A method and system for determining dynamic early warning indicators of flash flood disasters

Abstract

The present invention provides a method and system for determining dynamic warning indicators for flash flood disasters, which belongs to the technical field of data analysis, and specifically includes: dividing rainfall data within a unit time length into the same rainfall period, determining the deviation between rainfall data in different rainfall periods and prediction and warning indicators, and combining flash flood data in different rainfall periods to determine that when there is a deviation in the prediction and warning indicators, determining the deviation of indicator data between rainfall data in different historical flash flood processes and prediction and warning indicators in different dimensions, and using the indicator data deviation to determine a benchmark warning indicator and a benchmark flash flood period, determining a reference rainfall period in the rainfall period based on the benchmark flash flood period, and correcting the benchmark warning indicator based on the rainfall data in the reference rainfall period to obtain the flash flood warning indicator of the mountain, thereby ensuring the accuracy of the evaluation of the warning indicator.

Description

Technical Field

[0001] The present invention belongs to the technical field of data analysis, and in particular relates to a method and system for determining dynamic early warning indicators for flash flood disasters. Background Art

[0002] The influencing indicators of flash flood disasters include early warning indicators of various rainfall factors such as rainfall intensity, previous influencing rainfall, and cumulative rainfall per session. Therefore, in order to determine the early warning indicators, the invention patent application CN201910905968.1 "A medium- and long-term flash flood disaster early warning and prediction method" calculates the flash flood early warning indicators, which can greatly extend the forecast period and provide good technical support for flash flood disaster prevention and control. However, the existing technical solutions have the following technical problems:

[0003] For the same mountain, the occurrence of natural disasters such as flash floods and mudslides will cause changes in the terrain distribution of the land, which will in turn have a certain impact on the probability of flash floods under the same rainfall. Therefore, if the differentiated flash flood disaster warning indicators cannot be dynamically adjusted according to the actual data of the mountain, the accuracy of the flash flood disaster warning will be difficult to meet the requirements.

[0004] In view of the above technical problems, the present invention provides a method and system for determining dynamic early warning indicators for flash flood disasters. Summary of the invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0006] According to one aspect of the present invention, a method for determining dynamic early warning indicators for flash flood disasters is provided.

[0007] A method for determining dynamic early warning indicators for flash flood disasters, specifically comprising:

[0008] S1: obtaining terrain data of a mountain in different mountain areas, and determining prediction and early warning indicators of the mountain in different dimensions based on the terrain data and rainfall statistics of different years;

[0009] S2 divides the rainfall data within the unit time into the same rainfall period, determines the deviation between the rainfall data in different rainfall periods and the forecast and warning indicators, and when it is determined that the forecast and warning indicators have deviations in combination with the flash flood data in different rainfall periods, proceeds to the next step;

[0010] S3 determines the deviation of the rainfall data in different historical flash floods and the indicator data of the prediction and early warning indicators in different dimensions, and uses the indicator data deviation to determine the benchmark early warning indicator and the benchmark flash flood period;

[0011] S4 determines a reference rainfall period in the rainfall period based on the benchmark flash flood period, and modifies the benchmark warning index based on rainfall data of the reference rainfall period to obtain a flash flood warning index for the mountain.

[0012] The beneficial effects of the present invention are:

[0013] 1. In this application, the prediction and early warning indicators of the mountain in different dimensions are determined based on terrain data and rainfall statistics of different years. Not only the impact of the terrain data of the mountain on the warning indicators is taken into account, but also by further considering rainfall statistics, the technical problem of the accuracy of the determination of the warning indicators due to the single consideration of terrain data is avoided, thereby ensuring the accuracy of the evaluation of the prediction and early warning indicators.

[0014] 2. In the present application, the benchmark warning index is corrected based on the rainfall data of the reference rainfall period to obtain the warning index of flash floods in the mountain, thereby fully considering the impact of rainfall data on the changes in the mountain terrain and the warning index, and realizing the dynamic adjustment of the warning index of flash floods, thereby laying the foundation for the accuracy of the warning processing of flash floods in the mountain and ensuring the safety of the mountain.

