Disaster early warning data analysis method and system

Abstract

The invention provides a disaster early warning data analysis method and system, and the method comprises the steps: monitoring hydrological data through an automatic rainfall monitoring meter, and constructing a regional rainfall grid map according to the hydrological data; according to the regional rainfall grid map, determining a point location of which the rainfall exceeds a set rainfall threshold value as a first flood disaster early warning point; all the first flood disaster early warning points are traversed, data of the first flood disaster early warning points are analyzed, and if it is determined that a second flood disaster early warning point exists in the first flood disaster early warning points, first-level flood disaster early warning is carried out within a first preset range around the second flood disaster early warning point. The method comprises the following steps: screening out a first flood disaster early warning point through a rainfall grid map of a region, carrying out secondary screening on the first flood disaster early warning point, and carrying out first-level flood disaster early warning in a first preset range around a second flood disaster early warning point if it is determined that the second flood disaster early warning point exists. The early warning accuracy can be improved.

Description

Technical Field

[0001] The present invention relates to the field of disaster warning technology, and in particular to a disaster warning data analysis method and system. Background Art

[0002] China experienced four large-scale floods in the 20th century, while small-scale floods occurred almost every year. About two-thirds of the country was affected by floods of different types and severity. Floods can cause a reduction in grain production, lead to huge economic losses, damage land resources and the ecological environment, and have a multi-faceted impact on the social economy and the environment. Floods can be caused by many reasons. Among the various causes of disasters, heavy rain is the most common and most threatening. At the same time, heavy rain itself is also one of the most serious meteorological disasters. Heavy rain is often accompanied by thunder and lightning and strong winds, which often lead to waterlogging on flat ground, overflowing rivers, destruction of farmland, collapse of houses, etc.

[0003] With the continuous advancement of urbanization, urban areas are expanding, population density is increasing, and urban infrastructure is becoming increasingly complex, which increases the risk of urban flood disasters. In order to effectively deal with urban flood disasters, the establishment of an early warning and dispatching system is crucial. Traditional urban flood disaster early warning and dispatching methods mainly rely on manual experience judgment and simple model prediction. These methods are incapable of dealing with complex and changeable urban flood disasters.

[0004] Existing early warning dispatch methods are usually unable to effectively obtain and process real-time data. In the forecast and early warning service system for rainstorm and flood disasters, some foreign countries use Geographic Information Technology (GIS) technology to assist in predicting flood hazards. However, this method does not take into account the complexity of basin flood formation. Since basin flood formation is very complex, the relationship between rainfall and runoff is usually dynamic and nonlinear, and relying solely on GIS forecast results still lacks credibility in some aspects. Summary of the invention

[0005] The present application provides a disaster warning data analysis method and system for improving the prediction accuracy of flood disasters.

[0006] In view of this, the first aspect of the present application provides a disaster warning data analysis method, which includes: monitoring hydrological data through an automatic rainfall monitoring meter, and constructing a regional rainfall grid map based on the hydrological data; determining, based on the regional rainfall grid map, a point where rainfall exceeds a set rainfall threshold as a first flood disaster warning point; traversing all of the first flood disaster warning points, and analyzing the data of the first flood disaster warning points. If it is determined that there is a second flood disaster warning point among the first flood disaster warning points, a first-level flood disaster warning is issued within a first preset range around the second flood disaster warning point.

[0007] The rainfall grid map is constructed based on the rainfall data monitored by the automatic rainfall monitoring meter. If the warning reminder is issued only when it is determined to be the first flood disaster warning point, it is easy to make a misjudgment, the warning range is too large, and the credibility is low. Therefore, the first flood disaster warning point is first screened out through the regional rainfall grid map, and then the first flood disaster warning point is screened again. If it is determined that there is a second flood disaster warning point, the first level flood disaster warning is issued within the first preset range around the second flood disaster warning point. This can improve the accuracy of the warning.

[0008] In combination with the first aspect, in a possible implementation, constructing a regional rainfall grid map according to the hydrological data specifically includes: obtaining the rainfall q1, q2, ..., q n , where n≤N, N is the total number of automatic rain gauges; the rainfall q1, q2, ..., q n Fitting the surface, constructing the surface equation of the grid map is: q(x,y)=a1x 2 +a2y 2 +a3xy+a4x+a5y+a6, where x is the horizontal coordinate of the point to be measured, y is the vertical coordinate of the point to be measured, q is the rainfall at the point to be measured, and a1, a2, a3, a4, a5, a6 are constants. This method can be used to construct a rainfall grid map.

