Reservoir sediment and temperature dual density current inversion and prediction method

Abstract

The invention belongs to the technical field of water conservancy projects, and discloses a reservoir sediment and temperature dual density flow inversion and prediction method, which comprises the following steps: firstly, establishing a water temperature-sediment-ice coupling model; the water temperature-sediment-ice coupling model comprises a water power module, a sand module, a water temperature module and an ice module; secondly, constructing a profile model of the reservoir in the water flow and water depth directions, dividing the profile model into a plurality of grid units, and setting boundary conditions and initial conditions; and solving the water temperature-sediment-ice coupling model to obtain reservoir area sediment content space-time distribution, water temperature space-time distribution and ice condition space-time distribution of the reservoir. According to the method, under the consideration of the hydrodynamic force-water temperature-ice-sand coupling effect, the sediment movement process in different types of sand-containing river reservoirs in the cold region and the thermodynamic evolution process and rule of the water temperature and ice condition of the reservoirs are accurately obtained.

Description

Technical Field

[0001] The invention belongs to the technical field of water conservancy engineering, relates to the inversion and prediction of reservoir water temperature-sediment-ice conditions, and in particular to an inversion and prediction method for reservoir sediment and temperature dual density flow. Background Art

[0002] After the sand-laden water flows into the reservoir, there is a large density difference with the water in the reservoir, which causes the phenomenon of sediment density flow. Sediment density flow will not only change the sedimentation situation of the reservoir, but also affect the water temperature stratification characteristics of the reservoir, making its water temperature distribution different from that of the reservoir on the low-sand-content river. These changes directly affect the thermal process of the reservoir and its upstream and downstream rivers. In rivers and reservoirs north of 30° north latitude (referred to as cold zone reservoirs), ice conditions of varying degrees will occur every year. Ice jams and ice dams are easily formed in the river during the ice flood season, causing the cross-sectional area of ​​the river to decrease and the water level to rise, which can cause ice floods. Due to the downward movement of the maximum flow velocity point during the ice flood season, it will cause strong river bottom scouring, which will lead to a higher sediment content in the river during the ice flood season. The vertical water temperature in the reservoir area in winter is generally inverted. The inflowing low-temperature water carrying more sediment may sink to the bottom of the high-temperature water due to its high density, changing the original buoyancy mode and indirectly affecting the temporal and spatial distribution of the reservoir ice conditions.

[0003] It is worth noting that the development of water conservancy and hydropower projects is currently concentrated in cold and high-altitude river source areas. For example, the development of hydropower in the upper reaches of the Yellow River has provided a large amount of clean energy for the northwest region, helping to alleviate the problem of energy shortage. However, the construction of reservoirs in rivers with high sediment content will inevitably face the coupling problem of sediment, ice conditions and water temperature, such as the formation of inverted temperature distribution in the reservoir area when the sediment content entering the reservoir is high, the sediment density flow accelerates the discharge of water from the stagnant temperature layer at the bottom of the reservoir, the freezing and thawing of the reservoir area or the tail of the reservoir is delayed, and the ice space range is reduced.

[0004] The interaction between ice, water and sand in the reservoir is mainly reflected in the impact of sediment density flow on the thermal state of the reservoir. Since the movement of sediment density flow itself is relatively complex, coupled with the influence of water temperature stratification, the movement of the dual density flow coupled with water temperature and sediment is more complicated. When high-sediment-content water enters the reservoir, it not only destroys the existing water temperature stratification structure, but also has a significant impact on the stratified flow of the reservoir and the material exchange in the water body. In this field, there are few existing methods for inverting the water temperature and ice conditions of reservoirs on high-sediment-content rivers. In particular, the sediment settling velocity is mostly calculated based on the median particle size of a single group. When the water flow has a high sediment concentration and the sediment particle size range is widely distributed, the error is large, which affects the water temperature inversion effect.

[0005] Water temperature is one of the key factors affecting fish reproduction and spawning. Different fish have specific requirements for water temperature during their reproduction. Suitable water temperature can stimulate the development and maturation of fish gonads and prompt them to enter the reproductive state. In addition, sediment carries a wealth of biogenic substances. The movement and distribution of sediment changes the physical environment of the water body and the material flux in the water body, which in turn affects plankton, plants and fish. Therefore, accurately predicting the change process of water temperature and the movement process of sediment can provide a scientific basis for the protection and management of aquatic ecology in rivers and reservoirs.

[0006] In summary, the existence of high sediment content and ice conditions has brought great challenges to the inversion of reservoir water temperature and ice conditions, and also put forward higher requirements for the applicability of the model. At the same time, the accurate prediction of water temperature and sediment in reservoirs of high-sediment-content rivers is also of great significance. Therefore, the research on water-ice-sand coupling model and the inversion of water temperature and ice conditions of reservoirs in cold-region sediment-rich rivers have important scientific significance and engineering practical value, which can provide a scientific basis for reservoir water temperature regulation, sediment regulation, ice disaster prevention and reduction, and ecological protection on cold-region sediment-rich rivers. Summary of the invention

[0007] The purpose of the present invention is to overcome the deficiencies in the prior art and to provide a method for inversion and prediction of dual density flows of reservoir sediment and temperature, to accurately and efficiently simulate the water temperature, ice conditions and sediment content of the reservoir, to invert, predict and evaluate the thermal spatiotemporal changes of the water temperature and ice conditions of high-sediment-content river reservoirs and the degree and scope of the influence of sediment on the water temperature and ice conditions.

[0008] The key link in the present invention is to accurately simulate the sediment density flow by calculating the sediment grouping velocity. When the sediment density flow is moving in the water, it is subject to the resistance of the upper layer of clean water. Therefore, the density flow will also drive a part of the upper layer of clean water forward during the movement. At the same time, when the density flow is mixed with the clean water, it will also occupy the position of the original clean water, thus forming a clean water circulation above the density flow. Figure 2 As shown in the figure, the direction of movement of the surface water near the point where the density current enters is opposite to that of the muddy water, which is also called reverse compensation flow. If the incoming flow has a high sediment content, it will sink to form a bottom density current, and the upper clear water near the reservoir tail will form a vortex. However, due to the suction effect of the water intake, the turbulence in the area in front of the dam is strong and the flow state is more complicated. Although the flow direction of the density current near the dam area is the same as that of the water flow at the upper outlet, there is a large difference in flow velocity, which makes the middle layer of the water body unbalanced, has a greater disturbance effect on the flow field of the reservoir area, and further changes the thermal state of the reservoir.