[0015] A further technical solution is that the topographic data of the mountain area is determined based on the analysis results of the surveying and mapping image data of the mountain area.

[0016] A further technical solution is that the mountain area is divided according to the preset area based on the mountain.

[0017] A further technical solution is that the method for determining the prediction and early warning indicators is:

[0018] Taking a mountain with accurate early warning indicators as a reference mountain, determining the terrain similarity between the mountain and the reference mountain based on the terrain data of different mountain areas, and determining similar reference mountains using the terrain similarity;

[0019] Based on rainfall statistics of different years, the average annual rainfall times and the average annual rainfall amount of the mountain are determined, and based on the average annual rainfall times and the average annual rainfall amount, the similarity of rainfall data between the mountain and the similar reference mountain is determined, and similar mountains among the similar reference mountains are determined using the rainfall data similarity;

[0020] The average value of the early warning indicators of the similar mountains is used to determine the prediction and early warning indicators of the mountain in different dimensions.

[0021] A further technical solution is that the rainfall impact factor is determined according to a preset mapping relationship.

[0022] A further technical solution is that the benchmark flash flood period is a rainfall period corresponding to when the data deviation in the historical flash flood process is the smallest.

[0023] A further technical solution is that the method for determining the benchmark early warning indicator is:

[0024] The indicator deviation of the forecast and early warning indicators of different dimensions is determined by using the rainfall data in different historical flash flood outbreaks and the indicator data deviation of the forecast and early warning indicators of different dimensions;

[0025] Determine the deviation indexes in different historical flash flood outbreaks according to the index deviations of the prediction and early warning indexes in different dimensions, and determine the comprehensive deviations of the indexes in different historical flash flood outbreaks by using the number of deviation indexes and the index deviations of different deviation indexes;

[0026] The benchmark flash flood period in the historical flash flood process is determined by using the comprehensive deviation of indicators in different historical flash flood processes, and the early warning indicator corresponding to the benchmark flash flood period is used as the benchmark early warning indicator.

[0027] A further technical solution is that the reference rainfall period in the rainfall period is all rainfall periods after the benchmark flash flood period.

[0028] A further technical solution is that the method for determining the early warning index of the mountain flood is:

[0029] Determine the rainfall data deviation of the reference rainfall period according to the deviation between the rainfall data of the reference rainfall period and the prediction and warning indicators of different dimensions, and use the rainfall data deviation to determine the effective reference rainfall period in the reference rainfall period;

[0030] Determine the early warning indicator compensation amount of different effective reference rainfall periods by using the rainfall data deviation amount of different effective reference rainfall periods, the interval length with adjacent reference rainfall periods, and the rainfall data of different adjacent reference rainfall periods;

[0031] The benchmark warning index is corrected according to the warning index compensation amount of different effective reference rainfall periods to obtain the warning index of the mountain flood.

[0032] In a second aspect, the present invention provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, it executes the above-mentioned method for determining dynamic warning indicators for flash flood disasters.

[0033] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0034] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0036] Figure 1 It is a flow chart of a method for determining dynamic early warning indicators for flash flood disasters;

[0037] Figure 2 It is a flow chart of the method for determining the prediction and early warning indicators;

[0038] Figure 3 It is a flow chart of the method for determining the benchmark early warning indicator;

[0039] Figure 4 It is a flow chart of a method for determining early warning indicators of mountain flash floods;

[0040] Figure 5 It is a framework diagram of a computer system. DETAILED DESCRIPTION

[0041] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0042] For the same mountain, the occurrence of natural disasters such as flash floods and mudslides will cause changes in the terrain distribution of the land. Therefore, even under the same rainfall data, the risk of flash flood disasters will change. Therefore, in this application, the warning targets for flash flood disasters are determined in combination with the changes in the terrain distribution state of the mountain, which can greatly improve the accuracy of flash flood warnings.

