Method and system for determining background water temperature of thermal discharge from operating nuclear power plants based on remote sensing

Abstract

Disclosed are a method and a system for determining a background water temperature of thermal discharge from operating nuclear power plants based on the remote sensing. The system includes a station selection module, a model construction module, a background water temperature calculation module and a temperature rise calculation module; the general idea: constructing linear regression coefficients between water temperature reference station and water temperature estimation stations before the operation of the nuclear power plant based on historical satellite remote sensing water temperature data, and establishing a linear relationship model to calculate the background water temperature of the water temperature estimation of the operating nuclear power plant. The specific implementation route: the station selection module is connected with the model construction module, the model construction module is connected with the background water temperature calculation module, and the background water temperature calculation module is connected with the temperature rise calculation module.

Claims

1. A method for determining a background water temperature of thermal discharge from operating nuclear power plants based on remote sensing, comprising following steps: S1, collecting distributions of satellite remote sensing sea surface water temperatures with a high spatiotemporal resolution before and after nuclear power plant operations and background information of nuclear power plants, based on the distributions of the satellite remote sensing sea surface water temperatures before and after the nuclear power plant operations and the background information, selecting a water temperature reference station and water temperature estimation stations; S2, collecting hourly satellite remote sensing sea surface water temperatures of the water temperature reference station and the water temperature estimation stations in typical seasons before the nuclear power plant operation, based on the satellite remote sensing sea surface water temperatures with the high spatiotemporal resolution, constructing a linear relationship model of water temperatures between the water temperature reference station and the water temperature estimation stations; and based on the linear relationship model, screening and eliminating the water temperature estimation stations not in line with predetermined conditions; S3, collecting a sea surface water temperature observation value of the water temperature reference station after the nuclear power plant operation and a satellite remote sensing synchronous sea surface water temperature value after the nuclear power plant operation, correcting a value of the satellite remote sensing sea surface water temperature to obtain a corrected parameter of the linear relationship model between the water temperature reference station and the water temperature estimation stations; and based on the corrected parameter, obtaining background water temperatures of the water temperature estimation stations after the nuclear power plant operation; and S4, based on a water temperature of the water temperature reference station, calculating a difference value between the background water temperatures of the water temperature estimation stations and synchronous water temperatures of the water temperature estimation stations, and obtaining a temperature rise water temperature value.

2. The method for determining a background water temperature of thermal discharge from operating nuclear power plants based on remote sensing according to claim 1, wherein the background information in the S1 comprises a hydrological environment, a marine topography and meteorological information.

3. The method for determining a background water temperature of thermal discharge from operating nuclear power plants based on remote sensing according to claim 1, wherein a method for selecting the water temperature reference station in the S1 comprises: collecting the distributions of the satellite remote sensing sea surface water temperatures before and after the nuclear power plant operations, and selecting a station not affected by the thermal discharge as the water temperature reference station.

4. The method for determining a background water temperature of thermal discharge from operating nuclear power plants based on remote sensing according to claim 1, wherein a method for selecting the water temperature estimation stations in the S1 comprises: based on the distributions of the satellite remote sensing sea surface water temperatures before and after the nuclear power plant operations, selecting water temperature stations in a temperature-rising area of drainage outlets of the nuclear power plants; and carrying out an encryption interpolation on a distribution of the water temperature stations to obtain a plurality of the water temperature estimation stations.

5. The method for determining a background water temperature of thermal discharge from operating nuclear power plants based on the remote sensing according to claim 1, wherein the linear relationship model comprises: a water temperature value of the water temperature estimation station=A×a water temperature value of the water temperature reference station+B; wherein A and B are linear regression coefficients.

6. The method for determining a background water temperature of thermal discharge from operating nuclear power plants based on remote sensing according to claim 4, wherein a method for screening and eliminating the water temperature estimation stations not in line with the predetermined conditions in the S2 comprises: based on the linear relationship model, eliminating the water temperature estimation stations with a correlation below 0.85.

7. The method for determining a background water temperature of thermal discharge from operating nuclear power plants based on remote sensing according to claim 1, wherein a method for obtaining the background water temperatures of the water temperature estimation stations in the S3 comprises: collecting the sea surface water temperature observation value of the water temperature reference station and the satellite remote sensing synchronous sea surface water temperature value, and based on the sea surface water temperature observation value, correcting the value of the satellite remote sensing sea surface water temperature to obtain the corrected parameter; and based on the corrected parameter and the linear relationship model, obtaining the background water temperatures of the water temperature estimation stations, and a value of the background water temperature of the water temperature estimation station=A×the water temperature value of the water temperature reference station+B+the corrected parameter.

