A method for simulating heat flux in flooded lake wetlands in a watershed hydrological model

Abstract

The present invention discloses a method for simulating heat flux of flooded lake wetlands in a watershed hydrological model, which relates to the technical field of heat flux simulation and comprises the following steps: discretizing the watershed space into two parts: a slope river channel and a lake wetland; simulating water movement for the slope river channel unit; simulating surface energy exchange for the lake wetland unit on the basis of simulating the hydrological process; using a grid-based distributed hydrological model to simulate the sub-basin land surface hydrology and lake runoff; dividing the slope river channel and the lake wetland into simulation grid units respectively; establishing evapotranspiration, infiltration and surface runoff models; using a two-dimensional shallow water equation to process slope confluence; using a one-dimensional hydrodynamic model to calculate river confluence; establishing a lake water balance model to calculate lake water level; simulating the lake flooding process; and simulating the distributed heat flux process of the lake wetland. The model of the present invention has a simple structure and has the advantages of stable computing performance and improved efficiency, filling the technical gap in hydrothermal simulation of flooded wetlands.

Description

Technical Field

[0001] The present invention relates to the technical field of heat flux simulation, and in particular to a method for simulating heat flux of flooded lake wetlands in a watershed hydrological model. Background Art

[0002] Wetlands, a unique type of surface located in the transition zone between land and water, are often called the "kidneys of the Earth." Their water and heat fluxes are crucial for regulating regional climate, influencing internal water and heat cycles, and maintaining ecosystem health. Flooded lake wetlands, formed by the periodic wetting and drying cycles of the hydrological rhythm, account for approximately 15% of the world's total wetland area and are a crucial wetland type within wetland ecosystems. They serve as a critical interface for the exchange of water and energy between the Earth's surface and the atmosphere, playing a key role in the energy balance of the land-atmosphere coupled system. High water level fluctuations cause dramatic changes in wetland inundation dynamics, resulting in more complex interface properties and land surface parameters in flooded lake wetlands compared to conventional wetlands. Accurately modeling the dynamics of heat flux in flooded lake wetlands is crucial for understanding land-atmosphere interactions, exploring the mechanisms by which flooded wetlands regulate regional climate, and developing wetland conservation strategies.

[0003] As an important tool for studying land surface hydrological processes, hydrological models can simulate water and energy processes at the basin scale through modules such as surface water, groundwater, soil water, and lake hydrology. Most hydrological models focus on runoff generation and confluence processes, with the flow process at the outlet river section as the simulation target. For complex lake basins composed of sub-basins, rivers, and lakes, especially large flooded lakes, there is still a lack of universal hydrological models with strong applicability, high stability, and a certain degree of accuracy. Although some hydrological models at home and abroad have developed lake wetland water and heat flux modules, these parameterization schemes are all aimed at static wetlands that are flooded for a long time, and the underlying surface parameterization schemes are still based on fixed water surfaces or land as boundaries, which cannot describe the impact of large-scale flooding and exposure dynamics caused by large lake flooding processes on regional energy balance. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for simulating heat flux of flooded lake wetlands in a watershed hydrological model to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solution: a method for simulating heat flux of flooded lake wetlands in a watershed hydrological model, comprising the following steps:

[0006] S1: Discrete the watershed space into two parts: slope river channel and lake wetland;

[0007] S2: Divide the grid cells for the slope river channel and lake wetland respectively;

[0008] S3: Establish evapotranspiration, infiltration and surface runoff models, and analyze the main hydrological processes of evaporation, infiltration, runoff generation and confluence based on the models;

[0009] S4: Establish a lake water balance model to calculate the lake water level and the discharge at the lake outlet;

[0010] S5: Simulate the lake flooding process and simulate the distributed heat flux process of lake wetlands.

[0011] Furthermore, in step S1, the watershed space is discretized into two parts: slope river channels and lake wetlands. For the slope river channel units, the water movement process is simulated; for the lake wetland units, the surface energy exchange process is simulated on the basis of simulating the hydrological process. The slope river channel units and lake wetland units exchange water through the rivers entering or leaving the lake, and no overflow across the lake boundary will occur.

[0012] Furthermore, in step S2, the three parts of the slope, river channel and lake wetland are divided into grid units respectively. For the slope and lake wetland parts, square grid units are divided according to the established spatial resolution (1km~25km); for the river channel part, it is divided into rectangular grid units according to the shape of the river channel. Generally, the average river channel width is set as the grid width, and the grid length can be set according to the simulation accuracy of the confluence process (0.1~5km); the slope and river channel are divided into coarse grid units, and the lake wetland part is divided into fine grid units. The resolution of the coarse grid unit and the fine grid unit is an integer multiple, thereby realizing nesting between simulation areas.

