Flood control material dispatching method, device, electronic device and computer readable medium

Abstract

The embodiments of the present disclosure disclose a method, device, electronic device and computer-readable medium for dispatching flood control materials. A specific implementation of the method includes: obtaining a multi-source flood control information set; generating an urban flood control range; identifying flood control waterlogging risks in the urban flood control range to obtain an urban flood control risk location information set; predicting the depth of waterlogging in the urban flood control risk location information set to obtain an accumulated water depth information set; controlling waterlogging warning equipment to push waterlogging warning information, and determining a flood control material information set and an urban road condition information set; performing material dispatch processing on the flood control material information set to obtain flood control material dispatch information; generating a flood control material transportation path set; and controlling material transportation equipment to dispatch materials. This implementation can improve the accuracy of waterlogging risk identification, the accuracy of warning information push, and the rationality and timeliness of flood control material dispatch, reduce the waste of flood control resources, and improve the city's emergency response capabilities.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to a method, device, electronic device, and computer-readable medium for dispatching flood control materials. Background Art

[0002] With the acceleration of urbanization, the emergence of local climate anomalies and extreme weather in cities has caused urban waterlogging to occur frequently, resulting in disasters such as road blockages and house collapses. How to accurately and intelligently improve the identification of urban waterlogging risks, push early warning information of waterlogging disasters, and dispatch emergency resources for flood control resources has become an urgent problem to be solved. For the dispatch of flood control materials, the usual method is to monitor and warn the urban flood control situation through expert experience, obtain information on waterlogged areas, and send flood control warning information to each terminal. Then, emergency resource matching and resource dispatch are carried out on the waterlogged area information to obtain resource dispatch information. Finally, flood control resources are dispatched according to the resource dispatch information.

[0003] However, it is found in practice that when the above method is used to dispatch flood control materials, the following technical problems often occur: Since expert experience is subjective and the source of flood control data obtained by experts is relatively single, the accuracy of the generated flood warning information push and waterlogging area identification is low, which can easily increase the missed detection rate and false detection rate, increase the waste of emergency resources and the losses caused by waterlogging.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure concept and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. Summary of the invention

[0005] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0006] Some embodiments of the present disclosure propose flood control material dispatching methods, devices, electronic devices, and computer-readable media to solve one or more of the technical problems mentioned in the above background technology section.

[0007] In a first aspect, some embodiments of the present disclosure provide a method for dispatching flood control materials, comprising: obtaining a multi-source flood control information set, wherein the multi-source flood control information set includes at least one of the following: meteorological information, urban water conservancy information, a three-dimensional digital model of the city, and a historical flood control data set; generating an urban flood control range within a forecast time period based on the multi-source flood control information set; identifying flood control and waterlogging risks for the urban flood control range to obtain an urban flood control risk location information set; predicting the depth of waterlogging for each urban flood control risk location information in the urban flood control risk location information set to generate waterlogging depth information within the forecast time period to obtain a waterlogging depth information set; in response to determining that there is a waterlogging depth greater than or equal to a preset waterlogging depth in the waterlogging depth information set, at least one water accumulation depth information of a threshold, controlling the waterlogging warning device to push the waterlogging warning information, and determining the flood control material information and urban road condition information of each city flood control risk location information in at least one city flood control risk location information corresponding to the at least one water accumulation depth information, to obtain a flood control material information set and an urban road condition information set; performing material dispatch processing on the flood control material information set to obtain flood control material dispatch information; generating a flood control material transportation path set for the at least one city flood control risk location information according to the flood control material dispatch information and the city road condition information set; and controlling the material transportation equipment to dispatch materials according to the flood control material transportation path set according to the flood control material dispatch information.

[0008] In a second aspect, some embodiments of the present disclosure provide a flood control material dispatching device, comprising: an acquisition unit, configured to acquire a multi-source flood control information set, wherein the multi-source flood control information set includes at least one of the following: meteorological information, urban water conservancy information, a three-dimensional digital model of the city, and a historical flood control data set; a first generation unit, configured to generate an urban flood control range within a prediction time period based on the multi-source flood control information set; a flood control and waterlogging risk identification unit, configured to perform flood control and waterlogging risk identification on the urban flood control range, and obtain an urban flood control risk location information set; a water accumulation depth prediction unit, configured to perform water accumulation depth prediction on each urban flood control risk location information in the urban flood control risk location information set, so as to generate water accumulation depth information within the prediction time period and obtain a water accumulation depth information set; a first control unit, configured to respond to the determination of the water accumulation depth information set; There is at least one water accumulation depth information greater than or equal to a preset water accumulation depth threshold, controlling the waterlogging warning device to push the waterlogging warning information, and determining the flood control material information and urban road condition information of each city flood control risk location information in at least one city flood control risk location information corresponding to the above at least one water accumulation depth information, to obtain a flood control material information set and an urban road condition information set; a material dispatching unit is configured to perform material dispatching processing on the above flood control material information set to obtain flood control material dispatching information; a second generating unit is configured to generate a flood control material transportation path set for the above at least one city flood control risk location information according to the above flood control material dispatching information and the above city road condition information set; a second control unit is configured to control the material transportation equipment to dispatch materials according to the above flood control material transportation path set according to the above flood control material dispatching information.

[0009] In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner in the first aspect.

[0010] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method described in any implementation manner in the first aspect is implemented.

[0011] The above-mentioned embodiments of the present disclosure have the following beneficial effects: the flood control material dispatching of some embodiments of the present disclosure can understand the urban waterlogging situation in real time, improve the accuracy of waterlogging risk identification, the accuracy of warning information push and the rationality and timeliness of flood control material dispatching, reduce the waste of flood control resources, and improve the emergency response capability of the city. Specifically, the reason why the push of the relevant generated flood control warning information and the identification of the waterlogging area are low in accuracy, which is easy to increase the missed detection rate and the false detection rate, and increase the waste of emergency resources and the losses caused by waterlogging is that: due to the subjectivity of expert experience, and the source of flood control data obtained by experts is relatively single, resulting in the push of the generated flood control warning information and the identification of the waterlogging area. The accuracy is low, which is easy to increase the missed detection rate and the false detection rate, and increase the waste of emergency resources and the losses caused by waterlogging. Based on this, the flood control material dispatching method of some embodiments of the present disclosure can first obtain a multi-source flood control information set, wherein the multi-source flood control information set includes at least one of the following: meteorological information, urban water conservancy information, urban three-dimensional digital model and historical flood control data set. Here, the rapid transmission and sharing of data can be achieved, and the comprehensiveness of flood control information can be improved. Secondly, based on the above-mentioned multi-source flood control information set, the urban flood control scope within the forecast time period is generated. Here, the accuracy of the urban flood control scope can be improved, which is convenient for the subsequent further identification of the urban flood control risk location information. Thirdly, the flood control and waterlogging risk of the above-mentioned urban flood control scope is identified to obtain the urban flood control risk location information set. Here, the accuracy of the identification of waterlogging risk location information can be improved, so as to better understand the urban waterlogging situation and accurately determine the area where the waterlogging disaster occurs. Subsequently, the water accumulation depth is predicted for each urban flood control risk location information in the above-mentioned urban flood control risk location information set to generate the water accumulation depth information within the forecast time period and obtain the water accumulation depth information set. Here, the accuracy of the water accumulation depth prediction can be improved to better understand the degree of water accumulation of each waterlogging risk location information, so as to facilitate the subsequent dispatch of flood control materials. Next, in response to determining that there is at least one water accumulation depth information greater than or equal to the preset water accumulation depth threshold in the above-mentioned water accumulation depth information set, the waterlogging warning device is controlled to push the waterlogging warning information, and the flood control material information and urban road condition information of each urban flood control risk location information in the at least one urban flood control risk location information corresponding to the above-mentioned at least one water accumulation depth information are determined, and the flood control material information set and the urban road condition information set are obtained. Here, the accurate push of waterlogging warning information can be improved, and the missed detection rate and the false detection rate can be reduced. Afterwards, the above-mentioned flood control material information set is processed for material dispatch to obtain flood control material dispatch information. Here, the urban waterlogging risk response capability, the timeliness of material dispatch and the degree of urban losses caused by waterlogging risks can be improved. Then, based on the above-mentioned flood control material dispatch information and the above-mentioned urban road condition information set, a flood control material transportation path set for the above-mentioned at least one urban flood control risk location information is generated.Here, the accuracy and efficiency of the generated flood control material transportation path set can be improved, and the material transportation time and waste of flood control materials can be reduced. Finally, according to the above flood control material dispatching information, the material transportation equipment is controlled to dispatch materials according to the above flood control material transportation path set. Here, the transportation efficiency of the material transportation equipment is improved and the transportation time is shortened. It can be obtained that the flood control material dispatching method can understand the urban waterlogging situation in real time, improve the accuracy of waterlogging risk identification, the accuracy of early warning information push, and the rationality and timeliness of flood control material dispatching, reduce the waste of flood control resources, and improve the city's emergency response capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0013] Figure 1 is a flow chart of some embodiments of the flood control material dispatching method according to the present disclosure;

[0014] Figure 2 It is a structural schematic diagram of some embodiments of the flood control material dispatching device according to the present disclosure;

[0015] Figure 3 It is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0016] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0017] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0018] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0019] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0020] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0021] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0022] Figure 1 The process 100 of some embodiments of the flood control material dispatching method according to the present disclosure is shown. The flood control material dispatching method comprises the following steps:

[0023] Step 101, obtaining a multi-source flood control information set.

