Early warning method for flood countermeasures, apparatus, computer equipment, and storage media

Abstract

To provide an early warning method, apparatus, computer equipment, and storage medium for flood countermeasures, which considers an influence on a lower early warning node of each early warning node in a flood process when performing early warning for flood countermeasures, and effectively improves the precision, accuracy, and timeliness of the early warning for flood countermeasures.SOLUTION: This method includes: acquiring outflow process data corresponding to a plurality of different early warning nodes in a target area, and a connection relationship among the different early warning nodes; calculating, based on the connection relationship among the different early warning nodes and the outflow process data of each early warning node, an influence contribution value to a lower early warning node when a flood occurs at each early warning node; determining, based on the influence contribution values, a key early warning node from among the plurality of different early warning nodes; determining a key early warning region based on the key early warning node; and generating flood early warning information for the target area based on water level information and a predetermined water level threshold in the key early warning region.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to the technical field of early flood warning, and specifically to an early warning method, device, computer equipment and storage medium for flood countermeasures.

Background Art

[0002] Due to the influence of climate change and the rapid progress of urbanization, urban inland flooding caused by heavy rain and floods has become frequent, and the damage has become more serious. Accurate early warning of floods caused by heavy rain in cities is an effective way to reduce flood losses.

[0003] In related technologies, generally, by dividing the administrative area of a city, the rainfall forecast data of the city is input into a precipitation-runoff / confluence model for simulation to obtain the inundation situation of different administrative areas, and based on the inundation situation of each administrative area and the inundation threshold of the administrative area, it is determined whether to issue an early flood warning for the administrative area. However, due to the existence of urban drainage pipe networks and river systems, the flood process in one administrative area will be affected by other administrative areas. If early flood warning is issued only based on the simulation results of the inundation situation of administrative areas without considering the influence of the flood processes in other areas, the accuracy and precision of the early warning for flood countermeasures are low.

Summary of the Invention

Problems to be Solved by the Invention

[0004] In view of the above circumstances, in order to solve the problem that the accuracy and precision of the conventional early warning scheme for flood countermeasures are low, the present invention provides an early warning method, device, computer equipment and storage medium for flood countermeasures.

Means for Solving the Problems

[0005] In a first aspect, the present invention provides an early warning method for flood control, which includes the steps of obtaining outflow process data corresponding to a plurality of different early warning nodes in a target area and connection relationships between different early warning nodes, where the plurality of different early warning nodes are determined by the drain pipe network information and river water system information of the target area; calculating, based on the connection relationships between different early warning nodes and the outflow process data corresponding to different early warning nodes respectively, an influence contribution value to a lower-level early warning node when a flood occurs at each early warning node, where the influence contribution value represents the contribution amount to flood formation at the lower-level early warning node when a flood occurs at each early warning node; determining a key early warning node according to the influence contribution value; determining a key early warning area according to the key early warning node; obtaining water level information within the key early warning area; and generating flood early warning information for the target area based on the water level information within the key early warning area and a predetermined water level threshold.

[0006] The early warning method for flood control according to the present invention calculates an influence contribution value to a lower-level early warning node when a flood occurs at each early warning node based on the connection relationships between different early warning nodes and the outflow process data of each early warning node, determines a key early warning node from a plurality of different early warning nodes based on the influence contribution value, determines a key early warning area based on the key early warning node, generates flood early warning information for the target area based on the water level information within the key early warning area and a predetermined water level threshold, and when performing early warning for flood control, takes into account the influence on lower-level early warning nodes of each early warning node in the flood process, and performs early warning for flood control in the target area based on the determined key early warning area, effectively improving the accuracy, precision and timeliness of the early warning for flood control. In related technologies, when performing early warning for flood control, early flood warning is performed only based on the simulation results of the waterlogging situation in administrative regions, without considering the influence of the flood process in other regions, thus solving the problems of low accuracy and low precision of the early warning for flood control.

[0007] In one selectable embodiment, the step of calculating, based on the connection relationships between different early warning nodes and the outflow process data respectively corresponding to different early warning nodes, the influence contribution value to the lower-level early warning nodes when a flood occurs at each early warning node includes: determining at least one pair of early warning nodes based on the connection relationships between different early warning nodes, where the pair of early warning nodes consists of both a first early warning node and a second early warning node that are directly connected; calculating the target probability of the corresponding pair of early warning nodes based on the outflow process data of different early warning nodes, where the target probability is used to represent the probability that a flood occurs at the second early warning node when a flood occurs at the first early warning node in the pair of early warning nodes; and calculating the influence contribution value to the lower-level early warning nodes when a flood occurs at each early warning node based on the target probability.

[0008] The method according to this selectable embodiment determines the influence contribution value to the lower-level early warning nodes when a flood occurs at each early warning node based on the target probability that a flood occurs at the corresponding lower-level early warning node when a flood occurs at each early warning node, so that the calculation result of the influence contribution value is more accurate.

[0009] In one selectable embodiment, the step of obtaining the outflow process data respectively corresponding to a plurality of different early warning nodes in the target area includes: obtaining the historical rainfall information of each early warning node; and sequentially inputting the historical rainfall information of each early warning node into a pre-constructed outflow simulation model, and the outflow simulation model outputs the outflow process data of the corresponding early warning node.

[0010] The method according to this selectable embodiment can accurately realize the simulation of the outflow process of each early warning node based on the pre-constructed outflow simulation model.

[0011] In one selectable embodiment, the method further includes: determining a corresponding early warning area based on the location information of each early warning node; obtaining the outflow process corresponding to each early warning node in the target rainfall process and a predetermined outflow threshold of each early warning node; and generating early warning information for the early warning areas corresponding to different early warning nodes respectively based on the outflow process corresponding to each early warning node in the target rainfall process and the predetermined outflow threshold of the corresponding early warning node.

[0012] The method according to this selectable embodiment generates early warning information for the early warning areas corresponding to different early warning nodes respectively based on the outflow process corresponding to each early warning node in the target rainfall process and the predetermined outflow threshold of the corresponding early warning node, and accurately realizes flood forecasting for different early warning areas.