[0013] Furthermore, in step S3, the runoff generation and confluence processes of the sub-basin include a runoff generation process at the slope scale and a confluence process at the slope river scale. The runoff generation process includes precipitation, canopy interception, vegetation transpiration, soil evaporation, surface water infiltration, vertical movement of soil moisture, and soil-water-groundwater exchange. The confluence process includes overland flow and soil midflow submodules at the slope scale, and a river confluence submodule at the river scale, ultimately obtaining the runoff into the lake. The slope is directly connected to the river, and the slope directly provides lateral inflow to the river confluence through overland flow and soil midflow. Based on net radiation, saturated water vapor pressure, actual water vapor pressure, actual water vapor pressure, and wind speed, an evapotranspiration process model for evapotranspiration ET is established:

[0014]

[0015] The Δ is the slope of the saturated water vapor pressure curve (kPa / °C), which is related to temperature. n is the net radiation, in MJ / m 2d is the net value of radiant energy per unit area; γ is the dry air constant, in kPa / °C, usually taken as 0.066 kPa / °C; es is the saturated water vapor pressure, in kPa, which represents the maximum pressure of water vapor in the air at a specific temperature; ea is the actual water vapor pressure, in kPa, which represents the actual pressure of water vapor in the air under specific conditions; R is the wind speed;

[0016] Based on the saturated hydraulic conductivity of the soil, the hydraulic head of the soil, the pressure head of the water in the soil, the water potential of the soil, and the infiltration surface area, an infiltration process model for the total infiltration amount I(t) is established:

[0017]

[0018] where f(t) is the infiltration rate that changes with time; K s is the saturated hydraulic conductivity of the soil (m / s); h is the hydraulic head of the soil (m), which represents the pressure head of water in the soil; φ is the water potential of the soil (m), which usually represents the water absorption capacity of the soil; A1 is the infiltration surface area; I(t) is the total infiltration amount during the time period, obtained by integration;

[0019] Based on precipitation, evapotranspiration, soil moisture change, and soil water and groundwater exchange, the surface runoff Q1 is calculated as:

[0020] Q1=P1-ET-ΔS1+L;

[0021] Where Q1 is surface runoff, P1 is precipitation, ET is evapotranspiration, ΔS1 is soil moisture change, and L is the exchange rate between soil water and groundwater;

[0022] The two-dimensional shallow water equation is used to calculate the slope runoff, and its vector form is:

[0023]

[0024] Where U1 is the unknown quantity to be solved in the two-dimensional shallow water equation, E1 and G1 are the two-dimensional directional fluxes; S1 is the source term in the two-dimensional shallow water equation;

[0025] A one-dimensional hydrodynamic model is used to calculate the river confluence, and the governing equations are the Saint-Venant equations, which are in vector form:

[0026]

[0027] Where U2 is the unknown quantity to be solved, F is the flux, and S2 is the source term. The governing equations are spatially discretized with second-order accuracy using the finite volume method, and temporally discretized using a second-order Runge–Kutta explicit scheme. The inter-grid numerical fluxes are calculated using an approximate Riemann solver. The bottom slope term in the source term is calculated using the hydrostatic reconstruction method and central difference discretization. The friction term is fully implicit, using Newton–Raphson iteration to achieve better numerical stability. The model computational step size uses a condition-based adaptive time step to ensure computational stability.

[0028] Furthermore, in step S4, a lake water balance model is established based on the lake water level in the previous simulation period and the lake water level in the current period, taking into account the changes in lake water volume, lake surface precipitation, lake surface evaporation, lake surface area, total flow of rivers entering the lake, and flow at the lake outlet:

[0029] ΔV=(PE)*A+R in +R out

[0030]

[0031] Where ΔV is the change in lake water volume, P1 is the precipitation on the lake surface, E is the evaporation on the lake surface, A2 is the lake surface area, and R in is the total flow of rivers into the lake, R out is the discharge at the lake outlet. h1 and H2 are the lake water levels in the previous simulation period and the current period, respectively. The relationship between the lake area and the water level can be obtained through the water level-area curve. The total flow of rivers entering the lake includes the sum of the runoff of all rivers entering the lake.

[0032] R out The discharge R can be calculated by the following formula, based on the assumption of broad crest weir flow and assuming that the velocity head can be ignored. out :

[0033]

[0034] Where b is the stream width (m), g is the acceleration of gravity, z is the current lake depth (m), and z min is the elevation above the weir or lake mouth (m). Discharge coefficient c d Used to consider inflow velocity, top non-parallel streamlines and energy loss, c d The value of varies between approximately 0.8 and 1.2.

[0035] Furthermore, in step S5, the seed-based flooding algorithm is as follows: the seed-based flooding algorithm takes the seed point as the starting point, and marks adjacent pixel areas as the same type or color by gradually diffusing and filling pixels. The seed-based flooding algorithm is used in conjunction with the DEM to simulate the active flooding process of shallow lakes. The steps of simulating the lake flooding process based on the seed-based flooding algorithm include: determining the location and flow data of the river entering the lake, initialization, starting the seed flooding, and updating the flooding process.

