Scenarized flexible early warning system and method under dynamic optimization of water level early warning indexes

Abstract

The invention discloses a scenarized flexible early warning system and method under dynamic optimization of a water level early warning index, and relates to the technical field related to water level monitoring and early warning, the system comprises a water area structure analysis unit used for analyzing the water area structure of a current area; the water level real-time monitoring unit is used for performing water level real-time monitoring on the father node and the child node respectively; the sub-node evaluation unit is used for evaluating the residual recovery capability indexes corresponding to the sub-nodes; the flexible analysis unit is used for carrying out water level early warning index flexible analysis to obtain a water level early warning flexible index; and the water level early warning signal generation unit is used for generating a water level early warning signal. The technical problems that in the prior art, water level early warning indexes are fixed and cannot adapt to complex water area structures and real-time water flow changes, and the early warning indexes cannot be dynamically adjusted by fully utilizing real-time data, so that the early warning accuracy and timeliness are insufficient are solved, scenarized flexible early warning is achieved, and the early warning efficiency is improved. The technical effect of improving the accuracy and timeliness of water level early warning is achieved.

Description

Technical Field

[0001] The present application relates to the technical field related to water level monitoring and early warning, and specifically to a scenario-based flexible early warning system and method under the dynamic optimization of water level early warning indicators. Background Art

[0002] Traditional water level warning methods mostly use fixed warning indicators, which are difficult to adapt to complex and changeable water environments. There are significant differences in the water structure of different regions, and their water flow characteristics, river capacity and other factors are different. Fixed warning indicators cannot be flexibly adjusted for specific scenarios, resulting in a significant reduction in the accuracy and timeliness of warnings. On the one hand, with the expansion of cities and climate change, the frequency and intensity of flood disasters have increased, and urban waterlogging has become more serious. An accurate and adaptive water level warning system has become an urgent need. Since it cannot accurately reflect the real-time conditions of different regions, the accuracy of water level warnings is insufficient; on the other hand, when facing complex water structures, existing water level monitoring fails to fully consider the dynamic relationship and characteristics between branches. It is difficult to accurately judge the trend of water level changes based on fixed indicators, and it is impossible to flexibly adjust the water level warning indicators of the confluence branch according to the remaining recovery capacity of the sub-branch in time, resulting in delayed or inaccurate warning information. Therefore, in the current related technologies, there are technical problems such as fixed water level warning indicators, inability to adapt to complex water structure and real-time water flow changes, and inability to make full use of real-time data to dynamically adjust warning indicators, resulting in insufficient accuracy and timeliness of warnings. Summary of the invention

[0003] This application solves the technical problems in the prior art that water level warning indicators are fixed, cannot adapt to complex water body structures and real-time water flow changes, cannot make full use of real-time data to dynamically adjust warning indicators, resulting in insufficient warning accuracy and timeliness, by providing a scenario-based flexible warning system and method under dynamic optimization of water level warning indicators. This realizes scenario-based flexible warning and achieves the technical effect of improving the accuracy and timeliness of water level warnings.

[0004] This application provides a scenario-based flexible early warning system with dynamically optimized water level early warning indicators. The system includes: a water area structure analysis unit for analyzing the water area structure of the current area and identifying parent nodes and child nodes, where the parent node is a confluence branch and the child node is a sub-branch that recovers the confluence branch corresponding to the parent node; a water level real-time monitoring unit for integrating a water level sensing device and performing real-time water level monitoring on the parent node and the child node respectively according to the water level sensing device to obtain a parent node monitoring data set and a child node monitoring data set; a child node evaluation unit for evaluating the remaining recovery capacity index corresponding to the child node according to the child node monitoring data set; a flexible analysis unit for sending the remaining recovery capacity index corresponding to the child node to the water level early warning index flexible adjustment module of the parent node, and performing flexible analysis of the water level early warning index according to the parent node monitoring data set and the remaining recovery capacity index to obtain a water level early warning flexible index; a water level early warning signal generation unit for performing water level monitoring on the parent node according to the water level early warning flexible index, and generating a water level early warning signal if the water level of the parent node is greater than the water level early warning flexible index.

[0005] In a possible implementation, the scenario-based flexible early warning system with dynamically optimized water level early warning indicators also performs the following processing: analyzing the water area structure of the current area and identifying multiple node groups, each node group including a parent node and at least one child node; analyzing the multiple node groups respectively through the water level early warning index flexible adjustment module and outputting multiple water level early warning flexible indexes of the multiple node groups; performing water level monitoring on the parent nodes corresponding to the multiple node groups according to the multiple water level early warning flexible indexes and generating multiple water level early warning signals.

[0006] In a possible implementation, the scenario-based flexible early warning system with dynamically optimized water level early warning indicators also performs the following processing: determining whether there is a tree relationship among the multiple node groups, where the tree relationship is a tree relationship in which the parent node of one node group is the child node of another node group; if there is a tree relationship among the multiple node groups, connecting the node groups with a tree relationship to obtain a node tree; and performing flexible conduction analysis of the water level early warning index on the node tree by the water level early warning index flexible adjustment module to update the water level early warning flexible index.

[0007] In a possible implementation, the scenario-based flexible early warning system with dynamically optimized water level early warning indicators also performs the following processing: setting flexible conduction rules for the node tree; if the water level early warning index of any node in the node tree is updated, conducting the water level early warning index layer by layer upward from the current node according to the flexible conduction rules to update the water level early warning index of the node tree.

[0008] In a possible implementation, the scenario-based flexible early warning system under dynamic optimization of the water level early warning index further performs the following processes: obtaining the historical water level data, historical flow velocity data, and total allowable flow of each child node; collecting the historical water level data, historical flow velocity data, and total allowable flow of all child nodes, and establishing a recovery capacity model; the recovery capacity model analyzes the remaining recovery capacity index corresponding to each child node according to the child node monitoring data set, where the remaining recovery capacity index represents the remaining recovery flow that the current child node can accommodate.

