Lake surface evaporation capacity processing method based on multi-model evaporator dynamic conversion coefficient

Abstract

The embodiment of the invention relates to a lake surface evaporation capacity processing method based on dynamic conversion coefficients of multi-model evaporators. The method comprises the steps that observation evaporation capacity of a plurality of first evaporators, observation evaporation capacity of a plurality of second evaporators and observation evaporation capacity of a plurality of third evaporators within preset duration are obtained; calculating a first conversion coefficient and a second conversion coefficient on the daily scale of the first period; calculating a first conversion coefficient and a second conversion coefficient on a monthly scale of the first period according to the first conversion coefficient and the second conversion coefficient on the daily scale of the first period; calculating a first conversion coefficient and a second conversion coefficient on the monthly scale of the second period; determining a target coefficient; calculating a first lake surface evaporation capacity set corresponding to the current time according to a first conversion coefficient on a monthly scale corresponding to the period and the first evaporator observation evaporation capacity at the current time; calculating a second lake surface evaporation capacity set corresponding to the current time; and according to a set index and the observed evaporation capacity of the third evaporator at the current time, the first and second day, month and year lake surface evaporation capacities are evaluated, and final data representing the lake surface evaporation capacity are determined.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly relates to a method for processing lake evaporation based on dynamic conversion coefficients of multiple types of evaporators. Background Art

[0002] Lake Surface Evaporation (LSE) is an important part of the water and energy balance of lakes. Accurately estimating LSE is crucial for the scientific water resources management of alpine lakes on the Qinghai-Tibet Plateau under the background of global warming. However, the lack of hydrometeorological observation data and the limited parameterization of local models hinder the accuracy of LSE estimation, especially during the lake freezing period. Summary of the Invention

[0003] The purpose of the present invention is to address the deficiencies of the prior art and provide a method and device for processing lake evaporation based on dynamic conversion coefficients of multiple types of evaporators to solve the problems existing in the prior art.

[0004] To achieve the above purpose, the present invention provides a method for processing lake evaporation based on dynamic conversion coefficients of multiple types of evaporators, including:

[0005] Obtaining multiple first evaporator observed evaporation amounts, second evaporator observed evaporation amounts, and third evaporator observed evaporation amounts within a preset time period respectively; the first evaporator observed evaporation amount includes the observed evaporation amounts in the first period and the second period, the second evaporator observed evaporation amount includes the observed evaporation amount in the first period, and the third evaporator observed evaporation amount includes the observed evaporation amount in the first period;

[0006] Calculating a first conversion coefficient on a daily scale in the first period according to the first evaporator observed evaporation amount and the third evaporator observed evaporation amount;

[0007] Calculating a second conversion coefficient on a daily scale in the first period according to the second evaporator observed evaporation amount and the third evaporator observed evaporation amount;

[0008] Calculating a first conversion coefficient and a second conversion coefficient on a monthly scale in the first period respectively according to the first conversion coefficient and the second conversion coefficient on a daily scale in the first period;

[0009] Calculating a first conversion coefficient and a second conversion coefficient on a monthly scale in the second period respectively according to the first evaporator observed evaporation amount, the second evaporator observed evaporation amount, and the third evaporator observed evaporation amount on a monthly scale in the second period;

[0010] Determine the target coefficient based on the first conversion coefficient and the second conversion coefficient on the daily scale in the first period, as well as the first conversion coefficient and the second conversion coefficient on the monthly scale in the first period and the second period respectively;

[0011] When taking the first conversion coefficient and the second conversion coefficient on the monthly scale as the target coefficient, determine the period in which the current time is located;

[0012] Calculate the first lake evaporation volume set corresponding to the current time according to the first conversion coefficient on the monthly scale corresponding to the period and the observed evaporation volume of the first evaporator at the current time; wherein, the first lake evaporation volume set includes the daily lake evaporation volume, the monthly lake evaporation volume and the annual lake evaporation volume;

[0013] Calculate the second lake evaporation volume set corresponding to the current time according to the second conversion coefficient on the monthly scale corresponding to the period and the observed evaporation volume of the second evaporator at the current time; wherein, the second lake evaporation volume set includes the daily lake evaporation volume, the monthly lake evaporation volume and the annual lake evaporation volume;

[0014] Evaluate the daily lake evaporation volume, the monthly lake evaporation volume and the annual lake evaporation volume of the first one, as well as the daily lake evaporation volume, the monthly lake evaporation volume and the annual lake evaporation volume of the second one according to the set index and the observed evaporation volume of the third evaporator at the current time, and determine the data finally representing the lake evaporation volume.

[0015] In a possible implementation manner, calculating the first conversion coefficient on the daily scale in the first period according to the observed evaporation volume of the first evaporator and the observed evaporation volume of the third evaporator specifically includes:

[0016] Calculate the first conversion coefficient of each day according to the ratio of the observed evaporation volume of the third evaporator of each day to the corresponding observed evaporation volume of the first evaporator;

[0017] Calculate the mean value of the first conversion coefficients of the same date of each year within a preset time period to obtain the first conversion coefficient on the daily scale of each day.

[0018] In a possible implementation manner, calculating the second conversion coefficient on the daily scale in the first period according to the observed evaporation volume of the second evaporator and the observed evaporation volume of the third evaporator specifically includes:

[0019] Calculate the second conversion coefficient of each day according to the ratio of the observed evaporation volume of the third evaporator of each day to the corresponding observed evaporation volume of the second evaporator;

[0020] Calculate the mean value of multiple second conversion coefficients of the same date of each year within a preset time period to obtain the second conversion coefficient on the daily scale of each day.