8. A system for determining a background water temperature of thermal discharge from operating nuclear power plants based on remote sensing, comprising a station selection module, a model construction module, a background water temperature calculation module and a temperature rise calculation module; the station selection module is connected with the model construction module, and the station selection module is used for selecting the water temperature reference station and the water temperature estimation stations; the model construction module is connected with the background water temperature calculation module, and the model construction module is used for constructing a linear relationship model between the water temperature values of the water temperature reference station and the water temperature estimation stations; the background water temperature calculation module is connected with the temperature rise calculation module, and the background water temperature calculation module is used for calculating the background water temperatures of the water temperature estimation stations based on the linear relationship model; and the temperature rise calculation module is used for calculating the temperature rise water temperature values of the water temperature estimation stations.

9. The system for determining a background water temperature of thermal discharge from operating nuclear power plants based on remote sensing according to claim 8, wherein the station selection module comprises an acquisition unit and a station selection unit; the acquisition unit is connected with the station selection unit, and the acquisition unit is used for acquiring the distributions of the satellite remote sensing sea surface water temperatures and the background information of the nuclear power plants; and the station selection unit is used for selecting the water temperature reference station and the water temperature estimation stations based on the distributions of the satellite remote sensing sea surface water temperatures before and after the nuclear power plant operations and the background information.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) To explain the technical scheme of this application more clearly, the drawings needed in the embodiments are briefly introduced below. The drawings in the following description are only some embodiments of this application. For ordinary technicians in this field, other drawings may be obtained according to these drawings without paying creative labor.

(2) FIG. 1 is a schematic flow diagram of a method according to the application.

(3) FIG. 2 is a schematic structural diagram of a system according to the application.

(4) FIG. 3 is a linear fitting diagram of hourly water temperatures of w134 station and w135 station in Embodiment 3 according to the application.

(5) FIG. 4 is a linear fitting diagram of hourly water temperatures of w126 station and w131 station in Embodiment 3 according to the application.

(6) FIG. 5 is a linear fitting diagram of hourly water temperatures of w126 station and w123 station in Embodiment 3 according to the application.

(7) FIG. 6 is a linear fitting diagram of hourly water temperatures of w121 station and w122 station in Embodiment 3 according to the application.

(8) FIG. 7 is a schematic diagram of correlation analysis between measured sea surface water temperature data and synchronous remote sensing sea surface water temperature in Embodiment 4 according to the application.

(9) FIG. 8 is a schematic diagram showing positions of a water temperature reference station and each water temperature estimation station in Embodiment 5 according to the application.

(10) FIG. 9 is a linear fitting diagram of water temperatures between the water temperature reference station and the water temperature estimation station T1 in Embodiment 5 according to the application.

(11) FIG. 10 is a linear fitting diagram of water temperatures between the water temperature reference station and the water temperature estimation station T2 in Embodiment 5 according to the application.

(12) FIG. 11 is a linear fitting diagram of water temperatures between the water temperature reference station and the water temperature estimation station T3 in Embodiment 5 according to the application.

(13) FIG. 12 is a linear fitting diagram of water temperatures between the water temperature reference station and the water temperature estimation station T4 in Embodiment 5 according to the application.

(14) FIG. 13 is a linear fitting diagram of water temperatures between the water temperature reference station and the water temperature estimation station T5 in Embodiment 5 according to the application.

(15) FIG. 14 is a linear fitting diagram of water temperatures between the water temperature reference station and the water temperature estimation station T6 in Embodiment 5 according to the application.

DETAILED DESCRIPTION

(16) In the following, the technical scheme in the embodiment of the application will be clearly and completely described concerning the drawings in the embodiment of the application. The described embodiment is only a part of the embodiment of the application, but not the whole embodiment. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work belong to the protection scope of this application.

(17) To make the above objects, features and advantages of this application more obvious and easier to understand, the application will be further described in detail with the attached drawings and specific embodiments.

