Prediction method for water temperature of river channel

Abstract

The invention provides a river channel water temperature prediction method, which comprises the following steps of: acquiring basic information data such as vertical water temperature distribution of a reservoir, randomly obtaining a data set for elevation to be valued between a power generation port and a pumping and storage water diversion port, constructing k discharged water temperature prediction formulas according to the data set, and obtaining downstream river channel water temperature prediction values at different moments by combining basic information time sequence data. And determining a prediction formula according to a decision coefficient through comparison with a measured value, finding out an optimal elevation determination model to be valued, and finally generating a change rule of the discharged water temperature of the reservoir based on the water temperature prediction value # imgabs0 # of each downstream river in a preset time period, and outputting the change rule of the discharged water temperature of the reservoir. According to the method for predicting the water temperature of the river channel, the complex calculation process is simplified, dependence on calculation resources is reduced, the real-time performance of prediction is improved, and the instant influence of operation of a power station on the water temperature of the downstream can be rapidly reflected.

Description

Technical Field

[0001] The invention relates to the technical field of water conservancy and hydropower engineering, and in particular to a method for predicting river water temperature. Background Art

[0002] As an important variable in the thermal characteristics of river systems, water temperature is affected by multiple factors, including meteorological conditions (such as temperature, wind speed, sunshine), hydrological characteristics (such as flow, velocity, river morphology) and human activities (such as reservoir construction and river basin development). These factors work together through complex mechanisms to affect the thermodynamic behavior of rivers and the health of ecosystems. Especially in the case of reservoir downstream water bodies, due to the different heat capacity of water bodies and changes in flow paths, water temperature often presents different dynamic characteristics from natural water systems.

[0003] In summer, small reservoirs on streams often cause water temperatures in the downstream river to rise because the water stays in the reservoir for a longer time and absorbs more solar radiation. Therefore, under the influence of these small reservoirs, the increase in water temperature may put pressure on the downstream aquatic ecological environment. In contrast, deepwater reservoirs have relatively low temperatures in the bottom water due to their greater depth and thermal stratification. The release of cooler water through discharge in summer may cause the water temperature in the downstream river to drop, while in winter, warmer bottom water may be released, forming the so-called "warm in winter and cool in summer" effect. The impact of this seasonal change in water temperature on the downstream ecosystem is complex and difficult to predict.

[0004] Existing water temperature assessment methods mainly rely on numerical simulation and prototype observation. Although these technologies can provide a certain degree of prediction accuracy, they usually require high computing costs and time, and are difficult to adapt to the rapidly changing reservoir operation needs. In addition, these methods often lack simplicity and real-time performance, and cannot provide high-precision predictions in dynamic environments.

[0005] Therefore, it is necessary to design a method for predicting river water temperature to solve the problem that the existing water temperature prediction method relies on complex numerical simulation and prototype observation, needs to process a large number of variables and parameters, and involves tedious mathematical calculation processes, which is not only time-consuming, but also has high professional requirements for computing resources and technical personnel. It cannot provide accurate prediction results in a timely manner, thus leading to delays in management decisions. When considering influencing factors, it only focuses on a single or limited number of factors, ignoring the comprehensive effect of multiple factors in the complex dynamic changes of water temperature, which limits the accuracy and applicability of the prediction results. Summary of the invention

[0006] In view of this, the present invention proposes a method for predicting river water temperature, aiming to solve the problems that the existing water temperature prediction methods are time-consuming, have high professional requirements on computing resources and technical personnel, and have limited accuracy and applicability of prediction results.

[0007] In one aspect, the present invention provides a method for predicting river water temperature, comprising:

[0008] Obtain the basic information data of the reservoir, which includes the vertical water temperature distribution T i , reservoir water level, downstream water temperature T out , discharge flow q dis and pumped storage flow q pump ;

[0009] The elevation of the power generation water intake is h dis and the elevation of the pumped storage inlet h pump The height h between middle Randomly take values ​​and get the data set

[0010] According to the downstream water temperature prediction model, the elevation h to be taken after taking the value middle Construct k downstream water temperature prediction formulas with basic information data;

[0011] According to the time series data of the basic information data, the predicted values ​​of the downstream river water temperature at different times of k downstream river water temperature prediction formulas are obtained.

