River terrain reconstruction method and device based on coupling of energy loss and genetic algorithm

Abstract

The invention belongs to the technical field of hydrology and landform, and discloses a riverway terrain reconstruction method and device based on energy loss and genetic algorithm coupling, and the method comprises the steps: collecting a remote sensing image of a riverway, the actual measurement data of a hydrological station, and the elevation data; determining a water surface width sequence of a river channel overflowing section based on the river channel water surface vector of the remote sensing image; analyzing actually measured data near the river channel, and determining hydraulic parameters corresponding to the river channel overflowing section; based on the hydraulic parameters, with the minimum energy loss as the optimization target, determining a target width-depth ratio sequence of the river channel overflowing section by adopting a genetic algorithm; based on the water surface width sequence and the target width-depth ratio sequence of the river channel overflowing section, constructing a river channel underwater terrain; and fusing the underwater topography with the elevation model data to complete reconstruction of the river topography. According to the scheme, on the basis of the measured data and the optical remote sensing image of the river channel, various hydraulic parameter characteristics and energy loss corresponding to the overflowing section are considered, and the more accurate river channel terrain can be reconstructed.

Description

Technical Field

[0001] The invention relates to the technical field of hydrological geomorphology, and in particular to a river terrain reconstruction method and device based on energy loss and genetic algorithm coupling. Background Art

[0002] Underwater terrain data is a key boundary condition for modeling hydrodynamic processes and will affect the model's predictive ability. Under the current hydrodynamic theory framework, although the model can accept various boundary conditions as input, when it comes to underwater terrain description, the model pays more attention to the geometric and physical characteristics of the terrain. In order to accurately capture the underwater terrain characteristics. Some researchers use publicly available global digital elevation model (DEM) data to obtain the noise value of the elevation within the river channel and perform sliding average optimization as the underwater terrain. The disadvantage of this method is that the river channel noise value is affected by many factors, and it cannot form a consistent correlation with the riverbed terrain. Although the results obtained meet the calculation of the hydrodynamic model under certain conditions, they lose consistency with the real river channel terrain, so the method of river channel terrain reconstruction needs to be improved. Some researchers have also reconstructed riverbed digital terrain based on SRTM DEM data to solve the shortcomings of public data source DEM data in describing riverbed terrain. They use a strong local weighted regression algorithm to smooth the river network longitudinal profile elevation extracted from DEM data to eliminate abnormal elevation values ​​in the original data. Using the river surface polygon data as a mask, the inverse distance weighted interpolation method is used to interpolate the unknown elevation pixels inside the river surface to obtain a three-dimensional digital river surface. Combining the river surface elevation and water depth information, the cross-sectional shape of the riverbed is assumed to complete the three-dimensional digital terrain reconstruction of the riverbed area. However, for river sections without water depth information, this method cannot be used to reconstruct digital terrain. Summary of the invention

[0003] To solve the above problems, the present invention provides a river channel topography reconstruction method and device based on the coupling of energy loss and genetic algorithm, which takes the measured data of the river channel and optical remote sensing images as the data basis, considers the characteristics of various hydraulic parameters corresponding to the flow section and energy loss, and can reconstruct a more accurate river channel topography.

[0004] To achieve the above object, the present invention adopts the following technical solution:

[0005] In a first aspect, the present invention provides a river terrain reconstruction method based on energy loss and genetic algorithm coupling, comprising:

[0006] Collect optical remote sensing images of the river, measured data from hydrological stations near the river, and elevation model data of the river;

[0007] Based on the river surface vector of optical remote sensing images, determine the water surface width sequence of the river flow section;

[0008] Analyze the measured data of the hydrological stations near the river channel to determine the hydraulic parameters corresponding to the flow section of the river channel;

[0009] Based on the hydraulic parameters corresponding to the flow section of the river, and taking the minimum energy loss as the optimization goal, a genetic algorithm is used to determine the target width-to-depth ratio sequence of the flow section of the river.

[0010] Based on the water surface width sequence of the river flow section and the target width-to-depth ratio sequence of the river flow section, the underwater topography of the river channel is constructed;

[0011] The underwater topography of the river is integrated with the elevation model data of the river to complete the reconstruction of the river topography.

[0012] Furthermore, the measured data of the hydrological stations near the river channel are analyzed to determine the hydraulic parameters corresponding to the flow section of the river channel, including:

[0013] Generalize and analyze the measured cross-section data in the hydrological station measured data to determine the fitting model of the river flow cross-section morphology;

[0014] The river flow section is fitted by fitting the shape coefficient of the model, and the shape of the river flow section is generalized into a geometric shape;

[0015] Determine the hydraulic radius of the river flow section based on the area formula of the river flow section with geometric shape;

[0016] Based on the hydraulic radius of the river flow section and Manning's formula, the water flow velocity of the river flow section is determined.

