A method, device and equipment for controlling and managing ecological influence of cross-domain canal dredging and a storage medium

Abstract

The application provides a cross-domain canal dredging ecological influence control method, device, equipment and storage medium, the method generates a quantitative relationship model of dredging operation parameters and suspended sediment disturbance intensity based on large water tank physical model test and computational fluid dynamics simulation data; combined with habitat change information, water and sediment water quality change, aquatic community structure and predefined threshold, generate ecological impact evaluation standard; obtain water body physicochemical and benthic organism monitoring data during the implementation of the project, screen out candidate ecological diagnosis indexes through multivariate statistical analysis, and then verify and determine the key diagnosis index set of the ecological state by using isotope dating technology; accordingly, the control instruction is generated. The method constructs the "operation parameter-disturbance intensity" model to realize accurate control from the source, integrates multiple data sources to establish the threshold manual, screens and verifies the key indexes to realize monitoring feedback, realizes whole-chain, quantitative closed-loop control, and overcomes the defects of the prior art.

Description

Technical Field

[0001] This application pertains to the field of canal dredging, and particularly relates to a method, apparatus, equipment, and storage medium for controlling the ecological impact of cross-regional canal dredging. Background Technology

[0002] Currently, dredging operations rely on the experience of construction workers to control key parameters such as cutter head rotation speed and lateral movement speed to complete the dredging task. Regarding ecological impact assessment, fragmented monitoring methods such as satellite imagery, UAV aerial surveys, and on-site water quality and biological sampling are used to obtain information on the project's impact on wetland landscapes, water quality, and biological communities at different scales. This approach allows for basic control over the project's progress and provides a qualitative or semi-quantitative understanding of the environmental impact of construction.

[0003] The above-mentioned method of construction relying on experience and combined with scattered monitoring suffers from three major drawbacks because the various stages are fragmented and lack quantitative correlation: First, there is a lack of quantitative models between dredging operation parameters and the intensity of the resulting suspended sediment disturbance, which means that the control of the disturbance source relies entirely on experience and has low accuracy. Second, there is a lack of a systematic approach that integrates multi-scale impact data from "engineering-habitat-hydrology-biology", making it difficult to formulate scientific quantitative control thresholds from both engineering safety and ecological safety perspectives. Third, the disconnect between environmental impact monitoring data and engineering control instructions prevents the formation of a closed loop of "real-time monitoring-assessment-feedback control," resulting in delayed control measures. Summary of the Invention

[0004] The purpose of this application is to overcome the deficiencies in the prior art and provide a method, apparatus, equipment and storage medium for controlling the ecological impact of cross-regional canal dredging.

[0005] This application provides a method for managing the ecological impact of cross-regional canal dredging, including: Based on experimental data from a large-scale water tank physical model and computational fluid dynamics simulation data, a quantitative relationship model for disturbance intensity is generated, characterizing the quantitative relationship between dredging operation parameters and the intensity of suspended sediment disturbance. Ecological impact assessment standards are generated by extracting habitat change information from time-series remote sensing images, simulating water and sediment quality changes by a water-sediment coupling numerical model, obtaining aquatic biological community structure from environmental DNA analysis, and predefined thresholds for engineering safety, ecotoxicity, and habitat quality. During the project implementation, water physicochemical and benthic organism monitoring data were obtained. Candidate ecological diagnostic indicators were screened by multivariate statistical analysis of the benthic organism monitoring data. Isotope dating technology was used to analyze wetland sediment columns to verify the candidate ecological diagnostic indicators, thereby determining the set of key ecological status diagnostic indicators. Based on the quantitative relationship model of disturbance intensity, the ecological impact assessment standard, and the set of key diagnostic indicators for ecological status, an ecological impact control instruction for cross-regional canal dredging is generated.