[0013] In one selectable embodiment, the step of obtaining the outflow process corresponding to each early warning node in the target rainfall process includes: obtaining target rainfall information; and inputting the target rainfall information into a pre-constructed outflow simulation model, and the outflow simulation model outputs outflow process data corresponding to each early warning node in the target rainfall process.

[0014] The method according to this selectable embodiment can accurately simulate the outflow process of key early warning areas under target rainfall conditions by using a pre-constructed outflow simulation model, which facilitates subsequent early flood warnings.

[0015] In one selectable embodiment, the step of calculating the target probability of the corresponding early warning node pair based on the outflow process data of different early warning nodes includes: determining the marginal distribution function of the outflow process corresponding to the first early warning node in each early warning node pair and the marginal distribution function of the outflow process corresponding to the second early warning node based on the outflow process data of different early warning nodes; establishing the joint distribution function of each early warning node pair based on a predetermined connection function, the marginal distribution function of the outflow process corresponding to the first early warning node in each early warning node pair, and the marginal distribution function of the outflow process corresponding to the second early warning node; and calculating the target probability of the corresponding early warning node pair based on the joint distribution function of each early warning node pair.

[0016] The method according to this selectable embodiment can establish the joint distribution function of each early warning node pair based on a predetermined connection function, the marginal distribution function of the outflow process corresponding to the first early warning node in each early warning node pair, and the marginal distribution function of the outflow process corresponding to the second early warning node, and calculate the target probability of the corresponding early warning node pair based on the joint distribution function of each early warning node pair, thereby realizing the calculation of the target probability.

[0017] In one selectable embodiment, the step of determining the key early warning area based on the key early warning node includes: obtaining the digital elevation data of the target area and the location information of the key early warning node; determining the corresponding catchment area when a flood occurs at the key early warning node based on the digital elevation data of the target area and the location information of the key early warning node; and determining the key early warning area based on the corresponding catchment area when a flood occurs at the key early warning node.

[0018] The method according to this selectable embodiment can accurately determine the corresponding catchment area when a flood occurs at the key early warning node based on the digital elevation data of the target area and the location information of the key early warning node, and determine the key early warning area.

[0019] In a second aspect, the present invention is used to obtain outflow process data corresponding to a plurality of different early warning nodes in a target area and connection relationships between different early warning nodes. The plurality of different early warning nodes include a first acquisition module determined by the drain pipe network information and river water system information of the target area, and based on the connection relationships between different early warning nodes and the outflow process data corresponding to different early warning nodes respectively, it is used to calculate the influence contribution value to the lower-level early warning nodes when a flood occurs at each early warning node. The influence contribution value represents the contribution amount to the flood formation at the lower-level early warning nodes when a flood occurs at each early warning node. It includes a calculation module, a first determination module used to determine a key early warning node according to the influence contribution value, a second determination module used to determine a key early warning area according to the key early warning node, a second acquisition module used to obtain water level information within the key early warning area, and a first processing module used to generate early flood warning information for the target area based on the water level information within the key early warning area and a predetermined water level threshold, and provides an early warning device for flood control.

[0020] In one selectable embodiment, the calculation module includes a first determination sub-module used to determine at least one early warning node pair based on the connection relationships between different early warning nodes, and the early warning node pair is composed of both a first early warning node and a second early warning node that are directly connected; a first calculation sub-module used to calculate the target probability of the corresponding early warning node pair based on the outflow process data of different early warning nodes, and the target probability represents the probability that a flood occurs at the second early warning node when a flood occurs at the first early warning node in the early warning node pair; and a second calculation sub-module used to calculate the influence contribution value to the lower-level early warning nodes when a flood occurs at each early warning node based on the target probability.

[0021] In one selectable embodiment, the first acquisition module includes a first acquisition sub-module used to acquire the historical rainfall information of each early warning node, and a processing sub-module used to sequentially input the historical rainfall information of each early warning node into a pre-constructed outflow simulation model, so that the outflow simulation model outputs the outflow process data of the corresponding early warning node.

[0022] In one selectable embodiment, the device further includes a third determination module used to determine the corresponding early warning area based on the position information of each early warning node, a second acquisition module used to acquire the outflow process corresponding to each early warning node in the target rainfall process and the predetermined outflow threshold of each early warning node, and a processing module used to generate the early warning information of the early warning area corresponding to different early warning nodes based on the outflow process corresponding to each early warning node in the target rainfall process and the predetermined outflow threshold of the corresponding early warning node.

[0023] In one selectable embodiment, the second acquisition module includes a second acquisition sub-module used to acquire the target rainfall information, and a processing sub-module used to input the target rainfall information into a pre-constructed outflow simulation model, so that the outflow simulation model outputs the outflow process data corresponding to each early warning node in the target rainfall process.

[0024] In one selectable embodiment, the first calculation sub-module includes a determination unit used to determine the marginal distribution function of the outflow process corresponding to the first early warning node and the marginal distribution function of the outflow process corresponding to the second early warning node in each pair of early warning nodes based on the outflow process data of different early warning nodes, an establishment unit used to establish the joint distribution function of each pair of early warning nodes based on a predetermined connection function, the marginal distribution function of the outflow process corresponding to the first early warning node, and the marginal distribution function of the outflow process corresponding to the second early warning node in each pair of early warning nodes, and a calculation unit used to calculate the target probability of the corresponding pair of early warning nodes based on the joint distribution function of each pair of early warning nodes.

[0025] In a third aspect, the present invention provides a computer device including a memory and a processor, where the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to implement the early warning method for flood control in the first aspect or any one of the corresponding embodiments.

[0026] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the early warning method for flood control in the first aspect or any one of the corresponding embodiments.

Brief Description of the Drawings

[0027] To more clearly illustrate the specific embodiments of the present invention or the technical solutions of the prior art, the following briefly describes the drawings that need to be used in the description of the specific embodiments or the prior art. Obviously, the drawings described below are some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without creative labor.

[0028]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

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Figure 7

Embodiments for Carrying Out the Invention

[0029] In order to make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, hereinafter, with reference to the drawings of the embodiments of the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are some but not all of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present invention.

