Urban waterlogging risk analysis method, device and electronic equipment

Abstract

The present invention provides a method, device and electronic device for analyzing urban waterlogging risk, belonging to the field of data processing technology, the method comprising: establishing an urban surface flooding simulation model to obtain a waterlogging map of the city; performing overlay analysis on a facility distribution map, a population distribution map and a waterlogging map to obtain a waterlogging risk value, several sub-facility impact values, several sub-population impact values ​​and several sub-economic loss values ​​of each grid unit; determining a waterlogging risk level value of any grid unit based on a result of weighted summation of multiple sub-element values; the first weight of multiple sub-element values ​​is predetermined based on the importance of the sub-element relative to the parent element; determining a waterlogging risk level map of the city based on the waterlogging risk level values ​​of all grid units. The present invention can comprehensively consider the inherent impact and extended impact of waterlogging events occurring in the city, more scientifically and reasonably determine a waterlogging risk level map of the city, and accurately identify areas in the city that are severely affected by waterlogging.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method, device and electronic equipment for analyzing urban waterlogging risk. Background Art

[0002] Analyzing urban waterlogging risks is an important part of effectively preventing and controlling urban waterlogging.

[0003] At present, the commonly used method for urban waterlogging risk analysis is to analyze the risk of urban waterlogging events themselves, that is, to determine the waterlogging risk level of different areas in the city by analyzing the depth and flow rate of urban waterlogging.

[0004] However, determining the urban waterlogging risk level by simply analyzing the risks of waterlogging events themselves does not take into account the particularity of waterlogging events occurring in cities, that is, it does not take into account other impacts of waterlogging events on cities. As a result, the waterlogging risk level determined by the analysis cannot accurately identify areas in the city that are severely affected by waterlogging, making it impossible to help effectively carry out waterlogging prevention and control work. Summary of the invention

[0005] The present invention provides a method, device and electronic equipment for analyzing urban waterlogging risk, which are used to solve the defect that the waterlogging risk level determined by analysis in the prior art cannot accurately identify the areas in the city that are seriously affected by waterlogging, and can accurately identify the areas in the city that are seriously affected by waterlogging, so as to help effectively carry out waterlogging prevention and control work.

[0006] The present invention provides a method for analyzing urban waterlogging risk, comprising:

[0007] Establish a simulation model for urban surface flooding and obtain urban waterlogging maps;

[0008] Using spatial analysis tools, the facility distribution map, population distribution map and waterlogging map of the city are overlaid and analyzed to obtain multiple sub-element values ​​of each grid unit in the city; the multiple sub-element values ​​include waterlogging risk value, several sub-facility impact values, several sub-population impact values ​​and several sub-economic loss values;

[0009] For any grid cell, based on the result of weighted summation of the multiple sub-element values ​​and their first weights, determine the waterlogging risk level value of the any grid cell; the first weights of the multiple sub-element values ​​are predetermined based on the importance of the sub-element relative to the parent element;

[0010] Based on the waterlogging risk level values ​​of all grid cells, a waterlogging risk level map of the city is determined.

[0011] According to a method for analyzing urban waterlogging risk provided by the present invention, before determining the waterlogging risk level value of any grid cell based on the result of weighted summation of the multiple sub-element values ​​and their first weights, determining the first weights of the multiple sub-element values ​​based on the importance of the sub-element relative to the parent element includes:

[0012] Determining a second weight of each of the parent elements;

[0013] For a first parent element including multiple child elements, a judgment matrix is ​​constructed based on the comparison result of the importance between every two child elements in the multiple child elements; each column value of the judgment matrix is ​​normalized to obtain a normalized judgment matrix; the normalized judgment matrix is ​​added row by row and normalized to obtain a weight feature vector of the first parent element; based on the weight feature vector, the weights of the multiple child elements are determined to determine the first weights of the sub-element values ​​corresponding to the multiple child elements;

[0014] For a second parent element that includes two or fewer child elements, the first weight of the child element values ​​corresponding to the two or fewer child elements is determined based on the second weight of the parent element.

[0015] According to a method for analyzing urban waterlogging risk provided by the present invention, before determining the weights of the plurality of sub-elements based on the weight feature vector, the method comprises:

[0016] Performing a consistency check on the judgment matrix;

[0017] If the consistency check passes, determining the weights of the plurality of sub-elements based on the weight feature vector;

[0018] If the consistency check fails, the importance comparison result is updated, a new judgment matrix is ​​constructed, a new weight feature vector is determined based on the new judgment matrix, and the new judgment matrix is ​​checked for consistency again until the consistency check passes.

[0019] According to a method for analyzing urban waterlogging risk provided by the present invention, the waterlogging risk value is determined based on the following method:

[0020] Determine the flooding time disaster factor based on the simulated flooding time and simulated flooding depth;

[0021] Determining a water depth hazard parameter based on the simulated water depth;

[0022] The waterlogging risk value is determined based on the simulated waterlogging time, the simulated waterlogging depth, the waterlogging time disaster factor, the water depth hazard parameter and the simulated waterlogging flow rate.

[0023] According to a method for analyzing urban waterlogging risk provided by the present invention, the sub-economic loss values ​​include residential economic loss values, hospital economic loss values, school economic loss values ​​and commercial economic loss values;

[0024] The economic loss value of the residential buildings is determined based on the number, value and first loss rate curve of the flooded residential buildings in the grid unit; the first loss rate curve is determined based on the movable attributes, number of floors, number of mezzanines and number of basements of the flooded residential buildings;

[0025] The hospital economic loss value is determined based on the number, value and second loss rate curve of the flooded hospitals in the grid unit; the second loss rate curve is determined based on the movable attributes, number of floors, number of mezzanines and number of basements of the flooded hospitals;

[0026] The school economic loss value is determined based on the number, value and third loss rate curve of the flooded schools in the grid unit; the third loss rate curve is determined based on the movable attributes, number of floors, number of mezzanines and number of basements of the flooded schools;

[0027] The economic loss value of the commercial entity is determined based on the number of flooded commercial structures in the grid unit, the duration of the flooding shutdown and the output value per unit time.

[0028] According to a method for analyzing urban waterlogging risk provided by the present invention, the sub-population impact value includes a resident population impact value, an employed population impact value and a visiting population impact value;

[0029] The residential population impact value is determined based on the number of residents in the grid unit; the number of residents is the number of map users whose nighttime stay time is greater than their daytime stay time within a preset period and whose mobile terminals are connected to a stable wireless network signal;

[0030] The employment population impact value is determined based on the number of employed people in the grid unit; the number of employed people is the number of map users whose daytime stay time is greater than nighttime stay time and whose mobile terminals are connected to stable wireless network signals within the preset time period;

[0031] The visiting population impact value is determined based on the number of visiting population excluding the number of resident population and the number of employed population within the preset time period.

[0032] According to a method for analyzing urban waterlogging risk provided by the present invention, the sub-facility impact values ​​include subway station impact values, water supply and power supply facility impact values, bus station impact values, school impact values ​​and hospital impact values.

[0033] According to a method for analyzing urban waterlogging risk provided by the present invention, determining a waterlogging risk level map of the city based on waterlogging risk level values ​​of all grid cells includes:

[0034] Performing spatial intersection analysis on the boundaries of all the grid cells and all the community management units to determine the grid cells within each community management unit;

[0035] For any community management unit, based on the weighted sum of the waterlogging risk level values ​​of the grid units within the community management unit, determine the waterlogging risk level value of the community management unit;

[0036] Based on the waterlogging risk level values ​​of all community management units, a waterlogging risk level map of the city is determined.

