Multi-model coupling calculation method and system based on basic section topological benchmark

Abstract

The invention discloses a multi-model coupling calculation method and system based on a basic section topological benchmark. The method comprises the following steps: acquiring basic section data corresponding to a target watershed and calculation unit data divided by each heterogeneous hydrological model; constructing a composite topological structure according to the basic section data and the calculation unit data, wherein the composite topological structure is used for representing a 1: N dynamic mapping relation between a single basic section and each calculation unit; and performing hierarchical topological sorting based on the composite topological structure, and generating a flood control scheduling result corresponding to the target drainage basin. According to the method, the unified topology reference is established, so that data coupling deviation caused by division standard difference is eliminated; a calculation path planning algorithm based on hierarchical topological sorting is designed, and the scheduling efficiency bottleneck under a composite topological structure is broken through; a'basic section-calculation unit 'dynamic control relation model is innovatively provided, automatic scheduling time sequence judgment of a non-basic section calculation unit is achieved through a downstream section inheritance mechanism, and manual intervention dependence is eliminated.

Description

Technical Field

[0001] The present application relates to the field of coupled calculation of watershed hydrological models, and in particular to a multi-model coupled calculation method and system based on a basic section topology benchmark. Background Art

[0002] With the increasing demand for multi-model coupled computing in river basin water forecasting and flood control scheduling, the topological coupling mechanism of heterogeneous models in existing technologies urgently needs to be optimized. Currently, the field of coupled computing technology for river basin hydrological models generally has the following technical limitations:

[0003] 1. Heterogeneity of existing model partitioning mechanisms

[0004] In traditional hydrological modeling, different mechanism models employ different spatial discretization criteria. For example, the three typical hydrological models employed in the Huaihe River Basin exhibit significant differences in their unit divisions: the spatiotemporal variable source model divides 16 computational units based on key nodes and basin area characteristics, the Xin'an River model constructs 54 computational units based on the distribution of monitoring sections, and the hydrodynamic model uses 15 computational units based on the distribution of flood storage and detention areas. This multi-criteria division results in significant heterogeneity in the computational units of each model in terms of spatial granularity and topological connectivity, making it difficult to establish a unified scheduling benchmark.

[0005] 2. Technical bottlenecks in cross-model coupling calculations

[0006] Existing technologies usually use the following two methods to handle multi-model hybrid computing: (1) performing serial computing by manually presetting priorities, which leads to rigid scheduling logic; (2) using a single topological sorting algorithm to handle complex association relationships, which cannot adapt to multi-level topological structures.

[0007] Both methods have problems such as redundant computing paths and incomplete processing of upstream and downstream dependencies, making it difficult to meet the real-time requirements of minute-level scheduling response.

[0008] 3. Deficiencies in the cross-sectional correlation mechanism

[0009] The cross-section control strategy used in traditional methods has two major flaws: (1) the cross-section-to-computational unit mapping relationship is too constrained (1:1 rigid binding); and (2) there is a lack of a dynamic inheritance mechanism, which means that downstream cross-sections cannot effectively control upstream units of unfounded cross-sections. This leads to control blind spots in the topological network in complex watershed scenarios, affecting the convergence of the calculation results.

[0010] Although current mainstream technical solutions have made progress in single model optimization, they have not solved the following core problems:

[0011] (1) Normalized mapping method for spatial discrete standard of multi-model computational units;

[0012] (2) Dynamic scheduling order generation mechanism under composite topology;

[0013] (3) Adaptive inheritance algorithm of section control relationship.

[0014] Therefore, the existing technology has technical problems such as low computational efficiency (typical scenarios take >30 minutes) and inaccurate topological relationship processing in cross-model coupling calculations, which makes it difficult to meet the needs of smart water conservancy systems for real-time basin scheduling.

[0015] The content of this background technology description is only for facilitating understanding of the relevant technology in this field and is not regarded as an admission of the prior art. Summary of the Invention

[0016] In order to solve the above technical problems, this application provides a multi-model coupling calculation method and system based on the basic cross-section topology benchmark. The specific solution is as follows:

[0017] In a first aspect, an embodiment of the present application provides a multi-model coupling calculation method based on a basic cross-section topology benchmark, the multi-model coupling calculation method based on a basic cross-section topology benchmark comprising:

[0018] Obtain the basic cross-section data corresponding to the target watershed and the calculation unit data divided by each heterogeneous hydrological model;

[0019] Constructing a composite topology structure based on the basic section data and the computing unit data, wherein the composite topology structure is used to characterize the upstream and downstream dependency relationship of each basic section, the upstream and downstream sequence relationship between each computing unit, and the 1:N dynamic mapping relationship between a single basic section and each computing unit, where N is a non-negative integer;

[0020] Performing hierarchical topological sorting based on the composite topological structure to generate a flood control dispatch result corresponding to the target watershed;

[0021] The flood control dispatching result is output to the flood control dispatching decision-making system.

