Dynamic simulation method for alga culture water environment in open sea area

Abstract

The invention provides a dynamic simulation method for a seaweed culture water environment in an open sea area, which comprises the following steps of: arranging a plurality of space observation points at a seaweed culture bay, and acquiring seawater salinity, actually measured concentration of dissolved organic carbon and geographical location information of each observation point; based on two-end-member mixed analysis of a fresh water end member and a seawater end member, constructing a hydrological background correction model, and calculating the conservative mixed concentration of dissolved organic carbon at each observation point; constructing a two-dimensional hydrodynamic exchange model, simulating a bay water body flow and exchange process, and outputting water body half-exchange time and daily average water body exchange flow of each observation point; coupling the hydrological background correction model and the hydrodynamic force exchange model, and calculating the net flux of the dissolved organic carbon of the algae source at each observation point in combination with the actually measured concentration of the dissolved organic carbon at each observation point; constructing a coupling model of algae growth and dissolved organic carbon release based on the net flux of algae source dissolved organic carbon at different culture time; the simulation and prediction of the net flux of the dissolved organic carbon of the gulf algae source along with the culture time change are realized.

Description

Technical Field

[0001] This invention belongs to the field of carbon sink monitoring in aquaculture and dynamic simulation of open marine water environment, specifically involving a dynamic simulation method for the water environment of seaweed aquaculture in open sea areas. Background Technology

[0002] Dissolved organic carbon (DOC) is a key component of the marine organic carbon pool. Macroalgae aquaculture, as an important marine carbon sink pathway, releases a significant proportion of primary productivity into surrounding waters as algal-derived DOC. This carbon flux is a core parameter for assessing the ecological effects of aquaculture and its carbon sink potential. Therefore, developing methods to accurately quantify the net flux of algal-derived DOC in open marine aquaculture environments is crucial for scientifically assessing the carbon sink contribution of aquaculture, understanding regional carbon cycle processes, and supporting a blue carbon sink measurement and certification system.

[0003] In existing technologies, the analysis and estimation of DOC in water bodies mainly follow the traditional approaches of aquatic environmental chemistry and ecology. One mainstream method is based on enclosure or culture experiments. For example, by simulating algal growth in controlled closed or semi-closed culture devices, changes in DOC concentration in the water are directly measured to estimate the DOC release rate per unit biomass or per unit time. While this method is valuable for mechanistic exploration and parameter acquisition, its fundamental limitation lies in completely severing the continuous and intense hydrological exchange process between the aquaculture water body and the real marine environment. In actual bays or coastal aquaculture areas, the water renewal, advection, and diffusion effects caused by tides and currents are significant, and DOC released from aquaculture is rapidly diluted, migrated, and transformed. The static release rate obtained from enclosure experiments cannot be directly extrapolated to dynamic open sea areas with complex hydrodynamic backgrounds, leading to systematic biases in the estimation of actual net flux.

[0004] Another approach focuses on the compositional analysis and spatiotemporal distribution characterization of DOC. For example, high-resolution mass spectrometry is used to deeply analyze the molecular composition of algal DOC and its transformation mechanism into the inert carbon pool (RDOC); or statistical models and machine learning algorithms are used to invert the spatial distribution pattern of DOC concentration and its main environmental influencing factors based on large-area, multi-temporal field observation data. These studies have deepened our understanding of DOC biogeochemical processes, but their core objective is to describe the current state and causes of the concentration field, rather than directly quantifying the contribution of a specific source (such as an aquaculture area) at the net flux level. More importantly, these methods typically treat the observed DOC concentration as the result of multiple sources, sinks, and mixing processes, failing to effectively isolate and quantitatively calculate the net flux increase purely from algal aquaculture activities. In the context of dynamic water exchange, directly using observed concentrations for flux calculations severely obscures the background value changes caused by differences in water sources (such as freshwater input and seawater mixing) from the actual contribution of aquaculture activities themselves.