[0009] In a possible implementation, the scenario-based flexible early warning system under dynamic optimization of the water level early warning index further performs the following processes: obtaining the initial water level early warning threshold of the parent node; judging whether the current water level of the parent node reaches the initial water level early warning threshold according to the parent node monitoring data set; if the initial water level early warning threshold is reached, setting a flexible threshold according to the remaining recovery capacity index, increasing the initial water level early warning threshold according to the flexible threshold, and outputting the flexible water level early warning index.

[0010] In a possible implementation, the scenario-based flexible early warning system under dynamic optimization of the water level early warning index further performs the following processes: detecting whether a marked scenario is triggered according to the parent node monitoring data set; if the marked scenario is triggered, identifying the influence weight of the triggered scenario type on the flexible threshold, and updating the flexible threshold.

[0011] In a possible implementation, the scenario-based flexible early warning system under dynamic optimization of the water level early warning index further performs the following processes: identifying an independent node, where the independent node is a node without a recovery sub-branch; analyzing the historical water level early warning index of the independent node, and making a prediction according to the historical water level early warning index, and outputting the flexible water level early warning index corresponding to the independent node.

[0012] In a possible implementation, the scenario-based flexible early warning system under dynamic optimization of the water level early warning index further performs the following processes: identifying an independent node, where the independent node is a node without a recovery sub-branch; analyzing the historical water level early warning index of the independent node, and making a prediction according to the historical water level early warning index, and outputting the flexible water level early warning index corresponding to the independent node.

[0013] The present application also provides a scenario-based flexible warning method under dynamic optimization of water level warning indicators. The method includes: analyzing the water area structure of the current area to identify parent nodes and child nodes, where the parent nodes are confluent branches, and the child nodes are sub-branches that recover the confluent branches corresponding to the parent nodes; integrating water level sensing devices to respectively perform real-time water level monitoring on the parent nodes and the child nodes to obtain a parent node monitoring data set and a child node monitoring data set; evaluating the remaining recovery capacity indicators corresponding to the child nodes according to the child node monitoring data set; sending the remaining recovery capacity indicators corresponding to the child nodes to the water level warning indicator flexible adjustment module of the parent node, and performing flexible analysis of the water level warning indicators according to the parent node monitoring data set and the remaining recovery capacity indicators to obtain water level warning flexible indicators; performing water level monitoring on the parent nodes according to the water level warning flexible indicators, and if the water level of the parent node is greater than the water level warning flexible indicators, generating a water level warning signal.

[0014] It is intended to solve the technical problems existing in the prior art, such as fixed water level warning indicators, inability to adapt to complex water area structures and real-time water flow changes, and inability to make full use of real-time data to dynamically adjust warning indicators, resulting in insufficient warning accuracy and timeliness, through the scenario-based flexible warning system, method, water area structure analysis unit, water level real-time monitoring unit, child node evaluation unit, flexible analysis unit, and water level warning signal generation unit provided by the present application. The water area structure analysis unit is used to analyze the water area structure of the current area; the water level real-time monitoring unit is used to respectively perform real-time water level monitoring on the parent nodes and the child nodes; the child node evaluation unit is used to evaluate the remaining recovery capacity indicators corresponding to the child nodes; the flexible analysis unit is used to perform flexible analysis of the water level warning indicators according to the parent node monitoring data set and the remaining recovery capacity indicators to obtain water level warning flexible indicators; the water level warning signal generation unit is used to generate a water level warning signal. The technical effect of improving the accuracy and timeliness of water level warning is achieved by realizing scenario-based flexible warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments of the present disclosure will be briefly introduced below. Flowcharts are used in the present application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the operations in the front or below do not necessarily need to be executed precisely in sequence. On the contrary, according to the need, they can be executed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several operations can be removed from these processes.

[0016] Figure 1 It is a schematic structural diagram of a scenario-based flexible warning system under dynamic optimization of water level warning indicators provided by an embodiment of the present application.

[0017] Figure 2Schematic flowchart of the scenario-based flexible warning method under dynamic optimization of water level warning indicators provided by the embodiments of the present application.

[0018] Explanation of reference numerals: The water area structure analysis unit 10, the real-time water level monitoring unit 20, the sub-node evaluation unit 30, the flexible analysis unit 40, and the water level warning signal generation unit 50. Detailed implementation manners

[0019] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the following specifically gives the detailed implementation manners of the present application.

[0020] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present application.

[0021] In the following description, "some embodiments" are involved, which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. The terms "first / second" involved are only used to distinguish similar objects and do not represent a specific order for the objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, system, product or server including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules not clearly listed or inherent to these processes, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application.

[0022] The embodiments of the present application provide a scenario-based flexible warning system under dynamic optimization of water level warning indicators, as Figure 1 shown. The system includes: The water area structure analysis unit 10 is used to analyze the water area structure of the current area, identify the parent node and the sub-node, where the parent node is the confluence branch, and the sub-node is the sub-branch that recovers the confluence branch corresponding to the parent node.

[0023] Preferably, obtain the geographical information data of the current water area from the Geographic Information System (GIS) database and satellite remote sensing images, and collect the hydrological data of the current area from hydrological monitoring stations. Among them, the geographical information data includes the high-precision map of the area, such as the water area positions and contour information of topography, landforms, rivers, channels, etc., and the hydrological data includes historical hydrological information, such as water level, flow rate, and flow velocity data. Then, analyze the water area structure based on these data, and identify the confluence branch and the sub-branches connected to it as the parent node and the sub-node respectively. Specifically, the confluence branch refers to a larger water flow channel where multiple water flow paths converge, and the sub-node is the sub-branch that collects the corresponding confluence branch of the parent node, and its water flow will eventually flow into the confluence branch of the parent node. For example, taking the urban drainage system as an example, multiple smaller street rainwater pipes converge into a main drainage pipe, and the main drainage pipe is regarded as the parent node, that is, the confluence branch; each street rainwater pipe connected to the main drainage pipe is the sub-node, and each sub-node has its own different water flow conditions and characteristics, and the change of its water flow state directly affects the water level of the parent node. By identifying the parent node and the sub-node, the flow path and the mutual relationship of the water flow in the entire water area structure can be clearly understood, which helps to monitor and analyze the water levels at different positions more pertinently, so as to achieve more accurate water level early warning.

