Semi-theoretical and semi-empirical method for quickly predicting water temperature based on air temperature

Abstract

The invention relates to a semi-theoretical and semi-empirical method for quickly predicting water temperature based on air temperature. The method comprises the following steps: collecting data; establishing a nonlinear relation between the water temperature and the air temperature; solving five semi-theoretical semi-empirical parameters; acquiring future temperature data; predicting future water temperature; and drawing a predicted water temperature and air temperature curve. According to the invention, a correlation between water temperature and air temperature is constructed based on a water body energy conservation equation, and a semi-theoretical and semi-empirical water temperature rapid prediction method based on air temperature is provided. According to the method, the water body energy conservation theory and the statistical regression theory are fused, and the interpretability of a mechanism model and the simplicity and convenience of a statistical model are both achieved. The required calculation data is less, and the water temperature process can be calculated only through the air temperature data. The method is rapid and efficient, the water temperature is rapidly calculated by counting the non-linear relation between the regressed water temperature and the air temperature, and a complex equation set does not need to be solved, so that the operation speed is increased, water temperature prediction is more timely, and wider decision-making time is provided for disaster prevention and reduction.

Description

Technical Field

[0001] The present invention relates to a semi-theoretical and semi-empirical method for rapidly predicting water temperature based on air temperature, which is a hydraulic calculation method and a method for rapidly estimating the water temperature of open channels for water conveyance in water network projects. Background Art

[0002] The water temperature of medium and long-distance water conveyance channels in the north temperate zone at 35-40° north latitude (such as the Yellow River Basin in northern China) fluctuates significantly between day and night. In some cases, the diurnal temperature difference even exceeds 0.8°C. This phenomenon of rapid water temperature fluctuation in a short period of time not only affects the water ecological environment and water quality stability of rivers and channels, but may also directly affect the icing of water bodies in long-distance water diversion projects, thereby threatening the safety of the water conveyance system. Especially in winter, if local icing occurs due to water temperature changes during open channel water conveyance, it may cause problems such as ice jams and flow breaks, and in severe cases, it may even affect the normal operation of the entire water network system.

[0003] At present, the water temperature mechanism model based on energy conservation is comprehensively affected by multiple factors such as meteorological conditions (such as solar radiation, wind speed, air temperature), hydrodynamic processes (such as flow velocity, turbulent diffusion), and aquatic ecological processes (such as biological metabolism, pollutant exchange). There are still simplifications in some mechanisms (such as ice-water phase change, heat exchange process) in the existing model, which affects the prediction accuracy of the model. Secondly, the mechanism model requires high-resolution meteorological data, hydrological data, and flow field data, but the actual monitoring network often fails to provide sufficiently dense spatio-temporal data, resulting in limited application scenarios of the model. Many water temperature empirical models rely on statistical regression methods for heat exchange calculation, but the relevant parameters are often based on specific regions or experimental data, and their adaptability is poor when transplanted to other basins, resulting in limited application scenarios.

[0004] In summary, the existing water temperature prediction models cannot meet the requirements of rapid water temperature prediction for open channels in water network projects, restricting the high-quality and rapid development of water network projects. There is an urgent need to establish a rapid water temperature prediction method for open channels in water network systems. Summary of the Invention

[0005] To overcome the problems of the existing technology, the present invention proposes a semi-theoretical and semi-empirical method for rapidly predicting water temperature based on air temperature. The complex air temperature prediction is greatly simplified by integrating the theory of water body energy conservation and the theory of statistical regression, solving the problem of rapid water temperature prediction for open channels in water conveyance.

[0006] The object of the present invention is achieved as follows: A semi-theoretical and semi-empirical method for rapidly predicting water temperature based on air temperature, and the steps of the method are as follows:

[0007] Step 1, data collection: For the historical water temperature and air temperature data required for calculating the water conveyance open channel, that is, collect the air temperature and water temperature data of the water body in the past 20 days or more than 20 days;

[0008] Step 2, establish the non-linear relationship between water temperature and air temperature: Based on the water body energy conservation equation of the water conveyance open channel in the water network project, simplify the heat exchange process between the water body and the air to obtain the non-linear relationship between water temperature and air temperature. The equation:

[0009]

