A method, device, equipment and storage medium for calculating the flow rate of river network in a river basin

Abstract

The present invention provides a method, device, equipment and storage medium for calculating the confluence flow of a river network in a basin. A method for calculating the confluence flow of a river network in a basin, comprising: obtaining the river network data of a target basin, preprocessing the river network data of the target basin, and generating confluence runoff depth data; based on the confluence runoff depth data, determining the slope confluence flow using the unit line method of the dual-parameter gamma distribution; based on the slope confluence flow, generating the confluence flow of the river network in the basin using the one-dimensional Saint-Venant equations. This method meets the confluence calculation requirements for different types of data, and improves the cumbersome link of the previous river network confluence calculation that can only calculate the confluence flow of the river network in the basin first and then calculate the confluence flow of a certain section, and realizes the direct calculation of the river network confluence flow of a certain section, thereby improving the flexibility of the basin confluence calculation and laying a foundation for the comprehensive management of the target basin.

Description

Technical Field

[0001] The present invention relates to the technical field of basin hydrological process simulation, and in particular to a method, device, equipment and storage medium for calculating the flow rate of a river network in a basin. Background Art

[0002] The existing basin runoff calculation mainly includes three technical means: one is the basin river network generalization method, the second is the slope runoff calculation method, and the third is the river network runoff calculation method. River network generalization technology mainly includes two forms: grid river network and vector river network. The basin river network generalization result and generalization degree directly affect the accuracy of subsequent runoff calculation. Raster river network generalization refers to the process of dividing the basin river network into several hydrological response units (HRU) or other spatial discrete units defined in the hydrological model in the form of a grid according to the basin topography or catchment area boundary. Vector river network generalization is to represent the river section of the basin river network in the form of lines, and each line segment represents the river section and the HRU where it is located, and the upstream and downstream HRUs are connected through the line segments. The slope runoff calculation generally adopts the unit line method and the isocurrent line method. There are two main methods for calculating river network confluence. One is the hydrological method based on the river section water balance equation and the channel storage equation, such as the Muskingum method. The other is the method of directly solving the complete Saint-Venant equations or their simplified equations, namely the hydraulic method, such as the kinematic wave method and the diffusion wave method.

[0003] The existing river network confluence calculation method discloses: obtaining surface geographic data and river network geographic data in the target area; discretizing the surface geographic data to obtain a surface two-dimensional grid model; discretizing the river network geographic data to obtain a river network one-dimensional line segment model; based on the coincidence relationship between the surface two-dimensional grid model and the river network one-dimensional line segment model, coupling calculation of surface confluence and river network confluence; wherein, discretizing the surface geographic data to obtain a surface two-dimensional grid model includes: grid discretizing the surface area corresponding to the surface geographic data to obtain a plurality of two-dimensional grids; encoding the plurality of two-dimensional grids according to a first preset encoding method to obtain first encoding information of the surface two-dimensional grid; based on the encoding information, constructing a first parameter matrix corresponding to each of the two-dimensional grids; determining each two-dimensional grid equipped with the first parameter matrix as the surface two-dimensional grid model; wherein, The data is discretized to obtain a one-dimensional line segment model of a river network, including: discretizing the river channel area corresponding to the river network geographical data to obtain a plurality of one-dimensional line segments of the river channel; encoding the one-dimensional line segments of the river channel according to the first preset encoding method to obtain second encoding information of the one-dimensional line segments of the river channel; determining the river section attribute information corresponding to the river channel based on the second encoding information and the river network geographical data; determining the one-dimensional line segments of the river channel carrying the river section attribute information as the one-dimensional line segment model of the river network; segmenting the river channel based on the river network geographical data to obtain a plurality of river channel sub-segments; encoding the river channel sub-segments according to the second preset encoding method to obtain river channel segment encoding information, wherein the river channel segment encoding information includes the upstream and downstream relationship of the river channel; constructing a second parameter matrix corresponding to each of the river channel sub-segments based on the river channel segment encoding information; and determining each of the river channel sub-segments carrying the second parameter matrix as the river network calculation model.

[0004] The existing river network confluence calculation method discloses the following steps: Step 1, obtain DEM data and remote sensing image data of the basin, and use each grid unit of the DEM as a calculation unit, and divide the calculation unit into river grid units and non-river grid units according to whether there is a river on the calculation unit; Step 2, based on the DEM data and remote sensing image data, extract the spatial information of the river-blocking water conservancy project; according to the extracted spatial information of the river-blocking water conservancy project, obtain the flood control storage capacity, location and control range of each river-blocking water conservancy project; Step 3, calculate the river channel interception and storage capacity of each river channel grid unit in the basin, and estimate the initial river channel interception and storage capacity of each river channel grid unit; Step 4, use the grid-by-grid confluence calculation method considering the river channel interception and storage capacity to perform river network confluence calculation.

