Dynamic risk avoidance transfer method and system for flood storage and detention areas based on flood information and road network reconstruction

Abstract

The present invention provides a method and system for dynamic risk avoidance transfer in a flood storage and detention area based on flood information and road network reconstruction, and relates to the technical field of risk management of flood storage and detention areas. The method constructs a one-dimensional river hydraulic model and a two-dimensional flood storage and detention area hydrodynamic model, and couples the two to form a one- and two-dimensional coupling model for simulating the flooding process of the flood storage and detention area, and obtains the flood evolution information of the flood storage and detention area; in addition, an initial road network topology structure is constructed, and the static shortest path is solved with the shortest travel time as the goal; the initial road network topology structure is reconstructed using the flood evolution information, and a dynamic risk avoidance path is calculated, which is used as the optimal transfer path during the flood evolution process. The present invention can take into account the real-time flood information and the dynamic changes of the road network structure during the flooding process of the flood storage and detention area, obtain the latest time to ensure that all villages inside the flood storage and detention area complete the risk avoidance transfer, avoid the irrationality of the traditional flood storage and detention area transfer path planning method, and reduce the risks of the traditional method.

Description

Technical Field

[0001] The present invention relates to the technical field of risk management of flood storage and detention areas, and in particular to a method and system for dynamic risk avoidance transfer of flood storage and detention areas based on flood information and road network reconstruction. Background Art

[0002] Under the background of climate change, extreme weather events occur frequently, and the number of rainstorms and floods exceeding the standard increases. The uncertainty of extreme flood events increases, leading to an increase in the probability of sudden collapse of embankments in flood storage areas. A reasonable and efficient risk avoidance and transfer plan is crucial.

[0003] Traditional flood storage and detention area evacuation schemes usually obtain inundation information such as the maximum inundation depth and maximum flow rate of the flood storage and detention area based on the flood magnitude of the flood evacuation and transfer, and determine the evacuation area, evacuation unit, transfer method and number of people to be transferred based on this. However, when formulating the evacuation and transfer route, the impact of flood evolution on road traffic is not considered. It is a static evacuation and transfer planning scheme, which is widely used in the context of determining the activation of flood storage and detention areas and transferring residents in advance. However, with the increase in super-standard rainstorm and flood events, the probability of sudden collapse of embankments in flood storage and detention areas has increased, and the embankments have collapsed instantly. The traffic conditions of roads inside the flood storage and detention areas can be regarded as a process of dynamic changes with the evolution of floods. The flood evolution speed is extremely fast, which can easily lead to the flooding of the evacuation and transfer routes planned by the flood storage and detention areas. The internal residents cannot be transferred in time and effectively according to the original route, resulting in a high risk of evacuation and transfer of residents in the flood storage and detention areas.

[0004] In summary, the traditional evacuation and transfer methods cannot be effectively applied when the dikes in this flood storage area suddenly burst. In the case of sudden dike burst, there is still a research gap in real-time updating of the topological structure of the road network and the impact of floods on road traffic speed, and dynamically considering the dynamic changes of the transfer path and transfer time of the evacuation unit. The key challenge at this stage is how to dynamically consider the impact of flood evolution on roads in real time, while improving the rationality of the evacuation path and the efficiency of evacuation and transfer. Summary of the invention

[0005] Purpose of the invention: In order to solve the problems of unreasonable paths in traditional evacuation route planning, instantaneous collapse of levees, and emergency evacuation route planning in flood storage areas, a dynamic evacuation method for flood storage areas based on flood information and road network reconstruction is proposed, and a system that can implement the above method is further proposed.

[0006] The present invention proposes a method for dynamic risk avoidance transfer of flood storage areas based on flood information and road network reconstruction, which comprises the following steps:

[0007] Construct a one-dimensional river hydraulic model for the mainstream river of the target basin;

[0008] Divide flood storage and detention areas within the target basin and establish a two-dimensional hydrodynamic model of flood storage and detention areas;

[0009] Setting breach information, coupling the one-dimensional river channel hydraulic model and the two-dimensional flood storage area hydrodynamic model to form a one-dimensional and two-dimensional coupled model;

[0010] Using the one- and two-dimensional coupling model to simulate the flood discharge process in the flood storage and detention area, and obtain flood evolution information in the flood storage and detention area;

[0011] Construct an initial road network topology structure, and based on the initial road network topology structure, solve the static shortest path with the shortest travel time as the goal;

[0012] The initial road network topology structure is reconstructed using the flood evolution information; a dynamic risk avoidance path is calculated based on the reconstructed road network topology structure and used as the optimal transfer path during the flood evolution process.

[0013] In a further embodiment, the process of constructing a one-dimensional river hydraulic model for the mainstream river of the target basin specifically includes:

[0014] Obtain the measured mainstream river section and elevation data of the target basin, determine the upper and lower boundaries of the mainstream river, and establish a one-dimensional river hydraulic model based on the Saint-Venant equations, wherein the one-dimensional river hydraulic model is expressed by a continuity equation and a momentum equation;

[0015] The continuity equation is as follows:

[0016]

[0017] The momentum equation is as follows:

[0018]

[0019] In the formula, Q represents the flow rate; q represents the side inflow flow rate; A represents the cross-sectional area of ​​the water flow; h represents the water level; R represents the hydraulic radius; C represents the Xie Cai coefficient; a represents the momentum correction coefficient; g represents the acceleration of gravity;

[0020] Obtain the measured water level and flow data of the upper boundary hydrological station and the measured water level and flow data of the lower boundary hydrological station of the target basin; determine the roughness of the mainstream river channel, select a predetermined simulation step size, and calibrate and verify the one-dimensional river channel hydrodynamic model.