[0024] In some embodiments, the execution subject (e.g., electronic device) of the flood control material dispatching method can obtain a multi-source flood control information set through a wired connection or a wireless connection, wherein the multi-source flood control information set includes at least one of the following: meteorological information, urban water conservancy information, a three-dimensional digital model of the city, and a historical flood control data set. The multi-source flood control information set can be data obtained from a database established by multiple relevant departments. The multiple relevant departments can include, but are not limited to, at least one of the following: urban meteorological department, urban water conservancy department, and urban traffic management department. The meteorological information can be information related to rainfall. For example, the meteorological information can include, but are not limited to, at least one of the following: rainfall, rainfall duration, and rainfall intensity. The urban water conservancy information can be information related to drainage pipe networks and reservoirs in the city. For example, the urban water conservancy information can include, but are not limited to, at least one of the following: drainage pipe network layout information, drainage outlet location and number, reservoir water level and storage capacity. The three-dimensional digital model of the city can be a model that displays a three-dimensional stereoscopic image of the city in a digital form. For example, the three-dimensional digital model of the city can be a DEM (Digital Elevation Model) model of the city. The historical flood control data in the historical flood control data set may be data before the current time, including rainfall, waterlogging depth, urban water conservancy operation status information and urban disaster status information. The urban disaster status information may include but is not limited to at least one of the following: number of casualties, scope of urban flooding, and road congestion information.

[0025] Step 102, generating a city flood control range within a forecast time period based on a multi-source flood control information set.

[0026] In some embodiments, the execution entity may generate a city flood control range within a forecast time period based on the multi-source flood control information set. The forecast time period may be a pre-set future time period. For example, the forecast time period may be one hour in the future. The city flood control range may be an area where a rainstorm and waterlogging disaster occurs. For example, the city flood control range may be xx district in xx city.

[0027] As an example, the execution entity may input the multi-source flood control information set into a SWMM (Storm Water Management Model) model to obtain the urban flood control scope within the forecast period.

[0028] In some optional implementations of some embodiments, generating the urban flood control range within the forecast time period according to the multi-source flood control information set may include the following steps:

[0029] In the first step, the meteorological information, historical flood control data set and urban water conservancy information included in the above multi-source flood control information set are subjected to data standardization processing to obtain standardized meteorological information, standardized historical flood control data set and standardized urban water conservancy information.

[0030] The second step is to input the above-mentioned standardized meteorological information, the above-mentioned standardized historical flood control data set and the above-mentioned standardized urban water conservancy information into the urban waterlogging hydrodynamic model to obtain the urban waterlogging information set. Among them, the urban waterlogging information in the above-mentioned urban waterlogging information set can be the information of urban terrain and the information of the depth of water accumulation in the terrain under the above-mentioned standardized meteorological information and the above-mentioned standardized urban water conservancy information. The above-mentioned urban waterlogging hydrodynamic model can be a model that simulates the urban flow generation and confluence caused by rainfall under the current situation of drainage of the water flow generated by the standardized meteorological information and the urban drainage pipes of the urban water conservancy corresponding to the above-mentioned standardized urban water conservancy information based on the water flow characteristics of the above-mentioned standardized historical flood control data set. The above-mentioned urban waterlogging hydrodynamic model can be a one-dimensional hydraulic model.

[0031] The third step is to extract the waterlogging spatial feature data set and waterlogging temporal feature data set from the urban waterlogging information set. The waterlogging spatial feature data in the waterlogging spatial feature data set may be spatial feature data related to rainfall information, urban surface runoff information, and water conservancy drainage information corresponding to urban water conservancy information. The waterlogging temporal feature data in the waterlogging temporal feature data set may be a temporal feature data set related to rainfall information and urban waterlogging depth.

[0032] In the fourth step, the waterlogging spatial feature data set is input into the urban waterlogging spatial prediction model to obtain the urban waterlogging waterlogging location information set and the urban waterlogging waterlogging depth information set. The urban waterlogging waterlogging location information in the urban waterlogging waterlogging location information set may be the information of the location where the waterlogging waterlogging occurs. The urban waterlogging waterlogging depth information in the urban waterlogging waterlogging depth information set may be the information of the depth of the waterlogging waterlogging generated at the urban waterlogging waterlogging location. The urban waterlogging spatial prediction model may be a model for extracting spatial features from the input waterlogging spatial feature data set. The urban waterlogging spatial prediction model may be a model for inputting the waterlogging spatial feature data into the support vector set, random forest, XGBoost model (eXtreme Gradient Boosting, extreme gradient boosting model) and K nearest neighbor model respectively, and performing weighted sum fusion on the output results to obtain the urban waterlogging waterlogging location information set and the urban waterlogging waterlogging depth information set.

[0033] The fifth step is to input the above-mentioned waterlogging time feature data set into the urban waterlogging time prediction model to obtain the urban waterlogging water depth time series data set. Among them, the urban waterlogging water depth time series data in the above-mentioned urban waterlogging water depth time series data set can represent the data of the urban waterlogging water depth changing over time. The above-mentioned urban waterlogging time prediction model can be a model that predicts the change of water depth over time in the prediction time period based on the waterlogging time feature data set. The above-mentioned urban waterlogging time prediction model can be a bidirectional gated recurrent unit model including a convolutional attention mechanism layer.

[0034] The sixth step is to determine the urban flood control scope with the above-mentioned urban waterlogging location information set, the above-mentioned urban waterlogging depth information set and the above-mentioned urban waterlogging depth time series data set.

[0035] In some optional implementations of some embodiments, the step of inputting the standardized meteorological information, the standardized historical flood control data set, and the standardized urban water conservancy information into an urban waterlogging hydrodynamic model to obtain an urban waterlogging information set may include the following steps:

[0036] In the first step, the city corresponding to the above three-dimensional digital model of the city is divided into regions to obtain a set of urban sub-catchment areas. The urban sub-catchment areas in the above urban sub-catchment area set can be areas within a unit terrain area where water flows generated by rainfall converge and drain water in a centralized manner.

[0037] As an example, the execution subject may use the Thiessen polygon algorithm to perform regional division processing on the city corresponding to the three-dimensional digital model of the city to obtain a set of urban sub-catchment areas.

[0038] In the second step, for each urban subcatchment in the above urban subcatchment set, perform the following generation steps:

[0039] Sub-step 1, according to the standardized meteorological information, determine the regional rainfall intensity and the regional rainfall duration for the urban sub-catchment area. The regional rainfall intensity can represent the amount of rainfall per unit surface per unit time. The regional rainfall duration can be the duration of rainfall. The regional rainfall duration can be data extracted from the standardized meteorological information.

[0040] As an example, the above-mentioned execution entity may input the above-mentioned standardized meteorological information into a preset rainstorm intensity formula to obtain the regional rainfall intensity for the above-mentioned urban sub-catchment area. The above-mentioned preset rainstorm intensity formula may be a rainstorm intensity formula issued by meteorological bureaus of different provinces and cities.

[0041] Sub-step 2, input the above-mentioned urban three-dimensional digital model, the above-mentioned regional rainfall intensity and the above-mentioned regional rainfall duration into the urban rainfall waterlogging hydrological model to obtain a time-varying runoff coefficient. Among them, the above-mentioned time-varying runoff coefficient can characterize the proportional coefficient of the slope water flow formed by the surface flow after rainfall. The above-mentioned urban rainfall waterlogging hydrological model can be a model of the time-varying runoff coefficient determined under the surface conditions of different terrain types of permeable ground and impermeable ground corresponding to the above-mentioned urban three-dimensional digital model. The above-mentioned permeable ground can be a ground where water can penetrate into the ground. The above-mentioned permeable ground can include but is not limited to at least one of the following: woodland, grassland, bare soil. The above-mentioned impermeable ground can be a ground where water cannot penetrate into the ground. The above-mentioned impermeable ground can include but is not limited to at least one of the following: roof, square, parking lot. For example, the above-mentioned urban rainfall waterlogging hydrological model can be a SWAT (Soil and Water Assessment Tool) model.

[0042] Sub-step 3, based on the above-mentioned standardized historical flood control data set, determine the regional seasonal runoff coefficient factor, regional soil erosion risk coefficient factor, regional rainfall interval coefficient factor and slope crown interception coefficient factor within the above-mentioned prediction time period. Among them, the above-mentioned regional seasonal runoff coefficient factor can characterize the infiltration capacity of the urban surface corresponding to the above-mentioned three-dimensional digital model of the city to rainfall in different seasons. The above-mentioned regional soil erosion risk coefficient factor can characterize the impact of soil erosion on the water storage performance of the city. The above-mentioned regional rainfall interval coefficient factor can characterize the impact of the rainfall interval on the permeability of the urban soil. The above-mentioned slope crown interception coefficient factor can characterize the impact of different terrain slopes and canopy interception on the runoff coefficient of the city. The above-mentioned slope crown interception coefficient factor can be obtained by statistically fitting the standardized historical flood control data set using the multivariate regression analysis method.

