CN114417613B - System and method for forecasting development trend of enteromorpha prolifera in yellow sea under combined action of physics and ecology - Google Patents
System and method for forecasting development trend of enteromorpha prolifera in yellow sea under combined action of physics and ecology Download PDFInfo
- Publication number
- CN114417613B CN114417613B CN202210066677.XA CN202210066677A CN114417613B CN 114417613 B CN114417613 B CN 114417613B CN 202210066677 A CN202210066677 A CN 202210066677A CN 114417613 B CN114417613 B CN 114417613B
- Authority
- CN
- China
- Prior art keywords
- enteromorpha
- data
- forecast
- information
- forecasting
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C13/00—Surveying specially adapted to open water, e.g. sea, lake, river or canal
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Geometry (AREA)
- Computer Hardware Design (AREA)
- Life Sciences & Earth Sciences (AREA)
- Hydrology & Water Resources (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The system downloads external forced data and enteromorpha satellite remote sensing data, carries out calculation and prediction according to the external forced data, the enteromorpha satellite remote sensing data, enteromorpha drift calculation parameters under the action of multi-scale wind flow and enteromorpha growth and death calculation parameters under the action of biochemical process, obtains forecast data of drift transport path and biomass scale change of enteromorpha in the yellow sea under the action of geochemical combination, and finally processes and visually displays information such as early warning of drift path, biomass, distribution area, shore supporting moment and the like of enteromorpha particles in the yellow sea based on the forecast data. Therefore, according to the implementation mode, the forecasting timeliness can be improved through the web crawler and automatic forecasting, and the forecasting accuracy of the drift rate, direction and biomass forecasting elements of the enteromorpha prolifera is improved through considering the turbulent small-scale motion random process and the biochemical process of various nutrient salts.
Description
Technical Field
The application relates to the field of physical oceans and marine ecological dynamics, in particular to a system and a method for forecasting development trend of enteromorpha prolifera in yellow sea under the combined action of physical ecology.
Background
Large-scale green tide disasters with enteromorpha as dominant species are outbreaked in the middle and south China sea areas of the yellow sea in 4-8 months every year. In the prior art, the numerical simulation of drift transport of enteromorpha flava phytoplankton on sea is mainly based on lagrangian method to carry out post-reporting simulation of drift transport of enteromorpha flava (namely, carrying out numerical simulation on the outbreak time of enteromorpha flava which has occurred in the past). However, in practice, it has been found that this method has the problem of poor prediction timeliness and the problem of low ocean current driving resolution.
Disclosure of Invention
The embodiment of the application aims to provide a system and a method for forecasting the development trend of enteromorpha prolifera in yellow sea under the combined action of physical and ecology, which can improve the forecasting timeliness through web crawlers and automatic forecasting and improve the forecasting accuracy of the drift rate, direction and biomass of enteromorpha prolifera in yellow sea by considering a turbulent small-scale motion random process and a biochemical process of various nutrient salts.
In a first aspect, the embodiments of the present application provide a system for forecasting the development trend of enteromorpha prolifera in yellow sea under the combined action of physical and ecological features, the system comprises a data subsystem, a forecasting subsystem and an application subsystem, wherein,
the data subsystem is used for downloading external forced data and enteromorpha satellite remote sensing data;
the data subsystem is further used for performing data format conversion according to the external forcing data to obtain external forcing data in a netcdf format, and interpolating the external forcing data into a horizontal grid of the forecasting subsystem;
the data subsystem is further used for acquiring longitude and latitude information of the enteromorpha position according to the enteromorpha satellite remote sensing data;
the forecasting subsystem is used for acquiring the external forced data, the longitude and latitude information of the enteromorpha position, enteromorpha drifting calculation parameters under the action of multi-scale wind flow input by a user and enteromorpha growth and death calculation parameters under the action of biochemical processes input by the user;
the forecasting subsystem is further used for carrying out space-time calculation forecasting according to the external forcing data, the longitude and latitude information of the enteromorpha position and the enteromorpha drift calculation parameter to obtain drift path forecasting information of the enteromorpha particle in the yellow sea;
the forecasting subsystem is further used for calculating and forecasting according to the external forcing data, the longitude and latitude information of the enteromorpha position and the enteromorpha growth and death calculation parameters under the action of the biochemical process to obtain biomass forecasting information in the yellow sea enteromorpha growth and death process;
the application subsystem is used for processing the drift path forecast information of the enteromorpha flavea particles and the biomass forecast information in the growth and death process of the enteromorpha flavea to obtain drift direction, distribution area, early warning at the shore arrival moment, biomass abundance information and visually display the information.
Further, the data subsystem includes:
the data control module is used for controlling the operation of the data subsystem based on the shell script file; the log file downloading method comprises the steps of specifically calling different data downloading modules to carry out data downloading processing and outputting corresponding log files; the log file is used for displaying all processes of data downloading processing of the external forced data downloading module and the enteromorpha satellite remote sensing data downloading module and whether the processes are successful or not;
the external forcing data downloading module is used for acquiring and downloading external forcing data based on the web crawler; the external forcing data at least comprises short-term forecast field data of a global forecast system used in short-term forecast for 10 days in the future and long-term forecast field data of a climate forecast system used in long-term forecast for 9 months in the future;
the data format processing module is used for converting the data formats of the short-term forecast field data and the long-term forecast field data into a netcdf format based on a wgrib data processing method; the original data format of the short-term forecast field data and the long-term forecast field data is grb2 format;
the data interpolation module is used for interpolating the short-term forecast field data and the long-term forecast field data in a netcdf format into a horizontal grid of the forecast branch system based on a bilinear interpolation method;
the enteromorpha satellite remote sensing data downloading module is used for acquiring and downloading enteromorpha satellite remote sensing data of MODIS and HY water color series satellites based on web crawlers;
the enteromorpha satellite image information processing module is used for processing various enteromorpha satellite remote sensing data based on a data fusion method; the method is also used for obtaining an enteromorpha satellite remote sensing picture based on a vegetation index inversion method; and the method is also used for acquiring the longitude and latitude information of the enteromorpha position based on a ginput picture dotting calculation method.