[0009] In combination with the first aspect, in a possible implementation, the determining that there is a second flood disaster warning point in the first flood disaster warning point specifically includes: obtaining the surface properties of the first flood disaster warning point, wherein the surface properties include seepage areas and impermeable areas; if it is determined that the surface properties of the first flood disaster warning point are seepage areas, then determining the water flow rate of the seepage area: C1 = (i-j) × Δt-M; wherein C1 is the amount of water accumulated in the seepage area (mm), i is the rainfall intensity (mm / h), j is the surface permeability of the seepage area (mm / h), Δt is the rainfall duration, and M is the natural evaporation of the accumulated water (mm); if it is determined that the amount of water accumulated C1 at the first flood disaster warning point exceeds the historical warning line of the area where the first flood disaster warning point is located, determining the first flood disaster warning point as the second flood disaster warning point. In this way, when the first flood disaster warning point is a seepage area, it can be determined whether it is the second flood disaster warning point.

[0010] In combination with the first aspect, in a possible implementation, the method further includes: if it is determined that the surface property of the first flood disaster warning point is a non-seepage area, then determining the water flow rate of the non-seepage area to be: C2 = i × Δt-M; if it is determined that the water flow rate C2 of the first flood disaster warning point exceeds the historical warning line of the area where the first flood disaster warning point is located, determining the first flood disaster warning point to be a second flood disaster warning point. In this way, when the first flood disaster warning point is a non-seepage area, it can be determined whether it is a second flood disaster warning point.

[0011] In combination with the first aspect, in a possible implementation method, the method also includes: traversing all second flood disaster warning points, and determining whether there is a third flood disaster warning point among the second flood disaster warning points, wherein there is at least one first flood disaster warning point within the second preset range of the third flood disaster warning point; if it is determined that the rainfall intensity of the third flood disaster warning point is greater than the first preset rainfall intensity threshold, then it is determined that the third flood disaster warning point has a risk of dam breach, and a second-level flood disaster warning is issued within the first preset range around the third flood disaster warning point.

[0012] When there is at least one first flood disaster warning point within the second preset range of the second flood disaster warning point, it can be defined as a third flood disaster warning point. If the third flood disaster warning point exists in the first flood disaster warning point around it and there is a risk of dike breach, then it is necessary to focus on the third flood disaster warning point. If the third flood disaster warning point has a high continuous rainfall intensity and the second flood disaster warning point has a dike breach risk, then a second-level flood disaster warning will be issued within the first preset range around the third flood disaster warning point. This is used for key warnings.

[0013] In combination with the first aspect, in a possible implementation, the method further includes: when it is determined that there is a risk of levee breach at the third flood disaster warning point, determining the lowest point of the terrain within the second preset range of the third flood disaster warning point, and starting from the lowest point of the terrain, predicting the possible path of the flood in the direction of decreasing terrain. In this way, the risk that the flood may pass through can be simply predicted.

[0014] In combination with the first aspect, in a possible implementation, after constructing the possible path of the flood in the direction of decreasing terrain, the method further includes a step of dynamically adjusting the path: in the possible path, obtaining the current grid node (x e , y e ), the previous grid node (x e―1 , y e―1 ), and the second grid node (x e+1 , y e+1 ), the third grid node (x e+2 , y e+2 ); calculating m1 = (x e+1 ― x e ) / (x e ― x e―1 ), m2 = (y e+1 ― y e ) / (y e ― y e―1 ); if m1 > m2, then dynamically adjusting the third grid node (x e+2 + Δx, y e+2 ); if m1 < m2, then dynamically adjusting the third grid node (x e+2 , y e+2 + Δy), where Δx and Δy are preset step values. In fact, the direction of flood flow has a lot of uncertainties, but it will be affected by inertia and gravitational potential energy. When m1 > m2, it can be predicted that the flood inertia tends to the x-axis direction, and then one step length can be adjusted to the x-axis at the next grid node. If m1 < m2, it can be predicted that the flood inertia tends to the y-axis direction, and then one step length can be adjusted to the y-axis at the next grid node. In this way, the accuracy of predicting the flood path can be improved to a certain extent.

