Flood and secondary disaster early warning method and system based on space-space-ground three-dimensional monitoring

Abstract

The invention discloses a flood and secondary disaster early warning method and system based on space-air-ground three-dimensional monitoring, and relates to the technical field of space-air-ground detection, and the method comprises the steps: obtaining pre-rainfall data, water vapor content data, actual rainfall data and main stream flood peak flow data; inputting the pre-rainfall data, the water vapor content data, the actual rainfall data and the main stream flood peak flow data into an algorithm model to generate flood stroke and evolution data; and early warning information and an emergency scheme are sent according to the flood journey and evolution data, and flood and secondary disaster early warning is realized. Through cooperation of air-based monitoring, space-based monitoring and foundation monitoring, accurate data of flood formation and evolution are calculated, and then emergency response is started when continuous heavy rainfall occurs or disastrous flood is predicted; by carrying out reservoir pre-discharge scheduling in advance, the river water level is reduced, the reservoir capacity is vacated, and production and life losses caused by flood disasters are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of air-space-ground detection, and particularly to a method and system for flood and secondary disaster warning based on air-space-ground three-dimensional monitoring. Background Art

[0002] In recent years, global climate change has become increasingly significant, and extreme weather events have occurred frequently. Especially in summer, persistent heavy rainfall is common. Such extreme rainfall not only causes natural disasters such as urban waterlogging, mountain torrents, and debris flows, but also causes serious casualties and property losses. The economic losses caused by natural disasters triggered by heavy rain globally each year reach up to tens of billions of US dollars. Therefore, improving the warning ability of rainstorm floods is an urgent task. Traditional flood warning systems mainly rely on rainfall monitoring at meteorological stations and simple hydrological models, and have inherent defects such as short lead time and low accuracy. Especially for small mountainous basins, due to complex terrain and short concentration time, it is difficult for conventional ground monitoring networks to capture the formation process of sudden floods in a timely manner. For example, in steep mountainous areas, heavy rainfall may form destructive mountain torrents within 1-2 hours, while traditional warning methods often fail to provide sufficient warning time.

[0003] Modern hydrometeorological theory shows that accurate flood forecasting requires comprehensive consideration of multiple factors such as rainfall intensity, terrain characteristics, soil conditions, and vegetation cover. However, the current monitoring means still have obvious deficiencies in spatial resolution and time continuity, resulting in poor quality of input data for flood forecasting models and affecting the forecasting effect. Especially in complex terrain areas, existing monitoring networks often have blind spots and cannot comprehensively grasp the spatial distribution characteristics of rainfall. In addition, with the acceleration of the urbanization process, the area of impervious ground has increased, accelerating the formation speed of stormwater runoff. Traditional warning systems are difficult to adapt to this change. In the context of climate change, the frequency and intensity of extreme rainfall events are both on the rise, which puts forward higher requirements for improving the adaptability of warning systems. Summary of the Invention

[0004] In view of the above problems, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is how to provide a method and system for flood and secondary disaster warning based on air-space-ground three-dimensional monitoring, and a method for solving the problems of extending the lead time, forecasting period, and accuracy of floods.

[0006] To solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides a method for monitoring floods and secondary disaster warnings based on space-air-ground three-dimensional monitoring, which includes obtaining predicted rainfall data, water vapor content data, actual rainfall data, and main stream peak flow data; inputting the predicted rainfall data, the water vapor content data, the actual rainfall data, and the main stream peak flow data into an algorithm model to generate flood travel and evolution data; and sending warning information and emergency plans according to the flood travel and evolution data to achieve flood and secondary disaster warnings.

[0008] As a preferred solution of the method for monitoring floods and secondary disaster warnings based on space-air-ground three-dimensional monitoring according to the present invention, wherein: the obtaining of the predicted rainfall data, the water vapor content data, the actual rainfall data, and the main stream peak flow data includes: obtaining the predicted rainfall data of 48 hours over the region through a meteorological satellite; obtaining the water vapor content data within the range of 0-2 km over the region through a rain gauge radar; calculating the cloud water content data and the predicted precipitation data within the region 1-3 hours before rainfall according to the water vapor content data; obtaining the actual rainfall data per unit time through a rain gauge station at a minute-level frequency, wherein the measurement accuracy of the rain gauge station is 0.1 mm; obtaining the main stream peak flow data through a hydrological station with a density of 2.5 square kilometers per station, wherein the hydrological station is set at the confluence of a rain-flood ditch and the main stream, and the monitoring frequency of the hydrological station is at a second-level.

