Recursive calculation method, device and equipment for sediment yield of multi-water-storage-body watershed and storage medium

Abstract

The invention provides a recursive calculation method, device and equipment for the sediment yield of a multi-water-storage-body drainage basin and a storage medium. Relates to the technical field of basin sediment simulation. The method comprises the steps of extracting flow, flow direction grids and water storage body vector points based on drainage basin DEM data and water storage body vector planar data; grid paths are obtained through breadth-first search, vector lines are converted, a communication relation is determined, and a directed graph containing construction age limit and storage capacity attributes is constructed; the method comprises the following steps of: obtaining effective sub-basins after topological sorting, traversing a sorting dictionary, calculating a soil erosion modulus according to a modified general soil loss equation, and recursively simulating the sediment yield of the basin and a transportation process after multi-stage interception in combination with a sediment transportation ratio and capture efficiency to realize refined simulation. Based on DEM and remote sensing data, in combination with a flow direction modeling method, real topological network reconstruction between the ponds is realized, and the problems of pond merging and distortion representation of a traditional model are solved.

Description

Technical Field

[0001] The present application relates to the technical field of watershed sediment simulation, and in particular to a method, device, equipment and storage medium for recursively calculating sediment yield in a watershed with multiple water storage bodies. Background Art

[0002] Water storage bodies (such as ponds and small reservoirs), typical of small-scale agricultural water conservancy projects, are numerous and widely distributed. Water storage bodies not only provide important ecological services by providing irrigation water and reducing pollutants in watersheds, but also significantly intercept sediment, thereby altering downstream sediment transport processes. Furthermore, the amount of sediment accumulated in water storage bodies reflects the amount of sediment produced upstream. However, existing methods for modeling watershed sediment production often ignore or incompletely consider the contribution of water storage bodies to sediment transport and interception. This results in poor sediment prediction in watersheds with multiple water storage bodies, hindering the effective deployment of control measures.

[0003] Existing technologies have the following shortcomings when simulating sediment transport in a basin with multiple water bodies:

[0004] 1. Insufficient representation of the spatial distribution of water storage bodies.

[0005] Limited by the resolution of remote sensing data (such as 30m×30m DEM), and because the area of ​​a single water body is small, existing models (such as SWAT and AnnAGNPS) usually merge water bodies into a single water body or merge them into cultivated land types, losing the detailed distribution information of the water bodies.

[0006] 2. The interception mechanism of water storage bodies is oversimplified.

[0007] Different reservoirs have different sediment interception capacities due to their varying storage capacities and drainage areas. Existing models often use a uniform interception coefficient or fixed interception volume, failing to account for individual differences in reservoirs and resulting in reduced model accuracy.

[0008] 3. There is a lack of description of the cascade interception effect of multiple water bodies.

[0009] Multiple water bodies within a watershed have different spatial connectivity and topological structures. The interception efficiency of downstream water bodies is affected by the residual sediment interception of upstream water bodies. However, existing models generally fail to consider the connectivity of water bodies and their dynamic feedback on sediment transport in the watershed. Summary of the Invention

[0010] This application provides a recursive calculation method, device, equipment, and storage medium for sediment yield in a multi-watershed basin. For distributed watersheds with multiple watersheds, this approach provides a sediment transport simulation scheme that considers the topological connectivity of the watersheds and the cascade interception effects of the watershed networks. This scheme can significantly improve the accuracy of basin sediment yield simulations, providing technical support for optimizing soil and water conservation measures and comprehensive watershed management.

[0011] In a first aspect, the present application provides a method for recursively calculating sediment yield in a multi-water reservoir basin, comprising: Extract flow raster data, flow direction raster data and water storage vector point data based on watershed DEM data and water storage vector surface data; Based on the flow grid data and the water storage body vector point data, a breadth-first search is used to search according to the maximum flow direction in eight directions in the grid, and the grid path from the water storage body point to the outlet is extracted and converted into vector line data; Determining the connectivity relationship of the water storage body based on the vector line data; Using the water storage body vector point data as nodes, connecting them into directed edges in the order of flow direction according to the connectivity relationship of the water storage bodies, constructing a directed graph structure, and adding the water storage body construction year and original storage capacity attributes to the nodes; Topologically sorting the directed graph structure, and obtaining the effective sub-basin range of each water storage body based on the flow direction grid, and writing the effective sub-basin range of each water storage body into a dictionary with topological sorting to obtain a dictionary structure; The dictionary structure is traversed, and the soil erosion modulus of each effective sub-basin is calculated according to the modified general soil loss equation. The amount of sediment entering the water storage body is calculated based on the sediment transport ratio and the soil erosion amount of the effective sub-basin. In combination with the sediment capture efficiency of the water storage body, the amount of sediment input downstream after sediment interception is calculated.

