Reservoir desilting control method and system based on remote sensing monitoring and electronic equipment

Abstract

The invention discloses a reservoir desilting control method and system based on remote sensing monitoring and electronic equipment, and particularly relates to the technical field of reservoir desilting. The method is used for solving the problems that in existing reservoir desilting operation, unified alignment of multi-source monitoring data is difficult, a quantitative decision basis is lacked in desilting task planning and scheduling, closed-loop supervision of the construction process is difficult, and the desilting effect is difficult to evaluate and dynamically optimize. The method comprises the following steps of: uniformly mapping a reservoir terrain, a water level operation record, remote sensing sedimentation distribution and a dredging equipment construction track into a dredging task unit under a double-anchor time base by constructing a dredging reference grid divided according to an elevation zone, and forming a risk field and a benefit field based on a safety constraint value and a recovery benefit value; and task cluster scheduling and instruction template issuing are driven in a construction window, so that closed-loop control of reservoir desilting monitoring, decision making, execution and evaluation is realized on a unified space-time carrier, dependence of decision making on experience is reduced, and targeted safety and quantifiable management capability of a desilting scheme are improved.

Description

Technical Field

[0001] This invention relates to the field of reservoir dredging technology, specifically to a reservoir dredging control method, system, and electronic equipment based on remote sensing monitoring. Background Technology

[0002] In existing reservoir dredging projects, dredging plans typically rely on one-time or phased topographic surveys, supplemented by water level records and some field investigation results, to divide the siltation area into zones and develop a construction plan. Constrained by measurement cycles and data acquisition costs, most projects primarily use traditional cross-sectional measurements and a small amount of cross-sectional interpolation, resulting in limited spatial resolution and difficulty in timely reflecting the dynamic changes in siltation patterns within the reservoir area. The division of dredging areas largely depends on manual experience, roughly dividing the area according to reservoir sections, bank sections, or administrative units. The dredging sequence and construction window arrangements mainly rely on technical personnel's experience-based judgment of flood control safety, water supply needs, and equipment capacity, lacking quantifiable and reusable decision-making basis.

[0003] With the development of remote sensing monitoring technology, some projects have begun to utilize satellite or UAV imagery to identify changes in reservoir water surface and siltation. The siltation distribution retrieved from remote sensing is then comprehensively analyzed with data such as reservoir topography and water level records to help determine key dredging areas. However, current practices suffer from inconsistencies in coordinate, elevation, and time signatures among various data types. They often rely on layer overlay, manual interpretation, and simple threshold filtering, lacking a unified spatiotemporal reference framework for dredging decision-making. Remote sensing identification results are often limited to "delineating heavily silted areas," failing to establish a structured correspondence with specific dredging task granularity, vessel and machinery resource constraints, and construction window arrangements. Quantitative assessments of dredging safety risks and benefits are also primarily based on single-point or single-time calculations, making it difficult to form a continuous spatial distribution and a traceable evaluation chain.

[0004] At the construction and operation management level, existing technologies typically archive the dredging process and results through construction logs, scheduling records, and periodic retest reports. They lack a unified structure that uses task units as carriers to link construction trajectories, workloads, monitoring indicators, and prior planning assumptions, making it difficult to establish stable comparative benchmarks across multiple rounds of construction and retesting. Adjustments to dredging rules largely rely on managers revising plans for the next round based on experience, lacking a systematic feedback mechanism based on historical task performance. This makes it difficult to achieve refined adjustments to safety boundaries, dredging priorities, and resource allocation strategies across multiple operational cycles.

[0005] In summary, existing reservoir dredging, even with the introduction of remote sensing monitoring and multi-source information, still faces a prominent technical problem: it cannot organically link topography, water level, remote sensing sedimentation identification with dredging task division, risk and benefit constraints, construction scheduling, and multi-cycle performance evaluation within a unified spatiotemporal reference framework, thus failing to form a quantitative decision-making chain and a closed-loop optimization mechanism oriented towards dredging task units. This results in insufficient targeting, controllability, and adaptability of dredging schemes. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a reservoir dredging control method, system, and electronic equipment based on remote sensing monitoring, in order to solve the problems mentioned in the background section.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a reservoir dredging control method based on remote sensing monitoring, comprising: S1. Acquire reservoir topographic data, operation records and remote sensing images, construct a dredging benchmark grid divided by elevation zones, and establish dual-anchor time-base aligned data; S2. Map the remote sensing silt distribution onto the baseline grid, aggregate candidate areas according to connectivity, elevation zone and construction radius, and subdivide them into dredging task units according to equipment capabilities and assign task keys. S3. Combine water level, inflow, equipment parameters and environmental protection boundaries to calculate safety constraint values ​​and recovery benefit values ​​for each task unit, and form risk field and benefit field on the baseline grid; S4. Within the preset construction window, take the dredging task unit as the decision unit, and establish a scheduling optimization model in combination with the risk field, benefit field and ship and machine resources to obtain the dredging task cluster that meets the constraints and generate an instruction template that specifies the operation polygon area, the allowable range of water level changes and the target elevation zone for bottom cleaning. S5. Collect the location trajectory and dredging volume of the dredging equipment according to the instruction template, locate the corresponding dredging task unit on the benchmark grid, establish the task state machine and record the trajectory and monitoring indicators during state transition. S6. Based on the subsequent remote sensing sediment distribution, the data is remapped to the baseline grid. Performance indicators are calculated according to the target elevation of the task unit. The risk field threshold and benefit weight are adjusted according to the performance indicators, and a rule version is generated for subsequent task unit generation and scheduling.

[0008] Furthermore, S1 includes: The reservoir topographic data were converted according to a unified elevation datum and plane coordinate datum, and the coordinate transformation parameters and version marks were recorded. A time base is obtained by constructing a time anchor based on the standard time of the dispatch center, using the time stamps of water level operation records and remote sensing images as intrinsic anchors, correcting the time stamps based on the time difference between the time anchor and the intrinsic anchors and registering the time alignment rule version. Elevation zones are divided according to the designed beneficial water level, dead water level, and flood control limit water level. A regular grid with a unique number is generated within the plane of the reservoir area. In each grid cell, the elevation zone identifier, the topographic base elevation, the siltation thickness record, the safety risk record, the benefit record, the task status record, and the construction trajectory record are recorded to form a dredging benchmark grid.

[0009] Furthermore, S2 includes: Multi-temporal remote sensing images are corrected according to coordinate and elevation benchmarks, and the siltation distribution covering the reservoir area is obtained based on water surface range identification and water depth inversion. The silt distribution is mapped to the dredging baseline grid, and the silt thickness, elevation zone, source of silt thickness, remote sensing image version marker, and mapping time marker are recorded in each grid cell. Based on the siltation thickness threshold, grid cells with siltation thickness below the threshold are registered as grids that do not require dredging; Register grid units located in areas where dredging is prohibited as dredging grids; Grid cells that simultaneously meet the criteria of having a siltation thickness threshold and being located within an allowable dredging area will be registered as candidate dredging grids.

[0010] Furthermore, in the dredging benchmark grid, for the grid cells registered as candidate dredging grids, candidate regions are generated by aggregation based on planar adjacency and elevation zone continuity, and the range of the candidate regions is constrained based on the construction radius of the dredging equipment. Within the candidate area, dredging task units are generated by subdividing the dredging equipment based on its operating width, draft, transfer distance, and operational capabilities. Each dredging task unit is associated with a defined grid set and target elevation zone, and the expected dredging volume is registered. A unique task key is generated, which is a combination of the grid set summary, target elevation zone identifier, remote sensing image version marker, and dredging baseline grid rule version marker. The unique task key is then registered in the task list and associated with version management.

[0011] Furthermore, S3 includes: During the dredging control cycle, based on the water level sequence in the water level operation record, the inflow scenario formed by the inflow forecast, the operating water depth range and maximum continuous operating time in the dredging equipment parameters, as well as the prohibited areas and turbidity control boundaries in the ecological and environmental protection boundaries, the observation window corresponding to the construction window of each dredging task unit is extracted. Based on the water level changes and bank slope stability conditions within the observation window, safety constraint values ​​are determined. Based on the expected reservoir volume to be restored by the dredging task unit and the impact on the operation status of key flood control sections and water intakes, restoration benefit values ​​are determined. The safety constraint values ​​and restoration benefit values ​​are then written into the dredging baseline grid according to the grid units covered by the dredging task unit to generate risk and benefit fields. Register the task key, water level sequence version, inflow scenario version, and equipment parameter version in the relevant grid cells.

