Water conservancy flood prevention monitoring system based on multi-dimensional information model

Abstract

The embodiment of the invention discloses a water conservancy flood prevention monitoring system based on a multi-dimensional information model. In one specific embodiment, the system comprises a water conservancy flood prevention monitoring cloud platform and a plurality of monitoring devices. According to the embodiment, the whole water network water level of the monitoring area is calculated through the water conservancy flood prevention monitoring platform to obtain the water network water level map, and it can be avoided that the water network water level error of important areas is large, and judgment of the important areas such as flood-prone areas is affected. According to the method, an information model containing multiple dimensions such as space, time and attributes is constructed. And a scientific basis is provided for river management, flood control and disaster reduction and water resource scheduling. The monitoring device ensures the low power consumption capability of the device; when the data is abnormal, the data is uploaded at a relatively high preset frequency, so that the real-time performance of data transmission is ensured; in order to ensure the reliability of water conservancy flood prevention monitoring, the water flow velocity, rainfall, water level and other data which are crucial to water flood monitoring are collected, and the real-time condition of the water network and the water flood can be mastered in time.

Description

Technical Field

[0001] The present invention relates to the field of water conservancy and flood control monitoring, and more specifically, to a water conservancy and flood control monitoring system based on a multidimensional information model. Background Art

[0002] At present, the existing water network water level map is obtained through optical remote sensing images. However, this method is affected by weather and terrain images, resulting in large errors in the measured water network water level, poor timeliness of water level information, and serious water body information leakage. Therefore, it is only used to judge the overall water body condition, and it is not easy to carry out more detailed early warning.

[0003] In the field of river management and flood prevention and disaster reduction, it is crucial to accurately and timely obtain and analyze river water level, water flow rate and rainfall data. Traditional data analysis methods are often limited to single-dimensional data display, such as only displaying water level changes through time series graphs or analyzing water flow rate data alone, which makes it difficult to fully reflect the dynamic characteristics and spatial distribution of river systems. In addition, rainfall data is one of the key factors affecting river water level and flow rate. Its temporal variation characteristics and spatial distribution have an important impact on the prediction and evaluation of river status, but traditional methods often ignore the inherent connection and interaction between these data.

[0004] Traditional water conservancy and flood control monitoring systems mostly rely on a single monitoring method, such as only monitoring water level changes through water level gauges. These data often lack comprehensiveness and real-time nature, and it is difficult to fully reflect the real-time conditions of rivers and basins.

[0005] With the rapid development of information technology, especially the widespread application of technologies such as the Internet of Things, big data and cloud computing, new technical means have been provided for water conservancy and flood control monitoring. However, the water conservancy and flood control monitoring systems in the existing technology still have many shortcomings. For example, although some systems can realize multi-parameter monitoring, their data processing and analysis capabilities are limited, and they cannot fully utilize the collected multi-dimensional information to analyze and predict the data; although other systems have data processing capabilities, the monitoring data collection frequency is fixed, or the frequency is too high, requiring real-time and fast data transmission, which leads to excessive energy consumption of the monitoring device, which greatly reduces the battery power supply time and increases the difficulty of device maintenance. On the other hand, if the monitoring frequency is too low, the monitoring results will not be accurate and timely.

[0006] In addition, most of the existing water conservancy and flood control monitoring systems lack unified cloud platform support, which makes it difficult to share data between monitoring devices and to achieve cross-regional and cross-departmental collaborative monitoring and early warning. At the same time, in abnormal situations, such as abnormally high river levels, faster water flow or a surge in rainfall, the existing system is often unable to respond in time and collect additional video data, thus limiting the emergency response capabilities of the monitoring system. Summary of the invention

[0007] The purpose of the present invention is to provide a water conservancy and flood control monitoring system based on a multidimensional information model to solve the problems mentioned in the background technology.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions:

[0009] The first aspect of the present invention provides a water conservancy and flood control monitoring system based on a multidimensional information model, comprising:

[0010] Water conservancy and flood control monitoring cloud platform and multiple monitoring devices;

[0011] Each of the monitoring devices is configured at a preset water network point, and is used to collect river water level data, river water flow rate data, and rainfall data at the preset water network point, and obtain and upload the collected data to the water conservancy and flood control monitoring cloud platform at a first preset frequency; and when the river water level data, river water flow rate data, or rainfall data is abnormal, collect and store video data at the preset water network point, send an early warning signal to the water conservancy and flood control monitoring cloud platform, and obtain and upload the river water level data, river water flow rate data, rainfall data, and video data at the preset point to the water conservancy and flood control monitoring cloud platform at a second preset frequency; the second preset frequency is greater than the first preset frequency;

[0012] The water conservancy and flood control monitoring cloud platform is used to calculate the water level of the entire water network in the monitored area to obtain a water network water level map, obtain the river water level data, river water flow rate data, rainfall data, warning signals and video data of the preset water network points uploaded by each monitoring device, and update the water level of each preset water network point in the water network point map based on the acquired data; at the same time, a multidimensional information model is constructed based on the river water level, river water flow rate and rainfall data of each preset water network point; and it is also used to predict the river water level of the preset water network point based on the river water level data, river water flow rate data and rainfall data of the corresponding preset water network point.