[0005] Therefore, current technological advancements face a key bottleneck in addressing the practical need for precise carbon sequestration in open, highly exchange-oriented marine environments: the lack of a systematic method capable of simultaneously correcting for natural hydrological mixing and quantifying hydrodynamic exchange processes. This method effectively isolates algal-derived DOC from complex, dynamic background signals and accurately calculates its net flux. Existing methods either fail to consider actual hydrological conditions or cannot analyze flux sources, making it difficult to meet the urgent need for reliable, dynamic simulation and prediction of net algal-derived DOC flux in aquaculture areas. Summary of the Invention

[0006] To address the shortcomings and deficiencies of existing technologies, this invention provides a dynamic simulation method and system for the aquatic environment of open-ocean seaweed cultivation. This method acquires key hydrological characteristic data such as seawater salinity and measured dissolved organic carbon (DOC) concentration by deploying multiple spatial observation points in the seaweed cultivation bay. The core of this method lies in first constructing a hydrological background correction model based on two-endmember mixing analysis of freshwater and seawater endmembers. This model calculates the conservative mixing concentration of DOC at each observation point under natural hydrological exchange conditions, effectively removing and eliminating interference from differences in water sources such as freshwater input and seawater mixing on the background DOC value. Simultaneously, a two-dimensional hydrodynamic exchange model is constructed to simulate the flow and exchange process of the bay water, accurately outputting the half-exchange time and daily average water exchange flow rate at each observation point. By coupling the two models and combining the measured DOC concentrations at each observation point, this invention can calculate the daily-scale net flux of algal-source DOC corrected for hydrological interactions. Furthermore, based on net flux data at different cultivation times, a coupled model of algal growth and DOC release is constructed to characterize and quantify the dynamic relationship between the two. Ultimately, this coupled model enables dynamic simulation and prediction of the net DOC flux of algae sources throughout the bay as aquaculture time changes, providing reliable technical support for accurate carbon sequestration in open sea algae aquaculture.

[0007] The specific technical solution adopted by this invention to solve its technical problem is as follows:

[0008] A dynamic simulation method for the aquatic environment of open marine seaweed cultivation includes:

[0009] Multiple spatial observation points were set up in the seaweed farming bay to obtain the seawater salinity, measured concentration of dissolved organic carbon, and geographical location information of each observation point.

[0010] Based on the two-endmember mixing analysis of freshwater and seawater endmembers, a hydrological background correction model is constructed to calculate the conservative mixing concentration of dissolved organic carbon under natural hydrological exchange conditions at each observation point, so as to eliminate the interference of differences in water source.

[0011] A two-dimensional hydrodynamic exchange model was constructed to simulate the flow and exchange process of water in the bay, and the half-exchange time and daily average water exchange flow rate of each observation point were output.

[0012] The hydrological background correction model and the hydrodynamic exchange model are coupled together, and the measured concentration of dissolved organic carbon at each observation point is combined with the daily net flux of algal source dissolved organic carbon at each observation point after hydrological interaction correction.

[0013] Based on the net flux of dissolved organic carbon from algae at different cultivation times, a coupled model of algal growth and dissolved organic carbon release was constructed to characterize the dynamic relationship between the two.

[0014] The coupling model was used to simulate and predict the change in net dissolved organic carbon flux from Gulf algae over time.

[0015] Furthermore, the seaweed is at least one of laver, sea lettuce, or kelp; the multi-spatial observation points are distributed along the main hydrological areas of the bay and the seaweed cultivation area, and the observation period covers the seaweed seedling stage, growth stage, and maturity stage; the seawater salinity and dissolved organic carbon concentration are obtained by on-site sampling combined with laboratory TOC analysis instruments.

[0016] Furthermore, the freshwater end-member is a low-salinity external water source, and the seawater end-member is a high-salinity internal water source. The calculation method for the two-end-member mixture analysis is as follows: based on the freshwater end-member salinity, the seawater end-member salinity, and the salinity of the water sample at the observation point, the contribution ratio of the freshwater end-member is determined as the ratio of (seawater end-member salinity - water sample salinity) to (seawater end-member salinity - freshwater end-member salinity), and the contribution ratio of the seawater end-member is determined as the ratio of (water sample salinity - freshwater end-member salinity) to (seawater end-member salinity - freshwater end-member salinity). Then, the dissolved organic carbon concentration of the two end-members is multiplied by the corresponding proportion and summed to obtain the conservative mixture concentration of dissolved organic carbon.

[0017] Furthermore, the two-dimensional hydrodynamic exchange model is constructed based on the shallow water wave equation to simulate the velocity field and water level field, and outputs the half-exchange time and daily average water exchange flow rate at each observation point; the model is specifically a two-dimensional shallow water hydrodynamic finite element model, whose parameters include spatial coordinates, latitudinal and meridional components of water flow velocity, Coriolis parameters, gravitational acceleration, sea surface height, seabed drag coefficient and total water depth, and the total water depth is the superposition value of the average water depth and sea surface height.