(18) Embodiment 1

(19) As shown in FIG. 1, a method for determining a background water temperature of thermal discharge from operating nuclear power plants based on remote sensing is provided, and the method includes the following steps:

(20) S1, collecting distributions of satellite remote sensing sea surface water temperatures with a high spatiotemporal resolution before and after nuclear power plant operations and background information of nuclear power plants, based on the distributions of the satellite remote sensing sea surface water temperatures before and after the nuclear power plant operations and the background information, selecting a water temperature reference station and water temperature estimation stations;

(21) where the background information includes a hydrological environment, a marine topography and meteorological information. In this embodiment, Himawari satellite is used, its time resolution is 1 hour and its spatial resolution is 2 kilometers, which may meet the needs of continuous water temperature calculation. Compared with the general satellite that only provides a daily average temperature, the Himawari satellite remote sensing data has high time resolution, which may meet the needs of continuous calculation, and at the same time, the spatial resolution may meet the needs of selected stations in the sea area near the drainage outlet of the coastal nuclear power plant.

(22) A method for selecting the water temperature reference station is as follows: collecting the satellite remote sensing sea surface water temperature distribution before and after the nuclear power plant operation, and selecting the station that is not affected by thermal discharge and is convenient for long-term observation of the sea surface water temperature in the later stage as the water temperature reference station. A method for selecting the water temperature estimation stations is as follows: according to the resolution of satellite remote sensing sea surface water temperature, arranging multiple water temperature sampling stations around the drainage outlet of the nuclear power plant, because the distribution of surface water temperatures near the site is similar before the operation of the nuclear power plant, at the same time, to ensure the calculation of background water temperature in the sea area around the drainage outlet, multiple water temperature estimation stations are arranged near the water outlet, and the spatial resolution of the water temperature estimation stations is higher than that of the water temperature sampling stations, and the water temperature of the water temperature sampling stations is interpolated to the water temperature estimation stations.

(23) S2, collecting hourly satellite remote sensing sea surface water temperatures of the water temperature reference station and the water temperature estimation stations in typical seasons before the nuclear power plant operation, based on the satellite remote sensing sea surface water temperatures with the high spatiotemporal resolution, constructing a linear relationship model of water temperatures between the water temperature reference station and the water temperature estimation stations; and based on the linear relationship model, screening and eliminating the water temperature estimation stations not in line with predetermined conditions;

(24) where the typical seasons include: summers and winters;

(25) the seawater temperature equations are shown in the following formula (1), formula (2) and formula (3):

(26) $\begin{matrix} \frac{\partial u}{\partial x} + \frac{\partial v}{\partial y} + \frac{\partial w}{\partial z} = 0; & (1) \end{matrix}$

(27) $\begin{matrix} \frac{\partial T}{\partial t} + u \frac{\partial T}{\partial x} + v \frac{\partial T}{\partial_{y}} + w \frac{\partial T}{\partial z} = \frac{\partial}{\partial z} (K_{h} \frac{\partial T}{\partial z}) + F_{T}; & (2) \end{matrix}$

(28) where u, v and w respectively represent current velocity components in x, y and z directions; T represents the seawater temperature; t represents time; K.sub.h represents a thermal vertical vortex viscosity coefficient; and FT represents a heat diffusion term or a heat source term.

(29) At the sea surface z=ζ(x,y,t):

(30) $\begin{matrix} \frac{\partial T}{\partial z} = \frac{1}{ρ C_{p} K_{h}} [Q_{n} (x, y, z) - S W (x, y, ζ, z)]; & (3) \end{matrix}$

(31) where represents the fluctuation of sea level, Q.sub.n(x,y,z) represents the net heat flux of the sea surface, including net downward long-wave radiation, net downward short-wave radiation, latent heat flux and sensible heat flux; SW(x,y,ζ,z) represents short-wave radiation from the sea surface; C.sub.p represents the specific heat of seawater; long-wave radiation, sensible heat flux and latent heat flux usually occur on the sea surface.

(32) According to the seawater temperature equation (1), the seawater temperature equation (2) and the seawater temperature equation (3), it is known that the sea surface water temperature is closely related to heat fluxes and sea currents without the influence of the heat source term. In an open sea area or a semi-closed bay, the sea surface heat fluxes of two points C and D which are not far apart (generally within 20 kilometers) are the same. If the hydrological environments of the two points are basically the same (current distribution characteristics and the marine topography), the water temperature of points C and D will show a significant linear relationship without the influences of runoffs and other cold and heat sources.

(33) The linear relationship model includes:

(34) a water temperature value of the water temperature estimation station=A×a water temperature value of the water temperature reference station+B;

(35) where A and B are linear regression coefficients.