[0037] The present invention also provides an urban waterlogging risk analysis device, comprising:

[0038] The waterlogging map acquisition module is used to establish a city surface flooding simulation model and obtain the city's waterlogging map;

[0039] A sub-element value determination module is used to use a spatial analysis tool to perform an overlay analysis on the facility distribution map, the population distribution map and the waterlogging map of the city to obtain multiple sub-element values ​​for each grid unit in the city; the multiple sub-element values ​​include a waterlogging risk value, a number of sub-facility impact values, a number of sub-population impact values ​​and a number of sub-economic loss values;

[0040] A risk level value determination module, for determining, for any grid cell, a waterlogging risk level value of the grid cell based on a result of weighted summation of the multiple sub-element values ​​and their first weights; the first weights of the multiple sub-element values ​​are predetermined based on the importance of the sub-element relative to the parent element;

[0041] The risk level map acquisition module is used to determine the waterlogging risk level map of the city based on the waterlogging risk level values ​​of all grid cells.

[0042] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, any of the above-mentioned urban waterlogging risk analysis methods is implemented.

[0043] The urban waterlogging risk analysis method, device and electronic equipment provided by the present invention obtain the sub-element values ​​of the waterlogging risk value, sub-facility impact value, sub-population impact value and sub-economic loss value of each grid unit by overlaying analysis on the waterlogging waterlogging map and the facility distribution map and population distribution map of the city, and determine the waterlogging risk level of different areas in the city by weighted summation calculation of the sub-element values ​​according to the weight determined by the sub-element relative to the parent element. It can comprehensively consider the impact and extended impact of waterlogging incidents occurring in the city, determine the waterlogging risk level map of the city more scientifically and reasonably, and accurately identify the areas in the city that are severely affected by waterlogging, so as to help effectively carry out waterlogging prevention and control work. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 This is one of the flow charts of the urban waterlogging risk analysis method provided by the present invention.

[0046] Figure 2 It is an example diagram of the first loss rate curve set provided by the present invention.

[0047] Figure 3 This is the second flow chart of the urban waterlogging risk analysis method provided by the present invention.

[0048] Figure 4 It is a structural schematic diagram of the urban waterlogging risk analysis device provided by the present invention.

[0049] Figure 5 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] It should be noted that, in the description of the present invention, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0052] The terms "first", "second", etc. in the present invention are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged when appropriate, so that the embodiments of the present invention can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" means at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0053] Combine the following Figure 1-Figure 5 The urban waterlogging risk analysis method, device and electronic device provided by the present invention are described. It should be noted that all actions of obtaining signals, information or data in the present invention are carried out under the premise of complying with the corresponding data protection laws and policies of the location and with the authorization given by the corresponding device owner.

[0054] Figure 1 This is one of the flow charts of the urban waterlogging risk analysis method provided by the present invention, such as Figure 1 As shown, the urban waterlogging risk analysis method includes but is not limited to steps 101 to 104.

[0055] It should be noted that the execution entity of the urban waterlogging risk analysis method provided by the present invention can be a server, a computer device, such as a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a personal digital assistant (PDA), etc.

[0056] Step 101: Establish an urban surface inundation simulation model and obtain a waterlogging map of the city.

[0057] The smallest unit in the urban surface inundation simulation model that assigns waterlogging data such as waterlogging time, waterlogging depth, and waterlogging flow rate for risk analysis is called a grid unit. Common grid units include 5m×5m grids and 10m×10m grids.

[0058] Specifically, an urban surface inundation simulation model is established by establishing a numerical model, coupling a digital elevation model (DEM), a rainfall model and a stormwater pipe network model. This can simulate the waterlogging data such as the waterlogging time, waterlogging depth, and waterlogging flow rate of each grid unit in the urban surface inundation simulation model under a certain rainfall level, and draw a city's urban waterlogging map based on these waterlogging data.

[0059] Among them, the water flow rate can describe the impact of water flow on people or objects and the harm caused by it during urban waterlogging under certain rainfall scenarios. The greater the water flow rate, the greater the impact of water flow on people or objects and the harm caused by it.

[0060] By obtaining the urban waterlogging map, it is possible to quickly and conveniently identify the grid cells on the urban surface that exceed the preset waterlogging depth, that is, to identify the urban waterlogging points.

[0061] Step 102: Using a spatial analysis tool, overlay analysis is performed on the facility distribution map, population distribution map and waterlogging map of the city to obtain a plurality of sub-element values ​​of each grid cell in the city.

[0062] The multiple sub-element values ​​include a waterlogging risk value, several sub-facility impact values, several sub-population impact values ​​and several sub-economic loss values.

[0063] Specifically, before performing overlay analysis on the facility distribution map, the population distribution map and the waterlogging map, the facility distribution map and the population distribution map are first obtained.

[0064] For example, obtain the city's facility distribution map from public geographic information platforms, third-party map services, open source map projects, etc.; obtain the city's population distribution map from public geographic information platforms, population distribution thematic maps, census databases, etc.

[0065] Among them, the facilities on the facility distribution map include but are not limited to the city’s subway stations, hospitals, schools, bus stops, power and water supply facilities, etc.

[0066] Spatial analysis tools (such as ArcGIS) are used to overlay the obtained facility distribution map, population distribution map and urban waterlogging map to obtain information such as facilities and population affected by urban waterlogging, and then determine multiple sub-element values ​​for each grid unit in the city, including waterlogging risk value, several sub-facility impact values, several sub-population impact values ​​and several sub-economic loss values.

[0067] Optionally, the waterlogging risk value is obtained by analyzing the waterlogging map using spatial analysis tools.

[0068] Optionally, the sub-facility impact value and the sub-economic loss value are obtained by analyzing the waterlogging map and the facility distribution map using a spatial analysis tool.

[0069] Optionally, the sub-population impact value is obtained by analyzing the waterlogging map and population distribution map using spatial analysis tools.

[0070] Step 103: for any grid cell, based on the result of weighted summation of the multiple sub-element values ​​and their first weights, determine the waterlogging risk level value of the any grid cell.

[0071] The first weights of the multiple child element values ​​are predetermined based on the importance of the child elements relative to the parent element.

[0072] The first weight is the weight of different sub-element values ​​corresponding to different sub-elements belonging to the same parent element when used for weighted summation to obtain the waterlogging risk level value of the grid unit.

[0073] The second weight is the weight pre-assigned to the parent element.

[0074] For example, when the sub-element value is a waterlogging risk value, there is only one sub-element that is a waterlogging risk element, and the parent element is a waterlogging element. The weights of the sub-element and the parent element corresponding to the sub-element value are the same.

[0075] For another example, when the sub-element value is a number of sub-facility impact values, the sub-element is a number of sub-facility impact elements, and the parent element is a waterlogging impact facility element. The weights of the sub-elements corresponding to different sub-element values ​​are predetermined based on the importance of the sub-element relative to the parent element, and the sum of the first weights of the sub-facility impact values ​​is equal to the second weight of the waterlogging impact facility element.

[0076] Similarly, when the sub-element value is a number of sub-population impact values, the sub-element is a number of sub-population impact elements, the parent element is the urban waterlogging impact population element, and the sum of the first weights of each sub-population impact value is equal to the second weight of the urban waterlogging impact population element; when the sub-element value is a number of sub-economic loss values, the sub-element is a number of sub-economic loss elements, the parent element is the urban waterlogging economic loss element, and the sum of the first weights of each sub-economic loss value is equal to the second weight of the urban waterlogging economic loss element.

