A smart water conservancy early warning method and system based on digital twin technology

Abstract

The present invention relates to the field of water conservancy engineering technology, specifically to a smart water conservancy early warning method and system based on digital twin technology, which monitors and predicts soil erosion and landslides, and issues corresponding early warning notifications for exceeding the standard, thereby preventing the problem of excessive sand accumulation in the reservoir. The system consists of a data acquisition unit, a data processing unit, and a prediction and early warning unit. The reservoir sand accumulation is predicted through three aspects: downstream soil erosion, landslides, and the solid content of the incoming water. The three types of data are processed and merged into a comprehensive data, and it is judged whether the comprehensive data exceeds the comprehensive threshold. If it exceeds the threshold, it is judged which of the three types of data exceeds the corresponding threshold, and sent to a mobile terminal to notify the staff to take corresponding measures. The present invention realizes intelligent water conservancy early warning management, and can effectively prevent the problem of excessive sand accumulation in the reservoir from the source.

Description

Technical Field

[0001] The present invention relates to the field of water conservancy projects, and in particular to a smart water conservancy early warning method and system based on digital twin technology. Background Art

[0002] Digital twins refer to the creation of a digital "clone" based on a device or system. This "clone" is a dynamic simulation of the physical object. The real-time status of the original object and the external environmental conditions will be reproduced on the "twin". If the system design needs to be changed, or if you want to know how the system responds under special external conditions, engineers can conduct "experiments" on the twin, which not only avoids the impact on the original object, but also improves efficiency and saves costs. Digital twins are a very promising cutting-edge technology.

[0003] Reservoirs are artificial water bodies formed in valleys, rivers or low-lying areas by means of dams, dikes, sluice gates, weirs and other projects. Reservoirs can intercept floods, concentrate drop, regulate river runoff and underground runoff, so they can be used for flood control, hydropower generation, irrigation, shipping, urban water supply, breeding, tourism, environmental improvement and many other aspects, and play an important role in social and economic development. Therefore, the continuous optimization of reservoir projects is the top priority in water conservancy engineering tasks.

[0004] The problem of reservoir sediment accumulation has always been a headache. Excessive sediment accumulation will lead to higher water levels, reduced reservoir capacity, and reduced river channel water flow capacity, thus affecting flood control, hydropower generation and other functions. In addition, it is difficult for humans to completely solve the problem of reservoir sediment accumulation. Therefore, a smart water conservancy early warning method and system based on digital twin technology is proposed. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In response to the shortcomings of the existing problems, the present invention provides a smart water conservancy early warning method and system based on digital twin technology. The system prevents reservoir sand accumulation based on the causes of its occurrence, thereby reducing the possibility of sediment entering the reservoir from the source.

[0007] (II) Technical solution

[0008] The technical solution adopted by this patent is: a smart water conservancy early warning method and system based on digital twin technology, specifically a water conservancy early warning system designed for reservoir silt deposition, which collects relevant data through different sensors and measuring instruments, processes data through calculations and judges the results against the set critical values. If it is higher than the critical value, a corresponding early warning alarm will be issued to the terminal, and staff can receive alarm reminders on mobile devices in real time.

[0009] There are many reasons that affect reservoir sediment accumulation. The present invention mainly focuses on the three aspects of downstream soil erosion, landslides and solid content in the water entering the reservoir to design a smart water conservancy early warning method and system. Specifically, it includes the following steps:

[0010] Step S1, firstly, the soil area on both sides of the river channel downstream of the reservoir is divided, and symmetrical areas of equal area are selected on both sides of the river channel as sampling areas, soil points are evenly selected in the sampling area, and a soil tester is placed at each soil point to collect the sand, silt and clay content of the soil at each soil point, and measure the slope and slope length of each soil point;

[0011] Step S2, calculating the soil erosion modulus A of each soil point in real time according to the Chinese Soil Loss Equation CSLE;

[0012] Step S3, calculating the soil erosion index I of each soil point according to the soil erosion modulus and the straight-line distance between each soil point and the river; dividing the sampling area selected in step S1 into a number of equal-sized areas as calculation areas, taking the average of the soil erosion indexes of all soil points in the calculation area to obtain the average soil erosion index in the area

[0013] Step S4, placing speed sensors on a hillside with a height greater than 100 meters and a slope greater than 20° around the reservoir, placing three speed sensors evenly on the top of the hillside, and placing one speed sensor at 1 / 3 and 2 / 3 of the height of the hillside, respectively, to measure and calculate the motion acceleration of the hillside;