[0024] The real-time water level monitoring unit 20 is used to integrate the water level sensing device, and respectively conduct real-time water level monitoring on the parent node and the sub-node according to the water level sensing device, so as to obtain the parent node monitoring data set and the sub-node monitoring data set.

[0025] Preferably, through integrating the water level sensing device, realize real-time and accurate monitoring of the water levels of the parent node and the sub-node in the water area structure, and generate corresponding monitoring data sets. Among them, the water level sensing device can sense the water level change and convert it into an electrical signal or other measurable signals, such as a pressure type water level sensor, an ultrasonic type water level sensor, a radar type water level sensor, etc. Specifically, according to the current water area environment and monitoring requirements, arrange the water level sensing device at the parent node (confluence branch) and the sub-node (sub-branch). For example, at the confluence of the river (parent node), install a radar type water level sensor with higher accuracy to accurately measure the water level change in a larger range; while in the narrower sub-branch, select an ultrasonic type water level sensor.

[0026] Preferably, for the convergence point (parent node) of the water flows of multiple sub-branches, the water level change is affected by multiple factors such as the water inflow, water flow velocity, and water flow pattern after confluence of each sub-branch. The water level sensor continuously monitors data such as the water level height and the water level change rate at the parent node. Whether the water level rises or falls slowly or changes sharply in a short period of time, the monitoring data is obtained in a timely manner; the water level sensing device monitors the water level of each sub-node separately and obtains its water level data, including the water level height, the water level change rate, and the water flow velocity, etc.; then, at certain time intervals (such as every minute, every hour, etc.), the water level data collected by the water level sensing device is sampled and recorded to form a parent node monitoring data set and a sub-node monitoring data set, which not only contains the water level information at the current moment, but also records the trend of the water level change over time. Through analysis, the water level change rules of the parent node and sub-nodes in the water area can be understood, and then accurate water level early warning can be carried out to detect abnormal situations in a timely manner.

[0027] The sub-node evaluation unit 30 is configured to evaluate the remaining recovery ability index corresponding to the sub-node according to the sub-node monitoring data set.

[0028] Preferably, the remaining recovery ability index corresponding to the sub-node is evaluated according to the sub-node monitoring data set, that is, the data in the sub-node monitoring data set is analyzed and transformed to obtain a quantitative index that can reflect the ability of the sub-node to accommodate and transmit water flow under the current state. Specifically, according to the physical structure of the sub-node, such as the width, depth, shape, etc. of the river channel, the maximum water storage capacity of the sub-node in the ideal state, that is, the total capacity of the sub-node, is determined; through the real-time water level data and water flow velocity data in the sub-node monitoring data set, the actual water storage volume and water flow rate in the current sub-node are calculated; then, considering the total capacity, current water storage volume, and flow rate of the sub-node, etc., the remaining recovery ability index is calculated. For example, subtract the current water storage volume from the total capacity of the sub-node and then divide by the coefficient related to the flow rate to obtain a value that can reflect the remaining ability of the sub-node to accommodate and transmit water flow. The larger this value is, the stronger the remaining recovery ability of the sub-node, and vice versa, which helps to more accurately analyze the water level change trend of the parent node and perform a flexible analysis of the water level early warning index.

[0029] The flexible analysis unit 40 is configured to send the remaining recovery ability index corresponding to the sub-node to the water level early warning index flexible adjustment module of the parent node, and perform a flexible analysis of the water level early warning index according to the parent node monitoring data set and the remaining recovery ability index to obtain a water level early warning flexible index.

[0030] Preferably, the remaining recovery capacity index corresponding to the child node is sent to the water level warning index flexible adjustment module of the parent node to realize data transmission from the child node to the parent node, enabling the parent node to obtain the key water level information of the child nodes related to itself, so as to comprehensively consider the water flow condition of the parent node itself and the potential impact of the child nodes on the parent node; then through the water level warning index flexible adjustment module, flexible analysis of the water level warning index is carried out according to the monitoring data set of the parent node and the remaining recovery capacity index. Specifically, the water level warning index flexible adjustment module sets multiple levels of warning thresholds for different water level warning flexible indexes according to the historical data, water area environment, etc. of the current area. For example, the water level warning flexible index is divided into four levels, namely low risk, medium risk, high risk and extremely high risk, and corresponding water level values are set; then the latest data of the water level warning flexible index is obtained in real time and compared and analyzed with the set warning thresholds at all levels. If the water level of the parent node continues to rise and the rising speed is relatively fast, and the remaining recovery capacity index of the child nodes shows that the water flow accommodation and transmission capabilities of some child nodes are weak, the water level change trend of the parent node is evaluated. For example, when the real-time water level warning flexible index shows that the current water level is on the rise and gradually approaches the threshold of the high-risk level, the water level warning index flexible adjustment module determines whether the rising trend continues and whether there are other factors affecting the water level change; and then dynamically adjusts the water level warning index, including lowering the warning threshold of the water level warning and sending out a warning signal in advance, so as to take measures in time to deal with it; finally, the water level warning flexible index is obtained, that is, a dynamic value that comprehensively considers various factors of the parent node and the child nodes, which can more accurately reflect the actual water level risk status of each parent node in the current water area structure, so as to be able to respond more flexibly and accurately to the complex and changeable water level changes in the water area, improving the accuracy and scientific nature of the warning.

