River water environment monitoring method, device and equipment and storage medium

Abstract

The invention discloses a river water environment monitoring method, device and equipment and a storage medium, and relates to the technical field of environmental governance, and the method comprises the steps: constructing an observation data set according to the target observation data of a river; according to the observation data set and a three-dimensional geometric section model of the river channel, constructing river channel baseline information, and according to the river channel baseline information, constructing a baseline data set; identifying a plurality of environmental disturbance events based on the observation data set, classifying the environmental disturbance events, and processing the environmental disturbance events according to classification results to generate real-time correction results and correction suggestions; and screening a target correction entry from the plurality of initial correction entries of the correction suggestions, determining a correction entry set according to the target correction entry, correcting the baseline data set based on the correction entry set, and monitoring the water environment of the river channel in real time based on the corrected baseline data set and the real-time correction result. According to the invention, continuous and stable monitoring of the river water environment under multi-source disturbance can be realized.

Description

Technical Field

[0001] This invention relates to the field of environmental governance technology, and in particular to a method, apparatus, equipment and storage medium for monitoring river water environment. Background Technology

[0002] River water environment monitoring technology is used to perceive and dynamically assess river hydrology, water quality, and ecological elements in real time, supporting flood control scheduling, water pollution control, and ecological restoration. Existing river water environment monitoring systems typically combine multi-source sensor networks, remote sensing observation, and hydrodynamic models to automatically monitor and provide early warnings of river conditions by collecting data on water level, flow, water quality, and meteorological data. Some systems further incorporate data assimilation and model calibration techniques, which can improve the accuracy and response efficiency of monitoring results to a certain extent, providing important data support and decision-making basis for watershed water environment management.

[0003] Because river environmental disturbances are characterized by multiple sources, sudden occurrences, and non-stationarity, existing technologies have several shortcomings. Firstly, monitoring data is updated frequently, but the hydrodynamic model, as the core constraint structure, often lags behind environmental changes in parameter updates and boundary corrections, resulting in a mismatch between monitoring data and the physical model's rhythm. This leads to delayed or unstable model output responses to short-term disturbances. Secondly, traditional technologies often employ a unidirectional monitoring-analysis process, lacking a dynamic coordination mechanism between monitoring data and physical constraints. This makes it difficult to maintain structural equilibrium and monitoring continuity under complex disturbances, frequently resulting in response lag, parameter drift, and distorted results, affecting the scientific rigor and timeliness of governance decisions. Furthermore, existing systems do not adequately address the risk differences in different river regions and lack differentiated update strategies. This fails to meet the precise monitoring needs of high-risk areas and may also lead to resource waste in low-risk areas.

[0004] In summary, how to achieve continuous and stable monitoring of the river water environment under multi-source disturbances is a technical problem that urgently needs to be solved. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide a method, apparatus, equipment, and storage medium for monitoring river water environment, capable of achieving continuous and stable monitoring of river water environment under multi-source disturbances. The specific solution is as follows: Firstly, this application provides a method for monitoring the water environment of a river channel, comprising: Raw observation data of the river channel is collected, and the raw observation data is preprocessed to obtain target observation data, and an observation dataset is constructed based on the target observation data; Based on the observation dataset and using the three-dimensional geometric profile model of the river channel, the river channel baseline information is constructed, and a baseline dataset is constructed based on the river channel baseline information; the river channel baseline information includes the river channel cross-sectional morphology, roughness distribution, boundary conditions, and hydrodynamic parameters; Several environmental disturbance events are identified based on the observation dataset, and each environmental disturbance event is classified. The environmental disturbance events are then processed according to the classification results to generate corresponding real-time correction results and correction suggestions. The environmental disturbance events are either real-time response events or events to be corrected. The real-time correction results are the results obtained by correcting the real-time response events, and the correction suggestions are correction suggestions corresponding to the events to be corrected. Target correction entries are selected from several initial correction entries of the correction suggestions, and a set of correction entries is determined based on the target correction entries. The baseline dataset is corrected based on the set of correction entries, and the water environment of the river is monitored in real time based on the corrected baseline dataset and the real-time correction results.

[0006] Optionally, the process of collecting raw observation data of the river channel and preprocessing the raw observation data to obtain target observation data includes: The raw observation data of the river channel were collected using water level gauges, flow meters, water quality sensors, shore weather stations, and remote sensing images. The original observation data is subjected to time synchronization, spatial registration, quality control, and anomaly processing to obtain the target observation data based on the processed data; The target observation data includes river water level data, flow data, water quality data, meteorological data, and image data.

[0007] Optionally, constructing the river baseline information based on the observation dataset and using a three-dimensional geometric profile model of the river channel includes: Based on the topographic mapping data and cross-sectional measurement data corresponding to the river channel, a three-dimensional geometric profile model of the river channel is constructed, and the roughness distribution in the three-dimensional geometric profile model is determined, as well as the boundary conditions corresponding to the three-dimensional geometric profile model are defined. The hydrodynamic parameters are determined based on the three-dimensional geometric profile model, the observation dataset, the roughness distribution, and the boundary conditions. The observation dataset, the three-dimensional geometric profile model, the roughness distribution, the boundary conditions, and the hydrodynamic parameters are integrated to construct the river baseline information.

[0008] Optionally, the step of identifying several environmental disturbance events based on the observation dataset, classifying each environmental disturbance event, and processing each environmental disturbance event according to the classification results to generate corresponding real-time correction results and correction suggestions includes: The magnitude of change of the target observation data in the observation dataset is extracted by time window sliding statistics and robust smoothing algorithm; If the change exceeds a preset disturbance threshold, the environmental disturbance event corresponding to the target observation data is identified; The environmental disturbance events are classified to obtain several real-time response events and several events to be corrected. The real-time response events are then corrected in real time to generate the real-time correction results. Calculate the deviation distribution corresponding to each of the events to be corrected, generate each correction entry based on each deviation distribution, adjust each correction entry to obtain several initial correction entries, and construct the correction suggestion based on each initial correction entry; The suddenness of the real-time response event is higher than a preset suddenness threshold and the duration is lower than a preset time threshold, while the influence range of the event to be corrected is higher than a preset influence range threshold and the rate of change is lower than a preset rate threshold.