[0014] Step S5, collecting the data measured by each sensor in real time, and integrating the data of the five sensors of each hillside, calculating the overall acceleration of each hillside, and taking the ratio of the overall acceleration to the limit acceleration as the landslide index P, and taking the rain into consideration;

[0015] Step S6, select an area in the reservoir water storage river to place a suspended matter tester, measure the solid content in the water at regular intervals, and average the data measured by all the testers to obtain the solid content TS in the water storage river;

[0016] Step S7, at regular time intervals, the calculated average soil erosion index in each soil area, the maximum value of the landslide index of each hillside, and the solid content in the reservoir river are dimensionlessly processed to obtain the reservoir sand accumulation warning value YJ; if the reservoir sand accumulation warning value YJ exceeds the threshold, the system will turn to check which specific value exceeds the threshold; and send a corresponding alarm to the mobile terminal, and the staff can receive the alarm information through various mobile devices and take corresponding preventive measures; if the reservoir sand accumulation warning value YJ does not exceed the threshold, the system will not issue any alarm.

[0017] Specifically, the Chinese soil loss equation CSLE in step S2 is:

[0018] A=R×K×LS×B×E×T

[0019] By processing the collected data, the erosion modulus can be obtained.

[0020] Among them, A is the desired erosion modulus; R is the rainfall erosivity factor, which is calculated using the rainfall intensity formula based on daily rainfall and previous daily, monthly, and annual rainfall; K is the soil erodibility factor, which is calculated using the K value table method based on the land use type and soil type of the sampling area; L and S are the slope factor and slope length factor, respectively. The LS value is calculated by combining the digital elevation model and geographic information system technology, and analyzing and processing the terrain; B is the plant coverage and biological measure factor. The plant coverage is represented by the NDVI normalized difference vegetation index. The NDVI value is calculated by the reflectivity of the reflectivity and the reflectivity of the red light band. The corresponding plant coverage is found in the NDVI corresponding table according to the value of the NDVI index; the biological measure factor is calculated by the response and evaluation index of the receptor organism to the biological measure factor.; E and T are the engineering measure factor and the tillage measure factor, respectively, that is, the use of the measured land. Different uses have different values. The corresponding E value and T value are found according to the land use type and soil type of the sampling area.

[0021] Specifically, the calculation process of the soil erosion index in step 3 is as follows:

[0022] Measure the horizontal distance s between each test point and the river channel, as well as the height h from the horizontal plane, and use the distance formula to calculate the straight-line distance between the soil point and the river edge plane. This distance is inversely proportional to the erosion modulus, and the two are calculated as follows:

[0023]

[0024] The value of I is the soil erosion index of the soil point. The sampling area is divided into several areas of equal size as the calculation area, and the soil erosion index of all soil points in the calculation area is averaged to obtain the average soil erosion index in the area.

[0025] Specifically, the calculation process of the slope acceleration and the landslide index in step 5 is as follows:

[0026] Observe the x, y, and z values ​​on the sensor in real time, and process the three values ​​to get the overall acceleration:

[0027]

[0028] Among them, gen is the overall acceleration; the average value of the acceleration measured by the five sensors on the same slope in the same time period is taken as the acceleration in this area within the time window:

[0029]

[0030] N represents the number of all sensors in this area, and count is the number of sensor uploads in this time window;

[0031] Introducing limiting acceleration:

[0032] ext=0.5*count*g

[0033] ext is the limit acceleration; the ratio of the acceleration in the area to the limit acceleration represents the intensity of the movement. Considering the factor of rain, the specific expression is:

[0034]

[0035] m is the number of sensors with water, and P is the landslide index;

[0036] Specifically, the calculation of the reservoir sedimentation warning value YJ in step 7 is as follows:

[0037]

[0038] Where YJ is the reservoir sediment warning value, is the average soil erosion index for all soil regions The maximum value in P max is the maximum value of the landslide index P of all hillsides, TS is the solid content in the reservoir river, A, B, C are different weights, and D is a constant correction coefficient.

