Plain water network area standard-exceeding rainstorm risk assessment and analysis method

Abstract

The invention belongs to the technical field of flood risk assessment, and particularly relates to a plain water network area standard-exceeding rainstorm risk assessment analysis method, which comprises the following steps: 1, data acquisition: acquiring comprehensive data of a to-be-assessed area, the comprehensive data comprises landform, a hydraulic pipe network, hydrologic catchment, a station gate, a river network, a river channel, an embankment, past rainfall and humanity information; 2, module coupling: according to the acquired comprehensive data, constructing a comprehensive data module of the to-be-evaluated region, and constructing a stereoscopic model of the to-be-evaluated region through the comprehensive data module; 3, verifying the model; 4, simulating rainfall; and 5, outputting a result. By establishing a plurality of data modules, the plurality of data modules are coupled into the region model, and rainfall is simulated through the rainfall module, so that real-time calculation of rainstorm in the assessment region is realized, the real condition of the assessment region is better fit, and the effect of improving the risk assessment accuracy is achieved.

Description

Technical Field

[0001] The invention belongs to the technical field of urban flood risk status assessment, and specifically is a method for risk assessment and analysis of excessive rainstorms in plain water network areas. Background Art

[0002] With the continuous intensification of global climate change and the rapid development of urbanization, extreme rainstorms occur frequently with huge rainfall in a short period of time. Whether in cities or rural areas, if timely dredging and drainage cannot be met, rainstorms will harm the growth of crops, disrupt normal agricultural production and the normal development of other industries, and even endanger human life, health and safety.

[0003] At present, the existing technology has also proposed some solutions for rainstorm risk prediction. For example, the Chinese patent announced as CN113723824B discloses a rainstorm disaster risk assessment method, which evaluates the disaster-causing capacity of rainstorms by selecting four evaluation indicators: precipitation, precipitation intensity, precipitation distribution and precipitation duration.

[0004] In the above technical scheme, judging the disaster-causing capacity of heavy rain by four indicators, namely precipitation amount, precipitation intensity, precipitation distribution and precipitation duration, is not rigorous and does not take into account the actual terrain, water conservancy distribution and other factors in the region, and the prediction results are relatively general.

[0005] To this end, the present invention provides a risk assessment and analysis method for excessive rainstorms in plain water network areas. Summary of the invention

[0006] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0007] The technical solution adopted by the present invention to solve the technical problem is: a risk assessment and analysis method for excessive rainstorms in plain water network areas described in the present invention comprises the following steps:

[0008] S1. Data collection: Obtain comprehensive data of the area to be assessed, including topography, hydraulic pipe network, hydrological water collection, station gates, river network and river channels, levees, past rainfall and humanities information;

[0009] S2, module coupling: Based on the acquired comprehensive data, build a comprehensive data module for the area to be evaluated, and construct a three-dimensional model of the area to be evaluated through the comprehensive data module;

[0010] S3, model verification: verify the accuracy of the three-dimensional model of the area to be evaluated. If the verification is qualified, proceed to the next step. If the verification is unqualified, it indicates that there are abnormal data in the comprehensive data collected in step S1. Find the abnormal data and correct it, then return to step S2 to optimize the comprehensive data module;

[0011] S4, simulated rainfall: access future meteorological data and risk avoidance data of the area to be assessed, and simulate future rainfall on the three-dimensional model of the area to be assessed based on the future meteorological data;

[0012] S5. Result output: By simulating future rainfall, when there is heavy rain, the three-dimensional model of the area to be assessed will simulate whether there is waterlogging according to the drainage functions of different areas, and output the heavy rain risk database of the area to be assessed based on the regional conditions of waterlogging in the area to be assessed.

[0013] Furthermore, the specific method of model verification described in step S3 is as follows:

[0014] Step 1: Obtain historical data on past rainstorm disasters in the area to be assessed;

[0015] Step 1: Put the rainfall data when the rainstorm disaster occurs into the three-dimensional model for simulation;

[0016] Step 3: Compare the historical disaster characteristics with the three-dimensional model simulation; if the comparison results are consistent, the verification is qualified; if the comparison results are inconsistent, the verification fails.

[0017] Furthermore, the risk avoidance data in step S4 includes the real-time water level of the catchment area, which is obtained by installing a water level monitoring device inside the catchment area and feeding back the water level data in real time through wireless communication technology.

[0018] Furthermore, the risk avoidance data described in step S4 also includes the regional pipeline network abnormality rate F i , the specific method of obtaining it is:

[0019] The area to be assessed is divided into n regions, and different regions are numbered, specifically {1, 2, 3...i...n}, and the number of past rainstorm disasters in different regions is obtained as H, and the total number of pipelines built in the region during past rainstorm disasters is obtained as The total number of abnormal pipe networks in the area during the same rainstorm disaster is set to , then the regional pipeline network abnormality rate F in different areas i It can be calculated by the following formula:

[0020] *100%;

[0021] When simulating future rainfall on the three-dimensional model of the area to be assessed, turn off the F i Proportional pipe network.