[0018] Furthermore, the daily-scale algal source dissolved organic carbon net flux corrected for hydrological interaction is calculated by multiplying the difference between the measured concentration of dissolved organic carbon at the observation point and the conservative mixed concentration by the daily average water exchange flow at the corresponding observation point. The overall daily average algal source dissolved organic carbon net flux of the bay is the sum of the net fluxes at all observation points.

[0019] Furthermore, the coupling model between algal growth and dissolved organic carbon release is an empirical model obtained through regression analysis. The model uses the algal cultivation time as the independent variable and the average daily net flux of dissolved organic carbon from algae sources in the bay as the dependent variable. The analytical equation of the model is obtained by fitting flux data from multiple observation periods. Specifically, the empirical model is a nonlinear regression model.

[0020] Furthermore, the rules for determining the end-member parameters in the two-end-member mixed analysis are as follows: for different aquaculture stages or observation periods, the freshwater end-member and seawater end-member parameters corresponding to that period are selected respectively; wherein, the freshwater end-member parameters are determined based on the observation data of the low-salinity freshwater estuary area near the bay during that period, and the seawater end-member parameters are determined based on the observation data of the high-salinity open sea area outside the bay during that period.

[0021] Furthermore, a dynamic simulation system for the aquatic environment of open-sea algae cultivation, used to implement the method described above, includes:

[0022] The data acquisition module is used to connect with remote sensing equipment, field monitoring instruments and laboratory analysis equipment to acquire and integrate seawater salinity, measured dissolved organic carbon concentration and geographical location information of the observation point;

[0023] The hydrological background correction module is used to construct a hydrological background correction model and calculate the conservative mixing concentration of dissolved organic carbon based on the two-endmember mixing analysis logic of freshwater endmembers and seawater endmembers and the endmember parameter determination rules.

[0024] The hydrodynamic simulation module is used to run a two-dimensional hydrodynamic exchange model based on the shallow water wave equation, and outputs the water half-exchange time and daily average water exchange flow rate at the observation points.

[0025] The flux coupling calculation module is used to couple the output data of the hydrological background correction model and the hydrodynamic exchange model, calculate the corrected daily algal source net flux of dissolved organic carbon by combining the measured concentration of dissolved organic carbon, and construct a coupling model of algal growth and dissolved organic carbon release.

[0026] The simulation and prediction module is used to simulate and predict the change of net dissolved organic carbon flux from Gulf algae over aquaculture time based on the coupled model.

[0027] And a computer device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the method described above.

[0028] A non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described above.

[0029] Compared with the prior art, the present invention and its preferred embodiments have at least the following beneficial effects:

[0030] First, it effectively adapts to the real hydrological environment of seaweed farming in open sea areas, solving the measurement bias problem caused by the neglect of dynamic hydrological interactions such as tides and ocean currents in traditional enclosure methods and static models. By dynamically selecting end-member parameters for different farming stages or observation periods, and combining them with a two-dimensional hydrodynamic exchange model based on shallow water wave equations to simulate water flow and exchange processes, it can more realistically restore the natural mixing state of bay waters, eliminate the interference of differences in water sources and changes in hydrological background over time on the analysis of dissolved organic carbon (DOC) concentration, and make the simulation results more consistent with the actual marine conditions.

[0031] Secondly, it significantly improves the accuracy of measurement of net addition or removal of DOC from algae. By coupling the hydrological background correction model and the hydrodynamic exchange model, the difference between the measured concentration of dissolved organic carbon and the conservative mixed concentration is corrected by combining the water exchange flow rate. This can effectively separate the DOC concentration changes caused by natural water mixing from the actual contribution of DOC from algae, avoiding the measurement error caused by the inability of traditional methods to distinguish the influence of the two. This provides a reliable technical path for accurately obtaining the net flux of DOC from algae in the entire bay and at each observation point.

[0032] Furthermore, it has achieved the ability to dynamically simulate and predict changes in algal DOC. Based on net flux data at different cultivation times, it has constructed a coupled model of algal growth and DOC release, which can cover key stages such as algal seedling, growth, and maturity. This breaks through the limitations of traditional short-term simulations or single-point monitoring, which cannot reflect the dynamic changes in DOC throughout the entire cultivation cycle. It can quickly obtain data on the net addition or removal of algal DOC at any time period according to the cultivation time, providing dynamic support for understanding the changes in dissolved organic carbon storage in open bay water environments.