[0039] Furthermore, every T time, the system updates the reservoir sedimentation warning value based on the measured data and calculated results; if the updated reservoir sedimentation warning value YJ exceeds the preset sedimentation threshold, the sub-parameter exceeding the corresponding threshold is determined, and the corresponding warning is sent to the mobile terminal; if the average soil erosion index in the soil area is The maximum value in If the maximum value P in the landslide index P of the hillside is greater than the threshold, the area where the soil erosion index exceeds the corresponding threshold is determined, and a soil erosion alarm and information about the area where soil erosion has occurred are sent to the mobile terminal; maxIf the threshold is exceeded, the slope whose landslide index exceeds the corresponding threshold is determined, and a landslide alarm and information on slopes with a high probability of landslide are sent to the mobile terminal; if the solid content in the reservoir river is found to exceed the threshold, the system will send an alarm of excessive solid content in the water to the mobile terminal.

[0040] Furthermore, upon receiving a soil erosion alert, soil maintenance will be carried out in areas with severe soil erosion, organic matter will be added to the soil in these areas, cover crops will be placed on the corresponding soil, and trees will be planted in nearby areas; upon receiving a landslide alert, the sand retaining device at the foot of the mountain will be opened; upon receiving an alert of excessive solid content in the water, the sedimentation tank at the water inlet will be opened to reduce the water flow rate, and the filter screen will be opened at the water inlet.

[0041] Furthermore, weather forecast information for the location of the reservoir is obtained. When the weather forecast predicts moderate rain, heavy rain or rainstorm, the reservoir sand accumulation warning value is updated every 1 / 3T, and the thresholds of various data are lowered by 1 / 2.

[0042] Specifically, a smart water conservancy early warning system based on digital twin technology includes:

[0043] Data collection unit: collects soil data, slope movement data and water solid content data for subsequent analysis and processing;

[0044] Data processing unit: pre-process the collected data, such as missing value processing, outlier processing and noise processing; bring the pre-processed data into the operation to calculate the soil erosion modulus, landslide index and solid content in water; and perform dimensionless processing on the three calculated data to obtain the reservoir sedimentation warning value;

[0045] Prediction and warning unit: The system determines whether it is necessary to issue a warning based on whether the reservoir sand accumulation warning value exceeds the threshold; if the reservoir sand accumulation warning value exceeds the set threshold, the system will further analyze which data exceeds the threshold and issue a corresponding warning to the mobile terminal; the staff will take corresponding measures after receiving the warning.

[0046] (III) Beneficial effects

[0047] The present invention provides a smart water conservancy early warning method and system based on digital twin technology, which has the following beneficial effects: it can accurately predict the occurrence of soil erosion and landslides, and detect the solid content in water before the water enters the reservoir to prevent water containing a large amount of sediment from entering the reservoir, so as to achieve earliest discovery and alarm upon discovery, thereby minimizing the total amount of sediment input into the reservoir. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a structural schematic diagram of the intelligent water conservancy early warning system of the present invention. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] like Figure 1 As shown, this embodiment provides a smart water conservancy early warning method based on digital twin technology, a water conservancy early warning system designed for reservoir sediment deposition, and the present invention is composed of a data acquisition unit, a data processing unit, and a prediction and early warning unit. The specific implementation process is: collect information on relevant data through different sensors and measuring instruments, process data through calculations and judge the results with the set critical value. If it is higher than the critical value, a corresponding early warning alarm will be issued to the terminal, and the staff can receive the alarm reminder on the mobile device in real time.

[0051] There are many factors that affect sand accumulation in reservoirs. The present invention mainly designs a smart water conservancy early warning method and system based on three aspects: downstream soil erosion, landslides and the solid content in the water entering the reservoir.

[0052] The downstream soil erosion part is to find out the soil erosion modulus, and its design and ideas are as follows:

[0053] First, the soil areas on both sides of the river channel downstream of the reservoir were divided, and symmetrical areas of equal area were taken on both sides of the river channel as sampling areas. Soil points were evenly selected in the sampling area, and a soil tester was placed at each soil point to collect the sand, silt, and clay content of the soil in each soil point, and measure the slope and slope length of each soil point.

[0054] The collected data are processed according to the Chinese Soil Loss Equation (CSLE):

[0055] A=R×K×LS×B×E×T

[0056] Among them, A is the desired erosion modulus;

[0057] R is the rainfall erosivity factor, which is calculated using the rainfall intensity formula based on daily rainfall and previous daily, monthly, and annual rainfall;

[0058] K is the soil erodibility factor, and the K value table method is used to find the corresponding K value according to the land use type and soil type of the soil in the sampling area;

[0059] L and S are the slope factor and slope length factor respectively. The LS value is calculated by combining the digital elevation model and geographic information system technology, analyzing and processing the terrain;

[0060] B is the plant coverage and biological measure factor. The plant coverage is represented by the NDVI normalized difference vegetation index. The NDVI value is calculated by the reflectivity of the reflectivity and the reflectivity of the red light band. The corresponding plant coverage is found in the NDVI corresponding table according to the value of the NDVI index. The biological measure factor is calculated by the response of the receptor organism to the biological measure factor and the evaluation index. ;

[0061] E and T are engineering measures factor and tillage measures factor respectively, that is, the usage of the measured land. Different usages have different values. The corresponding E and T values ​​are found according to the land use type and soil type of the soil in the sampling area.

