CN116882215B - Multi-element self-excitation early warning method - Google Patents
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Abstract
The invention relates to a multi-element self-excitation early warning method, which comprises the steps of obtaining the actual water level, precipitation amounts at different positions and precipitation time lengths at different positions; a digital twin model is called, wherein the digital twin model comprises the topography and profile distribution conditions and geological information of mountain bodies, river channels and reservoirs and a water level prediction algorithm; determining the water level change of the reservoir in the digital twin model according to the precipitation amounts and precipitation time lengths of different positions based on the water level prediction algorithm to obtain a reference water level; and correcting the digital twin model according to the actual water level and the reference water level based on the correction model. The method is convenient for accurately predicting the water level of the reservoir and realizes accurate early warning.
Description
Technical Field
The application relates to the technical field of hydraulic engineering monitoring, in particular to a multi-element self-excitation early warning method.
Background
Generally, under the common influence of summer monsoon and subtropical high pressure, china can burst a large range of precipitation, so that each river can enter the flood season with the largest water amount. The reservoirs built at the narrow openings of the mountain ditches or the rivers can play roles in flood control, water storage irrigation, water supply, power generation and the like.
However, in the case of reservoirs built in mountain, there are many unknown factors in analyzing the influence of precipitation on the water level of the reservoir due to the influence of many factors such as topography, weather, etc., which increases the difficulty of analysis. Especially when the precipitation reaches the precipitation level of an extra heavy storm level, the water level of the reservoir may increase suddenly. At this time, the situation that the suddenly increased water quantity overflows from the reservoir easily occurs, and when the water flows from high to low, the water in the reservoir also accumulates a large potential energy, so that the possibility that the dam is washed down is increased. Therefore, it is necessary to predict the water level of the reservoir.
Disclosure of Invention
The application aims to provide a multi-element self-excitation early warning method which has the characteristic of accurately predicting the water level of a reservoir.
The first object of the present application is achieved by the following technical solutions:
a multi-element self-excitation early warning method comprises the following steps:
acquiring the actual water level and precipitation amounts at different positions and precipitation time lengths at different positions;
a digital twin model is called, wherein the digital twin model comprises the topography and profile distribution conditions and geological information of mountain bodies, river channels and reservoirs and a water level prediction algorithm;
determining the water level change of the reservoir in the digital twin model according to the precipitation amounts and precipitation time lengths of different positions based on the water level prediction algorithm to obtain a reference water level;
and correcting the digital twin model according to the actual water level and the reference water level based on the correction model.
By adopting the technical scheme, the digital twin model is built according to the actual environment, the water level change is predicted according to the water level prediction algorithm, and the digital twin model is corrected according to the difference value between the actual water level and the reference water level, so that the digital twin model can be predicted more accurately. Only when the reference water level is closer to the actual water level, the result of the digital twin model prediction is more accurate, and the method can be used for predicting the water level change of the reservoir so as to perform early warning.
The present application may be further configured in a preferred example to: the determining the water level change of the reservoir in the digital twin model according to the precipitation amounts and precipitation durations of the different positions based on the water level prediction algorithm, and the obtaining the reference water level comprises the following steps:
determining the total amount of river channel precipitation, the total amount of mountain precipitation and the total amount of reservoir precipitation according to the topography and profile distribution conditions, the precipitation amounts and the precipitation time lengths of different positions;
determining mountain water loss according to the distribution condition of the topography, precipitation amounts at different positions, precipitation time length and geological information;
and determining a reference water level according to the total river precipitation, the total reservoir precipitation, the total mountain precipitation and the mountain water loss, and the acquired reservoir size and initial water level.
The present application may be further configured in a preferred example to: the mountain waste water quantity comprises evaporation water quantity, and the determining of the mountain waste water quantity according to the distribution condition of the topography and the land relief, precipitation time length and geological information comprises the following steps:
acquiring the original evaporation capacity, and temperature information, wind speed information, humidity information and geographic position information corresponding to the original evaporation capacity;
establishing a corresponding relation model between the evaporation water quantity and the temperature information, the wind speed information, the humidity information and the geographic position information according to the original evaporation quantity and the temperature information, the wind speed information, the humidity information and the geographic position information corresponding to the original evaporation quantity;
acquiring current temperature information, wind speed information, humidity information and geographic position information;
and determining the evaporation water quantity according to the current temperature information, the wind speed information, the humidity information and the geographic position information based on the corresponding relation model.