[0012] In one possible design, based on the watershed DEM data, flow raster data, flow direction raster data, and water storage vector point data are extracted, including: Based on the watershed DEM data, the D8 flow direction algorithm is used to extract the flow raster data and flow direction raster; Overlay the flow raster data with the water storage area vector data and extract the largest raster in each water storage area. The largest grid in each water storage area is converted into water storage vector point data, and the maximum flow grid in the watershed is extracted as the outlet.

[0013] In one possible design, determining the connectivity relationship of water storage bodies based on the vector line data includes: The distance from the starting point in the vector line data to the water body vector point data s in the vector line data is traversed, the water body points are sorted in ascending order of distance, and the connection relationship between the water bodies is obtained as the water body connectivity relationship.

[0014] In one possible design, the modified universal soil loss equation is expressed as:

[0015] ;

[0016] Where, is the soil erosion modulus due to hydrodynamics in each unit; is the rainfall erosivity factor; is the soil erodibility factor; is the slope length and slope factor; C is the vegetation cover management factor; P is the soil and water conservation measures factor; The calculation formula for the soil erosion amount in the effective sub-basin is: ; Where, is the amount of soil erosion generated in the effective sub-basin, is the soil erosion modulus of grid cell i; is the area of ​​grid cell i; This is the amount of sediment transported by the upstream pond. If there is no pond upstream, the value is 0.

[0017] In one possible design, the calculation formula for the sediment transport ratio is:

[0018] ;

[0019] Where, is the sediment transport ratio of the sub-basin of the storage body w; 、 is an undetermined coefficient, which depends on the characteristics of the watershed; is the drainage area of ​​the sub-basin.

[0020] In one possible design, the calculation formula for the sediment capture efficiency is:

[0021] ;

[0022] Where, is the sediment capture efficiency of the water storage body w; , is the hydraulic retention time of the water body w, is the current storage capacity of the water storage body; is the average annual cumulative flow at the inlet of the water storage body w; is a constant, usually set to 1.

[0023] In one possible design, the amount of sediment delivered downstream after sediment interception is calculated using the following formula:

[0024] ;

[0025] Where, is the amount of sediment input downstream after sediment interception; is the sediment capture efficiency of the water storage body w; is the sediment transport ratio of the sub-basin of the storage body w; is the effective watershed soil erosion modulus of the water storage body w.

[0026] In a second aspect, the present application provides a device for recursively calculating sediment yield in a multi-water reservoir basin, comprising:

[0027] A target selection module is configured to select an interactive target based on a neighborhood configuration; wherein the neighborhood configuration includes two interactive methods: a buffer-based method and a graph-based method to find neighborhood attributes of the target plot. The neighborhood attributes include the size of the neighborhood radiation range, the number of plots, the radiation intensity, and the interactive influence of the plots.

[0028] a feature extraction module configured to extract features from the interactive target to obtain features of the interactive target; wherein the features of the interactive target include land use categories, spatial variable features, and non-spatial variable features;

[0029] A graph structure construction module is configured to construct a graph structure based on the features of the interaction targets; wherein the graph structure includes edges and nodes, the nodes include the features of the interaction targets, and the edges include adjacency relationships between adjacent interaction targets;

[0030] A network construction module is configured to construct a high-order graph attention network based on the graph structure; wherein, during a training phase of constructing the high-order graph attention network, an updated node feature representation is generated by weighted aggregation of neighboring nodes, the model is optimized using a cross-entropy loss function, and a suitability score of land use change of a plot is output; after the high-order graph attention network is constructed, a self-attention mechanism is introduced through the graph attention network to calculate interaction weights between neighboring nodes to capture spatial heterogeneity and long-range dependencies;

[0031] The extended simulation module is configured to integrate a vector cellular automaton into the high-order graph attention network to obtain an HGAT-VCA model, and implement recursive calculation of sediment yield in multi-water body basins based on the HGAT-VCA model; wherein the vector cellular automaton is used to calculate the overall transition probability and determine the land use type.

[0032] In a third aspect, an embodiment of the present application provides an electronic device comprising: at least one processor and a memory; the memory stores computer-executable instructions; the at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the recursive calculation method for sediment yield in a multi-water body basin as described in the first aspect and various possible designs of the first aspect.

[0033] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores computer-executable instructions. When a processor executes the computer-executable instructions, it implements the recursive calculation method for sediment yield in a multi-water storage basin as described in the first aspect and various possible designs of the first aspect.

[0034] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the recursive calculation method for sediment yield in multiple water storage basins as described in the first aspect and various possible designs of the first aspect.

[0035] Compared with the prior art, this application has the following significant advantages:

[0036] (1) Accurately depict the spatial structure and connectivity of water storage bodies.

[0037] Based on DEM and water storage vector surface data, combined with flow direction modeling methods, the real topological network reconstruction between water storage bodies is realized, solving the problems of traditional models merging water storage bodies and distorted representation.