[0077] Specifically, for any grid cell in the city, the waterlogging risk level value of the grid cell is determined based on the weighted sum of each sub-element value of the grid cell obtained by overlay analysis and its corresponding first weight. The spatial analysis tool is used to perform weighted summation calculation on each grid cell in the city, that is, the waterlogging risk level value of all grid cells in the city is obtained.

[0078] Step 104: Determine a waterlogging risk level map of the city based on the waterlogging risk level values ​​of all grid cells.

[0079] Specifically, after obtaining the waterlogging risk level values ​​of all grid cells in the city, the waterlogging risk level of each grid cell is determined according to the level interval in which the waterlogging risk level value of each grid cell is located, and then the waterlogging risk level map of the entire city is determined.

[0080] Optionally, according to different waterlogging risk levels, labels of different colors and / or shapes are allocated to areas with different waterlogging risk levels on the waterlogging risk level map to intuitively display the urban waterlogging risk.

[0081] For example, the higher the flood risk level of a certain area in a city, the higher the flood risk, and a warm fill color is assigned to the area; the lower the flood risk level of a certain area in a city, the lower the flood risk, and a cold fill color is assigned to the area.

[0082] The urban waterlogging risk analysis method provided by the present invention obtains the sub-element values ​​of the waterlogging risk value, sub-facility impact value, sub-population impact value and sub-economic loss value of each grid unit by overlaying analysis on the waterlogging waterlogging map and the facility distribution map and population distribution map of the city, and determines the waterlogging risk level of different areas in the city by weighted summation calculation of the sub-element values ​​according to the weights determined by the sub-element relative to the parent element. It can comprehensively consider the impact and extended impact of waterlogging incidents occurring in the city, determine the waterlogging risk level map of the city more scientifically and reasonably, accurately identify the areas in the city that are severely affected by waterlogging, and help to effectively carry out waterlogging prevention and control work.

[0083] Based on the above embodiment, as an optional embodiment, before determining the waterlogging risk level value of any grid cell based on the result of weighted summation of the multiple sub-element values ​​and their first weights for any grid cell, determining the first weights of the multiple sub-element values ​​based on the importance of the sub-element relative to the parent element includes:

[0084] Determining a second weight of each of the parent elements;

[0085] For a first parent element including multiple child elements, a judgment matrix is ​​constructed based on the comparison result of the importance between every two child elements in the multiple child elements; each column value of the judgment matrix is ​​normalized to obtain a normalized judgment matrix; the normalized judgment matrix is ​​added row by row and normalized to obtain a weight feature vector of the first parent element; based on the weight feature vector, the weights of the multiple child elements are determined to determine the first weights of the sub-element values ​​corresponding to the multiple child elements;

[0086] For a second parent element that includes two or fewer child elements, the first weight of the child element values ​​corresponding to the two or fewer child elements is determined based on the second weight of the parent element.

[0087] The first parent element is a parent element to which the number of child elements attributed is multiple.

[0088] The second parent element is a parent element to which the number of child elements attributed is two or less.

[0089] Specifically, before determining the waterlogging risk level value of the grid unit using the result of weighted summation of multiple sub-element values, it is necessary to determine the first weight of each sub-element value.

[0090] When determining the first weight of each child element value, first determine the second weight of each parent element. Generally speaking, the second weight of the parent element is determined based on historical analysis data, and the sum of the second weights of each parent element is equal to 1.

[0091] For a second parent element having only one child element, the second weight of the second parent element is also the first weight of the child element value corresponding to the child element.

[0092] For example, when the child element value is a waterlogging risk value, the first weight of the waterlogging risk value is also the second weight of the waterlogging element (parent element).

[0093] For the second parent element with two child elements, the second weight of the parent element can be directly allocated to the child element values ​​corresponding to the two child elements according to the comparison result of the importance between the two child elements.

[0094] For a first parent element with multiple child elements, a judgment matrix is ​​constructed based on the comparison result of the importance between every two child elements in the multiple child elements.

[0095] Taking the parent element as the flood economic loss element as an example, the child elements include four sub-economic loss elements: residential economic loss element, hospital economic loss element, school economic loss element, and commercial economic loss element. Table 1 is an example table of the importance comparison results of the parent element being the flood economic loss element. As shown in Table 1, a 4×4 judgment matrix can be determined based on the importance comparison results between every two of the four sub-elements.

[0096] Table 1 Example of comparison results of importance of elements whose parent element is economic loss from flooding

[0097]

[0098] After constructing the judgment matrix, normalize each column of the judgment matrix to obtain a normalized judgment matrix; add the normalized judgment matrix row by row and perform normalization to obtain the weight feature vector of the first parent element. According to the weight feature vector The transposed vector of , and transpose the vector The product of the value in and the second weight of the first parent element is used as the first weight of the sub-element value corresponding to each child element of the first parent element.

[0099] Optionally, after determining the parent elements used for urban waterlogging risk analysis and the child elements they include, the importance comparison result sets between every two child elements in all child elements under the same parent element can be determined based on historical statistical data with different screening conditions such as rainfall time and rainfall intensity, so that the importance comparison result set can be directly called when constructing the judgment matrix to quickly construct the judgment matrix.

[0100] Optionally, the importance comparison result between each two sub-elements in a plurality of sub-elements can be determined using a scaling method of 1-9. Table 2 is a scale definition table of the importance comparison result provided by the present invention. As shown in Table 2, the larger the scale data, the higher the importance of one sub-element relative to the other sub-element; the inverse of the scale represents the unimportance of one sub-element relative to the other sub-element.

[0101] Table 2 Scale definition table for comparison results of importance

[0102]

[0103] The urban waterlogging risk analysis method provided by the present invention aims at the different numbers of child elements belonging to the same parent element. When the number of child elements is less than two, the weight of the child element is directly determined according to the second weight of the parent element. When there are multiple child elements, the weight of the sub-element value corresponding to the child element is finally determined by constructing a judgment matrix and normalizing, adding by row, and normalizing again to obtain a weight feature vector. The weights of different child element values ​​under the parent element can be determined more objectively, scientifically and meticulously, thereby improving the calculation accuracy of the waterlogging risk level value of each grid unit, and finally improving the analysis accuracy of the urban waterlogging risk level map.

[0104] Based on the above embodiment, as an optional embodiment, before determining the weights of the plurality of sub-elements based on the weight feature vector, the method further includes:

[0105] Performing a consistency check on the judgment matrix;

[0106] If the consistency check passes, determining the weights of the plurality of sub-elements based on the weight feature vector;

[0107] If the consistency check fails, the importance comparison result is updated, a new judgment matrix is ​​constructed, a new weight feature vector is determined based on the new judgment matrix, and the new judgment matrix is ​​checked for consistency again until the consistency check passes.

[0108] Specifically, when a parent element includes multiple child elements, after obtaining a weight feature vector by constructing a judgment matrix and normalizing, adding rows, and normalizing again, the judgment matrix is ​​checked for consistency before determining the weights of the multiple child elements based on the weight feature vector.

[0109] If the consistency check passes, the first weight of the sub-element value corresponding to the sub-element may be determined according to the weight feature vector.

[0110] If the consistency check fails, it indicates that the obtained weight feature vector deviates from the actual situation. This deviation is caused by inappropriate importance comparison results. Therefore, the importance comparison results will be updated (for example, different importance comparison result sets will be called instead), and a new judgment matrix will be constructed based on the new importance comparison results. The new weight feature vector is re-determined, and the new judgment matrix is ​​checked for consistency again. If the consistency check fails again, the step of updating the importance comparison results to obtain the weight feature vector is executed again until the judgment matrix passes the consistency check, thereby determining the first weight of the sub-element value corresponding to the sub-element.

