Coral reef bleaching early warning method and system based on bottom seawater temperature

Abstract

The present invention provides a coral reef bleaching early warning method and system based on bottom seawater temperature, comprising: obtaining coral reef bleaching early warning data, the coral reef bleaching early warning data including layered seawater temperature data and water depth data of each grid; reclassifying the water depth data of each grid so that the water depth data of each grid corresponds to a predefined band; calculating daily bottom seawater temperature data based on the water depth data of each grid corresponding to the predefined band; calculating the highest monthly average water temperature of the bottom layer over many years based on the reclassified water depth data; calculating bleaching hotspots based on the daily bottom seawater temperature data and the highest monthly average water temperature of the bottom layer over many years; calculating weekly heat based on the bleaching hotspots; and performing bleaching early warning classification on the coral reefs based on the bleaching hotspots and the weekly heat to obtain a classification result. The method can quickly and accurately predict coral reef bleaching, improve the accuracy of coral reef bleaching early warning, realize daily updating of bleaching products, and lower the technical threshold.

Description

Technical Field

[0001] The present invention relates to the field of marine ecological environment technology, and in particular to a coral reef bleaching early warning method and system based on bottom seawater temperature. Background Art

[0002] Due to climate change, coral bleaching is becoming increasingly frequent and severe worldwide. Causes of coral bleaching include abnormal sea temperatures, ultraviolet radiation, storms, pollution, and bacterial or viral infections. However, the primary cause of large-scale coral bleaching is prolonged, abnormally high sea temperatures. Therefore, using sea temperature as an early warning indicator for coral bleaching has become a widely accepted practice both domestically and internationally.

[0003] Currently, domestic and foreign government agencies, scientific research institutions, etc. have carried out a lot of work in the investigation of the current status of coral reef bleaching and early warning, and have also issued a number of standards and normative documents related to coral reef early warning. Through the collection and analysis of domestic and foreign technical documents, the following problems exist:

[0004] First, the threshold setting of the evaluation indicators is not yet able to accurately warn of coral reef bleaching conditions, and the accuracy of the bleaching thermal stress monitoring index of the National Oceanic and Atmospheric Administration (NOAA) in actual application is poor.

[0005] Second, coral reef warnings carried out at home and abroad mostly use surface seawater temperature to predict coral reef bleaching or fixed deep water temperature. However, coral reefs are distributed in the bottom seawater. Monitoring and survey data show that my country's coral reefs are distributed in areas with a water depth of 7 to 40 meters. In the coral reef distribution area, the temperature difference between the surface seawater and the bottom seawater is between 0 and 8.5°C, and there are large differences in the surface and bottom temperature differences in different seasons. Studies have shown that when the ambient water temperature is 1 to 2°C higher than the average temperature of the highest month, coral bleaching may occur. Summary of the Invention

[0006] In view of this, the purpose of the present invention is to provide a coral reef bleaching early warning method and system based on bottom seawater temperature, which can quickly and accurately predict coral reef bleaching, improve the accuracy of coral reef bleaching early warning, realize daily updating of bleaching products, and lower the technical threshold.

[0007] In a first aspect, an embodiment of the present invention provides a coral reef bleaching early warning method based on bottom seawater temperature, the method comprising:

[0008] Acquiring coral reef bleaching early warning data, the coral reef bleaching early warning data including layered seawater temperature data and water depth data for each grid;

[0009] Reclassifying the water depth data of each grid so that the water depth data of each grid corresponds to a predefined band;

[0010] Calculate daily bottom seawater temperature data based on the water depth data of each grid corresponding to a predefined band;

[0011] Calculate the multi-year maximum monthly mean bottom water temperature based on the reclassified bathymetric data;

[0012] Calculating bleaching hotspots based on the daily bottom seawater temperature data and the multi-year maximum monthly average bottom seawater temperature;

[0013] Calculating weekly heat according to the whitening hotspot;

[0014] Bleaching warning classification is performed on the coral reef according to the bleaching hotspot and the weekly heat to obtain a classification result.