[0031] The water level warning signal generation unit 50 is used to monitor the water level of the parent node according to the water level warning flexible index, and if the water level of the parent node is greater than the water level warning flexible index, a water level warning signal is generated.

[0032] Preferably, the water level of the parent node is monitored according to the water level warning flexible index, the real-time water level data and the water level fluctuation condition of the parent node are obtained, and then the real-time obtained water level of the parent node is compared with the water level warning flexible index. When the water level of the parent node is greater than the water level warning flexible index, it indicates that the current water level has reached or exceeded the set warning threshold, and then a water level warning signal is immediately generated, such as sending a text message to notify relevant personnel, displaying a prominent red warning sign on the monitoring interface, starting an alarm to emit a sound alarm, etc., to inform relevant personnel that the water level condition of the current parent node is relatively dangerous and corresponding measures need to be taken to deal with possible disaster situations to ensure the safety of the surrounding areas.

[0033] Furthermore, the specific configuration of the water level warning signal generation unit 50 further includes analyzing the water area structure of the current area, identifying multiple node groups, each node group including a parent node and at least one child node; analyzing the multiple node groups respectively through the water level warning index flexible adjustment module, and outputting multiple water level warning flexible indexes of the multiple node groups; monitoring the water level of the parent nodes corresponding to the multiple node groups according to the multiple water level warning flexible indexes, and generating multiple water level warning signals.

[0034] Preferably, analyze the water area structure of the current area to understand the distribution of the water area, the flow direction of the water flow, the water flow connectivity between different areas, etc., and then divide the entire water area into multiple node groups, each node group consisting of a parent node and at least one child node. Among them, the parent node represents the confluence branch at a higher level in the water area, and the child node is the surrounding water area position connected to the parent node. Then, for each node group, the water level warning index flexible adjustment module conducts separate analyses, that is, comprehensively considering the parent node monitoring data set and the remaining recovery ability index of the child node, etc. For the parent node, collect real-time monitoring data such as its water level, flow rate, and flow velocity, as well as the change law of the water level in historical data, etc.; for the child node, evaluate its remaining recovery ability, that is, the ability of the child node to accommodate and process the water flow from the parent node under the current state; through integrated calculation, output a water level warning flexible index for each node group, obtaining multiple water level warning flexible indexes. For example, according to the principle of hydrodynamics, combined with the water level change trend of the parent node and the accommodation ability of the child node, predict the possible change situation of the water level of the parent node under different conditions. Among them, the water level warning flexible index is dynamically generated according to the specific situation of each node group and can accurately reflect the water level risk status faced by the node group. Finally, according to the water level warning flexible indexes of each node group, conduct real-time water level monitoring on the corresponding parent nodes, continuously obtain the actual water level data of the parent nodes, and compare it with the corresponding water level warning flexible indexes. If the water level of the parent node is greater than its corresponding water level warning flexible index, it indicates that the node group faces the risk of excessive water level, and immediately generate a water level warning signal, and then generate multiple water level warning signals, so as to timely understand the water level conditions in different areas and take corresponding flood control and disaster reduction measures, such as dispatching water resources.

[0035] Furthermore, the specific configuration of the water level warning signal generation unit 50 further includes determining whether there is a tree relationship among the multiple node groups, where the tree relationship is a tree relationship in which the parent node of one node group is the child node of another node group; if there is a tree relationship among the multiple node groups, connect the node groups with a tree relationship to obtain a node tree; the water level warning index flexible adjustment module conducts a water level warning index flexible conduction analysis on the node tree and updates the water level warning flexible index.

[0036] Preferably, after analyzing the regional water area structure and dividing it into multiple node groups, further determine whether there is a tree relationship between the multiple node groups, that is, the parent node of one node group is the child node of another node group. For example, in a water system network, a tributary converges with the main stream to form a node group, and this tributary itself may be formed by the convergence of multiple smaller tributaries. These smaller tributaries and this tributary form another node group. At this time, there is a situation where the parent node (tributary) of one node group is the child node of another node group (relative to the main stream). By judging the tree relationship, the hierarchical association between various parts of the entire water area structure can be grasped more accurately.

[0037] Preferably, after determining that there is a tree relationship between multiple node groups, connect these node groups with tree relationships according to their hierarchical relationships to form a node tree, which can clearly show the hierarchical structure between each node group and the water flow conduction path; then use the water level warning index flexible adjustment module to conduct a flexible conduction analysis of the water level warning index for the constructed node tree. Specifically, since there is a tree relationship between each node group in the node tree, a change in the water level of one node group will affect other related node groups through the conduction of water flow, and then more accurately evaluate the water level risk of each node group according to the water flow conduction effect. For example, when the water level of the upstream node group changes, the water level of its downstream node group will also be affected accordingly. The flexible conduction analysis comprehensively considers the time delay of water flow conduction, water volume change, etc., and transmits the water level change information of the upstream node group to the downstream node group, and then analyzes the impact on the water level warning index of the downstream node group; finally, based on the results of the flexible conduction analysis, the water level warning index flexible adjustment module updates the water level warning flexible index of each node group to more accurately reflect the actual situation of the entire water area at present and improve the accuracy and timeliness of water level warning.

[0038] Furthermore, the specific configuration of the water level warning signal generation unit 50 also includes setting the flexible conduction rule of the node tree; if the water level warning index of any node in the node tree is updated, the water level warning index is conducted layer by layer upward from the current node according to the flexible conduction rule to update the water level warning index of the node tree.