[0030] In related technologies, generally, by dividing the administrative regions of a city, the rainfall forecast data of the city is input into a precipitation-runoff / confluence model for simulation to obtain the waterlogging situation of different administrative regions, and based on the waterlogging situation of each administrative region and the waterlogging threshold of the administrative region, it is determined whether to issue an early flood warning for the administrative region. However, due to the existence of urban drainage pipe networks and river systems, the flood process in one administrative region will be affected by other administrative regions. If early flood warnings are issued only based on the simulation results of the waterlogging situation in the administrative region without considering the influence of the flood processes in other regions, the accuracy and precision of the early warning for flood control are low.

[0031] In view of the above circumstances, an embodiment of the present invention provides a flood control early warning method applicable to processor implementation for realizing early warning against floods in a target area. The method according to the present invention, when performing flood control early warning, considers the influence on lower-level early warning nodes of each early warning node in the flood process, effectively improves the accuracy, precision and timeliness of flood control early warning, and in the related art, when performing flood control early warning, flood early warning is performed only based on the simulation results of the inundation situation in the administrative area, without considering the influence of the flood process in other areas, thus solving the problem of low accuracy and low precision of flood control early warning.

[0032] In an embodiment of the present invention, an embodiment of the flood control early warning method is provided. The steps shown in the flowchart of the drawings may be executed in a computer system such as a set of computer-executable instructions, and although the flowchart shows a logical order, in some cases, the steps shown or described may be executed in an order different from the order here.

[0033] In this embodiment, a flood control early warning method is provided, which can be applied to the above-mentioned processor. FIG. 1 is a flowchart of the flood control early warning method according to an embodiment of the present invention. As shown in FIG. 1, the process includes the following steps.

[0034] Step S101: Obtain the outflow process data corresponding to a plurality of different early warning nodes in the target area and the connection relationship between different early warning nodes. The plurality of different early warning nodes are determined by the drain pipe network information and river water system information of the target area.

[0035] Exemplarily, the target area may be any area that requires early warning for flood control. The drain pipe network information may be drain pipe network planning data. The river water system information may be vector information of the river water system within the target area. Here, the vector information generally refers to an open format (ESRI Shapefile, shp) file of spatial data read in GIS. A plurality of different early warning nodes are determined according to the drain pipe network information, river water system information, and basic information of the ground surface in the target area. The outflow process data corresponding to each of the plurality of different early warning nodes may be determined by the outflow process under the historical rainfall conditions of the corresponding early warning node. In the embodiments of the present application, the target area may be a predetermined urban area. Intersection P1 where the river water system enters and exits the urban boundary, rainwater manhole P2 within the city, intersection P3 between the drain pipe network and ditches or rivers, and confluence point P4 of the main stream and tributaries of the river water system, etc. are determined as early warning nodes. A schematic diagram of the positions and connection relationships of the early warning nodes may be shown in FIG. 2 below.

[0036] Step S102: Based on the connection relationships between different early warning nodes and the outflow process data corresponding to each of the different early warning nodes, calculate the influence contribution values to the lower-level early warning nodes when a flood occurs at each early warning node. The influence contribution value represents the contribution amount to the formation of a flood at the lower-level early warning node when a flood occurs at each early warning node.

[0037] Exemplarily, in the embodiments of the present application, when a flood occurs at one early warning node, it will have a certain impact on the outflow process of the lower-level early warning nodes, which may lead to the occurrence of a flood at the lower-level early warning nodes. Based on the outflow process data of different early warning nodes, the contribution amount to the formation of a flood at the lower-level early warning nodes when a flood occurs at each early warning node can be analyzed.

[0038] Step S103: Determine the key early warning nodes according to the influence contribution values.

[0039] Exemplarily, in the embodiments of the present application, the upper early warning node with the largest contribution to the occurrence of floods at the lower early warning nodes is set as the key early warning node.

[0040] Step S104: Determine the key early warning area according to the key early warning node.

[0041] Exemplarily, in the embodiments of the present application, when a flood occurs at the key early warning node, the corresponding catchment area can be analyzed, and the catchment area can be determined as the key early warning area.

[0042] Step S105: Obtain the water level information within the key early warning area.

[0043] Exemplarily, in the embodiments of the present application, the water level information within the key early warning area is collected by a water level monitoring device pre-installed at a predetermined position within the key area, and the predetermined position may be the position of a place where floods are likely to occur within the key early warning area.

[0044] Step S106: Generate flood early warning information for the target area based on the water level information within the key early warning area and a predetermined water level threshold.

[0045] Exemplarily, compare the water level information within the key early warning area with the predetermined water level threshold. If the water level information within the key early warning area is greater than the predetermined outflow threshold, it can be determined that there may be a flood in the key area, and the corresponding flood early warning information is generated. In the embodiments of the present application, according to the heavy rain flood process recorded in the history ledger and the simulated outflow threshold, the water level threshold for inundation corresponding to the key early warning section feature site is determined. If there is a designed inundation water level value history for the heavy rain at the key section feature site, it is determined as the inundation water depth threshold. If there is no threshold related to the relevant history at the key section feature site, it is obtained by inverse calculation using the outflow threshold of the outlet node of the simulated key section. The specific calculation process is shown in the following formula (1).

[0046] In the formula of JPEG2025077966000002.jpg35170, H is the average value of the water depth of waterlogging in the key early warning area under a predetermined heavy rain condition, and h i represents the elevation value corresponding to grid point i within the key early warning area, and q k、シミュレーション represents the outflow value of the key node under a predetermined heavy rain condition simulated at time k, and q 排水 represents the maximum drainage capacity corresponding to the drainage pipe network of the node, and h represents the water level threshold of waterlogging corresponding to the designed heavy rain condition characteristic site. Specifically, based on each early warning node, the corresponding early warning area is determined, based on each rainfall condition, the corresponding water level threshold is set, and also, the early warning response level of each early warning area is determined. For example, according to the hydraulic relationship between upstream and downstream, from top to bottom, the control catchment area at the boundary point where the river system enters the city is the first-level response early warning unit D1, the control catchment area of the urban rainwater manhole is the second-level unit D2, the control catchment area at the intersection of the drainage pipe network and the river system is the third-level unit D3, and the control catchment area of the main stream and tributaries of the river system is determined as the fourth-level response early warning unit D4. Based on different water level thresholds and the water level information of the key early warning area, respond to the early warning for flood control in the early warning area within the target area. For example, when the water level in the key early warning area exceeds the water level threshold of level 1, an early warning for flood control is issued to the first-level response early warning unit.

