A flow real-time monitoring system for river ecological restoration

Abstract

The application discloses a kind of flow real-time monitoring system for river ecological restoration, it is related to flow monitoring technical field, including: data acquisition calculation module is used to gather and process river section water level and flow rate data, and carry out local anomaly detection;Communication transmission module is used to transmit the data after processing to remote monitoring center;Flow analysis and evaluation module is used to calculate ecological flow index according to the received data, and assess whether current flow meets preset ecological flow threshold;Early warning alarm module is used to generate hierarchical early warning information according to the evaluation result and push to relevant personnel;Visual display module is used to show real-time monitoring state, ecological flow compliance condition, and provide dispatching scheme comparison function.The application is based on multi-source data fusion as data, real-time analysis river flow, solve the technical problems of single data source and low measurement accuracy in the prior art of ecological flow measurement.

Description

Technical Field

[0001] This application relates to the field of flow monitoring technology, and in particular to a real-time flow monitoring system for river ecological restoration. Background Technology

[0002] River ecological flow is a fundamental hydrological condition for maintaining the health of river ecosystems, ensuring the integrity of aquatic habitats, and facilitating the normal operation of ecological processes. With the advancement of river ecological restoration efforts, higher demands are placed on the accurate monitoring and scientific assessment of ecological flow. Existing flow monitoring systems typically consist of water level / flow sensors, data acquisition terminals, communication modules, and host computer software, enabling real-time acquisition, transmission, and display of flow data, and providing alarms for exceeding preset thresholds. In ecological flow assessment, widely used methods include the Tennant method, the 7Q10 method, and the minimum monthly average flow method. These methods are based on long-term hydrological statistics and determine ecological flow thresholds through empirical percentage or frequency analysis. For example, the Tennant method uses a percentage of the multi-year average flow as a recommended ecological flow value, while the 7Q10 method uses the 7-day average flow during the driest period (once in ten years) as a low flow indicator. These methods are simple to calculate and have low data requirements, and have been applied in the planning stage and initial management.

[0003] However, the data sources relied upon for calculating ecological flow thresholds in existing plans are relatively singular. Traditional methods only use historical flow sequences and do not integrate multi-source information such as real-time water quality parameters, weather forecasts, river topography, and biological habitats. This results in thresholds that cannot reflect the dynamic changes in environmental stress and ecological needs. At the same time, ecological flow thresholds are mostly static or only roughly segmented by season, making it difficult to adapt to the actual needs of river ecosystems to dynamically fluctuate with species life history stages, water temperature changes, and meteorological conditions. This can easily lead to inaccurate ecological water demand assessments or frequent false alarms, reducing management efficiency. In addition, existing monitoring systems generally lack the ability to convert flow data into ecologically meaningful indicators. Simply comparing measured flow with statistical thresholds cannot directly reflect changes in the area of ​​usable habitat for target species, making it difficult to scientifically determine whether the flow truly meets ecological restoration goals. Moreover, in situations of communication interruption or harsh environments, field monitoring equipment can usually only store data and cannot perform local ecological flow assessments, resulting in insufficient real-time and reliable early warnings and affecting the timeliness of ecological dispatch responses.

[0004] Therefore, there is an urgent need for a real-time flow monitoring system that can integrate multi-source data and dynamically calculate ecological flow thresholds to overcome the above-mentioned shortcomings and meet the actual needs of river ecological restoration for accurate monitoring and scientific decision-making. Summary of the Invention

[0005] This invention provides a real-time flow monitoring system for river ecological restoration. By using multi-source data fusion as the data foundation, it analyzes river flow in real time, solving the technical problems of single data source and low measurement accuracy in existing ecological flow measurement technologies.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: This invention provides a real-time flow monitoring system for river ecological restoration, comprising: The data acquisition and computing module is used to collect and process water level and flow velocity data of river cross sections, and to perform local anomaly detection. The communication transmission module is used to transmit the processed data to the remote monitoring center; The traffic analysis and evaluation module is used to calculate ecological traffic indicators based on the received data and evaluate whether the current traffic meets the preset ecological traffic threshold. The early warning and alarm module is used to generate tiered early warning information based on the assessment results and push it to relevant personnel; The visualization module is used to display real-time monitoring status and ecological flow compliance, and provides a function to compare scheduling schemes.