Further, the data subsystem further comprises:
the first data information storage module is used for classifying and storing the external forcing data, the short-term forecasting field data, the long-term forecasting field data, the short-term forecasting field data in the netcdf format, the long-term forecasting field data in the netcdf format, the enteromorpha satellite remote sensing data and the enteromorpha position longitude and latitude information.
Further, the forecasting subsystem comprises:
the forecast control module is used for controlling the operation of the forecast subsystem based on the shell script file; the system is specifically used for acquiring longitude and latitude information of the enteromorpha position and acquiring the short-term forecast field data in the netcdf format or the long-term forecast field data in the netcdf format according to a forecast mode; the forecasting mode is short-term forecasting or long-term forecasting;
the refined area circulation calculation module is used for calculating marine physical and ecological forecast data based on the short-term forecast field data or the long-term forecast field data; the marine physical ecology forecast data at least comprises yellow sea marine circulation data, sea temperature data, nitrate data, phosphate data and silicate data; the marine physical and ecological forecast data is used for forecasting drifting transportation and growth and death of enteromorpha prolifera;
the parameter input module is used for acquiring enteromorpha drifting calculation parameters under the action of multi-scale wind flow input by a user and enteromorpha growth and death calculation parameters under the action of a biochemical process; the enteromorpha drift calculation parameters at least comprise a time step length, total simulation days, a drift deflection angle, a wind speed compression coefficient, a flow speed compression coefficient and a turbulent flow small-scale motion equation coefficient; the enteromorpha growth death calculation parameters under the action of the biochemical process at least comprise the maximum enteromorpha growth rate, the enteromorpha death rate, the optimal enteromorpha illumination intensity and the nutrient salt half-saturation rate;
the drift transport prediction module is used for performing space-time calculation prediction according to turbulent small-scale motion data, the short-term prediction field data or the long-term prediction field data, the marine physical and ecological prediction data, the enteromorpha position longitude and latitude information and the enteromorpha drift calculation parameters by adopting a Lagrange method and a fourth-order solution method to obtain drift path prediction information of the enteromorpha particle in the yellow sea;
and the life-disappearing process forecasting module is used for calculating and forecasting according to the marine physical and ecological forecast data, the longitude and latitude information of the enteromorpha position and the enteromorpha growth and death calculation parameters under the biochemical action to obtain biomass forecast information in the life-disappearing process of the enteromorpha in the yellow sea.
Further, the forecasting control module is specifically further used for judging whether the satellite monitors enteromorpha on the same day according to the longitude and latitude information of the enteromorpha position; if the enteromorpha is monitored on the same day, calling the longitude and latitude information data of the position of the enteromorpha for prediction; if the enteromorpha is not monitored in the current day, calling the longitude and latitude information data of the enteromorpha position in the previous day for prediction.
And further, the drifting transportation forecasting module is also used for judging whether the enteromorpha prolifera particles land on the shore or not by adopting a coast line segment intersection method according to a turbulent small-scale motion random process during drifting diffusion of the enteromorpha prolifera particles and a straight line formed by connecting two points of the current time position point and the next time position point of the enteromorpha prolifera particles.
Further, the life and elimination process forecasting module is specifically used for carrying out calculation and prediction according to the marine physical and ecological forecast data, the longitude and latitude information of the enteromorpha position, the life and elimination calculation parameters of the enteromorpha, the temperature, the illumination and the nutrient salt to obtain biomass forecast information in the life and elimination process of the enteromorpha of the yellow sea; the nutrient salts include at least phosphate, nitrate and silicate.
Further, the forecasting subsystem further comprises:
the second data information storage module is used for classifying and storing the drift path forecast information of the enteromorpha flavea particles and the biomass forecast information in the process of living and disappearing of the enteromorpha flavea; and storing the drift path forecast information and the biomass forecast information as txt document data of a plurality of time steps.
Further, the application subsystem includes:
the prediction data processing module is used for carrying out average processing on the drift path forecast information of the enteromorpha flavea particles and the biomass forecast information in the process of living and disappearing of the enteromorpha flavea according to preset time length to obtain a processing result; the data format of the processing result is converted into a netcdf format; further for storing said processing result in said netcdf format; the system is also used for processing the drift path forecast information of the enteromorpha prolifera particles and the biomass forecast information in the growth and death process of the enteromorpha prolifera to obtain the drift direction, the distribution area, the early warning at the shore arrival time and the biomass abundance information of the enteromorpha prolifera;
and the visual picture making module is used for visually making the drift path forecast information of the enteromorpha flavea particles, the biomass forecast information in the process of living and disappearing the enteromorpha flavea, the drift direction of the enteromorpha flavea, the distribution area, the shore arrival moment early warning and the biomass abundance information, and generating a yellow sea enteromorpha drift transport path forecast map and an enteromorpha biomass forecast map which at least comprise an urban base map and a coastline base map.
The second aspect of the embodiment of the application provides a method for forecasting the development trend of enteromorpha prolifera in yellow sea under the combined action of physical and ecological conditions, wherein the method comprises the following steps:
downloading external forced data and enteromorpha satellite remote sensing data;
performing data format conversion according to the external forcing data to obtain external forcing data in a netcdf format;
acquiring the longitude and latitude information of the position of the enteromorpha according to the enteromorpha satellite remote sensing data;
acquiring enteromorpha drifting calculation parameters under the action of multi-scale wind flow input by a user and enteromorpha growth and death calculation parameters under the action of a biochemical process;
performing space-time calculation prediction according to the external forced data, the enteromorpha position longitude and latitude information and the enteromorpha drift calculation parameters under the action of the multi-scale wind flow to obtain drift path prediction information of the enteromorpha prolifera particles in the yellow sea;
calculating and predicting according to the external forcing data, the longitude and latitude information of the enteromorpha position and the enteromorpha growth and death calculation parameters under the action of the biochemical process to obtain biomass forecast information in the living and disappearing process of the enteromorpha of the yellow sea;
processing the drift path forecast information of the enteromorpha prolifera particles and the biomass forecast information in the growth and death process of the enteromorpha prolifera to obtain the drift direction, the distribution area, the early warning at the shore arrival time and the biomass abundance information of the enteromorpha prolifera;
and visually displaying data such as drift path forecast information of the enteromorpha flavea particles, biomass forecast information in the process of living and disappearing of the enteromorpha flavea, the drift direction of the enteromorpha flavea, the distribution area, early warning at the shore arrival moment, the biomass abundance and the like.