[0111] In one embodiment, the consistency check of the judgment matrix is ​​implemented based on the random consistency ratio (Consistency Ratio, CR).

[0112] Among them, the expression of random consistency ratio is as follows:

[0113] ; (1)

[0114] in, is the random consistency ratio; is the consistency index (CI) of the judgment matrix, It is the average random consistency index (Random Index, RI) of the judgment matrix.

[0115] Consistency index of judgment matrix The larger the value is, the greater the deviation of the judgment matrix from complete consistency. Conversely, the judgment matrix is ​​close to complete consistency. The higher the order n of the judgment matrix, the greater the deviation from complete consistency caused by human factors, and vice versa. That is, the error amount will increase with the increase of the order n of the judgment matrix. Therefore, the random consistency ratio is used. Implementing consistency check of the judgment matrix can eliminate the influence of the order of the judgment matrix.

[0116] Optionally, when the random consistency ratio When the ratio is less than or equal to the preset value, the consistency test of the judgment matrix passes; the random consistency ratio When it is greater than the preset ratio value, the consistency check of the judgment matrix fails, and the importance comparison result needs to be updated to adjust the judgment matrix.

[0117] For example, the preset ratio value is 0.1.

[0118] Table 3 is a list of average random consistency indicators provided by the present invention. As shown in Table 3, the average random consistency indicator of the judgment matrix is ​​determined from the list of average random consistency indicators according to the order of the judgment matrix. Moreover, when the order of the judgment matrix is ​​equal to 1 or 2, the judgment matrix always has complete consistency.

[0119] Table 3 List of average random consistency indicators

[0120]

[0121] In one embodiment, the consistency index of the judgment matrix is determined based on the following expression:

[0122] ; (2)

[0123] in, is the consistency index of the judgment matrix; is the largest eigenvalue of the judgment matrix; is the order of the judgment matrix.

[0124] Taking the parent element of the flood economic loss element as an example, the child elements include the residential economic loss element, hospital economic loss element, school economic loss element and commercial economic loss element. After constructing a 4th-order judgment matrix based on the importance comparison results, the weighted eigenvector (0.50, 0.07, 0.28, 0.15) is obtained, and the maximum eigenvalue is calculated. The consistency index is 4.18. The random consistency ratio is 0.06. It is 0.07, which is less than the preset ratio value of 0.1. The judgment matrix passes the consistency check and can determine the first weights of the economic loss values ​​of residential houses, hospitals, schools and businesses according to the weight eigenvector (0.50, 0.07, 0.28, 0.15).

[0125] The urban waterlogging risk analysis method provided by the present invention performs a consistency check on the judgment matrix for calculating the weighted characteristic vector after obtaining the weighted characteristic vector, updates the importance comparison result when the consistency check fails, reconstructs the judgment matrix and calculates the weighted characteristic vector, and determines the first weight of the sub-element value corresponding to each sub-element according to the weighted characteristic vector after the judgment matrix passes the consistency check, thereby ensuring the effectiveness of determining the waterlogging risk level value by weighted summation, improving the calculation accuracy of the waterlogging risk level value of each grid unit, and ultimately improving the analysis accuracy of the urban waterlogging risk level map.

[0126] Based on the above embodiment, as an optional embodiment, the water accumulation risk value is determined based on the following method:

[0127] Determine the flooding time disaster factor based on the simulated flooding time and simulated flooding depth;

[0128] Determining a water depth hazard parameter based on the simulated water depth;

[0129] The waterlogging risk value is determined based on the simulated waterlogging time, the simulated waterlogging depth, the waterlogging time disaster factor, the water depth hazard parameter and the simulated waterlogging flow rate.

[0130] Specifically, an urban surface inundation simulation model is established by establishing numerical models, DEM models, rainfall models and rainwater pipe network models, and the waterlogging data of each grid unit in the city under a certain rainfall level is simulated, including but not limited to simulated waterlogging time, simulated waterlogging depth, simulated waterlogging flow rate, etc., so as to determine the urban waterlogging map.

[0131] When calculating the waterlogging risk value of each grid unit of the urban waterlogging map, the waterlogging time hazard factor is determined according to the simulated waterlogging time and the simulated waterlogging depth, the water depth hazard parameter is determined according to the simulated waterlogging depth, and finally the waterlogging risk value is determined based on the simulated waterlogging time, the simulated waterlogging depth, the waterlogging time hazard factor, the water depth hazard parameter and the simulated waterlogging flow rate.

[0132] Optionally, after obtaining the simulated waterlogging time by establishing an urban surface flooding simulation model, a weighted average is taken of the simulated waterlogging time and the actual time when waterlogging occurred in the same grid unit under the same historical rainfall level, and the simulated waterlogging time after the weighted average is used to determine the waterlogging risk value, thereby improving the simulation accuracy of the urban surface flooding simulation model by correcting the simulated waterlogging time and preventing the simulation error from being amplified.

[0133] In one embodiment, the expression for determining the waterlogging risk value based on the simulated waterlogging time, the simulated waterlogging depth, the waterlogging time hazard factor, the water depth hazard parameter and the simulated waterlogging flow rate is as follows:

[0134] ; (3)

[0135] in, is the waterlogging risk value; is the simulated water depth (unit: meter); is the simulated waterlogging time (unit: hours); is the simulated water flow rate (unit: m / s); is the water depth hazard parameter; It is the disaster factor of waterlogging time.

[0136] Optionally, Table 4 is a corresponding relationship table of waterlogging time disaster factors provided by the present invention. As shown in Table 4, waterlogging time disaster factors The simulated water accumulation time can be obtained by simulation and simulated water depth Obtained by looking up the table.

[0137] Table 4 Corresponding relationship between flooding time and disaster factors

[0138]

[0139] In one embodiment, the mapping relationship between the water depth and the water depth hazard parameter is determined by comprehensively considering factors such as whether the water depth affects the passage of pedestrians and motor vehicles, whether it affects the clear identification of pedestrians and car drivers of the ground range and lane positions, whether it exceeds the height of the car exhaust pipe, air intake and other components, resulting in water ingress and engine stall and permanent damage to the vehicle, and whether it makes it difficult for minors or adults to stand firmly and their mouths and noses are located below the surface of the water when they fall and stand up.

[0140] For example, when the water depth is less than or equal to 0.15m, the water depth hazard parameter is 0.5; when the water depth is greater than 0.15m, the water depth hazard parameter is 1.0.

[0141] Optionally, different display colors are assigned to the grid cells of the waterlogging map according to different waterlogging risk values ​​of the grid cells, so as to intuitively display the waterlogging information about the city to the user.

[0142] For example, when the waterlogging risk value of the grid cell is less than 1.0, the grid cell is defined as a low-risk cell for waterlogging, and a green display color is assigned to the low-risk cell for waterlogging; when the waterlogging risk value of the grid cell is greater than or equal to 1.0 and less than 2.0, the grid cell is defined as a medium-risk cell for waterlogging, and a blue display color is assigned to the medium-risk cell for waterlogging; when the waterlogging risk value of the grid cell is greater than or equal to 2.0 and less than 3.0, the grid cell is defined as a high-risk cell for waterlogging, and a yellow display color is assigned to the high-risk cell for waterlogging; when the waterlogging risk value of the grid cell is greater than or equal to 3.0, the grid cell is defined as a high-risk cell for waterlogging, and a green display color is assigned to the high-risk cell for waterlogging.

