CN117273218A - Fine prediction method and application of nitrogen and phosphorus loss of freshwater aquaculture fishpond - Google Patents

Fine prediction method and application of nitrogen and phosphorus loss of freshwater aquaculture fishpond Download PDF

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CN117273218A
CN117273218A CN202311213267.4A CN202311213267A CN117273218A CN 117273218 A CN117273218 A CN 117273218A CN 202311213267 A CN202311213267 A CN 202311213267A CN 117273218 A CN117273218 A CN 117273218A
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黄佳聪
张帅
季雨来
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Nanjing Institute of Geography and Limnology of CAS
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Abstract

The invention relates to a method for finely predicting nitrogen and phosphorus loss of a freshwater aquaculture fish pond and application thereof, comprising the following steps: acquiring meteorological, hydrological and water quality data of a fish pond and surrounding rivers thereof and fish pond management information; establishing a fishpond nitrogen and phosphorus circulation model, wherein the fishpond nitrogen and phosphorus circulation model comprises a water quantity balance module, a dissolved oxygen balance module, a nitrogen and phosphorus biological geochemical circulation module and an aquatic organism growth and death module; the aquatic organism growth and death module simulates nitrogen and phosphorus assimilation and excretion of the aquatic organisms in the fishpond; based on the acquired data information and the fishpond nitrogen and phosphorus circulation model, simulating the dynamic change of the fishpond nitrogen and phosphorus day by day, accounting the sediment-water and water-air interface and the nitrogen and phosphorus exchange quantity of the fishpond and the surrounding river, and predicting the nitrogen and phosphorus loss quantity of the fishpond. The method integrates the technologies of fine expression of key processes, identification and optimization of sensitive parameters of the model and the like, comprehensively considers the unique migration and transformation rules of nitrogen and phosphorus in the fish pond, breaks through the difficult problem of accurate prediction of the loss amount of nitrogen and phosphorus in the fish pond, and can provide key technical support for the control of nitrogen and phosphorus pollution in the fish pond.

Description

Fine prediction method and application of nitrogen and phosphorus loss of freshwater aquaculture fishpond
Technical Field
The invention belongs to the technical field of water environment health evaluation, and particularly relates to a method for finely predicting nitrogen and phosphorus loss of a freshwater aquaculture pond and application thereof.
Background
The freshwater aquaculture pond (hereinafter referred to as a pond) seriously affects the regional water environment due to nitrogen and phosphorus loss, and is a main nutrition source for causing water eutrophication and cyanobacterial bloom. The accurate prediction of the loss amount of nitrogen and phosphorus is the basis of the pollution control and management of the fish pond, but due to the large input amount of nitrogen and phosphorus of the fish pond, rich aquatic organism types and complex bio-geochemical circulation, a refined accounting method for the source, migration, transformation and loss amount of nitrogen and phosphorus of the fish pond is still lacking at present.
The water quality model (MIKE 11, EFDC and the like) can systematically simulate the migration and conversion process of nitrogen and phosphorus in river and lake water bodies, but lacks consideration of aquatic organisms (river crabs, fishes, macrophytes, phytoplankton and zooplankton) in a fish pond and high-strength artificial regulation (water level control, feed input, oxygenation and the like) and lacks systematic description of the geochemical circulation of nitrogen and phosphorus organisms; therefore, the method is not suitable for the fine prediction of the loss of nitrogen and phosphorus in the fish pond, and development of a new technical method is urgently needed.
Disclosure of Invention
The invention aims to fill the blank of the prior art, develop a Pond nitrogen and phosphorus circulation model (Pond-NP) covering the growth and extinction of aquatic organisms and the bio-geochemical circulation, realize the fine simulation of water balance, dissolved oxygen balance, the growth and extinction of aquatic organisms and the bio-geochemical circulation process of nitrogen and phosphorus, predict the daily loss amount of nitrogen and phosphorus, and provide a fine prediction method for the nitrogen and phosphorus loss of a freshwater aquaculture Pond.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a method for finely predicting nitrogen and phosphorus loss of a freshwater aquaculture fish pond comprises the following steps:
acquiring meteorological, hydrological and water quality data of a fish pond and surrounding rivers thereof and fish pond management information;
establishing a fishpond nitrogen-phosphorus circulation model (Pond-NP) comprising a water quantity balance module, a dissolved oxygen balance module, a nitrogen-phosphorus bio-geochemical circulation module and an aquatic organism growth extinction module; the aquatic organism is river crab, fish, macrophyte, phytoplankton and zooplankton in the fishpond, and the aquatic organism growth and death module simulates the nitrogen and phosphorus assimilation and excretion of the aquatic organism in the fishpond, including the feeding, assimilation, excretion and death processes of the aquatic organism;
based on the acquired data information and the fishpond nitrogen and phosphorus circulation model, simulating the dynamic change of the fishpond nitrogen and phosphorus day by day, accounting the sediment-water and water-air interface and the exchange quantity of the fishpond and the surrounding river nitrogen and phosphorus, and predicting the loss quantity of the fishpond nitrogen and phosphorus.
Because the characteristic of high-density aquatic organisms exists in the ecological system of the fish Pond, the characteristic of the high-density aquatic organisms identifies a key process affecting the prediction of nitrogen and phosphorus loss, the invention focuses on the feeding, nitrogen and phosphorus assimilation and excretion processes of the aquatic organisms, designs a fish Pond nitrogen and phosphorus circulation model (Pond-NP) which covers the growth and death of the aquatic organisms and the bio-geochemical circulation, and quantitatively simulates the water quantity exchange, the geochemical circulation driven by the aquatic organisms, a sediment-water interface and a water-air interface diffusion mechanism, and the key process of the nitrogen and phosphorus loss of the fish Pond is covered by the mechanism. Compared with the existing water environment model (MIKE 21 and the like), the nitrogen-phosphorus circulation model increases generalization of influence of aquatic organism growth and extinction on the geochemical circulation of nitrogen and phosphorus in the water body, comprises absorption, ingestion, excretion, death processes and the like, and improves applicability of the model artificial culture fishpond.