In a third aspect of the embodiments of the present application, an electronic device is provided, which includes a memory and a processor, where the memory is used to store a computer program, and the processor runs the computer program to make the electronic device execute the method for forecasting the development trend of enteromorpha flavicana under the action of the physical and ecological federation described in the second aspect of the embodiments of the present application.
A fourth aspect of the embodiments of the present application provides a computer-readable storage medium, which stores computer program instructions, and when the computer program instructions are read and executed by a processor, the method for forecasting the development trend of enteromorpha prolifera in yellow sea under the combined action of physical and ecological features according to the second aspect of the embodiments of the present application is executed.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a system schematic diagram of a system and a method for forecasting the development trend of enteromorpha prolifera in yellow sea under the combined action of physics and ecology provided in the embodiment of the present application;
FIG. 2 is a schematic diagram of a system application of a data subsystem according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a system application of a forecasting subsystem according to an embodiment of the present application;
fig. 4 is a schematic flow chart of a system and a method for forecasting the development trend of enteromorpha prolifera in yellow sea under the combined action of physical and ecological aspects provided in the embodiments of the present application;
fig. 5 shows a drift path of an enteromorpha in one day and longitude and latitude information of an enteromorpha position thereof, which are predicted by an annual measure according to an embodiment of the present application;
fig. 6 is a diagram of enteromorpha biomass prediction of annual prediction of enteromorpha prolifera in yellow sea on different dates according to an embodiment of the present application;
fig. 7 is a pre-report form of annual prediction of biomass change trend of enteromorpha prolifera in yellow sea provided in the embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not construed as indicating or implying relative importance.
Example 1
Referring to fig. 1, fig. 1 is a system schematic diagram of a system for forecasting development trend of enteromorpha prolifera in yellow sea under combined action of physical and ecological factors in this embodiment. Wherein, the system for the drifting transportation and growth and death process of the enteromorpha prolifera in the yellow sea comprises a data subsystem 100, a forecast subsystem 200 and an application subsystem 300, wherein,
the data subsystem 100 is used for downloading external forced data and enteromorpha satellite remote sensing data;
the data subsystem 100 is further configured to perform data format conversion according to the external forcing data to obtain external forcing data in a netcdf format, and interpolate the external forcing data into a horizontal grid of the forecasting subsystem;
the data subsystem 100 is further used for acquiring longitude and latitude information of the enteromorpha position according to the enteromorpha satellite remote sensing data;
the forecasting subsystem 200 is used for acquiring external forced data, the longitude and latitude information of the enteromorpha position, enteromorpha drifting calculation parameters under the action of multi-scale wind flow input by a user and enteromorpha growth and death calculation parameters under the action of biochemical processes input by the user;
the forecasting subsystem 200 is further used for performing space-time calculation forecasting according to the external forced data, the longitude and latitude information of the enteromorpha position and the enteromorpha drift calculation parameters to obtain drift path forecasting information of the enteromorpha prolifera particles in the yellow sea;
the forecasting subsystem 200 is also used for carrying out calculation and prediction according to external forced data, the longitude and latitude information of the enteromorpha position and the enteromorpha growth and death calculation parameters under the action of a biochemical process to obtain biomass forecasting information in the growth and death process of the enteromorpha in the yellow sea;
and the application subsystem 300 is used for processing the drift path forecast information of the enteromorpha prolifera particles and the biomass forecast information in the growth and death process of the enteromorpha prolifera to obtain the drift direction, the distribution area and the early warning information of the enteromorpha prolifera in the yellow sea at the bank-butting moment and visually display the early warning information.
In this embodiment, the longitude and latitude information of the enteromorpha position is the longitude and latitude information of an enteromorpha envelope line.
As an alternative embodiment, data subsystem 100 includes:
the data control module 110 is used for controlling the operation of the data subsystem based on the shell script file; the log file downloading method comprises the steps of specifically calling different data downloading modules to carry out data downloading processing and outputting corresponding log files; the log file is used for displaying all processes of data downloading processing of the external forced data downloading module and the enteromorpha satellite remote sensing data downloading module and whether the processes are successful or not;
an external forcing data downloading module 120, configured to obtain and download external forcing data based on a web crawler; the external forcing data at least comprises short-term forecast field data of a global forecast system used in short-term forecast for 10 days in the future and long-term forecast field data of a climate forecast system used in long-term forecast for 9 months in the future;
a data format processing module 130, configured to convert data formats of the short-term prediction field data and the long-term prediction field data into a netcdf format based on a wgrib data processing method; the original data formats of the short-term forecast field data and the long-term forecast field data are grb2 formats;
a data interpolation module 140, configured to interpolate, based on a bilinear interpolation method, short-term prediction field data and long-term prediction field data in a netcdf format into a horizontal grid of the prediction subsystem 200;
the enteromorpha satellite remote sensing data downloading module 150 is used for acquiring and downloading enteromorpha satellite remote sensing data of American MODIS and Chinese HY water color series satellites based on web crawlers;
the enteromorpha satellite image information processing module 160 is used for processing various enteromorpha satellite remote sensing data based on a data fusion method; the method is also used for obtaining an enteromorpha satellite remote sensing picture based on a vegetation index inversion method; and the method is also used for acquiring the longitude and latitude information of the enteromorpha position based on a ginput picture dotting calculation method.
As an alternative embodiment, data subsystem 100 further includes:
the first data information storage module 170 is used for classifying and storing external forced data, short-term forecast field data, long-term forecast field data, netcdf format short-term forecast field data, netcdf format long-term forecast field data, enteromorpha satellite remote sensing data and enteromorpha position longitude and latitude information.
In this embodiment, the data subsystem system 100 is controlled to operate based on a shell script file, and meanwhile, the data subsystem system 100 may also archive and store different data. The data subsystem 100 can also output a manual interactive interface, so that the data subsystem can be conveniently used for customizing the history postreport of the enteromorpha prolifera or predicting the future. In addition, the data subsystem 100 may also call different data downloading modules to perform data downloading processing. Moreover, the data subsystem can also output a log file so that a user can check whether the data downloading is successful or not through the log file.
