Dike outburst flood risk assessment method, system and device and storage medium

Abstract

The invention discloses an embankment outburst flood risk assessment method, system and device and a storage medium, embankment outburst flood risk assessment is performed based on an embankment outburst mechanism model and data driving, and the embankment outburst mechanism model is used to provide a data basis for an embankment outburst prediction model based on machine learning. The method comprises the following steps: predicting the probability of dike burst by using a dike burst prediction model, judging whether each sub-dike section breaks or not by using a pseudo-random number generator, updating the boundary condition of a dike burst mechanism model according to the burst judgment result of each sub-dike section, and finally obtaining the grid water level and grid flow velocity of each flood area grid in a preset future time period after multiple cycles. Therefore, the flood risk level of each flood area grid can be determined. According to the method, a data basis is provided for drawing the dike outburst flood risk map, the accuracy and reliability of dike outburst flood risk assessment are improved, and the method can be widely applied to the technical field of artificial intelligence.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a dike breach flood risk assessment method, system, device and storage medium. Background Art

[0002] Against the backdrop of global climate change and intensified human activities, the frequency and intensity of natural disasters have shown a significant upward trend. Among them, dam-breaking floods have become one of the major factors threatening the safety of human life and property due to their suddenness and destructiveness. Flood-breaking floods can not only destroy homes in an instant and cause casualties, but also have a huge impact on the social economy, including long-term impacts such as infrastructure damage, crop yield reduction, and water pollution. In addition, the accelerated urbanization process has led to an increasing number of people and assets concentrated along rivers and in low-lying areas, further increasing the risk and potential losses of flood disasters.

[0003] In the face of increasingly severe flood threats, scientific and reasonable risk management strategies are particularly important. As a core part of preventive measures, the compilation of flood risk maps aims to provide decision-making support for local governments by systematically assessing the probability of floods in specific areas and the extent of damage they may cause, helping them to formulate effective flood prevention plans and emergency response plans. Flood risk maps can not only identify sensitive areas susceptible to floods, but also provide a basis for land use planning, building design standards, evacuation route planning, etc., thereby reducing the possibility of future disasters and their negative impacts.

[0004] Dam breach flood simulation is an integral part of flood management and risk assessment, which helps to understand the mechanism of flood occurrence, predict the development of floods, and assess their potential impact. At present, the simulation methods of dam breach floods are mainly based on mechanism models, and each method has its own characteristics and limitations.

[0005] Mechanistic model-based numerical simulation of dam-break floods is usually based on known hydrological data and historical flood event records, and uses fluid mechanics principles to predict the behavior of floods under specific conditions. The advantage of this type of simulation method is that the calculation process is relatively simple and clear, and it is more effective when dealing with deterministic input conditions. However, there are several drawbacks:

[0006] 1) Singularity assumption: Deterministic simulations often assume that input parameters (such as rainfall, soil moisture, etc.) are fixed and unchanging, but in fact these parameters have great uncertainty. Especially in the current situation of frequent extreme weather events, this assumption may lead to large deviations between simulation results and actual conditions.

[0007] 2) Lack of uncertainty handling: Due to the neglect of the randomness and complexity of natural processes, deterministic simulations are difficult to accurately reflect the probabilistic characteristics of flood occurrence, thus limiting their prediction accuracy and reliability.

[0008] 3) Poor adaptability: With environmental changes and socio-economic development, the original hydrological conditions will change, and deterministic simulation may not be able to update model parameters in time to adapt to new situations.

[0009] In summary, the existing levee breach flood risk assessment schemes have the defect of insufficient accuracy. Summary of the invention

[0010] The purpose of the present invention is to solve one of the technical problems existing in the prior art to at least a certain extent.

[0011] To this end, an object of an embodiment of the present invention is to provide a dike breach flood risk assessment method, which improves the accuracy and reliability of dike breach flood risk assessment.

[0012] Another object of an embodiment of the present invention is to provide a dike breach flood risk assessment system.