[0017] Furthermore, based on the hydraulic parameters corresponding to the river flow section and taking the minimum energy loss as the optimization goal, a genetic algorithm is used to determine the target width-to-depth ratio sequence of the river flow section, including:

[0018] Based on the hydraulic parameters of adjacent flow sections in the river flow section, the Darcy-Weisbach algorithm is used to determine the energy loss of adjacent flow sections.

[0019] Based on the energy loss of adjacent flow sections, the Bernoulli equation is used to determine the theoretical water level of adjacent flow sections.

[0020] Obtain the initial width-to-depth ratio sequence of the river flow section;

[0021] Based on the initial width-to-depth ratio, terrain factor constraints, width-to-depth ratio range constraints, and water flow continuity constraints, and taking the minimum energy loss as the optimization goal, a genetic algorithm is used to determine the target width-to-depth ratio sequence of the flow section of the river crossing.

[0022] Furthermore, based on the water surface width sequence of the river flow section and the target width-to-depth ratio sequence of the river flow section, the underwater topography of the river channel is constructed, including:

[0023] Based on the water surface width sequence of the river flow section and the target width-to-depth ratio sequence of the river flow section, the water depth and river bottom elevation of all the flow sections in the river flow section are determined;

[0024] Based on the cross-sectional shape of the flow section, the riverbed elevation is interpolated to construct the underwater topography of the river.

[0025] In a second aspect, the present invention further provides a river terrain reconstruction device based on energy loss and genetic algorithm coupling, comprising:

[0026] The collection module is used to collect optical remote sensing images of the river, measured data from hydrological stations near the river, and elevation model data of the river;

[0027] A determination module is used to determine the water surface width sequence of the flow section of the river channel based on the river channel water surface vector of the optical remote sensing image;

[0028] The analysis module is used to analyze the measured data of the hydrological station near the river channel and determine the hydraulic parameters corresponding to the flow section of the river channel;

[0029] A calculation module is used to determine the target width-to-depth ratio sequence of the river flow section by using a genetic algorithm based on the hydraulic parameters corresponding to the river flow section and taking the minimum energy loss as the optimization goal;

[0030] A construction module, used for constructing the underwater topography of the river channel based on a water surface width sequence of the river channel flow section and a target width-to-depth ratio sequence of the river channel flow section;

[0031] The fusion module is used to fuse the underwater topography of the river with the elevation model data of the river to complete the reconstruction of the river topography.

[0032] Furthermore, the analysis module is also used to:

[0033] Generalize and analyze the measured cross-section data in the hydrological station measured data to determine the fitting model of the river flow cross-section morphology;

[0034] The river flow section is fitted by fitting the shape coefficient of the model, and the shape of the river flow section is generalized into a geometric shape;

[0035] Determine the hydraulic radius of the river flow section based on the area formula of the river flow section with geometric shape;

[0036] Based on the hydraulic radius of the river flow section and Manning's formula, the water flow velocity of the river flow section is determined.

[0037] Furthermore, the computing module is also used for:

[0038] Based on the hydraulic parameters of adjacent flow sections in the river flow section, the Darcy-Weisbach algorithm is used to determine the energy loss of adjacent flow sections.

[0039] Based on the energy loss of adjacent flow sections, the Bernoulli equation is used to determine the theoretical water level of adjacent flow sections.

[0040] Obtain the initial width-to-depth ratio sequence of the river flow section;

[0041] Based on the initial width-to-depth ratio, terrain factor constraints, width-to-depth ratio range constraints, and water flow continuity constraints, and taking the minimum energy loss as the optimization goal, a genetic algorithm is used to determine the target width-to-depth ratio sequence of the flow section of the river crossing.

[0042] Furthermore, the building blocks are also used to:

[0043] Based on the water surface width sequence of the river flow section and the target width-to-depth ratio sequence of the river flow section, the water depth and river bottom elevation of all the flow sections in the river flow section are determined;

[0044] Based on the cross-sectional shape of the flow section, the riverbed elevation is interpolated to construct the underwater topography of the river.

[0045] In a third aspect, the present invention further provides an electronic device, comprising: a processor and a memory;

[0046] The processor is coupled to the memory;

[0047] The processor is used to read and execute the program or instructions stored in the memory, so that the device executes the method of the first aspect.

[0048] In a fourth aspect, the present invention further provides a computer-readable storage medium storing a computer program, which implements the method of the first aspect when executed by a processor.

[0049] The technical solution provided by the present invention has at least the following technical effects or advantages:

[0050] The technical solution of the present invention is to calculate the hydrological parameters corresponding to the cross section of the river terrain based on the measured data of the hydrological station, that is, by generalizing the cross section of the river bottom, determine the geometric shape of the cross section and the corresponding power function model, and determine the hydrological parameters corresponding to the cross section of the river terrain according to the area formula of the cross section shape combined with the shape coefficient in the power function model. The target width-to-depth ratio of the flow section is determined based on the hydraulic parameters and the energy loss of the flow section, and the riverbed elevation of the river is determined in combination with the water surface width extracted from the optical remote sensing image. According to the shape of the flow section and the riverbed elevation, the underwater topography of the riverbed is constructed, and then the reconstruction of the river terrain is completed. The solution of the present invention, based on the measured data and optical remote sensing images of the river channel, takes into account the characteristics of various hydraulic parameters and energy loss corresponding to the flow section, and can reconstruct a more accurate river terrain.