[0021] In a further embodiment, a flood storage and detention area is divided in the target watershed, and a two-dimensional flood storage and detention area hydrodynamic model is established. The specific process includes:

[0022] In the target basin, the flood storage area is divided into triangular grids, and the triangular grids within the predetermined range around the water-land interface, roads, and embankments are encrypted, and quadrilateral grids are used to divide the area, set the maximum grid area, and perform elevation interpolation on the grids;

[0023] According to the continuity equation and momentum equation, a two-dimensional hydrodynamic model of flood storage area is established:

[0024]

[0025]

[0026]

[0027] Where t is time; x and y are the horizontal and vertical coordinates in the right-handed Cartesian coordinate system; h is the water depth; u and v are the components of the flow velocity in the x and y directions respectively; is the local atmospheric pressure; is the water density, is the reference water density; is the Coriolis force parameter; and is the acceleration caused by the rotation of the Earth; , , , is the radiation stress component; , , , is the horizontal viscous stress term; S is the source and sink term; is the source-sink flow velocity in the x direction, is the source-sink flow velocity in the y direction; represents the wind stress in the x direction; represents the bottom stress in the x direction; represents the wind stress in the y direction; represents the bottom stress in the y direction; Indicates the average flow velocity in the x direction at a certain point at a depth of h The product of It represents the flow rate along the x direction at a certain point at a depth of h; Indicates the average flow velocity in the y direction at a certain point at a depth of h The product of It represents the flow rate along the y direction at a certain point at a water depth of h; Represents the surface wave coefficient.

[0028] In a further embodiment, the one-dimensional river hydrodynamic model is calibrated and verified by using absolute error, Nash efficiency coefficient, and determination coefficient. The one-dimensional river hydrodynamic model is judged to meet the simulation requirements when the maximum absolute error of the water level is less than 0.1, and the Nash efficiency coefficient and determination coefficient are greater than 0.85.

[0029] The absolute error is calculated as follows:

[0030]

[0031] The Nash efficiency coefficient is calculated as follows:

[0032]

[0033] The formula for calculating the coefficient of determination is as follows:

[0034]

[0035] In the formula, is the measured water level series; is the mean of the measured water level series; To simulate the water level series; is the total number of time steps; represents the observation value at the t-th time step; represents the simulated value at the t-th time step; Represents the maximum value among all time steps between the observed and simulated values.

[0036] In a further embodiment, breach information is set, and the one-dimensional river hydraulic model and the two-dimensional flood storage area hydrodynamic model are coupled. The specific process includes:

[0037] Determine whether the breach is at the confluence point and calculate the maximum width of the breach:

[0038] At the confluence point:

[0039] Not at confluence:

[0040] In the formula, A represents the width of the breach; B represents the width of the river;

[0041] The one-dimensional river channel hydraulic model and the two-dimensional flood storage area hydrodynamic model are coupled by lateral connection, and the breach is connected to finally form a one-dimensional and two-dimensional coupled model.

[0042] In a further embodiment, the one- and two-dimensional coupling model is used to simulate the flood diversion process of the flood storage and detention area to obtain flood evolution information of the flood storage and detention area, wherein the flood evolution information includes the inundation range, inundation depth, flow velocity, and arrival time of the flood storage and detention area.

[0043] In a further embodiment, the process of constructing the initial road network topology structure specifically includes:

[0044] Based on the geometric characteristics of the road, the intersections in the road are generalized into nodes v, and the road sections are generalized into edges E. The road network is represented by a graph consisting of a finite number of nodes v and edges E. The adjacency matrix of the road network is represented by G:

[0045]

[0046]

[0047] Where i and j are the rows and columns of the adjacency matrix of the road network respectively; represents the adjacency matrix of the road network; n represents the number of nodes in the road network; represents the i-th node; represents the jth node;

[0048] Calculate the initial travel time weight of the road based on the road length and road travel speed:

[0049]

[0050] In the formula, is the vehicle speed on the i-th road section; represents the travel time of the i-th road section; represents the length of the i-th road segment; r represents the total number of road segments.

[0051] In a further embodiment, based on the initial road network topology, a static shortest path is solved with the shortest travel time as the goal, and the specific process includes:

[0052] Step A, determine the initial node o and the end point e in the path planning;

[0053] Step B, add array T[*] and set Q; T[*] contains the travel time from the initial node o to all nodes, and its initial state is T[o]=0, and the travel time between node o and node v in the adjacency matrix is ​​T(v); set Q is used to store the shortest travel time node and time consumption from the current state to the initial node o, and its initial state is (o,0);

[0054] Create a set P, which is used to store visited nodes and is initially an empty set;

[0055] Step C: traverse the adjacent nodes of the current node v. Each time the traversal is calculated, take out the information (v, T[v]) in the set Q to determine whether the adjacent node is in the set P. If it is in P, continue to traverse the next adjacent node; otherwise, add the node to P.