[0047] The early warning method for flood control measures according to this embodiment calculates the influence contribution value to the lower-level early warning nodes when a flood occurs at each early warning node based on the connection relationship between different early warning nodes and the outflow process data of each early warning node. Based on the influence contribution value, a key early warning node is determined from a plurality of different early warning nodes, a key early warning area is determined based on the key early warning node, and flood early warning information for the target area is generated based on the water level information within the key early warning area and a predetermined water level threshold value. When performing an early warning for flood control measures, the influence on the lower-level early warning nodes of each early warning node in the flood process is considered, and an early warning for flood control measures is performed on the target area based on the determined key early warning area, effectively improving the accuracy, precision, and timeliness of the early warning for flood control measures. In the related art, when performing an early warning for flood control measures, an early flood warning is performed only based on the simulation result of the flooding situation in the administrative area, without considering the influence of the flood process in other areas, thus solving the problem of low accuracy of the early warning for flood control measures.

[0048] In this embodiment, an early warning method for flood control measures is provided, which can be applied to the above-mentioned processor. FIG. 3 is a flowchart of the early warning method for flood control measures according to an embodiment of the present invention. As shown in FIG. 3, the process includes the following steps.

[0049] Step S301: Obtain the outflow process data corresponding to a plurality of different early warning nodes within the target area and the connection relationship between different early warning nodes. The plurality of different early warning nodes are determined by the drain pipe network information and river water system information of the target area. Specifically, reference may be made to step S101 of the embodiment shown in FIG. 1, and repeated descriptions are omitted here.

[0050] Specifically, the above step S301 includes steps S3011 to S3012.

[0051] Step S3011: Obtain the historical rainfall information of each early warning node.

[0052] Exemplarily, in the embodiments of the present application, the historical rainfall information of each early warning node can be obtained from the relevant data in the meteorological water level monitoring database.

[0053] Step S3012: Input the historical rainfall information of each early warning node into the pre-constructed outflow simulation model in sequence, and the outflow simulation model outputs the outflow process data of the corresponding early warning node.

[0054] Exemplarily, in the embodiments of the present application, the pre-constructed outflow simulation model includes a distributed hydrological model and an urban rainfall-outflow simulation model. By outputting the historical rainfall process, meteorological and surface basic information of the target area to the distributed hydrological model (Soil and Water Assessment Tool, SWAT), the outflow process of the early warning node in the river can be simulated. By outputting the historical rainfall process, meteorological and surface basic information of the target area to the urban rainfall-outflow simulation model (Storm water management model, SWMM), the outflow process of the early warning node such as the drainage pipe network can be simulated.

[0055] Step S302: Based on the connection relationship between different early warning nodes and the outflow process data corresponding to different early warning nodes respectively, calculate the influence contribution value to the lower-level early warning nodes when a flood occurs at each early warning node. The influence contribution value represents the contribution amount to the formation of flood at the lower-level early warning nodes when a flood occurs at each early warning node. For details, refer to Step S102 of the embodiment shown in FIG. 1, and the repeated description is omitted here.

[0056] Specifically, the above Step S302 includes Steps S3021 to S3022.

[0057] Step S3021: Determine at least one early warning node pair based on the connection relationship between different early warning nodes. The early warning node pair is composed of both a first early warning node and a second early warning node that are directly connected.

[0058] Exemplarily, based on the connection relationship between different early warning nodes, two directly connected early warning nodes are taken as one early warning node pair to obtain a plurality of early warning node pairs. One early warning node pair consists of a first early warning node and a second early warning node. In the embodiments of the present application, the second early warning node may be a lower-level early warning node located downstream of the first early warning.

[0059] Step S3022: Calculate the target probability of the corresponding early warning node pair based on the outflow process data of different early warning nodes. The target probability is used to represent the probability that when a flood occurs at the first early warning node in the early warning node pair, a flood occurs at the second early warning node.

[0060] Exemplarily, based on the outflow process data of each early warning node, calculate the probability that when a flood occurs at the first early warning node in each early warning node pair, a flood occurs at the second early warning node.

[0061] In some alternative embodiments, the above step S3022 includes steps a1 to a3.

[0062] Step a1: Determine the marginal distribution function of the outflow process corresponding to the first early warning node and the marginal distribution function of the outflow process corresponding to the second early warning node in each early warning node pair based on the outflow process data of different early warning nodes.

[0063] Exemplarily, based on the outflow process of each early warning node, determine the marginal distribution function of the outflow process corresponding to the first early warning node and the marginal distribution function of the outflow process corresponding to the second early warning node in each early warning node pair. In the embodiments of the present application, the marginal distribution function of the outflow process corresponding to the first early warning node is u1 is represented, and the marginal distribution function of the outflow process corresponding to the second early warning node may be u 2 and may be represented by

[0064] Step a2: Based on the predetermined connection function, the marginal distribution function of the outflow process corresponding to the first early warning node in each early warning node pair, and the marginal distribution function of the outflow process corresponding to the second early warning node, establish the joint distribution function of each early warning node pair.

[0065] Exemplarily, in the embodiments of the present application, the predetermined connection function may be a Copula function. The joint distribution function of each early warning node pair is established using the Copula function, and the basic principle is shown in the following formula (2).

[0066] JPEG2025077966000003.jpg16170Where C n (u 1 , u 2 , …, u n ) is the n-dimensional joint distribution function of random variables, which is used to represent the correlation structure between variables. u 1 , u 2 , …, u n are the marginal distribution functions of variables 1 to n. For the outflow process, generally, a P-III type distribution function or the like is selected. φ is an Archimedean generation operator, which is a continuous monotonic decreasing function, and φ(0) = ∞, φ(1) = 0.

[0067] In the embodiments of the present application, in order to establish the joint distribution function of the marginal distribution function of the outflow process corresponding to the first early warning node and the marginal distribution function of the outflow process corresponding to the second early warning node in each early warning node pair, it can be determined as a two-dimensional joint distribution function. That is, the joint distribution function of each early warning node pair may be represented by the following formulas (3) and (4).