[0039] Preferably, distance parameters, water flow velocity parameters, and flow rate change parameters are determined as conduction parameters. Specifically, according to the actual distance between nodes, the distance is divided into different intervals, such as short distance (0 - 100 meters), medium distance (101 - 500 meters), and long distance (more than 500 meters). The closer the distance, the higher the conduction coefficient. For example, the conduction coefficient for short distance can be set to 0.8, for medium distance to 0.5, and for long distance to 0.3. Based on historical water flow velocity data and real-time monitoring data, the water flow velocity is divided into low speed (0 - 1 meter per second), medium speed (1 - 3 meters per second), and high speed (more than 3 meters per second). The faster the water flow velocity, the greater the conduction speed factor. For example, the conduction speed factor is 1 at low speed, 2 at medium speed, and 3 at high speed. Analyze the impact of flow rate changes on water level, set the threshold of the flow rate change rate. When the flow rate change rate is within ±10%, it indicates that the impact on water level is small, and the conduction correction coefficient is 1; when the change rate is between 10% and 30%, the correction coefficient is 1.5; when the change rate exceeds 30%, the correction coefficient is 2.

[0040] Preferably, when the water level warning index of the child node changes, it is conducted to the parent node according to the following formula: , where is the updated water level warning index of the parent node, is the changed water level warning index of the child node, is the distance conduction coefficient, is the water flow velocity conduction factor, is the flow rate change correction coefficient, is the original water level warning index of the parent node; when the water level warning index of the parent node changes and is conducted to the child node, consider the importance weight (such as determined according to the population density in the area where the child node is located), and conduct it to the child node according to the following formula, , where is the updated water level warning index of the child node, is the changed water level warning index of the parent node, is the original water level warning index of the child node. Then consider the influence of environmental factors. For example, adjust the conduction rule according to the water flow characteristics in different seasons. The water flow velocity increases and the flow rate increases during the rainy season, and the conduction speed can be increased by 50% - 100% compared with usual; in case of extreme weather such as heavy rain and flood, uniformly adjust the conduction coefficient to 0.6 (regardless of the distance), and at the same time increase the flow rate change correction coefficient by 0.5 to highlight the influence of flow rate changes on the conduction of water level warning index.

[0041] Preferably, different conduction thresholds and speeds are set for different warning levels. When the warning level is low, the conduction of water level changes is relatively conservative. The conduction occurs only when the water level change exceeds a certain amplitude (e.g., 10%) and lasts for a certain period of time (e.g., 6 hours). When the warning level is high, the conduction occurs immediately when the water level change exceeds 5% and lasts for 3 hours, and the conduction speed is increased. The corresponding conduction parameters are adjusted accordingly. For example, the distance conduction coefficient is increased by 0.2, and both the water flow speed conduction factor and the flow rate change correction coefficient are multiplied by 1.2. According to these comprehensive settings of the flexible conduction rules of the node tree, it can conduct the water level warning indicators flexibly and accurately according to the actual situation to achieve the best warning effect.

[0042] Preferably, when the water level warning indicator of any node in the node tree is updated, it is conducted according to the flexible conduction rules. Suppose the water level warning indicator of a certain child node is updated. For example, due to a sudden increase in precipitation in the area where the child node is located, the water level rises, so it is necessary to lower its water level warning indicator. According to the flexible conduction rules, the updated water level warning indicator will be conducted layer by layer upward from the current node. Specifically, the current node transmits the water level change to the parent node, and the parent node adjusts and updates its own water level warning indicator according to the flexible conduction rules, in combination with its relationship with the child node and the current water flow condition, etc.; then it continues to be transmitted to the parent node's parent node, and so on, until it is transmitted to the root node of the node tree or until a node believes according to the conduction rules that there is no need to update its upper-level node anymore. Thus, the water level warning indicators of the entire node tree can timely and accurately reflect the potential risk changes in the entire water area caused by the water level change of a certain node, so as to take corresponding preventive measures in time.

[0043] Furthermore, the specific configuration of the child node evaluation unit 30 also includes obtaining the historical water level data, historical flow velocity data, and total allowable flow of each child node; collecting the historical water level data, historical flow velocity data, and total allowable flow of all child nodes to establish a recovery capacity model; the recovery capacity model analyzes the corresponding remaining recovery capacity indicators of each child node according to the child node monitoring data set, where the remaining recovery capacity indicator represents the remaining recovery flow that the current child node can accommodate.

[0044] Preferably, historical water level data, historical flow velocity data, and the total flow capacity that can be accommodated are obtained for each child node. Among them, the historical water level data refers to the measurement value records of the past water levels of each child node, reflecting the change of the water level of the child node over time, including the high and low fluctuations of the water level, seasonal changes, etc.; the historical flow velocity data records the historical information of the water flow velocity of the child node. When the flow velocity is relatively fast, it may be more likely to cause a rapid rise or fall of the water level, and different flow velocities have different effects on the scouring and siltation of the water body, etc.; the total flow capacity that can be accommodated represents the maximum flow value that the water area where each child node is located can accommodate. Then, check whether there are missing values in the historical water level data and historical flow velocity data, and perform interpolation to supplement them. Then, perform data standardization processing, and further calculate the water level characteristics at each time point, including the water level change rate (the difference between the current water level and the water level at the previous moment divided by the water level at the previous moment), the flow velocity change rate, etc. Construct a recovery capacity model, such as a linear regression model, a decision tree model, etc. Then, use the historical water level data, historical flow velocity data, and the total flow capacity that can be accommodated, with the remaining recovery flow as the target variable and the processed water level characteristics as the independent variables, to perform model training to obtain the recovery capacity model.