[0013] Furthermore, the monitoring device also includes a river water level measurement module, a river water flow rate measurement module, a rain gauge, a controller, a video monitoring terminal, a local storage module and a wireless communication terminal;

[0014] The river water level measurement module is used to collect river water level data at a preset water network point;

[0015] The river water flow rate measurement module is used to collect river water flow rate data at a preset water network point;

[0016] The rain gauge is used to collect rainfall data at the preset water network point;

[0017] The controller is used to obtain and upload the collected data to the water conservancy and flood control monitoring cloud platform at a first preset frequency; and when the river water level data, river water flow rate data or rainfall data are abnormal, the video data of the preset water network point is collected through the video monitoring terminal, the data collected by the video monitoring terminal is stored through the local storage module, an early warning signal is sent to the water conservancy and flood control monitoring cloud platform, and the river water level data, river water flow rate data, rainfall data and video data of the preset point are obtained and uploaded to the water conservancy and flood control monitoring cloud platform at a second preset frequency; the second preset frequency is greater than the first preset frequency.

[0018] Furthermore, the monitoring device also includes a power supply battery, a solar panel and a charge controller;

[0019] The solar panel is used to charge the power supply battery through a charge controller; the power supply battery is used to supply power to the controller, the video monitoring terminal and the wireless communication terminal through the charge controller.

[0020] Furthermore, the water conservancy and flood control monitoring cloud platform also includes a water network water level calculation module, which is used to obtain digital elevation models and actual river source data; in response to user setting operations, multiple catchment area thresholds are obtained from a preset catchment area threshold range; the following calculations are performed based on each catchment area threshold: according to the digital elevation model, the actual river source data and the set catchment area threshold, the corresponding river channel and basin data are calculated based on the SWAT model to obtain the river channel surface vector; lake and reservoir vectors are obtained and extracted based on synthetic aperture radar image data: the obtained river channel surface vector is merged with the obtained lake and reservoir vector to obtain a water network vector; For each set catchment area threshold, calculate the distance error between the extracted water network vector and the actual river source; obtain the closest point to the actual river source, and calculate the distance between the two points to get the distance error; and use the catchment area threshold corresponding to the minimum distance error as the optimal catchment area threshold; use the water network vector corresponding to the optimal catchment area threshold as the optimal water network vector; obtain the optical remote sensing image and crop it according to the optimal water network vector to obtain the optical remote sensing image of the corresponding water network, establish a multi-band combination model based on the optical remote sensing image to calculate the water depth of the water network, calculate the water level of the water network according to the water depth of the water network at the corresponding position and the elevation of the bottom of the water network, and generate a water level map of the water network.

[0021] Furthermore, the acquisition module is used to acquire the river water level data, river water flow rate data and rainfall data of the preset water network points uploaded by each monitoring device;

[0022] The updating module is used to update the water level of each preset water network point in the preset water network point map based on the acquired data.

[0023] Furthermore, the water conservancy and flood control monitoring cloud platform includes a multi-dimensional information model building module;

[0024] The multidimensional information model building module is used to build a multidimensional information model based on the river water level data, river water flow rate data and rainfall data of each preset water network point.

[0025] Furthermore, the multi-dimensional information model is constructed based on the river water level data, river water flow velocity data and rainfall data of each preset water network point, including:

[0026] The preset water network points are numbered; a three-dimensional coordinate system is constructed with the preset water network point number as the first coordinate axis, the river water level as the second coordinate axis, and the river water flow rate as the third coordinate axis; a surface map or contour map of the water level and water flow rate at different time points is drawn in the three-dimensional coordinate system to respectively display the spatial distribution of the water level and the water flow rate; the rainfall data, as a variable in the time dimension, is displayed in the three-dimensional coordinate system in the form of a time series graph to reflect the change of rainfall data over time, so as to construct a multidimensional information model.

[0027] Furthermore, the water conservancy and flood control monitoring cloud platform also includes a prediction module corresponding to each preset water network point;

[0028] The prediction module is used to predict the river water level at the preset water network point based on the river water level data, river water flow rate data and rainfall data corresponding to the preset water network point.

[0029] Furthermore, the training method of the prediction module corresponding to each preset water network point includes:

[0030] The historical data of river water level data, river water flow velocity data and rainfall data corresponding to the preset water network points are obtained to obtain the original data set; the original data set is divided into a training set and a test set, and the training set is input into the long short-term memory neural network model for training. During the training process, the weights and biases of the neural network are updated through the back propagation algorithm to obtain a trained long short-term memory neural network model.

[0031] Furthermore, the preset water network points are arranged at river turning points, river confluences, reservoir inlets and outlets, and flood-prone areas.

[0032] The beneficial effects of the present invention are as follows:

[0033] In the present invention, not only the water level of the entire water network in the monitoring area is calculated by the water conservancy and flood control monitoring platform to obtain a water network water level map, but also the river water level data, river water flow rate data, rainfall data, early warning signals and video data of each preset water network point uploaded by each monitoring point are obtained through the monitoring device, so as to monitor the water level, water flow rate and rainfall conditions of more important water network points in the monitored area and update the data on the water network water level map, so as to avoid large errors in the measured water network water level, which affects the judgment of important areas such as flood-prone areas. The present invention combines the calculated water network water level map with the highly timely data uploaded by the monitoring device, which not only improves the overall data accuracy of the water network water level map, but also can analyze the overall operation of the water network of the water network water level map through the data uploaded by the monitoring device when performing macro-overall data analysis, and mutually verify the analysis results based on the data uploaded by the monitoring device, thereby increasing the accuracy of the overall data analysis of the water network water level map; the present invention can also timely grasp the water body operation status of each preset water network point, making the present invention more accurate in flood monitoring and flood warning at important preset water network points.