[0009] Optionally, before filtering the target correction entry from the plurality of initial correction entries of the correction proposal, the method further includes: In the current time period, determine the target difference between the latest output time of the correction proposal and the latest update time of the baseline dataset, and determine the absolute value corresponding to the quotient of the target difference and the current time period as the target phase difference; The target state is determined based on the comparison between the target phase difference and the first preset phase difference interval; Accordingly, determining the target state based on the comparison result between the target phase difference and the first preset phase difference interval includes: If the target phase difference is lower than the first preset phase difference interval, the target state is determined to be a preset synchronization state, and the river is divided into zones according to the spatial risk mask of the river, and the risk index and the second preset phase difference interval corresponding to each zone are determined. If the risk index of the partition is greater than a preset risk index threshold and the target phase difference is lower than the second preset phase difference interval, then the target correction entry is selected from the initial correction entries of the correction suggestion to determine the correction entry set based on the target correction entry; If the target phase difference is within the first preset phase difference interval, the target state is determined to be a preset state to be coordinated, and the baseline dataset is stopped from being corrected in the current time period. The water environment of the river is monitored in real time based directly on the baseline dataset and the real-time correction result. If the target phase difference exceeds the first preset phase difference interval, the target state is determined to be a preset frozen state, and the correction of the baseline dataset is prohibited. The water environment of the river channel is monitored in real time based directly on the baseline dataset and the real-time correction result.

[0010] Optionally, correcting the baseline dataset based on the set of correction entries includes: Construct a target buffer space and perform a difference operation on the baseline dataset and the set of correction entries to generate a corresponding candidate baseline dataset based on the difference operation results; The candidate baseline dataset is verified according to the mass conservation criterion and the energy conservation criterion. If the verification error is lower than the preset error threshold, the candidate baseline dataset is used as the corrected baseline dataset.

[0011] Optionally, the method for monitoring the river water environment further includes: A decision signal is constructed based on the latest output time of the proposed correction, the latest update time of the baseline dataset, the target phase difference, and the target state, and a corresponding write control table is generated based on the set of correction entries. Based on the monitoring results of the water environment of the river, the judgment signal, the writing to the control table, the real-time correction results, and the corrected baseline dataset, a corresponding feedback signal is generated, and the monitoring process of the water environment of the river is optimized based on the feedback signal.

[0012] Secondly, this application provides a monitoring device for river water environment, comprising: An observation dataset construction module is used to collect raw observation data of the river channel, perform data preprocessing on the raw observation data to obtain target observation data, and construct an observation dataset based on the target observation data. The baseline dataset construction module is used to construct river baseline information based on the observation dataset and using a three-dimensional geometric profile model of the river channel, and to construct a baseline dataset based on the river baseline information; the river baseline information includes the river channel cross-sectional morphology, roughness distribution, boundary conditions, and hydrodynamic parameters. The correction suggestion generation module is used to identify several environmental disturbance events based on the observation dataset, classify each environmental disturbance event, and process each environmental disturbance event according to the classification results to generate corresponding real-time correction results and correction suggestions; the environmental disturbance event is a real-time response event or an event to be corrected, the real-time correction result is the result obtained by correcting the real-time response event, and the correction suggestion is a correction suggestion corresponding to the event to be corrected; The water environment monitoring module is used to select target correction items from a number of initial correction items of the correction suggestions, determine a set of correction items based on the target correction items, correct the baseline dataset based on the set of correction items, and monitor the water environment of the river in real time based on the corrected baseline dataset and the real-time correction results.

[0013] Thirdly, this application provides an electronic device, comprising: Memory, used to store computer programs; A processor is used to execute the computer program to implement the aforementioned method for monitoring the river water environment.

[0014] Fourthly, this application provides a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned method for monitoring the river water environment.

[0015] In this application, raw observation data of the river channel is first collected, and the raw observation data is preprocessed to obtain target observation data, and an observation dataset is constructed based on the target observation data. Then, based on the observation dataset and using a three-dimensional geometric profile model of the river channel, river baseline information is constructed, and a baseline dataset is constructed based on the river baseline information. The river baseline information includes the river channel cross-sectional morphology, roughness distribution, boundary conditions, and hydrodynamic parameters. Next, several environmental disturbance events are identified based on the observation dataset, and each environmental disturbance event is classified. Based on the classification results, each environmental disturbance event is processed to generate corresponding real-time correction results and correction suggestions. The environmental disturbance events are real-time response events or events to be corrected. The real-time correction results are the results obtained by correcting the real-time response events, and the correction suggestions are correction suggestions corresponding to the events to be corrected. Finally, target correction entries are selected from several initial correction entries of the correction suggestions, and a set of correction entries is determined based on the target correction entries. The baseline dataset is corrected based on the set of correction entries, and the water environment of the river channel is monitored in real time based on the corrected baseline dataset and the real-time correction results. As can be seen from the above, this application first collects raw river observation data and preprocesses it to form an observation dataset. Then, combined with a three-dimensional geometric profile model of the river, a baseline dataset containing information such as cross-sectional morphology and roughness distribution is constructed. Subsequently, based on the observation dataset, environmental disturbance events are identified and classified to obtain real-time response events or events to be corrected. Then, correction suggestions are generated for the real-time response events and the events to be corrected. Finally, target correction items are selected to form a set of correction items, the baseline dataset is corrected, and the real-time correction results are combined for real-time monitoring of the river's water environment. In this way, this application ensures input reliability through data standardization, uses baseline data as a stable reference to support accurate disturbance identification, and achieves targeted correction through scientific classification and screening. This not only solves the problems of response lag and parameter drift in traditional monitoring, but also improves the continuity, stability, and accuracy of monitoring under multi-source disturbances by combining dynamic baseline correction with real-time monitoring, providing reliable data support and decision-making basis for river water environment management. In this way, this application can maintain the continuity of the river water environment monitoring process and the stability of the baseline structure under multi-source disturbance conditions. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0017] Figure 1A flowchart of a method for monitoring river water environment provided in this application; Figure 2 A flowchart illustrating a specific preset phase difference determination mechanism provided in this application; Figure 3 A flowchart of a specific preset partition asynchronous timing mechanism is provided for this application; Figure 4 A schematic diagram of the structure of a specific river water environment monitoring system provided in this application; Figure 5 A schematic diagram of a river water environment monitoring device provided in this application; Figure 6 This application provides a structural diagram of an electronic device. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] River water environment monitoring technology is used to perceive and dynamically assess river hydrology, water quality, and ecological elements in real time to support flood control scheduling, water pollution control, and ecological restoration. Existing river water environment monitoring systems typically combine multi-source sensor networks, remote sensing observation, and hydrodynamic models to automatically monitor and provide early warnings of river conditions by collecting data on water level, flow, water quality, and meteorology. Some systems have incorporated data assimilation and model calibration techniques to improve the accuracy and response efficiency of monitoring results, providing crucial data support and decision-making basis for watershed water environment management. However, due to the multi-source, sudden, and non-stationary characteristics of river environmental disturbances, existing technologies have many shortcomings. Therefore, this application provides a river water environment monitoring scheme that enables continuous and stable monitoring of the river water environment under multi-source disturbances.