[0033] Finally, the overall technical solution is closely aligned with the actual needs of carbon sink monitoring in aquaculture. The layout of observation points, model construction, and result output all revolve around the core objective of "accurately measuring the DOC contribution of algae sources." It is also clearly adapted to common large-scale cultivated algae such as laver, seaweed, and kelp. Compared with existing technologies that focus on molecular mechanism analysis or short-term simulation, it has greater practical application value and can provide accurate and feasible technical support for assessing the carbon sink potential of algae aquaculture in open sea areas. Attached Figure Description

[0034] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0035] Figure 1 This is a schematic diagram illustrating the calculation process for dissolved organic carbon from algae in bay water according to an embodiment of the present invention.

[0036] Figure 2 This is a diagram showing the sampling station layout in the bay during different aquaculture periods (January to June) according to an embodiment of the present invention;

[0037] Figure 3 This is a multiple regression fitting curve of the total net addition or removal of ΔDOC in bay water versus time, according to an embodiment of the present invention. Detailed Implementation

[0038] To make the features and advantages of the present invention more apparent and understandable, specific embodiments are described below in detail:

[0039] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0040] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0041] This invention, based on a two-endmember mixing model and a two-dimensional shallow-water hydrodynamic model, calculates the corrected net addition or removal of dissolved organic carbon (DOC) at all observation points. Based on this, it obtains the average daily net addition to the bay and further regresses and fits the algal growth time t and the total net addition or removal of DOC in the bay to obtain and calculate the net increase in algal-source DOC in the bay water. This invention utilizes the calculation of conservative mixing concentration of DOC in water under marine hydrological interactions, the prediction of exchange cycles, and the calculation of DOC addition or removal in water, to more accurately simulate the bay water state under marine hydrological exchanges, achieving a more accurate simulation and calculation of the average daily change in algal-source DOC in the open seawater environment of the bay at any given time.

[0042] The implementation process of the present invention can be referred to the following steps:

[0043] (1) Obtain marine characteristic data from multiple observation points in the bay waters with seaweed cultivation. The seawater characteristic data for each observation point shall include at least latitude and longitude, seawater salinity, conservative mixed data of dissolved organic carbon (DOC), seawater flow velocity and seawater DOC concentration measurement data.

[0044] (2) Select endmembers and calculate the selected endmember water body characteristic data based on the two-endmember mixing model to obtain the conservative mixed concentration data of DOC in seawater at different time periods under the interaction of tidal hydrology.

[0045] (3) Based on the two-dimensional tidal hydrodynamic model, the hydrodynamic interaction of the water body is analyzed to obtain the seawater hydrological interaction type, exchange cycle and average daily water flow at each observation point;

[0046] (4) The conservative mixed concentration of DOC, DOC measurement data and water flow obtained from all observation points are fitted and calculated to obtain the average daily net addition or removal of DOC (ΔDOC) at each observation point after correction for hydrodynamic interaction. i) and the average daily net addition to the Gulf .

[0047] (5) The effects of seaweed cultivation time t and Model fitting was performed to determine the average daily change in total DOC from algae sources in seawater. As output data, a quantitative model for the net addition or removal of algal-derived DOC in the target sea area is constructed.

[0048] (6) Based on the established measurement model, obtain the net addition or removal of DOC from algae in the bay water at any time during the cultivation cycle according to the corresponding algae cultivation time data, and obtain the data on the change of dissolved organic carbon storage in the open seawater environment in the bay.

[0049] As a preferred embodiment, the specific implementation of step (2) above includes:

[0050] We selected exogenous (freshwater end, low salinity) and endogenous (seawater end, high salinity) endmember combinations to construct training datasets for seawater feature data of all endmember combinations. Each sample includes seawater salinity data and DOC data of the selected endmember for any time period.

[0051] Using seawater salinity data and endmember DOC data from the sample as input data, a two-endmember mixing model was used to calculate the conservative mixed concentration data of DOC in the water body under two-dimensional tidal hydrological interaction.

[0052] The following formula is used for the analysis and calculation of the two-endmember mixture model:

[0053]

[0054] Where S is the salinity of the water sample, S A For freshwater end-member salinity, S B Oceanic end-member salinity; C DOCA and C DOCB The concentrations of the two endmembers, C, are respectively. DOC This represents a conservative mixing concentration.