[0021] In a possible implementation manner, calculating the first conversion coefficient and the second conversion coefficient on a monthly scale according to the first conversion coefficient and the second conversion coefficient on a daily scale of the first time period specifically includes:

[0022] Calculating the average value of multiple first conversion coefficients on a daily scale within the same month of each year during a preset time period to obtain the first conversion coefficient on a monthly scale for each month;

[0023] Calculating the average value of multiple second conversion coefficients on a daily scale within the same month of each year during a preset time period to obtain the second conversion coefficient on a monthly scale for each month; and,

[0024] Calculating the first conversion coefficient and the second conversion coefficient on a monthly scale of the second time period according to the first observed evaporation amount of the first evaporator, the second observed evaporation amount of the second evaporator, and the third observed evaporation amount of the third evaporator on a monthly scale of the second time period specifically includes:

[0025] Calculating the first conversion coefficient on a monthly scale of the second time period according to the ratio of the third observed evaporation amount of the third evaporator to the first observed evaporation amount of the first evaporator on a monthly scale of the second time period;

[0026] Calculating the second conversion coefficient on a monthly scale of the second time period according to the ratio of the third observed evaporation amount of the third evaporator to the first observed evaporation amount of the first evaporator on a monthly scale of the second time period.

[0027] In a possible implementation manner, determining the target coefficient according to the first conversion coefficient and the second conversion coefficient on a daily scale of the first time period, and the first conversion coefficient and the second conversion coefficient on a monthly scale in the first time period and the second time period respectively specifically includes:

[0028] Determining the first change amplitude of adjacent first conversion coefficients on a daily scale, the second change amplitude of adjacent second conversion coefficients on a daily scale, the third change amplitude of adjacent first conversion coefficients on a monthly scale, and the fourth change amplitude of adjacent second conversion coefficients on a monthly scale within a preset time period;

[0029] Determining to use the first conversion coefficient on a monthly scale as one of the target coefficients according to the first change amplitude and the third change amplitude;

[0030] Determining to use the second conversion coefficient on a monthly scale as the other one of the target coefficients according to the second change amplitude and the fourth change amplitude.

[0031] In a possible implementation manner, calculating the first lake evaporation amount set corresponding to the current time according to the first conversion coefficient on a monthly scale corresponding to the time period and the first observed evaporation amount of the first evaporator at the current time specifically includes:

[0032] Calculate the first daily lake evaporation by multiplying the first conversion coefficient on a monthly scale for the month in which the current time falls by the observed evaporation of the first evaporator at the current time;

[0033] Calculate the first monthly lake evaporation by multiplying the first conversion coefficient on a monthly scale for the month in which the current time falls by the observed evaporation of the first evaporator in the month in which the current time falls;

[0034] Sum the first monthly lake evaporation for each month in the year according to the year in which the current time falls to obtain the first annual lake evaporation; and,

[0035] Calculate the second lake evaporation corresponding to the current time according to the second conversion coefficient on a monthly scale corresponding to the period and the observed evaporation of the second evaporator at the current time. Specifically, it includes:

[0036] Calculate the second daily lake evaporation by multiplying the second conversion coefficient on a monthly scale for the month in which the current time falls by the observed evaporation of the second evaporator at the current time;

[0037] Calculate the second monthly lake evaporation by multiplying the second conversion coefficient on a monthly scale for the month in which the current time falls by the observed evaporation of the second evaporator in the month in which the current time falls;

[0038] Sum the second monthly lake evaporation for each month in the year according to the year in which the current time falls to obtain the second annual lake evaporation.

[0039] In a possible implementation manner, the evaluation of the first daily lake evaporation, the first monthly lake evaporation, and the first annual lake evaporation, as well as the second daily lake evaporation, the second monthly lake evaporation, and the second annual lake evaporation according to the set indicators and the observed evaporation of the third evaporator at the current time to determine the data finally representing the lake evaporation specifically includes:

[0040] Calculate the determination coefficient, root mean square error, mean bias error, and mean absolute error of multiple first daily lake evaporation, first monthly lake evaporation, and first annual lake evaporation respectively with the observed evaporation of the third evaporator to obtain a first result;

[0041] Calculate the determination coefficient, root mean square error, mean bias error, and mean absolute error of multiple second daily lake evaporation, second monthly lake evaporation, and second annual lake evaporation respectively with the observed evaporation of the third evaporator to obtain a second result;

[0042] Determine the data finally representing the lake evaporation amount according to the first result and the second result; wherein, on the daily scale and monthly scale, the determination coefficient of the second result is greater than that of the first result, and the root mean square error, mean bias error and mean absolute error of the second result are less than those of the first result. On the annual scale, the determination coefficient of the first result is greater than that of the second result, and the root mean square error, mean bias error and mean absolute error of the first result are less than those of the second result; to obtain the high-resolution lake evaporation amount for the whole year period, in the first period, use the lake evaporation amount on the second day as the data finally representing the lake evaporation amount, and in the second period, use the lake evaporation amount on the first day as the data finally representing the lake evaporation amount.

[0043] In a possible implementation manner, the method further includes:

[0044] Obtain meteorological elements on the daily scale; the meteorological elements include daily average air temperature, daily average lake water temperature, daily precipitation, daily actual water vapor pressure, daily average relative humidity, daily saturation water vapor pressure difference, and daily water-air temperature difference;

[0045] Use the daily average air temperature, daily average lake water temperature, daily precipitation, daily actual water vapor pressure, daily average relative humidity, daily saturation water vapor pressure difference, and daily water-air temperature difference as independent variables, use the lake evaporation amount on the second day in the first period and the lake evaporation amount on the first day in the second period as initial dependent variables, divide the independent variables and initial dependent variables into a training set and a test set, and bring them into the random forest regression model (RFRM), adjust the parameters of the RFRM, train the RFRM, and obtain the trained RFRM;

[0046] Substitute the independent variables of the test set into the trained RFRM to obtain the target dependent variable;

[0047] Compare the target dependent variable with the evaporation amount observed by the third evaporator on the daily scale to determine whether the trained RFRM meets the requirements;

[0048] When the trained RFRM meets the requirements, based on the output of the RFRM, determine the influence degree of each meteorological element on the lake evaporation amount on the second day in the first period combined with the lake evaporation amount on the first day in the second period.