[0068] JPEG2025077966000004.jpg47170Where φ(1) = 0 and φ -1is the inverse function of φ, x is the outflow sequence value, and for the meanings of the remaining variables, refer to the above formula (2), and duplicate explanations are omitted here.

[0069] Step a3: Calculate the target probability of each corresponding early warning node pair based on the simultaneous distribution function of each early warning node pair.

[0070] Exemplarily, in the embodiments of the present application, based on the simultaneous distribution function of each early warning node pair, the flood encounter probability of the response early warning nodes with hydraulic relationships is calculated in order from upstream to downstream, and its basic principle is shown in the following formulas (5) and (6).

[0071] JPEG2025077966000005.jpg47170 In the formula, x and y are the sequence values of the outflows of the key nodes, x f and y f are the characteristic flow values corresponding to the quantiles f of the key nodes, P(*,*) represents the calculated probability, and F X (u x ) represents the cumulative frequency value of P(x < xf) corresponding to the fitting frequency curve, u x and u f are the peripheral distribution functions of the outflows of the upper and lower nodes respectively, and C(*,*) is the simultaneous distribution function.

[0072] Step S3023: Calculate the influence contribution value to the lower early warning nodes when a flood occurs at each early warning node based on the target probability.

[0073] Exemplarily, in the embodiments of the present application, the influence contribution value of the lower nodes in the flood process of the upper response early warning nodes to the lower nodes is calculated inversely from downstream to upstream, and the key upper nodes with a large influence on the formation of floods at the lower nodes are determined in descending order of the contribution values. The calculation process of the contribution value may be shown in the following formula (7).

[0074] JPEG2025077966000006.jpg47141 In the formula, SS i represents the contribution value of the lower early warning nodes of the upper early warning node i to the formation of floods, and qi is the average value of the long sequence of the outflow of the upper node i obtained by simulation, Q is the average value of the long sequence of the outflow of the lower node obtained by simulation, and p i represents the flood encounter probability value of the upper early warning node i and its lower early warning node, and ω 1 and ω 2 respectively represent the contribution weights of the flood volume and encounter probability of the upper early warning node to the lower flood.

[0075] Step S303: Determine the key early warning node according to the contribution value. For details, reference may be made to Step S103 of the embodiment shown in FIG. 1, and duplicate descriptions are omitted here.

[0076] Step S304: Determine the key early warning area according to the key early warning node. For details, reference may be made to Step S104 of the embodiment shown in FIG. 1, and duplicate descriptions are omitted here.

[0077] Step S305: Obtain the water level information within the key early warning area. For details, reference may be made to Step S105 of the embodiment shown in FIG. 1, and duplicate descriptions are omitted here.

[0078] Step S306: Generate flood early warning information for the target area based on the water level information within the key early warning area and a predetermined water level threshold. For details, reference may be made to Step S106 of the embodiment shown in FIG. 1, and duplicate descriptions are omitted here.

[0079] In this embodiment, an early warning method for flood control is provided, which can be applied to the above processor. FIG. 4 is a flowchart of the early warning method for flood control according to an embodiment of the present invention. As shown in FIG. 4, the process includes the following steps.

[0080] Step S401: Obtain the outflow process data corresponding to each of a plurality of different early warning nodes within the target area and the connection relationships between different early warning nodes. The plurality of different early warning nodes are determined by the drain pipe network information and river water system information of the target area. For details, reference may be made to Step S101 of the embodiment shown in FIG. 1, and duplicate descriptions are omitted here.

[0081] Step S402: Based on the connection relationships between different early warning nodes and the outflow process data corresponding to different early warning nodes respectively, calculate the influence contribution values to the lower-level early warning nodes when a flood occurs at each early warning node. The influence contribution value represents the contribution amount to the formation of a flood at the lower-level early warning node when a flood occurs at each early warning node. For details, reference may be made to Step S102 of the embodiment shown in FIG. 1, and duplicate descriptions are omitted here.

[0082] Step S403: Determine the key early warning nodes according to the influence contribution values. For details, reference may be made to Step S103 of the embodiment shown in FIG. 1, and duplicate descriptions are omitted here.

[0083] Step S404: Determine the key early warning areas according to the key early warning nodes. For details, reference may be made to Step S104 of the embodiment shown in FIG. 1, and duplicate descriptions are omitted here.

[0084] Step S405: Obtain the water level information within the key early warning areas. For details, reference may be made to Step S105 of the embodiment shown in FIG. 1, and duplicate descriptions are omitted here.

[0085] Step S406: Generate flood early warning information for the target area based on the water level information within the key early warning areas and a predetermined water level threshold. For details, reference may be made to Step S106 of the embodiment shown in FIG. 1, and duplicate descriptions are omitted here.

[0086] Step S4061: Obtain the numerical elevation data of the target area and the position information of the key early warning nodes.

[0087] Exemplarily, in the embodiments of the present application, basic information of the urban-watershed in the target area is acquired. The basic information of the urban-watershed includes high-precision digital elevation model (DEM) information, meteorological and hydrological monitoring data, basic data of the ground surface, urban drainage pipe network planning data, river system vector data, and historical heavy rain and flood ledger information, etc. According to the drainage pipe network, river system vector information, and geographical location information of the response early warning key nodes, programming processing of the urban-watershed DEM is performed. That is, according to the hydraulic relationship of the drainage pipe network and the river system, from upstream to downstream, with the response early warning key node as the boundary, the DEM elevation reduction processing is performed in sequence to ensure that the DEM values of the downstream pipe network and river channel are smaller than those on the upstream side, and the elevation data of the target area is obtained.

[0088] Step S4062: Based on the elevation data of the target area and the position information of the key early warning nodes, determine the corresponding catchment area when a flood occurs at the key early warning nodes.

[0089] Exemplarily, in the embodiments of the present application, based on the programmed DEM data and in combination with the position information of the response early warning key nodes, a hydrological analysis tool is used to generate the catchment area range of the key early warning nodes.