[0005] The existing river network confluence calculation method discloses: extracting rivers and channels based on DEM data, and classifying the basin grids into slope grids, channel grids, and river grids by category; calculating the confluence path length from each grid to the basin outlet, and counting the number of channels and the average length of channels according to the channel grid category; setting the confluence attributes of each grid in the basin according to the river or channel grid that each grid finally merges into; determining the runoff distribution coefficients of the contour belt slope, channel, and river channel respectively according to the grid confluence attributes, using the motion wave equation as the basic simulation formula for the confluence of the slope, channel, and river channel, and simulating the confluence of the sub-basin and contour belt. This method can take into account the impact of the channel confluence process on the water cycle and improve the simulation effect of the confluence process.

[0006] However, in the above-mentioned existing technologies, the main problem in the basin river network generalization method is that both the vector and raster river network generalization technologies have certain shortcomings. The vector river network generalization technology can more accurately represent the current river channel position and HRU characteristics and other information, and is generally more accurate than the raster generalization technology, but it takes longer time in simulation calculations; although the raster river network generalization technology does not have as high generalization accuracy for basin river networks as the vector river network, it has more advantages in the accuracy of characterizing the flow direction of the river network, especially when processing lower-resolution river network data. The advantage in describing the accuracy of the river network flow direction is more obvious, and it also has a great advantage in the calculation speed when generalizing large-scale high-resolution data.

[0007] In the river network confluence calculation method, the kinematic wave does not consider the inertia term and additional gradient term in the dynamic equation, and is suitable for mountainous areas with steep slopes. The diffusion wave does not consider the inertia term, can reflect the impact of backwater, and can be used in plain river network areas. Therefore, the diffusion wave has a wider range of application than the kinematic wave.

[0008] The main disadvantage of existing basin runoff calculation technology is its lack of flexibility: first, most of the existing technologies are inventions based on a type of river network data in a vector or raster, and cannot adapt to the runoff calculation needs of different types of data; second, the existing technologies mainly adopt the method of performing runoff calculations in sequence from upstream to downstream along all river sections of the river network, and cannot conveniently calculate the runoff at any cross-sectional location, that is, when calculating the flow at any location, it is also necessary to first calculate the runoff of the entire basin in order to obtain the runoff at the target cross-section. Summary of the invention

[0009] Therefore, the technical solution of the present invention mainly solves the defects that the existing basin runoff calculation technology cannot adapt to the runoff calculation needs of different types of data and cannot conveniently calculate the runoff volume at any cross-sectional location, thereby providing a basin river network runoff flow calculation method, device, equipment and storage medium.

[0010] In a first aspect, an embodiment of the present invention provides a method for calculating the flow rate of a river network in a river basin, comprising:

[0011] Acquire river network data of a target watershed, pre-process the river network data of the target watershed, and generate runoff depth data;

[0012] Based on the runoff depth data, the slope runoff flow is determined by using the unit line method of the two-parameter gamma distribution;

[0013] Based on the slope runoff, the one-dimensional Saint-Venant equations are used to generate the river network runoff in the watershed, and the river network runoff in the watershed is used to manage the river network in the target watershed.

[0014] A method for calculating the runoff flow of a river network in a watershed provided in an embodiment of the present invention generates runoff depth data by preprocessing the river network data of a target watershed, thereby meeting the runoff calculation requirements for different types of data, and generates the runoff flow of a river network in a watershed by using a one-dimensional Saint-Venant equation group. This improves the cumbersome process of previous river network runoff calculation, in which the runoff flow of the river network in the watershed can only be calculated first and then the runoff flow of a certain section, and realizes the direct calculation of the river network runoff flow of a certain section, thereby improving the flexibility of the watershed runoff calculation and laying a foundation for the comprehensive management of the target watershed.

[0015] In combination with the first aspect, in a possible implementation manner, preprocessing the target river basin river network data to generate runoff depth data includes:

[0016] The type of the target basin river network data is judged, and when the type of the target basin river network data is grid river network data, the grid river network data is subjected to grid discretization processing to generate the runoff depth data;

[0017] When the type of the target watershed river network data is vector river network data, the vector river network data is superimposed on the hydrological response grid to generate the runoff depth data.

[0018] In combination with the first aspect, in another possible implementation, the preprocessing of the target river basin river network data to generate runoff depth data further includes:

[0019] When the type of the target river network data of the watershed is vector river network data, the watershed river network water system topological relationship information is determined based on the vector river network data.

[0020] In combination with the first aspect, in another possible implementation, determining the slope runoff flow rate based on the runoff depth data using a unit line method of a two-parameter gamma distribution includes:

[0021] The unit line of the two-parameter gamma distribution, the time step and the slope confluence time are obtained, and the slope confluence flow is determined based on the confluence runoff depth data, the unit line of the two-parameter gamma distribution, the time step and the slope confluence time.

[0022] In combination with the first aspect, in another possible implementation, the generating the river network flow rate of the basin based on the slope flow rate by using the one-dimensional Saint-Venant equations includes:

[0023] Establishing a one-dimensional diffusion wave equation based on the one-dimensional Saint-Venant equations;

[0024] Based on the slope runoff, determining the river runoff using the one-dimensional diffusion wave equation;

[0025] The flow rate of the river network in the river basin is determined based on the flow rate of the river section.