As a preferred embodiment, the specific process of nitrogen and phosphorus assimilation and excretion of the simulated fish pond organism comprises:
collecting fish pond aquatic organism data, including investigation of initial throwing density and final recapture rate of the fish pond aquatic organisms (river crabs, fish, macrophytes, phytoplankton and zooplankton), according to the final recapture rate, accounting the daily death rate of the aquatic organisms, and investigation of nitrogen and phosphorus assimilation efficiency of each organism and organic and inorganic nitrogen and phosphorus proportion in excrement;
constructing a fishpond aquatic organism food net by depending on the ecological niche relation;
the mathematical characterization method of the aquatic organism growth and death process is designed to simulate the unique nitrogen and phosphorus circulation process under the drive of aquatic organisms in a fish pond, wherein the unique nitrogen and phosphorus circulation process comprises the inorganic nitrogen and phosphorus (ammonia nitrogen, nitrate nitrogen and phosphate) absorbed by the growth of macrophytes and phytoplankton and the organic nitrogen and phosphorus released by death or putrefaction, and the organic nitrogen and phosphorus quantity excreted by undigested or unutilized river crabs, fish and zooplankton after ingestion and the ammonia nitrogen and phosphate quantity excreted after digestion.
As a preferred embodiment, the niche relationship comprises river crabs feeding feeds and macrophytes, fish feeding phytoplankton and zooplankton feeding phytoplankton and detritus, macrophytes and phytoplankton growing by absorption of inorganic nitrogen (ammonia nitrogen and nitrate nitrogen) and inorganic phosphorus (phosphate).
As a preferred embodiment, the control equation of the aquatic organism growth and death module is as follows:
wherein T represents the time, deltaT represents the time step, Y T And Y T-ΔT Representing biomass of the organism at time T and T-DeltaT, sigma X q X2Y Representing the biomass of organisms X ingested by heterotrophs (river crabs, fish, zooplankton) Y,shows the growth amount of autotrophs (macrophytes, phytoplankton), Σ R q Y2R The relationship of food network is shown in figure 1, q Y2OE Represents the organic matter excretion amount, q of the organism Y Y2IE Represents the inorganic matter excretion amount, q of the organism Y Y2M Indicating the death or spoilage of organism Y, FT (Y) indicating the temperature limiting factor for organism growth or ingestion, FL (Y) indicating the light limiting factor for autotroph growth, FNP (Y) indicating the nitrogen-phosphorus limiting factor for autotroph growth, FDO (Y) indicating the oxygen limiting factor for heterotroph ingestion, FA (X, Y) indicating the food limiting factor for heterotroph ingestion, I z Indicating the illumination intensity->Represents ammonia nitrogen concentration->Indicating nitrate nitrogen concentration,/->Indicating phosphate concentration, DO T Represents the dissolved oxygen concentration; all parameters contained in the formula are as follows, +.>Indicating the maximum growth rate of organisms,/->Indicating maximum feeding rate of the organism, +.>Represents the optimal, minimum and maximum water temperature, T, for the growth of a suitable organism Y Ave Represents average water temperature +.>Represents the saturated intensity of the growth of autotroph Y, KN Y Represents the half-saturated concentration of inorganic nitrogen for the growth of autotroph Y, KP Y KO representing the half-saturated concentration of inorganic phosphorus for the growth of autotroph Y Y Represents the dissolved oxygen half-saturated concentration of the heterotrophic Y feed, KH X2Y Representing the half-saturated concentration of feeding organism X by heterotrophic organism Y.
As a preferred embodiment, the water balance module simulates the water exchange of a fish pond with a surrounding river and the atmosphere;
the water quantity exchange between the fishpond and the atmosphere comprises precipitation and evaporation processes;
the water volume exchange between the fish pond and the surrounding river comprises the processes of seepage, water diversion and drainage.
Further, the specific process of water volume exchange between the simulated fish pond and the surrounding river and the atmosphere comprises the following steps:
collecting meteorological hydrologic monitoring data, and simulating migration and transformation of four waters (atmospheric water, surface water, soil water, underground water) under hydrologic driving, wherein the meteorological data comprise daily monitoring data such as solar radiation, rainfall, relative humidity, wind speed and the like, and the hydrologic data comprise daily data such as pond water level, drainage, water diversion and the like;
inputting a Penman evaporation model to estimate potential evaporation capacity of the water surface of the fish pond according to meteorological data such as daily humidity, atmospheric pressure, wind speed, air temperature, humidity, radiation and the like, and calculating daily water quantity exchange between the fish pond and the atmosphere by combining rainfall capacity;
simulating the water quantity of the fish pond which is lost to the peripheral river day by day through seepage by depending on the water level of the cultured fish pond, and accounting daily water quantity exchange between the fish pond and the peripheral river by combining the drainage quantity and the diversion quantity;
according to the exchange water quantity and the nitrogen and phosphorus concentration of the fishpond, the surrounding river and the precipitation, the nitrogen and phosphorus quantity of the fishpond and the nitrogen and phosphorus exchange quantity of the fishpond and the surrounding river are calculated.
The fish pond is a pond water ecological system for culturing freshwater aquatic products, is widely distributed in plain river network areas such as middle and lower reaches of Yangtze river, zhujiang delta and the like, adopts a mixed culture mode (throwing aquatic organisms), and depends on feed feeding, oxygenation devices, a water changing system and other necessary facilities to keep healthy growth of the cultured organisms.
As a preferable implementation mode, the dissolved oxygen balancing module simulates the processes of water reoxygenation, photosynthetic oxygenation of aquatic organisms, oxygen consumption of aquatic organisms by breathing and the like of the fishpond aerator.
Further, the specific process for simulating the water reoxygenation, the photosynthesis oxygenation and the breathing oxygen consumption processes of the aquatic organisms of the fishpond aerator comprises the following steps:
collecting reoxygenation data of a fish pond water body, including collecting power of an aerator of the fish pond and total electricity consumption of the fish pond, accounting the total aeration duration of the aerator of the month and averaging the aeration duration to daily, and quantifying the increment of dissolved oxygen caused by daily aeration;
simulating an oxygen diffusion process of a water-gas interface, wherein the simulation of the daily atmospheric sedimentation oxygen amount and the upward diffusion amount of water dissolved oxygen depends on meteorological data such as daily humidity, atmospheric pressure, wind speed, air temperature, humidity and radiation;
simulating photosynthesis and respiration processes of aquatic organisms, including simulating oxygen production of day-to-day photosynthesis according to meteorological data such as sunlight duration, radiation, air temperature and the like of macrophytes and phytoplankton biomass, and simulating day-to-day respiration oxygen consumption according to the aquatic biomass;
according to the artificial aeration, the water-air interface diffusion, the photosynthesis of aquatic organisms and the respiratory dissolved oxygen quantity simulated daily, the daily dynamic change process of the concentration of the dissolved oxygen in the water body of the fish pond is calculated.