[0036] Determine the location and flow data of the river entering the lake: Determine the location of the injection point of the river entering the lake and the corresponding flow data. The injection point is regarded as the seed of the lake basin, and the flooding simulation process starts from the injection point;

[0037] Initialization: The injection point is used as the seed point, and the flow at the seed point is used as the initial flooding flow. At the same time, the lake basin DEM data and initial water level data are loaded into the computing environment;

[0038] Seed flooding starts: Starting from the seed point, the eight-neighborhood connected domain search spreads to the surrounding eight neighboring grids, layer by layer, judging whether each grid meets the flooding conditions, and adding the grid that meets the conditions to the queue for processing; this process is iterated continuously until no new grids are flooded;

[0039] Update the flooding process: Based on the flooding elevation values ​​at each time period, a dynamic image of the flooding process can be generated to show the gradual expansion of the flooding range, thereby updating the flooding value H new :

[0040]

[0041] The H new is the updated flood elevation value, H old is the inundation elevation value of the current grid, Q3 is the injection flow data, and A3 is the injection flow impact range;

[0042] The cell grids are divided into two categories: lake grids and non-lake grids, where the lake grids have seasonal inundation extent changes during the simulation period;

[0043] The energy balance equation is used to calculate the surface energy components of each grid and analyze the net radiation R n :

[0044] R n =H+ρ w *λ v *E0+G;

[0045] where R n is the net radiation (W*m -2 ), H is the sensible heat flux (W*m -2 ), ρ w *λv *E is the latent heat flux (W*m -2 )(ρ w is the density of liquid water, in kg*m -3 ;λ v is the latent heat of vaporization of water, in J*kg -1 ), E0 is evapotranspiration, G is geothermal flux (W*m -2 );

[0046] Based on the surface albedo, downward shortwave radiation, surface emissivity and downward longwave radiation, the net radiation R input to the grid is obtained. n :

[0047]

[0048] Where α is the surface albedo of the land cover type, R s is the downward shortwave radiation (W*m -2 ), ε is the surface emissivity of the land cover type, R L is downward long-wave radiation (W*m -2 ), T s is the surface temperature (K), σ is the Stefan-Boltzmann constant (5.67×10-8W*m -2 *K -4 );

[0049] The sensible heat flux H is calculated based on the aerodynamic resistance of the heat flow, air density, air specific heat capacity, surface temperature and surface air temperature:

[0050]

[0051] Where α is the grid flooded area ratio, T W is the water surface temperature, T g is the soil surface temperature of the exposed part of the grid, T a is the air temperature, ρ a is the air density, c p is the specific heat capacity of air, r h,w is the aerodynamic resistance on the water surface, r h,g is the aerodynamic resistance on the land surface, r s,w is the surface resistance of water, r s,g is the soil evaporation resistance.

[0052] The inundation ratio is used to achieve a continuous transition between water and land energy fluxes, accurately characterizing the heat exchange behavior of "partially inundated" grids; the water temperature calculation includes a heat storage term to reflect the thermal buffering effect during flood retention; the introduction term includes the influence of the pressure gradient force to avoid overestimation of latent heat flux in high humidity environments; the land surface resistance term is related to soil moisture, and the model's feedback on evaporation suppression during drought periods is more significant.

[0053] Derivation process: Assume that the grid contains two types of surfaces, the water area accounts for α, and the surface temperature is T W ; The soil area is 1-α, and the surface temperature is T g The total sensible heat flux needs to be summed by the area weight. According to the law of conservation of energy, the greater the resistance, the smaller the sensible heat flux. The sensible heat flux on the surface of the water body is determined by the temperature difference T W -T a Drive, resistance includes aerodynamic resistance r h,w (reflecting the effect of air turbulence on heat transfer) and water surface resistance r s,w (May be introduced due to evaporation suppression or water surface characteristics.) The formula for calculating the sensible heat flux of water is:

[0054]

[0055] The soil sensible heat flux is similar, with aerodynamic resistance r h,g (soil roughness affects turbulence) and soil evaporation resistance r s,g (related to soil moisture, dry soil has higher impedance) Two resistance terms.

[0056]

[0057] Combining the contributions of water and soil according to area weights, we can obtain the sensible heat flux calculation formula for the mixed grid of water and soil:

[0058]

[0059] Based on the soil thermal conductivity, the soil temperature between the first and second soil layers, and the thickness of the first soil layer, the geothermal flux G of the top soil layer is calculated:

[0060]

[0061] Where k is the thermal conductivity of soil (W*m -1 *K -1 ), T1 is the soil temperature between the first and second soil layers (K), D1 is the thickness of the first soil layer (m);

[0062] The net surface radiation R is calculated based on the sensible heat flux, latent heat flux, changes in heat storage in the overlying water and soil of the floodplain, the advection heat flux carried by the water flow, and the heat flux entering the underlying soil. n :

[0063] R n =H+LE+ΔS2+A4+Q B ;

[0064] where R n is the net surface radiation, H is the sensible heat flux, LE is the latent heat flux, ΔS2 is the change in heat storage in the overlying water and soil of the floodplain wetland, A4 is the advection heat flux carried by the water flow, Q B is the heat flux into the underlying soil. H and LE are obtained from flux observation data, while ΔS2 and A4 need to be estimated based on key parameters such as specific heat capacity and flow rate combined with the energy equation;

[0065] Based on soil depth, soil temperature, soil specific heat capacity and reference depth z ref The heat flux at , by integrating the one-dimensional heat diffusion equation, can be obtained as follows:

[0066]

[0067] Where z is the soil depth (m), T is the soil temperature (K), ρ s c s is the specific heat capacity of soil (J*kg -1 *K -1 ), S(z ref ) is the reference depth z ref The heat flux at . If z ref Greater than 1m and S(z ref ) is less than 1% of the surface soil heat flux, it can be assumed that S(z ref )=0;