[0051] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0053] Figure 1 It is a schematic flow chart of a river terrain reconstruction method based on energy loss and genetic algorithm coupling in an embodiment of the present invention;

[0054] Figure 2 A schematic diagram of a common river flow cross-section in an embodiment of the present invention;

[0055] Figure 3 It is a schematic diagram of the shape of the assumed flow cross section in an embodiment of the present invention;

[0056] Figure 4 A triangular cross-sectional schematic diagram of a generalized cross-sectional shape of a river flow in an embodiment of the present invention;

[0057] Figure 5 It is a schematic diagram of a power function section that generalizes the cross-sectional morphology of a river flow in an embodiment of the present invention;

[0058] Figure 6 It is a schematic structural diagram of a river terrain reconstruction device based on energy loss and genetic algorithm coupling in an embodiment of the present invention;

[0059] Figure 7 The present invention is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] Figure 1 It is a river terrain reconstruction method based on energy loss and genetic algorithm coupling. As shown in the figure, the method includes:

[0062] The technical solution of the present invention is further described below:

[0063] 1. Collect optical remote sensing images of the river, measured data from hydrological stations near the river, and elevation model data of the river;

[0064] (1) Collect high-resolution optical remote sensing images of the river, including but not limited to Landsat series, Sentinel series, Keyhole series, and Gaofen series satellite remote sensing images;

[0065] (2) Obtain river elevation model (DEM) data by clipping from publicly available global digital elevation model (DEM) data;

[0066] (3) Collect measured data from hydrological stations near the river, including measured cross-sectional data, daily flow data, daily water level data, etc.;

[0067] (4) Collect on-site measured data of the river channel, including drone aerial survey images and underwater topographic data collected by an unmanned boat equipped with an acoustic Doppler current profiler (ADCP), to verify the accuracy of optical remote sensing data and measured data from hydrological stations.

[0068] 2. Determine the water surface width sequence of the river flow section based on the river surface vector of the optical remote sensing image;

[0069] Import the optical remote sensing image of the river into the common remote sensing image processing tools, perform radiation calibration and atmospheric correction on the optical remote sensing image, and extract the river surface vector; import the river surface vector into the geographic information system tool and determine the center line of the river. To obtain the river surface vector, the water body index method and other technologies can be used.

[0070] A stable flow river channel is a river section where the flow is constant over a certain period of time, the riverbed morphology is relatively fixed and is not subject to significant external interference. The stable flow channel has a stable flow value, which facilitates the calculation of subsequent hydraulic parameters.

[0071] The migration parameters such as the migration distance, migration speed and migration acceleration of the center line of the river channel are obtained by using geographic information system tools, and cluster analysis is performed on the migration parameters to calculate the relative stability index RSIRR-G (relative stability index of river section) of the entire river channel. If the value of the relative stability index RSIRR-G meets the specified threshold requirement, the river channel is a stable flow river channel. The river channel terrain reconstruction in the present invention refers to the terrain reconstruction of a stable river section.

[0072] The flow section refers to the cross section perpendicular to the direction of river flow, and the river flow section refers to the sequence of all flow sections.

[0073] The “Create Vertical Line” tool of the geographic information system tool is used to generate a vertical line along the center line, and the vertical line is superimposed with the water surface vector to calculate the water surface width w of each flow section in the river flow section, thereby determining the water surface width sequence of the river flow section.

[0074] 3. Analyze the measured data of the hydrological stations near the river channel to determine the hydraulic parameters corresponding to the flow section of the river channel;

[0075] The hydraulic parameter data corresponding to the flow section of the river can reflect the movement characteristics of water flow in a specific terrain, including: cross-sectional shape, hydraulic radius, wetted perimeter, water flow velocity, etc.

[0076] The measured data of the hydrological station near the river channel is used as the data source for river channel topography reconstruction, that is, the cross-sectional data in the measured data of the hydrological station can be regarded as the data source of the river channel flow cross-sectional data. The measured cross-sectional data in the measured data of the hydrological station is generalized and analyzed to determine the fitting model of the river channel flow cross-sectional morphology, which can be expressed as:

[0077]

[0078] In the formula, y represents the water depth of the flow section; x represents the water surface width of the flow section; and γ represent the morphological coefficient;

[0079] The river flow section is fitted by fitting the morphological coefficient of the model, and the morphology of the river flow section is generalized into a geometric shape. When the morphological coefficient γ = 1, the river flow section can be generalized into a triangular section; when the morphological coefficient γ = 2, the river flow section can be generalized into a standard power function section; when γ takes other values, it corresponds to other geometric shapes; the generalized river flow section has a certain morphological coefficient and γ, that is, it has a certain fitting model; all geometric forms corresponding to the generalized river flow section can be collectively referred to as power function forms; based on the area formula of the geometric river flow section, the hydraulic radius of the river flow section is determined; based on the hydraulic radius of the river flow section and Manning's formula, the water flow velocity of the river flow section is determined. The geometric form of the generalized river flow section is the cross-sectional form in the hydraulic parameters.