[0022] According to a specific embodiment disclosed in the present application, the step of constructing a composite topological structure based on the basic cross-section data and the calculation unit data includes:

[0023] generating a directed acyclic graph according to the basic cross-section data and the calculation unit data;

[0024] topologically sorting the directed acyclic graph using a preset topological sorting algorithm so that the directed acyclic graph after topological sorting has no loops and conforms to the hydrological conduction order, wherein the preset topological sorting algorithm includes a Kahn algorithm;

[0025] Based on the preset association relationship between each basic section and each calculation unit, a dynamic mapping relationship of 1:N is established between a single basic section and each calculation unit, wherein the basic section and the calculation unit are in a control-controlled relationship;

[0026] A composite topological structure is constructed based on the directed acyclic graph after the topological sorting and the dynamic mapping relationship.

[0027] According to a specific embodiment disclosed in the present application, based on the preset association relationship between each basic section and each calculation unit, the steps of establishing a 1:N dynamic mapping relationship between a single basic section and each calculation unit include:

[0028] Obtaining a preset association relationship between each of the basic sections and each of the calculation units;

[0029] Determining whether a single basic section controls at least one upstream computing unit according to the preset association relationship;

[0030] If so, establishing a first mapping relationship between the basic section and at least one upstream computing unit controlled by it;

[0031] If not, the empty cell is recursively traced back to the nearest basic section through the downstream inheritance mechanism, and a second mapping relationship is established between the basic section and the empty cell, wherein the empty cell is a calculation cell that has no directly associated basic section;

[0032] The first mapping relationship and the second mapping relationship are integrated into a 1:N dynamic mapping relationship between a single basic section and each computing unit.

[0033] According to a specific embodiment disclosed in the present application, the step of performing hierarchical topological sorting based on the composite topological structure to generate a flood control scheduling result corresponding to the target basin includes:

[0034] Grouping and aggregating the computing units based on the composite topological structure to obtain a plurality of aggregation groups, wherein any of the aggregation groups includes a computing unit and a basic section associated with the computing unit;

[0035] Performing inter-group sorting and intra-group sorting on each of the aggregation groups to obtain a hierarchical topological sorting result, wherein the inter-group sorting is to sort the aggregation groups in reverse order according to the maximum position of the basic section in the aggregation group, and the intra-group sorting is to sort according to the upstream and downstream dependency relationship of each basic section in the aggregation group;

[0036] The hierarchical topological sorting result is determined as the flood control scheduling result corresponding to the target watershed.

[0037] According to a specific embodiment disclosed in the present application, the composite topology structure is a basic section-computational unit association matrix architecture, and the multi-model coupling calculation method based on the basic section topology benchmark further includes:

[0038] Monitoring whether the heterogeneous hydrological model corresponding to the target watershed has changed;

[0039] If the heterogeneous hydrological model corresponding to the target watershed changes, the real-time basic section data corresponding to the target watershed and the real-time calculation unit data divided by each heterogeneous hydrological model are connected, and the dynamic access and coupling calculation of multi-model calculation units are realized through the dynamic expansion technology of matrix dimensions.

[0040] In a second aspect, an embodiment of the present application provides a multi-model coupling computing system based on a basic section topology benchmark, for implementing the multi-model coupling computing method based on a basic section topology benchmark described in any one of the first aspects, wherein the multi-model coupling computing system based on a basic section topology benchmark includes a data acquisition layer, a topology modeling layer, a scheduling engine layer, and an application layer;

[0041] The data acquisition layer is used to obtain the basic cross-section data corresponding to the target watershed and the calculation unit data divided by each heterogeneous hydrological model;

[0042] The topology modeling layer is used to construct a composite topology structure based on the basic section data and the computing unit data, wherein the composite topology structure is used to characterize the upstream and downstream dependency relationship of each basic section, the upstream and downstream sequence relationship between each computing unit, and the 1:N dynamic mapping relationship between a single basic section and each computing unit, where N is a non-negative integer;

[0043] The scheduling engine layer is used to perform hierarchical topological sorting based on the composite topological structure to generate a flood control scheduling result corresponding to the target basin;

[0044] The application layer is used to output the flood control scheduling result to an external flood control scheduling decision system.

[0045] According to a specific embodiment disclosed in this application, the topology modeling layer is further used to:

[0046] generating a directed acyclic graph according to the basic cross-section data and the calculation unit data;

[0047] topologically sorting the directed acyclic graph using a preset topological sorting algorithm so that the directed acyclic graph after topological sorting has no loops and conforms to the hydrological conduction order, wherein the preset topological sorting algorithm includes a Kahn algorithm;

[0048] Based on the preset association relationship between each basic section and each calculation unit, a dynamic mapping relationship of 1:N is established between a single basic section and each calculation unit, wherein the basic section and the calculation unit are in a control-controlled relationship;

[0049] A composite topological structure is constructed based on the directed acyclic graph after the topological sorting and the dynamic mapping relationship.

[0050] According to a specific embodiment disclosed in this application, the scheduling engine layer is further used to:

[0051] Grouping and aggregating the computing units based on the composite topological structure to obtain a plurality of aggregation groups, wherein any of the aggregation groups includes a computing unit and a basic section associated with the computing unit;

[0052] Performing inter-group sorting and intra-group sorting on each of the aggregation groups to obtain a hierarchical topological sorting result, wherein the inter-group sorting is to sort the aggregation groups in reverse order according to the maximum position of the basic section in the aggregation group, and the intra-group sorting is to sort according to the upstream and downstream dependency relationship of each basic section in the aggregation group;

[0053] The hierarchical topological sorting result is determined as the flood control scheduling result corresponding to the target watershed.