[0013] In order to achieve the above technical objectives, the technical solutions adopted by the embodiments of the present invention include:

[0014] In a first aspect, an embodiment of the present invention provides a method for assessing the risk of dike breach flood, comprising the following steps:

[0015] Acquire basic levee data of the target levee area, and establish a levee breach mechanism model based on the basic levee data, wherein the levee breach mechanism model includes a one-dimensional hydrodynamic model of the river channel and a two-dimensional hydrodynamic model of the floodplain;

[0016] Dividing the target levee area into a plurality of sub-levee sections and a plurality of floodplain grids, and obtaining inlet and outlet water level and flow data of the target levee area;

[0017] Using the inlet and outlet water level flow data as boundary conditions, the target dike area is simulated for dike breach flood through the dike breach mechanism model to obtain the river water level and river flow velocity of each sub-dike section;

[0018] Inputting the river channel water level and the river channel flow velocity into the pre-trained dike breach prediction model of the target dike area to obtain the breach probability of each sub-dike section, and determining whether each sub-dike section has breached by using a pseudo-random number generator;

[0019] updating the boundary conditions according to the breach judgment results of each of the sub-dike sections, and returning to the step of simulating the breach flood of the target dike area through the dike breach mechanism model until a preset number of simulations is reached, and obtaining the grid water level and grid flow velocity of each of the floodplain grids in a preset future period;

[0020] The flood risk level of each floodplain grid is determined according to the grid water level and the grid flow velocity.

[0021] Furthermore, in one embodiment of the present invention, the one-dimensional hydrodynamic model of the river channel is:

[0022]

[0023] Among them, t and x represent time and distance respectively, U1 is a vector of conserved variables, F is flux, S1 is source term, A is cross-sectional area, Q is flow rate, I1 and I2 are hydrostatic pressure term and lateral pressure term respectively, g is gravitational acceleration, S0 is bottom slope term, S f is the friction term.

[0024] Furthermore, in one embodiment of the present invention, the two-dimensional hydrodynamic model of the floodplain is:

[0025]

[0026] Where t represents time, U2 is a vector of conserved variables, E and G are fluxes in the x and y directions, S2 is the source term, h represents water level, u and v represent the average flow velocity along the water level in the x and y directions, and q e is the mass source term per unit area, g represents the gravitational acceleration, S 0x and S 0y are the bottom slope terms in the x and y directions, S fx and S fy are the friction slopes in the x and y directions respectively, and n represents the Manning roughness coefficient.

[0027] Furthermore, in one embodiment of the present invention, the one-dimensional hydrodynamic model of the river channel and the two-dimensional hydrodynamic model of the floodplain are coupled through a Riemann solver, and the Riemann solver is used to solve the breach flow according to the water level and flow velocity on both sides of the levee, and the breach flow is obtained by the following formula:

[0028] Q b =W b F Riemann (h L ,h R ,u L ,u R )

[0029] Among them, Q brepresents the breach flow, W b Indicates the width of the breach, F Riemann represents the Riemann solver, h represents the water level, u represents the flow velocity, and the subscripts L and R refer to the two-dimensional units of the river channel and the surface, respectively.

[0030] Further, in one embodiment of the present invention, the dike breach prediction model is trained by the following steps:

[0031] Acquire levee sample data and corresponding levee distress status of the target levee area in multiple historical periods, and determine levee distress labels of each levee sample data according to the levee distress status;

[0032] Constructing a training data set based on the levee sample data and the levee distress labels;

[0033] Inputting the training data set into a pre-built machine learning model to obtain a trained levee breach prediction model;

[0034] Among them, the machine learning model is one of a random forest model, a support vector machine model and a neural network model.

[0035] Furthermore, in one embodiment of the present invention, the determining whether each of the sub-dike sections has collapsed by using a pseudo-random number generator specifically includes:

[0036] Generate a random number in the interval [0,1] by using the pseudo-random number generator;

[0037] When the random number is smaller than the probability of breach, it is determined that the corresponding sub-dike section has breached;

[0038] When the random number is greater than or equal to the probability of breach, it is determined that the corresponding sub-dike section will not breach.

[0039] Further, in one embodiment of the present invention, the determining the flood risk level of each floodplain grid according to the grid water level and the grid flow velocity specifically includes:

[0040] Determine a first flood risk value of each of the floodplain grids according to the grid water level and a preset water level threshold;

[0041] Determining a second flood risk value of each of the floodplain grids according to the grid flow velocity and a preset flow velocity threshold;

[0042] The first flood risk value and the second flood risk value are weighted and summed according to a preset weighting coefficient to obtain a target flood risk value of each floodplain grid, and the flood risk level is determined according to the target flood risk value.

[0043] In a second aspect, an embodiment of the present invention provides a dike breach flood risk assessment system, comprising:

[0044] A dike breach mechanism model establishment module is used to obtain basic dike data of a target dike area and establish a dike breach mechanism model based on the basic dike data. The dike breach mechanism model includes a one-dimensional hydrodynamic model of a river channel and a two-dimensional hydrodynamic model of a floodplain.