[0068] Given a temperature profile T(z i ), based on the time interval of discrete time steps, reference depth, vertical interval, and vertical depth coordinate, the soil heat flux G is calculated:

[0069]

[0070] Where Δt represents the time interval, which is used for discrete time steps; t represents the current moment; z ref represents the reference depth, Δz represents the vertical interval, z i Indicates the depth coordinate in the vertical direction, T (zi,t) For depth Z i, the soil temperature corresponding to time t, the soil specific heat capacity can be calculated based on the soil water content and soil porosity, and the temperature profile is estimated using the soil heat diffusion equation;

[0071] Based on the total water depth, average water temperature, and the change in average water temperature, the change in water body heat storage during the flooding period ΔS is calculated. w :

[0072]

[0073] Among them, ρ w c p is the specific heat capacity of water (J*kg -1 *K -1 ), z w is the total water depth, T w is the average water temperature, ΔT w is the change in average water temperature during the Δt period. Based on water temperature observations, when the water depth is less than 1m, the lake water temperature is considered to be uniformly mixed; when the water depth is greater than 1m, ΔT is estimated by water thermal conductivity and surface temperature from remote sensing. w Heat storage changes are based on the change in water heat storage during the flood season (ΔS w ) and the weighted average of the soil heat flux (G) in the dry season. Due to the drastic changes in water conditions, the surface flow velocity of the flooded wetland water body is relatively fast, and the horizontal advection flux of the overlying water body is calculated by the following formula:

[0074]

[0075] Where u is the water velocity along the temperature gradient measurement direction, x is the horizontal distance, is the horizontal gradient of water temperature, ρ w c p is the specific heat capacity of water.

[0076] Compared with the existing technology, the beneficial effects achieved by the present invention are: overcoming the defect of traditional hydrological models in insufficiently depicting the hydrothermal processes of large lake wetlands, making up for the problem that the existing hydrological model lake wetland hydrothermal simulation parameterization scheme is too dependent on complex hydrodynamic equations, realizing multi-level nested simulation of basin-river-lake and refined grid encryption of lake wetlands, using seed spreading algorithm to simulate flooding and inundation process, and using inundation dynamic variables to drive energy balance equation, improving the model's simulation ability of heat flux in flooded wetlands, quantifying the hydrothermal balance process of large lake wetlands, enriching and improving the theoretical system of lake-atmosphere energy exchange and regional atmospheric hydrological cycle response. From the perspective of practical application, the present invention has the ability to improve the accuracy of regional hydrological and meteorological simulation and prediction from a physical mechanism. Compared with the existing hydrodynamic simulation scheme, it has the advantages of low computational cost, low data requirements, simple model structure, stable computational performance, and improved efficiency, filling the technical gap in hydrothermal simulation of flooded wetlands. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0078] Figure 1 The present invention is a flow chart of a method for simulating heat flux of flooded lake wetlands in a watershed hydrological model. DETAILED DESCRIPTION

[0079] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0080] See also Figure 1 The present invention provides a technical solution: a method for simulating heat flux of flooded lake wetlands in a watershed hydrological model, comprising the following steps:

[0081] S1: Discrete the watershed space into two parts: slope river channel and lake wetland;

[0082] S2: Divide the grid cells for the slope river channel and lake wetland respectively;

[0083] S3: Establish evapotranspiration, infiltration and surface runoff models, and analyze the main hydrological processes of evaporation, infiltration, runoff generation and confluence based on the models;

[0084] S4: Establish a lake water balance model to calculate the lake water level and the discharge at the lake outlet;

[0085] S5: Simulate the lake flooding process and simulate the distributed heat flux process of lake wetlands.

[0086] In step S1, the watershed space is discretized into two parts: slope river channels and lake wetlands. For the slope river channel units, the water movement process is simulated; for the lake wetland units, the surface energy exchange process is simulated at the same time on the basis of simulating the hydrological process. The slope river channel units and lake wetland units exchange water through the inflow or outflow rivers, and no overflow across the lake boundary will occur.

[0087] In step S2, the three parts of the slope, river channel and lake wetland are divided into grid units respectively. For the slope and lake wetland parts, square grid units are divided according to the established spatial resolution (1km~25km); for the river channel part, it is divided into rectangular grid units according to the shape of the river channel. Generally, the average river channel width is set as the grid width, and the grid length can be set according to the simulation accuracy of the confluence process (0.1~5km); the slope and river channel are divided into coarse grid units, and the lake wetland part is divided into fine grid units. The resolution of the coarse grid unit and the fine grid unit is an integer multiple, so as to achieve nesting between simulation areas.