[0012] Furthermore, S4 includes: During the construction organization phase, the dredging task unit is used as the scheduling granularity. Within the construction window, the dredging task unit is selected based on the safety constraint value in the risk field and the recovery benefit value in the benefit field. The dredging task unit that meets the safety constraint and resource constraint is determined in combination with the ship and machine capacity in the ship and machine resource pool. Dredging task clusters are generated by combining dredging task units according to spatial proximity and operational route coherence. A command template is generated for each dredging task cluster. The command template specifies the working polygon area, the allowable range of water level changes, the target elevation zone for dredging, and the monitoring index thresholds. It is then sent to the construction terminal through the scheduling and control channel. The instruction template carries a unique instruction identifier and a corresponding set of task keys. The construction terminal executes the dredging operation according to the instruction template and generates an execution result record.

[0013] Furthermore, S5 includes: During the execution of the dredging task cluster, the construction terminal collects the location trajectory of the dredging equipment, underwater suction flow rate, water level monitoring value and turbidity monitoring value according to the instruction template; Project the current position of the equipment onto the dredging reference grid to determine the grid cell to which it belongs and index the corresponding dredging task cell. Establish a task state machine for each dredging task cell, including the states of pending execution, execution, execution completion, and need for review. The process transitions between pending execution, execution, and execution completion states based on whether the equipment enters or leaves the task area and whether the cumulative dredging volume reaches the expected dredging volume ratio. When the water level monitoring value exceeds the allowable range of water level change or the turbidity monitoring value exceeds the turbidity control limit, the task status will be changed to "required for review". Each time the task status is changed, an operation record with a bound task key and rule version number will be generated and written to the operation archive for subsequent scheduling and performance evaluation.

[0014] Furthermore, S6 includes: After the construction window ends and the re-measurement is completed, the reservoir capacity restoration index and local secondary siltation rate are calculated based on the subsequent remote sensing siltation distribution mapping of the siltation benchmark grid, according to the grid set covered by the siltation task unit. Performance records are generated at the dredging task unit and dredging task cluster levels, and these performance records are associated with task keys, task state machine records, and operation record units in the operation archive. Analyze safety and benefit performance according to risk level, adjust the risk threshold of the risk field and the weight parameters of the benefit field, generate rule versions and record the version number chain; Establish an index relationship between task keys and rule version numbers, call the rule version in subsequent dredging task unit generation and dredging task cluster construction, and form a cross-cycle evidence chain through performance records and operation record units in the operation archive.

[0015] On the other hand, the present invention provides a reservoir dredging control system based on remote sensing monitoring, comprising: The reference grid and time base construction module is used to acquire reservoir topographic data, operation records and remote sensing images, construct a dredging reference grid divided by elevation zones, and establish a dual-anchor time base to complete the data alignment of reservoir topographic data, operation records and remote sensing images. Task Unit Generation Module: This module maps the remote sensing silt distribution to the dredging baseline grid, aggregates candidate areas based on connectivity, elevation zone, and construction radius, and further subdivides the candidate areas based on the operational capabilities of the dredging equipment to generate dredging task units, assigning a unique task key to each dredging task unit. Risk and benefit generation module: It is used to combine water level, inflow, equipment parameters and environmental boundaries to calculate safety constraint value and recovery benefit value for each dredging task unit, and to register the safety constraint value and recovery benefit value according to the grid unit on the dredging benchmark grid to form risk field and benefit field; The scheduling and instruction template generation module is used to establish a scheduling optimization model within a preset construction window, using dredging task units as decision units, and combining risk field, benefit field and ship and machinery resources to obtain dredging task clusters that meet safety constraints and resource constraints, and generate instruction templates that include the operation area, water level range and target elevation. Process monitoring and task status management module: It is used to collect the location trajectory and dredging volume of the dredging equipment according to the instruction template, locate the corresponding dredging task unit on the dredging benchmark grid, establish a task state machine that corresponds one-to-one with each dredging task unit, and record equipment trajectory segments and related monitoring indicators when the task status changes. The performance feedback and rule version generation module is used to remap the dredging baseline grid based on the subsequent remote sensing silt distribution, calculate performance indicators according to the target elevation of each dredging task unit, adjust the threshold of the risk field and the weight of the benefit field according to the performance indicators, and generate updated rule versions for subsequent dredging task unit generation and scheduling.

[0016] On the other hand, the present invention provides an electronic device for reservoir dredging based on remote sensing monitoring, comprising: Processor: Used to execute program instructions stored in memory to analyze, process, and schedule data based on remote sensing monitoring; Memory: Used to store remote sensing image data, reservoir topographic data, operation record data, and program instructions for executing reservoir dredging control; Communication interface: Used to enable data interaction between electronic devices and remote sensing acquisition terminals, construction terminals, and dispatch centers.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. By constructing a dredging benchmark grid divided by elevation zones, the reservoir topography, water level operation records, remote sensing siltation distribution, and dredging equipment construction trajectory are uniformly mapped into dredging task units bound to task keys under a dual-anchor time base. Based on safety constraint values ​​and restoration benefit values, risk fields and benefit fields are formed on the benchmark grid. These fields drive the scheduling of task clusters and the issuance of instruction templates within the construction window. This enables closed-loop control of reservoir dredging from monitoring, decision-making, execution to evaluation on a unified spatiotemporal carrier, significantly reducing the dependence of dredging decisions on experience and improving the pertinence, safety, and quantifiable management capabilities of dredging schemes.

[0018] 2. By configuring task state machines, operation archives, and performance records for dredging task units, and using task keys and rule version number chains as indexes, the construction process records are linked with reservoir capacity restoration indicators and secondary siltation trends. The risk thresholds and benefit weights are periodically adjusted, so that the dredging control rules can be gradually iterated with the effects and evolution characteristics of multiple rounds of construction, forming a traceable and auditable adaptive scheduling mechanism. Under the premise of meeting flood control safety and ecological constraints, the efficiency of ship and machinery resource utilization and the overall coordination of dredging organization are improved. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the reservoir dredging control method based on remote sensing monitoring according to the present invention. Figure 2 This is a schematic diagram of the reservoir dredging control system based on remote sensing monitoring according to the present invention; Figure 3 This is a schematic diagram of the electronic device for reservoir dredging based on remote sensing monitoring according to the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1: Figure 1 A flowchart illustrating the reservoir dredging control method based on remote sensing monitoring of the present invention is provided. The reservoir dredging control method based on remote sensing monitoring includes: S1. Acquire reservoir topographic data, operation records and remote sensing images, construct a dredging benchmark grid divided by elevation zones, and establish dual-anchor time-base aligned data; S2. Map the remote sensing silt distribution onto the baseline grid, aggregate candidate areas according to connectivity, elevation zone and construction radius, and subdivide them into dredging task units according to equipment capabilities and assign task keys. S3. Combine water level, inflow, equipment parameters and environmental protection boundaries to calculate safety constraint values ​​and recovery benefit values ​​for each task unit, and form risk field and benefit field on the baseline grid; S4. Within the preset construction window, take the dredging task unit as the decision unit, and establish a scheduling optimization model in combination with the risk field, benefit field and ship and machine resources to obtain the dredging task cluster that meets the constraints and generate an instruction template that specifies the operation polygon area, the allowable range of water level changes and the target elevation zone for bottom cleaning. S5. Collect the location trajectory and dredging volume of the dredging equipment according to the instruction template, locate the corresponding dredging task unit on the benchmark grid, establish the task state machine and record the trajectory and monitoring indicators during state transition. S6. Based on the subsequent remote sensing sediment distribution, the data is remapped to the baseline grid. Performance indicators are calculated according to the target elevation of the task unit. The risk field threshold and benefit weight are adjusted according to the performance indicators, and a rule version is generated for subsequent task unit generation and scheduling.

[0022] The technical connections and implementation logic of the six steps are as follows: First, S1 unifies the spatial and temporal benchmarks of reservoir topographic data, water level operation records, and remote sensing imagery to establish a dredging benchmark grid and dual-anchor time base covering the entire reservoir area, providing a unique coordinate framework for the spatial mapping and temporal alignment of all subsequent data. Based on this, S2 projects the remote sensing silt distribution onto the dredging benchmark grid cells. Through connectivity determination, elevation zone continuity constraints, and construction radius limitations, candidate areas are aggregated and segmented. Combined with equipment operational capabilities, the smallest executable dredging task unit is formed, uniquely identified by a task key, realizing a physical mapping from "remote sensing" to "construction objects." Then, S3 calls upon water level sequences, inflow scenarios, equipment capability parameters, and ecological and environmental boundary conditions to simultaneously calculate safety constraint values ​​and restoration benefit values ​​for each dredging task unit. The results are then backfilled into the grid layer, constructing a risk field and benefit field for the entire reservoir area, providing quantitative constraints and multi-objective evaluation benchmarks for scheduling decisions. In S4, risks are loaded within the construction window, using a single dredging task unit as the scheduling granularity. The system constructs a scheduling optimization model based on the field, benefit field, and ship and machinery resource status. It combines and matches task units that meet safety and resource constraints to form dredging task clusters and generates instruction templates that bind the boundaries of the work area, water level control intervals, and target elevation zones for bottom clearing. This transforms the decision-making model into a system capable of issuing construction instructions. Subsequently, in S5, the construction terminal collects equipment trajectory and workload data in real time based on the instruction templates. It projects and locates the work position in the dredging baseline grid to back-match dredging task units. The task state machine manages the state migration of the work progress and writes the trajectory data and monitoring indicators into the operation archive, achieving full-process traceability and control. Finally, in S6, the grid is remapped by introducing remote sensing silt distribution data obtained after construction. The performance indicators are calculated by comparing the changes in target elevation before and after construction. The actual performance of the positions is fed back to the risk field threshold and benefit weight configuration, generating a new rule version for the next round of task division and scheduling. This achieves a closed-loop control mechanism where the scheduling strategy continuously self-corrects and evolves based on construction results and risk performance.