[0006] Optionally, the model for generating a quantitative relationship between dredging operation parameters and the intensity of suspended sediment disturbance, comprising: By performing multivariate nonlinear regression analysis on the physical model test data of the large water tank and the computational fluid dynamics simulation data, a composite function model containing multiple key operating parameters and their interaction terms is established to characterize the quantitative impact of the coordinated changes of the multiple key operating parameters on the intensity of suspended sediment disturbance.

[0007] Optionally, the generated ecological impact assessment criteria include: The ecological impact assessment standard is constructed in a matrix structure, wherein one dimension of the matrix is ​​the ecologically sensitive zone and the other dimension is the engineering stage. For each combination of ecologically sensitive zone and engineering stage, a set of differentiated quantitative control thresholds are integrated and set.

[0008] Optionally, the step of screening candidate ecological diagnostic indicators by performing multivariate statistical analysis on the benthic organism monitoring data includes: Principal component analysis was performed on the benthic organism monitoring data to extract principal components representing the variability of the ecosystem state; The extracted principal component scores and dredging operation disturbance intensity data are input into a generalized additive model for analysis, and the parameters of the nonlinear response are selected as candidate ecological diagnostic indicators.

[0009] Optionally, the analysis of wetland sediment columns using isotope dating techniques to verify the candidate ecological diagnostic indicators includes: A time-depth model of the wetland sediment column was established based on ^210Pb / ^137Cs isotope dating technology. Identify the peak concentration of pollutants in the wetland sediment column and the corresponding sedimentary age of the peak concentration in the age-depth model; The depositional ages corresponding to the peak values ​​are compared with the historical timeline of cross-basin canal projects. The impact of the projects is verified based on the temporal consistency, and the effectiveness of the candidate ecological diagnostic indicators is validated accordingly.

[0010] Optionally, the generation of ecological impact control instructions for cross-regional canal dredging includes: Real-time acquisition of monitoring values ​​of parameters determined by the set of key diagnostic indicators for the ecological state; The monitored values ​​are dynamically compared with the quantitative control thresholds set in the ecological impact assessment standard for the ecologically sensitive zone to which the current work location belongs and the current stage of the project. When the monitored value exceeds the quantitative control threshold, an inversion calculation is performed based on the quantitative relationship model of disturbance intensity to generate an operational parameter adjustment scheme that can reduce the predicted suspended sediment disturbance intensity to below the quantitative control threshold, which serves as the ecological impact control instruction.

[0011] Optionally, the habitat change information extracted from time-series remote sensing images, the water and sediment quality change process simulated by a water-sediment coupling numerical model, and the aquatic biological community structure obtained from environmental DNA analysis include: The areas of significant habitat change identified in the habitat change information are used as spatial constraints to define the simulation range of the water, sediment and water quality change process; The output parameters of the water, sediment and water quality change process obtained within the simulation range are used as environmental driving factors. The environmental driving factors are correlated with the aquatic biological community structure data within the same spatial range to analyze the transmission path of engineering disturbances through habitat and aquatic environment changes to the biological community response.

[0012] This application also provides an ecological impact control device for cross-regional canal dredging, comprising: The model module generates a quantitative relationship model of disturbance intensity, based on experimental data from a large-scale water tank physical model and computational fluid dynamics simulation data, characterizing the quantitative relationship between dredging operation parameters and the intensity of suspended sediment disturbance. The analysis module generates ecological impact assessment standards based on habitat change information extracted from time-series remote sensing images, water and sediment quality change processes simulated by water and sediment coupling numerical models, aquatic biological community structure obtained from environmental DNA analysis, and predefined thresholds for engineering safety, ecotoxicity, and habitat quality. The indicator module acquires water physicochemical and benthic organism monitoring data during the project implementation period. It then uses multivariate statistical analysis of the benthic organism monitoring data to screen out candidate ecological diagnostic indicators. Finally, it uses isotope dating technology to analyze wetland sediment columns to verify the candidate ecological diagnostic indicators, thereby determining the set of key ecological status diagnostic indicators. The instruction module generates ecological impact control instructions for cross-regional canal dredging based on the quantitative relationship model of disturbance intensity, the ecological impact assessment standard, and the set of key diagnostic indicators for ecological status.