[0015] In combination with the first aspect, in a possible implementation, the method further includes: issuing a third-level flood disaster warning for the key nodes on the path and prompting the flood arrival time: where the distance between the key node and the starting point: (X1, Y1) is the grid coordinate of the starting point, (X end , Y end) is the grid coordinate of the key node; the predicted arrival time t = H / v, where v is the predicted water flow velocity.

[0016] The actual distance between the key node and the starting point is generally greater than or equal to the absolute distance calculated here. In this way, the warning time may be advanced, giving people at the key nodes that may be affected more time to prepare.

[0017] The second aspect of the present application provides a disaster warning data analysis system, which is applied to the disaster warning data analysis method described in any possible implementation method of the first aspect to the first aspect of the present application, and the system includes: a data monitoring module, which is used to monitor hydrological data through an automatic rainfall monitoring meter; a data processing module, which is used to construct a regional rainfall grid map according to the hydrological data; the data processing module is also used to determine, according to the regional rainfall grid map, a point where the rainfall exceeds a set rainfall threshold as a first flood disaster warning point; the data processing module is also used to traverse all the first flood disaster warning points and analyze the data of the first flood disaster warning points. If it is determined that there is a second flood disaster warning point among the first flood disaster warning points, a first-level flood disaster warning is performed within a first preset range around the second flood disaster warning point.

[0018] The present application provides a disaster warning data analysis method and system, the method comprising: monitoring hydrological data through an automatic rainfall monitoring meter, and constructing a regional rainfall grid map based on the hydrological data; determining a point where rainfall exceeds a set rainfall threshold as a first flood disaster warning point based on the regional rainfall grid map; traversing all of the first flood disaster warning points, and analyzing the data of the first flood disaster warning points, and if it is determined that a second flood disaster warning point exists among the first flood disaster warning points, performing a first-level flood disaster warning within a first preset range around the second flood disaster warning point. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A schematic diagram of a flow chart of a disaster warning data analysis method provided in an embodiment of the present application;

[0020] Figure 2 A schematic diagram of a regional rainfall grid map constructed in a disaster warning data analysis method provided in an embodiment of the present application;

[0021] Figure 3 A schematic diagram of a flow chart of a disaster warning data analysis method provided in an embodiment of the present application;

[0022] Figure 4 A schematic diagram of the structure of a disaster warning data analysis system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0024] The term "and / or" in this application can be a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this application generally indicates that the associated objects before and after are in an "or" relationship.

[0025] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] The increasing complexity of urban infrastructure has increased the risk of urban flood disasters. In order to effectively deal with urban flood disasters, the establishment of an early warning and dispatching system is crucial. Traditional urban flood disaster early warning and dispatching methods mainly rely on manual experience judgment and simple model prediction, which are incapable of dealing with complex and changeable urban flood disasters.

[0027] Existing early warning dispatch methods are usually unable to effectively obtain and process real-time data. In the forecast and early warning service system for rainstorm and flood disasters, some foreign countries use GIS technology to assist in predicting flood hazards. However, this method does not take into account the complexity of basin flood formation. Since basin flood formation is very complex, the relationship between rainfall and runoff is usually dynamic and nonlinear, and relying solely on GIS forecast results still lacks credibility in some aspects.

[0028] Therefore, this application provides a disaster warning data analysis method, please refer to Figure 1 , the method comprising:

[0029] 101. Monitor hydrological data through automatic rain gauges and construct regional rainfall grid maps based on the hydrological data.

[0030] The hydrological data is detected by automatic rain gauges, and a raster map of regional rainfall is constructed based on the hydrological data. Figure 2 The hydrological data may include but is not limited to rainfall.

[0031] It should be noted that a large number of automatic rain gauges are deployed in the flood disaster prediction model provided by this application. Rainfall is the average precipitation per unit area when it rains in a region, and rainfall can objectively and accurately show the precipitation level in a region.

[0032] Specifically, constructing a regional rainfall grid map according to the hydrological data may include:

[0033] Get the rainfall q1, q2, ..., q of n automatic rain gauges n , where n≤N, N is the total number of automatic rain gauges;

[0034] The rainfall q1, q2, ..., q n Fit the surface and construct the surface equation of the grid map:

[0035] q(x,y)=a1x 2 +a2y 2 +a3xy+a4x+a5y+a6, where x is the horizontal coordinate of the point to be measured, y is the vertical coordinate of the point to be measured, q is the rainfall at the point to be measured, and a1, a2, a3, a4, a5, and a6 are constants.