[0043] Specifically, this application is divided into four steps:

[0044] 1. Use the similarities between rainfall statistics and terrain data to determine similar mountains, and use the average value of the early warning indicators of similar mountains to determine the predicted early warning indicators of the mountains.

[0045] 2. According to the deviation between rainfall data in historical rainfall processes and forecast and warning indicators, the forecast and warning indicators with deviations are determined. Specifically, the number of flash floods that did not reach the forecast and warning indicators is used to determine the forecast and warning indicators with deviations.

[0046] 3. Determine the benchmark flash flood outbreak time by using the flash flood time when the deviation from the forecast and warning indicators is within the preset range;

[0047] 4. Using the rainfall data from the benchmark flash flood outbreak time to the present time, the number of rainfalls with rainfall amounts greater than the preset rainfall amounts is used to correct the benchmark warning indicators at the benchmark flash flood outbreak time to obtain warning indicators.

[0048] Similar mountains: determined based on the mountain area, mountain height and rainfall. Specifically, in a possible embodiment, the average value of the deviation rate of the mountain area, the deviation rate of the mountain height and the deviation rate of the rainfall is 0.3, and the similarity coefficient is 0.7. Mountains with a similarity coefficient greater than 0.6 are regarded as similar mountains.

[0049] Forecast and warning indicators with deviations: Forecast and warning indicators that fail to meet the forecast and warning indicators but have occurred more than twice are considered as forecast and warning indicators with deviations.

[0050] Benchmark flash flood outbreak time: For example, when the average deviation rates of different flash flood outbreak times and prediction and warning indicators in different dimensions are 0.3, 0.2, and 0.1, the flash flood outbreak time corresponding to 0.1 is used as the benchmark flash flood outbreak time, and the warning indicator corresponding to the benchmark flash flood outbreak time is used as the benchmark warning indicator.

[0051] Warning index: Determine the corresponding compensation coefficient based on the number of times the rainfall is greater than the preset rainfall, and determine the warning index by multiplying the compensation coefficient by the benchmark warning index.

[0052] To solve the above problems, according to one aspect of the present invention, Figure 1 As shown, a method for determining dynamic early warning indicators for flash flood disasters is provided, which specifically includes:

[0053] S1: obtaining terrain data of a mountain in different mountain areas, and determining prediction and early warning indicators of the mountain in different dimensions based on the terrain data and rainfall statistics of different years;

[0054] S2 divides the rainfall data within the unit time into the same rainfall period, determines the deviation between the rainfall data in different rainfall periods and the forecast and warning indicators, and when it is determined that the forecast and warning indicators have deviations in combination with the flash flood data in different rainfall periods, proceeds to the next step;

[0055] S3 determines the deviation of the rainfall data in different historical flash floods and the indicator data of the prediction and early warning indicators in different dimensions, and uses the indicator data deviation to determine the benchmark early warning indicator and the benchmark flash flood period;

[0056] S4 determines a reference rainfall period in the rainfall period based on the benchmark flash flood period, and modifies the benchmark warning index based on rainfall data of the reference rainfall period to obtain a flash flood warning index for the mountain.

[0057] Furthermore, the terrain data of the mountain area is determined based on the analysis results of the surveying and mapping image data of the mountain area.

[0058] It can be understood that the mountain area is divided according to the preset area based on the mountain.

[0059] It should be noted that if Figure 2 As shown, the method for determining the prediction and early warning indicators is:

[0060] Taking a mountain with accurate early warning indicators as a reference mountain, determining the terrain similarity between the mountain and the reference mountain based on the terrain data of different mountain areas, and determining similar reference mountains using the terrain similarity;

[0061] Based on rainfall statistics of different years, the average annual rainfall times and the average annual rainfall amount of the mountain are determined, and based on the average annual rainfall times and the average annual rainfall amount, the similarity of rainfall data between the mountain and the similar reference mountain is determined, and similar mountains among the similar reference mountains are determined using the rainfall data similarity;

[0062] The average value of the early warning indicators of the similar mountains is used to determine the prediction and early warning indicators of the mountain in different dimensions.