[0080] The details are as follows:

[0081] The cross section of a river usually presents a V shape. Due to the large longitudinal gradient, fast flow velocity and strong scouring effect, the water depth, water surface width and cross-sectional area will fluctuate with the flow rate (see Figure 2 (a)). In mountainous and plain rivers, the river channel is affected by the topography and geological conditions, and the cross section often presents asymmetric characteristics, with steep slopes on one side and gentle slopes on the other side (see Figure 2 (b)), such cross-sections can be generalized as triangles; for rivers in plain and hilly areas, due to the small longitudinal gradient and slow flow rate, the cross-section shape is characterized by a large width-to-depth ratio (see Figure 2 (c) and (d)). When there are significant topographic protrusions in the river channel, the cross-sectional morphology becomes more complex (see Figure 2 (e)).

[0082] Figure 2 (a)(b) can be roughly generalized as a triangle, the difference is that, Figure 2 (a) is bilaterally symmetrical, Figure 2 (b) is a special case of Figure 2 (a)(b) is generalized into a triangular cross section for analysis. Figure 2 For the wide and shallow river channel shown in (c), (d), and (e), the relationship between the water surface width and the water depth can be approximately generalized into a power function model, and the function form is:

[0083]

[0084] In the formula, y represents the water depth of the flow section; x represents the water surface width of the flow section; and γ represent the morphology coefficient.

[0085] Assume that the water surface width of the flow section is 100m and the water depth is 10m. When γ and γ take the values ​​given in Table 1, the cross-sectional shape is as follows Figure 3 As shown. It can be seen that according to the power function With the given The cross-sectional shape drawn by the and γ values ​​is similar to some wide and shallow river sections in actual projects. Therefore, the wide and shallow sections in the project can be fitted using the power function, but the coefficients and the exponent γ will change with the cross-sectional size.

[0086] Based on the river flow calculation formula and the known functional relationship between the cross-section water surface width, water surface depth, water flow velocity and flow, further analysis of the assumed flow cross-section can determine that any cross-section, including a triangle, can be fitted using the power function model;

[0087] River flow calculation formula:

[0088] Q=whv (3-1)

[0089] Where Q is the flow rate of the flow section, unit is m 3 / s; w is the width of the flow section, unit: m; h is the water depth of the flow section, unit: m; v is the flow velocity of the flow section, unit: m / s

[0090] The functional relationship between water surface width, average water depth of the section and average flow velocity and flow rate is:

[0091] w=aQ b

[0092] d=cQ f

[0093] v=kQ m (3-2)

[0094] Where a, c and k are coefficients; b, f and m are exponents.

[0095] Substituting (3-2) into (3-1), the following relationship must be satisfied:

[0096] b+f+m=1

[0097] ack=1 (3-3)

[0098]

[0099] In the formula, y represents the water depth of the flow section; x represents the water surface width of the flow section; and γ represent the morphology coefficient.

[0100] Table 1

[0101]

[0102] When γ = 1, the cross-section equation is At this time, the flow cross section is a triangular cross section, and the exponents are b=0.375, f=0.375, and m=0.25.

[0103] When γ = 2, the river section is parabolic, and the exponents b, f and m are 0.23, 0.46 and 0.31 respectively.

[0104] Based on the measured data of the hydrological station, the flow section is fitted by adjusting the shape coefficient of the fitting model, and the shape of the flow section is generalized into a geometric shape. The generalized shape of the flow section has a certain shape coefficient. and γ, that is, with a certain fitting model. For example, Figure 2 The flow sections in the figure are several common cross-sectional shapes. Figure 2 (a)(b) can be generalized as Figure 4 Analyze the triangular section shown in Figure 2 The wide and shallow river channel shown in (c), (d), and (e) is generalized as Figure 5 The power function section shown is analyzed.

[0105] Triangular section:

[0106] The calculation formula of the flow cross-sectional area A is:

[0107]

[0108] Where: w is the width of the flow section, unit is m, h is the maximum water depth of the triangular flow section, unit is m;

[0109] The calculation formula of the wetted perimeter χ of the flow section is:

[0110]

[0111] Where, χ is the wetted perimeter of the flow section, in m; θ1 and θ2 are the two angles of the triangular section vertex.

[0112] The calculation formula for hydraulic radius R is:

[0113]

[0114] In the formula, R is the hydraulic radius, in m; w is the flow section width, in m; θ1 and θ2 are the two angles of the triangular section vertex.

[0115] Manning's formula:

[0116]

[0117] Where: v: flow velocity of the flow section; R: hydraulic radius, unit: m; J: hydraulic slope; n: Manning roughness.

[0118] The water flow velocity in the flow section is:

[0119]

[0120] Power function section:

[0121] Calculation formula for flow cross-sectional area A

[0122]

[0123] Where w is the water surface width of the flow section, unit: m.