[0022] Furthermore, the total number of abnormal pipe networks in the area to be assessed during the rainstorm disaster The acquisition process is as follows:

[0023] Step 1: Obtain the total number of abnormal pipe networks and the disaster season in the area to be assessed during the same rainstorm disaster, and build a data model of abnormal pipe networks in four seasons in the area to be assessed based on the SARIMA model;

[0024] Step 2: Get the time of the last rainstorm disaster in the area to be evaluated. If the time interval between the last rainstorm disaster in the area to be evaluated and the predicted rainstorm is less than half a month, then output If it is equal to 0, if the time interval between the last rainstorm disaster in the area to be assessed and the predicted rainstorm is greater than half a month, then proceed to the next step;

[0025] Step 3: Determine the season of the predicted rainstorm and input it into the abnormal pipe network data model of the four seasons in the area to be evaluated. The abnormal pipe network data model of the four seasons in the area to be evaluated outputs the total number of abnormal pipe networks when the rainstorm causes disasters in the current season. .

[0026] Furthermore, the specific output method of the rainstorm risk database of the area to be assessed in step S5 is as follows:

[0027] Step 1: Determine whether the cause of waterlogging in waterlogged area i is due to the catchment area or the pipe network;

[0028] Step 2: Output the severity level N of waterlogging according to whether the waterlogging in area i is caused by the catchment area or the pipe network. i or M i ;

[0029] Step 3: Obtain the GDP proportion G of waterlogged area i in the area to be assessed i , and the proportion of the population of waterlogged area i in the area to be assessed P i ;

[0030] Step 4: Integrate the risk data of all flooded areas i, including: G i , P i and N i or M i , and make a database output.

[0031] Furthermore, the process of determining the cause of waterlogging in waterlogged area i is as follows:

[0032] The total future rainfall in the flooded area i is obtained by using future meteorological data and recorded as J all , the current maximum water volume of the catchment area is recorded as V all , calculate J all With V all If the ratio is less than 1, it means that the area is not flooded due to water catchment problems. all With V allThe ratio is greater than 1. According to its specific value, the severity level N of the waterlogging in the waterlogged area i is given. i , N i Includes: low risk, medium risk, high risk, or very high risk.

[0033] Furthermore, when J all With V all When the ratio is less than 1, the future rainfall duration of waterlogged area i is divided into {2, 3...a} equal time periods according to future meteorological data, and then the future rainfall D in a single time period of waterlogged area i is calculated. all , and then combined with the regional pipeline network abnormality rate F i Calculate the maximum discharge volume L in a single time period of the flooded area i all , calculate D all With L all The ratio of D is greater than 1, indicating that area i will experience waterlogging due to insufficient pipe network capacity during this period. all With L all The ratio of and the duration of waterlogging are used to determine the severity of waterlogging in waterlogged area i.

[0034] Further, obtain D all With L all The duration of the period in which the ratio is greater than 1 is recorded as T a , get D all With L all The duration of the period in which the ratio is greater than 1 is b, and the area of ​​the waterlogged area i is recorded as S i， The ideal water depth per square meter in the flooded area i is Z i It can be calculated by the following formula:

[0035] *100

[0036] According to the ideal water depth Z i The specific value of gives the severity level M of waterlogging in waterlogged area i. i , M i Includes: low risk, medium risk, high risk, or very high risk.

[0037] Furthermore, the rainstorm risk database described in step S5 also includes rainstorm prevention suggestions, and the specific analysis process is as follows:

[0038] When the flood severity level N output by flood area i i When the risk is low or medium, determine whether the current water storage volume of the catchment area of ​​waterlogging area i is greater than J all With V all If the difference is greater than , the output suggestion is: empty the catchment area;

[0039] If the current water storage capacity of the catchment area i is greater than J all With V all The difference between the values ​​of the flood severity level N and the flood severity level N output by the flood area i i When the risk is high or extremely high, the output recommendation is: expand the maximum water catchment capacity of waterlogged area i;

[0040] When the flood severity level M output by flood area i i When the risk is low or medium, judge F i When J is equal to zero, all With V all Is the ratio less than 1? If so, output suggestions: check for abnormalities in the pipe network and ensure that the pipe network is unobstructed;

[0041] If F i When J is equal to zero, all With V all The ratio is still greater than 1, or the waterlogging severity level M output by waterlogging area i i When the risk is high or extremely high, the output suggestion is: expand the number of pipe networks in waterlogged area i.

[0042] The beneficial effects of the present invention are as follows:

[0043] 1. The method for risk assessment and analysis of excessive rainstorms in plain water network areas described in the present invention establishes multiple data modules, couples the multiple data modules into a regional model, and simulates rainfall through a rainfall module, thereby achieving real-time calculation of rainstorms occurring in the assessment area, which is more in line with the actual situation in the assessment area, thereby achieving the effect of improving the accuracy of risk assessment.

[0044] 2. The method for risk assessment and analysis of excessive rainstorms in plain water network areas described in the present invention analyzes the causes of waterlogging in waterlogged areas, thereby distinguishing different types of waterlogging situations, effectively assisting personnel in further analyzing and preventing waterlogging situations, and reducing the losses caused by rainstorm disasters in the areas to be assessed. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The present invention will be further described below in conjunction with the accompanying drawings.