[0045] A data acquisition module, used to divide the target dike area into a plurality of sub-dike sections and a plurality of floodplain grids, and to acquire inlet and outlet water level and flow data of the target dike area;

[0046] A dike breach flood simulation module is used to use the inlet and outlet water level flow data as boundary conditions, perform dike breach flood simulation on the target dike area through the dike breach mechanism model, and obtain the river water level and river flow velocity of each sub-dike section;

[0047] A breach occurrence determination module is used to input the river water level and the river flow velocity into a pre-trained dike breach prediction model for the target dike area, obtain the breach occurrence probability of each sub-dike section, and determine whether each sub-dike section has breached through a pseudo-random number generator;

[0048] A grid water level and flow velocity determination module is used to update the boundary conditions according to the breach judgment results of each of the sub-dike sections, and return to the step of simulating the breach flood of the target dike area through the dike breach mechanism model until a preset number of simulations is reached, and obtain the grid water level and grid flow velocity of each of the floodplain grids in a preset future period;

[0049] The flood risk level determination module is used to determine the flood risk level of each floodplain grid according to the grid water level and the grid flow velocity.

[0050] In a third aspect, an embodiment of the present invention provides a dike breach flood risk assessment device, comprising:

[0051] at least one processor;

[0052] at least one memory for storing at least one program;

[0053] When the at least one program is executed by the at least one processor, the at least one processor implements the above-mentioned method for assessing the risk of dike breach flood.

[0054] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, in which a program executable by a processor is stored. When the program executable by the processor is executed by the processor, it is used to execute the above-mentioned method for assessing the risk of levee breach flood.

[0055] The advantages and beneficial effects of the present invention will be partly given in the following description, partly become apparent from the following description, or be understood through the practice of the present invention:

[0056] The embodiment of the present invention obtains basic levee data of a target levee area, establishes a levee breach mechanism model based on the basic levee data, and the levee breach mechanism model includes a one-dimensional hydrodynamic model of a river channel and a two-dimensional hydrodynamic model of a floodplain. The target levee area is divided into a plurality of sub-levee sections and a plurality of floodplain grids, and the inlet and outlet water level and flow data of the target levee area are obtained. The inlet and outlet water level and flow data are used as boundary conditions, and a levee breach flood simulation is performed on the target levee area through the levee breach mechanism model to obtain the river channel water level and river channel flow velocity of each sub-levee section, and the river channel water level and flow velocity are used as boundary conditions. The river flow velocity is input into the pre-trained levee breach prediction model of the target levee area to obtain the breach probability of each sub-levee section, and a pseudo-random number generator is used to determine whether each sub-levee section will breach. The boundary conditions are updated according to the breach determination results of each sub-levee section, and the step of simulating the levee breach flood in the target levee area through the levee breach mechanism model is returned until the preset number of simulations is reached. The grid water level and grid flow velocity of each floodplain grid in the preset future period are obtained, and the flood risk level of each floodplain grid is determined according to the grid water level and grid flow velocity. The embodiment of the present invention performs a dike breach flood risk assessment based on a dike breach mechanism model and data-driven, uses the dike breach mechanism model to provide a data basis for a dike breach prediction model based on machine learning, uses the dike breach prediction model to predict the probability of dike breach, uses a pseudo-random number generator to determine whether each sub-dike section has breached, and updates the boundary conditions of the dike breach mechanism model according to the breach judgment results of each sub-dike section. After multiple cycles, the grid water level and grid flow velocity of each floodplain grid in a preset future time period are finally obtained, so that the flood risk level of each floodplain grid can be determined, which provides a data basis for the drawing of a dike breach flood risk map and improves the accuracy and reliability of dike breach flood risk assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solution in the embodiments of the present invention, the following introduction is made to the drawings required for use in the embodiments of the present invention. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solution of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0058] Figure 1 A flowchart of the steps of a dike breach flood risk assessment method provided by an embodiment of the present invention;

[0059] Figure 2 A schematic diagram showing the comparison of a dike before and after collapse provided by an embodiment of the present invention;

[0060] Figure 3 A schematic diagram of the results of a dike breach flood simulation provided by an embodiment of the present invention;

[0061] Figure 4 A structural block diagram of a dike breach flood risk assessment system provided by an embodiment of the present invention;

[0062] Figure 5 A structural block diagram of a dike breach flood risk assessment device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0063] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limitations of the present invention. For the step numbers in the following embodiments, they are only provided for the convenience of explanation, and the order between the steps is not limited in any way, and the execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0064] In the description of the present invention, the meaning of "a plurality" is two or more than two. If there is a description of "a first" or "a second", it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features. In addition, unless otherwise defined, all technical and scientific terms used in this document have the same meaning as those commonly understood by those skilled in the art.