[0013] This application also provides an electronic device, including: A memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0014] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the above-described method.

[0015] The beneficial effects of this application are: This application provides a method for ecological impact control of cross-regional canal dredging, comprising: generating a quantitative relationship model of disturbance intensity based on experimental data from a large-scale flume physical model and computational fluid dynamics simulation data, characterizing the quantitative relationship between dredging operation parameters and suspended sediment disturbance intensity; generating ecological impact assessment standards based on habitat change information extracted from time-series remote sensing images, water and sediment quality change processes simulated by a water-sediment coupling numerical model, aquatic biological community structure obtained from environmental DNA analysis, and predefined thresholds for engineering safety, ecotoxicity, and habitat quality; acquiring water body physicochemical and benthic biological monitoring data during the project implementation period, screening candidate ecological diagnostic indicators through multivariate statistical analysis of the benthic biological monitoring data, analyzing wetland sediment columns using isotope dating technology to verify the candidate ecological diagnostic indicators, thereby determining a set of key ecological status diagnostic indicators; and generating ecological impact control instructions for cross-regional canal dredging based on the quantitative relationship model of disturbance intensity, the ecological impact assessment standards, and the set of key ecological status diagnostic indicators. This application achieves precise source control by constructing a quantitative model of "operational parameters-disturbance intensity", provides a scientific basis for management and control by integrating multi-source data to establish a quantitative threshold manual, and realizes feedback of monitoring to management and control by screening and verifying a set of key diagnostic indicators. Thus, it realizes full-chain, quantitative closed-loop management and control of the ecological impact of cross-regional canal dredging, overcoming the defects of inaccurate control, lack of data for management and control, and disconnection of management in existing technologies. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the ecological impact control process for cross-regional canal dredging; Figure 2 This is a schematic diagram of an ecological impact control device for cross-regional canal dredging. Detailed Implementation

[0017] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it is to be understood that various forms of implementation of the present disclosure are intended and should not be limited to the embodiments set forth herein. Rather, the embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0018] This application provides a method for managing the ecological impact of cross-basin canal dredging, which is applied in the fields of water conservancy engineering, environmental engineering and ecological protection technology. It solves the problems of irreversible impact of dredging operations on highly sensitive wetland ecosystems during the construction of cross-basin canals, as well as the low accuracy of disturbance control, lack of systematic quantitative impact methods and real-time management closed loop in existing technologies.

[0019] Please refer to Figure 1 As shown, the method for controlling the ecological impact of cross-regional canal dredging includes: S101. Based on the test data of the physical model of the large water tank and the computational fluid dynamics simulation data, a quantitative relationship model of disturbance intensity is generated to characterize the quantitative relationship between dredging operation parameters and the disturbance intensity of suspended sediment.

[0020] The dredging operation parameters include cutter speed, lateral speed, cutting thickness, and suction vacuum.

[0021] The intensity of suspended sediment disturbance is reflected in the suspended sediment concentration field, the maximum longitudinal diffusion distance of the diffusion cloud, and the width.

[0022] In this application, the specific implementation involves establishing a quantitative model of "operational parameters-disturbance intensity", which includes the process of quantifying the disturbance response mechanism.

[0023] In a large indoor, movable submerged tank, a typical substrate, such as silty clay, obtained from the target canal section, is laid. Using a precisely controllable simulated dredging device, the system modulates four key parameters: cutter speed, lateral velocity, cutting thickness, and suction vacuum.

[0024] The concentration field of suspended sediment, the maximum longitudinal diffusion distance and width of diffusion clouds were measured simultaneously using an array-type high-frequency turbidimeter and a particle image velocimeter under different parameter combinations, thereby obtaining physical model test data.

[0025] During the modeling phase, multivariate nonlinear regression analysis is performed on the experimental data to establish quantitative empirical formulas, such as: , in, denoted as the maximum suspended sediment concentration, k1 as the comprehensive coefficient, A as the cutter rotation speed, B as the traverse speed, C as the cutting thickness, and α, β, and γ as the power exponents of each parameter.