[0054] In a third aspect, an embodiment of the present application provides a computer device, comprising a memory and a processing device, wherein the memory stores a computer program, and when the computer program is executed on the processor, the multi-model coupling calculation method based on the basic section topology benchmark described in any one of the first aspects is implemented, and the multi-model coupling calculation system based on the basic section topology benchmark described in any one of the second aspects is loaded on the processing device.

[0055] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed on a processing device, it implements the multi-model coupling calculation method based on the basic section topology benchmark described in any embodiment of the second aspect.

[0056] Compared with the prior art, this application has the following beneficial effects:

[0057] This application discloses a multi-model coupling calculation method and system based on a basic section topology benchmark, specifically including: obtaining basic section data corresponding to the target watershed and calculation unit data divided by various heterogeneous hydrological models; constructing a composite topology structure based on the basic section data and calculation unit data, the composite topology structure being used to characterize the 1:N dynamic mapping relationship between a single basic section and each calculation unit; performing hierarchical topological sorting based on the composite topology structure to generate flood control scheduling results corresponding to the target watershed. This application eliminates data coupling deviations caused by differences in division standards by establishing a unified topology benchmark; designs a calculation path planning algorithm based on hierarchical topological sorting to break through the scheduling efficiency bottleneck under the composite topology structure; and innovatively proposes a "section-unit" dynamic control relationship model to achieve automated scheduling timing determination for calculation units without basic sections through a downstream section inheritance mechanism, eliminating reliance on manual intervention. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0059] Figure 1 A schematic flow chart of a multi-model coupling calculation method based on a basic cross-section topology benchmark provided in an embodiment of the present application;

[0060] Figure 2 A schematic diagram of the control relationship between the basic section and the calculation unit involved in the multi-model coupling calculation method based on the basic section topology benchmark provided in an embodiment of the present application;

[0061] Figure 3 A schematic diagram of the empty cell processing mechanism involved in the multi-model coupling calculation method based on the basic cross-section topology benchmark provided in an embodiment of the present application;

[0062] Figure 4 One of the schematic diagrams of the composition of the multi-model coupling calculation system based on the basic cross-section topology benchmark provided in an embodiment of the present application;

[0063] Figure 5 The second schematic diagram of the composition of the multi-model coupling calculation system based on the basic cross-section topology benchmark provided in the embodiment of the present application;

[0064] Figure 6 This is a schematic diagram of an exemplary structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0065] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments.

[0066] The components of the embodiments of the present application generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed application, but rather merely represents selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative effort are within the scope of protection of the present application.

[0067] Hereinafter, the terms "including", "having" and their cognates, which may be used in various embodiments of the present application, are intended only to indicate specific features, numbers, steps, operations, elements, components or combinations of the foregoing items, and should not be understood as first excluding the existence of one or more other features, numbers, steps, operations, elements, components or combinations of the foregoing items or the possibility of adding one or more features, numbers, steps, operations, elements, components or combinations of the foregoing items.

[0068] Furthermore, the terms “first,” “second,” “third,” etc., are merely used for distinguishing descriptions and are not to be understood as indicating or implying relative importance.

[0069] Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by those skilled in the art to which the various embodiments of the present application belong. The terms (such as those defined in generally used dictionaries) will be interpreted as having the same meaning as in the context of the relevant technical field and will not be interpreted as having an idealized meaning or an overly formal meaning unless clearly defined in the various embodiments of the present application.

[0070] See also Figure 1 , Figure 1 Schematic diagram of the process of the multi-model coupling calculation method based on the basic cross-section topology benchmark provided in the embodiment of the present application. Figure 1 As shown, the multi-model coupling calculation method based on the basic cross-section topology benchmark mainly includes:

[0071] Step S101: Obtain basic cross-section data corresponding to the target watershed and calculation unit data divided by various heterogeneous hydrological models.

[0072] During specific implementation, the target basin refers to the specific basin that the user expects to analyze in a specific application scenario. The basic section is a hydrological section, which refers to a section perpendicular to the average flow direction of the water flow. The elevation of the water surface on the basic section is the water level, and the volume of water flowing through the section per second is the flow rate. The specific location of the basic section is generally set in an area where the river channel is straight, the water flow is relatively stable, and there are no diversion ditches nearby, which can keep the water level and flow rate in a relatively stable relationship. The calculation unit data of the heterogeneous hydrological model division refers to the division results of the calculation units of each model, such as the 16 calculation units of the spatiotemporal variable source model mentioned in the background technology, the 54 calculation units of the Xin'anjiang model, and the 14 calculation units of the hydrodynamic model.

[0073] Step S102, constructing a composite topological structure based on the basic section data and the computing unit data, wherein the composite topological structure is used to characterize the upstream and downstream dependency relationship of each basic section, the upstream and downstream sequence relationship between each computing unit, and the 1:N dynamic mapping relationship between a single basic section and each computing unit, where N is a non-negative integer.