[0063] Furthermore, the rainfall impact factor is determined according to a preset mapping relationship.

[0064] In another embodiment, the method for determining the prediction and early warning indicators is:

[0065] Taking the terrain data of different mountain areas as input, the model output results of the preset model are used to determine the initial prediction and early warning indicators of the mountain in different dimensions;

[0066] Based on the rainfall statistics of different years, the average annual rainfall times and the average annual rainfall amount of the mountain are determined, and based on the average annual rainfall times and the average annual rainfall amount, the rainfall influencing factor of the mountain is determined;

[0067] The initial prediction and warning indicators are corrected by using the rainfall impact factor to obtain prediction and warning indicators of the mountain in different dimensions.

[0068] In another embodiment, the method for determining the prediction and early warning indicators is:

[0069] S11 uses the terrain data of different mountain areas as input, and uses the model output results of the preset model to determine the initial prediction and early warning indicators of the mountain in different dimensions;

[0070] S12 determines the rainfall of the mountain in different years based on the rainfall statistics of different years, and judges whether the rainfall of the mountain in different years is less than the preset rainfall. If so, proceed to the next step; if not, proceed to step S15;

[0071] S13 determines whether the mountain has a historical rainfall number with a rainfall amount greater than a preset threshold. If so, proceed to the next step. If not, use the initial prediction and warning indicators to determine the prediction and warning indicators of the mountain in different dimensions;

[0072] S14 obtains the rainfall in different years, and determines the rainfall impact values ​​of different years in combination with the rainfall in different historical rainfall times, and determines whether there are years in which the rainfall impact values ​​do not meet the requirements. If so, proceed to the next step; if not, use the initial prediction and warning indicators to determine the prediction and warning indicators of the mountain in different dimensions;

[0073] S15 obtains the rainfall in different years, and determines the rainfall impact values ​​in different years in combination with the rainfall in different historical rainfall times, and determines whether there are years in which the rainfall impact values ​​do not meet the requirements, and if so, proceeds to the next step, and if not, corrects the initial prediction and warning indicators of the mountain in different dimensions based on the number of years in which the rainfall impact values ​​do not meet the requirements to obtain the prediction and warning indicators of the mountain in different dimensions;

[0074] S16 determines the average annual rainfall times and average annual rainfall of the mountain based on rainfall statistical data of different years, and determines the rainfall influencing factor of the mountain based on the average annual rainfall times and average annual rainfall, and uses the rainfall influencing factor to correct the initial prediction and warning indicators to obtain the prediction and warning indicators of the mountain in different dimensions.

[0075] It should be noted that the initial prediction and warning indicators of the mountain in different dimensions are corrected based on the number of years in which the rainfall impact value does not meet the requirements to obtain the prediction and warning indicators of the mountain in different dimensions, which specifically include:

[0076] The corresponding index compensation amount is determined based on the number of years in which the rainfall impact value does not meet the requirements, and the initial prediction and warning index is corrected by using the index compensation amount to obtain the prediction and warning index of the mountain in different dimensions.

[0077] Furthermore, the unit duration is determined according to a preset duration, and the specific value range is between 3 days and 7 days.

[0078] It is understandable that the determination of the existence of deviations in the forecast and early warning indicators specifically includes:

[0079] Using flash flood data of different rainfall periods, the rainfall period is divided into a flash flood rainfall period and a non-flash flood rainfall period;

[0080] Determine the deviation of rainfall data in the flash flood period and the deviation of rainfall data in the non-flash flood period based on the deviation of rainfall data in different flash flood periods and the forecast and warning indicators, and the deviation of rainfall data in the non-flash flood period and the forecast and warning indicators;

[0081] The indicator data accuracy of the forecast and early warning indicator is calculated by using the rainfall data deviation in the outbreak period and the rainfall data deviation in the non-outbreak period, and the indicator data accuracy is used to determine whether the forecast and early warning indicator has a deviation.

