An intelligent water conservancy monitoring method for sudden flood of river in flood season

Abstract

The application discloses an intelligent water conservancy monitoring method for sudden flood rise of a river in a flood season, and relates to the technical field of water conservancy projects, which comprises the following steps: obtaining at least one target tributary set; analyzing a floating deviation value of a normal water level; regarding a part of river water above a reference surface and located in a target monitoring area as a characteristic part; analyzing a moving speed and a shape vector of the characteristic part; establishing a flood rise estimation model to estimate a peak water level and a peak speed of the target tributary; estimating a confluence water level of the target tributary in the target river after confluence, and analyzing a critical water level of the target river in the flood rise. Through the classification of the target tributary according to the correlation of the flood rise, the formation of the floating deviation value, and the estimation of the peak water level and the peak speed of the target tributary, the confluence water level after confluence in the target river can be predicted according to the obtained parameters, so that the scale of the flood rise that has not yet appeared can be predicted.

Description

Technical Field

[0001] This invention relates to the field of water conservancy engineering technology, specifically to an intelligent water conservancy monitoring method for sudden rises in river water levels during the flood season. Background Technology

[0002] River floods are natural phenomena caused by factors such as torrential rain, snowmelt, ice jams, or failures in water conservancy projects, resulting in a surge in water volume and a rapid rise in water levels in rivers and lakes. Monitoring rivers and predicting future water level rises based on the monitoring results allows for advance preparation of flood discharge by water conservancy facilities. However, current technology lacks predictive monitoring capabilities for river water levels. Furthermore, the existence of multiple tributaries in the upper reaches of rivers and the lack of research on their confluence patterns make accurate predictive monitoring difficult. Summary of the Invention

[0003] To address the aforementioned technical problems, an intelligent water conservancy monitoring method for sudden rises in river water levels during the flood season is provided. This technical solution solves the problems mentioned in the background section.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A smart water conservancy monitoring method for sudden rises in river water levels during the flood season includes: Acquire the target river to be monitored, acquire at least one target tributary flowing into the target river, and install water conservancy monitoring equipment at the confluence of the target tributary and the target river; The target tributaries are classified according to their correlation with the rise in water level, resulting in at least one set of target tributaries; Obtain the maximum monitoring distance of the water conservancy monitoring equipment and the target monitoring area of ​​the water conservancy monitoring equipment; Based on the changes in river water level during the flood season, the fluctuation deviation value of the normal water level is obtained by analysis; Based on historical monitoring data, a reference surface is formed for the water surface within the target monitoring area, and the portion of the river water above the reference surface and located within the target monitoring area is taken as the feature part; At least one monitoring image of the feature portion moving within the target monitoring area is acquired, and the moving speed and shape vector of the feature portion are analyzed based on the monitoring image. A flood forecasting model is established, and the peak water level and peak velocity of the target tributary are estimated based on the flood forecasting model. The confluence water level of the target tributaries in the target tributary set after they converge in the target river is estimated. Based on historical data, the critical water level of the target river for flooding is analyzed. If the confluence water level exceeds the critical water level, it is determined that the target river will experience a sudden flood; otherwise, it is determined that the target river will not experience a sudden flood.

[0005] Preferably, classifying the target tributaries according to their correlation with flood level to obtain at least one set of target tributaries includes the following steps: The location where the target tributary flows into the target river is used as the feature location. The feature locations are numbered according to the order in which the river water passes through the target river. The feature location numbers are then matched with the target tributary corresponding to the feature location. Obtain at least one historical flood level of the target river, and summarize the target tributaries that have experienced flooding in the historical flood level to form a feature set of historical flood level; Target rivers with consecutive numbers in the feature set are considered as associated rivers, and the associated target rivers are aggregated to form a target tributary set.

[0006] Preferably, the acquisition of the target monitoring area of ​​the water conservancy monitoring equipment includes the following steps: The target tributary is uniformly divided into at least one sampling block. If the distance from the center of the sampling block to the corresponding characteristic location of the target tributary does not exceed the maximum monitoring distance, the sampling block is used as a characteristic sampling block. The characteristic sampling blocks of the target tributary are summarized to obtain the target monitoring area of ​​the water conservancy monitoring equipment installed on the target tributary.