The present application may be further configured in a preferred example to: the mountain waste water amount also comprises the total accumulated water amount, and the mountain waste water amount determining step for determining the mountain waste water amount according to the distribution condition of the topography and the land features, the precipitation amount of different positions, the precipitation duration and the geological information further comprises the following steps:
determining a water accumulation position and the water accumulated amount of each water accumulation position according to the topography distribution condition;
determining the corresponding precipitation amount and precipitation time according to the water accumulation position;
determining the actual water accumulation amount according to the precipitation amount, the precipitation duration and the water accumulation amount;
and determining the total water accumulation amount according to the actual water accumulation amount of each water accumulation position.
The present application may be further configured in a preferred example to: the determining the actual water accumulation amount according to the precipitation amount, the precipitation duration and the water accumulation amount comprises the following steps:
determining the reference water accumulation amount of the water accumulation position according to the precipitation amount and the precipitation duration;
if the reference water volume is larger than the water volume which can be accumulated, the actual water volume is the water volume which can be accumulated;
if the reference water volume is smaller than or equal to the water volume which can be accumulated, the actual water volume is the reference water volume.
The present application may be further configured in a preferred example to: the mountain waste water quantity further comprises a penetrating water quantity, and the mountain waste water quantity is determined according to the distribution condition of the topography and the relief, the precipitation quantity of different positions, the precipitation duration and the geological information, and further comprises:
the geological information comprises soil components at different positions of the mountain;
determining the permeability of different positions according to the soil components;
and determining the osmotic water quantity according to the precipitation quantity, the precipitation time length and the osmotic rate of different positions.
The present application may be further configured in a preferred example to: the method for determining the original evaporation amount comprises the following steps:
determining the overflow water amount of the mountain according to the total amount of precipitation of the mountain, the total amount of accumulated water and the osmotic water amount during the same precipitation;
determining a reference water level according to the total river precipitation, the total reservoir precipitation and the mountain overflow amount, and the acquired reservoir size and initial water level;
and calculating a water level difference value between the reference water level and the actual water level to obtain the original evaporation capacity.
The present application may be further configured in a preferred example to: the digital twin model is corrected according to the actual water level and the reference water level based on the correction model, and comprises the following steps:
the digital twin model is corrected according to the actual water level and the reference water level based on the correction model, and comprises the following steps:
calculating a water level difference value between the actual water level and the reference water level;
acquiring historical data;
and correcting the corresponding relation model according to the historical data and the water level difference value.
The present application may be further configured in a preferred example to: the method for determining the total river precipitation amount, the mountain precipitation amount and the reservoir precipitation amount according to the topography and profile distribution condition, precipitation amounts at different positions and precipitation time length comprises the following steps:
dividing the monitored area in the digital twin model to obtain a plurality of unit areas;
estimating the surface area of the river channel according to a plurality of unit areas where the river channel is positioned;
determining the total precipitation amount of the river channel according to precipitation amounts of a plurality of unit areas where the river channel is located, corresponding precipitation time periods and the surface area of the river channel;
estimating the surface area of the mountain according to a plurality of unit areas where the mountain is located;
determining the total precipitation amount of the mountain according to precipitation amounts of a plurality of unit areas where the mountain is located, corresponding precipitation time periods and the surface area of the mountain;
estimating the surface area of the reservoir according to a plurality of unit areas where the reservoir is located;
and determining the total amount of reservoir precipitation according to the precipitation amounts of the plurality of unit areas where the reservoir is located, the corresponding precipitation duration and the surface area of the reservoir.
The present application may be further configured in a preferred example to: the dividing the monitored area in the digital twin model to obtain a plurality of unit areas comprises:
acquiring a top view of the monitored area;
and dividing the top view into areas.
In summary, the present application includes at least one of the following beneficial technical effects:
and establishing a digital twin model according to the actual environment, predicting the water level change according to a water level prediction algorithm, and correcting the digital twin model according to the difference between the actual water level and the reference water level, so that the digital twin model can be predicted more accurately. Only when the reference water level is closer to the actual water level, the result of the digital twin model prediction is more accurate, and the method can be used for predicting the water level change of the reservoir so as to perform early warning.
Drawings
Fig. 1 is a flow chart of a multi-element self-excitation early warning method according to an embodiment of the present application.
FIG. 2 is a system diagram of a multi-element self-energizing early warning system according to one embodiment of the present application.
Fig. 3 is a schematic structural diagram of an intelligent terminal according to an embodiment of the present application.
In the figure, 21, an acquisition module; 22. a calling module; 23. a determining module; 24. a correction module; 301. a CPU; 302. a ROM; 303. a RAM; 304. a bus; 305. an I/O interface; 306. an input section; 307. an output section; 308. a storage section; 309. a communication section; 310. a driver; 311. removable media.