[0056] Step D: Basis , determine the fastest-reaching neighboring node point of node v, and add (point, T[point]) to the set Q;

[0057] Step E: Repeat step C and step D until the end point e is reached, obtain the fastest path from the initial node o to the end point e and the nodes passed through, and use ArcGIS for visualization.

[0058] In a further embodiment, the initial road network topology is reconstructed using the flood evolution information, and the specific process includes:

[0059] The flood depth of the flood storage area at time T is spatially connected with the roads, and the roads and nodes with flood depth ≥ 0.5m are eliminated;

[0060] For roads with flood depth less than 0.5m, the speed decay function is used to calculate the travel speed :

[0061]

[0062] Where z is the flooding depth; V 0 is the design vehicle speed at that location; a is half of the critical water depth that causes the vehicle to stagnate; b is the attenuation elastic coefficient, which represents the rate at which the vehicle speed on the road decays with the depth of water. The smaller the value of b, the faster the speed decays;

[0063] Calculate the dynamic time path of transferring villages to resettlement areas:

[0064]

[0065] In the formula, Indicates the travel time to transfer the village; Design speed for vehicles on the i-th road section; represents the length of the i-th road segment; represents the total number of road sections from the relocated villages to the resettlement area; z is the flood depth; a is half of the critical water depth that causes vehicle stagnation; b is the attenuation elasticity coefficient, which represents the rate at which the vehicle speed on the road decays with the depth of water. The smaller the value of b, the faster the speed decays;

[0066] The safe transfer time of the transferred villages and the dynamic time paths in different time periods were counted and visualized using GIS.

[0067] In addition, the present invention further proposes a dynamic risk avoidance and transfer system for flood storage and detention areas, the system comprising at least one processor; and a memory communicatively connected to at least one of the processors; wherein the memory stores instructions executable by the processor, and the instructions are used to be executed by the processor to implement the dynamic risk avoidance and transfer method for flood storage and detention areas based on flood information and road network reconstruction disclosed above.

[0068] Beneficial effects: The present invention proposes a method for dynamic risk avoidance transfer in flood storage and detention areas based on flood information and road network reconstruction. The method constructs a dynamic risk avoidance path planning algorithm based on the Dijkstra shortest path optimization algorithm. On the basis of the original static algorithm, the original road network topology and road weights are reconstructed considering the flood evolution stage, so as to realize the dynamic perception of floods and the planning of risk avoidance paths during the flood diversion process in the flood storage and detention area. The proposed dynamic risk avoidance transfer model with superimposed flood evolution information and road network reconstruction can consider the impact of floods on roads and make timely route adjustments according to the flood evolution stage, dynamically and real-time output the risk avoidance transfer route of the village and calculate the corresponding safe transfer time, providing a new risk avoidance transfer method when the levee collapses instantly. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 This is a flow chart of Example 1 of the present invention.

[0070] Figure 2 This is a flow chart of Example 2 of the present invention.

[0071] Figure 3 This is a schematic diagram of the large-section distribution of the river channel according to Example 3 of the present invention.

[0072] Figure 4 This is the two-dimensional grid division result of the flood storage area in Example 3 of the present invention.

[0073] Figure 5 This is the quadrilateral mesh generation result near the land-water boundary, roads, embankments, etc. in the flood storage area of ​​Example 3 of the present invention.

[0074] Figure 6 This is a standard connection diagram of the coupling model between the one-dimensional hydrodynamic model of the mainstream river channel and the two-dimensional hydrodynamic model of the flood storage area in Example 3 of the present invention.

[0075] Figure 7 This is a comparison chart of the simulated water level and the measured water level of the one-dimensional hydrodynamic model of the mainstream river channel at Hukou Station in Example 3 of the present invention.

[0076] Figure 8 This is a comparison chart of the simulated water level and the measured water level at Pengze Station using the one-dimensional hydrodynamic model of the mainstream river channel in Example 3 of the present invention.

[0077] Fig. 9This is a schematic diagram of the effective structure of the road network in Example 3 of the present invention.

[0078] Fig.10 Embodiment 3 of the present invention is a schematic diagram of the evacuation route of Sanxing Village taking into account flood inundation information.

[0079] Fig.11 A schematic diagram of a risk evacuation route for Qiaobei Village taking into account flood inundation information is shown in Example 3 of the present invention.

[0080] Fig.12 Embodiment 3 of the present invention is a schematic diagram of the evacuation route of Batou Village taking into account flood inundation information.

[0081] Fig.13 Embodiment 3 of the present invention is a schematic diagram of the evacuation route of Huayanghe Zongchang Village taking into account flood inundation information. DETAILED DESCRIPTION

[0082] In the following description, a large number of specific details are provided to provide a more thorough understanding of the present invention. However, it is apparent to those skilled in the art that the present invention can be implemented without one or more of these details. In other examples, in order to avoid confusion with the present invention, some technical features known in the art are not described.

[0083] Embodiment 1:

[0084] Reference Figure 1 As shown, this embodiment discloses a method for dynamic risk avoidance transfer of a flood storage area based on flood information and road network reconstruction, and the steps are as follows:

[0085] Step 1: Construct a one-dimensional river channel and a two-dimensional flood storage area hydrodynamic model for the mainstream river and flood storage area.