[0026] Establish the functional relationship between diffusion distance L and maximum suspended sediment concentration and background velocity: , In addition to physical model experiments, computational fluid dynamics software is needed to establish detailed three-dimensional models of water flow, sediment, and machinery to conduct numerical simulations of the entire process of excavation, pumping, and lateral movement, thereby obtaining computational fluid dynamics simulation data.

[0027] By comparing and verifying experimental data with simulation data, we can deepen our understanding of the disturbance process from the perspective of fluid mechanics. Finally, we can generate a composite function model that can characterize the quantitative impact of the coordinated changes of key operating parameters on the disturbance intensity of suspended sediment, namely, the quantitative relationship model of disturbance intensity.

[0028] Furthermore, in the process of establishing a quantitative relationship model between "operational parameters and disturbance intensity", the multivariate nonlinear regression analysis of the experimental data aims to establish a composite function model containing multiple key operational parameters and their interaction terms, so as to characterize the quantitative impact of the coordinated changes of the multiple key operational parameters on the disturbance intensity of suspended sediment.

[0029] Furthermore, in the experiment of quantifying the disturbance response mechanism, the four key parameters of the system change have specific numerical ranges. A specific example is: the range of the cutter speed is 10-40 rpm, the range of the lateral speed is 0.1-0.4 m / s, and the range of the cutting thickness is 0.5-2.0 m.

[0030] S102. Based on habitat change information extracted from time-series remote sensing images, water and sediment quality change processes simulated by water and sediment coupling numerical models, aquatic biological community structure obtained from environmental DNA analysis, and predefined thresholds for engineering safety, ecotoxicity, and habitat quality, an ecological impact assessment standard is generated.

[0031] The time-series remote sensing images are used to interpret changes in land use, vegetation cover, and water surface area.

[0032] The water-sediment coupling numerical model is used to simulate the spatiotemporal changes of abiotic factors such as flow velocity, flow direction, water level, suspended matter, and nutrients caused by engineering projects.

[0033] The environmental DNA analysis is used to analyze changes in the structure of biological communities such as plankton, benthic animals, and fish.

[0034] The predefined thresholds include engineering safety thresholds to ensure slope stability, ecotoxicity thresholds to protect local representative species, and habitat quality thresholds required to maintain the habitat function of key species.

[0035] This step involves constructing an impact assessment and low-impact development threshold system for cross-basin canal ecosystems, comprising two main parts: multi-scale impact mechanism analysis and threshold system construction.

[0036] In the analysis of multi-scale influence mechanisms: At the landscape and habitat scale, time-series satellite remote sensing images before and after the project were collected. Deep learning models were used to interpret changes in land use, vegetation cover, and water surface area. High-precision digital elevation models were generated by combining UAV aerial surveys to quantify changes in wetland micro-topography and extract habitat change information.

[0037] In terms of hydrological and water quality processes, a coupled numerical model of hydrodynamics, water quality, and sediment is constructed to simulate the changes in water, sediment, and water quality caused by engineering projects.

[0038] In terms of biological and ecological responses, aquatic biological community structure data were obtained by combining on-site sampling with environmental DNA macrobarcoding technology. Statistical methods were then used to correlate community changes with the aforementioned hydrological and water quality changes in order to analyze the transmission path of engineering disturbances through habitat and aquatic environment changes to biological community responses.

[0039] The significant habitat change areas identified in the habitat change information are used as spatial constraints to define the simulation range of the water, sediment and water quality change process. Then, the output parameters of the water, sediment and water quality change process obtained within the simulation range are used as environmental driving factors. Finally, the environmental driving factors are correlated with the aquatic biological community structure data within the same spatial range, such as redundancy analysis, to quantify the contribution rate of each environmental factor and clarify the key impact pathways.