[0046] Figure 1 It is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0047] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0048] like Figure 1As shown, a method for risk assessment and analysis of excessive rainstorms in plain water network areas according to an embodiment of the present invention comprises the following steps:

[0049] S1. Data collection: Obtain comprehensive data of the area to be assessed, including topography, hydraulic pipe network, hydrological water collection, station gates, river network and river channels, levees, past rainfall and humanities information;

[0050] S2, module coupling: Based on the acquired comprehensive data, build a comprehensive data module for the area to be evaluated, and construct a three-dimensional model of the area to be evaluated through the comprehensive data module;

[0051] S3, model verification: verify the accuracy of the three-dimensional model of the area to be evaluated. If the verification is qualified, proceed to the next step. If the verification is unqualified, it indicates that there are abnormal data in the comprehensive data collected in step S1. Find the abnormal data and correct it, then return to step S2 to optimize the comprehensive data module;

[0052] S4, simulated rainfall: access future meteorological data and risk avoidance data of the area to be assessed, and simulate future rainfall on the three-dimensional model of the area to be assessed based on the future meteorological data;

[0053] S5. Result output: By simulating future rainfall, when there is heavy rain, the three-dimensional model of the area to be assessed will simulate whether there is waterlogging according to the drainage functions of different areas, and output the heavy rain risk database of the area to be assessed based on the regional conditions of waterlogging in the area to be assessed.

[0054] According to the acquired comprehensive data, build a comprehensive data module, mainly including: build a terrain module with topographic data, build a hydraulic module with hydraulic pipe network data, build a hydrological module with hydrological water collection data, build a station lock module with station lock data, build a river network module with river network and river channel data, build a dike module with dike data, and build a humanities module with humanities information data;

[0055] A terrain module, wherein the terrain module is configured to simulate the geomorphic features of the area to be evaluated; the geomorphic features are formed by a combination of elevation point data;

[0056] A hydraulic module, wherein the hydraulic module is configured to input node attributes and pipeline attributes through the pipeline network census data of the area to be evaluated; the input node attributes include the pipeline network system type, node coordinates, manhole bottom elevation, and manhole ground elevation; pipeline attributes include pipeline shape, length, height and width, roughness, and pipe bottom elevation; establish a spatial topological relationship between the upstream and downstream node numbers of the pipeline, simulate the dynamics of water bodies inside the drainage network, and perform hydrodynamic calculations on the water flow inside the pipeline network based on the one-dimensional Saint-Venant equations;

[0057] A hydrological module, wherein the hydrological module is configured to feedback the water collection characteristics of the watershed in the area to be evaluated; the water collection characteristics include the watershed area, the runoff parameters, and the runoff coefficient;

[0058] The station gate module is configured to simulate the basic information of the station gate in the area to be evaluated; the basic information of the station gate includes the drainage flow of the pump station, the gate top height, the gate bottom height, the number of gate holes, the gate hole width, and the station gate coordinate information. By inputting the control and scheduling parameters of the station gate, the gate opening and closing water level, the pump station opening and closing process curve and other properties are simulated;

[0059] A river network module, wherein the river network module is configured to simulate the river parameters of the area to be evaluated; the basic attributes of the river network, the topological connection relationship and the river confluence direction are determined through the river centerline, the cross-section line and the river bank line, and the gridded river system is simulated;

[0060] A dike module, wherein the dike module is configured to simulate dike parameters of the area to be assessed; through key parameters such as the location, crest height, and width of the dike, the module simulates complex hydraulic processes such as leakage and breach of the dike;

[0061] A water level module, wherein the water level module is configured to simulate the flow movement and water level change of a river in the area to be assessed under a rainfall scenario;

[0062] The humanities module is configured to simulate and evaluate the humanities information of a region; the humanities information includes regional population density, regional GDP per capita, and the proportion of cultivated land in the region.

[0063] The specific steps for constructing a three-dimensional model of the area to be assessed using comprehensive data are as follows:

[0064] First, the hydraulic module, hydrological module, and river network module are coupled to construct a one-dimensional analysis, convert rainfall into surface runoff, and flow the surface runoff into the hydraulic module for hydraulic calculation to form a one-dimensional model;

[0065] Then the one-dimensional model is coupled with the terrain module, levee module, station gate module and water level module to form a three-dimensional model;

[0066] In the module coupling process, the sub-catchment area is divided according to the established hydraulic module, and the land use type, runoff generation and convergence mode, runoff generation surface type and related runoff generation coefficient are defined in the sub-catchment area attribute table, so as to couple the hydrological module with the hydraulic module; the coupled model can perform pipe network drainage capacity analysis and node water level analysis: the hydrological module converts rainfall into surface runoff and enters the hydraulic module, and the hydraulic module transmits water flow through hydraulic calculation formulas. If the water flow exceeds the pipe network drainage capacity, it will overflow from the node;

[0067] The terrain module extracts the elevation point data of each pipeline and runoff surface in the hydraulic module and the hydrological module and couples it with the one-dimensional model. At the same time, the one-dimensional runoff mode or the two-dimensional runoff mode is selected by setting the attribute information of the hydrological module in different ways. The hydraulic module and the hydrological module can simulate the two-dimensional flooding process. When the incoming water collected in the pipe network exceeds its discharge capacity, the water will overflow from the node to the terrain module, forming two-dimensional water accumulation according to the different terrains, and conducting waterlogging risk analysis.