Detailed Description
The present application is described in further detail below with reference to the accompanying drawings.
The present embodiment is merely illustrative of the present application and is not intended to be limiting, and those skilled in the art, after having read the present specification, may make modifications to the present embodiment without creative contribution as required, but is protected by patent laws within the scope of the claims of the present application.
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, unless otherwise specified, the term "/" generally indicates that the associated object is an "or" relationship.
The embodiment of the application provides a multi-element self-excitation early warning method which is used for simulating the change of the water level of a reservoir through a digital twin model so as to predict the water level.
The digital twin is to fully utilize data such as a physical model, sensor update, operation history and the like, integrate simulation processes of multiple disciplines, multiple physical quantities, multiple scales and multiple probabilities, and establish mirror images of real equipment in a virtual space, wherein the mirror images reflect the life of the real equipment and the real-time condition of the real equipment in each life.
The digital twin model may simulate any area that is desired to be monitored. In the application, the digital twin model mainly simulates the actual environment of the reservoir built according to mountains, and comprises the position relationship among mountains, river channels and reservoirs. Specifically, the river channel is built along the mountain body, and the river channel is connected with a reservoir. Correspondingly, a three-dimensional model which is completely consistent with the actual environment is constructed in the digital twin model. The three-dimensional model not only can reflect the topography of monitored mountain, river channel and reservoir, but also can simulate mountain environment, such as tree, soil, illumination, temperature, humidity, wind speed and the like.
It can be appreciated that the reservoir is also provided with spillways, water ports, gates and vent holes. Spillways are used to drain excess water through overflow when the reservoir level exceeds a water level threshold. The water diversion port is used for discharging water of the reservoir, a motor is arranged on a water discharge channel communicated with the water diversion port, and the motor generates electricity according to the discharged water. The gate is used for discharging water in the reservoir when the reservoir capacity can not continuously store flood, and the gate is a water outlet with the largest water discharge compared with the spillway, the water diversion port and the emptying hole. The emptying hole is positioned at the bottom of the reservoir and is used for discharging sediment at the bottom of the reservoir or emptying the reservoir when maintenance is performed.
Embodiments of the present application are described in further detail below with reference to the drawings attached hereto.
The main flow of the multi-element self-excitation early warning method provided by the embodiment of the application is described as follows.
As shown in fig. 1:
step S100: and acquiring the actual water level and precipitation amounts at different positions and the precipitation time lengths at different positions.
It can be appreciated that, due to the larger detected area, precipitation at different positions may occur, and precipitation at partial areas may also occur, so that precipitation at different positions needs to be collected so as to more accurately predict the change of the reservoir water level. Similarly, the starting node and the stopping node of precipitation at different positions are different, and intermittent precipitation can also occur, so that the precipitation time periods at different positions also need to be acquired. For intermittent precipitation, an interval duration threshold may be preset. And when the interval duration between the two precipitation is smaller than or equal to the interval duration threshold, the two precipitation is regarded as one precipitation, namely the precipitation duration is the sum of the precipitation durations of the two precipitation. Of course, the situation of multiple precipitation is also applicable. In the embodiment of the application, the precipitation amount and the corresponding precipitation duration can be obtained through a weather station.
Wherein the actual water level is the actual water level of the reservoir. In the present application, the water level after each precipitation may be referred to, and the water level after a period of precipitation may be referred to. In the embodiment of the application, the actual water level can be acquired through a water level monitoring device arranged in the reservoir.
Step S200: and calling the digital twin model.
The digital twin model comprises the topography and topography distribution conditions and geological information of mountain bodies, river channels and reservoirs and a water level prediction algorithm. When the precipitation amount is input to the digital twin model for a period of time, the digital twin model can output the variation of the water level of the water reservoir or the final water level of the water reservoir in the period of time.
The topography distribution condition of the topography can reflect the topography of mountain, river and reservoir. For example, the trend of the topography of the river channel at different positions, the relationship between the different positions of the river channel and the surrounding mountain, the relationship between the river channel and the reservoir, the relationship between the reservoir and the mountain, the relationship between the topography of each position on the mountain, the trend of the topography, etc. The geological information can reflect the geological condition of the mountain. Such as soil composition at various locations on the mountain and rock types at various locations. The water level prediction algorithm is an algorithm for calculating the water level of the reservoir according to the mountain environment simulated by the digital twin model.
The construction process of the digital twin model is a common technical means for a person skilled in the relevant art, and will not be described in detail here.