[0012] The downstream river water temperature prediction value and the measured water temperature of the downstream river The coefficient of determination was R 2 The error evaluation index determines the k downstream river water temperature prediction formulas;

[0013] Find the coefficient of determination R 2 The maximum elevation h middle The value of is used to determine the final downstream river water temperature prediction model;

[0014] Based on the predicted values ​​of the water temperature of each downstream river within a preset period and the measured water temperature of the downstream river Generate the temperature variation law of the water discharged from the reservoir and output it.

[0015] Furthermore, water temperature sensors are set at different depths of the reservoir to measure and record the vertical water temperature distribution T every day. i , used to obtain the change of water temperature at different depths over time; based on the water level of the reservoir area detected by the water level meter, a dynamic change diagram of the reservoir water storage capacity is generated; using a water temperature probe and a flow meter to measure the downstream water temperature T out and the downstream flow q dis ; Using electromagnetic flowmeter and ultrasonic flowmeter to detect the pumped storage flow qpump , used to record flow data at different times during the pumping and releasing process.

[0016] Furthermore, the elevation h of the power generation water intake is measured using a level and a total station. dis and the elevation of the pumped storage water intake h pump , determine the elevation range between the two, and determine the value interval, and use a random number generator to randomly select values ​​in each interval to generate k groups of data.

[0017] Further, the elevation h to be taken middle And the elevation h to be taken middle The corresponding vertical water temperature distribution T i , the reservoir water level, the downstream water temperature T out , the downstream flow q dis and the pumped storage flow q pump Bring in the downstream water temperature prediction model to form k downstream water temperature prediction formulas;

[0018] The downstream water temperature prediction model formula is:

[0019]

[0020] In the formula, T represents the water temperature, T out is the predicted downstream river water temperature, T dis 、T pump Respectively represent the water temperature at the power generation water intake and pumped storage water intake of the hydropower station, T(h middle ) represents the height h middle The water temperature at the water intake; Q is the maximum allowable discharge flow at the water intake, q d is ,q pump They represent the actual discharge flow and average pumped storage flow at the power generation inlet and pumped storage inlet of the hydropower station respectively.

[0021] Furthermore, the collected basic information data are sorted in chronological order to form a time series data set. For the data at each time point, they are respectively substituted into the constructed k prediction formulas, and the prediction value of each time point is calculated in turn according to the time series to obtain k groups of the downstream river water temperature prediction values ​​that change with time. sequence.

[0022] Furthermore, at the same time point, the k groups of downstream river water temperature prediction values ​​are Compared with the actual measured water temperature of the downstream river One-to-one comparison was performed and the coefficient of determination was R 2 The error evaluation index determines the elevation h to be taken middle The value of

[0023] The coefficient of determination R 2 The specific formula is as follows:

[0024]

[0025] In the formula, is the measured average water temperature of the downstream river; is the determination coefficient of the jth downstream river temperature prediction formula

[0026] The coefficient of determination is R 2 The closer it is to 1, the better the fit between the downstream river temperature prediction formula and the measured data. By comparing the R 2 The best fitting formula is selected to determine the quality of k downstream river temperature prediction formulas.

[0027] Furthermore, the determination coefficient R of each downstream river temperature prediction formula is 2 Sort and find out where R 2 The formula with the largest value, the h corresponding to this formula middle The value is the optimal value, and this h middle The value is substituted into the downstream water temperature prediction model to form the final downstream river water temperature prediction model.