[0074] See also Figure 2 , Figure 2 Schematic diagram of the control relationship between the basic section and the calculation unit involved in the multi-model coupling calculation method based on the basic section topology benchmark provided in the embodiment of the present application. Figure 2 As shown:

[0075] (1) Hierarchical structure

[0076] Basic section topology: It consists of several key monitoring basic sections, reflecting the actual upstream and downstream relationship of the river (such as section 1 → section 2);

[0077] Computational unit topology: It is composed of hydrological computational units, and virtual connecting lines / arrows between computational units indicate the computational dependency direction (e.g., unit A → unit B).

[0078] (2) Control relationship

[0079] The basic section points to the calculation unit it controls through the dotted arrow (such as section 1 control unit A). It should be emphasized that each calculation unit can be controlled by multiple basic sections, and a basic section can also control multiple upstream calculation units.

[0080] (3) Typical examples

[0081] Calculation unit B: is directly controlled by basic section 2 and receives the output data of calculation unit A at the same time.

[0082] The step of constructing a composite topological structure according to the basic section data and the calculation unit data includes:

[0083] generating a directed acyclic graph according to the basic cross-section data and the calculation unit data;

[0084] topologically sorting the directed acyclic graph using a preset topological sorting algorithm so that the directed acyclic graph after topological sorting has no loops and conforms to the hydrological conduction order, wherein the preset topological sorting algorithm includes a Kahn algorithm;

[0085] Based on the preset association relationship between each basic section and each calculation unit, a dynamic mapping relationship of 1:N is established between a single basic section and each calculation unit, wherein the basic section and the calculation unit are in a control-controlled relationship;

[0086] A composite topological structure is constructed based on the directed acyclic graph after the topological sorting and the dynamic mapping relationship.

[0087] During specific implementation, a directed acyclic graph (DAG) is generated based on river channel GIS data such as basic section data and the calculation unit data, and an adjacency list can be used to store the upstream and downstream relationships of the basic sections.

[0088] In graph theory, a directed graph is a directed acyclic graph if there are no edges from any vertex that can be returned to that vertex. A directed graph is one in which each edge carries a direction from one vertex to another. A path in a directed graph is a series of edges where each edge ends at the same point as the next; if the starting point of a path is also the end point of the path, then the path is a cycle. A directed acyclic graph is a directed graph without cycles.

[0089] Furthermore, based on the preset association relationship between each basic section and each calculation unit, the step of establishing a 1:N dynamic mapping relationship between a single basic section and each calculation unit includes:

[0090] Obtaining a preset association relationship between each of the basic sections and each of the calculation units;

[0091] Determining whether a single basic section controls at least one upstream computing unit according to the preset association relationship;

[0092] If so, establishing a first mapping relationship between the basic section and at least one upstream computing unit controlled by it;

[0093] If not, the empty cell is recursively traced back to the nearest basic section through the downstream inheritance mechanism, and a second mapping relationship is established between the basic section and the empty cell, wherein the empty cell is a calculation cell that has no directly associated basic section;

[0094] The first mapping relationship and the second mapping relationship are integrated into a 1:N dynamic mapping relationship between a single basic section and each computing unit.

[0095] In specific implementation, the dynamic mapping relationship between a single basic section and each calculation unit is 1:N, which includes two cases:

[0096] (1) A single basic section controls multiple upstream computing units;

[0097] (2) The calculation unit has no directly associated section.

[0098] In this case, for the second case, it is necessary to recursively trace back to the nearest calculation unit containing the basic section through the downstream inheritance mechanism. Figure 3 , Figure 3 Schematic diagram of the empty cell processing mechanism involved in the multi-model coupling calculation method based on the basic cross-section topology benchmark provided in the embodiment of this application. Figure 3 As shown in the figure, the calculation unit X has no directly associated basic section, that is, "empty unit X". The processing steps are as follows:

[0099] Sub-step a: Identify the empty cell X and obtain a list of all its direct downstream computational cells;

[0100] Sub-step b: Breadth-first traverse the downstream computational units until the first computational unit Y associated with the base section is found;

[0101] Sub-step c: Establish a virtual control link from calculation unit X to calculation unit Y, and the basic cross-section data associated with calculation unit Y will be used as input to calculation unit X.

[0102] Step S103: performing hierarchical topological sorting based on the composite topological structure to generate a flood control dispatch result corresponding to the target watershed.

[0103] In view of the characteristics of scheduling systems with complex topologies, this application innovatively adopts the Hierarchical Dependency Topological Sorting (HDTS) algorithm in this technical field, fully combining multi-level dependencies with group sorting strategies to enhance topology. This algorithm has the following characteristics:

[0104] (1) Two-level topological sorting (basic section topology + computational unit topology);

[0105] (2) Many-to-many relationship processing;

[0106] (3) Hybrid sort index generation;

[0107] The steps of performing hierarchical topological sorting based on the composite topological structure to generate a flood control dispatch result corresponding to the target basin include:

[0108] Grouping and aggregating the computing units based on the composite topological structure to obtain a plurality of aggregation groups, wherein any of the aggregation groups includes a computing unit and a basic section associated with the computing unit;

[0109] Performing inter-group sorting and intra-group sorting on each of the aggregation groups to obtain a hierarchical topological sorting result, wherein the inter-group sorting is to sort the aggregation groups in reverse order according to the maximum position of the basic section in the aggregation group, and the intra-group sorting is to sort according to the upstream and downstream dependency relationship of each basic section in the aggregation group;

[0110] The hierarchical topological sorting result is determined as the flood control scheduling result corresponding to the target watershed.