[0065] In recent years, with the development of big data technology and machine learning algorithms, data-driven methods have gradually become one of the effective ways to solve complex system problems. In the field of dam breach flood simulation, data-driven methods also show their unique advantages, especially in dealing with nonlinear relationships, high-dimensional data, and uncertainty. Data-driven methods provide new ideas and tools for dam breach flood simulation, which helps to improve the accuracy and reliability of flood warning systems and is of great significance for disaster prevention and mitigation. In summary, the integration of mechanism models and data-driven methods to simulate dam breach flood processes more flexibly and comprehensively and identify flood risks is a future development trend. This can not only enhance people's ability to fight flood disasters, but also help promote the development of water resources management in a refined and intelligent direction.

[0066] Reference Figure 1 The embodiment of the present invention provides a method for assessing the risk of dike breach flood, which specifically includes the following steps:

[0067] S101, obtaining basic levee data of the target levee area, and establishing a levee breach mechanism model based on the basic levee data, wherein the levee breach mechanism model includes a one-dimensional hydrodynamic model of the river channel and a two-dimensional hydrodynamic model of the floodplain;

[0068] S102, dividing the target levee area into a plurality of sub-levee sections and a plurality of floodplain grids, and obtaining the inlet and outlet water level flow data of the target levee area;

[0069] S103, using the inlet and outlet water level flow data as boundary conditions, simulating the levee breach flood in the target levee area through the levee breach mechanism model, and obtaining the river water level and river flow velocity of each sub-levee section;

[0070] S104, inputting the river water level and the river flow velocity into the pre-trained dike breach prediction model of the target dike area to obtain the probability of breach of each sub-dike section, and determining whether each sub-dike section has breached through a pseudo-random number generator;

[0071] S105, updating the boundary conditions according to the breach judgment results of each sub-dike section, and returning to the step of simulating the breach flood of the target dike area through the dike breach mechanism model until a preset number of simulations is reached, and obtaining the grid water level and grid flow velocity of each floodplain grid in a preset future period;

[0072] S106. Determine the flood risk level of each floodplain grid according to the grid water level and grid flow velocity.

[0073] Specifically, the embodiment of the present invention performs a dike breach flood risk assessment based on a dike breach mechanism model and data-driven, uses the dike breach mechanism model to provide a data basis for a dike breach prediction model based on machine learning, uses the dike breach prediction model to predict the probability of dike breach, uses a pseudo-random number generator to determine whether each sub-dike section has breached, and updates the boundary conditions of the dike breach mechanism model based on the breach judgment results of each sub-dike section. After multiple cycles, the grid water level and grid flow velocity of each floodplain grid in a preset future time period are finally obtained, so that the flood risk level of each floodplain grid can be determined, which provides a data basis for the drawing of a dike breach flood risk map and improves the accuracy and reliability of dike breach flood risk assessment.

[0074] In some optional embodiments, the one-dimensional hydrodynamic model of the river uses the Godunov format finite volume method to solve the one-dimensional Saint-Venant equations to simulate the water level and flow rate of each section in the river. The two-dimensional hydrodynamic model of the floodplain uses the Godunov format finite volume method to solve the two-dimensional shallow water equations to simulate the water level and flow rate in the two-dimensional grid of the floodplain. The one-dimensional model and the two-dimensional model are coupled using an improved Riemann solver.

[0075] As an optional implementation, the one-dimensional hydrodynamic model of the river is:

[0076]

[0077] Among them, t and x represent time and distance respectively, U1 is a vector of conserved variables, F is flux, S1 is source term, A is cross-sectional area, Q is flow rate, I1 and I2 are hydrostatic pressure term and lateral pressure term respectively, g is gravitational acceleration, S0 is bottom slope term, S f is the friction term.

[0078] Specifically, the governing equations of the one-dimensional hydrodynamic model of the river channel are the Saint-Venant equations. For the shallow water equations of a natural river channel with irregular cross-section characteristics, the conservation form is:

[0079]

[0080] Where: t, x are time and distance respectively; U1 is the vector of conserved variables, F is the flux, and S1 is the source term. The specific forms of each vector are:

[0081]

[0082] Where: A is the cross-sectional area of ​​the water flow; Q is the flow rate; I1 and I2 are the hydrostatic pressure term and the lateral pressure term respectively; g is the gravitational acceleration; S0 is the bottom slope term, S f Friction term = n 2 Q|Q| / (A 2 R 43 ).