[0086] Step 2: Set breach information, couple one-dimensional river channel and two-dimensional flood storage and detention area hydrodynamic models, simulate the flood diversion process of the flood storage and detention area, obtain the flooding range, flooding depth, flow velocity, and arrival time of the flood storage and detention area, and determine the transfer range and transfer batches.

[0087] Step 3: Construct the road network topology and establish a static shortest path solution model based on the shortest travel time.

[0088] Step 4: Reconstruct the road network based on flood evolution information, establish a dynamic risk avoidance transfer model, solve the dynamic risk avoidance transfer model, and obtain the optimal transfer path at different times during the flood evolution process.

[0089] Embodiment 2:

[0090] Based on the examples, this example discloses some details of the above four steps. Figure 2It should be noted that the details disclosed in this embodiment are only one feasible way and do not represent a limitation on the specific implementation method.

[0091] Step 1: Construct a one-dimensional river channel and a two-dimensional flood storage area hydrodynamic model for the mainstream river and flood storage area.

[0092] Step 11: Determine the modeling scope of the mainstream river channel in the basin, obtain the measured river channel section and its elevation data in the predetermined basin, determine the upper and lower boundaries of the predetermined river channel, and establish a one-dimensional river channel hydraulic model based on the Saint-Venant equations:

[0093] Continuity equation:

[0094] Momentum equation:

[0095] Where: Q represents the flow rate m 3 / s; q represents the side inflow flow m 3 / s; A represents the water flow cross-sectional area m 2 ; h represents water level m; R represents hydraulic radius m; C represents the coefficient m 1 / 2 / s; a represents the momentum correction coefficient; g represents the gravitational acceleration m 2 / s.

[0096] Step 12: Obtain the measured water level and flow data of the upper boundary hydrological station and the lower boundary hydrological station of the current basin; determine the river roughness, select an appropriate simulation step size, and use absolute error, Nash efficiency coefficient and determination coefficient to calibrate and verify the one-dimensional river hydrodynamic model.

[0097] Absolute error:

[0098] Nash efficiency coefficient:

[0099] Coefficient of determination:

[0100] In the formula, is the measured water level series; is the mean of the measured water level series; To simulate the water level series; is the total number of time steps; represents the observation value at the t-th time step; represents the simulated value at the t-th time step; Represents the maximum value among all time steps between the observed and simulated values.

[0101] Step 13: Determine the appropriate research scope of the flood storage and detention area, collect basic geographic information data such as high-precision terrain elevation data and underlying surface type of the flood storage and detention area, collect water conservancy project data such as embankments, sluice pumps, and correct the terrain data of roads, embankments and other locations.

[0102] Step 14: Use triangular meshing to divide the flood storage area, encrypt the meshes near the water-land interface, roads, levees, etc., use quadrilateral meshing, set the maximum mesh area, and perform elevation interpolation on the meshes.

[0103] Step 15: Based on the continuity equation and momentum equation, establish a two-dimensional flood storage area hydrodynamic model:

[0104]

[0105]

[0106]

[0107] Where t is time; x and y are the horizontal and vertical coordinates in the right-handed Cartesian coordinate system; h is the water depth; u and v are the components of the flow velocity in the x and y directions respectively; is the local atmospheric pressure; is the water density, is the reference water density; is the Coriolis force parameter; and is the acceleration caused by the rotation of the Earth; , , , is the radiation stress component; , , , is the horizontal viscous stress term; S is the source and sink term; is the source-sink flow velocity in the x direction, is the source-sink flow velocity in the y direction; represents the wind stress in the x direction; represents the bottom stress in the x direction; represents the wind stress in the y direction; represents the bottom stress in the y direction; Indicates the average flow velocity in the x direction at a certain point at a depth of h The product of It represents the flow rate along the x direction at a certain point at a depth of h; Indicates the average flow velocity in the y direction at a certain point at a depth of h The product of It represents the flow rate along the y direction at a certain point at a water depth of h; Represents the surface wave coefficient.

[0108] Step 16: Introduce point and line buildings such as roadbed and culverts in the flood storage area onto the basic terrain in the form of "structure" in MIKE 21 to reflect the changes in local flow capacity.

[0109] Step 17: Combine the land use type information data and assign different grid roughness coefficients.

[0110] Step 2: Set breach information, couple one-dimensional river channel and two-dimensional flood storage and detention area hydrodynamic models, simulate the flood diversion process of the flood storage and detention area, obtain the flooding range, flooding depth, flow velocity, and flood arrival time of the flood storage and detention area, and determine the transfer range and transfer batches.

[0111] Step 21: Determine whether the breach is at the confluence point, and use an empirical formula to calculate the maximum width of the breach. The calculation formula for the breach width includes:

[0112] At the confluence point:

[0113] Not at confluence:

[0114] in, A indicates the width of the breach; B indicates the width of the river.

[0115] Step 22: Use lateral connection to couple the one-dimensional hydrodynamic model of the mainstream river and the two-dimensional hydrodynamic model of the flood storage area, and use standard connection to connect the breach.