[0023] S1. Acquire reservoir topographic data, operation records, and remote sensing images; construct a dredging baseline grid divided by elevation zones; and establish dual-anchor time-base aligned data. The specific implementation is as follows: In reservoir dredging scenarios, to stably construct dredging task units, risk fields, and benefit fields and track the construction trajectory of dredging equipment in subsequent stages, the site first acquires reservoir topographic data, water level operation records, and multi-temporal remote sensing images covering the entire reservoir area. The reservoir topographic data refers to the digital elevation surface of the reservoir area established using a unified elevation datum. This data can originate from multibeam bathymetry results, as-built survey data, and subsequent supplementary survey results. Preferably, the elevation of each measuring point is recorded in meters, and a continuous elevation surface covering the reservoir water surface is formed through interpolation. The planar position of the measuring points is preferably represented using a unified plane rectangular coordinate or latitude and longitude coordinate. In cases where different coordinate systems or elevation systems exist, the original data is uniformly converted to the selected datum system. The conversion residual is preferably controlled within one to five meters in the horizontal direction and within one to 0.5 meters in the vertical direction. The conversion relationship, residual range, configuration version number, and applicable scope are recorded in the conversion parameter table for subsequent verification and evidence preservation. The water level operation records refer to the data generated by the reservoir water level gauge... Alternatively, the water level can be continuously recorded at upstream hydrological stations, preferably at intervals of five minutes to one hour, with the water level value expressed in meters. The records should include station identification and acquisition time markers. When multiple water level gauges are in operation, the records at the same time should be checked for consistency. Records exceeding the preset difference limit should be marked as suspicious values. Preferably, the water level difference threshold should be set to 0.1 meters to 0.3 meters for priority processing in subsequent smoothing. Multi-temporal remote sensing images refer to satellite or UAV images covering the reservoir area acquired on different observation dates. Preferably, at least several images should be acquired within a dredging control cycle. The dredging control cycle can be understood as the time period from the start of a dredging task planning to the end of the corresponding construction and the completion of the re-measurement, usually several weeks to several months. The spatial resolution of the remote sensing images can be set to several meters to more than ten meters. The acquisition date, shooting time marker, and image quality marker should be included in the image file to indicate adverse factors such as cloud cover, strong reflection, and water surface ripples.

[0024] To ensure consistency in subsequent calculations, reservoir topographic data, water level operation records, and multi-temporal remote sensing images all adopt the same spatial coordinate and elevation reference. Coordinate and elevation transformation parameters are locked with a configuration version number, serving as part of the evidence chain for subsequent dredging task unit generation and construction record tracing. At the time level, a time synchronization anchor is constructed using the standard time source currently used by the reservoir dispatch center. All sensor acquisition times, water level recording times, and remote sensing image capture times are uniformly converted to this standard time, while retaining the local time stamps in the original records. The time stamps inherent to each data source are considered intrinsic anchors. By comparing the time difference between the time synchronization anchor and the intrinsic anchor, records with offsets are corrected or marked. Preferably, the allowable time deviation for a single record is controlled within one to five minutes. When the deviation exceeds a preset threshold, the original record is retained and a time offset mark is added. The correspondence between the time synchronization anchor and the intrinsic anchor, as well as the time offset correction rules, are registered with a time alignment configuration version number for subsequent time caliber restoration. Based on this, a dual-anchor time base is formed throughout the entire dredging control cycle to constrain the positional relationship of multi-source information on the same timeline.

[0025] To reduce the impact of on-site acquisition errors and occasional interference, water level operation records can be resampled according to a preset time step, preferably a time step of not less than five minutes. For isolated deviation points in continuous records, a nearby multi-point smoothing method is used to weaken their impact. For time periods with continuous missing data not exceeding the set upper limit, interpolation is used to complete the water level sequence. For time periods exceeding the upper limit, a missing data mark is retained in the water level record to prompt subsequent steps to adopt a conservative strategy when using the information of this time period. For unreliable local areas in remote sensing images caused by cloud cover or strong reflection, an image quality mask can be set according to the image quality mark and the image brightness range. Areas covered by the mask will not be included in elevation estimation or sediment inversion for the time being.

[0026] After unifying the time and spatial references, based on the design beneficial water level, dead water level, and flood control limit water level given in the reservoir design data, the vertical range of the reservoir area is divided into several continuous elevation zones. Preferably, multiple layers are divided between the design beneficial water level and the dead water level at fixed elevation intervals of 0.5 meters to 1 meter. Above the flood control limit water level, whether to divide additional elevation zones depends on project needs, so that potential siltation areas under different operating conditions have clear vertical stratification. In the horizontal direction, the reservoir area is covered by a regular grid with the maximum extension range of the entire reservoir area as the boundary. Preferably, the planar size of the grid unit is set to 20 to 50 meters, and each grid unit is assigned... Each grid cell is assigned a unique number and registered along with its corresponding elevation zone range, thus forming a dredging reference grid layered by elevation zone. Each grid cell includes at least the planar location, elevation zone identifier, topographic base elevation, and fields for storing siltation thickness, safety risk value, benefit value, task status, and construction trajectory markers. Preferably, it is stored in a relational database in tabular form, with each record corresponding to a grid number and including a data source identifier and time stamp for association with the dual-anchor time base. In another implementation, the dredging reference grid can also be stored as a raster file, and the correspondence between the grid number and the file row and column numbers is maintained in an external configuration table.

[0027] After the dredging baseline grid is formed, the reservoir topographic data is spatially aligned with the baseline grid to assign a basic topographic elevation to each grid cell. Water level records are determined at each observation time using a dual-anchor time base. Multi-temporal remote sensing images, after geometric correction and matching with the reservoir boundary, map the water surface area and elevation to the dredging baseline grid at each acquisition time. This establishes a consistent relationship between reservoir topography, water level changes, and remote sensing observations at a unified spatial unit and time node. This allows subsequent dredging task unit division, risk and benefit field construction, and dredging equipment trajectory projection to directly reference the grid number and time marker in the dredging baseline grid for association, avoiding deviations caused by inconsistencies in coordinates and time between different data sources. This process is applicable to various reservoir projects with medium to large reservoir capacities and basic hydrological monitoring and remote sensing acquisition capabilities. For scenarios with only partial data sources, the dual-anchor time base and dredging data can be retained. Under the premise of a siltation baseline grid, some steps can be simplified. For example, when remote sensing conditions are temporarily lacking, the results of denser water depth measurements can be used to replace some remote sensing information. Preferably, for a typical medium-sized reservoir, the planar unit size of the siltation baseline grid can be set to 20 to 50 meters, the elevation band spacing can be set to 0.5 to 1 meter, the water level operation record sampling interval can be set to 5 to 30 minutes, and the remote sensing image retesting cycle can be set to 15 to 30 days. Under this combination of parameters, the spatial resolution of siltation control can be guaranteed to meet the accuracy requirements of conventional siltation operations, while the data storage scale and computational load can be controlled within the range that the existing computing resources of the dispatch center can bear. After engineering technicians configure coordinates and time references, perform resampling and smoothing, divide elevation bands and generate a siltation baseline grid according to the above steps, they can stably overlay siltation distribution, water level changes and equipment trajectories on the grid, so as to achieve orderly connection and reproduction of subsequent siltation control links.

[0028] S2. Map the remote sensing silt distribution onto the baseline grid, aggregate candidate areas according to connectivity, elevation zone, and construction radius, subdivide them into dredging task units based on equipment capabilities, and assign task keys. The specific implementation is as follows: After establishing the dredging reference grid, the acquired multi-temporal remote sensing images are geometrically corrected and radiometrically processed according to the aforementioned coordinate and elevation references. Based on water surface range identification and water depth inversion, the silt distribution results covering the reservoir area are obtained. Preferably, the silt distribution results are presented in raster form, with the estimated silt thickness at each raster location, in meters, along with the acquisition time and version marker of the corresponding remote sensing image. Based on the spatial registration relationship between the dredging reference grid and the remote sensing image, the silt distribution results are mapped to the dredging reference grid. Within each grid cell, the corresponding silt thickness value is statistically calculated or interpolated according to its planar position and elevation zone range. The silt thickness and elevation zone information are registered for each grid cell, and the source of the silt thickness, the remote sensing image version marker, and the mapping time marker are recorded in the grid field to ensure that subsequent updates to the same grid cell can be identified and reconstructed in chronological order.