[0026] In combination with the first aspect, in another possible implementation manner, determining the river section runoff flow based on the slope runoff flow using the one-dimensional diffusion wave equation includes:

[0027] Acquire a water flow cross-sectional area, and determine a wave velocity based on the slope confluence flow and the water flow cross-sectional area;

[0028] Acquire the width and gradient of a river channel, and determine the diffusion rate based on the slope runoff, the width and gradient of the river channel;

[0029] Acquire the current river channel position, and determine the river section unit line based on the slope confluence time, the current river channel position, the wave velocity and the diffusion rate;

[0030] Obtaining unit runoff depth, and determining a convolution integral of the river section flow based on the river section unit line and the unit runoff depth;

[0031] The one-dimensional diffusion wave equation is solved based on the convolution integral of the river section flow to generate the river section flow.

[0032] In combination with the first aspect, in another possible implementation manner, the river section runoff convolution integral is determined based on the river section unit line and the unit runoff depth, and the calculation formula of the river section runoff convolution integral is as follows:

[0033]

[0034] Among them, q represents the confluence flow of the river section, U(ts) represents the unit runoff depth in the ts period, h(x,s) represents the unit line of the river section, t represents the slope confluence time, s represents the exit time, and x represents the current river channel position.

[0035] In a second aspect, an embodiment of the present invention further provides a device for calculating the flow rate of a river network in a river basin, comprising:

[0036] A preprocessing module is used to obtain the river network data of the target watershed, preprocess the river network data of the target watershed, and generate runoff depth data;

[0037] A determination module, used for determining the slope runoff flow rate by using a unit line method of a dual-parameter gamma distribution based on the runoff depth data;

[0038] A generation module is used to generate a river network flow in a watershed based on the slope flow using a one-dimensional Saint-Venant equation group, and the river network flow in the watershed is used to manage the target river network in the watershed.

[0039] In the third aspect, an embodiment of the present invention further discloses an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of a method for calculating the confluence flow of a river network in a watershed as described in the first aspect or any optional embodiment of the first aspect.

[0040] In a fourth aspect, an embodiment of the present invention further discloses a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a method for calculating the flow rate of a river network in a river basin as described in the first aspect or any optional embodiment of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 A flow chart of a method for calculating the flow rate of a river network in a river basin provided by an embodiment of the present invention;

[0043] Figure 2 A flowchart of S101 provided in an embodiment of the present invention;

[0044] Figure 3 A schematic diagram of the structure of a generator of an adversarial neural network model provided by an embodiment of the present invention;

[0045] Figure 4 A schematic diagram of the structure of a discriminator of an adversarial neural network model provided in an embodiment of the present invention;

[0046] Figure 5 A flowchart of S103 provided in an embodiment of the present invention;

[0047] Figure 6 A flowchart of S1032 provided in an embodiment of the present invention;

[0048] Figure 7 A block diagram of a device for calculating the flow rate of a river network in a river basin provided by an embodiment of the present invention;

[0049] Figure 8 FIG. 4 is a specific example diagram of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] In the description of the present invention, it should be noted that the terms "first", "second" and "third" are used for descriptive purposes only and should not be understood as indicating or implying relative importance. In addition, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a mechanical connection, or an electrical connection; or it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components, which can be a wireless connection or a wired connection. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0052] The embodiment of the present invention provides a method for calculating the flow rate of a river network in a river basin, such as Figure 1 As shown, including:

[0053] S101, obtaining river network data of a target watershed, preprocessing the river network data of the target watershed, and generating runoff depth data.

[0054] Specifically, the basin river network data uses the HydroSHEDS dataset (Hydrological data and mapsbased on SHuttle Elevation Derivatives at multiple Scales, geo-referenced hydrological dataset). The HydroSHEDS dataset provides a set of geo-referenced datasets (vectors and rasters) of different scales, including river networks, river lengths, basin boundaries, confluence directions, catchment areas, etc. The spatial resolution is 500m×500m (15 arc seconds).

[0055] S102. Based on the above runoff depth data, the slope runoff flow is determined using the unit line method of the two-parameter gamma distribution.

[0056] Specifically, the unit line of the two-parameter gamma distribution, the time step and the slope confluence time are obtained, and the slope confluence flow is determined based on the confluence runoff depth data, the unit line of the two-parameter gamma distribution, the time step and the slope confluence time.

[0057] Furthermore, slope runoff refers to the process in which runoff formed by precipitation converges along the slope from the place where it is formed to the river channel, where the unit line of the two-parameter gamma distribution can be expressed as:

[0058]

[0059] Where t represents the slope confluence time, the unit is s, seconds, α represents the shape parameter (α>0), and θ represents the time parameter; the shape parameter and time parameter are mainly determined by the physical characteristic parameters of HRU, and the size of the two mainly affects the distribution shape (α-1)θ and distribution variance αθ of the unit line 2 .