[0009] The present invention provides an inversion and prediction method for reservoir sediment and temperature dual density flow, which comprises the following steps:

[0010] Step 1: establishing a water temperature-sediment-ice coupling model; the water temperature-sediment-ice coupling model includes a hydrodynamic module, a sand module, a water temperature module and an ice module;

[0011] The hydrodynamic module includes a water flow continuity equation, a momentum equation, a turbulence equation, a water state equation regarding water density, and a free water surface equation obtained by vertically integrating the continuity equation;

[0012] The sand module includes suspended matter convection-diffusion equations considering sediment settling;

[0013] The water temperature module includes a heat transfer equation;

[0014] The ice module includes an initial ice sheet formation equation and an ice sheet thermal generation and dissipation equation;

[0015] Step 2 constructs a cross-sectional model of the reservoir along the flow and depth directions, divides it into a number of grid cells, and sets boundary conditions and initial conditions;

[0016] Step 3 solves the water temperature-sediment-ice coupling model to obtain the spatiotemporal distribution of sediment content, water temperature and ice conditions in the reservoir area; this step includes the following sub-steps:

[0017] Step 3.1 Based on the spatial distribution of hydraulic pressure, sediment content, and ice conditions at the previous moment, the hydraulic spatial distribution at the current moment is preliminarily obtained through the hydraulic module;

[0018] Step 3.2: Based on the spatial distribution of sediment content at the previous moment and the hydraulic spatial distribution at the current moment, the spatial distribution of sediment content at the current moment is obtained through the sediment content module;

[0019] Step 3.3: Based on the water temperature spatial distribution at the previous moment and the hydraulic spatial distribution at the current moment, the water temperature spatial distribution at the current moment is obtained through the water temperature module;

[0020] Step 3.4 traverses the surface grid cells of the reservoir to determine whether the water temperature of the surface grid cells at the current time has dropped below the freezing point. If so, the initial ice cover thickness is determined by the initial ice cover generation equation, and the surface water temperature is set to the freezing point and the surface grid cell attribute is changed from an ice-free state to an ice-covered state, and then proceeds to step 3.5, otherwise, directly proceeds to step 3.5;

[0021] Step 3.5 traverses the surface grid cells of the reservoir, calculates the ice thickness change value of the surface grid cells with existing ice thickness, and determines the growth and disappearance process of the ice cover; if the ice thickness change value is positive, the ice thickness is growing; if the ice thickness change value is negative, the ice thickness is melting. When the ice thickness at the current moment is less than the melting ice thickness change value, the current surface grid cell state changes from ice-covered state to ice-free state;

[0022] Increase the time step and repeat the above steps S3.1-3.5 until the upper limit of the set time period is reached, and the reservoir hydraulic spatiotemporal distribution, sediment content spatiotemporal distribution, water temperature spatiotemporal distribution and ice condition spatiotemporal distribution of the reservoir area are obtained.

[0023] The core idea of ​​this invention is to further carry out the calculation of ice conditions based on the calculation of the impact of high-concentration sediment-laden water flow on reservoir hydrodynamics and water temperature. This invention proposes a water temperature-sediment-ice coupling model, such as Figure 1 As shown in Figure 1, it includes a hydrodynamic module, a sand module, a water temperature module, and an ice module. The sediment module uses the group median particle size to determine the sediment settling velocity of the group, simulates the coupling effect of temperature differential density flow and sediment differential density flow, and then realizes the inversion and prediction of the spatiotemporal variation law of water-ice-sand in the reservoir.

[0024] The key link in the present invention is to accurately simulate the sediment density flow by calculating the sediment grouping velocity. When the sediment density flow is moving in the water, it is subject to the resistance of the upper layer of clean water. Therefore, the density flow will also drive a part of the upper layer of clean water forward during the movement. At the same time, when the density flow is mixed with the clean water, it will also occupy the position of the original clean water, thus forming a clean water circulation above the density flow. Figure 2 As shown in the figure, the direction of movement of the surface water near the point where the density current enters is opposite to that of the muddy water, which is also called reverse compensation flow. If the incoming flow has a high sediment content, it will sink to form a bottom density current, and the upper clear water near the reservoir tail will form a vortex. However, due to the suction effect of the water intake, the turbulence in the area in front of the dam is strong and the flow state is more complicated. Although the flow direction of the density current near the dam area is the same as that of the water flow at the upper outlet, there is a large difference in flow velocity, which makes the middle layer of the water body unbalanced, has a greater disturbance effect on the flow field of the reservoir area, and further changes the thermal state of the reservoir.

[0025] In step 1 above, for the hydrodynamic module, the water flow continuity equation is:

[0026]

[0027] Where: U is the longitudinal velocity, m / s; x is the flow direction; W is the vertical velocity, m / s; z is the vertical direction of the reservoir; q is the net inflow per unit width of the lateral grid unit, m 3 / s; B is the lateral width of the reservoir at different elevations along the flow direction, m.

[0028] The momentum equation includes the longitudinal momentum equation and the vertical momentum equation;

[0029] The longitudinal momentum equation is:

[0030]

[0031] Vertical momentum equation:

[0032]

[0033] Where: α is the riverbed slope, rad; τ xx is the turbulent normal stress, N / m 2 ; τ xz is the turbulent shear stress, N / m 2 ; η is the water surface elevation, m; U x is the x-direction component of the tributary velocity in the water flow direction, m / s; g is the gravitational acceleration, m / s 2 ; ρ is water density, kg / m 3 ; p is hydrostatic pressure, N / m 2 .

[0034] Turbulence equation:

[0035]

[0036] Where: k is the turbulent kinetic energy, m 2 / s 2 ; ε is the turbulent kinetic energy dissipation rate; ν t is the turbulent eddy viscosity coefficient, ν t =C μ k 2 / ε,m 2 / s; ρ is water density, kg / m 3 ; P is the turbulent kinetic energy generation term, m 2 / s 3 ; G is the buoyancy term, m 2 / s 3 ;P k , P ε is the turbulent kinetic energy and dissipation rate generated by boundary friction; σ k , σ ε are the turbulent kinetic energy and the dissipation rate Prandtl number, which are 1.0 and 1.3 respectively; δ t is the turbulent Prandtl number, which is 1.0; C μ , C ε1 and C ε2 are empirical constants, which are 0.09, 1.44 and 1.92 respectively.