[0007] The beneficial effects of the technical solution provided by this invention include at least the following: This invention constructs a dynamic ecological flow threshold calculation unit that integrates multi-source data, incorporating real-time hydrological data, water quality data, meteorological forecast data, and river geography and biological habitat data into a unified analysis framework. This breaks through the limitations of traditional methods that rely solely on historical flow sequences, enabling the ecological flow threshold to be dynamically adjusted in response to changes in environmental stress and ecological needs. By converting flow data into the weighted available habitat area of ​​the target species, a quantitative relationship between flow and habitat suitability is directly established. This elevates ecological flow assessment from a simple comparison of flow values ​​to a scientific judgment based on ecological response, more accurately reflecting the actual effect of river ecological restoration.

[0008] This invention employs a multi-objective optimization solution aimed at maximizing ecological benefits and minimizing water supply losses. Under the constraints of ensuring river flow prevention and flood control safety, it automatically obtains a compromise threshold that balances ecological protection and water supply demand, providing a quantifiable decision-making basis for ecological scheduling and improving the scientific nature and operability of water resource management.

[0009] This invention integrates edge computing units and local anomaly detection functions into the data acquisition and computing module, enabling it to independently complete ecological flow threshold judgment and early warning recording even under extreme conditions such as communication interruption. It automatically retransmits data after communication is restored. Furthermore, through the dynamic threshold mechanism and three-level hierarchical early warning system of the early warning and alarm module, it effectively reduces false alarms and missed alarms caused by fixed thresholds, improving the targeting of early warnings and the efficiency of management response. Moreover, through automatic report generation and scheduling scheme comparison functions, it reduces the data analysis difficulty for management personnel and improves the efficiency of daily supervision and consultation decision-making. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a framework diagram of a real-time flow monitoring system for river ecological restoration provided in an embodiment of the present invention. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0013] Example A real-time flow monitoring system for river ecological restoration.

[0014] Please refer to Figure 1 This is a framework diagram of a real-time flow monitoring system for river ecological restoration provided in an embodiment of the present invention.

[0015] I. Data Acquisition and Calculation Module The data acquisition and computing module includes a traffic acquisition unit, an image capture unit, an image recognition unit, and an ecological acquisition unit.

[0016] The flow acquisition unit employs a combination of a radar flow meter and a pressure level gauge. The radar flow meter is installed above the river channel, measuring the surface velocity of the water by emitting radar waves; the pressure level gauge is installed at a fixed location on the riverbed or bank, measuring water pressure and converting it into water level. The data collected by both are processed by the processor built into the data acquisition and calculation module, combined with the cross-sectional relationship of the river channel, to calculate the cross-sectional flow rate.

[0017] For example, for a regular rectangular cross-section, the flow rate Q = v × A (where v is the average flow velocity measured by radar after correction by the cross-sectional average velocity coefficient, and A is the flow area calculated based on the water level and cross-sectional shape). Radar flow meters and pressure level gauges serve as backups for each other: when the radar flow meter experiences abnormal flow velocity data due to wind, waves, or floating debris, the system can estimate the flow rate solely based on the water level data and historical water level-flow relationship (such as the Manning formula or calibration curve); conversely, the same applies.

[0018] The image capture unit uses a fixed camera aimed at the water gauge or river surface. The camera captures images of the water gauge at regular intervals or triggered automatically. The image recognition unit uses image recognition algorithms to read the water gauge scale. Specifically, template matching or edge detection methods can be used to extract the position of the boundary line between the water gauge and the water surface, thereby obtaining the water level value. This water level value serves as third-party verification data, in addition to radar flow meters and pressure level gauges, to determine whether other water level sensors have drifted or malfunctioned. When two of the three water level data sources are consistent while the third deviates by more than a preset threshold (e.g., ±2 cm), the system automatically marks the source of deviation as suspicious and prompts for maintenance.

[0019] The ecological data acquisition unit includes a water temperature sensor, a dissolved oxygen sensor, a turbidity sensor, a pH sensor, and a conductivity sensor. Each sensor is connected to the data acquisition and computing module via RS485 or an analog interface. These sensors can be integrated into a single multi-parameter water quality probe, installed at an appropriate depth below the river surface. The data acquisition frequency can be set to once every 15 minutes and supports remote configuration.