[0068] The river network module is combined with the hydraulic and hydrological module in the form of flap gates. The water flow in the pipe network enters the river channel in one direction through the flap gates. After coupling the river network module with the hydraulic and hydrological modules, the water flows into the river channel in one direction. The rising water level in the river channel has a supporting effect on the pipe network connected to the drainage outlet, causing the water level in the pipe network to rise, increasing the difficulty of discharge. When the water level in the river channel reaches the highest, the pipe network cannot continue to discharge water to the river channel;

[0069] The station lock module is usually represented by several independent or interconnected station lock structures. The structures usually exist in the model in the form of connections. The topological relationship is established by determining the coordinates of the upstream and downstream connection points. The station lock module can be connected to the hydraulic module or the river network module, or to the hydraulic module and the river network module at the same time.

[0070] The dike module is combined with the river network module. The water body of the river channel inside the dike area interacts with the river channel outside the dike through the dike. When the water level of the river channel inside the dike is higher than that of the river channel outside the dike, the river channel inside the dike overflows and discharges to the river channel outside the dike; when the water level of the river channel outside the dike is higher than that of the river channel inside the dike, the water level of the river channel outside the dike has a supporting effect on the river channel inside the dike, causing the water level of the river channel inside the dike to rise, making it difficult to discharge;

[0071] The water level module is combined with the levee module. By inputting the historical measured most unfavorable water level or the designed excessive rainfall water level data, the water level module data is converted into surface runoff and entered into the hydraulic module or river network module.

[0072] When the hydraulic module is coupled with the river network module, the end of the pipe network of the hydraulic module is connected to the river channel of the river network module; during the simulation, precipitation flows into the river channel through the end of the pipe network, and the rising water level in the river channel will have a supporting effect on the water flow inside the pipe network, affecting the water discharge of the pipe network. When the water level in the river channel rises to the highest water level, the pipe network outlet can no longer drain water, and overflow occurs at the node. The water flow forms two-dimensional water accumulation on the two-dimensional terrain module, which improves the authenticity of the simulation.

[0073] Furthermore, the specific method of model verification described in step S3 is as follows:

[0074] Step 1: Obtain historical data on past rainstorm disasters in the area to be assessed;

[0075] Step 1: Put the rainfall data when the rainstorm disaster occurs into the three-dimensional model for simulation;

[0076] Step 3: Compare the historical disaster characteristics with the three-dimensional model simulation; if the comparison results are consistent, the verification is qualified; if the comparison results are inconsistent, the verification fails.

[0077] When using the established model for simulation, its accuracy needs to be verified in advance. If there are problems with the model, resulting in the risk of heavy rain in some areas without early warning, it is very likely to cause significant losses. This application substitutes the historical heavy rain disaster data of the area to be evaluated, simulates the model, and compares the simulation results with the actual disaster situation, so as to judge the accuracy of the model and improve the accuracy of the model when simulating heavy rain.

[0078] It should be noted that when verifying the regional model, it is necessary to consider the actual pipeline network construction and watershed planning. When verifying the rainstorm disaster situation in different periods, the pipeline system and watershed area that have not been established in the area at that time should be shielded to ensure the accuracy of the verification.

[0079] Furthermore, the risk avoidance data in step S4 includes the real-time water level of the catchment area, which is obtained by installing a water level monitoring device inside the catchment area and feeding back the water level data in real time through wireless communication technology.

[0080] Before a rainstorm arrives, the factors that cause a rainstorm disaster are not just future rainfall. The current existing technology is too one-sided to judge the risk of rainstorm disasters only by rainfall. In reality, there are situations where the rainfall in the area is not large but still causes waterlogging. One of the reasons for this is that the water level in the catchment area of ​​the area is too high. The high water level in the catchment area will result in the catchment area being unable to store too much rainwater when a rainstorm comes, which will in turn cause the catchment area to break and form waterlogging. This application monitors the water level in the catchment area in real time, thereby correcting the model, and can calculate the storage situation of the catchment area more in line with reality, which helps to improve the accuracy of rainstorm risk assessment.

[0081] Furthermore, the risk avoidance data described in step S4 also includes the regional pipeline network abnormality rate F i , the specific method of obtaining it is:

[0082] The area to be assessed is divided into n regions, and different regions are numbered, specifically {1, 2, 3...i...n}, and the number of past rainstorm disasters in different regions is obtained as H, and the total number of pipelines built in the region during past rainstorm disasters is obtained as The total number of abnormal pipe networks in the area during the same rainstorm disaster is set to , then the regional pipeline network abnormality rate F in different areas i It can be calculated by the following formula:

[0083] *100%;

[0084] When simulating future rainfall on the three-dimensional model of the area to be assessed, turn off the F i Proportional pipe network.