[0060] Furthermore, the slope runoff flow is calculated by convolution of gamma distribution and runoff depth. The calculation formula of slope runoff flow is as follows:

[0061]

[0062] Among them, q(s t ) is the time step s t The flow rate, in m 3 / s, cubic meters / second, R is the runoff depth of the HRU unit, in mm, millimeters, s tmax is the maximum time of the gamma distribution, in s, s t is the time step, in s.

[0063] S103. Based on the slope runoff, the one-dimensional Saint-Venant equations are used to generate the river network runoff in the watershed. The river network runoff in the watershed is used to manage the target river network in the watershed.

[0064] Specifically, river network confluence refers to the process of collecting and calculating the slope confluence flow calculated by each HRU unit along the river channels at each level step by step downstream. The time step of river network confluence is consistent with the time scale of runoff data, generally on an hourly or daily scale. The river network confluence flow is calculated by directly solving the one-dimensional Saint-Venant equations.

[0065] Furthermore, the continuity equation in the Saint-Venant equations is expressed as:

[0066]

[0067] The momentum equation is expressed as:

[0068]

[0069] Where q represents the flow at time t at position x in the river network, in m 3 / s, A represents the cross-sectional area of ​​water flow, unit is m 2 , square meters, v represents the flow velocity, the unit is m / s, meter / second, y represents the river depth, the unit is m, meter, S 0 represents the river gradient, S f represents the friction ratio, g represents the acceleration due to gravity, and is taken as 9.81m / s 2 , x represents the position in the river network.

[0070] Furthermore, the diffusion wave equation is derived through the one-dimensional Saint-Venant equations. The diffusion wave method does not need to calculate the confluence according to the upstream and downstream order of the river sections. It only needs to perform convolution integral on each river section to calculate the confluence of the river section, and then sum up the confluence flow of all river sections to get the confluence flow of the river network in the basin.

[0071] The present embodiment proposes a method for calculating the runoff flow of a river network in a river basin. By preprocessing the river network data of the target river basin, the runoff depth data is generated, thereby meeting the runoff calculation requirements for different types of data. The one-dimensional Saint-Venant equations are used to generate the runoff flow of the river network in the river basin. This improves the previous cumbersome process of calculating the runoff flow of the river network in the river basin and then calculating the runoff flow of a certain section. The method realizes the direct calculation of the river network runoff flow of a certain section, thereby improving the flexibility of the runoff calculation in the river basin and laying a foundation for the comprehensive management of the target river basin.

[0072] As an optional embodiment of the present invention, Figure 2 As shown, the above S101, i.e., determining the slope runoff flow rate by using the unit line method of the dual-parameter gamma distribution based on the above runoff depth data, includes:

[0073] S1011. Determine the type of the target river network data. When the target river network data is grid river network data, perform grid discretization on the grid river network data to generate the runoff depth data.

[0074] Specifically, Figure 3As shown in the figure, the hydrological response unit (HRU) is used as the runoff calculation unit, and the runoff data such as the runoff results of the hydrological model or the runoff results calculated by other methods are directly used as input. The runoff data is discretized in the grid river network, that is, the runoff of each grid in the HRU is superimposed and calculated, and the runoff results of each grid are superimposed and mapped to the HRU where it is located. The runoff of each HRU is calculated and expressed as the runoff depth of the HRU unit, which is recorded as R.

[0075] Furthermore, a grid river network preprocessing script based on languages ​​such as Python (computer programming language) can be developed to identify each HRU in the basin river network and its corresponding grid river network data, so as to realize the rapid calculation of the flow yield of each HRU.

[0076] S1012. When the type of the target river basin river network data is vector river network data, the vector river network data is superimposed on the hydrological response grid to generate the runoff depth data.

[0077] Specifically, when the type of the above-mentioned target river network data is vector river network data, the river network water system topological relationship information of the river basin is determined based on the above-mentioned vector river network data.

[0078] Furthermore, if Figure 4 As shown in the figure, the river network relationship in the basin is determined according to the upstream river section information of each river section. By developing a network topology information recognition program, the upstream river section information, upstream HRU information, upstream basin area information, etc. of each river section are identified to determine the topological relationship information of different river sections. The HRU unit is used as the confluence calculation unit, and the river network runoff data is superimposed on the HRU. The runoff of each HRU is calculated and expressed as the runoff depth of the HRU unit, which is recorded as R.

[0079] The above optional implementation method determines the topological relationship of the river network in the basin through preprocessing of the basin river network data, including the connectivity relationship between river channels, the relationship between main and tributary rivers, the relationship between upstream and downstream, the relationship between flow directions, etc., to provide support for the basin confluence calculation; and, based on the calculation of grid river network data and based on vector river network data, the estimation of the river flow value at any section in the basin river network is realized, which improves the deficiency that the previous river network confluence calculation can only be performed on one type of river network data, either vector or raster. Both the raster generalized river network data and the vector generalized river network data can be used to perform confluence calculation along all river sections in the river network data, or to perform confluence calculation at any specified position section. When the confluence calculation is performed at any specified section, the calculation cost can be reduced.