[0034] On the other hand, the present invention proposes a comprehensive analysis system for river water level, water flow rate and rainfall data based on a multidimensional information model. The system integrates data from different sources, including river water level data, river water flow rate data and rainfall data at preset water network points, to construct an information model with multiple dimensions such as space, time and attributes. The model can not only intuitively display the spatial distribution characteristics of river water level and water flow rate, but also reflect the change pattern of rainfall data over time, as well as the interaction between these variables, providing a scientific basis for river management, flood prevention and disaster reduction, and water resources scheduling.

[0035] In the present invention, when the monitoring device does not determine that the data is abnormal, the data is uploaded at a lower first preset frequency, and the video monitoring is not turned on, which ensures the low power consumption capability of the device; and when the data is abnormal, the data is uploaded at a higher second preset frequency, which ensures the real-time data transmission; therefore, the monitoring device in the present invention has both low power consumption and real-time data transmission. In addition, in order to ensure the reliability of water conservancy and flood control monitoring, the present invention collects a variety of data such as water flow rate, rainfall, and water level that are crucial to flood monitoring, and has both comprehensiveness and real-time data, so as to timely grasp the real-time situation of water network floods. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The specific implementation modes of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0037] Figure 1 A schematic diagram showing an overall structure in which an embodiment of the present invention can be applied.

[0038] Figure 2A schematic structural diagram of a monitoring device provided in the first embodiment of the present invention is shown.

[0039] Figure 3 A schematic structural diagram of a monitoring device provided by a second embodiment of the present invention is shown.

[0040] Figure 4 A schematic diagram of the structure of a water conservancy and flood prevention monitoring cloud platform provided by an embodiment of the present invention is shown.

[0041] Figure 5 A schematic diagram showing the structure of a computer system for implementing the apparatus provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0042] In order to explain the present invention more clearly, the present invention is further described below in conjunction with embodiments and drawings. Similar components in the drawings are represented by the same reference numerals. It should be understood by those skilled in the art that the content specifically described below is illustrative rather than restrictive, and the protection scope of the present invention should not be limited thereto.

[0043] In view of this, if Figure 1 As shown, an embodiment of the present invention provides a water conservancy and flood control monitoring system based on a multidimensional information model, including:

[0044] Water conservancy and flood control monitoring cloud platform and multiple monitoring devices;

[0045] Each monitoring device is configured at a preset water network point, and is used to collect river water level data, river water flow rate data and rainfall data at the preset water network point, and obtain and upload the collected data to the water conservancy and flood control monitoring cloud platform at a first preset frequency; and when the river water level data, river water flow rate data or rainfall data is abnormal, collect and store video data of the preset water network point, send an early warning signal to the water conservancy and flood control monitoring cloud platform, and obtain and upload the river water level data, river water flow rate data, rainfall data and video data at the preset point to the water conservancy and flood control monitoring cloud platform at a second preset frequency; the second preset frequency is greater than the first preset frequency; for example, the first preset frequency may be to obtain and send data to the water conservancy and flood control monitoring cloud platform once every 10 minutes; and the second preset frequency may be to obtain and send data to the water conservancy and flood control monitoring cloud platform once every 1 second.

[0046] The water conservancy and flood control monitoring cloud platform is used to calculate the water level of the entire water network in the monitored area to obtain a water network water level map, obtain the river water level data, river water flow rate data, rainfall data, warning signals and video data of the preset water network points uploaded by each monitoring device, and update the water level of each preset water network point in the water network point map based on the acquired data; at the same time, a multidimensional information model is constructed based on the river water level, river water flow rate and rainfall data of each preset water network point; it is also used to predict the river water level of the preset water network point based on the river water level data, river water flow rate data and rainfall data of the corresponding preset water network point. In a specific embodiment, when the monitoring device uploads data at a first preset frequency, the water conservancy and flood control monitoring cloud platform obtains the data uploaded by the corresponding monitoring device at the first preset frequency, and when the warning signal sent by the corresponding monitoring device is received, the data uploaded by the corresponding monitoring device is obtained at a second preset frequency; when there is no abnormality in the data, the data processing volume of the water conservancy and flood control monitoring cloud platform is reduced to reduce its operating load.

[0047] In a specific implementation, when the river water level data is greater than the preset water level threshold, the river water level data is determined to be abnormal. Similarly, when the river water flow rate data is greater than the preset water flow rate threshold, the river water flow rate is determined to be abnormal. When the rainfall data is greater than the preset rainfall threshold, the rainfall data is determined to be abnormal. Among them, the preset water level threshold, the preset water flow rate threshold and the rainfall threshold are obtained based on the historical data of the corresponding data of the preset water network point. On the other hand, it is used to set the preset water level threshold, the preset water flow rate threshold and the rainfall threshold of each monitoring device through the water conservancy and flood control monitoring cloud platform according to the setting needs.