[0085] In real life, there will be more or less abnormalities in the pipeline network, such as abnormal blockage and damage of the pipeline network. These situations are emergencies and cannot be effectively predicted. When simulating the risk of heavy rain, the existing technology often assumes that the pipeline system in the area is normal, which is bound to be inconsistent with the actual situation, resulting in inaccurate evaluation results. By calculating the regional pipeline network abnormality rate F in different areas, the regional pipeline network abnormality rate F is calculated. i , according to the regional pipeline network abnormality rate F i To simulate future anomalies, F should be turned off when simulating rainfall through the three-dimensional model of the area to be evaluated. i The number of pipe networks in proportion can improve the accuracy of rainfall simulation to a certain extent; it should be noted that the total number of pipe networks during previous rainstorm disasters R i It is necessary for personnel to collect data synchronously when collecting data in step S1; specifically, after each rainstorm, there must be staff from the water conservancy network department to dredge the network and record it in the register. R can be obtained through relevant records. i Specific value of

[0086] Wherein, t is any positive integer from 1 to H. represents the total number of pipe networks in the area when the tth rainstorm caused a disaster, represents the total number of abnormal pipe networks in the area during the t-th rainstorm disaster; i is any positive integer from 1 to n, F i represents the regional pipe network anomaly rate of the ith region. When simulating rainfall through the three-dimensional model of the area to be evaluated, F should be closed. i The number of proportional pipe networks can be increased to improve the accuracy of the simulation.

[0087] Furthermore, the total number of abnormal pipe networks in the area to be assessed during the rainstorm disaster The acquisition process is as follows:

[0088] Step 1: Obtain the total number of abnormal pipe networks and the disaster season in the area to be assessed during the same rainstorm disaster, and build a data model of abnormal pipe networks in four seasons in the area to be assessed based on the SARIMA model;

[0089] Step 2: Get the time of the last rainstorm disaster in the area to be evaluated. If the time interval between the last rainstorm disaster in the area to be evaluated and the predicted rainstorm is less than half a month, then output If it is equal to 0, if the time interval between the last rainstorm disaster in the area to be assessed and the predicted rainstorm is greater than half a month, then proceed to the next step;

[0090] Step 3: Determine the season of the predicted rainstorm and input it into the abnormal pipe network data model of the four seasons in the area to be evaluated. The abnormal pipe network data model of the four seasons in the area to be evaluated outputs the total number of abnormal pipe networks when the rainstorm causes disasters in the current season. .

[0091] Specifically, the data model of abnormal pipeline networks in four seasons in the area to be evaluated obtains the number of historical abnormal pipeline networks, disaster-causing seasons and disaster-causing times when heavy rains occurred in the area to be evaluated, and divides them by season. Output the results; it should be noted that when the interval between two rainstorms is short, it is assumed that the pipe network system has been completely cleared and prevented from clogging after the last rainstorm, so the output is equal to 0;

[0092] When a rainstorm disaster occurs, the abnormality rate of the pipeline network in different seasons is also different. This is because heavy rain is often accompanied by strong winds. In spring, the branches and leaves on the trees have not yet fully grown, and in winter, the fallen leaves on the trees have basically fallen completely. This makes the road surface in the area to be evaluated often clean and leafless, so the probability of foreign objects blocking the pipeline network during the drainage process of the pipeline network is low; in summer or autumn, there are often more leaves on the trees, especially in autumn, when the leaves fall off more easily. At this time, the pipeline network is often prone to accumulation of more leaves and blockage, resulting in a higher abnormality rate of the pipeline network; this application distinguishes the seasons to distinguish the F in different seasons. i Evaluate so that F i The numerical values ​​are more accurate and closer to reality, which improves the simulation effect of the model. It is of great significance for accurately issuing rainstorm disaster warnings and making scientific decisions on disaster prevention, mitigation and relief.

[0093] Furthermore, the specific output method of the rainstorm risk database of the area to be assessed in step S5 is as follows:

[0094] Step 1: Determine whether the cause of waterlogging in waterlogged area i is due to the catchment area or the pipe network;

[0095] Step 2: Output the severity level N of waterlogging according to whether the waterlogging in area i is caused by the catchment area or the pipe network. i or M i ;

[0096] Step 3: Obtain the GDP proportion G of waterlogged area i in the area to be assessed i , and the proportion of the population of waterlogged area i in the area to be assessed P i ;

[0097] Step 4: Integrate the risk data of all flooded areas i, including: Gi , P i and N i or M i , and make a database output.

[0098] At present, when assessing the risk of heavy rain, existing technologies often simply judge whether a disaster will occur based on the total rainfall. However, when a heavy rain actually comes, if the rainfall per unit time in a certain area exceeds the bearing capacity of its pipe network, waterlogging disasters will definitely occur in the area.