[0045] Preferably, the recovery capacity model analyzes the collected data and calculates the remaining recovery capacity index corresponding to each child node, which characterizes the remaining recovery flow that the current child node can accommodate. Specifically, the recovery capacity model calculates the remaining recovery flow that each node can accommodate according to the current water level, historical water level change trend, real-time flow velocity, and the total flow capacity that can be accommodated of the child node. For example, if a child node has a relatively low current water level, small historical water level fluctuations, slow real-time flow velocity, and a large total flow capacity that can be accommodated, then its remaining recovery capacity index is relatively high, indicating that the child node has a large space to accommodate more water flow, that is, the remaining recovery flow is relatively large; on the contrary, if the current water level is close to the water level corresponding to the total flow capacity that can be accommodated, the flow velocity is relatively fast, and there have often been rapid rises in the water level in history, the remaining recovery capacity index is relatively low, indicating that the remaining recovery flow that the child node can accommodate is relatively small.

[0046] Furthermore, the specific configuration of the flexible analysis unit 40 further includes obtaining the initial water level warning threshold of the parent node; judging whether the current water level of the parent node reaches the initial water level warning threshold according to the monitoring data set of the parent node; if the initial water level warning threshold is reached, setting a flexible threshold according to the remaining recovery capacity index, and increasing the initial water level warning threshold according to the flexible threshold, and outputting a flexible water level warning index.

[0047] Preferably, the initial water level warning threshold is a water level value preset according to historical water level data, which is used to determine whether the water level of the parent node is in a state where measures need to be taken. By real-time monitoring the water level data of the parent node and comparing it with the initial water level warning threshold, if the current water level reaches or exceeds the initial water level warning threshold, it indicates that the water level has reached the preset warning level and corresponding measures need to be taken, including setting a flexible threshold according to the remaining recovery capacity index. Specifically, if the remaining recovery capacity of the child node is strong, it means there is still a certain buffer space to cope with the further rise of the water level, and the flexible threshold may be set relatively high; conversely, if the remaining recovery capacity of the child node is weak, the flexible threshold is set low to issue a warning more timely. Then, the initial water level warning threshold is adjusted upward according to the set flexible threshold. If the flexible threshold is high, the initial water level warning threshold will be adjusted upward more, leaving more time to cope with the rising water level; if the flexible threshold is low, the upward adjustment range of the initial water level warning threshold will be small to more strictly control the water level risk. Finally, the flexible index of water level warning is output, which can more comprehensively and accurately reflect the current water level condition of the water area and the degree of risk faced.

[0048] Furthermore, the specific configuration of the flexible analysis unit 40 further includes detecting whether a marked scenario is triggered according to the parent node monitoring data set; if the marked scenario is triggered, identifying the influence weight of the triggered scenario type on the flexible threshold, and updating the flexible threshold.

[0049] Preferably, the marked scenario is a combination of some specific conditions preset in advance, such as rapid water level rise and abnormal flow rate, water level reaching a specific height and sudden change in flow rate, etc. By analyzing information such as water level, flow rate and flow of the parent node monitoring data set, it is judged whether the predefined marked scenario appears; if the marked scenario is triggered, the influence weight of the triggered scenario type on the flexible threshold is identified. Specifically, the influence degrees of different marked scenario types are different. For example, when "rapid water level rise and abnormal flow rate" appears, it indicates the occurrence of an emergency situation, and the influence weight on the flexible threshold will be relatively high. By analyzing and evaluating different scenario types, the respective influence weights on the flexible threshold are determined to adjust the flexible threshold more accurately. For example, if the influence weight of a certain scenario type is high and this scenario is triggered, the flexible threshold will be adjusted significantly, including reducing the flexible threshold to more strictly control the water level risk and issue a warning in time. According to different actual scenario situations, the flexible threshold is dynamically updated to make the water level warning more flexible and accurate and better adapt to various complex operating conditions.

[0050] Further, the specific configuration of the water area structure analysis unit 10 further includes identifying independent nodes, where the independent nodes are nodes without a recycling sub-branch; analyzing the historical water level warning indicators of the independent nodes, making a prediction based on the historical water level warning indicators, and outputting the water level warning flexibility indicators corresponding to the independent nodes.

[0051] Preferably, the independent nodes are nodes without a recycling sub-branch, that is, there are no subordinate branches connected thereto for recycling or regulating water flow. Identifying the independent nodes for separate analysis and processing, obtaining the historical water level warning indicators of the independent nodes, which may include water level peaks, water level change frequencies, the number of times of reaching the warning water level in different past periods, etc. By analyzing the historical data, understand the change law of the water level during the past operation of the independent node and under what circumstances a warning will be triggered. For example, whenever the rainy season comes, the water level will rise rapidly and reach a specific water level value multiple times to trigger a warning; then use the information contained in the historical water level warning indicators to estimate the future water level situation of the independent node. For example, use a machine learning model to predict the change of the water level under different conditions based on various features in the historical data, and then understand in advance the water level risks that the independent node may face, and output the water level warning flexibility indicators corresponding to the independent nodes, which can be flexibly adjusted according to different situations, so as to provide more personalized and accurate water level warning information for the independent nodes, and help better manage and control the water level safety.

[0052] The specific configuration of the flexibility analysis unit 40 further includes determining the basin type where the independent node is located, performing upstream and downstream linkage analysis on the historical water level warning indicators according to the basin type to obtain the linkage influence weight; updating the water level warning flexibility indicators according to the linkage influence weight.