[0009] As a preferred solution of the method for monitoring floods and secondary disaster warnings based on space-air-ground three-dimensional monitoring according to the present invention, wherein: the generating of the flood travel and evolution data includes space-based monitoring, space-based monitoring, and ground-based monitoring.

[0010] As a preferred solution of the method for monitoring floods and secondary disaster warnings based on space-air-ground three-dimensional monitoring according to the present invention, wherein: the space-based monitoring includes the following steps: inputting the predicted rainfall data into the algorithm model to analyze the rainfall trend in the next 48 hours; inputting the water vapor content data, the cloud water content data, and the predicted precipitation data into the algorithm model to establish a precipitation prediction model 1-3 hours before rainfall; establishing a macroscopic rainfall distribution map based on the predicted rainfall data and dividing the rainfall influence area; establishing a microscopic rainfall intensity map based on the water vapor content data, the cloud water content data, and the predicted precipitation data to determine the local rainfall center; and performing superposition analysis on the macroscopic rainfall distribution map and the microscopic rainfall intensity map to generate rainfall prediction data.

[0011] As a preferred embodiment of the method for monitoring floods and secondary disaster warnings based on space-air-ground three-dimensional monitoring according to the present invention, the space-based monitoring includes the following steps: inputting the actual rainfall data into the algorithm model, establishing a real-time rainfall distribution map based on the actual rainfall data, and analyzing the spatio-temporal variation characteristics of rainfall intensity; superimposing the real-time rainfall distribution map with the terrain data to calculate and form the critical rainfall threshold for surface runoff; when the rainfall monitored by the rain gauge station is greater than the critical rainfall threshold, starting the surface runoff calculation module; the surface runoff calculation module calculates the runoff yield based on the actual rainfall data, and calculates the confluence velocity in combination with the underlying surface characteristics to generate surface runoff data.

[0012] As a preferred embodiment of the method for monitoring floods and secondary disaster warnings based on space-air-ground three-dimensional monitoring according to the present invention, the ground-based monitoring includes the following steps: inputting the main stream peak flow data into the algorithm model, establishing a real-time water regime monitoring network for the river network in the basin based on the main stream peak flow data, and analyzing the water volume accumulation in the river channel; performing correlation analysis on the data of the real-time water regime monitoring network and the surface runoff data to establish a runoff-confluence coupling model; calculating the peak flow, peak arrival time, and flood propagation path of rivers at all levels in the basin through the runoff-confluence coupling model; dynamically correcting the calculation results of the runoff-confluence coupling model based on the real-time monitoring data of the hydrological station.

[0013] As a preferred embodiment of the method for monitoring floods and secondary disaster warnings based on space-air-ground three-dimensional monitoring according to the present invention, the warning information includes flood warning information, mountain flood warning information, and waterlogging risk warning information; the recipients of the warning information include households in the basin and the flood control headquarters.

[0014] In a second aspect, to further solve the security problems existing in space-air-ground detection, the embodiments of the present invention provide a system for monitoring floods and secondary disaster warnings based on space-air-ground three-dimensional monitoring, which includes: a data acquisition module for obtaining pre-rainfall data using a meteorological satellite, obtaining water vapor content data using a rain gauge radar, obtaining actual rainfall data using a rain gauge station, and obtaining main stream peak flow data using a hydrological station; a disaster prediction module for inputting the pre-rainfall data, water vapor content data, actual rainfall data, and main stream peak flow data into an algorithm model to generate flood travel and evolution data; a disaster warning module for sending warning information and emergency plans according to the flood travel and evolution data.