[0143] Compared with the method of assessing waterlogging risk by only considering factors such as the depth and flow rate of waterlogging events, the urban waterlogging risk analysis method provided by the present invention couples the waterlogging time when determining the waterlogging risk to conduct waterlogging risk analysis, and further incorporates the product of the water depth hazard parameter and the waterlogging time hazard factor as a comprehensive hazard factor into the risk level evaluation. This can more reasonably, scientifically and accurately determine the waterlogging risk value, thereby improving the calculation accuracy of the waterlogging risk level value of each grid unit, and ultimately improving the analysis accuracy of the urban waterlogging risk level map.

[0144] Based on the above embodiment, as an optional embodiment, the sub-economic loss values ​​include residential economic loss values, hospital economic loss values, school economic loss values ​​and commercial economic loss values;

[0145] The economic loss value of the residential buildings is determined based on the number, value and first loss rate curve of the flooded residential buildings in the grid unit; the first loss rate curve is determined based on the movable attributes, number of floors, number of mezzanines and number of basements of the flooded residential buildings;

[0146] The hospital economic loss value is determined based on the number, value and second loss rate curve of the flooded hospitals in the grid unit; the second loss rate curve is determined based on the movable attributes, number of floors, number of mezzanines and number of basements of the flooded hospitals;

[0147] The school economic loss value is determined based on the number, value and third loss rate curve of the flooded schools in the grid unit; the third loss rate curve is determined based on the movable attributes, number of floors, number of mezzanines and number of basements of the flooded schools;

[0148] The economic loss value of the commercial entity is determined based on the number of flooded commercial structures in the grid unit, the duration of the flooding shutdown and the output value per unit time.

[0149] The first loss rate curve is an empirical curve fitted based on historical water accumulation depth data, historical loss rate data of flooded residential houses, movable properties of flooded residential houses, number of floors, number of mezzanines and number of basements, etc. It is used to calculate the economic loss value of flooded residential houses.

[0150] The second loss rate curve is an empirical curve fitted based on historical water accumulation depth data, historical flooded hospital loss rate data, the movable properties of the flooded hospitals, the number of floors, mezzanines and basements, etc. It is used to calculate the economic loss value of the flooded hospitals.

[0151] The third loss rate curve is an empirical curve fitted based on historical water accumulation depth data, historical loss rate data of flooded schools, the movable properties of flooded schools, the number of floors, mezzanines and basements, etc. It is used to calculate the economic loss value of flooded schools.

[0152] Specifically, by overlaying the facility distribution map and the waterlogging map, it is possible to extract the situations of residential houses, hospitals, schools, commercial buildings and other structures that are affected when the water depth exceeds a certain depth threshold.

[0153] When the sub-economic loss value includes the economic loss value of residential houses, the economic loss value of hospitals, the economic loss value of schools and the economic loss value of commercial entities, the sub-economic loss element correspondingly includes the economic loss element of residential houses, the economic loss element of hospitals, the economic loss element of schools and the economic loss element of commercial entities, and the parent element is the economic loss element of urban flooding.

[0154] Taking the economic loss value of residential buildings as an example, for residential buildings in a certain grid unit, the facility distribution map and the waterlogging map are overlaid and analyzed to extract the number of flooded residential buildings in the grid unit when the water depth exceeds a certain depth threshold. According to the movable attributes, number of floors, number of mezzanines and number of basements of each flooded residential building, the first loss rate curve applicable to the flooded residential building is determined from the first loss rate curve set. Then, the economic loss value of the residential buildings in the grid unit is determined based on the number, value and first loss rate curve of the flooded residential buildings in the grid unit.

[0155] In one embodiment, the expression for determining the economic loss value of residential buildings according to the number, value and first loss rate curve of flooded residential buildings in the grid unit is as follows:

[0156] ; (4)

[0157] in, is the economic loss value of residential buildings in the grid unit, in ten thousand yuan; is the number of flooded residential buildings in the grid cell; The grid cell The loss rate determined by the first loss rate curve for the flooded residential buildings; The grid cell The value of the flooded residential houses, in ten thousand yuan.

[0158] Figure 2 is an example diagram of the first loss rate curve set provided by the present invention, such as Figure 2 As shown, the first loss rate curve set includes 6 first loss rate curves (loss rate percentage-water accumulation depth), specifically including: (1) the first loss rate curve of an immovable residential building with 1 storey, 0 mezzanines and 0 basements; (2) the first loss rate curve of an immovable residential building with 2 storeys, 0 mezzanines and 0 basements; (3) the first loss rate curve of an immovable residential building with 2 storeys, 0 mezzanines and 1 basement; (4) the first loss rate curve of an immovable residential building with 2 storeys, 1 mezzanine and 0 basements; (5) the first loss rate curve of an immovable residential building with 2 storeys, 1 mezzanine and 1 basement; (6) the first loss rate curve of a movable residential building with 1 storey, 0 mezzanines and 0 basements.

[0159] It is understandable that the calculation method of the economic loss value of the hospital and the economic loss value of the school in the grid unit is the same as the calculation method of the economic loss value of the residential house, and the present invention will not elaborate on this.

[0160] It is understandable that for different types of structures, the water depth thresholds for determining whether residential houses, hospitals, and schools are flooded can be the same or different, and can be specifically determined based on the analysis results of historical waterlogging events, and the present invention is not limited to this.

[0161] For the economic loss value of a commercial entity in a certain grid unit, the facility distribution map and the waterlogging map are overlaid for analysis. According to the architectural layout, floor structure (basically multi-story buildings) and other factors of the commercial structures, the number of flooded commercial structures in the grid unit that are unable to operate normally or have personnel stranded after the water depth exceeds a certain depth threshold and the water enters the set number of floors of the commercial structures is determined. Then the duration of the suspension of flooding for each flooded commercial structure is determined. Finally, the economic loss value of the commercial entity in the grid unit is determined based on the number of flooded commercial structures in the grid unit, the duration of the suspension of flooding for each flooded commercial structure and the output value per unit time.

[0162] In one embodiment, the expression for determining the economic loss value of a commercial entity according to the number of flooded commercial structures in a grid unit, the duration of the flooding shutdown, and the output value per unit time is as follows:

[0163] ; (5)

[0164] in, is the economic loss value of the commercial entity in the grid unit, in ten thousand yuan; is the number of flooded commercial structures within the grid cell; The grid cell The duration of the flooding outage of the flooded commercial structure, in hours; The grid cell The unit time output value of the flooded commercial structures, in units of ten thousand yuan per hour.

[0165] Optionally, the output value per unit time of commercial structures is estimated based on data from the Economic Statistical Yearbook.

[0166] The urban waterlogging risk analysis method provided by the present invention comprehensively considers the economic losses of non-commercial structures such as residential houses, hospitals, schools and commercial structures when they are flooded, determines the loss rate curve according to the movable properties, number of floors, number of mezzanines and number of basements of the non-commercial structures, accurately calculates the economic losses of each flooded non-commercial structure in the grid unit, and simultaneously determines the economic losses of the commercial structures according to the downtime due to flooding and the output value per unit time, so as to determine each sub-economic loss value of the grid unit, which helps to determine a waterlogging risk level value that is more suitable for urban waterlogging risk analysis, so that the finally determined waterlogging risk level map can help staff accurately identify areas in the city that are severely affected by waterlogging, so as to help effectively carry out waterlogging prevention and control work.

