Flood prevention early warning method, device, computer device, and storage medium

Abstract

The present invention provides an early warning method, device, computer equipment and storage medium for flood control that, when issuing an early warning for flood control, takes into account the impact of each early warning node on lower-level early warning nodes during the flood process, and effectively improves the accuracy, precision and timeliness of the early warning for flood control. [Solution] The method obtains runoff process data corresponding to each of a plurality of different early warning nodes in a target area and the connection relationships between the different early warning nodes, calculates the influence contribution value on lower-level early warning nodes when a flood occurs at each early warning node based on the connection relationships between the different early warning nodes and the runoff process data of each early warning node, determines a key early warning node from the 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, and generates flood early warning information for the target area based on the water level information in the key early warning area and a predetermined water level threshold.

Description

[Technical field]

[0001] The present invention relates to the technical field of flood early warning, and in particular to a method, device, computer device and storage medium for flood early warning. [Background technology]

[0002] Due to the effects of climate change and rapid urbanization, inland flooding in cities due to heavy rains and floods is becoming more frequent and the damage caused by it is becoming more serious. Accurate early warning of urban floods due to heavy rains is an effective way to reduce the losses caused by floods.

[0003] In the related art, generally, a city is divided into administrative districts, and rainfall forecast data for the city is input into a precipitation-runoff-confluence model to perform a simulation, and the flooding conditions of different administrative districts are obtained, and whether or not to issue a flood early warning for the administrative district is determined based on the flooding conditions of each administrative district and the flooding threshold of the administrative district. However, since there are drainage pipe networks and river water systems in the city, the flood process of one administrative district is affected by other administrative districts, and if an early flood warning is issued based only on the simulation results of the flooding conditions of an administrative district without considering the influence of the flooding process of other districts, the accuracy and precision of the early warning for flood control is low. Summary of the Invention [Problem to be solved by the invention]

[0004] In view of the above circumstances, the present invention provides an early warning method, apparatus, computer device and storage medium for flood control, to solve the problem of low accuracy and low precision of early warning provided by conventional flood control early warning schemes. [Means for solving the problem]

[0005] In a first aspect, the present invention provides an early warning method for flood control, including the steps of: 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, where the plurality of different early warning nodes are determined by drainage network information and river system information of the target area; calculating an influence contribution value on a lower early warning node when a flood occurs in each early warning node based on the connection relationships between the different early warning nodes and the runoff process data corresponding to the different early warning nodes, where the influence contribution value represents the contribution amount to flood formation at 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; acquiring water level information in the key early warning area; and generating flood early warning information for the target area based on the water level information in 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 on 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 runoff process data of each early warning node, determines a key early warning node from multiple 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 a target area based on the water level information in the key early warning area and a predetermined water level threshold, and when performing early warning for flood control, takes into account the influence of each early warning node on lower-level early warning nodes in the flood process, and performs early warning for flood control for the target area based on the determined key early warning area, thereby effectively improving the accuracy, precision and timeliness of early warning for flood control. This solves the problem that in the related art, when performing early warning for flood control, flood early warning is performed based only on the simulation result of the flood situation of an administrative area, and the influence of the flood process of other areas is not taken into account, resulting in low accuracy and precision of early warning for flood control.

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

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

[0009] In one optional embodiment, the step of acquiring runoff process data respectively corresponding to a plurality of different early warning nodes in the target area includes the steps of acquiring historical rainfall information of each early warning node, inputting the historical rainfall information of each early warning node into a pre-constructed runoff simulation model in sequence, and outputting the runoff process data of the corresponding early warning node from the runoff simulation model.

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

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

[0012] The method of this optional embodiment generates early warning information of early warning areas respectively corresponding to different early warning nodes based on the runoff process corresponding to each early warning node in the target rainfall process and the predetermined runoff threshold of the corresponding early warning node, thereby accurately realizing flood forecasting by early warning area.