[0053] Preferably, the basin type where the independent node is located is judged, that is, whether the independent node is located in the upstream, midstream or downstream. Nodes in different basin locations have different water flow characteristics and influencing factors. Then, according to the basin type where the independent node is located, an upstream and downstream linkage analysis is performed on the historical water level warning indicators, that is, the relationship between it and other upstream and downstream nodes is analyzed. Specifically, for the independent node in the upstream, the impact of its water level changes on the midstream and downstream nodes should be considered; for the independent node in the midstream, it is necessary to analyze the impact of the upstream water on its water level warning indicators, and also consider the transmission effect of its own water level changes on the downstream; the downstream independent node mainly evaluates the comprehensive impact of the upstream nodes on its water level. The influence of upstream and downstream influences is used to determine the degree to which independent nodes of different types of basins are affected by upstream and downstream, that is, the linkage influence weight, which indicates the relative importance of upstream and downstream nodes to the water level warning index of the current independent node; finally, according to the linkage influence weight obtained, the original water level warning flexibility index is updated, that is, the influence of upstream and downstream nodes is included in the calculation of the water level warning flexibility index of the current independent node. If an independent node is downstream and the linkage influence weight of the upstream node is large, when the water level of the upstream node changes abnormally, according to this weight, the water level warning flexibility index of the downstream independent node is adjusted greatly, making it more inclined to issue a warning to deal with the possible water level risk in advance. In this way, the interaction between nodes in the basin can be considered more comprehensively and accurately, so that the water level warning flexibility index is more in line with the actual situation, and the accuracy and reliability of the water level warning of the entire basin are improved.

[0054] In the above, refer to Figure 1 The following describes in detail the scenario-based flexible warning system under the dynamic optimization of water level warning indicators according to an embodiment of the present invention. Figure 2 The following describes a scenario-based flexible warning method under dynamic optimization of water level warning indicators according to an embodiment of the present invention. Figure 2 As shown, the method includes: analyzing the water structure of the current area, identifying the parent node and the child node, wherein the parent node is a confluent branch, and the child node is a child branch that recycles the confluent branch corresponding to the parent node; integrating a water level sensing device, and performing real-time water level monitoring on the parent node and the child node respectively according to the water level sensing device to obtain a parent node monitoring data set and a child node monitoring data set; evaluating the remaining recovery capacity index corresponding to the child node according to the child node monitoring data set; sending the remaining recovery capacity index corresponding to the child node to the water level warning index flexible adjustment module of the parent node, performing water level warning index flexibility analysis according to the parent node monitoring data set and the remaining recovery capacity index, and obtaining a water level warning flexibility index; monitoring the water level of the parent node according to the water level warning flexibility index, and generating a water level warning signal if the water level of the parent node is greater than the water level warning flexibility index.

[0055] In a possible implementation, the scenario-based flexible early warning method under the dynamic optimization of the water level early warning index further includes: analyzing the water area structure of the current area, identifying a plurality of node groups, each node group including a parent node and at least one child node; analyzing the plurality of node groups respectively through the water level early warning index flexible adjustment module, and outputting a plurality of water level early warning flexible indexes of the plurality of node groups; monitoring the water levels of the parent nodes corresponding to the plurality of node groups according to the plurality of water level early warning flexible indexes, and generating a plurality of water level early warning signals.

[0056] In a possible implementation, the scenario-based flexible early warning method under the dynamic optimization of the water level early warning index further includes: determining whether there is a tree relationship among the plurality of node groups, where the tree relationship is a tree relationship in which the parent node of one node group is the child node of another node group; if there is a tree relationship among the plurality of node groups, connecting the node groups with the tree relationship to obtain a node tree; the water level early warning index flexible adjustment module performs a flexible conduction analysis of the water level early warning index on the node tree, and updates the water level early warning flexible index.

[0057] In a possible implementation, the scenario-based flexible early warning method under the dynamic optimization of the water level early warning index further includes: setting a flexible conduction rule for the node tree; if the water level early warning index of any node in the node tree is updated, the water level early warning index is conducted layer by layer upward from the current node according to the flexible conduction rule, and the water level early warning index of the node tree is updated.

[0058] In a possible implementation, the scenario-based flexible early warning method under the dynamic optimization of the water level early warning index further includes: obtaining the historical water level data, historical flow velocity data and total allowable flow of each child node; collecting the historical water level data, historical flow velocity data and total allowable flow of all child nodes, and establishing a recovery capacity model; the recovery capacity model analyzes the corresponding remaining recovery capacity indexes of each child node according to the child node monitoring data set, where the remaining recovery capacity index represents the remaining recovery flow that the current child node can accommodate.

[0059] In a possible implementation, the scenario-based flexible early warning method under the dynamic optimization of the water level early warning index further includes: obtaining the initial water level early warning threshold of the parent node; judging whether the current water level of the parent node reaches the initial water level early warning threshold according to the parent node monitoring data set; if it reaches the initial water level early warning threshold, setting a flexible threshold according to the remaining recovery capacity index, and increasing the initial water level early warning threshold according to the flexible threshold, and outputting a water level early warning flexible index.

[0060] In a possible implementation, the scenario-based flexible warning method under the dynamic optimization of the water level warning index further includes: detecting whether a marked scenario is triggered according to the parent node monitoring data set; if the marked scenario is triggered, identifying the influence weight of the triggered scenario type on the flexible threshold, and updating the flexible threshold.

[0061] In a possible implementation, the scenario-based flexible warning method under the dynamic optimization of the water level warning index further includes: marking an independent node, where the independent node is a node without a recycled sub-branch; analyzing the historical water level warning index of the independent node, making a prediction according to the historical water level warning index, and outputting the water level warning flexible index corresponding to the independent node.

[0062] In a possible implementation, the scenario-based flexible warning method under the dynamic optimization of the water level warning index further includes: judging the basin type where the independent node is located, performing upstream and downstream linkage analysis on the historical water level warning index according to the basin type, obtaining the linkage influence weight; updating the water level warning flexible index according to the linkage influence weight.

[0063] The scenario-based flexible warning system under the dynamic optimization of the water level warning index provided by the embodiments of the present invention can execute the scenario-based flexible warning method under the dynamic optimization of the water level warning index provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0064] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, however, any number of different modules can be used and run on the user terminal and / or the server. The included individual units and modules are only divided according to the functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the present invention.