[0116] Step 23: Determine the flood diversion plan for the flood storage and detention areas. Generally, it is necessary to combine the flood magnitude corresponding to the current flood control standard and the envelope superposition of the inundation range formed by all scenarios under the maximum flood magnitude, and comprehensively consider the depth and breadth of the flood inundation, and select the most unfavorable situation as the flood magnitude for flood risk avoidance and transfer analysis.

[0117] Step 24: Use the constructed one- and two-dimensional coupling model of the flood storage and detention area to simulate the plan, obtain the flooding range, flooding depth, flow rate, and flood arrival time of the flood storage and detention area, and determine the transfer range and transfer batches.

[0118] Step 3: Construct the road network topology and establish a static shortest path solution model based on the shortest travel time.

[0119] Step 31: Use the primitive method to construct an initial road network topology model. Based on the geometric characteristics of the road, the intersections in the road are generalized into nodes, and the road sections in the road are generalized into edges. That is, the road network is represented by a graph consisting of a finite number of nodes v and edges E. The adjacency matrix of the road network is represented by G:

[0120]

[0121]

[0122] Where i and j are the rows and columns of the adjacency matrix of the road network respectively; represents the adjacency matrix of the road network; n represents the number of nodes in the road network; represents the i-th node; represents the jth node.

[0123] Step 32: Calculate the initial weight of the road based on the road length and the road travel speed;

[0124]

[0125] In the formula, is the vehicle speed on the i-th road section; represents the travel time of the i-th road section; represents the length of the i-th road segment; r represents the total number of road segments.

[0126] Step 33: Taking the shortest travel time as the goal, use the Dijkstra algorithm to solve the shortest path.

[0127] Step 34: Determine the initial node o and the end point e in the path planning.

[0128] Step 35, add an array T[*] and a set Q; T[*] contains the travel time from the initial node o to all nodes, and its initial state is T[o]=0, and the travel time between node o and node v in the adjacency matrix is ​​T(v); set Q is used to store the shortest travel time node and time consumption from the current state to the initial node o, and its initial state is (o,0); create a set P, which is used to store the visited nodes, and is initially an empty set.

[0129] Step 36: traverse the adjacent nodes of the current node v. Each time the traversal is performed, the information (v, T[v]) in the set Q is retrieved to determine whether the adjacent node is in the set P. If it is in P, continue to traverse the next adjacent node. Otherwise, add the node to P.

[0130] Step 37: Based on , determine the fastest-reaching adjacent node point of node v and add (point, T[point]) to the set Q.

[0131] Step 38: Repeat steps 36 and 37 until the end point e is reached, and the fastest path from the initial node o to the end point e and the nodes passed through are obtained, and visualized using ArcGIS.

[0132] Step 4: Reconstruct the road network based on flood evolution information, establish a dynamic risk avoidance transfer model, solve the dynamic risk avoidance transfer model, and obtain the optimal transfer path during the flood evolution process.

[0133] Step 41, simulating the flood process of the maximum magnitude of the flood storage and detention area, and obtaining the inundation range and water depth of the flood storage and detention area at each time step.

[0134] Step 42: spatially connect the flooded range, water depth and roads of the flood storage area at time T, remove roads and nodes with water depth > 0.5m, and use the speed attenuation function to calculate the travel speed of roads with flooded water depth < 0.5m. Use the step 31 to construct the road topology structure at time T, and use the step 32 to calculate the road weight, where the road travel speed attenuation formula is as follows:

[0135]

[0136] is the vehicle speed, km / h; z is the flooding depth, V 0 is the design vehicle speed at that location, km / h; a is half of the critical water depth that causes the vehicle to stagnate, which is 50 cm; b is the attenuation elasticity coefficient, which represents the rate at which the vehicle speed on the road decays with the depth of water, and its value is generally 3~5. The smaller the value of b, the faster the speed decays.

[0137] Step 43: Calculate the dynamic risk avoidance path from the transferred village to the resettlement area:

[0138]

[0139] In the formula, Indicates the travel time to transfer the village; Design speed for vehicles on the i-th road section; represents the length of the i-th road segment; It represents the total number of road sections from the relocated villages to the resettlement areas; z is the flood depth; a is half of the critical water depth that causes vehicles to stagnate; b is the attenuation elasticity coefficient, which represents the rate at which the vehicle speed on the road decays with the depth of water. The smaller the value of b, the faster the speed decays.

[0140] Step 44: Count the safe transfer time of the transferred villages and the transfer routes at different time periods, and use GIS for visualization.

[0141] Embodiment 3:

[0142] This embodiment takes the Huayang River flood storage area in the middle and lower reaches of the Yangtze River as the research area, and proposes a dynamic risk avoidance transfer method for the flood storage area based on flood information and road network reconstruction. The following are the technical details:

[0143] S1) Construction of one-dimensional hydrodynamic model of the mainstream river and two-dimensional hydrodynamic model of the flood storage area: 278 measured cross-section data from Jiujiang to Datong Station in the mainstream of the Yangtze River in 2012 were obtained. The total length of the river is 238.0 km, and the average cross-section interval is 1.0 km to 2.0 km. The cross-section distribution map of the mainstream river is constructed, as shown in Figure 2. Figure 3 , Figure 3 The square box refers to the boundary conditions, from left to right they are the upstream Jiujiang boundary, the Poyang Lake point source inflow boundary, and the downstream Datong boundary. The black line refers to the cross-sectional shape. The 1:10000 terrain data of the Huayang River flood storage area is interpolated, and the micro-topography such as roads, ditches, culverts, and embankments are corrected. When dividing the grid, the grid is appropriately encrypted at the micro-topography. In order to avoid the jagged distribution of flooding caused by the rising water level in the lake and the flooding of the land, a 500-meter-wide buffer zone is set at the junction of water and land around the lake. The buffer zone grid is divided into quadrilateral grids, and the rest are divided into unstructured grids. Figure 4 and Figure 5 As shown in Figure 2, the Huayang River flood storage area is divided into 76,875 triangular grids, with the maximum triangular grid side length controlled within 300 m and the maximum grid area no greater than 0.1 km. 2 , collect the land use type distribution data of 30m spatial resolution in the Huayang River flood storage area, and assign the model roughness, as shown in Table 1. Considering the location distribution of each breach in the Huayang River area, Jiujiang is taken as the upper boundary, the flow process is given, Datong is taken as the lower boundary, and the water level flow relationship is given. The inflow from Poyang Lake flows into the Yangtze River in the form of a point source. The model was calibrated using the measured flood in 1998. The roughness values ​​of the main channel and floodplain obtained by calibration were 0.024 and 0.033 respectively. The absolute errors of the highest water levels at Hukou Station and Pengze Station were 0.07m and -0.09m respectively, the Nash efficiency coefficients were 0.96 and 0.97 respectively, and the solution coefficients were 1.00. The simulation results are good, such as Figure 6 , Figure 7 . Figure 6 In the figure, (a) is the coupling model of the one-dimensional hydrodynamic model of the mainstream river and the two-dimensional hydrodynamic model of the flood storage area, and (b) is the standard connection schematic diagram of the breach. Figure 7 In the figure, (a) is the process distribution diagram of water level simulation value and measured value, and (b) is the scatter plot of correlation coefficient between simulation value and measured value.

[0144] Table 1: Roughness values ​​for different land use types

[0145]

[0146] S2) Determine the breach information and couple the one-dimensional hydrodynamic model of the Yangtze River mainstream and the two-dimensional hydrodynamic model of the Huayang River flood storage area: Take the confluence breach of the Huayang River flood storage area as the research object. The breach is not located at the confluence point, and the water surface width of this section of the Yangtze River is generally between 1000 and 2000 m. Take 1500 m, and the width calculated by the breach width determination formula is 507 m. Set up a virtual river channel at the breach in the one-dimensional hydrodynamic model of the Yangtze River mainstream and set up breach buildings on the virtual river channel. Then, use standard connection technology to couple the virtual river channel with the grid of the two-dimensional model. The breach building adopts the instantaneous breach mode, the breach width is set to 507 m, and the elevation of the bottom of the breach is the floodplain elevation of this section of the Yangtze River. For the remaining embankment sections, lateral connections are used for coupling, and the results are as follows: Figure 8 , Figure 8 In the figure, (a) is the distribution diagram of the simulated and measured water level process, and (b) is the scatter plot of the correlation coefficient between the simulated and measured values. The boundary conditions of the one-dimensional model of the Yangtze River mainstream take the 1954-type 300-year flow process of Jiujiang Station as the upper boundary, and the 1954-type 300-year water level flow of Datong Station as the lower boundary. The point source inflow of Poyang Lake is considered in the interval; the boundary conditions of the two-dimensional model of the flood storage area are calculated. On the lake surface, the appropriate bottom water level (15.01m) is selected as the initial condition, and the land surface above the bottom water level is taken as the starting condition. The model simulation step is set to 3600s, and the flood inundation depth and arrival time of the Huayang River flood storage area are simulated. Based on the maximum flood inundation depth and flow rate (Table 2), several villages that need to be relocated and several resettlement areas are determined.

[0147] Table 2: Risk-off shift analysis classification basis

[0148]

[0149] S3) Construct the road network topology, establish a static shortest path solution model based on the shortest travel time, and solve the risk avoidance transfer route without considering flood information: Use the original method to generalize the road network. In the original method, according to the geometric characteristics of the roads in the flood storage area, the intersections in the road are generalized into nodes in the road network, and the road sections are generalized into edges in the road network. That is, the road network is represented by a graph consisting of n "nodes" and "edges", which is converted into an n-dimensional adjacency matrix. The design speed V of the road is used. 0 As the weight of the road, V 0 Mainly related to the road grade. Combined with the actual roads in the study area, the road grade relationship used in this application is shown in Table 3, forming an n-dimensional road right matrix. As the objective function, the Dijkstra algorithm is used to solve the shortest path; the evacuation routes of several villages without considering the flood evolution scenario are obtained, and the transfer time and the corresponding path length are shown in Table 4.

