A method for calculating evaporation of plateau lake by remote sensing considering terrain and water body heat storage effect

Abstract

The application discloses a kind of plateau lake evaporation remote sensing calculation method considering terrain and water body heat storage effect, belong to surface evapotranspiration quantitative remote sensing inversion technical field.This method realizes the high-precision estimation of plateau lake evaporation capacity by adjacent terrain effect and water body layered heat transfer process.First, remote sensing image, meteorological data and digital elevation model are obtained and preprocessed;Then, the terrain corrected sky visible factor and terrain configuration factor are calculated, and the influence of terrain on radiation transmission is quantified;Then, the water temperature distribution of different depth layers of the lake is simulated using a one-dimensional heat transfer equation, and the water body heat storage flux is accurately calculated;Finally, the spatialization estimation of evaporation rate is realized by combining energy balance equation and meteorological parameters.The application innovatively solves the key problems that traditional evaporation model ignores terrain effect and water body heat storage in the application of plateau lake, and provides reliable technical support for water resource management and ecological protection in plateau area.

Description

Technical Field

[0001] This invention relates to the field of quantitative remote sensing inversion technology of surface evapotranspiration, and in particular to a remote sensing calculation method for evaporation of plateau lakes that takes into account topography and the thermal storage effect of water bodies. Background Technology

[0002] High-altitude lakes are not only habitats for various rare aquatic plants and animals, but also important sources of freshwater for the middle and lower reaches of the lake, significantly impacting the development of numerous densely populated cities in these areas. Lake evaporation is a crucial link in lake water balance and a significant component of lake water loss. Currently, observation techniques and methods for lake evaporation mainly fall into two categories: real-time observation based on water surface monitoring stations and indirect inversion based on remote sensing technology. Observation techniques based on water surface stations primarily include eddy covariance systems (EC), ripple ratio systems, and large-aperture scintillation meters. Remote sensing-based lake evaporation estimation techniques utilize precisely acquired water-thermal parameters of the lake's spatial environment (such as lake surface temperature (LWST), albedo, and lake surface area) obtained through remote sensing, and then use these parameters to indirectly estimate lake evaporation. The main methods include: water surface energy balance methods, aerodynamic methods, water balance methods, and comprehensive models such as the Priestley-Taylor (PT) and Penman-Monteith (PM) equations and their linear and nonlinear combinations.

[0003] Due to the complex geographical and hydrological conditions of plateau lakes, the aforementioned techniques for estimating lake evaporation still have certain limitations. Evaporation observation methods based on water surface stations suffer from expensive equipment, difficulty in installing equipment on the lake surface, high operation and maintenance costs, and poor spatial representativeness, making it difficult to achieve large-scale lake evaporation observation. Although remote sensing technology can be used for evaporation estimation of large-area lakes, most current lake evaporation estimation methods are based on terrestrial evapotranspiration models, neglecting the effects of topographic effects in the surrounding mountainous areas and the heat flux stored in the water, making them unsuitable for high-precision remote sensing estimation of plateau lake evaporation. Therefore, to achieve accurate quantification and monitoring analysis of the spatiotemporal changes in plateau lake evaporation, it is urgent to construct a remote sensing evaporation estimation model that considers topographic effects and the heat flux stored in the water, enabling long-term accurate monitoring of plateau lake evaporation. This has become a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a remote sensing calculation method for evaporation of plateau lakes that considers topography and the thermal storage effect of water bodies. This method enables remote sensing estimation of evaporation in plateau lakes, effectively improving work efficiency and estimation accuracy.

[0005] To achieve the above technology, the specific steps are as follows: S1. Acquire remote sensing image data of the target area, lake surface water temperature data, meteorological dataset, and digital elevation model (DEM) dataset, and perform preprocessing operations on the acquired data; The objects to be preprocessed are: remote sensing image datasets and lake surface water temperature data. The methods include: Preprocessing of the MODIS remote sensing image dataset: The MODIS remote sensing image dataset includes MOD03, MOD35, MOD43, and MOD11 products. First, the image information of the MODIS dataset is extracted, and the .hdf format image data of MODIS is converted to .tif format using HEG software. Second, the quality control of the remote sensing images is carried out through visual interpretation and MOD35 cloud mask data, removing images with cloud cover greater than 20%, and radiometric calibration and cropping of the remote sensing images are performed. Preprocessing of lake surface water temperature data (Lakes_cci): Using Python, the .nc format data of Lakes_cci is converted into .tif format image data. After projection transformation, resampling and cropping of the images, they are matched with MODIS image data. Preprocessing of meteorological data: First, use Python to convert meteorological data into .tif format image data; second, use ArcGIS 10.7 to perform projection transformation, bilinear resampling, and cropping on the .tif format image data to match MODIS imagery.