[0040] In constructing the threshold system, the engineering safety threshold obtained from numerical simulation, the ecotoxicity threshold obtained from indoor biotoxicity tests, and the habitat quality threshold obtained from habitat simulation analysis are integrated to ultimately form a matrix-structured ecological impact assessment standard.

[0041] Furthermore, the aforementioned generation of ecological impact assessment standards refers to the construction of a matrix-structured ecological impact assessment standard, wherein one dimension of the matrix is ​​the ecologically sensitive zone and the other dimension is the engineering stage. For each combination of ecologically sensitive zone and engineering stage, a set of differentiated quantitative control thresholds are integrated and set.

[0042] The matrix-structured ecological impact assessment standards are presented in the form of a "Threshold Manual." For example, when the ecological zone is a core protected area and the control phase is the construction period, the core indicator is the increase in suspended solids 500 meters downstream of the work area, with a recommended threshold of ≤20 mg / L, based on the NOEC 28-day chronic toxicity test of river clams. When the ecological zone is an ecological restoration area and the control phase is the operation period, the core indicator is the change rate of flow velocity in a certain fish spawning ground, with a recommended threshold of ≤±10%, based on habitat suitability index model analysis. When the ecological zone is a general control area and the control phase is the entire cycle, the core indicator is the width of the riparian vegetation buffer zone, with a recommended threshold of ≥30 m, based on simulation of non-point source pollution interception efficiency.

[0043] S103. Obtain water physicochemical and benthic organism monitoring data during the project implementation period, screen candidate ecological diagnostic indicators by performing multivariate statistical analysis on the benthic organism monitoring data, analyze wetland sediment columns using isotope dating technology, verify the candidate ecological diagnostic indicators, and thus determine the set of key ecological status diagnostic indicators.

[0044] A comprehensive ecological and environmental monitoring network needs to be established. Specifically, monitoring sections, including background sections, impact sections, and control sections, should be set up along the direction of water flow and perpendicular to the shoreline, with the dredging construction area as the center.

[0045] The monitoring content includes the water environment, interfacial processes, and ecological communities.

[0046] Water environment monitoring employs online monitoring buoys to monitor parameters such as pH, dissolved oxygen, turbidity, and chlorophyll a at high frequencies. Interface process monitoring uses pore water samplers to collect water samples from the mud-water interface, analyzing the concentration gradients of nitrogen, phosphorus, and heavy metals in the laboratory to calculate pollutant diffusion fluxes. Ecological community monitoring involves periodically collecting water and sediment samples for eDNA sequencing and traditional morphological identification, analyzing the community structure and diversity indices of phytoplankton and macrobenthic animals to obtain benthic organism monitoring data.

[0047] After acquiring long-term monitoring data, key diagnostic indicators were identified and empirically verified. Specifically, multivariate statistical analysis was conducted on a large amount of environmental and biological data to screen out a few indicators that were most sensitive and stable in response to dredging disturbance as candidate ecological diagnostic indicators.

[0048] The multivariate statistical analysis includes principal component analysis and generalized additive model analysis: Principal component analysis was performed on the benthic organism monitoring data to extract the main components that represent the variability in ecosystem state. The scores of these extracted principal components were input into a generalized additive model along with the dredging operation disturbance intensity data for analysis. Parameters that exhibit a nonlinear response to disturbances were selected and used as candidate ecological diagnostic indicators, such as ammonia nitrogen release flux, relative abundance of Nitrifying Spirogyra, and biomass of Hopkins tubifex.

[0049] To validate the validity of these candidate indicators and provide “geological evidence” for the impact assessment, isotopic dating techniques are needed to analyze wetland sediment columns. Specifically, undisturbed sediment columns are drilled from suspected affected areas, and the sediment columns are then spaced out in the laboratory.

[0050] A time-depth model of the wetland sedimentary column was established using 210Pb / 137Cs isotope dating, which determined the depositional ages of sediment layers at different depths. Then, the contents of pollutants such as heavy metals and nutrients in each sedimentary layer were measured, the peak concentrations of these pollutants were identified, and the depositional ages corresponding to these peak concentrations in the time-depth model were determined.