[0124] For wide and shallow rivers, the wetted perimeter χ is approximately equal to the river width w. Therefore, the calculation formula for the hydraulic radius is:

[0125]

[0126] According to Manning's formula, v∝R 2 / 3 Therefore, the average flow velocity v∝w 2 / 3 ;

[0127]

[0128] 4. Based on the hydraulic parameters corresponding to the river flow section and taking the minimum energy loss as the optimization goal, a genetic algorithm is used to determine the target width-to-depth ratio sequence of the river flow section;

[0129] The river flow section refers to the sequence of all flow sections. Based on the hydraulic parameters corresponding to the adjacent flow sections in the river flow section, the Darcy-Weisbach algorithm is used to determine the energy loss of the adjacent flow sections; based on the energy loss of the adjacent flow sections, the Bernoulli equation is used to determine the theoretical water level of the adjacent flow sections; the initial width-to-depth ratio sequence of the river flow section is obtained; based on the initial width-to-depth ratio, terrain factor constraints, width-to-depth ratio range constraints, and water flow continuity constraints, the genetic algorithm is used to determine the target width-to-depth ratio sequence of the river flow section with the minimum energy loss as the optimization goal;

[0130] The details are as follows:

[0131] The total energy loss calculated by the Darcy-Weisbach formula refers to the head loss along the way h f and local head loss h j sum.

[0132] The Darcy-Weisbach formula is used to calculate the head loss h between two adjacent sections. f :

[0133]

[0134] Xie Cai coefficient:

[0135]

[0136] in, is the average velocity of two adjacent sections. Unit: m / s; is the average value of the Xie Cai coefficient of two adjacent sections, is the average hydraulic radius of two adjacent cross-sections, in m; L is the length of the centerline of the river channel between the two cross-sections, in m.

[0137] Local head loss between two adjacent cross-sections:

[0138]

[0139] In the formula, v i and v i+1 are the average flow velocities of two adjacent cross-sections, in m / s; g is the acceleration of gravity, in m 2 / s; ζ is the local head loss coefficient. Based on the "Hydraulic Calculation Handbook", the value of ζ is generally 0 in the contraction section; in the diffusion section, since v2 < v1, so ζ < 0; in the gradually expanding section, the value of ζ is generally -0.333; in the sudden expansion section and at the bridge crossing, the value is -0.05 to 0.1.

[0140] Combining (3-12) and (3-14) gives the total energy loss:

[0141] h w = h f + h j (3-15)

[0142] Using the Bernoulli equation to calculate the theoretical water level along the river channel, the Bernoulli equation:

[0143]

[0144] In the formula, α is the kinetic energy correction coefficient, here taking 1.01; Z i and Z i+1 are the water levels of two adjacent cross-sections; v i and v i+1 are the average flow velocities of two adjacent cross-sections; h w is the total energy loss.

[0145] Among them, v i and v i+1 Calculation of the average flow velocities of two adjacent cross-sections:

[0146] v i = Q / A i (3-17)

[0147] In the formula, v i is the flow velocity of the cross-section, in m / s; Q is the flow rate of the cross-section. Since it is a stable flow river channel, the flow rate remains unchanged, in m 3 / s; A i is the cross-sectional area of each cross-section, in m 2

[0148] The initial width-to-depth ratio sequence of the river flow section is obtained as follows:

[0149] Based on the measured hydrological data near the river channel, CAD is used to draw each flow section and water level closed area map in the river flow section. The closed area A0 and the flow section width w0 can be directly obtained through the calculation tool. Combined with the flow section shape determined above, that is, the triangular section or the power function section, the initial water depth h0 of the flow section is calculated, and the initial width-to-depth ratio λ0 is further calculated, which can be expressed as: λ0 = w0 / h0. The initial width-to-depth ratio of all flow sections in the river flow section is obtained by calculation.

[0150] Taking the initial width-to-depth ratio sequence of the river flow section as the initial reference point, a genetic algorithm is introduced to optimize the width-to-depth ratio and gradually converge to the global optimal solution. Taking energy loss minimization as the objective function, water flow continuity and terrain constraint factors as constraints, the width-to-depth ratio sequence that best suits the hydrodynamic characteristics of a given river section is obtained, that is, the target width-to-depth ratio sequence of the river flow section.

[0151] The main steps of genetic algorithm include:

[0152] a. Initialize the population: randomly generate a set of solutions (population), each solution is called an individual, and here the individual consists of a series of width-to-depth ratios.

[0153] b. Evaluate fitness: Define a fitness function to measure the quality of each individual. The higher the value of the fitness function, the better the individual.

[0154] c. Selection: Select individuals from the current population for reproduction, and the selection probability is proportional to the individual fitness.

[0155] d. Crossover (hybridization): Two individuals exchange some genes to produce new offspring.

[0156] e. Mutation: Changing a gene of an individual with a certain probability to increase population diversity.

[0157] f. Iteration: Repeat the above process until the preset number of iterations is reached or other termination conditions are met.