[0037] The present invention takes into account the change of density in the gravity term in the control equation, and takes into account the state equation of water temperature, total dissolved solids and suspended solids, that is, the water body state equation, which is in the following form:

[0038]

[0039] Where: T w is the water temperature; ρ T is the density of water under the influence of temperature; △ρ ss,iis the water density increment caused by the i-th level of suspended sediment; C i is the sediment content per unit volume of water; s,i is the dry bulk density of suspended sediment at the i-th level; n represents the number of sediment level groups.

[0040] In order to simulate the change of water level, the free water surface equation is also needed. By integrating the continuity equation from the bottom of the water to the surface of the water, the free water surface equation is obtained:

[0041]

[0042] Where: B η is the lateral width of the reservoir surface along the flow direction, m; η is the water surface elevation, m; h is the riverbed elevation, m.

[0043] For the sand module, the present invention uses the suspended sediment convection diffusion equation to represent the sediment transport process in the reservoir, while considering the influence of sediment sedimentation. The suspended sediment is divided into i levels, and the suspended sediment convection diffusion equation for each level is:

[0044]

[0045] Where: C i is the sediment content per unit volume of water; ω s,i D is the sediment settling velocity; x , D z are the longitudinal turbulent diffusion coefficient and the vertical turbulent diffusion coefficient respectively;

[0046] The formula for the sediment settling velocity of a single particle uses the commonly used Stokes formula as follows:

[0047]

[0048] Where: d i is the median particle size of the suspended sediment particles at level i, m; υ is the kinematic viscosity of water, m 2 / s; γ T is the bulk density of water without sand, γ T =ρ T g,N / m 3 ; γ s,i is the dry bulk density of suspended sediment at the i-th level, γ s,i =ρ s,i g,N / m 3 , ρ s,i is the density of suspended sediment at the i-th level, kg / m 3 .

[0049] Generally speaking, the density current can only carry fine sediment with a particle size of d < 25 μm. After entering the reservoir, the medium and coarse sediment with larger particle size settles faster under the influence of gravity, mainly silting at the end of the reservoir. The fine sand has better followability. The finer part of the suspended sediment can even reach the front of the dam and be transported downstream under the action of the density current. Taking the sediment particles with a particle size of 25 μm as an example, in the static water body at 20℃, according to the Stokes formula, the settling speed will reach 38.2m / day (4.4×10 -4 m / s), so the present invention ignores the influence of medium sand and coarse sand on the flow temperature field near the dam area, and mainly considers the fine sand (d<25μm). The fine sand is further subdivided into three levels of 0-5μm, 5-10μm, and 10-25μm, and the settling velocity corresponding to the median particle size is calculated using formula (2-2).

[0050] For the water temperature module, the heat transfer equation is:

[0051]

[0052] Where: T w is water temperature, ℃; D x is the longitudinal diffusion coefficient, m 2 / s;D z is the vertical diffusion coefficient, m 2 / s; Q is the rate of lateral heat flux in and out of the grid unit, Q = qT q , T q is the water temperature of the lateral flow, °C; S is the source-sink term, including surface heat exchange, riverbed heat exchange, ice-water heat exchange or / and the absorption of solar radiation at depth z, J / m 3 / s.

[0053] Water surface heat exchange mainly consists of three parts: radiation, evaporation and heat conduction, which can be expressed by the following formula:

[0054] φ n =H s +H a -H b -H e -H c (3-2)

[0055] In the formula, φ n Net heat flux through the water surface, W / m 2 ;H s is the solar shortwave radiation absorbed within 1m of the surface water, W / m 2 ;H a is the long-wave radiation returned by the atmosphere, W / m 2 ;H b is the long-wave radiation from the water surface, W / m 2 ;H eis the evaporation heat flux, W / m 2 ;H c is the heat conduction flux, W / m 2 .

[0056] (1) Solar shortwave radiation H s

[0057] H s =H s0 (1-γ)β(1-0.65C 2 ) (3-3)

[0058] In the formula, H s0 is the shortwave solar radiation reaching the water surface on a sunny day, W / m 2 ; γ is the reflectivity of the water surface; β is the degree of solar radiation absorption within 1m of the water surface; C is the cloud coverage rate.

[0059] Solar radiation entering a body of water is attenuated according to Beer's law:

[0060] H s (z) = (1-β)(1-γ)H s0 e -ζz (3-4)

[0061] In the formula, H s (z) is the solar radiation at water depth z, W / m 2 ;ζ is the solar radiation attenuation coefficient, 1 / m.

[0062] (2) Atmospheric longwave radiation H a

[0063] The solar energy absorbed by the atmosphere is emitted to the ground in the form of long waves. The intensity of its long-wave radiation depends on the temperature and cloud cover and can be calculated using the Stefan-Boltzman law:

[0064] H a =(1-γ a )σε a (273.15+T a ) 4 (3-5)

[0065] Where, T a (℃) is the temperature at 2m above the water surface, ℃; γ a is the long-wave reflectivity; σ is the Stefan-Boltzman constant, which is 5.67×10 -8 W / (m 2 ·K 4 ); a Atmospheric emissivity, atmospheric emissivity ε on a clear day ac It can be calculated using the Idso and Jackson formulas.

[0066] ε ac =1-0.261·exp(-7.77×10 -4 T a 2 ) (3-6)

[0067] In cloudy weather, the Bolz formula can be used to correct it:

[0068] ε a =ε ac ·(1+K c ·C 2 ) (3-7)

[0069] The parameter K c Related to cloud height, the Tennessee Engineering Administration recommends an average value of 0.17.

[0070] (3) Water body long wave return radiation H b

[0071] The long-wave return radiation of water is an important part of the heat loss of water, which can be calculated using the Stefan-Boltzman law:

[0072] H b =σε w (273.15+T ws ) 4 (3-8)

[0073] In the formula, ε w is the long-wave emissivity of water; T ws is the surface water temperature of the reservoir, ℃.

[0074] (4) Evaporation heat loss H e

[0075] The evaporation process of water requires the absorption of heat, and the evaporation heat loss expression is:

[0076] H e =f(W)(e s -e a ) (3-9)

[0077] Where f(W) is the wind function:

[0078] f(W)=9.2+0.46W 2 (3-10)

[0079] Where W is the wind speed at 2m above the ground, m / s; e s is the saturated evaporation pressure of the water surface, mmHg; e a is the atmospheric vapor pressure, mmHg.