[0013] In one optional embodiment, the step of obtaining runoff processes corresponding to each early warning node in the target rainfall process includes the steps of obtaining target rainfall information, inputting the target rainfall information into a pre-constructed runoff simulation model, and the runoff simulation model outputting runoff process data corresponding to each early warning node in the target rainfall process.

[0014] The method according to this optional embodiment can use a pre-constructed runoff simulation model to accurately simulate the runoff process in key early warning areas under target rainfall conditions, facilitating subsequent flood early warning.

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

[0016] The method according to this optional embodiment establishes a joint distribution function of each early warning node pair based on a predetermined connection function and a marginal distribution function of an outflow process corresponding to a first early warning node and a marginal distribution function of an outflow process corresponding to a second early warning node in each early warning node pair, and calculates a 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 optional embodiment, the step of determining a key early warning area based on a key early warning node includes the steps of obtaining digital elevation data of a target area and location information of a key early warning node, determining a 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 a 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 optional embodiment can accurately determine the corresponding catchment area when 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 provides an early warning device for flood control, including: a first acquisition module, which is used for acquiring runoff process data corresponding to a plurality of different early warning nodes in a target area and the connection relationships between the different early warning nodes, where the plurality of different early warning nodes are determined by drainage network information and river system information of the target area; a calculation module, which is used for calculating an influence contribution value of a lower early warning node when a flood occurs in each early warning node based on the connection relationships between the different early warning nodes and the runoff process data corresponding to the different early warning nodes, where the influence contribution value represents the contribution amount to flood formation at the lower early warning node 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, which is used for determining a key early warning area according to the key early warning node; a second acquisition module, which is used for acquiring water level information in the key early warning area; and a first processing module, which is used for generating flood early warning information for the target area based on the water level information in the key early warning area and a predetermined water level threshold.

[0020] In one optional embodiment, the calculation module includes: a first determination sub-module, which is used for determining at least one early warning node pair based on the connection relationship between different early warning nodes, where 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, which is used for calculating a target probability of a corresponding early warning node pair based on the runoff process data of different early warning nodes, where the target probability is used to represent the probability that a flood will occur in the second early warning node when a flood occurs in the first early warning node in the early warning node pair; and a second calculation sub-module, which is used for calculating an influence contribution value on a lower-level early warning node when a flood occurs in each early warning node based on the target probability.

[0021] In one optional embodiment, the first acquisition module includes 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 for sequentially inputting the historical rainfall information of each early warning node into a pre-constructed runoff simulation model, and outputting runoff process data of the corresponding early warning node by the runoff simulation model.

[0022] In one optional embodiment, the device further includes a third determination module used for determining corresponding early warning areas based on location information of each early warning node; a second acquisition module used for acquiring runoff processes corresponding to each early warning node in the target rainfall process and predetermined runoff thresholds of each early warning node; and a processing module used for generating early warning information of early warning areas respectively corresponding to different early warning nodes based on the runoff processes corresponding to each early warning node in the target rainfall process and the predetermined runoff thresholds of the corresponding early warning nodes.

[0023] In one optional embodiment, the second acquisition module includes a second acquisition sub-module used for acquiring target precipitation information, and a processing sub-module used for inputting the target precipitation information into a pre-constructed runoff simulation model, and for the runoff simulation model to output runoff process data corresponding to each early warning node in the target precipitation process.

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

[0025] In a third aspect, the present invention provides a computer device comprising a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the early warning method for flood control in the first aspect or any one of its corresponding embodiments.