[0088] In step S3, the runoff generation and confluence processes of the sub-basin include the runoff generation process at the slope scale and the confluence process at the slope river scale. The runoff generation process includes precipitation, canopy interception, vegetation transpiration, soil evaporation, surface water infiltration, vertical movement of soil moisture, and soil-groundwater exchange. The confluence process includes the overland flow and soil midflow sub-modules at the slope scale, and the river confluence sub-module at the river scale, ultimately obtaining the runoff into the lake. The slope is directly connected to the river, and the slope directly provides lateral inflow to the river confluence through overland flow and soil midflow. Based on net radiation, saturated water vapor pressure, actual water vapor pressure, actual water vapor pressure, and wind speed, an evapotranspiration process model for evapotranspiration (ET) is established:

[0089]

[0090] The Δ is the slope of the saturated water vapor pressure curve (kPa / °C), which is related to temperature. n is the net radiation, in MJ / m 2 d is the net value of radiant energy per unit area; γ is the dry air constant, in kPa / °C, usually taken as 0.066 kPa / °C; es is the saturated water vapor pressure, in kPa, which represents the maximum pressure of water vapor in the air at a specific temperature; ea is the actual water vapor pressure, in kPa, which represents the actual pressure of water vapor in the air under specific conditions; R is the wind speed;

[0091] Based on the saturated hydraulic conductivity of the soil, the hydraulic head of the soil, the pressure head of the water in the soil, the water potential of the soil, and the infiltration surface area, an infiltration process model for the total infiltration amount I(t) is established:

[0092]

[0093] where f(t) is the infiltration rate that changes with time; K s is the saturated hydraulic conductivity of the soil (m / s); h is the hydraulic head of the soil (m), which represents the pressure head of water in the soil; φ is the water potential of the soil (m), which usually represents the water absorption capacity of the soil; A1 is the infiltration surface area; I(t) is the total infiltration amount during the time period, obtained by integration;

[0094] Based on precipitation, evapotranspiration, soil moisture change, and soil water and groundwater exchange, the surface runoff Q1 is calculated as:

[0095] Q1=P1-ET-ΔS1+L;

[0096] Where Q1 is surface runoff, P1 is precipitation, ET is evapotranspiration, ΔS1 is soil moisture change, and L is the exchange rate between soil water and groundwater;

[0097] The two-dimensional shallow water equation is used to calculate the slope runoff, and its vector form is:

[0098]

[0099] Where U1 is the unknown quantity to be solved in the two-dimensional shallow water equation, E1 and G1 are the two-dimensional directional fluxes; S1 is the source term in the two-dimensional shallow water equation;

[0100] A one-dimensional hydrodynamic model is used to calculate the river confluence, and the governing equations are the Saint-Venant equations, which are in vector form:

[0101]

[0102] Where U2 is the unknown quantity to be solved, F is the flux, and S2 is the source term. The governing equations are spatially discretized with second-order accuracy using the finite volume method, and temporally discretized using a second-order Runge–Kutta explicit scheme. The inter-grid numerical fluxes are calculated using an approximate Riemann solver. The bottom slope term in the source term is calculated using the hydrostatic reconstruction method and central difference discretization. The friction term is fully implicit, using Newton–Raphson iteration to achieve better numerical stability. The model computational step size uses a condition-based adaptive time step to ensure computational stability.

[0103] In step S4, a lake water balance model is established based on the lake water level in the previous simulation period and the lake water level in the current period, taking into account the changes in lake water volume, lake surface precipitation, lake surface evaporation, lake surface area, total flow of rivers entering the lake, and flow at the lake outlet:

[0104] ΔV=(PE)*A+R in +R out

[0105]

[0106] Where ΔV is the change in lake water volume, P1 is the precipitation on the lake surface, E is the evaporation on the lake surface, A2 is the lake surface area, and R in is the total flow of rivers into the lake, R out is the discharge at the lake outlet. h1 and H2 are the lake water levels in the previous simulation period and the current period, respectively. The relationship between the lake area and water level can be obtained from the water level-area curve. The total flow of rivers entering the lake includes the sum of the runoff of all rivers entering the lake.

[0107] R out The discharge R can be calculated by the following formula, based on the assumption of broad crest weir flow and assuming that the velocity head can be ignored. out :

[0108]

[0109] Where b is the stream width (m), g is the acceleration of gravity, z is the current lake depth (m), and z min is the elevation above the weir or lake mouth (m). Discharge coefficient c d Used to consider inflow velocity, top non-parallel streamlines and energy loss, c d The value of varies between approximately 0.8 and 1.2.

[0110] In step S5, the seed-based flooding algorithm is as follows: the seed-based flooding algorithm takes the seed point as the starting point, and gradually diffuses and fills the pixels to mark adjacent pixel areas as the same type or color. The seed-based flooding algorithm is used in conjunction with the DEM to simulate the active flooding process of shallow lakes. The steps of simulating the lake flooding process based on the seed-based flooding algorithm include: determining the location and flow data of the river entering the lake, initialization, starting the seed flooding, and updating the flooding process;

[0111] Determine the location and flow data of the river entering the lake: Determine the location of the injection point of the river entering the lake and the corresponding flow data. The injection point is regarded as the seed of the lake basin, and the flooding simulation process starts from the injection point;

[0112] Initialization: The injection point is used as the seed point, and the flow at the seed point is used as the initial flooding flow. At the same time, the lake basin DEM data and initial water level data are loaded into the computing environment;

[0113] Seed flooding starts: Starting from the seed point, the eight-neighborhood connected domain search spreads to the surrounding eight neighboring grids, layer by layer, judging whether each grid meets the flooding conditions, and adding the grid that meets the conditions to the queue for processing; this process is iterated continuously until no new grids are flooded;