[0083] As an optional implementation, the two-dimensional hydrodynamic model of the floodplain is:

[0084]

[0085] Where t represents time, U2 is a vector of conserved variables, E and G are fluxes in the x and y directions, S2 is the source term, h represents water level, u and v represent the average flow velocity along the water level in the x and y directions, and q e is the mass source term per unit area, g represents the gravitational acceleration, S 0x and S 0y are the bottom slope terms in the x and y directions, S fx and S fy are the friction slopes in the x and y directions respectively, and n represents the Manning roughness coefficient.

[0086] Specifically, the control equation of the two-dimensional hydrodynamic model of the floodplain consists of the mass conservation equation and the momentum conservation equations in the x and y directions, and its conservation form is as follows:

[0087]

[0088] Where: U2 is the vector of conserved variables; E and G are the fluxes in the x and y directions; S2 is the source term, which mainly includes the mass source term S e and the bottom slope term S b , friction term S f The specific form of the above vector is:

[0089]

[0090] Where: h is the water level; u and v are the average flow velocities along the water level in the x and y directions; q e is the mass source term per unit area, mainly including rainfall, infiltration, stormwater discharge, overflow, etc.; g is the gravitational acceleration; the bottom slope term S 0x and S 0y Reflects the terrain changes in the x and y directions; S fx and S fy is the friction slope in the x and y directions, calculated here by the Manning formula:

[0091]

[0092] Where: n is the Manning roughness coefficient.

[0093] As an optional implementation, the one-dimensional hydrodynamic model of the river channel and the two-dimensional hydrodynamic model of the floodplain are coupled through a Riemann solver. The Riemann solver is used to solve the breach flow according to the water level and flow velocity on both sides of the levee. The breach flow is obtained by the following formula:

[0094] Q b =W b F Riemann (h L ,h R ,u L ,u R )

[0095] Among them, Q b represents the breach flow, W b Indicates the width of the breach, F Riemann represents the Riemann solver, h represents the water level, u represents the flow velocity, and the subscripts L and R refer to the two-dimensional units of the river channel and the surface, respectively.

[0096] Specifically, the improved Riemann solver of the embodiment of the present invention has the following features: according to the water level and flow velocity on the left and right sides of the dike, the numerical flux is solved using approximate Riemann operators such as HLLC, HLL, and Roe;

[0097] Q b =W b F Riemann (h L ,h R ,uL ,u R )

[0098] Where Q b is the breach flow; W b F is the breach width; Riemann is a Riemann solver, which can be any common Riemann solver; h is the water level, u is the flow velocity; the subscripts L and R refer to the two-dimensional units of the river channel and the surface, respectively.

[0099] like Figure 2 The figure shows a comparison diagram of the dike before and after the breach provided by the embodiment of the present invention. The water level h on the left side of the dike is L According to the breach elevation Z b and river water level Z R Set equal to max(0,Z R -Z b ); water level on the right side of the embankment h R According to the water level Z in the floodplain c and breach elevation Z b Set, equal to max(0, Z c -Z b ), if there is water on the left or right side of the interface, the flow velocity on the left and right sides of the interface is equal to the flow velocity of the two-dimensional unit in the floodplain.

[0100] The breach width and the bottom elevation of the breach can change over time, and the calculation formula for the breach width change is:

[0101]

[0102] Where W b is the breach width, W0 is the breach width at the initial moment, τ is the shear stress of the water flow, τ c is the critical shear stress of soil, γ is the bulk density of soil, c w is the lateral scour coefficient.

[0103] The calculation formula for the change in breach depth is:

[0104]

[0105] Where: Z b is the elevation of the breach top; Z b0 is the breach elevation at the initial moment, the breach top elevation; c z is the vertical scour coefficient.

[0106] As an optional implementation, the dike breach prediction model is trained by the following steps:

[0107] S201, obtaining levee sample data and corresponding levee distress status of a target levee area in multiple historical periods, and determining a levee distress label of each levee sample data according to the levee distress status;

[0108] S202, constructing a training data set based on levee sample data and levee distress labels;

[0109] S203, inputting the training data set into a pre-built machine learning model to obtain a trained levee breach prediction model;

[0110] Among them, the machine learning model is one of a random forest model, a support vector machine model and a neural network model.