[0080] (5) Heat conduction flux H c

[0081] H c =C c f(W)(T ws -T a ) (3-11)

[0082] In the formula, C c is the Bowen constant, which is taken as 0.47 mmHg / ℃.

[0083] Compared with the heat exchange on the water surface, the heat exchange on the riverbed is smaller in magnitude, and many models do not consider the heat exchange on the riverbed. Studies have shown that the heat exchange on the riverbed must be considered to accurately simulate the water temperature of the stagnant layer at the bottom of the reservoir. The formula for heat exchange on the riverbed is:

[0084] H bw =K bw (T b -T wb ) (3-12)

[0085] Where: H bw is the heat exchange flux between the riverbed and the bottom water, W / m 2 ; K bw is the heat exchange coefficient, W / (m 2 ·℃), generally 0.3; T wb is the water temperature at the bottom of the reservoir, ℃; T b is the riverbed temperature, ℃, which is generally estimated using the average temperature over many years.

[0086] When covered by ice, the heat flux form of the reservoir surface is transformed from water-air heat exchange to ice-water heat exchange. The ice-water heat exchange calculation can be expressed by the following formula:

[0087] H wi =h wi (T ws -T m ) (3-13)

[0088] Where: H wi is the heat exchange flux between the reservoir surface and the bottom of the ice sheet, W / m 2 ;h wi is the ice-water heat exchange coefficient, Wm -2 ℃ -1 ; T m is the ice-water interface temperature, 0°C.

[0089] For the ice module, the formation and disappearance of ice cover is related to the reservoir surface weather, water temperature under the ice, ice thickness, etc. It is a complex heat exchange process. At the same time, the ice cover is also related to the hydrodynamic factors of the reservoir (hydrodynamic factors will affect the ice-water heat exchange coefficient). The heat exchange during the freezing and melting process mainly includes ice-air heat exchange, ice-water heat exchange and heat conduction inside the ice body.

[0090] Before the initial ice sheet is formed, the water surface temperature drops to freezing point. As the water surface continues to lose heat, the initial ice sheet begins to form. The thickness of the initial ice sheet is calculated by the following formula:

[0091]

[0092] Where: θ0 is the initial ice thickness, m; C p is the constant pressure specific heat capacity of water (constant), J / (kg·℃); θ s is the vertical grid thickness of the surface layer, m; ρ is the water density, kg / m 3 ρ i is the density of ice, kg / m 3 ; L f is the latent heat of freezing (constant), J / kg.

[0093] The ice sheet heat generation and dissipation equation for ice thickness θ is given by:

[0094]

[0095] Where: θ represents ice thickness, m; T a is the air temperature, °C; k i is the thermal conductivity of ice, W / (m·℃); h ai is the ice-air heat exchange coefficient, W / (m 2 ·℃).

[0096] In the above step 2, the cold region reservoir water area is taken as the research object, and it is divided into a number of triangular units or rectangular units (i.e., grid units) along the specified rectangular coordinate system, and the hydraulics, sediment content, water temperature, and ice conditions of the nodes of each grid unit are used to characterize the hydraulics, sediment content, water temperature, and ice conditions of the location. The hydraulic spatiotemporal distribution includes the change process of flow velocity and water surface elevation over time; the spatiotemporal distribution of sediment content is the change process of sediment content in the reservoir area over time; the spatiotemporal distribution of water temperature is the change process of water temperature in the reservoir area over time; and the spatiotemporal distribution of ice conditions is the change process of surface ice thickness in the reservoir area over time.

[0097] In the above step 3, the present invention discretizes each model using the finite volume method for all the models constructed in the above step 1, obtains a discrete equation group of each model on the grid unit, and then solves the discrete equation group.

[0098] Combined with the above analysis, it can be seen that the present invention takes into account the influence of sediment particle size grouping on water density. Through the suspended matter convection diffusion equation, different levels of sediment are calculated and the corresponding sediment content distribution is obtained, and the water density is further updated.

[0099] The hydraulic, sediment content, water temperature and ice condition parameters obtained at the previous moment are assigned to each variable as the initial value of the hydraulic, sediment content, water temperature and ice condition parameter variables at the current moment. The hydraulic, sediment content, water temperature and ice condition of the reservoir area at each moment are solved through time iteration, thereby obtaining the hydraulic and spatial distributions of the reservoir area, sediment content, water temperature and ice condition.

[0100] The convergence conditions of the hydrodynamic field, temperature field, and sediment field are:

[0101] (1) Under the condition of accurately given initial fields, the various field data calculated are the intended time series results;

[0102] (2) When the initial field cannot be accurately given, the initial conditions can be determined by random initialization, and then multiple time period cycles are used. When the result of the mth period is within the allowable difference range with the result of the m-1th period, the result of the mth period is considered to be the intended time series result.

[0103] The reservoir boundary conditions include inflow flow, inflow water temperature, inflow sand volume and gradation, meteorological conditions, and outflow flow. The initial conditions are given flow field, temperature field, and sediment field. The initial ice thickness is 0, that is, there is no ice cover on the surface of the reservoir. The water temperature at the inlet boundary uses the measured or given water temperature at the end of the reservoir, and the velocity is assumed to be a uniform flow velocity. At the dam body and outlet section, the outlet section is assumed to be fully developed turbulence, and the dam body surface adopts a no-slip boundary condition, and it is an adiabatic boundary. A no-slip boundary condition is adopted at the bottom of the reservoir.

[0104] Stability is an important aspect to be considered when solving numerical simulations, and can be verified by the time step. In numerical calculations, the time step of the grid unit must satisfy the following formula conditions:

[0105]

[0106] Where △t is the time step, s; △x and △z are the lengths of the grid unit along the x and z directions respectively; A x is the longitudinal eddy viscosity, m 2 / s; A z is the vertical eddy viscosity, m 2 / s;Q e is the total flow into or out of the grid cell, m 3 / s; V is the grid unit volume, m 3; H is the depth of the water column where the unit grid is located, m; ρ is the water density; △ρ is the maximum density difference of the water column where the unit grid is located, kg / m 3 .