[0015] In a third aspect, the embodiments of the present invention provide a computer device, including a memory and a processor, where the memory stores a computer program, and: when the computer program is executed by the processor, any step of the method for monitoring floods and secondary disaster warnings based on space-air-ground three-dimensional monitoring as described in the first aspect of the present invention is implemented.

[0016] Fourthly, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, wherein: when the computer program is executed by a processor, any step of the method for monitoring floods and secondary disaster situations and early warning based on space-air-ground three-dimensional monitoring as described in the first aspect of the present invention is implemented.

[0017] Advantages of the present invention: The present invention proposes a method and system for monitoring floods and secondary disaster situations and early warning based on space-air-ground three-dimensional monitoring. Through the cooperation of space-based monitoring, space-based monitoring, and ground-based monitoring, three lines of defense are formed and accurate measurements are carried out, and accurate data on the formation and evolution of floods are calculated. Furthermore, when continuous heavy rainfall occurs or it is predicted that large catastrophic floods may form, the flood control headquarters immediately initiates an emergency response; by pre-discharging and dispatching reservoirs, lowering the river water level, and vacating the reservoir storage capacity in advance according to the early warning obtained, the losses caused by flood disasters to production and life are reduced. Description of the Drawings

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings. Among them:

[0019] Figure 1 It is the overall flowchart of the method for monitoring floods and secondary disaster situations and early warning based on space-air-ground three-dimensional monitoring in Embodiment 1.

[0020] Figure 2 It is the structural schematic diagram of the computer device in Embodiment 3. Detailed Embodiments

[0021] In order to make the above-mentioned objects, features, and advantages of the present invention more obvious and understandable, the following will make a detailed description of the specific embodiments of the present invention in conjunction with the drawings of the specification.

[0022] Many specific details are set forth in the following description in order to fully understand the present invention, but the present invention can also be implemented in other ways different from those described herein. Those skilled in the art can make similar generalizations without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0023] Secondly, the so-called "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that can be included in at least one implementation manner of the present invention. The "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that mutually excludes other embodiments.

[0024] Example 1

[0025] Reference Figure 1 , which is the first embodiment of the present invention. This embodiment provides a method for flood and secondary disaster warning based on space-air-ground three-dimensional monitoring.

[0026] The existing disaster warning methods mainly have the following problems: First, there are still obvious deficiencies in the spatial resolution and temporal continuity of the current monitoring means, resulting in poor quality of the input data of the flood forecasting model and affecting the forecasting effect. Especially in complex terrain areas, there are often blind spots in the existing monitoring network, and it is impossible to comprehensively grasp the spatial distribution characteristics of rainfall; in addition, with the acceleration of the urbanization process, the area of impervious ground has increased, accelerating the formation speed of storm runoff. Traditional warning systems are difficult to adapt to this change. Under the background of climate change, the frequency and intensity of extreme rainfall events are both on the rise, which puts higher requirements on improving the adaptability of the warning system.

[0027] This application provides a solution that can effectively solve the above-mentioned problems. Next, multiple embodiments will be combined to elaborate in detail how to implement the method for flood and secondary disaster warning based on space-air-ground three-dimensional monitoring.

[0028] Figure 1 The overall flowchart of the method for flood and secondary disaster warning based on space-air-ground three-dimensional monitoring is shown, including:

[0029] S1: Obtain pre-rainfall data, water vapor content data, actual rainfall data, and main-stream peak flow data.

[0030] Preferably, obtaining pre-rainfall data, water vapor content data, actual rainfall data, and main-stream peak flow data includes: obtaining 48-hour pre-rainfall data over the region through a meteorological satellite.

[0031] Obtaining water vapor content data within a range of 0 - 2 km above the region through a rain gauge radar.

[0032] Calculating the cloud water content data and pre-precipitation data within the region 1 - 3 hours before rainfall according to the water vapor content data.

[0033] Obtaining actual rainfall data per unit time through a rain gauge station at a minute-level frequency, where the measurement accuracy of the rain gauge station is 0.1 mm.

[0034] Obtaining main-stream peak flow data through a hydrological station with a density of 2.5 square kilometers per station, where the hydrological station is set at the confluence of the rain-flood ditch and the main stream, and the monitoring frequency of the hydrological station is at a second-level.

