Determination system for suitable elevation of mangrove restoration in aquaculture pond based on tidal level numerical simulation

Abstract

The application discloses a system for determining suitable elevation of mangrove restoration in a breeding pond based on numerical simulation of tidal level, and relates to the technical field of marine ecological restoration, and specifically comprises a collection and processing module, a tidal level model module, a scenario simulation module, a relationship analysis module, a screening and comparison module and an optimization decision module. The system first collects basic data; a three-dimensional hydrodynamic numerical model is established based on the principle of hydrodynamics; the water level response under different working conditions is simulated according to the basic data and the operation rules of the gate; through statistical analysis, the daily average flooding time of any given elevation point in the breeding pond within the simulation period is calculated, and a corresponding relationship curve of the elevation at different positions and the daily average flooding time is established; the data of the flooding tolerance time of the target mangrove plant species is taken as a screening condition, and is compared with the corresponding relationship curve; finally, the theoretical suitable elevation range is calculated, and the suitable elevation range determined under the working condition is taken as the basis for guiding the design of the suitable elevation of the mangrove restoration in the breeding pond.

Description

Technical Field

[0001] This invention relates to the field of marine ecological restoration technology, specifically to a system for determining suitable elevations for mangrove restoration in aquaculture ponds based on numerical simulation of tidal levels. Background Technology

[0002] Mangroves are important ecosystems growing in the intertidal zone of tropical and subtropical coasts, playing vital roles in wave dissipation and shoreline protection, carbon sequestration and storage, water purification, and maintaining biodiversity. Traditional coastal aquaculture ponds (such as fish ponds and shrimp ponds) encroach on the distribution space of coastal ecosystems such as mangroves and salt marshes, and traditional aquaculture methods also bring many ecological and environmental problems, damaging the marine ecosystem.

[0003] The mangrove-aquaculture hybrid model is a sustainable ecological aquaculture approach that aims to create a mutually beneficial and symbiotic system by planting mangroves within aquaculture ponds. Mangroves directly or indirectly provide food for the farmed organisms and improve the aquaculture environment, while the excrement of the farmed organisms provides nutrients for mangrove growth, thus achieving a win-win situation for ecological protection and economic development. One of the key technologies of this restoration model is identifying and constructing a "suitable elevation zone" for mangrove growth within the aquaculture ponds. Prolonged flooding can cause mangrove seedlings to die from oxygen deprivation, while prolonged exposure to the water surface can also lead to mangrove death, failing to achieve the goal of ecological restoration.

[0004] In existing technologies, determining the suitable elevation for mangrove planting largely relies on field surveys and empirical judgment, or estimation based on the local mangrove distribution range on natural mudflats. However, for semi-enclosed artificial systems like sluice-controlled aquaculture ponds, the internal water level is regulated by artificial gates, differing significantly from natural tidal processes. Directly planting within the pond based on the elevation of natural mudflats will result in a mismatch in flooding regimes and failure. Currently, the lack of a scientific and quantitative method to guide the precise determination of suitable mangrove planting elevations within aquaculture ponds has become a bottleneck for promoting this model.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a system for determining the appropriate elevation for mangrove restoration in aquaculture ponds based on numerical simulation of tidal levels, in order to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a system for determining suitable elevations for mangrove restoration in aquaculture ponds based on tidal level numerical simulation, specifically including: a data acquisition and processing module, a tidal level model module, a scenario simulation module, a relationship analysis module, a screening and comparison module, and an optimization decision-making module;

[0008] Data Acquisition and Processing Module: Collects and preprocesses basic data of the target aquaculture pond and its surrounding area;

[0009] Tidal model module: Based on hydrodynamic principles, a three-dimensional hydrodynamic numerical model covering the aquaculture pond and surrounding area is established, and calibrated and verified based on the aforementioned basic data;

[0010] Scenario simulation module: Based on the calibrated and verified three-dimensional hydrodynamic numerical model, it simulates the water level response under different gate operating conditions according to basic data and gate operation rules;

[0011] Relationship Analysis Module: Based on the simulated output water level response, statistical analysis is performed to calculate the average daily flooding time at any given elevation point in the aquaculture pond during the simulation period, and to establish the correspondence curve between the elevation at different locations in the aquaculture pond and the average daily flooding time.