[0036] Among them, the error sum of n points is:

[0037]

[0038] When the error R is the smallest,

[0039]

[0040] Thus, the values ​​of a1, a2, a3, a4, a5, and a6 are obtained.

[0041] 102. According to the regional rainfall grid map, the point where the rainfall exceeds the set rainfall threshold is determined as the first flood disaster warning point.

[0042] According to the rainfall grid map, the point where the rainfall exceeds the set rainfall threshold is determined as the first flood disaster warning point. The set rainfall threshold can be freely set according to demand, for example, it can be set to 100 mm, 200 mm, etc.

[0043] The points whose rainfall exceeds the set rainfall threshold are selected from the rainfall grid map and determined as the second flood disaster warning points. In this way, multiple points and small areas may be selected, which can also become the second flood disaster warning area. If it is a region, the point with the highest peak value can be taken as the first flood disaster warning point, or the whole can be used as the second flood disaster warning area. The method of selecting points can be random or according to the set rules, and there is no restriction here.

[0044] When the rainfall exceeds the set rainfall threshold, it means that the first flood disaster warning point has a certain flood disaster risk, and you can choose to issue an early warning or not. Considering that the first flood disaster warning point may not necessarily have serious consequences, there is no immediate warning here.

[0045] 103. Traverse all first flood disaster warning points and analyze the data of the first flood disaster warning points. If it is determined that there is a second flood disaster warning point among the first flood disaster warning points, issue a first-level flood disaster warning within a first preset range around the second flood disaster warning point.

[0046] All the first flood disaster warning points are traversed and the data of the first flood disaster warning points are analyzed. If it is determined that there is a second flood disaster warning point among the first flood disaster warning points, a first-level flood disaster warning is issued within a first preset range around the second flood disaster warning point.

[0047] Specifically, the surface properties of the first flood disaster warning point can be distinguished.

[0048] Acquiring the surface properties of the first flood disaster warning point, wherein the surface properties include permeable areas and impermeable areas;

[0049] If the surface property of the first flood disaster warning point is determined to be a seepage area, the accumulated water flow rate of the seepage area is determined:

[0050] C1=(i―j)×Δt-M;

[0051] Wherein, C1 is the amount of water accumulated in the seepage area (mm), i is the rainfall intensity (mm / h), j is the surface permeability of the seepage area (mm / h), Δt is the rainfall duration, and M is the natural evaporation of the accumulated water (mm). The rainfall intensity and rainfall duration can be obtained from weather forecasts, and the surface permeability of the seepage area can be obtained from GIS data. The natural evaporation is related to the temperature and humidity at the time, and can be simulated by computer or set as a fixed constant.

[0052] If it is determined that the accumulated water volume C1 of the first flood disaster warning point exceeds the historical warning line of the area where the first flood disaster warning point is located, the first flood disaster warning point is determined to be the second flood disaster warning point.

[0053] If the surface property of the first flood disaster warning point is determined to be a non-seepage area, the water flow rate of the non-seepage area is determined to be:

[0054] C2=i×Δt-M;

[0055] If it is determined that the accumulated water flow C2 of the first flood disaster warning point exceeds the historical warning line of the area where the first flood disaster warning point is located, the first flood disaster warning point is determined to be the second flood disaster warning point.

[0056] A first-level flood disaster warning is issued within a first preset range around the second flood disaster warning point. The first preset range can be set according to actual needs. For example, the first preset range can be set to a one-kilometer range centered on the second flood disaster warning point.

[0057] It should be noted that there are many reasons for waterlogging in the affected area, and the relationship model is related to factors such as surface properties, topography, drainage network, rainfall, etc. Among them, the weight of each cause is inconsistent, and the model provided in this application only takes into account representative properties and rainfall intensity.

[0058] Generally speaking, when the depth of water accumulation is 0-30mm, the water accumulation can subside on its own in a short period of time, and has little impact on human social activities. When the depth of water accumulation is 30-100mm, urban areas with drainage systems can subside on their own within a certain period of time, and have little impact on human social activities. When the depth of water accumulation is 100-250mm, the water accumulation cannot subside on its own within a certain period of time, and there is a certain amount of water accumulation on the road, causing inconvenience to people's travel. When the depth of water accumulation is more than 250mm, the water accumulation will not only fail to subside on its own for a long time, but if the rainfall continues, the degree of flooding will be further aggravated, and large areas of water will appear on the road, seriously affecting traffic and normal human social activities, causing serious economic losses, and even more seriously causing traffic paralysis, posing a huge threat to the safety of human life and property.