[0082] It should be noted that the accuracy of the indicator data is used to determine whether the prediction and early warning indicators have deviations, specifically including:

[0083] When the accuracy of the indicator data is less than the preset accuracy, it is determined that there is a deviation in the prediction and warning indicator.

[0084] In another embodiment, determining that the prediction and early warning indicator has a deviation specifically includes:

[0085] Using flash flood data of different rainfall periods, the rainfall period is divided into a flash flood rainfall period and a non-flash flood rainfall period;

[0086] Based on the deviation between rainfall data of different flash flood rainfall periods and the forecast and warning indicators, a flash flood rainfall period that has not reached the forecast and warning indicators is determined and used as a deviation flood period;

[0087] Determine the non-outburst rainfall period that reaches the forecast and warning index according to the deviation between the rainfall data of the non-outburst rainfall period and the forecast and warning index, and use it as the deviation non-outburst rainfall period;

[0088] The indicator data accuracy of the forecast and early warning indicator is determined based on the proportion of the deviation outbreak period and the deviation non-outbreak period in the rainfall period, and the indicator data accuracy is used to determine whether the forecast and early warning indicator has a deviation.

[0089] In another embodiment, determining that the prediction and early warning indicator has a deviation specifically includes:

[0090] S21 divides the rainfall period into a flash flood rainfall period and a non-flash flood rainfall period by using flash flood data of different rainfall periods;

[0091] S22 determines whether there is a flash flood rainfall period that has not reached the forecast warning index based on the deviation of rainfall data of different flash flood rainfall periods and the forecast warning index. If so, proceed to step S25; if not, proceed to the next step;

[0092] S23 determines whether there is a non-burst rainfall period that reaches the forecast warning index according to the deviation between the rainfall data of the non-burst rainfall period and the forecast warning index, if so, proceeds to the next step, if not, determines that there is no deviation in the forecast warning index;

[0093] S24: taking the flash flood rainfall period that has not reached the forecast and warning index as the deviation outbreak period, determining the rainfall index deviation amount of different deviation outbreak periods according to the deviation between the rainfall data of different deviation outbreak periods and the forecast and warning index, determining the outbreak data deviation amount based on the rainfall index deviation amount of different deviation outbreak periods, and judging whether the outbreak data deviation amount meets the requirement, if so, proceeding to the next step, if not, determining that the forecast and warning index has a deviation;

[0094] S25 determines the rainfall period that does not break out when the forecast and warning indicators are met, and uses it as the deviation non-break out period, determines the rainfall indicator deviation amounts of different deviation non-break out periods according to the deviations between the rainfall data of different deviation non-break out periods and the forecast and warning indicators, determines the non-break out data deviation amounts based on the rainfall indicator deviation amounts of different deviation non-break out periods, and determines whether the non-break out data deviation amount meets the requirements, if so, proceeds to the next step, if not, determines that the forecast and warning indicators have deviations;

[0095] S26 determines the indicator data accuracy of the prediction and early warning indicator based on the outbreak data deviation and the non-outbreak data deviation, and uses the indicator data accuracy to determine whether the prediction and early warning indicator has a deviation.

[0096] Specific examples, such as Figure 3 As shown, the method for determining the benchmark early warning indicator is:

[0097] The indicator deviation of the forecast and early warning indicators of different dimensions is determined by using the rainfall data in different historical flash flood outbreaks and the indicator data deviation of the forecast and early warning indicators of different dimensions;

[0098] Determine the data deviation in different historical flash flood processes according to the average value of the indicator deviation of the prediction and warning indicators in different dimensions;

[0099] The data deviation is used to determine a benchmark flash flood period in the historical flash flood process, and the early warning indicator corresponding to the benchmark flash flood period is used as the benchmark early warning indicator.

[0100] Furthermore, the benchmark flash flood period is a rainfall period corresponding to when the data deviation in the historical flash flood process is the smallest.