[0167] Based on the above embodiment, as an optional embodiment, the sub-population impact value includes the resident population impact value, the employed population impact value and the visiting population impact value;

[0168] The residential population impact value is determined based on the number of residents in the grid unit; the number of residents is the number of map users whose nighttime stay time is greater than their daytime stay time within a preset period and whose mobile terminals are connected to a stable wireless network signal;

[0169] The employment population impact value is determined based on the number of employed people in the grid unit; the number of employed people is the number of map users whose daytime stay time is greater than nighttime stay time and whose mobile terminals are connected to stable wireless network signals within the preset time period;

[0170] The visiting population impact value is determined based on the number of visiting population excluding the number of resident population and the number of employed population within the preset time period.

[0171] Specifically, the location information (such as foot traffic distribution information) of the mobile terminals (such as mobile phones, tablet computers, etc.) of the map application users are extracted, and the number of map application users whose nighttime stay time is greater than their daytime stay time within a preset time period and whose mobile terminals are connected to a stable wireless network signal (such as a Wifi signal) is extracted as the number of resident population of the grid unit; the number of map users whose daytime stay time is greater than their nighttime stay time within a preset time period and whose mobile terminals are connected to a stable wireless network signal is extracted as the number of employed population of the grid unit; the number of map users other than the number of resident population and the number of employed population within a preset time period is extracted as the number of visiting population of the grid unit; and the resident population impact value, the employed population impact value and the visiting population impact value are determined based on the number of resident population, the number of employed population and the number of visiting population.

[0172] Compared with the traditional approach of directly calling existing statistical data to determine the population of statistical grid units, the urban waterlogging risk analysis method provided by the present invention determines the resident population, employed population and visiting population of the grid units by analyzing the usage data of map applications, and then determines the resident population impact value, the employed population impact value and the visiting population impact value and assigns different first weights. This helps to determine a waterlogging risk level value that is more suitable for urban waterlogging risk analysis from the perspective of population analysis, so that the final determined waterlogging risk level map can help staff accurately identify areas in the city that are severely affected by waterlogging, so as to help effectively carry out waterlogging prevention and control work.

[0173] Based on the above embodiment, as an optional embodiment, the sub-facility impact value includes a subway station impact value, a water supply and power supply facility impact value, a bus station impact value, a school impact value and a hospital impact value.

[0174] Specifically, by overlaying the facility distribution map and the urban waterlogging map, we can extract data such as the number of subway stations, water supply and power supply facilities, bus stops, schools, hospitals and other structures affected when the water depth exceeds a certain depth threshold, the duration of flooding, and other data.

[0175] Further based on the number of affected subway stations, water supply and power supply facilities, bus stops, schools and hospitals, and / or the number of affected subway stations, water supply and power supply facilities, bus stops, schools and hospitals that are flooded for more than a certain period of time, the sub-facility impact values ​​including the subway station impact value, water supply and power supply facilities impact value, bus stop impact value, school impact value and hospital impact value are determined.

[0176] It is understandable that for different types of structures, the water depth thresholds for determining whether residential houses, hospitals, and schools are flooded can be the same or different, and can be specifically determined based on the analysis results of historical waterlogging events, and the present invention is not limited to this.

[0177] The urban waterlogging risk analysis method provided by the present invention helps to determine a waterlogging risk level value that is more suitable for urban waterlogging risk analysis by fully considering the different facilities affected in the city and obtaining the final waterlogging risk level value through the weighted summation of the impact values ​​of different sub-facilities of the affected facilities and their weights, so that the finally determined waterlogging risk level map can help staff accurately identify areas in the city that are severely affected by waterlogging, so as to help effectively carry out waterlogging prevention and control work.

[0178] Based on the above embodiment, as an optional embodiment, determining the waterlogging risk level map of the city based on the waterlogging risk level values ​​of all grid cells includes:

[0179] Performing spatial intersection analysis on the boundaries of all the grid cells and all the community management units to determine the grid cells within each community management unit;

[0180] For any community management unit, based on the weighted sum of the waterlogging risk level values ​​of the grid units within the community management unit, determine the waterlogging risk level value of the community management unit;

[0181] Based on the waterlogging risk level values ​​of all community management units, a waterlogging risk level map of the city is determined.

[0182] Upscaling is a process commonly used in fields such as climate, geography, and ecology to predict or explain large-scale phenomena and changes through small-scale observations and analysis.

[0183] Specifically, when determining the urban waterlogging risk level map according to the waterlogging risk level values ​​of all grid cells, a spatial intersection analysis is performed on the boundaries of all grid cells in the urban surface inundation simulation model and all community management units in the city to determine the grid cells within each community management unit.

[0184] For any community management unit, a weighted sum is performed on the waterlogging risk level values ​​of all grid units within the community management unit and the weights of the corresponding risk level intervals, and the weighted sum result is used as the waterlogging risk level value of the community management unit.

[0185] Generally speaking, the higher the waterlogging risk level value of a grid cell, the greater the weight of the risk level interval corresponding to the grid cell. For example, if the risk level interval corresponding to the waterlogging risk level value of grid cell A is high risk, and the risk level interval corresponding to the waterlogging risk level value of grid cell B is high risk, then the weight of the waterlogging risk level value of grid cell A is greater than the weight of the waterlogging risk level value of grid cell B.

[0186] Repeat the step of determining the waterlogging risk level value of the community management unit based on the weighted sum of the waterlogging risk level values ​​of the grid units within the community management unit, obtain the waterlogging risk level values ​​of all community management units in the city, and finally determine the waterlogging risk level map of the city.

[0187] Generally speaking, the simulation of waterlogging event data such as waterlogging depth, waterlogging time, waterlogging flow rate, and the determination of urban flooding risks through models are all limited by the grid unit size of the original input data grid, and cannot be linked or integrated with the city’s community management units in actual social production and life.

[0188] The urban waterlogging risk analysis method provided by the present invention normalizes the waterlogging risk level values ​​of the grid units to the community management units in an area-weighted manner, distributes the waterlogging risks to the smallest community management units, and realizes the up-scaling distribution of the risk level. The originally dispersed risk level values ​​are more concentratedly reflected on the community management units, which helps to scientifically and reasonably feed back the analyzed risk level results to the community management personnel, so that before the flood season arrives, risk prevention and control measures can be prepared in advance according to different community risk levels.

[0189] In order to better illustrate the urban waterlogging risk analysis method provided by the present invention, an embodiment is provided below to elaborate on the overall steps of the urban waterlogging risk analysis method in detail.

[0190] Figure 3 This is the second flow chart of the urban waterlogging risk analysis method provided by the present invention, such as Figure 3 As shown in the figure, based on the integrated twin data planning platform, an urban surface inundation simulation model is established to obtain the urban waterlogging map, and the waterlogging risk value of each grid cell in the waterlogging map is calculated based on the simulated waterlogging time, waterlogging depth, and waterlogging flow rate. Since there is only one child element under the parent element of the waterlogging risk value, the weight of the waterlogging risk value is expressed as B1 or C1.

[0191] Further obtain the facility distribution map and population distribution map, and perform overlay analysis on the facility distribution map and the waterlogging map to obtain the sub-element values ​​corresponding to each sub-element under the parent element of the waterlogging impact facility element with a weight of B2, including the subway station impact value, water supply and power supply facility impact value, bus station impact value, school impact value and hospital impact value with weights C2, C3, C4, C5 and C6, and combine the number of flooded structures, loss rate curve, value, etc. to obtain the sub-element values ​​corresponding to each sub-element under the parent element of the waterlogging economic loss element with a weight of B4, including the economic loss value of residential buildings, hospital economic loss value, school economic loss value and commercial economic loss value with weights C10, C11, C12 and C13. Among them, the sum of weights C2, C3, C4, C5 and C6 is equal to B2, and the sum of weights C10, C11, C12 and C13 is equal to B4.