[0051] By comparing the depositional ages corresponding to the peak values ​​with the historical timeline of inter-basin canal projects, if the ages match, the impact of the project disturbance can be empirically verified, and the effectiveness of the candidate ecological diagnostic indicators can be validated. Through the above screening and verification process, a "rapid ecological impact diagnostic indicator set" containing a few indicators that are most sensitive and stable to dredging disturbance response is finally determined, namely, the key ecological status diagnostic indicator set.

[0052] Furthermore, the step of screening candidate ecological diagnostic indicators by performing multivariate statistical analysis on the benthic organism monitoring data includes performing principal component analysis on the benthic organism monitoring data to extract principal components representing the variation in ecosystem state, and inputting the scores of the extracted principal components and dredging operation disturbance intensity data into a generalized additive model for analysis to screen out parameters of nonlinear response as candidate ecological diagnostic indicators.

[0053] Furthermore, the analysis of wetland sedimentary columns using isotope dating techniques to verify the candidate ecological diagnostic indicators includes establishing a time-depth model of the wetland sedimentary column based on 210Pb / 137Cs isotope dating techniques, identifying the peak concentration of pollutants in the wetland sedimentary column and the corresponding depositional age of the peak concentration in the time-depth model, comparing the depositional age corresponding to the peak concentration with the historical timeline of the inter-basin canal project, verifying the impact of the project based on the time-to-time consistency, and verifying the effectiveness of the candidate ecological diagnostic indicators accordingly.

[0054] S104. Based on the quantitative relationship model of disturbance intensity, the ecological impact assessment standard, and the set of key diagnostic indicators for ecological status, generate an ecological impact control instruction for cross-regional canal dredging.

[0055] The integration and application of the aforementioned specialized technical systems forms a concrete realization of a real-time closed loop of "monitoring-evaluation-control," which corresponds to the development and workflow of a low-impact intelligent dredging system.

[0056] The cutter suction dredger integrates a sensing module, a decision control module, and an execution module.

[0057] The sensing module includes a forward-looking multibeam sonar and a turbidity monitoring array around the ship and downstream, used to acquire in real time the monitoring values ​​of parameters determined by the set of key ecological state diagnostic indicators, such as background turbidity and forward topography.

[0058] The core algorithm of the decision control module incorporates the quantitative relationship model of the disturbance intensity and can access the ecological impact assessment standard.

[0059] During operation, the decision control module reads the monitoring data provided by the sensing module in real time and dynamically compares the monitored values ​​with the quantitative control thresholds set in the ecological impact assessment standard for the ecologically sensitive zone to which the current operation location belongs and the current engineering stage. When the monitored value approaches or exceeds the quantitative control threshold, the system performs inversion calculations based on the quantitative relationship model of disturbance intensity to generate an operation parameter adjustment scheme that can reduce the predicted suspended sediment disturbance intensity below the quantitative control threshold.

[0060] Specifically, the algorithm dynamically calculates the maximum permissible operating intensity under the current environment without exceeding the threshold, such as the highest cutter speed and the fastest lateral movement speed, and generates corresponding control commands.

[0061] Finally, the execution module receives the control command and automatically controls the hydraulic drive system to adjust the operating parameters such as the cutter speed and lateral movement speed to the safe range.

[0062] If the turbidity monitoring value at the downstream monitoring point still approaches the threshold after adjustment, the system will further reduce the speed or suspend the operation, thereby achieving adaptive closed-loop control. The operation parameter adjustment scheme or control command generated in this way is the ecological impact control command, which directly controls the intensity of dredging operations from the source, ensuring that engineering activities are within the threshold range of ecological safety.