[0114] Update the flooding process: Based on the flooding elevation values ​​at each time period, a dynamic image of the flooding process can be generated to show the gradual expansion of the flooding range, thereby updating the flooding value H new :

[0115]

[0116] The H new is the updated flood elevation value, H old is the inundation elevation value of the current grid, Q3 is the injection flow data, and A3 is the injection flow impact range;

[0117] The cell grids are divided into two categories: lake grids and non-lake grids, where the lake grids have seasonal inundation extent changes during the simulation period;

[0118] The energy balance equation is used to calculate the surface energy components of each grid and analyze the net radiation R n :

[0119] R n =H+ρ w *λ v *E0+G;

[0120] where R n is the net radiation (W*m -2 ), H is the sensible heat flux (W*m -2 ), ρ w *λ v *E is the latent heat flux (W*m -2 )(ρ w is the density of liquid water, in kg*m -3 ;λ v is the latent heat of vaporization of water, in J*kg -1 ), G is the geothermal flux (W*m -2 );

[0121] Based on the surface albedo, downward shortwave radiation, surface emissivity and downward longwave radiation, the net radiation R input to the grid is obtained. n :

[0122]

[0123] Where α is the surface albedo of the land cover type, R s is the downward shortwave radiation (W*m -2 ), ε is the surface emissivity of the land cover type, R L is downward long-wave radiation (W*m -2 ), σ is the Stefan-Bolt zmann constant (5.67×10-8W*m -2 *K -4 );

[0124] The sensible heat flux H is calculated based on the aerodynamic resistance of the heat flow, air density, air specific heat capacity, surface temperature and surface air temperature:

[0125]

[0126] Where α is the grid flooded area ratio, T W is the water surface temperature, T g is the soil surface temperature of the exposed part of the grid, T a is the air temperature, ρ a is the air density, c p is the specific heat capacity of air, r h,w is the aerodynamic resistance on the water surface, r h,g is the aerodynamic resistance on the land surface, r s,w is the surface resistance of water, r s,g is the soil evaporation resistance.

[0127] The inundation ratio is used to achieve a continuous transition between water and land energy fluxes, accurately characterizing the heat exchange behavior of "partially inundated" grids; the water temperature calculation includes a heat storage term to reflect the thermal buffering effect during flood retention; the introduction term includes the influence of the pressure gradient force to avoid overestimation of latent heat flux in high humidity environments; the land surface resistance term is related to soil moisture, and the model's feedback on evaporation suppression during drought periods is more significant.

[0128] where r h is the aerodynamic resistance of heat flow (s*m -1 ), ρ a is the air density, c p is the specific heat capacity of air, T s is the surface temperature, T a is the surface air temperature;

[0129] Based on the soil thermal conductivity, the soil temperature between the first and second soil layers, and the thickness of the first soil layer, the geothermal flux G of the top soil layer is calculated:

[0130]

[0131] Where k is the thermal conductivity of soil (W*m -1 *K -1 ), T1 is the soil temperature between the first and second soil layers (K), D1 is the thickness of the first soil layer (m);

[0132] The net surface radiation R is calculated based on the sensible heat flux, latent heat flux, changes in heat storage in the overlying water and soil of the floodplain, the advection heat flux carried by the water flow, and the heat flux entering the underlying soil. n :

[0133] R n =H+LE+ΔS2+A4+Q B ;

[0134] where R n is the net surface radiation, H is the sensible heat flux, LE is the latent heat flux, ΔS2 is the change in heat storage in the overlying water and soil of the floodplain wetland, A4 is the advection heat flux carried by the water flow, Q B is the heat flux into the underlying soil. H and LE are obtained from flux observation data, while ΔS2 and A4 need to be estimated based on key parameters such as specific heat capacity and flow rate combined with the energy equation;

[0135] Based on soil depth, soil temperature, soil specific heat capacity and reference depth z ref The heat flux at , by integrating the one-dimensional heat diffusion equation, can be obtained as follows:

[0136]

[0137] Where z is the soil depth (m), T is the soil temperature (K), ρ s c s is the specific heat capacity of soil (J*kg -1 *K -1 ), S(z ref ) is the reference depth z ref The heat flux at . If z ref Greater than 1m and S(z ref ) is less than 1% of the surface soil heat flux, it can be assumed that S(z ref )=0;

[0138] Given a temperature profile T(z i ), based on the time interval of discrete time steps, reference depth, vertical interval, and vertical depth coordinate, the soil heat flux G is calculated:

[0139]

[0140] Where Δt represents the time interval, which is used for discrete time steps; t represents the current moment; z ref represents the reference depth, Δz represents the vertical interval, z i represents the depth coordinate in the vertical direction. The soil specific heat capacity can be calculated based on the soil water content and soil porosity, and the temperature profile is estimated using the soil heat diffusion equation;

[0141] Based on the total water depth, average water temperature, and the change in average water temperature, the change in water body heat storage during the flooding period ΔS is calculated. w :

[0142]

[0143] Among them, ρ w c p is the specific heat capacity of water (J*kg -1 *K -1 ), z w is the total water depth, T w is the average water temperature, ΔT w is the change in average water temperature during the Δt period. Based on water temperature observations, when the water depth is less than 1m, the lake water temperature is considered to be uniformly mixed; when the water depth is greater than 1m, ΔT is estimated by water thermal conductivity and surface temperature from remote sensing. w Heat storage changes are based on the change in water heat storage during the flood season (ΔS w ) and the weighted average of the soil heat flux (G) in the dry season. Due to the drastic changes in water conditions, the surface flow velocity of the flooded wetland water body is relatively fast, and the horizontal advection flux of the overlying water body is calculated by the following formula:

[0144]

[0145] Where u is the water velocity along the temperature gradient measurement direction, x is the horizontal distance, is the horizontal gradient of water temperature, ρ w c p is the specific heat capacity of water.