(36) A method for screening and eliminating the water temperature estimation stations includes the following steps:

(37) based on the linear relationship model, eliminating the water temperature estimation stations with a correlation coefficient between the water temperature estimation station and the water temperature reference station below 0.85.

(38) S3, collecting a sea surface water temperature observation value of the water temperature reference station after the nuclear power plant operation and a satellite remote sensing synchronous sea surface water temperature value after the nuclear power plant operation, correcting a value of the satellite remote sensing sea surface water temperature to obtain a corrected parameter of the linear relationship model between the water temperature reference station and the water temperature estimation stations; and based on the corrected parameter, obtaining background water temperatures of the water temperature estimation stations after the nuclear power plant operation;

(39) a method for obtaining the background water temperatures of the water temperature estimation stations includes the following steps:

(40) collecting the sea surface water temperature observation value of the water temperature reference station and the satellite remote sensing synchronous sea surface water temperature value, and based on the sea surface water temperature observation value, correcting the value of the satellite remote sensing sea surface water temperature to obtain the corrected parameter; and

(41) based on the corrected parameter and the linear relationship model, obtaining the background water temperatures of the water temperature estimation stations;

(42) that is, a value of the background water temperature of the water temperature estimation station=A×the water temperature value of the water temperature reference station+B+the corrected parameter.

(43) S4, based on a water temperature of the water temperature reference station, calculating a difference value between the background water temperatures of the water temperature estimation stations and synchronous water temperatures of the water temperature estimation stations, and obtaining a temperature rise water temperature value.

(44) According to the seawater temperature method mentioned above, when one of points C or D is affected by a heat source, its linear relationship will be broken. Assuming that point C is affected by a heat source and point D is not affected by the heat source, when the temperature of point C is affected by an additional superimposed heat source, the water temperature of point C=the background water temperature of point C+temperature rise value or temperature drop value of point C; therefore, when the heat source affects point C and point D is not affected by the heat source, the temperature rise value or temperature drop value at point C cannot be directly distinguished by the on-site water temperature observation, but the environmental background water temperature at point C may be obtained through the water temperature at point D and the previous linear relationship between the water temperature at point C and the water temperature at point D, and the temperature rise value or temperature drop value at point C may be obtained through the on-site absolute water temperature observation (the environmental background water temperature+the temperature rise value or the temperature drop value) and the calculated environmental background water temperature at point C, thus obtaining the temperature rise value or the temperature drop value at point C influenced by the heat sources. Therefore, if the water temperature at points C and D is observed in advance before any point C or D is affected by the heat source, the linear relationship between the two is obtained, when one point of C or D is affected by a heat source or a cold source, the background water temperature of the affected point can be calculated through the linear relationship between the two, to obtain the water temperature rise value or water temperature drop value.

(45) Embodiment 2

(46) As shown in FIG. 2, a system for determining a background water temperature of thermal discharge from operating nuclear power plants based on remote sensing is also provided in the application, and the system includes a station selection module, a model construction module, a background water temperature calculation module and a temperature rise calculation module;

(47) the station selection module is connected with the model construction module, and the station selection module includes an acquisition unit and a station selection unit; a working process of the station selection module includes following steps:

(48) collecting the satellite remote sensing sea surface water temperature distribution before and after the nuclear power plant operation, and selecting the station that is not affected by thermal discharge, and is convenient for long-term observation of the sea surface water temperature in the later stage as the water temperature reference station. A method for selecting the water temperature estimation stations is as follows: according to the resolution of satellite remote sensing sea surface water temperature, arranging multiple water temperature sampling stations around the drainage outlet of the nuclear power plant, because the distribution of surface water temperatures near the site is similar before the operation of the nuclear power plant, at the same time, in order to ensure the calculation of background water temperature in the sea area around the drainage outlet, multiple water temperature estimation stations are arranged near the water outlet, and the spatial resolution of the water temperature estimation stations is higher than that of the water temperature sampling stations, and the water temperature of the water temperature sampling stations is interpolated to the water temperature estimation stations.

(49) The model construction module is connected with the background water temperature calculation module, and a working process of the model construction module includes following steps:

(50) the seawater temperature equations are shown in the following formula (1), formula (2) and formula (3):

(51) $\begin{matrix} \frac{\partial u}{\partial x} + \frac{\partial v}{\partial y} + \frac{\partial w}{\partial z} = 0; & (1) \end{matrix}$

(52) $\begin{matrix} \frac{\partial T}{\partial t} + u \frac{\partial T}{\partial x} + v \frac{\partial T}{\partial y} + w \frac{\partial T}{\partial z} = \frac{\partial}{\partial z} (K_{h} \frac{\partial T}{\partial z}) + F_{T}; & (2) \end{matrix}$

(53) where u, v and w respectively represent current velocity components in x, y and z directions; T represents the seawater temperature; t represents time; K.sub.h represents a thermal vertical vortex viscosity coefficient; and F.sub.T represents a heat diffusion term or a heat source term.