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

[0027] In order to more clearly describe the specific embodiments of the present invention or the technical solutions of the prior art, the drawings that need to be used to describe the specific embodiments or the prior art will be briefly described below. It will be apparent that 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] 2 is a flowchart of an early warning method for flood control according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a schematic diagram of the location and connection relationship of early warning nodes in an embodiment of the present invention; [Diagram 3] 4 is a flowchart of another early warning method for flood control according to an embodiment of the present invention. [Figure 4] 4 is a flowchart of yet another early warning method for flood control according to an embodiment of the present invention. [Diagram 5] FIG. 2 is a distribution schematic diagram of early warning partitions corresponding to each early warning node in an embodiment of the present invention; [Figure 6] 1 is a structural frame diagram of an early warning device for flood control according to an embodiment of the present invention; [Figure 7] FIG. 2 is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0029] In order to make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be described clearly and completely below with reference to the drawings of the embodiments of the present invention, it is obvious that the described embodiments are only some of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, other embodiments that a person skilled in the art can obtain without creative labor all belong to the protection scope of the present invention.

[0030] In the related art, generally, a city is divided into administrative districts, and rainfall forecast data for the city is input into a precipitation-runoff-confluence model to perform a simulation, and the flooding conditions of different administrative districts are obtained, and whether or not to issue a flood early warning for the administrative district is determined based on the flooding conditions of each administrative district and the flooding threshold of the administrative district. However, since there are drainage pipe networks and river water systems in the city, the flood process of one administrative district is affected by other administrative districts, and if an early flood warning is issued based only on the simulation results of the flooding conditions of an administrative district without considering the influence of the flooding process of other districts, the accuracy and precision of the early warning for flood control is low.

[0031] In view of the above, an embodiment of the present invention provides an early warning method for flood control, which is applicable to processor implementation for realizing early warning for flood control in a target area. When performing early warning for flood control, the method of the present invention considers the influence of each early warning node on its lower-level early warning node in the flood process, and effectively improves the accuracy, precision and timeliness of early warning for flood control, thereby solving the problem that in the related art, early warning for flood control is performed based only on the simulation result of the flood situation of an administrative area, and does not consider the influence of the flood process of other areas, resulting in low accuracy and low precision of early warning for flood control.

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

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

[0034] Step S101: Obtain 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, and the plurality of different early warning nodes are determined according to drainage network information and river system information of the target area.

[0035] For example, the target area may be any area that requires early warning for flood control, the drainage network information may be drainage network plan data, and the river water system information may be vector information of the river water system in the target area, where the vector information generally refers to an open format (ESRI Shapefile, shp) file of spatial data read in GIS, and the multiple different early warning nodes are determined according to the drainage network information, river water system information, and basic information of the ground surface of the target area. The runoff process data corresponding to the multiple different early warning nodes may be determined by the runoff process under the historical rainfall conditions of the corresponding early warning node. In an embodiment of the present application, the target area may be a certain urban area, and the intersection P1 where the river water system enters and leaves the boundary of the city, the storm water well P2 in the city, the intersection P3 between the drainage network and the culvert or river, and the junction P4 of the main stream and the tributary of the river water system are determined as early warning nodes, and the schematic diagram of the location and connection relationship of the early warning nodes may be shown in the following FIG. 2.

[0036] Step S102: Based on the connection relationships between different early warning nodes and the runoff process data respectively corresponding to different early warning nodes, calculate the impact contribution values ​​on the lower-level early warning nodes when a flood occurs in each early warning node, and the impact contribution values ​​represent the contribution amounts to flood formation in the lower-level early warning nodes when a flood occurs in each early warning node.

[0037] For example, in an embodiment of the present application, when a flood occurs in one early warning node, it may have a certain impact on the outflow process of its lower-level early warning node, leading to the occurrence of flood in the lower-level early warning node. Based on the outflow process data of different early warning nodes, the contribution amount to flood formation in the lower-level early warning node when a flood occurs in each early warning node can be analyzed.

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

[0039] For example, in the embodiment of the present application, the upper early warning node that has the largest influence contribution amount on flood occurrence among the lower early warning nodes is set as the key early warning node.

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

[0041] Illustratively, in an embodiment of the present application, the corresponding catchment area when a flood occurs in a key early warning node can be analyzed, and the catchment area can be determined as a key early warning region.