[0158] Objective function:

[0159] Minimal energy loss:

[0160]

[0161] In the formula, f is the objective function, h is w For energy loss;

[0162] Constraints:

[0163] Aspect ratio range constraints:

[0164] λ-2≤λ≤λ+2 (3-19)

[0165] Where λ is the aspect ratio.

[0166] Water flow continuity constraints:

[0167] Q=Av (3-20)

[0168] Terrain factor constraints:

[0169]

[0170] Where S is the terrain constraint factor, that is, the terrain constraint factor of adjacent sections.

[0171] 5. Construct the underwater topography of the river channel based on the water surface width sequence of the river channel flow section and the target width-to-depth ratio sequence of the river channel flow section;

[0172] Based on the water surface width sequence of the river flow section and the target width-to-depth ratio sequence of the river flow section, the water depth and riverbed elevation of all flow sections in the river flow section are determined; based on the cross-sectional morphology of the flow section, the riverbed elevation is interpolated to construct the underwater topography of the river.

[0173] The details are as follows:

[0174] Using the target width-to-depth ratio sequence of the river flow section, combined with the river water surface vector based on optical remote sensing images, the water surface width sequence of the river flow section can be determined, and the water depth h of all the flow sections in the river flow section can be further calculated. i and river bottom elevation H 河底 .

[0175] Calculate riverbed elevation at flow section

[0176] H 河底 =Z i -h i

[0177] λ is the width-to-depth ratio; Q is the flow rate of the flow section; λ is the width-to-depth ratio; S is the hydraulic slope; Z i , Z i+1 Water level of two adjacent sections; L is the length of the river centerline between two sections, in meters.

[0178] Using geographic information system tools, along the river flow direction, each flow section in the river channel is taken as a section perpendicular to the river flow direction, and a cross-sectional diagram of the riverbed elevation and water surface elevation corresponding to each flow section is drawn. The riverbed elevation is interpolated according to the shape of the flow section determined above to construct the underwater topography of the river channel.

[0179] 6. Integrate the underwater topography of the river with the elevation model data of the river to complete the reconstruction of the river topography.

[0180] The underwater terrain of the river is obtained from the public global digital elevation model (DEM) data by clipping the river elevation model (DEM) data to obtain a DEM raster file containing the underwater terrain. The details are as follows:

[0181] Step 1: Interpolation of riverbed elevation between sections

[0182] Let x i is the cross-section position coordinate along the river flow direction (i=1,2,…,n), y i is the riverbed elevation of the corresponding section. The cubic spline interpolation formula is:

[0183]

[0184] Among them, a i ,b i ,c i ,d i It is an undetermined coefficient and needs to be determined according to the following conditions:

[0185] S(x i )=y i (Interpolation condition, that is, the value of the spline function at each section is equal to the riverbed elevation of that section).

[0186] S′(x i+1 ) = S′(x i )(First order derivative continuity condition).

[0187] S″(x i+1 )=S″(x i )(Second order derivative continuity condition).

[0188] Use the "Interpolation Analysis" tool in the GIS tool and select the spline interpolation method to interpolate the riverbed elevation. In the "Interpolation Analysis" dialog box, set the interpolation data source to the calculated riverbed elevation data, and set appropriate interpolation parameters, such as the interpolation method to cubic spline interpolation, search radius, etc. After interpolation, continuous underwater terrain data will be obtained.

[0189] Step 2: Fusion with original DEM raster data

[0190] Use the "Raster Calculator" tool of the GIS tool to fuse the interpolated underwater terrain data with the original DEM raster data. In the "Raster Calculator" dialog box, set the expression of the original DEM raster data and the interpolated underwater terrain data, use the weighted average method, set the appropriate weight coefficient, and obtain the fused DEM raster file containing the underwater terrain. That is, the reconstruction of the river terrain is completed.

[0191] 7. Collect optical remote sensing images of the river at different times, and perform the above steps 2-6 to reconstruct the river topography multiple times to optimize the accuracy of the river topography.

[0192] Collect optical remote sensing images from the dry season to the flood season, perform steps 2-6 above to reconstruct the river terrain multiple times, define the water level in the dry season as a low water level, and define the water level in the flood season as a high water level;

[0193] In the process of multiple river channel topography reconstructions, for the same flow section in the river channel topography, the error analysis of the water depth of the flow section at low water level and the water depth of the section at high water level is performed; error evaluation indicators can be used for analysis, including: mean square error (MSE), mean absolute error (MAE) or relative error and other error indicators for quantitative analysis, specifically analyzing the difference in cross-section water depth. The following are the calculation formulas for these indicators, which are suitable for analyzing the accuracy of cross-section water depth reconstructed under different water level conditions. Root mean square error (MSE): This indicator measures the square average of the difference in water depth between low water level and high water level, and is used to quantitatively evaluate the overall error of water depth difference. This indicator can be expressed as:

[0194]

[0195] Where n is the total number of flow section samples; is the water depth of the ith section at low water level; is the water depth of the ith section at high water level.