[0080] As an optional embodiment of the present invention, Figure 5 As shown, the above S103, i.e., based on the above slope runoff flow, using the one-dimensional Saint-Venant equations to generate the basin river network runoff flow, includes:

[0081] S1031. Establish a one-dimensional diffusion wave equation based on the above one-dimensional Saint-Venant equations.

[0082] Specifically, assuming that the river channel is a uniform rectangular steady flow, the momentum equation of the one-dimensional Saint-Venant equations can be written as:

[0083]

[0084] Furthermore, the formula for flow q can be expressed in the form of river flood carrying capacity:

[0085]

[0086] Among them, K c is the flood discharge capacity of the river, and its calculation formula is as follows:

[0087]

[0088] Furthermore, by substituting formula (6) into formula (5), the momentum equation can be written as:

[0089]

[0090] Furthermore, the continuity equation can be written as:

[0091]

[0092] Furthermore, by integrating the continuity equation (9) and the momentum equation (8), we can obtain:

[0093]

[0094] Furthermore, due to K c is a function of A and y, so the second part of formula (10) can be written as:

[0095]

[0096] Furthermore, by substituting formula (11) into formula (10), we can obtain the one-dimensional diffusion wave equation, which can be expressed as:

[0097]

[0098] Among them, C is the wave velocity and D is the diffusion rate.

[0099] S1032. Based on the above slope runoff, use the above one-dimensional diffusion wave equation to determine the river section runoff.

[0100] Specifically, the one-dimensional diffusion wave equation is solved by the convolution integral of the confluence of each river section, and then the confluence of all river sections is summed to obtain the discharge at the basin outlet.

[0101] S1033. Determine the flow rate of the river network in the above-mentioned river basin based on the flow rate of the above-mentioned river section.

[0102] Specifically, the sum of the runoff of all river sections is taken as the runoff of the river network in the basin.

[0103] As an optional embodiment of the present invention, Figure 6 As shown, the above S1032, i.e., the above determining the river section confluence flow based on the above slope confluence flow by using the above one-dimensional diffusion wave equation, includes:

[0104] S10321. Obtain the water-passing cross-sectional area, and determine the wave velocity based on the slope confluence flow and the water-passing cross-sectional area.

[0105] Specifically, the calculation formula of wave speed C is as follows:

[0106]

[0107] Where A represents the water flow cross-sectional area.

[0108] S10322. Obtain the river channel width and the river channel gradient, and determine the diffusion rate based on the slope confluence flow, the river channel width and the river channel gradient.

[0109] Specifically, the calculation formula of the diffusion coefficient D is as follows:

[0110]

[0111] Where ω is the width of the river.

[0112] S10323. Obtain the current river channel position, and determine the unit line of the river section based on the slope confluence time, the current river channel position, the wave velocity and the diffusion rate.

[0113] Specifically, in a given river section or outlet river section, a set of unique unit lines can be constructed for all river sections according to the distance between the upstream river section and the outlet river section, namely the river section unit line. The calculation formula of the river section unit line h(x,s) is as follows:

[0114]

[0115] Among them, x represents the current river position.

[0116] S10324. Obtain unit runoff depth, and determine the convolution integral of the river section flow based on the river section unit line and the unit runoff depth.

[0117] Specifically, the calculation formula of the convolution integral of the above river section flow is as follows:

[0118]

[0119] Among them, q represents the flow rate of the river section, U(ts) represents the unit runoff depth in the ts period, h(x,s) represents the unit line of the river section, t represents the slope confluence time, and s represents the exit time.

[0120] S10325. Solve the one-dimensional diffusion wave equation based on the convolution integral of the river section flow to generate the flow rate of the river section flow.

[0121] The embodiment of the present invention also discloses a device for calculating the flow rate of a river network in a river basin, such as Figure 7 As shown, including:

[0122] The preprocessing module 71 is used to obtain the river network data of the target watershed, preprocess the river network data of the target watershed, and generate the runoff depth data.

[0123] Specifically, the basin river network data uses the HydroSHEDS dataset (Hydrological data and mapsbased on SHuttle Elevation Derivatives at multiple Scales, geo-referenced hydrological dataset). The HydroSHEDS dataset provides a set of geo-referenced datasets (vectors and rasters) of different scales, including river networks, river lengths, basin boundaries, confluence directions, catchment areas, etc. The spatial resolution is 500m×500m (15 arc seconds).

[0124] The determination module 72 is used to determine the slope runoff flow rate based on the above runoff depth data by using the unit line method of the dual-parameter gamma distribution.

[0125] Specifically, the unit line of the two-parameter gamma distribution, the time step and the slope confluence time are obtained, and the slope confluence flow is determined based on the confluence runoff depth data, the unit line of the two-parameter gamma distribution, the time step and the slope confluence time.