[0007] Preferably, the analysis to obtain the fluctuation deviation value of the normal water level includes the following steps: A preset time is formed, and at least one time group is formed when the target tributary has not risen. The time group consists of two characteristic times with an interval equal to the preset time. At the time point equal to the characteristic time, the water level of the target tributary is statistically analyzed to obtain at least one normal water level. The normal water levels collected at the characteristic time in the time group are subtracted and the absolute value is taken to obtain the preliminary deviation. The maximum value of all the preliminary deviations of at least one target tributary is taken as the floating deviation value. The specific time for setting the preset time is as follows: At least one sampling point is collected evenly throughout the day. At the sampling point, the water level of the target tributary is statistically analyzed to obtain the sampling water level. Arrange the water levels collected at the sampling points in the order of the sampling points, and take one of the water levels at least once as the characteristic water level. If the product of the differences between two adjacent water levels and the characteristic water level is positive, then the characteristic water level is taken as the target water level. When the feature sampling water level traverses at least one sampling water level, at least one target sampling water level is obtained. The difference between the sampling points corresponding to adjacent target sampling water levels is calculated and the absolute value is taken to obtain the reference time. The minimum value of the reference time of all target tributaries is taken as the preset time.

[0008] Preferably, the process of establishing a reference surface for the water surface within the target monitoring area includes the following steps: At least one sample point is evenly selected from the dates of the year. In the historical monitoring data, at least one historical water level at the sample point is obtained. The average water level of the sample point is obtained by taking the average of the at least one historical water level at the sample point. The floating deviation value is superimposed with the average water level of the sample point to obtain the sample water level of the sample point. The sample points are paired with the corresponding sample water levels and fitted to obtain a reference fitting function. The current monitoring date is then substituted into the reference fitting function to obtain the reference water level. The plane containing the water surface of the reference water level is used as the reference surface.

[0009] Preferably, the analysis to obtain the moving speed and shape vector of the feature portion includes the following steps: At least one dividing line is taken at equal intervals within the target monitoring area, and the dividing line is perpendicular to the riverbank of the target tributary where the target monitoring area is located; The distance from the dividing line to the corresponding water conservancy monitoring equipment in the target monitoring area is used as the characteristic distance. The difference between the maximum and minimum values ​​of the characteristic distance is used to obtain the benchmark distance. The time when the feature first reaches the dividing line is taken as the accompanying time of the dividing line. The difference between the maximum and minimum values ​​of the accompanying time is used to obtain the reference time. The reference distance is divided by the reference time to obtain the moving speed of the feature. Arrange the dividing lines according to their corresponding feature distances from smallest to largest to obtain a dividing line sequence; At least one dividing point is uniformly selected on the dividing line. When the characteristic part moves to the corresponding water monitoring equipment for the first time, the actual water level at the dividing point is obtained. The actual water level is subtracted from the height of the reference surface to obtain the characteristic water level of the dividing point. The average value of the characteristic water levels of the dividing points on the dividing line is taken to obtain the characteristic average water level. The characteristic average water level is combined in the order of the dividing line sequence to form a shape vector.

[0010] Preferably, the establishment of the flood prediction model includes the following steps: At least one historical flood level of the target tributary is obtained in advance. In the historical flood level, the portion of the river water above the reference surface of the target tributary is obtained as a sample portion. The end with the thinnest part of the sample is taken as the front end. The sample is divided by cutting lines. The number of cutting lines is the same as the number of dividing lines, and the spacing between the cutting lines is the same as the spacing between the dividing lines. One of the cutting lines passes through the front end of the sample and the dividing line is perpendicular to the riverbank of the target tributary. At least one dividing point is uniformly selected on the dividing line, and the average thickness of the sample portion at the dividing point on the dividing line is taken to obtain the dividing thickness of the dividing line. The dividing lines are arranged in ascending order of their distance from the front end of the sample portion to obtain a dividing line sequence; The sample vector of the sample part is formed by combining the segmentation thicknesses of the segmentation lines according to the sequence of segmentation lines. The moving speed at the point of maximum thickness in the sample portion is taken as the peak speed of the sample portion, and the thickness at the point of maximum thickness in the sample portion is taken as the peak thickness of the sample portion. The moving speed of the front end of the sample part is obtained as the reference speed of the sample part.

[0011] Preferably, estimating the peak water level and peak velocity of the target tributary includes the following steps: According to the preset relationship, the weight of the sample part is obtained. The preset relationship is: the sample vector of the sample part and the weight of the sample part are multiplied and summed to equal the shape vector of the characteristic part of the target tributary. The reference velocity of the sample part and the weight of the sample part are multiplied and summed to equal the moving velocity of the characteristic part of the target tributary. The peak velocity of the target tributary is obtained by multiplying the peak velocity of the sample portion by its weight and summing the results. The peak thickness of the target tributary is obtained by multiplying the peak thickness of the sample portion by its weight and summing the results. The peak thickness of the target tributary is then added to the height of the reference surface of the target tributary to obtain the peak water level of the target tributary.