[0146] Example 1: The basin has both slopes and river channels formed by undulating mountains and large areas of lakes and wetlands, which are of great significance to regional ecology and water resource regulation.

[0147] First, the basin space is discretized into two parts: slope river channels and lake wetlands. For slope river channel units, the focus is on simulating the water movement process, such as how water flows on the slope after precipitation, and the convergence and transmission of water in the river channel. For lake wetland units, while simulating hydrological processes such as the inflow and outflow of lake water and water level changes, the surface energy exchange process must also be simulated, because the energy exchange of lake wetlands has a key impact on their ecosystems. It is assumed that slope and river channel units and lake wetland units only exchange water through inflow or outflow rivers to prevent overflow across lake boundaries.

[0148] Next, simulation grid cells were divided for the slopes, river channels, and lake wetlands. The slopes and lake wetlands were divided into square grid cells according to a predetermined spatial resolution, enabling more accurate simulation of their hydrological and energy processes. The river channel was divided into rectangular grids based on its shape to accommodate its morphological characteristics. Furthermore, the slopes and river channels were divided into coarse grid cells, while the lake wetlands were divided into fine grid cells. The resolution of the coarse and fine grid cells was an integer multiple, enabling effective simulation at different scales.

[0149] The sub-basin runoff generation and confluence process at the slope scale includes precipitation, canopy interception, vegetation transpiration, soil evaporation, surface water infiltration, vertical soil moisture movement, and soil-water-groundwater exchange. The confluence process at the slope-scale river channel scale encompasses the overland flow and soil flow submodules at the slope scale, as well as the river channel confluence submodule at the river channel scale, ultimately resulting in the precise calculation of runoff into the lake.

[0150] A lake water balance model was established, taking into account factors such as changes in lake water volume, precipitation over the lake, evaporation from the lake, lake surface area, total inflow of rivers into the lake, and outflow at the lake outlet. This model accurately captures the dynamic changes in lake water levels. A seed-based inundation algorithm, combined with a DEM, simulates the active inundation process of shallow lakes, vividly demonstrating the dynamic process of the gradual expansion of the inundation range. Simultaneously, a distributed heat flux process was simulated, and through methods such as the energy balance equation, key energy components such as net radiation, sensible heat flux, and geothermal flux were comprehensively analyzed. This provides strong support for a deeper understanding of the basin's hydrological and energy conditions, and facilitates the scientific management and protection of the basin.

[0151] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

Claims

1. A method for simulating heat flux in flooded lake wetlands in a watershed hydrological model, characterized by: The method comprises the following steps: S1: Discrete the watershed space into two parts: slope river channel and lake wetland; S2: Divide the grid cells for the slope river channel and lake wetland respectively; S3: Establish evapotranspiration, infiltration and surface runoff models, and analyze the main hydrological processes of evaporation, infiltration, runoff generation and confluence based on the models; S4: Establish a lake water balance model to calculate the lake water level and the discharge at the lake outlet; S5: simulate the lake flooding process and conduct distributed heat flux simulation of lake wetlands; In step S5, the lake inundation process is simulated based on a seed inundation algorithm to simulate the distributed heat flux process of the lake wetland. The seed inundation algorithm is as follows: the seed inundation algorithm takes the seed point as the starting point, and marks adjacent pixel areas as the same type or color by gradually diffusing and filling pixels. The seed inundation algorithm is used in conjunction with the DEM to simulate the active inundation process of shallow lakes. The steps of simulating the lake inundation process based on the seed inundation algorithm include: determining the location and flow data of the river entering the lake, initialization, starting the seed inundation, and updating the inundation process. Determine the location and flow data of the river entering the lake: Determine the location of the injection point of the river entering the lake and the corresponding flow data. The injection point is regarded as the seed of the lake basin, and the flooding simulation process starts from the injection point; Initialization: The injection point is used as the seed point, and the flow at the seed point is used as the initial flooding flow. At the same time, the lake basin DEM data and initial water level data are loaded into the computing environment; Seed flooding starts: Starting from the seed point, the eight-neighborhood connected domain search spreads to the surrounding eight neighboring grids, layer by layer, judging whether each grid meets the flooding conditions, and adding the grid that meets the conditions to the queue for processing; this process is iterated continuously until no new grids are flooded; Update the flooding process: Based on the flooding elevation values ​​at each time period, a dynamic image of the flooding process can be generated to show the gradual expansion of the flooding range, thereby updating the flooding value H new .