As a preferred embodiment, the nitrogen-phosphorus bio-geochemical cycle module simulates a pond nitrogen-phosphorus migration and transformation process and a sediment-water-vapor interface diffusion mechanism, namely a nitrogen-phosphorus morphological transformation process caused by aquatic organism growth extinction and water ecological geochemistry, and migration processes of nitrogen and phosphorus in various forms at sediment-water-vapor interfaces, wherein the nitrogen in various forms comprises organic nitrogen, ammonia nitrogen and nitrate nitrogen; the phosphorus comprises organic phosphorus and phosphate in each form, and the concentration unit mg/L is adopted.
Further, the specific process for simulating the nitrogen and phosphorus migration conversion process and the sediment-water-vapor interface diffusion mechanism of the fishpond comprises the following steps:
constructing a nitrogen-phosphorus bio-geochemical circulation control equation driven by the growth and extinction of aquatic organisms in a fish pond, and quantitatively simulating the processes controlled by the temperature and the dissolved oxygen concentration, including organic nitrogen-phosphorus mineralization, ammonia nitrogen nitrification, nitrate nitrogen denitrification, anaerobic ammonia oxidation, sediment release, biological absorption, excretion, death, putrefaction and the like;
describing a sediment-water interface nitrogen-phosphorus diffusion mechanism, which comprises the processes of sediment organic nitrogen-phosphorus re-suspension, sediment pore water inorganic nitrogen-phosphorus release, water organic nitrogen-phosphorus sedimentation and the like, wherein the sediment-water interface diffusion driving force is the concentration difference of sediment and overlying water nitrogen-phosphorus;
describing a nitrogen-phosphorus diffusion mechanism of a water-gas interface, wherein the nitrogen-phosphorus diffusion mechanism comprises the processes of atmospheric dry sedimentation of inorganic nitrogen, precipitation input of dissolved nitrogen-phosphorus, water surface denitrification, anaerobic ammoxidation and the like, and the driving force of the water-gas interface diffusion is weather conditions such as precipitation, temperature, humidity, wind speed and the like;
and (3) accounting the balance and balance conditions of nitrogen and phosphorus in each form in geochemical circulation under the drive of aquatic organisms, and simulating the daily dynamic change process of the nitrogen and phosphorus concentration in each form in the fishpond.
The nitrogen and phosphorus flow rate of the fishpond provided by the invention comprises three paths: nitrogen and phosphorus gas loss generated by water-gas interface diffusion comprises daily denitrification and anaerobic ammoxidation processes; nitrogen and phosphorus solid loss generated by sediment-water interface diffusion comprises daily biological excretion, death, putrefaction and sedimentation processes; loss of dissolved nitrogen and phosphorus due to water exchange, including daily drainage and leakage processes.
As a preferred implementation mode, the method further comprises the steps of carrying out model verification based on actually measured meteorological data, hydrologic data and water quality monitoring data, calibrating model parameters, and improving model simulation accuracy, wherein the meteorological monitoring data refer to indexes such as daily rainfall, average air temperature, highest air temperature, lowest air temperature, average humidity, average atmospheric pressure, average wind speed and the like, the hydrologic monitoring data refer to daily pond water level and water level changes caused by water diversion and water drainage, and the water quality monitoring data refer to indexes of total nitrogen, organic nitrogen, ammonia nitrogen, nitrate nitrogen, total phosphorus, organic phosphorus and phosphate concentration of a month-by-month pond and surrounding rivers.
Furthermore, the model verification is to adopt ten most sensitive parameters of a Morris identification model of a global sensitivity analysis method, an intelligent optimal mode (SCE-UA algorithm) of the sensitive parameters of the model is constructed, the optimal combination of the sensitive parameters of the model is prioritized, and the model simulation precision is improved.
Further, based on measured meteorological, hydrological and water quality monitoring data, comparing simulation values and measured values of concentration indexes of total nitrogen, organic nitrogen, ammonia nitrogen, nitrate nitrogen, total phosphorus, organic phosphorus and phosphate, quantitatively evaluating the fitting degree of a model by adopting Nash efficiency coefficients and decision coefficients, and evaluating the error of the model by adopting proportional deviation.
Furthermore, based on the intelligent optimal total nitrogen and total phosphorus evaluation precision model parameter combination, simulating the daily change of nitrogen and phosphorus during the fish pond culture, and accounting the flux of the nitrogen and phosphorus migration and conversion process, thereby obtaining the daily loss amount of nitrogen and phosphorus in the fish pond and finely predicting the nitrogen and phosphorus loss in the fish pond.
It is another object of the present invention to provide the use of the above method for optimizing cultivation management.
The invention provides an application mode, which comprises the following steps:
simulating different cultivation throwing densities by adjusting initial values of state variables of river crabs, fishes and macrophytes, simulating a combination scene of different cultivation throwing densities by utilizing a fishpond nitrogen-phosphorus circulation model, and calculating flux and source sink balance in a nitrogen-phosphorus migration conversion process based on a simulation result to obtain the change condition of the nutrition utilization rate of the nitrogen-phosphorus of the combination of different cultivation throwing densities, so as to determine a preferable scheme of the cultivation throwing densities;
or, simulating different tail water treatment scenes by adjusting initial values of state variables of the nitrogen and phosphorus circulation model of the fish pond, simulating different tail water treatment scenes based on the model, calculating reduction amount of nitrogen and phosphorus in the tail water by using simulation results, analyzing reduction conditions of nitrogen and phosphorus in different tail water treatment modes, and determining a preferable scheme of the tail water treatment mode; the tail water treatment scenario includes in situ treatment and ex situ treatment.
The invention combines the simulation technologies of aquatic organism growth and extinction, bio-geochemical circulation, sediment-water and water-gas interface diffusion and the like, and by developing a Pond nitrogen-phosphorus circulation model (Pond-NP) which covers the aquatic organism growth and extinction and bio-geochemical circulation, the input, output and migration transformation processes of three forms of nitrogen (organic nitrogen, ammonia nitrogen and nitrate nitrogen) and two forms of phosphorus (organic phosphorus and phosphate) of the Pond are simulated, the source and sink balance mechanism of nitrogen and phosphorus is ascertained, the sediment-water interface, the water-gas interface and the nitrogen and phosphorus exchange quantity of the Pond and the surrounding river are calculated, and the nitrogen and phosphorus loss of the Pond is finely predicted. The mechanism method of the invention provides technical support for the investigation of the nitrogen and phosphorus loss pollution of the fish pond widely distributed in the middle and downstream of the Yangtze river, the Zhujiang river basin and other coastal areas in China.