Step S300: and determining the water level change of the reservoir in the digital twin model according to the precipitation amounts and precipitation time lengths of different positions based on the water level prediction algorithm to obtain a reference water level.
It will be appreciated that the purpose of modeling the reservoir level by creating a digital twin model is to monitor the reservoir level. When the water level prediction algorithm is more accurate, the result of predicting the water level of the reservoir through the digital twin model is more accurate, and the change of the water level of the reservoir can be monitored more accurately through the prediction result of the digital twin model. For this reason, correction of the water level prediction algorithm is required. In order to implement the correction of the water level prediction algorithm, it is necessary to know the actual water level of the reservoir at the same time node and the reference water level calculated according to the water level prediction algorithm. The method for determining the reference water level in the present application is as follows:
optionally, the step S300 includes the following steps (step S310 to step S330):
step S310: and determining the total amount of river channel precipitation, the total amount of mountain precipitation and the total amount of reservoir precipitation according to the distribution condition of the topography and the topography, the precipitation amounts of different positions and the precipitation duration.
The total amount of river precipitation is the total amount of precipitation dropped in the river, the total amount of mountain precipitation is the total amount of precipitation dropped in the mountain, and the total amount of reservoir precipitation is the total amount of precipitation dropped in the reservoir. The total amount of reservoir precipitation can directly cause the water level of the reservoir to rise, and the total amount of mountain precipitation flows to the river course, converges with the total amount of river course precipitation and flows to the reservoir, so that the water level of the reservoir rises. In the process that the total amount of mountain precipitation flows to the river channel, the total amount of mountain precipitation flowing to the river channel can be gradually reduced under the influence of various factors such as the topography of mountain, soil property, humiture and the like. In order to accurately predict the change of the reservoir water level, it is necessary to consider the loss generated when the total amount of mountain precipitation flows to the river channel. Therefore, it is necessary to specify the total amount of river precipitation, the total amount of mountain precipitation, and the total amount of reservoir precipitation, respectively.
The method for determining the total river precipitation, the total mountain precipitation and the total reservoir precipitation comprises the following steps:
first, a plurality of unit areas are obtained by dividing the monitored area in the digital twin model. It can be understood that the precipitation amount calculated according to the three-dimensional division into the unit areas and the actual precipitation amount may deviate due to the staggered topography of the monitored area. Therefore, in the present application, before dividing the monitored area in the digital twin model, it is also necessary to obtain a top view of the monitored area. In the case of not considering the influence of wind force and wind direction, the rainwater should fall vertically under the influence of gravity, so theoretically the precipitation area should be the area on the top view of the monitored area. In other embodiments, the rainfall area may be further analyzed based on real-time wind force and wind direction to more accurately calculate precipitation. In addition, in order to facilitate calculation of the area, in the embodiment of the present application, the unit area is selected to have a size such as 1 square centimeter, 1 square decimeter, or 1 square meter, and in particular, an appropriate size may be selected according to the ratio of the top view.
Then, the surface area of the river channel is estimated according to a plurality of unit areas where the river channel is located. Wherein, in estimating the river surface area, it may be estimated in such a manner that the ratio of the river portion in each unit area is based. Specifically, if the river section in the cell area occupies 100%, the river area in the cell area is the area of the cell area. If the river section in one unit area occupies 30% and the river section in the other unit area occupies 70%, the river area in both unit areas is the area of one unit area. Furthermore, the river surface area can be rapidly estimated by determining the number of the unit areas of the river which occupy 100% of the river, and then determining the number of the unit areas of the river which occupy 100% of the river. Since the plan view is a two-dimensional view and is deviated from the actual river structure, the surface area is not the actual surface area of the river.
Further, the total amount of river precipitation is determined according to the precipitation amounts of a plurality of unit areas where the river is located, the corresponding precipitation duration and the river surface area. Specifically, the total precipitation amount per unit area is the product of the precipitation amount and the precipitation time period. For the case of constantly changing precipitation, the total precipitation per unit area can be obtained by accumulating the precipitation per time node. Similarly, the total precipitation amount of the river is the sum of precipitation amounts of all the unit areas. It should be noted that, for a unit area in which only a part of the unit area is a river channel, the total amount of precipitation in the river channel portion may be determined according to the river channel portion ratio and the total amount of precipitation in the unit area. In other embodiments, other means of calculating the total amount of precipitation in the river may be used.