(54) At the sea surface z=ζ(x,y,t):

(55) $\begin{matrix} \frac{\partial T}{\partial z} = \frac{1}{ρ C_{p} K_{h}} [Q_{n} (x, y, z) - S W (x, y, ζ, z)]; & (3) \end{matrix}$

(56) where ζ represents the fluctuation of sea level, Q.sub.n(x,y,z) represents the net heat flux of the sea surface, including net downward long-wave radiation, net downward short-wave radiation, latent heat flux and sensible heat flux; SW(x,y,ζ,z) represents short-wave radiation from the sea surface; C.sub.p represents the specific heat of seawater; long-wave radiation, sensible heat flux and latent heat flux usually occur on the sea surface.

(57) According to the seawater temperature equation (1), the seawater temperature equation (2) and the seawater temperature equation (3), it is known that the sea surface water temperature is closely related to heat fluxes and sea currents without the influence of the heat source term. In an open sea area or a semi-closed bay, the sea surface heat fluxes of two points C and D which are not far apart (generally within 20 kilometers) are basically the same. If the hydrological environments of the two points are basically the same (current distribution characteristics and the marine topography), the water temperature of points C and D will show a significant linear relationship without the influences of runoffs and other cold and heat sources.

(58) Constructing the linear relationship model:

(59) the water temperature value of the water temperature estimation station=A×a water temperature value of the water temperature reference station+B;

(60) where A and B are linear regression coefficients.

(61) A method for screening and eliminating the water temperature estimation stations includes the following steps:

(62) based on the linear relationship model, eliminating the water temperature estimation stations with a correlation coefficient between the water temperature estimation station and the water temperature reference station below 0.85.

(63) The background water temperature calculation module is connected with the temperature rise calculation module, and the working process of the background water temperature calculation module includes:

(64) collecting the sea surface water temperature observation value after the operation of the water temperature reference station and the synchronized sea surface water temperature value after the operation of the satellite remote sensing, and correcting the sea surface water temperature value obtained by satellite remote sensing based on the sea surface water temperature observation value of the water temperature reference station to obtain the corrected parameters of the remote sensing water temperature of the water temperature reference station;

(65) that is, a value of the background water temperature of the water temperature estimation station=A×the water temperature value of the water temperature reference station+B+the corrected parameter.

(66) A working process of the temperature rise calculation module includes following steps:

(67) According to the seawater temperature method mentioned above, a linear relationship will be broken when one of points C and D is affected by a heat source. Assuming that point C is affected by a heat source and point D is not affected by the heat source, when the temperature of point C is affected by an additional superimposed heat source, the water temperature of point C=the background water temperature of point C+temperature rise value or temperature drop value of point C; therefore, when the heat source affects point C and point D is not affected by the heat source, the temperature rise value or temperature drop value at point C cannot be directly distinguished by the on-site water temperature observation, but the environmental background water temperature at point C may be obtained through the water temperature at point D and the previous linear relationship between the water temperature at point C and the water temperature at point D, and the temperature rise value or temperature drop value at point C may be obtained through the on-site absolute water temperature observation (the environmental background water temperature+the temperature rise value or the temperature drop value) and the calculated environmental background water temperature at point C, thus obtaining the temperature rise value or the temperature drop value at point C influenced by the heat sources. Therefore, if the water temperature at points C and D is observed in advance before any point C or D is affected by the heat source, the linear relationship between the two is obtained, when one point of C or D is affected by a heat source or a cold source, the background water temperature of the affected point can be calculated through the linear relationship between the two, so as to obtain the water temperature rise value or water temperature drop value.