[0055] As a preferred embodiment, the specific implementation of step (3) above includes:

[0056] A two-dimensional shallow water hydrodynamic finite element model was selected to simulate the seawater hydrological interaction at the observation point and to calculate the seawater exchange capacity.

[0057] Based on the analysis results of the two-dimensional shallow water hydrodynamic finite element model, the half-exchange time (T) of the regional water body was obtained. h (and average daily water flow).

[0058] The two-dimensional shallow water hydrodynamic finite element model consists of a coupled advection and diffusion module, and its momentum and continuity equations are as follows:

[0059]

[0060] In the formula, x and y are spatial coordinates, u and v are the latitudinal and meridional components of the velocity, respectively; f is the Coriolis parameter, g is the gravitational acceleration, η is the sea surface height, r is the seabed drag coefficient, and H is the total water depth (H = h + η, H is the average water depth).

[0061] As a preferred embodiment, in step (4) above, the average daily net DOC addition or removal (ΔDOC) at each observation point after hydrodynamic interaction correction is... i ) and the average daily net addition to the Gulf The following formula is used for calculation:

[0062]

[0063]

[0064] In the formula ΔDOC i C represents the amount of DOC added or removed at point i. DOCi *Represents the measured DOC concentration in the water sample at point i. DOC V represents the conservative mixed concentration of two-terminal DOC. i The water flow rate in the sea area at the observation point.

[0065] As a preferred embodiment, in step (6) above, a measurement model for the net addition or removal of algal DOC in the target sea area is constructed in the following manner:

[0066] Based on all observation points ΔDOC c and the corresponding flow volume V i To obtain the average daily net addition to the Gulf. ;

[0067] For the breeding time t and Perform multiple linear regression fitting (e.g., least squares method) to determine the average daily change in total DOC of algae in seawater. As output data, the econometric model analytical equation for the total change in DOC of algal sources in the target sea area during different aquaculture periods was obtained;

[0068] The analytical equation of the econometric model is:

[0069] Specifically, algae sources refer to laver, seaweed, and kelp.

[0070] Based on the above design method, this invention also provides a calculation system for dissolved organic carbon (DOC) from algae in bay water, capable of implementing the calculation method for DOC from algae in bay water disclosed in the foregoing embodiments. The system includes a memory and a processor. The memory stores computer programs, and the processor runs the computer programs to enable the electronic device to execute the calculation methods of the two-terminal element mixing analysis model, the two-dimensional shallow water hydrodynamic finite element model, and the measurement model of total DOC change in bay water versus aquaculture time t as described in the embodiments. Preferably, the electronic device can be a server.

[0071] Compared with existing technologies, the technical advantages of the above solutions in the embodiments of this invention include: traditional calculations of average DOC concentration in enclosed environments are not applicable to open water environments under marine hydrological exchange. This invention integrates an end-member mixing analysis model and a two-dimensional shallow-water hydrodynamic finite element model to theoretically simulate and analyze different seawater backgrounds at different times, eliminating the problem of inaccurate measurement due to the constantly changing nature of actual backgrounds; based on the shallow-water model, it calculates the seawater flow interaction capacity, accurately calculating the conservative mixing concentration of DOC at each site under marine interaction, the water exchange cycle, and the average daily water flow. Through the calculation and application of these parameters, the influence of marine interaction and end-member water sources is effectively eliminated, the calculation of DOC addition or removal in the water is corrected, more accurate detection data is obtained, and thus a multiple regression analysis (ΔDOC~t) of the total net increase of DOC in seawater and the cultivation time t is carried out, establishing a quantitative model for the total change of algal DOC in the target sea area at different cultivation times, and more accurately obtaining the average daily net addition or removal of algal DOC in the bay water at any time during the cultivation cycle.

[0072] This invention, through the calculation and application of multiple models, more accurately simulates the actual seawater exchange and the mixing of different end-members. It overcomes the technical difficulties of accurately calculating the DOC concentration in marine waters under marine hydrological interactions using traditional DOC storage measurement methods, and the inaccurate calculation of the net increase of DOC from algae sources in seawater. It provides a more accurate calculation scheme for the DOC storage released by large-scale seaweed farming.

[0073] The implementation process of the present invention will be further demonstrated and introduced below with reference to the accompanying drawings through a more specific application example:

[0074] like Figure 1 As shown, perform the following steps:

[0075] Step S1: Obtain seawater characteristic data from multiple observation points within the bay area.