[0012] Screening and comparison module: The flood tolerance duration data of the target mangrove plant species is used as the screening condition and compared with the corresponding relationship curve;

[0013] The optimization decision-making module calculates the theoretically suitable elevation range based on the optimal water level response under different gate operating conditions, and uses the suitable elevation range determined under the operating conditions as the final basis for guiding the elevation design and engineering leveling of the mangrove planting area in the aquaculture pond.

[0014] As a preferred embodiment of the system for determining suitable elevations for mangrove restoration in aquaculture ponds using tidal level numerical simulation as described in this invention, wherein:

[0015] Data was collected through field measurements and unmanned aerial vehicle surveys.

[0016] The basic data includes: the layout plan of the aquaculture pond, existing gate data, elevation data of the pond bottom and embankment, historical tide level observation data, expected design parameters of the new gate to be renovated, and flood tolerance data of one or more mangrove plant species to be planted.

[0017] The existing gate data includes the location, size, and elevation of the existing gates; the expected design parameters of the new gates to be upgraded include the type, size, and opening / closing logic of the new gates; and the flood resistance time data includes the upper and lower limits of the suitable daily flood time for the target planting area.

[0018] The preprocessing specifically includes:

[0019] Detect missing values ​​in the basic data and delete the corresponding missing value records;

[0020] The system detects and deletes extreme values, drift, duplicate records, and excessively high proportions of null values ​​in the basic data.

[0021] The plan layout data, elevation data of the pond bottom and embankment are projected onto a unified coordinate system based on the GPS system.

[0022] Align the elevation of the pond bottom and the embankment with the 0m water level.

[0023] Check the consistency of gate position, size, and current elevation, remove duplicate data, and correct coordinate errors;

[0024] Verify the consistency of the new gate type, opening and closing logic, and logical constraints.

[0025] As a preferred embodiment of the system for determining suitable elevations for mangrove restoration in aquaculture ponds using tidal level numerical simulation as described in this invention, wherein:

[0026] Based on the aforementioned basic data and hydrodynamic principles, the aquaculture pond and its surrounding area are mapped onto a three-dimensional network to construct a three-dimensional hydrodynamic numerical model.

[0027] The hydrodynamic principles described use a shallow-water approximation of the three-dimensional Navier-Stokes equations based on the hydrostatic pressure assumption to describe the motion, pressure changes, and velocity distribution of water bodies.

[0028] The three-dimensional hydrodynamic numerical model is discretized horizontally and vertically;

[0029] The initial water depth and boundary conditions of the three-dimensional hydrodynamic numerical model are defined based on the aforementioned basic data.

[0030] The boundary conditions include tidal level drive of open boundaries, shoreline and pond bottom boundaries, gate coupling boundaries, and wind stress and air pressure source terms.

[0031] Input basic data to perform a preliminary run, and output a three-dimensional tidal field;

[0032] The three-dimensional tidal field includes a water level field, a velocity field, and a stratified field;

[0033] The three-dimensional tidal field during the monitoring process is compared with the historical three-dimensional tidal field, and the deviation between the two is calculated for calibration and verification.

[0034] As a preferred embodiment of the system for determining suitable elevations of mangrove planting and restoration areas based on tidal level numerical simulation as described in this invention, wherein:

[0035] M gate operating conditions are preset and N rounds of random simulation are performed. The number of simulations is within a preset range, and the input three-dimensional tidal field is different in each round of simulation, and the similarity is less than a threshold.

