Dam overtopping risk degree calculation system based on hec-hms hydrological model simulation

Abstract

This invention belongs to the field of reservoir overtopping risk prediction technology, specifically involving an overtopping risk calculation system based on the HEC-HMS hydrological model simulation. This risk calculation system includes a data reading module, a data extraction module, a numerical simulation module, a random sampling module, a calculation module, a statistical module, a risk assessment module, and a central control unit. This calculation system can perform comprehensive calculations based on the reservoir's initial regulating water level, wind bulge height on the reservoir surface, and wave run-up data, thereby obtaining a more accurate overtopping risk rate. This allows residents around or downstream of the reservoir to evacuate in a timely manner, minimizing losses to their lives and property. Simultaneously, by combining the overtopping hazard assignment model, it accurately determines the overtopping hazard level, enabling people to take appropriate response measures based on different alarm information, thus avoiding subsequent damage to residents' lives and property from overtopping.

Description

Technical Field

[0001] This invention belongs to the field of reservoir overtopping risk prediction technology, specifically involving an overtopping risk calculation system based on HEC-HMS hydrological model simulation. Background Technology

[0002] Overtopping is a highly destructive and catastrophic disaster for reservoirs. Uncertainties in the reservoir's initial regulating water level, wind bulge height, and wave rise are all important factors that can cause overtopping. While the dam height is fixed, overtopping can threaten the lives and property of residents living downstream. Therefore, calculating the risk of overtopping is essential. Researchers consider the impact of the surrounding environment on the reservoir's water level and input this information into various hydrological models to calculate the risk of overtopping, thereby determining the trend of water level changes and using this as the basis for the risk assessment of overtopping.

[0003] However, existing calculations of dam overtopping risk mainly focus on the initial adjustment water level of the reservoir, lacking research on wind speed and volume above the reservoir surface. When the initial adjustment water level is lower than the dam height, strong winds can cause excessively high surging waves on the reservoir surface. These surging waves are very likely to overtake the dam, thereby threatening the lives and property of residents around or downstream of the reservoir. Summary of the Invention

[0004] The purpose of this invention is to provide a dam overtopping risk calculation system based on the HEC-HMS hydrological model simulation. It can perform comprehensive calculations based on the reservoir's initial water level, wind bulge height on the reservoir surface, and wave run-up data, thereby obtaining a more realistic dam overtopping risk rate. This allows residents around or downstream of the reservoir to evacuate in a timely manner, minimizing the loss of their lives and property.

[0005] The specific technical solution adopted by this invention is as follows:

[0006] The overtopping risk calculation system based on the HEC-HMS hydrological model simulation includes a data reading module, a data extraction module, a random sampling module, a statistics module, a calculation module, a risk assessment module, and a central control unit.

[0007] The data reading module is used to read the feature information that affects the reservoir dam overflow, wherein the feature information includes multiple element information that affects the reservoir dam overflow;

[0008] The numerical simulation module is used to substitute the first variable information into the HEC-HMS hydrological model and perform data interpolation in the form of numerical simulation to form the first variable information without missing information.

[0009] The data extraction module is used to extract first variable information and second variable information from the element information;

[0010] The random sampling module is used to randomly extract multiple sets of first sample information that affect the risk rate of reservoir overtopping based on the first variable information.

[0011] The statistical module is used to read multiple sets of the first sample information and substitute them into the statistical model to obtain the second sample information that satisfies the statistical model.

[0012] The calculation module is used to substitute the second sample information and the second variable information into the dam inundation risk calculation model to obtain the dam inundation risk rate of the reservoir.

[0013] The risk assessment module is used to substitute the dam inrush risk rate into the dam inrush hazard assignment model to obtain the dam inrush hazard.

[0014] The central control unit is used to connect the data reading module, data extraction module, random sampling module, calculation module, statistics module and risk assessment module.

[0015] In a preferred embodiment, the first variable information is environmental information affecting the reservoir overtopping, including wind bulge height and wave run-up, and the second variable information is baseline information affecting the reservoir overtopping, including reservoir starting water level information.