[0062] After calculating the above values, the soil erosion modulus of the location can be obtained by using the CSLE equation and stored in the terminal memory. The higher the erosion modulus, the higher the degree of soil erosion; the higher the degree of soil erosion, the softer the soil will be, the more sediment particles will be in the soil and the easier it will slide off. When water flows through, it will carry away more sediment. When the reservoir is filled with water, if the downstream soil erosion degree is higher, the water in the reservoir will contain more sediment, and sediment accumulation will be more likely to occur.

[0063] Since the probability of being washed away is different at different locations, the closer to the inlet river, the higher the probability of sediment being washed away; the lower the terrain, the higher the probability of sediment being washed away. Therefore, it is unreasonable to only consider the erosion modulus without considering the location. The soil erosion impact index I should be calculated based on the soil erosion index of each soil point and the straight-line distance between each soil point and the river. Then the selected sampling area is divided into several areas of equal size as the calculation area, and the soil erosion index of all soil points in the calculation area is averaged to obtain the average soil erosion index in the area. Will Compare with the set soil erosion index critical value, the specific method is as follows:

[0064] Measure the horizontal distance s of each test point from the nearest river bank and the height h from the horizontal plane, and use the Pythagorean theorem to calculate the straight-line distance between the measurement point and the river edge plane. This distance is inversely proportional to the erosion modulus, and the two are calculated as follows:

[0065]

[0066] The value of I is a more accurate soil erosion impact index, and the average value is calculated to obtain the average soil erosion impact index of this area.

[0067] The landslide part predicts the probability of landslide by calculating the intensity of movement. Its design and ideas are as follows:

[0068] Velocity sensors are placed on hillsides around the reservoir with a height greater than 100 meters and a slope greater than 20°. Three velocity sensors are evenly placed on the top of the hillside, and one velocity sensor is placed at 1 / 3 and 2 / 3 of the height of the hillside to measure and calculate the motion acceleration of the hillside. Each hillside is regarded as an independent area. The x, y, and z values ​​on the sensor are observed in real time, and the three values ​​are processed to obtain the overall acceleration:

[0069]

[0070] gen is the overall acceleration. In order to reduce errors, the average value of the acceleration measured by sensors in the same area in the same time period is used as the acceleration in this area within the time window:

[0071]

[0072] N represents the number of all sensors in this area, and count is the number of sensor uploads in this time window.

[0073] The magnitude of the acceleration in the area alone cannot accurately reflect the landslide situation. Another value is needed for reference. Here, the limit acceleration is introduced:

[0074] ext=0.5*count*g

[0075] ext is the limit acceleration. The acceleration in the area is compared with the limit acceleration, and the result is used to indicate the intensity of the movement. Usually, the critical value is 0.4%. When it rains, landslides are more likely to occur. In order to ensure the accuracy of the results, the rain factor should also be considered in the judgment conditions. The specific expression is:

[0076]

[0077] m is the number of sensors with water, and P is the landslide index.

[0078] The solid content in the water entering the reservoir is used to predict the probability of landslides by calculating the intensity of the movement. The design and ideas are as follows:

[0079] A suspended matter tester is placed in an area of ​​the reservoir water storage river. The solid content in the water is measured at regular intervals, and the data measured by all the testers are averaged to obtain the solid content TS in the water storage river.

[0080] At regular intervals, the average soil erosion index in each soil area, the maximum value of the landslide index of each hillside, and the solid content in the reservoir river are dimensionlessly processed to obtain the reservoir sedimentation warning value YJ:

[0081]

[0082] Where YJ is the reservoir sediment warning value, is the average soil erosion index for all soil regions The maximum value in P max is the maximum value of the landslide index P of all hillsides, TS is the solid content in the reservoir river, A, B, C are different weights, and D is a constant correction coefficient.