[0020] See Figure 1 As shown in the figure, an embodiment of the present invention discloses a method for monitoring the river water environment, which may include: Step S11: Collect raw observation data of the river channel, perform data preprocessing on the raw observation data to obtain target observation data, and construct an observation dataset based on the target observation data.

[0021] In this embodiment, a monitoring data module is designed to collect and integrate multi-source observation information of the river channel. It can perform data fusion processing based on a unified time reference and spatial coordinates, providing unified and reliable input data for the river water environment monitoring system. The monitoring data module collects raw observation data of the river channel and performs data preprocessing to obtain target observation data. The specific process may include: firstly, collecting the raw observation data of the river channel through water level gauges, flow meters, water quality sensors, riverside meteorological stations, and remote sensing images; then, performing time synchronization, spatial registration, quality control, and anomaly processing on the raw observation data to obtain the target observation data based on the processed data; wherein, the target observation data includes river water level data, flow data, water quality data, meteorological data, and image data.

[0022] Specifically, firstly, the raw observation data from different sources are synchronized in time and registered spatially. Interpolation algorithms are used to eliminate sampling frequency differences, ensuring that data from all monitoring points are aligned on the same time axis. Secondly, quality control and anomaly correction are performed, automatically identifying missing measurements, jumps, and outliers, and repairing them based on neighboring observations and physical constraints. Records with persistent anomalies or exceeding thresholds are also filtered out. After these processes, target observation data is generated, and a standardized observation dataset is constructed based on this target observation data. The observation dataset includes data such as river level, flow rate, water quality, and meteorological data. Each record contains a timestamp, spatial index, feature name, value, and confidence level.

[0023] Step S12: Based on the observation dataset and using the three-dimensional geometric profile model of the river channel, construct the river channel baseline information, and construct the baseline dataset based on the river channel baseline information; the river channel baseline information includes the river channel cross-sectional morphology, roughness distribution, boundary conditions, and hydrodynamic parameters.

[0024] In this embodiment, a hydrodynamic baseline module is designed to maintain the river channel's geometry, boundary conditions, and hydrodynamic parameter set, forming the hydrodynamic constraint domain of the river water environment monitoring system. The input to the hydrodynamic baseline module is the observation dataset. The measured data, such as water level, flow velocity, and flow rate, are processed at a slow pace and kept frozen during non-writing phases, serving as a stable reference for the environmental response domain. The hydrodynamic baseline module can use the observed dataset... The long-term trend information maintains the stability of physical constraints, while short-term disturbances only enter the update process when the rhythm coordination module triggers a write.

[0025] It should be noted that the hydrodynamic baseline module includes a baseline construction unit, which can construct river baseline information based on the observation dataset and the three-dimensional geometric profile model of the river channel. The specific process may include: first, constructing the three-dimensional geometric profile model of the river channel based on the topographic mapping data and cross-sectional measurement data corresponding to the river channel, determining the roughness distribution in the three-dimensional geometric profile model, and defining the boundary conditions corresponding to the three-dimensional geometric profile model; then, determining the hydrodynamic parameters based on the three-dimensional geometric profile model, the observation dataset, the roughness distribution, and the boundary conditions; finally, integrating the observation dataset, the three-dimensional geometric profile model, the roughness distribution, the boundary conditions, and the hydrodynamic parameters to construct the river baseline information.

[0026] Specifically, the baseline construction unit establishes a three-dimensional geometric profile model of the river channel based on topographic mapping data and cross-sectional measurement data. It determines hydrodynamic parameters by combining roughness distribution and boundary conditions, integrates them to obtain the river channel baseline information, and then constructs a baseline dataset based on the river channel baseline information to obtain the initial baseline version V(0). V(t) represents the formal baseline version at time step t, which is used to describe the current set of physical constraint parameters of the river channel.

[0027] Step S13: Identify several environmental disturbance events based on the observation dataset, classify each environmental disturbance event, and process each environmental disturbance event according to the classification results to generate corresponding real-time correction results and correction suggestions; the environmental disturbance event is a real-time response event or an event to be corrected, the real-time correction result is the result obtained by correcting the real-time response event, and the correction suggestion is the correction suggestion corresponding to the event to be corrected.

[0028] In this embodiment, a water environment response module is designed to identify deviations in environmental conditions based on changes in observed data, and to perform immediate response corrections or generate correction suggestion sets according to the type of disturbance. This is the fastest dynamically updated domain in the river water environment monitoring system. The input to the water environment response module is the observed dataset. and with baseline dataset As a physical reference.

[0029] It should be noted that the water environment response module includes a disturbance identification unit, a trend analysis unit, and a response and correction unit, which are used to sequentially complete disturbance detection, trend extraction, and candidate correction generation. The water environment response module can identify several environmental disturbance events based on an observation dataset, classify each environmental disturbance event, and process each environmental disturbance event according to the classification results to generate corresponding real-time correction results and correction suggestions. The specific process may include: first, extracting the change amplitude corresponding to the target observation data in the observation dataset through time window sliding statistics and robust smoothing algorithms; if the change amplitude exceeds a preset disturbance threshold, identifying the environmental disturbance event corresponding to the target observation data; then, classifying each environmental disturbance event to obtain several real-time response events and several events to be corrected, and performing immediate correction on each real-time response event to generate the real-time correction result; then calculating the deviation distribution corresponding to each event to be corrected, generating correction entries based on each deviation distribution, adjusting each correction entry to obtain several initial correction entries, and constructing the correction suggestions based on each initial correction entry; wherein, the suddenness of the real-time response event is higher than a preset suddenness threshold and the duration is lower than a preset time threshold, and the influence range of the event to be corrected is higher than a preset influence range threshold and the change rate is lower than a preset rate threshold.

[0030] Specifically, the perturbation identification unit is used to identify the observed dataset. All significant disturbance events in the data: Short-term fluctuations and background trends of each monitoring element in the observation dataset are extracted using time-window sliding statistics and robust smoothing algorithms. Statistical deviation is used as the disturbance criterion to obtain the change amplitude corresponding to the target observation data. When the change amplitude exceeds a preset disturbance threshold, the point is marked as a significant deviation event, identifying the corresponding environmental disturbance event and forming a preliminary disturbance identifier set for subsequent trend analysis. The trend analysis unit is used to perform spatiotemporal characteristics and risk assessment on each environmental disturbance event in the disturbance identifier set. The river water environment monitoring system calculates the persistence and risk level of environmental disturbance events and, combined with the frequency of change and trend direction, classifies environmental disturbance events into real-time response events and events requiring correction. Real-time response events correspond to disturbances with high suddenness and short duration, while events requiring correction correspond to disturbances with slow change rates and wide impact ranges. The two types of events enter different processing paths. The response and correction unit is used to perform differentiated processing on the two types of events while maintaining physical consistency.