In this embodiment, the enteromorpha satellite image information processing module 160 may obtain an enteromorpha satellite remote sensing picture through a vegetation index inversion method, and then manually obtain enteromorpha envelope longitude and latitude information through a manual interactive interface based on a ginput picture dotting calculation method.
Referring to fig. 2, fig. 2 is a schematic diagram of a system application of a data subsystem according to an embodiment of the present application.
As an alternative embodiment, the forecasting subsystem 200 includes:
the forecast control module 210 is used for controlling the operation of the forecast subsystem based on the shell script file; the method is specifically used for acquiring longitude and latitude information of the position of the enteromorpha and acquiring short-term forecast field data in a netcdf format or long-term forecast field data in the netcdf format according to a forecast mode; the forecasting method is short-term forecasting or long-term forecasting;
the refined area circulation calculation module 220 is used for calculating forecast data based on the short-term forecast field data of the global forecast system in the future of 10 days or the long-term forecast field data of the climate forecast system in the future of 9 months; the marine physical and ecological forecast data at least comprises yellow sea circulation data, sea temperature data, nitrate data, phosphate data and silicate data, and the forecast data is used for forecasting drift transportation and growth loss of the enteromorpha prolifera;
the parameter input module 230 is used for acquiring enteromorpha drifting calculation parameters under the action of multi-scale wind flow input by a user and enteromorpha growth and death calculation parameters under the action of a biochemical process; the enteromorpha drift calculation parameters under the action of the multi-scale wind flow at least comprise a time step, total simulation days, a drift deflection angle, a wind speed compression coefficient, a flow velocity compression coefficient and a turbulence small-scale motion equation coefficient; the calculation parameters of enteromorpha growth and death under the action of the biochemical process at least comprise the maximum growth rate of enteromorpha, the death rate of enteromorpha, the optimal illumination intensity of enteromorpha and the nutrient salt half-saturation coefficient;
the drift transportation forecasting module 240 is used for performing space-time calculation and prediction according to short-term forecast field data or long-term forecast field data, marine physical and ecological forecast data, enteromorpha position longitude and latitude information and enteromorpha drift calculation parameters under the action of multi-scale wind flow by adopting a Lagrange method and a fourth-order solution method to obtain drift path forecast information of the enteromorpha particles in the yellow sea;
and the life-disappearing process forecasting module 250 is used for calculating and forecasting according to the marine physical and ecological forecast data, the longitude and latitude information of the enteromorpha position and the enteromorpha growth and death calculation parameters under the action of the biochemical process to obtain biomass forecast information in the yellow sea enteromorpha life-disappearing process.
As an optional implementation manner, the forecasting control module 210 is specifically further configured to determine whether the satellite monitors enteromorpha on the same day according to the longitude and latitude information of the position of the enteromorpha; if the enteromorpha is monitored on the same day, calling the longitude and latitude information data of the enteromorpha position for prediction; and if the enteromorpha is not monitored on the current day, calling the longitude and latitude information data of the enteromorpha position on the previous day for prediction.
As an optional implementation manner, the drifting transportation forecasting module 240 is further configured to determine whether the enteromorpha prolifera particles land on the shore based on a straight line formed by connecting two points of the current time position point and the next time position point of the enteromorpha prolifera particles according to a turbulent small-scale motion random process during drifting diffusion of the enteromorpha prolifera particles by using a coast line segment intersection method.
As an optional implementation manner, the life-saving process forecasting module 250 is specifically configured to calculate and predict according to forecast data, information of longitude and latitude of the position of enteromorpha, and enteromorpha growth and death calculation parameters, temperature, illumination and nutrient salt under the action of a biochemical process, so as to obtain biomass in the life-saving process of enteromorpha of yellow sea; the nutrient salts include at least phosphates, nitrates and silicates.
As an optional implementation, the forecasting subsystem 200 further includes:
the second data information storage module 260 is used for classifying and storing the drift path of the enteromorpha prolifera particles and the biomass in the process of living and disappearing the enteromorpha prolifera; wherein, the drift path and the biomass are stored as txt document data of a plurality of time steps.
In this embodiment, the lagrangian method is a lagrangian method.
In this embodiment, the fourth-order solver is a fourth-order solver (mille) method.
In this embodiment, the digestion process prediction module 250 calculates and predicts the digestion process of enteromorpha prolifera only by considering the temperature, illumination and the influence of nutritive salts (phosphate, nitrate and silicate) on the growth and death of enteromorpha prolifera.
Referring to fig. 3, fig. 3 is a schematic diagram of a system application of a forecasting subsystem according to an embodiment of the present application.
As an alternative embodiment, the application subsystem 300 includes:
the prediction data processing module 310 is used for carrying out average processing on the drift path prediction information of the enteromorpha flavea particles and the biomass prediction information in the process of living and disappearing of the enteromorpha flavea according to the preset time length to obtain a processing result; the data processing device is also used for converting the data format of the processing result into a netcdf format; also for storing the processing result in netcdf format; the system is also used for processing drift path forecast information of the enteromorpha prolifera particles and biomass forecast information in the growth and death process of the enteromorpha prolifera to obtain drift direction, distribution area, early warning at shore arrival time and biomass abundance information of the enteromorpha prolifera;
the visual picture making module 320 is used for making the drift path prediction information of the enteromorpha flavea particles, the biomass prediction information in the process of living and disappearing the enteromorpha flavea, the drift direction and the distribution area of the enteromorpha flavea, the early warning of the shore arrival moment and the biomass abundance information in a visual way, and generating a drift transport path prediction map and an enteromorpha biomass prediction map which at least comprise an urban base map and a coastline base map.
In this embodiment, the application subsystem 300 may perform average processing on these data on an hourly basis and an daily basis, and store the processed data as netcdf format data for storage and archiving.