[0126] Furthermore, slope runoff refers to the process in which runoff formed by precipitation converges along the slope from the place where it is formed to the river channel, where the unit line of the two-parameter gamma distribution can be expressed as:

[0127]

[0128] Where t represents the slope confluence time, the unit is s, seconds, α represents the shape parameter (α>0), and θ represents the time parameter; the shape parameter and time parameter are mainly determined by the physical characteristic parameters of HRU, and the size of the two mainly affects the distribution shape (α-1)θ and distribution variance αθ of the unit line 2 .

[0129] Furthermore, the slope runoff flow is calculated by convolution of gamma distribution and runoff depth. The calculation formula of slope runoff flow is as follows:

[0130]

[0131] Among them, q(s t ) is the time step s t The flow rate, in m 3 / s, cubic meters per second, R is the runoff depth of the HRU unit, in mm, millimeters, is the maximum time of the gamma distribution, in s, s t is the time step, in s.

[0132] The generation module 73 is used to generate the river network flow of the basin based on the above-mentioned slope flow and use the one-dimensional Saint-Venant equations. The above-mentioned river network flow is used to manage the target basin river network.

[0133] Specifically, river network confluence refers to the process of collecting and calculating the slope confluence flow calculated by each HRU unit along the river channels at each level step by step downstream. The time step of river network confluence is consistent with the time scale of runoff data, generally on an hourly or daily scale. The river network confluence flow is calculated by directly solving the one-dimensional Saint-Venant equations.

[0134] Furthermore, the continuity equation in the Saint-Venant equations is expressed as:

[0135]

[0136] The momentum equation is expressed as:

[0137]

[0138] Where q represents the flow at time t at position x in the river network, in m 3 / s, A represents the cross-sectional area of ​​water flow, unit is m 2 , square meters, v represents the flow velocity, the unit is m / s, meter / second, y represents the river depth, the unit is m, meter, S 0 represents the river gradient, S f represents the friction ratio, g represents the acceleration due to gravity, and is taken as 9.81m / s 2 , x represents the position in the river network.

[0139] Furthermore, the diffusion wave equation is derived through the one-dimensional Saint-Venant equations. The diffusion wave method does not need to calculate the confluence according to the upstream and downstream order of the river sections. It only needs to perform convolution integral on each river section to calculate the confluence of the river section, and then sum up the confluence flow of all river sections to get the confluence flow of the river network in the basin.

[0140] The present invention provides a device for calculating the runoff flow of a river network in a watershed. The device generates runoff depth data by preprocessing the river network data of a target watershed, thereby meeting the runoff calculation requirements for different types of data. The device also generates the runoff flow of a river network in a watershed by using a one-dimensional Saint-Venant equation group, thereby improving the cumbersome process of the previous river network runoff calculation, which can only calculate the runoff flow of the river network in the watershed first and then calculate the runoff flow of a certain section. The device realizes the direct calculation of the river network runoff flow of a certain section, thereby improving the flexibility of the watershed runoff calculation and laying a foundation for the comprehensive management of the target watershed.

[0141] As an optional embodiment of the present invention, the preprocessing module 71 includes:

[0142] The discretization processing submodule is used to judge the type of the above-mentioned target basin river network data. When the type of the above-mentioned target basin river network data is grid river network data, the above-mentioned grid river network data is grid discretized to generate the above-mentioned runoff depth data.

[0143] Specifically, Figure 3 As shown in the figure, the hydrological response unit (HRU) is used as the runoff calculation unit, and the runoff data such as the runoff results of the hydrological model or the runoff results calculated by other methods are directly used as input. The runoff data is discretized in the grid river network, that is, the runoff of each grid in the HRU is superimposed and calculated, and the runoff results of each grid are superimposed and mapped to the HRU where it is located. The runoff of each HRU is calculated and expressed as the runoff depth of the HRU unit, which is recorded as R.

[0144] Furthermore, a grid river network preprocessing script based on languages ​​such as Python (computer programming language) can be developed to identify each HRU in the basin river network and its corresponding grid river network data, so as to realize the rapid calculation of the flow yield of each HRU.

[0145] The superposition submodule is used to superimpose the above-mentioned vector river network data into the hydrological response grid when the type of the above-mentioned target basin river network data is vector river network data, so as to generate the above-mentioned runoff depth data.

[0146] Specifically, when the type of the above-mentioned target river network data is vector river network data, the river network water system topological relationship information of the river basin is determined based on the above-mentioned vector river network data.

[0147] Furthermore, if Figure 4As shown in the figure, the river network relationship in the basin is determined according to the upstream river section information of each river section. By developing a network topology information recognition program, the upstream river section information, upstream HRU information, upstream basin area information, etc. of each river section are identified to determine the topological relationship information of different river sections. The HRU unit is used as the confluence calculation unit, and the river network runoff data is superimposed on the HRU. The runoff of each HRU is calculated and expressed as the runoff depth of the HRU unit, which is recorded as R.

[0148] As an optional implementation of the present invention, the generation module 73 includes:

[0149] A submodule is established for establishing a one-dimensional diffusion wave equation based on the above one-dimensional Saint-Venant equations.