The beneficial effects of the invention are as follows: (1) The method for describing the dynamic rule of the nitrogen and the phosphorus in the fish pond is beneficial to accurately identifying the main control factors for driving the loss of the nitrogen and the phosphorus in the fish pond; (2) The method provides a fine means for accounting the loss of nitrogen and phosphorus in the fish pond, and provides technical support for the treatment and control of nitrogen and phosphorus pollution in the fish pond; (3) The simulation technology for simulating the nitrogen and phosphorus circulation of the fishpond under the driving of aquatic organisms can predict the nitrogen and phosphorus loss change condition under different cultivation schemes or relieving measures, and the scheme for supporting the prevention and control of nitrogen and phosphorus pollution is preferable.
Drawings
FIG. 1 shows the mechanism process of the invention for the modeling of nitrogen and phosphorus circulation in fish ponds.
FIG. 2 shows the location of a case fish pond and a cultivation management mode.
Fig. 3 shows simulation results of nitrogen and phosphorus concentration in various forms of fishpond nitrogen and phosphorus circulation model 2020-2021.
Fig. 4 shows the flux of nitrogen-phosphorus migration and conversion process derived from the pond nitrogen-phosphorus circulation model.
Fig. 5 shows the nitrogen-phosphorus source sink balance mechanism derived from the pond nitrogen-phosphorus circulation model.
Fig. 6 shows nitrogen and phosphorus recovery rates in different fish and river crab feed density scenarios.
Fig. 7 shows nitrogen and phosphorus concentration ranges and nitrogen and phosphorus fixation amounts in different macrophyte planting density scenarios.
Fig. 8 shows nitrogen and phosphorus reduction rates in the case of in situ and ex situ treatment of the aquaculture tail.
Detailed Description
The technical scheme of the invention is further described below with reference to the accompanying drawings and the detailed description.
Example 1
Example 1 the method of the present invention will be further described by taking the example of a refined prediction of nitrogen and phosphorus loss in a typical fishpond (Liyang, jiangsu province).
In the embodiment, a constructed Pond nitrogen and phosphorus circulation model (Pond-NP) is used as a basis, a typical Pond hydrologic water quality monitoring and cultivation practice survey (2020-2021) is developed, the dynamic daily change of Pond nitrogen and phosphorus is simulated, the nitrogen and phosphorus migration conversion, input and output processes are analyzed, sediment-water interface, water-gas interface and Pond and surrounding river nitrogen and phosphorus exchange quantity are calculated, and the nitrogen and phosphorus loss quantity of the Pond is finely predicted. The implementation of the refined prediction of the nitrogen and phosphorus loss of the fish pond comprises four steps:
(1) Fish pond hydrologic water quality monitoring and cultivation practice investigation
The present example investigated a typical aquaculture concentration area of a pond located downstream of the Yangtze river in China-Jiangsu province Liyang city with a pond area of about 0.2ha and an average water depth of about 1.5m (FIG. 2). In this embodiment, the model usage data is constructed to include water quality and water level data of the fish ponds and surrounding rivers monitored month by month in 2020 to 2021, wherein the water quality monitoring indicators include total nitrogen, organic nitrogen, ammonia nitrogen, nitrate nitrogen, total phosphorus, organic phosphorus and phosphate concentration, and the water level data is recorded by a water level gauge. The model-driven meteorological data come from Li-yang meteorological stations, including daily air pressure, precipitation, average air temperature, highest air temperature, lowest air temperature, average humidity, average wind speed, sunshine duration and the like. The cultivation practice investigation projects comprise the time and density of throwing fishes, river crabs and macrophytes by fishermen, the consumption of feed per month, the power consumption of a month aerator, the drainage date, water quantity, harvesting time, the recapture rate of various cultivation organisms and the like.
(2) Construction and dynamic simulation of fishpond nitrogen and phosphorus circulation model
Model state variables (river crab biomass, fish biomass, macrophyte biomass, zooplankton biomass, total nitrogen concentration, organic nitrogen concentration, ammonia nitrogen concentration, nitrate nitrogen concentration, total phosphorus concentration, organic phosphorus concentration, phosphate concentration, dissolved oxygen concentration and water level) and initial values are determined.
The mathematical characterization method described by the design model simulates the unique migration and transformation process of nitrogen and phosphorus circulation under the drive of aquatic organisms in the fishpond. Organic nitrogen and phosphorus sources include biological excretion, death, spoilage and sediment re-suspension, sink to include ingestion, sedimentation and mineralization; the ammonia nitrogen source comprises atmospheric sedimentation, sediment release, biological excretion and mineralization, and the sink comprises biological absorption, anaerobic ammonia oxidation and nitrification; the nitrate nitrogen source comprises nitrification, atmospheric sedimentation and sediment release, and the sink comprises biological absorption and denitrification; phosphate sources include sediment release, bio-excretion and mineralization, sink including bio-absorption. The control equation for the process simulation is as follows:
(1) total nitrogen total phosphorus:
TN T ＝ON T +NH 3 T +NO x T (1)
TP T ＝OP T +PO 4 T (2)
(2) the multi-biology-driven nitrogen-phosphorus circulation process, namely the design of the application, introduces a control equation for describing the growth and death of aquatic organisms in a fish pond:
wherein formula (3) is an aquatic biomass control equation describing the dynamics of the aquatic biomass in the biological processes under consideration (feeding, growing, being fed, excreted and dying); the formula (4) is biomass with increased nutrient growth ingested by autotrophs (macrophytes and phytoplankton) in the aquatic organisms; formula (5) increases biomass for the feeding process of aquatic organisms, including feeding (e.g., phytoplankton fed by zooplankton) and predation (zooplankton fed by silver carp). Formulas (6) - (10) are temperature, light, nitrogen phosphorus, dissolved oxygen, and food availability limiting factors, respectively, of the biological process.
Further, the biological X, Y, Z in the formula is described as follows:
organism Y can be used to represent all aquatic organisms considered (river crabs, fish, zooplankton, macrophytes and phytoplankton) and X (organisms ingested by Y) and R (organisms ingested by Y) will be determined after Y is determined, thus X, R is a temporary variable. For example, when Y is zooplankton, X is zooplankton, R is fish, and when Y is zooplankton, X is empty, R is zooplankton and fish, and the food network relationship can be seen in FIG. 1. Organisms other than X and R are not considered in calculating the dynamic changes in biomass of organism Y.