[0111] Specifically, the measured data of levee breach in the target levee area are collected, including data such as levee soil type, levee slope, levee width, distance from levee top to bottom, river curvature, river flow, river topography, dangerous water level, and dangerous location. The collected basic levee data are processed and the levee data are divided into two categories: dangerous levees and non-dangerous levees. Whether the levee is in danger, the dangerous water level, and the dangerous location are used as dependent variables, that is, the dangerous status of the levee, and other data are used as independent variables, that is, the levee sample data. Based on the processed levee data, a levee breach prediction model is obtained by training using random forest, support vector machine, convolutional neural network, etc.

[0112] After establishing the levee breach mechanism model based on river terrain sections, floodplain DEM and other data, the measured hydrological data was used to verify the calculation accuracy of the model. The levee is then subdivided into several sub-levee sections, and the length of the levee section should not exceed 1 / 4 of the length of a single bend section of the river. The inlet water level and outlet flow process of the river are selected as the boundary conditions for the numerical simulation of the flood, and the hydrodynamic model outputs the simulation results every 1 hour. The levee breach prediction model reads the river water level and river flow velocity simulated by the hydrodynamic model, and calculates the probability of breach of each unbroken levee section.

[0113] As an optional implementation, a pseudo-random number generator is used to determine whether each sub-dike segment has collapsed, which specifically includes:

[0114] S1041, generating a random number in the interval [0,1] by using a pseudo-random number generator;

[0115] S1042, when the random number is less than the probability of breach, it is determined that the corresponding sub-dike section has breached;

[0116] S1043. When the random number is greater than or equal to the probability of breach, it is determined that the corresponding sub-dike section will not breach.

[0117] Specifically, the embodiment of the present invention uses a random number generator to determine whether a dike breach occurs. The process of determining whether a dike breach occurs can be written as:

[0118] Random(x)∈[0,1]

[0119] if x <P,Occur=Ture

[0120] if x≥P,Occur=False

[0121] In the formula: Random is a pseudo-random number generator; x is a random number; P is the probability of an event occurring; Occur is whether an event will occur. Assume that the initial width of the breach is 1m, and the breach height is a random number from the water level to the embankment foot elevation.

[0122] After determining whether each sub-dike section has breached, the dike breach mechanism model reads the breach conditions of each sub-dike section, uses the breach conditions of the sub-dike section as boundary conditions to re-simulate the numerical simulation, obtains the hydrodynamic conditions in the river channel and floodplain at the next moment, and outputs the hydrodynamic simulation results, and then performs dike breach judgment again. Using the Monte Carlo simulation concept, multiple dike breach flood simulations and dike breach judgments are performed, and finally the last output dike breach flood simulation results are obtained, which include the hydrodynamic simulation results of the floodplain grid, i.e., the grid water level and grid flow velocity. Figure 3 Shown is a schematic diagram of the results of a dike breach flood simulation provided by an embodiment of the present invention.

[0123] As an optional implementation, the flood risk level of each floodplain grid is determined according to the grid water level and the grid flow velocity, which specifically includes:

[0124] S1061, determining a first flood risk value of each floodplain grid according to the grid water level and a preset water level threshold;

[0125] S1062, determining a second flood risk value of each floodplain grid according to the grid flow velocity and a preset flow velocity threshold;

[0126] S1063. Perform weighted summation of the first flood risk value and the second flood risk value according to a preset weighting coefficient to obtain a target flood risk value of each floodplain grid, and determine a flood risk level according to the target flood risk value.

[0127] Specifically, the embodiment of the present invention compares the grid water level and the network flow velocity with the corresponding threshold conditions respectively to obtain a first flood risk value and a second flood risk value, and then performs weighted summation according to a preset weighting coefficient to obtain a target flood risk value of each floodplain grid, and then determines the flood risk level according to the target flood risk value.

[0128] The method steps of the embodiment of the present invention are described above. It can be recognized that the embodiment of the present invention performs a dike breach flood risk assessment based on a dike breach mechanism model and data-driven, uses a dike breach mechanism model to provide a data basis for a dike breach prediction model based on machine learning, uses a dike breach prediction model to predict the probability of dike breach, uses a pseudo-random number generator to determine whether each sub-dike segment has breached, and updates the boundary conditions of the dike breach mechanism model according to the breach judgment results of each sub-dike segment. After multiple cycles, the grid water level and grid flow velocity of each floodplain grid in a preset future period are finally obtained, so that the flood risk level of each floodplain grid can be determined, which provides a data basis for the drawing of a dike breach flood risk map and improves the accuracy and reliability of dike breach flood risk assessment.