[0049] In a possible implementation manner, according to Calculate the daily saturation water vapor pressure; the e s is the daily saturation water vapor pressure, and the T a is the daily average air temperature;

[0050] According to Calculate the daily average relative humidity; e a is the actual observed water vapor pressure;

[0051] According to VPD = e s -e a Calculate the daily saturated water vapor pressure difference;

[0052] Obtain the daily water - air temperature difference based on the daily average lake surface water temperature and the daily average air temperature.

[0053] In a second aspect, the present invention provides a device, including a memory and a processor. The memory is used to store programs, and the processor is used to execute the method described in any one of the first aspects.

[0054] In a third aspect, the present invention provides a computer - readable storage medium. A computer program is stored on the computer - readable storage medium, and when the computer program is executed by a processor, it executes the method described in any one of the first aspects.

[0055] By applying the lake surface evaporation amount processing method based on dynamic conversion coefficients of multiple - model evaporators provided in the embodiments of the present invention, accurate LSE quantification is performed using multi - source daily evaporation observations and dynamic conversion coefficients, thereby realizing the quantification of the daily evaporation amount of alpine lakes throughout the year, including the non - freezing period and the freezing period, and with relatively high accuracy. Further, this application can quantify the meteorological elements affecting the daily evaporation amount of alpine lakes, and further verifies the accuracy of the daily lake surface evaporation amount obtained through the conversion coefficient by RFRM. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 is one of the schematic flowcharts of the lake surface evaporation amount processing method based on dynamic conversion coefficients of multiple - model evaporators provided in the embodiments of the present invention;

[0057] Figure 2 is Figure 1 the flowchart of step 150 in;

[0058] Figure 3 is Figure 1 the flowchart of step 170 in;

[0059] Figure 4 is Figure 1 the flowchart of step 180 in;

[0060] Figure 5 is Figure 1 the flowchart of step 190 in;

[0061] Figure 6 is the second schematic flowchart of the lake surface evaporation amount processing method based on dynamic conversion coefficients of multiple - model evaporators provided in the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0062] To make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0063] Figure 1 This is one of the schematic flowcharts of the lake evaporation amount processing method based on the dynamic conversion coefficients of multiple types of evaporators provided by the embodiments of the present invention. The main processing object of the present application is the application of alpine lakes. Since alpine lakes have a freezing period and a non-freezing period, it is difficult to estimate the evaporation amount during the freezing period. The following combines Figure 1 , and illustrates the technical solution of the present invention with specific embodiments. As Figure 1 shown, the present application includes the following steps:

[0064] Step 100, respectively obtain a plurality of first evaporator observed evaporation amounts, second evaporator observed evaporation amounts, and third evaporator observed evaporation amounts within a preset time period; the first evaporator observed evaporation amount includes the observed evaporation amounts in the first period and the second period, the second evaporator observed evaporation amount includes the observed evaporation amount in the first period, and the third evaporator observed evaporation amount includes the observed evaporation amount in the first period;

[0065] Among them, the first evaporator is the first evaporation dish, such as a 20 cm evaporation dish, the second evaporator is an E601 evaporator, and the third evaporator is an evaporation pond, such as a 20 ㎡ evaporation pond. The first period is the non-freezing period, and the second period is the freezing period. The first evaporator observed evaporation amount can be the daily evaporation amount observed through the first evaporator. The water level change in the 20 cm evaporation dish during the non-freezing period and the weight change of the 20 cm evaporation dish during the freezing period can represent E -20cm , that is, the daily-scale E -20cm is observed throughout the year. Correspondingly, the second evaporator observed evaporation amount can be the daily evaporation amount observed through the second evaporator. At this time, each day is a day during the non-freezing period. The third evaporator observed evaporation amount can be the daily evaporation amount observed through the third evaporator. At this time, each day is also a day during the non-freezing period. The evaporation amounts of the E601 evaporation dish and the 20 ㎡ evaporation pond can be obtained by the measuring needle method. And since the E601 evaporation dish and the 20-square-meter evaporation pond usually cannot work during the freezing period, therefore, E -E601 and E -20m 2 's daily evaporation amount can only be obtained during the non-freezing period.

[0066] Step 110: Calculate the first conversion coefficient on a daily scale for the first period based on the observed evaporation of the first evaporator and the observed evaporation of the third evaporator.

[0067] Specifically, calculating the first conversion coefficient on a daily scale for the first period based on the observed evaporation of the first evaporator and the observed evaporation of the third evaporator specifically includes:

[0068] Calculate the first conversion coefficient for each day based on the ratio of the observed evaporation of the third evaporator to the corresponding observed evaporation of the first evaporator for each day.

[0069] Within a preset time period, calculate the mean value of the first conversion coefficients for the same date of each year to obtain the first conversion coefficient on a daily scale for each day.

[0070] Among them, the preset time period can be set as needed, such as 10 years. For example, for a certain day during the non-freezing period, such as May 20th, to calculate the first conversion coefficient on a daily scale for May 20th from 2009 to 2018 in these 10 years, the first conversion coefficients for each May 20th in these 10 years can be calculated, and then the mean value of the 10 first conversion coefficients can be taken to obtain the first conversion coefficient on a daily scale for May 20th.