[0016] In a preferred embodiment, the random sampling module randomly selects multiple sets of first sample information affecting the reservoir overtopping risk rate based on the first variable information as follows:

[0017] Determine the sampling period, set it to (q1, q2), where q1 is the start time point and q2 is the end time point;

[0018] The function for generating random numbers for wind bulge height is: Among them, X i The height of the wind dam is represented by a random number. σ represents the mean height of the wind bulge. x u represents the root mean square error of the wind bulge height. i This represents the uniform distribution number of wind bulge height within the interval (q1, q2);

[0019] Obtain wind speed information on the reservoir surface and calculate the average wind bulge height based on it. and mean square error σ x ,in, In the formula, K represents the overall friction coefficient. σ represents the mean effective wind speed over the reservoir surface. WThe root mean square error of the effective wind speed over the reservoir surface is represented by , D represents the wind distance over the reservoir, g is the acceleration due to gravity, and H represents the average water depth of the reservoir area.

[0020] The function for extracting random numbers from the wave climb is: Among them, Y i v represents a random number indicating the wave's rise. i This represents the uniform distribution number of wave rise within the interval (q1, q2), where v represents the distribution parameter, specifically... θ represents the mean of the wave rise. x This represents the mean squared error of the wave rise;

[0021] Obtain wind speed information on the reservoir surface, and substitute this information into the formula. and In the formula, K Δ K represents the slope roughness and permeability coefficient. W Represents the empirical coefficient. This represents the average wave height. The wavelength of the wave is represented by λ, and the slope coefficient of the slope is represented by m.

[0022] The random numbers for wind bulge height and wave rise are extracted and determined as the first sample information.

[0023] In a preferred embodiment, a function is constructed using the statistical model, and the first sample information is substituted into the function.

[0024] The standard formula for the function is G. j +X i +Y i ≥D, where G j D represents the initial water level, and D represents the dam crest height.

[0025] The total number of samples for the random numbers of wind bulge height and wave rise is determined to be i, where i is a positive integer greater than zero;

[0026] Arrange the random numbers for wind bulge height and wave rise into multiple sets of position data in descending order of position, and then substitute the position data into the function in descending order of position.

[0027] If the substituted position data satisfies the function, then continue to substitute the next set of data into the function according to the position.

[0028] If the substituted position data does not satisfy the function, then stop substituting position data into the function.

[0029] Extract all positional data that satisfy the functional function and determine them as the second sample information.

[0030] In a preferred embodiment, a flood dam risk rate function is constructed based on the risk degree calculation model. The second sample information and the second variable information are then substituted into the flood dam risk rate function to obtain... In the formula, P represents the overtopping risk rate, n represents the positional data that satisfies the function, and n < i.

[0031] In a preferred embodiment, the height of the initial adjustment water level is sampled based on the height of the reservoir dam, specifically as follows:

[0032] The height of the dam crest is determined as h, and two-thirds of the dam height is marked as the baseline that can cause the dam to overflow.

[0033] The value is determined by taking the height from two-thirds of the dam's height to the dam crest.

[0034] After determining the number of samples for the second feature information, in the interval The equal amounts of the initial adjustment water level height G are distributed. j .

[0035] In a preferred embodiment, the overtopping risk model is as follows: Where Q represents the risk of overtopping, P s P represents the acceptable rate of dam overflow risk to the general public. d This indicates the frequency corresponding to the reservoir design standard, where b is a defined parameter;

[0036] The hazard level is determined based on the value of the dam overflow hazard.

[0037] When 0 ≤ Q ≤ 0.2, the risk level of the dam overflow is low.

[0038] When 0.2≤Q≤0.6, the risk level of the dam overflow is moderate.

[0039] When Q > 0.6, the risk level of the dam overflow is high.

[0040] In a preferred embodiment, if the dam overflow hazard level is determined to be low risk, the central control unit does not provide any feedback.

[0041] If the risk level of the dam overflow is determined to be moderate, the central control unit generates an abnormal signal and transmits it to the alarm. The alarm receives the instruction and issues a level one alarm message.

[0042] If the risk level of the dam overflow is determined to be high risk, the central control unit generates an abnormal signal and transmits it to the alarm. The alarm receives the instruction and issues a level two alarm message.

[0043] The level of the secondary alarm information is higher than that of the primary alarm information.

[0044] In a preferred embodiment, the central control unit is used to transmit and receive information between the data reading module, data extraction module, random sampling module, calculation module, statistics module, and risk assessment module.

[0045] The present invention also provides a device for calculating the risk of overtopping based on the HEC-HMS hydrological model simulation, including a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program to implement the calculation process of the overtopping risk calculation system described above.