[0020] The local anomaly detection function runs in the processor of the data acquisition and computing module. It performs a reasonableness assessment on the collected water level, flow velocity, and ecological parameters. The specific anomaly detection rules include: Mutation detection: Calculate the change between two consecutive data collections. If the change exceeds the preset physical limits (e.g., water level changes by more than 0.5m in 10 minutes, or flow velocity changes by more than 1 m / s in 10 minutes), it is marked as suspicious. Continuous Invariance Detection: If the same parameter is collected for 6 consecutive times and the values ​​are exactly the same (the difference is less than the sensor resolution), it is determined that the sensor is stuck or there is a communication failure. Anomaly detection of water level-flow correlation: Based on the water level-flow relationship curve established by historical data, when the deviation between the measured flow rate corresponding to the measured water level and the measured flow rate exceeds a certain proportion (such as 50%), it is judged as an anomaly.

[0021] It should be noted that data marked as suspicious is prioritized for storage in the local cache and carries an anomaly indicator. Both normal and suspicious data are uploaded via the communication transmission module; if communication is interrupted, the data is stored locally and retransmitted once communication is restored.

[0022] II. Communication Transmission Module The communication transmission module uses 4G Cat.1 communication as the main channel. 4G Cat.1 modules are deployed at field monitoring sites to send data to the remote monitoring center server through the operator network. For areas with no public network signal or weak signal, such as tributaries and canyons, LoRa gateways are configured.

[0023] It should be noted that the LoRa gateway is deployed at sites with 4G signal. Multiple sensor nodes in areas without signal can wirelessly aggregate data to the LoRa gateway, which then uploads the data via 4G. Both the LoRa node and the gateway are designed for low power consumption, and the communication distance can reach several kilometers.

[0024] The communication transmission module also integrates a Beidou short message communication module as an emergency backup channel. When 4G communication is interrupted (such as by base station failure or signal interruption caused by extreme weather) and continues for more than a preset time (such as 5 minutes), the system automatically switches to Beidou short message mode.

[0025] It should be noted that the BeiDou short message service has limited bandwidth, therefore only critical information is sent, including the station number, current water level, current flow rate, outage status indicator, and a brief alarm code. The transmission frequency can be set to once every 30 minutes until 4G communication is restored. Once 4G is restored, the system automatically switches back to the main channel and retransmits all data cached during the interruption to the center in chronological order, achieving resume transmission. Simultaneously, critical data (such as real-time data triggering alarms) has the highest priority in the transmission queue and is uploaded first.

[0026] III. Traffic Analysis and Evaluation Module The traffic analysis and assessment module is deployed on the server of the remote monitoring center. It includes a data access unit, an ecological simulation unit, an environmental stress correction unit, and a target optimization unit, and is used to realize the dynamic ecological traffic threshold calculation of multi-source data fusion.

[0027] The data access unit receives real-time hydrological data (flow rate, water level, flow velocity), water quality data (water temperature, dissolved oxygen, turbidity, pH, conductivity) and meteorological forecast data (rainfall and temperature for the next 24-72 hours) and river geography and habitat data from the communication transmission module. The river geography and habitat data includes river cross-section topographic survey data, riverbed sediment distribution maps, and ecological habit information of target species (such as suitable flow velocity range, water depth range, and sediment preferences). This data is entered during system construction or updated periodically.

[0028] The ecological simulation unit is used to convert flow data into weighted usable area (WUA) for the target species. Its core is the use of three suitability functions: flow velocity suitability function, water depth suitability function, and substrate suitability function. The flow velocity suitability function represents the relationship between the suitability of a target species to a water flow velocity and the change in flow velocity value. Taking an adult native fish as an example, its flow velocity suitability function can be defined as a piecewise linear function: when the flow velocity is less than 0.1 m / s, the suitability index is 0.2; when the flow velocity is between 0.1 and 0.2 m / s, the suitability index increases linearly from 0.2 to 0.8; when the flow velocity is between 0.2 and 0.6 m / s, the suitability index is 1.0; when the flow velocity is between 0.6 and 1.0 m / s, the suitability index decreases linearly from 1.0 to 0.4; and when the flow velocity is greater than 1.0 m / s, the suitability index is 0.