[0015] Furthermore, the water depth data of each grid is reclassified so that the water depth data of each grid corresponds to a predefined band, including:

[0016] Determining the corresponding relationship between the layered water depth and the wave band according to the layered seawater temperature data;

[0017] Based on the correspondence between the layered water depths and the bands, a classification tool is used to reclassify the water depth data of each grid into the predefined bands.

[0018] Furthermore, the daily bottom seawater temperature data is calculated based on the water depth data of each grid corresponding to the predefined band, including:

[0019] Extracting specific water temperature data from the daily water temperature data in different bands according to the predefined bands corresponding to the water depth data of each grid;

[0020] The specific water temperature data is used as the daily bottom seawater temperature data.

[0021] Furthermore, the multi-year maximum monthly mean bottom water temperature is calculated based on the reclassified water depth data, including:

[0022] The multi-year monthly average bottom water temperature from January to December was calculated based on the reclassified water depth data;

[0023] After comparing the multi-year monthly average bottom water temperatures from January to December, the highest monthly average water temperature in each grid is extracted;

[0024] The multi-year maximum monthly average water temperature of the bottom layer is obtained based on the maximum monthly average water temperature in each grid.

[0025] Furthermore, the bleaching hotspots are calculated based on the daily bottom seawater temperature data and the multi-year maximum monthly average bottom seawater temperature, including:

[0026] The whitening hotspot is calculated according to the following formula:

[0027]

[0028] Among them, T hotspoti is the bleaching hotspot for each day, T st is the daily bottom sea temperature data, T mmm It is the highest monthly average water temperature of the bottom layer over many years.

[0029] Furthermore, calculating the weekly heat according to the whitening hotspot includes:

[0030] The weekly popularity is calculated according to the following formula:

[0031]

[0032] Among them, H DHW is the weekly heat, These are the latest 84-day bleaching hotspots.

[0033] Furthermore, the coral reef is graded for bleaching warning according to the bleaching hotspot and the weekly heat, and a grading result is obtained, including:

[0034] When the whitening hotspot is less than or equal to 0, the warning level is level 0, the risk level is no risk, and the classification result is no whitening risk;

[0035] When the whitening hotspot is greater than 0 and less than the first threshold, the warning level is level 1, the risk level is whitening observation, and the classification result is no whitening risk, but observation is required;

[0036] When the whitening hotspot is greater than or equal to the first threshold, and the weekly heat is greater than 0 and less than or equal to the second threshold, the warning level is level 2, the risk level is whitening warning, and the classification result is that there is a whitening risk;

[0037] When the bleaching hotspot is greater than or equal to the first threshold, and the weekly heat is greater than the third threshold and less than or equal to the fourth threshold, the warning level is level 3, the risk level is level 1 alert, and the classification result is that coral reef bleaching may occur;

[0038] When the bleaching hotspot is greater than or equal to the fifth threshold, and the weekly heat is greater than the fourth threshold, the warning level is level 4, the risk level is level 2 alert, and the classification result is large-scale bleaching and the death of coral reefs;

[0039] The first threshold is smaller than the second threshold, the second threshold is smaller than the third threshold, the third threshold is smaller than the fourth threshold, and the fifth threshold is larger than the first threshold and smaller than the second threshold.

[0040] In a second aspect, an embodiment of the present invention provides a coral reef bleaching early warning system based on bottom seawater temperature, the system comprising:

[0041] An acquisition module is used to acquire coral reef bleaching early warning data, wherein the coral reef bleaching early warning data includes layered seawater temperature data and water depth data of each grid;

[0042] A classification module, configured to reclassify the water depth data of each grid so that the water depth data of each grid corresponds to a predefined band;

[0043] A bottom seawater temperature data calculation module is used to calculate daily bottom seawater temperature data based on the water depth data of each grid corresponding to a predefined band;

[0044] The maximum monthly average water temperature calculation module is used to calculate the multi-year maximum monthly average water temperature of the bottom layer based on the reclassified water depth data;

[0045] a bleaching hotspot calculation module, configured to calculate bleaching hotspots based on the daily bottom seawater temperature data and the multi-year maximum monthly average water temperature of the bottom seawater;

[0046] A weekly heat calculation module, used to calculate the weekly heat according to the whitened hot spots;

[0047] An early warning classification module is used to perform bleaching early warning classification on the coral reef according to the bleaching hotspot and the weekly heat to obtain a classification result.