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

[0043] Illustratively, in an embodiment of the present application, water level information within the key early warning area is collected by a water level monitoring device pre-installed at a predetermined location within the key area, and the predetermined location may be a location of a flood-prone area within the key early warning area.

[0044] Step S106: Generate flood early warning information for the target area according to the water level information in the key early warning area and the predetermined water level threshold.

[0045] For example, the water level information in the key early warning area is compared with a predetermined water level threshold. If the water level information in the key early warning area is greater than the predetermined runoff threshold, it can be determined that there is a possibility of flooding occurring in the key area, and corresponding flood early warning information is generated. In an embodiment of the present application, a flood water level threshold corresponding to the key early warning area characteristic site is determined according to the heavy rain flood process recorded in the history ledger and the simulated runoff threshold. If the key area characteristic site has a flood water level value history corresponding to heavy rain, it is determined as the flood depth threshold. If the key area characteristic site does not have a threshold for related history, it is obtained by back calculation with the runoff threshold of the exit node of the simulated key area. The specific calculation process is shown in the following formula (1).

[0046] JPEG0007625123000002.jpg35170In the formula, H is the average flood depth of the key early warning area under the specified heavy rain conditions, and h i represents the elevation value corresponding to grid point i in the key early warning area, and q k、シミュレーション represents the runoff value of the key node under the given simulated heavy rainfall conditions at time k, and q 排水 represents the maximum drainage capacity corresponding to the drainage network of the node, and h represents the flood water level threshold corresponding to the designed heavy rain condition characteristic site. Specifically, based on each early warning node, determine the corresponding early warning area, set the corresponding water level threshold according to each rainfall condition, and determine the early warning response level of each early warning area, for example, according to the upstream and downstream hydraulic relationship, determine from top to bottom the control catchment area of ​​the boundary point where the river system enters the city as the first level response early warning unit D1, the control catchment area of ​​the city's storm water well as the second level unit D2, the control catchment area of ​​the intersection between the drainage network and the river system as the third level unit D3, and the control catchment areas of the main and tributaries of the river system as the fourth level response early warning unit D4, and respond to the early warning for flood control of the early warning area in the target area according to the different water level thresholds and the water level information of the key early warning area, for example, when the water level of the key early warning area exceeds the water level threshold of level 1, issue an early warning for flood control to the first level response early warning unit.

[0047] The early warning method for flood control in this embodiment calculates the influence contribution value of each early warning node on lower-level early warning nodes when a flood occurs based on the connection relationship between different early warning nodes and the runoff process data of each early warning node, determines a key early warning node from multiple different early warning nodes based on the influence contribution value, determines a key early warning area based on the key early warning node, and generates 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. When performing early warning for flood control, the influence of each early warning node on lower-level early warning nodes in the flood process is taken into consideration, and early warning for flood control is performed for the target area based on the determined key early warning area, thereby effectively improving the accuracy, precision and timeliness of early warning for flood control. This solves the problem that in the related art, when early warning for flood control, flood early warning is performed based only on the simulation results of the flood situation in an administrative area, and the influence of the flood process in other areas is not taken into consideration, resulting in low accuracy of early warning for flood control.

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

[0049] Step S301: Obtain runoff process data corresponding to a plurality of different early warning nodes in a target area and the connection relationships between the different early warning nodes, and the plurality of different early warning nodes are determined according to the drainage pipe network information and river water system information of the target area. For details, refer to step S101 in the embodiment shown in Figure 1, and repeated description will be 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] Illustratively, in the embodiment of the present application, the historical rainfall information of each early warning node can be obtained through the associated data in the weather water level monitoring database.

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

[0054] For example, in an embodiment of the present application, the pre-constructed runoff simulation model includes a distributed hydrological model and an urban rainfall-runoff simulation model, and the historical rainfall process, weather, and basic information of the ground surface of the target area can be output to a distributed hydrological model (Soil and Water Assessment Tool, SWAT) to simulate the runoff process of an early warning node in a river, and the historical rainfall process, weather, and basic information of the ground surface of the target area can be output to an urban rainfall-runoff simulation model (Storm water management model, SWMM) to simulate the runoff process of an early warning node such as a drainage pipe network.