Therefore, the system can acquire external forced data of the download model and satellite remote sensing enteromorpha and satellite tablet data in real time through a web crawler technology; by the method, the problem of poor forecasting timeliness in the prior art can be solved;
then, the system can judge whether short-term prediction or long-term prediction is carried out according to the current date; the problem of simplification of the prediction period in the prior art can be solved by the method;
then, the system can obtain high-resolution forecast data such as temperature, flow field and nutrient salt according to an autonomously established high-resolution three-dimensional temperature and salt flow coupled biogeochemical business forecast system; the method can solve the problem that the existing enteromorpha drifting and growth death model is low in driving forced resolution;
in addition, the system can obtain the enteromorpha occurrence position at the current moment according to the historical statistics of the initial position and time of enteromorpha outbreak or the satellite real-time data, and simulate the drift transportation path and the living and disappearing process of enteromorpha in the yellow sea; by means of the overlapped release judging module, the problem that the enteromorpha particles are not released continuously in the prior art is solved;
finally, the system can add a turbulent small-scale movement process and an enteromorpha growth and death process, and predicts the distribution area, the shore reaching time, the offshore distance, the shore climbing prediction and the biomass abundance, so that the drift transport and growth and death conditions of the enteromorpha in yellow sea can be more intuitively known by a visual product.
Example 2
Referring to fig. 4, fig. 4 is a schematic flow chart of the method for forecasting the development trend of enteromorpha prolifera under the combined action of physical and ecological features provided in this embodiment. As shown in fig. 4, the method for forecasting the drifting transportation and growth and death processes of enteromorpha prolifera comprises the following steps:
s401, downloading external forced data and enteromorpha satellite remote sensing data.
S402, carrying out data format conversion according to the external forcing data to obtain the external forcing data in a netcdf format.
And S403, acquiring the position longitude and latitude information of the enteromorpha according to enteromorpha satellite remote sensing fusion data obtained by fusing various enteromorpha satellite remote sensing data.
S404, acquiring enteromorpha drift calculation parameters under the action of multi-scale wind flow input by a user and enteromorpha growth and death calculation parameters under the action of a biochemical process.
S405, performing space-time calculation prediction according to the external forced data, the enteromorpha position longitude and latitude information and the enteromorpha drift calculation parameters under the action of multi-scale wind flow to obtain drift path prediction information of the enteromorpha prolifera particles in the yellow sea.
S406, calculating and predicting according to the external forcing data, the enteromorpha position longitude and latitude information and the enteromorpha growth and death calculation parameters under the action of the biochemical process to obtain biomass forecast information in the living and disappearing process of the enteromorpha in the yellow sea.
S407, processing the drift path forecast information of the enteromorpha prolifera particles and the biomass forecast information in the growth and death process of the enteromorpha prolifera to obtain early warning information of the drift direction, the distribution area and the shore arrival time of the enteromorpha prolifera.
S408, performing visual display on data such as drift path prediction information of the enteromorpha prolifera particles, biomass prediction information in the process of living and disappearing of the enteromorpha prolifera, drift direction, distribution area, early warning of shore arrival time, biomass abundance and the like.
In this embodiment, the execution subject of the method may be a computing device such as a computer and a server, and is not limited in this embodiment.
In this embodiment, an execution subject of the method may also be an intelligent device such as a smart phone and a tablet computer, which is not limited in this embodiment.
Referring to fig. 5, fig. 5 is a diagram illustrating an annual shift path of enteromorpha prolifera in yellow sea and longitude and latitude information of the enteromorpha prolifera position of the annual shift path.
Referring to fig. 6, fig. 6 is a diagram illustrating annual prediction of enteromorpha biomass at different dates for enteromorpha prolifera in yellow sea according to an embodiment of the present application.
Referring to fig. 7, fig. 7 is a pre-report of annual prediction of biomass variation trend of enteromorpha prolifera in yellow sea according to an embodiment of the present application.
In the embodiment of the application, for explanation of the method for forecasting the development trend of enteromorpha prolifera in yellow sea under the combined action of physical and ecological factors, reference may be made to the description in embodiment 1, and further description is not repeated in this embodiment.
Therefore, by implementing the method for forecasting the development trend of enteromorpha prolifera under the combined physical and ecological effect, the timeliness of the drift forecasting of enteromorpha prolifera can be improved, and the effect of real-time release and forecasting every day is realized; meanwhile, the forecasting system can realize long-term/annual forecasting of the enteromorpha in the yellow sea, can let the state/local government know the drift characteristics of the enteromorpha in the yellow sea of the next year, and implement a specific scheme to process the enteromorpha according to specific characteristics. In addition, the method increases a turbulent small-scale movement process in the drift diffusion process of the enteromorpha prolifera; in the yellow sea enteromorpha annual prediction process, the method increases the sustained release process of enteromorpha particles; in addition, the influence process of hydrological, meteorological, biological and chemical factors on the growth and death of the enteromorpha prolifera is considered, so that the effect of improving the prediction precision is realized.
The embodiment of the application provides electronic equipment, which comprises a memory and a processor, wherein the memory is used for storing a computer program, and the processor runs the computer program so as to enable the electronic equipment to execute the method for predicting the drifting transportation and growth and death processes of enteromorpha prolifera in embodiment 1 of the application.
The embodiment of the application provides a computer-readable storage medium, which stores computer program instructions, and when the computer program instructions are read and executed by a processor, the method for predicting the drifting transportation and growth and death processes of enteromorpha prolifera in embodiment 1 of the application is executed.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.