[0048] In a third aspect, an embodiment of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and the processor implements the above-mentioned method when executing the computer program.

[0049] In a fourth aspect, an embodiment of the present invention provides a computer-readable medium having a non-volatile program code executable by a processor, wherein the program code enables the processor to execute the method described above.

[0050] An embodiment of the present invention provides a coral reef bleaching early warning method and system based on bottom seawater temperature, comprising: obtaining coral reef bleaching early warning data, the coral reef bleaching early warning data including layered seawater temperature data and water depth data of each grid; reclassifying the water depth data of each grid so that the water depth data of each grid corresponds to a predefined band; calculating daily bottom seawater temperature data based on the water depth data of each grid corresponding to the predefined band; calculating the multi-year maximum monthly average bottom water temperature based on the reclassified water depth data; calculating bleaching hotspots based on the daily bottom seawater temperature data and the multi-year maximum monthly average bottom water temperature; calculating weekly heat based on the bleaching hotspots; and grading coral reef bleaching early warnings based on the bleaching hotspots and weekly heat to obtain grading results. The method can quickly and accurately predict coral reef bleaching, improve the accuracy of coral reef bleaching early warnings, achieve daily updates of bleaching products, and lower technical barriers.

[0051] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0052] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0054] Figure 1 A flow chart of a coral reef bleaching early warning method based on bottom seawater temperature provided in Example 1 of the present invention;

[0055] Figure 2 This is a logic diagram of bottom seawater temperature calculation provided by the first embodiment of the present invention;

[0056] Figure 3 A schematic diagram of superimposing the coral reef status survey data and the early warning results provided in Example 1 of the present invention;

[0057] Figure 4 Schematic diagram of a coral reef bleaching early warning system based on bottom seawater temperature provided in Example 2 of the present invention. DETAILED DESCRIPTION

[0058] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0059] To facilitate understanding of this embodiment, the embodiment of the present invention is described in detail below.

[0060] Example 1:

[0061] Figure 1 This is a flow chart of the coral reef bleaching early warning method based on bottom seawater temperature provided in Example 1 of the present invention.

[0062] Reference Figure 1 , the method comprises the following steps:

[0063] Step S101, obtaining coral reef bleaching early warning data, the coral reef bleaching early warning data including layered seawater temperature data and water depth data of each grid;

[0064] Specifically, coral reef bleaching warning data is obtained using seawater temperature data from the Global High-Resolution Coupled Ice-Ocean Reanalysis (CORA 2.0) and Etopo depth data from the China Marine Information Network. CORA 2.0 has a horizontal grid resolution of 1 / 12° and a vertical stratification range of 0-5500m, with daily updates. Etopo is terrain elevation data with a resolution of 1′.

[0065] Step S102, reclassifying the water depth data of each grid so that the water depth data of each grid corresponds to a predefined band;

[0066] Step S103, calculating daily bottom seawater temperature data based on the water depth data of each grid corresponding to the predefined band;

[0067] Specifically, CORA 2.0 provides stratified seawater temperature data, recording water temperatures at different depths daily. Depth data selection uses the mapping between depth and bands in CORA 2.0 to reclassify the depth data for each grid, assigning each grid to a specific band. Based on the band assigned to each grid, specific water temperature data is extracted from the daily band-specific water temperature data. This extracted specific water temperature data represents the daily bottom seawater temperature data, reflecting the temperature fluctuations at a specific depth within that band.

[0068] Step S104, calculating the multi-year maximum monthly average water temperature of the bottom layer based on the reclassified water depth data;

[0069] Step S105, calculating bleaching hotspots based on daily bottom seawater temperature data and the multi-year maximum monthly average bottom seawater temperature;

[0070] Specifically, the bleaching hotspot is the difference between the daily bottom seawater temperature data and the highest monthly average water temperature of the bottom over many years. It describes the extent to which the seawater temperature in a specific area is higher than the hottest monthly temperature in the area over a long period of time, and is used to assess the degree of heat stress on corals at a certain point in time.