[0071] Step 120: Calculate the second conversion coefficient on a daily scale for the first period based on the observed evaporation of the second evaporator and the observed evaporation of the third evaporator.

[0072] Calculating the second conversion coefficient on a daily scale for the first period based on the observed evaporation of the second evaporator and the observed evaporation of the third evaporator specifically includes:

[0073] Calculate the second conversion coefficient for each day based on the ratio of the observed evaporation of the third evaporator to the corresponding observed evaporation of the second evaporator for each day.

[0074] Within a preset time period, calculate the mean value of the multiple second conversion coefficients for the same date of each year to obtain the second conversion coefficient on a daily scale for each day.

[0075] For example, for a certain day during the non-freezing period, such as May 20th, to calculate the second conversion coefficient on a daily scale for May 20th from 2009 to 2018 in these 10 years, the second conversion coefficients for each May 20th in these 10 years can be calculated, and then the mean value of the 10 second conversion coefficients can be taken to obtain the second conversion coefficient on a daily scale for May 20th.

[0076] Step 130: Calculate the first conversion coefficient and the second conversion coefficient on a monthly scale for the first period respectively based on the first conversion coefficient and the second conversion coefficient on a daily scale for the first period.

[0077] Specifically, within a preset duration, calculate the mean of multiple first conversion factors on a daily scale within the same month of each year in the first period to obtain the first conversion factor on a monthly scale for each month in the first period;

[0078] Within a preset duration, calculate the mean of multiple second conversion factors on a daily scale within the same month of each year in the first period to obtain the second conversion factor on a monthly scale for each month in the first period.

[0079] Specifically, for example, to calculate the first conversion factor for May 2009, the mean of the first conversion factors of each day in May on a daily scale can be taken to obtain the first conversion factor for May on a monthly scale.

[0080] Step 140: Calculate the first conversion factor and the second conversion factor on a monthly scale for the second period based on the observed evaporation amounts of the first evaporator, the second evaporator, and the third evaporator on a monthly scale in the second period respectively;

[0081] Specifically, the observed evaporation amount of the first evaporator on a monthly scale in the second period refers to the observed evaporation amount of the first evaporator for each month in the second period. At this time, the observed evaporation amounts of the first evaporator for each day can be accumulated to obtain the observed evaporation amount of the first evaporator for each month. For the observed evaporation amounts of the second evaporator and the third evaporator on a monthly scale in the second period, they can be obtained by the weighing method or the needle measurement method.

[0082] The first conversion factor on a monthly scale for the second period can be calculated based on the ratio of the observed evaporation amount of the third evaporator to the observed evaporation amount of the first evaporator on a monthly scale in the second period. The second conversion factor on a monthly scale for the second period can be calculated based on the ratio of the observed evaporation amount of the third evaporator to the observed evaporation amount of the second evaporator on a monthly scale in the second period.

[0083] Step 150: Determine the target coefficient based on the first conversion factor and the second conversion factor on a daily scale in the first period, and the first conversion factor and the second conversion factor on a monthly scale in the first period and the second period respectively;

[0084] Specifically, as Figure 2 shown, step 150 includes the following content:

[0085] Step 1501: Determine the first change amplitude of the first conversion factor on adjacent daily scales, the second change amplitude of the second conversion factor on adjacent daily scales, the third change amplitude of the first conversion factor on adjacent monthly scales, and the fourth change amplitude of the second conversion factor on adjacent monthly scales within the preset duration;

[0086] Step 1502: Determine one of the target coefficients as the first conversion coefficient on a monthly scale according to the first change amplitude and the third change amplitude.

[0087] Step 1503: Determine the other of the target coefficients as the second conversion coefficient on a monthly scale according to the second change amplitude and the fourth change amplitude.

[0088] Specifically, the number of target coefficients is 2. The first change amplitude within a preset time duration can be compared with the third change amplitude to determine that the third change amplitude is less than the first change amplitude, or rather, the average change of the third change amplitude is less than the average change of the first change amplitude, so as to determine that the first conversion coefficient on a monthly scale is one of the target coefficients. Correspondingly, determine that the second conversion coefficient on a monthly scale is the other of the target coefficients.

[0089] Step 160: When the first conversion coefficient and the second conversion coefficient on a monthly scale are used as the target coefficients, determine the period in which the current time is located.

[0090] Specifically, if the observed evaporation of the evaporator at the current time is to be obtained, it is necessary to first determine whether the current time is in the first period or the second period. If it is in the first period, subsequent calculations can be carried out through the first conversion coefficient and the second conversion coefficient on a monthly scale corresponding to the first period; if it is in the second period, subsequent calculations can be carried out through the first conversion coefficient and the second conversion coefficient on a monthly scale corresponding to the second period.

[0091] Step 170: Calculate the first set of lake evaporation amounts corresponding to the current time according to the first conversion coefficient on a monthly scale corresponding to the period and the first observed evaporation amount of the evaporator at the current time; among them, the first set of lake evaporation amounts includes the daily lake evaporation amount, the monthly lake evaporation amount, and the annual lake evaporation amount.

[0092] Specifically, as Figure 3 shown, Step 170 includes the following steps:

[0093] Step 1701: Calculate the daily lake evaporation amount according to the product of the first conversion coefficient on a monthly scale corresponding to the month in which the current time is located and the first observed evaporation amount of the evaporator at the current time.

[0094] Step 1702: Calculate the monthly lake evaporation amount according to the product of the first conversion coefficient on a monthly scale corresponding to the month in which the current time is located and the first observed evaporation amount of the evaporator in the month in which the current time is located.

[0095] Step 1703: Add up the monthly lake evaporation amounts within the year according to the year in which the current time is located to obtain the annual lake evaporation amount.