[0090] Step S4063: Determine the key early warning area based on the corresponding catchment area when a flood occurs at the key early warning nodes. In the embodiments of the present application, the catchment area corresponding to the key early warning nodes is used as the key early warning area.

[0091] Step S407: Based on the position information of each early warning node, determine the corresponding early warning area.

[0092] Exemplarily, in the embodiments of the present application, based on the DEM data after programming, in combination with the location information of the response early warning key nodes, the ARCGIS hydrological analysis tool is used to generate the catchment area range of each response early warning node. According to the upstream and downstream hydraulic relationships, from top to bottom, the control catchment area of the boundary point where the river system enters the city is the first-level response early warning unit D1, the control catchment area of the urban stormwater manholes is the second-level unit D2, the control catchment area of the intersection of the drainage pipe network and the river system is the third-level unit D3, and the control catchment areas of the main stream and tributaries of the river system are determined as the fourth-level response early warning unit D4. The distribution pattern diagram of the inundation area corresponding to each early warning node is shown in FIG. 5.

[0093] Step S408: Obtain the outflow process corresponding to each early warning node in the target rainfall process and the predetermined outflow threshold of each early warning node.

[0094] Exemplarily, in the embodiments of the present application, the calculation process of the predetermined outflow threshold is to screen the rainfall processes corresponding to various levels of inland water flooding caused by heavy rains recorded in the urban history ledger, input the pre-designed heavy rain process into the established distributed hydrological model and the urban rainfall-runoff simulation model, simulate to obtain the outflow thresholds of each level of early warning nodes corresponding to the designed rainfall, and the calculation principle of the outflow thresholds of the response early warning nodes at the same level is shown in the following formula (8).

[0095] JPEG2025077966000007.jpg92170In the formula, q 1i ~q 4i represents the outflow thresholds corresponding to the response early warning nodes i at the designed heavy rain condition levels 1 to 4, and Q 1i ~Q 4i represents the simulated outflow values corresponding to the response early warning nodes i at the designed heavy rain condition levels 1 to 4 obtained by simulation.

[0096] In some alternative embodiments, the above step S308 includes steps b1 to b2.

[0097] Step b1: Obtain target rainfall information. Exemplarily, the target rainfall process is any one of the rainfall processes within the target area. In the embodiments of the present application, the rainfall process may be a rainfall process forecast by a weather forecasting system.

[0098] Step b2: Input the target rainfall information into a pre-constructed outflow simulation model, and the outflow simulation model outputs outflow process data corresponding to each early warning node in the target rainfall process. Exemplarily, input the target rainfall process into the outflow simulation model, and the outflow simulation model outputs the outflow process of each early warning node.

[0099] Step S409: Generate early warning information for the early warning areas corresponding to different early warning nodes based on the outflow process corresponding to each early warning node in the target rainfall process and the predetermined outflow threshold of the corresponding early warning node.

[0100] Exemplarily, in the embodiments of the present application, compare the outflow process corresponding to each early warning node in the target rainfall process with the corresponding predetermined outflow threshold, determine whether there is a flood risk for the corresponding node based on the comparison result, and if there is a flood risk, generate early warning information for the early warning area corresponding to the early warning node.

[0101] In this embodiment, an early warning device for flood control is further provided. The device is used to implement the above embodiments and preferred embodiments, and for the parts that have been described, duplicate descriptions are omitted. As used below, the term "module" can implement a combination of software and / or hardware with a predetermined function. The device described in the following embodiments is preferably implemented in software, but implementation in hardware or a combination of software and hardware is also possible and contemplated.

[0102] This embodiment provides an early warning device for flood control. As shown in FIG. 6, It is used to obtain the outflow process data corresponding to a plurality of different early warning nodes in the target area and the connection relationship between different early warning nodes. The plurality of different early warning nodes are determined by the drain pipe network information and river water system information of the target area. The first acquisition module 601, Based on the connection relationship between different early warning nodes and the outflow process data corresponding to different early warning nodes respectively, it is used to calculate the influence contribution value to the lower-level early warning nodes when a flood occurs at each early warning node. The influence contribution value represents the contribution amount to the formation of flood at the lower-level early warning nodes when a flood occurs at each early warning node. The calculation module 602, The first determination module 603 used to determine the key early warning node according to the influence contribution value, The second determination module 604 used to determine the key early warning area according to the key early warning node, The second acquisition module 605 used to obtain the water level information within the key early warning area, The first processing module 606 used to generate the flood early warning information of the target area based on the water level information within the key early warning area and a predetermined water level threshold value, and includes.

[0103] In some alternative embodiments, the calculation module 602 is used to determine at least one early warning node pair based on the connection relationship between different early warning nodes. The early warning node pair is composed of both the first early warning node and the second early warning node that are directly connected. The first determination sub-module, and based on the outflow process data of different early warning nodes, it is used to calculate the target probability of the corresponding early warning node pair. The target probability represents the probability that a flood occurs at the second early warning node when a flood occurs at the first early warning node in the early warning node pair. The first calculation sub-module, and it is used to calculate the influence contribution value to the lower-level early warning nodes when a flood occurs at each early warning node based on the target probability. The second calculation sub-module, and includes.

[0104] In some selectable embodiments, the first acquisition module 601 includes a first acquisition sub-module used to acquire historical rainfall information of each early warning node, and a processing sub-module used to sequentially input the historical rainfall information of each early warning node into a pre-constructed outflow simulation model, and output the outflow process data of the corresponding early warning node by the outflow simulation model.

[0105] In some selectable embodiments, the device further includes a third acquisition module used to acquire the water level process of a key early warning area, a comparison module used to compare the water level process with a predetermined water level threshold to obtain a comparison result, and a second processing module used to generate warning information for the target area based on the comparison result.

[0106] In some selectable embodiments, the second acquisition module 605 includes a second acquisition sub-module used to acquire the water level process of a key early warning area, a comparison sub-module used to compare the water level process with a predetermined water level threshold to obtain a comparison result, and a second processing module used to generate warning information for the target area based on the comparison result.