[0071] Step S106, calculating weekly heat according to the whitened hot spots;

[0072] Specifically, coral bleaching is caused by long-term heat stress caused by seawater temperature. Coral reef bleaching hotspots can only measure the heat stress suffered by corals on a certain day and cannot show the long-term cumulative effects of heat stress. Practice has shown that corals are very sensitive to long-term and continuous accumulation of heat stress.

[0073] Weekly heat index reflects the cumulative extent of coral bleaching hotspots in a specific area over the past 12 weeks (84 days), and is used to assess the sustained impact of heat stress on coral bleaching over a specific period of time. Related research results show that when bleaching hotspots are below 1°C, they are insufficient to cause significant heat stress to corals; accumulation only occurs when bleaching hotspots are greater than or equal to 1°C.

[0074] Step S107: performing bleaching warning classification on the coral reefs according to the bleaching hot spots and the weekly heat, and obtaining a classification result.

[0075] Furthermore, step S102 includes the following steps:

[0076] Step S201, determining the correspondence between the layered water depth and the wave band according to the layered seawater temperature data;

[0077] Step S202 : Based on the correspondence between the layered water depth and the band, a classification tool is used to reclassify the water depth data of each grid into a predefined band.

[0078] Specifically, the correspondence between the stratified water depth and the band is determined based on the stratified seawater temperature data (CORA 2.0 data), see Table 1.

[0079] Table 1

[0080] Band Water depth (m) Band Water depth (m) Band Water depth (m) Band Water depth (m) 1 -5 14 -140 26 -722 38 -2276 2 -15 15 -154 27 -814 39 -2491 3 -25 16 -172 28 -910 40 -2729 4 -35 17 -195 29 -1007 41 -2990 5 -45 18 -223 30 -1106 42 -3274 6 -55 19 -257 31 -1306 43 -3581 7 -65 20 -300 32 -1409 44 -3911 8 -75 21 -351 33 -1517 45 -4264 9 -85 22 -410 34 -1634 46 -4640 10 -95 23 -477 35 -1765 47 -5039 11 -105 24 -553 36 -1914 48 -5461 12 -116 25 -635 37 -2084 49 -5906 13 -127

[0081] Reclassification: Use a classification tool to reclassify the water depth data for each grid into predefined bands. This step is similar to mapping continuous values ​​(such as specific water depth values) to discrete categories (band ranges). The classification tool can be a GIS or a programming tool (such as the pandas or rasterio libraries in Python).

[0082] Output: Each grid cell now has a clear band label representing the temperature layer corresponding to its water depth.

[0083] Furthermore, step S103 includes the following steps:

[0084] Step S301, extracting specific water temperature data from the daily water temperature data in different bands according to the predefined bands corresponding to the water depth data of each grid;

[0085] Step S302: Using the specific water temperature data as daily bottom seawater temperature data.

[0086] Specifically, in the CORA 2.0 data file, the water temperature of each band is recorded as a different layer every day. Based on the predefined band corresponding to the water depth data of each grid, the water temperature data of the corresponding band is found.

[0087] Extract and match water temperature: Use matching tools (such as SQL, Python's numpy, pandas, or the extraction function in GIS tools) to extract the water temperature values ​​of the band belonging to a specific grid from the daily water temperature file.

[0088] The specific water temperature data extracted is the daily bottom sea temperature data, which can reflect the changes in sea water temperature at a specific water depth in this band.

[0089] Reference Figure 2 , determine the predefined bands corresponding to the water depth data of each grid, such as band 1, band 2 and band 3; extract the corresponding water temperature data according to band 1; extract the corresponding water temperature data according to band 2; extract the corresponding water temperature data according to band 3; obtain the bottom seawater temperature data based on the water temperature data corresponding to band 1, the water temperature data corresponding to band 2 and the water temperature data corresponding to band 3.

[0090] Furthermore, step S104 includes the following steps:

[0091] Step S401, calculating the multi-year monthly average bottom water temperature from January to December based on the reclassified water depth data;

[0092] Step S402, after comparing the multi-year monthly average bottom water temperatures from January to December, extract the highest monthly average water temperature in each grid;

[0093] Step S403: Obtain the multi-year maximum monthly average water temperature of the bottom layer based on the maximum monthly average water temperature in each grid.