[0029] To avoid unnecessary dredging decisions for areas with very thin siltation or uncertain measurements, a siltation thickness threshold can be pre-set. Grid cells below this threshold are considered areas that do not require dredging. The siltation thickness threshold is preferably determined comprehensively based on the reservoir's design allowable siltation value, dredging costs, and the minimum effective excavation thickness of the equipment. For example, it can be set in the range of 0.3 meters to 1 meter. At the same time, in conjunction with the permitted dredging area range delineated by the reservoir management unit, grid cells located in primary drinking water source protection zones, ecologically sensitive areas, or other prohibited construction areas are marked as prohibited dredging grids and do not participate in subsequent candidate area aggregation.

[0030] For grid cells whose siltation thickness reaches a preset threshold and are located within the allowable dredging area, their classification as belonging to the same continuous siltation patch is determined within the dredging reference grid by combining the spatial connectivity and elevation band continuity of adjacent grid cells. Spatial connectivity is preferably determined based on the adjacency relationship of grid cells in the planar direction, and can be set to four or eight adjacencies. Elevation band continuity preferably allows for an elevation difference within a defined range between two adjacent elevation bands, for example, a range of one to two meters, to ensure construction continuity of the candidate area in both the planar and vertical directions. Based on this, combined with single-ship or single-machine construction... The radius constrains the size of the candidate area. The construction radius of a single ship or machine can be understood as the effective operating radius that the dredging equipment can cover without large-scale relocation. It is preferably determined by a combination of the equipment arm length, suction pipe length and navigation accuracy. In practical applications, it can be set to a range of tens to hundreds of meters. By appropriately dividing the connected areas that exceed the construction radius limit, the interconnected grid cells that meet the construction radius constraint are aggregated into several candidate areas. The attributes such as the number of covered grids, average silt thickness, total silt volume and elevation zone distribution of the candidate areas are recorded at the candidate area level.

[0031] For each candidate area, to take into account the operational capabilities of different specifications of dredging equipment and on-site organization methods, dredging task units are further subdivided within the candidate area based on the operating width, allowable draft, transfer distance, and operational capacity of the dredging equipment that can be deployed on-site. The operating width can be understood as the effective lateral width that the dredging equipment can cover in a single round trip, preferably determined based on the hull width and the equipment's working radius. The allowable draft can be understood as the minimum and maximum water depth range that the equipment can withstand while ensuring safe navigation and stable operation, preferably verified in conjunction with water level operation records and elevation zone division results. The transfer distance can be understood as the allowable distance that the equipment can move between different work areas within the same construction window, preferably with an upper limit set while considering fuel consumption and time costs. The operational capacity can be understood as the volume of silt or work area that the equipment can complete per unit time, and can be set to a certain range value based on the equipment nameplate parameters and historical construction records, for example, a range of 100 to 1000 cubic meters per hour on an hourly scale.

[0032] Based on the above parameters, the candidate area is divided into multiple strips or blocks along the working width direction and the elevation band direction. It is ensured that the expected workload of each subdivided unit within a given construction window does not exceed the working capacity of the corresponding dredging equipment. On this basis, the subdivided units that meet the above constraints are determined as dredging task units. Each dredging task unit is associated with a set of defined grids, a target elevation band interval consisting of one or more adjacent elevation bands, and the expected dredging volume calculated according to the siltation thickness and grid area. It can also be accompanied by auxiliary attributes such as the relative position of the task unit in the reservoir area and the minimum distance from the water intake and important buildings.

[0033] To enable idempotent invocation and cross-stage traceability in subsequent scheduling, construction recording, and performance evaluation processes, a unique task key is generated for each dredging task unit. The unique task key can be set as an coded string formed by combining a grid number set summary, a target elevation zone identifier, a remote sensing image version marker, and a dredging baseline grid rule version marker. This coded string is registered in the task list table when the task unit is generated and is associated with the version management system of the dredging baseline grid and remote sensing images. Preferably, when the task key generation strategy changes, it is distinguished by the rule version number, so that dredging task units generated in the same spatial area under different remote sensing time phases can be distinguished and associated through the combination relationship of task key and version number.

[0034] By employing the above method, without altering the overall structure of the dredging baseline grid, the silt distribution obtained through remote sensing inversion is systematically mapped onto grid cells. Candidate areas and dredging task units are then layered according to constraints such as silt thickness threshold, allowable dredging area, spatial connectivity, elevation zone continuity, construction radius, and equipment capacity. This allows engineering technicians to directly call upon dredging task units within a unified data structure to complete subsequent scheduling optimization and construction control. Preferably, in a typical medium-sized reservoir scenario, the silt thickness threshold can be set to 0.5 meters, the single-vessel construction radius can be set to 100 to 200 meters, the number of grids covered by a single dredging task unit can be set to 10 to 50, and the corresponding expected dredging volume can be set to the range of 1,000 to 5,000 cubic meters. Under this parameter combination, both sufficient operational scale and economic efficiency of the dredging task unit are ensured, while also facilitating completion within a limited timeframe using a single device within the construction window. This allows for the direct reproduction and widespread application of the dredging task unit generation process in practice.

[0035] S3. Combining water level, inflow, equipment parameters, and environmental boundaries, calculate safety constraint values ​​and recovery benefit values ​​for each task unit, forming risk and benefit fields on the baseline grid. The specific implementation is as follows: After completing the division of dredging task units, in order to form a safety risk profile and dredging benefit profile within the reservoir area that can be used for scheduling decisions and construction constraints, the water level sequence in the water level operation record, the inflow scenario formed by the inflow forecast, the operating water depth range and maximum continuous operation time reflected in the dredging equipment parameters, and the prohibited areas and turbidity control boundaries in the ecological and environmental protection boundary are called in to calculate the safety constraint value and restoration benefit value for each dredging task unit.

[0036] The water level sequence in the water level operation record can be understood as a continuous water surface elevation sequence after alignment with the aforementioned dual-anchor time base. It is preferably recorded with time steps ranging from minutes to hours. During calculation, an observation window covering the planned construction window of the dredging task unit is extracted from the water level sequence according to the location and elevation zone of the dredging task unit. The length of the observation window is preferably the same as the length of the construction window. Within the observation window, the water level change amplitude is compared with the safe water level range corresponding to the elevation zone where the task unit is located. The safe water level range is preferably set with upper and lower limits based on the slope stability calculation results, ship draft requirements, and wave protection requirements.

[0037] Water inflow forecast can be understood as the future inflow sequence obtained based on upstream basin rainfall forecast and water inflow model. Water inflow scenario is a set of scenarios formed under different combinations of water inflow volume and duration. Preferably, the inflow is divided into several levels, and the duration range and probability of occurrence are set under each level. The water inflow scenario is mapped to the water level change trend through the reservoir water level-flow relationship, so as to determine whether there is a possibility that the water level may exceed the safe water level range for a short period of time within the construction window.

[0038] The operating water depth range reflected in the dredging equipment parameters can be understood as the minimum and maximum water depths allowed under the conditions of ensuring the equipment's sludge suction capacity and the stability of the vessel. The maximum continuous operating time can be understood as the upper limit of the continuous operating time of the equipment under the condition that there is no refueling, no personnel rotation, and no excessive temperature rise of the equipment. These parameters are preferably verified through the equipment manual and historical construction records. The prohibited areas in the ecological and environmental protection boundary refer to the areas where dredging operations are not allowed, as designated by the reservoir management department based on the requirements of drinking water protection, aquatic organism habitat protection, and cultural relic protection. The turbidity control boundary can be understood as the upper limit of water turbidity allowed at the downstream section or the boundary of the protected area during the dredging operation, preferably expressed in the form of turbidity meter readings or suspended solids concentration.

[0039] For each dredging task unit, based on its elevation zone and spatial location in the reservoir area, an observation window covering the construction window of the task unit is extracted from the water level sequence and inflow scenario. The observation window is compared with the safe water level range to determine whether there is an over-limit period. The inflow scenario is compared to determine whether a high inflow level will lead to a rapid rise in water level. At the same time, the slope stability coefficient and slope soil conditions of the bank section where the task unit is located are combined to comprehensively evaluate the construction safety of the task unit within the construction window. The evaluation results are summarized into safety constraint values. The safety constraint values ​​can be set as multi-level values ​​or continuous scores, preferably divided into several levels. A high level indicates that the safe water level range and slope stability requirements are met under various inflow scenarios, while a low level indicates that there is a risk of over-limit under some scenarios.