(68) Embodiment 3

(69) In this embodiment, the coastal bank of Ningde City in Fujian Province is taken as an example, a plurality of temporary water temperature observation stations are arranged and divided into three groups for testing the correlation of the water temperature linear relationship, which respectively represent open sea areas and a bay sea area. The distance between each group of stations is 10 kilometers-30 kilometers, as shown in Table 1. The water temperature observation time of each group is the same, and the water temperature observation adopts RBR XR-620 CTD. There are no less than 2 water temperature observation stations in each group. One station in each group is selected as the water temperature reference station, and the remaining stations are used as its water temperature estimation stations. The linear relationship between the water temperatures of the water temperature reference station and the water temperature estimation station is fitted, and the mean square deviation of the fitted water temperature is calculated, to prove the linear correlation between each group of stations, and to test the accuracy of the fitted water temperature at the same time.

(70) TABLE-US-00001 TABLE 1 Water temperature observation position and observation time information Station Locations Observation duration Groups numbers Longitude Latitude in summer Group 1 w134 119.794261 26.501725 6 Jun.-3 Jul. 2021 (open sea area) w135 119.810886 26.462253 Group 2 w123 120.011108 26.771256 11 Jun.-4 Jul. 2021 (bay sea area) w126 119.901431 26.690111 w131 119.693817 26.673664 Group 3 w121 120.314617 26.949786 6 Jun.-3 Jul. 2021 (open sea area) w122 120.243806 26.930319

(71) (1) In the first group of water temperature linear fitting, w134 station is taken as the water temperature reference station (with an average water temperature of 23.978° C.), and w135 station is taken as its water temperature estimation station (with an average water temperature of 24.264° C.), and the daily average water temperature correlation coefficient of the two stations is 0.924, with a reliability exceeding 99%. There is a following linear relationship in calculating the water temperatures of the two stations: T.sub.w135=0.867×T.sub.w134+3.467, and the mean square deviation is 0.069, indicating that there is a significant linear relationship between the two stations. The water temperature of w135 station calculated by taking w134 station as the water temperature reference station is more accurate. Therefore, the formula T.sub.w135=0.867×T.sub.w134+3.467 and the hourly water temperature measured at w134 station may be used to calculate the hourly water temperature at w135 station in summer. As shown in FIG. 3, a linear fitting diagram of hourly water temperatures of w134 station and w135 station is shown.

(72) (2) In the second group of water temperature linear fitting, w126 station is taken as the water temperature reference station (with an average water temperature of 26.354° C.), and w123 station and w131 station are taken as its water temperature estimation stations (with average water temperatures of 26.461° C. and 25.571° C.). Through correlation analysis, the daily average water temperature correlation coefficient of w123 station and w126 station is 0.937, and the daily average water temperature correlation coefficient of w126 station and w131 station is 0.879, with reliabilities exceeding 99%. It is obtained that the hourly water temperatures of station w126 and station w123 and the hourly water temperatures of station w126 and station w131 have the following linear relationships: T.sub.w123=1.069×T.sub.w126−1.725, T.sub.w131=0.710×T.sub.w126+6.834, and the mean square deviation are 0.274 and 0.133, respectively. Therefore, it may be seen that there are significant linear relationships among the three stations. Therefore, the formula T.sub.w123=1.069×T.sub.w126−1.725, the formula T.sub.w131=0.710×T.sub.w126+6.834, and the hourly water temperature measured at w126 station may be used to calculate the hourly water temperature at w123 station and w131 station in summer. As shown in FIG. 4 and FIG. 5, a linear fitting diagram of hourly water temperatures of w126 station and w131 station, and a linear fitting diagram of hourly water temperatures of w126 station and w123 station are respectively shown.

(73) (3) In the third group of water temperature linear fitting, w121 station is taken as the water temperature reference station (with an average water temperature of 25.075° C.), and w122 station is taken as its water temperature estimation station (with an average water temperature of 25.832° C.). Through correlation analysis, the daily average water temperature correlation coefficient of w121 station and w122 station is 0.875, with a reliability exceeding 99%. It is obtained that the hourly water temperatures of the two stations has the following linear relationships: T.sub.w122=0.878×T.sub.w121+3.802, and the mean square error is 0.246, indicating that there is a significant linear relationship between the two stations. Therefore, the formula T.sub.w122=0.878×T.sub.w121+3.802 and the hourly water temperature measured at w121 station may be used to calculate the hourly water temperature at w122 station in summer. As shown in FIG. 6, a linear fitting diagram of hourly water temperatures of w121 station and w122 station is shown.

(74) From the above experimental results of linear fitting of water temperature, it may be seen that, whether in the bay or in the open sea area, when the current distribution characteristics, water depth topography characteristics and meteorological conditions of each group of stations are similar, and the distance between each group of stations is less than 30 kilometers, there is a significant linear relationship between the water temperatures of each group of stations, and the mean square deviation is very small. Therefore, when the water temperature of one water temperature station in the group is affected by the heat source, the environmental background water temperature of the affected water temperature station is calculated by the other water temperature station.