[0010] Where, Δt is the calculated time step; is the water temperature corresponding to the current time; is the water temperature corresponding to the next time; is the air temperature corresponding to the current time; c1, c2, c3, c4, c5 are 5 semi-theoretical and semi-empirical parameters to be determined; t k is the current calculated time; t f is the period of water temperature change;

[0011] Step 3, solve the five semi-theoretical and semi-empirical parameters: Based on the collected air temperature and water temperature data, use the least squares method in regression analysis to fit and solve the five semi-theoretical and semi-empirical parameters in Equation (1);

[0012] Step 4, obtain future air temperature data: Obtain the future air temperature data of adjacent meteorological stations through the air temperature prediction model or the meteorological observatory;

[0013] Step 5, predict the future water temperature: Substitute the obtained future air temperature prediction data into Equation (2) to quickly predict the future water temperature value of the corresponding water body:

[0014]

[0015] Step 6, draw the predicted water temperature and air temperature curves: The abscissa is stepped in days, and the ordinate is stepped in degrees Celsius. Mark the predicted air temperature curve and the corresponding water temperature prediction curve.

[0016] The advantages and beneficial effects of the present invention are: The present invention constructs the correlation between water temperature and air temperature based on the water body energy conservation equation, and proposes a semi-theoretical and semi-empirical method for quickly predicting water temperature based on air temperature. This method combines the water body energy conservation theory and the statistical regression theory, and has both the interpretability of the mechanism model and the simplicity of the statistical model. The required calculation data is small, and only air temperature data is needed to calculate the water temperature process. This method is fast and efficient. It quickly calculates the water temperature through the non-linear relationship between the statistical regression water temperature and air temperature, without the need to solve complex equations, thereby improving the operation speed, making the water temperature prediction more timely, and providing more generous decision-making time for disaster prevention and mitigation. Description of the Drawings

[0017] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0018] Figure 1 is the flowchart of the method described in the embodiments of the present invention;

[0019] Figure 2 is the measured air temperature and water temperature data of the Hutuo River inverted siphon check gate from December 1, 2023 to January 31, 2024, which is an application example of the embodiments of the present invention;

[0020] Figure 3 is the predicted air temperature and water temperature curves of the Hutuo River inverted siphon check gate from February 1, 2024 to March 1, 2024, which is an application example of the embodiments of the present invention. Specific implementation manners

[0021] Embodiment:

[0022] This embodiment is a semi-theoretical and semi-empirical method for quickly predicting water temperature based on air temperature.

[0023] The following combines the application example of the water temperature prediction in front of the Hutuo River inverted siphon check gate of the backbone project of the national water network in China to illustrate the specific implementation manner of this embodiment. The flowchart of the method is as Figure 1 shown, and the specific implementation steps are as follows:

[0024] Step 1, data collection: For the historical water temperature and air temperature data of the water conveyance open channel to be calculated, that is, collect the air temperature and water temperature data of the water body for the past 20 days or more than 20 days.

[0025] In this step, the measured data of the air temperature and water temperature of the Hutuo River inverted siphon check gate in front of the middle route project of the South-to-North Water Diversion Project from December 1, 2023 to January 31, 2024 for a total of 62 days are collected and sorted out, and a table is made with the temperature as the vertical axis and the time as the horizontal axis to form a comparison of the changes in water temperature and air temperature, as Figure 2 shown. In the table, it is calibrated in degrees Celsius by the thermometer, and the time is calculated in days.

[0026] Step 2, establish the non-linear relationship between water temperature and air temperature: Based on the energy conservation equation of the water body in the water conveyance open channel of the water network project, the non-linear relationship between water temperature and air temperature can be obtained by simplifying the heat exchange process between the water body and the air. The equation:

[0027]

[0028] where, Δt is the calculated time step; is the water temperature corresponding to the current time; is the water temperature corresponding to the next time; is the air temperature corresponding to the current time; c1, c2, c3, c4, c5 are five semi-theoretical and semi-empirical parameters to be determined; t k is the current calculated time; t f is the period of water temperature change, generally taken as 1 year, i.e., 31536000 seconds.

[0029] Step 3, solve the five semi-theoretical and semi-empirical parameters: Based on the collected air temperature and water temperature data, use the least squares method in regression analysis to fit and solve the five semi-theoretical and semi-empirical parameters in Equation (1).