[0035] S2: Input the pre-rainfall data, water vapor content data, actual rainfall data, and main-stream peak flow data into an algorithm model to generate flood formation and evolution data.

[0036] Preferably, generating flood travel and evolution data includes airborne monitoring, space-based monitoring, and ground-based monitoring. After the Emergency Response Department calculates the accurate data of the corresponding flood travel and evolution based on the relevant data of airborne monitoring, space-based monitoring, and ground-based monitoring, early warning information and emergency plans are sent to the households and flood control headquarters within the basin.

[0037] Specifically, airborne monitoring includes the following steps: Input the pre-rainfall data into the algorithm model to analyze the rainfall trend in the next 48 hours.

[0038] Input the water vapor content data, cloud water content data, and pre-rainfall data into the algorithm model to establish a precipitation prediction model for 1 - 3 hours before rainfall.

[0039] Based on the pre-rainfall data, establish a macroscopic rainfall distribution map and divide the rainfall - affected areas.

[0040] Based on the water vapor content data, cloud water content data, and pre-rainfall data, establish a microscopic rainfall intensity map to determine the local rainfall centers.

[0041] Overlay and analyze the macroscopic rainfall distribution map and the microscopic rainfall intensity map to generate rainfall prediction data, where the rainfall prediction data is used to guide the key monitoring areas of rain gauges and hydrological stations.

[0042] Preferably, the present invention overlays and analyzes the macroscopic rainfall distribution map and the microscopic rainfall intensity map. The 48 - hour pre-rainfall data obtained by meteorological satellites provides a macroscopic perspective, while the water vapor content data within the range of 0 - 2 km obtained by rain - measuring radars provides microscopic accuracy. This combination can overcome the limitations of a single data source and improve the spatial accuracy of rainfall prediction.

[0043] Specifically, space-based monitoring includes the following steps: Input the actual rainfall data into the algorithm model, establish a real-time rainfall distribution map based on the actual rainfall data, and analyze the spatio-temporal variation characteristics of rainfall intensity.

[0044] Overlay the real-time rainfall distribution map with the terrain data and calculate the critical rainfall threshold for forming surface runoff.

[0045] When the rainfall measured by the rain gauge is greater than the critical rainfall threshold, start the surface runoff calculation module.

[0046] The surface runoff calculation module calculates the runoff yield based on the actual rainfall data, combines the underlying surface characteristics to calculate the confluence velocity, and generates surface runoff data, where the surface runoff data is used to provide a basis for predicting the monitoring focus of hydrological stations.

[0047] Preferably, the present invention introduces a critical rainfall threshold and combines it with topographic data. By establishing an overlay analysis of the real-time rainfall distribution map and topographic data, the formation conditions of surface runoff can be judged more accurately, solving the problem that the influence of topography is often ignored in traditional monitoring and improving the accuracy of runoff prediction.

[0048] Specifically, the ground-based monitoring includes the following steps: inputting the main-stream peak flow data into an algorithm model, establishing a real-time water regime monitoring network for the river network in the basin based on the main-stream peak flow data, and analyzing the water volume accumulation in the river channel.

[0049] Carry out a correlation analysis on the data of the real-time water regime monitoring network and the surface runoff data to establish a runoff-confluence coupling model.

[0050] Calculate the peak flow, peak arrival time, and flood propagation path of rivers at all levels in the basin through the runoff-confluence coupling model.

[0051] Dynamically correct the calculation results of the runoff-confluence coupling model based on the real-time monitoring data of the hydrological station to improve the accuracy of flood routing prediction.

[0052] Preferably, the present invention proposes a runoff-confluence coupling model. By arranging hydrological stations at the confluence of rain-flood ditches and the main stream and adopting a monitoring frequency of seconds, the monitoring accuracy is significantly improved. The design of this high-density and high-frequency monitoring network, combined with the dynamic correction mechanism of the runoff-confluence coupling model, can achieve precise tracking of the flood routing process and solve the problem of monitoring blind spots caused by insufficient station density in traditional monitoring.

[0053] S3: Send early warning information and emergency plans according to the flood journey and evolution data to achieve flood and secondary disaster warning.