[0107] The reservoir sediment and temperature dual density flow inversion and prediction method provided by the present invention has the following beneficial effects:

[0108] (1) The present invention establishes a water temperature-sediment-ice coupling model from the perspective of thermodynamics and kinetics, which can simulate the coupling effect of temperature density flow and sediment density flow, and can scientifically and reasonably reflect the spatiotemporal evolution of the water temperature structure of the reservoir area of ​​the high-sediment-content river reservoir in the cold region and quantify the influence period and influence degree of low-temperature water and high-temperature water discharged after the reservoir is operated;

[0109] (2) The present invention adopts the method of determining the sediment settling velocity of the group by the median particle size of the group, which better reflects the effect of fine-grained sediment on the water temperature structure of the reservoir area and the downstream water temperature process; the relatively fine sediment has a small settling velocity and good flow-following property, and produces a greater disturbance to the flow field and temperature field in the reservoir and in front of the dam by diving, forming a large circulation inside the reservoir, and producing a "crowding out" effect on the water body retained at the bottom of the reservoir, and the water temperature in the reservoir area shows an inverted temperature distribution structure of "the bottom is higher than the middle and upper layers in spring and summer"; in winter, when there is sediment inflow in cold region reservoirs, the cold water entering the reservoir will dive due to the presence of sediment, rather than the surface buoyancy flow process of cold water, further affecting the spatiotemporal process of ice conditions in the reservoir; in rivers with high sediment content and wide particle size distribution range, using the median particle size of the group to calculate the sediment settling velocity can more truly reflect the spatiotemporal process of reservoir heat transfer under the coupling of water and sediment;

[0110] (3) The present invention can accurately obtain the sediment movement process in different types of sand-containing river reservoirs in cold regions and the thermal evolution process and laws of reservoir water temperature and ice conditions by taking into account the coupling effect of hydrodynamics, water temperature, ice and sand. BRIEF DESCRIPTION OF THE DRAWINGS

[0111] Figure 1 This is a block diagram of the water temperature-sediment-ice coupling model of the present invention;

[0112] Figure 2 It is a schematic diagram of the simulation process of sediment density flow involved in the present invention;

[0113] Figure 3 This is a schematic diagram of the reservoir model grid division;

[0114] Figure 4 In the calculation process of the test of the impact of sediment inflow into the reservoir, the sediment treatment adopts the comparison of the change of water temperature over time of single group and three groups and the situation without sediment;

[0115] Figure 5In the calculation process of the test of the impact of sediment inflow into the reservoir, the sediment treatment adopts the change process of sediment content over time in a single group and three groups;

[0116] Figure 6 The annual change process of reservoir water temperature in three groups is compared with the situation without sediment (representative months in each season) in order to simulate the reservoir sediment grouping throughout the year;

[0117] Figure 7 The comparison of the annual change process of water temperature in front of the dam with the sediment in the reservoir during the whole year and the sediment-free period (15th of each month) was adopted in three groups to simulate the reservoir sediment inflow throughout the year;

[0118] Figure 8 The simulated reservoir sediment inflow was divided into three groups for the discharge water temperature process, the discharge water temperature process without sediment and the natural water temperature process at the dam site (without reservoir) were compared.

[0119] Fig. 9 To simulate the reservoir sediment entering the reservoir throughout the year, three groups of water temperature changes during the winter ice period were used to compare with the situation when there was no sediment. DETAILED DESCRIPTION

[0120] The present invention is described in detail below through embodiments and application examples. It is necessary to point out that the present embodiments are only used to further illustrate the present invention and cannot be understood as limiting the scope of protection of the present invention. Technical personnel skilled in the art can make some non-essential improvements and adjustments based on the above-mentioned contents of the present invention.

[0121] Example 1

[0122] This embodiment uses the inversion and prediction method of reservoir sediment and temperature dual density flow provided by the present invention to predict the water temperature distribution and ice cover distribution after the construction of a reservoir on the Yellow River.

[0123] The inversion and prediction method of reservoir sediment and temperature dual density flow provided in this embodiment includes the following steps:

[0124] Step 1: Establish a water temperature-sediment-ice coupling model, such as Figure 1 The water temperature-sediment-ice coupling model includes a hydrodynamic module, a sand module, a water temperature module and an ice module.

[0125] The hydrodynamic module includes the water flow continuity equation (Formula (1-1)), the momentum equation (Formula (1-2)-(1-3)), the turbulence equation (Formula (1-4)-(1-5)), the water state equation about water density (Formula (1-6)-(1-8)), and the free water surface equation obtained by vertical integration of the continuity equation (Formula (1-9));

[0126] The sand module includes suspended matter convection-diffusion equations after sediment settling (Formulas (2-1)-(2-2));

[0127] The water temperature module includes the heat transfer equation (Formula (3-1));

[0128] The ice module includes the initial ice sheet formation equation (Formula (4-1)) and the ice sheet thermal generation and disappearance equation (Formula (4-2)).

[0129] Step 2 constructs a cross-sectional model of the reservoir along the flow and depth directions, divides it into several grid cells, and sets boundary conditions and initial conditions.

[0130] In this embodiment, unequally spaced rectangular grids are used to perform grid division based on the reservoir's large cross-section, cross-section spacing, horizontal grid spacing distribution, and vertical grid spacing distribution. The rectangular grid size is set according to the reservoir's characteristics. In this embodiment, the reservoir is discretized into 382×62 rectangular grids, with a longitudinal (along the mainstream direction) grid size of 20 to 800 m and a vertical (along the water depth direction) grid size of 2 m. The grids after division are as follows: Figure 3 The water temperature and surface ice cover conditions of each grid unit are used to represent the water temperature and ice cover conditions at its location.

[0131] The reservoir boundary conditions include inflow flow, inflow water temperature, inflow sediment volume and gradation, meteorological conditions, and outflow flow. The initial conditions are the given flow field, temperature field, and sediment field. The initial ice thickness is 0, that is, there is no ice cover on the surface of the reservoir. The water temperature at the inlet boundary uses the measured or given water temperature at the end of the reservoir, and the velocity is assumed to be a uniform flow velocity. At the dam body and outlet section, the outlet section is assumed to be fully developed turbulence, and the no-slip boundary condition is adopted on the dam body surface, and it is an adiabatic boundary. The no-slip boundary condition is adopted at the bottom of the reservoir.

[0132] Step 3 solves the water temperature-sediment-ice coupling model to obtain the spatiotemporal distribution of sediment content, water temperature, and ice conditions in the reservoir area.

[0133] The spatiotemporal distribution of hydraulic power includes the changes of flow velocity and water surface elevation over time; the spatiotemporal distribution of sediment content is the changes of sediment content in the reservoir area over time; the spatiotemporal distribution of water temperature is the changes of water temperature in the reservoir area over time; the spatiotemporal distribution of ice conditions is the changes of surface ice thickness in the reservoir area over time.