[0036] Initialize the gate's operating conditions based on the initial time series;

[0037] Using three-dimensional tidal fields of different time series as simulation inputs, M water level responses are obtained;

[0038] The discreteness of the three-dimensional tidal field of each time series in N rounds of stochastic simulation is evaluated through periodic iterative simulation of no less than 15 days, and the stability coefficient is calculated.

[0039] The simulated quantity is used as the horizontal axis, and the water level response is used as the vertical axis;

[0040] Calculate the local discreteness of the corresponding water level response in N simulations respectively;

[0041] After normalizing the number of simulations in N rounds, the local discreteness is weighted and fused as the weight of each simulation number on the horizontal axis to calculate the stability coefficient.

[0042] The water level response with the highest stability coefficient is selected as the optimal water level response for the gate operation state in the corresponding time series.

[0043] As a preferred embodiment of the system for determining suitable elevations for mangrove restoration in aquaculture ponds based on tidal level numerical simulation as described in this invention, wherein:

[0044] Initialize the average daily flooding time for any given elevation point;

[0045] The time series of water level response is resampled to daily granularity, and for any given elevation point at any given intraday time, it is determined whether the current water level response has submerged the surface elevation of that point.

[0046] By pairing any given elevation point with the average daily flooding time, a curve showing the correspondence between the elevation of different locations within the aquaculture pond and the average daily flooding time is established through numerical integration.

[0047] On the other hand, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, it implements the steps of the system for determining the suitable elevation for mangrove restoration in aquaculture ponds based on tidal level numerical simulation as described above.

[0048] On the other hand, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements the steps of the system for determining the suitable elevation for mangrove restoration in aquaculture ponds based on tidal level numerical simulation as described above.

[0049] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0050] 1. Starting from one of the key limiting factors for mangrove growth, the flooding time is quantitatively predicted through hydrodynamic numerical simulation, avoiding the blindness of experience-based judgment and determining a more scientific and accurate elevation range.

[0051] 2. Before the actual engineering modification, the effects of different gate modification schemes and operation strategies can be simulated and evaluated in the computer model, realizing a closed loop of "design-simulation-optimization" and reducing the risk of project failure.

[0052] 3. It can adapt to aquaculture pond renovation projects of different regions, scales, and mangrove species. By adjusting model parameters and operating conditions, it can provide customized solutions for a wide variety of specific projects.

[0053] 4. By comparing the results under different operating conditions, the balance between ecological and production needs can be revealed intuitively, providing scientific support for managers to formulate the optimal gate joint scheduling scheme and truly realize "planting and breeding coupling". Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0055] Figure 1 This is a flowchart of the method for determining the suitable elevation for mangrove restoration in aquaculture ponds based on tidal level numerical simulation, as per the present invention.

[0056] Figure 2 This is a schematic diagram of the module of the system for determining the suitable elevation for mangrove restoration in aquaculture ponds based on tidal level numerical simulation, as per the present invention. Detailed Implementation

[0057] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0058] Example 1, referring to Figure 1 and Figure 2 This is the first embodiment of the present invention, which provides a system for determining the suitable elevation for mangrove restoration in aquaculture ponds based on numerical simulation of tidal levels, specifically including:

[0059] Data Acquisition and Processing Module: Collects and preprocesses basic data of the target aquaculture pond and its surrounding area;

[0060] The data acquisition and processing module collects data through field measurements and unmanned aerial vehicle surveys.

[0061] The basic data includes: the layout plan of the aquaculture pond, existing gate data, elevation data of the pond bottom and embankment, historical tide level observation data, expected design parameters of the new gate to be renovated, and flood tolerance data of one or more mangrove plant species to be planted.

[0062] The existing gate data includes the location, size, and elevation of the existing gates; the expected design parameters of the new gates to be upgraded include the type, size, and opening / closing logic of the new gates; and the flood resistance time data includes the upper and lower limits of the suitable daily flood time for the target planting area.