[0048] In a specific implementation, video data users can manually collect and view video data from each monitoring device through the water conservancy and flood control monitoring cloud platform.

[0049] In the present invention, not only the water level of the entire water network in the monitoring area is calculated by the water conservancy and flood control monitoring platform to obtain a water network water level map, but also the river water level data, river water flow rate data, rainfall data, early warning signals and video data of each preset water network point uploaded by each monitoring point are obtained through the monitoring device, so as to monitor the water level, water flow rate and rainfall conditions of more important water network points in the monitored area and update the data on the water network water level map, so as to avoid large errors in the measured water network water level, which affects the judgment of important areas such as flood-prone areas. The present invention combines the calculated water network water level map with the highly timely data uploaded by the monitoring device, which not only improves the overall data accuracy of the water network water level map, but also can analyze the overall operation of the water network of the water network water level map through the data uploaded by the monitoring device when performing macro-overall data analysis, and mutually verify the analysis results based on the data uploaded by the monitoring device, thereby increasing the accuracy of the overall data analysis of the water network water level map; the present invention can also timely grasp the water body operation status of each preset water network point, making the present invention more accurate in flood monitoring and flood warning at important preset water network points.

[0050] On the other hand, the present invention proposes a comprehensive analysis system for river water level, water flow rate and rainfall data based on a multidimensional information model. The system integrates data from different sources, including river water level data, river water flow rate data and rainfall data at preset water network points, to construct an information model with multiple dimensions such as space, time and attributes. The model can not only intuitively display the spatial distribution characteristics of river water level and water flow rate, but also reflect the change pattern of rainfall data over time, as well as the interaction between these variables, providing a scientific basis for river management, flood prevention and disaster reduction, and water resources scheduling.

[0051] In the present invention, when the monitoring device does not determine that the data is abnormal, the data is uploaded at a lower first preset frequency, and the video monitoring is not turned on, which ensures the low power consumption capability of the device; and when the data is abnormal, the data is uploaded at a higher second preset frequency, which ensures the real-time data transmission; therefore, the monitoring device in the present invention has both low power consumption and real-time data transmission. In addition, in order to ensure the reliability of water conservancy and flood control monitoring, the present invention collects a variety of data such as water flow rate, rainfall, and water level that are crucial to flood monitoring, and has both comprehensiveness and real-time data, so as to timely grasp the real-time situation of water network floods.

[0052] In one possible implementation, Figure 2 As shown, the monitoring device also includes a river water level measurement module, a river water flow rate measurement module, a rain gauge, a controller, a video monitoring terminal, a local storage module and a wireless communication terminal;

[0053] The river water level measurement module is used to collect river water level data at the preset water network points;

[0054] The river water flow velocity measurement module is used to collect river water flow velocity data at the preset water network points;

[0055] The rain gauge is used to collect rainfall data at the preset water network points;

[0056] The controller is used to obtain and upload the collected data to the water conservancy and flood control monitoring cloud platform at a first preset frequency; and when the river water level data, river water flow rate data or rainfall data are abnormal, collect the video data of the preset water network point through the video monitoring terminal, store the data collected by the video monitoring terminal through the local storage module, send an early warning signal to the water conservancy and flood control monitoring cloud platform, and obtain and upload the river water level data, river water flow rate data, rainfall data and video data of the preset point to the water conservancy and flood control monitoring cloud platform at a second preset frequency; the second preset frequency is greater than the first preset frequency.

[0057] In a specific implementation manner, the controller is a Siemens SMART series, 1200 series or 1500 series PLC.

[0058] In a specific implementation, the wireless communication terminal may be a 4G wireless communication terminal, a 5G wireless communication terminal, or a GPRS communication terminal.

[0059] In a specific implementation, the device commonly used in the river water level measurement module is a river water level monitoring device or a water level sensor. These devices can convert the water level change of the river into an electrical signal output. Common sensor types include pressure water level sensors, ultrasonic water level sensors, float-type water level sensors, and radar sensors.

[0060] The pressure water level sensor calculates the water level by measuring the pressure exerted by the water on the sensor.

[0061] Ultrasonic digital sensors use the propagation speed and time difference of ultrasonic waves in the air to calculate the water level. They have the characteristics of wide measurement range and high accuracy.

[0062] The float type digital sensor senses the change of water level by the up and down movement of the float and converts it into an electrical signal for output.

[0063] Radar water level sensors measure water levels by emitting radar waves and receiving their reflected signals. Radar waves propagate at a constant speed in the air. When they encounter the water surface, part of the radar waves will be reflected back. After the sensor receives the reflected signal, it calculates the time difference between the transmitted and received signals to obtain the round-trip distance of the radar waves, thereby determining the water level.

[0064] The device usually used in the river water flow velocity measurement module is a flow meter or flow sensor. These devices can measure the speed of water flow in the river. Common types include Doppler flow meters, electromagnetic flow meters, propeller flow meters, etc.

[0065] Doppler current meter: It uses the principle of Doppler effect to measure water flow velocity by emitting and receiving ultrasonic signals. It is suitable for measuring rivers with high sand content.