[0101] In another embodiment, the method for determining the benchmark early warning indicator is:

[0102] The indicator deviation of the forecast and early warning indicators of different dimensions is determined by using the rainfall data in different historical flash flood outbreaks and the indicator data deviation of the forecast and early warning indicators of different dimensions;

[0103] Determine the deviation indexes in different historical flash flood outbreaks according to the index deviations of the prediction and early warning indexes in different dimensions, and determine the comprehensive deviations of the indexes in different historical flash flood outbreaks by using the number of deviation indexes and the index deviations of different deviation indexes;

[0104] The benchmark flash flood period in the historical flash flood process is determined by using the comprehensive deviation of indicators in different historical flash flood processes, and the early warning indicator corresponding to the benchmark flash flood period is used as the benchmark early warning indicator.

[0105] It should be noted that the reference rainfall period in the rainfall period is all rainfall periods after the benchmark flash flood period.

[0106] Specifically, Figure 4 As shown, the method for determining the early warning index of the mountain flood is:

[0107] Determine the rainfall data deviation of the reference rainfall period according to the deviation between the rainfall data of the reference rainfall period and the prediction and warning indicators of different dimensions, and use the rainfall data deviation to determine the effective reference rainfall period in the reference rainfall period;

[0108] Determine the early warning indicator compensation amount of different effective reference rainfall periods by using the rainfall data deviation amount of different effective reference rainfall periods, the interval length with adjacent reference rainfall periods, and the rainfall data of different adjacent reference rainfall periods;

[0109] The benchmark warning index is corrected according to the warning index compensation amount of different effective reference rainfall periods to obtain the warning index of the mountain flood.

[0110] In another embodiment, the method for determining the early warning index of the mountain flood is:

[0111] Determine the deviation of rainfall data in the reference rainfall period according to the deviation between rainfall data in the reference rainfall period and prediction and warning indicators of different dimensions, and use the rainfall data deviation to determine the effective reference rainfall period in the reference rainfall period, and judge whether the number of effective reference rainfall periods is greater than the preset number of periods. If so, use the preset compensation amount to correct the benchmark warning indicator to obtain the warning indicator of flash floods in the mountain. If not, proceed to the next step.

[0112] Determine the cross-influence reference rainfall period in the effective reference rainfall period by using the interval between the effective reference rainfall period and the adjacent reference rainfall period and the rainfall data of different adjacent reference rainfall periods, and judge whether the number of the cross-influence reference rainfall periods is within the preset period number interval; if so, use the preset compensation amount to correct the benchmark warning index to obtain the flash flood warning index of the mountain; if not, proceed to the next step;

[0113] Determine the warning index compensation amount of different effective reference rainfall periods by the rainfall data deviation amount of different effective reference rainfall periods, the interval time length with adjacent reference rainfall periods and the rainfall data of different adjacent reference rainfall periods, and use the warning index compensation amount to determine the screening reference rainfall period in the effective reference rainfall period, and judge whether the number of the screening reference rainfall period is within the preset reference period number interval. If so, use the preset compensation amount to correct the benchmark warning index to obtain the flash flood warning index of the mountain. If not, proceed to the next step.

[0114] A comprehensive compensation amount is determined according to the compensation amounts of the early warning indicators of different effective reference rainfall periods, and the comprehensive compensation amount is used to correct the benchmark early warning indicator to obtain the early warning indicator of the mountain flood.

[0115] Second, as Figure 5As shown, the present invention provides a computer system, comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, it executes the above-mentioned method for determining dynamic warning indicators of flash flood disasters.