(75) Embodiment 4

(76) In this embodiment, the measured sea surface water temperature of the dock of the National Deep-Sea Base Management Center is taken as an example to verify the accuracy of the nearshore sea surface water temperature obtained by the Himawari satellite.

(77) In order to verify the accuracy of the nearshore surface water temperature remote sensing data obtained by the Himawari satellite in the coastal waters, the surface water temperature is observed at the dock of the National Deep-Sea Base Management Center from May 13 to Jul. 12, 2022. The float-up method is used to observe the sea surface water temperature, and the water temperature observation equipment is placed under the floating ball to ensure the accuracy and reliability of the acquired sea surface water temperature data, meanwhile, the synchronized hourly remote sensing data of surface water temperature obtained by the Himawari satellite at the dock location during the observation period are collected. The correlation between the measured sea surface water temperature data and the synchronized remote sensing sea surface water temperature is analyzed. The linear analysis result is shown in FIG. 7, and the correlation coefficient between them is 0.957, which shows that the hourly sea surface water temperature remote sensing data obtained by the Himawari satellite is accurate, and may be used to obtain the water temperature data before the operation of nuclear power plants. Through the sea surface water temperature remote sensing data obtained by the Himawari satellite, the selection and correlation analysis of the water temperature reference station and water temperature estimation station may be carried out.

(78) Embodiment 5

(79) This embodiment takes the Haiyang nuclear power plant Phase I project in Yantai City, Shandong Province as an example, and introduces in detail the method for determining a background water temperature of thermal discharge from operating nuclear power plants of this application.

(80) Firstly, the surface water temperatures obtained by the Himawari satellite remote sensing in typical seasons before and after the nuclear power plant operation is selected, that is, the surface water temperature remote sensing data in July 2017 and July 2022. At the same time, combined with the prediction results of thermal discharge in the sea area utilization demonstration report of this project, within 20 kilometers of the sea area around the drainage outlet, the area where the water temperature basically does not change before and after the nuclear power plant operation is selected as the water temperature reference station. Through comparative analysis, it may be known that the water temperature at Haiyangxingang, which is about 8.2 kilometers away from the drainage outlet, is not affected by thermal discharge. At the same time, according to the numerical calculation results of the temperature rise influence of thermal discharge in the sea area utilization demonstration report of Haiyang Nuclear Power Plant Phase I project, the location of Haiyangxingang is outside the temperature rise range of 0.1° C., so it is selected as the water temperature reference station, and six stations within 4 kilometers of the drainage outlet of the nuclear power plant are selected as the water temperature estimation stations, i.e. T1, T2, T3, T4, T5 and T6, the distance between adjacent water temperature estimation stations is about 700 meters-1.1 kilometers, which is basically within the influence range of 1° C.-4° C. in the temperature rise zone of thermal discharge. The position schematic of water temperature reference station and water temperature estimation stations is shown in FIG. 8.

(81) According to the sea surface temperature distribution obtained by the Himawari satellite remote sensing from 1:00 on Jul. 3, 2017 to 0:00 on Jul. 29, 2017, the time series distribution of sea surface temperature of the water temperature reference station and the water temperature estimation station is extracted, and the linear correlation analysis of water temperature reference station and water temperature estimation station is carried out to obtain the linear relationship between the water temperature reference station and each water temperature estimation station, where T.sub.c represents the water temperature of the water temperature reference station, and T1, T2, T3, T4, T5 and T6 represent the water temperature of each water temperature estimation station, as shown in Table 2. The linear fitting diagrams of water temperature between the water temperature reference station and each water temperature estimation station are shown in FIG. 9, FIG. 10, FIG. 11, FIG. 12, FIG. 13 and FIG. 14. Table 2 is a summary of the linear relationship between the water temperature reference station and each water temperature estimation station. It may be seen from Table 2 that there is a very good linear relationship between the water temperature reference station and each water temperature estimation station, and the mean square deviations are very small, which shows that the environmental background water temperature of each water temperature estimation station may be calculated through the water temperature reference stations and the linear regression coefficients, that is T.sub.i=A.sub.i×T.sub.c+B.sub.i, where A.sub.i and B.sub.i represent the linear regression coefficients corresponding to the i-th water temperature estimation station, and T.sub.i represents the environmental background water temperature of the i-th water temperature estimation station.