[0043] As an example, the execution subject may first perform a discreteness test on the standardized historical flood control data set to obtain the historical monthly average rainfall set corresponding to the standardized historical flood control data set. Secondly, the historical monthly average rainfall set is sorted to obtain a historical monthly average rainfall sequence. Thirdly, the rainfall ranking value of the rainfall intensity in the above-mentioned region in the above-mentioned historical monthly average rainfall sequence is determined, and the seasonal regional compensation coefficient is determined. Among them, the seasonal regional compensation coefficient can characterize the influence of weather climate and historical rainfall on the regional ground permeability. The seasonal regional compensation coefficient can be a coefficient obtained by querying a preset seasonal regional compensation coefficient table. Finally, the rainfall ranking value and the seasonal regional compensation coefficient are input into the preset seasonal runoff coefficient formula to obtain the regional seasonal runoff coefficient factor. Among them, the preset regional seasonal runoff coefficient formula can be a formula of 0.1 multiplied by the regional compensation coefficient parameter, multiplied by the product of the logarithmic function of the rainfall ranking value with a base of 10, and 1.

[0044] The execution entity may first determine the regional soil erosion area ratio of the urban sub-catchment area. The regional soil erosion area ratio may be a value obtained by statistically analyzing historical flood control data sets. Then, the ratio of 1 divided by 1 to the regional soil erosion area ratio is determined as the regional soil erosion risk coefficient factor.

[0045] The execution subject may first determine the regional rainfall interval duration of the above-mentioned urban sub-catchment area. Secondly, the Horton infiltration formula is regressed and fitted through the above-mentioned standardized historical flood control data set to obtain the surface medium infiltration parameter value. Subsequently, an exponential function value with e as the base and the inverse of the ratio of the above-mentioned surface medium infiltration parameter value and 7 as the exponent is determined as the target rainfall interval coefficient value. Then, the rainfall interval range in which the above-mentioned regional rainfall interval duration is located is determined as the target rainfall interval range. Finally, in response to determining that the target rainfall interval range is greater than or equal to 7, the target rainfall interval coefficient value is determined as the regional rainfall interval coefficient factor. In response to determining that the target rainfall interval range is [3, 7), the product of 1.1 and the target rainfall interval coefficient value is determined as the regional rainfall interval coefficient factor. In response to determining that the target rainfall interval range is less than 3, the product of 1.2 and the target rainfall interval coefficient value is determined as the regional rainfall interval coefficient factor. Among them, the unit of the target rainfall interval range may be days.

[0046] Sub-step 4, determining the product of the above regional seasonal runoff coefficient factor, the above regional soil erosion risk coefficient factor, the above regional rainfall interval coefficient factor and the above slope crown interception coefficient factor as the regional real-time runoff coefficient.

[0047] Sub-step 5: Generate a regional drainage flow for the urban sub-catchment area based on the standardized urban water conservancy information, wherein the regional drainage flow can represent the drainage capacity of the urban drainage system corresponding to the standardized urban water conservancy information for rainfall.

[0048] As an example, the execution subject may first determine the drainage flow of the rainwater grate subset corresponding to the standardized urban water conservancy information in the urban sub-catchment area. Secondly, determine the drainage volume of the drainage pipe set corresponding to the standardized urban water conservancy information in the urban sub-catchment area. Subsequently, determine the ratio of the drainage volume to the regional surface area corresponding to the urban sub-catchment area as the regional drainage volume density. The regional drainage volume density may characterize the ability of the underground pipe corresponding to the urban sub-catchment area to quickly discharge the runoff entering the rainwater inlet. Finally, determine the product of the drainage flow and the regional drainage volume density as the regional drainage flow.

[0049] Sub-step 6, generating regional surface runoff flow according to the regional rainfall intensity, the regional real-time runoff coefficient, and the regional area corresponding to the urban sub-catchment area. The regional surface runoff flow may be the rainfall that forms waterlogging on the surface.

[0050] As an example, the execution subject may first determine the rainfall intensity of the region, the real-time runoff coefficient of the region, and the unit conversion coefficient of the area of ​​the region. Then, the product of the rainfall intensity of the region, the real-time runoff coefficient of the region, the surface area of ​​the region, and the unit conversion coefficient is determined as the regional surface runoff flow.

[0051] Sub-step 7: Determine the difference between the regional surface runoff flow and the regional drainage flow as the regional runoff flow.

[0052] Sub-step 8, generating the depth of waterlogging in the region according to the regional runoff flow, wherein the depth of waterlogging in the region may be the depth of water accumulated on the surface formed by the regional runoff flow.

[0053] In the third step, the obtained rainfall intensity in each area, rainfall duration in each area, surface runoff flow in each area, drainage flow in each area, runoff flow in each area and waterlogging depth in each area are determined as the urban waterlogging information set.

[0054] In some optional implementations of some embodiments, generating the depth of waterlogging in the region according to the runoff generated in the region may include the following steps:

[0055] The first step is to determine the average regional slope gradient, regional water flow cross-sectional area, regional water flow cross-sectional wet perimeter, regional water flow cross-sectional width and regional surface roughness of the above-mentioned urban sub-catchment area. Among them, the above-mentioned average regional slope gradient can be the average value of the ratio of the elevation difference and the horizontal distance between any two points in the above-mentioned urban sub-catchment area. The above-mentioned average regional slope gradient can characterize the inclination degree of the urban sub-catchment area. The above-mentioned regional water flow cross-sectional area can be the size of the lateral space occupied by the surface runoff during the flow process. For example, in a rectangular river channel, the above-mentioned regional water flow cross-sectional area can be the product of the width of the river channel and the water depth. The above-mentioned regional water flow cross-sectional wet perimeter can be the length of the peripheral boundary of the contact between the water flow and the cross-sectional area on the water flow cross-sectional area. For example, when the water flow cross-sectional area is a circular water flow cross-sectional area, the regional water flow cross-sectional wet perimeter can be the perimeter of the circular water flow cross-sectional area. The above-mentioned regional water flow cross-sectional width can be the road width of the above-mentioned urban sub-catchment area. The above-mentioned regional surface roughness can characterize the friction resistance between the surface runoff and the surface objects during the flow process. The rougher the surface, the greater the surface roughness of the above-mentioned area.

[0056] In the second step, the surface roughness of the above-mentioned area is input into the Xie Cai formula to obtain the parameter correlation relationship between the regional hydraulic radius parameter and the Xie Cai parameter. Among them, the above-mentioned regional hydraulic radius parameter can be the ratio of the regional water-passing cross-sectional area to the wet perimeter of the regional water-passing cross-sectional area. The above-mentioned regional hydraulic radius parameter can characterize the water conveyance capacity of the underground pipeline. The above-mentioned Xie Cai parameter can characterize the resistance characteristics of surface runoff flow. The rougher the above-mentioned surface, the larger the above-mentioned Xie Cai parameter.

[0057] The third step is to determine the regional hydraulic radius value corresponding to the regional hydraulic radius parameter according to the above parameter correlation relationship, the regional runoff flow, the above average regional slope gradient and the regional water flow cross-sectional area.

[0058] As an example, the execution subject may first determine the Xiecai hydraulic radius expression of the Xiecai parameter with respect to the regional hydraulic radius parameter through the above parameter association relationship. Secondly, the Xiecai hydraulic radius expression, the regional water flow cross-sectional area, the average regional slope gradient, the regional hydraulic radius parameter and the regional runoff flow are input into the preset water flow cross-sectional area calculation formula for solution to obtain the urban hydraulic radius value corresponding to the regional hydraulic radius parameter. Among them, the preset water flow cross-sectional area calculation formula may be the product of the regional water flow cross-sectional area, the Xiecai parameter multiplied by the arithmetic square root of the product of the regional hydraulic radius parameter and the average regional slope gradient, which is equal to the calculation formula of the regional runoff flow.

[0059] The fourth step is to determine the depth of waterlogging in the area based on the hydraulic radius value of the above area, the width of the water-passing cross-section of the above area and the wetted perimeter of the water-passing cross-section of the above area.

[0060] As an example, the execution entity may first determine the product of the urban water conservancy radius value and the water flow cross-sectional width of the region as the first value. Secondly, determine the difference between the water flow cross-sectional width of the region and 2 times the product of the urban water conservancy radius value as the second value. Finally, determine the ratio of the first value to the second value as the waterlogging depth in the region.

[0061] Step 103, identifying the flood control and waterlogging risks in the urban flood control area, and obtaining an urban flood control risk location information set.

[0062] In some embodiments, the execution subject may identify the flood control and waterlogging risks of the urban flood control range to obtain an urban flood control risk location information set. The urban flood control risk location information in the urban flood control risk location information set may be information about high-risk locations obtained by further identifying the urban prevention range. The urban flood control risk location information may be information about a location within the current urban flood control range where the water depth is greater than or equal to a preset water depth threshold.