[0038] (2) Dynamically calculate the interception effect of individual water bodies.

[0039] Taking into account the differentiated storage capacity and catchment area of ​​the water body, the error caused by the unified interception coefficient is avoided and the physical authenticity of the model is improved.

[0040] (3) Realize recursive simulation of sediment transport.

[0041] Based on the network topology, the step-by-step interception and release of sediment in the water storage system is recursively simulated, fully reflecting the regulatory role of the cascade interception effect of the water storage network on the sediment production process in the basin.

[0042] (4) Data input is simple and has a wide range of applications.

[0043] This application offers excellent applicability and simplicity. Simply inputting a digital elevation model (DEM) and surface vector data of water bodies automatically constructs a topological network of relationships between water bodies. Compared to traditional methods, this approach is less dependent on data accuracy and watershed scale. It operates stably in areas with limited data access or low resolution, making it suitable for large-scale, multi-scale watershed sediment yield simulation and management practices. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0045] Figure 1 A flowchart of a recursive calculation method for sediment yield in a multi-water reservoir basin provided in an embodiment of the present application;

[0046] Figure 2 A flowchart of a recursive calculation method for sediment yield in a multi-water reservoir basin provided in an embodiment of the present application;

[0047] Figure 3 Schematic diagram of the directed graph construction provided in the embodiment of the present application; wherein, (a) is relationship 1; (b) is relationship 2; (c) is directed graph G;

[0048] Figure 4 A diagram showing the topological relationship and directed graph construction of sub-basin ponds provided in an embodiment of the present application; wherein: (a) the overall layout of the basin; (b) a zoomed-in view of a specific area; and (c) a topological diagram consisting of nodes and directed edges (lines).

[0049] Figure 5 Schematic diagram of pond topology and sub-basin division provided in the embodiment of the present application; (a) shows how the pond is divided into sub-basins; (b) the sediment transport process affected by the year of pond construction;

[0050] Figure 6 This is a diagram showing the simulation results of the basin's multi-year sediment yield provided in the embodiments of this application;

[0051] Figure 7 A schematic diagram of the structure of a device for recursively calculating sediment yield in a multi-water reservoir basin provided in an embodiment of the present application;

[0052] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0053] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0054] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0055] In the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of information such as financial data, user data or medical image data involved shall comply with the provisions of relevant laws and regulations and shall not violate public order and good morals.

[0056] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0057] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0058] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0059] Example 1:

[0060] This embodiment of the present application provides a recursive calculation method for sediment yield in a watershed with multiple water bodies. It should be noted that the water bodies described herein include, but are not limited to, distributed water storage facilities with sediment interception functions, such as artificial ponds, irrigation ponds, small silt dams, and small reservoirs.

[0061] Figure 1 This is a flow chart of a recursive calculation method for sediment yield in a multi-water reservoir basin provided in an embodiment of the present application. Figure 1 As shown, the recursive calculation method for the sediment yield of a multi-water-storage basin can be implemented based on an electronic terminal, and the recursive calculation method for the sediment yield of a multi-water-storage basin includes the following steps S10 to S60.

[0062] S10: Based on the watershed DEM data and the water storage body vector surface data, the flow raster data, flow direction raster data and water storage body vector point data are extracted.

[0063] In this example, based on the watershed DEM data and the D8 flow direction algorithm from the WhiteboxTools library, the flow_acc and flow_dir rasters are extracted. The flow_acc raster data is overlaid with the pond vector surface data (where pond has two attributes: its original storage capacity, basic_volume, and construction year). The largest raster within each watershed surface is extracted and converted into pond_points, a watershed vector point data. Simultaneously, the outlet raster with the maximum flow rate in the watershed is extracted and converted into max_points, a water outlet vector point data.

[0064] S20: Based on the flow raster data and the water storage body vector point data, a breadth-first search is used to search according to the maximum flow direction in the eight directions in the raster, and the raster path from the water storage body point to the outlet is extracted and converted into vector line data.

[0065] In this embodiment, based on the flow raster data flow_acc generated in S10 and the extracted water storage body vector point data pond_points, a Breadth-First Search (BFS) algorithm is used to search according to the maximum flow direction in the eight directions in the grid, extract the raster path from the water storage body point to the outlet, and convert it into a vector line data stream.

[0066] S30: Determine the connectivity relationship of the water storage body based on the vector line data.

[0067] In this embodiment, the distance from the starting point start_point of the vector line data stream obtained in S20 to the water body vector point data pont_points in the vector line data is traversed, and the water body points are sorted in ascending order of distance to obtain the connection relationships between the water bodies.

[0068] S40: Using the water storage body vector point data as nodes, according to the connectivity relationship of the water storage body, connect them into directed edges in the order of flow direction, build a directed graph structure, and add the water storage body construction year and original storage capacity attributes to the nodes.