[0065] The above specific implementation manners do not constitute a limitation to the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations and substitutions can be made according to the design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. The scenario-based flexible early warning system under the dynamic optimization of water level early warning indicators is characterized by: The system comprises: A water area structure analysis unit, used to analyze the water area structure of the current area, and identify a parent node and a child node, wherein the parent node is a confluent branch, and the child node is a child branch that recycles the confluent branch corresponding to the parent node; A water level real-time monitoring unit, which is used to integrate a water level sensor device, and to perform real-time water level monitoring on the parent node and the child node respectively according to the water level sensor device, and obtain a parent node monitoring data set and a child node monitoring data set; A subnode evaluation unit, configured to evaluate a remaining recycling capacity indicator corresponding to the subnode according to the subnode monitoring data set; A flexible analysis unit, used to send the remaining recycling capacity indicator corresponding to the child node to the water level warning indicator flexible adjustment module of the parent node, perform water level warning indicator flexibility analysis according to the parent node monitoring data set and the remaining recycling capacity indicator, and obtain the water level warning flexibility indicator; The water level warning signal generating unit is used to monitor the water level of the parent node according to the water level warning flexibility index, and generate a water level warning signal if the water level of the parent node is greater than the water level warning flexibility index.

2. The scenario-based flexible early warning system under dynamic optimization of water level early warning indicators as claimed in claim 1 is characterized in that: The steps performed by the water level warning signal generating unit include: Analyze the water structure of the current area and identify multiple node groups, each of which includes a parent node and at least one child node; Analyze the multiple node groups respectively through the water level warning indicator flexible adjustment module, and output multiple water level warning flexible indicators of the multiple node groups; The water levels of the parent nodes corresponding to the multiple node groups are monitored according to the multiple water level warning flexibility indicators to generate multiple water level warning signals.

3. The scenario-based flexible early warning system under dynamic optimization of water level early warning indicators as claimed in claim 2 is characterized in that: The steps performed by the water level warning signal generating unit include: Determine whether the plurality of node groups have a tree relationship, wherein the tree relationship is a tree relationship in which a parent node of one node group is a child node of another node group; If the plurality of node groups are in a tree-like relationship, connecting the node groups in the tree-like relationship to obtain a node tree; The water level warning indicator flexible adjustment module performs a water level warning indicator flexible conduction analysis on the node tree and updates the water level warning flexible indicator.

4. The scenario-based flexible early warning system under dynamic optimization of water level early warning indicators as claimed in claim 3 is characterized in that: The steps performed by the water level warning signal generating unit include: Setting a flexible conduction rule for the node tree; If the water level warning indicator of any node in the node tree is updated, the water level warning indicator is transmitted upward layer by layer from the current node according to the flexible transmission rule to update the water level warning indicator of the node tree.

5. The scenario-based flexible early warning system under dynamic optimization of water level early warning indicators as claimed in claim 1 is characterized in that: The steps performed by the subnode evaluation unit include: Obtain the historical water level data, historical flow rate data and total flow capacity of each child node; Collect historical water level data, historical flow rate data and total flow that can be accommodated from all subnodes to establish a recycling capacity model; The recycling capacity model analyzes the remaining recycling capacity index corresponding to each sub-node according to the sub-node monitoring data set, wherein the remaining recycling capacity index represents the remaining recycling flow that can be accommodated by the current sub-node.

6. The scenario-based flexible early warning system under dynamic optimization of water level early warning indicators as claimed in claim 1, characterized in that: The steps performed by the flexible analysis unit include: Obtaining the initial water level warning threshold of the parent node; Determining whether the current water level of the parent node reaches the initial water level warning threshold according to the parent node monitoring data set; If the initial water level warning threshold is reached, a flexible threshold is set according to the remaining recovery capacity indicator, the initial water level warning threshold is increased according to the flexible threshold, and the water level warning flexible indicator is output.

7. The scenario-based flexible early warning system under dynamic optimization of water level early warning indicators as claimed in claim 6, characterized in that: The steps performed by the flexible analysis unit include: Detecting whether a marked scene is triggered according to the parent node monitoring data set; If the identified scene is triggered, the influence weight of the triggered scene type on the flexible threshold is identified, and the flexible threshold is updated.

8. The scenario-based flexible early warning system under dynamic optimization of water level early warning indicators as claimed in claim 1, characterized in that: The steps performed by the water area structure analysis unit also include: Identify an independent node, where the independent node is a node without a recycling sub-branch; Analyze the historical water level warning indicators of the independent node, make predictions based on the historical water level warning indicators, and output the water level warning flexibility indicators corresponding to the independent node.

9. The scenario-based flexible early warning system under dynamic optimization of water level early warning indicators as claimed in claim 8, characterized in that: The steps performed by the flexible analysis unit also include: Determine the type of the watershed where the independent node is located, perform upstream and downstream linkage analysis on the historical water level warning indicator according to the watershed type, and obtain linkage influence weight; The water level warning flexibility indicator is updated according to the linkage influence weight.

10. The scenario-based flexible early warning method under dynamic optimization of water level early warning indicators is characterized by: The method is applied to the scenario-based flexible early warning system under the dynamic optimization of the water level early warning index according to any one of claims 1 to 9, and the method comprises: Analyze the water structure of the current area and identify the parent node and the child node, wherein the parent node is a confluent branch and the child node is a child branch that recycles the confluent branch corresponding to the parent node; An integrated water level sensor device is used to monitor the water levels of the parent node and the child node in real time, and obtain a parent node monitoring data set and a child node monitoring data set; Evaluate the remaining recycling capacity indicator corresponding to the subnode according to the subnode monitoring data set; Sending the remaining recycling capacity indicator corresponding to the child node to the water level warning indicator flexible adjustment module of the parent node, performing water level warning indicator flexibility analysis according to the parent node monitoring data set and the remaining recycling capacity indicator, and obtaining the water level warning flexibility indicator; The water level of the parent node is monitored according to the water level warning flexibility index, and if the water level of the parent node is greater than the water level warning flexibility index, a water level warning signal is generated.

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