[0029] The water depth suitability function represents the relationship between the suitability of a target species to water depth and the water depth value. Taking this fish as an example: when the water depth is less than 0.15m, the suitability index is 0.1; when the water depth is 0.15-0.3m, the index increases linearly from 0.1 to 0.8; when the water depth is 0.3-1.2m, the index is 1.0; when the water depth is 1.2-2.0m, the index decreases linearly from 1.0 to 0.3; and when the water depth is greater than 2.0m, the index is 0.1.

[0030] The substrate suitability function represents the suitability of a target species for different riverbed substrate types, and is presented in the form of a discrete mapping table. For example, the suitability index for silt substrate is 0.1, for sand substrate is 0.6, for gravel substrate is 1.0, for pebble substrate is 0.8, and for rock substrate is 0.2.

[0031] The hydraulic parameters of a river cross section include cross-sectional shape, riverbed roughness, and sediment distribution. The cross-sectional shape is obtained through measured cross-sectional topographic data, the riverbed roughness is determined based on the sediment type and empirical values ​​(e.g., Manning roughness n=0.03 for gravel riverbeds), and the sediment distribution is obtained through underwater photography or manual sampling.

[0032] In the offline phase, the ecological simulation unit utilizes the aforementioned suitability functions and cross-sectional hydraulic parameters, employing a one-dimensional hydrodynamic model (such as HEC-RAS) or simplified hydraulic calculation methods to simulate the water depth and velocity distribution of each transverse sub-unit of the cross-section under different flow levels (e.g., from 0.1 m³ / s to flood control flow, with a step size of 0.1 m³ / s). For each sub-unit, the velocity suitability index, water depth suitability index, and substrate suitability index are calculated separately, and the comprehensive suitability index CSI = SI_v × SI_d × SI_s is obtained using the product method. Multiplying the CSI by the transverse width of the sub-unit and the length of the representative river segment (which can be normalized to 1 m) yields the usable habitat area contribution of that sub-unit. Summing all sub-units gives the WUA at that flow level. This calculation is performed sequentially for all flow levels, generating a "flow-WUA" relationship table. Different suitability functions are defined according to the season and fish life history stages (e.g., spawning period, juvenile stage, adult stage), and multiple sets of relationship tables are pre-generated.

[0033] It should be noted that during real-time calculation, the ecological simulation unit automatically selects the corresponding relationship table based on the current date and the preset species life history stage, and quickly obtains the weighted available habitat area (WUA) corresponding to the current flow by looking up the table or linear interpolation based on the real-time flow value.

[0034] The environmental stress correction unit dynamically corrects the water temperature and dissolved oxygen (WUA) output by the ecological simulation unit based on real-time water temperature and dissolved oxygen data. The specific correction method is as follows: Water temperature stress coefficient: When the water temperature is within the suitable range for the target species (e.g., 15–25℃), the stress coefficient K_T = 1.0; for every 1℃ the water temperature exceeds the upper limit of the suitable range, K_T decreases by 0.1; when the water temperature is below the lower limit of the suitable range, it decreases according to a similar rule. The lower limit of K_T is 0.2.

[0035] Dissolved oxygen stress coefficient: When the dissolved oxygen concentration is greater than 5 mg / L, K_DO=1.0; when the dissolved oxygen is between 3 and 5 mg / L, K_DO increases linearly from 0.6 to 1.0; when the dissolved oxygen is less than 3 mg / L, K_DO=0.2.

[0036] It should be noted that the revised weighted available habitat area is WUA'=WUA×K_T×K_DO.

[0037] The environmental stress correction unit also adjusts the ecological flow threshold based on short-term weather forecasts. For example, if a significant rainfall (e.g., exceeding 20 mm) is forecast for the next 24 hours, and upstream water inflow is expected to increase, the ecological flow threshold for the current period can be appropriately reduced by 5% to 10% to avoid triggering unnecessary warnings due to impending short-term natural water replenishment.