[0055] Step S302: According to the connection relationship between different early warning nodes and the runoff process data corresponding to different early warning nodes, calculate the influence contribution value of each early warning node to the lower early warning node when flood occurs, and the influence contribution value represents the contribution amount to flood formation in the lower early warning node when flood occurs in each early warning node. For details, please refer to step S102 in the embodiment shown in Figure 1, and repeated description will be omitted here.

[0056] Specifically, the above step S302 includes steps S3021 to S3022.

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

[0058] Illustratively, based on the connection relationship between different early warning nodes, two directly connected early warning nodes are regarded as an early warning node pair to obtain multiple early warning node pairs, where one early warning node pair consists of a first early warning node and a second early warning node, and in the embodiment of the present application, the second early warning node may be a lower-level early warning node located downstream of the first early warning node.

[0059] Step S3022: Based on the runoff process data of different early warning nodes, calculate a target probability of a corresponding early warning node pair, where the target probability is used to represent the probability that a flood occurs in the second early warning node when a flood occurs in the first early warning node in the early warning node pair.

[0060] For example, the probability that a flood occurs in the second early warning node in each pair of early warning nodes when a flood occurs in the first early warning node is calculated based on the runoff process data of each early warning node.

[0061] In some optional embodiments, step S3022 includes steps a1 to a3.

[0062] Step a1: based on the outflow process data of different early warning nodes, 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.

[0063] Illustratively, based on the outflow process of each early warning node, 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 are determined, and in an embodiment of the present application, the marginal distribution function of the outflow process corresponding to the first early warning node may be represented by u1, and the marginal distribution function of the outflow process corresponding to the second early warning node may be represented by u2.

[0064] Step a2: Establish a joint distribution function of each early warning node pair based on the predetermined connection function and 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 in each early warning node pair.

[0065] Illustratively, in the embodiment of the present application, the predetermined connection function may be a Copula function, and the Copula function is used to establish the joint distribution function of each early warning node pair, and the basic principle is shown in the following equation (2):

[0066] JPEG0007625123000003.jpg16170In formula, C n (u1,u2,…,u n ) is an n-dimensional joint distribution function of random variables, and is used to represent the association structure between variables, u1,u2,…,u n is the marginal distribution function of variables 1 to n. For the outflow process, we generally select the P-III type distribution function, etc., and φ is the Archimedean generation operator, which is a continuous monotonically decreasing function, φ(0)=∞, φ(1)=0.

[0067] In the embodiment 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 in each early warning node pair and the marginal distribution function of the outflow process corresponding to the second early warning node, it can be determined as a two-dimensional joint distribution function, that is, the joint distribution function of each early warning node pair can be expressed by the following equations (3) and (4).

[0068] JPEG0007625123000004.jpg47170In the formula, φ(1)=0, and φ-1 is 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 joint distribution function of each early warning node pair.

[0070] Exemplarily, in the embodiments of the present application, based on the joint distribution function of each early warning node pair, the flood encounter probabilities of the response early warning nodes having a hydraulic relationship are calculated in sequence from upstream to downstream, and the basic principle is shown in the following formulas (5) and (6).

[0071] JPEG0007625123000005.jpg47170 where 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 fitted frequency curve, and u x and u f are the marginal distribution functions of the outflows of the upper and lower nodes respectively, and C(*,*) is the joint distribution function.

[0072] Step S3023: 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.

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

[0074] JPEG0007625123000006.jpg47141 where SS irepresents the contribution value of the lower early warning node of the upper early warning node i to flood formation, and q i 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 nodes, and ω1 and ω2 represent the influence contribution weights of the flood volume and encounter probability of the upper early warning node on the lower flood, respectively.