[0096] Thus, through the above three steps, the daily lake evaporation, monthly lake evaporation, and annual lake evaporation corresponding to the current time can be calculated. Here, the first, second, and third are used to distinguish from the subsequent steps of calculation using the second conversion coefficient.

[0097] Step 180: Calculate the second lake evaporation set corresponding to the current time according to the second conversion coefficient on the monthly scale corresponding to the period and the observed evaporation of the second evaporator at the current time. Among them, the second lake evaporation set includes the second daily lake evaporation, the second monthly lake evaporation, and the second annual lake evaporation.

[0098] Specifically, as Figure 4 shown, Step 180 includes the following steps:

[0099] Step 1801: Calculate the second daily lake evaporation according to the product of the second conversion coefficient on the monthly scale of the month where the current time is located and the observed evaporation of the second evaporator at the current time.

[0100] Step 1802: Calculate the second monthly lake evaporation according to the product of the second conversion coefficient on the monthly scale of the month where the current time is located and the observed evaporation of the second evaporator in the month where the current time is located.

[0101] Step 1803: Add up the second monthly lake evaporation of each month in the year according to the year where the current time is located to obtain the second annual lake evaporation.

[0102] Step 190: Evaluate the first daily lake evaporation, the first monthly lake evaporation, the first annual lake evaporation, the second daily lake evaporation, the second monthly lake evaporation, and the second annual lake evaporation according to the set index and the observed evaporation of the third evaporator at the current time, and determine the data finally representing the lake evaporation.

[0103] Specifically, as Figure 5 shown, Step 190 includes the following steps:

[0104] Step 1901: Calculate the determination coefficient, root mean square error, mean bias error, and mean absolute error of multiple first daily lake evaporations, first monthly lake evaporations, and first annual lake evaporations respectively with the observed evaporation of the third evaporator to obtain the first result.

[0105] Step 1902: Calculate the determination coefficient, root mean square error, mean bias error, and mean absolute error of multiple second daily lake evaporations, second monthly lake evaporations, and second annual lake evaporations respectively with the observed evaporation of the third evaporator to obtain the second result.

[0106] Step 1903: Determine the data finally representing the lake evaporation according to the first result and the second result.

[0107] Among them, the formulas for calculating the coefficient of determination (R2), root mean square error (RMSE), mean bias error (MBE), and mean absolute error (MAE) are shown in the following formulas in sequence:

[0108]

[0109] where x i is the observed evaporation of the third evaporator, and xi' is the daily lake evaporation sequence composed of the lake evaporation on the second day of the first period and the lake evaporation on the first day of the second period selected is the average value of the observed evaporation, calculated by and n is the total number of samples.

[0110] For example, when xi' is the lake evaporation on the first day, n lake evaporations on the first day can be obtained, and then the observed evaporations of the third evaporator for each day corresponding to these n dates can be obtained, and then a set of coefficient of determination, root mean square, mean bias error, and mean absolute error can be calculated. Correspondingly, a set of coefficient of determination, root mean square, mean bias error, and mean absolute error for the lake evaporation on the first month, the first year, the second day, the second month, and the second year can be obtained. Thus, the data finally representing the lake evaporation is determined. When R2 is higher and RMSE, MAE, and MBE are lower, it indicates that the estimation accuracy of LSE is better.

[0111] Therefore, according to the above four evaluation parameters, it can be determined that on the daily scale and monthly scale, the coefficient of determination of the second result is greater than that of the first result, and the root mean square error, mean bias error, and mean absolute error of the second result are less than those of the first result. On the annual scale, the coefficient of determination of the first result is greater than that of the second result, and the root mean square error, mean bias error, and mean absolute error of the first result are less than those of the second result; since this application is to obtain the high-resolution lake evaporation for the whole year, the smaller the time scale, the higher the resolution of the obtained lake evaporation. Therefore, this application can use the lake evaporation on the second day as the data finally representing the lake evaporation in the first period, and use the lake evaporation on the first day as the data finally representing the lake evaporation in the second period.

[0112] For example, in one example, the lake evaporation estimated using the second conversion coefficient on a daily scale and a monthly scale is more accurate; while on an annual scale, the lake evaporation estimated using the first conversion coefficient is more accurate. However, since the main objective of this application is to obtain high-resolution (daily scale) lake evaporation for the entire year (including both the freezing period and the non-freezing period), therefore, it can be determined here that when there are daily observations of E-E601, the lake evaporation on the second day is estimated using the second conversion coefficient, and when there are no daily observations of E-E601, the lake evaporation on the first day corresponding to the day is estimated using the first conversion coefficient. By combining the two methods, the daily-scale lake evaporation for the entire time series can be obtained.

[0113] Furthermore, as Figure 6 shown, this application further includes:

[0114] Step 610, obtaining meteorological elements on a daily scale; the meteorological elements include daily average air temperature, daily average lake surface water temperature, daily precipitation, daily actual water vapor pressure, daily average relative humidity, daily saturation water vapor pressure difference, and daily water-air temperature difference;

[0115] Among them, according to calculate the daily saturation water vapor pressure; e s is the daily saturation water vapor pressure, and T a is the daily average air temperature;

[0116] According to calculate the daily average relative humidity; e a is the actually observed water vapor pressure;

[0117] According to VPD = e s -e a calculate the daily saturation water vapor pressure difference;

[0118] Obtain the daily water-air temperature difference based on the daily average lake surface water temperature and the daily average air temperature.