[0111] In specific implementation, the step of performing hierarchical topological sorting based on the composite topological structure to generate the flood control dispatch result corresponding to the target basin can be divided into the following sub-steps:

[0112] (1) Unit grouping aggregation

[0113] Each computing unit needs to process its associated basic sections. If the computing unit directly manages basic sections, it will be directly added to the aggregation group corresponding to the computing unit. If the computing unit has no directly associated basic sections, it will recursively collect all basic sections of downstream computing units.

[0114] Example: The downstream of calculation unit X is calculation unit Y (associated basic section C), then the aggregation group corresponding to calculation unit X includes the associated basic section C of calculation unit Y.

[0115] (2) Merge sort strategy

[0116] a. Sorting between groups: sort by the maximum cross-section position of the aggregation group in reverse order, i.e. the one with the larger number takes priority. For example: if the maximum position of aggregation group A is 3 and that of aggregation group B is 5, then aggregation group B is sorted before aggregation group A;

[0117] b. Sorting within a group: The original order of sections is maintained within the aggregation group. Example: Aggregation group B contains basic sections B (sequence number 1) and C (sequence number 2), then the order is basic section B → basic section C;

[0118] In specific applications, if an error is detected in the final generated ring topology, an alarm can be triggered. For example, a loop of basic section A → basic section B → basic section A is formed. At this time, manual intervention can be introduced to correct the data. No specific restrictions are made here.

[0119] The key design ideas of this part mainly include:

[0120] (1) Dependency guarantee: topological sorting is used to ensure that the execution order does not destroy the upstream and downstream relationships;

[0121] (2) Group aggregation: The calculation unit may affect the downstream basic section and needs to be merged;

[0122] (3) Efficient scheduling: Sort by the maximum position of the aggregation group, giving priority to the aggregation group with the largest impact range;

[0123] Furthermore, the above process steps can be compared to logistics sorting to facilitate understanding of the overall technical solution:

[0124] (1) Package classification (equivalent to basic cross-section topological sorting): sort packages by distance to the destination;

[0125] (2) Truck marshaling (calculation unit grouping): Each truck is responsible for a specific area. If there is no cargo in this area, it will load the cargo of the downstream truck;

[0126] (3) Departure order (combined order): Trucks destined for the farthest station will be given priority, and packages in the same truck will be loaded in the original order.

[0127] Executing in the above order can not only satisfy upstream and downstream dependencies, but also optimize resource scheduling efficiency.

[0128] Step S104: output the flood control dispatch result to a flood control dispatch decision system.

[0129] The composite topology structure is a basic section-computational unit association matrix architecture, and the multi-model coupling calculation method based on the basic section topology benchmark further includes:

[0130] Monitoring whether the heterogeneous hydrological model corresponding to the target watershed has changed;

[0131] If the heterogeneous hydrological model corresponding to the target watershed changes, the real-time basic section data corresponding to the target watershed and the real-time calculation unit data divided by each heterogeneous hydrological model are connected, and the dynamic access and coupling calculation of multi-model calculation units are realized through the dynamic expansion technology of matrix dimensions.

[0132] Specifically, the composite topology structure adopted in this application is the basic section-computational unit association matrix architecture. Based on the scalability of the matrix, the dynamic access and coupling calculation of multi-model computing units are realized through the dynamic expansion technology of the matrix dimension, supporting the plug-and-play expansion of the basin-level model.

[0133] The key points and protection points of this application are summarized as follows:

[0134] (1) Basic cross-section bidirectional topology database construction technology

[0135] Technical Description: An innovative cross-section data structure with bidirectional topological constraints is designed to map the unit division standards of heterogeneous models into a unified topological benchmark, enabling adaptive matching of spatial topological relationships between computing units across models.

[0136] Protection points: A topological data modeling method based on the dynamic configuration of key sections in the watershed.

[0137] (2) Hierarchical topological sorting scheduling algorithm

[0138] Technical Description: This paper proposes a hierarchical decomposition algorithm for composite directed graphs. By dynamically partitioning the topology layers and generating parallel computation paths, it overcomes the computational redundancy problem of traditional serial sorting and achieves minute-level computational response under composite topological structures.

[0139] Protection Point: A hierarchical scheduling approach based on a composite topology network, including a dynamic priority adjustment strategy.

[0140] (3) Basic section-calculation unit dynamic control relationship model

[0141] Technical Description: Establish a "1:N" dynamic control association model, realize the automatic scheduling control of foundationless section units through the downstream section inheritance mechanism, and support dynamic reconstruction and fault tolerance of topological relationships between cross-model units;

[0142] Protection point: Topology control logic based on downstream inheritance, including abnormal unit backtracking mechanism.

[0143] (4) Section correlation matrix architecture

[0144] Technical Description: Design an extensible cross-section correlation matrix, and achieve dynamic access and coupling calculation of multiple model calculation units through dynamic matrix dimension expansion technology, supporting plug-and-play expansion of basin-level models;

[0145] Protection points: dimension mapping method of correlation matrix and matrix operation acceleration mechanism.