[0006] S2. Obtain terrain parameters, surface parameters, and auxiliary data for the target area; Topographic parameters include: slope, aspect, sky visibility factor (SVF), and terrain configuration factor (TCF). Slope and aspect are calculated using ArcGIS 10.7 spatial analysis tools based on a Digital Elevation Model (DEM) dataset. The SVF and TCF are calculated using Matlab programming, followed by resampling to generate data matching the MODIS imagery. The expressions are as follows: In the formula, Indicates the search direction, where, An index indicating the search direction; Indicates the vertical elevation angle; Surface parameters include: lake albedo Lake water surface temperature Atmospheric transmittance Lake emission rate air emissivity Extinction coefficient of lake water ; Lake surface temperature Obtained by Lakes_cci; Lake albedo Obtained from the MOD43 dataset, the expression is as follows: In the formula, and These represent the albedo values ​​for white and black sky, respectively, obtained from the Albedo BSA shortwave and Albedo WSA shortwave bands of the MOD43 dataset. This represents the proportion of actual diffuse light reflected from the sky. Atmospheric transmittance The expression is as follows: In the formula, Indicates cloud transmittance; Indicates water vapor transmission rate; Indicates gas permeability; Indicates Rayleigh scattering transmittance; This represents the aerosol permeability; 0.013 is used as an empirical correction term to avoid negative values. Lake emission rate The expression is as follows: In the formula, Indicates the albedo of a lake; air emissivity The expression is as follows: In the formula, Indicates the cloud scaling factor; Indicates the actual water vapor pressure; Indicates air temperature; Extinction coefficient of lake water Based on experimental observations; The auxiliary data include: solar zenith angle SZA, observed zenith angle VZA, average lake depth d, lake surface area A, number of lake layers and depth of each layer; in this invention, the solar zenith angle SZA and observed zenith angle VZA are obtained from the MOD03 dataset; the average lake depth d is obtained from HydroLAKES; the lake surface area A is obtained from the Google Earth Engine (GEE) platform JRC Global Surface Water Mapping Layers, v1.4 dataset.

[0007] S3. Using the parametric radiative transfer model and preprocessed remote sensing image data, calculate the downflow shortwave radiation, upflow longwave radiation, downflow longwave radiation and net radiation of the plateau lake surface, taking into account the effect of adjacent topography. The steps include: S3.1. Based on the radiative transfer model coupled with topographic factors, a downwave shortwave radiation estimation model for plateau lakes is constructed to calculate the downwave shortwave radiation of plateau lakes. The expression is as follows: In the formula, SR dir Indicates direct solar radiation; SR dif Indicates scattered radiation from the sky; SR ref This indicates the radiation reflected by the surrounding terrain; S3.2 Calculate the uplink longwave radiation using the lake's emissivity and surface temperature, as shown in the following expression: In the formula, Indicates the lake's emission rate; It is the Stephen-Boltzmann constant; Indicates the surface temperature of the lake; S3.3 Calculate the downward longwave radiation using atmospheric emissivity and air temperature, as shown in the following expression: In the formula, This indicates long-wave downward radiation on a flat surface; Indicates air emissivity; Indicates air temperature; Indicates downlink longwave radiation; This represents the upward longwave radiation reflected by the surrounding terrain; S3.4. Based on the downlink shortwave radiation estimation model, uplink longwave radiation, and downlink longwave radiation, calculate the net radiation at the lake surface, as shown in the following expression: .