[0063] As an example, the execution entity may determine a set of regional risk levels for multiple flood control sub-areas within the urban flood control range. Then, at least one regional risk level greater than or equal to a preset regional risk level threshold is selected from the regional risk level information set as the target regional risk level set. The preset regional risk level threshold may be a preset regional risk level, i.e., the maximum value of the current water depth. Finally, the set of flood control sub-areas corresponding to the target regional risk level set is determined as the urban flood control risk location information set.

[0064] Step 104, predicting the water depth for each urban flood risk location information in the urban flood risk location information set, to generate water depth information within a prediction time period, and obtain a water depth information set.

[0065] In some embodiments, the execution entity may perform a water depth prediction for each urban flood risk location information in the urban flood risk location information set to generate water depth information within a prediction period to obtain a water depth information set. The water depth information may be information on the depth of water accumulated at the predicted urban flood risk location.

[0066] In some optional implementations of some embodiments, the above-mentioned prediction of the waterlogging depth for each urban flood risk location information in the above-mentioned urban flood risk location information set to generate waterlogging depth information within the prediction time period to obtain the waterlogging depth information set may include the following steps:

[0067] In the first step, for each urban flood risk location information in the above urban flood risk location information set, the following flood depth prediction steps are performed:

[0068] Sub-step 1, obtaining the current water depth information, current regional rainfall intensity and current regional drainage flow of the above-mentioned urban flood risk location information. Among them, the above-mentioned current water depth information can be the depth of the water accumulated at the current moment. The above-mentioned regional rainfall intensity information can be the regional rainfall intensity at the urban flood risk location at the current moment. The above-mentioned current regional drainage flow can be the drainage flow at the urban flood risk location at the current moment.

[0069] Sub-step 2, input the current waterlogging depth information, the current regional rainfall intensity and the current regional drainage flow into the first feature extraction network included in the regional depth prediction model to obtain the first regional waterlogging feature vector set, wherein the regional depth prediction model also includes: a second feature extraction network, a third feature extraction network, a first temporal recurrent gating network, a second temporal recurrent gating network, an attention mechanism layer and a waterlogging depth prediction layer. Among them, the first regional waterlogging feature vector in the first regional waterlogging feature vector set can characterize the rainfall feature information and drainage feature information of the current waterlogging depth information, the current regional rainfall intensity and the current regional drainage flow. The regional depth prediction model can be a neural network model that predicts the input current waterlogging depth information, the current regional rainfall intensity and the current regional drainage flow in time series to generate the waterlogging depth within a preset time period. The first feature extraction network, the second feature extraction network and the third feature extraction network can be convolutional neural networks. The waterlogging depth prediction layer can be a fully connected layer.

[0070] Sub-step 3: input the first regional waterlogging feature vector set into the second feature extraction network to obtain the second regional waterlogging feature vector set.

[0071] Sub-step 4: input the second regional waterlogging feature vector set into the third feature extraction network to obtain a third regional waterlogging feature vector set.

[0072] Sub-step 5: input the third regional water accumulation feature vector set into the first temporal recurrent gating network to obtain a first regional water accumulation temporal feature vector set. The first regional water accumulation temporal feature vector in the first regional water accumulation temporal feature vector set can represent the temporal feature information of the extracted third regional water accumulation feature vector.

[0073] Sub-step 6: input the first regional waterlogging time series feature vector set into the second regional waterlogging time series recurrent gating network to obtain a second regional waterlogging time series feature vector set.

[0074] Sub-step 7, inputting the second regional water accumulation time series feature vector set into the attention mechanism layer to obtain a regional water accumulation weight feature vector set. The regional water accumulation weight feature vector in the regional water accumulation weight feature vector set can represent the weight values ​​of the feature vectors of different dimensions in the second regional water accumulation time series feature vector set.

[0075] Sub-step 8: input the regional waterlogging weight feature vector set into the waterlogging depth prediction layer to obtain a waterlogging depth information set.

[0076] Step 105, in response to determining that there is at least one water accumulation depth information greater than or equal to a preset water accumulation depth threshold in the water accumulation depth information set, controlling the urban flood warning device to push the urban flood warning information, and determining the flood control material information and urban road condition information of each city flood control risk location information in at least one city flood control risk location information corresponding to the at least one water accumulation depth information, to obtain a flood control material information set and an urban road condition information set.

[0077] In some embodiments, the execution subject may control the waterlogging warning device to push waterlogging warning information in response to determining that there is at least one waterlogging depth information greater than or equal to a preset waterlogging depth threshold in the waterlogging depth information set, and determine the flood control material information and urban road condition information of each urban flood control risk location information in at least one urban flood control risk location information corresponding to the at least one waterlogging depth information, and obtain a flood control material information set and an urban road condition information set. Among them, the preset waterlogging depth threshold may be a maximum value of a preset waterlogging depth. For example, the preset waterlogging depth threshold may be 20cm. The flood control material information may be material storage location information of each flood control material storage site, and information on the type and quantity of flood control materials. The urban road condition information may characterize the degree of urban roads being flooded by rainwater and the condition information of the roads being passable. The waterlogging warning device may be a device for sending warning information. The waterlogging warning device may be a server.

[0078] Step 106, performing material dispatch processing on the flood control material information set to obtain flood control material dispatch information.

[0079] In some embodiments, the execution subject may perform material dispatch processing on the flood control material information set to obtain flood control material dispatch information. The flood control material dispatch information may represent information on the dispatch of materials from various material storage locations to the urban flood control risk location corresponding to the at least one urban flood control risk location information. For example, the flood control material dispatch information may be dispatch information for the first type of flood control materials from the first material storage location to the corresponding urban flood control risk location along the flood control path.

[0080] As an example, the execution entity may perform material dispatch processing on the flood control material information set through a mixed integer programming model to obtain flood control material dispatch information.

[0081] In some optional implementations of some embodiments, performing material dispatch processing on the flood control material information set to obtain flood control material dispatch information may include the following steps:

[0082] The first step is to determine the regional disaster-affected population density and regional disaster level information of each urban flood risk location information in the above-mentioned urban flood risk location information set, and obtain the regional disaster-affected population density set and the regional disaster level information set. Among them, the regional disaster-affected population density of the above-mentioned regional disaster-affected population density set can be the number of people per unit area in the urban flood risk location. The above-mentioned regional disaster-affected population density can be determined by population heat map, surrounding residential area distribution and residential area active population data. The above-mentioned regional disaster level information can characterize the degree of disaster in the urban flood risk location. The above-mentioned regional disaster level information can be obtained by grading the predicted water depth information.

[0083] The second step is to determine the flood risk level information of each urban flood risk location information in the urban flood risk location information set based on the regional disaster population density set and the regional disaster level information set, and obtain the flood risk level information set. The flood risk level information in the flood risk level information set can characterize the degree of influence of rainfall on the area under the regional disaster population density and regional disaster level information.

[0084] As an example, the execution entity may perform weighted sum processing on the disaster-affected population density of each region in the disaster-affected population density set and the corresponding regional disaster level information in the regional disaster level information set to obtain a flood control risk level information set.

[0085] The third step is to perform flood control resource matching processing on the urban flood control risk location information set corresponding to the above-mentioned flood control risk level information set and the above-mentioned flood control material information set to obtain a regional material matching information set. Among them, the regional material matching information in the above-mentioned regional material matching information set can be information on flood control materials of different types located in different material storage locations obtained by matching the urban flood control risk location corresponding to the flood control risk level information.

[0086] As an example, the execution subject may determine the material demand urgency group of different types of flood control materials required for each urban flood control risk location information in the urban flood control risk location information set corresponding to the flood control risk level information set, and obtain a material demand urgency group set. Then, using a multi-objective optimization method, with the priority of the material demand urgency group set, the priority of the flood control risk level information set, and the minimization of the distance between the material storage location and the urban flood control risk location as the objective function set, the urban flood control risk location information set corresponding to the flood control risk level information set and the flood control material information set are matched with flood control resources to obtain a regional material matching information set.

[0087] The fourth step is to determine the flood control constraint information set of the above-mentioned flood control material information set and the above-mentioned urban flood control risk location information set. Among them, the flood control constraint information in the above-mentioned flood control constraint information set may be a constraint condition that needs to be followed in the process of completing the dispatch of flood control materials. The above-mentioned flood control constraint information set may include: the amount of flood control materials dispatched to each urban flood control risk location is less than the amount of flood control materials provided, the amount of flood control materials dispatched from each material storage location cannot be a negative number, and the transportation capacity of the material transportation equipment is greater than or equal to the amount of flood control materials transported.

[0088] As an example, the execution subject may filter the constraint information of the preset material dispatch constraint information pool to obtain a flood control constraint information set. The preset material dispatch constraint information pool may be a plurality of material dispatch constraint conditions under different pre-set flood control risk level information. The preset material dispatch constraint information pool may also include: transportation condition requirements for different types of flood control materials, and combined transportation of different types of flood control materials.