[0046] The technical effects achieved by this invention are as follows:

[0047] This invention uses a combination of wind bulge height and wave run-up height to obtain wind and wave data on the reservoir surface. This wind and wave data is then combined with the initial adjustment water level and substituted into the overtopping risk rate function. This allows for the acquisition of the overtopping risk rate under different wind bulge height and wave run-up height data. Furthermore, this calculation result can more realistically reflect the overtopping risk rate of the reservoir, so as to alert people to take timely countermeasures.

[0048] This invention uses a dam overflow risk model to rate the risk level. Since there are corresponding drainage systems in the residential areas around or downstream of the reservoir, the overflow water volume under low risk will not exceed the drainage capacity of the drainage system, and therefore will not affect the residential areas around or downstream of the reservoir. Thus, no corresponding response plan is needed. If the risk level reaches medium or high, it means that the safety of residents' lives and property will be greatly affected. At this time, evacuation should be arranged in time to avoid the subsequent overflow water volume from causing damage to the safety of residents' lives and property. Attached Figure Description

[0049] Figure 1 This is a flowchart of the overtopping risk calculation system provided in an embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram of the internal structure of a computing device provided in an embodiment of the present invention. Detailed Implementation

[0051] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0052] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0053] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that mutually excludes other embodiments.

[0054] Secondly, the present invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of the present invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not according to the usual scale. Furthermore, the schematic diagrams are merely examples and should not limit the scope of protection of the present invention. In addition, actual fabrication should include three-dimensional spatial dimensions of length, width, and depth.

[0055] Please see the appendix Figure 1 As shown, the present invention provides a dam overtopping risk calculation system based on HEC-HMS hydrological model simulation, including a data reading module, a data extraction module, a random sampling module, a statistics module, a calculation module, a risk assessment module, and a central control unit;

[0056] The data reading module is used to read the characteristic information that affects the reservoir dam overflow, including information on multiple factors that affect the reservoir dam overflow.

[0057] The data extraction module is used to extract first variable information and second variable information from feature information;

[0058] The numerical simulation module is used to substitute the first variable information into the HEC-HMS hydrological model and perform data interpolation in the form of numerical simulation to form the first variable information without missing information.

[0059] The random sampling module is used to randomly select multiple sets of first sample information that affect the risk rate of reservoir overtopping based on the first variable information;

[0060] The statistics module is used to read multiple sets of first sample information and substitute them into the statistical model to obtain second sample information that satisfies the statistical model.

[0061] The calculation module is used to substitute the second sample information and the second variable information into the dam inundation risk calculation model to obtain the dam inundation risk rate of the reservoir;

[0062] The risk assessment module is used to substitute the overtopping risk rate into the overtopping hazard assignment model to obtain the overtopping hazard level;

[0063] The central control unit is used to connect the data reading module, data extraction module, random sampling module, calculation module, statistics module and risk assessment module. The central control unit is used to send and receive information between the data reading module, data extraction module, random sampling module, calculation module, statistics module and risk assessment module.