[0134] In this step, for all the models constructed in the above step 1, the finite volume method is used to discretize each model to obtain a discrete equation group of each model on the grid unit, and then the discrete equation group is solved.

[0135] In this step, the hydraulic, sediment content, water temperature, and ice condition parameters obtained at the previous moment are assigned to each variable as the initial value of the hydraulic, sediment content, water temperature, and ice condition parameter variables at the current moment (for the initial moment, the hydraulic, sediment content, water temperature, and ice condition at the current moment correspond to the initial conditions), and the hydraulic, sediment content, water temperature, and ice condition of the reservoir area at each moment are solved through time iteration to obtain the hydraulic and spatial-temporal distributions of the reservoir area, sediment content, water temperature, and ice condition, so as to obtain the spatial-temporal distributions of the hydraulic, sediment content, water temperature, and ice condition.

[0136] This step includes the following sub-steps:

[0137] Step 3.1: Based on the spatial distribution of hydraulic pressure, sediment content, and ice conditions at the previous moment, the hydraulic spatial distribution at the current moment is preliminarily obtained through the hydraulic module.

[0138] In this step, the initial values ​​of the hydraulic, sediment content, water temperature and ice condition parameter variables at the current moment are set according to the spatial distribution of hydraulic, sediment content and ice conditions at the previous moment. Combined with the boundary conditions, the water flow continuity equation, momentum equation, turbulence equation, water body state equation and free water surface equation of the hydrodynamic module are discretely solved to obtain the flow velocity (U and W) and water surface elevation (η) at the current moment, that is, the hydraulic spatial distribution at the current moment.

[0139] Step 3.2 obtains the spatial distribution of sediment content at the current moment through the sediment content module based on the spatial distribution of sediment content at the previous moment and the hydraulic spatial distribution at the current moment.

[0140] In this step, the initial value of the sediment content at the current moment is set according to the spatial distribution of the sediment content at the previous moment. Combined with the boundary conditions and the hydraulic spatial distribution at the current moment, the suspended sediment convection diffusion equations at each level of the sand module are discretely solved to obtain the spatial distribution of sediment at different levels at the current moment (C i ), and then the spatial distribution of sediment content at the current moment is obtained.

[0141] Step 3.3 obtains the spatial distribution of water temperature at the current moment through the water temperature module based on the spatial distribution of water temperature at the previous moment and the hydraulic spatial distribution at the current moment.

[0142] In this step, the initial value of the water temperature at the current moment is set according to the spatial distribution of the water temperature at the previous moment. The heat transfer equation of the water temperature module is discretely solved in combination with the boundary conditions and the hydraulic spatial distribution at the current moment to obtain the spatial distribution of the water temperature at the current moment (T w ).

[0143] Step 3.4 traverses the surface grid cells of the reservoir to determine whether the water temperature of the surface grid cells at the current moment has dropped below the freezing point. If so, the initial ice cover thickness is determined by the initial ice cover generation equation, and the surface water temperature is set to the freezing point and the properties of the surface grid cells are changed from an ice-free state to an ice-covered state, and then proceeds to step 3.5, otherwise directly proceeds to step 3.5.

[0144] In this step, each grid cell on the surface of the reservoir is traversed to determine whether the water temperature of the surface grid cell at the current moment has dropped below the freezing point. If so, the initial ice cover thickness is calculated according to the initial ice cover generation equation given above, and the surface water temperature is set to the freezing point and the properties of the surface grid cell are changed from an ice-free state to an ice-covered state, and then go to step 3.5, otherwise go directly to step 3.5.

[0145] Step 3.5 traverses the surface grid cells of the reservoir, calculates the ice thickness change value of the surface grid cells with existing ice thickness, and determines the growth and disappearance process of the ice cover; if the ice thickness change value is positive, the ice thickness is growing; if the ice thickness change value is negative, the ice thickness is melting. When the ice thickness at the current moment is less than the melting ice thickness change value, the current surface grid cell state changes from an ice-covered state to an ice-free state.

[0146] In this step, the initial value of ice thickness at the current moment is set according to the spatial distribution of ice conditions at the previous moment, and the ice module's ice cover thermal generation and disappearance equation is discretely solved in combination with boundary conditions and the spatial distribution of water temperature at the current time to obtain the surface ice thickness (θ) of the surface grid cells with existing ice thickness at the current moment. Then, the surface ice thickness of each surface grid cell at the current moment is subtracted from the surface ice thickness of the corresponding grid cell at the previous moment to obtain the ice thickness change value; the generation and disappearance process of the ice cover is judged based on the ice thickness change value: if the ice thickness change value is positive, the ice thickness is growing; if the ice thickness change value is negative, the ice thickness is melting. When the ice thickness at the current moment is less than the melting ice thickness change value, the current surface grid cell state changes from ice-covered state to ice-free state.

[0147] Increase the time step and repeat the above steps S3.1-3.5 until the upper limit of the set time period is reached, and the reservoir hydraulic spatiotemporal distribution, sediment content spatiotemporal distribution, water temperature spatiotemporal distribution and ice condition spatiotemporal distribution of the reservoir area are obtained.

[0148] The convergence conditions of the hydrodynamic field, temperature field, and sediment field are:

[0149] (1) Under the condition of accurately given initial fields, the various field data calculated are the intended time series results;

[0150] (2) When the initial field cannot be accurately given, the initial conditions can be determined by random initialization, and then multiple time period cycles are used. When the result of the mth period is within the allowable difference range with the result of the m-1th period, the result of the mth period is considered to be the intended time series result.

[0151] The setting of the time step meets the requirements of formula (5) given above.

[0152] The water temperature distribution of the Yellow River reservoir mentioned above and the inversion and situation of ice cover distribution are explained in detail below.