[0076] Multiple sites are set up in the bay, such as Figure 2As shown, 20 sampling points were set up in the selected bay (e.g., a bay) along the direction of ocean current movement and the distribution area of ​​algae cultivation areas, and samples were taken in January, March, April and June, respectively, during the intensive algae cultivation period.

[0077] The seawater characteristic data for each observation point include at least latitude and longitude, seawater salinity, conservative mixed data of dissolved organic carbon (DOC), seawater flow velocity, and seawater DOC concentration measurement data.

[0078] The latitude, longitude, and seawater salinity profile data for each observation point can be obtained through remote sensing data or on-site measurements.

[0079] Conservative mixing data of dissolved organic carbon (DOC) and seawater flow velocity at each observation point can be obtained based on analysis of a two-terminal mixing model and calculation of a two-dimensional shallow water hydrodynamic finite element model.

[0080] The DOC concentration data for each observation point can be obtained by collecting water samples on-site and measuring them in the laboratory using a TOC analyzer (TOC-L).

[0081] Step S2: Analyze the data based on the two-terminal mixing model to obtain the conservative mixed concentration data of DOC in the water.

[0082] (1) Derivation of the two-end-member mixed analysis equation:

[0083]

[0084]

[0085] Among them, f A and f B C represents the fraction of freshwater and marine endmembers in the sample (totaling 1). DOCA and C DOCB These represent the concentrations of the two endmembers, respectively.

[0086] Assume the freshwater salinity is S. A The salinity of the marine endmember is S. B The sample's f A Then it is f B for , where S is the salinity of the sample. f A and f B Substituting, we get:

[0087]

[0088] Where S is the salinity of the water sample, S A For freshwater end-member salinity, S B Oceanic end-member salinity; C DOCA and CDOCB The concentrations of the two endmembers, C, are respectively. DOC This represents a conservative mixing concentration.

[0089] (2) Analysis of conservative mixed concentrations of DOC:

[0090] Based on the fact that the salinity distribution in a bay during the sampling period showed an increasing trend from the vicinity of Jiaoxi or Huotongxi in the bay to the outside of the bay, conservative mixture analysis was performed in January, March, April and June using the freshwater end (low salinity) and seawater end (high salinity) endmember values, respectively. The calculation results of the DOC conservative mixture analysis endmember values ​​are shown in Table 1.

[0091] Table 1. Conservative Mixed Concentration of DOC in Water Samples from a Bay from January to June

[0092]

[0093] Step S3: Based on two-dimensional tidal hydrodynamic exchange simulation, determine the seawater exchange cycle and flow rate at all sites.

[0094] (1) Selection of hydrodynamic model for the bay. A two-dimensional shallow water hydrodynamic finite element model is adopted to study the hydrological characteristics of the bay, especially its seawater exchange capacity.

[0095] The momentum and continuity equations for the two-dimensional shallow water hydrodynamic finite element model are:

[0096]

[0097] In the formula, u and v are the zonal and meridional components of the velocity, respectively; η is the sea surface height, H is the total water depth (H = h + η, H is the average water depth), f is the Coriolis parameter, ris is the seafloor drag coefficient, and g is the acceleration due to gravity. This model is coupled with an advection and diffusion module, which typically reproduces changes in water level and ocean currents within the study area.

[0098] (2) Half-exchange time fitting and calculation of average daily water flow

[0099] Based on a two-dimensional shallow-water hydrodynamic finite element model, the influence of the current field and water exchange in a bay area was predicted and calculated. The half-exchange time (T) of seawater at the sampling points in the bay area was also calculated. h The specific data distribution is shown in Table 2, indicating that the tidal current in a certain bay area is reciprocating, and the water exchange capacity varies greatly at different locations, with a half-exchange time T. h The difference between the average daily water flow and the average flow rate is too large to be calculated using the traditional average flow velocity data of the bay.

[0100] Table 2. Water half-exchange time (T) at different stations in a bay h )distributed

[0101]

[0102] Step S4: Further calculate to obtain the corrected average daily net change in DOC and the average daily net addition to the Gulf for each observation point.

[0103] (1) Average daily water volume C DOC Add or remove concentration calculations.

[0104] Based on the measured DOC concentration and conservative mixed DOC concentration data of water samples at each monitoring point, the average daily DOC concentration in the water body is calculated using the following formula. DOC Add or remove concentration:

[0105]

[0106] In the formula ΔC DOC To add or remove concentration, C DOC *Represents the measured concentration of the water sample, C. DOC This represents a conservative mixing concentration.