[0094] Specifically, the multi-year monthly average product of CARA2.0 was used to calculate the multi-year monthly average three-dimensional temperature from January to December. The reclassified water depth data was used to calculate the multi-year monthly average bottom water temperature from January to December month by month. The multi-year monthly average bottom water temperatures of 12 months were compared, and the highest monthly average water temperature in each grid was extracted to form the multi-year maximum monthly average bottom water temperature.

[0095] Furthermore, step S105 includes:

[0096] Calculate the whitening hotspot according to formula (1):

[0097]

[0098] Among them, T hotspoti For each day's bleaching hotspot, T st is the daily bottom sea temperature data, T mmm This is the highest monthly average water temperature at the bottom layer over the years.

[0099] Furthermore, step S106 includes:

[0100] Calculate weekly popularity according to formula (2):

[0101]

[0102] Among them, H DHW For weekly popularity, It is the latest 84-day bleaching hotspot.

[0103] Furthermore, step S107 includes the following steps:

[0104] Step S501: When the whitening hotspot is less than or equal to 0, the warning level is level 0, the risk level is no risk, and the classification result is no whitening risk;

[0105] When the bleaching hotspot is greater than 0 and less than the first threshold, the warning level is level 1, the risk level is bleaching observation, and the classification result is no bleaching risk, but observation is required;

[0106] When the whitening hotspot is greater than or equal to the first threshold, and the weekly heat is greater than 0 and less than or equal to the second threshold, the warning level is level 2, the risk level is whitening warning, and the classification result is that there is a whitening risk;

[0107] When the bleaching hotspot is greater than or equal to the first threshold, and the weekly heat is greater than the third threshold and less than or equal to the fourth threshold, the warning level is level 3 and the risk level is level 1 alert, indicating that coral reef bleaching may occur;

[0108] When the bleaching hotspot is greater than or equal to the fifth threshold, and the weekly heat is greater than the fourth threshold, the warning level is level 4 and the risk level is level 2 alert. The classification result is large-scale bleaching and accompanied by the death of coral reefs;

[0109] The first threshold is smaller than the second threshold, the second threshold is smaller than the third threshold, the third threshold is smaller than the fourth threshold, and the fifth threshold is larger than the first threshold and smaller than the second threshold.

[0110] Specifically, based on bleaching hotspots and weekly heat, the approximate location, coverage, and potential degree of bleaching of coral reefs currently under heat stress are displayed. In order to more conveniently and directly reflect the degree of coral bleaching and provide feedback information to users, coral reefs are graded for bleaching warnings based on the value range of bleaching hotspots and weekly heat, combined with measured coral bleaching data. The warning levels are divided into five levels: no risk, bleaching observation, bleaching warning, level 1 alert, and level 2 alert. The criteria for judgment are shown in Table 2:

[0111] Table 2

[0112]

[0113] Among them, the first threshold is 0.68, the second threshold is 2.78, the third threshold is 4, the fourth threshold is 8, and the fifth threshold is 1.

[0114] This application greatly improves the accuracy of coral reef bleaching early warning. Using a pilot evaluation conducted from June to August 2020, it can accurately predict coral reef bleaching events in the sea area. The method is simple and easy to use. It makes full use of the public CORA2.0 product to quickly predict coral reef bleaching, realizes daily updates of bleaching products, and lowers the technical threshold.

[0115] This application uses data from July to August 2020 in the South China Sea to conduct a coral reef early warning assessment. The results clearly demonstrate the progression of coral bleaching across China's coral reef distribution areas during the summer of 2020. Coral reefs across China faced widespread bleaching risk in the summer of 2020, with bleaching levels reaching Level 2 in some islands and reefs in the Beibu Gulf, Xisha, Dongsha, and Nansha Islands. From July to August, the bleaching risk in the Beibu Gulf region initially increased and then decreased.

[0116] The accuracy of the bleaching warning results was verified by selecting the Qiongzhou Strait, where there is relatively abundant coral reef survey and monitoring data. The coral reef status survey data and the warning results were superimposed; Figure 3As shown, it can be seen that Xuwen in Guangdong has the highest bleaching rate, with most stations having a bleaching rate greater than 1%, followed by the waters northeast of Hainan Island, with some stations having a bleaching rate greater than 1%. The bleaching rate in the coastal waters of Wenchang is relatively low, with a bleaching rate less than 1%. There is no bleaching phenomenon in the coastal coral reefs of Qionghai. The results are basically consistent with the early warning results and are also consistent with the results of the National Coral Reef Ecological Status Report released by the Ministry of Natural Resources.