[0066] Electromagnetic flow meter: Based on Faraday's law of electromagnetic induction, it calculates the water flow velocity by measuring the electromotive force generated by the water flow cutting the magnetic lines of force. It has the advantages of accurate measurement and is not affected by the properties of the fluid.

[0067] Propeller current meter: The water flow velocity is calculated by the rotation speed of the propeller in the water flow, and is suitable for measuring cleaner rivers.

[0068] A rain gauge is a device specifically used to measure rainfall. Common types include tipping bucket rain gauges, radar precipitation monitors, ultrasonic rain gauges, and digital rain gauges.

[0069] Tipping bucket rain gauge: records rainfall through a fixed tipping bucket. When the water level in the container reaches a predetermined value, the container will tip over and record the rainfall data.

[0070] Radar precipitation monitor: uses radar technology to monitor rainfall conditions over a wide area, capable of real-time and accurate monitoring of rainfall amount and intensity.

[0071] Ultrasonic rain gauge: uses sound wave technology to monitor rainfall. When raindrops fall, sound wave signals are generated. The sensor receives the signals and processes the data.

[0072] Digital rain gauges: monitor the intensity and amount of rainfall through precise electronic measurements, using sensors that can accurately measure the size and intensity of each rainfall.

[0073] In one possible implementation, Figure 3 As shown, the monitoring device also includes a power supply battery, a solar panel and a charge controller;

[0074] The solar panel is used to charge the power supply battery through the charge controller; the power supply battery is used to power the controller, the video monitoring terminal and the wireless communication terminal through the charge controller.

[0075] The present invention improves the endurance of the monitoring device by controlling the power supply and charging process of the storage battery through a charge controller.

[0076] In one possible implementation, the water conservancy and flood control monitoring cloud platform also includes a water network water level calculation module, which is used to obtain digital elevation models and actual river source data; in response to user setting operations, multiple catchment area thresholds are obtained from a preset catchment area threshold range; the following calculations are performed based on each catchment area threshold: according to the digital elevation model, the actual river source data and the set catchment area threshold, the corresponding river channel and watershed data are calculated based on the SWAT model to obtain the river channel surface vector; lake and reservoir vectors are obtained and extracted based on synthetic aperture radar image data: the obtained river channel surface vector is merged with the obtained lake and reservoir vector to obtain the water channel surface vector; network vector; for each set catchment area threshold, calculate the distance error between the extracted water network vector and the actual river source; obtain the closest point to the actual river source, and calculate the distance between the two points to obtain the distance error; and use the catchment area threshold corresponding to the minimum distance error as the optimal catchment area threshold; use the water network vector corresponding to the optimal catchment area threshold as the optimal water network vector; obtain the optical remote sensing image and crop it according to the optimal water network vector to obtain the optical remote sensing image of the corresponding water network, establish a multi-band combination model based on the optical remote sensing image to calculate the water depth of the water network, calculate the water level of the water network according to the water depth of the water network at the corresponding position and the elevation of the bottom of the water network, and generate a water level map of the water network.

[0077] In a specific embodiment, Figure 4 As shown in the figure, the water network water level calculation module is an important part of the water conservancy flood control monitoring cloud platform. It uses advanced mathematical models and remote sensing technology to achieve high-precision water level calculation of water network elements such as rivers, lakes, and reservoirs. This module integrates multiple data sources such as digital elevation model (DEM), actual river source data, synthetic aperture radar (SAR) image data, and optical remote sensing images to achieve comprehensive and real-time monitoring of water network water levels. The specific process is as follows:

[0078] Data preparation:

[0079] Digital Elevation Model (DEM): GIS data used to describe the spatial distribution of regional landforms and is the basis for elevation information of water network elements such as rivers, lakes, and reservoirs.

[0080] Actual river source data: including the actual direction of the river, the location and shape of lakes and reservoirs, etc., is an important reference for calculating the water level of the water network.

[0081] Synthetic Aperture Radar (SAR) image data: used to extract vector information of lakes and reservoirs and provide high-resolution surface information.

[0082] Optical remote sensing images: used to establish multi-band combination models and calculate water network depth.

[0083] Catchment area threshold setting:

[0084] In response to the user's setting operation, multiple catchment area thresholds are obtained from the preset catchment area threshold range. These thresholds are used for subsequent water network extraction and calculation.

[0085] Water network extraction based on SWAT model:

[0086] For each set catchment area threshold, the corresponding river channel and watershed data are calculated based on the SWAT model according to the digital elevation model, actual river source data and the set catchment area threshold.

[0087] The SWAT model is a basin-scale hydrological model that can simulate the water quality and quantity of surface water and groundwater and is suitable for hydrological simulation in complex basins.

[0088] The river channel and basin data calculated by the SWAT model can be further used to obtain the river channel surface vector.

[0089] Lake and Reservoir Vector Extraction:

[0090] Vector information of lakes and reservoirs is extracted using synthetic aperture radar (SAR) image data.

[0091] This vector information includes key features such as the boundaries and shapes of lakes and reservoirs.

[0092] Water mesh vector merge:

[0093] The obtained river surface vector is merged with the lake and reservoir vector to obtain a complete water network vector.