[0196] Mean Absolute Error (MAE): This metric provides a more intuitive error measure by calculating the average absolute value of the difference between the low water level and the high water level depth, which is less affected by outliers:

[0197]

[0198] Relative error (RE): It indicates the ratio of the difference between the low water level and the high water level to the high water level, expressed as a percentage, and is used to compare the relative degree of the difference in water depth at different sections:

[0199]

[0200] In the iterative process of the genetic algorithm, the constraint range of the width-to-depth ratio and other parameters are continuously adjusted according to the error analysis to enhance the convergence speed and accuracy of the algorithm under specific conditions. Specifically: when the error is large, the current width-to-depth ratio value is not accurate enough, and the search range of the width-to-depth ratio can be expanded to allow the algorithm to explore in a larger solution space and increase the possibility of finding the optimal solution; when the error is small, it indicates that the width-to-depth ratio is close to the optimal solution, and the search range can be appropriately narrowed to reduce the invalid search area, thereby accelerating the convergence speed of the algorithm. Through the above multiple reconstructions of river channel topography, error analysis and parameter adjustment during the reconstruction process, a high-precision river channel topography is finally obtained.

[0201] The technical solution in the embodiments of the present invention has at least the following technical effects or advantages:

[0202] The technical solution of the present invention is to calculate the hydrological parameters corresponding to the cross section of the river terrain based on the measured data of the hydrological station, that is, by generalizing the cross section of the river bottom, determine the geometric shape of the cross section and the corresponding power function model, and determine the hydrological parameters corresponding to the cross section of the river terrain according to the area formula of the cross section shape combined with the shape coefficient in the power function model. The target width-to-depth ratio of the river flow cross section is determined based on the hydraulic parameters and the energy loss of the river flow cross section, and the river bottom elevation of the river is determined in combination with the water surface width extracted from the optical remote sensing image. According to the shape of the flow cross section and the river bottom elevation, the underwater topography of the river bottom is constructed, and then the reconstruction of the river terrain is completed. The solution of the present invention, based on the measured data and optical remote sensing images of the river channel, takes into account the characteristics of various hydraulic parameters and energy loss corresponding to the flow cross section, and can reconstruct a more accurate river terrain.

[0203] Figure 6 A river terrain reconstruction device based on energy loss and genetic algorithm coupling is provided in an embodiment of the present invention. As shown in the figure, the device includes:

[0204] The collection module is used to collect optical remote sensing images of the river, measured data from hydrological stations near the river, and elevation model data of the river;

[0205] A determination module, used to determine the water surface width sequence of the flow section of the river channel based on the river channel water surface vector of the optical remote sensing image;

[0206] The analysis module is also used to analyze the measured data of the hydrological station near the river channel to determine the hydraulic parameters corresponding to the flow section of the river channel;

[0207] A calculation module is used to determine the target width-to-depth ratio sequence of the river flow section by using a genetic algorithm based on the hydraulic parameters corresponding to the river flow section and taking the minimum energy loss as the optimization goal;

[0208] A construction module, used for constructing the underwater topography of the river channel based on a water surface width sequence of the river channel flow section and a target width-to-depth ratio sequence of the river channel flow section;

[0209] The fusion module is used to fuse the underwater topography of the river with the elevation model data of the river to complete the reconstruction of the river topography.

[0210] It should be noted that, for the sake of convenience, Figure 6 For example, only the main modules of the river terrain reconstruction device structure based on energy loss and genetic algorithm coupling are shown. In practical applications, the system may also include modules or components not shown in the figure; the system is not limited to the above module structure, but may also be other module structures for implementing the above method embodiments.

[0211] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. As shown in the figure, the electronic device includes: a processor and a memory;

[0212] The processor is used to read and execute programs and instructions stored in the memory, so that the electronic device executes the above method embodiment.

[0213] It should be noted that, for the sake of convenience, Figure 7 For example, only the main components of the electronic device are shown. In actual applications, the electronic device may also include components or assemblies not shown in the figure.

[0214] The present invention also provides a computer-readable storage medium storing a program or instruction. When a computer reads and executes the program or instruction, the computer executes the above method embodiment.

[0215] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A river terrain reconstruction method based on energy loss and genetic algorithm coupling, characterized in that: include: Collect optical remote sensing images of the river, measured data from hydrological stations near the river, and elevation model data of the river; Based on the river surface vector of optical remote sensing images, determine the water surface width sequence of the river flow section; Analyze the measured data of the hydrological stations near the river channel to determine the hydraulic parameters corresponding to the flow section of the river channel; Based on the hydraulic parameters corresponding to the flow section of the river, and taking the minimum energy loss as the optimization goal, a genetic algorithm is used to determine the target width-to-depth ratio sequence of the flow section of the river. Based on the water surface width sequence of the river flow section and the target width-to-depth ratio sequence of the river flow section, the underwater topography of the river channel is constructed; The underwater topography of the river is integrated with the elevation model data of the river to complete the reconstruction of the river topography.