[0107] Furthermore, the average daily net addition or removal of carbon DOC in the marine water body is calculated as follows:

[0108]

[0109] In the formula ΔC DOC This refers to the average daily net addition or removal of carbon from DOC, expressed in tons of carbon (t C·d). -1 V i The volume of water at monitoring point i is expressed in liters (L).

[0110] Based on the above calculation equations, the average daily net addition or removal of carbon DOC at each sampling point in January, March, April and June was calculated, as shown in Table 3 (taking the January sampling point as an example).

[0111] Table 3. Fitted calculation of average daily DOC carbon addition in the bay waters (taking January as an example)

[0112]

[0113] (3) Average daily net addition to the Gulf.

[0114] Based on the breeding time data, such as when breeding lasts for 39 days in January, the following formula is used for calculation:

[0115] =18.93 t C·d -1

[0116] Based on the calculations, the average net daily DOC addition to the bay water is 18.93 t C·d. -1 .

[0117] Step S5: Combine the culture time to construct a quantitative model of net addition or removal of DOC from algae sources in the bay on culture time t (t ~ ΔDOC).

[0118] Based on the cultivation cycle of macroalgae, the sampling times selected in this invention were January, March, April, and June, corresponding to cultivation periods of 39, 93, 121, 145, and 188 days. A model was fitted between the net addition or removal of DOC in seawater at 20 stations in the seaweed cultivation area and the cultivation time. Multiple linear regression analysis was performed using cultivation time t and the total change in DOC in the bay water as variables and dependent variables, respectively. Figure 3 The results show that the net DOC addition in the bay water gradually increases with the increase of the cultivation time t, and decreases in the later stage of kelp maturity. The econometric equation for the fitted model is as follows:

[0119]

[0120] Step S6: Based on the established metrology model, calculate the net addition or removal of DOC from algae sources in the bay water at any given time.

[0121] The equation for the fitted econometric model of aquaculture time t and total DOC change in bay water is as follows:

[0122]

[0123] Depending on the different cultivation time, such as t being 15, 30, 60, 90, etc., the corresponding net addition or removal of DOC from algae can be calculated based on the equation of the econometric model, as shown in Table 4:

[0124] Table 4. Calculation of average daily DOC carbon addition in the bay waters under different aquaculture periods.

[0125]

[0126] Based on the same inventive concept, this invention also provides a computer device, comprising: one or more processors, and a memory for storing one or more computer programs; the programs include program instructions, and the processor executes the program instructions stored in the memory. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, used to implement one or more instructions, specifically for loading and executing one or more instructions stored in a computer storage medium to implement the above-described method.

[0127] It should be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium storing a computer program, which, when executed by a processor, performs the above-described method. This storage medium can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0128] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0129] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

[0130] This invention is not limited to the above-described preferred embodiments. Anyone inspired by this invention can derive other forms of dynamic simulation methods for open-sea algae aquaculture environments. All equivalent variations and modifications made within the scope of the claims of this invention should be included within the scope of this invention.

Claims

1. A method for dynamically simulating an open sea seaweed farming water environment, characterized by, The application relates to a method for simulating and predicting seaweed source dissolved organic carbon (DOC) net flux in a seaweed cultivation bay. The method comprises the following steps: arranging multiple space observation points in the seaweed cultivation bay, and obtaining seawater salinity, measured DOC concentration and geographical position information of the observation points; Based on two-end-member mixing analysis of the freshwater end member and the seawater end member, a hydrological background correction model is constructed to calculate the conservative mixing concentration of DOC under the natural hydrological exchange condition of the observation points, so that the interference of water body source difference is eliminated; A two-dimensional hydrodynamic exchange model is constructed to simulate the water flow and exchange process in the bay, and the water body half-exchange time and daily average water exchange flow of each observation point are outputted; The hydrological background correction model and the hydrodynamic exchange model are coupled, and the daily scale seaweed source DOC net flux of each observation point after hydrological interaction correction is calculated by combining the measured DOC concentration of each observation point. Based on the seaweed source DOC net flux under different cultivation times, a coupling model of seaweed growth and DOC release is constructed to represent the dynamic correlation between the two. The coupling model is used to simulate and predict the seaweed source DOC net flux in the bay with the change of cultivation time.