[0069] In this embodiment, the water storage body vector point data pond_points is used as a node, and is connected into directed edges in the order of flow direction based on the connection relationship relations obtained in S30, thereby constructing a directed graph structure, and at the same time, the water storage body construction year and original storage capacity attributes are added to the node.

[0070] S50: topologically sorting the directed graph structure, and obtaining the effective sub-basin range of each water storage body based on the flow direction grid, and writing the effective sub-basin range of each water storage body into a dictionary with topological sorting to obtain a dictionary structure.

[0071] In this embodiment, the directed graph is topologically sorted, and based on the flow direction grid flow_dir obtained in S10, the reverse D8 algorithm is used to obtain the effective sub-basin range of each water storage body (the upstream basin part that provides flow or sediment to the current pond), and it is written into a dictionary with topological sorting.

[0072] S60: Traverse the dictionary structure, calculate the soil erosion modulus of each effective sub-basin according to the modified universal soil loss equation, calculate the amount of sediment entering the water storage body according to the sediment transport ratio and the soil erosion amount of the effective sub-basin, and calculate the amount of sediment input downstream after sediment interception based on the sediment capture efficiency of the water storage body.

[0073] In this embodiment, the aforementioned dictionary structure is traversed, and the Revised Universal Soil Loss Equation (RUSLE) is used to calculate the soil erosion modulus for each effective sub-basin. The soil erosion amount is then calculated using the soil erosion calculation formula for the effective sub-basin. The amount of sediment entering the reservoir is then calculated by multiplying the soil erosion amount by the Sediment Delivery Ratio (SDR). This is then combined with the reservoir's Sediment Trapping Efficiency (STE) to calculate the amount of sediment delivered downstream after interception. Specifically, the amount of sediment entering a reservoir multiplied by the reservoir's Sediment Trapping Efficiency (STE) gives the amount of sediment captured by that reservoir. The amount of sediment delivered downstream after interception is calculated by subtracting the amount of sediment captured from the amount of sediment entering the reservoir. In the actual calculation process, the above method is applied to each reservoir, recursively analyzing the sediment yield in the basin after multiple levels of interception by reservoirs within the basin. For example, the amount of sediment input downstream after the current water storage body is intercepted is calculated. When calculating the next water storage body, the amount of soil erosion in the effective sub-basin is calculated based on the amount of sediment input downstream after the current water storage body is intercepted. In this way, recursive calculation can be achieved to obtain the sediment yield in the basin after interception by water storage bodies at all levels.

[0074] In some embodiments, the soil erosion modulus is calculated as:

[0075] ;

[0076] Where:

[0077] is the soil erosion modulus due to water dynamics in each unit, that is, the average erosion rate of soil erosion (t·ha -1 ·a -1 );

[0078] is the rainfall erosivity factor (MJ·mm / (hm 2 ·h·a));

[0079] is the soil erodibility factor (t·hm 2 ·h·hm -2 ·MJ -1 mm -1 );

[0080] is the slope length and slope factor (dimensionless);

[0081] C is the vegetation cover management factor (dimensionless);

[0082] P is the soil and water conservation measure factor (dimensionless).

[0083] In some embodiments, the soil erosion amount of an effective sub-basin is calculated as follows: ; Where, is the amount of soil erosion generated in the effective sub-basin, is the soil erosion modulus of grid cell i; is the area of ​​grid cell i; This is the amount of sediment transported by the upstream pond. If there is no pond upstream, the value is 0.

[0084] In some embodiments, the SDR calculation formula is as follows:

[0085] ;

[0086] Where: is the sediment transport ratio of the sub-basin of the storage body w; 、 is an undetermined coefficient, which depends on the characteristics of the watershed; is the drainage area of ​​the sub-basin (km 2 ).

[0087] In some embodiments, the STE calculation formula is as follows:

[0088] ;

[0089] Where: is the sediment capture efficiency of the water storage body w; , is the hydraulic retention time of the water body w, is the current storage capacity of the water body w (m 3 ), is the annual average cumulative flow at the inlet of the water storage body w (m 3 ), The value is 1.

[0090] In some embodiments, the amount of sediment delivered downstream after sediment interception is calculated as follows: ;

[0091] Where, is the amount of sediment input downstream after sediment interception; is the sediment capture efficiency of the water storage body w; is the sediment transport ratio of the sub-basin of the storage body w; is the effective watershed soil erosion modulus of the water storage body w.

[0092] Example 2:

[0093] The present application embodiment provides a method for recursively calculating the sediment yield of a multi-water reservoir basin. This embodiment uses a pond as an example of a water reservoir. Figure 2 FIG. 1 is a flow chart of a method for recursively calculating sediment yield in a multi-water-storage basin provided by an embodiment of the present application. The method for recursively calculating sediment yield in a multi-water-storage basin includes the following steps S1 to S4.

[0094] S1: Basic dataset construction.