[0028] Furthermore, the downstream river water temperature prediction value and the measured water temperature of the downstream river The data is sorted according to the time series, and a line graph of the water temperature over time is drawn using the drawing function. The data is sorted into a text table format using Python's file operation function and saved in CSV format for management personnel to view and analyze specific values.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] (1) The present invention can quickly and systematically analyze the impact of the operation of a hybrid pumped-storage power station on the water temperature of the downstream river, improve the accuracy of the assessment, enhance the reliability of the prediction, and provide a scientific basis for the management and scheduling of water conservancy and power projects. This method combines multiple influencing factors and can reflect the comprehensive impact of the operation of a hybrid pumped-storage power station on the water temperature, ensuring the accuracy of the prediction results.

[0031] (2) The changing trend of the fast quantification formula of the present invention is consistent with the existing prototype observation and simulation research results. The formula simultaneously considers the vertical water temperature distribution in front of the dam of the hybrid pumped storage power station, the water level in the reservoir area, the downstream water temperature, the downstream flow rate, and the influence of the pumped storage flow rate on the downstream river water temperature. middle ), T dis 、Tpump The vertical water temperature distribution and water level in front of the dam on the downstream river water temperature were quantified. middle ,q dis ,q pump The influence of the maximum influencing flow layer, the discharge flow and the pumped storage flow on the water temperature of the downstream river channel was quantified. For a certain reservoir, as the water level rises, the head and depth of the water diversion power generation outlet and the pumped storage outlet increase, T(h middle ), T dis 、T pump The prediction model shows that the water temperature in the downstream river T out The discharge flow rate of the power generation water intake q d is And the pumped storage flow rate q pump The relationship is close and can effectively reflect the impact of water temperature caused by flow changes. Therefore, the changing trend of the rapid quantification formula is consistent with the results of existing prototype observations and numerical simulation studies.

[0032] (3) By establishing a quantitative formula based on the theory of water temperature stratified flow and water intake layer, the present invention can simplify the complex water temperature prediction process, so that reservoir managers can quickly obtain the prediction results of downstream river water temperature changes in real-time scheduling, and then make more timely and effective scheduling decisions, which has good applicability. This simplified method greatly reduces the dependence on computing resources, making the prediction process more efficient and faster.

[0033] (4) The present invention can be compiled by computer language to visually display the change pattern of the downstream water temperature of the reservoir in a flat plane, and can also be output as a text table. This not only enhances the visualization of the results, making it easier for managers to understand and analyze the data, but also allows the data to be conveniently used for further research and report writing, providing convenient data support for research in other related fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0035] Figure 1 A flow chart of a method for predicting river water temperature according to an embodiment of the present invention;

[0036] Figure 2 It is a vertical water temperature distribution diagram in front of a dam actually measured in a reservoir in the second embodiment of the present invention;

[0037] Figure 3 It is a sequence diagram of the measured water level and the downstream flow of a certain reservoir in the second embodiment of the present invention;

[0038] Figure 4 It is a comparison chart of the prototype measured value of the water temperature in the downstream river channel and the value calculated by the optimal formula in the second embodiment of the present invention. DETAILED DESCRIPTION

[0039] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to be able to fully convey the scope of the present invention to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the implementation regulations.

[0040] Reference Figure 1 As shown, in some embodiments of the present application, a method for predicting river water temperature includes:

[0041] Obtain the basic information data of the reservoir, including the vertical water temperature distribution T i , reservoir water level, downstream water temperature T out , discharge flow q dis and pumped storage flow q pump ;

[0042] The elevation of the power generation water intake is h dis and the elevation of the pumped storage inlet h pump The height h between middle Randomly take values ​​and get the data set Where j = 1, 2, ..., k, k is the height h to be taken middle The number of groups;

[0043] According to the downstream water temperature prediction model and using the value to be taken after the value is taken middle Construct k downstream water temperature prediction formulas with basic information data;

[0044] According to the time series data of basic information data, the predicted values ​​of downstream river water temperature at different times of k downstream river water temperature prediction formulas are obtained.

[0045] The predicted water temperature of the downstream river and the measured water temperature of the downstream river The coefficient of determination was R 2 The error evaluation index determines the k downstream river water temperature prediction formulas;

[0046] Find the coefficient of determination R 2The maximum height h to be taken middle The value of is used to determine the final downstream river water temperature prediction model;

[0047] Through computer language compilation, the temperature variation patterns of water discharged from the reservoir are output in the form of flat intuitive display and text table.