[0083] Every T time, the system updates the reservoir sedimentation warning value based on the measured data and calculated results; if the updated reservoir sedimentation warning value YJ exceeds the preset sedimentation threshold, the sub-parameters exceeding the corresponding threshold are determined, and the corresponding warning is sent to the mobile terminal; if the average soil erosion index in the soil area is The maximum value in If the maximum value P in the landslide index P of the hillside is greater than the threshold, the area where the soil erosion index exceeds the corresponding threshold is determined, and a soil erosion alarm and information about the area where soil erosion has occurred are sent to the mobile terminal; max If the threshold is exceeded, the slope whose landslide index exceeds the corresponding threshold is determined, and a landslide alarm and information on slopes with a high probability of landslide are sent to the mobile terminal; if the solid content in the reservoir river is found to exceed the threshold, the system will send an alarm of excessive solid content in the water to the mobile terminal.

[0084] After receiving a soil erosion alert, soil maintenance will be carried out in areas where soil erosion is severe. Organic matter will be added to the soil in these areas, cover crops will be placed on the corresponding soil, and trees will be planted in nearby areas. After receiving a landslide alert, the sand retaining device at the foot of the mountain will be opened. After receiving an alert that the solid content in the water exceeds the standard, the sedimentation tank at the water inlet will be opened to reduce the water flow rate, and the filter will be opened at the water inlet.

[0085] Obtain weather forecast information for the location of the reservoir. When the weather forecast predicts moderate rain, heavy rain or rainstorm, update the reservoir sand accumulation warning value every 1 / 3T, and lower the threshold of each data by 1 / 2.

[0086] The various critical values ​​in this case can be manually imported into the device by the user or obtained through digital twin technology.

[0087] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A smart water conservancy early warning method based on digital twin technology, characterized in that: The steps include: Step S1, setting two sampling areas of equal area on both sides of the river channel, evenly selecting soil points in the sampling areas, and placing a soil tester at each soil point to collect the sand, silt, and clay content of the soil at each soil point, and measuring the slope and slope length at each soil point; Step S2, using the Chinese Soil Loss Equation (CSLE) to calculate the soil erosion modulus A of each soil point; Step S3, calculating the soil erosion index I of each soil point according to the soil erosion modulus and the straight-line distance between each soil point and the river; dividing the sampling area into a number of sub-areas of equal size and using them as calculation areas, taking the average of the soil erosion indexes of all soil points in the calculation area, and obtaining the average soil erosion index I in the area; The calculation process of the soil erosion index is as follows: Obtain the horizontal distance s between the test point and the river channel and the height h from the horizontal plane, and use the distance formula to calculate the straight-line distance between the soil point and the river edge plane Calculate the two as follows: The value of I sought is the soil erosion index of the soil point; The sampling area is divided into several areas of equal size as the calculation area, and the soil erosion index of all soil points in the calculation area is averaged to obtain the average soil erosion index in the area. Step S4, placing speed sensors on a hillside with a height greater than 100 meters and a slope greater than 20° around the reservoir, and evenly placing three speed sensors on the top of the hillside, and placing one speed sensor at 1 / 3 and 2 / 3 of the height of the hillside, respectively, to measure and calculate the motion acceleration of the hillside; Step S5, collecting the data measured by each sensor in real time, and integrating the data of the five sensors of each hillside, calculating the overall acceleration of each hillside, and taking the ratio of the overall acceleration to the limit acceleration as the landslide index P, and taking the rain into consideration; The calculation method of acceleration and landslide index is as follows: Observe the x, y, and z values ​​on the sensor and process the three values ​​to get the overall acceleration: Among them, gen is the overall acceleration; the average value of the acceleration measured by the five sensors on the same slope in the same time period is taken as the acceleration in this area within the time window: N represents the number of all sensors in this area, and count is the number of sensor uploads in this time window; Introducing limiting acceleration: ext=0.5*count*g ext is the limit acceleration; the ratio of the acceleration in the area to the limit acceleration represents the intensity of the movement. Considering the factor of rain, the specific expression is: m is the number of sensors with water, and P is the landslide index; Step S6, select an area in the reservoir water storage river to place a suspended matter tester, measure the solid content in the water at regular intervals, and average the data measured by all the testers to obtain the solid content TS in the water storage river; Step S7, at fixed intervals, the average soil erosion index in each soil area and the maximum value of the landslide index of each hillside, as well as the solid content in the reservoir river are dimensionlessly processed to obtain a reservoir sedimentation warning value YJ. If the reservoir sedimentation warning value YJ exceeds a preset sedimentation threshold, the sub-parameter exceeding the corresponding threshold is determined, and a corresponding alarm is sent to the mobile terminal; The calculation of reservoir sedimentation warning value YJ in step 7 is as follows: Where YJ is the reservoir sediment warning value, is the average soil erosion index for all soil regions is the maximum value among all the landslide indices P, Pmax is the maximum value among all the landslide indices P of all the hillsides, TS is the solid content in the storage river, A, B, C are different weights respectively, and D is the constant correction coefficient.