[0054] Specifically, sending early warning information and emergency plans according to the flood journey and evolution data includes the following steps: combining rainfall prediction data, surface runoff data, peak flow of rivers at all levels in the basin, peak arrival time, and flood propagation path, establishing an evaluation standard based on the historical flood database, and quantitatively calculating the flood risk levels of different regions.

[0055] Determine the spatial scope and warning level of the warning area according to the quantitative calculation results of the flood risk levels.

[0056] Combining the regulation ability of flood control projects, establish an emergency response plan by region and time, and generate early warning information based on the emergency response plan.

[0057] Preferably, the early warning information includes flood early warning information, mountain flood early warning information, and risk warning information of waterlogging.

[0058] Furthermore, the recipients of the early warning information include households in the basin and the flood control headquarters.

[0059] Specifically, sending early warning information and emergency plans includes formulating emergency plans, executing emergency responses, and adjusting emergency measures.

[0060] Specifically, formulating an emergency plan includes: determining a reservoir pre-discharge operation plan based on flood early warning information, including pre-discharge time, pre-discharge flow rate, and pre-discharge target water level.

[0061] Dividing the evacuation routes of people within the mountain flood impact area based on mountain flood early warning information, and clarifying the evacuation order and evacuation time limit of people.

[0062] Formulating a drainage pumping station operation plan based on the risk early warning information of waterlogging, and clarifying the drainage area, drainage capacity, and drainage priority.

[0063] Specifically, executing an emergency response includes: the emergency response department sending early warning information and emergency plans to the households within the basin, including evacuation routes, disaster avoidance sites, and precautions.

[0064] The emergency response department sending early warning information and emergency plans to the flood control headquarters, including the time node for starting the emergency response, the specific flood control operation plan, and the personnel and material allocation plan.

[0065] Lowering the river water level according to the reservoir pre-discharge operation plan, and monitoring the pre-discharge effect through a hydrological station.

[0066] Carrying out flood prevention work according to the drainage pumping station operation plan to reduce the risk of waterlogging.

[0067] Specifically, adjusting emergency measures includes the following steps: real-time monitoring of the water regime changes in the early warning area through a hydrological station to obtain the latest main stream peak flow data.

[0068] Inputting the main stream peak flow data into an algorithm model to update the flood evolution prediction result.

[0069] According to the updated flood evolution prediction result, adjusting the release strategy of early warning information, including the early warning area and early warning level.

[0070] Evaluating the effect of emergency response measures based on the monitoring data of the hydrological station, dynamically optimizing the emergency measures, and improving the pertinence and effectiveness of the emergency measures.

[0071] Preferably, the present invention establishes an emergency response plan by region and time, and dynamically optimizes it according to real-time monitoring data. This dynamic adjustment mechanism based on multi-dimensional data can improve the pertinence of emergency measures. Among them, through the coordinated cooperation of the reservoir pre-discharge operation plan and the drainage pumping station operation plan, the flood risk can be effectively reduced.

[0072] In summary, the present invention proposes a method and system for flood and secondary disaster warning based on space-air-ground three-dimensional monitoring. Through the cooperation of space-based monitoring, space-based monitoring, and ground-based monitoring, three lines of defense are formed and accurate measurements are carried out to calculate accurate data on the formation and evolution of floods. Furthermore, when continuous heavy rainfall occurs or it is predicted that large catastrophic floods may form, the flood control headquarters immediately initiates an emergency response; by pre-discharging and scheduling reservoirs in advance, reducing the river water level, and vacating the reservoir storage capacity according to the early warning, the losses caused by flood disasters to production and life are reduced.

[0073] Embodiment 2 is an embodiment of the present invention, which provides a space-air-ground three-dimensional monitoring flood and secondary disaster warning system, including: a data acquisition module for obtaining pre-rainfall data using a meteorological satellite, obtaining water vapor content data using a rain gauge radar, obtaining actual rainfall data using a rain gauge station, and obtaining main stream peak flow data using a hydrological station; a disaster prediction module for inputting the pre-rainfall data, water vapor content data, actual rainfall data, and main stream peak flow data into an algorithm model to generate flood formation and evolution data; a disaster warning module for sending warning information and emergency plans according to the flood formation and evolution data.