[0048] It is understandable that a method for predicting river water temperature not only simplifies the complex calculation process and reduces the dependence on computing resources, but also improves the real-time nature of the prediction, and can quickly reflect the immediate impact of power station operation on downstream water temperature. This method greatly enhances the practicality and reliability of water temperature prediction, allowing reservoir managers to quickly obtain accurate prediction data in a dynamically changing environment, thereby making scientific and reasonable scheduling decisions. At the same time, the present invention also provides strong technical support for the protection of the downstream ecological environment, which helps to maintain the balance and health of the water ecosystem while ensuring power supply.

[0049] Specifically, water temperature sensors are set at different depths of the reservoir to measure and record the vertical water temperature distribution T every day. i , used to obtain the changes of water temperature at different depths over time; use the water level gauge installed on the shore of the reservoir to check and record the water level in the reservoir area to reflect the dynamic changes of the reservoir water storage capacity; use the water temperature probe and current meter combination device to synchronously measure the downstream water temperature T out and the discharge flow q dis ; Use electromagnetic flowmeter and ultrasonic flowmeter installed on the pumped storage pipeline to detect the pumped storage flow q pump , used to record flow data at different times during the pumping and releasing process.

[0050] Specifically, the elevation h of the power generation water intake is measured using a level and a total station. dis and the elevation of the pumped storage inlet h pump , determine the elevation range between the two, and determine the value interval, and use a random number generator to randomly select values ​​in each interval to generate k groups of data.

[0051] Specifically, the height h to be taken middle And the height h to be taken middle Corresponding vertical water temperature distribution T i , reservoir water level, downstream water temperature T out , discharge flow q dis and pumped storage flow q pump Bring it into the downstream water temperature prediction model to form k downstream water temperature prediction formulas

[0052] The downstream water temperature prediction model formula is:

[0053]

[0054] In the formula, T represents the water temperature, T out is the predicted downstream river water temperature, T dis 、T pump Respectively represent the water temperature at the power generation water intake and pumped storage water intake of the hydropower station, T(h middle ) represents the height h middle The water temperature at the water intake; Q is the maximum allowable discharge flow at the water intake, q d is ,q pump They represent the actual discharge flow and average pumped storage flow at the power generation inlet and pumped storage inlet of the hydropower station respectively.

[0055] It is understandable that the method of substituting the elevation to be taken and related data into the downstream water temperature prediction model to construct multiple formulas fully considers the comprehensive influence of multiple key factors on water temperature, and can comprehensively cover the possibility of water temperature changes at different elevations and the relationship between flow and water temperature during power generation and pumping storage, thereby increasing the accuracy and reliability of the prediction, laying the foundation for the subsequent screening of the prediction formula that best suits the actual situation, and effectively improving the scientificity and practicality of the entire river water temperature prediction method, so that it can better cope with complex water temperature changes and provide strong support for reservoir management and ecological protection.

[0056] Specifically, the collected basic information data are sorted in chronological order to form a time series data set. For the data at each time point, they are substituted into the constructed k prediction formulas, and the prediction values ​​of each time point are calculated in turn according to the time series to obtain k groups of downstream river water temperature prediction values ​​that change with time. sequence.

[0057] It is understandable that by organizing the basic information data into a time series data set and substituting it into multiple prediction formulas for calculation, the time dimension information of the data is fully utilized, and the impact of various factors on the river water temperature at different time points is comprehensively examined. Multiple sets of prediction value sequences that change over time can be obtained. This not only helps to analyze the dynamic change trend of water temperature in more detail, but also can screen out the prediction formula that best fits the actual water temperature change law by comparing the performance of different formulas at different times, thereby greatly improving the accuracy and reliability of river water temperature prediction, and providing more valuable reference basis for relevant decisions such as reservoir management and ecological protection.