2. The river terrain reconstruction method based on energy loss and genetic algorithm coupling according to claim 1 is characterized in that: The analysis of measured data from hydrological stations near the river channel to determine the hydraulic parameters corresponding to the flow section of the river channel includes: Generalize and analyze the measured cross-section data in the hydrological station measured data to determine the fitting model of the river flow cross-section morphology; The river flow section is fitted by fitting the shape coefficient of the model, and the shape of the river flow section is generalized into a geometric shape; Determine the hydraulic radius of the river flow section based on the area formula of the river flow section with geometric shape; Based on the hydraulic radius of the river flow section and Manning's formula, the water flow velocity of the river flow section is determined.

3. The river terrain reconstruction method based on energy loss and genetic algorithm coupling according to claim 1 is characterized in that: The method of determining the target width-to-depth ratio sequence of the river flow section based on the hydraulic parameters corresponding to the river flow section and taking the minimum energy loss as the optimization goal is to use a genetic algorithm, including: Based on the hydraulic parameters of adjacent flow sections in the river flow section, the Darcy-Weisbach algorithm is used to determine the energy loss of adjacent flow sections. Based on the energy loss of adjacent flow sections, the Bernoulli equation is used to determine the theoretical water level of adjacent flow sections. Obtain the initial width-to-depth ratio sequence of the river flow section; Based on the initial width-to-depth ratio, terrain factor constraints, width-to-depth ratio range constraints, and water flow continuity constraints, and taking the minimum energy loss as the optimization goal, a genetic algorithm is used to determine the target width-to-depth ratio sequence of the flow section of the river crossing.

4. The river terrain reconstruction method based on energy loss and genetic algorithm coupling according to any one of claims 1 to 3, characterized in that: The constructing of the underwater terrain of the river channel based on the water surface width sequence of the river channel flow section and the target width-to-depth ratio sequence of the river channel flow section includes: Based on the water surface width sequence of the river flow section and the target width-to-depth ratio sequence of the river flow section, the water depth and river bottom elevation of all the flow sections in the river flow section are determined; Based on the cross-sectional shape of the flow section, the riverbed elevation is interpolated to construct the underwater topography of the river.

5. A river terrain reconstruction device based on energy loss and genetic algorithm coupling, characterized in that: include: The collection module is used to collect optical remote sensing images of the river, measured data from hydrological stations near the river, and elevation model data of the river; A determination module is used to determine the water surface width sequence of the flow section of the river based on the river surface vector of the optical remote sensing image; The analysis module is used to analyze the measured data of the hydrological station near the river channel and determine the hydraulic parameters corresponding to the flow section of the river channel; A calculation module is used to determine the target width-to-depth ratio sequence of the river flow section by using a genetic algorithm based on the hydraulic parameters corresponding to the river flow section and taking the minimum energy loss as the optimization goal; A construction module, used for constructing the underwater topography of the river channel based on a water surface width sequence of the river channel flow section and a target width-to-depth ratio sequence of the river channel flow section; The fusion module is used to fuse the underwater topography of the river with the elevation model data of the river to complete the reconstruction of the river topography.

6. The river terrain reconstruction device based on energy loss and genetic algorithm coupling according to claim 5 is characterized in that: The analysis module is further used for: Generalize and analyze the measured cross-section data in the hydrological station measured data to determine the fitting model of the river flow cross-section morphology; The river flow section is fitted by fitting the shape coefficient of the model, and the shape of the river flow section is generalized into a geometric shape; Determine the hydraulic radius of the river flow section based on the area formula of the river flow section with geometric shape; Based on the hydraulic radius of the river flow section and Manning's formula, the water flow velocity of the river flow section is determined.

7. The river terrain reconstruction device based on energy loss and genetic algorithm coupling according to claim 6 is characterized in that: The computing module is further used for: Based on the hydraulic parameters of adjacent flow sections in the river flow section, the Darcy-Weisbach algorithm is used to determine the energy loss of adjacent flow sections. Based on the energy loss of adjacent flow sections, the Bernoulli equation is used to determine the theoretical water level of adjacent flow sections. Obtain the initial width-to-depth ratio sequence of the river flow section; Based on the initial width-to-depth ratio, terrain factor constraints, width-to-depth ratio range constraints, and water flow continuity constraints, and taking the minimum energy loss as the optimization goal, a genetic algorithm is used to determine the target width-to-depth ratio sequence of the flow section of the river crossing.

8. The river terrain reconstruction device based on energy loss and genetic algorithm coupling according to any one of claims 5 to 7, characterized in that: The building blocks are also used to: Based on the water surface width sequence of the river flow section and the target width-to-depth ratio sequence of the river flow section, the water depth and river bottom elevation of all the flow sections in the river flow section are determined; Based on the cross-sectional shape of the flow section, the riverbed elevation is interpolated to construct the underwater topography of the river.

9. An electronic device, characterized in that: include: Processor and memory; The processor is coupled to the memory; The processor is used to read and execute the program or instruction stored in the memory, so that the device executes the method according to any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that: A computer program is stored, and when the program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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