[0146] (5) Inherited topology control mechanism

[0147] Technical Description: This paper proposes an inheritance control algorithm based on topological paths, dynamically adjusts the control priority of non-section units, and ensures scheduling timing consistency in complex networks.

[0148] Protection point: inherits the dynamic optimization method of the control link.

[0149] This application innovatively proposes a multi-model coupling calculation architecture based on the basic section topology benchmark. By establishing a basic section database with bidirectional topological constraints, the section-unit association matrix is used to realize the intelligent mapping of cross-model calculation units. Among them, a "1:N" dynamic control relationship is constructed between the basic section and the calculation unit: a single basic section can belong to the only calculation unit of a specific model, and at the same time, the topological control of the non-section unit is realized through the downstream section inheritance mechanism. This architecture, combined with the hierarchical topological sorting algorithm, effectively solves the calculation path optimization problem under the composite topology network, and improves the efficiency of multi-model coupling calculation to the minute-level response level.

[0150] Corresponding to the above method embodiment, see Figure 4 and Figure 5 , Figure 4 This is one of the schematic diagrams of the composition of the multi-model coupling calculation system based on the basic cross-section topology benchmark provided in the embodiment of the present application. Figure 5 The second schematic diagram of the composition of the multi-model coupling calculation system based on the basic cross-section topology benchmark provided in the embodiment of the present application. Figure 4 As shown, the present invention also provides a multi-model coupling computing system 400 based on a basic section topology benchmark, wherein the multi-model coupling computing system 400 based on a basic section topology benchmark includes a data acquisition layer 401, a topology modeling layer 402, a scheduling engine layer 403 and an application layer 404;

[0151] The data acquisition layer 401 is used to obtain the basic cross-section data corresponding to the target watershed and the calculation unit data divided by each heterogeneous hydrological model;

[0152] The topology modeling layer 402 is used to construct a composite topology structure based on the basic section data and the computing unit data, wherein the composite topology structure is used to represent the upstream and downstream dependency relationship of each basic section, the upstream and downstream sequence relationship between each computing unit, and the 1:N dynamic mapping relationship between a single basic section and each computing unit, where N is a non-negative integer;

[0153] The scheduling engine layer 403 is used to perform hierarchical topological sorting based on the composite topological structure to generate a flood control scheduling result corresponding to the target basin;

[0154] The application layer 404 is used to output the flood control scheduling result to an external flood control scheduling decision system.

[0155] In a specific implementation, the topology modeling layer 402 is further used to:

[0156] generating a directed acyclic graph according to the basic cross-section data and the calculation unit data;

[0157] topologically sorting the directed acyclic graph using a preset topological sorting algorithm so that the directed acyclic graph after topological sorting has no loops and conforms to the hydrological conduction order, wherein the preset topological sorting algorithm includes a Kahn algorithm;

[0158] Based on the preset association relationship between each basic section and each calculation unit, a dynamic mapping relationship of 1:N is established between a single basic section and each calculation unit, wherein the basic section and the calculation unit are in a control-controlled relationship;

[0159] A composite topological structure is constructed based on the directed acyclic graph after the topological sorting and the dynamic mapping relationship.

[0160] In specific implementation, the scheduling engine layer 403 is also used to:

[0161] Grouping and aggregating the computing units based on the composite topological structure to obtain a plurality of aggregation groups, wherein any of the aggregation groups includes a computing unit and a basic section associated with the computing unit;

[0162] Performing inter-group sorting and intra-group sorting on each of the aggregation groups to obtain a hierarchical topological sorting result, wherein the inter-group sorting is to sort the aggregation groups in reverse order according to the maximum position of the basic section in the aggregation group, and the intra-group sorting is to sort according to the upstream and downstream dependency relationship of each basic section in the aggregation group;

[0163] The hierarchical topological sorting result is determined as the flood control scheduling result corresponding to the target watershed.

[0164] Those skilled in the art will understand that the multi-model coupling calculation system based on the basic section topology benchmark according to the embodiment of the present application can be combined with the features of the multi-model coupling calculation method based on the basic section topology benchmark according to the embodiment of the present application, and vice versa.

[0165] Figure 6 A schematic diagram of a computer device 600 that can implement a method or realize an embodiment of the present application is shown. In some embodiments, more or fewer computer devices may be included than shown. In some embodiments, the method can be implemented using a single computer device or multiple computer devices. In some embodiments, the method can be implemented using cloud-based or distributed computer devices.

[0166] like Figure 6As shown, the computer device 600 includes a processor 601, which can perform various appropriate operations and processes according to the programs and / or data stored in the read-only memory (ROM) 602 or the programs and / or data loaded from the storage part 608 into the random access memory (RAM) 603. The processor 601 can be a multi-core processor or can include multiple processors. In some embodiments, the processor 601 can include a general-purpose main processor and one or more special coprocessors, such as a central processing unit (CPU), a graphics processing unit (GPU), a neural network processor (NPU), a digital signal processor (DSP), etc. In the RAM 603, various programs and data required for the operation of the computer device 600 are also stored. The processor 601, ROM 602 and RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0167] The processor and memory are used together to execute the program stored in the memory. When the program is executed by the computer, the methods, steps or functions described in the above embodiments can be implemented.