[0008] S4. Using the one-dimensional heat transfer equation (Hoster model) and the lake surface temperature, downflow shortwave radiation, upflow longwave radiation, downflow longwave radiation, and lake physical parameters, the water temperature at different depths of the lake is calculated, as shown in the following expression: In the formula, This represents the lake surface temperature, which is greater than 0 in this embodiment, so lake freezing is not considered. Indicates the molecular diffusion coefficient; Indicates the wind-driven eddy diffusion coefficient; Indicates the enhanced diffusion coefficient; Indicates the specific heat capacity of water; Indicates the current time; The term representing the solar shortwave heat source absorbed by the water body; This indicates the depth from the water surface to the target layer.

[0009] S5. Calculate the water body heat storage flux using the water temperature at different depths calculated in S4, as shown in the following expression: In the formula, This indicates the specific heat capacity of water, expressed in J / (kg·K). The density of the water is represented by a value of 1000 kg / m³. 3 ; This indicates the number of water depth layers, set to 11. Indicates the first The temperature difference between the top and bottom layers of the water; Indicates the first The depth of the layer.

[0010] S6. Calculate the lake evaporation rate using the calculated net radiation, water body heat flux, and meteorological data. The expression is as follows: In the formula, The slope representing the saturated water vapor pressure versus air temperature; Represents the wet-bulb and dry-bulb constants; Indicates corrected net radiation; G Indicates the heat flux stored in the water body; Represent the wind profile equation; Indicates saturated water vapor pressure, This indicates the actual water vapor pressure.

[0011] S7. Using the lake evaporation rate calculated in S6 and the lake surface area obtained in S2, the evaporation of plateau lakes is calculated, as shown in the following expression: In the formula, For lake evaporation, The surface area of ​​the lake.

[0012] Beneficial effects of the present invention This invention solves the problem that existing lake evaporation models are difficult to accurately calculate the heat storage flux of water bodies. At the same time, it considers the influence of the adjacent topography on the evaporation of plateau lakes, expands the applicability of remote sensing evaporation models to plateau lakes, and improves the accuracy and efficiency of remote sensing estimation of evaporation in plateau lakes. Attached Figure Description

[0013] Figure 1 This is a flowchart illustrating an embodiment of a remote sensing estimation method for evaporation in plateau lakes according to the present invention. Detailed Implementation

[0014] The present invention will be further described in detail below with reference to specific embodiments.

[0015] like Figure 1 As shown, a remote sensing calculation method for evaporation of plateau lakes considering topography and water body thermal storage effects is presented, with the following steps: S1. Acquire remote sensing image data of the target area, lake surface water temperature data, meteorological dataset, and digital elevation model (DEM) dataset, and perform preprocessing operations on the acquired data; In this invention, the target area is Erhai Lake in Dali Prefecture, Yunnan Province, China; In this embodiment, the remote sensing image data of the target area is obtained as follows: the remote sensing image data (MODIS) dataset used is downloaded from NASA (https: / / ladsweb.modaps.eosdis.nasa.gov / ), with a spatial variability of 1000m; In this embodiment, the surface water temperature data of the target lake was downloaded from the European Space Agency's Climate Change Initiative (Lakes_cci) project (https: / / data.ceda.ac.uk / neodc / esacci / lakes / data / lake_products / L3S / v2.1 / ), with a spatial resolution of 1000m and a temporal variability of 1 day; In this embodiment, the meteorological dataset for the target area is obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF), with a data download address (https: / / cds.climate.copernicus.eu / ), a spatial variability of 0.1°, and a temporal resolution of 1 day. In this embodiment, the digital elevation model (DEM) dataset of the target area is obtained by using ASTER GDEM data (https: / / www.gscloud.cn / sources / index?pid=263) published by the China Geospatial Data Cloud Platform, with a spatial resolution of 30m; The objects to be preprocessed are: remote sensing image datasets and lake surface water temperature data. The methods include: Preprocessing of the MODIS remote sensing image dataset: The MODIS remote sensing image dataset includes MOD03, MOD35, MOD43, and MOD11 products. First, the image information of the MODIS dataset is extracted, and the .hdf format image data of MODIS is converted to .tif format using HEG software. Second, the quality control of the remote sensing images is carried out through visual interpretation and MOD35 cloud mask data, removing images with cloud cover greater than 20%, and radiometric calibration and cropping of the remote sensing images are performed. Preprocessing of lake surface water temperature data (Lakes_cci): Using Python, the .nc format data of Lakes_cci is converted into .tif format image data. After projection transformation, resampling and cropping of the images, they are matched with MODIS image data. The meteorological data was preprocessed as follows: First, the meteorological data was converted into .tif format image data using Python; second, ArcGIS 10.7 was used to perform projection transformation, bilinear resampling, and cropping on the .tif format image data to match the MODIS image. In this embodiment, Erhai Lake in Dali Prefecture, Yunnan Province, China was selected as the study area, with 287 images from 2010 to 2021 as the study period, as the basic data, to estimate the evaporation of Erhai Lake.

[0016] S2. Obtain terrain parameters, surface parameters, and auxiliary data for the target area; Topographic parameters include: slope, aspect, sky visibility factor (SVF), and terrain configuration factor (TCF). Slope and aspect are calculated using ArcGIS 10.7 spatial analysis tools based on a Digital Elevation Model (DEM) dataset. The SVF and TCF are calculated using Matlab programming, followed by resampling to generate data matching the MODIS imagery. The expressions are as follows: In the formula, Indicates the search direction; in this embodiment, ,in, An index indicating the search direction; Indicates the vertical elevation angle; Surface parameters include: lake albedo Lake water surface temperature Atmospheric transmittance Lake emission rate air emissivity Extinction coefficient of lake water ; Lake surface temperature Obtained by Lakes_cci; Lake albedo Obtained from the MOD43 dataset, the expression is as follows: In the formula, and These represent the albedo values ​​for white and black sky, respectively, obtained from the Albedo BSA shortwave and Albedo WSA shortwave bands of the MOD43 dataset. The proportion of actual diffuse light from the sky is expressed as follows: In the formula, The solar zenith angle at noon is represented by the SZA product of MOD03 in this invention. Atmospheric transmittance The expression is as follows: In the formula, Indicates cloud transmittance; Indicates water vapor transmission rate; Indicates gas permeability; Indicates Rayleigh scattering transmittance; This represents the aerosol permeability; 0.013 is used as an empirical correction term to avoid negative values. Lake emission rate The expression is as follows: In the formula, Indicates the albedo of a lake; air emissivity The expression is as follows: In the formula, Indicates the cloud scaling factor; Indicates the actual water vapor pressure; Indicates air temperature; Extinction coefficient of lake water Based on experimental observations, the extinction coefficient of Erhai Lake was set. The value is 2.64m; The auxiliary data includes: solar zenith angle (SZA), observed zenith angle (VZA), average lake depth (d), lake surface area (A), number of lake layers, and depth of each layer. In this invention, the solar zenith angle (SZA) and observed zenith angle (VZA) were obtained from the MOD03 dataset; the average lake depth (d) was obtained from HydroLAKES, which can be downloaded from https: / / www.hydrosheds.org / products / hydrolakes; and the lake surface area (A) was obtained from the Google Earth Engine (GEE) platform JRC GlobalSurface Water Mapping. Layers, v1.4 dataset acquisition; In this invention, the average depth of Erhai Lake is 10m, and Erhai Lake is divided into 11 layers according to depth, namely 0.1, 0.6, 1.2, 1.8, 2.4, 3.0, 3.6, 4.2, 4.8, 5.4, and 6.0, in units (m). The initial depth is 0.1m, and each layer is divided into layers with a depth of 0.6m. The depths of the middle layers of each layer are 0.35, 0.9, 1.5, 2.1, 2.7, 3.3, 3.9, 4.5, 5.1, and 5.7, in units (m).

[0017] The characteristics, sources, and descriptions of the data parameters are shown in Table 1. Table 1: Parameter characteristics and their descriptions S3. Using the parametric radiative transfer model and preprocessed remote sensing image data, calculate the downflow shortwave radiation, upflow longwave radiation, downflow longwave radiation and net radiation of the plateau lake surface, taking into account the effect of adjacent topography. The steps include: S3.1. Based on the radiative transfer model coupled with topographic factors, a downwave shortwave radiation estimation model for plateau lakes is constructed to calculate the downwave shortwave radiation of plateau lakes. The expression is as follows: In the formula, SR dir Indicates direct solar radiation; SR dif Indicates scattered radiation from the sky; SR ref Represents the radiation reflected by the surrounding terrain; the expressions for direct solar radiation, sky-scattered radiation, and radiation reflected by the surrounding terrain are as follows: In the formula, This represents solar radiation at the top of the atmosphere; This represents the local angle of incidence, which is the angle between the normal to the slope and the incident sunlight. This represents the downward shortwave radiation on the horizontal plane. S3.2 Calculate the uplink longwave radiation using the lake's emissivity and surface temperature, as shown in the following expression: In the formula, Indicates the lake's emission rate; It is the Stephen-Boltzmann constant; Indicates the surface temperature of the lake; S3.3 Calculate the downward longwave radiation using atmospheric emissivity and air temperature, as shown in the following expression: In the formula, This indicates long-wave downward radiation on a flat surface; Indicates air emissivity; Indicates air temperature; Indicates downlink longwave radiation; The expression representing the upward longwave radiation reflected by the surrounding terrain is as follows: In the formula, and These represent the average surface emissivity and average surface temperature within a 3km radius centered on the target pixel, respectively. S3.4. Based on the downlink shortwave radiation estimation model, uplink longwave radiation, and downlink longwave radiation, calculate the net radiation at the lake surface, as shown in the following expression: .

[0018] S4. Using the one-dimensional heat transfer equation (Hoster model) and the lake surface temperature, downflow shortwave radiation, upflow longwave radiation, downflow longwave radiation, and lake physical parameters, the water temperature at different depths of the lake is calculated, as shown in the following expression: In the formula, This represents the lake surface temperature, which is greater than 0 in this embodiment, so lake freezing is not considered. Indicates the molecular diffusion coefficient; Indicates the wind-driven eddy diffusion coefficient; Indicates the enhanced diffusion coefficient; Indicates the specific heat capacity of water; Indicates the current time; The term representing the solar shortwave heat source absorbed by the water body; This represents the depth from the water surface to the target layer; the expressions for the molecular diffusion coefficient, wind-driven eddy diffusion coefficient, enhanced diffusion coefficient, and the solar shortwave heat source term absorbed by the water body are as follows: In the formula, This represents the Karman constant, which is 0.41 in this invention; Indicates friction speed; Indicates the current water depth; This indicates the value of Prandtl's constant; in this invention, it is set to 1. Indicates the attenuation coefficient; Represents Richardson's number; Indicates the buoyancy frequency; This indicates the proportion of shortwave waves that are assumed to be absorbed at a depth of 0.6 m in the upper part of the lake, set to 0.4. This represents the extinction coefficient of the lake water, which is related to the lake depth and is set to 0.45.

[0019] S5. Calculate the water body heat storage flux using the water temperature at different depths calculated in S4, as shown in the following expression: In the formula, This indicates the specific heat capacity of water, expressed in J / (kg·K). The density of the water is represented by a value of 1000 kg / m³. 3 ; This indicates the number of water depth layers, set to 11. Indicates the first The temperature difference between the top and bottom layers of the water; Indicates the first The depth of the layer.

[0020] S6. Calculate the lake evaporation rate using the calculated net radiation, water body heat flux, and meteorological data. The expression is as follows: In the formula, The slope representing the saturated water vapor pressure versus air temperature; Represents the wet-bulb and dry-bulb constants; Indicates corrected net radiation; G Indicates the heat flux stored in the water body; Represent the wind profile equation; Indicates saturated water vapor pressure, This indicates the actual water vapor pressure.

[0021] S7. Using the lake evaporation rate calculated in S6 and the lake surface area obtained in S2, the evaporation of plateau lakes is calculated, as shown in the following expression: In the formula, For lake evaporation, The surface area of ​​the lake.

[0022] Therefore, this invention solves the problem that existing lake evaporation models are difficult to accurately calculate the heat storage flux of water bodies. At the same time, it considers the influence of the adjacent topography on the evaporation of plateau lakes, expands the applicability of remote sensing evaporation models to plateau lakes, and improves the accuracy and efficiency of remote sensing estimation of evaporation in plateau lakes.

[0023] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A remote sensing calculation method for evaporation of plateau lakes considering topography and water body thermal storage effects, characterized in that, Includes the following steps: S1. Acquire remote sensing image data of the target area, lake surface water temperature data, meteorological dataset, and digital elevation model dataset, and perform preprocessing operations on the acquired data; S2. Obtain terrain parameters, surface parameters, and auxiliary data for the target area; The terrain parameters include: Slope, Aspect, Sky Visibility Factor (SVF), and Terrain Configuration Factor (TCF). The surface parameters include: lake albedo. Lake water surface temperature Atmospheric transmittance Lake emission rate air emissivity Extinction coefficient of lake water ; The auxiliary data include: solar zenith angle SZA, observed zenith angle VZA, average lake depth d, lake surface area A, number of lake layers and depth of each layer; S3. Using a parametric radiative transfer model and preprocessed remote sensing image data, calculate the downflow shortwave radiation, upflow longwave radiation, downflow longwave radiation, and net radiation of the plateau lake surface, taking into account the effects of adjacent topography. Specific steps include: S3.

1. Based on the radiative transfer model coupled with topographic factors, a downwave shortwave radiation estimation model for plateau lakes is constructed to calculate the downwave shortwave radiation of plateau lakes. The expression is as follows: In the formula, SR dir Indicates direct solar radiation; SR dif Indicates scattered radiation from the sky; SR ref This indicates the radiation reflected by the surrounding terrain; S3.2 Calculate the uplink longwave radiation using the lake's emissivity and surface temperature, as shown in the following expression: In the formula, Indicates the lake's emission rate; It is the Stephen-Boltzmann constant; Indicates the surface temperature of the lake; S3.3 Calculate the downward longwave radiation using atmospheric emissivity and air temperature, as shown in the following expression: In the formula, This indicates long-wave downward radiation on a flat surface; Indicates air emissivity; Indicates air temperature; Indicates downlink longwave radiation; This represents the upward longwave radiation reflected by the surrounding terrain; S3.

4. Based on the downlink shortwave radiation estimation model, uplink longwave radiation, and downlink longwave radiation, calculate the net radiation at the lake surface, as shown in the following expression: ； S4. Using the one-dimensional heat transfer equation and the lake surface temperature, downflow shortwave radiation, upflow longwave radiation, downflow longwave radiation, and lake physical parameters, calculate the water temperature at different depths of the lake. The expression is as follows: In the formula, This represents the lake's surface temperature, with a value greater than 0, so lake freezing is not considered. Indicates the molecular diffusion coefficient; Indicates the wind-driven eddy diffusion coefficient; Indicates the enhanced diffusion coefficient; Indicates the specific heat capacity of water; Indicates the current time; The term representing the solar shortwave heat source absorbed by the water body; Indicates the depth from the water surface to the target layer; S5. Calculate the water body heat storage flux using the water body temperature at different depths calculated in S4. S6. Calculate the lake evaporation rate using the calculated net radiation, water body heat flux, and meteorological data; S7. Using the lake evaporation rate calculated in S6 and the lake surface area obtained in S2, calculate the evaporation of the plateau lakes to complete the calculation.

2. The remote sensing calculation method for evaporation of plateau lakes considering topography and water body thermal storage effects according to claim 1, characterized in that, The expression for calculating the water body heat storage flux using the water temperature at different depth layers calculated by S4 is as follows: In the formula, This indicates the specific heat capacity of water, expressed in J / (kg·K). Indicates the density of water; This indicates the number of water depth layers, set to 11. Indicates the first The temperature difference between the top and bottom layers of the water; Indicates the first The depth of the layer.

3. The remote sensing calculation method for evaporation of plateau lakes considering topography and water body thermal storage effects according to claim 1, characterized in that, The expression for calculating the lake evaporation rate using calculated net radiation, water body heat flux, and meteorological data is as follows: In the formula, The slope representing the saturated water vapor pressure versus air temperature; Represents the wet-bulb and dry-bulb constants; Indicates corrected net radiation; G Indicates the heat flux stored in the water body; Represent the wind profile equation; Indicates saturated water vapor pressure, This indicates the actual water vapor pressure.

4. The remote sensing calculation method for evaporation of plateau lakes considering topography and water body thermal storage effects according to claim 1, characterized in that, The expression for calculating the evaporation of plateau lakes using the lake evaporation rate calculated in S6 and the lake surface area obtained in S2 is as follows: In the formula, For lake evaporation, The surface area of ​​the lake.

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