[0119] Step 620, using the daily average air temperature, daily average lake surface water temperature, daily precipitation, daily actual water vapor pressure, daily average relative humidity, daily saturation water vapor pressure difference, and daily water-air temperature difference as independent variables, using the lake evaporation on the second day of the first period and the lake evaporation on the first day of the second period as initial dependent variables, dividing the independent variables and the initial dependent variables into a training set and a test set, and bringing them into a random forest regression model (Random Forest Regression, RFRM), adjusting the parameters of the RFRM, training the RFRM, and obtaining the trained RFRM;

[0120] Step 630, substituting the independent variables of the test set into the trained RFRM to obtain the target dependent variable;

[0121] Step 640: Compare the target dependent variable with the third evaporator observed evaporation on a daily scale to determine whether the trained RFRM meets the requirements.

[0122] Step 650: When the trained RFRM meets the requirements, based on the output of the RFRM, determine the influence degree of each meteorological element on the lake surface evaporation on the second day of the first period combined with the lake surface evaporation on the first day of the second period.

[0123] Among them, the lake surface evaporation on the second day of the first period and the lake surface evaporation on the first day of the second period constitute a complete daily lake surface evaporation sequence within a preset time period.

[0124] Specifically, in this application, 70% of the data samples are used as the training set, and 30% of the data is used as the test set. 70% of the samples are used to train the regression relationship between the daily lake surface evaporation and different meteorological factors; continuously adjust the parameters of the RFRM, such as the number of nodes, the number of leaves, etc. For example, set the number of decision trees and the minimum number of leaf nodes to 1000 and 2 respectively, and train the RFRM to obtain the trained RFRM. On this basis, substitute the independent variables of the remaining 30% of the data into the trained RFRM to obtain the target dependent variable, and compare and verify the target dependent variable with the third evaporator observed evaporation on a daily scale. The results show that the R2, RMSE, MAE, and MBE between the target dependent variable and the third evaporator observed evaporation on a daily scale are 0.38, 0.85 mm / d, 0.64 mm / d, and 0.0308 mm / d respectively. This shows that the LSE predicted by the trained RFRM has high accuracy. Therefore, based on this trained RFRM, the relative importance of each meteorological factor in different meteorological elements to the change of the daily lake surface evaporation can be directly output. The relative importance can also be called the influence degree, which can be represented by specific numerical values. The larger the numerical value, the greater the influence degree.

[0125] Furthermore, this application can also:

[0126] Process the meteorological elements and the finally estimated lake surface evaporation on the second day of the first period combined with the lake surface evaporation on the first day of the second period. Specifically, the coefficient of variation (Cv), Pearson correlation analysis, and moving average filtering can be used for data preprocessing and analysis.

[0127] Cv describes the dispersion degree of the variable. The higher the value, the greater the fluctuation over time. σ and μ represent the standard deviation and the mean respectively. Here, Cv can be used to analyze the fluctuations of meteorological elements (such as Ta, Tw, and RH), evaporation, and daily and monthly conversion coefficients.

[0128]

[0129] Pearson correlation analysis measures the linear correlation between two variables. The closer the correlation coefficient (r) is to 1 or -1, the stronger the linear relationship between the two variables. p < 0.05, p < 0.01, and p < 0.001 indicate significant correlations between variables at the 0.05, 0.01, and 0.001 levels, respectively. This application mainly uses Pearson correlation analysis to test the correlation between daily meteorological elements and LSE.

[0130] Moving average filtering usually smooths data by performing arithmetic or weighted averaging on a data sequence over a moving window. Specifically, the method slides the data sequence over a fixed window of length L. During this process, the old data in front of the window is removed, and new data behind the window enters, with each slide sampling interval. At the same time, the L data within each sliding window are arithmetically averaged, ultimately obtaining a filtered data set. This method was applied to the original daily meteorological data to better reveal their interannual variation trends. Considering the obvious seasonal variations of meteorological elements, the moving window and average step size were set to 365 days and 1.

[0131] The node purity increase index of each predictor variable can be further divided by the sum of the node purity increase indices of all predictor variables. Then, the result is converted to a percentage to intuitively compare the relative importance of different meteorological elements to the change in LSE.

[0132] Further analysis of the interannual variation trends of air temperature, actual vapor pressure, saturation vapor pressure, and evaporation shows that: from 2009 to 2018, the air temperature decreased significantly, resulting in a decrease in the saturation vapor pressure that is positively correlated with the air temperature, while the actual vapor pressure increased. Correspondingly, the saturation vapor pressure difference VPD (i.e., saturation vapor pressure es - actual vapor pressure ea) decreased. The evaporation showed an insignificantly decreasing trend from 2009 to 2018. This indicates that the increase in actual vapor pressure ea and the decrease in saturation vapor pressure es caused by the decrease in air temperature Ta are the main factors leading to the decrease in the saturation vapor pressure difference VPD, which in turn leads to the decreasing trend of the daily lake surface evaporation LSE.

[0133] Consistent with the results of simple Pearson linear correlation analysis, the saturation vapor pressure difference VPD plays the most dominant role in the change of the daily lake surface evaporation (contribution rate reaches 26.2%), followed by the water - air temperature difference (contribution rate is 24.3%), and precipitation has the least impact on it (contribution rate is less than 10%).

[0134] Thus, this application quantifies the key meteorological elements affecting alpine lakes and further verifies the accuracy of the daily lake surface evaporation obtained through the conversion coefficient by RFRM. By applying the lake surface evaporation processing method based on the dynamic conversion coefficient of multiple types of evaporators provided in the embodiments of the present invention, during the non - freezing period, LSE can be calculated using the monthly evaporation conversion coefficient (E -20m2 / E -E601 ) multiplied by daily E -E601 to estimate well; during the freezing period, the monthly conversion coefficient (E -20m 2 / E -20cm ) can be multiplied by daily E -20cm to estimate. The estimated daily LSE decreases slightly, but the fluctuation is significant, mainly controlled by the decrease in the saturation vapor pressure deficit, which is the combined result of the increase in the actual vapor pressure and the decrease in the saturation vapor pressure. This application uses multi-source daily evaporation observations and dynamic conversion coefficients to achieve the quantification of the daily evaporation of alpine lakes throughout the year, including the non-freezing period and the freezing period, with high accuracy. Further, this application can quantify the meteorological elements affecting the daily evaporation of alpine lakes, and further verifies the accuracy of the daily lake surface evaporation estimated based on the dynamic conversion coefficient through RFRM.