[0168] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, a touch screen, and the like; an output section 607 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 608 including devices such as a hard disk; and a communication section 609 including a network interface card such as a LAN card or a modem. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. Removable media 611, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 610 as needed, so that computer programs read therefrom can be installed into the storage section 608 as needed. Figure 6 Only some components are shown schematically, which does not mean that the computer system 600 only includes Figure 6 Components shown.

[0169] The systems, devices, modules, or units described in the above embodiments may be implemented by a computer or its associated components. The computer may be, for example, a mobile terminal, a smartphone, a personal computer, a laptop computer, an in-vehicle human-computer interaction device, a personal digital assistant, a media player, a navigation device, a game console, a tablet computer, a wearable device, a smart TV, an Internet of Things system, a smart home, an industrial computer, a server, or a combination thereof.

[0170] In an embodiment of the present application, a computer-readable storage medium is provided, which stores a computer program. The computer program is configured to execute any multi-model coupling calculation method based on a basic section topology benchmark in any embodiment of the present application when run.

[0171] The storage media in the embodiments of the present application include permanent and non-permanent, removable and non-removable items that can be used to store information by any method or technology. Examples of storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0172] The methods, programs, systems, and apparatuses of the embodiments of the present application may be executed or implemented in a single or multiple networked computers, or may be practiced in a distributed computing environment. In the embodiments of this specification, in these distributed computing environments, tasks may be performed by remote processing devices connected via a communication network.

[0173] The specific implementation process of the provided computer device and computer-readable storage medium can refer to the specific implementation process of the multi-model coupling calculation system or method based on the basic cross-section topology benchmark provided in the above embodiment, which will not be repeated here.

[0174] Based on the computer device and computer-readable storage medium provided in this application, a basic section database with bidirectional topological constraints is established, and a section-unit association matrix is used to achieve intelligent mapping of cross-model computational units. A "1:N" dynamic control relationship is established between basic sections and computational units: a single basic section can belong to a unique computational unit of a specific model, while topological control of non-section units is achieved through a downstream section inheritance mechanism. This architecture, combined with a hierarchical topological sorting algorithm, effectively solves the problem of computational path optimization in complex topological networks, improving the efficiency of multi-model coupled computations to a response level of minutes.

[0175] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, those skilled in the art will appreciate that the functional modules / units or controllers and related method steps described in the above embodiments may be implemented using software, hardware, or a combination of software / hardware.

[0176] Unless explicitly stated, the actions or steps of the methods, procedures, and embodiments of the present application do not have to be performed in a specific order and can still achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0177] In this document, multiple embodiments of the present application are described, but for the sake of brevity, the description of each embodiment is not exhaustive, and the same or similar features or parts between the various embodiments may be omitted. In this document, "one embodiment", "some embodiments", "example", "specific example", or "some examples" are intended to apply to at least one embodiment or example according to the present application, rather than all embodiments. The above terms do not necessarily mean to refer to the same embodiment or example. Those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they contradict each other.

[0178] While the exemplary systems and methods of the present application have been specifically shown and described with reference to the above-described embodiments, these are merely examples of the best modes for implementing the present systems and methods. Those skilled in the art will appreciate that various changes may be made to the embodiments of the systems and methods described herein when implementing the present systems and / or methods without departing from the spirit and scope of the present application as defined in the appended claims.

Claims

1. A multi-model coupling calculation method based on basic cross-section topology benchmark, characterized in that: The multi-model coupling calculation method based on the basic cross-section topology benchmark includes: Obtain the basic cross-section data corresponding to the target watershed and the calculation unit data divided by each heterogeneous hydrological model; Constructing a composite topology structure based on the basic section data and the computing unit data, wherein the composite topology structure is used to characterize the upstream and downstream dependency relationship of each basic section, the upstream and downstream sequence relationship between each computing unit, and the 1:N dynamic mapping relationship between a single basic section and each computing unit, where N is a non-negative integer; Performing hierarchical topological sorting based on the composite topological structure to generate a flood control dispatch result corresponding to the target watershed; The flood control dispatching result is output to the flood control dispatching decision-making system.

2. The multi-model coupling calculation method based on the basic cross-section topology benchmark according to claim 1 is characterized in that: The step of constructing a composite topological structure according to the basic section data and the calculation unit data includes: generating a directed acyclic graph according to the basic cross-section data and the calculation unit data; topologically sorting the directed acyclic graph using a preset topological sorting algorithm so that the directed acyclic graph after topological sorting has no loops and conforms to the hydrological conduction order, wherein the preset topological sorting algorithm includes a Kahn algorithm; Based on the preset association relationship between each basic section and each calculation unit, a dynamic mapping relationship of 1:N is established between a single basic section and each calculation unit, wherein the basic section and the calculation unit are in a control-controlled relationship; A composite topological structure is constructed based on the directed acyclic graph after the topological sorting and the dynamic mapping relationship.