(3) Three morphological nitrogen (organic nitrogen, ammonia nitrogen and nitrate nitrogen) bio-geochemical cycle control equations:
ON T ＝ON T-ΔT +q ONResu +q ONWs +q ONFer +∑ Y q Y2OE ×Y N -q ONSedi -q ONMine -q ON2Z (11)
(4) two forms of phosphorus (organophosphorus and phosphate) bio-geochemical cycling control equations:
OP T ＝OP T-ΔT +q OPResu +q OPWs +q OPFer +∑ Y q Y2OE ×Y P -q OPSedi -q OPMine -q OP2Z (14)
(5) water quantity and dissolved oxygen balance control equation:
WL T ＝WL T-ΔT +q WLPr +q WLPumpin -q WLEva -q WLSeep -q WLPumpout (16)
DO T ＝DO T-ΔT +q DODep +q DOPhot -q DOResp (17)
wherein T represents the time, deltaT represents the time step, TN T Indicating the total nitrogen concentration at time T, ON T Represents the organic nitrogen concentration at the T moment, NH 3 T Represents the ammonia nitrogen concentration at the time T and NO x T Indicating the nitrate nitrogen concentration at the time T, TP T Indicating the total phosphorus concentration at time T, OP T Represents the concentration of organic phosphorus and PO at the T moment 4 T Represents the phosphate concentration at time T, WL T And DO T Represents the water level and the dissolved oxygen concentration at the time T, Y T And Y T-ΔT The biomass (g/m) of the organism at time T and at time T-DeltaT 2 ) Formula (3) is a general biomass (river crab, fish, zooplankton, macrophyte and phytoplankton) control equation, Σ X q X2Y Representing the biomass of organisms X ingested by heterotrophs (river crabs, fish, zooplankton) Y (heterotrophs Y being the heterotrophs in aquatic organisms Y),represents the growth amount (autotroph, i.e., autotroph in aquatic organism Y) of autotrophs (macrophytes, phytoplankton), Σ R q Y2R The relationship of food network is shown in figure 1, q Y2OE Represents the organic matter excretion amount, q of the organism Y Y2IE Represents the inorganic matter excretion amount, q of the organism Y Y2M Indicating the death or spoilage of organism Y, FT (Y) indicating the temperature limiting factor for organism growth or ingestion, FL (Y) indicating the light limiting factor for autotroph growth, FNP (Y) indicating the nitrogen-phosphorus limiting factor for autotroph growth, FDO (Y) indicating the oxygen limiting factor for heterotroph ingestion, FA (X, Y) indicating the food limiting factor for heterotroph ingestion, I z Indicating the illumination intensity->Indicating the maximum growth rate of organisms,/->Indicating maximum feeding rate of the organism, +.>Represents the optimal, minimum and maximum water temperature, T, for the growth of a suitable organism Y Ave Represents average water temperature +.>Represents the saturated intensity of the growth of autotroph Y, KN Y Represents the half-saturated concentration of inorganic nitrogen for the growth of autotroph Y, KP Y KO representing the half-saturated concentration of inorganic phosphorus for the growth of autotroph Y Y Represents the dissolved oxygen half-saturated concentration of the heterotrophic Y feed, KH X2Y Represents the half-saturated concentration, q, of the feeding organism X of the heterotrophic organism Y ONResu 、q OPResu Represents the concentration change of organic nitrogen and phosphorus caused by re-suspension, q ONWs 、q OPWs 、q NH3Ws 、q NOxWs 、q PO4Ws Represents the concentration change of organic nitrogen, phosphorus, ammonia nitrogen, nitrate nitrogen and phosphate generated by water diversion, q ONFer 、q OPFer 、q NH3Fer 、q NOxFer 、q OP4Fer Represents the concentration change of organic nitrogen and phosphorus, ammonia nitrogen, nitrate and phosphate generated by fertilization, Y N 、Y P Represents the nitrogen and phosphorus content in the organism, q ONSedi 、q OPSedi Represents the change of organic nitrogen and phosphorus concentration caused by sedimentation, q ONMine 、q OPMine Represents the change of organic nitrogen and phosphorus concentration caused by mineralization, q ON2Z 、q OP2Z Represents the change of organic nitrogen and phosphorus concentration caused by ingestion of zooplankton, q NH3Rele 、q NOxRele 、q PO4Rele Represents the concentration change of ammonia nitrogen, nitrate nitrogen and phosphate generated by the release of bottom mud, q NH3Pr 、q NOxPr 、q PO4Pr Represents the concentration change of ammonia nitrogen, nitrate nitrogen and phosphate generated by precipitation, q NH3Dep 、q NOxDep 、q PO4Dep Represents the concentration change of ammonia nitrogen, nitrate nitrogen and phosphate generated by atmospheric sedimentation, k NH3 Represents the proportion of ammonia nitrogen absorbed by plants in inorganic nitrogen, q WLPr 、q WLPumpin 、q WLEva 、q WLSeep 、q WLPumpout Represents the change of the water level of the fish pond caused by precipitation, water diversion, evaporation, seepage and drainage, q DODep 、q DOPhot 、q DOResp The change of the dissolved oxygen concentration of the fish pond caused by atmospheric sedimentation, photosynthesis and respiration of aquatic organisms is shown.
And compiling an executable program of the model to simulate the dynamic change of nitrogen and phosphorus in the fish pond. Setting the simulation step length as a day, calibrating sensitive parameters based on a 2020 weather, hydrology and water quality monitoring data verification model, and using 2021 water quality monitoring data verification model to extrapolate prediction capability. Model checksum parameter calibration comprises the steps of identifying model sensitive parameters by using a global sensitivity analysis method Morris, constructing an intelligent optimization mode of the model sensitive parameters by using an SCE-UA algorithm, and iterating an optimal parameter set of a preferred model. Using Nash efficiency coefficient (NSE), determination coefficient (R 2 ) The model fitness is quantitatively evaluated, and the error of the model is evaluated by adopting proportional deviation (PBIAS), so that the accurate simulation of the dynamic change of the nitrogen and the phosphorus in the fish pond is realized (figure 3).