2. The method of dynamic simulation of the water environment of open sea seaweed farming according to claim 1, characterized in that: The seaweed is at least one of Porphyra, Gracilaria or Laminaria; the multiple space observation points are arranged along the main hydrological region and seaweed cultivation area of the bay, and the observation period covers the seaweed seedling period, growth period and mature period; wherein the seawater salinity and measured DOC concentration are obtained by on-site sampling combined with laboratory TOC analysis instrument.

3. The method of dynamic simulation of the water environment of open sea seaweed farming according to claim 1, characterized in that: The freshwater end member is a low-salinity exogenous water body, and the seawater end member is a high-salinity endogenous water body; the calculation method of two-end-member mixing analysis is as follows: based on the salinity of the freshwater end member, the salinity of the seawater end member and the salinity of the water sample of the observation point, the contribution proportion of the freshwater end member is determined as the ratio of (the salinity of the seawater end member minus the salinity of the water sample) to (the salinity of the seawater end member minus the salinity of the freshwater end member), the contribution proportion of the seawater end member is determined as the ratio of (the salinity of the water sample minus the salinity of the freshwater end member) to (the salinity of the seawater end member minus the salinity of the freshwater end member), and then the DOC concentration of the two end members is multiplied by the corresponding proportion and summed to obtain the conservative mixing concentration of DOC.

4. The method of dynamic simulation of an open sea seaweed farming water environment according to claim 1, characterized in that: The two-dimensional hydrodynamic exchange model is constructed based on the shallow water wave equation and is used for simulating the flow field and water level field and outputting the water body half-exchange time and daily average water exchange flow of each observation point; the model is a two-dimensional shallow water fluid dynamic finite element model, the parameters of which include spatial coordinates, latitudinal and longitudinal components of water flow velocity, Coriolis parameter, gravitational acceleration, sea surface height, seabed resistance coefficient and total water depth, and the total water depth is the superposition value of the average water depth and the sea surface height.

5. The method of dynamic simulation of an open sea seaweed farming water environment according to claim 1, characterized in that: The daily scale seaweed source DOC net flux after hydrological interaction correction is calculated by multiplying the difference between the measured DOC concentration and the conservative mixing concentration of the observation point by the daily average water exchange flow of the corresponding observation point, and the daily average seaweed source DOC net flux of the whole bay is the sum of the net fluxes of all the observation points.

6. The method of dynamic simulation of an open sea seaweed farming water environment according to claim 1, characterized in that: The coupling model of seaweed growth and DOC release is an empirical model fitted through regression analysis, the seaweed cultivation time is the independent variable, the daily average seaweed source DOC net flux of the bay is the dependent variable, the model analytical equation is fitted through the flux data of multiple observation periods, and the empirical model is a nonlinear regression model.

7. The method of dynamic simulation of an open sea seaweed farming water environment according to claim 3, characterized in that: The end member parameter determination rule of the two-end member mixing analysis is that: for different culture stages or observation periods, the corresponding freshwater end member and seawater end member parameters of the period are selected respectively; wherein the freshwater end member parameters are determined based on the observation data of the period in the low salinity freshwater inlet area of the coastal bay, and the seawater end member parameters are determined based on the observation data of the period in the high salinity open sea area outside the bay.

8. A dynamic simulation system of an open sea seaweed farming water environment, characterized by, For implementing the method of claim 1, comprising: a data acquisition module for connecting remote sensing equipment, field monitoring instruments and laboratory analysis equipment, obtaining and integrating seawater salinity, dissolved organic carbon measured concentration and geographic location information of the observation point; a hydrological background correction module for constructing a hydrological background correction model and calculating the conservative mixing concentration of dissolved organic carbon based on the two-end member mixing analysis logic and end member parameter determination rule of the freshwater end member and the seawater end member; a hydrodynamic simulation module for running a two-dimensional hydrodynamic exchange model based on shallow water wave equation to output the water body half-exchange time and daily average water body exchange flow of the observation point; a flux coupling calculation module for coupling the output data of the hydrological background correction model and the hydrodynamic exchange model, calculating the corrected daily scale algal dissolved organic carbon net flux combined with the measured concentration of dissolved organic carbon, and constructing the coupling model of algal growth and dissolved organic carbon release; a simulation and prediction module for simulating and predicting the change of the algal dissolved organic carbon net flux in the bay with the culture time based on the coupling model.

9. A computer device, comprising: The storage medium stores a computer program, and the processor executes the computer program to implement the method of any one of claims 1-7.

10. A non-transitory computer-readable storage medium, comprising: The storage medium stores a computer program, and the processor executes the computer program to implement the method of any one of claims 1-7.

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