[0059] The historical warning line can be set with reference to the water depth, or can be set according to the historical water level of each area.

[0060] It is understandable that the first-level flood disaster warning can be divided according to the warning level from high to low, which can be a mild warning, a moderate warning, and a mild warning among severe warnings. Or according to the color classification, it can be a yellow warning among yellow warning, orange warning, and red warning. The warning method can be through group text messages or weather service reminders, which are not limited here.

[0061] See also Figure 3 Based on the above embodiments, the disaster warning data analysis method provided by the present application may further include:

[0062] 201. Traverse all second flood disaster warning points and determine whether there is a third flood disaster warning point among the second flood disaster warning points.

[0063] All second flood disaster warning points are traversed, and it is determined whether there is a third flood disaster warning point among the second flood disaster warning points, wherein there is at least one first flood disaster warning point within a second preset range of the third flood disaster warning point.

[0064] The second preset range can be set according to demand, for example, 50 meters.

[0065] It should be noted that, in step 102, the first flood disaster warning point screened out may actually be a point or an area. If the first flood disaster warning point is an area, the second flood disaster warning point determined in step 103 may also be an area.

[0066] If the second flood disaster warning point is an area, the second preset range is expanded outward from the edge of the area. If the first flood disaster warning point exists within the second preset range, the second flood disaster warning point can be determined as the third flood disaster warning point. At this time, the third flood disaster warning point is also an area like the second flood disaster warning point. The third flood disaster warning point needs to be paid special attention to.

[0067] 202. If it is determined that the rainfall intensity at the third flood disaster warning point is greater than the first preset rainfall intensity threshold, it is determined that the third flood disaster warning point has a risk of dam breach, and a second-level flood disaster warning is issued within the first preset range around the third flood disaster warning point.

[0068] If the rainfall intensity at the third flood disaster warning point is greater than the first preset rainfall intensity threshold, it is determined that the third flood disaster warning point has a risk of dam breach, and a second-level flood disaster warning is performed within the first preset range around the third flood disaster warning point. Exemplarily, the first preset rainfall intensity threshold is 10 mm / h. The first preset range can be set according to actual needs, for example, the first preset range can be set to a one-kilometer range centered on the third flood disaster warning point. The second-level flood disaster warning can be a moderate warning or an orange warning.

[0069] 203. When it is determined that the third flood disaster warning point has the risk of dam breach, the lowest point within the second preset range of the third flood disaster warning point is determined, and the lowest point is used as the starting point to predict the possible path of the flood in the direction from high to low.

[0070] When it is determined that the third flood disaster warning point has the risk of dam breach, the lowest point within the second preset range of the third flood disaster warning point is determined, and with the lowest point as the starting point, the possible path of the flood is predicted in the direction from high to low.

[0071] The third flood disaster warning point can be an area as described in step 201, and the lowest point can be the lowest point of the area. Or when the third flood disaster warning point is a point, the lowest point of the terrain within the second preset range can be centered on the third flood disaster warning point. The second preset range can be set as required, such as 10 meters, 50 meters, etc. The terrain height can be obtained through GIS. A flood prediction route is obtained from high to low.

[0072] It should be noted that the prediction of flood paths has always been a difficult problem in the industry. The direction of flood flow may be affected by many factors such as topography, rainfall, and surface soil. However, the general direction is still from high to low terrain. Therefore, this application obtains terrain data through GIS, takes the lowest point in the second preset range, and takes the lowest point as the starting point to predict the possible path of the flood from high to low terrain.