Claims (7)
1. A system for forecasting the development trend of Enteromorpha prolifera in yellow sea under the combined action of physics and ecology is characterized in that the forecasting system comprises a data subsystem, a forecasting subsystem and an application subsystem, wherein,
the data subsystem is used for downloading external forced data and enteromorpha satellite remote sensing data;
the data subsystem is further used for performing data format conversion according to the external forcing data to obtain external forcing data in a netcdf format, and interpolating the external forcing data into a horizontal grid of the forecasting subsystem;
the data subsystem is further used for acquiring longitude and latitude information of the enteromorpha position according to the enteromorpha satellite remote sensing data;
the forecasting subsystem is used for acquiring the external forced data, the longitude and latitude information of the enteromorpha position, enteromorpha drifting calculation parameters under the action of multi-scale wind flow input by a user and enteromorpha growth and death calculation parameters under the action of biochemical processes input by the user;
the forecasting subsystem is further used for carrying out space-time calculation and forecasting according to the external forced data, the longitude and latitude information of the enteromorpha position and the enteromorpha drift calculation parameters under the action of the multi-scale wind flow to obtain drift path forecasting information of the enteromorpha prolifera particles in the yellow sea;
the forecasting subsystem is further used for calculating and forecasting according to the external forcing data, the longitude and latitude information of the enteromorpha position and the enteromorpha growth and death calculation parameters under the action of the biochemical process to obtain biomass forecasting information in the yellow sea enteromorpha growth and death process;
the application subsystem is used for processing the drift path forecast information of the enteromorpha flavea particles and the biomass forecast information in the growth and death process of the enteromorpha flavea to obtain drift direction, distribution area, early warning at the shore arrival moment, biomass abundance information and visually displaying the information;
wherein the data subsystem comprises:
the data control module is used for controlling the operation of the data subsystem based on the shell script file; the log file downloading method comprises the steps of specifically calling different data downloading modules to carry out data downloading processing and outputting corresponding log files; the log file is used for displaying all processes of data downloading processing of the external forced data downloading module and the enteromorpha satellite remote sensing data downloading module and whether the processes are successful or not;
the external forcing data downloading module is used for acquiring and downloading external forcing data based on the web crawler; the external forcing data at least comprises short-term forecast field data of a global forecast system used in short-term forecast for 10 days in the future and long-term forecast field data of a climate forecast system used in long-term forecast for 9 months in the future;
the data format processing module is used for converting the data formats of the short-term forecast field data and the long-term forecast field data into a netcdf format based on a wgrib data processing method; the original data format of the short-term forecast field data and the long-term forecast field data is grb2 format;
the data interpolation module is used for interpolating the short-term forecast field data and the long-term forecast field data in a netcdf format into a horizontal grid of the forecast branch system based on a bilinear interpolation method;
the enteromorpha satellite remote sensing data downloading module is used for acquiring and downloading enteromorpha satellite remote sensing data of MODIS and HY water color series satellites based on web crawlers;
the enteromorpha satellite image information processing module is used for processing various enteromorpha satellite remote sensing data based on a data fusion method; the method is also used for obtaining an enteromorpha satellite remote sensing picture based on a vegetation index inversion method; the system is also used for obtaining the longitude and latitude information of the enteromorpha position based on a ginput picture dotting calculation method;
the data subsystem further includes:
the first data information storage module is used for classifying and storing the external forcing data, the short-term forecast field data in the netcdf format, the long-term forecast field data in the netcdf format, the short-term forecast field data in the grb2 format, the long-term forecast field data in the grb2 format, the enteromorpha satellite remote sensing data and the enteromorpha position longitude and latitude information;
wherein, the forecast branch system includes:
the forecast control module is used for controlling the operation of the forecast subsystem based on the shell script file; the system is specifically used for acquiring longitude and latitude information of the enteromorpha position and acquiring the short-term forecast field data in the netcdf format or the long-term forecast field data in the netcdf format according to a forecast mode; the forecasting mode is short-term forecasting or long-term forecasting;
the refined area circulation calculation module is used for calculating marine physical and ecological forecast data based on the short-term forecast field data or the long-term forecast field data; the marine physical ecology forecast data at least comprises yellow sea marine circulation data, sea temperature data, nitrate data, phosphate data and silicate data; the marine physical and ecological forecast data is used for forecasting drifting transportation and growth and death of enteromorpha prolifera;
the parameter input module is used for acquiring enteromorpha drifting calculation parameters under the action of multi-scale wind flow input by a user and enteromorpha growth and death calculation parameters under the action of a biochemical process; the enteromorpha drift calculation parameters at least comprise a time step length, total simulation days, a drift deflection angle, a wind speed compression coefficient, a flow velocity compression coefficient and a turbulent flow small-scale motion equation coefficient; the enteromorpha growth death calculation parameters under the action of the biochemical process at least comprise the maximum enteromorpha growth rate, the enteromorpha death rate, the optimal enteromorpha illumination intensity and the nutrient salt half-saturation rate;
the drift transport prediction module is used for performing space-time calculation prediction according to turbulent small-scale motion data, the short-term prediction field data or the long-term prediction field data, the marine physical and ecological prediction data, the enteromorpha position longitude and latitude information and the enteromorpha drift calculation parameters under the action of the multi-scale wind flow by adopting a Lagrange method and a fourth-order solution to obtain drift path prediction information of the enteromorpha particles in the yellow sea;
and the life-disappearing process forecasting module is used for calculating and forecasting according to the marine physical and ecological forecast data, the longitude and latitude information of the enteromorpha position and the enteromorpha growth and death calculation parameters under the biochemical action to obtain biomass forecast information in the life-disappearing process of the enteromorpha in the yellow sea.
2. The system for forecasting the development trend of enteromorpha prolifera in yellow sea under the combined physical and ecological effect according to claim 1, wherein the forecasting control module is further specifically configured to judge whether the satellite monitors enteromorpha prolifera in the same day according to the longitude and latitude information of the position of enteromorpha prolifera; if the enteromorpha is monitored on the same day, calling the longitude and latitude information data of the enteromorpha position for prediction; and if the enteromorpha is not monitored on the current day, calling the longitude and latitude information data of the enteromorpha position on the previous day for prediction.
3. The system for forecasting the development trend of enteromorpha prolifera in yellow sea under the combined physical and ecological effect according to claim 1, wherein the drift transportation forecasting module is further used for judging whether the enteromorpha prolifera particles land on the shore or not by adopting a coast line segment intersection method according to a random process of turbulent small-scale motion during drift diffusion of the enteromorpha prolifera particles and a straight line formed by connecting two points of a current time position point and a next time position point of the enteromorpha prolifera particles.
4. The system for forecasting the development trend of enteromorpha prolifera in yellow sea under the combined physical and ecological effect according to claim 1, wherein the digestion process forecasting module is specifically used for carrying out calculation and prediction according to the forecast data, the longitude and latitude information of the position of enteromorpha prolifera, the digestion calculation parameters, temperature, illumination and nutrient salt of enteromorpha prolifera to obtain biomass forecast information in the digestion process of enteromorpha prolifera in yellow sea; the nutrient salts include at least phosphates, nitrates and silicates.
5. The system for forecasting the development trend of Enteromorpha prolifera under the combined action of physics and ecology according to claim 1, wherein the forecasting subsystem further comprises:
the second data information storage module is used for classifying and storing the drift path forecast information of the enteromorpha flavea particles and the biomass forecast information in the process of living and disappearing of the enteromorpha flavea; and storing the drift path forecast information and the biomass forecast information as txt document data of a plurality of time steps.