[0135] Embodiment 2 of the invention provides a device, including a memory and a processor. The memory is used to store programs and can be connected to the processor through a bus. The memory can be a non-volatile memory, such as a hard disk drive and a flash memory, and software programs and device driver programs are stored in the memory. The software program can execute various functions of the above method provided by Embodiment 1 of the invention; the device driver program can be a network and interface driver program. The processor is used to execute the software program, and when the software program is executed, it can implement the method provided by Embodiment 1 of the invention.

[0136] Embodiment 3 of the invention provides a computer program product containing instructions, which when run on a computer, causes the computer to execute the method provided by Embodiment 1 of the invention.

[0137] Embodiment 4 of the invention provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the method provided by Embodiment 1 of the invention.

[0138] Those skilled in the art should also further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the invention.

[0139] The steps of the methods or algorithms described in connection with the embodiments disclosed herein may be implemented by hardware, software modules executed by a processor, or a combination of both. The software modules may be placed in a random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium well-known in the art.

[0140] The specific embodiments described above have further elaborated on the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above description is only for the specific embodiments of the present invention and is not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for processing lake evaporation based on dynamic conversion coefficients of multiple types of evaporators, characterized in that, The method includes: Obtaining a plurality of first evaporator observed evaporation amounts, second evaporator observed evaporation amounts, and third evaporator observed evaporation amounts within a preset time period respectively; the first evaporator observed evaporation amount includes the observed evaporation amounts in the first period and the second period, the second evaporator observed evaporation amount includes the observed evaporation amount in the first period, and the third evaporator observed evaporation amount includes the observed evaporation amount in the first period; Calculating a first conversion coefficient on a daily scale in the first period according to the first evaporator observed evaporation amount and the third evaporator observed evaporation amount; Calculating a second conversion coefficient on a daily scale in the first period according to the second evaporator observed evaporation amount and the third evaporator observed evaporation amount; Calculating a first conversion coefficient and a second conversion coefficient on a monthly scale in the first period respectively according to the first conversion coefficient and the second conversion coefficient on a daily scale in the first period; Calculating a first conversion coefficient and a second conversion coefficient on a monthly scale in the second period respectively according to the first evaporator observed evaporation amount, the second evaporator observed evaporation amount, and the third evaporator observed evaporation amount on a monthly scale in the second period; Determining a target coefficient according to the first conversion coefficient and the second conversion coefficient on a daily scale in the first period, and the first conversion coefficient and the second conversion coefficient on a monthly scale in the first period and the second period respectively; When taking the first conversion coefficient and the second conversion coefficient on a monthly scale as the target coefficient, determining the period where the current time is located; Calculating a first lake evaporation amount set corresponding to the current time according to the first conversion coefficient on a monthly scale corresponding to the period and the first evaporator observed evaporation amount at the current time; wherein, the first lake evaporation amount set includes a first daily lake evaporation amount, a first monthly lake evaporation amount, and a first annual lake evaporation amount; Calculating a second lake evaporation amount set corresponding to the current time according to the second conversion coefficient on a monthly scale corresponding to the period and the second evaporator observed evaporation amount at the current time; wherein, the second lake evaporation amount set includes a second daily lake evaporation amount, a second monthly lake evaporation amount, and a second annual lake evaporation amount; Evaluating the first daily lake evaporation amount, the first monthly lake evaporation amount, and the first annual lake evaporation amount, and the second daily lake evaporation amount, the second monthly lake evaporation amount, and the second annual lake evaporation amount according to the set index and the third evaporator observed evaporation amount at the current time, and determining the data finally representing the lake evaporation amount.

2. The method according to claim 1, wherein Calculating a first conversion coefficient on a daily scale in the first period according to the first evaporator observed evaporation amount and the third evaporator observed evaporation amount specifically includes: Calculating a first conversion coefficient for each day according to the ratio of the third evaporator observed evaporation amount and the corresponding first evaporator observed evaporation amount for each day; Calculating the mean value of the first conversion coefficients of the same date in each year within a preset time period to obtain the first conversion coefficient on a daily scale for each day.

3. The method according to claim 1, wherein The calculating a second conversion coefficient on a daily scale in the first period according to the second evaporator observed evaporation amount and the third evaporator observed evaporation amount specifically includes: Calculating a second conversion coefficient for each day according to the ratio of the third evaporator observed evaporation amount and the corresponding second evaporator observed evaporation amount for each day; Within a preset time period, calculate the mean of multiple second conversion coefficients for the same date of each year to obtain the second conversion coefficient on a daily scale for each day.

4. The method according to claim 1, wherein The specific calculation of the first conversion coefficient and the second conversion coefficient on a monthly scale based on the first conversion coefficient and the second conversion coefficient on a daily scale in the first period includes: Within a preset time period, calculate the mean of multiple first conversion coefficients on a daily scale within the same month of each year to obtain the first conversion coefficient on a monthly scale for each month; Within a preset time period, calculate the mean of multiple second conversion coefficients on a daily scale within the same month of each year to obtain the second conversion coefficient on a monthly scale for each month; and, The specific calculation of the first conversion coefficient and the second conversion coefficient on a monthly scale in the second period based on the observed evaporation of the first evaporator, the observed evaporation of the second evaporator, and the observed evaporation of the third evaporator on a monthly scale in the second period includes: Calculate the first conversion coefficient on a monthly scale in the second period according to the ratio of the observed evaporation of the third evaporator to the observed evaporation of the first evaporator on a monthly scale in the second period; Calculate the second conversion coefficient on a monthly scale in the second period according to the ratio of the observed evaporation of the third evaporator to the observed evaporation of the first evaporator on a monthly scale in the second period.