[0063] The preprocessing specifically includes:

[0064] Detect missing values ​​in the basic data and delete the corresponding missing value records;

[0065] The system detects and deletes extreme values, drift, duplicate records, and excessively high proportions of null values ​​in the basic data.

[0066] The plan layout data, elevation data of the pond bottom and embankment are projected onto a unified coordinate system based on the GPS system.

[0067] Align the elevation of the pond bottom and the embankment with the 0m water level.

[0068] Check the consistency of gate position, size, and current elevation, remove duplicate data, and correct coordinate errors;

[0069] Verify the consistency of the new gate type, opening and closing logic, and logical constraints;

[0070] It should also be noted that the deployment method for field tide level and hydrological observation includes deploying water level recorders and flow velocity profile measurement equipment at several representative locations inside and around the aquaculture pond, as well as at surrounding tide level stations; the preprocessing also includes observation data quality control procedures: time synchronization correction, baseline drift correction, instrument error correction, and spectrum analysis to identify storm surges or abnormal events.

[0071] Tidal model module: Based on hydrodynamic principles, a three-dimensional hydrodynamic numerical model covering the aquaculture pond and surrounding area is established, and calibrated and verified based on the aforementioned basic data;

[0072] Based on the aforementioned basic data and hydrodynamic principles, the aquaculture pond and its surrounding area are mapped onto a three-dimensional network to construct a three-dimensional hydrodynamic numerical model.

[0073] The hydrodynamic principles described use a shallow-water approximation of the three-dimensional Navier-Stokes equations based on the hydrostatic pressure assumption to describe the motion, pressure changes, and velocity distribution of water bodies.

[0074] The three-dimensional hydrodynamic numerical model is discretized horizontally and vertically;

[0075] The initial water depth and boundary conditions of the three-dimensional hydrodynamic numerical model are defined based on the aforementioned basic data.

[0076] The boundary conditions include tidal level drive of open boundaries, shoreline and pond bottom boundaries, gate coupling boundaries, and wind stress and air pressure source terms.

[0077] Input basic data to perform a preliminary run, and output a three-dimensional tidal field;

[0078] The three-dimensional tidal field includes a water level field, a velocity field, and a stratified field;

[0079] The three-dimensional tidal field during the monitoring process is compared with the historical three-dimensional tidal field, and the deviation between the two is calculated for calibration and verification.

[0080] Scenario simulation module: Based on the calibrated and verified three-dimensional hydrodynamic numerical model, it simulates the water level response under different gate operating conditions according to basic data and gate operation rules;

[0081] M gate operating conditions are preset and N rounds of random simulation are performed. The number of simulations is within a preset range, and the input three-dimensional tidal field is different in each round of simulation, and the similarity is less than a threshold.

[0082] Initialize the gate's operating conditions based on the initial time series;

[0083] Using three-dimensional tidal fields of different time series as simulation inputs, M water level responses are obtained;

[0084] The discreteness of the three-dimensional tidal field of each time series in N rounds of stochastic simulation is evaluated through periodic iterative simulation of no less than 15 days, and the stability coefficient is calculated.

[0085] The simulated quantity is used as the horizontal axis, and the water level response is used as the vertical axis;

[0086] Calculate the local discreteness of the corresponding water level response in N simulations respectively;

[0087] After normalizing the number of simulations in N rounds, the local discreteness is weighted and fused as the weight of each simulation number on the horizontal axis to calculate the stability coefficient.

[0088] The water level response with the highest stability coefficient is selected as the optimal water level response for the gate operation state in the corresponding time series.

[0089] Relationship Analysis Module: Based on the simulated output water level response, statistical analysis is performed to calculate the average daily flooding time at any given elevation point in the aquaculture pond during the simulation period, and to establish the correspondence curve between the elevation at different locations in the aquaculture pond and the average daily flooding time.

[0090] Initialize the average daily flooding time for any given elevation point;

[0091] The time series of water level response is resampled to daily granularity, and for any given elevation point at any given intraday time, it is determined whether the current water level response has submerged the surface elevation of that point.