[0058] Specifically, at the same time point, the predicted water temperature values ​​of the downstream river in group k are Compared with the actual measured water temperature of the downstream river One-to-one comparison was performed and the coefficient of determination was R 2 The error evaluation index determines the height h to be taken middle The value of

[0059] Coefficient of determination R 2 The specific formula is as follows:

[0060]

[0061] In the formula, is the measured average water temperature of the downstream river; is the determination coefficient of the jth downstream river temperature prediction formula

[0062] The coefficient of determination is R 2 The closer it is to 1, the better the fit between the downstream river temperature prediction formula and the measured data. By comparing the R 2 The best fitting formula is selected to determine the quality of k downstream river temperature prediction formulas.

[0063] It is understandable that by comparing the predicted values ​​with the measured values ​​at the same time point and using the determination coefficient as an error evaluation indicator to determine the elevation values ​​to be taken and the screening formula, we can accurately quantify the degree of fit between each prediction formula and the actual situation. By virtue of the characteristic that the closer the determination coefficient is to 1, the better the fit, the most reliable prediction formula can be effectively identified, thereby significantly enhancing the scientificity and accuracy of the entire prediction method, and providing a solid guarantee for the subsequent accurate prediction of river water temperature, scientific management of reservoirs and maintenance of water ecological balance.

[0064] Specifically, the determination coefficient R of each downstream river temperature prediction formula is 2 Sort and find out where R 2 The formula with the largest value, the h corresponding to this formula middle The value is the optimal value, and this h middle The value is substituted into the downstream water temperature prediction model to form the final downstream river water temperature prediction model.

[0065] Specifically, the predicted water temperature of the downstream river is and the measured water temperature of the downstream river The data is sorted according to the time series, and a line graph of the water temperature over time is drawn using the drawing function. The data is sorted into a text table format using Python's file operation function and saved in CSV format for management personnel to view and analyze specific values.

[0066] It can be understood that by sorting the determination coefficients to find the value corresponding to the maximum value and substituting it into the model to form the final prediction model, this method can accurately determine the optimal parameter combination among a variety of possible model construction conditions, so that the final river water temperature prediction model is in line with the actual water temperature change law to the greatest extent, effectively improving the prediction accuracy and reliability of the model, and providing highly accurate and practical water temperature prediction results for water conservancy project management, ecological environmental protection, etc., to ensure the scientificity and rationality of related decisions.

[0067] On the one hand, some embodiments of the present invention also provide a method for quickly predicting the impact of a pumped-storage power station on the water temperature of a downstream river.

[0068] Embodiment 1

[0069] Step A: Obtain the vertical water temperature distribution T of the reservoir measured historically i , reservoir water level, downstream water temperature T out Discharge flow qd is And the pumped storage flow q pump .

[0070] Step B, by middle Randomly take values ​​and obtain several groups Among them, h middle is the elevation variable to be taken, located at h pump and h dis j=1,2,……,k,k is h middle The number of groups is calculated, and k downstream water temperature prediction formulas are established based on the downstream water temperature prediction model of the hybrid pumped storage power station.

[0071] The downstream water temperature prediction model in step B is:

[0072]

[0073] In the formula, T represents the water temperature, T out is the predicted downstream river water temperature, T dis 、T pump Respectively represent the water temperature at the power generation water intake and pumped storage water intake of the hydropower station, T(h middle ) represents the height h middle The water temperature at the water intake; Q is the maximum allowable discharge flow at the water intake, q d is ,q pump represent the actual discharge flow and average pumped storage flow at the power generation and pumped storage inlets of the hydropower station, respectively. d is and q pump It is determined by the reservoir historical data collected in step A.

[0074] Step C, based on the vertical water temperature distribution, reservoir water level, downstream water temperature, downstream flow rate and pumped storage flow time series collected in step A, obtain the downstream water temperature prediction value of k downstream river channel water temperature prediction formulas at time i

[0075] Step D: The downstream river water temperature prediction values ​​at different times obtained by k downstream water temperature prediction formulas are Compared with the measured water temperature in the downstream river Compare and compare the value h in the downstream river water temperature prediction model middle , using error evaluation index to determine h middle The value of is then used to determine the downstream river water temperature prediction model of the hybrid pumped-storage hydropower station.