[0012] Preferably, estimating the confluence water level of the target tributaries in the target tributary set after they converge in the target river includes the following steps: The peak water level of the target tributary is multiplied by the width of the target tributary to obtain the cross-sectional area of ​​the target tributary. The cross-sectional area of ​​the target tributary is multiplied by the peak velocity of the target tributary to obtain the flow velocity of the target tributary. The characteristic velocity is obtained by averaging the peak velocities of at least one target tributary in the target tributary set. The flow velocities of at least one target tributary in the target tributary set are superimposed to obtain the total increase in flow velocity. The characteristic area is obtained by dividing the total increase in flow velocity by the characteristic velocity. Dividing the feature area by the width of the target river yields the water level increase height. This water level increase height is then superimposed on the real-time water level of the target river to obtain the confluence water level.

[0013] Preferably, the analysis to obtain the critical water level for the target river to rise includes the following steps: Obtain at least one historical flood level of the target river, obtain the previous water level after the flood in the historical flood level, and take the minimum value of at least one previous water level as the first critical value; Obtain at least one historical normal condition when the target river is not flooded. Obtain the normal water level when the river is not flooded from the historical normal condition. Take the maximum value of at least one normal water level as the second critical value. Take the average value of the second critical value and the first critical value as the critical water level when the target river is flooded.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: By classifying target tributaries according to their correlation with flood rise, generating floating deviation values, obtaining the movement speed and shape vectors of characteristic parts, and estimating the peak water level and peak velocity of the target tributaries, and based on the morphological laws of flood formation, a flood rise prediction model is established. Through the calculation of simultaneous equations, the weights of the sample parts in the flood rise prediction model are obtained, thereby estimating the peak water level and peak velocity of the target tributaries. Based on the obtained parameters, the confluence water level after the confluence in the target river can be predicted, thus predicting the scale of flood rises that have not yet occurred. The prediction results have high accuracy. Furthermore, based on the prediction results, parameters for flood discharge operations of water conservancy facilities can be set in advance, avoiding damage to water conservancy facilities caused by excessively high water levels. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating the intelligent water conservancy monitoring method for sudden rises in river water levels during the flood season, as described in this invention. Figure 2 This is a schematic diagram of the process of classifying target tributaries according to the correlation of rising water levels to obtain at least one set of target tributaries according to the present invention. Figure 3 This is a schematic diagram of the process for obtaining the fluctuation deviation value of the normal water level according to the present invention; Figure 4 This is a schematic diagram illustrating the process of forming a reference surface on the water surface within the target monitoring area according to the present invention; Figure 5 This is a schematic diagram illustrating the process of obtaining the moving speed and shape vector of the feature portion through analysis according to the present invention. Figure 6 This is a schematic diagram of the process for establishing a flood prediction model according to the present invention; Figure 7 This is a schematic diagram illustrating the process of estimating the peak water level and peak velocity of the target tributary according to the present invention. Figure 8 This is a schematic diagram illustrating the process of estimating the confluence water level of the target tributaries in the target tributary set after they converge in the target river, as per the present invention. Figure 9 This is a schematic diagram illustrating the process of obtaining the critical water level for the target river's rise in water level according to the analysis of this invention. Detailed Implementation

[0016] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0017] Reference Figure 1 As shown, an intelligent water conservancy monitoring method for sudden rises in river water levels during the flood season includes: Acquire the target river to be monitored, acquire at least one target tributary flowing into the target river, and install water conservancy monitoring equipment at the confluence of the target tributary and the target river; The target tributaries are classified according to their correlation with the rise in water level, resulting in at least one set of target tributaries; Obtain the maximum monitoring distance of the water conservancy monitoring equipment and the target monitoring area of ​​the water conservancy monitoring equipment; Based on the water level changes during the flood season, the fluctuation deviation value of the normal water level is obtained by analysis; Based on historical monitoring data, a reference surface is formed for the water surface within the target monitoring area, and the portion of the river water above the reference surface and located within the target monitoring area is taken as the feature part; Acquire at least one monitoring image of the feature portion moving within the target monitoring area, and analyze the moving speed and shape vector of the feature portion based on the monitoring image; A flood forecasting model is established, and the peak water level and peak velocity of the target tributary are estimated based on the flood forecasting model. The confluence water level of the target tributaries in the target tributary set after they converge in the target river is estimated. Based on historical data, the critical water level of the target river for flooding is analyzed. If the confluence water level exceeds the critical water level, it is determined that the target river will experience a sudden flood; otherwise, it is determined that the target river will not experience a sudden flood.