[0099] This application analyzes the causes of waterlogging in waterlogged area i, thereby distinguishing different types of waterlogging, effectively assisting personnel to further analyze and prevent waterlogging, and at the same time, through the form of a database, combined with the GDP proportion of waterlogged area i in the area to be evaluated, G i , and the proportion of the population of waterlogged area i in the area to be assessed P i When it is necessary to prevent waterlogging in area i, personnel can combine relevant G i With P i The data can be used to tilt prevention resources and reduce the losses caused by heavy rains in the assessed areas.

[0100] Furthermore, the process of determining the cause of waterlogging in waterlogged area i is as follows:

[0101] The total future rainfall in the flooded area i is obtained by using future meteorological data and recorded as J all , the current maximum water volume of the catchment area is recorded as V all (The current water storage capacity of the catchment area is estimated through the real-time water level of the catchment area, and the current maximum water collection capacity V is calculated by subtracting the current water storage capacity of the catchment area from the maximum water collection capacity of the catchment area all ), calculate J all With V all If the ratio is less than 1, it means that the area is not flooded due to water catchment problems. all With V all The ratio is greater than 1. According to its specific value, the severity level N of the waterlogging in the waterlogged area i is given. i , N i Includes: low risk, medium risk, high risk, or very high risk.

[0102] When evaluating the risk of heavy rain through future meteorological data, the existing technology generally does not take into account the actual water volume of the catchment area, which will cause errors in the evaluation process, that is, there is a situation where waterlogging occurs in the area when there is no risk, so that the area does not book a treatment plan in advance, resulting in property losses; However, through the real-time water level of the catchment area collected in S4, the actual water volume of the waterlogged area i can be accurately calculated. By comparing the future rainfall in the area, the risk of heavy rain can be effectively estimated, thereby improving the subsequent evaluation of the severity of waterlogging N i Accuracy of judgment;

[0103] Specifically, when J all With V all When the ratio is greater than 1.0 and less than 1.1, output N i is low risk; when J all With V all When the ratio is greater than 1.1 and less than 1.3, output N i For medium risk; when J all With V all When the ratio is greater than 1.3 and less than 1.5, output N i For high risk; when J all With V all When the ratio is greater than 1.5, output N i For extremely high risks, by quantifying the water catchment volume of waterlogged area i and providing feedback on the overall situation of the region in a numerical manner, regional management can make corresponding rainstorm risk prevention measures based on the actual situation in the region.

[0104] Furthermore, when J all With V all When the ratio is less than 1, the future rainfall duration of waterlogged area i is divided into {2, 3...a} equal time periods according to future meteorological data, and then the future rainfall D in a single time period of waterlogged area i is calculated. all , and then combined with the regional pipeline network abnormality rate F i Calculate the maximum discharge volume L in a single time period of the flooded area i all , calculate D all With L all The ratio of D is greater than 1, indicating that area i will experience waterlogging due to insufficient pipe network capacity during this period. all With L all The ratio of and the duration of waterlogging are used to determine the severity of waterlogging in waterlogged area i.

[0105] When the rainfall intensity in a certain area is too high and exceeds the load of the pipe network in the area, waterlogging will inevitably occur in the area. This waterlogging will gradually disappear as the rainfall intensity decreases, but the losses caused are irreversible, and disaster prevention needs to be carried out in advance. In the existing technology, when evaluating the risk of heavy rain, the rainfall intensity is often used as a parameter to calculate the risk. It is not clear whether it will cause an impact and what kind of impact it will cause, which causes great trouble to the prevention of heavy rain disasters in the region.

[0106] In particular, when the pipe network system in a certain area is not well developed, its drainage per unit time is limited. If the rainfall per unit time is too large and exceeds the drainage per unit time of the area, it will cause a certain degree of urban waterlogging. At the same time, the total rainfall of this rainstorm happens to be within the range that the catchment area of ​​the area can bear. In this case, the existing technology is very likely to give a low-risk or no-risk prompt for this rainstorm. However, in reality, the area does experience waterlogging due to drainage capacity reasons, resulting in property losses. This application distinguishes the causes of waterlogging by calculation, thereby screening out the causes of D all With L all The resulting waterlogging scenarios were identified and classified and analyzed, which improved the information on regional rainstorm risk assessment, avoided the situation where disasters occurred without early warning due to the intensity of rainstorms, and improved the completeness of rainstorm risk assessment.

[0107] Further, obtain D all With L all The duration of the period in which the ratio is greater than 1 is recorded as T a , get D all With L all The duration of the period in which the ratio is greater than 1 is b, and the area of ​​the waterlogged area i is recorded as S i， The ideal water depth per square meter in the flooded area i is Z i It can be calculated by the following formula:

[0108] *100

[0109] According to the ideal water depth Z i The specific value of gives the severity level M of waterlogging in waterlogged area i. i , M i Includes: low risk, medium risk, high risk, or very high risk.