(3) Flux and sink balance analysis in nitrogen and phosphorus migration and conversion process of fish pond
According to the model, the flux of the migration and conversion process of nitrogen and phosphorus is calculated. According to the daily simulation result of the model, the source-sink balance of three forms of nitrogen and two forms of phosphorus is calculated, and the flux of the migration and conversion process of nitrogen and phosphorus is counted on the scale of the cultivation period (3-10 months) (figure 4). According to the method, the internal mechanism of the dynamic change rule of the nitrogen and the phosphorus in the fish pond is explored, and the main control factors for driving the nitrogen and the phosphorus to circulate are accurately identified. Internal driving forces for dynamic changes in nitrogen and phosphorus in a fish pond include diversion, biological excretion, sediment-water interface diffusion and macrophyte absorption, wherein sediment-water interface diffusion dominates dynamic changes in organic nitrogen and phosphorus, temperature-controlled mineralization and macrophyte dominates dynamic changes in inorganic nitrogen and phosphorus. The key process of the nitrogen and phosphorus circulation of the fish pond comprises feed input, organic nitrogen and phosphorus resuspension, river crab excretion, macrophyte absorption and denitrification, wherein the main control factor is the feed input.
Further analyzes the balance mechanism of the source and sink of the nitrogen and the phosphorus in the fish pond. Boundary inputs in the model for controlling the nitrogen and phosphorus circulation process comprise feed, fertilizer, fish and crab fries, atmosphere and peripheral rivers, and boundary outputs comprise sediment, atmosphere, peripheral rivers, macrophytes, fish and river crabs, so that the balance of the nitrogen and phosphorus in the fish pond in the source and sink of the cultivation period is calculated, and the source and sink amount of the fish pond in the month scale is further refined (figure 5). In four sources of nitrogen and phosphorus in the fish pond, the feed investment plays a leading role, the fertilizer and fish and crab fries are only input in the initial stage of cultivation, the atmospheric settlement is mainly nitrogen, and the diversion of water from the peripheral river is mainly concentrated in summer. In the six-item pool of nitrogen and phosphorus in the fish pond, the sediment deposits the most nitrogen and phosphorus, and then the sediment is assimilated by macrophytes, river crabs and fish, and the rest of nitrogen and phosphorus is lost to the surrounding river and the atmosphere.
(4) Fine prediction of nitrogen and phosphorus loss in fish pond
In the embodiment, the step (2) realizes the dynamic fine simulation of the nitrogen and phosphorus in the fishpond (figure 3), the step (3) calculates the flux of the migration and conversion process of the nitrogen and phosphorus in the fishpond, analyzes a source sink balance mechanism, comprises the loss amount of the nitrogen and phosphorus in the fishpond to bottom mud, peripheral rivers and the atmosphere (figure 4) and the time sequence difference (figure 5), and realizes the fine prediction of the loss amount of the nitrogen and the phosphorus in the fishpond.
Example 2
Example 2 the method of the present invention and its potential application are further described taking as an example the optimization of the effect of fishermen's farming management practices on nitrogen and phosphorus loss in a fish pond.
The method is based on a constructed Pond nitrogen and phosphorus circulation model (Pond-NP), and by gradually adjusting an initial value of aquatic biomass and a tail water treatment scene multiple-time operation model, the influence of different culture densities and tail water treatment modes of the Pond on nitrogen and phosphorus loss is simulated, and the effect of fishermen optimizing culture management on reducing the nitrogen and phosphorus loss of the Pond is evaluated. The implementation is divided into four steps:
(1) Model generalization of cultivation management scenario
Modeling of different culture density combinations of river crabs, fish and macrophytes. The mixed culture mode of the fish pond is considered to be an effective means for improving the utilization rate of nitrogen and phosphorus and reducing the loss because the mixed culture mode can utilize nutrition of different levels by various aquatic organisms. At present, mixed health matters of the fish pond in China comprise fishes, river crabs, macrophytes and the like, the river crabs ingest feed, the unutilized or excreted feed is absorbed by the macrophytes and zooplankton, and then the fishes ingest the zooplankton (phytoplankton and zooplankton) to realize secondary utilization of nutrition. However, there is currently no efficient way to determine the optimal combination of dosing densities for different organisms, thereby achieving the highest utilization of nutrients. The fishpond nitrogen and phosphorus circulation model (Pond-NP) constructed by the invention can analyze the responses of nitrogen and phosphorus utilization and loss to different biological input density combinations by using a scene simulation means and finely describing the food network and nitrogen and phosphorus migration and conversion process in the multi-biological complex ecological system of the fishpond. The optimal scheme of the cultivation throwing density is analyzed by modifying initial values of state variables of river crabs, fishes and macrophytes, running a model program for a plurality of times, calculating flux and source sink balance in the nitrogen-phosphorus migration and conversion process based on simulation results, and analyzing the change condition of the nitrogen-phosphorus nutrition utilization rate under different combinations of the biological throwing densities.
Modeling of the cultivation tail water treatment scene. The fishpond and the peripheral river water amount are frequently exchanged, and in particular, in the pond cleaning process after the fishpond is harvested, the eutrophic tail water is discharged to the peripheral river, so that a great amount of nitrogen and phosphorus are lost, and the peripheral water ecological system is directly influenced. In order to avoid eutrophication of the surrounding river and deterioration of water quality, various ecological relief projects have been developed for treating the culture tail water, and can be roughly classified into two types according to the treatment process: in situ treatment and ex situ treatment. The two treatment modes have no effective comparison on the purification effect of the tail water, so that the tail water treatment mode is difficult to be optimized by fishermen. The fishpond nitrogen and phosphorus circulation model (Pond-NP) constructed by the invention can use a scene simulation means, and response of nitrogen and phosphorus purification effect to different tail water treatment modes can be obtained through describing the internal nitrogen and phosphorus reduction process during tail water ecological treatment. And (3) through adjusting the initial value of the model state variable, running the model program for a plurality of times, calculating the nitrogen and phosphorus reduction amount of the tail water based on the model simulation result, analyzing the nitrogen and phosphorus reduction conditions of different tail water treatment modes, and providing support for the optimization of the ecological relief engineering of the cultivation tail water.
(2) Evaluation of influence of fish pond throwing density on nitrogen and phosphorus utilization
The range of the simulation scene of the throwing density of the fish pond is set to be 60-90kg/ha of river crabs, 0-80kg/ha of fishes and 0-2000kg/ha of macrophytes based on investigation.