[0063] Furthermore, the generation of ecological impact control instructions for cross-regional canal dredging includes: acquiring in real time the monitoring values ​​of parameters determined by the set of key ecological status diagnostic indicators; dynamically comparing the monitoring values ​​with the quantitative control thresholds set in the ecological impact assessment standards for the ecologically sensitive zone to which the current operation location belongs and the current engineering stage; when the monitoring values ​​exceed the quantitative control thresholds, performing inversion calculations based on the quantitative relationship model of disturbance intensity to generate an operation parameter adjustment scheme that can reduce the predicted suspended sediment disturbance intensity to below the quantitative control thresholds, as the ecological impact control instructions.

[0064] Furthermore, the perception module of the low-impact intelligent dredging system specifically includes a forward-looking multibeam sonar, a ship perimeter and downstream turbidity monitoring array, a decision control module consisting of an industrial computer and controller, and an execution module consisting of a hydraulic drive system.

[0065] like Figure 2 As shown, this application also provides an ecological impact control device for cross-regional canal dredging, comprising: Model module 201 generates a quantitative relationship model of disturbance intensity based on experimental data of physical model of large water tank and computational fluid dynamics simulation data, which characterizes the quantitative relationship between dredging operation parameters and the disturbance intensity of suspended sediment. Analysis module 202 generates ecological impact assessment standards based on habitat change information extracted from time-series remote sensing images, water and sediment quality change processes simulated by water and sediment coupling numerical models, aquatic biological community structure obtained from environmental DNA analysis, and predefined thresholds for engineering safety, ecotoxicity, and habitat quality. The indicator module 203 acquires water body physicochemical and benthic organism monitoring data during the project implementation period, screens candidate ecological diagnostic indicators by performing multivariate statistical analysis on the benthic organism monitoring data, analyzes wetland sediment columns using isotope dating technology, verifies the candidate ecological diagnostic indicators, and thus determines the set of key ecological status diagnostic indicators. The instruction module 204 generates an ecological impact control instruction for cross-regional canal dredging based on the quantitative relationship model of disturbance intensity, the ecological impact assessment standard, and the set of key diagnostic indicators for ecological status.

[0066] This application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the system as described above.

[0067] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to execute the system described above.

[0068] The above description of the embodiments is provided to enable those skilled in the art to understand and apply this application. Those skilled in the art will readily make various modifications to the above embodiments and apply the general principles described herein to other embodiments without inventive effort. Therefore, this application is not limited to the above embodiments, and any improvements and modifications made to this application based on the disclosure thereof should be within the scope of protection of this application.

Claims

1. A method for managing the ecological impact of cross-regional canal dredging, characterized in that, include: Based on experimental data from a large-scale water tank physical model and computational fluid dynamics simulation data, a quantitative relationship model for disturbance intensity is generated, characterizing the quantitative relationship between dredging operation parameters and the intensity of suspended sediment disturbance. Ecological impact assessment standards are generated by extracting habitat change information from time-series remote sensing images, simulating water and sediment quality changes through a water-sediment coupling numerical model, obtaining aquatic biological community structure from environmental DNA analysis, and using predefined thresholds for engineering safety, ecotoxicity, and habitat quality. During the project implementation, water physicochemical and benthic organism monitoring data were obtained. Candidate ecological diagnostic indicators were screened by multivariate statistical analysis of the benthic organism monitoring data. Isotope dating technology was used to analyze wetland sediment columns to verify the candidate ecological diagnostic indicators, thereby determining the set of key ecological status diagnostic indicators. Based on the quantitative relationship model of disturbance intensity, the ecological impact assessment standard, and the set of key diagnostic indicators for ecological status, an ecological impact control instruction for cross-regional canal dredging is generated.

2. The method according to claim 1, characterized in that, The quantitative relationship model for generating disturbance intensity, which characterizes the quantitative relationship between dredging operation parameters and the intensity of suspended sediment disturbance, includes: By performing multivariate nonlinear regression analysis on the physical model test data of the large water tank and the computational fluid dynamics simulation data, a composite function model containing multiple key operating parameters and their interaction terms is established to characterize the quantitative impact of the coordinated changes of the multiple key operating parameters on the intensity of suspended sediment disturbance.