[0116] The above-mentioned method for determining dynamic early warning indicators of flash flood disasters specifically includes:

[0117] Obtaining terrain data of the mountain in different mountain areas, and determining the prediction and early warning indicators of the mountain in different dimensions based on the terrain data and rainfall statistics of different years;

[0118] The rainfall data within the unit time is divided into the same rainfall period, and the deviation between the rainfall data in different rainfall periods and the forecast and warning indicators is determined. When it is determined that the forecast and warning indicators have deviations in combination with the flash flood data in different rainfall periods, the next step is entered;

[0119] The indicator deviation of the forecast and early warning indicators of different dimensions is determined by using the rainfall data in different historical flash flood outbreaks and the indicator data deviation of the forecast and early warning indicators of different dimensions;

[0120] Determine the data deviation in different historical flash flood processes according to the average value of the indicator deviation of the prediction and warning indicators in different dimensions;

[0121] Determine the benchmark flash flood period in the historical flash flood process by using the data deviation, and use the early warning index corresponding to the benchmark flash flood period as the benchmark early warning index and the determination of the benchmark flash flood period;

[0122] Determine a reference rainfall period in the rainfall period based on the benchmark flash flood period, determine the rainfall data deviation of the reference rainfall period according to the deviation between the rainfall data of the reference rainfall period and the prediction and warning indicators of different dimensions, and use the rainfall data deviation to determine a valid reference rainfall period in the reference rainfall period, and judge whether the number of the valid reference rainfall periods is greater than the preset number of periods. If so, use the preset compensation amount to correct the benchmark warning indicator to obtain the flash flood warning indicator of the mountain. If not, proceed to the next step.

[0123] Determine the cross-influence reference rainfall period in the effective reference rainfall period by using the interval between the effective reference rainfall period and the adjacent reference rainfall period and the rainfall data of different adjacent reference rainfall periods, and judge whether the number of the cross-influence reference rainfall periods is within the preset period number interval; if so, use the preset compensation amount to correct the benchmark warning index to obtain the flash flood warning index of the mountain; if not, proceed to the next step;

[0124] Determine the warning index compensation amount of different effective reference rainfall periods by the rainfall data deviation amount of different effective reference rainfall periods, the interval time length with adjacent reference rainfall periods and the rainfall data of different adjacent reference rainfall periods, and use the warning index compensation amount to determine the screening reference rainfall period in the effective reference rainfall period, and judge whether the number of the screening reference rainfall period is within the preset reference period number interval. If so, use the preset compensation amount to correct the benchmark warning index to obtain the flash flood warning index of the mountain. If not, proceed to the next step.

[0125] A comprehensive compensation amount is determined according to the compensation amounts of the early warning indicators of different effective reference rainfall periods, and the comprehensive compensation amount is used to correct the benchmark early warning indicator to obtain the early warning indicator of the mountain flood.