[0129] Reference Figure 4 The embodiment of the present invention provides a dike breach flood risk assessment system, comprising:

[0130] The dike breach mechanism model building module is used to obtain the basic dike data of the target dike area and build the dike breach mechanism model based on the basic dike data. The dike breach mechanism model includes a one-dimensional hydrodynamic model of the river channel and a two-dimensional hydrodynamic model of the floodplain.

[0131] A data acquisition module is used to divide the target dike area into multiple sub-dike sections and multiple floodplain grids, and obtain the inlet and outlet water level flow data of the target dike area;

[0132] The dike breach flood simulation module is used to use the inlet and outlet water level flow data as boundary conditions, simulate the dike breach flood in the target dike area through the dike breach mechanism model, and obtain the river water level and river flow velocity of each sub-dike section;

[0133] The breach occurrence judgment module is used to input the river water level and river flow velocity into the pre-trained levee breach prediction model of the target levee area, obtain the breach probability of each sub-levee section, and judge whether each sub-levee section has breached through a pseudo-random number generator;

[0134] The grid water level and flow velocity determination module is used to update the boundary conditions according to the breach judgment results of each sub-dike section, and return to the step of simulating the breach flood of the target dike area through the dike breach mechanism model until the preset number of simulations is reached, and the grid water level and grid flow velocity of each floodplain grid in the preset future period are obtained;

[0135] The flood risk level determination module is used to determine the flood risk level of each floodplain grid based on the grid water level and grid flow velocity.

[0136] The contents of the above method embodiments are all applicable to the present system embodiments. The functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0137] Reference Figure 5 The embodiment of the present invention provides a dike breach flood risk assessment device, comprising:

[0138] at least one processor;

[0139] at least one memory for storing at least one program;

[0140] When the at least one program is executed by the at least one processor, the at least one processor implements the above-mentioned method for assessing the risk of dike breach flood.

[0141] The contents of the above method embodiments are all applicable to the present device embodiments. The functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0142] An embodiment of the present invention further provides a computer-readable storage medium, in which a program executable by a processor is stored. When the program executable by the processor is executed by the processor, it is used to execute the above-mentioned dike breach flood risk assessment method.

[0143] A computer-readable storage medium according to an embodiment of the present invention can execute a dike breach flood risk assessment method provided by an embodiment of the present invention, can execute any combination of implementation steps of the method embodiment, and has the corresponding functions and beneficial effects of the method.

[0144] The embodiment of the present invention also discloses a computer program product or a computer program, wherein the computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes Figure 1 The method shown.

[0145] In some optional embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the above-mentioned boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the present invention is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. The optional embodiment is expected, wherein the order of various operations is changed and the sub-operation described as a part of a larger operation is performed independently.

[0146] In addition, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise specified to the contrary, one or more of the above-mentioned functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present invention. More specifically, in view of the properties, functions and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional skills of the engineer. Therefore, those skilled in the art can implement the present invention set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0147] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the above methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0148] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0149] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and editable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the above-mentioned program is printed, since the above-mentioned program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or processing in other suitable ways as necessary, and then stored in a computer memory.

[0150] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0151] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0152] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

[0153] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A method for assessing the risk of dike breach floods, characterized in that: The following steps are involved: Acquire basic levee data of the target levee area, and establish a levee breach mechanism model based on the basic levee data, wherein the levee breach mechanism model includes a one-dimensional hydrodynamic model of the river channel and a two-dimensional hydrodynamic model of the floodplain; Dividing the target levee area into a plurality of sub-levee sections and a plurality of floodplain grids, and obtaining inlet and outlet water level and flow data of the target levee area; Using the inlet and outlet water level flow data as boundary conditions, the target dike area is simulated for dike breach flood through the dike breach mechanism model to obtain the river water level and river flow velocity of each sub-dike section; Inputting the river channel water level and the river channel flow velocity into the pre-trained dike breach prediction model of the target dike area to obtain the breach probability of each sub-dike section, and determining whether each sub-dike section has breached by using a pseudo-random number generator; updating the boundary conditions according to the breach judgment results of each of the sub-dike sections, and returning to the step of simulating the breach flood of the target dike area through the dike breach mechanism model until a preset number of simulations is reached, and obtaining the grid water level and grid flow velocity of each of the floodplain grids in a preset future period; The flood risk level of each floodplain grid is determined according to the grid water level and the grid flow velocity.