[0040] The calculation of the recovery benefit value is based on the expected reservoir volume to be restored by the dredging task unit. The reservoir volume can be obtained by summing the siltation thickness and the grid surface area of ​​the task unit's covered grid set. In order to characterize the contribution of the task unit to the overall flood control scheduling and water supply security, it is preferable to construct benefit indicators based on the relative positional relationship between the area where the task unit is located and the key flood control section, the improvement of reservoir storage capacity at high water levels, and the degree of improvement of water depth and flow velocity conditions near the water intake. These indicators are combined according to preset weights to form the recovery benefit value. The weight configuration is preferably to assign a higher weight to the impact of the reduction of flood level at the key flood control section than to the improvement of the flow state at the water intake.

[0041] The calculated safety constraint values ​​and recovery benefit values ​​are backfilled into the dredging baseline grid according to the grid set covered by the dredging task unit. The corresponding safety constraint value and recovery benefit value are written into each relevant grid cell, and the task key of the dredging task unit associated with the grid cell, as well as the water level sequence version, inflow scenario version, and equipment parameter version are registered in the field. This forms a risk field describing the spatial distribution of safety risks and a benefit field describing the spatial distribution of dredging benefits throughout the entire reservoir area. Each grid value in the risk field can be understood as the safety risk level or risk intensity of the dredging operation at the corresponding location. The higher the value, the greater the risk. Each grid value in the benefit field can be understood as the benefit level of the dredging operation at the corresponding location under the current operating target. The higher the value, the greater the benefit. The two types of fields are stored in the database in the form of fields that correspond one-to-one with the dredging baseline grid. The task key ensures that multiple grid cells covered by the same dredging task unit can be merged and called in the scheduling and evaluation process.

[0042] Under the optimal operating conditions of a typical medium-sized reservoir, the safe water level range can be set to a range of 0.5 to 1 meter above or below the design beneficial water level, the observation window length can be set to one to three days, and the safety constraint value can be divided into several levels. The recovery benefit value can be quantified based on the impact of unit reservoir capacity recovery on the reduction of the design flood level and the impact on the increase of the number of days of water supply guarantee during the dry season. The risk field and benefit field generated on this basis can be directly called by the scheduling module to prioritize the dredging task units with better safety constraint values ​​and higher recovery benefit values ​​and include them in the construction plan. Thus, the calculation process of safety constraint values ​​and recovery benefit values ​​and their application in the dredging control system can be reproduced in engineering practice.

[0043] S4. Within the preset construction window, using the dredging task unit as the decision-making unit, and combining the risk field, benefit field, and ship and machinery resources, establish a scheduling optimization model to obtain the dredging task cluster that satisfies the constraints and generate an instruction template specifying the operation polygon area, the allowable range of water level changes, and the target elevation zone for bottom clearing. The specific implementation is as follows: Upon entering the construction organization phase, based on the established dredging baseline grid, dredging task units, risk fields, and benefit fields, the dredging task units serve as the basic granularity for scheduling. Combined with the construction windows defined in the reservoir's annual scheduling plan, vessels, machinery, and personnel are organized to carry out dredging operations. A construction window can be understood as a continuous time period allocated for dredging operations while ensuring flood control safety, ecological protection, and equipment maintenance. Preferably, its start and end times are comprehensively divided based on the flood control water level process line, the breeding season of important fish species, the sensitive period of aquatic vegetation, and the maintenance plan of major dredging equipment. These times are then registered in the scheduling system in the form of start time, end time, and applicable water level range. Within each construction window, the dispatch terminal reads the safety risk level or risk intensity of the grid area corresponding to each dredging task unit from the risk field, reads the recovery benefit level of each dredging task unit from the benefit field, and obtains the list of dredging vessels and auxiliary vessels that can be called upon in the current window from the vessel and machinery resource pool. The vessel and machinery resource pool can be understood as a resource registration form that records the current status and available capabilities of various vessels and machinery. It includes at least the vessel and machinery identification, equipment type, working width, allowable draft, single-shift working time, daily available shift time, vessel speed, distance coefficient used to estimate relocation time, and applicable water level range, and indicates whether the vessel and machinery are under maintenance, on standby, or performing other tasks.

[0044] Based on this, the dispatching terminal constructs dispatching constraints, which include at least: whether the safety constraint value of the dredging task unit within the current construction window meets the set lower limit of the safety level, whether the recovery benefit value is higher than the benefit threshold, whether the water level in the area where the task unit is located within the construction window is within the applicable water level range of the corresponding vessel and machinery, whether the time required for the vessel and machinery to transfer from the current working position or mooring position to the area where the task unit is located is within the allowable range of the remaining time of the construction window, and whether the operating capacity of the vessel and machinery within the remaining shift time can cover the expected dredging volume of the task unit, etc.; when there are multiple candidate task units, the dispatching terminal performs weighted sorting of the safety constraint value and recovery benefit value of each task unit according to the pre-set safety priority weight and benefit priority weight. Preferably, task units with lower safety risks are given higher priority during sorting, and task units with higher recovery benefits are selected from task units with similar safety levels to enter the combined candidate set.

[0045] Subsequently, under the premise of meeting the above safety and resource constraints, the dispatching terminal combines several dredging task units into dredging task clusters according to spatial proximity and operational route continuity. Spatial proximity can be determined based on whether the distance between the geometric centers of the grid sets covered by the dredging task units is lower than a preset distance threshold. Operational route continuity can be achieved by optimizing the number of turns and large-angle reversals of the vessel operation path to not exceed a preset upper limit, thereby reducing equipment idle runs and frequent U-turns. A dredging task cluster can be understood as a set of dredging task units that are continuously completed by one or more vessels within a construction window. Each dredging task cluster records the list of dredging task units it contains, the corresponding task key set, the vessel identifier to be deployed, the planned start time, the planned completion time, and the total expected dredging volume.

[0046] For each dredging task cluster, the dispatch terminal generates a corresponding instruction template. The instruction template can be understood as a structured operation instruction unit for the construction terminal to execute. It at least specifies the operation polygon area of ​​the corresponding vessel and machine within the construction window, the allowable range of water level changes, the target elevation zone for bottom cleaning, and the monitoring index thresholds that need to be monitored on-site and trigger shutdown or load reduction actions. The operation polygon area can be constructed by connecting the boundaries of the grid set where the dredging task unit is located. Preferably, the vertex coordinates of the polygon are appropriately simplified to reduce the instruction length but keep it consistent with the original task unit boundary within the preset tolerance range. The allowable range of water level changes can be set as the upper and lower limits based on the intersection of the safe water level range and the applicable water level range of the vessel and machine. The target elevation zone for bottom cleaning can be set as the target elevation or target elevation range based on the target elevation zone range defined by each dredging task unit. The monitoring index triggering conditions may include water level exceeding the allowable range, turbidity exceeding the control limit, equipment vibration or temperature rise approaching the set upper limit, etc. When the construction terminal detects that the corresponding index continuously exceeds the threshold for a preset duration, it triggers the predefined load reduction, shutdown or evacuation actions.

[0047] The generated instruction template is sent from the dispatching terminal to the construction terminal via the dispatching control channel. The dispatching control channel can be understood as a communication link connecting the dispatching center with the control terminal on the ship or the shore-based operation terminal. Preferably, it supports information interaction functions such as instruction issuance, confirmation of receipt, and status reporting. When the instruction template is issued, it is accompanied by a unique instruction identifier and a set of task keys corresponding to the dredging task cluster to ensure idempotency and traceability during execution. When issuing the instruction template, the dispatching terminal limits the confirmation time limit of the construction terminal. It can be set to no more than a preset number of minutes between the issuance of the instruction and the receipt of the confirmation receipt from the construction terminal. If no confirmation is received within the specified time limit, the instruction template is resent according to the preset number of resends. The number of resends is preferably set to one to three. After multiple failures, the dredging task cluster is marked as requiring manual intervention to prevent erroneous instructions from continuously occupying resources.

[0048] After receiving the instruction template and completing local legality checks, the construction terminal returns a confirmation receipt. Subsequently, it organizes dredging equipment to perform specific dredging actions within the specified area and time according to the work polygon area, allowable water level variation range, and target elevation zone for bottom clearing as defined in the instruction template. During construction, it determines in real-time whether to proactively reduce load or suspend operations based on monitoring indicator trigger conditions. Upon completion or termination of construction, it returns an execution result record to the dispatch terminal, including the actual start time, actual completion time, actual dredging volume, and triggered monitoring event markers. This process is used in the optimal construction process of typical medium-sized reservoirs. In this case, the construction window length can be set to several to more than ten days, a single dredging task cluster can contain several to more than ten dredging task units, the instruction template acknowledgment time limit can be set to five to fifteen minutes, and the instruction resending number can be set to one to three times. Through the above settings, under the premise of ensuring scheduling safety and dredging efficiency, the scheduling terminal and the construction terminal can achieve stable issuance and execution of dredging task clusters under controllable delay and limited communication quality conditions. Thus, in engineering practice, the construction organization and scheduling control process based on dredging task units as the basic granularity and risk field and benefit field as the decision-making basis can be reproduced.