Similarly, the mountain surface area is estimated according to a plurality of unit areas where the mountain is located, the total amount of mountain precipitation is determined according to the precipitation amounts, the corresponding precipitation durations and the mountain surface areas of the plurality of unit areas where the mountain is located, the reservoir surface area is estimated according to the plurality of unit areas where the reservoir is located, and the total amount of reservoir precipitation is determined according to the precipitation amounts, the corresponding precipitation durations and the reservoir surface areas of the unit areas where the reservoir is located. For specific calculation methods, reference may be made to the above methods, and redundant descriptions are not repeated here.
Step S320: and determining the mountain water loss according to the distribution condition of the topography and the topography, the precipitation amount of different positions, the precipitation duration and the geological information.
The mountain water loss amount is a difference value between the total amount of mountain precipitation and the total amount of precipitation flowing to the river channel in value. The difference between the total amount of mountain precipitation and the total amount of precipitation flowing to the river channel is mainly caused by the fact that the precipitation is evaporated under the influence of the environment, accumulated water is generated in the area with lower topography, and the accumulated water is absorbed by soil. Therefore, the mountain waste water mainly comprises three parts of evaporation water, accumulated water and permeated water.
The method for calculating the total accumulated water comprises the following steps:
firstly, determining a water accumulation position and the water depositable quantity of each water accumulation position according to the distribution condition of the topography and the topography.
Normally, the topography of the ponding location is in a state of low middle, high surrounding. By analyzing the distribution of the topography, the position meeting the topography can be found out, namely the ponding position. The water amount which can be accumulated in each water accumulation position is the water amount which can be collected, is mainly related to the shape and depth of the water accumulation position, and can be specifically determined according to the edge of the water accumulation position and the difference between the topography of the edge of the water accumulation position and the topography of the center topography reflected by the topography and topography distribution condition.
And then, determining the corresponding precipitation amount and precipitation duration according to the water accumulation position.
And determining the actual water accumulation amount according to the precipitation amount, the precipitation duration and the water accumulation amount.
It will be appreciated that the actual water volume will not exceed the water integrable volume at most. Before the actual water accumulation is determined, the reference water accumulation of the water accumulation position is determined according to the precipitation amount and the precipitation time. The reference water volume is the water volume of the water accumulation position without considering the overflow condition. The reference water accumulation amount is the product of the surface area of the water accumulation position and the precipitation amount and the precipitation duration. If the reference water volume is larger than the water volume which can be accumulated, the actual water volume is the water volume which can be accumulated. If the reference water volume is smaller than or equal to the water volume which can be accumulated, the actual water volume is the reference water volume.
And finally, determining the total accumulated water according to the actual accumulated water amount of each accumulated water position. The total accumulated water amount is the sum of the actual accumulated water amount of each accumulated water position.
The method for calculating the osmotic water quantity comprises the following steps:
first, the permeability of different locations is determined according to the soil composition.
It will be appreciated that the soil composition of the feet, hills and tops of a mountain may vary from one mountain to another. However, different soil compositions may also cause differences in permeability at different locations. Therefore, it is necessary to identify soil components at different positions of the mountain first. In some specific embodiments, after determining the soil composition, the permeability at different locations may be determined based on a comparison of the soil composition and the permeability. The relationship between the soil composition and the permeability may be stored in advance in a storage device having a storage function such as a memory.
And then determining the osmotic water quantity according to the precipitation quantity, the precipitation time length and the osmotic rate of different positions.
In general, the permeability will decrease over time until the permeability remains constant after decreasing to a steady permeability. Specifically, each soil component corresponds to a permeability profile over time. The permeability versus time curves for different soil components are different. It should be noted that the time for decreasing the permeability to the stable permeability is generally 2 to 3 hours, however, when the permeability has not reached the stable permeability in practice, some precipitation flows to the river channel. Therefore, the permeation duration needs to be considered in calculating the amount of permeated water. Taking a certain position as an example, the osmotic water amount is the sum of the osmotic rate in the osmotic time period. For the whole mountain, the amount of permeated water is the sum of the amounts of permeated water at each position.
It is worth noting that the amount of evaporated water needs to take into account more environmental factors than the total amount of accumulated water and the amount of permeated water, and is difficult to directly calculate. The original evaporation amount is estimated for this application. The original evaporation capacity is the first calculated evaporation capacity.
The method for calculating the original evaporation amount comprises the following steps:
firstly, determining the overflow water quantity of the mountain according to the total precipitation quantity of the mountain, the total accumulated water quantity and the seepage water quantity during the same precipitation.