[0075] Step S303: Determine the key early warning node according to the influence contribution value. For details, refer to step S103 in the embodiment shown in FIG. 1, and the duplicated description will be omitted here.

[0076] Step S304: Determine the key early warning region according to the key early warning node. For details, refer to step S104 in the embodiment shown in FIG. 1, and the repeated description will be omitted here.

[0077] Step S305: Obtain water level information within key early warning areas. For details, refer to step S105 in the embodiment shown in FIG. 1, and repeated description will be omitted here.

[0078] Step S306: Generate flood early warning information for the target area according to the water level information in the key early warning area and the predetermined water level threshold value. For details, refer to step S106 in the embodiment shown in FIG. 1, and the repeated description will be 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 the embodiment of the present invention. As shown in FIG. 4, the process includes the following steps:

[0080] Step S401: Obtain runoff process data corresponding to a plurality of different early warning nodes in a target area and the connection relationships between the different early warning nodes, and the plurality of different early warning nodes are determined according to the drainage network information and river water system information of the target area. For details, refer to step S101 in the embodiment shown in Figure 1, and the repeated description will be omitted here.

[0081] Step S402: According to the connection relationship between different early warning nodes and the runoff process data corresponding to different early warning nodes, calculate the influence contribution value of each early warning node to the lower early warning node when flood occurs, and the influence contribution value represents the contribution amount to flood formation in the lower early warning node when flood occurs in each early warning node. For details, please refer to step S102 of the embodiment shown in Figure 1, and repeated description will be omitted here.

[0082] Step S403: Determine the key early warning node according to the influence contribution value. For details, refer to step S103 in the embodiment shown in FIG. 1, and the duplicated description will be omitted here.

[0083] Step S404: Determine the key early warning region according to the key early warning node. For details, refer to step S104 in the embodiment shown in FIG. 1, and the repeated description will be omitted here.

[0084] Step S405: Obtain water level information within key early warning areas. For details, refer to step S105 in the embodiment shown in FIG. 1, and repeated description will be omitted here.

[0085] Step S406: Generate flood early warning information for the target area according to the water level information in the key early warning area and the predetermined water level threshold. For details, refer to step S106 in the embodiment shown in Figure 1, and the repeated description will be omitted here.

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

[0087] For example, in an embodiment of the present application, basic information of the city-basin of a target area is obtained, the basic information of the city-basin including high-precision digital elevation (DEM) information, meteorological and hydrological monitoring data, basic data of the ground surface, urban drainage network planning data, river system vector data, and historical heavy rain and flood ledger information, etc., and according to the geographic location information of the drainage network, river system vector information, and responsive early warning key nodes, a programming process of the city-basin DEM is performed, that is, according to the hydraulic relationship of the drainage network and the river system, from upstream to downstream, the elevation reduction process of the DEM is performed in sequence, with the responsive early warning key nodes as boundaries, to ensure that the DEM values ​​of the downstream network and river channel are smaller than those of the upstream side, and digital elevation data of the target area is obtained.

[0088] Step S4062: According to the digital elevation data of the target area and the location information of the key early warning nodes, determine the corresponding catchment area when the key early warning nodes are flooded.

[0089] Illustratively, in the embodiment of the present application, based on the post-programming DEM data, in combination with the location information of the responsive early warning key nodes, a hydrological analysis tool is used to generate catchment area coverage of the key early warning nodes.

[0090] Step S4063: determine a key early warning region according to the corresponding catchment area when the key early warning node occurs flood. In the embodiment of the present application, the catchment area corresponding to the key early warning node is taken as the key early warning region.