[0092] Pair any given elevation point with the average daily flooding time, and establish the correspondence curve between the elevation of different locations in the aquaculture pond and the average daily flooding time through numerical integration;

[0093] It should be further noted that in nature, the tide level is a quasi-sine wave, and the relationship between elevation and the average daily flooding time is monotonous and relatively fixed. However, in sluice-controlled ponds, the tide level may exhibit a stepped, sawtooth, or long plateau period. Therefore, the mapping relationship between elevation and the average daily flooding time is non-linear and discontinuous.

[0094] Screening and comparison module: The flood tolerance duration data of the target mangrove plant species is used as the screening condition and compared with the corresponding relationship curve;

[0095] It should also be noted that, during the comparison process, the flood tolerance duration data of the target mangrove plants were cross-analyzed with the corresponding relationship curves, specifically including:

[0096] Determine the flood tolerance conditions of the target mangrove plant (the specific species cannot be submerged for more than 12 hours per day);

[0097] Find the average daily flooding time for each elevation point in the corresponding relationship curve;

[0098] Identify elevation ranges where the average daily flooding time meets or falls below the flood tolerance requirements for target mangrove plants;

[0099] By comparing and selecting suitable elevation points for the growth of this mangrove plant, the design of the aquaculture pond was further optimized based on these elevation points.

[0100] The optimization decision-making module calculates the theoretically suitable elevation range based on the optimal water level response under different gate operating conditions, and uses the suitable elevation range determined under the operating conditions as the final basis for guiding the elevation design and engineering leveling of the mangrove planting area in the aquaculture pond.

[0101] Starting with one of the key limiting factors for mangrove growth, flood tolerance time, we quantitatively predict flood duration through hydrodynamic numerical simulation, avoiding the blindness of experience-based judgments and determining a more scientific and accurate elevation range.

[0102] Before physical engineering modifications, the effects of different gate modification schemes and operating strategies can be simulated and evaluated in computer models, realizing a closed loop of "design-simulation-optimization" and reducing the risk of project failure.

[0103] It can adapt to aquaculture pond renovation projects of different regions, scales, and mangrove species. By adjusting model parameters and operating conditions, it can provide customized solutions for a wide variety of specific projects.

[0104] By comparing the results under different operating conditions, the balance between ecological and production needs can be intuitively revealed, providing scientific support for managers to formulate the optimal gate joint scheduling scheme and truly realize "planting and breeding coupling".

[0105] The technical solution of the present invention is not limited to terrain modification, and whether or not the terrain is modified does not affect the implementation of the technical solution of the present invention.