The total accumulated water and the permeated water quantity in the same precipitation are calculated in the first precipitation. Since the amount of evaporation water cannot be determined, the amount of evaporation water is not considered when determining the amount of mountain waste water at this time, that is, the amount of mountain waste water at this time is the sum of the total amount of accumulated water and the amount of permeated water.
The mountain overflow water quantity is the water quantity flowing to the river channel in the total mountain precipitation quantity, and can be obtained by making the difference between the total mountain precipitation quantity and the mountain waste water quantity.
And then, determining a reference water level according to the total river channel precipitation, the total reservoir precipitation and the mountain overflow water quantity, and the acquired reservoir size and the initial water level.
Wherein the initial water level is the initial water level of the reservoir. The water level of the reservoir rises due to the total amount of river precipitation, the total amount of reservoir precipitation and the overflow amount of mountain. The variation of water level is the ratio of the sum of the total river precipitation, the total reservoir precipitation and the overflow of mountain to the size of the reservoir. The reservoir size is the area of the reservoir surface. Further, after the variation of the water level is determined, the current reference water level can be calculated according to the initial water level.
And finally, calculating the difference between the reference water level and the actual water level to obtain the original evaporation capacity.
Since the amount of evaporation water is not calculated when the amount of mountain waste water is calculated, the reference water level may be higher than the actual water level. And the difference between the reference water level and the actual water level is the original evaporation capacity. It should be noted that the original evaporation amount calculated here is only an estimated value.
In a specific example, in order to obtain a more accurate actual water level and reference water level, the reservoir may be drained before the precipitation is collected into the reservoir, so that the reservoir can completely accommodate the amount of water of one precipitation. When the reservoir is waterproof, the overflow condition can not occur in the precipitation process, so that the change of the water level can be obtained more accurately according to the measured initial water level and the actual water level. Of course, the digital twin model also requires a synchronous setup.
Further, after determining the original evaporation amount, the method for determining the evaporation amount of each precipitation after that includes:
first, an original evaporation amount is acquired, and temperature information, wind speed information, humidity information, and geographical position information corresponding to the original evaporation amount are acquired.
The temperature information, the wind speed information, the humidity information and the geographic position information are all factors which influence the evaporation water quantity. That is, the higher the temperature, the greater the amount of evaporated water; the larger the wind speed, the larger the amount of evaporated water; the greater the humidity, the smaller the amount of evaporated water; the closer to the sea, the smaller the amount of evaporated water; the higher the topography, the smaller the amount of evaporated water.
In order to be able to further clarify the original evaporation amount and the relationship between the temperature information, the wind speed information, the humidity information, and the geographical position information corresponding to the original evaporation amount, it is necessary to acquire the environmental information, i.e., the temperature information, the wind speed information, the humidity information, and the geographical position information at that time, at which the original evaporation amount is generated.
And then, establishing a corresponding relation model between the evaporation water quantity and the temperature information, the wind speed information, the humidity information and the geographic position information according to the original evaporation quantity and the temperature information, the wind speed information, the humidity information and the geographic position information corresponding to the original evaporation quantity.
And acquiring current temperature information, wind speed information, humidity information and geographical position information.
And finally, determining the evaporation water quantity according to the current temperature information, wind speed information, humidity information and geographical position information based on the corresponding relation model.
Because the corresponding relation model already stores the corresponding relation between the original evaporation capacity and the temperature information, the wind speed information, the humidity information and the geographic position information, when the current temperature information, the wind speed information, the humidity information and the geographic position information are acquired, the evaporation water quantity can be determined according to the influence degree of each environmental factor on the evaporation water quantity.
Step S330: and determining a reference water level according to the total river precipitation, the total reservoir precipitation, the total mountain precipitation and the mountain water loss, and the acquired reservoir size and initial water level.
Similarly, the water quantity collected into the reservoir is the difference between the sum of the total river precipitation, the total reservoir precipitation and the total mountain precipitation and the mountain water loss. And then, determining the reference water level according to the acquired reservoir size and the initial water level.
Step S400: and correcting the digital twin model according to the actual water level and the reference water level based on the correction model.
It can be understood that when the digital twin model is more attached to the actual environment, the digital twin model is used for prediction to be more accurate, and the change of the water level in the actual environment is more favorably predicted, so that the effect of accurate early warning is achieved. Therefore, it is necessary to correct the digital twin model.
It can be understood from the above description that the original evaporation amount calculated at the beginning is inaccurate, and thus the correspondence model obtained based thereon is also inaccurate. Therefore, a part of the reasons for the bias of the reference water level and the actual water level are because the correspondence model is inaccurate.