(82) TABLE-US-00002 TABLE 2 Summary of the linear relationship between the water temperature reference station and each water temperature estimation station Serial Mean square number Linear relationship deviation 1 T1 = 0.9944 × T.sub.c + 0.2142 0.0407 2 T2 = 0.9880 × T.sub.c + 0.6042 0.2142 3 T3 = 0.9998 × T.sub.c + 0.0861 0.0440 4 T4 = 0.9882 × T.sub.c + 0.5424 0.0501 5 T5 = 0.9883 × T.sub.c + 0.5893 0.0851 6 T6 = 0.9752 × T.sub.c + 0.3174 0.0369

(83) From Jun. 11, 2022 to Jun. 23, 2022, the surface water temperature observation of seawater is carried out at the water temperature reference station in Haiyangxingang for about 13 days, which is used to correct the water temperature observation value of the water temperature reference station and the water temperature of the water temperature reference station obtained by the Himawari satellite remote sensing so as to improve the accuracy of calculation; after correction, the average difference between the surface water temperature measured by the water temperature reference station and the surface water temperature interpreted by satellite remote sensing is 0.074° C., that is, the corrected parameter=0.074. Therefore, the calculation formula of environmental background water temperature of six water temperature estimation stations is: T.sub.i=A.sub.i×T.sub.c+B.sub.i+0.074, where T.sub.c represents the water temperature of the water temperature reference station, A.sub.i and B.sub.i represent the linear regression coefficients corresponding to the i-th water temperature estimation station, and T.sub.i represents the environmental background water temperature of the i-th water temperature estimation station.

(84) According to the above formula, the environmental background water temperature of each water temperature estimation station may be calculated by using the hourly seawater surface water temperature observation value of the water temperature reference station on Jun. 12, 2022, and the estimated environmental background water temperature of each water temperature estimation station is shown in Table 3.

(85) TABLE-US-00003 TABLE 3 Summary of environmental background water temperature calculation values of each water temperature calculation station Station number Time T1 T2 T3 T4 T5 T6 1:00 21.148 21.416 21.122 21.358 21.407 20.887 2:00 21.175 21.444 21.150 21.385 21.434 20.914 3:00 21.209 21.477 21.183 21.419 21.468 20.947 4:00 21.172 21.441 21.147 21.383 21.431 20.911 5:00 21.356 21.623 21.331 21.565 21.614 21.091 6:00 21.305 21.573 21.281 21.515 21.564 21.041 7:00 21.296 21.564 21.272 21.506 21.555 21.033 8:00 21.322 21.590 21.297 21.532 21.580 21.047 9:00 21.327 21.594 21.302 21.536 21.585 21.063 10:00 21.578 21.844 21.554 21.786 21.835 21.309 11:00 21.441 21.707 21.417 21.649 21.698 21.174 12:00 21.289 21.557 21.264 21.499 21.547 21.025 13:00 21.220 21.488 21.195 21.430 21.479 20.958 14:00 21.407 21.674 21.383 21.616 21.665 21.141 15:00 21.453 21.720 21.429 21.662 21.711 21.186 16:00 21.542 21.808 21.518 21.750 21.799 21.273 17:00 21.689 21.954 21.666 21.896 21.945 21.417 18:00 21.687 21.952 21.664 21.894 21.943 21.416 19:00 21.825 22.089 21.803 22.032 22.080 21.551 20:00 21.919 22.183 21.898 22.125 22.174 21.644 21:00 21.924 22.188 21.903 22.130 22.179 21.648 22:00 21.986 22.249 21.965 22.191 22.240 21.709 23:00 22.545 22.805 22.527 22.747 22.796 22.257 0:00 22.145 22.407 22.125 22.350 22.399 21.865

(86) After the environmental background water temperature of each water temperature estimation station is calculated, the actual temperature rise value may be obtained by subtracting the actual water temperature observation value of each water temperature estimation station at the site after the operation of the nuclear power plant from the synchronized environmental background water temperature calculation value.

(87) The above-mentioned embodiment is only a description of the preferred mode of the application, and does not limit the scope of the application. Under the premise of not departing from the design spirit of the application, various modifications and improvements made by ordinary technicians in the field to the technical scheme of the application shall fall within the protection scope determined by the claims of the application.

Method and system for determining background water temperature of thermal discharge from operating nuclear power plants based on remote sensing

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