5. The method according to claim 1, wherein The specific determination of the target coefficient based on the first conversion coefficient and the second conversion coefficient on a daily scale in the first period, and the first conversion coefficient and the second conversion coefficient on a monthly scale in the first period and the second period respectively includes: Determine the first change amplitude of the first conversion coefficient on adjacent daily scales, the second change amplitude of the second conversion coefficient on adjacent daily scales, the third change amplitude of the first conversion coefficient on adjacent monthly scales, and the fourth change amplitude of the second conversion coefficient on adjacent monthly scales within a preset time period; Determine to use the first conversion coefficient on a monthly scale as one of the target coefficients according to the first change amplitude and the third change amplitude; Determine to use the second conversion coefficient on a monthly scale as the other one of the target coefficients according to the second change amplitude and the fourth change amplitude.

6. The method according to claim 1, wherein The specific calculation of the first lake evaporation volume set corresponding to the current time based on the first conversion coefficient on a monthly scale corresponding to the period and the observed evaporation of the first evaporator at the current time includes: Calculate the daily lake evaporation volume on the first day according to the product of the first conversion coefficient on a monthly scale of the month where the current time is located and the observed evaporation of the first evaporator at the current time; Calculate the monthly lake evaporation volume on the first month according to the product of the first conversion coefficient on a monthly scale of the month where the current time is located and the observed evaporation of the first evaporator of the month where the current time is located; Add up the monthly lake evaporation volumes of each month within the year according to the year where the current time is located to obtain the annual lake evaporation volume on the first; and, The specific calculation of the second lake evaporation volume set corresponding to the current time based on the second conversion coefficient on a monthly scale corresponding to the period and the observed evaporation of the second evaporator at the current time includes: Calculate the daily lake evaporation volume on the second day according to the product of the second conversion coefficient on a monthly scale of the month where the current time is located and the observed evaporation of the second evaporator at the current time; Calculate the second monthly lake evaporation by multiplying the second conversion coefficient on the monthly scale of the month where the current time is located by the observed evaporation of the second evaporator in the month where the current time is located; According to the year where the current time is located, add up the second monthly lake evaporation of each month in that year to obtain the second annual lake evaporation.

7. The method according to claim 1, characterized in that The evaluation of the first daily lake evaporation, the first monthly lake evaporation, the first annual lake evaporation, the second daily lake evaporation, the second monthly lake evaporation, and the second annual lake evaporation according to the set indicators and the observed evaporation of the third evaporator at the current time to determine the data finally representing the lake evaporation specifically includes: Calculate the determination coefficient, root mean square error, mean bias error, and mean absolute error of multiple first daily lake evaporation, first monthly lake evaporation, and first annual lake evaporation respectively with the observed evaporation of the third evaporator to obtain the first result; Calculate the determination coefficient, root mean square error, mean bias error, and mean absolute error of multiple second daily lake evaporation, second monthly lake evaporation, and second annual lake evaporation respectively with the observed evaporation of the third evaporator to obtain the second result; Determine the data finally representing the lake evaporation according to the first result and the second result; wherein, on the daily and monthly scales, the determination coefficient of the second result is greater than that of the first result, and the root mean square error, mean bias error, and mean absolute error of the second result are less than those of the first result. On the annual scale, the determination coefficient of the first result is greater than that of the second result, and the root mean square error, mean bias error, and mean absolute error of the first result are less than those of the second result; to obtain the high-resolution lake evaporation for the whole year, in the first period, use the second daily lake evaporation as the data finally representing the lake evaporation, and in the second period, use the first daily lake evaporation as the data finally representing the lake evaporation.

8. The method according to claim 7, characterized in that, The method further includes: Obtain meteorological elements on the daily scale; the meteorological elements include daily average air temperature, daily average lake water temperature, daily precipitation, daily actual water vapor pressure, daily average relative humidity, daily saturated water vapor pressure difference, and daily water-air temperature difference; Take the daily average air temperature, daily average lake water temperature, daily precipitation, daily actual water vapor pressure, daily average relative humidity, daily saturated water vapor pressure difference, and daily water-air temperature difference as independent variables, take the second daily lake evaporation in the first period and the first daily lake evaporation in the second period as initial dependent variables, divide the independent variables and initial dependent variables into a training set and a test set, and bring them into the random forest regression model RFRM, adjust the parameters of the RFRM, and train the RFRM to obtain the trained RFRM; Substitute the independent variables of the test set into the trained RFRM to obtain the target dependent variable; Compare the target dependent variable with the observed evaporation of the third evaporator on the daily scale to determine whether the trained RFRM meets the requirements; When the trained RFRM meets the requirements, based on the output of the RFRM, determine the influence degree of each meteorological element on the lake evaporation on the second day of the first period combined with the lake evaporation on the first day of the second period.

9. The method according to claim 8, wherein According to calculate the daily saturated water vapor pressure; the e s is the daily saturated water vapor pressure, and the T a is the daily average temperature; According to Calculate the daily average relative humidity; e a is the actual observed water vapor pressure; According to VPD = e s - e a Calculate the daily saturated vapor pressure deficit; Obtain the daily water-air temperature difference according to the daily average lake water temperature and the daily average air temperature.

10. A device, comprising a memory and a processor, characterized in that, The memory is used to store programs, and the processor is used to execute the method according to any one of claims 1-9.

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