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

[0092] For example, in the embodiment of the present application, based on the programmed DEM data, combined with the location information of the responsive early warning key nodes, the ARCGIS hydrological analysis tool is used to generate the catchment area range of each responsive early warning node. According to the upstream and downstream hydraulic relationship, from top to bottom, the control catchment area of ​​the boundary point where the river system enters the city is determined as the first-level responsive early warning unit D1, the control catchment area of ​​the urban storm water well is determined as the second-level unit D2, the control catchment area of ​​the intersection between the drainage network and the river system is determined as the third-level unit D3, and the control catchment areas of the mainstream and tributaries of the river system are determined as the fourth-level responsive early warning unit D4. A schematic distribution diagram of the flooded areas corresponding to each early warning node is shown in FIG. 5.

[0093] Step S408: Obtain runoff processes corresponding to each early warning node in the target precipitation process and the predetermined runoff thresholds of each early warning node.

[0094] For example, in the embodiment of the present application, the calculation process of a predetermined runoff threshold value involves screening rainfall processes corresponding to various levels of inland flooding caused by heavy rainfall recorded in the city's history ledger, inputting the pre-designed heavy rainfall processes into the established distributed hydrological model and the urban rainfall-runoff simulation model, and simulating to obtain the runoff threshold value of each level of early warning node corresponding to the designed rainfall. The calculation principle of the runoff threshold value of the response early warning node at the same level is shown in the following equation (8).

[0095] JPEG0007625123000007.jpg92170In formula, q 1i ~q 4i represents the runoff threshold corresponding to the designed response early warning node i for heavy rainfall conditions levels 1 to 4, and Q 1i ~Q 4i represents the simulated runoff value corresponding to the response early warning node i for the designed heavy rainfall condition levels 1–4 by simulation.

[0096] In some optional embodiments, step S308 includes steps b1 to b2.

[0097] Step b1: obtain target precipitation information. Illustratively, the target precipitation event is any one of the precipitation events in the target area, and in the embodiment of the present application, the precipitation event can be the precipitation event forecasted by the weather forecast system.

[0098] Step b2: input the target rainfall 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 rainfall process. Illustratively, the target rainfall process is input into the runoff simulation model, and the runoff simulation model outputs the runoff process of each early warning node.

[0099] Step S409: Generate early warning information of early warning areas respectively corresponding to different early warning nodes according to the runoff processes corresponding to each early warning node in the target precipitation process and the predetermined runoff thresholds of the corresponding early warning nodes.

[0100] Illustratively, in an embodiment of the present application, the runoff process corresponding to each early warning node in a target precipitation process is compared with a corresponding predetermined runoff threshold, and based on the comparison result, it is determined whether the corresponding node has a risk of flooding, and if there is a risk of flooding, early warning information of the early warning area corresponding to the early warning node is generated.

[0101] This embodiment further provides an early warning device for flood control, which is used to realize the above embodiment and preferred embodiment, and the description already given will be omitted. As used hereinafter, the term "module" can realize a combination of software and / or hardware of a given function. The device described in the following embodiment is preferably realized in software, but it is also possible and envisioned to realize in hardware or a combination of software and hardware.

[0102] This embodiment provides an early warning device for flood control, as shown in FIG. A first acquisition module 601, which is used to acquire 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, and the plurality of different early warning nodes are determined according to drainage network information and river system information of the target area; a calculation module 602, which is used to calculate the influence contribution value of the lower early warning node when a flood occurs in each early warning node according to the connection relationship between different early warning nodes and the runoff process data corresponding to each different early warning node, and the influence contribution value represents the contribution amount of the lower early warning node to the flood formation when a flood occurs in each early warning node; A first determining module 603, which is used for determining a key early warning node according to the influence contribution value; A second determining module 604, which is used for determining a key early warning area according to the key early warning node; A second acquisition module 605, which is used for acquiring water level information in key early warning areas; a first processing module 606, which is used for generating flood early warning information for the target area according to the water level information in the key early warning area and the predetermined water level threshold.