Initial values of the states of the river crabs and the fishes in the model are adjusted in a step-by-step combined mode with the step length of 10kg/ha, and the nitrogen and phosphorus recovery rate of the fish crabs under different putting density combinations is analyzed (figure 6). The result shows that the lower the stocking density of the river crabs is, the higher the recovery rate of nitrogen and phosphorus is; a fish launch density of 50kg/ha gives the highest nitrogen and phosphorus recovery, exceeding which levels may negatively impact fish growth performance. The fish-crab combination simulation shows that the highest nitrogen-phosphorus recovery rate can be obtained by putting 60kg/ha of river crabs and 50kg/ha of fishes, and compared with the current nitrogen-phosphorus recovery rate, the nitrogen-phosphorus recovery rate is respectively improved by 0.8 percent and 1.2 percent.
And gradually adjusting the initial value of the state of the model macrophyte with the step length of 100kg/ha, and analyzing the water quality change (total nitrogen and total phosphorus concentration range during cultivation) of the fishpond and the nitrogen and phosphorus fixation effect of the macrophyte under different throwing densities (figure 7). The result shows that increasing the planting density of the macrophytes from 0kg/ha to 800kg/ha gradually increases the utilization amount of nitrogen and phosphorus, wherein the highest utilization amount of nitrogen and phosphorus is 36.8kg/ha/yr and 5.6kg/ha/yr respectively, and compared with the current nitrogen and phosphorus recovery rate, the nitrogen and phosphorus recovery rates are respectively improved by 1.2 percent and 0.4 percent; however, exceeding 800kg/ha further increases the planting density without increasing the nitrogen and phosphorus utilization. In the range of 0-1000kg/ha of planting density, the total nitrogen and total phosphorus concentration range of the fish pond is obviously reduced during cultivation. The total phosphorus is reduced from 0.24-0.37mg/L to 0.07-0.17mg/L, and the median is reduced by 71.0%; the total nitrogen is reduced from 0.78-2.49mg/L to 0.48-1.36mg/L, the median is reduced by 58.8%, and when the planting density exceeds 1000kg/ha, the total nitrogen and total phosphorus concentration range is not changed significantly.
According to the verification of the scene simulation result, 60kg/ha of river crabs, 50kg/ha of fishes and 800kg/ha of macrophytes can obtain the highest nitrogen and phosphorus recovery rate, and compared with the current nitrogen and phosphorus recovery rate, the nitrogen and phosphorus recovery rate is respectively improved by 2.0 percent and 1.6 percent, which also means that the nitrogen and phosphorus loss of the fishpond is respectively reduced by 2.0 percent and 1.6 percent according to the preferable result of the scene simulation input density combination.
(3) Evaluation of influence of fishpond tail water treatment on nitrogen and phosphorus loss
Two scenes of in-situ treatment and ex-situ treatment under the same water ecological system are designed, and the first scene is in-situ treatment, namely, after the fish pond is harvested, nitrogen and phosphorus are reduced by putting algae, silver carps and macrophytes into the fish pond. The second scenario is ectopic treatment, namely, the cultivation tail water is introduced into an ecological treatment pool, the same ecological species as the first scenario is put in to cut nitrogen and phosphorus, and the main difference between the two scenarios is the enrichment level of nutrients in the sediment. Setting the tail water treatment period to be 11 months 1 day to 12 months 31 days, setting the simulation step length to be days, running a model program by adjusting the initial value of a model state variable, calculating the reduction amount of nitrogen and phosphorus in the tail water based on the model simulation result, and analyzing the reduction conditions of nitrogen and phosphorus in different tail water treatment modes.
The nitrogen and phosphorus reduction rates for in situ treatment were 9.6% and 5.1%, respectively (fig. 8). The main reduction effects comprise denitrification and absorption by macrophytes, 56.0% and 53.4% of nitrogen and phosphorus in the tail water are reduced respectively, and the algae-silver carp combination only reduces 1.0% of nitrogen and phosphorus in the tail water, but the eutrophic sediment is used as a nitrogen and phosphorus source to release 47.4% and 49.1% of nitrogen and phosphorus.
The nitrogen and phosphorus reduction rates for the ex-situ treatment were 40.2% and 45.3%, respectively (fig. 8). The main reduction results from sedimentation, denitrification and absorption by macrophytes, respectively reducing 39.2% and 44.4% of nitrogen and phosphorus in the tail water, and the algae-silver carp combination only reduces 1.0% and 0.9% of nitrogen and phosphorus in the tail water, probably due to low temperature in the tail water treatment period and not in the growth period of algae and fish. The nutrient-deficient sediment is taken as a sink to respectively settle 14.0 percent and 23.3 percent of nitrogen and phosphorus, which is the key that the reduction rate of the nitrogen and phosphorus of the ectopic treatment is obviously superior to that of the in-situ treatment.
According to the result of the scene simulation, the reduction rate of nitrogen and phosphorus in the ex-situ treatment (40.2% and 45.3%) is obviously better than that in-situ treatment (9.6% and 5.1%), wherein the nutrition-rich degree of the sediment is the key of the nitrogen and phosphorus reduction in the tail water ecological treatment. The conclusion can provide technical support for the pollution control and management of the nitrogen and phosphorus loss of the fish pond.

Claims (10)

1. A method for finely predicting nitrogen and phosphorus loss of a freshwater aquaculture fish pond is characterized by comprising the following steps:
acquiring meteorological, hydrological and water quality data of a fish pond and surrounding rivers thereof and fish pond management information;
establishing a fishpond nitrogen and phosphorus circulation model, wherein the fishpond nitrogen and phosphorus circulation model comprises a water quantity balance module, a dissolved oxygen balance module, a nitrogen and phosphorus biological geochemical circulation module and an aquatic organism growth and death module; the aquatic organism is river crab, fish, macrophyte, phytoplankton and zooplankton in the fishpond, and the aquatic organism growth and death module simulates the nitrogen and phosphorus assimilation and excretion of the aquatic organism in the fishpond, including the feeding, assimilation, excretion and death processes of the aquatic organism;
based on the acquired data information and the fishpond nitrogen and phosphorus circulation model, simulating the dynamic change of the fishpond nitrogen and phosphorus day by day, accounting the sediment-water and water-air interface and the exchange quantity of the fishpond and the surrounding river nitrogen and phosphorus, and predicting the loss quantity of the fishpond nitrogen and phosphorus.