[0089] The fifth step is to determine the material dispatch objective function set of the flood control material information set and the urban flood control risk location information set. The material dispatch objective function in the material dispatch objective function set can be a linear function that maximizes or minimizes the target that needs to be achieved in the flood control material dispatch process. The material dispatch objective function set can include: minimizing the flood control material dispatch cost and minimizing the flood control material dispatch time.

[0090] As an example, the execution subject may filter the preset material dispatch objective function pool through the flood risk level information set to obtain the material dispatch objective function set. The preset material dispatch objective function pool may be a plurality of material dispatch objective functions under different pre-set flood risk level information. The preset material dispatch objective function pool may also include: maximizing the matching degree between flood control materials and urban flood control risk location information, and minimizing the flood control materials required at urban flood control risk locations under the premise of meeting the rescue requirements.

[0091] The sixth step is to input the above-mentioned flood control risk level information set, the above-mentioned regional material matching information set and the above-mentioned flood control material information set into the above-mentioned material scheduling objective function set to generate flood control material scheduling information under the above-mentioned flood control constraint information set.

[0092] Step 107, generating a set of flood control material transportation routes for at least one city's flood control risk location information based on the flood control material dispatch information and the urban road condition information set.

[0093] In some embodiments, the execution entity may generate a set of flood control material transportation paths for the at least one urban flood risk location information based on the flood control material dispatch information and the urban road condition information set. The flood control material transportation paths in the flood control material transportation path set may be the paths dispatched to transport flood control materials to the corresponding urban flood risk location.

[0094] As an example, the execution subject may use a path planning algorithm to generate a set of flood control material transportation paths for the flood control risk location information of at least one city based on the flood control material dispatch information and the urban road condition information set. The path planning algorithm may be a single path planning algorithm or a planning algorithm obtained by combining multiple path algorithms. The single path planning algorithm may be one of the following: Dijkstra algorithm, A* algorithm, RRT (Rapidly-exploring Random Tree) algorithm.

[0095] In the process of adopting technical solutions to solve the above-mentioned technical problem one, the following technical problem two is often accompanied: how to accurately plan the transportation route of flood control materials from the material storage site where flood control materials are stored to the urban flood risk location to shorten the material dispatch time. For the above-mentioned technical problem two, the conventional solution is generally: using a fast search random algorithm to dynamically adjust the local path within the global road network formed by the global material dispatch path set included in the flood control material dispatch information to generate a flood control material transportation path. However, the above-mentioned conventional solution still has the following problems: Since the fast search random tree algorithm dynamically adjusts the local path on the global road network, the search range of the dynamic adjustment is too large, the search time is long, and some redundant paths are generated, resulting in the generated flood control material transportation path. The accuracy is low, the dynamic adjustment efficiency is low, the transportation time of flood control materials is increased, and the waste of flood control materials is reduced.

[0096] In some optional implementations of some embodiments, generating a set of flood control material transportation routes for the at least one urban flood control risk location information according to the flood control material dispatch information and the urban road condition information set may include the following steps:

[0097] The first step is to determine the urban road section information set corresponding to the global material dispatch path set included in the flood control material dispatch information. Among them, the global material dispatch path in the global material dispatch path set can be the global path of different urban roads that a type of flood control material passes through from the material storage location to different urban flood control risk locations. The urban road section information in the urban road section information set can be the information of the road located between two adjacent intersections with turning functions. The urban road section information can include: urban road section code, urban road section starting point, urban road section end point and road length.

[0098] The second step is to determine the road section risk information of each urban road section information in the urban road section information set according to the urban road condition information set, and obtain a road section risk value set. The road section risk value in the road section risk value set can represent the road risk degree of the urban road section.

[0099] As an example, the execution subject may extract the water accumulation depth information set, the road section crowd congestion coefficient set and the road section traffic control degree value set of each urban road section from the urban road condition information set. The road section crowd congestion coefficient may be the number of people per unit road area. The road section traffic control degree value may characterize the degree of traffic flow. The road section traffic control degree value of an urban road section where there is a traffic police directing traffic and the road section is not open may be infinite. The road section traffic control degree value of an urban road section where there is a traffic police directing traffic and the road section is open may be 2. The road section traffic control degree of an urban road section where there is no traffic directing may be 1. Then, the water accumulation depth information set, the road section crowd congestion coefficient set and the road section traffic control degree value set are weighted summed to obtain a road section risk value set.

[0100] The third step is to select at least one urban road section information whose corresponding road section risk value is greater than or equal to a preset road section risk threshold from the above urban road section information set as the target urban road section information set. The above road section risk threshold may be the maximum value of the pre-set road section risk value. It should be noted that the above road section risk threshold may be determined according to actual conditions and is not limited here.

[0101] Step 4: for each target city road section information in the target city road section information set, perform the following determination steps:

[0102] Sub-step 1: determining a road section topology structure for the target city road section information, wherein the road section topology structure may represent a connection relationship between the city road section corresponding to the city road section information and other city road sections.

[0103] As an example, the execution subject may first select at least one target urban road section information having the same urban road section start point or urban road section end point as the urban road section information after selection from the target urban road section information set, and then perform topological connection between the urban road section information after selection and the urban road section information to obtain a road section topology result.

[0104] Sub-step 2, performing distance search on the road section topology structure, obtaining a road section distance value set and a reachable road path set from the target city road section information to each removed city road section information in the removed city road section information set. The removed city road section information set may be a section information set obtained by removing the target city road section information from the target city road section information set. The reachable road path in the reachable road path set may be a smooth traversable road path from the city road section corresponding to the target city road section information to the removed city road section corresponding to the removed city road section information.

[0105] As an example, the above-mentioned execution entity can use the KNN (K-Nearest Neighbor) algorithm to perform a distance search on the above-mentioned road section topological structure, and obtain a set of distance values ​​and a set of reachable road paths from the above-mentioned target city road section information to each road section in the above-mentioned removed city road section information set.

[0106] Sub-step 3, selecting at least one road section distance value less than or equal to a preset road section distance threshold from the road section distance value set, and determining it as the target road section distance value set. The preset road section distance threshold may be a preset minimum value of the road section distance. For example, the preset road section distance threshold may be 600 meters.

[0107] Sub-step 4, generating a road section random tree corresponding to the above-mentioned urban road section information according to the urban road section starting point, the urban road section end point, the above-mentioned target road section distance value set and the reachable road path set corresponding to the above-mentioned target road section distance value set. Among them, the above-mentioned road section random tree can be a section topology structure that displays the above-mentioned target urban road section in a tree structure. The nodes in the above-mentioned road section random tree can be the target urban road section information. The root node and the terminal node of the above-mentioned road section random tree are respectively the target urban road section corresponding to the above-mentioned target urban road section information and the target urban road section including the urban flood control risk position corresponding to the global material dispatch path.

[0108] As an example, the execution subject may first determine the starting point of the urban road section or the end point of the urban road section as a node of the road section tree structure. Then, the target road section distance value set is determined as the reachable section distance set of each reachable road path in the reachable road path set in the road section tree structure. Finally, a road section random tree corresponding to the target urban road section information is generated through the nodes of the road section tree structure and the reachable section distance set.

[0109] Sub-step 5, based on the target root node urban road segment of the above road segment random tree, perform the following row segment connection steps:

[0110] The first sub-step is to determine the starting random section of the target root node urban road section and the starting target sampling section of the starting random section. The starting random section may be a subsequent section of the target urban road section selected by the target bias sampling strategy. The starting target sampling section may be a road section closest to the starting random section. The target root node urban road section may be a target urban road section located at the root node of the road section random tree.

[0111] The second sub-step is to establish a termination gravitational potential field function and an obstacle repulsion potential field function for the starting random road segment. Among them, the above-mentioned termination gravitational potential field function can characterize the potential field function formed by the gravitational force of the urban flood prevention risk position of the global material dispatch path corresponding to the target root node urban road segment on the material transportation equipment. The above-mentioned obstacle repulsion potential field function can characterize the potential field function formed by the repulsion of the road segment obstacles included in each target urban road segment of the above-mentioned road segment tree structure on the material transportation equipment. The above-mentioned road segment obstacles may include but are not limited to at least one of the following: urban buildings, vehicles and pedestrians moving on the road.

[0112] The third sub-step is to decompose the gravitational force and repulsive force corresponding to the termination gravitational potential field function and the obstacle repulsive force potential field function, determine the target segment vector resultant force of the initial target sampling segment, and determine the force direction corresponding to the target segment vector resultant force as the segment sampling direction of the road segment random tree. The target segment vector resultant force can be the total resultant force of the termination gravitational potential field function and the obstacle repulsive force potential field function on the target city road segment where the material transportation equipment is located.

[0113] The fourth sub-step is to determine the subsequent sampling section of the initial target sampling section according to the target section vector force, the initial target sampling section and the section sampling direction. The subsequent sampling section may be an urban road section obtained by the next step of sampling of the initial target sampling section.