[0064] Specifically, after the data reading module reads multiple factors affecting the reservoir's overtopping, it sends a reading completion signal to the central control unit. Upon receiving this signal, the central control unit controls the data extraction module to operate. The data extraction module extracts first variable information and second variable information from the multiple factors. The difference between the first variable information and the second variable information lies in the different factors affecting their changes. Information directly related to the reservoir is recorded as the second variable information, while information related to the environment is recorded as the first variable information. The first variable information is environmental information affecting the reservoir's overtopping, including wind bulge height and wave run-up. The second variable information is baseline information affecting the reservoir's overtopping, including the reservoir's initial regulation water level. Wind bulge height and wave run-up are not directly related. These are independent variables. When the wind bulge height is high, the wave run-up on the reservoir surface will also increase accordingly. Conversely, when the wave run-up is high, the wind bulge height on the reservoir surface will necessarily be relatively high. This is the specific variable studied in this scheme. The change in the regulating water level information is closely related to the reservoir's discharge capacity, reservoir capacity, and precipitation in the reservoir area. Compared to the wind bulge height and wave run-up, the regulating water level has a relatively long change cycle, and the change is slow and not too drastic. Its impact on the reservoir overtopping time is a long-term factor. Conversely, the wind bulge height and wave run-up are short-term or instantaneous factors affecting the occurrence of reservoir overtopping events. Because the reservoir's regulating water level information has a long change cycle and the change is relatively rapid, the regulation water level is a long-term factor. Because the dam height is small, direct sampling is used. However, the uncertainty of wind bulge height and wave rise is significant, so sampling needs to be performed within a fixed period. After extracting the first variable information, the data extraction module sends an extraction completion signal to the central control unit. Upon receiving this signal, the central control unit sends a sampling instruction to the random sampling module. After receiving the instruction, the random sampling module works in conjunction with the statistical module to obtain a random value that satisfies the dam overflow risk rate, i.e., the second sample information. After the first variable information sampling is completed, the statistical module sends a sampling end signal to the central control unit. Upon receiving this signal, the central control unit sends a calculation quality to the calculation module. The calculation module then performs calculations based on the information provided by the statistical module. After the second sample information is combined with the second variable information for calculation, the overtopping risk rate of the reservoir can be obtained. After the overtopping risk rate is determined, the central control unit will also receive the value of this overtopping risk rate. Then, the control risk assessment module will evaluate the overtopping risk rate to obtain the level of overtopping risk. This level of overtopping risk information will be fed back to the central control unit. The central control unit will determine whether to send a signal to the alarm based on this level of overtopping risk information. If it is a low risk, no signal will be sent. If it is a medium or high risk, different levels of alarm instructions will be sent to the alarm. After receiving this instruction, the alarm will issue the corresponding medium or high risk alarm signal.

[0065] In a preferred embodiment, the random sampling module randomly selects multiple sets of first sample information affecting the reservoir overtopping risk rate based on the first variable information as follows:

[0066] S1. Determine the sampling period, set it as (q1, q2), where q1 is the start time point and q2 is the end time point;

[0067] S2, The function for generating random numbers for wind bulge height is: Among them, X i The height of the wind dam is represented by a random number. σ represents the mean height of the wind bulge. x u represents the root mean square error of the wind bulge height. i This represents the uniform distribution number of wind bulge height within the interval (q1, q2);

[0068] S3. Obtain wind speed information on the reservoir surface and calculate the average wind bulge height based on it. and mean square error σ x ,in, In the formula, K represents the overall friction coefficient. σ represents the mean effective wind speed over the reservoir surface. W The root mean square error of the effective wind speed over the reservoir surface is represented by , D represents the wind distance over the reservoir, g is the acceleration due to gravity, and H represents the average water depth of the reservoir area.

[0069] S4. The function for extracting random numbers from the wave climb is: Among them, Y i v represents a random number indicating the wave's rise. i This represents the uniform distribution number of wave rise within the interval (q1, q2), where v represents the distribution parameter, specifically... θ represents the mean of the wave rise. x This represents the mean squared error of the wave rise;

[0070] S5. Obtain wind speed information on the reservoir surface and substitute it into the formula. and In the formula, K Δ K represents the slope roughness and permeability coefficient. W This represents an empirical coefficient, the value of which is related to wind speed and the average water depth of the basin, and can be determined by referring to a table. This represents the average wave height. The wavelength of the wave is represented by λ, and the slope coefficient of the slope is represented by m.

[0071] S6. Extract random numbers of wind bulge height and wave rise, and determine them as the first sample information.

[0072] As described in steps S1-S6 above, in this embodiment, the sampling of wind bulge height and wave run-up height both adopt the inverse function method. Compared with the mean first second moment method, direct integration method, etc., its solution process is simpler. When sampling, it is necessary to obtain effective wind speed information on the reservoir surface. Generally, the wind speed information obtained is between 5 and 10 meters above the reservoir surface. The wind speed in this range has a significant direct impact on the reservoir surface, and the wind speed determines the height of wave run-up. Therefore, when sampling wave run-up height, it is also based on the wind speed information between 5 and 10 meters above the reservoir surface.

[0073] In a preferred implementation, a function is constructed using a statistical model, and the information from the first sample is substituted into the function.

[0074] The standard formula for the function of performance is G. j +X i +Y i ≥D, where G j This indicates the starting water level. Here, the starting water level is set to be close to the top of the reservoir dam. Specifically, it can be set to 90% of the top of the reservoir dam. D represents the height of the dam top.