[0049] S5. Based on the instruction template, collect the location trajectory of the dredging equipment and the amount of dredging, locate the corresponding dredging task unit on the baseline grid, establish the task state machine, and record the trajectory and monitoring indicators during state transitions. The specific implementation is as follows: During the execution of the dredging task cluster, the construction terminal continuously collects the equipment location trajectory, underwater suction flow rate, and water level and turbidity monitoring values ​​during the operation period by the dredging equipment according to the aforementioned instruction template. The location trajectory can be understood as the coordinate sequence of the equipment center or operation head under a unified spatial coordinate reference, recorded at fixed time steps, preferably at time intervals of seconds to tens of seconds. The suction flow rate can be understood as the volumetric flow rate reading given by the flow meter installed on the sludge suction pipeline, and the unit can be set to cubic meters per hour or cubic meters per second. The water level monitoring value can be taken from the water level meter reading near the operation area. The turbidity monitoring value can be taken from the turbidity meter reading or suspended solids concentration reading deployed near the operation area or downstream control section. All of the above monitoring values ​​are accompanied by collection time markers and measuring point identifiers.

[0050] After the construction terminal collects the location trajectory, it projects the current position of the equipment onto the dredging reference grid in real time according to the spatial coordinate reference and grid division parameters of the aforementioned dredging reference grid. By calculating the inclusion relationship between the equipment position and the planar range of each grid unit, the grid unit where the current equipment is located is determined. The corresponding dredging task unit is indexed according to the pre-registered task key and target elevation zone information in the grid unit. In the case where the equipment's operating range covers multiple grid units, the grid unit where the equipment's center point is located can be preferred as the main grid unit, or the dredging volume can be distributed among multiple grid units according to the proportion of the overlapping area between the equipment's operating polygon and the grid unit.

[0051] For each dredging task unit, a corresponding task state machine is established in the dispatching terminal or construction terminal before construction begins. The state set of the task state machine includes at least four states: pending execution, in execution, completed execution, and requiring review. The pending execution state indicates that the equipment has not yet entered the work area. The in execution state indicates that the equipment has entered the work area covered by the task unit and is carrying out effective work. The completed execution state indicates that the cumulative dredging volume or operation time of the task unit has reached the preset completion threshold and the conditions for requiring review have not been triggered. The requiring review state indicates that a situation has occurred during the construction process that exceeds the safety or environmental protection boundaries or that the construction has not achieved the expected results. A manual or automatic review is required during the dispatching phase.

[0052] As the dredging equipment moves along the work polygon area defined by the instruction template, the construction terminal determines whether to transition from the pending state to the executing state based on whether its current position has entered the grid set corresponding to the dredging task unit. When it is detected that the equipment is continuously located within the grid set covered by the task unit for a period of time and the suction flow rate is continuously higher than the set effective working flow rate lower limit, the state of the task unit is set to executing, and the dredging volume and effective working time corresponding to the task unit are accumulated. When it is detected that the equipment position completely leaves the grid set covered by the task unit for a period of time exceeding the set departure threshold, and the accumulated dredging volume reaches the preset ratio of the expected dredging volume calculated based on the siltation thickness and the target elevation zone, the state of the task unit is transitioned from executing to executing. In a preferred case, the preset ratio can be set to 0.8 to 1 times the expected dredging volume. If the ratio is not reached but the equipment has left the task area and will not return in the short term, the state can be transitioned to the need-to-review state to prompt the dispatcher to review the area in the next round of task generation.

[0053] To ensure traceability and evidence retention during the construction process, at each task status transition, the construction terminal traces back a certain observation time window from its current location, recording equipment trajectory segments, cumulative dredging volume, and water level and turbidity monitoring values ​​for the corresponding time period. These records are packaged together with the task key of the dredging task unit and the currently effective rule version number to generate a corresponding operation record unit. The operation record unit can be temporarily stored locally on the construction terminal and uploaded to the operation archive at the scheduling end through the scheduling control channel according to the set batch reporting cycle or status transition time. The operation archive organizes each operation record with the task key as the primary key and records the rule version number used when the record was generated. This is used to restore and analyze the historical construction process according to the current rule definition even after rule adjustments.

[0054] During construction, when the construction terminal detects that the water level or turbidity value is close to or exceeds the allowable range of water level variation or the turbidity control limit defined by the instruction template—for example, when the water level is close to the upper limit within a preset proportion for several consecutive sampling times or the turbidity exceeds the control limit by a preset proportion—the task status of the task unit can be immediately locked as requiring review. A safety or environmental protection marker is added to the operation record to distinguish whether the suspension is due to safety reasons or environmental restrictions. After the task status is locked as requiring review, the construction terminal can perform load reduction, shutdown, or evacuation according to the predefined actions in the instruction template. When the dispatching terminal generates dredging task units and dredging task clusters in the next round, it queries the operation archive containing the required review status. The task keys for reviewing status and safety markers are listed as key review targets. Priority is given to retesting siltation conditions or adjusting construction windows, water level control strategies, and equipment combinations. Under the optimal operating conditions of a typical medium-sized reservoir, the sampling interval for equipment location trajectory can be set to one to five seconds, the lower limit of effective operating flow can be set to a proportional range of the equipment's rated flow, and the time step for transmitting water level and turbidity monitoring values ​​can be set to ten seconds to one minute. After configuring the acquisition rhythm, state transition conditions, and operation archive structure in the above manner, engineering technicians can reproduce the state machine management and operation record process centered on the dredging task unit task keys and rule versions in actual projects, providing a complete basic record for subsequent performance evaluation and rule optimization.

[0055] S6. Based on the subsequent remote sensing sediment distribution, remap it to the baseline grid, calculate performance indicators according to the target elevation of the task unit, adjust the risk field threshold and benefit weight according to the performance indicators, and generate a rule version for subsequent task unit generation and scheduling. The specific implementation is as follows: After one or more construction windows are completed and the corresponding time sequence is retested, in order to evaluate the actual effect of this round of dredging and to revise the subsequent dredging control strategy, the dispatching terminal obtains the subsequent remote sensing silt distribution results covering the reservoir area after this round of construction. After the subsequent remote sensing silt distribution results are geometrically corrected and quality-screened according to the aforementioned coordinate and elevation benchmarks, they are mapped to the dredging benchmark grid again, and the silt thickness and its time marker after construction are registered in each grid cell.

[0056] The dispatching unit, based on the target elevation zone agreed upon in the instruction template for each dredging task unit, compares the pre-construction siltation thickness, post-construction siltation thickness, and the design elevation corresponding to the target elevation zone within the grid set covered by that task unit. It then calculates the reservoir capacity recovery index for that dredging task unit. The reservoir capacity recovery index can be understood as the ratio between the change in effective reservoir capacity before and after construction within the task unit area and the theoretically recoverable reservoir capacity. The theoretically recoverable reservoir capacity is preferably calculated based on the elevation difference between the pre-construction siltation thickness and the target elevation zone, combined with the grid area. The actual reservoir capacity recovery is based on the post-construction siltation thickness... The elevation difference between the elevation and the target elevation zone is corrected; at the same time, the local secondary siltation rate is calculated in this area. The local secondary siltation rate can be understood as the ratio of the newly added siltation thickness from the end of construction to the re-measurement period to the allowable residual siltation space above the target elevation zone after construction. It is used to reflect the re-siltation trend in this area after this round of construction. For the same dredging task unit to which the dredging task cluster belongs, the reservoir capacity recovery index and local secondary siltation rate of multiple dredging task units covered by it can be weighted and aggregated according to the grid area or expected reservoir capacity contribution to obtain the reservoir capacity recovery index and local secondary siltation rate at the level of the dredging task cluster.

[0057] After the above calculations are completed, the scheduling terminal associates the reservoir capacity recovery index and local secondary siltation rate of each dredging task unit and dredging task cluster with the corresponding task key, task state machine record, and operation record unit stored in the operation archive to form a performance record. The performance record can be understood as a comprehensive record unit with the task key as the main identifier, while also carrying construction process information and construction result information. It includes at least the task key, the identifier of the dredging task cluster to which it belongs, the rule version number, the reservoir capacity recovery index, the local secondary siltation rate, whether the status requiring review is triggered during the construction process, the safety mark or environmental protection mark, and the statistical characteristics of the main monitoring indicators. In the scheduling interface, the reservoir capacity recovery index can be divided into several levels. For example, above 0.8 is marked as a high recovery level, 0.5 to 0.8 is marked as a medium recovery level, and below 0.5 is marked as a low recovery level, so as to intuitively display the dredging effect of different areas.