[0107] In some selectable embodiments, the first calculation sub-module includes a determination unit used to determine the marginal distribution function of the outflow process corresponding to the first early warning node and the marginal distribution function of the outflow process corresponding to the second early warning node in each pair of early warning nodes based on the outflow process data of different early warning nodes. An establishment unit used to establish the joint distribution function of each early warning node pair based on a specified connection function and the marginal distribution functions of the outflow processes corresponding to the first early warning node in each early warning node pair and the marginal distribution functions of the outflow processes corresponding to the second early warning node, and a calculation unit used to calculate the target probability of the corresponding early warning node pair based on the joint distribution function of each early warning node pair.

[0108] In some alternative embodiments, the second determination module 604 includes a second acquisition sub-module used to acquire the digital elevation data of the target area and the location information of the key early warning nodes, a second determination sub-module used to determine the corresponding catchment area when a flood occurs at the key early warning node based on the digital elevation data of the target area and the location information of the key early warning nodes, and a third determination sub-module used to determine the key early warning area based on the corresponding catchment area when a flood occurs at the key early warning node.

[0109] For further functional descriptions of the above modules and units, they are the same as the corresponding embodiments above, and duplicate descriptions are omitted here.

[0110] The flood prevention early warning device in this embodiment is presented in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0111] An embodiment of the present invention further provides a computer device having the flood prevention early warning device shown in FIG. 6 above.

[0112] As shown in reference to FIG. 7, FIG. 7 is a structural schematic diagram of a computer device according to an alternative embodiment of the present invention. As shown in FIG. 7, the computer device includes one or more processors 10, a memory 20, and an interface including a high-speed interface and a low-speed interface for connecting each component. Each component is communicably connected to each other via different buses and may be attached to a common motherboard or attached in other ways as needed. The processor can process instructions executed within the computer device and includes instructions stored in or on the memory for displaying graphic information of the GUI on an external input / output device (for example, a display device coupled to the interface). In some alternative embodiments, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories as needed. Similarly, multiple computer devices may be connected, and each device may provide some of the necessary operations (for example, as a server array, a set of blade servers, or a multiprocessor system). In FIG. 7, one processor 10 is taken as an example.

[0113] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable logic gate array, a general-purpose array logic, or any combination thereof.

[0114] The memory 20 stores instructions executable by at least one processor 10, causing the at least one processor 10 to execute and implement the method shown in the above embodiment.

[0115] The memory 20 may include a program storage area for storing an operating system and application programs necessary for at least one function, and a data storage area for storing data created according to the use of the computer device. The memory 20 may also include a high-speed random access memory, and may further include a non-temporary memory such as at least one disk storage device, a flash memory device, or other non-temporary solid-state storage devices. In some selectable embodiments, the memory 20 includes a memory that is selectively installed remotely from the processor 10, and these remote memories can be connected to the computer device via a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0116] The memory 20 may include a volatile memory such as a random access memory, the memory may include a non-volatile memory such as a flash memory, hardware, or a solid-state drive, and the memory 20 may include a combination of the above types of memories.

[0117] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0118] Embodiments of the present invention further provide a computer-readable storage medium. The method according to the embodiments of the present invention may be implemented in hardware or firmware, or may be implemented in a recordable manner on a storage medium, or may be implemented as computer code downloaded via a network and originally stored in a remote storage medium or a non-transitory machine-readable storage medium but stored in a local storage medium, whereby the method described herein may be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium may be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, hardware, or a solid-state drive, etc., and further, the storage medium may further include a combination of the above types of memories. Understandably, a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component capable of storing or receiving software or computer code, and when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the method shown in the above embodiments is realized.

[0119] The embodiments of the present invention have been described with reference to the drawings. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications fall within the scope defined by the appended claims.

Claims

1. An early warning method for flood control, comprising: obtaining runoff process data corresponding to a plurality of different early warning nodes in a target area and connection relationships between the different early warning nodes, the plurality of different early warning nodes being determined according to drainage network information and river water system information of the target area, the target area being an urban area, the plurality of different early warning nodes including intersections where river water systems enter and leave urban boundaries, storm water wells in the city, intersections between drainage network and ditches or rivers, and junctions between the main stream and tributaries of the river water system; Calculating an influence contribution value to a lower early warning node when a flood occurs in each early warning node according to the connection relationship between the different early warning nodes and the runoff process data corresponding to each different early warning node, the influence contribution value representing a contribution amount to flood formation in the lower early warning node when a flood occurs in each early warning node; determining a key early warning node according to the influence contribution value; determining a key early warning area according to the key early warning node; obtaining water level information within a key early warning area; generating flood early warning information for a target area according to the water level information in the key early warning area and a predetermined water level threshold; generating flood early warning information for a target area based on the water level information in the key early warning area and a predetermined water level threshold, Obtaining early warning zone information corresponding to each early warning node, early warning response levels of the early warning zones corresponding to each early warning node, and predetermined water level thresholds corresponding to each early warning response level; comparing the water level information within the key early warning zone with predetermined water level thresholds respectively corresponding to different early warning response levels to determine a target early warning response level; determining at least one target early warning area from the early warning areas respectively corresponding to different early warning nodes according to the target early warning response level and the early warning response levels of the early warning areas corresponding to each early warning node; generating flood early warning information for the target area based on the target early warning area.

2. calculating an influence contribution value of each early warning node to a lower early warning node when a flood occurs in each early warning node according to the connection relationship between the different early warning nodes and the runoff process data corresponding to each different early warning node; determining at least one early warning node pair based on a connection relationship between the different early warning nodes, the early warning node pair being composed of both a first early warning node and a second early warning node that are directly connected; Calculating a target probability of a corresponding pair of early warning nodes according to the spill process data of different early warning nodes, the target probability being used to represent the probability that the second early warning node in the pair of early warning nodes will be flooded when the first early warning node in the pair is flooded; The method according to claim 1, further comprising: calculating an influence contribution value to a lower-level early warning node when a flood occurs in each early warning node based on the target probability.

3. The step of obtaining runoff process data respectively corresponding to a plurality of different early warning nodes in the target area includes: obtaining historical rainfall information of each early warning node; The method according to claim 1, further comprising: inputting the historical rainfall information of each early warning node into a pre-constructed runoff simulation model in sequence, and the runoff simulation model outputs the runoff process data of the corresponding early warning node.