3. The multi-model coupling calculation method based on the basic cross-section topology benchmark according to claim 2 is characterized in that: The steps of establishing a 1:N dynamic mapping relationship between a single basic section and each calculation unit based on a preset association relationship between each basic section and each calculation unit include: Obtaining a preset association relationship between each of the basic sections and each of the calculation units; Determining whether a single basic section controls at least one upstream computing unit according to the preset association relationship; If so, establishing a first mapping relationship between the basic section and at least one upstream computing unit controlled by it; If not, the empty cell is recursively traced back to the nearest basic section through the downstream inheritance mechanism, and a second mapping relationship is established between the basic section and the empty cell, wherein the empty cell is a calculation cell that has no directly associated basic section; The first mapping relationship and the second mapping relationship are integrated into a 1:N dynamic mapping relationship between a single basic section and each computing unit.

4. The multi-model coupling calculation method based on the basic cross-section topology benchmark according to claim 1 is characterized in that: The steps of performing hierarchical topological sorting based on the composite topological structure to generate a flood control dispatch result corresponding to the target basin include: Grouping and aggregating the computing units based on the composite topological structure to obtain a plurality of aggregation groups, wherein any of the aggregation groups includes a computing unit and a basic section associated with the computing unit; Performing inter-group sorting and intra-group sorting on each of the aggregation groups to obtain a hierarchical topological sorting result, wherein the inter-group sorting is to sort the aggregation groups in reverse order according to the maximum position of the basic section in the aggregation group, and the intra-group sorting is to sort according to the upstream and downstream dependency relationship of each basic section in the aggregation group; The hierarchical topological sorting result is determined as the flood control scheduling result corresponding to the target watershed.

5. The multi-model coupling calculation method based on the basic cross-section topology benchmark according to claim 1 is characterized in that: The composite topology structure is a basic section-computational unit association matrix architecture, and the multi-model coupling calculation method based on the basic section topology benchmark further includes: Monitoring whether the heterogeneous hydrological model corresponding to the target watershed has changed; If the heterogeneous hydrological model corresponding to the target watershed changes, the real-time basic section data corresponding to the target watershed and the real-time calculation unit data divided by each heterogeneous hydrological model are connected, and the dynamic access and coupling calculation of multi-model calculation units are realized through the dynamic expansion technology of matrix dimensions.

6. A multi-model coupling calculation system based on basic cross-section topology benchmark, characterized in that: Implementing the multi-model coupling calculation method based on the basic section topology benchmark according to any one of claims 1 to 5, the multi-model coupling calculation system based on the basic section topology benchmark includes a data acquisition layer, a topology modeling layer, a scheduling engine layer and an application layer; The data acquisition layer is used to obtain the basic cross-section data corresponding to the target watershed and the calculation unit data divided by each heterogeneous hydrological model; The topology modeling layer is used to construct a composite topology structure based on the basic section data and the computing unit data, wherein the composite topology structure is used to characterize the upstream and downstream dependency relationship of each basic section, the upstream and downstream sequence relationship between each computing unit, and the 1:N dynamic mapping relationship between a single basic section and each computing unit, where N is a non-negative integer; The scheduling engine layer is used to perform hierarchical topological sorting based on the composite topological structure to generate a flood control scheduling result corresponding to the target basin; The application layer is used to output the flood control scheduling result to an external flood control scheduling decision system.

7. The multi-model coupling calculation system based on basic cross-section topology benchmark according to claim 1 is characterized in that: The topology modeling layer is also used to: generating a directed acyclic graph according to the basic cross-section data and the calculation unit data; topologically sorting the directed acyclic graph using a preset topological sorting algorithm so that the directed acyclic graph after topological sorting has no loops and conforms to the hydrological conduction order, wherein the preset topological sorting algorithm includes a Kahn algorithm; Based on the preset association relationship between each basic section and each calculation unit, a dynamic mapping relationship of 1:N is established between a single basic section and each calculation unit, wherein the basic section and the calculation unit are in a control-controlled relationship; A composite topological structure is constructed based on the directed acyclic graph after the topological sorting and the dynamic mapping relationship.

8. The multi-model coupling calculation method based on the basic cross-section topology benchmark according to claim 6 is characterized in that: The scheduling engine layer is also used to: Grouping and aggregating the computing units based on the composite topological structure to obtain a plurality of aggregation groups, wherein any of the aggregation groups includes a computing unit and a basic section associated with the computing unit; Performing inter-group sorting and intra-group sorting on each of the aggregation groups to obtain a hierarchical topological sorting result, wherein the inter-group sorting is to sort the aggregation groups in reverse order according to the maximum position of the basic section in the aggregation group, and the intra-group sorting is to sort according to the upstream and downstream dependency relationship of each basic section in the aggregation group; The hierarchical topological sorting result is determined as the flood control scheduling result corresponding to the target watershed.

9. A computer device, characterized in that: The computer device includes a memory and a processing device, the memory stores a computer program, and when the computer program is executed on the processor, it implements the multi-model coupling calculation method based on the basic section topology benchmark described in any one of claims 1 to 5, and the processing device is loaded with the multi-model coupling calculation system based on the basic section topology benchmark described in any one of claims 6 to 8.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed on a processing device, implements the multi-model coupling calculation method based on a basic section topology benchmark according to any one of claims 1 to 5.

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