[0150] Specifically, assuming that the river channel is a uniform rectangular steady flow, the momentum equation of the one-dimensional Saint-Venant equations can be written as:

[0151]

[0152] Furthermore, the formula for flow q can be expressed in the form of river flood carrying capacity:

[0153]

[0154] Among them, K c is the flood discharge capacity of the river, and its calculation formula is as follows:

[0155]

[0156] Furthermore, by substituting formula (6) into formula (5), the momentum equation can be written as:

[0157]

[0158] Furthermore, the continuity equation can be written as:

[0159]

[0160] Furthermore, by integrating the continuity equation (9) and the momentum equation (8), we can obtain:

[0161]

[0162] Furthermore, due to K c is a function of A and y, so the second part of formula (10) can be written as:

[0163]

[0164] Furthermore, by substituting formula (11) into formula (10), we can obtain the one-dimensional diffusion wave equation, which can be expressed as:

[0165]

[0166] Among them, C is the wave velocity and D is the diffusion rate.

[0167] The first determination submodule is used to determine the river section runoff flow based on the slope runoff flow using the one-dimensional diffusion wave equation.

[0168] Specifically, the one-dimensional diffusion wave equation is solved by the convolution integral of the confluence of each river section, and then the confluence of all river sections is summed to obtain the discharge at the basin outlet.

[0169] The second determination submodule is used to determine the confluence flow of the river network in the above-mentioned river basin based on the confluence flow of the above-mentioned river section.

[0170] Specifically, the sum of the runoff of all river sections is taken as the runoff of the river network in the basin.

[0171] As an optional implementation manner of the present invention, the first determining submodule includes:

[0172] The first determination unit is used to obtain the water-passing cross-sectional area and determine the wave velocity based on the slope confluence flow and the water-passing cross-sectional area.

[0173] Specifically, the calculation formula of wave speed C is as follows:

[0174]

[0175] Where A represents the water flow cross-sectional area.

[0176] The second determination unit is used to obtain the river channel width and the river channel gradient, and determine the diffusion rate based on the above-mentioned slope confluence flow, the above-mentioned river channel width and the above-mentioned river channel gradient.

[0177] Specifically, the calculation formula of the diffusion coefficient D is as follows:

[0178]

[0179] Where ω is the width of the river.

[0180] The third determination unit is used to obtain the current river channel position and determine the unit line of the river section based on the above-mentioned slope confluence time, the above-mentioned current river channel position, the above-mentioned wave velocity and the above-mentioned diffusion rate.

[0181] Specifically, in a given river section or outlet river section, a set of unique unit lines can be constructed for all river sections according to the distance between the upstream river section and the outlet river section, namely the river section unit line. The calculation formula of the river section unit line h(x,s) is as follows:

[0182]

[0183] Among them, x represents the current river position.

[0184] The fourth determination unit is used to obtain the unit runoff depth and determine the convolution integral of the river section flow based on the above-mentioned river section unit line and the above-mentioned unit runoff depth.

[0185] Specifically, the calculation formula of the convolution integral of the above river section flow is as follows:

[0186]

[0187] Among them, q represents the flow rate of the river section, U(ts) represents the unit runoff depth in the ts period, h(x,s) represents the unit line of the river section, t represents the slope confluence time, and s represents the exit time.

[0188] A solving unit is used to solve the one-dimensional diffusion wave equation based on the convolution integral of the river section confluence to generate the confluence flow of the river section.

[0189] In addition, an embodiment of the present invention further provides an electronic device, such as Figure 8 As shown, the electronic device may include a processor 110 and a memory 120, wherein the processor 110 and the memory 120 may be connected via a bus or in other ways. Figure 8 In the example, the connection through a bus is taken. In addition, the electronic device further includes at least one interface 130, and the at least one interface 130 may be a communication interface or other interface, which is not limited in this embodiment.

[0190] The processor 110 may be a central processing unit (CPU). The processor 110 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0191] The memory 120, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as program instructions / modules corresponding to the video synthesis method in the embodiment of the present invention. The processor 110 executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory 120, that is, to implement a method for calculating the confluence flow of a river network in a watershed in the above method embodiment.

[0192] The memory 120 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and applications required for at least one function; the data storage area may store data created by the processor 110, etc. In addition, the memory 120 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 120 may optionally include a memory remotely arranged relative to the processor 110, and these remote memories may be connected to the processor 110 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0193] In addition, at least one interface 130 is used for communication between the electronic device and external devices, such as communication with a server, etc. Optionally, at least one interface 130 can also be used to connect external input and output devices, such as a keyboard, a display screen, etc.

[0194] The one or more modules are stored in the memory 120 and when executed by the processor 110, perform the following steps: Figure 1 A method for calculating the flow rate of a river network in a basin in the illustrated embodiment.

[0195] For details of the above electronic equipment, please refer to Figure 1 The corresponding related descriptions and effects in the illustrated embodiments can be understood and will not be repeated here.

[0196] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk (HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above-mentioned types of memory.