[0074] Embodiment 3 is an embodiment of the present invention, which is different from the previous embodiment in that:

[0075] As Figure 2 shown, if the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. And the aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0076] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definable sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or used in combination with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0077] More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, a computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing it as appropriate, and then storing it in a computer memory.

[0078] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having suitable combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0079] Embodiment 4, an embodiment of the present invention, provides a method for flood and secondary disaster situation early warning based on space-air-ground three-dimensional monitoring. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0080] In this example, by simulating a tributary in the Yangtze River Basin, rainfall prediction data and water vapor content data for a certain period of time were obtained, and the cloud water content and predicted precipitation were calculated through a professional algorithm model. Subsequently, each monitoring station began to enter the intensive observation state; during the experiment, by generating a macroscopic rainfall distribution map and a microscopic rainfall intensity map and performing an overlay analysis of the two maps, three local heavy rainfall centers were successfully identified. Based on this information, early warning messages and emergency plans were sent to the monitoring stations in the relevant areas, and the performance of the present invention was analyzed from two aspects: comparison with the prior art and different rainfall conditions. Table 1 shows the data comparison table of different monitoring methods.

[0081] Table 1 Data comparison table of different monitoring methods

[0082] Monitoring method Early warning lead time (h) Rainfall prediction error (%) Peak flood flow prediction error (%) Traditional single monitoring 2.5 35.6 42.3 Dual-source monitoring 4.2 28.4 33.1 Method of the present invention 6.8 12.5 15.6

[0083] As can be seen from Table 1, through the systematic analysis of the test data, the method of the present invention has significant advantages compared with the traditional monitoring methods. In terms of the early warning time advance, the present invention can achieve an early warning time advance of 6.8 hours, which is a 172% increase compared with 2.5 hours of the traditional single monitoring method, thanks to the precise capture of meteorological elements by the space-based monitoring system and the fusion analysis of multi-source data; in terms of prediction accuracy, the rainfall prediction error of the present invention is only 12.5%, and the flood peak flow prediction error is 15.6%, which has better performance compared with the prior art. This significant improvement is mainly due to the synergistic effect of the three-dimensional monitoring system.

[0084] Table 2 shows the system performance comparison table under different rainfall intensity conditions.

[0085] Table 2 System performance comparison table under different rainfall intensity conditions

[0086] Rainfall intensity (mm / h) False alarm rate of traditional method (%) False alarm rate of the present invention (%) 0-10 12.3 3.2 10-25 10.5 2.8 25-50 8.6 2.3

[0087] Through the comparison of the performance data of the present invention and the prior art under different rainfall intensities, it can be seen that the present invention forms three lines of defense through the cooperation of space-based monitoring, space-based monitoring and ground-based monitoring, which can effectively reduce the false alarm rate and reflect the reliability and stability of the present invention under extreme weather conditions.

[0088] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A method for monitoring floods and secondary disasters based on air-ground-space stereoscopic monitoring, characterized in that: include: Obtain predicted rainfall data, water vapor content data, actual rainfall data, and mainstream flood peak flow data; Inputting the predicted rainfall data, the water vapor content data, the actual rainfall data and the mainstream flood peak flow data into an algorithm model to generate flood travel and evolution data; According to the flood course and evolution data, early warning information and emergency plans are sent to achieve flood and secondary disaster warning.

2. The method for flood and waterlogging monitoring and secondary disaster early warning based on air-ground-space stereoscopic monitoring as claimed in claim 1, characterized in that: The acquisition of predicted rainfall data, water vapor content data, actual rainfall data and mainstream flood peak flow data includes: Obtain 48-hour forecast rainfall data over the region through meteorological satellites; The water vapor content data within 0-2km above the region is obtained through the rain radar; Calculate the cloud moisture content data and the predicted precipitation data in the region 1-3 hours before rainfall based on the water vapor content data; The actual rainfall data per unit time is obtained at a frequency of minutes through a rain gauge station, wherein the measurement accuracy of the rain gauge station is 0.1 mm; The peak flow data of the main stream are obtained through hydrological stations with a density of 2.5 square kilometers per station. The hydrological stations are set at the intersection of the rainwater ditch and the main stream, and the monitoring frequency of the hydrological stations is in seconds.