2. A dike breach flood risk assessment method according to claim 1, characterized in that: The one-dimensional hydrodynamic model of the river channel is: Among them, t and x represent time and distance respectively, U1 is a vector of conserved variables, F is flux, S1 is source term, A is cross-sectional area, Q is flow rate, I1 and I2 are hydrostatic pressure term and lateral pressure term respectively, g is gravitational acceleration, S0 is bottom slope term, S f is the friction term.

3. A dike breach flood risk assessment method according to claim 1, characterized in that: The two-dimensional hydrodynamic model of the floodplain is: Where t represents time, U2 is a vector of conserved variables, E and G are fluxes in the x and y directions, S2 is the source term, h represents water level, u and v represent the average flow velocity along the water level in the x and y directions, and q e is the mass source term per unit area, g represents the gravitational acceleration, S 0x and S 0y are the bottom slope terms in the x and y directions, S fx and S fy are the friction slopes in the x and y directions respectively, and n represents the Manning roughness coefficient.

4. A dike breach flood risk assessment method according to claim 1, characterized in that: The one-dimensional hydrodynamic model of the river channel and the two-dimensional hydrodynamic model of the floodplain are coupled through a Riemann solver, and the Riemann solver is used to solve the breach flow according to the water level and flow velocity on both sides of the levee. The breach flow is obtained by the following formula: Q b =W b F Riemann (h L ,h R ,u L ,u R ) Among them, Q b represents the breach flow, W b Indicates the width of the breach, F Riemann represents the Riemann solver, h represents the water level, u represents the flow velocity, and the subscripts L and R refer to the two-dimensional units of the river channel and the surface, respectively.

5. A dike breach flood risk assessment method according to claim 1, characterized in that: The dike breach prediction model is trained by the following steps: Acquire levee sample data and corresponding levee distress status of the target levee area in multiple historical periods, and determine levee distress labels of each levee sample data according to the levee distress status; Constructing a training data set based on the levee sample data and the levee distress labels; Inputting the training data set into a pre-built machine learning model to obtain a trained levee breach prediction model; Among them, the machine learning model is one of a random forest model, a support vector machine model and a neural network model.

6. A dike breach flood risk assessment method according to claim 1, characterized in that: The step of determining whether each of the sub-dike sections has collapsed by using a pseudo-random number generator specifically includes: Generate a random number in the interval [0,1] by using the pseudo-random number generator; When the random number is smaller than the probability of breach, it is determined that the corresponding sub-dike section has breached; When the random number is greater than or equal to the probability of breach, it is determined that the corresponding sub-dike section will not breach.

7. A dike breach flood risk assessment method according to any one of claims 1 to 6, characterized in that: Determining the flood risk level of each floodplain grid according to the grid water level and the grid flow velocity specifically includes: Determine a first flood risk value of each of the floodplain grids according to the grid water level and a preset water level threshold; Determining a second flood risk value of each of the floodplain grids according to the grid flow velocity and a preset flow velocity threshold; The first flood risk value and the second flood risk value are weighted and summed according to a preset weighting coefficient to obtain a target flood risk value of each floodplain grid, and the flood risk level is determined according to the target flood risk value.

8. A dike breach flood risk assessment system, characterized in that: include: A dike breach mechanism model establishment module is used to obtain basic dike data of a target dike area and establish a dike breach mechanism model based on the basic dike data. The dike breach mechanism model includes a one-dimensional hydrodynamic model of a river channel and a two-dimensional hydrodynamic model of a floodplain. A data acquisition module, used to divide the target dike area into a plurality of sub-dike sections and a plurality of floodplain grids, and to acquire inlet and outlet water level and flow data of the target dike area; A dike breach flood simulation module is used to use the inlet and outlet water level flow data as boundary conditions, perform dike breach flood simulation on the target dike area through the dike breach mechanism model, and obtain the river water level and river flow velocity of each sub-dike section; A breach occurrence determination module is used to input the river water level and the river flow velocity into a pre-trained dike breach prediction model for the target dike area, obtain the breach occurrence probability of each sub-dike section, and determine whether each sub-dike section has breached through a pseudo-random number generator; A grid water level and flow velocity determination module is used to update the boundary conditions according to the breach judgment results of each of the sub-dike sections, and return to the step of simulating the breach flood of the target dike area through the dike breach mechanism model until a preset number of simulations is reached, and obtain the grid water level and grid flow velocity of each of the floodplain grids in a preset future period; The flood risk level determination module is used to determine the flood risk level of each floodplain grid according to the grid water level and the grid flow velocity.

9. A dike breach flood risk assessment device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements a dike breach flood risk assessment method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to execute a dike breach flood risk assessment method according to any one of claims 1 to 7 when executed by the processor.

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