[0117] Example 2:

[0118] Figure 4 Schematic diagram of a coral reef bleaching early warning system based on bottom seawater temperature provided in Example 2 of the present invention.

[0119] Reference Figure 4 , the system comprises:

[0120] Acquisition module, used to obtain coral reef bleaching warning data, which includes layered seawater temperature data and water depth data of each grid;

[0121] The classification module is used to reclassify the water depth data of each grid so that the water depth data of each grid corresponds to a predefined band;

[0122] The bottom seawater temperature data calculation module is used to calculate the daily bottom seawater temperature data according to the water depth data of each grid corresponding to the predefined band;

[0123] The maximum monthly average water temperature calculation module is used to calculate the maximum monthly average water temperature of the bottom layer over many years based on the reclassified water depth data;

[0124] The bleaching hotspot calculation module is used to calculate the bleaching hotspots based on the daily bottom seawater temperature data and the multi-year maximum monthly average water temperature of the bottom seawater;

[0125] Weekly heat calculation module, used to calculate weekly heat based on whitening hot spots;

[0126] The early warning classification module is used to classify coral reef bleaching early warnings according to bleaching hotspots and weekly heat to obtain classification results.

[0127] This application starts from reality and selects bottom sea water temperature as the coral reef bleaching early warning evaluation indicator, which greatly improves the accuracy of coral reef bleaching early warning. The trial evaluation results show that this application can achieve full prediction of coral reef bleaching events in the summer of 2020.

[0128] This application makes full use of the publicly released CORA 2.0 and Etopo products to achieve rapid prediction of coral reef bleaching products, improve the accuracy of coral reef bleaching warnings, and lower the technical threshold.

[0129] An embodiment of the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the coral reef bleaching early warning method based on bottom seawater temperature provided in the above embodiment are implemented.

[0130] An embodiment of the present invention also provides a computer-readable medium having non-volatile program code executable by a processor, wherein a computer program is stored on the computer-readable medium. When the computer program is executed by the processor, the steps of the coral reef bleaching early warning method based on bottom seawater temperature of the above embodiment are executed.

[0131] The computer program product provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the previous method embodiments. For specific implementation, please refer to the method embodiments and will not be repeated here.

[0132] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems and devices can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0133] In addition, in the description of the embodiments of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0134] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0135] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0136] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A coral reef bleaching early warning method based on bottom seawater temperature, characterized in that: The method comprises: Acquiring coral reef bleaching early warning data, the coral reef bleaching early warning data including layered seawater temperature data and water depth data for each grid; Reclassifying the water depth data of each grid so that the water depth data of each grid corresponds to a predefined band; Calculate daily bottom seawater temperature data based on the water depth data of each grid corresponding to a predefined band; Calculate the multi-year maximum monthly mean bottom water temperature based on the reclassified bathymetric data; Calculating bleaching hotspots based on the daily bottom seawater temperature data and the multi-year maximum monthly average bottom seawater temperature; Calculating weekly heat according to the whitening hotspot; Performing bleaching early warning classification on the coral reef according to the bleaching hotspot and the weekly heat, and obtaining a classification result; Reclassifying the water depth data of each grid so that the water depth data of each grid corresponds to a predefined band, including: Determining the corresponding relationship between the layered water depth and the wave band according to the layered seawater temperature data; Based on the correspondence between the layered water depths and the bands, a classification tool is used to reclassify the water depth data of each grid into the predefined bands; Calculate daily bottom seawater temperature data based on the water depth data of each grid corresponding to the predefined band, including: Extracting specific water temperature data from the daily water temperature data in different bands according to the predefined bands corresponding to the water depth data of each grid; The specific water temperature data is used as the daily bottom seawater temperature data.