[0073] However, as the energy accumulated by the surging flood increases, the water may not flow completely from high to low terrain due to the potential energy and inertia of the water, but may gradually deviate. After the deviation occurs, the deviation will gradually deepen during the flow from high terrain to low terrain. In response to this, this application also adjusts the flood prediction path to more accurately predict the path of the flood. Specifically:

[0074] In the possible path, the current grid node (x e ,y e ), the previous grid node (x e―1 ,y e―1 ) and the second grid node (x e+1 ,y e+1 ), the third grid node (x e+2 ,y e+2 );

[0075] Calculate m1 = (x e+1 ―x e ) / (x e ―x e―1 ), m2=(y e+1 ―y e ) / (y e ―y e―1 );

[0076] If m1>m2, the third grid node (x e+2 +Δx,y e+2 );

[0077] If m1≤m2, the third grid node (x e+2 ,y e+2 +Δy), Δx and Δy are pre-set step values ​​and can be set according to actual conditions.

[0078] It is worth noting that after the prediction of the flood flow path is completed, the GIS data can be used to determine whether there are key nodes on the path, such as industrial parks, schools or other buildings. The third-level flood disaster warning can be issued for the key nodes, and the arrival time of the flood can be predicted.

[0079] Specifically, the third-level flood disaster warning is issued to key nodes on the path, and the arrival time of the flood is prompted:

[0080] Among them, the distance between the key node and the starting point is:

[0081] (X1, Y1) is the grid coordinate of the starting point, (X end , Y end ) is the grid coordinate of the key node;

[0082] The predicted arrival time t=H / v, where v is the predicted water flow velocity, which can be obtained based on computer simulation or set to a fixed value.

[0083] The present application provides a method and system for analyzing disaster warning data, which includes: monitoring hydrological data through an automatic rainfall monitoring meter, and constructing a regional rainfall grid map based on the hydrological data; determining a point where the rainfall exceeds a set rainfall threshold as a first flood disaster warning point based on the regional rainfall grid map; traversing all the first flood disaster warning points, and analyzing the data of the first flood disaster warning points, and if it is determined that there is a second flood disaster warning point among the first flood disaster warning points, a first-level flood disaster warning is performed within a first preset range around the second flood disaster warning point. The first flood disaster warning point is first screened out through the regional rainfall grid map, and then the first flood disaster warning point is screened for a second time. If it is determined that there is a second flood disaster warning point, a first-level flood disaster warning is performed within a first preset range around the second flood disaster warning point. This can improve the accuracy of the warning.

[0084] See the disaster warning data analysis method provided in this application. This application also provides a disaster warning data analysis system, see Figure 4The disaster warning data analysis system provided by this application includes:

[0085] Data monitoring module, used to monitor hydrological data through automatic rain gauges;

[0086] A data processing module, used for constructing a regional rainfall grid map based on the hydrological data;

[0087] The data processing module is further used to determine, based on the regional rainfall grid map, a point where the rainfall exceeds a set rainfall threshold as a first flood disaster warning point;

[0088] The data processing module is also used to traverse all the first flood disaster warning points and analyze the data of the first flood disaster warning points. If it is determined that there is a second flood disaster warning point among the first flood disaster warning points, a first-level flood disaster warning is issued within a first preset range around the second flood disaster warning point.

[0089] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0090] In the embodiments provided in this application, it should be understood that the disclosed methods can be implemented in other ways without exceeding the spirit and scope of this application. The current embodiment is only an illustrative example and should not be used as a limitation. The specific content given should not limit the purpose of this application. For example, some features can be ignored or not executed.

[0091] The technical means disclosed in the present application are not limited to the technical means disclosed in the above-mentioned implementation methods, but also include technical solutions composed of any combination of the above technical features. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of this application, and these improvements and modifications are also regarded as the protection scope of this application.

[0092] The above is a detailed introduction to a disaster warning data analysis method and system provided by the embodiments of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for those of ordinary skill in the art, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein; and these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A disaster warning data analysis method, characterized in that: The method comprises: monitoring hydrological data through an automatic rain gauge and constructing a regional rainfall grid map based on the hydrological data; Determine, according to the regional rainfall grid map, a point where the rainfall exceeds a set rainfall threshold as the first flood disaster warning point; Traverse all the first flood disaster warning points and analyze the data of the first flood disaster warning points. If it is determined that a second flood disaster warning point exists among the first flood disaster warning points, issue a first-level flood disaster warning within a first preset range around the second flood disaster warning point.