[0192] The facility distribution map and population distribution map are overlaid and analyzed, and combined with the population footprint flow analysis, the sub-element values ​​corresponding to each sub-element under the parent element of the waterlogging-affected population element with a weight of B3 are obtained, including the residential population impact value, the employed population impact value, and the visiting population impact value with weights C7, C8, and C9, respectively. Among them, the sum of the weights C7, C8, and C9 is equal to B3.

[0193] Therefore, the calculation of each grid cell's child elements, parent elements and final waterlogging risk level values ​​has the characteristics of transferability, attribute consistency and functional dependence. By setting the maximum number of hierarchical elements to 13, the problem of too many dominant elements and difficulty in constructing the subsequent judgment matrix can be avoided.

[0194] Furthermore, the weight C1 of the waterlogging risk value is equal to B1; the weight characteristic vector is determined by constructing the judgment matrix of each child element under the parent element of the waterlogging-affected facility element, and the judgment matrix is ​​checked for consistency, and finally the specific weight values ​​of C2, C3, C4, C5 and C6 are obtained; the weight characteristic vector is determined by constructing the judgment matrix of each child element under the parent element of the waterlogging-affected economic loss element, and the judgment matrix is ​​checked for consistency, and finally the specific weight values ​​of C10, C11, C12 and C13 are obtained; the weight characteristic vector is determined by constructing the judgment matrix of each child element under the parent element of the waterlogging-affected population element, and the judgment matrix is ​​checked for consistency, and finally the specific weight values ​​of C7, C8 and C9 are obtained.

[0195] Taking the grid unit as the unit, the result of weighted summation of 13 sub-elements and their weights is taken as the waterlogging risk level value of the grid unit. Finally, the waterlogging risk level value of the grid unit is concentratedly reflected on the community management unit by area weighting, and the waterlogging risk level map based on the community management unit is obtained.

[0196] Generally speaking, this embodiment introduces waterlogging time as a key factor of waterlogging events, and couples waterlogging time analysis to obtain a more scientific and reasonable waterlogging map, as well as a waterlogging risk value for each grid unit that is more suitable for urban waterlogging risk analysis. The twin data planning platform is used to further introduce the parent elements of waterlogging-affected facility elements, waterlogging-affected population elements, and waterlogging-affected economic loss elements to analyze the impact of urban waterlogging on the economy, society, population, and facilities. Through the objective weighting method and spatial coupling overlay analysis, the waterlogging risk level value of the comprehensive population, economic loss, affected facilities, and waterlogging risk itself is obtained. Finally, based on the area-weighted risk level upscaling method, the grid-scale waterlogging risk level value is well spatially coupled with the community management unit, the grid-scale risk value is discretized into the community, and the area-weighted sum is used to evenly divide it into the community management unit to obtain a comprehensive evaluation of the waterlogging risk level map, which well overcomes the problem that the traditional model analysis results cannot be scientifically and reasonably linked to the administrative management unit, and can provide more scientific, reasonable, and targeted guidance for urban waterlogging risk analysis, thereby improving the effectiveness of urban waterlogging prevention and control.

[0197] Figure 4 is a schematic diagram of the structure of the urban waterlogging risk analysis device provided by the present invention, such as Figure 4 As shown, the urban waterlogging risk analysis device includes but is not limited to a waterlogging waterlogging map acquisition module 401 , a sub-element value determination module 402 , a risk level value determination module 403 and a risk level map acquisition module 404 .

[0198] The waterlogging map acquisition module 401 is used to establish a city surface flooding simulation model and acquire a waterlogging map of the city.

[0199] The sub-element value determination module 402 is used to use a spatial analysis tool to perform an overlay analysis on the facility distribution map, the population distribution map and the waterlogging map of the city to obtain multiple sub-element values ​​of each grid unit in the city.

[0200] The multiple sub-element values ​​include a waterlogging risk value, several sub-facility impact values, several sub-population impact values ​​and several sub-economic loss values.

[0201] The risk level value determination module 403 is used to determine the waterlogging risk level value of any grid cell based on the result of weighted summation of the multiple sub-element values ​​and their first weights for any grid cell.

[0202] The first weights of the plurality of child element values ​​are predetermined based on the importance of the child elements relative to the parent element.

[0203] The risk level map acquisition module 404 is used to determine the waterlogging risk level map of the city based on the waterlogging risk level values ​​of all grid cells.

[0204] It should be noted that the urban waterlogging risk analysis device provided by the present invention can execute the urban waterlogging risk analysis method described in any of the above embodiments during specific operation, which will not be elaborated in this embodiment.

[0205] The urban waterlogging risk analysis device provided by the present invention obtains the sub-element values ​​of the waterlogging risk value, sub-facility impact value, sub-population impact value and sub-economic loss value of each grid unit by overlaying analysis on the waterlogging waterlogging map and the facility distribution map and population distribution map of the city, and determines the waterlogging risk level of different areas in the city by weighted summation calculation of the sub-element values ​​according to the weights determined by the sub-element relative to the parent element. It can comprehensively consider the impact and extended impact of waterlogging incidents occurring in the city, determine the waterlogging risk level map of the city more scientifically and reasonably, and accurately identify the areas in the city that are severely affected by waterlogging, so as to help effectively carry out waterlogging prevention and control work.

[0206] Figure 5 is a schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 5 As shown, the electronic device may include: a processor (Processor) 510, a communication interface (Communications Interface) 520, a memory (Memory) 530 and a communication bus 540, wherein the processor 510, the communication interface 520, and the memory 530 communicate with each other through the communication bus 540. The processor 510 can call the logic instructions in the memory 530 to execute the urban waterlogging risk analysis method provided by any of the above embodiments, and the urban waterlogging risk analysis method includes but is not limited to the following steps: establishing an urban surface inundation simulation model to obtain an urban waterlogging waterlogging map; using a spatial analysis tool to overlay the facility distribution map, the population distribution map and the waterlogging waterlogging map of the city to obtain multiple sub-element values ​​for each grid cell in the city; the multiple sub-element values ​​include a waterlogging risk value, several sub-facility impact values, several sub-population impact values ​​and several sub-economic loss values; for any grid cell, based on the result of the weighted summation of the multiple sub-element values ​​and their first weights, determine the waterlogging risk level value of the any grid cell; the first weight of the multiple sub-element values ​​is predetermined based on the importance of the sub-element relative to the parent element; based on the waterlogging risk level values ​​of all grid cells, determine the waterlogging risk level map of the city.

[0207] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0208] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the urban waterlogging risk analysis method provided in any of the above embodiments. The urban waterlogging risk analysis method includes but is not limited to the following steps: establishing an urban surface inundation simulation model to obtain a waterlogging map of the city; using a spatial analysis tool to overlay an analysis of the facility distribution map, the population distribution map and the waterlogging map of the city to obtain multiple sub-element values ​​for each grid unit in the city; the multiple sub-element values ​​include a waterlogging risk value, several sub-facility impact values, several sub-population impact values ​​and several sub-economic loss values; for any grid unit, based on the result of the weighted summation of the multiple sub-element values ​​and their first weights, determine the waterlogging risk level value of the any grid unit; the first weight of the multiple sub-element values ​​is predetermined based on the importance of the sub-element relative to the parent element; based on the waterlogging risk level values ​​of all grid units, determine the waterlogging risk level map of the city.