[0094] This step achieves a comprehensive representation of water network elements such as rivers, lakes, and reservoirs.

[0095] Distance error calculation and optimal water collection area threshold determination:

[0096] For each set catchment area threshold, the distance error between the extracted water network vector and the actual river source is calculated.

[0097] Get the point closest to the actual river source and calculate the distance between the two points to get the distance error. Take the catchment area threshold corresponding to the minimum distance error as the optimal catchment area threshold. Select the water network vector corresponding to the optimal catchment area threshold as the optimal water network vector.

[0098] Water network water level calculation and water level map generation:

[0099] According to the optimal water network vector, the optical remote sensing image of the corresponding water network is obtained by clipping. The multi-band combination model is established using the optical remote sensing image to calculate the water depth of the water network. The water level of the water network is calculated according to the water depth of the water network at the corresponding position and the elevation of the bottom of the water network. The water level map of the water network is generated to provide intuitive and accurate water level information for water conservancy and flood control monitoring.

[0100] The present invention establishes the relationship between the distance error between the actual river source and the extracted water system river source and the size of the grid number through the implementation of the water network water level calculation module. Based on the principle of minimizing the error between the two points, a method for solving the uniqueness problem of watershed water system extraction is used to obtain the optimal water collection surface threshold, so as to avoid the water collection surface threshold being too large during the selection process, resulting in only large-scale rivers and basins being extracted, while some small-scale tributaries and subtle water system features may be ignored. The extracted river channel deviates from the actual situation, and the water collection surface threshold is too small, resulting in some pseudo-rivers in the system that may not actually exist, which increases the difficulty of subsequent data processing or calculation. In addition, the water conservancy and flood control monitoring cloud platform can realize high-precision water level calculation of water network elements such as rivers, lakes, and reservoirs. This can not only improve the accuracy and timeliness of water conservancy and flood control monitoring, but also provide a scientific basis for the planning, design and management of water conservancy projects. At the same time, the implementation of this module has also promoted the process of digitalization and intelligent transformation of the water conservancy industry.

[0101] In a possible implementation, the acquisition module is used to acquire the river water level data, river water flow rate data and rainfall data of the preset water network point uploaded by each monitoring device;

[0102] The updating module is used to update the water level of each preset water network point in the preset water network point map based on the acquired data.

[0103] In one possible implementation, the water conservancy and flood control monitoring cloud platform includes a multi-dimensional information model building module;

[0104] The multidimensional information model building module is used to build a multidimensional information model based on the river water level data, river water flow velocity data and rainfall data of each preset water network point.

[0105] In a possible implementation, constructing a multidimensional information model based on the river water level data, river water flow velocity data and rainfall data of each preset water network point includes:

[0106] The preset water network points are numbered; a three-dimensional coordinate system is constructed with the preset water network point number as the first coordinate axis, the river water level as the second coordinate axis, and the river water flow rate as the third coordinate axis; surface maps or contour maps of water level and water flow rate at different time points are drawn in the three-dimensional coordinate system to respectively show the spatial distribution of water level and water flow rate; rainfall data, as a variable in the time dimension, is displayed in the three-dimensional coordinate system in the form of a time series graph to reflect the change of rainfall data over time. For sparse data points, data interpolation methods (such as linear interpolation, Kriging interpolation, etc.) can be used to estimate the water level, water flow rate and rainfall of unknown points. The interpolated data is gridded so that continuous surface maps or contour maps can be drawn in three-dimensional space to build a multidimensional information model.

[0107] In this embodiment, by constructing a multidimensional information model, the present invention can simultaneously consider multiple key variables such as river water level, water flow rate, and rainfall, and realize comprehensive monitoring and analysis of the state of the river system. This comprehensive analysis method is more accurate than single-dimensional data analysis and can more truly reflect the dynamic characteristics and spatial distribution laws of the river system. Using a three-dimensional coordinate system and visualization technology, the present invention converts complex data information into intuitive graphical representations, such as surface maps, contour maps, and time series maps. These graphics are not only easy to understand, but also help users quickly identify key information and trends in the data, thereby improving decision-making efficiency and accuracy.

[0108] The multidimensional information model of the present invention has good scalability and flexibility, and can easily cope with new data types and analysis requirements that may be added in the future. By adding new dimensions or adjusting the parameter settings of existing dimensions, the system can continuously adapt to new challenges and new requirements in the field of river management.

[0109] In one possible implementation, the water conservancy and flood control monitoring cloud platform also includes a prediction module corresponding to each preset water network point;

[0110] The prediction module is used to predict the river water level at the preset water network point based on the river water level data, river water flow rate data and rainfall data corresponding to the preset water network point.

[0111] In a possible implementation, the training method of the prediction module corresponding to each preset water network point includes:

[0112] The historical data of river water level data, river flow velocity data and rainfall data corresponding to the preset water network points are obtained to obtain the original data set; the original data set is divided into a training set and a test set, and the training set is input into the long short-term memory neural network model for training. During the training process, the weights and biases of the neural network are updated through the back propagation algorithm to obtain the trained long short-term memory neural network model.

[0113] In one possible implementation, preset water network points are configured at river turning points, river confluences, reservoir entrances and exits, and flood-prone areas.

[0114] In the water network for flood control monitoring, the location of the preset water network points is crucial. They should be able to fully and accurately reflect the water level, water flow rate and rainfall in the water area, so as to timely warn and respond to possible flood disasters. It includes the key locations of the river, specifically the river turning point: the water flow direction changes at the turning point of the river, which may produce vortices and backflows, and is sensitive to water level changes. It is an ideal location for setting monitoring points. River confluence: The water flow at the confluence of multiple rivers is complex and the water level changes rapidly. Monitoring points should be set up to monitor changes in water level and flow rate. Reservoir inlet and outlet: The water flow at the inlet and outlet of the reservoir is greatly affected by human regulation, which is a key location for monitoring water level and water flow changes. It also includes flood-prone areas: specifically low-lying areas, which are prone to water accumulation and are high-risk areas for flood disasters. Monitoring points should be set up to provide early warnings; along the river: along the river, especially where there are dense populations, important industrial and mining enterprises and infrastructure, monitoring points should be set up to monitor water level changes and ensure safety.

[0115] like Figure 5 As shown, a computer system suitable for implementing the water conservancy and flood control monitoring cloud platform provided in the above embodiment includes a central processing module (CPU), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) or a program loaded from a storage part into a random access memory (RAM). In the RAM, various programs and data required for the operation of the computer system are also stored. The CPU, ROM, and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0116] The following components are connected to the I / O interface: an input part including a keyboard, a mouse, etc.; an output part including a liquid crystal display (LCD), etc. and a speaker, etc.; a storage part including a hard disk, etc.; and a communication part including a network interface card such as a LAN card, a modem, etc. The communication part performs communication processing via a network such as the Internet. A drive is also connected to the I / O interface as needed. Removable media, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., are installed on the drive as needed so that the computer program read therefrom is installed into the storage part as needed.

[0117] In particular, according to this embodiment, the process described in the flowchart above can be implemented as a computer software program. For example, this embodiment includes a computer program product, which includes a computer program tangibly contained on a computer-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part, and / or installed from a removable medium.

[0118] The flow chart and schematic diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product of the present embodiment. In this regard, each square box in the flow chart or schematic diagram can represent a part of a module, program segment or code, and a part of the above-mentioned module, program segment or code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the schematic diagram and / or flow chart, and the combination of the square boxes in the schematic diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0119] As another aspect, the present embodiment further provides a non-volatile computer storage medium, which may be a non-volatile computer storage medium included in the above-mentioned device in the above-mentioned embodiment, or a non-volatile computer storage medium that exists independently and is not installed in a terminal. The above-mentioned non-volatile computer storage medium stores one or more programs, and when the above-mentioned one or more programs are executed by a device, the above-mentioned device: calculates the water level of the water network of the entire monitored area to obtain a water network water level map, obtains the river water level data, river water flow rate data, rainfall data, warning signals and video data of the preset water network points uploaded by each monitoring device, and updates the water level of each preset water network point in the water network point map based on the acquired data; at the same time, a multidimensional information model is constructed based on the river water level, river water flow rate and rainfall data of each preset water network point; and is also used to predict the river water level of the preset water network point based on the river water level data, river water flow rate data and rainfall data of the corresponding preset water network point. In a specific embodiment, when the monitoring device uploads data at a first preset frequency, the water conservancy and flood control monitoring cloud platform obtains the data uploaded by the corresponding monitoring device at the first preset frequency. When a warning signal sent by the corresponding monitoring device is received, the data uploaded by the corresponding monitoring device is obtained at a second preset frequency.

[0120] In the description of the present invention, it should be noted that the terms "upper", "lower", etc. indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific position, be constructed and operated in a specific position, and therefore cannot be understood as a limitation on the present invention. Unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.

[0121] It should also be noted that, in the description of the present invention, relational terms such as first and second, etc., are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0122] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the embodiments here. All obvious changes or modifications derived from the technical solution of the present invention are still within the protection scope of the present invention.

Claims

1. A water conservancy and flood control monitoring system based on a multidimensional information model, characterized in that: include: Water conservancy and flood control monitoring cloud platform and multiple monitoring devices; Each of the monitoring devices is configured at a preset water network point, and is used to collect river water level data, river water flow rate data, and rainfall data at the preset water network point, and obtain and upload the collected data to the water conservancy and flood control monitoring cloud platform at a first preset frequency; and when the river water level data, river water flow rate data, or rainfall data is abnormal, collect and store video data at the preset water network point, send an early warning signal to the water conservancy and flood control monitoring cloud platform, and obtain and upload the river water level data, river water flow rate data, rainfall data, and video data at the preset point to the water conservancy and flood control monitoring cloud platform at a second preset frequency; the second preset frequency is greater than the first preset frequency; The water conservancy and flood control monitoring cloud platform is used to calculate the water level of the entire water network in the monitored area to obtain a water network water level map, obtain the river water level data, river water flow rate data, rainfall data, warning signals and video data of the preset water network points uploaded by each monitoring device, and update the water level of each preset water network point in the water network point map based on the acquired data; at the same time, a multidimensional information model is constructed based on the river water level, river water flow rate and rainfall data of each preset water network point; and it is also used to predict the river water level of the preset water network point based on the river water level data, river water flow rate data and rainfall data of the corresponding preset water network point.

2. The water conservancy and flood control monitoring system based on multidimensional information model according to claim 1 is characterized in that: The monitoring device also includes a river water level measurement module, a river water flow rate measurement module, a rain gauge, a controller, a video monitoring terminal, a local storage module and a wireless communication terminal; The river water level measurement module is used to collect river water level data at a preset water network point; The river water flow rate measurement module is used to collect river water flow rate data at a preset water network point; The rain gauge is used to collect rainfall data at the preset water network point; The controller is used to obtain and upload the collected data to the water conservancy and flood control monitoring cloud platform at a first preset frequency; and when the river water level data, river water flow rate data or rainfall data are abnormal, the video data of the preset water network point is collected through the video monitoring terminal, the data collected by the video monitoring terminal is stored through the local storage module, an early warning signal is sent to the water conservancy and flood control monitoring cloud platform, and the river water level data, river water flow rate data, rainfall data and video data of the preset point are obtained and uploaded to the water conservancy and flood control monitoring cloud platform at a second preset frequency; the second preset frequency is greater than the first preset frequency.

3. The water conservancy and flood control monitoring system based on multidimensional information model according to claim 2 is characterized in that: The monitoring device also includes a power supply battery, a solar panel and a charge controller; The solar panel is used to charge the power supply battery through a charge controller; the power supply battery is used to supply power to the controller, the video monitoring terminal and the wireless communication terminal through the charge controller.

4. The water conservancy and flood control monitoring system based on multidimensional information model according to claim 1 is characterized in that: The water conservancy and flood control monitoring cloud platform also includes a water network water level calculation module, which is used to obtain digital elevation models and actual river source data; in response to user setting operations, multiple catchment area thresholds are obtained from the preset catchment area threshold range; the following calculations are performed based on each catchment area threshold: according to the digital elevation model, the actual river source data and the set catchment area threshold, the corresponding river channel and basin data are calculated based on the SWAT model to obtain the river channel surface vector; lake and reservoir vectors are obtained and extracted based on synthetic aperture radar image data: the obtained river channel surface vector is merged with the obtained lake and reservoir vector to obtain a water network vector; for each set catchment area threshold, the distance error between the extracted water network vector and the actual river source is calculated; The closest point to the actual river source is obtained, and the distance between the two points is calculated to obtain the distance error; the catchment area threshold corresponding to the minimum distance error is used as the optimal catchment area threshold; the water network vector corresponding to the optimal catchment area threshold is used as the optimal water network vector; the optical remote sensing image is obtained and cropped according to the optimal water network vector to obtain the optical remote sensing image of the corresponding water network, a multi-band combination model is established based on the optical remote sensing image to calculate the water depth of the water network, the water level of the water network is calculated according to the water depth of the water network at the corresponding position and the elevation of the bottom of the water network, and a water level map of the water network is generated.

5. The water conservancy and flood control monitoring system based on multidimensional information model according to claim 4 is characterized in that: An acquisition module is used to acquire the river water level data, river water flow rate data and rainfall data of the preset water network points uploaded by each monitoring device; The updating module is used to update the water level of each preset water network point in the preset water network point map based on the acquired data.

6. The water conservancy and flood control monitoring system based on multidimensional information model according to claim 5 is characterized in that: The water conservancy and flood control monitoring cloud platform includes a multi-dimensional information model building module; The multidimensional information model building module is used to build a multidimensional information model based on the river water level data, river water flow rate data and rainfall data of each preset water network point.

7. The water conservancy and flood control monitoring system based on multidimensional information model according to claim 6 is characterized in that: The multidimensional information model is constructed based on the river water level data, river water flow velocity data and rainfall data of each preset water network point, including The preset water network points are numbered; a three-dimensional coordinate system is constructed with the preset water network point number as the first coordinate axis, the river water level as the second coordinate axis, and the river water flow rate as the third coordinate axis; a surface map or contour map of the water level and water flow rate at different time points is drawn in the three-dimensional coordinate system to respectively display the spatial distribution of the water level and the water flow rate; the rainfall data, as a variable in the time dimension, is displayed in the three-dimensional coordinate system in the form of a time series graph to reflect the change of rainfall data over time, so as to construct a multidimensional information model.

8. The water conservancy and flood control monitoring system based on multidimensional information model according to claim 5 is characterized in that: The water conservancy and flood control monitoring cloud platform also includes a prediction module corresponding to each preset water network point; The prediction module is used to predict the river water level at the preset water network point based on the river water level data, river water flow rate data and rainfall data corresponding to the preset water network point.

9. The water conservancy and flood control monitoring system based on multidimensional information model according to claim 8 is characterized in that: The training method of the prediction module corresponding to each preset water network point includes The historical data of river water level data, river water flow velocity data and rainfall data corresponding to the preset water network points are obtained to obtain the original data set; the original data set is divided into a training set and a test set, and the training set is input into the long short-term memory neural network model for training. During the training process, the weights and biases of the neural network are updated through the back propagation algorithm to obtain a trained long short-term memory neural network model.

10. The water conservancy and flood control monitoring system based on multidimensional information model according to claim 5, characterized in that: The preset water network points are arranged at river turning points, river confluences, reservoir inlets and outlets, and flood-prone areas.

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