[0153] Since the sediment settling velocity characteristics will significantly affect the sediment distribution in the reservoir area and thus affect the water temperature structure, it is particularly important to reasonably deal with the sediment settling velocity of the group. Figure 4 The paper presents the comparison of the water temperature change with time in the process of the test calculation of the impact of sediment inflow into the reservoir, when the sediment treatment adopts a single group (0-25μm sediment median particle size) and three groups (0-5μm, 5-10μm, 10-25μm three levels of sediment median particle size, the mass ratio of the three levels of sediment is 3:1:3) and the case without sediment. Figure 5 A two-dimensional distribution diagram of reservoir sediment content is given using the sediment grouping (3 groups) median particle size calculation method and the single group median particle size calculation method. The calculation is started from July, the flood season with relatively large sediment content (there is no sediment influence before July), under the same given initial and boundary conditions, and the simulation results on the 6th, 12th, 18th and 24th days are given. The settling velocity of the median particle size of a single group of non-uniform sand is calculated to be 3m / day. The numerical results show that the vertical diffusion of sediment is inhibited. The large density difference between clear and turbid water causes the clear water layer to form a continuous vortex during the infiltration of the density flow. The vortex drives the turbid water with high local temperature and high sediment content to flow in the non-mainstream direction. The sediment is divided into three groups according to its particle size from small to large, and the corresponding settling velocity of each group of sediment is obtained. Among them, the sediment group with a smaller particle size has a small settling velocity (0.38m / day), good flow-following property, and is easy to diffuse vertically, which inhibits the generation of vortices. The temperature field and sediment field are relatively uniform. At the same time, fine-grained sediment is easier to reach the front of the dam, and the vertical water temperature and sediment content in front of the dam increase faster. The sediment entering the reservoir has different particle sizes. Under the action of water flow, the median particle size of the sediment shows a characteristic of decreasing from the tail of the reservoir to the front of the dam. At the same time, the density flow is blocked by the dam, which will form a muddy reservoir. Generally, the boundary between the clear and muddy interface is clear and almost parallel to the water surface. The calculation results after particle size grouping basically meet the above characteristics. Fine sand is the main factor affecting the water temperature and flow field structure in front of the dam. Therefore, the median particle size of the sediment particle size grouping is used to calculate the settling velocity in the present invention.

[0154] Figure 6The comparison between the two-dimensional distribution of water temperature in the reservoir area predicted by the present invention and the one without sediment is given. Figure 7 To correspond to the vertical water temperature distribution in front of the dam (the 15th of each month). Overall, the present invention better simulates the coupling effect of reservoir sediment density flow and temperature density flow. The water temperature structure of the reservoir is mainly controlled by the sediment content of the incoming water body. Except for May and June, the inflow water body in each month is mainly diving. The high-sediment hot water in the flood season basically replaces the cold water in the reservoir area. The suspended sediment increases the density of the water body at the bottom of the reservoir, causing the vertical mixing in front of the dam to weaken in winter, and the hot water stagnates in front of the dam. During the warming period, the high-temperature inflow water dives, supporting the low-temperature water at the bottom of the reservoir to exit the reservoir, and forming an inverted temperature distribution. The overall vertical stratification is weak, and the vertical temperature difference is 1.2 to 13.7°C. When there is no sediment, the water temperature in the reservoir area undergoes a major reversal in March and November to form an isothermal distribution. When there is sediment, in addition to the isothermal distribution in March, the high-temperature water entering the reservoir in August during the flood season gradually sinks to replace the low-temperature water in the reservoir to form an isothermal distribution. In November, due to the influence of the sinking of the high-temperature water during the flood season, a certain vertical temperature difference is always maintained in front of the dam.

[0155] Figure 8 The predicted reservoir discharge water temperature process and the natural water temperature process at the dam site are compared. The present invention simulates the flattening effect and delay effect of the discharge water temperature under the influence of double density flow. Compared with the natural water temperature process at the dam site, there is a phenomenon of low-temperature water discharge from March to July, and a phenomenon of high-temperature water discharge from September to February of the following year. Under the influence of sediment, the maximum low-temperature water amplitude is 10.2℃. The low-temperature water discharge from May to August is more obvious, among which the low-temperature water amplitude increases in July. The main reason is that the sediment content of the water entering the reservoir during this period increases, and the density flow dives, which accelerates the discharge of low-temperature water stored at the bottom of the reservoir, thereby causing a substantial drop in the discharge water temperature. Due to the high sediment content inflow, the water temperature structure of the reservoir is changed, especially in summer, the water body of the stagnant temperature layer at the bottom of the reservoir is basically replaced by high-temperature water. After entering the cooling period, the inflow flow and sediment content are reduced, the high-temperature water discharge is slow, and the water temperature at the bottom of the reservoir is high in winter, which leads to a large amplitude of high-temperature water in winter, with a maximum amplitude of 11.1℃.

[0156] Fig. 9 The comparison between the water temperature process during the ice period predicted by the present invention and the one without sediment is given. Due to the inflow of sandy water, the ice condition of the reservoir in winter is weakened. Sediment changes the buoyancy pattern of the water body, and low-temperature water sinks with the sediment density flow. The vertical flow contributes less to the cooling of the surface water body. Therefore, compared with the one without sediment, the surface water temperature of the reservoir cools down more slowly, the ice cover advances slower, and the ice range is smaller.

Claims

1. A method for inversion and prediction of reservoir sediment and temperature dual density flow, characterized in that: The following steps are involved: Step 1: establishing a water temperature-sediment-ice coupling model; the water temperature-sediment-ice coupling model includes a hydrodynamic module, a sand module, a water temperature module and an ice module; The hydrodynamic module includes a water flow continuity equation, a momentum equation, a turbulence equation, a water state equation regarding water density, and a free water surface equation obtained by vertically integrating the continuity equation; The sand module includes suspended matter convection-diffusion equations considering sediment settling; The water temperature module includes a heat transfer equation; The ice module includes an initial ice sheet formation equation and an ice sheet thermal generation and dissipation equation; Step 2 constructs a cross-sectional model of the reservoir along the flow and depth directions, divides it into a number of grid cells, and sets boundary conditions and initial conditions; Step 3 solves the water temperature-sediment-ice coupling model to obtain the spatiotemporal distribution of sediment content, water temperature and ice conditions in the reservoir area; this step includes the following sub-steps: Step 3.1 Based on the spatial distribution of hydraulic pressure, sediment content, and ice conditions at the previous moment, the hydraulic spatial distribution at the current moment is preliminarily obtained through the hydraulic module; Step 3.2: Based on the spatial distribution of sediment content at the previous moment and the hydraulic spatial distribution at the current moment, the spatial distribution of sediment content at the current moment is obtained through the sediment content module; Step 3.3: Based on the water temperature spatial distribution at the previous moment and the hydraulic spatial distribution at the current moment, the water temperature spatial distribution at the current moment is obtained through the water temperature module; Step 3.4 traverses the surface grid cells of the reservoir to determine whether the water temperature of the surface grid cells at the current time has dropped below the freezing point. If so, the initial ice cover thickness is determined by the initial ice cover generation equation, and the surface water temperature is set to the freezing point and the surface grid cell attribute is changed from an ice-free state to an ice-covered state, and then proceeds to step 3.5, otherwise, directly proceeds to step 3.5; Step 3.5 traverses the surface grid cells of the reservoir, calculates the ice thickness change value of the surface grid cells with existing ice thickness, and determines the growth and disappearance process of the ice cover; if the ice thickness change value is positive, the ice thickness is growing; If the ice thickness change value is negative, the ice thickness undergoes a melting process. When the ice thickness at the current moment is less than the melting ice thickness change value, the current surface grid unit state changes from an ice-covered state to an ice-free state. Increase the time step and repeat the above steps S3.1-3.5 until the upper limit of the set time period is reached, and the reservoir hydraulic spatiotemporal distribution, sediment content spatiotemporal distribution, water temperature spatiotemporal distribution and ice condition spatiotemporal distribution of the reservoir area are obtained.