6. The system for forecasting the development trend of Enteromorpha prolifera under the combined action of physical and ecology according to claim 1, wherein the application subsystem comprises:
the prediction data processing module is used for carrying out average processing on the drift path forecast information of the enteromorpha flavea particles and the biomass forecast information in the process of living and disappearing of the enteromorpha flavea according to preset time length to obtain a processing result; the data format of the processing result is converted into a netcdf format; further for storing the processing result in the netcdf format; the system is also used for processing the drift path forecast information of the enteromorpha prolifera particles and the biomass forecast information in the growth and death process of the enteromorpha prolifera to obtain the drift direction, the distribution area, the early warning at the shore arrival time and the biomass abundance information of the enteromorpha prolifera;
and the visual picture making module is used for visually making the drift path forecast information of the enteromorpha flavea particles, the biomass forecast information in the process of living and disappearing of the enteromorpha flavea, the drift direction of the enteromorpha flavea, the distribution area and the shore arrival moment early warning information and generating a drift transport path forecast map and an enteromorpha biomass forecast map at least comprising an urban base map and a coastline base map.
7. A method for forecasting the development trend of Enteromorpha prolifera in yellow sea under the combined action of physics and ecology is characterized by comprising the following steps:
downloading external forced data and enteromorpha satellite remote sensing data;
performing data format conversion according to the external forcing data to obtain external forcing data in a netcdf format, and interpolating the external forcing data into a horizontal grid of a forecasting subsystem;
acquiring the longitude and latitude information of the position of the enteromorpha according to the enteromorpha satellite remote sensing data;
acquiring enteromorpha drifting calculation parameters under the action of multi-scale wind flow input by a user and enteromorpha growth and death calculation parameters under the action of a biochemical process;
performing space-time calculation prediction according to the external forced data, the enteromorpha position longitude and latitude information and the enteromorpha drift calculation parameters under the action of the multi-scale wind flow to obtain drift path prediction information of the enteromorpha prolifera particles in the yellow sea;
calculating and predicting according to the external forcing data, the enteromorpha position longitude and latitude information and enteromorpha growth and death calculation parameters under the action of the biochemical process to obtain biomass forecast information in the living and consumption process of enteromorpha in the yellow sea;
processing the drift path forecast information of the enteromorpha prolifera particles and the biomass forecast information in the growth and death process of the enteromorpha prolifera to obtain the drift direction, the distribution area, the early warning at the shore arrival time and the biomass abundance information of the enteromorpha prolifera;
carrying out visual display on the drift path forecast information of the enteromorpha flavea particles, the biomass forecast information in the life and consumption process of the enteromorpha flavea, the drift direction of the enteromorpha flavea, the distribution area, the early warning at the shore arrival moment and the biomass abundance;
the step of obtaining the longitude and latitude information of the position of the enteromorpha according to the enteromorpha satellite remote sensing data comprises the following steps:
controlling the operation of a data subsystem based on the shell script file; the log file downloading method comprises the steps of specifically calling different data downloading modules to carry out data downloading processing and outputting corresponding log files; the log file is used for displaying all processes of data downloading processing of the external forced data downloading module and the enteromorpha satellite remote sensing data downloading module and whether the processes are successful or not;
acquiring and downloading external forcing data based on the web crawler; the external forcing data at least comprise short-term forecast field data of a global forecast system used in short-term forecast for 10 days in the future and long-term forecast field data of a climate forecast system used in long-term forecast for 9 months in the future;
converting the data formats of the short-term forecast field data and the long-term forecast field data into a netcdf format based on a wgrib data processing method; the original data format of the short-term forecast field data and the long-term forecast field data is grb2 format;
interpolating the short-term forecast field data and the long-term forecast field data in netcdf format into a horizontal grid of the forecast sub-system based on a bilinear interpolation method;
acquiring and downloading enteromorpha satellite remote sensing data of MODIS and HY water color series satellites based on web crawlers;
processing various enteromorpha satellite remote sensing data based on a data fusion method; acquiring an enteromorpha satellite remote sensing picture based on a vegetation index inversion method; obtaining the longitude and latitude information of the enteromorpha position based on a ginput picture dotting calculation method;
the step of obtaining the longitude and latitude information of the position of the enteromorpha according to the enteromorpha satellite remote sensing data further comprises the following steps:
classifying and storing the external forcing data, the short-term forecast field data in the netcdf format, the long-term forecast field data in the netcdf format, the short-term forecast field data in the grb2 format, the long-term forecast field data in the grb2 format, the enteromorpha satellite remote sensing data and the enteromorpha position longitude and latitude information;
wherein, the step of converting the data format according to the external forcing data to obtain the external forcing data in the netcdf format comprises the following steps:
the forecast subsystem is used for controlling the operation of the forecast subsystem based on the shell script file; the system is specifically used for acquiring longitude and latitude information of the enteromorpha position and acquiring the short-term forecast field data in the netcdf format or the long-term forecast field data in the netcdf format according to a forecast mode; the forecasting mode is short-term forecasting or long-term forecasting;
the step of obtaining enteromorpha drifting calculation parameters under the action of multi-scale wind flow input by a user and enteromorpha growth and death calculation parameters under the action of a biochemical process comprises the following steps:
acquiring enteromorpha drift calculation parameters input by a user under the action of multi-scale wind flow and enteromorpha growth and death calculation parameters under the action of biochemical process; the enteromorpha drift calculation parameters at least comprise a time step length, total simulation days, a drift deflection angle, a wind speed compression coefficient, a flow speed compression coefficient and a turbulent flow small-scale motion equation coefficient; the enteromorpha growth death calculation parameters under the action of the biochemical process at least comprise the maximum enteromorpha growth rate, the enteromorpha death rate, the optimal enteromorpha illumination intensity and the nutrient salt half-saturation rate;