[0038] The objective optimization unit aims to maximize ecological benefits and minimize water supply losses. Under the constraints of the lower limit of flow interruption prevention and the upper limit of flood control safety, a multi-objective optimization algorithm is used to solve for the optimal ecological flow threshold.

[0039] The ecological benefit objective function can be defined as: maximizing the weighted sum of the modified weighted available habitat area (WUA') and the water quality compliance rate. The water supply loss objective function can be defined as: minimizing the deviation between the actual discharge flow and the agricultural / domestic water demand flow. Constraints include: the flow rate is not less than the lower limit of river channel interruption (e.g., 0.1 m³ / s) and not greater than the flood control safety flow (e.g., a certain proportion of the design flood flow).

[0040] The objective optimization unit employs either the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm or the NSGA-II algorithm, running daily or weekly. The algorithm outputs a set of Pareto optimal solutions, each representing an ecological flow threshold scheme corresponding to different combinations of ecological benefits and water supply losses. The system automatically selects a compromise solution as the ecological flow threshold for the current time period based on preset management preferences (ecological priority or water supply priority). For example, in ecological priority mode, the solution with the highest ecological benefit is selected; in water supply priority mode, the solution with the lowest water supply loss is selected; and in equilibrium mode, the solution closest to the ideal point is selected.

[0041] The final determined ecological flow threshold is output to the early warning and alarm module for comparison with the real-time measured flow.

[0042] IV. Early Warning and Alarm Module The early warning and alarm module employs a dynamic threshold mechanism. The system presets different ecological flow threshold levels based on the season and the fish's life cycle stage. For example, during the fish spawning season (April-June), the ecological flow threshold is set to a higher value, such as 30% of the multi-year average flow; during the non-spawning season, it is set to 20% of the multi-year average flow. The system automatically switches the threshold according to the current date, without requiring manual intervention.

[0043] The early warning and alarm module compares the measured traffic with the currently effective ecological traffic threshold and generates a three-level early warning system: Level 1: Measured traffic is below 80% but above 50% of the ecological traffic, triggering a yellow warning, with notification via in-system message and SMS alert; Level 2: Measured traffic is below 50% but above 30% of the ecological traffic, or there is no interruption of traffic, triggering an orange warning, with notification via SMS and WeChat push, and requiring on-duty personnel to confirm; Level 3: Measured traffic is below 30% of the ecological traffic, or an interruption of traffic is detected (traffic close to 0), triggering a red warning, with notification via telephone voice and SMS, and simultaneously activating the emergency plan and notifying relevant responsible personnel.

[0044] The early warning and alarm module also generates electronic work orders, recording information such as the warning time, site, level, current traffic, and ecological traffic threshold, and pushes them to the designated person in charge. The person in charge must provide feedback on the processing results in the system within a specified time (e.g., 2 hours for yellow alerts, 1 hour for orange alerts, and 30 minutes for red alerts), forming a closed-loop management system of early warning, response, and feedback.

[0045] V. Visualization Module The visualization module includes a report generation unit and a scheduling scheme comparison unit.

[0046] The report generation unit automatically fills in real-time data, statistical charts, and textual conclusions according to a preset fixed template, generating daily or monthly ecological traffic reports. For example, a daily report includes information such as the hourly traffic curves for each site, ecological traffic threshold lines, statistics on periods of compliance, and the number of consecutive days of non-compliance. The report can be exported as a PDF or automatically sent to a specified email address.

[0047] The scheduling scheme comparison unit receives the user-inputted proposed water volume (e.g., an increase of 1 m³ / s in the discharge from the upstream reservoir). It then uses hydrological methods (such as the Muskingan method or simple flow evolution) to calculate the predicted flow values ​​for each monitoring section in future time periods and the corresponding ecological flow compliance rate. The system displays the prediction results for multiple scheduling schemes (e.g., increases of 0.5, 1.0, and 1.5 m³ / s) in tabular form, including the predicted flow values ​​and ecological flow compliance rates for each section in the next 24, 48, and 72 hours, for management personnel to consult and make decisions.

[0048] It should be noted that the visualization module also provides a mobile access interface, supporting the viewing of real-time data, receiving early warning information, and uploading on-site handling records and photos via a mobile app or mini-program.