[0095] In this example, the basic dataset includes watershed attribute data and pond attribute data. The watershed data primarily consists of a 5m×5m Digital Elevation Model (DEM), land use data for two time periods (5m×5m), specifically data for the period before and after the 2005 land use boundary, including seven categories: paddy fields, dry land, woodland, grassland, water bodies, urban construction land, and unused land; surface soil texture data from 0 to 20cm depth (90m×90m), including the percentage of silt, sand, clay, and soil organic carbon; and daily rainfall data from 1965 to 2024. The pond attribute data primarily includes surface vector data of the pond, the year of pond construction, and the original reservoir capacity of the pond.

[0096] S2: Construction of topological relationships, including the following steps S201-S204.

[0097] S201: Conversion of pond surface points and identification of watershed outlet points.

[0098] Based on the DEM data, the D8 flow direction algorithm in the WhiteboxTools library was used to extract the corresponding cumulative flow raster, flow_acc, and the flow direction raster, flow_dir. The original reservoir capacity and construction year of the pond surface data were added. By overlaying the flow_acc flow raster data with the pond surface vector data, the largest raster in each pond surface was extracted and converted into pond vector point data, pond_points. The maximum flow raster point in the watershed was also identified and converted into vector point data, max_points.

[0099] S202: Extraction of the path from the pond to the watershed outlet.

[0100] Combining the flow raster data flow_acc from S201, the pond vector point data pond_points, and the outlet vector point data max_points, a breadth-first search (BFS) algorithm is used. A directional lookup table is set up according to the eight directions in the raster. The search continues in the direction of maximum flow and the position (row and column number) is recorded until the watershed outlet is found. The raster path from each pond point to the watershed outlet is extracted and converted into a vector line data stream.

[0101] S203: Construction of directed graph structure.

[0102] First, traverse the runoff data stream extracted in S202, calculate the distance from each pond point on the runoff to the runoff starting point, and sort them in ascending order according to the distance. Thus, a relationship is stored according to the pond number and distance. Figure 3 As shown, it is a schematic diagram of the directed graph construction provided in the embodiment of the present application. Figure 3 In the figure, relationship 1 shows a simple directed chain, with node A pointing to B via a directed edge, and B pointing to C, forming a unidirectional connection relationship of A→B→C. Similarly, relationship 2 is also a directed chain, with node E pointing to B via a directed edge, and B pointing to C, presenting a unidirectional connection of E→B→C. Digraph G is a comprehensive directed graph that integrates the previous two relationships. In this graph, nodes A and E both point to B via directed edges, and B points to C, constructing a directed connection structure in which A and E jointly point to B, and then to C. This clearly demonstrates the convergence of multiple nodes to the same node and the subsequent transitive relationship.

[0103] Then, a directed graph structure is constructed based on the relationship, thereby eliminating duplicate nodes and storing these scattered pond relationships into a complete directed graph. In addition, the nodes in the graph store key information, such as the year of pond construction and original reservoir capacity. In order to clearly present the connectivity characteristics of the pond water system, this example selects a typical sub-basin containing 12 ponds in the basin for visualization. Figure 4 As shown, the sub-basin pond topological relationship and directed graph construction diagram provided in the embodiment of the present application. Figure 4 In the figure, (a) shows the overall layout of the basin, including key elements such as ponds, basin outlets, sub-basin ranges, and basin ranges, and is equipped with pointers and scales to clearly present the geographical distribution of the basin. Sub-basin and basin line map: (b) is a local enlarged map, showing the basin line, ponds and sub-basin ranges in detail, also with pointers and scales, focusing on the distribution of water systems and ponds in the sub-basin. (c) is a topological map composed of nodes and directed edges (lines), which reveals the connection relationship between ponds and reflects the topological structure of the pond network in the basin. It should be noted that Figure 4 The numbers 0-12 in the table refer to the pond numbers.

[0104] S204: Topological sorting and sub-basin division.

[0105] The pond nodes are topologically sorted according to the directed graph structure obtained in S203. That is, according to the in-degree characteristics of the directed graph structure nodes, in-degree refers to the number of edges with a node as the end point in the directed graph. Nodes with in-degree 0 are selected, and the order of ponds at the same level is controlled by their own node numbers. Then, the currently selected node is removed, and the process of iteratively selecting nodes with in-degree 0 is continued, thereby completing the topological sorting of the ponds. Then, based on the sorting results, the reverse D8 algorithm is applied to divide the sub-basins of the ponds. Specifically, if Figure 5 As shown, dividing the sub-basin range requires judging whether there are other ponds upstream of the pond. If so, the basin range where the upstream pond is located is removed.

[0106] S3: Calculate the sediment yield of the basin in that year.