2. A smart water conservancy early warning method based on digital twin technology according to claim 1, characterized in that: The Chinese soil loss equation CSLE in step S2 is: A=R×K×LS×B×E×T By processing the collected data, the soil erosion modulus at the collection point can be obtained; Among them, A is the desired erosion modulus; R is the rainfall erosivity factor, which is calculated using the rainfall intensity formula based on daily rainfall and previous daily, monthly, and annual rainfall; K is the soil erodibility factor. The K value table method is used to find the corresponding K value according to the land use type and soil type of the sampling area. L and S are the slope factor and slope length factor, respectively. The LS value is calculated by combining the digital elevation model and geographic information system technology, analyzing and processing the terrain. B is the plant coverage and biological measure factor. The plant coverage is expressed by the NDVI normalized difference vegetation index. The NDVI value is calculated by the reflectivity of the reflectivity and the reflectivity of the red light band. The corresponding plant coverage is found in the NDVI corresponding table according to the value of the NDVI index. The biological measure factor is calculated by the response of the receptor organism to the biological measure factor and the evaluation index. E and T are engineering measures factor and tillage measures factor respectively, that is, the usage of the measured land. Different usages have different values. The corresponding E and T values ​​are found according to the land use type and soil type of the soil in the sampling area.

3. According to the smart water conservancy early warning method based on digital twin technology described in claim 1, it is characterized by: Take T time as the time interval to obtain the new reservoir sediment warning value YJ; If the reservoir sedimentation warning value YJ after a certain update exceeds the preset sedimentation threshold, the sub-parameter exceeding the corresponding threshold is determined, and a corresponding warning is sent to the mobile terminal; If the average soil erosion index in the soil area The maximum value in If the threshold is exceeded, the area where the soil erosion index exceeds the corresponding threshold is determined, and a soil erosion alarm and information about the area where soil erosion has occurred are sent to the mobile terminal; If the maximum value Pmax of the landslide index P of the hillside exceeds the threshold, the hillside whose landslide index exceeds the corresponding threshold is determined, and a landslide alarm and information about the hillside with a high probability of landslide are sent to the mobile terminal; If it is found that the solid content in the reservoir river exceeds the threshold, the system will send an alarm of excessive solid content in the water to the mobile terminal.

4. A smart water conservancy early warning method based on digital twin technology according to claim 3, characterized in that: After receiving a soil erosion alert, soil maintenance will be carried out in areas where soil erosion is severe. Organic matter will be added to the soil in these areas, cover crops will be placed on the corresponding soil, and trees will be planted in nearby areas. After receiving a landslide alert, the sand retaining device at the foot of the mountain will be opened. After receiving an alert that the solid content in the water exceeds the standard, the sedimentation tank at the water inlet will be opened to reduce the water flow rate, and the filter will be opened at the water inlet.

5. A smart water conservancy early warning method based on digital twin technology according to claim 4, characterized in that: Obtain weather forecast information for the location of the reservoir. When the weather forecast predicts moderate rain, heavy rain or rainstorm, update the reservoir sedimentation warning value every 1 / 3T and lower the threshold of each data by 1 / 2.

6. A smart water conservancy early warning system based on digital twin technology using the smart water conservancy early warning method based on digital twin technology as claimed in claim 1, characterized in that: include: Data collection unit: collects soil data, slope movement data and water solid content data for subsequent analysis and processing; Data processing unit: preprocessing the collected data, such as missing value processing, outlier processing and noise processing; The pre-processed data were respectively brought into the operation to calculate the soil erosion modulus, landslide index and solid content in water; the three calculated data were dimensionlessly processed to obtain the reservoir sedimentation warning value; Prediction and warning unit: The system determines whether to issue a warning based on whether the reservoir sedimentation warning value exceeds the threshold. If the reservoir sedimentation warning value exceeds the set threshold, the system will further analyze which data exceeds the threshold and issue a corresponding warning to the mobile terminal. After receiving the warning, the staff will take appropriate measures.

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