[0049] The overall system workflow is as follows: After power-on, the data acquisition and calculation module collects data such as water level, flow rate, water temperature, and dissolved oxygen at preset frequencies using various sensors. Local anomaly detection checks the data, normal data is packaged and sent, and suspicious data is marked and cached first. The communication transmission module uploads data via the 4G Cat.1 main channel; if 4G is interrupted, it switches to BeiDou short message service to send key information, and retransmits all data after recovery. After receiving the data, the remote monitoring center's data access unit parses and stores the data. The ecological simulation unit selects the suitability function relationship table based on the current date and looks up the WUA corresponding to the current flow. The environmental stress correction unit corrects the WUA based on real-time water temperature and dissolved oxygen, and fine-tunes the threshold based on weather forecasts. The target optimization unit runs the optimization algorithm according to the set cycle and outputs the optimal ecological flow threshold for the current period. The early warning and alarm module compares the measured flow with the threshold. If the tiered early warning conditions are triggered, an early warning message and electronic work order are generated and pushed to relevant personnel. The visualization module refreshes and displays the status of each station in real time and generates reports and scheduling comparison results. The entire process forms a closed loop, enabling real-time monitoring, dynamic assessment, precise early warning, and scientific decision-making regarding river ecological flow.

[0050] Furthermore, it should be noted that the present invention can be provided as a method, apparatus, or computer program product. Therefore, embodiments of the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, embodiments of the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code.

[0051] The embodiments of the present invention are described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0052] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing terminal equipment to cause a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0053] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0054] Finally, it should be noted that the above description represents a preferred embodiment of the present invention. It should be pointed out that although preferred embodiments have been described, those skilled in the art, once they understand the basic inventive concept of the present invention, can make various improvements and modifications without departing from the principles described herein. These improvements and modifications should also be considered within the scope of protection of the present invention. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the embodiments of the present invention.

Claims

1. A real-time flow monitoring system for river ecological restoration, characterized in that, include: The data acquisition and computing module is used to collect and process water level and flow velocity data of river cross sections, and to perform local anomaly detection. The communication transmission module is used to transmit the processed data to the remote monitoring center; The traffic analysis and evaluation module is used to calculate ecological traffic indicators based on the received data and evaluate whether the current traffic meets the preset ecological traffic threshold. The early warning and alarm module is used to generate tiered early warning information based on the assessment results and push it to relevant personnel; The visualization module is used to display real-time monitoring status and ecological flow compliance, and provides a function to compare scheduling schemes.

2. The real-time flow monitoring system for river ecological restoration as described in claim 1, characterized in that, The data acquisition and calculation module is used to collect and process water level and flow velocity data of the river cross-section, and to perform local anomaly detection, wherein: The data acquisition and calculation module includes a traffic acquisition unit, an image capture unit, an image recognition unit, and an ecological acquisition unit; The flow acquisition unit includes a radar flow meter and a pressure level gauge. The radar flow meter is used to measure the surface velocity, and the pressure level gauge is used to measure the water level. The data from both are combined to calculate the flow rate through cross-sectional relationships, and they serve as backups for each other. The image capturing unit is used to capture images of the water level gauge, and the image recognition unit reads the water level gauge scale through an image recognition algorithm as a third-party verification of the water level data. The ecological data acquisition unit is used to collect at least one ecological environment parameter among water temperature, dissolved oxygen, turbidity, pH, and conductivity.

3. The real-time flow monitoring system for river ecological restoration as described in claim 2, characterized in that, The local anomaly detection is used to make reasonable judgments on the collected water level, flow rate and auxiliary parameters, identify data abrupt changes, continuous invariance and abnormal correlation between water level and flow rate, and mark suspicious data and cache it first, waiting for retransmission or manual confirmation.

4. The real-time flow monitoring system for river ecological restoration as described in claim 1, characterized in that, The communication transmission module is used to transmit the processed data to the remote monitoring center, wherein: The communication transmission module uses 4G Cat.1 communication as the main channel and is configured with a LoRa gateway for sensor data aggregation in areas without public network signals. It also integrates a Beidou short message communication module as an emergency backup channel. The communication transmission module supports a data interruption resumption mechanism and a critical data priority transmission mechanism, and automatically retransmits cached data after communication is restored.

