud coverage is closely related to precipitation. When the precipitation exceeds 5 mm, C = 100%; if there is no precipitation, C = 0%.

[0107] Snow surface longwave radiation: L t =ε s σ(T s +273.15) 4 ;

[0108] Where, σ is the Stefan-Bohzman constant 5.67×10 -8 W·m -2 K -4 ; T s is the snow surface temperature ℃; ε s is the long-wave emissivity of snow, which is taken as 0.97.

[0109] 2.2 Precipitation conduction flux: Q P =ρ w c w T a P r +ρ w c s T s P s ;

[0110] In the formula, ρ w is the density of water, take 1.0×10 3 kg / m 3 ;c w represents the specific heat capacity of water, taking 4.18×10 3 (J / kg) / ℃; c s Represents the specific heat capacity of snow and ice, generally taken as 2.09×10 3 (J / kg) / ℃; P r is the rainfall; P s is the snowfall, in mm; when Q P Negative values ​​indicate heat absorption from the snow layer.

[0111] 2.3 Geothermal flux: Q G =K G (T1-T2) / (z1-z2);

[0112] In the formula, K G represents the soil thermal conductivity, T1 is the temperature at the soil depth z1, and T2 is the temperature at the depth z2. In the absence of observations, it can be considered as a stable small constant or even negligible.

[0113] 2.4 Sensible heat flux:

[0114] Where, T s is the snow surface temperature, ρc p is the volume heat capacity of air, taking the constant as 1205 Jm -3 k -1 ; r as is the aerodynamic drag between the surface of the snow layer and the nearby reference height, calculated by the following formula:

[0115]

[0116] In the formula, z μ is the reference height for wind speed, usually 2m; x is the reference height for temperature, usually 1.2m; μ is the wind speed at the reference height; z m and z h are the dynamic impedance coefficient, heat and water vapor impedance coefficient, respectively, and for the snow surface, they are 0.001m and 0.0002m respectively: k1 is the VonKaman constant, and in this embodiment, it is 0.4. μ2 is the wind speed at an altitude of 2m (m / s), and the conversion method for the wind speed at any other height y is as follows:

[0117]

[0118] 2.5 Latent heat flux:

[0119] In the formula, λ V is the latent heat of evaporation, take 2.834×10 6 J / kg, R d is the dry air constant, 287 J·kg -1 K -1 ;e(T a ) and e(T s ) are respectively the air vapor pressure and the snow surface vapor pressure. It is usually considered that the snow surface is a saturated surface. The snow surface vapor pressure is the saturated vapor pressure at the snow surface temperature. The air vapor pressure is the product of the saturated vapor pressure at the air temperature and the relative humidity:

[0120] e(T a )=e svp (T a )×Rh

[0121] e svp (T a ) represents the saturated water vapor pressure, which is a function of temperature and is calculated using the Teten formula:

[0122]

[0123] 3. Determine the net energy of the snow layer based on the principle of the single-layer snowmelt model.

[0124] The net energy of the snow layer is calculated by the following formula: Net energy of the snow layer Q NET = Net radiation flux from snow surface Q R +Precipitation conduction flux Q P +Geothermal flux Q G +Sensible heat flux Q H + Latent heat flux Q LE .

[0125] 4. Calculate the snowmelt depth based on the net energy of the snow layer. The snowmelt depth is calculated using the following formula:

[0126] Snowmelt depth

[0127] Where: h is the snowmelt depth in mm; S is the melting heat of snow; ρ S is the snow density.

[0128] 5. Calculate the snow depth based on the snowmelt depth. The change of snow depth is obtained by inputting the temperature, humidity, air pressure, wind speed, snow surface temperature, initial snow depth, incident shortwave radiation, cloud coverage, snow surface albedo and the total amount of precipitation of various types in the corresponding time period in the specified area into the snow ablation model based on system dynamics. After the data are tested and found to be correct, the simulated snow depth data is finally calculated according to the snow depth calculation formula:

[0129] Snow depth = H 雨夹雪 / 2+H 降雪 -h

[0130] Among them, H 雨夹雪 is the snowfall depth of sleet, H 降雪 is the snowfall depth and h is the snowmelt depth.

[0131] In addition, the values ​​of various parameters used in the formula are shown in Table 1.