[0209] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the urban waterlogging risk analysis method provided by any of the above-mentioned embodiments, the urban waterlogging risk analysis method including but not limited to the following steps: establishing an urban surface inundation simulation model to obtain a waterlogging map of the city; using a spatial analysis tool to perform an overlay analysis on the facility distribution map, the population distribution map and the waterlogging map of the city to obtain a plurality of sub-element values ​​for each grid cell in the city; the plurality of sub-element values ​​include a waterlogging risk value, a plurality of sub-facility impact values, a plurality of sub-population impact values ​​and a plurality of sub-economic loss values; for any grid cell, based on the result of the weighted summation of the plurality of sub-element values ​​and their first weights, determining the waterlogging risk level value of the any grid cell; the first weight of the plurality of sub-element values ​​is predetermined based on the importance of the sub-element relative to the parent element; based on the waterlogging risk level values ​​of all grid cells, determining the waterlogging risk level map of the city.

[0210] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0211] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0212] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for analyzing urban waterlogging risk, characterized in that: include: Establish a simulation model for urban surface flooding and obtain urban waterlogging maps; Using spatial analysis tools, the facility distribution map, population distribution map and waterlogging map of the city are overlaid and analyzed to obtain multiple sub-element values ​​of each grid unit in the city; the multiple sub-element values ​​include waterlogging risk value, sub-facility impact value, sub-population impact value and sub-economic loss value; For any grid cell, based on the result of weighted summation of the multiple sub-element values ​​and their first weights, determine the waterlogging risk level value of the any grid cell; the first weights of the multiple sub-element values ​​are predetermined based on the importance of the sub-element relative to the parent element; Determining a waterlogging risk level map of the city based on the waterlogging risk level values ​​of all grid cells; The waterlogging risk value is determined based on the following method: Determine the waterlogging time disaster factor based on the simulated waterlogging time and the simulated waterlogging depth; determine the water depth hazard parameter based on the simulated waterlogging depth; determine the waterlogging risk value based on the simulated waterlogging time, the simulated waterlogging depth, the waterlogging time disaster factor, the water depth hazard parameter and the simulated waterlogging flow rate.

2. The urban waterlogging risk analysis method according to claim 1, characterized in that: Before determining the waterlogging risk level value of any grid cell based on the result of weighted summation of the multiple sub-element values ​​and their first weights for any grid cell, determining the first weights of the multiple sub-element values ​​based on the importance of the sub-element relative to the parent element includes: Determining a second weight of each of the parent elements; For a first parent element including multiple child elements, a judgment matrix is ​​constructed based on the comparison result of the importance between every two child elements in the multiple child elements; each column value of the judgment matrix is ​​normalized to obtain a normalized judgment matrix; the normalized judgment matrix is ​​added row by row and normalized to obtain a weight feature vector of the first parent element; based on the weight feature vector, the weights of the multiple child elements are determined to determine the first weights of the sub-element values ​​corresponding to the multiple child elements; For a second parent element that includes two or fewer child elements, the first weight of the child element values ​​corresponding to the two or fewer child elements is determined based on the second weight of the parent element.

3. The urban waterlogging risk analysis method according to claim 2, characterized in that: Before determining the weights of the plurality of sub-elements based on the weight feature vector, the method further includes: Performing a consistency check on the judgment matrix; If the consistency check passes, determining the weights of the plurality of sub-elements based on the weight feature vector; If the consistency check fails, the importance comparison result is updated, a new judgment matrix is ​​constructed, a new weight feature vector is determined based on the new judgment matrix, and the new judgment matrix is ​​checked for consistency again until the consistency check passes.

4. The urban waterlogging risk analysis method according to claim 1, characterized in that: The sub-economic loss values ​​include residential economic loss values, hospital economic loss values, school economic loss values ​​and commercial economic loss values; The economic loss value of the residential buildings is determined based on the number, value and first loss rate curve of the flooded residential buildings in the grid unit; the first loss rate curve is determined based on the movable attributes, number of floors, number of mezzanines and number of basements of the flooded residential buildings; The hospital economic loss value is determined based on the number, value and second loss rate curve of the flooded hospitals in the grid unit; the second loss rate curve is determined based on the movable attributes, number of floors, number of mezzanines and number of basements of the flooded hospitals; The school economic loss value is determined based on the number, value and third loss rate curve of the flooded schools in the grid unit; the third loss rate curve is determined based on the movable attributes, number of floors, number of mezzanines and number of basements of the flooded schools; The economic loss value of the commercial entity is determined based on the number of flooded commercial structures in the grid unit, the duration of the flooding shutdown and the output value per unit time.

5. The urban waterlogging risk analysis method according to claim 1, characterized in that: The sub-population impact values ​​include the resident population impact value, the employed population impact value and the visiting population impact value; The residential population impact value is determined based on the number of residents in the grid unit; the number of residents is the number of map users whose nighttime stay time is greater than their daytime stay time within a preset period and whose mobile terminals are connected to a stable wireless network signal; The employment population impact value is determined based on the number of employed people in the grid unit; the number of employed people is the number of map users whose daytime stay time is greater than nighttime stay time and whose mobile terminals are connected to stable wireless network signals within the preset time period; The visiting population impact value is determined based on the number of visiting population excluding the number of resident population and the number of employed population within the preset time period.

6. The urban waterlogging risk analysis method according to claim 1, characterized in that: The sub-facility impact values ​​include subway station impact values, water supply and power supply facility impact values, bus station impact values, school impact values ​​and hospital impact values.

7. The urban waterlogging risk analysis method according to claim 1, characterized in that: The determining of the waterlogging risk level map of the city based on the waterlogging risk level values ​​of all grid cells includes: Performing spatial intersection analysis on the boundaries of all the grid cells and all the community management units to determine the grid cells within each community management unit; For any community management unit, based on the weighted sum of the waterlogging risk level values ​​of the grid units within the community management unit, determine the waterlogging risk level value of the community management unit; Based on the waterlogging risk level values ​​of all community management units, a waterlogging risk level map of the city is determined.

8. An urban waterlogging risk analysis device, characterized in that: include: The waterlogging map acquisition module is used to establish a city surface flooding simulation model and obtain the city's waterlogging map; A sub-element value determination module is used to use a spatial analysis tool to perform an overlay analysis on the facility distribution map, the population distribution map and the waterlogging map of the city to obtain multiple sub-element values ​​for each grid unit in the city; the multiple sub-element values ​​include a waterlogging risk value, a sub-facility impact value, a sub-population impact value and a sub-economic loss value; A risk level value determination module, for determining, for any grid cell, a waterlogging risk level value of the any grid cell based on a result of weighted summation of the multiple sub-element values ​​and their first weights; the first weights of the multiple sub-element values ​​are predetermined based on the importance of the sub-element relative to the parent element; A risk level map acquisition module, used to determine a waterlogging risk level map of the city based on the waterlogging risk level values ​​of all grid cells; The waterlogging risk value is determined based on the following method: Determine the waterlogging time disaster factor based on the simulated waterlogging time and the simulated waterlogging depth; determine the water depth hazard parameter based on the simulated waterlogging depth; determine the waterlogging risk value based on the simulated waterlogging time, the simulated waterlogging depth, the waterlogging time disaster factor, the water depth hazard parameter and the simulated waterlogging flow rate.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the urban waterlogging risk analysis method as described in any one of claims 1 to 7 is implemented.

Images