[0031] In one specific implementation, for real-time response events, the response and correction unit performs small-scale, immediate corrections based on the parameters in the dataset, generates real-time correction results, and constructs a real-time correction result set. It is used to characterize the changes of observed elements within the current refresh cycle and outputs them in real time when the data is updated, providing input for the dynamic display and risk warning of the river water environment monitoring system.

[0032] In another specific implementation, for the event to be corrected, the response and correction unit calculates the deviation distribution and generates a set of correction candidates, each containing information such as disturbance identifier, target location, element type, and suggested correction amount. Subsequently, the river water environment monitoring system adjusts the suggested correction amount of the candidate candidates based on historical stability and risk level, obtaining several initial correction entries, and generates a set of correction suggestions based on these initial entries. Its payload is a set of correction candidates, which are then called by the subsequent rhythm coordination module.

[0033] Understandably, the water environment response module outputs two types of results: real-time correction result set. and set of amendments Among them, the real-time correction result set The response and correction unit is generated in real time when the monitoring data is refreshed, and is used for immediate trend adjustment and risk warning; correction suggestion set According to the coordination cycle It is periodically sent to the rhythm coordination module. The coordination period is the time base period for the water environment response module to perform cross-domain judgment and rhythm tuning, and is used to determine the rhythm frequency of coordination judgment and write trigger.

[0034] Step S14: Select target correction entries from several initial correction entries of the correction suggestions, determine a set of correction entries based on the target correction entries, correct the baseline dataset based on the set of correction entries, and monitor the water environment of the river in real time based on the corrected baseline dataset and the real-time correction results.

[0035] In this embodiment, a rhythm coordination module is designed as the control core of the river water environment monitoring system. It is used to achieve asynchronous interaction and rhythm determination between the hydrodynamic constraint domain and the environmental response domain. The rhythm coordination module operates based on a preset phase difference determination mechanism and a preset partitioned asynchronous beat mechanism, and operates within a coordination cycle. The system performs cross-domain rhythm tuning and partitioned write control to maintain the self-tuning of the river water environment monitoring system's rhythm. The rhythm coordination module receives a set of correction suggestions from the water environment response module. and baseline datasets from the hydrodynamic baseline module. This achieves rhythmic coordination between the hydrodynamic constraint domain and the environmental response domain in both temporal and spatial dimensions. When the coordination conditions are met, the river water environment monitoring system adjusts its recommendations accordingly. The approved target modification entries are selected to form a set of modification entries. and will Submit to the hydrodynamic baseline module to perform controlled writes to update the baseline dataset.

[0036] It should be noted that the rhythm coordination module includes a phase determination unit and a partitioned beat coordination unit. The workflow of the rhythm coordination module can specifically include: firstly, in the current time period, determining the target difference between the latest output time of the correction suggestion and the latest update time of the baseline dataset, and determining the absolute value corresponding to the quotient of the target difference and the current time period as the target phase difference; then, determining the target state based on the comparison result of the target phase difference and the first preset phase difference interval; correspondingly, the above-mentioned determination of the target state based on the comparison result of the target phase difference and the first preset phase difference interval can specifically include: if the target phase difference is lower than the first preset phase difference interval, determining the target state as a preset synchronization state, partitioning the river according to the spatial risk mask of the river channel, and determining the risk index and second preset risk index corresponding to each partition. A phase difference interval is defined. If the risk index of the partition is greater than a preset risk index threshold, and the target phase difference is lower than the second preset phase difference interval, then the target correction entry is selected from a plurality of initial correction entries of the correction suggestion to determine the correction entry set based on the target correction entry. If the target phase difference is within the first preset phase difference interval, then the target state is determined to be a preset state to be coordinated, and the correction of the baseline dataset is stopped in the current time period, and the water environment of the river is monitored in real time directly based on the baseline dataset and the real-time correction result. If the target phase difference exceeds the first preset phase difference interval, then the target state is determined to be a preset frozen state, and the correction of the baseline dataset is prohibited, and the water environment of the river is monitored in real time directly based on the baseline dataset and the real-time correction result.

[0037] Specifically, the phase determination unit implements a phase difference determination mechanism to identify the offset between the hydrodynamic constraint domain and the environmental response domain in terms of update time, and generates a phase difference determination signal. This embodiment pre-defines the phase difference determination mechanism; the process is described in [link to documentation]. Figure 2 As shown, the target phase difference is defined as follows: ; in, The most recent output revision suggestion set for the environmental response domain Time, The baseline dataset for the most recent update of the hydrodynamic constraint domain Time, The coordination period is preset. The river water environment monitoring system determines the threshold range based on preset phase settings. For target phase difference The classification process results in the following three states: Synchronization status :when This indicates that the environmental response domain and the hydrodynamic constraint domain are updated almost simultaneously. The river water environment monitoring system considers the phases to be perfectly aligned and sends a synchronization signal. Authorize subsequent partition clock coordination units to write; pending coordination status :when If the time deviation is small, it indicates that there is a slight time difference between the environmental response domain and the hydrodynamic constraint domain, but it is still within an acceptable range. The monitoring system for the river water environment remains in a wait-and-see state, does not immediately trigger the write, but records the difference and waits for the next coordination cycle to re-determine. Asynchronous state :when This indicates that the environmental response domain is updating too quickly or the hydrodynamic constraint domain is lagging, and cross-domain writes may cause version conflicts. The river water environment monitoring system generates a freeze signal based on this information. Cross-domain write triggers are prohibited; the baseline dataset of the current version is maintained. constant.

[0038] It should be noted that the river water environment monitoring system can construct a decision signal based on the latest output time of the correction proposal, the latest update time of the baseline dataset, the target phase difference, and the target state. , , The status identifiers form a set of synchronization determination signals. It is used to characterize the phase relationship between the hydrodynamic constraint domain and the environmental response domain within the current coordination cycle, providing a time reference for subsequent coordination processes.

[0039] In this embodiment, the partitioned beat coordination unit implements a partitioned asynchronous beat mechanism, which performs differentiated rhythm tuning in the spatial dimension based on time synchronization. This embodiment pre-defines the partitioned asynchronous beat mechanism; the process is described in [link to documentation]. Figure 3 As shown. The river water environment monitoring system receives a set of correction suggestions. With the set of judgment signals The river monitoring area is divided into zones based on a river spatial risk mask. This risk mask, generated by the river water environment monitoring system based on long-term monitoring data and management operation records, characterizes the stability differences between different areas of the river. The river water environment monitoring system calculates the risk index for each zone by statistically analyzing characteristic indicators such as water quality fluctuation frequency, flow velocity abrupt change rate, and the number of gate and pump openings and closings. This allows for the identification of high-risk areas such as sewage outfall areas, downstream areas of pumping stations, and backwater retention areas. Subsequently, the river water environment monitoring system aggregates zones based on similar risk indices, forming a zoning set and determining the number of zones. The river water environment monitoring system is configured with independent cycle parameters for each zone. The phase difference interval with the second preset phase tolerance interval and combined with risk index Determine write permissions. Define the partition trigger function as follows: ; in, For partition permission, indicate partition At any moment Write permission status, The preset risk index threshold.