[0103] In some optional embodiments, the calculation module 602 includes: a first determination sub-module, which is used for determining at least one early warning node pair based on the connection relationship between different early warning nodes, where 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, which is used for calculating a target probability of a corresponding early warning node pair based on the runoff process data of different early warning nodes, where the target probability is used to represent the probability that a flood will occur in the second early warning node when a flood occurs in the first early warning node in the early warning node pair; and a second calculation sub-module, which is used for calculating an influence contribution value on a lower-level early warning node when a flood occurs in each early warning node based on the target probability.

[0104] In some alternative embodiments, the first acquisition module 601: 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.

[0105] In some alternative embodiments, the apparatus comprises: A third acquisition module is used for acquiring the water level history of key early warning areas; a comparison module used for comparing the water level process with a predetermined water level threshold to obtain a comparison result; and a second processing module, which is used for generating alarm information for the target area according to the comparison result.

[0106] In some alternative embodiments, the second acquisition module 605: A second acquisition sub-module, which is used for acquiring the water level process of key early warning areas; a comparison submodule, which is used for comparing the water level process with a predetermined water level threshold and obtaining a comparison result; and a second processing module used for generating alarm information for the target area based on the comparison result.

[0107] In some alternative embodiments, the first calculation submodule: A determination unit is used for determining a marginal distribution function of an outflow process corresponding to a first early warning node and a marginal distribution function of an outflow process corresponding to a second early warning node in each pair of early warning nodes 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 the predetermined connection function and 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; a calculation unit used for calculating a target probability of a 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: A second acquisition sub-module, which is used for acquiring digital elevation data of a target area and location information of a key early warning node; A second determining sub-module is used for determining a corresponding catchment area when a flood occurs in the key early warning node according to the digital elevation data of the target area and the location information of the key early warning node; and a third determining sub-module, which is used for determining a key early warning area according to the corresponding catchment area when the key early warning node occurs flood.

[0109] Further functional descriptions of the above modules and units are the same as those of the corresponding embodiments, and therefore repeated descriptions will be omitted here.

[0110] The flood early warning device in this embodiment is presented in the form of a functional unit, where unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory running one or more software or fixed programs, and / or other device capable of providing the above functionality.

[0111] An embodiment of the present invention further provides a computer device, which comprises an early warning device for flood control as shown in FIG.

[0112] Referring 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 may be communicatively connected to each other via different buses and mounted on a common motherboard or mounted in other manners as needed. The processor can process instructions executed within the computer device, including a memory or instructions stored on the memory for displaying graphical information of a GUI on an external input / output device (e.g., 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, each device providing partially required operations (e.g., 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 the at least one processor 10, thereby causing the at least one processor 10 to execute and realize the methods shown in the above embodiments.

[0115] The memory 20 may include a program storage area for storing an operating system, an application program required for at least one function, and a data storage area for storing data generated in response to use of the computer device. The memory 20 may also include high-speed random access memory, and may further include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may include memory that is selectively located remotely with respect to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

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

[0117] The computing device further includes a communications interface 30 through which the computing device communicates with other devices or with a communications network.

[0118] The embodiments of the present invention further provide a computer readable storage medium, and the methods according to the embodiments of the present invention may be implemented in hardware, firmware, recordable in a storage medium, or as computer code downloaded over a network, originally stored in a remote storage medium or a non-transitory machine readable storage medium, but stored in a local storage medium, whereby the methods described herein may be processed by software stored in the 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 memory, a hardware or solid state drive, etc., and further, the storage medium may further include a combination of the above types of memory. It is understood that the computer, processor, microprocessor controller, or programmable hardware may include a storage component capable of storing or receiving the software or computer code, and when the software or computer code is accessed and executed by the computer, processor, or hardware, it realizes the methods shown in the embodiments.

[0119] Although the embodiments of the present invention have been described with reference to the drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and all such modifications and variations 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; An early warning method for flood control, characterized in that each step is executed by a computer.

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. Further, a step of determining a corresponding early warning area based on 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; 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; 2. The method of claim 1, wherein each step is performed by a computer.

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 a predetermined runoff threshold value 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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