[0107] As shown in Figure 5, when calculating the sediment yield of a watershed, the sediment yield of the effective sub-basin where the upstream pond is located is first calculated. The unsuccessful sediment interception by the pond is then transferred to the effective sub-basin of the downstream pond. Based on the topological sorting results of S2, the process continues iterating until it reaches the watershed outlet, thereby obtaining the overall sediment yield of the watershed. Specifically, step S3 can be implemented through the following steps S301-S305.

[0108] S301: Apply the above topological sorting and effective sub-basin division results to sequentially apply the modified universal soil loss equation (RUSLE) to the basin where the pond is located to calculate the soil erosion amount. The formula is as follows:

[0109] ;

[0110] In the formula, the rainfall erosivity factor is assumed to be consistent across the entire watershed. The soil erodibility factor, slope length and gradient factor, vegetation cover management factor, and soil and water conservation measures factor are the mask results for calculating the sub-watershed where pond w is located. The calculation methods for various factors can refer to the standard method.

[0111] S302: Calculate the soil erosion amount of the effective sub-basin. The formula is as follows: ; Where, is the amount of soil erosion generated in the effective sub-basin, is the soil erosion modulus of grid cell i; is the area of ​​grid cell i; This is the amount of sediment transported by the upstream pond. If there is no pond upstream, the value is 0.

[0112] S303: Calculate the sediment delivery ratio (SDR) of the sub-basin. The formula is as follows: The sediment delivery ratio (SDR) used in the present invention is obtained by calibrating the parameters of 52 basins with observation data ponds based on the method of the present invention. The obtained calculation formula is expressed as follows:

[0113] ;

[0114] In the formula is the effective drainage area of ​​the pond w sub-basin.

[0115] S304: Calculate the capture efficiency of the pond to intercept sediment. Through the current storage capacity and the average annual cumulative flow at the pond inlet To calculate, and the basin is located in Kaizhou District, so the present invention is based on the average water production coefficient of Kaizhou District in the Chongqing Water Resources Bulletin is 0.57 and the annual rainfall depth (m) to calculate. And at the same time record the current storage capacity of the pond affected by siltation in the current year and downstream input The specific calculation formula is as follows:

[0116] ;

[0117] ;

[0118] ;

[0119] ; Where, is the drainage area of ​​the pond sub-basin (m 2 ).

[0120] For the average bulk density of soil , which was calculated by collecting sediment samples from 70 ponds and drying and weighing them. The average soil bulk density of these ponds was then calculated to be 1.15 for easy transfer to other ponds in the basin.

[0121] S305: After continuous iterations, the sediment yield calculation of the basin outlet will be finally performed, that is, the sediment yield of the entire basin. The calculation method is the same as S301~S304.

[0122] S4: Calculate the sediment yield of the watershed over many years.

[0123] Starting from the earliest construction year of the ponds, i.e. 1965, the sediment yield of the basin was simulated for 60 years. This application takes into account the dynamic changes in pond sedimentation, which not only involves annual changes in rainfall and land use, but also introduces a dynamic iterative loop in the sediment yield calculation process to update the pond storage capacity and the corresponding capture efficiency year by year. , thereby calibrating the attenuating impact of pond siltation on basin sediment yield in subsequent years. Specifically, after completing a year's calculations, this method updates the pond's post-siltation storage capacity based on the amount of sediment intercepted by the pond that year, recalibrating the capture efficiency for the next year. This breaks the inherent assumption of constant STE in traditional models and greatly improves the accuracy and reliability of multi-year, long-sequence basin sediment yield simulations.

[0124] like Figure 6 As shown, it is a simulation result diagram of the multi-year sediment yield of the watershed provided in the embodiment of the present application. Figure 6 In the figure, the left vertical axis is annual sediment yield (t), the right vertical axis is cumulative sediment yield (t), and the horizontal axis is year (y), covering the period 1965-2024. The dotted line represents annual sediment yield, which fluctuates and peaks around 1980; the solid line represents cumulative sediment yield, which shows a continuous growth trend. This shows the sediment yield and accumulation in different years in the basin, reflecting the change in sediment yield over time. This example uses the modified general soil loss equation and other methods, combined with pond properties to recursively calculate sediment yield. From the fluctuations in annual sediment yield (the dotted line) and the continuous growth of cumulative sediment yield (the dotted line), it can be seen that it can accurately simulate the sediment production and transport after interception in different years, reflecting the dynamic changes of sediment under multi-stage pond interception within the basin, and effectively simulate the long-term sediment production process in the basin.

[0125] Tables 1 and 2 systematically display the total effective sub-basin erosion, sediment delivery ratio (SDR), sediment input to the pond, sediment capture efficiency (STE), sediment capture by the pond, and the change in pond storage capacity for each of the 462 ponds in the basin over the 60 years from 1965 to 2024. It can be seen that the SDR remains constant over the years because, in this study, SDR is only related to the basin area. Changes in STE are less significant because, as the STE formula indicates, it is related not only to the existing pond storage capacity but also to the average annual cumulative flow at its inlet. Although changes in individual ponds may have a relatively small impact on the basin as a whole, the cumulative effect of these 462 ponds on the basin's sediment yield is significant.