[0114] As an example, the execution subject may first decompose the vector resultant force of the target road section to obtain the horizontal coordinate force value and the vertical coordinate force value. Then, the ratio of the preset sampling step length to the horizontal coordinate force value is determined as the horizontal coordinate value, and the product of the preset sampling step length and the vertical coordinate force value is determined as the vertical coordinate value. Among them, the preset sampling step length may be a preset sampling distance value. Finally, according to the sampling direction of the road section, the coordinate values ​​corresponding to the above-mentioned starting target sampling road section and the above-mentioned horizontal coordinate value and vertical coordinate value are determined as the coordinates of the subsequent sampling road section. For example, if the sampling direction of the road section is positive in both the horizontal and vertical coordinate systems, the sum of the horizontal coordinate of the above-mentioned starting target sampling road section and the above-mentioned horizontal coordinate value is determined as the horizontal coordinate of the subsequent sampling road section, and the sum of the vertical coordinate of the above-mentioned starting target sampling road section and the above-mentioned vertical coordinate value is determined as the vertical coordinate of the subsequent sampling road section.

[0115] The fifth sub-step is to perform an obstacle collision test on the sampling road segment to obtain a collision detection result. The sampling road segment may be a line segment formed by the starting target sampling road segment and the subsequent sampling road segment. The obstacle collision test may be a test of whether the sampling road segment passes through an area where an obstacle is located.

[0116] The sixth sub-step is, in response to determining that the collision detection result characterizes that the detection has passed, generating a starting path of a section from the target urban road section to the subsequent sampling section, and determining whether the parent section of the subsequent sampling section needs to be updated. In practice, the above-mentioned execution subject can first determine the sampling section set included in the area with the subsequent sampling section as the center and the preset radius value as the radius. Secondly, determine the parent sampling section of each sampling section in the above-mentioned sampling section set to obtain the parent sampling section set. Then, determine the first distance value from each parent sampling section in the above-mentioned parent sampling section set to the target root node urban road section to obtain the first distance value set. And determine the subsequent sampling section as the parent sampling section of each sampling section in the above-mentioned sampling section set, and determine the parent sampling section of the above-mentioned sampling section as the second distance value from the subsequent sampling section to the target root node urban road section, as the second distance value set. Finally, in response to determining that there is a first distance value in the first distance value set that is smaller than the corresponding second distance value in the second distance value set, the parent section of the subsequent sampling section is updated, that is, the sampling section corresponding to the first distance value being smaller than the second distance value is determined as the parent section of the subsequent sampling section, and then traced back to the sections included in the target city road section in sequence.

[0117] The seventh sub-step, in response to determining that the parent section of the subsequent sampling section does not need to be updated, determines the target urban road section including the urban flood risk location in the road section random tree as the target root node urban road section, and determines the gravity function of the target root node urban road section to the target urban road section including the urban flood risk location as the termination gravitational potential field function, so as to perform the above-mentioned determination step again, and uses the obtained subsequent sampling section as the subsequent termination sampling section, and generates a section termination path from the target urban road section including the urban flood risk location to the subsequent termination sampling section.

[0118] In the eighth sub-step, in response to determining that the distance value between the subsequent terminating sampling section and the subsequent sampling section is less than or equal to a preset section distance threshold, the subsequent terminating sampling section and the subsequent sampling section are connected to obtain a section connection sampling path. The preset distance threshold may be a maximum value of a preset distance. The preset section distance threshold may be a minimum value between preset sections.

[0119] In a ninth sub-step, in response to determining that the segment connection sampling path does not pass through the obstacle area corresponding to the obstacle set, the segment start path, the segment end path and the segment connection sampling path are determined as the flood control material transportation path.

[0120] Sub-step 6, in response to determining that the road segment distance value is greater than the above-mentioned preset distance threshold, the subsequent sampling section is used as the target root node urban road section, and the subsequent termination sampling section is used as the target urban road section including the urban flood risk location, so as to execute the section connection step again.

[0121] The above technical solution and its related contents, combined with step "step 108", as an inventive point of an embodiment of the present disclosure, solves the second technical problem mentioned in the background technology: "Since the fast search random tree algorithm is to dynamically adjust the local path on the global road network, there is a large search range for dynamic adjustment, a long search time, and some redundant paths are generated, resulting in low accuracy of the generated flood control material transportation path, low dynamic adjustment efficiency, increased transportation time of flood control materials and increased waste of flood control materials." The factors that lead to low accuracy of the generated flood control material transportation path, low dynamic adjustment efficiency, increased transportation time of flood control materials and increased waste of flood control materials are often as follows: Since the fast search random tree algorithm is to dynamically adjust the local path on the global road network, there is a large search range for dynamic adjustment, a long search time, and some redundant paths are generated. If the above factors are solved, the effect of improving the accuracy of the generated flood control material transportation path, improving the dynamic adjustment efficiency, shortening the transportation time of flood control materials and reducing the waste of flood control materials can be achieved. In order to achieve this effect, the present disclosure first determines the road section risk value set of the urban road section information set corresponding to the material global dispatch path set included in the flood control material dispatch information, and can determine the impassable urban road sections in advance so that the impassable urban road sections can be replaced later to improve the safety of material transportation equipment and reduce the damage rate. Secondly, the target urban road sections corresponding to each target urban road section information in the target urban road section information set are searched for distance and the construction of a road section random tree can reduce the target urban road sections related to the target urban road sections and shorten the search range of subsequent dynamic adjustment. Subsequently, the target root node urban road sections included in the road section random tree and the target urban road sections including the urban flood control risk position are constructed in a bidirectional path, which can improve the efficiency of generating the flood control material transportation path and the efficiency of dynamic adjustment. Then, the termination gravitational potential field function and the obstacle repulsion potential field function are established to control the direction of the generated post-sequence sampling sections, which can reduce the space of random search and reduce the generation of redundant paths. Then, obstacle collision inspection is performed on the sampling path segments, which can improve the probability of material transportation equipment avoiding obstacle areas and improve the safety of material transportation equipment. Finally, the segment start path, segment end path and segment connection sampling path generated by cyclic iteration are spliced ​​to generate a dynamically adjusted flood control material transportation path, and the material transportation equipment is controlled to transport materials according to the flood control material transportation path, which can improve the accuracy of the generated flood control material transportation path, shorten the transportation time of flood control materials and reduce the waste of flood control materials.

[0122] Step 108, based on the flood control material dispatch information, control the material transportation equipment to dispatch materials according to the flood control material transportation route set.

[0123] In some embodiments, the execution subject may control the material transportation equipment to dispatch materials according to the flood control material transportation path set according to the flood control material dispatch information. The material transportation equipment may be equipment for transporting flood control materials. For example, the material transportation equipment may include but is not limited to at least one of the following: a car, a truck, or a helicopter.

[0124] As an example, the execution entity may send the flood control material dispatch information and the flood control material transportation route set to the material transportation equipment to control the material transportation equipment to perform material dispatch.

[0125] The above-mentioned embodiments of the present disclosure have the following beneficial effects: the flood control material dispatching of some embodiments of the present disclosure can understand the urban waterlogging situation in real time, improve the accuracy of waterlogging risk identification, the accuracy of warning information push and the rationality and timeliness of flood control material dispatching, reduce the waste of flood control resources, and improve the emergency response capability of the city. Specifically, the reason why the push of the relevant generated flood control warning information and the identification of the waterlogging area are low in accuracy, which is easy to increase the missed detection rate and the false detection rate, and increase the waste of emergency resources and the losses caused by waterlogging is that: due to the subjectivity of expert experience, and the source of flood control data obtained by experts is relatively single, resulting in the push of the generated flood control warning information and the identification of the waterlogging area. The accuracy is low, which is easy to increase the missed detection rate and the false detection rate, and increase the waste of emergency resources and the losses caused by waterlogging. Based on this, the flood control material dispatching method of some embodiments of the present disclosure can first obtain a multi-source flood control information set, wherein the multi-source flood control information set includes at least one of the following: meteorological information, urban water conservancy information, urban three-dimensional digital model and historical flood control data set. Here, the rapid transmission and sharing of data can be achieved, and the comprehensiveness of flood control information can be improved. Secondly, based on the above-mentioned multi-source flood control information set, the urban flood control scope within the forecast time period is generated. Here, the accuracy of the urban flood control scope can be improved, which is convenient for the subsequent further identification of the urban flood control risk location information. Thirdly, the flood control and waterlogging risk of the above-mentioned urban flood control scope is identified to obtain the urban flood control risk location information set. Here, the accuracy of the identification of waterlogging risk location information can be improved, so as to better understand the urban waterlogging situation and accurately determine the area where the waterlogging disaster occurs. Subsequently, the water accumulation depth is predicted for each urban flood control risk location information in the above-mentioned urban flood control risk location information set to generate the water accumulation depth information within the forecast time period and obtain the water accumulation depth information set. Here, the accuracy of the water accumulation depth prediction can be improved to better understand the degree of water accumulation of each waterlogging risk location information, so as to facilitate the subsequent dispatch of flood control materials. Next, in response to determining that there is at least one water accumulation depth information greater than or equal to the preset water accumulation depth threshold in the above-mentioned water accumulation depth information set, the waterlogging warning device is controlled to push the waterlogging warning information, and the flood control material information and urban road condition information of each urban flood control risk location information in the at least one urban flood control risk location information corresponding to the above-mentioned at least one water accumulation depth information are determined, and the flood control material information set and the urban road condition information set are obtained. Here, the accurate push of waterlogging warning information can be improved, and the missed detection rate and the false detection rate can be reduced. Afterwards, the above-mentioned flood control material information set is processed for material dispatch to obtain flood control material dispatch information. Here, the urban waterlogging risk response capability, the timeliness of material dispatch and the degree of urban losses caused by waterlogging risks can be improved. Then, based on the above-mentioned flood control material dispatch information and the above-mentioned urban road condition information set, a flood control material transportation path set for the above-mentioned at least one urban flood control risk location information is generated.Here, the accuracy and efficiency of the generated flood control material transportation path set can be improved, and the material transportation time and waste of flood control materials can be reduced. Finally, according to the above flood control material dispatching information, the material transportation equipment is controlled to dispatch materials according to the above flood control material transportation path set. Here, the transportation efficiency of the material transportation equipment is improved and the transportation time is shortened. It can be obtained that the flood control material dispatching method can understand the urban waterlogging situation in real time, improve the accuracy of waterlogging risk identification, the accuracy of early warning information push, and the rationality and timeliness of flood control material dispatching, reduce the waste of flood control resources, and improve the city's emergency response capabilities.