[0110] By calculating D all With L allThe ratio of water level to rainfall level can be used to estimate the highest water level during the duration of heavy rainfall, and the disaster situation of waterlogging can be judged by the highest water level, so as to facilitate risk prevention in the area; for example, appropriate water retaining lines should be arranged in advance at the entrances of underground places such as subway stations and underground parking lots, so as to effectively protect the property in the area and avoid further losses;

[0111] Specifically, when Z i When the value is greater than 10 and less than 20, output M i is low risk; when Z i When the value is greater than 20 and less than 50, output M i is medium risk; when Z i When the value is greater than 50 and less than 100, output M i为 High risk; when Z i When the value is greater than 100, output M i For extremely high risks, by quantifying the depth of waterlogging in waterlogged area i, the waterlogging situation in waterlogged area i can be effectively predicted so that personnel can deploy relevant measures to avoid property losses.

[0112] Furthermore, the rainstorm risk database described in step S5 also includes rainstorm prevention suggestions, and the specific analysis process is as follows:

[0113] When the flood severity level N output by flood area i i When the risk is low or medium, determine whether the current water storage volume of the catchment area of ​​waterlogging area i is greater than J all With V all If the difference is greater than , the output suggestion is: empty the catchment area;

[0114] If the current water storage capacity of the catchment area i is greater than J all With V all The difference between the values ​​of the flood severity level N and the flood severity level N output by the flood area i i When the risk is high or extremely high, the output suggestion is: expand the maximum water collection capacity of waterlogged area i; the specific output value is: the current maximum water collection capacity of waterlogged area i is recorded as V all Multiply by J all With V all The ratio of

[0115] When the flood severity level M output by flood area i i When the risk is low or medium, judge F i When J is equal to zero, all With V all Is the ratio less than 1? If so, output suggestions: check for abnormalities in the pipe network and ensure that the pipe network is unobstructed;

[0116] If F i When J is equal to zero,all With V all The ratio is still greater than 1, or the waterlogging severity level M output by waterlogging area i i When the risk is high or extremely high, the output suggestion is: expand the number of pipe networks in waterlogged area i; the specific output value is: the number of pipe networks in waterlogged area i multiplied by D all With L all ratio.

[0117] In the prior art, the assessment of rainstorm risk can often only achieve a simple assessment function, and will not further analyze the risks and causes of rainstorm disasters. It also does not take into account that the causes of rainstorm disasters in different areas of the same region are also different, and thus it is impossible to effectively give specific prevention suggestions; this application first divides the area to be assessed into various regions, classifies and assesses different regions, and also distinguishes and judges the causes of waterlogging in different regions, so as to effectively find out the pain points of rainstorm prevention in different regions, and give different prevention suggestions based on the pain points, which effectively helps the area to be assessed to resist rainstorms in the future, and is of great significance for accurately issuing rainstorm disaster warnings and making scientific decisions on disaster prevention, mitigation and relief.

[0118] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for risk assessment and analysis of excessive rainstorms in plain water network areas, characterized by: The following steps are involved: S1. Data collection: Obtain comprehensive data of the area to be assessed, including topography, hydraulic pipe network, hydrological water collection, station gates, river network and river channels, levees, past rainfall and humanities information; S2, module coupling: Based on the acquired comprehensive data, build a comprehensive data module for the area to be evaluated, and construct a three-dimensional model of the area to be evaluated through the comprehensive data module; S3, model verification: verify the accuracy of the three-dimensional model of the area to be evaluated. If the verification is qualified, proceed to the next step. If the verification is unqualified, it indicates that there are abnormal data in the comprehensive data collected in step S1. Find the abnormal data and correct it, then return to step S2 to optimize the comprehensive data module; S4, simulated rainfall: access future meteorological data and risk avoidance data of the area to be assessed, and simulate future rainfall on the three-dimensional model of the area to be assessed based on the future meteorological data; S5. Result output: By simulating future rainfall, when there is heavy rain, the three-dimensional model of the area to be assessed will simulate whether there is waterlogging according to the drainage functions of different areas, and output the heavy rain risk database of the area to be assessed based on the regional conditions of waterlogging in the area to be assessed.

2. The method for risk assessment and analysis of excessive rainstorms in plain water network areas according to claim 1 is characterized by: The specific method of model verification described in step S3 is as follows: Step 1: Obtain historical data on past rainstorm disasters in the area to be assessed; Step 1: Put the rainfall data when the rainstorm disaster occurs into the three-dimensional model for simulation; Step 3: Compare the historical disaster characteristics with the three-dimensional model simulation; if the comparison results are consistent, the verification is qualified; if the comparison results are inconsistent, the verification fails.

3. The method for risk assessment and analysis of excessive rainstorms in plain water network areas according to claim 2 is characterized by: The risk avoidance data in step S4 includes the real-time water level of the catchment area, which is obtained by installing a water level monitoring device inside the catchment area and feeding back the water level data in real time through wireless communication technology.

4. The method for risk assessment and analysis of excessive rainstorms in plain water network areas according to claim 3 is characterized by: The risk avoidance data described in step S4 also includes the regional pipeline network abnormality rate F i , the specific method of obtaining it is: The area to be assessed is divided into n regions, and different regions are numbered, specifically {1, 2, 3...i...n}, and the number of past rainstorm disasters in different regions is obtained as H, and the total number of pipelines built in the region during past rainstorm disasters is obtained as The total number of abnormal pipe networks in the area during the same rainstorm disaster is set to , then the regional pipeline network abnormality rate F in different regions i It can be calculated by the following formula: *100%; When simulating future rainfall on the three-dimensional model of the area to be assessed, turn off the F i Proportional pipe network.

