An ecological flow regulation system for a water conservancy hub based on digital twinning

Abstract

The application discloses a kind of based on digital twinning water conservancy hub ecological flow regulation system, it is related to intelligent ecological regulation technical field, the system obtains the digital elevation data DEM of riverbed and wetland, geometric profile image and coupling power data by multi-beam sonar, unmanned aerial vehicle remote sensing and sensor group, and realizes synchronization and pretreatment in twin simulation model, forms flow evolution data group and water and sediment power data group.Based on flow evolution data group, construct dynamic connectivity driving force index Dcl to carry out flow driving force evaluation, under the condition that driving force is sufficient, construct comprehensive connectivity determination index Eco to carry out ecological penetration evaluation, and according to the evaluation result, execute corresponding regulation instruction, realize the dynamic regulation of hub discharge flow and long-term maintenance of wetland ecological connectivity.The system can realize real-time monitoring, evaluation and regulation driven by digital twinning under complex water and sediment power conditions, and improve the protection capability of water conservancy hub to wetland ecosystem.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent ecological regulation, in particular to a water conservancy hub ecological flow regulation system based on digital twinning. BACKGROUND

[0002] Digital twinning technology has gradually extended from industrial manufacturing and urban governance to water conservancy and ecological fields in recent years. Its advantage lies in the realization of real-time reproduction and prediction of complex hydrological processes through the bidirectional mapping of virtual models and real systems. In the management of water conservancy hubs, ecological flow regulation has gradually gained attention. Its purpose is to meet the downstream water demand and flood control requirements while ensuring the continuous connectivity and stable succession of river and wetland ecosystems. With further research, the traditional idea of ensuring minimum ecological flow has gradually expanded to wetland ecological penetration regulation, which not only focuses on river inflow, but also takes into account wetland hydrological connectivity, penetration transmission, and sediment dynamics to maintain the integrity and function of the wetland ecosystem.

[0003] At present, there are still deficiencies in the practice of wetland ecological regulation. In most areas, single water level control or average flow indicators are still used as the basis for judgment, ignoring complex factors such as water level dynamics, bed siltation, and permeability changes. This coarse-grained regulation method often leads to the entry of water into the wetland in the short term, but the passage is easily blocked in the long term, and the water exchange efficiency decreases. In addition, the monitoring methods are mainly manual patrol or single-point monitoring, lacking multi-source data fusion and systematic analysis capabilities, making it difficult to dynamically capture the change rules of wetland connectivity. As a result, although the ecological flow is released, the recovery effect of the wetland ecological function is not ideal, and there is a clear disconnection between regulation efficiency and ecological benefits. SUMMARY

[0004] To overcome the deficiencies of the prior art, the present application provides a water conservancy hub ecological flow regulation system based on digital twinning, which solves the problems in the background art.

[0005] To achieve the above purpose, the present application realizes the following technical scheme: a water conservancy hub ecological flow regulation system based on digital twinning, comprising a data mapping module, a model synchronization module, a driving force evaluation module, a connectivity determination module, and a regulation execution module;

[0006] The data mapping module is used to collect digital elevation data DEM, geometric profile images, and coupled dynamic data of the riverbed and wetland respectively according to multi-beam sonar, unmanned aerial vehicle remote sensing equipment, and sensors;

[0007] The model synchronization module is used to receive digital elevation data DEM, geometric profile images, and coupled dynamic data in real time, and construct a terrain point cloud model and pre-process to obtain a flow evolution data set and a water and sediment dynamic data set;

[0008] The driving force evaluation module is configured to construct a dynamic connectivity driving force index Dcl according to the flow evolution data set, and perform flow driving force evaluation with a hydrodynamic triggering limit threshold Ah, and perform coupling resistance analysis when the evaluation is sufficient driving force;

[0009] The connectivity determination module is configured to perform coupling resistance analysis, construct a resistance dissipation index Rdz according to the water and sediment dynamic data set, obtain a comprehensive connectivity determination index Eco after summarizing the dynamic connectivity driving force index Dcl, and perform ecological penetration evaluation with an ecological penetration critical threshold Ae;

[0010] The regulation and control execution module is configured to execute corresponding regulation and control instructions according to the evaluation information.

[0011] Preferably, the data mapping module comprises a terrain acquisition unit and a data acquisition unit.

[0012] The terrain acquisition unit is configured to acquire digital elevation data DEM and geometric profile images of the riverbed and wetland respectively by the multi-beam sonar and unmanned aerial vehicle remote sensing equipment.

[0013] The data acquisition unit is configured to install sensor groups at various positions of the river and wetland, to acquire coupling dynamic data of the wetland and river in real time, and to record the longitude and latitude of each sensor group arrangement position.

[0014] The sensor group comprises a pressure type water level gauge, a pressure type micro water level gauge, a gate orifice flowmeter, a sediment concentration sensor, a multi-beam sonar depth finder, a multi-point buried osmometer, and an acoustic Doppler current profiler.

[0015] The pressure type water level gauge is configured to be installed at the underwater position of 0.5 meters of the river section pier foundation downstream the hub, to acquire the river water level hr in real time.

[0016] The pressure type micro water level gauge is configured to be buried with the top end flush with the wetland bottom mud surface, to acquire the wetland water level hw in real time.

[0017] The gate orifice flowmeter is configured to be arranged at the flood discharge hole water outlet, to acquire the hub discharge flow sl in real time.

[0018] The sediment concentration sensor is configured to be arranged at the underwater position of 0.5 meters of the river into the wetland diversion port, to acquire the sediment concentration cs in real time.

[0019] The multi-beam sonar depth finder is configured to be arranged at the section foundation pile measuring line position of the river and wetland intersection, to acquire the bed surface lifting amount ts in real time.

[0020] The multi-point buried osmometer is configured to be arranged across the river and wetland boundary at the riverbed and wetland intersection, to acquire the riverbed permeability sz in real time.

[0021] The acoustic Doppler flow velocity profiler is used to be arranged at the bottom of the intersection section of the river and the wetland to collect the bed shear stress tb in real time.

[0022] Preferably, the model synchronization module establishes a communication connection between the sensor group, the multi-beam sonar and the unmanned aerial vehicle remote sensing device and the ecological flow regulation system through a wireless network, and the ecological flow regulation system receives the digital elevation data DEM, the geometric profile image and the coupled dynamic data in real time, specifically including a data processing unit and a simulation model construction unit;

[0023] The simulation model construction unit is used to receive the digital elevation data DEM and the geometric profile image of the river and the wetland in real time, perform vectorization processing on the geometric profile image, identify the boundaries of the river and the wetland in the geometric profile image according to the edge detection technology and remove the areas outside the boundaries, and then embed the digital elevation data DEM as a terrain framework basis into the geometric profile image to perform point cloud fusion and generate a terrain point cloud model.

[0024] After obtaining the terrain point cloud model, the coupled dynamic data is synchronized to the corresponding position in the terrain point cloud model according to the labeled latitude and longitude information to form a twin simulation model.

[0025] Preferably, the data processing unit is used to preprocess the coupled dynamic data in the twin simulation model through the ecological flow regulation system to obtain a flow evolution data group and a water-sediment dynamic data group, respectively.

[0026] The preprocessing includes denoising, bias correction, time alignment and normalization processing.

[0027] The denoising is used to remove the noise in the coupled dynamic data through band-pass filtering; the bias correction is used to compensate for the drift of the coupled dynamic data according to the multi-source data cross-comparison method to eliminate the inherent bias and long-term drift of the sensor; the time alignment is used to project the coupled dynamic data with different sampling frequencies onto the same time axis, and linear interpolation is used to fill in the missing points and uneven coupled dynamic data to form a data sequence with uniform time steps; and the normalization processing is used to remove the dimension effect of the coupled dynamic data by the Max-Min maximum and minimum method.

[0028] The flow evolution data group includes the river water level hr, the wetland water level hw and the hub discharge flow sl.

[0029] The water-sediment dynamic data group includes the bed surface uplift amount ts, the riverbed permeability sz, the sediment concentration cs and the bed shear stress tb.

[0030] Preferably, the driving force evaluation module includes a driving force analysis unit and a dynamic evaluation unit.

[0031] The driving force analysis unit is used for data fitting on the flow evolution data set, taking the water level difference between the river water level hr and the wetland water level hw as an energy source, introducing the change rate of the water level difference with time to reflect the dynamic change trend of the water level difference, combining the logarithmic smoothing factor of the hub outflow sl as a denominator for correction, and finally fitting to obtain the dynamic connectivity driving force index Dcl, which is used to quantify the hydrodynamic driving effect generated by the river water level and the wetland water level difference, and reflects the water exchange thrust between the wetland and the river.

[0032] Preferably, the dynamic evaluation unit is used to collect the dynamic connectivity driving force index Dcl within half a year, and calculate the mean value by statistical method, and the mean value is preset as the hydrodynamic trigger limit threshold Ah, and then the dynamic connectivity driving force index Dcl obtained in real time is used for flow driving force evaluation, and the specific evaluation scheme is as follows.

[0033] When the dynamic connectivity driving force index Dcl is less than the hydrodynamic trigger limit threshold Ah, it indicates that the driving force is insufficient, and the wetland has the risk of flow interruption, and at this time, pulse water supplement information is generated.

[0034] When the dynamic connectivity driving force index Dcl is greater than or equal to the hydrodynamic trigger limit threshold Ah, it indicates that the driving force is sufficient, and the driving force can guarantee the wetland flow interruption, at this time, the outflow is kept unchanged, and the coupling resistance analysis is performed.

[0035] Preferably, the connectivity determination module is used to perform coupling resistance analysis when the flow driving force evaluation is sufficient driving force, and specifically includes a penetration analysis unit and a comprehensive analysis unit.

[0036] The penetration analysis unit is used for data fitting on the water and sediment dynamic data set, and the bed surface uplift ts and the river bed permeability sz are used to reflect the cross section reduction effect, the square form nonlinear amplification is used to amplify the deposition resistance, the logarithmic function form of the sediment concentration cs is introduced to reflect the deposition potential at high concentration, and the hyperbolic cosine function form of the ratio of the bed shear stress tb and the critical shear stress tc is used to amplify the deposition and friction effect, and finally the resistance dissipation index Rdz is fitted, which is used to quantify the resistance dissipation degree of the wetland penetration channel, and reflects the comprehensive obstacle level of the wetland connectivity channel.

[0037] Preferably, the comprehensive analysis unit includes a connectivity determination unit and a connectivity evaluation unit.

[0038] The connectivity determination unit is configured to non-linearly couple the dynamic connectivity driving force index Dcl and the resistance dissipation index Rdz, to smooth the antagonistic relationship by an arctangent function based on the ratio of the dynamic connectivity driving force index Dcl and the resistance dissipation index Rdz, and to form a sensitive determination value by applying a sine function to the ratio of the driving force and the square root of the resistance, and finally to fit the comprehensive connectivity determination index Eco to analyze the comprehensive response of the wetland connectivity under the joint action of the driving force and the resistance.

[0039] Preferably, the connectivity evaluation unit is configured to collect the comprehensive connectivity determination index Eco in half a year, calculate the mean value by a statistical method, preset the mean value as the ecological penetration critical threshold Ae, and perform the ecological penetration evaluation on the comprehensive connectivity determination index Eco obtained in real time, and the specific evaluation scheme is as follows.

[0040] When the comprehensive connectivity determination index Eco is less than the ecological penetration critical threshold Ae, it indicates that the connectivity is insufficient, and the river channel and the wetland flow channel are blocked, and at this time, the channel optimization information is generated.

[0041] When the comprehensive connectivity determination index Eco is greater than or equal to the ecological penetration critical threshold Ae, it indicates that the connectivity is sufficient, and the river channel and the wetland flow channel are smooth, and at this time, the smooth monitoring information is generated.

[0042] Preferably, the regulation execution module is configured to execute corresponding regulation instructions according to the evaluation information generated by the flow driving force evaluation and the ecological penetration evaluation, and the specific regulation instructions are as follows.

[0043] Pulse water supplement information: within 6 consecutive hours, increase the hub outflow by 20% for 3 hours, then decrease to the original flow within 3 hours, and perform iterative analysis through the driving force evaluation module, and restore the original flow when the driving force is sufficient;

[0044] Channel optimization information: increase the night period flow by 15% and decrease the daytime period flow by 8%, and perform iterative analysis once every 6 hours through the connectivity determination module, if the connectivity is still insufficient for 3 consecutive iterations, push the alarm information to the ecological monitoring department to remind that the wetland connectivity is insufficient, and require on-site patrol and dredging;

[0045] Smooth monitoring information: maintain the current outflow, and verify the wetland water area every 12 hours through synchronous remote sensing images, if the wetland water area change rate of adjacent two synchronous remote sensing images is not more than 2%, the current strategy is maintained, if the wetland water area change rate of adjacent two synchronous remote sensing images is more than 2%, the following flow regulation strategy is generated.

[0046] Wetland water area expansion more than 2%: reduce the hub outflow by 5%, and continuously monitor, and restore the original hub outflow when the wetland water area recovers to not more than 2%;

[0047] If the area of the wetland water area is reduced by more than 2%, the hub outflow is increased by 5%, and the original hub outflow is restored when the area of the wetland water area is restored to be within the range of not more than 2%.

[0048] The application provides a water conservancy hub ecological flow regulation system based on digital twinning.

[0049] (1) The system data mapping module can not only collect riverbed elevation, wetland geometric profile and water and sediment dynamics parameters through multi-beam sonar, unmanned aerial vehicle remote sensing equipment and sensor groups, but also accurately record the latitude and longitude of the sensor layout position, so that the collected data has spatial positioning properties, forming multi-dimensional original coupled dynamic data. Subsequently, the model synchronization module embeds these data into the point cloud terrain model, generates a high-precision twin simulation environment through vectorization and boundary recognition, and eliminates the deviation of coupled dynamic data by using denoising, bias correction, time alignment and normalization processing. The beneficial effect of this process is that the twin model not only ensures the authenticity and consistency of the data, but also enables managers to observe the dynamic evolution of the river and wetland in the virtual environment in real time, improving the visualization and prediction ability of regulation.

[0050] (2) The system driving force evaluation module establishes a dynamic connectivity driving force index Dcl by combining the river water level and wetland water level difference and its change rate in the flow evolution data set, and the correction of the hub outflow, effectively quantifies the energy source of wetland water replenishment, and performs flow driving force evaluation with the water dynamic trigger threshold Ah. When the flow driving force evaluation is sufficient, the coupling resistance analysis is performed, and the connectivity determination module is used to perform the coupling resistance analysis, which further considers the resistance factor, constructs the resistance dissipation index Rdz through the bed surface lifting amount ts, riverbed permeability sz, sediment concentration cs and bottom bed shear stress tb in the water and sediment dynamic data set, and then couples with the dynamic connectivity driving force index Dcl to generate the comprehensive connectivity determination index Eco, and performs ecological penetration evaluation with the ecological penetration critical threshold Ae. The beneficial effect of this double evaluation mechanism is that it can scientifically identify whether the insufficient connectivity of the wetland is caused by insufficient driving force or excessive resistance, avoiding misjudgment caused by a single index; and through nonlinear function processing, it avoids extreme value interference and enhances the sensitivity of the system in the critical state, thereby providing a scientific and reliable basis for the development of ecological water replenishment and dredging measures.

[0051] (3) The system regulation execution module converts the evaluation results into specific operation instructions, forming a closed-loop mechanism of "evaluation, regulation, and re-evaluation". When the driving force is insufficient, the system can timely trigger pulse water replenishment to ensure continuous flow in the wetland. When the connectivity is insufficient, structural regulation such as increasing the flow at night and moderately reducing the flow during the day is used to reduce the impact on downstream water resources. When the flow is sufficient, the system maintains stable output and combines remote sensing monitoring to dynamically verify the wetland water area, preventing water resource waste or wetland shrinkage. The beneficial effects of this mechanism are reflected in the following aspects: not only can it quickly respond in emergency situations, but also can gradually optimize the regulation strategy through iterative correction in long-term operation, taking into account the ecological safety of the wetland and the efficient use of water resources, and truly realizing intelligent scheduling of ecological flow under the digital twin driving. BRIEF DESCRIPTION OF DRAWINGS

[0052] Figure 1 A flowchart of a water conservancy hub ecological flow regulation system based on digital twinning is provided.

[0053] Figure 2 A schematic diagram of the operation principle of a water conservancy hub ecological flow regulation system based on digital twinning is provided. DETAILED DESCRIPTION

[0054] The technical solutions in the embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0055] Example 1

[0056] Please refer to Figure 1 The present application provides a water conservancy hub ecological flow regulation system based on digital twinning. To achieve the above purpose, the present application is implemented by the following technical solutions: including a data mapping module, a model synchronization module, a driving force evaluation module, a connectivity determination module, and a regulation execution module.

[0057] The data mapping module is used to collect digital elevation data DEM, geometric profile images, and coupled dynamic data of riverbeds and wetlands respectively from multi-beam sonar, unmanned aerial vehicle remote sensing equipment, and sensor groups.

[0058] The model synchronization module is used to receive digital elevation data DEM, geometric profile images, and coupled dynamic data in real time, and construct a terrain point cloud model and pre-process to obtain a flow evolution data set and a water and sediment dynamic data set.

[0059] The driving force evaluation module is configured to construct a dynamic connectivity driving force index Dcl according to the flow evolution data set, to perform flow driving force evaluation with a hydrodynamic triggering limit threshold Ah, and to perform coupling resistance analysis when the evaluation result is that the driving force is sufficient;

[0060] The connectivity determination module is configured to perform coupling resistance analysis, to construct a resistance dissipation index Rdz according to the water and sediment dynamic data set, to obtain a comprehensive connectivity determination index Eco after the dynamic connectivity driving force index Dcl is summarized, and to perform ecological penetration evaluation with an ecological penetration critical threshold Ae.

[0061] The regulation execution module is configured to perform corresponding regulation instructions according to the evaluation information.

[0062] In this embodiment, through the combination of the data mapping module and the model synchronization module, multi-dimensional information holographic acquisition and digital twin modeling of riverbed and wetland are realized. The data mapping module can simultaneously obtain digital elevation data DEM, geometric profile images and coupled dynamic data according to multi-beam sonar, unmanned aerial vehicle remote sensing equipment and sensor groups. The model synchronization module embeds these data into the point cloud terrain model, generates a high-precision twin simulation environment through vectorization and boundary recognition, and completes preprocessing such as denoising, bias correction and time alignment in the twin model, so that the real hydrology and terrain state are mapped with high fidelity in the virtual model. The completion of this task enables the evolution process of the river and the wetland to be grasped in real time in the digital environment, avoiding the data fragmentation and delay caused by traditional dependence on cross-section monitoring or manual investigation methods, thereby achieving the purpose of establishing a dynamic, continuous and visual ecological hydrology monitoring. Compared with the prior art, the system significantly improves the data integrity and real-time performance, providing a more solid foundation for subsequent flow regulation. The driving force evaluation module is used to construct a dynamic connectivity driving force index Dcl according to the flow evolution data group, which can quantitatively evaluate the driving ability of water level difference and flow to wetland water replenishment in real time, and evaluate the flow driving force with the water dynamic triggering threshold Ah. The connectivity determination module is used to construct a resistance dissipation index Rdz according to the water and sediment dynamic data group when the flow driving force evaluation is sufficient, and then obtain a comprehensive connectivity determination index Eco by combining the dynamic connectivity driving force index Dcl, and finally evaluate the ecological connectivity with the ecological penetration critical threshold Ae. The system comprehensively reveals the restriction of riverbed siltation, permeability, sediment concentration and friction on wetland connectivity. Compared with the prior art which only relies on single flow regulation to judge the effect of wetland water replenishment, the system can identify different causes of insufficient driving force and excessive resistance at the same time, thereby avoiding misjudgment and achieving more scientific and comprehensive ecological connectivity evaluation. The regulation execution module converts the evaluation results into specific scheduling instructions, forming a closed-loop link of data, modeling, evaluation and execution. When the driving force is insufficient, pulse water replenishment can be triggered to prevent flow interruption; when the connectivity is blocked, time-optimized flow regulation is performed; and when the connectivity is sufficient, the stable output is maintained and the change of wetland water area is verified by remote sensing. Compared with traditional static scheduling, the system realizes dynamic adaptation and iterative correction, significantly improving the flexibility and accuracy of regulation. The beneficial effects are that it not only guarantees the connectivity and ecological safety of the hydrological process of the wetland, but also avoids unnecessary waste of water resources, thereby achieving a win-win between water resource regulation and ecological protection.

[0063] Embodiment 2

[0064] Please refer to Figure 1 and Figure 2 , specifically: the data mapping module includes a terrain acquisition unit and a data acquisition unit;

[0065] The terrain acquisition unit is used to acquire digital elevation data DEM and geometric profile images of the riverbed and wetland respectively according to the multi-beam sonar and the unmanned aerial vehicle remote sensing device;

[0066] The data acquisition unit is used to install sensor groups at positions of the river channel and the wetland, acquire coupling dynamic data of the wetland and the river channel in real time, and record the longitude and latitude of each sensor group arrangement position;

[0067] The sensor groups include a pressure type water level gauge, a pressure type micro water level gauge, a gate orifice flowmeter, a sediment concentration sensor, a multi-beam sonar depth finder, a multi-point buried osmometer and an acoustic Doppler current profiler.

[0068] The pressure type water level gauge is used to be installed at a position 0.5 meters underwater at a pier foundation of a section of the river channel downstream of the hub, and is used to acquire a river water level hr in real time, which represents a real-time water level height of the river channel.

[0069] The pressure type micro water level gauge is used to be buried with a top end flush with a mud surface of the bottom of the wetland, and is used to acquire a wetland water level hw in real time, which represents a real-time water level height of the wetland.

[0070] The gate orifice flowmeter is used to be arranged at a water outlet of a flood discharge hole, and is used to acquire a hub discharge flow sl in real time, which represents a real-time discharge flow under hub scheduling.

[0071] The sediment concentration sensor is used to be arranged at a position 0.5 meters underwater at a river channel wetland diversion port, and is used to acquire a sediment concentration cs in real time, which means that a large amount of sand indicates a strong sedimentation potential.

[0072] The multi-beam sonar depth finder is used to be arranged at a foundation pile measuring line position of a section of a river channel and wetland intersection, and is used to acquire a bed surface lifting amount ts in real time, which is a bed surface elevation lifting amount at the river channel and wetland intersection position.

[0073] The multi-point buried osmometer is used to be arranged at a riverbed and wetland intersection across a river channel and wetland boundary, and is used to acquire a riverbed permeability sz in real time, which represents a transverse shrinkage rate of the river channel and the channel, affecting whether the water flow can smoothly diverge into the wetland.

[0074] The acoustic Doppler current profiler is used to be arranged at the bottom of a river channel and wetland intersection section, and is used to acquire a bottom bed shear stress tb in real time, which is a frictional effect of the water flow on the riverbed.

[0075] In this embodiment, the terrain acquisition unit obtains the digital elevation data DEM and geometric profile image of the riverbed and wetland through the multi-beam sonar and unmanned aerial vehicle remote sensing equipment, and constructs a terrain basic framework; the data acquisition unit arranges pressure type water level gauges, pressure type micro water level gauges, gate orifice flowmeters, sediment concentration sensors, multi-beam sonar depth sounders, multi-point buried osmometers and acoustic Doppler current profilers and other multi-source sensors at key positions of the river and wetland, and real-time acquisition of the coupling dynamic data of the riverbed and wetland is realized, and accurate positioning is realized in combination with the latitude and longitude information, realizing the double mapping of the terrain and the hydrodynamic process. Through the above arrangement and acquisition, not only the water-sediment exchange and connectivity state of the downstream river and wetland of the hub can be comprehensively reflected, avoiding the defects of insufficient information and lack of spatial correlation of traditional single-point monitoring, but also the twin model has real-time, spatial integrity and dynamic consistency, thereby providing high-precision data support for subsequent driving force evaluation and connectivity determination, achieving the purpose of improving the ecological flow regulation precision and the wetland connectivity guarantee capability, and realizing the significant improvement of ecological protection and efficient use of water resources.

[0076] Embodiment 3

[0077] Please refer to Figure 1 and Figure 2 , in detail: the model synchronization module establishes a communication connection between the sensor group, the multi-beam sonar and the unmanned aerial vehicle remote sensing equipment and the ecological flow regulation system through a wireless network, and the ecological flow regulation system receives the digital elevation data DEM, the geometric profile image and the coupling dynamic data in real time, specifically including a data processing unit and a simulation model construction unit;

[0078] The simulation model construction unit is used for real-time receiving of the digital elevation data DEM and the geometric profile image of the river and the wetland, vectorization processing of the geometric profile image, identification of the river and the wetland boundary in the geometric profile image according to the edge detection technology and elimination of the area outside the boundary, and then embedding the digital elevation data DEM as a terrain framework basis into the geometric profile image for point cloud fusion to generate a terrain point cloud model;

[0079] After obtaining the terrain point cloud model, the coupling dynamic data is synchronized to the corresponding position in the terrain point cloud model according to the labeled latitude and longitude information to form a twin simulation model.

[0080] The data processing unit is used for pre-processing of the coupling dynamic data in the twin simulation model through the ecological flow regulation system, and respectively obtaining a flow evolution data group and a water-sediment dynamic data group;

[0081] The preprocessing includes denoising, bias correction, time alignment and normalization processing;

[0082] The denoising is used for removing noise influence in the coupled dynamic data by band-pass filtering; the bias correction compensates for drift of the coupled dynamic data according to a multi-source data cross comparison method, and eliminates inherent bias and long-term drift of the sensor; the time alignment is used for uniformly projecting coupled dynamic data of different sampling frequencies to the same time axis, and linear interpolation is used to fill in missing points and uneven coupled dynamic data to form a data sequence with uniform time steps; the normalization processing removes the dimensional influence of the coupled dynamic data by the Max-Min maximum and minimum method.

[0083] The flow evolution data set includes river water level hr, wetland water level hw and hub outflow sl;

[0084] The water and sediment dynamic data set includes bed surface uplift ts, river bed permeability sz, sediment concentration cs and bed shear stress tb.

[0085] In this embodiment, the model synchronization module establishes wireless communication between the sensor group, multi-beam sonar and unmanned aerial vehicle remote sensing equipment and the ecological flow regulation platform, realizes real-time access of digital elevation data DEM, geometric profile image and coupled dynamic data; in the simulation model construction unit, the geometric profile image is processed by vectorization and edge detection, and then point cloud fusion is performed with the digital elevation data DEM to generate a fine terrain point cloud model, and the coupled dynamic data is embedded in the model combined with the sensor labeled latitude and longitude information to form a high-precision twin simulation model; then the data processing unit performs band-pass filtering denoising, multi-source cross comparison bias correction, uniform time axis projection and linear interpolation time alignment processing on the coupled dynamic data in the twin model, and eliminates the dimensional influence by the maximum and minimum normalization, so as to obtain the flow evolution data set including river water level hr, wetland water level hw and hub outflow sl, and the water and sediment dynamic data set including bed surface uplift ts, river bed permeability sz, sediment concentration cs and bed shear stress tb. This embodiment realizes accurate mapping and dynamic modeling of the water dynamic process of the river and the wetland. Compared with the traditional method of relying on single-point hydrological monitoring, it can more comprehensively, real-time and efficiently reflect the water dynamic and sediment evolution characteristics, thereby providing high-quality input data for subsequent driving force evaluation and connectivity analysis, achieving the purpose of improving the accuracy and reliability of ecological flow regulation, and further significantly enhancing the protection of wetland connectivity and the efficiency of water resource utilization.

[0086] Embodiment 4

[0087] Please refer to Figure 1 and Figure 2 , specifically: the driving force evaluation module includes a driving force analysis unit and a dynamic evaluation unit;

[0088] The driving force analysis unit is used for data fitting on the flow evolution data set, taking the water level difference of the river water level hr and the wetland water level hw as an energy source, introducing the change rate of the water level difference with time to reflect the dynamic change trend of the water level difference, combining the logarithmic smoothing factor of the hub outflow sl as a denominator for correction, and finally fitting to obtain the dynamic connection driving force index Dcl, which is used to quantify the water dynamic driving effect generated by the water level difference between the river and the wetland, and reflects the water exchange thrust between the wetland and the river, and the specific formula is: , wherein ln represents a logarithmic function, represents a first derivative operator, hr(t)-hw(t) represents the difference between the river water level and the wetland water level, and represents the instantaneous water energy difference, that is, the direct driving force of water exchange, represents the time change rate of the water level difference, reflecting whether the water level difference tends to expand or shrink, represents the adjustment effect of the hub outflow on the driving force, which is avoided by logarithm and square root under the condition of small flow.

[0089] The dynamic evaluation unit is used for collecting the dynamic connection driving force index Dcl in half a year, and calculating the mean value by statistical method, and the mean value is preset as the water dynamic trigger limit threshold Ah, and then the dynamic connection driving force index Dcl is obtained in real time to evaluate the flow driving force, and the specific evaluation scheme is as follows.

[0090] When the dynamic connection driving force index Dcl is less than the water dynamic trigger limit threshold Ah, it indicates that the driving force is insufficient, and the wetland has the risk of flow interruption, and at this time, the pulse water supplement information is generated;

[0091] When the dynamic connection driving force index Dcl is greater than or equal to the water dynamic trigger limit threshold Ah, it indicates that the driving force is sufficient, and the driving force can guarantee the wetland flow interruption, at this time, the outflow is kept unchanged, and the coupling resistance analysis is performed.

[0092] In this embodiment, the driving force evaluation module is composed of the driving force analysis unit and the dynamic evaluation unit: first, the driving force analysis unit takes the difference between the river water level hr and the wetland water level hw as the energy source, and combines the change rate of the water level difference with time and the logarithmic smoothing factor of the hub outflow sl for correction, and fits to obtain the dynamic connection driving force index Dcl, which is used to quantify the water dynamic driving effect generated by the water level difference, so as to accurately reflect the water exchange thrust between the wetland and the river.

[0093] The formula logic, derivation basis and significance, the core idea of the formula is derived from the energy equation of fluid mechanics and the water level difference driving principle of hydrodynamics. In the river and the wetland, the direct driving force of water exchange comes from the water level difference hr(t)-hw(t), which is the most basic driving force in classical hydrology to describe seepage and connected flow. The change rate of the water level difference with time The introduction is based on unsteady hydrodynamics, and the water power depends not only on the instantaneous water level difference, but also on the trend of change, which enables the formula to capture the critical state that the wetland may soon be disconnected or quickly connected; the form of the denominator part The form of the denominator part draws on the dispatch smoothing correction method in water conservancy engineering, in which the logarithm and square root operation of the flow are used to avoid the thrust being artificially high at small flow, which belongs to a nonlinear normalization and stabilization processing method. The square root further smoothes the flow correction, making the flow correction have a marginal decreasing effect, which is consistent with the actual situation of water conservancy; the numerator provides the size and trend of the driving force, and the denominator provides the dispatch correction and stabilization, so that the dynamic connectivity driving force index Dcl can maintain a reasonable numerical range under various flow and water level conditions, avoiding the false appearance of an excessively high index under small flow conditions under the traditional energy difference driving, while maintaining the sensitivity to the real trend of water power.

[0094] The dynamic evaluation unit collects the dynamic connectivity driving force index Dcl within half a year in long-term operation, calculates the average value and sets it as the water power trigger limit threshold Ah, and then evaluates the flow driving force with the real-time dynamic connectivity driving force index Dcl, to realize the judgment of the wetland disconnection risk and the sufficiency of the driving force, and automatically generate pulse water supplement information or maintain the outflow and enter the resistance analysis link. Through the above implementation mode, the system realizes the dynamic quantification and threshold determination of the wetland connectivity driving force, which not only overcomes the limitations of relying on single-point water level or empirical dispatch in traditional technology, but also significantly improves the scientificity and forward-looking nature of the water supplement strategy, ultimately ensuring the stability of the wetland continuous flow and ecological connectivity, achieving the dual effects of ecological protection and efficient use of water resources.

[0095] Embodiment 5

[0096] Please refer to Figure 1 and Figure 2 , specifically: the connectivity determination module is used to perform coupled resistance analysis when the flow driving force evaluation is sufficient driving force, specifically including a penetration analysis unit and a comprehensive analysis unit;

[0097] The penetration analysis unit is used to perform data fitting on the water and sediment power data set, and the bed surface uplift ts and the river bed permeability sz jointly reflect the cross-section reduction effect, the square form nonlinear amplification of siltation resistance is used to amplify the deposition and friction effect, and the logarithmic function form of the sediment concentration cs is introduced to reflect the deposition potential at high concentration, and the hyperbolic cosine function form of the ratio of the bed shear stress tb to the critical shear stress tc is used to amplify the deposition and friction effect, and finally the resistance dissipation index Rdz is fitted to quantify the resistance dissipation degree of the wetland penetration channel, and to reflect the comprehensive obstacle level of the wetland connectivity channel, and the specific formula is: , wherein ln represents a logarithmic function, cosh represents a hyperbolic cosine function, tc represents a critical shear stress of bed sand particles being carried by the water flow under standard conditions, (ts*sz) 2 The product of the bed surface lifting amount and the river bed permeability represents a nonlinear amplification effect, highlights the severity of the superposition of deposition and river bed permeability, and the square root amplifies the sensitivity to resistance, ln(1+cs) represents the influence of sediment concentration on resistance, and the logarithmic function nonlinearly amplifies the deposition effect to avoid numerical virtual high at low concentration, , which represents that the resistance is composed of geometric resistance and dynamic resistance, and the resistance increases significantly through the hyperbolic cosine function when the friction resistance approaches and exceeds the critical value.

[0098] The comprehensive analysis unit includes a connectivity determination unit and a connectivity evaluation unit;

[0099] The connectivity determination unit is used for nonlinearly coupling the dynamic connectivity driving force index Dcl and the resistance dissipation index Rdz, and smoothing the antagonistic relationship through the arctangent function based on the ratio of the dynamic connectivity driving force index Dcl and the resistance dissipation index Rdz, avoiding distortion of the result caused by extreme values, and at the same time, the ratio of the driving force and the square root of the resistance is subjected to the sine function to form a sensitive determination value, enhancing the sensitivity in the critical state, and finally fitting the comprehensive connectivity determination index Eco, analyzing the comprehensive response of the wetland connectivity under the joint action of the driving force and the resistance, and the specific formula is:

[0100] , wherein arctan represents an arctangent function conversion, and sin represents a sine function, , which is used to reflect the antagonistic relationship between the driving force and the resistance, and the arctangent function is added to compress the ratio value, avoiding infinite expansion of extreme data, The square root of the resistance is used to weaken the extreme resistance, avoiding excessive amplification in the case of small resistance, and the sine function is added to enhance the sensitivity, which is more sensitive in the critical state.

[0101] The connectivity evaluation unit is used for collecting the comprehensive connectivity determination index Eco in half a year, and calculating the mean value through statistical method, and the mean value is preset as the ecological penetration critical threshold Ae, and then the ecological penetration is evaluated by comparing the comprehensive connectivity determination index Eco obtained in real time with the comprehensive connectivity determination index Eco, and the specific evaluation scheme is as follows:

[0102] When the comprehensive connectivity determination index Eco is less than the ecological penetration critical threshold Ae, it indicates that the connectivity is insufficient, and the river channel and the wetland flow channel are hindered, and at this time, the channel optimization information is generated;

[0103] When the comprehensive connectivity determination index Eco is greater than or equal to the ecological penetration critical threshold Ae, it indicates that the connectivity is sufficient, and the river channel and the wetland flow channel are smooth, and at this time, the smooth monitoring information is generated.

[0104] In this embodiment, the connectivity determination module starts the coupling resistance analysis under the condition that the flow driving force evaluation is sufficient driving force. The penetration analysis unit comprehensively constructs the resistance dissipation index Rdz through the nonlinear superposition effect of the bed surface uplift amount ts and the riverbed permeability sz in the water and sediment dynamic data set, the logarithmic deposition potential of the sediment concentration cs, and the hyperbolic cosine amplification effect of the ratio of the bed shear stress tb to the critical shear stress tc, thereby truly reflecting the resistance level of the wetland channel under the multiple effects of silting, penetration, and friction.

[0105] Formula logic, derivation basis, and significance, (ts*sz) 2 Indicates the coupling effect of riverbed silting ts and permeation channel reduction sz. The product is squared to amplify the geometric obstruction effect. It is derived from hydraulics and seepage mechanics. The riverbed uplift amount ts reflects the geometric change of bed sedimentation, and the permeability sz reflects the channel capacity of water penetration through the riverbed. The multiplication of the two obtains the strength of the cross-section reduction effect, which is then nonlinearly amplified by squaring to highlight the superposition severity of silting and penetration, in line with the empirical law of "resistance and geometric change nonlinear enhancement" in actual hydrodynamics. ln(1+cs) reflects the influence of sediment concentration cs on resistance. The logarithmic form makes the change gentle at low concentrations and the resistance effect sharply increases at high concentrations. It is derived from sediment dynamics. The influence of sediment concentration cs on resistance often shows nonlinear growth. The form of ln(1+cs) is a reference to the information entropy formula and the logarithmic modification of fluid resistance, which ensures numerical stability at low concentrations and reflects the nonlinear amplification of sediment potential at high concentrations, in line with the characteristics of sediment potential. Reflects the bed surface friction effect and is derived from the critical shear stress theory. When the bed surface shear stress tb approaches or exceeds the critical shear stress tc, the bed sand particles start to move, and the coupling effect of friction and sedimentation significantly increases. This can smoothly amplify the resistance effect when approaching or exceeding the threshold, matches the critical shear stress theory, and can naturally simulate the rapid increase in resistance when approaching the threshold. Indicates the coupling of sedimentation resistance and friction resistance, reflects the double resistance effect of high sediment concentration and friction critical amplification, and uses the product form to strengthen the two effects.

[0106] The comprehensive analysis unit performs nonlinear coupling between the dynamic connectivity driving force index Dcl and the resistance dissipation index Rdz, introduces the composite operation of the inverse tangent function and the sine function, obtains the comprehensive connectivity determination index Eco, and realizes the smoothing and sensitization of the description of the antagonistic relationship between driving force and resistance.

[0107] Formula logic, derivation basis, and significance, The ratio of the dynamic compression connectivity driving force index Dcl and the resistance dissipation index Rdz is smoothed to avoid infinite expansion in extreme cases, the introduction of the arctangent function arctan comes from the compression characteristics of the mathematical function mapping, and the arctangent function arctan asymptotically approaches ±π / 2 when |x| tends to ∞, which is used to avoid the problem of infinite expansion caused by too large ratio, and the idea comes from the common compression function in mathematics, which is widely used in signal processing and stable calculation, and the denominator plus 1 avoids infinite when the resistance approaches zero, ensuring stable calculation; The sensitivity in the critical state is enhanced by the sine function, the introduction of the sine function sin is inspired by the signal amplification and sensitivity adjustment theory, sin(x) changes fast in the critical interval and slow in the stable interval, which is suitable for amplifying the sensitivity to the change near the threshold, in physics, similar methods are often used for resonance amplification or modification of nonlinear response curves, and is used to weaken the extreme resistance effect, the denominator plus 1 avoids infinite when the resistance approaches zero, ensuring stable calculation. Adding and logically forms a combination of "stability constraint plus sensitivity enhancement", which meets the goal of avoiding misjudgment and capturing risks in regulation.

[0108] The connectivity evaluation unit sets the ecological penetration critical threshold Ae based on the six-month statistical mean value, evaluates the ecological penetration of the comprehensive connectivity determination index Eco obtained in real time, and automatically generates channel optimization or stable monitoring information. Through this implementation, the system can not only accurately identify wetland connectivity obstacles and smoothness under complex water and sediment conditions, but also solve the problem that the existing technology relies too much on a single hydrological index and is not sensitive to critical states, realize dynamic quantification and intelligent early warning of ecological connectivity, and effectively improve the scientificity of water conservancy hub regulation, the pertinence of ecological protection, and the stability of the wetland connection process.

[0109] Embodiment 6

[0110] Please refer to Figure 1 and Figure 2 , specifically: the regulation execution module is used to execute the corresponding regulation instructions according to the evaluation information generated by the flow driving force evaluation and ecological penetration evaluation, specifically as follows;

[0111] Pulse water replenishment information: within 6 consecutive hours, increase the hub outflow by 20% for 3 hours, then decrease to the original flow within 3 hours, and iterate analysis through the driving force evaluation module, and restore the original flow when the driving force is sufficient;

[0112] Channel optimization information: increase 15% night period traffic, reduce 8% day period traffic, and perform iterative analysis through the connectivity determination module every 6 hours, if the connectivity is still insufficient for 3 consecutive iterations, push the alarm information to the ecological monitoring department, remind that the wetland connectivity is insufficient, and require on-site patrol and dredging;

[0113] Smooth monitoring information: maintain the current discharge flow, verify the wetland water area through synchronous remote sensing images every 12 hours, if the wetland water area change rate of adjacent two synchronous remote sensing images is not more than 2%, the current strategy is maintained, if it exceeds 2%, the following flow adjustment strategy is generated;

[0114] Wetland water area expansion more than 2%: reduce the hub discharge flow by 5%, and continuously monitor, when the wetland water area recovers within the range of not more than 2%, restore the original hub discharge flow;

[0115] Wetland water area reduction more than 2%: increase the hub discharge flow by 5%, and continuously monitor, when the wetland water area recovers within the range of not more than 2%, restore the original hub discharge flow.

[0116] In this embodiment, the control execution module realizes dynamic management and closed-loop control of the water conservancy hub discharge flow by converting the flow driving force evaluation and ecological connectivity evaluation results into hierarchical control instructions: when the driving force is insufficient, trigger pulse water replenishment, quickly increase and gradually reduce the flow to ensure continuous flow of the wetland; when the connectivity is blocked, differential regulation of night and day flow is combined with iterative analysis to ensure timely alarm and manual intervention when improvement is not significant; when the connectivity is sufficient, maintain smooth monitoring, and adjust the flow according to the dynamic change of the wetland water area through remote sensing images, automatically respond to the deviation of too large or too small area. The purpose of this implementation is to ensure the connectivity and stability of the wetland ecosystem through automatic and intelligent scheduling strategy, and to avoid waste of water resources. Compared with the existing scheduling method relying on manual experience and static threshold, the system can realize real-time iterative optimization under the driving of multiple source data, significantly improve the accuracy, flexibility and ecological protection efficiency of regulation, and further promote the synchronous improvement of water resource utilization efficiency and ecological safety level.

[0117] Although embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the application, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A water conservancy hub ecological flow regulation system based on digital twin, characterized in that: It includes a data mapping module, a model synchronization module, a driving force evaluation module, a connectivity determination module, and a regulation execution module; The data mapping module is used to collect digital elevation data (DEM), geometric contour images, and coupled dynamic data of riverbeds and wetlands based on multibeam sonar, UAV remote sensing equipment, and sensor groups, respectively. The model synchronization module is used to receive digital elevation data (DEM), geometric contour images, and coupled dynamic data in real time, and to construct a terrain point cloud model and perform preprocessing to obtain flow evolution data sets and hydro-sediment dynamic data sets. The flow evolution data set includes river water level hr, wetland water level hw, and reservoir outflow sl; The hydrodynamic data set includes bed uplift ts, riverbed permeability sz, sediment concentration cs, and bed shear stress tb; The driving force assessment module is used to construct a dynamic connectivity driving force index Dcl based on the flow evolution data set, and to assess the flow driving force with the hydrodynamic triggering threshold Ah. When the assessment indicates that the driving force is sufficient, coupling resistance analysis is performed. The specific formula for the dynamic connectivity driving force index Dcl is: In the formula, ln represents the logarithmic function. The operator represents the first derivative. The connectivity determination module is used to perform coupling resistance analysis. It constructs a resistance dissipation index Rdz based on the hydro-sediment dynamic data set, and obtains a comprehensive connectivity determination index Eco by summing it with the dynamic connectivity driving force index Dcl. Then, it performs ecological connectivity assessment by comparing it with the ecological connectivity critical threshold Ae. The specific formula for the resistance dissipation index Rdz is: In the formula, ln represents the logarithmic function, cosh represents the hyperbolic cosine function, and tc represents the critical shear stress when bed sand particles are carried up by water flow under standard conditions. The specific formula for the comprehensive connectivity index Eco is: In the formula, arctan represents the arctangent function transformation, and sin represents the sine function; The control execution module is used to execute corresponding control commands based on the evaluation information.

2. The water conservancy hub ecological flow regulation system based on digital twin as described in claim 1, characterized in that: The data mapping module includes a terrain acquisition unit and a data acquisition unit; The terrain acquisition unit is used to acquire digital elevation data (DEM) and geometric contour images of riverbeds and wetlands respectively using multibeam sonar and UAV remote sensing equipment. The data acquisition unit is used to install sensor groups at various locations in the river and wetland to collect coupled dynamic data of the wetland and river in real time, and record the latitude and longitude of the location of each sensor group. The sensor group includes a pressure level gauge, a pressure micro level gauge, a gate orifice flow meter, a sand concentration sensor, a multibeam sonar depth sounder, a multi-point buried piezometer, and an acoustic Doppler velocity profiler. The pressure-type water level gauge is installed 0.5 meters underwater at the pier foundation of the river section downstream of the hub to collect the river water level (hr) in real time. The pressure-type micro water level gauge is buried flush with the mud surface at the bottom of the wetland to collect the wetland water level hw in real time. The gate orifice flow meter is used to be installed at the outlet of the flood discharge hole to collect the outflow flow sl of the hub in real time. The sediment concentration sensor is installed at a depth of 0.5m underwater at the river's inlet into the wetland to collect sediment concentration (cs) in real time. The multibeam sonar depth sounder is used to measure the location of the foundation piles at the cross-section where the river and wetland meet, and to collect the bed surface uplift ts in real time. The multi-point buried piezometer is used to be deployed across the river and wetland boundaries at the junction of the riverbed and wetland to collect the riverbed permeability sz in real time. The acoustic Doppler current profiler is deployed at the bottom of the section where the river and wetland meet to collect the bed shear stress tb in real time.

3. The water conservancy hub ecological flow regulation system based on digital twin as described in claim 2, characterized in that: The model synchronization module establishes a communication connection between the sensor group, multibeam sonar, and UAV remote sensing equipment and the ecological flow control system through a wireless network. The ecological flow control system receives digital elevation data (DEM), geometric contour images, and coupled dynamic data in real time. Specifically, it includes a data processing unit and a simulation model construction unit. The simulation model building unit is used to receive digital elevation data (DEM) and geometric contour images of rivers and wetlands in real time. After vectorizing the geometric contour images, the boundary of the river and wetlands in the geometric contour images is identified by edge detection technology and the area outside the boundary is removed. Then, the digital elevation data (DEM) is used as the basis of the terrain framework and embedded into the geometric contour images for point cloud fusion to generate a terrain point cloud model. After acquiring the terrain point cloud model, the coupled dynamic data is synchronized to the corresponding position in the terrain point cloud model according to the labeled latitude and longitude information to form a twin simulation model.

4. The water conservancy hub ecological flow regulation system based on digital twin as described in claim 3, characterized in that: The data processing unit is used to preprocess the coupled dynamic data in the twin simulation model through the ecological flow regulation system to obtain the flow evolution data set and the water and sediment dynamic data set respectively. The preprocessing includes noise reduction, bias correction, time alignment, and normalization. The denoising is used to remove noise from the coupled dynamic data through bandpass filtering; Bias correction compensates for the drift of coupled dynamic data based on the multi-source data cross-comparison method, eliminating inherent sensor bias and long-term drift; time alignment is used to project coupled dynamic data with different sampling frequencies onto the same time axis, and linear interpolation is used to fill in missing points and uneven coupled dynamic data to form a data sequence with a unified time step; normalization is performed to remove the dimensional influence of coupled dynamic data through the Max-Min method.

5. A water conservancy hub ecological flow regulation system based on digital twins according to claim 4, characterized in that: The driving force evaluation module includes a driving force analysis unit and a dynamic evaluation unit; The driving force analysis unit is used to fit the flow evolution data set. The water level difference between the river water level hr and the wetland water level hw is used as the energy source. At the same time, the rate of change of the water level difference over time is introduced to reflect the dynamic change trend of the water level difference. The logarithmic smoothing factor of the outflow sl of the hub is used as the denominator for correction. Finally, the dynamic connectivity driving force index Dcl is obtained by fitting, which is used to quantify the hydrodynamic driving effect generated by the difference between the river water level and the wetland water level, and reflect the water exchange thrust between the wetland and the river.

6. A water conservancy hub ecological flow regulation system based on digital twin as described in claim 5, characterized in that: The dynamic evaluation unit is used to collect the dynamic connectivity driving force index Dcl within six months, calculate the mean value through statistical methods, preset the mean value as the hydrodynamic trigger limit threshold Ah, and then evaluate the flow driving force with the dynamic connectivity driving force index Dcl acquired in real time. The specific evaluation scheme is as follows. When the dynamic connectivity driving force index Dcl < hydrodynamic trigger threshold Ah, it indicates insufficient driving force and the wetland is at risk of flow interruption. At this time, pulse water replenishment information is generated. When the dynamic connectivity driving force index Dcl is greater than or equal to the hydrodynamic trigger threshold Ah, it indicates that the driving force is sufficient to ensure the wetland flow interruption. At this time, the outflow rate remains unchanged, and coupling resistance analysis is performed.

7. A water conservancy hub ecological flow regulation system based on digital twins according to claim 6, characterized in that: The connectivity determination module is used to perform coupling resistance analysis when the flow driving force is assessed as sufficient, and specifically includes a penetration analysis unit and a comprehensive analysis unit. The permeability analysis unit is used to fit the hydrodynamic data set. Based on the fact that the bed uplift ts and the riverbed permeability sz jointly reflect the cross-sectional reduction effect, the sedimentation resistance is nonlinearly amplified through a square form. By introducing the logarithmic function form of the sediment concentration cs, the deposition potential at high concentrations is reflected. Combined with the hyperbolic cosine function form of the ratio of bottom shear stress tb to critical shear stress tc, the deposition and friction effects are amplified. Finally, the resistance dissipation index Rdz is fitted to quantify the resistance dissipation degree of wetland infiltration channels and reflect the comprehensive obstacle level of the unobstructedness of wetland connectivity channels.

8. A water conservancy hub ecological flow regulation system based on digital twins according to claim 7, characterized in that: The comprehensive analysis unit includes a connectivity determination unit and a connectivity evaluation unit; The connectivity determination unit is used to nonlinearly couple the dynamic connectivity driving force index Dcl with the resistance dissipation index Rdz. Based on the ratio of the dynamic connectivity driving force index Dcl to the resistance dissipation index Rdz, the antagonistic relationship is smoothed by the arctangent function. At the same time, the ratio of the driving force to the square root of the resistance is applied with a sine function to form a sensitive determination value. Finally, the comprehensive connectivity determination index Eco is obtained by fitting, and the comprehensive response of wetland connectivity under the combined action of driving force and resistance is analyzed.

9. A water conservancy hub ecological flow regulation system based on digital twins according to claim 8, characterized in that: The connectivity assessment unit is used to collect the comprehensive connectivity judgment index Eco over a period of six months, calculate the mean using statistical methods, preset the mean as the ecological connectivity critical threshold Ae, and then conduct an ecological connectivity assessment with the real-time acquired comprehensive connectivity judgment index Eco. The specific assessment scheme is as follows. When the comprehensive connectivity index Eco < the ecological connectivity critical threshold Ae, it indicates insufficient connectivity and obstruction between the river channel and the wetland channel. At this time, channel optimization information is generated. When the comprehensive connectivity index Eco is greater than or equal to the ecological connectivity critical threshold Ae, it indicates that the connectivity is sufficient and the river and wetland channels are unobstructed, and stable monitoring information is generated at this time.

10. A water conservancy hub ecological flow regulation system based on digital twins according to claim 1, characterized in that: The regulation execution module is used to execute corresponding regulation commands based on the assessment information generated by the flow driving force assessment and the ecological connectivity assessment, as follows; Pulse water replenishment information: After increasing the hub outflow by 20% for 3 hours within 6 consecutive hours, the flow rate is gradually reduced to the original flow rate within 3 hours. The original flow rate is restored when the driving force assessment module is sufficient. Channel optimization information: Increase nighttime traffic by 15%, reduce daytime traffic by 8%, and perform iterative analysis every 6 hours through the connectivity determination module. If connectivity is still insufficient after 3 consecutive iterations, push alarm information to the ecological monitoring department to remind that wetland connectivity is insufficient and require on-site inspection and dredging. Stable monitoring information: Maintain the current outflow rate, and verify the wetland area every 12 hours through synchronous remote sensing images. If the change rate of wetland area between two consecutive synchronous remote sensing images does not exceed 2%, then maintain the current strategy. If it exceeds 2%, then generate the following flow adjustment strategy. If the wetland water area expands by more than 2%, reduce the outflow from the hub by 5% and continue monitoring. When the wetland water area recovers to no more than 2%, restore the original outflow from the hub. If the wetland water area decreases by more than 2%, increase the outflow from the hub by 5% and continue monitoring. When the wetland water area recovers to no more than 2%, restore the original outflow from the hub.

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