4. determining a corresponding early warning area according to the location information of each early warning node; Obtaining runoff processes corresponding to each early warning node in the target precipitation process and a predetermined runoff threshold value of each early warning node; The method according to claim 1, further comprising: generating early warning information of early warning areas respectively corresponding to different early warning nodes according to the runoff process corresponding to each early warning node in the target precipitation process and the predetermined runoff threshold of the corresponding early warning node.

5. The step of obtaining runoff processes corresponding to each early warning node in the target precipitation process includes: obtaining target rainfall information; The method according to claim 4, further comprising: inputting the target precipitation information into a pre-constructed runoff simulation model, and the runoff simulation model outputs runoff process data corresponding to each early warning node in the target precipitation process.

6. The step of calculating the target probability of the corresponding early warning node pair according to the outflow process data of different early warning nodes includes: According to the outflow process data of different early warning nodes, determining a marginal distribution function of the outflow process corresponding to the first early warning node and a marginal distribution function of the outflow process corresponding to the second early warning node in each early warning node pair; Establishing a joint distribution function of each early warning node pair according to a predetermined connection function and a marginal distribution function of an outflow process corresponding to the first early warning node and a marginal distribution function of an outflow process corresponding to the second early warning node in each early warning node pair; and calculating a target probability of each early warning node pair based on the joint distribution function of the corresponding early warning node pair.

7. The step of determining a key early warning area based on the key early warning node includes: Obtaining digital elevation data of a target area and location information of key early warning nodes; According to the digital elevation data of the target area and the location information of the key early warning node, determine the corresponding catchment area when the key early warning node occurs flood; and determining a key early warning region based on the corresponding catchment area when the key early warning node occurs flood.

8. An early warning device for flood control, comprising: A first acquisition module is used for acquiring runoff process data corresponding to a plurality of different early warning nodes in a target area and connection relationships between the different early warning nodes, the plurality of different early warning nodes are determined according to drainage network information and river system information of the target area, the target area is an urban area, the plurality of different early warning nodes include intersections where river systems enter and leave urban boundaries, storm water wells in cities, intersections between drainage networks and channels or rivers, and junctions between mainstreams and tributaries of river systems; a calculation module for calculating an influence contribution value of a lower early warning node when a flood occurs in each early warning node according to the connection relationship between the different early warning nodes and the runoff process data corresponding to each different early warning node, the influence contribution value representing the contribution amount of the lower early warning node to the flood formation when a flood occurs in each early warning node; A first determination module, which is used for determining a key early warning node according to the influence contribution value; A second determination module is used for determining a key early warning area according to the key early warning node; A second acquisition module is used for acquiring water level information in a key early warning area; a first processing module for generating flood early warning information for a target area according to the water level information in the key early warning area and a predetermined water level threshold; generating flood early warning information for a target area based on the water level information in the key early warning area and a predetermined water level threshold, Obtaining early warning zone information corresponding to each early warning node, early warning response levels of the early warning zones corresponding to each early warning node, and predetermined water level thresholds corresponding to each early warning response level; comparing the water level information within the key early warning zone with predetermined water level thresholds respectively corresponding to different early warning response levels to determine a target early warning response level; determining at least one target early warning area from the early warning areas respectively corresponding to different early warning nodes according to the target early warning response level and the early warning response levels of the early warning areas corresponding to each early warning node; and generating flood early warning information for the target area based on the target early warning area.

9. The computing module includes: A first determination submodule is used for determining at least one early warning node pair according to the connection relationship between the different early warning nodes, the early warning node pair being composed of both a first early warning node and a second early warning node that are directly connected; A first calculation submodule, which is used to calculate a target probability of a corresponding pair of early warning nodes according to the spill process data of different early warning nodes, and the target probability is used to represent the probability that the second early warning node in the pair of early warning nodes will be flooded when the first early warning node in the pair is flooded; The apparatus of claim 8, further comprising: a second calculation sub-module, which is used for calculating an influence contribution value of each early warning node to a lower-level early warning node when a flood occurs in the each early warning node based on the target probability.

10. The first acquisition module is A first acquisition sub-module, which is used for acquiring historical rainfall information of each early warning node; and a processing sub-module, which is used to input the historical rainfall information of each early warning node into a pre-constructed runoff simulation model in sequence, and output the runoff process data of the corresponding early warning node using the runoff simulation model.

11. A third determination module is used for determining a corresponding early warning area according to the location information of each early warning node; A second acquisition module is used for acquiring runoff processes corresponding to each early warning node in the target rainfall process and the predetermined runoff threshold of each early warning node; The device as described in claim 8, further comprising: a processing module used for generating early warning information of early warning areas respectively corresponding to different early warning nodes according to the runoff process corresponding to each early warning node in the target precipitation process and the predetermined runoff threshold of the corresponding early warning node.

12. The second acquisition module is A second acquisition sub-module, which is used for acquiring target precipitation information; The device as described in claim 11, further comprising: a processing sub-module, which is used to input the target precipitation information into a pre-constructed runoff simulation model, and output runoff process data corresponding to each early warning node in the target precipitation process by the runoff simulation model.

13. The first calculation sub-module: A determination unit is used for determining a marginal distribution function of an outflow process corresponding to the first early warning node and a marginal distribution function of an outflow process corresponding to the second early warning node in each early warning node pair according to the outflow process data of different early warning nodes; an establishment unit, which is used for establishing a joint distribution function of each early warning node pair according to a predetermined connection function and a marginal distribution function of an outflow process corresponding to the first early warning node in each early warning node pair and a marginal distribution function of an outflow process corresponding to the second early warning node; The apparatus of claim 9 , further comprising: a calculation unit adapted to calculate a target probability of a corresponding early warning node pair based on the joint distribution function of each early warning node pair.

14. 1. A computer device comprising: A computer device comprising a memory and a processor, the memory and the processor being communicatively connected to each other, computer instructions stored in the memory, and the processor executing the computer instructions to perform the early warning method for flood control described in any one of claims 1 to 7.

15. A computer-readable storage medium having stored thereon computer instructions for causing a computer to execute the flood control early warning method according to any one of claims 1 to 7.

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