2. The inversion and prediction method of reservoir sediment and temperature dual density flow according to claim 1 is characterized in that: In step 1, the water flow continuity equation is: Where: U is the longitudinal flow velocity; x is the flow direction; W is the vertical flow velocity; z is the vertical direction of the reservoir; q is the net inflow flow per unit width of the lateral grid unit; and B is the lateral width of the reservoir at different elevations along the flow direction. The momentum equation includes the longitudinal momentum equation and the vertical momentum equation; The longitudinal momentum equation is: Vertical momentum equation: Where: α is the riverbed slope; τ xx is the turbulent normal stress, τ xz is the turbulent shear stress; η is the water surface elevation; U x is the x-direction component of the tributary velocity in the water flow direction; g is the gravitational acceleration; ρ is the water density; p is the hydrostatic pressure; Turbulence equation: Where: k is the turbulent kinetic energy; ε is the turbulent kinetic energy dissipation rate; ν t is the turbulent eddy viscosity coefficient, ν t =C μ k 2 / ε; ρ is the water density; P is the turbulent kinetic energy generation term, G is the buoyancy term, P k , P ε is the turbulent kinetic energy and dissipation rate generated by boundary friction; σ k , σ ε are the turbulent kinetic energy and the dissipation rate Prandtl number respectively; δ t is the turbulent Prandtl number; C μ , C ε1 and C ε2 is an empirical constant; The specific form of the water state equation is as follows: Where: T w is the water temperature; ρ T is the density of water under the influence of temperature; △ρ ss,i is the water density increment caused by the i-th level of suspended sediment; C i is the sediment content per unit volume of water; s,i is the bulk density of the ith level of sediment particles; n represents the number of sediment level groups; The free water surface equation is: Where: B η is the lateral width of the reservoir surface along the flow direction; η is the water surface elevation; h is the riverbed elevation.

3. The inversion and prediction method of reservoir sediment and temperature dual density flow according to claim 1 or 2 is characterized in that: The suspended sediment is divided into i levels, and the suspended sediment convection diffusion equation of each level is: Where: C i is the sediment content per unit volume of water; ω s,i is the sediment settling velocity; x , D z are the longitudinal turbulent diffusion coefficient and the vertical turbulent diffusion coefficient respectively; The formula for the sediment settling velocity of a single particle uses the commonly used Stokes formula as follows: Where: s,i is the settling velocity of a single particle of sediment; d i is the median particle size of suspended sediment particles at level i; υ is the kinematic viscosity of water; γ T is the bulk density of water without sand, γ T =ρ T g; γ s,i is the dry bulk density of suspended sediment at the i-th level, γ s,i =ρ s, i g,ρ s,i is the density of suspended sediment at the i-th level.

4. The inversion and prediction method of reservoir sediment and temperature dual density flow according to claim 3 is characterized in that: The heat transfer equation is: Where: T w is the water temperature; Q is the rate of lateral heat flux in and out of the grid unit, Q = qT q , T q is the water temperature of the lateral flow; S is the source-sink term, including surface heat exchange, riverbed heat exchange, ice-water heat exchange and / or the absorption of solar radiation at the water depth z.

5. The inversion and prediction method of reservoir sediment and temperature dual density flow according to claim 4 is characterized in that: The initial ice sheet thickness is calculated by the following formula: Where: θ0 is the initial ice thickness; T ws is the surface water temperature of the reservoir; C p is the specific heat capacity of water at constant pressure; θ s is the vertical grid thickness of the surface layer; ρ is the water density; ρ i is the density of ice; L f is the latent heat of freezing; The ice sheet heat generation and dissipation equation for ice thickness θ is given by: Where: θ is the ice thickness; T m is the ice-water interface temperature; T a is the air temperature; k i is the thermal conductivity of ice; h ai is the ice-gas heat exchange coefficient; H wi is the heat exchange flux between the reservoir surface and the bottom of the ice sheet.

6. The inversion and prediction method of reservoir sediment and temperature dual density flow according to claim 1 is characterized in that: In step 2, the reservoir boundary conditions include inflow flow, inflow water temperature, inflow sediment volume and gradation, meteorological conditions, and outflow flow. The initial conditions are given flow field, temperature field, and sediment field. The initial ice thickness is 0, that is, there is no ice cover on the surface of the reservoir.

7. The inversion and prediction method of reservoir sediment and temperature dual density flow according to claim 1 is characterized in that: The spatiotemporal distribution of hydraulic power includes the changes of flow velocity and water surface elevation over time; the spatiotemporal distribution of sediment content is the changes of sediment content in the reservoir area over time; the spatiotemporal distribution of water temperature is the changes of water temperature in the reservoir area over time; the spatiotemporal distribution of ice conditions is the changes of surface ice thickness in the reservoir area over time.

8. The inversion and prediction method of reservoir sediment and temperature dual density flow according to claim 1 is characterized in that: The time step meets the following formula conditions: Where △t is the time step; A x is the longitudinal eddy viscosity; A z is the vertical eddy viscosity; Q e is the total flow into or out of the grid cell; V is the volume of the grid cell; H is the depth of the water column where the grid cell is located; ρ is the water density; △ρ is the maximum density difference in the water column where the grid cell is located.

9. The inversion and prediction method of reservoir sediment and temperature dual density flow according to claims 1 to 8, characterized in that: In step 3.2, the suspended matter convection-diffusion equation is used to calculate the sediment of different levels and obtain the corresponding sediment content distribution, and the water density is further updated.

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