Specifically, the correction method includes: firstly, historical data is acquired, then, the difference value between the actual water level and the reference water level is calculated, and then, the corresponding relation model is corrected according to the difference value between the historical data and the actual water level as well as the reference water level.
The historical data comprises environmental information at different times, and the influence of illumination intensity, illumination duration and geographic position on temperature information, wind speed information and humidity information can be obtained by analyzing the environmental information. Therefore, the influence of temperature information, wind speed information, humidity information and geographical position information on the evaporation water quantity can be more clearly determined according to the historical data, and the corresponding relation model is optimized, so that the difference between the actual water level and the reference water level is gradually reduced, and the digital twin model is corrected.
Fig. 2 is a schematic diagram of a multi-element self-excitation early warning system according to an embodiment of the present application.
The multi-element self-excitation early warning system as shown in fig. 2 comprises an acquisition module 21, a retrieval module 22, a determination module 23 and a correction module 24, wherein:
the obtaining module 21 is configured to obtain the actual water level, precipitation amounts at different positions, and precipitation durations at different positions.
The invoking module 22 is configured to invoke a digital twin model, where the digital twin model includes a topography profile and geological information of mountain, river, and reservoir, and a water level prediction algorithm.
And the determining module 23 is configured to determine a water level change of the reservoir in the digital twin model according to precipitation amounts and precipitation durations at different positions based on the water level prediction algorithm, so as to obtain a reference water level.
The correction module 24 is used for correcting the digital twin model according to the actual water level and the reference water level based on the correction model.
Fig. 3 shows a schematic structural diagram of a smart terminal suitable for implementing embodiments of the present application.
As shown in fig. 3, the smart terminal includes a Central Processing Unit (CPU) 301 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage section into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other through a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
The following components are connected to the I/O interface 305: an input section 306 including a keyboard, a mouse, and the like; an output portion 307 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 308 including a hard disk or the like; and a communication section 309 including a network interface card such as a LAN card, a modem, or the like. The communication section 309 performs communication processing via a network such as the internet. The drive 310 is also connected to the I/O interface 305 as needed. A removable medium 311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed on the drive 310 as needed, so that a computer program read out therefrom is installed into the storage section 308 as needed.
In particular, according to embodiments of the present application, the process described above with reference to flowchart fig. 1 may be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a machine-readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 309, and/or installed from the removable medium 311. The above-described functions defined in the system of the present application are performed when the computer program is executed by a Central Processing Unit (CPU) 301.
It should be noted that the computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present application may be implemented by software, or may be implemented by hardware. The described units or modules may also be provided in a processor, for example, as: a processor comprising: acquisition module 21, retrieval module 22, determination module 23 and correction module 24. The names of these units or modules do not in any way limit the units or modules themselves, and the acquisition module 21 may also be described as "a module for acquiring the actual water level and the precipitation amount at different locations, and the precipitation time periods at different locations", for example.
As another aspect, the present application also provides a computer-readable storage medium, which may be included in the intelligent terminal described in the above embodiment; or may exist alone without being assembled into the smart terminal. The computer-readable storage medium stores one or more programs that when executed by one or more processors perform the multi-element self-energizing early warning method described herein.
The foregoing description is only of the preferred embodiments of the present application and is presented as a description of the principles of the technology being utilized. It will be appreciated by persons skilled in the art that the scope of the application referred to in this application is not limited to the specific combinations of features described above, but it is intended to cover other embodiments in which any combination of features described above or their equivalents is possible without departing from the spirit of the application. Such as the above-mentioned features and the technical features having similar functions (but not limited to) applied for in this application are replaced with each other.