[0018] Real-time water level monitoring is a conventional technique, but it is not very effective. When floods are severe, it is necessary to release water at dams. However, due to the intensity of the flood, the water level at the dam may still rise even during the release, potentially causing damage. Therefore, conventional monitoring cannot meet the needs, and predictive monitoring is required to release water in advance and prevent the water level at the dam from becoming too high. The initial stage of the flood is relatively gentle, while the main part arrives with a delay. This is mainly achieved by analyzing the initial stage of the flood and then inferring the height and speed of the main part of the flood. This is because the greater the water force in the main part, the greater the water force at the initial stage of the flood. Therefore, a relationship can be established for identification. Furthermore, since there may be multiple target tributaries upstream of the target river, it is necessary to synthesize their confluence situation in order to obtain the confluence situation in the target river, and then set up a series of steps to process it.

[0019] Reference Figure 2 As shown, classifying target tributaries according to their correlation with flood level to obtain at least one set of target tributaries includes the following steps: The location where the target tributary flows into the target river is used as the feature location. The feature locations are numbered according to the order in which the river water passes through the target river. The feature location numbers are then matched with the target tributary corresponding to the feature location. Obtain at least one historical flood level of the target river, and summarize the target tributaries that have experienced flooding in the historical flood level to form a feature set of historical flood level; Target rivers with consecutive numbers in the feature set are considered as associated rivers, and the associated target rivers are aggregated to form a target tributary set.

[0020] When two target tributaries both experience rising water levels, if they are far apart, the rising water levels will not have a cumulative effect. Therefore, it is necessary to form a set of target tributaries, in which the rising water levels of the target tributaries have a cumulative effect. Because multiple water monitoring devices are installed on the target river, if the water level rises at a certain point in the target river, the highest water level within the range of the target tributaries in the target tributary set will be monitored by a certain water monitoring device. Therefore, the highest water level of the target river itself can be directly monitored and used as the real-time water level. However, water monitoring devices are only installed at the confluence of the target tributaries with the target river. Therefore, it is necessary to predict the rise of the target tributaries. Although setting up more water monitoring devices can also be used for monitoring, it will significantly increase the monitoring cost.

[0021] Obtaining the target monitoring area for water conservancy monitoring equipment includes the following steps: The target tributary is uniformly divided into at least one sampling block. If the distance from the center of the sampling block to the corresponding characteristic location of the target tributary does not exceed the maximum monitoring distance, the sampling block is used as a characteristic sampling block. The characteristic sampling blocks of the target tributary are summarized to obtain the target monitoring area of ​​the water conservancy monitoring equipment installed on the target tributary.

[0022] Reference Figure 3 As shown, the analysis to obtain the fluctuation deviation value of the normal water level includes the following steps: A preset time is formed, and at least one time group is formed when the target tributary has not risen. The time group consists of two characteristic times with an interval equal to the preset time. At the time point equal to the characteristic time, the water level of the target tributary is statistically analyzed to obtain at least one normal water level. The normal water levels collected at the characteristic time in the time group are subtracted and the absolute value is taken to obtain the preliminary deviation. The maximum value of all preliminary deviations of at least one target tributary is taken as the floating deviation value. The specific time for setting the preset time is as follows: At least one sampling point is collected evenly throughout the day. At the sampling point, the water level of the target tributary is statistically analyzed to obtain the sampling water level. Arrange the water levels collected at the sampling points in the order of the sampling points, and take one of the water levels at least once as the characteristic water level. If the product of the differences between two adjacent water levels and the characteristic water level is positive, then the characteristic water level is taken as the target water level. When the feature sampling water level traverses at least one sampling water level, at least one target sampling water level is obtained. The difference between the sampling points corresponding to adjacent target sampling water levels is calculated and the absolute value is taken to obtain the reference time. The minimum value of the reference time of all target tributaries is taken as the preset time.

[0023] During water level monitoring, there is a normal fluctuation range, and the monitored value is not completely fixed. Therefore, it is necessary to form a normal water level fluctuation deviation value. During monitoring, the fluctuation deviation value needs to be taken into account. In order to obtain the fluctuation deviation value, multiple sets of data need to be sampled, but the sampling interval needs to be specially set. Here, it is set to a preset time. Its main purpose is to ensure that the collected fluctuations are large enough within the preset time. According to the formation of the target sampling water level, the sampling water levels adjacent to the target sampling water level are either both greater than the target sampling water level or both less than the target sampling water level. Therefore, the water level between adjacent target sampling water levels is constantly increasing or constantly decreasing. The preset time is the minimum reference time of all target tributaries. Therefore, the preset time is relatively small and can be approximated as sampling at the same moment. Then, fluctuations can be estimated. In the case of multiple sets of sampling, there is a high probability that the water level is constantly increasing or constantly decreasing within the preset time. Therefore, a large fluctuation can be collected, which can be used as the normal water level fluctuation deviation value.