[0126] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0127] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0128] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A method for determining dynamic early warning indicators for flash flood disasters, characterized in that: Specifically include: Obtaining terrain data of the mountain in different mountain areas, and determining the prediction and early warning indicators of the mountain in different dimensions based on the terrain data and rainfall statistics of different years; The rainfall data within the unit time is divided into the same rainfall period, and the deviation between the rainfall data in different rainfall periods and the forecast and warning indicators is determined. When it is determined that the forecast and warning indicators have deviations in combination with the flash flood data in different rainfall periods, the next step is entered; Determine the deviation between rainfall data in different historical flash floods and forecast and early warning indicators in different dimensions, and use the deviation to determine the benchmark early warning indicators and benchmark flash flood periods; The reference rainfall period in the rainfall period is determined based on the reference flash flood period, and the reference warning index is corrected based on the rainfall data of the reference rainfall period to obtain the flash flood warning index of the mountain. The method for determining the prediction and early warning indicators is: S11 uses the terrain data of different mountain areas as input, and uses the model output results of the preset model to determine the initial prediction and early warning indicators of the mountain in different dimensions; S12 determines the rainfall of the mountain in different years based on the rainfall statistics of different years, and judges whether the rainfall of the mountain in different years is less than the preset rainfall. If so, proceed to the next step; if not, proceed to step S15; S13 determines whether the mountain has a historical rainfall number with a rainfall amount greater than a preset threshold. If so, proceed to the next step. If not, use the initial prediction and warning indicators to determine the prediction and warning indicators of the mountain in different dimensions; S14 obtains the rainfall in different years, and determines the rainfall impact values ​​of different years in combination with the rainfall in different historical rainfall times, and determines whether there are years in which the rainfall impact values ​​do not meet the requirements. If so, proceed to the next step; if not, use the initial prediction and warning indicators to determine the prediction and warning indicators of the mountain in different dimensions; S15 obtains the rainfall in different years, and determines the rainfall impact values ​​in different years in combination with the rainfall in different historical rainfall times, and determines whether there are years in which the rainfall impact values ​​do not meet the requirements, and if so, proceeds to the next step, and if not, corrects the initial prediction and warning indicators of the mountain in different dimensions based on the number of years in which the rainfall impact values ​​do not meet the requirements to obtain the prediction and warning indicators of the mountain in different dimensions; S16 determines the average annual rainfall times and average annual rainfall amount of the mountain based on rainfall statistical data of different years, and determines the rainfall influence factor of the mountain based on the average annual rainfall times and average annual rainfall, and uses the rainfall influence factor to correct the initial prediction and warning index to obtain the prediction and warning index of the mountain in different dimensions; The rainfall impact factor is determined according to a preset mapping relationship; The method for determining the benchmark early warning indicator is: The indicator deviation of the forecast and early warning indicators of different dimensions is determined by using the rainfall data in different historical flash flood outbreaks and the indicator data deviation of the forecast and early warning indicators of different dimensions; Determine the deviation indexes in different historical flash flood outbreaks according to the index deviations of the prediction and early warning indexes in different dimensions, and determine the comprehensive deviations of the indexes in different historical flash flood outbreaks by using the number of deviation indexes and the index deviations of different deviation indexes; Determine the benchmark flash flood period in the historical flash flood process by using the comprehensive deviation of indicators in different historical flash flood processes, and use the early warning indicator corresponding to the benchmark flash flood period as the benchmark early warning indicator; The reference rainfall period in the rainfall period is all rainfall periods after the reference flash flood period; Determining that the forecast and early warning indicators are biased includes: Using flash flood data of different rainfall periods, the rainfall period is divided into a flash flood rainfall period and a non-flash flood rainfall period; Determine the deviation of rainfall data in the flash flood period and the deviation of rainfall data in the non-flash flood period based on the deviation of rainfall data in different flash flood periods and the forecast and warning indicators, and the deviation of rainfall data in the non-flash flood period and the forecast and warning indicators; The indicator data accuracy of the forecast and early warning indicator is calculated by the deviation of the rainfall data in the outbreak period and the deviation of the rainfall data in the non-outbreak period, and the indicator data accuracy is used to determine whether the forecast and early warning indicator has a deviation; The method for determining the early warning index of the mountain flood is as follows: Determine the rainfall data deviation of the reference rainfall period according to the deviation between the rainfall data of the reference rainfall period and the prediction and warning indicators of different dimensions, and use the rainfall data deviation to determine the effective reference rainfall period in the reference rainfall period; Determine the early warning indicator compensation amount of different effective reference rainfall periods by using the rainfall data deviation amount of different effective reference rainfall periods, the interval length with adjacent reference rainfall periods, and the rainfall data of different adjacent reference rainfall periods; The benchmark warning index is corrected according to the warning index compensation amount of different effective reference rainfall periods to obtain the warning index of the mountain flood.

2. The method for determining dynamic early warning indicators for flash flood disasters according to claim 1, characterized in that: The topographic data of the mountain area is determined based on the analysis results of the surveying and mapping image data of the mountain area.

3. The method for determining dynamic early warning indicators for flash flood disasters according to claim 1, characterized in that: The mountain area is divided according to the preset area of ​​the mountain.

4. The method for determining dynamic early warning indicators for flash flood disasters according to claim 1, characterized in that: Determining whether the prediction and early warning indicators have deviations by using the accuracy of the indicator data includes: When the accuracy of the indicator data is less than the preset accuracy, it is determined that there is a deviation in the prediction and warning indicator.

5. A computer system comprising: A memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, a method for determining dynamic warning indicators for flash flood disasters as described in any one of claims 1-4 is executed.

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