[0126] Table 1 Sediment transport process information of individual ponds in the basin from 1965 to 2000

[0127] Table 2 Sediment transport process information for individual ponds in the basin from 2001 to 2024

[0128] Example 3:

[0129] Figure 7 This is a schematic diagram of the structure of the device for recursively calculating the sediment yield of a multi-water body basin provided by the embodiment of the present application. The embodiment of the present application also provides a device for recursively calculating the sediment yield of a multi-water body basin. Figure 7 As shown, the sediment yield recursive calculation device for a multi-water storage basin includes:

[0130] The data extraction module 701 is configured to extract flow raster data, flow direction raster data and water storage body vector point data based on the watershed DEM data;

[0131] The path extraction module 702 is configured to use a breadth-first search based on the flow raster data and the water body vector point data, searching along the eight directions of maximum flow in the raster, extracting the raster path from the water body point to the outlet, and converting the path into vector line data;

[0132] A connectivity relationship building module 703 is configured to determine a connectivity relationship of a water storage body based on the vector line data;

[0133] The directed graph construction module 704 is configured to use the water storage body vector point data as nodes, connect them into directed edges in the order of flow direction according to the water storage body connectivity, construct a directed graph structure, and add the water storage body construction year and original storage capacity attributes to the nodes;

[0134] A topological sorting module 705 is configured to perform topological sorting on the directed graph structure, obtain the effective sub-basin range of each water storage body based on the flow direction grid, and write the effective sub-basin range of each water storage body into a dictionary with topological sorting to obtain a dictionary structure;

[0135] The recursive calculation module 706 is configured to traverse the dictionary structure, calculate the soil erosion modulus of each effective sub-basin according to the modified universal soil loss equation, calculate the amount of sediment entering the water body according to the sediment transport ratio, and calculate the amount of sediment input downstream after sediment interception based on the sediment capture efficiency of the water body.

[0136] The device for recursively calculating the sediment yield of a multi-water-storage basin provided in the embodiment of the present application can be used to execute the technical solution of the recursive calculation method for the sediment yield of a multi-water-storage basin in the above embodiment. Its implementation principle and technical effects are similar and will not be repeated here.

[0137] Figure 8 This is a schematic diagram of the structure of the electronic device provided in the embodiment of the present application. Figure 8 As shown, the electronic device may include: a processor 801 and a memory 802 , wherein the processor 801 and the memory 802 may communicate with each other; illustratively, the processor 801 and the memory 802 communicate with each other via a communication bus 803 .

[0138] The processor 801 executes the computer-executable instructions stored in the memory 802, so that the processor 801 performs the solution in the above embodiment. The processor 801 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0139] Communication bus 803 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, among others. System buses can be categorized as address buses, data buses, and control buses. For ease of illustration, the figure uses only a single thick line, but this does not imply a single bus or type of bus. Transceivers are used to facilitate communication between the database access device and other computers (e.g., clients, read-write libraries, and read-only libraries). Memory may include random access memory (RAM) and non-volatile memory.

[0140] The electronic device provided in the embodiment of the present application may be the terminal device of the above embodiment.

[0141] An embodiment of the present application also provides a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed on a computer, the computer executes the technical solution of the recursive calculation method for sediment yield in multiple water storage basins of the above embodiment.

[0142] An embodiment of the present application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When at least one processor executes the computer program, it can implement the technical solution of the recursive calculation method for sediment yield in multiple water storage basins in the above embodiment.

[0143] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of modules is only a logical function division. In actual implementation, there may be other division methods, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or module, which can be electrical, mechanical or other forms.

[0144] Modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of these modules may be selected to implement the solution of this embodiment based on actual needs.

[0145] In addition, the functional modules in the various embodiments of the present application may be integrated into a single processing unit, or each module may exist physically separately, or two or more modules may be integrated into a single unit. The above-mentioned modules may be implemented in the form of hardware or hardware plus software functional units.

[0146] The integrated modules implemented in the form of software function modules can be stored in a computer-readable storage medium. The software function modules stored in a storage medium include a number of instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute some of the steps of the methods of various embodiments of the present application.

[0147] It should be understood that the processor described above may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules within the processor.

[0148] The memory may include a high-speed RAM memory, and may also include non-volatile storage NVM, such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a magnetic disk or an optical disk.

[0149] A bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be categorized as address buses, data buses, and control buses. For ease of illustration, the buses in the drawings of this application are not limited to just one bus or just one type of bus.

[0150] The storage medium may be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium may be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0151] An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic control unit or a main control device.