[0058] Based on the aggregated performance records, the dispatching unit can group dredging task units according to risk level and analyze the safety and efficiency performance of task units at different risk levels during actual construction. Safety performance can be statistically analyzed based on whether water level or turbidity exceedance events occur during construction, whether re-inspection status is frequently triggered, and whether mid-construction evacuation occurs. Efficiency performance can be compared based on the distribution of reservoir capacity recovery indicators, contribution to the reduction of water level at key flood control sections, and the degree of improvement in hydraulic conditions near the water intake. When it is found that dredging task units under a certain risk level generally have a high safety margin in multiple construction windows, the risk threshold used to generate safety constraint values ​​in the risk field can be relaxed accordingly, and the risk level of the task area originally classified as high risk level can be appropriately downgraded. When it is found that dredging task units under a certain risk level generally have safety boundaries approaching or exceeding limits, the risk level can be adjusted accordingly. When a situation triggers a re-inspection status multiple times, the risk threshold can be tightened accordingly. Task areas originally classified as medium-risk can be upgraded to higher risk levels or their combined scale within the same construction window can be restricted. When a dredging task unit in a certain spatial location or elevation zone is found to contribute significantly more to reservoir capacity restoration than other areas, or to improve the water level and intake conditions of flood control sections far more effectively than other areas, the weight parameters of different benefit indicators in the benefit field can be adjusted accordingly. The weight of the contribution to reservoir capacity at key flood control sections or the weight of benefit indicators related to water source security can be increased. An abnormal upper limit threshold can be set for the local secondary siltation rate. For example, the range of 0.5 to 0.8 can be designated as a suspicious resilation range, and areas above 0.8 can be marked as abnormal resilation ranges. This allows for more conservative construction strategies or increased monitoring frequency for such areas in subsequent cycles.

[0059] After completing the above analysis and adjustments, the scheduling terminal will solidify the new risk threshold configuration and benefit weight configuration, along with other rule parameters used for dredging task unit generation, dredging task cluster combination, instruction template generation, and task state machine management, into a new rule version. The new rule version carries a complete version number chain, which can be understood as an ordered sequence of version numbers recording the evolution relationship from the initial version to the current version, facilitating the tracing of the source and effective time of each adjustment in subsequent analysis. When generating a new rule version, an index relationship between each task key and the rule version number is established, associating the task key with all dredging task units, dredging task clusters, and performance records using that rule version, to ensure that tasks and construction results generated under different rule versions can be distinguished under multi-cycle operation conditions.

[0060] After the new rule version takes effect, it will be used to generate new dredging task units, construct new risk and benefit fields, and form new dredging task clusters in subsequent cycles. This will enable the dredging control strategy to be continuously corrected and optimized in a closed loop of multiple rounds of construction and retesting. At the same time, by maintaining the correspondence between task keys, rule version numbers, and monitoring records in the operation archive and performance records, an evidence chain covering multiple construction cycles will be formed. The evidence chain can be used by management units or third parties to review and review the implementation of safety boundaries, the fulfillment of ecological and environmental protection requirements, and the effectiveness of dredging when needed. Under the optimal working conditions of typical medium-sized reservoirs, the rule version can be updated annually or in several construction windows. The reservoir capacity recovery index level and the abnormal threshold of local secondary siltation rate can be set and adjusted through configuration parameters. After configuring the performance calculation rules, rule version management, and evidence chain recording mechanism in the above manner, engineering technicians can reproduce the multi-cycle adaptive adjustment process of the dredging control strategy in actual projects.

[0061] Example 2: Figure 2 A schematic diagram of the reservoir dredging control system based on remote sensing monitoring of the present invention is provided. The reservoir dredging control system based on remote sensing monitoring includes: The reference grid and time base construction module is used to acquire reservoir topographic data, operation records and remote sensing images, construct a dredging reference grid divided by elevation zones, and establish a dual-anchor time base to complete the data alignment of reservoir topographic data, operation records and remote sensing images. Task Unit Generation Module: This module maps the remote sensing silt distribution to the dredging baseline grid, aggregates candidate areas based on connectivity, elevation zone, and construction radius, and further subdivides the candidate areas based on the operational capabilities of the dredging equipment to generate dredging task units, assigning a unique task key to each dredging task unit. Risk and benefit generation module: It is used to combine water level, inflow, equipment parameters and environmental boundaries to calculate safety constraint value and recovery benefit value for each dredging task unit, and to register the safety constraint value and recovery benefit value according to the grid unit on the dredging benchmark grid to form risk field and benefit field; The scheduling and instruction template generation module is used to establish a scheduling optimization model within a preset construction window, using dredging task units as decision units, and combining risk field, benefit field and ship and machinery resources to obtain dredging task clusters that meet safety constraints and resource constraints, and generate instruction templates that include the operation area, water level range and target elevation. Process monitoring and task status management module: It is used to collect the location trajectory and dredging volume of the dredging equipment according to the instruction template, locate the corresponding dredging task unit on the dredging benchmark grid, establish a task state machine that corresponds one-to-one with each dredging task unit, and record equipment trajectory segments and related monitoring indicators when the task status changes. The performance feedback and rule version generation module is used to remap the dredging baseline grid based on the subsequent remote sensing silt distribution, calculate performance indicators according to the target elevation of each dredging task unit, adjust the threshold of the risk field and the weight of the benefit field according to the performance indicators, and generate updated rule versions for subsequent dredging task unit generation and scheduling.

[0062] Example 3: Figure 3 A schematic diagram of the electronic reservoir dredging device based on remote sensing monitoring of the present invention is provided. The electronic reservoir dredging device based on remote sensing monitoring includes a processor, a memory, and a communication interface. The processor is used to execute program instructions stored in memory to analyze, process, and schedule data based on remote sensing monitoring. The memory is used to store remote sensing image data, reservoir topographic data, operation record data, and program instructions for executing reservoir dredging control. The communication interface is used to enable data interaction between electronic devices and remote sensing acquisition terminals, construction terminals, and dispatch centers.

[0063] The hardware components of the electronic device and the functional connections between the processor, memory, and communication interface are as follows: The processor, memory, and communication interface form an integrated control and information interaction unit in the remote sensing-based reservoir dredging electronic device. The processor is electrically connected to the memory via a system bus and is used to call the dredging baseline grid generation program, dredging task unit partitioning program, risk field and benefit field construction program, construction scheduling and task state machine management program, and performance evaluation and rule version management program stored in the memory. During operation, it loads reservoir topographic data, water level operation records, remote sensing dredging distribution, vessel and machinery resource information, and construction monitoring records into the workspace for calculation and processing. The memory is used to store dredging baseline grid data, the mapping relationship between dredging task units and task keys, and risk fields and benefit fields in a structured manner. The system includes a data set, instruction templates and runtime archive, performance records and rule version number chain, and provides the processor with space to read and write program instructions and intermediate calculation results. The communication interface is electrically connected to the processor to establish a data interaction channel between the device and external remote sensing data sources, hydrological monitoring systems, ship and machinery construction terminals, and scheduling management platforms. It receives externally uploaded topography, water level, remote sensing images, equipment monitoring and execution result information, and sends the dredging instruction templates, task status update results and performance analysis results generated by the processor according to the program to the external system. This enables centralized operation of dredging control logic, real-time aggregation and distribution of multi-source information, and continuous maintenance of cross-cycle evidence chains under a unified hardware architecture.

[0064] All calculations involved in the embodiments are dimensionless numerical calculations, and the preset parameters and thresholds in the calculations are set by those skilled in the art according to the actual situation.

[0065] It should be noted that this invention can be deployed on the device itself to realize embedded applications, or it can run on a PC or other terminal with a user interface, thereby meeting various hardware environments and usage requirements.

[0066] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wireless or wired transmission; wired transmission methods include optical fiber, twisted pair, coaxial cable, etc.; wireless transmission includes infrared, microwave, etc. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center containing one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0067] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0068] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0069] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0070] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0071] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0072] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0073] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A reservoir dredging control method based on remote sensing monitoring, characterized in that, include: S1. Acquire reservoir topographic data, operation records and remote sensing images, construct a dredging benchmark grid divided by elevation zones, and establish dual-anchor time-base aligned data; S2. Map the remote sensing silt distribution onto the baseline grid, aggregate candidate areas according to connectivity, elevation zone and construction radius, and subdivide them into dredging task units according to equipment capabilities and assign task keys. S3. Combine water level, inflow, equipment parameters and environmental protection boundaries to calculate safety constraint values ​​and recovery benefit values ​​for each task unit, and form risk field and benefit field on the baseline grid; S4. Within the preset construction window, take the dredging task unit as the decision unit, and establish a scheduling optimization model in combination with the risk field, benefit field and ship and machine resources to obtain the dredging task cluster that meets the constraints and generate an instruction template that specifies the operation polygon area, the allowable range of water level changes and the target elevation zone for bottom cleaning. S5. Collect the location trajectory and dredging volume of the dredging equipment according to the instruction template, locate the corresponding dredging task unit on the benchmark grid, establish the task state machine and record the trajectory and monitoring indicators during state transition. S6. Based on the subsequent remote sensing sediment distribution, the data is remapped to the baseline grid. Performance indicators are calculated according to the target elevation of the task unit. The risk field threshold and benefit weight are adjusted according to the performance indicators, and a rule version is generated for subsequent task unit generation and scheduling.