[0106] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A system for determining suitable elevations for mangrove restoration in aquaculture ponds based on numerical tidal level simulation, characterized in that, Specifically, it includes: The system includes a data acquisition and processing module, a tide level model module, a scenario simulation module, a relationship analysis module, a screening and comparison module, and an optimization decision-making module. Data Acquisition and Processing Module: Collects and preprocesses basic data of the target aquaculture pond and its surrounding area; The basic data includes: the layout plan of the aquaculture pond, existing gate data, elevation data of the pond bottom and embankment, historical tide level observation data, expected design parameters of the new gate to be renovated, and flood tolerance data of one or more mangrove plant species to be planted. Tidal model module: Based on hydrodynamic principles, a three-dimensional hydrodynamic numerical model covering the aquaculture pond and surrounding area is established, and calibrated and verified based on the aforementioned basic data; Scenario simulation module: Based on the calibrated and verified three-dimensional hydrodynamic numerical model, it simulates the water level response under different gate operating conditions according to basic data and gate operation rules; Relationship Analysis Module: Based on the simulated output water level response, statistical analysis is performed to calculate the average daily flooding time at any given elevation point in the aquaculture pond during the simulation period, and to establish the correspondence curve between the elevation at different locations in the aquaculture pond and the average daily flooding time. Screening and comparison module: The flood tolerance duration data of the target mangrove plant species is used as the screening condition and compared with the corresponding relationship curve; Optimization Decision Module: Based on the optimal water level response under different gate operating conditions, calculate the theoretically suitable elevation range, and use the suitable elevation range determined under the operating conditions as the basis for guiding the elevation design of the mangrove planting and aquaculture coupled restoration planting area; In the scenario simulation module, M gate operating conditions are preset for N rounds of random simulation. The number of simulations is within a preset range, and the three-dimensional tidal field input for each round of simulation is different, with the similarity less than a threshold. Initialize the gate's operating conditions based on the initial time series; Using three-dimensional tidal fields of different time series as simulation inputs, M water level responses are obtained; The discreteness of the three-dimensional tidal field of each time series in N rounds of stochastic simulation is evaluated through periodic iterative simulation of no less than 15 days, and the stability coefficient is calculated. The simulated quantity is used as the horizontal axis, and the water level response is used as the vertical axis; Calculate the local discreteness of the corresponding water level response in N simulations respectively; After normalizing the number of simulations in N rounds, the local discreteness is weighted and fused as the weight of each simulation number on the horizontal axis to calculate the stability coefficient. The water level response with the highest stability coefficient is selected as the optimal water level response for the gate operation state in the corresponding time series.

2. The system for determining suitable elevations for mangrove restoration in aquaculture ponds based on tidal level numerical simulation as described in claim 1, characterized in that: The data acquisition and processing module collects data through field measurements and unmanned aerial vehicle surveys. The preprocessing specifically includes: Detect missing values ​​in the basic data and delete the corresponding missing value records; The system detects and deletes extreme values, drift, duplicate records, and excessively high proportions of null values ​​in the basic data. The plan layout data, elevation data of the pond bottom and embankment are projected onto a unified coordinate system based on the GPS system. Align the elevation of the pond bottom and the embankment with the 0m water level. Check the consistency of gate position, size, and current elevation, remove duplicate data, and correct coordinate errors; Verify the consistency of the new gate type, opening and closing logic, and logical constraints.

3. The system for determining suitable elevations for mangrove restoration in aquaculture ponds based on tidal level numerical simulation as described in claim 1, characterized in that: In the tidal level model module, the aquaculture pond and its surrounding area are mapped to a three-dimensional network based on the basic data and hydrodynamic principles to construct a three-dimensional hydrodynamic numerical model. The three-dimensional hydrodynamic numerical model is discretized horizontally and vertically; The initial water depth and boundary conditions of the three-dimensional hydrodynamic numerical model are defined based on the aforementioned basic data. The boundary conditions include tidal level drive of open boundaries, shoreline and pond bottom boundaries, gate coupling boundaries, and wind stress and air pressure source terms. Input basic data to perform a preliminary run, and output a three-dimensional tidal field; The three-dimensional tidal field during the monitoring process is compared with the historical three-dimensional tidal field, and the deviation between the two is calculated for calibration and verification.

4. The system for determining suitable elevations for mangrove restoration in aquaculture ponds based on tidal level numerical simulation as described in claim 1, characterized in that: In the relationship analysis module, the average daily flooding time is initialized for any given elevation point; The time series of water level response is resampled to daily granularity, and for any given elevation point at any given intraday time, it is determined whether the current water level response has submerged the surface elevation of that point. By pairing any given elevation point with the average daily flooding time, a curve showing the correspondence between the elevation of different locations within the aquaculture pond and the average daily flooding time is established through numerical integration.

5. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the module of the system for determining the appropriate elevation for mangrove restoration in aquaculture ponds based on numerical simulation of tidal levels, as described in any one of claims 1 to 4.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the module of the system for determining the appropriate elevation for mangrove restoration in aquaculture ponds based on numerical simulation of tidal levels as described in any of claims 1 to 4.

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