[0152] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0153] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application 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 replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A recursive calculation method for sediment yield in a multi-water storage basin, characterized in that: include: Extract flow raster data, flow direction raster data and water storage vector point data based on watershed DEM data and water storage vector surface data; Based on the flow grid data and the water storage body vector point data, a breadth-first search is used to search according to the maximum flow direction in eight directions in the grid, and the grid path from the water storage body point to the outlet is extracted and converted into vector line data; Determining the connectivity relationship of the water storage body based on the vector line data; Using the water storage body vector point data as nodes, connecting them into directed edges in the order of flow direction according to the connectivity relationship of the water storage bodies, constructing a directed graph structure, and adding the water storage body construction year and original storage capacity attributes to the nodes; Topologically sorting the directed graph structure, and obtaining the effective sub-basin range of each water storage body based on the flow direction grid, and writing the effective sub-basin range of each water storage body into a dictionary with topological sorting to obtain a dictionary structure; The dictionary structure is traversed, and the soil erosion modulus of each effective sub-basin is calculated according to the modified general soil loss equation. The amount of sediment entering the water storage body is calculated based on the sediment transport ratio and the soil erosion amount of the effective sub-basin. In combination with the sediment capture efficiency of the water storage body, the amount of sediment input downstream after sediment interception is calculated.

2. The method according to claim 1, characterized in that Based on the watershed DEM data, flow raster data, flow direction raster data, and water storage vector point data are extracted, including: Based on the watershed DEM data, the D8 flow direction algorithm is used to extract the flow raster data and flow direction raster; Overlay the flow raster data with the water storage area vector data and extract the largest raster in each water storage area. The largest grid in each water storage area is converted into water storage vector point data, and the maximum flow grid in the watershed is extracted as the outlet.

3. The method according to claim 1, characterized in that Determining the connectivity relationship of the water storage bodies based on the vector line data includes: The distance from the starting point in the vector line data to the water body vector point data s in the vector line data is traversed, the water body points are sorted in ascending order of distance, and the connection relationship between the water bodies is obtained as the water body connectivity relationship.

4. The method according to claim 1, wherein The modified universal soil loss equation is expressed as: ； Where, is the soil erosion modulus due to hydrodynamics in each unit; is the rainfall erosivity factor; is the soil erodibility factor; is the slope length and slope factor; C is the vegetation cover management factor; P is the soil and water conservation measures factor; The calculation formula for the soil erosion amount in the effective sub-basin is: ； Where, is the amount of soil erosion generated in the effective sub-basin, is the soil erosion modulus of grid cell i; is the area of ​​grid cell i; This is the amount of sediment transported by the upstream pond. If there is no pond upstream, the value is 0.

5. The method according to claim 1, wherein The calculation formula of the sediment transport ratio is: ； Where, is the sediment transport ratio of the w sub-basin of the storage body; 、 is an undetermined coefficient, which depends on the characteristics of the watershed; is the drainage area of ​​the sub-basin.

6. The method according to claim 1, characterized in that The calculation formula for the sediment capture efficiency is: ； Where, is the sediment capture efficiency of the water storage body w; , is the hydraulic retention time of the water body w, is the current storage capacity of the water storage body; is the average annual cumulative flow at the inlet of the water storage body w; is a constant, usually set to 1.

7. The method according to claim 4, characterized in that The amount of sediment delivered downstream after sediment interception is calculated using the following formula: ； Where, is the amount of sediment input downstream after sediment interception; is the sediment capture efficiency of the water storage body w; is the sediment transport ratio of the w sub-basin of the storage body; is the effective watershed soil erosion modulus of the water storage body w.

8. A recursive calculation device for sediment yield based on multiple water storage basins, characterized in that: include: A data extraction module is configured to extract flow raster data, flow direction raster data, and water storage body vector point data based on the watershed DEM data and the water storage body vector surface data; A path extraction module is configured to use a breadth-first search based on the flow raster data and the water storage body vector point data, search according to the maximum flow direction in eight directions in the raster, extract the raster path from the water storage body point to the outlet, and convert it into vector line data; a connectivity relationship building module configured to determine a connectivity relationship of a water storage body based on the vector line data; a directed graph construction module configured to use the water storage body vector point data as nodes, connect them into directed edges in a flow order according to the connectivity relationship of the water storage bodies, construct a directed graph structure, and add the water storage body construction age and original storage capacity attributes to the nodes; a topological sorting module configured to perform topological sorting on the directed graph structure, obtain the effective sub-basin range of each water storage body based on the flow direction grid, and write the effective sub-basin range of each water storage body into a dictionary with topological sorting to obtain a dictionary structure; The recursive calculation module is configured to traverse the dictionary structure, calculate the soil erosion modulus of each effective sub-basin according to the modified universal soil loss equation, calculate the amount of sediment entering the water storage body according to the sediment transport ratio, and calculate the amount of sediment input downstream after sediment interception based on the sediment capture efficiency of the water storage body.

9. An electronic device, characterized in that: include: a processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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