[0197] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the present invention.

Claims

1. A method for calculating the flow rate of a river network in a basin, characterized in that: include: Acquire river network data of a target watershed, pre-process the river network data of the target watershed, and generate runoff depth data; Based on the runoff depth data, the slope runoff flow is determined by using the unit line method of the two-parameter gamma distribution; Based on the slope runoff, a one-dimensional Saint-Venant equation group is used to generate a river network runoff in a watershed, and the river network runoff in a watershed is used to manage the river network in a target watershed; The method of generating the river network flow rate of a watershed based on the slope flow rate by using the one-dimensional Saint-Venant equations includes: Establishing a one-dimensional diffusion wave equation based on the one-dimensional Saint-Venant equations; Based on the slope runoff, determining the river runoff using the one-dimensional diffusion wave equation; Determine the river network confluence flow of the basin based on the river section confluence flow; The method of determining the river section runoff flow based on the slope runoff flow and using the one-dimensional diffusion wave equation comprises: Acquire a water flow cross-sectional area, and determine a wave velocity based on the slope confluence flow and the water flow cross-sectional area; Acquire the width and gradient of a river channel, and determine the diffusion rate based on the slope runoff, the width and gradient of the river channel; Acquire the current river channel position, and determine the river section unit line based on the slope confluence time, the current river channel position, the wave velocity and the diffusion rate; Obtaining unit runoff depth, and determining a convolution integral of the river section flow based on the river section unit line and the unit runoff depth; The one-dimensional diffusion wave equation is solved based on the convolution integral of the river section flow to generate the river section flow.

2. A method for calculating the flow rate of a river network in a river basin according to claim 1, characterized in that: The preprocessing of the target river basin river network data to generate runoff depth data includes: The type of the target basin river network data is judged, and when the type of the target basin river network data is grid river network data, the grid river network data is subjected to grid discretization processing to generate the runoff depth data; When the type of the target watershed river network data is vector river network data, the vector river network data is superimposed on the hydrological response grid to generate the runoff depth data.

3. A method for calculating the flow rate of a river network in a river basin according to claim 2, characterized in that: The preprocessing of the target basin river network data to generate runoff depth data also includes: When the type of the target river network data of the watershed is vector river network data, the watershed river network water system topological relationship information is determined based on the vector river network data.

4. A method for calculating the flow rate of a river network in a river basin according to claim 3, characterized in that: The method of determining the slope runoff flow rate based on the runoff depth data by using the unit line method of the dual-parameter gamma distribution includes: The unit line of the two-parameter gamma distribution, the time step and the slope confluence time are obtained, and the slope confluence flow is determined based on the confluence runoff depth data, the unit line of the two-parameter gamma distribution, the time step and the slope confluence time.

5. The method for calculating the flow rate of a river network in a river basin according to claim 1, characterized in that: The convolution integral of the river section flow is determined based on the river section unit line and the unit runoff depth. The calculation formula of the convolution integral of the river section flow is as follows: Among them, q represents the confluence flow of the river section, U(ts) represents the unit runoff depth in the ts period, h(x,s) represents the unit line of the river section, t represents the slope confluence time, s represents the exit time, and x represents the current river channel position.

6. A device for calculating the flow rate of a river network in a river basin, characterized in that: include: A preprocessing module is used to obtain the river network data of the target watershed, preprocess the river network data of the target watershed, and generate runoff depth data; A determination module, used for determining the slope runoff flow rate by using a unit line method of a dual-parameter gamma distribution based on the runoff depth data; A generation module, used for generating a river network flow rate of a watershed based on the slope flow rate by using a one-dimensional Saint-Venant equation group, wherein the river network flow rate of the watershed is used for managing the river network of a target watershed; The generating module comprises: Establishing a submodule for establishing a one-dimensional diffusion wave equation based on the one-dimensional Saint-Venant equations; A first determination submodule is used to determine the river section runoff flow based on the slope runoff flow using the one-dimensional diffusion wave equation; The second determination submodule is used to determine the confluence flow of the river network in the basin based on the confluence flow of the river section; The first determining submodule includes: A first determination unit is used to obtain a water-passing cross-sectional area and determine a wave velocity based on the slope confluence flow and the water-passing cross-sectional area; A second determination unit is used to obtain a river channel width and a river channel gradient, and determine a diffusion rate based on the slope confluence flow, the river channel width and the river channel gradient; A third determination unit is used to obtain the current river channel position, and determine the river section unit line based on the slope confluence time, the current river channel position, the wave velocity and the diffusion rate; A fourth determination unit is used to obtain a unit runoff depth, and determine a convolution integral of a river section flow based on the river section unit line and the unit runoff depth; A solving unit is used to solve the one-dimensional diffusion wave equation based on the convolution integral of the river section confluence to generate the river section confluence flow.

7. An electronic device, characterized in that: comprising a processor and a memory, the memory being coupled to the processor; The memory stores computer-readable program instructions, and when the instructions are executed by the processor, the method according to any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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