5. The real-time flow monitoring system for river ecological restoration as described in claim 1, characterized in that, The flow analysis and evaluation module is used to calculate ecological flow indicators based on the received data and to evaluate whether the current flow meets the preset ecological flow threshold, wherein: The traffic analysis and evaluation module includes a data access unit, an ecological simulation unit, an environmental stress correction unit, and a target optimization unit. The data access unit is used to receive real-time hydrological data, water quality data, meteorological forecast data, and river geography and biological habitat data. The ecological simulation unit is used to generate a weighted available habitat area relationship table for different flow levels offline based on the flow velocity suitability function, water depth suitability function and substrate suitability function of the target species, combined with the hydraulic parameters of the river section. During real-time calculation, the weighted available habitat area corresponding to the current flow can be quickly obtained by looking up the table. The environmental stress correction unit is used to dynamically correct habitat suitability based on real-time water temperature and dissolved oxygen data, and adjust the threshold according to short-term weather forecasts. The objective optimization unit aims to maximize ecological benefits and minimize water supply losses. Under the constraints of the lower limit for preventing flow interruption and the upper limit for flood control safety, it uses a multi-objective optimization algorithm to solve for the optimal ecological flow threshold.

6. The real-time flow monitoring system for river ecological restoration as described in claim 5, characterized in that, The ecological simulation unit is used to generate a weighted available habitat area table for different flow levels offline, based on the flow velocity suitability function, water depth suitability function, and substrate suitability function of the target species, combined with the hydraulic parameters of the river cross-section. During real-time calculation, the weighted available habitat area corresponding to the current flow rate is quickly obtained by looking up the table. The flow velocity suitability function represents the relationship between the suitability of a target species to a water flow velocity and the flow velocity value. The water depth suitability function represents the relationship between the suitability of the target species to water depth and the water depth value. The substrate suitability function represents the degree of suitability of the target species for different types of riverbed substrate; The hydraulic parameters of the river cross section include cross-sectional shape, riverbed roughness, and sediment distribution.

7. The real-time flow monitoring system for river ecological restoration as described in claim 5, characterized in that, The target optimization unit aims to maximize ecological benefits and minimize water supply losses. Under the constraints of the lower limit for preventing flow interruption and the upper limit for flood control safety, a multi-objective optimization algorithm is used to solve for the optimal ecological flow threshold, wherein: The target optimization unit uses an optimization algorithm to run once at regular intervals and outputs a set of Pareto optimal solutions. It automatically selects a compromise solution as the ecological flow threshold for the current period based on the preset ecological priority or water supply priority management preferences.

8. The real-time flow monitoring system for river ecological restoration as described in claim 6, characterized in that, The ecological simulation unit is equipped with an adaptive feedback mechanism, which periodically calibrates the flow velocity suitability function, water depth suitability function, and sediment suitability function based on actual ecological monitoring data, so as to continuously improve the accuracy of threshold calculation.

9. The real-time flow monitoring system for river ecological restoration as described in claim 1, characterized in that, The early warning and alarm module is used to generate tiered early warning information based on the assessment results and push it to relevant personnel, wherein: The early warning alarm module adopts a dynamic threshold mechanism, which presets different values ​​according to the season and the life cycle stage of the fish, and the system automatically switches the threshold according to the date. The tiered early warning information includes three levels: Level 1 is when the flow rate is lower than 80% of the ecological flow rate, Level 2 is lower than 50%, and Level 3 is lower than 30% or when the flow is interrupted. Each level of early warning corresponds to different notification methods and response requirements.

10. The real-time flow monitoring system for river ecological restoration as described in claim 1, characterized in that, The visualization module is used to display real-time monitoring status and ecological flow compliance, and provides a scheduling scheme comparison function, wherein: The visualization module includes a report generation unit and a scheduling scheme comparison unit; The report generation unit automatically fills in real-time data, statistical charts and text conclusions according to a fixed template to generate daily or monthly ecological traffic reports, and supports exporting or automatic sending. The scheduling scheme comparison unit calculates the predicted flow rate and ecological flow compliance rate of each monitoring section for future periods based on the user-inputted water volume, and displays the comparison results of multiple schemes in tabular form.

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