[0075] The total number of samples for determining the random number of wind bulge height and the random number of wave rise is i, where i is a positive integer greater than zero;

[0076] Arrange the random numbers for wind bulge height and wave rise into multiple sets of position data in descending order of position, and then substitute the position data into the function in descending order of position.

[0077] If the substituted position data satisfies the function, then continue to substitute the next set of data into the function according to the position.

[0078] If the substituted position data does not satisfy the function, then stop substituting position data into the function.

[0079] Extract all positional data that satisfy the functional function and determine them as the second sample information.

[0080] It should be noted that when sampling the random numbers for wind bulge height and wave rise, there are a total of i 2 We have a set of sample data, but strong winds inevitably bring large waves, while gentle breezes cannot create excessive waves on the reservoir surface. Therefore, during sorting, both are matched from high to low, resulting in set i of data. The cardinality of the sample data is correspondingly reduced in this case. However, to ensure the accuracy of the calculation results, we take 10,000 sets of data as an example, where i = 10,000. The cardinality of the resulting sample data is quite large. This embodiment mainly studies the overtopping risk rate, so in i... 2The sample data of each group will contain a large number of sample values ​​that do not meet the overtopping risk rate. If each group of data is substituted into the function, the amount of calculation will be huge. Therefore, the sample data of wind dam height and wave run-up are arranged in descending order to obtain the corresponding position data. If the substituted position data does not meet the function, then the data with a lower position than that position data must not meet the function. At this time, the position data that affects the reservoir overtopping can be screened out, which is the second sample information to participate in the subsequent risk rate calculation.

[0081] It should be further noted that the above ranking data are all calculated based on the assumption that the starting water level is above 90% of the reservoir dam height. However, the starting water level is also a variable. The range of starting water levels determined in this embodiment is within the range of... Therefore, the required positional data will vary depending on the initial water level of the reservoir. The calculation method is the same as described above. As the initial water level is set lower, the required wind bulge height and wave rise sample values ​​will gradually decrease. At this time, the calculation can be performed from low to high based on the positional data obtained above, which can reduce the amount of calculation and obtain the required second sample information more quickly.

[0082] In a preferred embodiment, a flood dam risk rate function is constructed based on a risk degree calculation model. The second sample information and the second variable information are then substituted into the flood dam risk rate function to obtain... In the formula, P represents the overtopping risk rate, n represents the positional data that satisfies the function, and n < i.

[0083] Furthermore, different starting water level heights G j The number of positional data n corresponding to the functional function is also inconsistent, resulting in different starting water level heights G. j The risk rates of dam overflow also vary, with wind dam height and wave run-up still playing a decisive role.

[0084] In a preferred embodiment, the height of the initial regulating water level is sampled based on the height of the reservoir dam, specifically:

[0085] The height of the dam crest is determined as h, and two-thirds of the dam height is marked as the baseline that can cause the dam to overflow.

[0086] The value is determined by taking the height from two-thirds of the dam's height to the dam crest.

[0087] After determining the number of samples for the second feature information, in the interval The equal amounts of the initial adjustment water level height G are distributed. j .

[0088] It should be noted that the dam height of the reservoir is fixed, and direct sampling is the simplest method for sampling. In this embodiment, two-thirds of the dam height is set as the minimum starting water level, which is also used as the benchmark value for the danger level. This means that when the starting water level is at this benchmark value, the water in the reservoir is severely affected by wind and waves, making it easy for the water in the reservoir to overflow the dam.

[0089] In a preferred embodiment, the overtopping risk model is as follows: Where Q represents the risk of overtopping, P s P represents the acceptable rate of dam overflow risk to the general public. d This indicates the frequency corresponding to the reservoir design standard, where b is a defined parameter;

[0090] The hazard level is determined based on the value of the hazard degree of the dam overflow.

[0091] When 0 ≤ Q ≤ 0.2, the risk level of the dam overflow is low.

[0092] When 0.2≤Q≤0.6, the risk level of the dam overflow is moderate.

[0093] When Q > 0.6, the risk level of the dam overflow is high.