5. The method for risk assessment and analysis of excessive rainstorms in plain water network areas according to claim 4 is characterized by: The total number of abnormal pipe networks in the area to be assessed during the rainstorm disaster The acquisition process is as follows: Step 1: Obtain the total number of abnormal pipe networks and the disaster season in the area to be assessed during the same rainstorm disaster, and build a data model of abnormal pipe networks in four seasons in the area to be assessed based on the SARIMA model; Step 2: Get the time of the last rainstorm disaster in the area to be evaluated. If the time interval between the last rainstorm disaster in the area to be evaluated and the predicted rainstorm is less than half a month, then output If it is equal to 0, if the time interval between the last rainstorm disaster in the area to be assessed and the predicted rainstorm is greater than half a month, then proceed to the next step; Step 3: Determine the season of the predicted rainstorm and input it into the abnormal pipe network data model of the four seasons in the area to be evaluated. The abnormal pipe network data model of the four seasons in the area to be evaluated outputs the total number of abnormal pipe networks when the rainstorm causes disasters in the current season. .

6. The method for risk assessment and analysis of excessive rainstorms in plain water network areas according to claim 5 is characterized by: The specific output method of outputting the rainstorm risk database of the area to be assessed in step S5 is as follows: Step 1: Determine whether the cause of waterlogging in waterlogged area i is due to the catchment area or the pipe network; Step 2: Output the severity level N of waterlogging according to whether the waterlogging in area i is caused by the catchment area or the pipe network. i or M i ; Step 3: Obtain the GDP proportion G of waterlogged area i in the area to be assessed i , and the proportion of the population of waterlogged area i in the area to be assessed P i ; Step 4: Integrate the risk data of all flooded areas i, including: G i , P i and N i or M i , and make a database output.

7. The method for risk assessment and analysis of excessive rainstorms in plain water network areas according to claim 6 is characterized by: The process of determining the cause of waterlogging in waterlogged area i is as follows: The total future rainfall in the flooded area i is obtained by using future meteorological data and recorded as J all , the current maximum water volume of the catchment area is recorded as V all , calculate J all With V all If the ratio is less than 1, it means that the area is not flooded due to water catchment problems. all With V all The ratio is greater than 1. According to its specific value, the severity level N of the waterlogging in the waterlogged area i is given. i , N i Includes: low risk, medium risk, high risk, or very high risk.

8. The method for risk assessment and analysis of excessive rainstorms in plain water network areas according to claim 7 is characterized by: When J all With V all When the ratio is less than 1, the future rainfall duration of waterlogged area i is divided into {2, 3...a} equal time periods according to future meteorological data, and then the future rainfall D in a single time period of waterlogged area i is calculated. all , and then combined with the regional pipeline network abnormality rate F i Calculate the maximum discharge volume L in a single time period of the flooded area i all , calculate D all With L all The ratio of D is greater than 1, indicating that area i will experience waterlogging due to insufficient pipe network capacity during this period. all With L all The ratio of and the duration of waterlogging are used to determine the severity of waterlogging in waterlogged area i.

9. The method for risk assessment and analysis of excessive rainstorms in plain water network areas according to claim 8 is characterized by: Get D all With L all The duration of the period in which the ratio is greater than 1 is recorded as T a , get D all With L all The number of durations during which the ratio of is greater than 1 is b, and the area of ​​waterlogged area i is recorded as S i， The ideal water depth per square meter in the flooded area i is Z i It can be calculated by the following formula: *100 According to the ideal water depth Z i The specific value of gives the severity level M of waterlogging in waterlogged area i. i , M i Includes: low risk, medium risk, high risk, or very high risk.

10. The method for risk assessment and analysis of excessive rainstorms in plain water network areas according to claim 9 is characterized by: The rainstorm risk database described in step S5 also includes rainstorm prevention suggestions, and the specific analysis process is as follows: When the flood severity level N output by flood area i i When the risk is low or medium, determine whether the current water storage volume of the catchment area of ​​waterlogging area i is greater than J all With V all If the difference is greater than , the output suggestion is: drain the catchment area; If the current water storage capacity of the catchment area i is greater than J all With V all The difference between the values ​​of the flood severity level N and the flood severity level N output by the flood area i i When the risk is high or extremely high, the output recommendation is: expand the maximum water catchment capacity of waterlogged area i; When the flood severity level M output by flood area i i When the risk is low or medium, judge F i When J is equal to zero, all With V all Is the ratio less than 1? If so, output suggestions: check for abnormalities in the pipe network and ensure that the pipe network is unobstructed; If F i When J is equal to zero, all With V all The ratio is still greater than 1, or the waterlogging severity level M output by waterlogging area i i When the risk is high or extremely high, the output suggestion is: expand the number of pipe networks in waterlogged area i.

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