[0150] Table 3: Design speeds for different road grades

[0151]

[0152] Table 4: Transfer time and corresponding path length

[0153]

[0154] S4) Superimpose flood information, reconstruct the road network topology, and solve the dynamic risk avoidance transfer model:

[0155] During the flood evolution, the topological structure of the road network will change due to the influence of the flood. When the flood depth is > 0.5m, node failure and road section failure will occur, such as Fig. 9 As shown. Set the time (start, end, interval time) of the dynamic risk avoidance model. The start time indicates the time when the dam breach begins, the end time indicates the time when the flooding ends, and the interval time indicates that the flood inundation data is retrieved every certain period of time. The time step of the hydrodynamic model simulation is 3600s. Gradually retrieve the flood inundation data, spatially link the flood inundation data domain and the road network data, and determine whether the flood depth of each road section is greater than or less than 0.5m. If the flood depth is greater than 0.5m, set the road to be impassable. Otherwise, calculate the driving speed of the road section. Take the shortest transfer time As the objective function, solve the evacuation path under this step length until the flooding ends. Output the optimal evacuation transfer route, transfer distance time and safe transfer time for each interval time. The results are shown in Table 5. The output results are visualized. The transfer routes of some villages at different times are shown in Table 5. Figure 10-13 shown.

[0156] The attenuation formula of road speed with flooding depth is:

[0157]

[0158] is the vehicle speed, km / h; z is the flooding depth, V 0 is the design vehicle speed at that location, km / h; a is half of the critical water depth that causes the vehicle to stagnate, which is 50 cm; b is the attenuation elastic coefficient, which characterizes the rate at which the vehicle speed on the road decays with the depth of water, and its value is generally 3 to 5. In Example 3, the value of b is 4.

[0159] Table 5: Safe transfer time and corresponding path length

[0160]

[0161] As described above, although the present invention has been shown and described with reference to specific preferred embodiments, it should not be construed as limiting the present invention itself. Various changes may be made to it in form and detail without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims

1. A method for dynamic risk avoidance transfer in flood storage areas based on flood information and road network reconstruction, characterized in that: The steps include: Construct a one-dimensional river hydraulic model for the mainstream river of the target basin; Divide flood storage and detention areas within the target basin and establish a two-dimensional hydrodynamic model of flood storage and detention areas; Setting breach information, coupling the one-dimensional river channel hydraulic model and the two-dimensional flood storage area hydrodynamic model to form a one-dimensional and two-dimensional coupled model; Using the one- and two-dimensional coupling model to simulate the flood discharge process in the flood storage and detention area, and obtain flood evolution information in the flood storage and detention area; Construct an initial road network topology structure, and based on the initial road network topology structure, solve the static shortest path with the shortest travel time as the goal, specifically including: Step A, determine the initial node o and the end point e in the path planning; Step B, add array T[*] and set Q; T[*] contains the travel time from the initial node o to all nodes, and its initial state is T[o]=0, and the travel time between node o and node v in the adjacency matrix is ​​T(v); set Q is used to store the shortest travel time node and time consumption from the current state to the initial node o, and its initial state is (o,0); Create a set P, which is used to store visited nodes and is initially an empty set; Step C: traverse the adjacent nodes of the current node v. Each time the traversal is calculated, take out the information (v, T[v]) in the set Q to determine whether the adjacent node is in the set P. If it is in P, continue to traverse the next adjacent node; otherwise, add the node to P. Step D: Basis , determine the fastest-reaching neighboring node point of node v, and add (point, T[point]) to the set Q; Step E: repeat step C and step D until the end point e is reached, obtain the fastest path from the initial node o to the end point e and the nodes passed through, and visualize them using ArcGIS; The initial road network topology structure is reconstructed using the flood evolution information; a dynamic risk avoidance path is calculated based on the reconstructed road network topology structure and used as the optimal transfer path during the flood evolution process.

2. The method for dynamic risk avoidance transfer of flood storage areas based on flood information and road network reconstruction according to claim 1 is characterized in that: The one-dimensional river hydraulic model is constructed for the mainstream river of the target basin, specifically including: Obtain the measured mainstream river section and elevation data of the target basin, determine the upper and lower boundaries of the mainstream river, and establish a one-dimensional river hydraulic model based on the Saint-Venant equations, wherein the one-dimensional river hydraulic model is expressed by a continuity equation and a momentum equation; The continuity equation is as follows: ； The momentum equation is as follows: ； In the formula, Q represents the flow rate; q represents the side inflow flow rate; A represents the cross-sectional area of ​​the water flow; h represents the water level; R represents the hydraulic radius; C represents the Xie Cai coefficient; a represents the momentum correction coefficient; g represents the acceleration of gravity; Obtain the measured water level and flow data of the upper boundary hydrological station and the measured water level and flow data of the lower boundary hydrological station of the target basin; determine the roughness of the mainstream river channel, select a predetermined simulation step size, and calibrate and verify the one-dimensional river channel hydrodynamic model.