[0094] It should be noted that rating the risk of dam overflow allows for better response measures. For example, in a low-risk situation, even if the reservoir overflows, the drainage system located around or downstream can handle the overflow volume, and it will not affect the lives and property of residents in the area. In a medium-risk situation, it indicates that the drainage system around or downstream of the reservoir cannot effectively handle the overflow volume, meaning that the overflow volume is greater than the drainage system's discharge capacity. This will have a certain impact on the lives and property of residents in the area, and to ensure safety, residents in the area need to be advised to evacuate when it is safe to do so. When the dam overflow risk level reaches high danger, it means that the overflow volume is much greater than the drainage capacity of the surrounding or downstream drainage systems, indicating that the drainage system is almost ineffective, and residents in the area need to be ordered to evacuate urgently for their own safety.

[0095] Furthermore, to calculate the mean and standard deviation of wind bulge height and wave run-up in future periods, it is necessary to obtain effective wind speed data above the reservoir surface for future periods. This information can be predicted based on historical statistical data of the reservoir area. After the reservoir is determined, the amount of rainfall has the greatest impact on the starting water level. The change in the starting water level can be calculated based on the amount of rainfall. Substituting this data into the function, the wind bulge height and wave run-up data with the risk of dam overflow can be predicted. Based on this information, the wind bulge height and wave run-up in the reservoir area can then be monitored.

[0096] In a preferred embodiment, if the dam overflow hazard level is determined to be low risk, the central control unit does not provide any feedback.

[0097] If the risk level of the dam overflow is determined to be moderate, the central control unit generates an abnormal signal and transmits it to the alarm. The alarm receives the instruction and issues a level one alarm.

[0098] If the risk level of the dam overflow is determined to be high, the central control unit generates an abnormal signal and transmits it to the alarm. The alarm receives the instruction and issues a level two alarm message.

[0099] Level 2 alarm information is of a higher level than Level 1 alarm information.

[0100] Furthermore, by using different levels of alarm information corresponding to different levels of danger, once the danger of dam overflow is estimated, people can make different response plans in a timely manner based on the different alarm information, thereby effectively protecting the safety of residents' lives and property. Under normal circumstances, the danger level of dam overflow will not immediately reach a high level of danger. Usually, a level one alarm information is issued first. As the wind bulge height, wave rise and the starting water level increase, if the level one alarm information has a long period of time, there is a high probability that a level two alarm information will be issued later. However, the order to evacuate residents around the reservoir or downstream should be notified at the moment the level one alarm information is issued, and the evacuation should be completed before the level two alarm information is issued, so as to avoid threatening the safety of residents' lives.

[0101] The present invention also provides a device for calculating the risk of dam overflow based on the HEC-HMS hydrological model simulation, including a memory storing a computer program, and a processor executing the computer program to implement the calculation process of any of the above-mentioned dam overflow risk calculation systems.

[0102] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0103] The above description is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained in this invention are implemented according to conventional methods in the art unless otherwise specified or limited.