[0030] This step is based on Figure 2 the air temperature and water temperature data in, and use the least squares method in regression analysis to fit and solve the five semi-theoretical and semi-empirical parameters in Equation (1), that is, substitute the air temperature and water temperature arrays at different times into Equation (1) to obtain an algebraic equation system containing five unknown variables c1, c2, c3, c4, c5, and then obtain the solution with the minimum fitting error through the least squares method. The calculation results are shown in the following table.

[0031] Table 1 Values of Five Semi-theoretical and Semi-empirical Parameters

[0032] <![CDATA[c1]]> <![CDATA[c2]]> <![CDATA[c3]]> <![CDATA[c4]]> <![CDATA[c5]]> -1.53E-02 1.34E-06 3.78E-06 -1.55E-02 1.71E-04

[0033] Step 4, obtain future air temperature data: Obtain the future air temperature data of adjacent meteorological stations through the air temperature prediction model or meteorological observatory.

[0034] This step is to collect the air temperature data predicted by the adjacent meteorological station, Shijiazhuang Station, of authoritative meteorological observatories such as the China National Meteorological Center from February 1, 2024 to March 1, 2024.

[0035] Step 5, predict the future water temperature: Substitute the obtained future air temperature prediction data into Equation (2) to quickly predict the future water temperature value of the corresponding water body.

[0036]

[0037] This step substitutes the obtained air temperature prediction data into Equation (2) to quickly predict the water temperature value of the Hutuo River Inverted Siphon Check Gate from February 1, 2024 to March 1, 2024.

[0038] Step 6, draw the predicted water temperature and air temperature curves: Mark the predicted air temperature curve and the corresponding water temperature prediction curve with the abscissa stepping by days and the ordinate stepping by degrees Celsius.

[0039] Figure 3 shows the predicted air temperature and water temperature curves of the Hutuo River Inverted Siphon Check Gate from February 1, 2024 to March 1, 2024. Figure 3Clearly shows the predicted temperature and water temperature change process from February 1, 2024 to March 1, 2024. Among them, the air temperature is the forecast result of the meteorological station, while the water temperature is the rapid calculation result of this method. Generally speaking, the rise and fall of the water temperature are positively correlated with the rise and fall of the air temperature, and the fluctuation range of the water temperature is smaller than that of the air temperature.

[0040] Finally, it should be noted that the above is only used to illustrate the technical solution of the present invention rather than a limitation. Although the present invention has been described in detail with reference to the preferred arrangement, those of ordinary skill in the art should understand that the technical solution of the present invention (such as the composition of the river channel, the application of various formulas, the sequence of steps, etc.) can be modified or equivalently replaced without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A semi-theoretical and semi-empirical method for quickly predicting water temperature based on air temperature, characterized in that: The steps of the method are as follows: Step 1, data collection: for the historical water temperature and air temperature data of the water delivery open channel to be calculated, that is, collect the air temperature and water temperature data of the water body for the past 20 days or more; Step 2, establish the nonlinear relationship between water temperature and air temperature: Based on the water energy conservation equation of the open channel of the water network project, the nonlinear relationship between water temperature and air temperature that can be obtained by simplifying the heat exchange process between water and air is: Where Δt is the time step of the calculation; is the water temperature corresponding to the current time; is the water temperature corresponding to the next time; is the temperature corresponding to the current time; c1, c2, c3, c4, c5 are five semi-theoretical and semi-empirical parameters to be determined; t k is the current calculation time; t f is the period of water temperature change; Step 3, solving five semi-theoretical and semi-empirical parameters: Based on the collected air and water temperature data, the least square method in regression analysis is used to fit and solve the five semi-theoretical and semi-empirical parameters in equation (1); Step 4, obtaining future temperature data: obtaining future temperature data predicted by nearby meteorological stations through temperature forecast models or meteorological stations; Step 5, predicting future water temperature: Substitute the obtained future temperature prediction data into equation (2) to quickly predict the future water temperature value of the corresponding water body; Step 6, draw the predicted water temperature and air temperature curves: the horizontal axis is in days, the vertical axis is in degrees Celsius, mark the predicted air temperature curve and the corresponding water temperature prediction curve.

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