[0076] The error evaluation index in step D uses the determination coefficient R 2 To determine the quality of k downstream river temperature prediction formulas, R 2 The larger the value, the better the model simulation effect is, and the greater the maximum determination coefficient R 2 The corresponding h middle The optimal h value to be used in the downstream river water temperature prediction model middle Get the value.

[0077] The coefficient of determination R 2 The specific formula is as follows:

[0078]

[0079] In the formula, is the measured average water temperature of the downstream river; is the determination coefficient of the water temperature prediction formula for the jth downstream river channel.

[0080] Embodiment 2:

[0081] This example takes the downstream river water temperature prediction research of a hybrid pumped storage hydropower station as an example, and proposes a rapid prediction formula for the downstream river water temperature through calibration with measured water temperature data. The specific implementation steps are as follows:

[0082] Step A, obtain the measured vertical water temperature distribution T of a hybrid pumped storage power station on the 5th, 15th and 25th of each month from 2019 / 5 / 5 to 2020 / 4 / 25 i , downstream water temperature T out Discharge flow q dis And the pumped storage flow q pump ,like Figure 2 and Figure 3 shown.

[0083] Step B, by middle Randomly select values ​​and get 6 h middle (j=1,2,……,6); Six downstream water temperature prediction formulas are established based on the downstream water temperature prediction model, as shown in the following table;

[0084] Table 1 shows the formula for establishing the prediction model for different downstream water temperatures. middle Value and R 2

[0085] Discharge water temperature prediction formula <![CDATA[h middle (m)]]> <![CDATA[R 2 ]]> Formula 1 2520 0.68 Formula 2 2530 0.78 Formula 2 2540 0.75 Formula 3 2550 0.82 Formula 4 2555 0.81 Formula 5 2560 0.85 Formula 6 2565 0.92

[0086] Step C: Based on the vertical water temperature distribution, reservoir water level, downstream water temperature, downstream flow rate and pumped storage flow time series collected in step A, the downstream water temperature prediction values ​​of the six downstream river channel water temperature prediction formulas at time i are obtained. Among them, Q is 1414m3 / s, which is determined when the reservoir is planned to be built and can be determined based on the historical discharge flow.

[0087] Step D: The downstream water temperature prediction values ​​at different times obtained by the downstream river water temperature prediction model are Compared with the measured water temperature in the downstream river Compare and get different h middle In this case, the minimum RSD is 18.1%. Figure 4 As shown. At this time h middle =h2565; and then finally determine the water temperature prediction formula of the downstream river channel of the hybrid pumped storage hydropower station as shown in the formula; Among them, the power generation water intake of the reservoir is at an elevation of 2510m in front of the reservoir dam, which is the position determined when the reservoir was planned and built. The pumped storage water intake of the reservoir is at an elevation of 2570m in front of the reservoir dam. The average pumped storage flow of the hybrid pumped storage hydropower station is q pump It is 257.4m3 / s.

[0088]

[0089] It should be noted that:

[0090] In the description provided herein, a large number of specific details are described. However, it is understood that the embodiments of the present application can be practiced without these specific details. In some instances, well-known structures and technologies are not shown in detail so as not to obscure the understanding of this description.

[0091] Furthermore, those skilled in the art will appreciate that although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features from different embodiments is meant to be within the scope of the present application and to form different embodiments.