[0040] when At that time, the river water environment monitoring system considered the zoning... In a state of synchronization and significant risk, immediately from The approved target modification entries are selected to form a set of modification entries. Items that are not granted permission will be marked for reassessment and will be re-evaluated in the next coordination cycle; when At that time, partition Keep it frozen and suspend updates to avoid the spread of disturbance.

[0041] It should be noted that, in order to achieve risk-driven dynamic rhythm adjustment, the river water environment monitoring system can execute rhythm parameters based on the risk index over multiple cycles. The adaptive adjustment is as follows: ; in, For preset beat adjustment coefficient, This represents the average risk index across the entire region. Through adaptive adjustment, the cycle time in high-risk areas can be gradually shortened, while that in low-risk areas can be gradually extended, thus forming a staggered and coordinated update pattern where high-risk areas are updated frequently and low-risk areas are updated infrequently.

[0042] It should be noted that the river water environment monitoring system can generate corresponding write control tables based on the set of correction entries. Write to the control table Used to record the write permission status of each partition. Beat parameters The authorized time window and execution result indication provide control basis for the correction and writing of the hydrodynamic baseline module. In this way, through the above steps, the rhythm coordination module achieves synchronous coordination between two domains in the time dimension through a preset phase difference judgment mechanism, and achieves differentiated coordination across multiple zones in the spatial dimension through a preset zone asynchronous beat mechanism. The two mechanisms work together to enable the river water environment monitoring system to maintain temporal consistency and spatial balance under multi-source disturbance conditions. The rhythm coordination module finally outputs and writes the control table. Synchronization determination signal set Among them, the synchronization determination signal set The monitoring system records the synchronization status and phase changes of the river water environment in the current cycle, which is used to drive the baseline data update and response scheduling for the next cycle.

[0043] It should be noted that the river water environment monitoring system is based on data entered into the control table. Synchronization determination signal set The authorization result will generate a set of correction entries. Submit to the hydrodynamic baseline module for partition writing. The baseline dataset is corrected based on the set of correction entries. The specific process may include: first, constructing a target buffer space, and performing a difference operation on the baseline dataset and the set of correction entries to generate a corresponding candidate baseline dataset based on the difference operation result; then, verifying the candidate baseline dataset according to the mass conservation criterion and the energy conservation criterion. If the verification error is lower than a preset error threshold, the candidate baseline dataset is used as the corrected baseline dataset.

[0044] Specifically, the hydrodynamic baseline module also includes a parameter update unit and a constraint verification unit; wherein, the parameter update unit receives a set of correction entries generated by the water environment response module and authorized by the rhythm coordination module. To ensure the security and reversibility of updates, the river water environment monitoring system establishes a target buffer space outside the main baseline version for temporary writing and verification, serving as a shadow region. Differential operations are performed within the shadow region to generate candidate baseline datasets, thus obtaining candidate versions. Then, wait for the verification results to be confirmed before submitting. Constrain the verification unit on candidate versions. Perform a physical consistency check, and detect whether parameter changes disrupt the river channel continuity and energy balance based on the mass conservation and energy conservation principles; if the check error is lower than the preset error threshold... At that time, the revised baseline dataset will be used as the official version. Otherwise, maintain the original version of the baseline dataset. The system remains unchanged and records any abnormal entries. The hydrodynamic baseline module can realize the observation dataset. To baseline dataset The cross-domain transmission is evident. It is clear that the rhythm coordination module, as a whole, achieves rhythm regulation and structural stability maintenance of cross-domain information flow, constituting a core supporting component for the adaptive operation of the river water environment monitoring system in a dynamic environment.

[0045] In this embodiment, a governance feedback module is also designed to comprehensively evaluate the operation status of the river water environment monitoring system and generate parameter adjustment signals after the cross-domain regulation is completed in rhythm coordination, so as to realize the closed-loop write-back of the governance strategy. Specifically, it can generate corresponding feedback signals based on the monitoring results, judgment signals, written control table, real-time correction results, and corrected baseline dataset corresponding to the river water environment, and optimize the river water environment monitoring process based on the feedback signals.

[0046] Specifically, the inputs to the governance feedback module include the observation results from external governance devices and the synchronous judgment signal set. And writing to the control table The system combines the latest outputs from the hydrodynamic baseline module and the water environment response module to calculate the comprehensive stability index and coordination performance index for the current monitoring period. The comprehensive stability index characterizes the structural steady-state level, while the coordination performance index measures the contribution of rhythm regulation to monitoring continuity and response accuracy. The governance feedback module can automatically generate a governance feedback signal set based on index deviations. , Composed of multiple sub-signals, it characterizes the operational deviations and adjustment directions of the river water environment monitoring system at different levels, specifically including: The rhythm coordination status feedback signal is used to reflect the consistency of cross-domain rhythms, record the phase judgment result and synchronization deviation score, and provide the rhythm coordination module with time tuning for the next cycle. The risk adjustment signal for each monitoring zone describes the risk change trend and stability level of each monitoring zone, and is used as a reference for the rhythm coordination module when configuring the zone's beat and determining permission. Baseline consistency feedback is used to reflect the consistency deviation and energy conservation status of the hydrodynamic baseline module in the previous cycle's write verification, so that it can perform self-checks and corrections during subsequent baseline maintenance; The environmental response correction signal is used to identify the deviation direction and confidence change of the water environment response module in the disturbance identification and trend analysis stage, and guide it to adjust the disturbance threshold or event classification strategy in the next cycle.

[0047] It is evident that the governance record set This is used to record evaluation metrics, deviations, and feedback on implementation status for each period. Governance Record Set In the next coordination cycle, the rhythm coordination module and the water environment response module read the data and use it to update the weight and threshold settings during the rhythm tuning and disturbance classification process. This enables the monitoring, response, coordination and feedback to be fully closed-loop, allowing the river water environment monitoring system to maintain long-term steady state and self-optimization capability under multi-source disturbances.

[0048] As can be seen from the above, in this embodiment, raw observation data of the river channel is first collected, and the raw observation data is preprocessed to obtain target observation data, and an observation dataset is constructed based on the target observation data. Then, based on the observation dataset and using a three-dimensional geometric profile model of the river channel, river baseline information is constructed, and a baseline dataset is constructed based on the river baseline information. The river baseline information includes the river channel cross-sectional morphology, roughness distribution, boundary conditions, and hydrodynamic parameters. Next, several environmental disturbance events are identified based on the observation dataset, and each environmental disturbance event is classified. Based on the classification results, each environmental disturbance event is processed to generate corresponding real-time correction results and correction suggestions. The environmental disturbance events are real-time response events or events to be corrected. The real-time correction results are the results obtained by correcting the real-time response events, and the correction suggestions are correction suggestions corresponding to the events to be corrected. Finally, target correction entries are selected from several initial correction entries of the correction suggestions, and a set of correction entries is determined based on the target correction entries. The baseline dataset is corrected based on the set of correction entries, and the water environment of the river channel is monitored in real time based on the corrected baseline dataset and the real-time correction results. As can be seen from the above, this embodiment first collects raw river observation data and preprocesses it to form an observation dataset. Then, combined with a three-dimensional geometric profile model of the river, a baseline dataset containing information such as cross-sectional morphology and roughness distribution is constructed. Subsequently, based on the observation dataset, environmental disturbance events are identified and classified to obtain real-time response events or events to be corrected. Correction suggestions corresponding to the real-time response events and events to be corrected are then generated. Finally, target correction items are selected to form a set of correction items, the baseline dataset is corrected, and the real-time correction results are combined for real-time monitoring of the river's water environment. In this way, this embodiment ensures input reliability through data standardization, uses baseline data as a stable reference to support accurate disturbance identification, and achieves targeted correction through scientific classification and screening. This not only solves the problems of traditional monitoring response lag and parameter drift, but also improves the continuity, stability, and accuracy of monitoring under multi-source disturbances by combining dynamic baseline correction with real-time monitoring, providing reliable data support and decision-making basis for river water environment management. In this way, this application can maintain the continuity of the river water environment monitoring process and the stability of the baseline structure under multi-source disturbance conditions.

[0049] In one specific embodiment, a schematic diagram of the river water environment monitoring system is shown below. Figure 4 As shown, it specifically includes: The monitoring data module 101 is used to collect monitoring data such as river water level, flow rate, water quality, and meteorological data, and to perform temporal and spatial benchmark unification and quality control, outputting a standardized observation dataset. This provides reliable real-time observation information for the river water environment monitoring system.

[0050] Hydrodynamic baseline module 102 is used to receive observation datasets. and a set of correction entries from the rhythm coordination module. Based on this, baseline information such as river channel cross-sectional morphology, roughness distribution, boundary conditions, and hydrodynamic parameters is established, maintained, and updated, and a verified baseline dataset is output. .in, Used to establish and maintain baseline datasets ; Correction of the collection of entries For guidance Perform the update. This module constitutes the hydrodynamic constraint domain of the river water environment monitoring system. It remains frozen during non-update phases, providing a stable reference for the environmental response domain.

[0051] Water environment response module 103 is used to receive observation datasets. And with hydrodynamic baseline dataset Using physical references, the module analyzes and responds to changes in monitoring data. The module outputs a real-time correction result set. and set of amendments , Used to display trend changes and risk warnings; Used to propose The module generates corrected candidate information. It constitutes the environmental response domain of the river water environment monitoring system, operating at a high update frequency to generate real-time data. To reflect changes in water quality and flow regime; at the same time, The rhythm coordination module is submitted to determine whether the synchronization conditions are met. If permission is granted, it is updated to the hydrodynamic constraint domain, thereby achieving dynamic coordination between the environmental response domain and the hydrodynamic constraint domain.

[0052] The rhythm coordination module 104 is used to coordinate the execution data coordination and write control between the hydrodynamic constraint domain and the environmental response domain. This module receives the hydrodynamic baseline dataset. With the set of revision suggestions By using a preset phase difference determination mechanism, the time-phase shift between the hydrodynamic constraint domain and the environmental response domain is identified, and a synchronization determination signal set is generated. ; and generate a write control table based on a preset partition asynchronous timing mechanism. Independent beat parameters and phase tolerance ranges are set for different spatial zones, enabling the river water environment monitoring system to achieve high-frequency updates in high-risk areas and low-frequency updates in low-risk areas; and Under the constraints, generate a set of correction entries. The approved correction information is submitted to the hydrodynamic baseline module for update, thereby enabling the river water environment monitoring system to maintain phase synchronization in the time dimension and achieve peak-shifting coordination and structural stability in the spatial dimension.

[0053] The governance feedback module 105 is used to assess the operational status of the river water environment monitoring system and generate governance feedback signals after the rhythm coordination is completed, realizing closed-loop linkage between monitoring and governance. The module receives a set of synchronization judgment signals. Write to control table The latest outputs of the hydrodynamic baseline module 102 and the water environment response module 103, and the output governance feedback signal set. and governance record set Governance feedback signal set Used to provide feedback information on operational deviations to the rhythm coordination module, water environment response module, and hydrodynamic baseline module. It is used to record the operating status and feedback results of each cycle, providing a basis for the adaptive adjustment of the river water environment monitoring system.

[0054] During the overall operation of the river water environment monitoring system, data is input from the monitoring data module, parsed by the water environment response module, and then written into the hydrodynamic baseline module by the rhythm coordination module when synchronization conditions are met. Simultaneously, the governance feedback module continuously transmits the operating status of the governance device, which, together with the observation data, influences the next round of information parsing and rhythm scheduling. This forms a closed-loop system of interaction between the monitoring main chain and the governance feedback chain, ensuring the consistency between monitoring data and the physical model under multi-source disturbances, and achieving stable tracking and adaptive optimization of the river water environment state at the structural level. As can be seen, the river water environment monitoring system can maintain the continuity of the monitoring process and the stability of the baseline structure under multi-source disturbances. A preset phase difference determination mechanism ensures the temporal consistency between the hydrodynamic constraint domain and the environmental response domain within the coordination cycle, avoiding model shifts caused by update lags. A preset partitioned asynchronous beat mechanism enables differentiated updates of spatial partitions according to risk levels, limiting the spread of local disturbances and maintaining the balance and controllability of the overall structure. The river water environment monitoring system has formed a closed-loop regulation mode of monitoring, response, coordination and feedback in long-term operation, so that environmental response data and hydrodynamic data are stably coupled between the two domains, providing support for the dynamic management and continuous optimization of the river water environment.

[0055] Accordingly, seeFigure 5 As shown in the embodiments of this application, a monitoring device for river water environment is also provided, which may include: The observation dataset construction module 11 is used to collect raw observation data of the river channel, perform data preprocessing on the raw observation data to obtain target observation data, and construct an observation dataset based on the target observation data. The baseline dataset construction module 12 is used to construct river baseline information based on the observation dataset and using the three-dimensional geometric profile model of the river channel, and to construct a baseline dataset based on the river baseline information; the river baseline information includes the river channel cross-sectional morphology, roughness distribution, boundary conditions and hydrodynamic parameters. The correction suggestion generation module 13 is used to identify several environmental disturbance events based on the observation dataset, classify each environmental disturbance event, and process each environmental disturbance event according to the classification results to generate corresponding real-time correction results and correction suggestions; the environmental disturbance event is a real-time response event or an event to be corrected, the real-time correction result is the result obtained by correcting the real-time response event, and the correction suggestion is a correction suggestion corresponding to the event to be corrected. The water environment monitoring module 14 is used to select target correction items from a number of initial correction items of the correction suggestions, determine a set of correction items according to the target correction items, correct the baseline dataset based on the set of correction items, and monitor the water environment of the river in real time based on the corrected baseline dataset and the real-time correction results.

[0056] In some specific embodiments, the observation dataset construction module 11 may include: The raw observation data acquisition unit is used to acquire the raw observation data of the river channel through water level gauges, flow meters, water quality sensors, shore weather stations and remote sensing images; The target observation data determination unit is used to perform time synchronization, spatial registration, quality control, and anomaly processing on the original observation data to obtain the target observation data based on the processed data; wherein, the target observation data includes river water level data, flow data, water quality data, meteorological data, and image data.

[0057] In some specific embodiments, the baseline dataset construction module 12 may include: A three-dimensional geometric profile model construction unit is used to construct the three-dimensional geometric profile model of the river channel based on the topographic mapping data and cross-sectional measurement data corresponding to the river channel, determine the roughness distribution in the three-dimensional geometric profile model, and define the boundary conditions corresponding to the three-dimensional geometric profile model. A hydrodynamic parameter determination unit is used to determine the hydrodynamic parameters based on the three-dimensional geometric profile model, the observation dataset, the roughness distribution, and the boundary conditions. The river baseline information construction unit is used to integrate the observation dataset, the three-dimensional geometric profile model, the roughness distribution, the boundary conditions, and the hydrodynamic parameters to construct the river baseline information.

[0058] In some specific embodiments, the correction suggestion generation module 13 may include: The variation amplitude extraction unit is used to extract the variation amplitude corresponding to the target observation data in the observation dataset through time window sliding statistics and robust smoothing algorithm; An environmental disturbance event identification unit is used to identify the environmental disturbance event corresponding to the target observation data if the change amplitude exceeds a preset disturbance threshold. The real-time correction result generation unit is used to classify each of the environmental disturbance events to obtain a number of real-time response events and a number of events to be corrected, and to correct each of the real-time response events in real time to generate the real-time correction result. The correction suggestion generation unit is used to calculate the deviation distribution corresponding to each of the events to be corrected, generate each correction entry based on each deviation distribution, adjust each correction entry to obtain several initial correction entries, and construct the correction suggestion based on each initial correction entry; wherein, the suddenness of the real-time response event is higher than a preset suddenness threshold and the duration is lower than a preset time threshold, and the influence range of the event to be corrected is higher than a preset influence range threshold and the rate of change is lower than a preset rate threshold.

[0059] In some specific embodiments, the river water environment monitoring device may further include: The target phase difference determination module is used to determine, in the current time period, the target difference between the latest output time of the correction suggestion and the latest update time of the baseline dataset, and to determine the absolute value corresponding to the quotient of the target difference and the current time period as the target phase difference; The target state determination module is used to determine the target state based on the comparison result between the target phase difference and the first preset phase difference interval; Accordingly, the target state determination module may include: The risk index determination unit is used to determine the target state as a preset synchronization state if the target phase difference is lower than the first preset phase difference interval, and to divide the river into partitions according to the spatial risk mask of the river, and to determine the risk index and the second preset phase difference interval corresponding to each partition. The correction entry filtering unit is used to filter the target correction entry from a plurality of initial correction entries of the correction suggestion if the risk index of the partition is greater than a preset risk index threshold and the target phase difference is lower than the second preset phase difference interval, so as to determine the correction entry set according to the target correction entry; The baseline dataset correction stop unit is used to determine the target state as a preset state to be coordinated if the target phase difference is located in the first preset phase difference interval, and to stop correcting the baseline dataset in the current time period, and to directly monitor the water environment of the river channel in real time based on the baseline dataset and the real-time correction result. The baseline dataset correction prohibition unit is used to determine the target state as a preset frozen state if the target phase difference exceeds the first preset phase difference interval, and to prohibit the correction of the baseline dataset, and to directly monitor the water environment of the river channel in real time based on the baseline dataset and the real-time correction result.

[0060] In some specific embodiments, the water environment monitoring module 14 may include: A candidate baseline dataset generation unit is used to construct a target buffer space and perform a difference operation on the baseline dataset and the set of correction entries to generate a corresponding candidate baseline dataset based on the difference operation result; The candidate baseline dataset verification unit is used to verify the candidate baseline dataset according to the mass conservation criterion and the energy conservation criterion. If the verification error is lower than a preset error threshold, the candidate baseline dataset is used as the corrected baseline dataset.

[0061] In some specific embodiments, the river water environment monitoring device may further include: The write control table generation module is used to construct a decision signal based on the latest output time of the correction suggestion, the latest update time of the baseline dataset, the target phase difference, and the target state, and to generate a corresponding write control table based on the set of correction entries. The feedback signal generation module is used to generate corresponding feedback signals based on the monitoring results of the water environment of the river, the judgment signal, the writing to the control table, the real-time correction results, and the corrected baseline dataset, and to optimize the monitoring process of the water environment of the river based on the feedback signals.

[0062] Furthermore, embodiments of this application also disclose an electronic device, Figure 6This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the river water environment monitoring method disclosed in any of the foregoing embodiments. Furthermore, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0063] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0064] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0065] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the river water environment monitoring method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include computer programs capable of performing other specific tasks.

[0066] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned method for monitoring the river water environment. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0067] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0068] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0069] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0070] Finally, it should 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. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0071] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for monitoring the water environment of a river, characterized in that, include: Raw observation data of the river channel is collected, and the raw observation data is preprocessed to obtain target observation data, and an observation dataset is constructed based on the target observation data; Based on the observation dataset and using the three-dimensional geometric profile model of the river channel, the river channel baseline information is constructed, and a baseline dataset is constructed based on the river channel baseline information; the river channel baseline information includes the river channel cross-sectional morphology, roughness distribution, boundary conditions, and hydrodynamic parameters; Based on the observation dataset, several environmental disturbance events are identified, and each environmental disturbance event is classified. Based on the classification results, each environmental disturbance event is processed to generate corresponding real-time correction results and correction suggestions. The environmental disturbance event is either a real-time response event or an event to be corrected. The real-time correction result is the result obtained by correcting the real-time response event. The correction suggestion is a correction suggestion corresponding to the event to be corrected. Target correction entries are selected from several initial correction entries of the correction suggestions, and a set of correction entries is determined based on the target correction entries. The baseline dataset is corrected based on the set of correction entries, and the water environment of the river is monitored in real time based on the corrected baseline dataset and the real-time correction results.

2. The method for monitoring river water environment according to claim 1, characterized in that, The process of collecting raw observation data of the river channel and preprocessing the raw observation data to obtain target observation data includes: The raw observation data of the river channel were collected using water level gauges, flow meters, water quality sensors, shore weather stations, and remote sensing images. The original observation data is subjected to time synchronization, spatial registration, quality control, and anomaly processing to obtain the target observation data based on the processed data; The target observation data includes river water level data, flow data, water quality data, meteorological data, and image data.

3. The method for monitoring river water environment according to claim 1, characterized in that, The process of constructing river baseline information based on the observation dataset and using a three-dimensional geometric profile model of the river channel includes: Based on the topographic mapping data and cross-sectional measurement data corresponding to the river channel, a three-dimensional geometric profile model of the river channel is constructed, and the roughness distribution in the three-dimensional geometric profile model is determined, as well as the boundary conditions corresponding to the three-dimensional geometric profile model are defined. The hydrodynamic parameters are determined based on the three-dimensional geometric profile model, the observation dataset, the roughness distribution, and the boundary conditions. The observation dataset, the three-dimensional geometric profile model, the roughness distribution, the boundary conditions, and the hydrodynamic parameters are integrated to construct the river baseline information.

4. The method for monitoring river water environment according to claim 1, characterized in that, The process involves identifying several environmental disturbance events based on the observed dataset, classifying each environmental disturbance event, and processing each environmental disturbance event according to the classification results to generate corresponding real-time correction results and correction suggestions, including: The magnitude of change of the target observation data in the observation dataset is extracted by time window sliding statistics and robust smoothing algorithm; If the change exceeds a preset disturbance threshold, the environmental disturbance event corresponding to the target observation data is identified. The environmental disturbance events are classified to obtain several real-time response events and several events to be corrected. The real-time response events are then corrected in real time to generate the real-time correction results. Calculate the deviation distribution corresponding to each of the events to be corrected, generate each correction entry based on each deviation distribution, adjust each correction entry to obtain several initial correction entries, and construct the correction suggestion based on each initial correction entry; The suddenness of the real-time response event is higher than a preset suddenness threshold and the duration is lower than a preset time threshold, while the influence range of the event to be corrected is higher than a preset influence range threshold and the rate of change is lower than a preset rate threshold.

5. The method for monitoring river water environment according to claim 1, characterized in that, Before filtering the target correction entry from the initial correction entries of the correction proposal, the method further includes: In the current time period, determine the target difference between the latest output time of the correction proposal and the latest update time of the baseline dataset, and determine the absolute value corresponding to the quotient of the target difference and the current time period as the target phase difference; The target state is determined based on the comparison between the target phase difference and the first preset phase difference interval; Accordingly, determining the target state based on the comparison result between the target phase difference and the first preset phase difference interval includes: If the target phase difference is lower than the first preset phase difference interval, the target state is determined to be a preset synchronization state, and the river is divided into zones according to the spatial risk mask of the river, and the risk index and the second preset phase difference interval corresponding to each zone are determined. If the risk index of the partition is greater than a preset risk index threshold and the target phase difference is lower than the second preset phase difference interval, then the target correction entry is selected from the initial correction entries of the correction suggestion to determine the correction entry set based on the target correction entry; If the target phase difference is within the first preset phase difference interval, the target state is determined to be a preset state to be coordinated, and the baseline dataset is stopped from being corrected in the current time period. The water environment of the river is monitored in real time based directly on the baseline dataset and the real-time correction result. If the target phase difference exceeds the first preset phase difference interval, the target state is determined to be a preset frozen state, and the correction of the baseline dataset is prohibited. The water environment of the river is monitored in real time based directly on the baseline dataset and the real-time correction result.

6. The method for monitoring river water environment according to any one of claims 1 to 5, characterized in that, The process of correcting the baseline dataset based on the set of corrected entries includes: Construct a target buffer space and perform a difference operation on the baseline dataset and the set of correction entries to generate a corresponding candidate baseline dataset based on the difference operation results; The candidate baseline dataset is verified according to the mass conservation criterion and the energy conservation criterion. If the verification error is lower than the preset error threshold, the candidate baseline dataset is used as the corrected baseline dataset.

7. The method for monitoring river water environment according to claim 5, characterized in that, Also includes: A decision signal is constructed based on the latest output time of the proposed correction, the latest update time of the baseline dataset, the target phase difference, and the target state, and a corresponding write control table is generated based on the set of correction entries. Based on the monitoring results of the water environment of the river, the judgment signal, the writing to the control table, the real-time correction results, and the corrected baseline dataset, a corresponding feedback signal is generated, and the monitoring process of the water environment of the river is optimized based on the feedback signal.

8. A monitoring device for river water environment, characterized in that, include: An observation dataset construction module is used to collect raw observation data of the river channel, perform data preprocessing on the raw observation data to obtain target observation data, and construct an observation dataset based on the target observation data. The baseline dataset construction module is used to construct river baseline information based on the observation dataset and using a three-dimensional geometric profile model of the river channel, and to construct a baseline dataset based on the river baseline information; the river baseline information includes the river channel cross-sectional morphology, roughness distribution, boundary conditions, and hydrodynamic parameters. The correction suggestion generation module is used to identify several environmental disturbance events based on the observation dataset, classify each environmental disturbance event, and process each environmental disturbance event according to the classification results to generate corresponding real-time correction results and correction suggestions. The environmental disturbance event is either a real-time response event or an event to be corrected. The real-time correction result is the result obtained by correcting the real-time response event. The correction suggestion is a correction suggestion corresponding to the event to be corrected. The water environment monitoring module is used to select target correction items from a number of initial correction items of the correction suggestions, determine a set of correction items based on the target correction items, correct the baseline dataset based on the set of correction items, and monitor the water environment of the river in real time based on the corrected baseline dataset and the real-time correction results.

9. An electronic device, characterized in that, The electronic device includes a processor and a memory; wherein the memory is used to store a computer program, which is loaded and executed by the processor to implement the method for monitoring the river water environment as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store a computer program, which, when executed by a processor, implements the method for monitoring the river water environment as described in any one of claims 1 to 7.

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