Claims

1. A system for calculating the risk of overtopping dams based on HEC-HMS hydrological model simulation, characterized in that: It includes a data reading module, a data extraction module, a numerical simulation module, a random sampling module, a statistics module, a calculation module, a risk assessment module, and a central control unit; The data reading module is used to read the characteristic information that affects the reservoir dam overflow, wherein the characteristic information includes multiple element information that affects the reservoir dam overflow; The data extraction module is used to extract first variable information and second variable information from the element information; The numerical simulation module is used to substitute the first variable information into the HEC-HMS hydrological model and perform data interpolation in the form of numerical simulation to form the first variable information without missing information. The random sampling module is used to randomly extract multiple sets of first sample information that affect the risk rate of reservoir overtopping based on the first variable information. The statistical module is used to read multiple sets of the first sample information and substitute them into the statistical model to obtain the second sample information that satisfies the statistical model. The calculation module is used to substitute the second sample information and the second variable information into the dam inundation risk calculation model to obtain the dam inundation risk rate of the reservoir. The risk assessment module is used to substitute the dam inundation risk rate into the dam inundation hazard assignment model to obtain the dam inundation hazard. The central control unit is used to connect the data reading module, data extraction module, random sampling module, calculation module, statistics module and risk assessment module; The random sampling module randomly selects multiple sets of first sample information affecting the reservoir overtopping risk rate based on the first variable information as follows: Determine the sampling period and set it to... ,in As the starting time point, The end time point; The function for generating random numbers for wind bulge height is: ,in, The height of the wind dam is represented by a random number. This represents the average height of the wind bulge. This represents the standard deviation of the wind bulge height. Representing an interval The uniform distribution of internal wind dam height; Obtain wind speed information on the reservoir surface and calculate the average wind bulge height based on it. and mean square deviation ,in, , In the formula, This represents the overall friction coefficient. This represents the average effective wind speed over the reservoir surface. This represents the standard deviation of the effective wind speed above the reservoir surface. Indicates the reservoir's pumping speed. It is the acceleration due to gravity. This indicates the average water depth of the reservoir. The function for extracting random numbers from the wave climb is: ,in, This represents a random number representing the wave's rise. Representing an interval The uniform distribution of the inner wave climb. Represents the distribution parameters, specifically: , This represents the average rise of the wave. This represents the mean squared error of the wave rise; Obtain wind speed information on the reservoir surface, and substitute this information into the formula. and In the formula, Represents the slope roughness and permeability coefficient. Represents the empirical coefficient. This represents the average wave height. This represents the average wavelength of the wave. This represents the slope coefficient of the slope. Extract the random numbers of wind bulge height and wave rise, and determine them as the first sample information; A functional function is constructed based on the statistical model, and the information of the first sample is substituted into the functional function; The standard formula for the function is: + + ≥ In the formula, Indicates the initial water level height. Indicates the height of the dam crest; The total number of samples for determining the wind bulge height random number and the wave run-up random number is 1. ,in, It is a positive integer greater than zero; Arrange the random numbers for wind bulge height and wave rise into multiple sets of position data in descending order of position, and then substitute the position data into the function in descending order of position. If the substituted position data satisfies the function, then continue to substitute the next set of data into the function according to the position. If the substituted position data does not satisfy the function, then stop substituting position data into the function. Extract all positional data that satisfy the functional function and determine them as the second sample information; Based on the risk calculation model, a flood dam risk rate function is constructed. The second sample information and the second variable information are then substituted into the flood dam risk rate function to obtain... In the formula, Indicates the risk rate of dam overflow. This represents the positional data that satisfies the functional function, and < .

2. The overtopping risk calculation system based on HEC-HMS hydrological model simulation according to claim 1, characterized in that: The first variable information is environmental information that affects the reservoir overflow, including wind bulge height and wave run-up. The second variable information is baseline information that affects the reservoir overflow, including the reservoir's initial water level.

3. The overtopping risk calculation system based on HEC-HMS hydrological model simulation according to claim 1, characterized in that: The height of the initial water level is based on a sampling of the reservoir dam height, specifically: The height of the dam crest is determined as h, and two-thirds of the dam height is marked as the baseline that can cause the dam to overflow. The value is determined by taking the height from two-thirds of the dam's height to the dam crest. ; After determining the number of second sample information, in the interval Divide the water level into equal portions. .

4. The overtopping risk calculation system based on HEC-HMS hydrological model simulation according to claim 1, characterized in that: The risk model for the overtopping dam is as follows: ,in, Indicates the degree of danger of the dam overflow. This indicates the acceptable rate of dam overflow risk to the general public. This indicates the frequency corresponding to the reservoir design standard. For definite parameters; The hazard level is determined based on the value of the dam overflow hazard. When 0≤ When the value is ≤0.2, the risk level of dam overflow is low. When 0.2≤ When the value is ≤0.6, the risk level of dam overflow is moderate. when When the value is greater than 0.6, the risk level of dam overflow is classified as highly dangerous.

5. The overtopping risk calculation system based on HEC-HMS hydrological model simulation according to claim 4, characterized in that: If the risk level of the dam overflow is determined to be low, the central control unit will not provide any feedback. If the risk level of the dam overflow is determined to be moderate, the central control unit generates an abnormal signal and transmits it to the alarm. The alarm receives the instruction and issues a level one alarm message. If the risk level of the dam overflow is determined to be high risk, the central control unit generates an abnormal signal and transmits it to the alarm. The alarm receives the instruction and issues a level two alarm message. The level of the secondary alarm information is higher than that of the primary alarm information.

6. The overtopping risk calculation system based on HEC-HMS hydrological model simulation according to claim 1, characterized in that: The central control unit is used to transmit and receive information between the data reading module, data extraction module, random sampling module, calculation module, statistics module, and risk assessment module.

7. A device for calculating the risk of overtopping dams based on HEC-HMS hydrological model simulation, characterized in that: It includes a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the calculation process of the dam risk calculation system according to any one of claims 1 to 6.

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