[0092] The above is only a preferred specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for predicting river water temperature, characterized in that: include: Obtain the basic information data of the reservoir, which includes the vertical water temperature distribution T i , reservoir water level, downstream water temperature T out , discharge flow q dis and pumped storage flow q pump ; The elevation of the power generation water intake h dis and the elevation of the pumped storage inlet h pump The height h between middle Randomly take values ​​and get the data set According to the downstream water temperature prediction model, the elevation h to be taken after taking the value middle Construct k downstream water temperature prediction formulas with basic information data; According to the time series data of the basic information data, the predicted values ​​of the downstream river water temperature at different times of k downstream river water temperature prediction formulas are obtained. The downstream river water temperature prediction value and the measured water temperature of the downstream river The coefficient of determination was R 2 The error evaluation index determines the k downstream river water temperature prediction formulas; Find the coefficient of determination R 2 The maximum elevation h middle The value of is used to determine the final downstream river water temperature prediction model; Based on the predicted values ​​of the water temperature of each downstream river within a preset period and the measured water temperature of the downstream river Generate the temperature variation law of the water discharged from the reservoir and output it.

2. A method for predicting river water temperature according to claim 1, characterized in that: Water temperature sensors are set at different depths of the reservoir to measure and record the vertical water temperature distribution T every day. i , used to obtain the change of water temperature at different depths over time; based on the water level of the reservoir area detected by the water level meter, a dynamic change diagram of the reservoir water storage capacity is generated; using a water temperature probe and a flow meter to measure the downstream water temperature T out and the downstream flow rate q d is ; Using electromagnetic flowmeter and ultrasonic flowmeter to detect the pumped storage flow q pump , used to record flow data at different times during the pumping and releasing process.

3. A method for predicting river water temperature according to claim 1, characterized in that: The elevation h of the power generation water intake is measured by using a level and a total station. dis and the elevation of the pumped storage water intake h pump , determine the elevation range between the two, and determine the value interval, and use a random number generator to randomly select values ​​in each interval to generate k groups of data.

4. A method for predicting river water temperature according to claim 1, characterized in that: The height h to be taken middle And the elevation h to be taken middle The corresponding vertical water temperature distribution T i , the reservoir water level, the downstream water temperature T out , the downstream flow q dis and the pumped storage flow q pump Bring in the downstream water temperature prediction model to form k downstream water temperature prediction formulas; The downstream water temperature prediction model formula is: In the formula, T represents the water temperature, T out is the predicted downstream river water temperature, T dis 、T pump Respectively represent the water temperature at the power generation water intake and pumped storage water intake of the hydropower station, T(h middle ) represents the height h middle The water temperature at the water intake; Q is the maximum allowable discharge flow at the water intake, q d is ,q pump They represent the actual discharge flow and average pumped storage flow at the power generation inlet and pumped storage inlet of the hydropower station respectively.

5. A method for predicting river water temperature according to claim 1, characterized in that: The collected basic information data are sorted in chronological order to form a time series data set. For the data at each time point, they are respectively substituted into the constructed k prediction formulas, and the prediction value of each time point is calculated in turn according to the time series to obtain k groups of the downstream river water temperature prediction values ​​that change with time. sequence.

6. A method for predicting river water temperature according to claim 1, characterized in that: At the same time point, the downstream river water temperature prediction values ​​of group k are Compared with the actual measured water temperature of the downstream river One-to-one comparison was performed and the coefficient of determination was R 2 The error evaluation index determines the elevation h to be taken middle The value of The coefficient of determination R 2 The specific formula is as follows: In the formula, is the measured average water temperature of the downstream river; is the determination coefficient of the jth downstream river temperature prediction formula The coefficient of determination is R 2 The closer it is to 1, the better the fit between the downstream river temperature prediction formula and the measured data. By comparing the R 2 The best fitting formula is selected to determine the quality of k downstream river temperature prediction formulas.

7. A method for predicting river water temperature according to claim 1, characterized in that: The determination coefficient R of each downstream river temperature prediction formula is 2 Sort and find out where R 2 The formula with the largest value, the h corresponding to this formula middle The value is the optimal value, and this h middle The value is substituted into the downstream water temperature prediction model to form the final downstream river water temperature prediction model.

8. A method for predicting river water temperature according to claim 1, characterized in that: The downstream river water temperature prediction value and the measured water temperature of the downstream river The data is sorted according to the time series, and a line graph of the water temperature over time is drawn using the drawing function. The data is sorted into a text table format using Python's file operation function and saved in CSV format for management personnel to view and analyze specific values.

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