2. The disaster warning data analysis method according to claim 1, characterized in that: The constructing of a regional rainfall grid map according to the hydrological data specifically includes: Get the rainfall q1, q2, ..., q of n automatic rain gauges n , where n≤N, N is the total number of automatic rain gauges; The rainfall q1, q2, ..., q n Fit the surface and construct the surface equation of the grid map: q(x,y)=a1x 2 +a2y 2 +a3xy+a4x+a5y+a6, where x is the horizontal coordinate of the point to be measured, y is the vertical coordinate of the point to be measured, q is the rainfall at the point to be measured, and a1, a2, a3, a4, a5, and a6 are constants.

3. The disaster warning data analysis method according to claim 1, characterized in that: The determining that there is a second flood disaster warning point among the first flood disaster warning points specifically includes: Acquiring the surface properties of the first flood disaster warning point, wherein the surface properties include permeable areas and impermeable areas; If the surface property of the first flood disaster warning point is determined to be a seepage area, the accumulated water flow rate of the seepage area is determined: C1=(i―j)×Δt-M; Wherein, C1 is the amount of water accumulated in the water seepage area, i is the rainfall intensity, j is the surface permeability of the water seepage area, Δt is the rainfall duration, and M is the natural evaporation of the accumulated water; If it is determined that the accumulated water volume C1 of the first flood disaster warning point exceeds the historical warning line of the area where the first flood disaster warning point is located, the first flood disaster warning point is determined to be the second flood disaster warning point.

4. The disaster warning data analysis method according to claim 3, characterized in that: The method further comprises: If the surface property of the first flood disaster warning point is determined to be a non-seepage area, the water flow rate of the non-seepage area is determined to be: C2=i×Δt-M; If it is determined that the accumulated water flow C2 of the first flood disaster warning point exceeds the historical warning line of the area where the first flood disaster warning point is located, the first flood disaster warning point is determined to be the second flood disaster warning point.

5. The disaster warning data analysis method according to claim 2, characterized in that: The method further comprises: Traversing all second flood disaster warning points, and determining whether there is a third flood disaster warning point among the second flood disaster warning points, wherein there is at least one first flood disaster warning point within a second preset range of the third flood disaster warning point; If it is determined that the rainfall intensity at the third flood disaster warning point is greater than the first preset rainfall intensity threshold, it is determined that the third flood disaster warning point has a risk of dam breach, and a second-level flood disaster warning is issued within a first preset range around the third flood disaster warning point.

6. The disaster warning data analysis method according to claim 5, characterized in that: The method further comprises: When it is determined that the third flood disaster warning point has the risk of dam breach, the lowest point within the second preset range of the third flood disaster warning point is determined, and the possible path of the flood is predicted from high to low in the direction of the terrain, taking the lowest point as the starting point.

7. The disaster warning data analysis method according to claim 6, characterized in that: After constructing the possible flood path according to the direction from high to low terrain, the method further includes a step of dynamically adjusting the path: In the possible path, the current grid node (x e ,y e ), the previous grid node (x e―1 ,y e―1 ) and the second grid node (x e+1 ,y e+1 ), the third grid node (x e+2 ,y e+2 ); Calculate m1 = (x e+1 −x e ) / (x e −x e―1 ), m2 = (y e+1 −y e ) / (y e −y e―1 ); If m1>m2, the third grid node (x e+2 +Δx,y e+2 ); If m1≤m2, the third grid node (x e+2 ,y e+2 +Δy), Δx and Δy are pre-set step values.

8. The disaster warning data analysis method according to claim 7, characterized in that: The method further comprises: Issue the third-level flood disaster warning to key nodes on the path, and indicate the arrival time of the flood: Among them, the distance between the key node and the starting point is: (X1, Y1) is the grid coordinate of the starting point, (X end , Y end ) is the grid coordinate of the key node; Predicted arrival time t = H / v, where v is the predicted water flow velocity.

9. A disaster warning data analysis system, characterized in that: The system is applied to the disaster warning data analysis method according to any one of claims 1 to 8, and the system comprises: Data monitoring module, used to monitor hydrological data through automatic rain gauges; A data processing module, used for constructing a regional rainfall grid map based on the hydrological data; The data processing module is further used to determine, based on the regional rainfall grid map, a point where the rainfall exceeds a set rainfall threshold as a first flood disaster warning point; The data processing module is also used to traverse all the first flood disaster warning points and analyze the data of the first flood disaster warning points. If it is determined that there is a second flood disaster warning point among the first flood disaster warning points, a first-level flood disaster warning is issued within a first preset range around the second flood disaster warning point.

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