[0126] Further references Figure 2 As an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a flood control material dispatching device. These device embodiments are similar to Figure 1 Corresponding to the method embodiments shown, the flood control material dispatching device can be specifically applied to various electronic devices.

[0127] like Figure 2As shown, a flood control material dispatching device 200 includes: an acquisition unit 201, a first generation unit 202, a waterlogging risk identification unit 203, a waterlogging depth prediction unit 204, a first control unit 205, a material dispatching unit 206, a second generation unit 207 and a second control unit 208. The acquisition unit 201 is configured to: acquire a multi-source flood control information set, wherein the multi-source flood control information set includes at least one of the following: meteorological information, urban water conservancy information, a three-dimensional digital model of the city and a historical flood control data set. The first generation unit 202 is configured to: generate an urban flood control range within a prediction time period according to the multi-source flood control information set. The flood control waterlogging risk identification unit 203 is configured to: perform flood control waterlogging risk identification on the urban flood control range to obtain an urban flood control risk location information set. The waterlogging depth prediction unit 204 is configured to: perform waterlogging depth prediction on each urban flood control risk location information in the urban flood control risk location information set to generate waterlogging depth information within the prediction time period to obtain a waterlogging depth information set. The first control unit 205 is configured to: in response to determining that there is at least one water accumulation depth information greater than or equal to the preset water accumulation depth threshold in the above-mentioned water accumulation depth information set, control the waterlogging warning device to push the waterlogging warning information, and determine the flood control material information and urban road condition information of each urban flood control risk location information in the at least one urban flood control risk location information corresponding to the above-mentioned at least one water accumulation depth information, and obtain the flood control material information set and the urban road condition information set. The material dispatching unit 206 is configured to: perform material dispatching processing on the above-mentioned flood control material information set to obtain flood control material dispatching information. The second generating unit 207 is configured to: generate a flood control material transportation path set for the above-mentioned at least one urban flood control risk location information according to the above-mentioned flood control material dispatching information and the above-mentioned urban road condition information set. The second control unit 208 is configured to: control the material transportation equipment to dispatch materials according to the above-mentioned flood control material transportation path set according to the above-mentioned flood control material dispatching information.

[0128] It is understandable that the units recorded in the flood control material dispatching device 200 are similar to those in the reference Figure 1 Therefore, the operations, features and beneficial effects described above for the method are also applicable to the flood control material dispatching device 200 and the units contained therein, and will not be repeated here.

[0129] Reference below Figure 3 , which shows a structural schematic diagram of an electronic device (eg, an electronic device) 300 suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0130] like Figure 3As shown, the electronic device 300 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 to a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0131] Typically, the following devices may be connected to the I / O interface 305: an input device 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 308 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 309. The communication device 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. Figure 3 The electronic device 300 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 3 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0132] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above-mentioned functions defined in the method of some embodiments of the present disclosure are executed.

[0133] It should be noted that the computer-readable medium mentioned above in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present disclosure, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. In some embodiments of the present disclosure, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer readable signal media may also be any computer readable medium other than computer readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0134] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (Hyper Text Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0135] The above-mentioned computer-readable medium may be included in the above-mentioned electronic device; or it may exist independently without being assembled into the electronic device. The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the electronic device, the electronic device: obtains a multi-source flood control information set, wherein the above-mentioned multi-source flood control information set includes at least one of the following: meteorological information, urban water conservancy information, a three-dimensional digital model of the city, and a historical flood control data set; generates an urban flood control range within a forecast time period based on the above-mentioned multi-source flood control information set; identifies flood control and waterlogging risks for the above-mentioned urban flood control range to obtain an urban flood control risk location information set; predicts the water accumulation depth for each urban flood control risk location information in the above-mentioned urban flood control risk location information set to generate water accumulation depth information within the forecast time period to obtain a water accumulation depth information set; in response to determining that there is a large amount of water accumulation depth information in the above-mentioned water accumulation depth information set at least one water accumulation depth information equal to a preset water accumulation depth threshold, controlling the waterlogging warning device to push the waterlogging warning information, and determining the flood control material information and urban road condition information of each urban flood control risk location information in at least one urban flood control risk location information corresponding to the at least one water accumulation depth information, to obtain a flood control material information set and an urban road condition information set; performing material dispatch processing on the flood control material information set to obtain flood control material dispatch information; generating a flood control material transportation path set for the at least one urban flood control risk location information according to the flood control material dispatch information and the urban road condition information set; and controlling the material transportation equipment to dispatch materials according to the flood control material transportation path set according to the flood control material dispatch information.

[0136] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0137] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0138] The units described in some embodiments of the present disclosure may be implemented by software or by hardware. The described units may also be provided in a processor, for example, may be described as: a processor including an acquisition unit, a first generation unit, a waterlogging risk identification unit, a waterlogging depth prediction unit, a first control unit, a material dispatching unit, a second generation unit, and a second control unit. The names of these units do not, in some cases, constitute limitations on the units themselves, for example, the acquisition unit may also be described as a "unit for acquiring a multi-source flood control information set".

[0139] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that may be used include, without limitation, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0140] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, the above features are replaced with (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A method for dispatching flood control materials, comprising: Acquire a multi-source flood control information set, wherein the multi-source flood control information set includes at least one of the following: meteorological information, urban water conservancy information, a three-dimensional digital model of the city, and a historical flood control data set; Generate the urban flood control scope within the forecast time period according to the multi-source flood control information set, wherein the generating the urban flood control scope within the forecast time period according to the multi-source flood control information set includes: Performing data standardization processing on the meteorological information, historical flood control data set and urban water conservancy information included in the multi-source flood control information set to obtain standardized meteorological information, standardized historical flood control data set and standardized urban water conservancy information; Inputting the standardized meteorological information, the standardized historical flood control data set and the standardized urban water conservancy information into the urban waterlogging hydrodynamics model to obtain an urban waterlogging information set, wherein the inputting the standardized meteorological information, the standardized historical flood control data set and the standardized urban water conservancy information into the urban waterlogging hydrodynamics model to obtain the urban waterlogging information set includes: Performing regional division processing on the city corresponding to the three-dimensional digital model of the city to obtain a set of urban sub-catchment areas; For each urban subcatchment in the urban subcatchment set, perform the following generation steps: Determining the regional rainfall intensity and the regional rainfall duration for the urban subcatchment area according to the standardized meteorological information; Inputting the three-dimensional digital model of the city, the rainfall intensity of the region and the duration of rainfall in the region into the urban rainfall waterlogging hydrological model to obtain a time-varying runoff coefficient; Determine the regional seasonal runoff coefficient factor, regional soil erosion risk coefficient factor, regional rainfall interval coefficient factor and slope crown interception coefficient factor within the forecast time period according to the standardized historical flood control data set; Determine the product of the time-varying runoff coefficient, the regional seasonal runoff coefficient factor, the regional soil erosion risk coefficient factor, the regional rainfall interval coefficient factor and the slope crown interception coefficient factor as the regional real-time runoff coefficient; Generating a regional drainage flow for the urban sub-catchment area according to the standardized urban water conservancy information; Generate regional surface runoff flow according to the regional rainfall intensity, the regional real-time runoff coefficient, and the regional area corresponding to the urban sub-catchment area; The difference between the regional surface runoff flow and the regional drainage flow is determined as the regional runoff flow; Generate the depth of waterlogging in the area according to the runoff generated in the area; The obtained rainfall intensity, rainfall duration, surface runoff, drainage, runoff and waterlogging depth in each area are determined as the urban waterlogging information set. Extracting a waterlogging spatial feature dataset and a waterlogging temporal feature dataset from the urban waterlogging information set; Inputting the waterlogging spatial feature data set into the urban waterlogging spatial prediction model to obtain an urban waterlogging waterlogging location information set and an urban waterlogging waterlogging depth information set; Inputting the waterlogging time characteristic data set into the urban waterlogging time prediction model to obtain the urban waterlogging water depth time series data set; Determine the urban waterlogging waterlogging location information set, the urban waterlogging waterlogging depth information set and the urban waterlogging waterlogging depth time series data set as the urban flood control range; Identify the flood control and waterlogging risks in the urban flood control area to obtain an urban flood control risk location information set; Predicting the waterlogging depth for each urban flood risk location information in the urban flood risk location information set to generate waterlogging depth information within a prediction time period to obtain a waterlogging depth information set; In response to determining that at least one water accumulation depth information greater than or equal to a preset water accumulation depth threshold exists in the water accumulation depth information set, controlling the waterlogging warning device to push waterlogging warning information, and determining flood control material information and urban road condition information of each urban flood control risk location information in at least one urban flood control risk location information corresponding to the at least one water accumulation depth information, to obtain a flood control material information set and an urban road condition information set; Performing material dispatch processing on the flood control material information set to obtain flood control material dispatch information; Generating a set of flood control material transportation routes for the at least one urban flood control risk location information according to the flood control material dispatch information and the urban road condition information set; According to the flood control material dispatching information, the material transportation equipment is controlled to dispatch the materials according to the flood control material transportation route set.