2. The method of claim 1, wherein simulating nitrogen and phosphorus assimilation and excretion of fish pond aquatic organisms comprises:
collecting data of aquatic organisms in the fishpond, including initial throwing density and final recapture rate of the aquatic organisms in the fishpond, calculating the daily death rate of the aquatic organisms according to the final recapture rate, and investigating the nitrogen and phosphorus assimilation efficiency of each organism and the organic and inorganic nitrogen and phosphorus proportion in excrement;
constructing a fishpond aquatic organism food net according to the ecological niche relation;
based on the collected data and the established food network, simulating the nitrogen and phosphorus circulation process under the drive of aquatic organisms in a fishpond by means of a mathematical characterization method, wherein the nitrogen and phosphorus circulation process comprises inorganic nitrogen and phosphorus absorbed by macrophytes and phytoplankton in the growth process and the amount of organic nitrogen and phosphorus released by death or putrefaction, and the amounts of organic nitrogen and phosphorus excreted by undigested or unutilized crabs, fish and zooplankton after ingestion, and the amounts of ammonia nitrogen and phosphate excreted after digestion.
3. The method of claim 2, wherein the niche relationship comprises river crab feeding and macrophytes, fish feeding phytoplankton and zooplankton feeding phytoplankton and detritus, macrophytes and phytoplankton growing by absorption of inorganic nitrogen and inorganic phosphorus.
4. The method of claim 1, wherein the control equation for the aquatic growth extinction module is as follows:
wherein T represents the time, deltaT represents the time step, Y T And Y T-ΔT The aquatic organisms are represented by time T and time T-delta TBiomass of the substance Σ X q X2Y Indicating the biomass of organism X ingested by heterotrophic organism Y,indicating the growth amount of autotrophs, sigma R q Y2R Biomass, q, representing ingestion of organism Y by heterotrophic organism R Y2OE Represents the organic matter excretion amount, q of the organism Y Y2IE Represents the inorganic matter excretion amount, q of the organism Y Y2M Indicating the death or spoilage of organism Y, FT (Y) indicating the temperature limiting factor for organism growth or ingestion, FL (Y) indicating the light limiting factor for autotroph growth, FNP (Y) indicating the nitrogen-phosphorus limiting factor for autotroph growth, FDO (Y) indicating the oxygen limiting factor for heterotroph ingestion, FA (X, Y) indicating the food limiting factor for heterotroph ingestion, I z Indicating the illumination intensity->Represents ammonia nitrogen concentration->Indicating nitrate nitrogen concentration,/->Indicating phosphate concentration, DO T Represents the dissolved oxygen concentration; wherein the parameters are as follows, (-)>Indicating the maximum growth rate of organisms,/->Indicating maximum feeding rate of the organism, +.>Represents the optimal, minimum and maximum water temperature, T, for the growth of a suitable organism Y Ave Represents average water temperature +.>Represents the saturated intensity of the growth of autotroph Y, KN Y Represents the half-saturated concentration of inorganic nitrogen for the growth of autotroph Y, KP Y KO representing the half-saturated concentration of inorganic phosphorus for the growth of autotroph Y Y Represents the dissolved oxygen half-saturated concentration of the heterotrophic Y feed, KH X2Y Representing the half-saturated concentration of feeding organism X by heterotrophic organism Y.
5. The method of claim 1, wherein the water balance module simulates the water exchange of a fish pond with the atmosphere, surrounding rivers;
the water quantity exchange between the fishpond and the atmosphere comprises precipitation and evaporation processes;
the water volume exchange between the fish pond and the surrounding river comprises the processes of seepage, water diversion and drainage.
6. The method of claim 1, wherein the dissolved oxygen balance module simulates oxygen re-oxygenation of an aerator water body, photosynthetic oxygenation of aquatic organisms, and respiratory oxygen consumption process of aquatic organisms.
7. The method according to claim 1, wherein the nitrogen-phosphorus bio-geochemical cycle module simulates a pond nitrogen-phosphorus migration and conversion process and migration process of nitrogen and phosphorus with different forms at sediment-water-air interfaces;
the nitrogen with different forms comprises organic nitrogen, ammonia nitrogen and nitrate nitrogen; the different forms of phosphorus include organic phosphorus and phosphate.
8. The method of claim 1, further comprising model checking, calibrating model parameters based on measured weather, hydrology, water quality monitoring data;
the model check is as follows: identifying the sensitive parameters of the model by adopting a global sensitivity analysis method Morris, constructing an intelligent optimization mode of the sensitive parameters of the model by using an SCE-UA algorithm, and obtaining an optimal parameter set of the model; comparing the simulation value and the actual measurement value of each nitrogen and phosphorus index, adopting Nash efficiency coefficient and determining coefficient to quantitatively evaluate the fitting degree of the model, and adopting proportional deviation to evaluate the model error.
9. Use of the method of any one of claims 1 to 8 for optimizing cultivation management.
10. The use according to claim 9, characterized in that it comprises:
simulating different cultivation throwing densities by adjusting initial values of state variables of river crabs, fishes and macrophytes, simulating a combination scene of different cultivation throwing densities by utilizing a fishpond nitrogen-phosphorus circulation model, and calculating flux and source sink balance in a nitrogen-phosphorus migration conversion process based on a simulation result to obtain the change condition of the nutrition utilization rate of the nitrogen-phosphorus of the combination of different cultivation throwing densities, so as to determine a preferable scheme of the cultivation throwing densities;
or, simulating different tail water treatment scenes by adjusting initial values of state variables of the nitrogen and phosphorus circulation model of the fish pond, simulating different tail water treatment scenes based on the model, calculating the reduction amount of nitrogen and phosphorus in the tail water by using a simulation result, analyzing the reduction conditions of nitrogen and phosphorus in different tail water treatment modes, and determining a preferable scheme of the tail water treatment mode; the tail water treatment scenario includes in situ treatment and ex situ treatment.
CN202311213267.4A 2023-09-19 2023-09-19 Fine prediction method and application of nitrogen and phosphorus loss of freshwater aquaculture fishpond Pending CN117273218A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117593146A (en) * 2024-01-18 2024-02-23 北京鑫创数字科技股份有限公司 Green circulation planting and breeding information processing system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117593146A (en) * 2024-01-18 2024-02-23 北京鑫创数字科技股份有限公司 Green circulation planting and breeding information processing system
CN117593146B (en) * 2024-01-18 2024-04-02 北京鑫创数字科技股份有限公司 Green circulation planting and breeding information processing system

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