2. The method for simulating heat flux of flooded lake wetlands in a watershed hydrological model according to claim 1, characterized in that: In step S1, the watershed space is discretized into two parts: slope river channels and lake wetlands. For the slope river channel units, the water movement process is simulated; for the lake wetland units, the surface energy exchange process is simulated at the same time on the basis of simulating the hydrological process. The slope river channel units and lake wetland units exchange water through the inflow or outflow rivers, and no overflow across the lake boundary will occur.

3. The method for simulating heat flux of flooded lake wetlands in a watershed hydrological model according to claim 2, characterized in that: In step S2, the three parts of the slope, river channel and lake wetland are divided into grid units respectively. For the slope and lake wetland parts, square grid units are divided according to the established spatial resolution; for the river channel part, rectangular grid units are divided according to the shape of the river channel; the slope and river channel are divided into coarse grid units, and the lake wetland part is divided into fine grid units, and the resolution of the coarse grid units and the fine grid units are integer multiples.

4. The method for simulating heat flux of flooded lake wetlands in a watershed hydrological model according to claim 3, characterized in that: In step S3, the runoff generation and confluence processes of the watershed include a runoff generation process at the slope scale and a confluence process at the slope river scale. The runoff generation process includes precipitation, canopy interception, vegetation transpiration, soil evaporation, surface water infiltration, vertical movement of soil moisture, and soil-water-groundwater exchange. The confluence process includes overland flow and soil midflow submodules at the slope scale, and a river confluence submodule at the river scale, ultimately obtaining runoff into the lake. The slope is directly connected to the river, and the slope directly provides lateral inflow to the river confluence through overland flow and soil midflow. Based on net radiation, saturated water vapor pressure, actual water vapor pressure, actual water vapor pressure, and wind speed, an evapotranspiration process model for evapotranspiration (ET) is established. Based on the saturated hydraulic conductivity of soil, soil hydraulic head, pressure head of water in soil, soil water potential, and infiltration surface area, an infiltration process model for the total infiltration amount I(t) is established. Based on precipitation, evapotranspiration, infiltration, and soil water and groundwater exchange, a surface runoff model for surface runoff Q1 is established. The two-dimensional shallow water equation is used to calculate the slope runoff, and the one-dimensional hydrodynamic model is used to calculate the river runoff.

5. The method for simulating heat flux of flooded lake wetlands in a watershed hydrological model according to claim 4, characterized in that: In step S4, a lake water balance model is established based on the lake water level in the previous simulation period and the lake water level in the current period, taking into account changes in lake water volume, lake surface precipitation, lake surface evaporation, lake surface area, total flow of rivers entering the lake, and flow at the lake outlet.

6. The method for simulating heat flux of flooded lake wetlands in a watershed hydrological model according to claim 5, characterized in that: The cell grids are divided into two categories: lake grids and non-lake grids, where the lake grids have seasonal inundation extent changes during the simulation period.

7. The method for simulating heat flux of flooded lake wetlands in a watershed hydrological model according to claim 6, characterized in that: The energy balance equation is used to calculate the surface energy components of each grid and analyze the net radiation R n ; Based on the surface albedo, downward shortwave radiation, surface emissivity and downward longwave radiation, the net radiation R input to the grid is obtained. n ; Calculate the sensible heat flux H based on the aerodynamic resistance to heat flow, air density, air specific heat capacity, surface temperature, and surface air temperature: ； Where α is the grid flooded area ratio, T W is the water surface temperature, T g is the soil surface temperature of the exposed part of the grid, T a is the air temperature, ρ a is the air density, c p is the specific heat capacity of air, r h,w is the aerodynamic resistance on the water surface, r h,g is the aerodynamic resistance on the land surface, r s,w is the surface resistance of water, r s,g is the soil evaporation resistance; Based on the soil thermal conductivity, the soil temperature between the first and second soil layers, and the thickness of the first soil layer, the geothermal flux G of the top soil layer is calculated: ； where k is the soil thermal conductivity, T1 is the soil temperature between the first and second soil layers, and D1 is the thickness of the first soil layer.

8. The method for simulating heat flux of flooded lake wetlands in a watershed hydrological model according to claim 7, characterized in that: The net surface radiation R is calculated based on the sensible heat flux, latent heat flux, changes in heat storage in the overlying water and soil of the floodplain, the advection heat flux carried by the water flow, and the heat flux entering the underlying soil. n ; Based on soil depth, soil temperature, soil specific heat capacity and reference depth z ref The heat flux at , by integrating the one-dimensional heat diffusion equation, can be obtained as follows: ； Given a temperature profile T(z i ), based on the time interval of discrete time steps, reference depth, vertical interval, and vertical depth coordinate, the soil heat flux G is calculated: ； Where Δt represents the time interval, which is used for discrete time steps; t represents the current moment; z ref represents the reference depth, Δz represents the vertical interval, z i represents the depth coordinate in the vertical direction. The soil specific heat capacity can be calculated based on the soil water content and soil porosity, and the temperature profile is estimated using the soil heat diffusion equation; Based on the total water depth, average water temperature, and the change in average water temperature, the change in water heat storage during the flooding period, ΔSw, was calculated; the horizontal advection flux A of the overlying water body was calculated using the following formula: ； Where u is the water velocity along the temperature gradient measurement direction, x is the horizontal distance, is the horizontal gradient of water temperature, ρ w c p is the specific heat capacity of water.

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