2. The method according to claim 1, wherein: Generating the depth of waterlogging in the region according to the runoff flow of the region includes: Determine the average regional slope gradient, regional water flow cross-sectional area, regional water flow cross-sectional wet perimeter, regional water flow cross-sectional width and regional surface roughness of the urban subcatchment area; Inputting the regional surface roughness into the Xie Cai formula to obtain the parameter correlation relationship between the regional hydraulic radius parameter and the Xie Cai parameter; Determine the regional hydraulic radius value corresponding to the regional hydraulic radius parameter according to the parameter association relationship, the regional runoff flow, the average regional slope gradient and the regional water flow cross-sectional area; The depth of waterlogging in the area is determined based on the hydraulic radius value of the area, the width of the water-passing cross-section of the area and the wet perimeter of the water-passing cross-section of the area.

3. The method according to claim 1, wherein: The method of performing waterlogging depth prediction on each urban flood risk location information in the urban flood risk location information set to generate waterlogging depth information within a prediction time period to obtain a waterlogging depth information set includes: For each urban flood risk location information in the urban flood risk location information set, the following waterlogging depth prediction steps are performed: Obtaining the current water depth information, the current regional rainfall intensity and the current regional drainage flow of the city's flood risk location information; Input the current waterlogging depth information, the current regional rainfall intensity and the current regional drainage flow into a first feature extraction network included in a regional depth prediction model to obtain a first regional waterlogging feature vector set, wherein the regional depth prediction model also includes: a second feature extraction network, a third feature extraction network, a first temporal recurrent gating network, a second temporal recurrent gating network, an attention mechanism layer and a waterlogging depth prediction layer; Inputting the first regional water accumulation feature vector set into the second feature extraction network to obtain a second regional water accumulation feature vector set; Inputting the second regional water accumulation feature vector set into the third feature extraction network to obtain a third regional water accumulation feature vector set; Inputting the third regional water accumulation feature vector set into the first sequential recurrent gating network to obtain a first regional water accumulation temporal feature vector set; Inputting the first regional water accumulation time series feature vector set into the second regional water accumulation time series feature vector set into the second regional water accumulation time series feature vector set; Inputting the second regional water accumulation time series feature vector set into the attention mechanism layer to obtain a regional water accumulation weight feature vector set; The regional waterlogging weight feature vector set is input into the waterlogging depth prediction layer to obtain waterlogging depth information.

4. The method according to claim 1, wherein: The material dispatching process is performed on the flood control material information set to obtain flood control material dispatching information, including: Determine the regional disaster-affected population density and regional disaster level information of each urban flood risk location information in the urban flood risk location information set, and obtain a regional disaster-affected population density set and a regional disaster level information set; Determine the flood control risk level information of each urban flood control risk location information in the urban flood control risk location information set according to the regional disaster affected population density set and the regional disaster level information set, and obtain the flood control risk level information set; Performing flood control resource matching processing on the urban flood control risk location information set and the flood control material information set corresponding to the flood control risk level information set to obtain a regional material matching information set; Determine a flood control constraint information set of the flood control material information set and the urban flood control risk location information set; Determine a material dispatch objective function set for the flood control material information set and the urban flood control risk location information set; The flood control risk level information set, the regional material matching information set and the flood control material information set are input into the material scheduling objective function set to generate flood control material scheduling information under the flood control constraint information set.

5. A flood control material dispatching device, comprising: An acquisition unit is configured to acquire a multi-source flood control information set, wherein the multi-source flood control information set includes at least one of the following: meteorological information, urban water conservancy information, a three-dimensional digital model of a city, and a historical flood control data set; The first generating unit is configured to generate a city flood control scope within a forecast time period according to the multi-source flood control information set, wherein the generating of the city flood control scope within a forecast time period according to the multi-source flood control information set comprises: performing data standardization processing on the meteorological information, historical flood control data set and urban water conservancy information included in the multi-source flood control information set to obtain standardized meteorological information, standardized historical flood control data set and standardized urban water conservancy information; inputting the standardized meteorological information, the standardized historical flood control data set and the standardized urban water conservancy information into an urban waterlogging hydrodynamic model to obtain an urban waterlogging information set, wherein the inputting of the standardized meteorological information, the standardized historical flood control data set and the standardized The urban water conservancy information is then input into the urban waterlogging hydrodynamic model to obtain an urban waterlogging information set, including: performing regional division processing on the city corresponding to the urban three-dimensional digital model to obtain an urban sub-catchment area set; for each urban sub-catchment area in the urban sub-catchment area set, performing the following generation steps: determining the regional rainfall intensity and the regional rainfall duration for the urban sub-catchment area according to the standardized meteorological information; inputting the urban three-dimensional digital model, the regional rainfall intensity and the regional rainfall duration into the urban rainfall waterlogging hydrological model to obtain a time-varying runoff coefficient; determining the regional seasonal runoff coefficient factor and the regional soil and water loss risk coefficient factor within the forecast time period according to the standardized historical flood control data set. The method comprises the following steps: determining the product of the time-varying runoff coefficient, the regional seasonal runoff coefficient factor, the regional soil erosion risk coefficient factor, the regional rainfall interval coefficient factor and the slope crown interception coefficient factor as the regional real-time runoff coefficient; generating a regional drainage flow for the urban sub-catchment area according to the standardized urban water conservancy information; generating a regional surface runoff flow according to the regional rainfall intensity, the regional real-time runoff coefficient and the regional area corresponding to the urban sub-catchment area; determining the difference between the regional surface runoff flow and the regional drainage flow as the regional runoff flow; generating a regional waterlogging depth according to the regional runoff flow; and obtaining the regional waterlogging depth. The rainfall intensity of each region, the duration of rainfall in each region, the surface runoff flow of each region, the drainage flow of each region, the runoff flow of each region and the waterlogging depth of each region are determined as the urban waterlogging information set; the waterlogging spatial feature data set and the waterlogging time feature data set in the urban waterlogging information set are extracted; the waterlogging spatial feature data set is input into the urban waterlogging spatial prediction model to obtain the urban waterlogging waterlogging location information set and the urban waterlogging waterlogging depth information set; the waterlogging time feature data set is input into the urban waterlogging time prediction model to obtain the urban waterlogging waterlogging depth time series data set; the urban waterlogging waterlogging location information set, the urban waterlogging waterlogging depth information set and the urban waterlogging waterlogging depth time series data set are determined as the urban flood control range; A flood control and waterlogging risk identification unit is configured to identify the flood control and waterlogging risks of the urban flood control range and obtain an urban flood control risk location information set; A water accumulation depth prediction unit is configured to perform water accumulation depth prediction on each urban flood control risk location information in the urban flood control risk location information set to generate water accumulation depth information within a prediction time period to obtain a water accumulation depth information set; The first control unit is configured to, in response to determining that there is at least one water accumulation depth information greater than or equal to a preset water accumulation depth threshold in the water accumulation depth information set, control the waterlogging warning device to push waterlogging warning information, and determine the flood control material information and urban road condition information of each urban flood control risk location information in at least one urban flood control risk location information corresponding to the at least one water accumulation depth information, to obtain a flood control material information set and an urban road condition information set; A material dispatching unit is configured to perform material dispatching processing on the flood control material information set to obtain flood control material dispatching information; A second generating unit is configured to generate a set of flood control material transportation routes for the at least one urban flood control risk location information according to the flood control material dispatching information and the urban road condition information set; The second control unit is configured to control the material transportation equipment to perform material dispatch according to the flood control material transportation path set based on the flood control material dispatch information.

6. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 4.

7. A computer readable medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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