2. The reservoir dredging control method based on remote sensing monitoring according to claim 1, characterized in that, S1 includes: The reservoir topographic data were converted according to a unified elevation datum and plane coordinate datum, and the coordinate transformation parameters and version marks were recorded. A time base is obtained by constructing a time anchor based on the standard time of the dispatch center, using the time stamps of water level operation records and remote sensing images as intrinsic anchors, correcting the time stamps based on the time difference between the time anchor and the intrinsic anchors and registering the time alignment rule version. Elevation zones are divided according to the designed beneficial water level, dead water level, and flood control limit water level. A regular grid with a unique number is generated within the plane of the reservoir area. In each grid cell, the elevation zone identifier, the topographic base elevation, the siltation thickness record, the safety risk record, the benefit record, the task status record, and the construction trajectory record are recorded to form a dredging benchmark grid.

3. The reservoir dredging control method based on remote sensing monitoring according to claim 1, characterized in that, S2 include: Multi-temporal remote sensing images are corrected according to coordinate and elevation benchmarks, and the siltation distribution covering the reservoir area is obtained based on water surface range identification and water depth inversion. The silt distribution is mapped to the dredging baseline grid, and the silt thickness, elevation zone, source of silt thickness, remote sensing image version marker, and mapping time marker are recorded in each grid cell. Based on the siltation thickness threshold, grid cells with siltation thickness below the threshold are registered as grids that do not require dredging; Register grid units located in areas where dredging is prohibited as dredging grids; Grid cells that simultaneously meet the criteria of having a siltation thickness threshold and being located within an allowable dredging area will be registered as candidate dredging grids.

4. The reservoir dredging control method based on remote sensing monitoring according to claim 3, characterized in that: In the dredging benchmark grid, for grid cells registered as candidate dredging grids, candidate regions are generated by aggregation based on planar adjacency and elevation zone continuity, and the range of candidate regions is constrained based on the construction radius of the dredging equipment. Within the candidate area, dredging task units are generated by subdividing the dredging equipment based on its operating width, draft, transfer distance, and operational capabilities. Each dredging task unit is associated with a defined grid set and target elevation zone, and the expected dredging volume is registered. A unique task key is generated, which is a combination of the grid set summary, target elevation zone identifier, remote sensing image version marker, and dredging baseline grid rule version marker. The unique task key is then registered in the task list and associated with version management.

5. The reservoir dredging control method based on remote sensing monitoring according to claim 1, characterized in that, S3 include: During the dredging control cycle, based on the water level sequence in the water level operation record, the inflow scenario formed by the inflow forecast, the operating water depth range and maximum continuous operating time in the dredging equipment parameters, as well as the prohibited areas and turbidity control boundaries in the ecological and environmental protection boundaries, the observation window corresponding to the construction window of each dredging task unit is extracted. Based on the water level changes and bank slope stability conditions within the observation window, safety constraint values ​​are determined. Based on the expected reservoir volume to be restored by the dredging task unit and the impact on the operation status of key flood control sections and water intakes, restoration benefit values ​​are determined. The safety constraint values ​​and restoration benefit values ​​are then written into the dredging baseline grid according to the grid units covered by the dredging task unit to generate risk and benefit fields. Register the task key, water level sequence version, inflow scenario version, and equipment parameter version in the relevant grid cells.

6. The reservoir dredging control method based on remote sensing monitoring according to claim 1, characterized in that, S4 include: During the construction organization phase, the dredging task unit is used as the scheduling granularity. Within the construction window, the dredging task unit is selected based on the safety constraint value in the risk field and the recovery benefit value in the benefit field. The dredging task unit that meets the safety constraint and resource constraint is determined in combination with the ship and machine capacity in the ship and machine resource pool. Dredging task clusters are generated by combining dredging task units according to spatial proximity and operational route coherence. A command template is generated for each dredging task cluster. The command template specifies the working polygon area, the allowable range of water level changes, the target elevation zone for dredging, and the monitoring index thresholds. It is then sent to the construction terminal through the scheduling and control channel. The instruction template carries a unique instruction identifier and a corresponding set of task keys. The construction terminal executes the dredging operation according to the instruction template and generates an execution result record.

7. The reservoir dredging control method based on remote sensing monitoring according to claim 1, characterized in that, S5 include: During the execution of the dredging task cluster, the construction terminal collects the location trajectory of the dredging equipment, underwater suction flow rate, water level monitoring value and turbidity monitoring value according to the instruction template; Project the current position of the equipment onto the dredging reference grid to determine the grid cell to which it belongs and index the corresponding dredging task cell. Establish a task state machine for each dredging task cell, including the states of pending execution, execution, execution completion, and need for review. The process transitions between pending execution, execution, and execution completion states based on whether the equipment enters or leaves the task area and whether the cumulative dredging volume reaches the expected dredging volume ratio. When the water level monitoring value exceeds the allowable range of water level change or the turbidity monitoring value exceeds the turbidity control limit, the task status will be changed to "required for review". Each time the task status is changed, an operation record with a bound task key and rule version number will be generated and written to the operation archive for subsequent scheduling and performance evaluation.

8. The reservoir dredging control method based on remote sensing monitoring according to claim 1, characterized in that, S6 include: After the construction window ends and the re-measurement is completed, the reservoir capacity restoration index and local secondary siltation rate are calculated based on the subsequent remote sensing siltation distribution mapping of the siltation benchmark grid, according to the grid set covered by the siltation task unit. Performance records are generated at the dredging task unit and dredging task cluster levels, and these performance records are associated with task keys, task state machine records, and operation record units in the operation archive. Analyze safety and benefit performance according to risk level, adjust the risk threshold of the risk field and the weight parameters of the benefit field, generate rule versions and record the version number chain; Establish an index relationship between task keys and rule version numbers, call the rule version in subsequent dredging task unit generation and dredging task cluster construction, and form a cross-cycle evidence chain through performance records and operation record units in the operation archive.

9. A reservoir dredging control system based on remote sensing monitoring, used to implement the reservoir dredging control method based on remote sensing monitoring as described in any one of claims 1-8, characterized in that, include: The reference grid and time base construction module is used to acquire reservoir topographic data, operation records and remote sensing images, construct a dredging reference grid divided by elevation zones, and establish a dual-anchor time base to complete the data alignment of reservoir topographic data, operation records and remote sensing images. Task Unit Generation Module: This module maps the remote sensing silt distribution to the dredging baseline grid, aggregates candidate areas based on connectivity, elevation zone, and construction radius, and further subdivides the candidate areas based on the operational capabilities of the dredging equipment to generate dredging task units, assigning a unique task key to each dredging task unit. Risk and benefit generation module: It is used to combine water level, inflow, equipment parameters and environmental boundaries to calculate safety constraint value and recovery benefit value for each dredging task unit, and to register the safety constraint value and recovery benefit value according to the grid unit on the dredging benchmark grid to form risk field and benefit field; The scheduling and instruction template generation module is used to establish a scheduling optimization model within a preset construction window, using dredging task units as decision units, and combining risk field, benefit field and ship and machinery resources to obtain dredging task clusters that meet safety constraints and resource constraints, and generate instruction templates that include the operation area, water level range and target elevation. Process monitoring and task status management module: It is used to collect the location trajectory and dredging volume of the dredging equipment according to the instruction template, locate the corresponding dredging task unit on the dredging benchmark grid, establish a task state machine that corresponds one-to-one with each dredging task unit, and record equipment trajectory segments and related monitoring indicators when the task status changes. The performance feedback and rule version generation module is used to remap the dredging baseline grid based on the subsequent remote sensing silt distribution, calculate performance indicators according to the target elevation of each dredging task unit, adjust the threshold of the risk field and the weight of the benefit field according to the performance indicators, and generate updated rule versions for subsequent dredging task unit generation and scheduling.

10. A reservoir dredging electronic device based on remote sensing monitoring, used to implement the reservoir dredging control method based on remote sensing monitoring as described in any one of claims 1-8 and the reservoir dredging control system based on remote sensing monitoring as described in claim 9, characterized in that, include: Processor: Used to execute program instructions stored in memory to analyze, process, and schedule data based on remote sensing monitoring; Memory: Used to store remote sensing image data, reservoir topographic data, operation record data, and program instructions for executing reservoir dredging control; Communication interface: Used to enable data interaction between electronic devices and remote sensing acquisition terminals, construction terminals, and dispatch centers.

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