2. The coral reef bleaching early warning method based on bottom seawater temperature according to claim 1, characterized in that: The multi-year maximum monthly mean bottom water temperature is calculated based on the reclassified bathymetric data, including: The multi-year monthly average bottom water temperature from January to December was calculated based on the reclassified water depth data; After comparing the multi-year monthly average bottom water temperatures from January to December, the highest monthly average water temperature in each grid is extracted; The multi-year maximum monthly average water temperature of the bottom layer is obtained based on the maximum monthly average water temperature in each grid.

3. The coral reef bleaching early warning method based on bottom seawater temperature according to claim 1, characterized in that: Calculate bleaching hotspots based on the daily bottom seawater temperature data and the multi-year maximum monthly average bottom seawater temperature, including: The whitening hotspot is calculated according to the following formula: in, For each day's bleaching hotspot, is the daily bottom sea temperature data, It is the highest monthly average water temperature of the bottom layer over many years.

4. The coral reef bleaching early warning method based on bottom seawater temperature according to claim 1, characterized in that: Calculating weekly heat according to the whitening hotspot includes: The weekly popularity is calculated according to the following formula: in, is the weekly heat, These are the latest 84-day bleaching hotspots.

5. The coral reef bleaching early warning method based on bottom seawater temperature according to claim 1, characterized in that: The coral reef is graded for bleaching warning according to the bleaching hotspot and the weekly heat, and a grading result is obtained, including: When the whitening hotspot is less than or equal to 0, the warning level is level 0, the risk level is no risk, and the classification result is no whitening risk; When the whitening hotspot is greater than 0 and less than the first threshold, the warning level is level 1, the risk level is whitening observation, and the classification result is no whitening risk, but observation is required; When the whitening hotspot is greater than or equal to the first threshold, and the weekly heat is greater than 0 and less than or equal to the second threshold, the warning level is level 2, the risk level is whitening warning, and the classification result is that there is a whitening risk; When the bleaching hotspot is greater than or equal to the first threshold, and the weekly heat is greater than the third threshold and less than or equal to the fourth threshold, the warning level is level 3, the risk level is level 1 alert, and the classification result is that coral reef bleaching may occur; When the bleaching hotspot is greater than or equal to the fifth threshold, and the weekly heat is greater than the fourth threshold, the warning level is level 4, the risk level is level 2 alert, and the classification result is large-scale bleaching and the death of coral reefs; The first threshold is smaller than the second threshold, the second threshold is smaller than the third threshold, the third threshold is smaller than the fourth threshold, and the fifth threshold is larger than the first threshold and smaller than the second threshold.

6. A coral reef bleaching early warning system based on bottom seawater temperature, characterized in that: The system comprises: An acquisition module is used to acquire coral reef bleaching early warning data, wherein the coral reef bleaching early warning data includes layered seawater temperature data and water depth data of each grid; A classification module, configured to reclassify the water depth data of each grid so that the water depth data of each grid corresponds to a predefined band; A bottom seawater temperature data calculation module is used to calculate daily bottom seawater temperature data based on the water depth data of each grid corresponding to a predefined band; The maximum monthly average water temperature calculation module is used to calculate the maximum monthly average water temperature of the bottom layer over many years based on the reclassified water depth data; a bleaching hotspot calculation module, configured to calculate bleaching hotspots based on the daily bottom seawater temperature data and the multi-year maximum monthly average water temperature of the bottom seawater; A weekly heat calculation module, used to calculate the weekly heat according to the whitened hot spots; An early warning classification module is used to perform bleaching early warning classification on the coral reef according to the bleaching hotspot and the weekly heat, and obtain a classification result; The classification module is specifically used for: Determining the corresponding relationship between the layered water depth and the wave band according to the layered seawater temperature data; Based on the correspondence between the layered water depths and the bands, a classification tool is used to reclassify the water depth data of each grid into the predefined bands; The bottom seawater temperature data calculation module is specifically used for: Extracting specific water temperature data from the daily water temperature data in different bands according to the predefined bands corresponding to the water depth data of each grid; The specific water temperature data is used as the daily bottom seawater temperature data.

7. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 5 is implemented.

8. A computer-readable medium having a non-volatile program code executable by a processor, characterized in that The program code causes the processor to execute the method according to any one of claims 1 to 5.

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