3. The method according to claim 1, characterized in that, The aforementioned ecological impact assessment standards include: The ecological impact assessment standard is constructed in a matrix structure, wherein one dimension of the matrix is ​​the ecologically sensitive zone and the other dimension is the engineering stage. For each combination of ecologically sensitive zone and engineering stage, a set of differentiated quantitative control thresholds are integrated and set.

4. The method according to claim 1, characterized in that, The process of screening candidate ecological diagnostic indicators through multivariate statistical analysis of the benthic organism monitoring data includes: Principal component analysis was performed on the benthic organism monitoring data to extract principal components representing the variability of the ecosystem state; The extracted principal component scores and dredging operation disturbance intensity data are input into a generalized additive model for analysis, and the parameters of the nonlinear response are selected as candidate ecological diagnostic indicators.

5. The method according to claim 1, characterized in that, The analysis of wetland sediment columns using isotope dating techniques to verify the candidate ecological diagnostic indicators includes: A time-depth model of the wetland sediment column was established based on ^210Pb / ^137Cs isotope dating technology. Identify the peak concentration of pollutants in the wetland sediment column and the corresponding sedimentary age of the peak concentration in the age-depth model; The depositional ages corresponding to the peak values ​​are compared with the historical timeline of cross-basin canal projects. The impact of the projects is verified based on the temporal consistency, and the effectiveness of the candidate ecological diagnostic indicators is validated accordingly.

6. The method according to claim 1, characterized in that, The generated instructions for managing the ecological impact of cross-regional canal dredging include: Real-time acquisition of monitoring values ​​of parameters determined by the set of key diagnostic indicators for the ecological state; The monitored values ​​are dynamically compared with the quantitative control thresholds set in the ecological impact assessment standard for the ecologically sensitive zone to which the current work location belongs and the current stage of the project. When the monitored value exceeds the quantitative control threshold, an inversion calculation is performed based on the quantitative relationship model of disturbance intensity to generate an operational parameter adjustment scheme that can reduce the predicted suspended sediment disturbance intensity to below the quantitative control threshold, which serves as the ecological impact control instruction.

7. The method according to claim 1, characterized in that, The habitat change information extracted from time-series remote sensing images, the water and sediment quality change processes simulated by a water-sediment coupling numerical model, and the aquatic biological community structure obtained from environmental DNA analysis include: The areas of significant habitat change identified in the habitat change information are used as spatial constraints to define the simulation range of the water, sediment and water quality change process; The output parameters of the water, sediment and water quality change process obtained within the simulation range are used as environmental driving factors. The environmental driving factors are correlated with the aquatic biological community structure data within the same spatial range to analyze the transmission path of engineering disturbances through habitat and aquatic environment changes to the biological community response.

8. A device for controlling the ecological impact of cross-regional canal dredging, characterized in that, include: The model module generates a quantitative relationship model of disturbance intensity, based on experimental data from a large-scale water tank physical model and computational fluid dynamics simulation data, characterizing the quantitative relationship between dredging operation parameters and the intensity of suspended sediment disturbance. The analysis module generates ecological impact assessment standards based on habitat change information extracted from time-series remote sensing images, water and sediment quality change processes simulated by water and sediment coupling numerical models, aquatic biological community structure obtained from environmental DNA analysis, and predefined thresholds for engineering safety, ecotoxicity, and habitat quality. The indicator module acquires water physicochemical and benthic organism monitoring data during the project implementation period. It then uses multivariate statistical analysis of the benthic organism monitoring data to screen out candidate ecological diagnostic indicators. Finally, it uses isotope dating technology to analyze wetland sediment columns to verify the candidate ecological diagnostic indicators, thereby determining the set of key ecological status diagnostic indicators. The instruction module generates ecological impact control instructions for cross-regional canal dredging based on the quantitative relationship model of disturbance intensity, the ecological impact assessment standard, and the set of key diagnostic indicators for ecological status.

9. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method as described in claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed in a computer, causes the computer to perform the method described in claims 1 to 7.

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