the step of performing space-time calculation prediction according to the external forced data, the enteromorpha position longitude and latitude information and the enteromorpha drift calculation parameters under the action of the multi-scale wind flow to obtain drift path prediction information of the enteromorpha prolifera particles in the yellow sea comprises the following steps:
performing space-time calculation prediction according to small-scale turbulent motion data, short-term forecast field data or long-term forecast field data, marine physical and ecological forecast data, enteromorpha position longitude and latitude information and enteromorpha drift calculation parameters under the action of the multi-scale wind flow by adopting a Lagrange method and a fourth-order solution method to obtain drift path forecast information of the enteromorpha particles in the yellow sea;
the step of carrying out calculation prediction according to the external forcing data, the enteromorpha position longitude and latitude information and the enteromorpha growth and death calculation parameters under the action of the biochemical process to obtain biomass forecast information in the living and consumption process of enteromorpha in yellow sea comprises the following steps:
and calculating and predicting according to the marine physical and ecological forecast data, the longitude and latitude information of the enteromorpha position and the enteromorpha growth and death calculation parameters under the biochemical action to obtain biomass forecast information in the living and digestion processes of the enteromorpha in the yellow sea.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210066677.XA CN114417613B (en) | 2022-01-20 | 2022-01-20 | System and method for forecasting development trend of enteromorpha prolifera in yellow sea under combined action of physics and ecology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210066677.XA CN114417613B (en) | 2022-01-20 | 2022-01-20 | System and method for forecasting development trend of enteromorpha prolifera in yellow sea under combined action of physics and ecology |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114417613A CN114417613A (en) | 2022-04-29 |
| CN114417613B true CN114417613B (en) | 2023-03-24 |
Family
ID=81275669
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210066677.XA Active CN114417613B (en) | 2022-01-20 | 2022-01-20 | System and method for forecasting development trend of enteromorpha prolifera in yellow sea under combined action of physics and ecology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114417613B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116467565B (en) * | 2023-06-20 | 2023-09-22 | 国家海洋局北海预报中心((国家海洋局青岛海洋预报台)(国家海洋局青岛海洋环境监测中心站)) | Enteromorpha green tide plaque optimal search area forecasting method |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112712553A (en) * | 2020-12-30 | 2021-04-27 | 自然资源部第一海洋研究所 | Enteromorpha shore resistance amount estimation method |
| CN113033865A (en) * | 2021-01-29 | 2021-06-25 | 南方海洋科学与工程广东省实验室(广州) | Ecological safety early warning system |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090228516A1 (en) * | 2008-03-10 | 2009-09-10 | The Hong Kong Polytechnic University | Harmful algae indexing (HaiDex) method |
| KR101421197B1 (en) * | 2013-05-15 | 2014-08-13 | 김혜봉 | Method and apparatus for forecasting generation of green tide and red tide based on yellow sand phenomenon |
| KR101774871B1 (en) * | 2015-02-05 | 2017-09-05 | (주)유엔이 | System and method for prediction of environmental pollution |
| CN108253943B (en) * | 2017-12-24 | 2020-08-21 | 航天恒星科技有限公司 | Integrated monitoring method for enteromorpha in red tide based on satellite remote sensing image |
| CN109326086A (en) * | 2018-10-16 | 2019-02-12 | 天津科技大学 | A kind of green tide disaster early warning system and its application method based on ecological model |
| CN112465186B (en) * | 2020-10-28 | 2022-04-01 | 山东省科学院海洋仪器仪表研究所 | Method for predicting death days of sea surface floating enteromorpha prolifera |
-
2022
- 2022-01-20 CN CN202210066677.XA patent/CN114417613B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112712553A (en) * | 2020-12-30 | 2021-04-27 | 自然资源部第一海洋研究所 | Enteromorpha shore resistance amount estimation method |
| CN113033865A (en) * | 2021-01-29 | 2021-06-25 | 南方海洋科学与工程广东省实验室(广州) | Ecological safety early warning system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114417613A (en) | 2022-04-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Dresback et al. | Skill assessment of a real-time forecast system utilizing a coupled hydrologic and coastal hydrodynamic model during Hurricane Irene (2011) | |
| JP5433913B2 (en) | Wave prediction system | |
| CN112949178A (en) | Sea surface wind field wind speed intelligent prediction forecasting system based on deep learning, computer equipment and storage medium | |
| CN114417613B (en) | System and method for forecasting development trend of enteromorpha prolifera in yellow sea under combined action of physics and ecology | |
| Qin et al. | Development of a GIS-based integrated framework for coastal seiches monitoring and forecasting: A North Jiangsu shoal case study | |
| Franz et al. | Coastal ocean observing and modeling systems in Brazil: initiatives and future perspectives | |
| Mayerle et al. | Development of a coastal information system for the management of Jeddah coastal waters in Saudi Arabia | |
| CN111985087A (en) | Ocean circulation simulation system and method based on big data | |
| CN116522648A (en) | Lake algae state prediction method and application | |
| Song et al. | Correlation analysis method for ocean monitoring big data in a cloud environment | |
| Georgas et al. | Marine forecasting for the New york urban waters and harbor approaches: the design and automation of NYHOPS | |
| Kim et al. | San Francisco Bay integrated flood forecasting project summary report | |
| Selvam et al. | The Impact of IoT and Sensor Integration on Real-Time Weather Monitoring Systems: A Systematic Review | |
| Simoncelli et al. | A collaborative framework among data producers, managers, and users | |
| CN117708226A (en) | Method, device, equipment and storage medium for visualizing storm surge along coastal river | |
| Becker et al. | Guidance note on the application of coastal monitoring for small island developing states: Part of the NOC-led project “Climate Change Impact Assessment: Ocean Modelling and Monitoring for the Caribbean CME states”, 2017-2020; under the Commonwealth Marine Economies (CME) Programme in the Caribbean. | |
| Frydel | Numerical model of late Pleistocene and Holocene ice-sheet and shoreline dynamics in the southern Baltic Sea, Poland | |
| Thompson et al. | A Near Real-Time Dashboard for the Flower Garden Banks National Marine Sanctuary Ocean Conditions | |
| Resio et al. | Next generation numerical models to address a complex future | |
| Pérez Gómez et al. | Final report describing the demonstration and the user feedback at European sites | |
| Rao et al. | Ocean data and information system (ODIS) and web-based services | |
| チョーテイツー ウー | Wave prediction by means of two distinct approaches: Numerical modelling and deep-learning | |
| Crosman et al. | John Horel | |
| DeVoe et al. | Regional Coastal IOOS development in the Southeastern United States: Emerging capabilities to address coastal natural hazards | |
| Kumar et al. | Iot Based Weather Monitoring System Using Nodemcu and Blynk |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |