A method and system for calculating the impact of high temperature heat waves on lake dissolved oxygen

Abstract

The present invention discloses a method and system for calculating the intensity of the impact of high temperature heat waves on dissolved oxygen in lakes, and belongs to the field of hydrology, meteorology and ecological environment. It includes: integrating synchronous sample point pairs and establishing a dissolved oxygen estimation model; calculating the 90% quantile temperature of the climate state based on the reanalysis data, creating temperature heat wave event identification conditions, and using the temperature heat wave event identification conditions to identify temperature heat wave events; obtaining the actual observed temperature during the occurrence time of the temperature heat wave event and the climate state average temperature in the corresponding base year; using the dissolved oxygen estimation model to calculate the dissolved oxygen concentration at the heat wave temperature and the dissolved oxygen concentration at the climate state average temperature, and analyzing the dissolved oxygen concentration at the climate state average temperature and the heat wave temperature to obtain the intensity of the impact of high temperature heat waves on the dissolved oxygen concentration of lakes. The present invention comprehensively considers a variety of climate, water quality and geographical factors, and evaluates the comprehensive impact intensity of high temperature heat waves on the dissolved oxygen concentration of water bodies through systematic model analysis.

Description

Technical Field

[0001] The present invention belongs to the field of hydrology, meteorology and ecological environment, and in particular relates to a method and system for calculating the intensity of the impact of high temperature heat waves on dissolved oxygen in lakes. Background Art

[0002] Dissolved oxygen is an essential substance for aquatic organisms (such as fish, invertebrates, plankton, etc.) to carry out metabolic activities, respiration and energy conversion. The concentration of dissolved oxygen directly affects the growth, reproduction, distribution and species diversity of aquatic organisms, and is an important indicator for measuring the health of water bodies. With the intensification of global climate change, extreme climate events, especially high temperature heat waves, are becoming one of the important factors affecting aquatic ecosystems.

[0003] At present, although some progress has been made in the study of the impact of high temperature heat waves on dissolved oxygen concentration in water bodies, the following problems still exist:

[0004] 1. Limitations of the assessment method: Existing assessment methods often rely on a single temperature variable, ignoring the combined effects of other climate factors (hydrological and meteorological conditions, wind speed, precipitation, etc.) and water quality factors (such as water color, phytoplankton biomass, etc.) on dissolved oxygen.

[0005] 2. Lack of multi-scale comprehensive analysis: Existing studies are mostly limited to a single water body or region, and have failed to effectively carry out systematic assessments across regions and global scales, making it difficult to provide more widely applicable and reliable assessment methods.

[0006] 3. Difficulties in data collection and processing: Changes in dissolved oxygen during high temperature heat waves are affected by many factors. Traditional data collection methods often rely on point observations and lack sufficient consideration of the spatial heterogeneity and temporal dynamic changes of water bodies.

[0007] Therefore, a new method is urgently needed that can comprehensively consider multiple climate, water quality and geographical factors and evaluate the comprehensive impact of high temperature heat waves on dissolved oxygen concentration in water bodies through systematic model analysis. This method should be widely applicable around the world and provide a scientific basis for addressing the impact of high temperature heat waves on aquatic ecology. Summary of the invention

[0008] In order to solve the technical problems existing in the above-mentioned background technology, the present invention provides a method and system for calculating the intensity of the impact of high temperature heat waves on the dissolved oxygen in lakes.

[0009] The present invention adopts the following technical solution: a method for calculating the impact intensity of high temperature heat waves on lake dissolved oxygen, comprising the following steps:

[0010] Reanalysis data are obtained respectively, and the reanalysis data are integrated with geographic data, algal bloom index, and dissolved oxygen data to obtain synchronized sample point pairs; a hyperparameter grid is constructed through grid search, and a dissolved oxygen estimation model is established based on the hyperparameter grid;

[0011] Calculate the 90% quantile temperature of the climatological state based on the reanalysis data, create a temperature heat wave event identification condition, and use the temperature heat wave event identification condition to identify the temperature heat wave event; obtain the actual observed temperature during the time when the temperature heat wave event occurs and the climatological state average temperature in the corresponding base year;

[0012] The actual observed temperature and the synchronous sample point pair are used as input data and input into the dissolved oxygen estimation model to calculate the dissolved oxygen concentration at the heat wave temperature; the climatological average temperature and the sample point pair are used as input data and input into the dissolved oxygen estimation model to calculate the dissolved oxygen concentration at the climatological average temperature;

[0013] The intensity of the impact of high temperature heat waves on lake dissolved oxygen was obtained based on the dissolved oxygen concentration at the average temperature of the climate state and the dissolved oxygen concentration at the heat wave temperature.

[0014] In a further embodiment, the reanalysis data is daily reanalysis data, including at least: daily average temperature, daily average air pressure, daily total solar radiation, daily total thermal radiation intensity, daily total precipitation and daily average wind speed.

[0015] In a further embodiment, the geographic data includes at least: a digital elevation model DEM and an absolute latitude value.

[0016] In a further embodiment, the calculation formula of the algal bloom index is as follows:

[0017] ;

[0018] In the formula, is the algal bloom index, , and They are the remote sensing reflectance of the red, blue, and near-infrared bands of the Moderate Resolution Imaging Spectrometer, , and They are the band coefficients of the red, blue and near-infrared bands of the imaging spectrometer respectively.

[0019] In a further embodiment, the dissolved oxygen data is obtained by on-site in-situ measurement, that is, in-situ dissolved oxygen data; correspondingly, the acquisition process of the synchronous sample point pair is as follows:

[0020] The synchronization time interval between the dissolved oxygen data and the reanalysis data is defined as : ,in, is the pre-set time interval threshold related to the climate factor, in minutes;

[0021] The synchronization time interval between the dissolved oxygen data and the algal bloom index is defined as : ,in, It is the pre-set time interval threshold related to dissolved oxygen data, in hours;

[0022] For each set of dissolved oxygen data, the following steps are performed: the observation position of the dissolved oxygen data is set as the center point, a pixel window of a predetermined size is given, and the average value of the observation factor is calculated using the following formula: , and use the average as the matching value:

[0023] ; In the formula, are the pixel row index and column index of the observation factor, respectively. For the Row, No. The pixel value of the row;

[0024] Select the coefficient of variation within a pixel window of a predetermined size Less than 10% of the data is synchronized to obtain synchronized sample point pairs.

[0025] In a further embodiment, taking lakes as units, the calculation process of the 90% quantile temperature of the climatic state is as follows:

[0026] Collect maximum temperature data for each Julian day , Represents the Julian day, which ranges from 1 to 365 days; the maximum temperature data of the same Julian day within the specified year is Arrange and number them in order from low to high to get the temperature sequence set: ,in, is the number of the highest temperature data on the same Julian day within the specified year. represents the lowest temperature in the temperature series set, represents the highest temperature in the temperature series set;

[0027] Then, the 90% quantile temperature of the climate state It is expressed as:

[0028] ;in, is the 90% percentile temperature position.

[0029] In a further embodiment, the temperature heat wave event identification condition is expressed in the following form:

[0030] ;

[0031] Where S is the duration of the heat wave event, is the daily maximum temperature, is the 90% quantile temperature of the climate state, For a given duration.

[0032] In a further embodiment, the analysis process of the impact intensity of the high temperature heat wave on the dissolved oxygen in the lake includes:

[0033] The following formula is used to calculate the Difference in relative percentage of dissolved oxygen between days :

[0034] ;

[0035] In the formula, During the heat wave Dissolved oxygen concentration under heat wave temperature During the heat wave Dissolved oxygen concentration at the climatological mean temperature of the day;

[0036] Then, the impact intensity of high temperature heat waves on lake dissolved oxygen is expressed as :

[0037] , Indicates a heat wave event. Indicates the duration of the heat wave event.

[0038] In a further embodiment, the dissolved oxygen estimation model is a dissolved oxygen random forest estimation model.

[0039] A system for calculating the impact intensity of a high temperature heat wave on dissolved oxygen in a lake, used to implement the above-mentioned calculation method, comprising:

[0040] The first module is configured to obtain reanalysis data respectively, integrate the reanalysis data with geographic data, algal bloom index, and dissolved oxygen data to obtain synchronized sample point pairs; construct a hyperparameter grid through grid search, and establish a dissolved oxygen estimation model based on the hyperparameter grid;

[0041] The second module is configured to calculate the 90% quantile temperature of the climatological state based on the reanalysis data, create a temperature heat wave event identification condition, and use the temperature heat wave event identification condition to identify the temperature heat wave event; obtain the actual observed temperature during the occurrence time of the temperature heat wave event and the climatological state average temperature in the corresponding base year;

[0042] The third module is configured to input the actual observed temperature and the synchronous sample point pair as input data into the dissolved oxygen estimation model to calculate the dissolved oxygen concentration at the heat wave temperature; input the climatological average temperature and the sample point pair as input data into the dissolved oxygen estimation model to calculate the dissolved oxygen concentration at the climatological average temperature;

[0043] The fourth module is configured to obtain the intensity of the impact of high temperature heat waves on lake dissolved oxygen by analyzing the dissolved oxygen concentration under the average temperature of the climate state and the dissolved oxygen concentration under the heat wave temperature.

[0044] Beneficial effects of the present invention: The present invention integrates daily reanalysis data (including daily average temperature, air pressure, radiation, precipitation, wind speed, etc.) with geographic data (such as digital elevation model DEM and absolute latitude value), algal bloom index, and dissolved oxygen data to construct synchronous sample point pairs. This fusion of multi-dimensional data comprehensively considers the various factors affecting lake dissolved oxygen, making subsequent analysis and calculation more scientific and accurate, and can truly reflect the complex relationship between lake dissolved oxygen and external environmental factors.

[0045] By inputting the actual observed temperature, the average temperature of the climatological state and the corresponding sample points into the dissolved oxygen estimation model, the dissolved oxygen concentration under different temperature conditions is calculated, and then the intensity of the impact of high temperature heat waves on lake dissolved oxygen is obtained. This comparative analysis method can intuitively and accurately quantify the impact of high temperature heat waves on lake dissolved oxygen, providing reliable data support for lake ecological research, water resources management, etc.

[0046] In summary, this paper takes into account a variety of climate, water quality and geographical factors, and evaluates the comprehensive impact of high temperature heat waves on dissolved oxygen concentration in water bodies through systematic model analysis. This method should be widely applicable around the world and provide a scientific basis for addressing the impact of high temperature heat waves on aquatic ecology. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a model diagram for estimating lake dissolved oxygen in Example 1 of the present invention.

[0048] Figure 2 This is a definition diagram of a high temperature heat wave in Example 1 of the present invention. DETAILED DESCRIPTION

[0049] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0050] Example 1

[0051] This embodiment aims to solve the deficiencies in the prior art and provides a method for calculating the impact intensity of high temperature heat waves on lake dissolved oxygen by combining meteorological, water quality and geographical factors, including the following steps:

[0052] Reanalysis data are obtained respectively, and the reanalysis data are integrated with geographic data, algal bloom index, and dissolved oxygen data to obtain synchronized sample point pairs; a hyperparameter grid is constructed through grid search, and a dissolved oxygen estimation model is established based on the hyperparameter grid;

[0053] Calculate the 90% quantile temperature of the climatological state based on the reanalysis data, create a temperature heat wave event identification condition, and use the temperature heat wave event identification condition to identify the temperature heat wave event; obtain the actual observed temperature during the time when the temperature heat wave event occurs and the climatological state average temperature in the corresponding base year;

[0054] The actual observed temperature and the synchronous sample point pair are used as input data and input into the dissolved oxygen estimation model to calculate the dissolved oxygen concentration at the heat wave temperature; the climatological average temperature and the sample point pair are used as input data and input into the dissolved oxygen estimation model to calculate the dissolved oxygen concentration at the climatological average temperature;

[0055] The intensity of the impact of high temperature heat waves on lake dissolved oxygen was obtained based on the dissolved oxygen concentration at the average temperature of the climate state and the dissolved oxygen concentration at the heat wave temperature.

[0056] In a further embodiment, the reanalysis data is daily reanalysis data, including: daily average temperature, daily average air pressure, daily total solar radiation, daily total thermal radiation intensity, daily total precipitation and daily average wind speed. The reanalysis data in this embodiment can be reflected by corresponding images.

[0057] For the average daily temperature, the daily average temperature data is obtained through a professional meteorological data platform. This data is based on a day as the time scale and accurately reflects the average condition of the atmospheric temperature. In the study of high temperature heat waves, the average daily temperature is the primary indicator of concern. When constructing the identification conditions for temperature heat wave events, the average daily temperature is compared with the 90% percentile temperature of the climate state. If the average daily temperature for many consecutive days is higher than the percentile temperature, it is determined to have entered a high temperature heat wave period. This directly determines the time range for studying the impact of high temperature heat waves on lake dissolved oxygen.

[0058] The daily average air pressure also comes from an authoritative meteorological data platform. In practical applications, when the air pressure rises, the pressure of the atmosphere on the water body increases, making oxygen more easily dissolved in the water body, promoting the replenishment of dissolved oxygen in the lake. On the contrary, a decrease in air pressure may inhibit the dissolution process of oxygen. When analyzing the dynamic changes of dissolved oxygen in lakes, the fluctuations of the daily average air pressure will be correlated with the changes in dissolved oxygen concentration to clarify its specific impact mechanism on dissolved oxygen.

[0059] The daily total solar radiation and daily total thermal radiation intensity can be obtained and calibrated through satellite remote sensing data combined with data from ground observation stations. Solar radiation is an important source of energy for lake water bodies. Strong solar radiation will increase the temperature of lake water and reduce the solubility of dissolved oxygen in water. At the same time, solar radiation provides energy for the photosynthesis of algae and other plankton. During periods of abundant sunshine, algae reproduce in large numbers, produce a large amount of oxygen through photosynthesis, and increase the dissolved oxygen content of the lake. By long-term monitoring of the changes in daily total solar radiation, daily total thermal radiation intensity and lake dissolved oxygen concentration, a quantitative relationship model between them is established.

[0060] There are various ways to obtain daily total precipitation data, including measured data from weather stations and inversion data from meteorological satellites. In the embodiments, the applicant found that when a large amount of precipitation occurs, on the one hand, the lake water is diluted, the salinity is reduced, and the concentration of nutrients also changes, which may affect the growth of microorganisms and algae in the water, and thus indirectly affect the production and consumption of dissolved oxygen. On the other hand, during precipitation, raindrops are in full contact with the atmosphere, carrying a certain amount of oxygen into the lake, which directly increases the dissolved oxygen content of the lake. By analyzing the changes in dissolved oxygen in the lake under different precipitation intensities and durations, the comprehensive impact of daily total precipitation on dissolved oxygen in the lake is evaluated.

[0061] The daily average wind speed data can be measured by the wind speed sensor of the ground meteorological station. In the lake ecosystem, the daily average wind speed plays an important physical regulation role. When the wind speed is high, large waves are generated on the lake surface, which promotes the mixing and convection of the lake water. The oxygen-rich water on the surface is fully exchanged with the water with low oxygen content in the bottom layer, making the overall dissolved oxygen distribution of the lake more uniform. By measuring the dissolved oxygen concentration at different depths of the lake under different wind speed conditions, the relationship between the daily average wind speed and the vertical distribution of dissolved oxygen in the lake is analyzed.

[0062] During the implementation of the present invention, the above-mentioned daily reanalysis data are organically integrated with geographic data, algal bloom index, and dissolved oxygen data to form synchronous sample point pairs, which provide a solid data foundation for the subsequent establishment of an accurate dissolved oxygen estimation model and in-depth analysis of the impact of high temperature heat waves on lake dissolved oxygen.

[0063] Correspondingly, the geographic data at least includes: a digital elevation model DEM and an absolute latitude value. The digital elevation model DEM is mainly obtained by scanning and mapping the earth's surface using a satellite equipped with a high-precision radar altimeter by means of aerospace remote sensing, thereby obtaining high-precision terrain data.

[0064] In the study of lake dissolved oxygen, DEM data can directly reflect the topographic and geomorphic features around the lake. For example, if there are high mountains or canyon terrain around the lake, a unique local climate will be formed during the movement of air flow. Valley terrain may lead to poor air circulation, causing heat waves to accumulate locally, affecting the temperature distribution around the lake, and then affecting the temperature and dissolved oxygen distribution of the lake water body. On the other hand, the ups and downs of the terrain will also affect the catchment area and water flow direction of the lake. When precipitation occurs, the surface runoff speed and direction under different terrain conditions are different, and the amount and location of the sediment, nutrients, etc. carried into the lake are also different, which has an indirect impact on the growth environment of algae in the lake and the production and consumption of dissolved oxygen. By combining DEM data with daily reanalysis data and dissolved oxygen data, the changing patterns of lake dissolved oxygen under different terrain conditions are analyzed.

[0065] The absolute latitude value can be obtained through the satellite positioning system and the geographic information system (GIS). In the global climate system, latitude is one of the key factors that determine the amount of solar radiation and the distribution of heat waves. Different absolute latitude values ​​mean that the angles and durations at which lakes receive solar radiation are different. Lakes located in low-latitude areas receive relatively more solar radiation throughout the year, the lake water temperature is relatively high, and the solubility of dissolved oxygen in the water is low. At the same time, sufficient light is also conducive to the reproduction of algae, resulting in a large amount of dissolved oxygen produced in the lake. Lakes in high-latitude areas have relatively less solar radiation, lower lake water temperature, and relatively higher dissolved oxygen solubility, but algae growth is limited by light and temperature, and the amount of dissolved oxygen produced is relatively small. By comparing the relevant data of lakes at different latitudes, the relationship between absolute latitude values ​​and lake dissolved oxygen is deeply studied.

[0066] Based on the above description, the calculation formula of the algal bloom index is as follows:

[0067] ;

[0068] In the formula, is the algal bloom index, , and They are the remote sensing reflectance of the red, blue, and near-infrared bands of the Moderate Resolution Imaging Spectrometer, , and They are the band coefficients of the red, blue and near-infrared bands of the imaging spectrometer respectively.

[0069] The algal bloom index of this embodiment not only includes the red light band and near-infrared band commonly used in conventional algal bloom indices (such as NDVI and FAI), but also takes into account the blue light band. The blue light band is a key band absorbed by phytoplankton in the water body, especially in the process of photosynthesis, algae have a strong absorption capacity for blue light. By measuring the reflectivity of the blue light band, the content and activity of algae in the water body can be more accurately reflected, thereby improving the sensitivity and accuracy of the occurrence of algal blooms.

[0070] In a further embodiment, , , , so the calculation formula of the algal bloom index is further expressed as:

[0071] .

[0072] Furthermore, the dissolved oxygen data are obtained by in-situ measurements using a calibrated optical dissolved oxygen meter. The dissolved oxygen observations from the mixed layer or deep water (depth > 1 m) are excluded, and only the observations from the surface water (depth ≤ 1 m) are retained, which are the in-situ dissolved oxygen data; correspondingly, the acquisition process of the synchronous sample point pair is as follows:

[0073] The synchronization time interval between the dissolved oxygen data and the reanalysis data is defined as : ,in, is a preset time interval threshold value related to the climate factor, in minutes; in a further embodiment, The value is 1 hour.

[0074] The synchronization time interval between the dissolved oxygen data and the algal bloom index is defined as : ,in, is a preset time interval threshold value related to dissolved oxygen data, in hours; in this embodiment, The value of is 1 day.

[0075] For each set of dissolved oxygen data, the following steps are performed: the observation position of the dissolved oxygen data is set as the center point, a pixel window of a predetermined size is given, and the average value of the observation factor is calculated using the following formula: , and use the average as the matching value:

[0076] ;

[0077] In the formula, are the pixel row index and column index of the observation factor, respectively. For the Row, No. The observation factors in this embodiment include: meteorological factors, terrain factors and water quality factors.

[0078] Conventional methods only select the center pixel as the matching sample point. The single center pixel may be affected by local outliers or noise, resulting in unstable matching results. This embodiment can take into account the environmental factors of the surrounding area by calculating the average value of dissolved oxygen data within a pixel window of a predetermined size, avoiding the limitation of relying only on a single center pixel. This helps to more accurately reflect the real situation around the observation point and improves the representativeness of the data.

[0079] Data with a coefficient of variation less than 10% within a pixel window of a predetermined size are selected for synchronization to obtain synchronized sample point pairs.

[0080] Furthermore, the coefficient of variation The calculation formula is as follows: .

[0081] Combined with the above description, geographic factors are static data and remain unchanged over time, so the corresponding synchronization time interval has not been set yet.

[0082] In another embodiment, taking lakes as units, the calculation process of the climatic state 90% quantile temperature is as follows:

[0083] Collect maximum temperature data for each Julian day , Represents the Julian day, which ranges from 1 to 365 days; it returns the highest temperature data on the same Julian day within a specified period of time (such as 30 years). Arrange and number them in order from low to high to get the temperature sequence set: ,in, is the number of the highest temperature data on the same Julian day within the specified year. represents the lowest temperature in the temperature series set, represents the highest temperature in the temperature series set;

[0084] Then, the 90% quantile temperature of the climate state It is expressed as:

[0085] ;in, 90% percentile temperature position.

[0086] It should be noted that this is a timekeeping method that uses consecutive days in the Julian cycle to calculate time. Combined with the above settings, the temperature heat wave event identification condition is expressed in the following form:

[0087] ;

[0088] Where S is the duration of the heat wave event, is the daily maximum temperature, is the 90% quantile temperature of the climate state, For a given duration, such as The value is 5 days.

[0089] In other words, an atmospheric heat wave event must meet the following criteria at the same time: 1) During the duration S of the heat wave event, the maximum temperature data for each day All exceeded the 90% percentile temperature of the climate state on the corresponding date ; 2) Continuously exceeds the 90th percentile temperature of the climate state The duration of the heat wave event S must be greater than or equal to m (e.g. 5 days), combined with Figure 2 .

[0090] Furthermore, the analysis process of the impact intensity of the high temperature heat wave on lake dissolved oxygen includes:

[0091] The following formula is used to calculate the Difference in relative percentage of dissolved oxygen between days :

[0092] ;

[0093] In the formula, is the dissolved oxygen concentration at the heat wave temperature on the kth day during the heat wave, is the dissolved oxygen concentration at the climatological mean temperature on the kth day during the heat wave;

[0094] Then, the impact intensity of high temperature heat waves on lake dissolved oxygen is expressed as :

[0095] , Indicates a heat wave event. Duration of heat wave events.

[0096] It is worth mentioning that Figure 1, the dissolved oxygen estimation model in this embodiment is a dissolved oxygen random forest estimation model. The random forest model is an integrated learning method that predicts dissolved oxygen by constructing multiple decision trees. First, the data set is divided into multiple subsets, each of which is extracted from the original data by sampling with replacement, so that each tree is trained on a different subset of the data. Secondly, in the construction process of each decision tree, the random forest does not consider all features, but randomly selects a subset from all features for splitting. In this way, the diversity of each tree is ensured and overfitting is avoided. After the training is completed, the prediction results of each tree for dissolved oxygen concentration will be calculated independently. Finally, the dissolved oxygen prediction results of all trees are voted (classification task) or averaged (regression task) to obtain the final prediction value of dissolved oxygen of the random forest.

[0097] Example 2

[0098] This embodiment is to implement the calculation method of the impact intensity of high temperature heat waves on lake dissolved oxygen described in the embodiment, and discloses a calculation system of the impact intensity of high temperature heat waves on lake dissolved oxygen, including:

[0099] The first module is configured to obtain reanalysis data respectively, integrate the reanalysis data with geographic data, algal bloom index, and dissolved oxygen data to obtain synchronized sample point pairs; construct a hyperparameter grid through grid search, and establish a dissolved oxygen estimation model based on the hyperparameter grid;

[0100] The second module is configured to calculate the 90% quantile temperature of the climatological state based on the reanalysis data, create a temperature heat wave event identification condition, and use the temperature heat wave event identification condition to identify the temperature heat wave event; obtain the actual observed temperature during the occurrence time of the temperature heat wave event and the climatological state average temperature in the corresponding base year;

[0101] The third module is configured to input the actual observed temperature and the synchronous sample point pair as input data into the dissolved oxygen estimation model to calculate the dissolved oxygen concentration at the heat wave temperature; input the climatological average temperature and the sample point pair as input data into the dissolved oxygen estimation model to calculate the dissolved oxygen concentration at the climatological average temperature;

[0102] The fourth module is configured to obtain the intensity of the impact of high temperature heat waves on lake dissolved oxygen by analyzing the dissolved oxygen concentration under the average temperature of the climate state and the dissolved oxygen concentration under the heat wave temperature.

Claims

1. A method for calculating the impact of high temperature heat waves on dissolved oxygen in lakes, characterized in that: The following steps are involved: Reanalysis data were obtained separately, and the reanalysis data were integrated with geographic data, algal bloom index, and dissolved oxygen data to obtain synchronized sample point pairs; A hyperparameter grid is constructed through grid search, and a dissolved oxygen estimation model is established based on the hyperparameter grid; The reanalysis data are daily reanalysis data, including at least: daily average temperature, daily average air pressure, daily total solar radiation, daily total thermal radiation intensity, daily total precipitation and daily average wind speed; The dissolved oxygen data is obtained by on-site in-situ measurement, that is, in-situ dissolved oxygen data; the acquisition process of the synchronous sample point pair is as follows: Define the synchronization time interval between dissolved oxygen data and reanalysis data as : ,in, is the pre-set time interval threshold related to the climate factor, in minutes; Define the synchronization time interval between dissolved oxygen data and algal bloom index as : ,in, It is the pre-set time interval threshold related to dissolved oxygen data, in hours; For each set of dissolved oxygen data, the following steps are performed: the observation position of the dissolved oxygen data is set as the center point, a pixel window of a predetermined size is given, and the average value of the observation factor is calculated using the following formula: , and take the average as the matching value: ; In the formula, are the pixel row index and column index of the observation factor, respectively. For the Row, No. The pixel value of the row; Select the coefficient of variation within a pixel window of a predetermined size Less than 10% of the data is synchronized to obtain synchronized sample point pairs; Calculate the 90% quantile temperature of the climate state based on the reanalysis data, create the temperature heat wave event identification conditions, and use the temperature heat wave event identification conditions to identify the temperature heat wave events; obtain the actual observed temperature during the time when the temperature heat wave event occurs and the climate state average temperature in the corresponding base year; The actual observed temperature and the synchronous sample point pairs are used as input data to the dissolved oxygen estimation model to calculate the dissolved oxygen concentration at the heat wave temperature; the climatological average temperature and the sample point pairs are used as input data to the dissolved oxygen estimation model to calculate the dissolved oxygen concentration at the climatological average temperature; The intensity of the impact of high temperature heat waves on lake dissolved oxygen was obtained by analyzing the dissolved oxygen concentration at the average climatic temperature and the dissolved oxygen concentration at the heat wave temperature.

2. The method for calculating the impact intensity of a high temperature heat wave on dissolved oxygen in a lake according to claim 1, characterized in that: The geographic data at least includes: a digital elevation model DEM and an absolute latitude value.

3. The method for calculating the impact intensity of a high temperature heat wave on dissolved oxygen in a lake according to claim 1, characterized in that: The calculation formula of the algal bloom index is as follows: ； In the formula, is the algal bloom index, , and They are the remote sensing reflectance of the red, blue, and near-infrared bands of the Moderate Resolution Imaging Spectrometer, , and They are the band coefficients of the red, blue and near-infrared bands of the imaging spectrometer respectively.

4. The method for calculating the impact intensity of a high temperature heat wave on dissolved oxygen in a lake according to claim 1, characterized in that: Taking lake as unit, the calculation process of 90% quantile temperature of the climate state is as follows: Collect maximum temperature data for each Julian day , Indicates the Julian day, which ranges from 1 to 365 days; The maximum temperature data of the same Julian day within the specified year Arrange and number them in order from low to high to get the temperature sequence set: ;in, is the number of the highest temperature data on the same Julian day within the specified year. represents the lowest temperature in the temperature series set, represents the highest temperature in the temperature series set; Then, the 90% quantile temperature of the climate state It is expressed as: ;in, Indicates the 90% percentile temperature position.

5. The method for calculating the impact intensity of high temperature heat waves on lake dissolved oxygen according to claim 4 is characterized in that: The temperature heat wave event identification condition is expressed in the following form: ； Where S is the duration of the heat wave event, is the daily maximum temperature, is the 90% quantile temperature of the climate state, For a given duration.

6. The method for calculating the impact intensity of a high temperature heat wave on dissolved oxygen in a lake according to claim 1, characterized in that: The analysis process of the impact of high temperature heat waves on lake dissolved oxygen intensity includes: The following formula is used to calculate the The relative percentage difference of dissolved oxygen in the day : ； In the formula, During the heat wave Dissolved oxygen concentration under heat wave temperature During the heat wave Dissolved oxygen concentration at the climatological mean temperature of the day; Then, the impact intensity of high temperature heat waves on lake dissolved oxygen is expressed as : , Indicates a heat wave event. Indicates the duration of the heat wave event.

7. The method for calculating the impact intensity of a high temperature heat wave on dissolved oxygen in a lake according to claim 1, characterized in that: The dissolved oxygen estimation model is a dissolved oxygen random forest estimation model.

8. A system for calculating the impact of high temperature heat waves on dissolved oxygen in lakes, used to implement the calculation method according to any one of claims 1 to 7, characterized in that: include: The first module is configured to obtain reanalysis data respectively, and integrate the reanalysis data with geographic data, algal bloom index, and dissolved oxygen data to obtain synchronized sample point pairs; constructing a hyperparameter grid through grid search, and establishing a dissolved oxygen estimation model based on the hyperparameter grid; The reanalysis data is daily reanalysis data, including at least: daily average temperature, daily average air pressure, daily total solar radiation, daily total thermal radiation intensity, daily total precipitation and daily average wind speed; dissolved oxygen data is obtained by on-site in-situ measurement, that is, in-situ dissolved oxygen data; the acquisition process of synchronous sample pairs is as follows: Define the synchronization time interval between dissolved oxygen data and reanalysis data as : ,in, is the pre-set time interval threshold related to the climate factor, in minutes; Define the synchronization time interval between dissolved oxygen data and algal bloom index as : ,in, It is the pre-set time interval threshold related to dissolved oxygen data, in hours; For each set of dissolved oxygen data, the following steps are performed: the observation position of the dissolved oxygen data is set as the center point, a pixel window of a predetermined size is given, and the average value of the observation factor is calculated using the following formula: , and take the average as the matching value: ; In the formula, are the pixel row index and column index of the observation factor, respectively. For the Row, No. The pixel value of the row; Select the coefficient of variation within a pixel window of a predetermined size Less than 10% of the data is synchronized to obtain synchronized sample point pairs; The second module is configured to calculate the 90% quantile temperature of the climatological state based on the reanalysis data, create a temperature heat wave event identification condition, and use the temperature heat wave event identification condition to identify the temperature heat wave event; obtain the actual observed temperature during the occurrence time of the temperature heat wave event and the climatological state average temperature in the corresponding base year; The third module is configured to input the actual observed temperature and the synchronous sample point pair as input data into the dissolved oxygen estimation model to calculate the dissolved oxygen concentration at the heat wave temperature; input the climatological average temperature and the sample point pair as input data into the dissolved oxygen estimation model to calculate the dissolved oxygen concentration at the climatological average temperature; The fourth module is configured to analyze the dissolved oxygen concentration at the average temperature of the climate state and the dissolved oxygen concentration at the heat wave temperature to obtain the intensity of the impact of high temperature heat waves on the dissolved oxygen in the lake.

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