[0024] Reference Figure 4 As shown, the steps to establish a reference surface for the water surface within the target monitoring area include: At least one sample point is evenly selected from the dates of the year. In the historical monitoring data, at least one historical water level at the sample point is obtained. The average water level of the sample point is obtained by taking the average of the at least one historical water level at the sample point. The floating deviation value is superimposed with the average water level of the sample point to obtain the sample water level of the sample point. The sample points are paired with the corresponding sample water levels and fitted to obtain a reference fitting function. The current monitoring date is then substituted into the reference fitting function to obtain the reference water level. The plane containing the water surface of the reference water level is used as the reference surface.

[0025] The reference surface is the plane where the normal water level is located within the target monitoring area. The reference surface is used to identify abnormal parts within the target monitoring area. However, since the water volume varies in different months, it is necessary to determine the current reference surface based on the date.

[0026] Reference Figure 5 As shown, the analysis to obtain the moving speed and shape vector of the feature part includes the following steps: At least one dividing line is taken at equal intervals within the target monitoring area, and the dividing line is perpendicular to the riverbank of the target tributary where the target monitoring area is located; The distance from the dividing line to the corresponding water conservancy monitoring equipment in the target monitoring area is used as the characteristic distance. The difference between the maximum and minimum values ​​of the characteristic distance is used to obtain the benchmark distance. The time when the feature first reaches the dividing line is taken as the accompanying time of the dividing line. The difference between the maximum and minimum values ​​of the accompanying time is used to obtain the reference time. The reference distance is divided by the reference time to obtain the moving speed of the feature. Arrange the dividing lines according to their corresponding feature distances from smallest to largest to obtain a dividing line sequence; At least one dividing point is uniformly selected on the dividing line. When the characteristic part moves to the corresponding water monitoring equipment for the first time, the actual water level at the dividing point is obtained. The actual water level is subtracted from the height of the reference surface to obtain the characteristic water level of the dividing point. The average value of the characteristic water levels of the dividing points on the dividing line is taken to obtain the characteristic average water level. The characteristic average water level is combined in the order of the dividing line sequence to form a shape vector.

[0027] The characteristic section is the leading part of the overall flood process. By analyzing the characteristic section, we can then infer the main part of the flood corresponding to the characteristic section. The height of the main part of the flood is the same, but since the characteristic section is the leading part, the water level at different locations is different. The closer to the front, the lower the water level. Here, the characteristic section is characterized from the aspects of shape and movement speed. Whether two characteristic sections are consistent actually depends on the shape and movement speed. Therefore, we can infer the main part of the flood based on this.

[0028] Reference Figure 6 As shown, establishing a flood prediction model includes the following steps: At least one historical flood level of the target tributary is obtained in advance. In the historical flood level, the portion of the river water above the reference surface of the target tributary is obtained as a sample portion. The end with the thinnest part of the sample is taken as the front end. The sample is divided by cutting lines. The number of cutting lines is the same as the number of dividing lines, and the spacing between the cutting lines is the same as the spacing between the dividing lines. One of the cutting lines passes through the front end of the sample and the dividing line is perpendicular to the riverbank of the target tributary. At least one dividing point is uniformly selected on the dividing line, and the average thickness of the sample portion at the dividing point on the dividing line is taken to obtain the dividing thickness of the dividing line. The dividing lines are arranged in ascending order of their distance from the front end of the sample portion to obtain a dividing line sequence; The sample vector of the sample part is formed by combining the segmentation thicknesses of the segmentation lines according to the sequence of segmentation lines. The moving speed at the point of maximum thickness in the sample portion is taken as the peak speed of the sample portion, and the thickness at the point of maximum thickness in the sample portion is taken as the peak thickness of the sample portion. The moving speed of the front end of the sample part is obtained as the reference speed of the sample part.

[0029] This involves a limited number of historical flood scenarios, thus requiring a relatively small amount of pre-acquired data. Since a sample segment that perfectly matches the characteristic segment cannot be directly found within these historical flood scenarios, a weighted combination of multiple sample segments is used to obtain results consistent with the characteristic segment. Following the same weighting method, the peak velocity and peak thickness of the sample segment can be processed to obtain the thickness and movement velocity of the main flood segment corresponding to the characteristic segment. From this, the peak water level and peak velocity of the target tributary can be obtained.

[0030] Reference Figure 7 As shown, estimating the peak water level and peak velocity of the target tributary includes the following steps: According to the preset relationship, the weight of the sample part is obtained. The preset relationship is: the sample vector of the sample part and the weight of the sample part are multiplied and summed to equal the shape vector of the characteristic part of the target tributary. The reference velocity of the sample part and the weight of the sample part are multiplied and summed to equal the moving velocity of the characteristic part of the target tributary. The peak velocity of the target tributary is obtained by multiplying the peak velocity of the sample portion by its weight and summing the results. The peak thickness of the target tributary is obtained by multiplying the peak thickness of the sample portion by its weight and summing the results. The peak thickness of the target tributary is then added to the height of the reference surface of the target tributary to obtain the peak water level of the target tributary.

[0031] Reference Figure 8 As shown, estimating the confluence water level of the target tributaries in the target tributary set after they converge in the target river includes the following steps: The peak water level of the target tributary is multiplied by the width of the target tributary to obtain the cross-sectional area of ​​the target tributary. The cross-sectional area of ​​the target tributary is multiplied by the peak velocity of the target tributary to obtain the flow velocity of the target tributary. The characteristic velocity is obtained by averaging the peak velocities of at least one target tributary in the target tributary set. The flow velocities of at least one target tributary in the target tributary set are superimposed to obtain the total increase in flow velocity. The characteristic area is obtained by dividing the total increase in flow velocity by the characteristic velocity. Dividing the feature area by the width of the target river yields the water level increase height. This water level increase height is then superimposed on the real-time water level of the target river to obtain the confluence water level.

[0032] The confluence water level is mainly calculated by summing the surface area of ​​the water flowing through a characteristic surface of multiple target tributaries. The characteristic surface is a vertically set surface. Since the flow velocity is equal to the product of the water flow area and the flow velocity through the characteristic surface, the total area of ​​the target tributaries in the target tributary set passing through the characteristic surface can be obtained, i.e., the characteristic area. The characteristic area is filled into the target river, so its width is the width of the target river. Therefore, its height is the water level plus the height. Thus, the confluence water level is predicted. During the confluence, since water conservancy monitoring equipment is installed at the connection points between the target tributaries and the target river in the target tributary set, it can acquire data on the main part of the rise in water level in the target river in real time without speculation. The real-time water level of the target river is the maximum value of the monitoring results of the water conservancy monitoring equipment of the target tributaries in the target tributary set on the target river, because the water level of the main part of the rise is relatively stable and also the maximum.

[0033] Reference Figure 9 As shown, the analysis to determine the critical water level for the target river to rise includes the following steps: Obtain at least one historical flood level of the target river, obtain the previous water level after the flood in the historical flood level, and take the minimum value of at least one previous water level as the first critical value; Obtain at least one historical normal condition when the target river is not flooded. Obtain the normal water level when the river is not flooded from the historical normal condition. Take the maximum value of at least one normal water level as the second critical value. Take the average value of the second critical value and the first critical value as the critical water level when the target river is flooded.

[0034] Instead of using the second or first critical value as the critical water level, this method uses the average of the second and first critical values ​​for identification. This results in a significant difference between the critical water level and the normal water level, avoiding misjudgments of water level fluctuations. Under normal circumstances, the water level will not exceed the critical water level. However, if it does exceed the critical water level, it indicates a large deviation from the normal water level, thus posing a significant risk of a large rise in water level. Therefore, it is necessary to release water from the dams of the target river in advance to lower the water level as early as possible.

[0035] Furthermore, this solution also proposes a storage medium on which a computer-readable program is stored. When the computer-readable program is invoked, it executes the aforementioned intelligent water conservancy monitoring method for sudden rises in river water levels during the flood season.

[0036] It is understandable that the storage medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid-state drive (SSD).

[0037] In summary, the advantages of this invention are as follows: by classifying target tributaries according to their correlation with flood rise, generating floating deviation values, obtaining the movement speed and shape vectors of characteristic parts, and estimating the peak water level and peak velocity of the target tributaries, and based on the morphological laws of flood formation, a flood rise prediction model is established. Through the calculation of simultaneous equations, the weights of the sample parts in the flood rise prediction model are obtained, thereby estimating the peak water level and peak velocity of the target tributaries. Based on the acquired parameters, the confluence water level in the target river after confluence can be predicted, thus enabling the prediction of the scale of flood rises that have not yet occurred. Furthermore, the prediction results have high accuracy. Based on the prediction results, parameters for flood discharge operations at water conservancy facilities can be set in advance, avoiding damage to water conservancy facilities caused by excessively high water levels.

[0038] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A smart water conservancy monitoring method for sudden rises in river water levels during the flood season, characterized in that, include: Acquire the target river to be monitored, acquire at least one target tributary flowing into the target river, and install water conservancy monitoring equipment at the confluence of the target tributary and the target river; The target tributaries are classified according to their correlation with the rise in water level, resulting in at least one set of target tributaries; Obtain the maximum monitoring distance of the water conservancy monitoring equipment and the target monitoring area of ​​the water conservancy monitoring equipment; Based on the changes in river water level during the flood season, the fluctuation deviation value of the normal water level is obtained by analysis; Based on historical monitoring data, a reference surface is formed for the water surface within the target monitoring area, and the portion of the river water above the reference surface and located within the target monitoring area is taken as the feature part; At least one monitoring image of the feature portion moving within the target monitoring area is acquired, and the moving speed and shape vector of the feature portion are analyzed based on the monitoring image. A flood forecasting model is established, and the peak water level and peak velocity of the target tributary are estimated based on the flood forecasting model. The confluence water level of the target tributaries in the target tributary set after they converge in the target river is estimated. Based on historical data, the critical water level of the target river for flooding is analyzed. If the confluence water level exceeds the critical water level, it is determined that the target river will experience a sudden flood; otherwise, it is determined that the target river will not experience a sudden flood. The analysis to obtain the fluctuation deviation value of the normal water level includes the following steps: A preset time is formed, and at least one time group is formed when the target tributary has not risen. The time group consists of two characteristic times with an interval equal to the preset time. At the time point equal to the characteristic time, the water level of the target tributary is statistically analyzed to obtain at least one normal water level. The normal water levels collected at the characteristic time in the time group are subtracted and the absolute value is taken to obtain the preliminary deviation. The maximum value of all preliminary deviations of at least one target tributary is taken as the floating deviation value. The specific time for setting the preset time is as follows: At least one sampling point is collected evenly throughout the day. At the sampling point, the water level of the target tributary is statistically analyzed to obtain the sampling water level. Arrange the water levels collected at the sampling points in the order of the sampling points, and take one of the water levels at least once as the characteristic water level. If the product of the differences between two adjacent water levels and the characteristic water level is positive, then the characteristic water level is taken as the target water level. When the feature sampling water level traverses at least one sampling water level, at least one target sampling water level is obtained. The difference between the sampling points corresponding to adjacent target sampling water levels is calculated and the absolute value is taken to obtain the reference time. The minimum value of the reference time of all target tributaries is taken as the preset time. The process of establishing a reference surface for the water surface within the target monitoring area includes the following steps: At least one sample point is evenly selected from the dates of the year. In the historical monitoring data, at least one historical water level at the sample point is obtained. The average water level of the sample point is obtained by taking the average of the at least one historical water level at the sample point. The floating deviation value is superimposed with the average water level of the sample point to obtain the sample water level of the sample point. The sample points are paired with the corresponding sample water levels and fitted to obtain a reference fitting function. The current monitoring date is substituted into the reference fitting function to obtain the reference water level. The plane where the water surface of the reference water level is located is used as the reference surface. The analysis to obtain the moving speed and shape vector of the feature portion includes the following steps: Within the target monitoring area, at least one dividing line is taken at equal intervals, and the dividing line is perpendicular to the riverbank of the target tributary where the target monitoring area is located; The distance from the dividing line to the corresponding water conservancy monitoring equipment in the target monitoring area is used as the characteristic distance. The difference between the maximum and minimum values ​​of the characteristic distance is used to obtain the benchmark distance. The time when the feature first reaches the dividing line is taken as the accompanying time of the dividing line. The difference between the maximum and minimum values ​​of the accompanying time is used to obtain the reference time. The reference distance is divided by the reference time to obtain the moving speed of the feature. Arrange the dividing lines according to their corresponding feature distances from smallest to largest to obtain a dividing line sequence; At least one dividing point is uniformly selected on the dividing line. When the characteristic part moves to the corresponding water monitoring equipment for the first time, the actual water level at the dividing point is obtained. The actual water level is subtracted from the height of the reference surface to obtain the characteristic water level of the dividing point. The average value of the characteristic water levels of the dividing points on the dividing line is taken to obtain the characteristic average water level. The characteristic average water level is combined in the order of the segmentation line sequence to form a shape vector; The establishment of the flood prediction model includes the following steps: At least one historical flood level of the target tributary is obtained in advance. In the historical flood level, the portion of the river water above the reference surface of the target tributary is obtained as a sample portion. The end with the thinnest part of the sample is taken as the front end. The sample is divided by cutting lines. The number of cutting lines is the same as the number of dividing lines, and the spacing between the cutting lines is the same as the spacing between the dividing lines. One of the cutting lines passes through the front end of the sample and the dividing line is perpendicular to the riverbank of the target tributary. At least one dividing point is uniformly selected on the dividing line, and the average thickness of the sample portion at the dividing point on the dividing line is taken to obtain the dividing thickness of the dividing line. The dividing lines are arranged in ascending order of their distance from the front end of the sample portion to obtain a dividing line sequence; The sample vector of the sample part is formed by combining the segmentation thicknesses of the segmentation lines according to the sequence of segmentation lines. The moving speed at the point of maximum thickness in the sample portion is taken as the peak speed of the sample portion, and the thickness at the point of maximum thickness in the sample portion is taken as the peak thickness of the sample portion. The moving speed of the front end of the sample part is obtained as the reference speed of the sample part; The estimation of the peak water level and peak velocity of the target tributary includes the following steps: According to the preset relationship, the weight of the sample part is obtained. The preset relationship is: the sample vector of the sample part and the weight of the sample part are multiplied and summed to equal the shape vector of the characteristic part of the target tributary. The reference velocity of the sample part and the weight of the sample part are multiplied and summed to equal the moving velocity of the characteristic part of the target tributary. The peak velocity of the target tributary is obtained by multiplying the peak velocity of the sample portion by its weight and summing the results. The peak thickness of the target tributary is obtained by multiplying the peak thickness of the sample portion by its weight and summing the results. The peak thickness of the target tributary is then added to the height of the reference surface of the target tributary to obtain the peak water level of the target tributary. The estimation of the confluence water level of the target tributaries in the target tributary set after they converge in the target river includes the following steps: The peak water level of the target tributary is multiplied by the width of the target tributary to obtain the cross-sectional area of ​​the target tributary. The cross-sectional area of ​​the target tributary is multiplied by the peak velocity of the target tributary to obtain the flow velocity of the target tributary. The characteristic velocity is obtained by averaging the peak velocities of at least one target tributary in the target tributary set. The flow velocities of at least one target tributary in the target tributary set are superimposed to obtain the total increase in flow velocity. The characteristic area is obtained by dividing the total increase in flow velocity by the characteristic velocity. Dividing the feature area by the width of the target river yields the water level increase height. This water level increase height is then superimposed on the real-time water level of the target river to obtain the confluence water level.

2. The intelligent water conservancy monitoring method for sudden rises in river water levels during the flood season, as described in claim 1, is characterized in that... The step of classifying the target tributaries according to their correlation with flood level to obtain at least one set of target tributaries includes the following steps: The location where the target tributary flows into the target river is used as the feature location. The feature locations are numbered according to the order in which the river water passes through the target river. The feature location numbers are then matched with the target tributary corresponding to the feature location. Obtain at least one historical flood level of the target river, and summarize the target tributaries that have experienced flooding in the historical flood level to form a feature set of historical flood level; Target rivers with consecutive numbers in the feature set are considered as associated rivers, and the associated target rivers are aggregated to form a target tributary set.

3. The intelligent water conservancy monitoring method for sudden rises in river water levels during the flood season, as described in claim 2, is characterized in that... The process of acquiring the target monitoring area of ​​the water conservancy monitoring equipment includes the following steps: The target tributary is uniformly divided into at least one sampling block. If the distance from the center of the sampling block to the corresponding characteristic location of the target tributary does not exceed the maximum monitoring distance, the sampling block is used as a characteristic sampling block. The characteristic sampling blocks of the target tributary are summarized to obtain the target monitoring area of ​​the water conservancy monitoring equipment installed on the target tributary.

4. The intelligent water conservancy monitoring method for sudden rises in river water levels during the flood season, as described in claim 3, is characterized in that... The analysis to determine the critical water level for the target river's rise includes the following steps: Obtain at least one historical flood level of the target river, obtain the previous water level after the flood in the historical flood level, and take the minimum value of at least one previous water level as the first critical value; Obtain at least one historical normal condition when the target river is not flooded. Obtain the normal water level when the river is not flooded from the historical normal condition. Take the maximum value of at least one normal water level as the second critical value. Take the average value of the second critical value and the first critical value as the critical water level when the target river is flooded.

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