[0132] Table 1

[0133]

[0134] 6.1 Inspection:

[0135] The snow melting model was tested through the "Check Units" and "Check Model" functions of VENSIM. The test results were "units OK" and "Model is OK", respectively, indicating that the model passed the dimensional test and operation test. After the structural test, a historical test is required to compare the model calculation results with the actual historical data, calculate the relative error between the two, and analyze and judge the accuracy of the model calculation. This example compares the simulated snow depth with the measured snow depth to finally determine the accuracy of the model simulation. The results are shown in Figures 3 to 6 .

[0136] This embodiment also provides a snow ablation prediction method based on system dynamics, including: obtaining the air temperature, humidity, air pressure, wind speed, snow surface temperature, initial snow depth, incident shortwave radiation, cloud coverage, snow surface albedo and the total amount of each type of precipitation in the corresponding time period in the target area, and inputting them into a snow ablation model to obtain the snow depth after snow ablation, wherein the snow ablation model is constructed according to the snow ablation model construction method.

[0137] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A snow melt model construction method based on system dynamics, characterized in that: include: According to meteorological data, obtain the snow surface net radiation flux, precipitation conduction flux, geothermal flux, sensible heat flux, and latent heat flux; Obtaining the net energy of the snow layer according to the snow surface net radiation flux, the precipitation conduction flux, the geothermal flux, the sensible heat flux and the latent heat flux; Obtaining a snow melt depth model according to the net energy of the snow layer; A snow melting model is constructed based on the precipitation type discrimination model and the snow melting depth model.

2. The method for constructing a snow ablation model based on system dynamics according to claim 1, characterized in that: The meteorological data include: air temperature, air pressure, humidity, snow surface temperature, wind speed, snow surface albedo, cloud coverage and incident shortwave radiation.

3. The method for constructing a snow ablation model based on system dynamics according to claim 2, characterized in that: Acquiring the snow surface net radiation flux comprises: acquiring the snow surface net radiation flux according to the sum of net shortwave radiation, atmospheric longwave radiation and snow surface longwave radiation, wherein the net shortwave radiation is acquired according to the incident shortwave radiation and the snow surface albedo, and the atmospheric longwave radiation is acquired according to the cloud coverage rate; Acquiring the precipitation conduction flux comprises: acquiring the precipitation conduction flux according to the density, specific heat capacity, surface temperature, precipitation amount, and snowfall amount of water and snow; Acquiring the geothermal flux includes: acquiring the geothermal flux according to soil temperatures at different depths; Acquiring the sensible heat flux comprises: acquiring the sensible heat flux according to aerodynamic resistance, snow surface temperature, air temperature and volume heat capacity of air, wherein the aerodynamic resistance is acquired according to the wind speed; Acquiring the latent heat flux includes: acquiring the latent heat flux according to air vapor pressure and snow surface vapor pressure.

4. The method for constructing a snow ablation model based on system dynamics according to claim 1, characterized in that: According to the net energy of the snow layer, obtaining a snow melt depth model includes: Where h is the snowmelt depth, Q NET is the net energy of the snow layer, S is the melting heat of snow, ρ S is the snow density, Q LE is the latent heat flux, λ V is the latent heat of evaporation, ρ W is the density of water.

5. The method for constructing a snow ablation model based on system dynamics according to claim 1, characterized in that: Obtaining the precipitation type discrimination model includes: Get the median of the range of wet-bulb temperatures where the transition from rain to snow occurs, based on relative humidity and altitude; According to the ratio of the temperature range of sleet occurrence to the temperature range of rain-snow transition, the maximum temperature threshold and the minimum temperature threshold are obtained; The precipitation type discrimination model is obtained according to the maximum temperature threshold, the minimum temperature threshold and the median of the wet-bulb temperature range in which rain-snow conversion occurs, wherein the precipitation type discrimination model is used to obtain the precipitation type and obtain the depth of different precipitation types.

6. The method for constructing a snow ablation model based on system dynamics according to claim 4, characterized in that: The snow melt model includes: Snow depth = H 雨夹雪 / 2+H 降雪 -h Among them, H 雨夹雪 is the amount of sleet, H 降雪 is the snowfall, and h is the snowmelt depth.

7. A snow melt prediction method based on system dynamics, characterized in that: The air temperature, humidity, air pressure, wind speed, snow surface temperature, initial snow depth, incident shortwave radiation, cloud coverage, snow surface albedo and the total amount of each type of precipitation in the corresponding time period of the target area are obtained and input into the snow ablation model to obtain the snow depth after snow ablation, wherein the snow ablation model is constructed according to any one of the methods of claims 1-6.

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