3. The method for dynamic risk avoidance transfer of flood storage areas based on flood information and road network reconstruction according to claim 2 is characterized in that: The said dividing the flood storage and detention area in the target basin and establishing a two-dimensional flood storage and detention area hydrodynamic model specifically includes: In the target basin, the flood storage area is divided into triangular grids, and the triangular grids within the predetermined range around the water-land interface, roads, and embankments are encrypted, and quadrilateral grids are used to divide the area, set the maximum grid area, and perform elevation interpolation on the grids; According to the continuity equation and momentum equation, a two-dimensional hydrodynamic model of flood storage area is established: ； ； ； Where t is time; x and y are the horizontal and vertical coordinates in the right-handed Cartesian coordinate system; h is the water depth; u and v are the components of the flow velocity in the x and y directions respectively; is the local atmospheric pressure; is the water density, is the reference water density; is the Coriolis force parameter; and is the acceleration caused by the rotation of the Earth; , , , is the radiation stress component; , , , is the horizontal viscous stress term; S is the source and sink term; is the source-sink flow velocity in the x direction, is the source-sink flow velocity in the y direction; represents the wind stress in the x direction; represents the bottom stress in the x direction; represents the wind stress in the y direction; represents the bottom stress in the y direction; Indicates the average flow velocity in the x direction at a certain point at a depth of h The product of It represents the flow rate along the x direction at a certain point at a water depth of h; Indicates the average flow velocity in the y direction at a certain point at a depth of h The product of It represents the flow rate along the y direction at a certain point at a water depth of h; Represents the surface wave coefficient.

4. The method for dynamic risk avoidance transfer of flood storage areas based on flood information and road network reconstruction according to claim 2 is characterized in that: The one-dimensional river hydrodynamic model is calibrated and verified by using absolute error, Nash efficiency coefficient and determination coefficient. The one-dimensional river hydrodynamic model meets the simulation requirements when the maximum absolute error of the water level is less than 0.1 and the Nash efficiency coefficient and determination coefficient are greater than 0.

85. The absolute error is calculated as follows: ； The Nash efficiency coefficient is calculated as follows: ； The formula for calculating the coefficient of determination is as follows: ； In the formula, is the measured water level series; is the mean of the measured water level series; To simulate the water level series; is the total number of time steps; represents the observation value at the t-th time step; represents the simulated value at the t-th time step; Represents the maximum value among all time steps between the observed and simulated values.

5. The method for dynamic risk avoidance transfer of flood storage areas based on flood information and road network reconstruction according to claim 1 is characterized in that: The setting of breach information and coupling of the one-dimensional river hydraulic model and the two-dimensional flood storage area hydrodynamic model specifically include: Determine whether the breach is at the confluence point and calculate the maximum width of the breach: At the confluence point: ; Not at confluence: ; In the formula, A represents the width of the breach; B represents the width of the river; The one-dimensional river channel hydraulic model and the two-dimensional flood storage area hydrodynamic model are coupled by lateral connection, and the breach is connected to finally form a one-dimensional and two-dimensional coupled model.

6. The method for dynamic risk avoidance transfer of flood storage areas based on flood information and road network reconstruction according to claim 5 is characterized in that: The one- and two-dimensional coupling model is used to simulate the flood diversion process of the flood storage and detention area to obtain flood evolution information of the flood storage and detention area, wherein the flood evolution information includes the flooding range, flooding depth, flow velocity and arrival time of the flood storage and detention area.

7. The method for dynamic risk avoidance transfer of flood storage areas based on flood information and road network reconstruction according to claim 6 is characterized in that: The constructing of the initial road network topology structure specifically includes: Based on the geometric characteristics of the road, the intersections in the road are generalized into nodes v, and the road sections are generalized into edges E. The road network is represented by a graph consisting of a finite number of nodes v and edges E. The adjacency matrix of the road network is represented by G: ； ； Where i and j are the rows and columns of the adjacency matrix of the road network respectively; represents the adjacency matrix of the road network; n represents the number of nodes in the road network; represents the i-th node; represents the jth node; Calculate the initial travel time weight of the road based on the road length and road travel speed: ； In the formula, is the vehicle speed on the i-th road section; represents the travel time of the i-th road section; represents the length of the i-th road segment; r represents the total number of road segments.

8. The method for dynamic risk avoidance transfer of flood storage areas based on flood information and road network reconstruction according to claim 7 is characterized in that: Reconstructing the initial road network topology structure using the flood evolution information specifically includes: The flood depth of the flood storage area at time T is spatially connected with the roads, and the roads and nodes with flood depth ≥ 0.5m are eliminated; For roads with flood depth less than 0.5m, the speed decay function is used to calculate the travel speed : ； Where z is the flood depth; V0 is the design vehicle speed at that location; a is half of the critical water depth that causes the vehicle to stagnate; b is the attenuation elastic coefficient, which represents the rate at which the vehicle speed on the road decays with the depth of water. The smaller the value of b, the faster the speed decays. Calculate the dynamic time path of transferring villages to resettlement areas: ； In the formula, Indicates the travel time to transfer the village; Design speed for vehicles on the i-th road section; represents the length of the i-th road segment; represents the total number of road sections from the relocated villages to the resettlement area; z is the flood depth; a is half of the critical water depth that causes vehicle stagnation; b is the attenuation elasticity coefficient, which represents the rate at which the vehicle speed on the road decays with the depth of water. The smaller the value of b, the faster the speed decays; The safe transfer time of the transferred villages and the dynamic time paths in different time periods were counted and visualized using GIS.

9. A dynamic risk avoidance and transfer system for flood storage and detention areas, characterized in that: include: at least one processor; as well as, a memory communicatively connected to at least one of the processors; wherein, The memory stores instructions executable by the processor, and the instructions are used to be executed by the processor to implement the dynamic risk avoidance transfer method of flood storage and detention areas based on flood information and road network reconstruction as described in any one of claims 1 to 8.

Images