3. The method for flood and waterlogging monitoring and secondary disaster early warning based on air-ground-space stereoscopic monitoring as claimed in claim 2, characterized in that: The generation of flood course and evolution data includes air-based monitoring, space-based monitoring and ground-based monitoring.

4. The method for flood and waterlogging and secondary disaster early warning based on air-ground-space stereoscopic monitoring as claimed in claim 3, characterized in that: The air-based monitoring comprises the following steps: Input the predicted rainfall data into the algorithm model to analyze the rainfall trend in the next 48 hours; Input the water vapor content data, the cloud moisture content data and the predicted precipitation data into the algorithm model to establish a precipitation prediction model 1-3 hours before rainfall; Establishing a macro rainfall distribution map based on the predicted rainfall data and dividing rainfall impact areas; Establishing a microscopic rainfall intensity map based on the water vapor content data, the cloud moisture content data and the predicted precipitation data to determine a local rainfall center; The macro-rainfall distribution map and the micro-rainfall intensity map are superimposed and analyzed to generate rainfall prediction data.

5. The method for flood and waterlogging and secondary disaster early warning based on air-ground-space stereoscopic monitoring as claimed in claim 4, characterized in that: The space-based monitoring comprises the following steps: Inputting the actual rainfall data into the algorithm model, establishing a real-time rainfall distribution map based on the actual rainfall data, and analyzing the spatiotemporal variation characteristics of rainfall intensity; The real-time rainfall distribution map is superimposed with the terrain data to calculate the critical rainfall threshold for forming surface runoff; When the rainfall monitored by the rain gauge station is greater than the critical rainfall threshold, starting the surface runoff calculation module; The surface runoff calculation module calculates the runoff based on the actual rainfall data, and calculates the convergence velocity in combination with the underlying surface characteristics to generate surface runoff data.

6. The method for flood and waterlogging and secondary disaster early warning based on air-ground-space stereoscopic monitoring as claimed in claim 5, characterized in that: The foundation monitoring comprises the following steps: Input the peak flow data of the main stream into the algorithm model, establish a real-time water regime monitoring network for the river network in the basin based on the peak flow data of the main stream, and analyze the water accumulation in the river channel; Correlation analysis is performed on the data of the real-time water regime monitoring network and the surface runoff data to establish a runoff coupling model; The peak flow, peak arrival time and flood propagation path of rivers at all levels in the basin are calculated by the flow generation and confluence coupling model; The calculation results of the runoff coupling model are dynamically corrected based on the real-time monitoring data of the hydrological station.

7. The method for flood and waterlogging and secondary disaster early warning based on air-ground-space stereoscopic monitoring as claimed in claim 6, characterized in that: The warning information includes flood warning information, mountain torrent warning information and waterlogging risk warning information; The recipients of the warning information include residents in the basin and flood control headquarters.

8. A system for monitoring floods and secondary disasters based on air-ground-space stereoscopic monitoring, based on the method for monitoring floods and secondary disasters based on air-ground-space stereoscopic monitoring as well as the method for early warning of secondary disasters according to any one of claims 1 to 7, characterized in that: include, The data acquisition module is used to obtain the predicted rainfall data using the meteorological satellite, obtain the water vapor content data using the rain measuring radar, obtain the actual rainfall data using the rain gauge station, and obtain the mainstream flood peak flow data using the hydrological station; The disaster prediction module is used to input the predicted rainfall data, water vapor content data, actual rainfall data and mainstream flood peak flow data into the algorithm model to generate flood travel and evolution data; The disaster warning module is used to send warning information and emergency plans based on flood travel and evolution data.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for flood monitoring and secondary disaster warning based on air-space-ground stereoscopic monitoring are implemented as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for flood monitoring and secondary disaster warning based on air-space-ground stereoscopic monitoring are implemented as described in any one of claims 1 to 7.

Images