Claims (7)
1. A multi-element self-excitation early warning method is characterized by comprising the following steps:
acquiring the actual water level and precipitation amounts at different positions and precipitation time lengths at different positions;
a digital twin model is called, wherein the digital twin model comprises the topography and profile distribution conditions and geological information of mountain bodies, river channels and reservoirs and a water level prediction algorithm;
determining the water level change of the reservoir in the digital twin model according to the precipitation amounts and precipitation time lengths of different positions based on the water level prediction algorithm to obtain a reference water level;
based on the correction model, correcting the digital twin model according to the actual water level and the reference water level;
the determining the water level change of the reservoir in the digital twin model according to the precipitation amounts and precipitation durations of the different positions based on the water level prediction algorithm, and the obtaining the reference water level comprises the following steps:
determining the total amount of river channel precipitation, the total amount of mountain precipitation and the total amount of reservoir precipitation according to the topography and profile distribution conditions, the precipitation amounts and the precipitation time lengths of different positions;
determining mountain water loss according to the distribution condition of the topography, precipitation amounts at different positions, precipitation time length and geological information;
determining a reference water level according to the total river precipitation, the total reservoir precipitation, the total mountain precipitation and the mountain water loss, and the acquired reservoir size and initial water level;
the mountain waste water quantity comprises evaporation water quantity, and the determining of the mountain waste water quantity according to the distribution condition of the topography and the land relief, precipitation time length and geological information comprises the following steps:
determining the overflow water amount of the mountain according to the total amount of precipitation of the mountain, the total amount of accumulated water and the osmotic water amount during the same precipitation;
determining a reference water level according to the total river precipitation, the total reservoir precipitation and the mountain overflow amount, and the acquired reservoir size and initial water level;
calculating a water level difference value between the reference water level and the actual water level to obtain an original evaporation capacity;
acquiring temperature information, wind speed information, humidity information and geographic position information corresponding to the original evaporation capacity;
establishing a corresponding relation model between the evaporation water quantity and the temperature information, the wind speed information, the humidity information and the geographic position information according to the original evaporation quantity and the temperature information, the wind speed information, the humidity information and the geographic position information corresponding to the original evaporation quantity;
acquiring current temperature information, wind speed information, humidity information and geographic position information;
and determining the evaporation water quantity according to the current temperature information, the wind speed information, the humidity information and the geographic position information based on the corresponding relation model.
2. The multi-element self-excitation early warning method according to claim 1, wherein the mountain waste water amount further comprises a total accumulated water amount, and the determining the mountain waste water amount according to the topography distribution condition, precipitation amounts at different positions, precipitation time periods and geological information further comprises:
determining a water accumulation position and the water accumulated amount of each water accumulation position according to the topography distribution condition;
determining the corresponding precipitation amount and precipitation time according to the water accumulation position;
determining the actual water accumulation amount according to the precipitation amount, the precipitation duration and the water accumulation amount;
and determining the total water accumulation amount according to the actual water accumulation amount of each water accumulation position.
3. The multi-element self-excitation early warning method according to claim 2, wherein the determining the actual water accumulation amount according to the precipitation amount, the precipitation duration, and the water accumulation amount comprises:
determining the reference water accumulation amount of the water accumulation position according to the precipitation amount and the precipitation duration;
if the reference water volume is larger than the water volume which can be accumulated, the actual water volume is the water volume which can be accumulated;
if the reference water volume is smaller than or equal to the water volume which can be accumulated, the actual water volume is the reference water volume.
4. The multi-element self-excitation early warning method according to claim 2, wherein the mountain waste water amount further comprises a penetration water amount, and the determining the mountain waste water amount according to the topography distribution condition, precipitation amounts at different positions, precipitation time periods and geological information further comprises:
the geological information comprises soil components at different positions of the mountain;
determining the permeability of different positions according to the soil components;
and determining the osmotic water quantity according to the precipitation quantity, the precipitation time length and the osmotic rate of different positions.
5. The multi-element self-excitation pre-warning method according to claim 1, wherein the correcting the digital twin model based on the actual water level and the reference water level comprises:
calculating a water level difference value between the actual water level and the reference water level;
acquiring historical data;
and correcting the corresponding relation model according to the historical data and the water level difference value.
6. The multi-element self-excitation early warning method according to claim 1, wherein the determining the total river precipitation, the total mountain precipitation and the total reservoir precipitation according to the topography distribution situation, precipitation amounts and precipitation durations of different positions comprises:
dividing the monitored area in the digital twin model to obtain a plurality of unit areas;
estimating the surface area of the river channel according to a plurality of unit areas where the river channel is positioned;
determining the total precipitation amount of the river channel according to precipitation amounts of a plurality of unit areas where the river channel is located, corresponding precipitation time periods and the surface area of the river channel;
estimating the surface area of the mountain according to a plurality of unit areas where the mountain is located;
determining the total precipitation amount of the mountain according to precipitation amounts of a plurality of unit areas where the mountain is located, corresponding precipitation time periods and the surface area of the mountain;
estimating the surface area of the reservoir according to a plurality of unit areas where the reservoir is located;
and determining the total amount of reservoir precipitation according to the precipitation amounts of the plurality of unit areas where the reservoir is located, the corresponding precipitation duration and the surface area of the reservoir.
7. The multi-element self-excitation pre-warning method according to claim 6, wherein the dividing the monitored region in the digital twin model to obtain a plurality of unit regions comprises:
acquiring a top view of the monitored area;
and dividing the top view into areas.
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