Plateau area natural drinking water resource water quality monitoring method

Abstract

The invention relates to the technical field of water quality monitoring, and discloses a plateau area natural drinking water resource water quality monitoring method, which comprises the following steps: arranging a plurality of monitoring point positions at the transverse and longitudinal positions of an upstream slow release area and a downstream slow release area of a target drainage basin; arranging water quality monitoring sensor groups at transverse monitoring point positions of the upstream slow-release area and the downstream slow-release area, acquiring a water quality monitoring data group of each transverse monitoring point position, and performing data preprocessing and standardization; flow velocimeters are arranged at longitudinal monitoring points of the upstream slow-release area and the downstream slow-release area, water flow velocity data sets of the longitudinal monitoring points of the upstream slow-release area and the downstream slow-release area are obtained, the average value is calculated, standardization processing is carried out, the standardized average water flow velocity is obtained, and correlation analysis is carried out; obtaining an influence coefficient of the water flow velocity on each piece of water quality monitoring data, and constructing a water quality monitoring model based on the water flow velocity for predicting the water quality monitoring data; the method improves the water quality monitoring data acquisition precision.

Description

Technical Field

[0001] This invention relates to the field of water quality monitoring technology, specifically to a method for monitoring the water quality of natural drinking water resources in plateau areas. Background Technology

[0002] Natural drinking water in plateau regions is characterized by its long water age, small molecular clusters, and rich content of various trace elements, giving it significant advantages, potential, and promising prospects for developing the natural drinking water industry. However, human activities and climate influences have led to water pollution and high hardness in plateau regions. Furthermore, key water resource protection areas such as rivers and lakes in plateau regions, due to their unique natural ecology and strategic importance, require continuous monitoring and management of water quality. Current water quality monitoring technologies largely rely on specialized sampling devices to sample water sources. These devices can only sample the surface of the water, not deeper layers, resulting in inaccurate monitoring data. Additionally, methods using automated optical equipment in designated areas exist, but these devices are expensive and require significant human resources. Summary of the Invention

[0003] To address the aforementioned shortcomings in the existing technology, this invention provides a method for monitoring the water quality of natural drinking water resources in plateau areas, thereby solving the problems of low accuracy of water quality monitoring data and high labor costs in the existing technology.

[0004] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows: A method for monitoring the water quality of natural drinking water resources in plateau areas includes the following steps: S1. Obtain the upstream and downstream slow-release zones of the target watershed, and set up several monitoring points in the horizontal and vertical positions of the upstream and downstream slow-release zones of the target watershed to obtain the horizontal monitoring points and the vertical monitoring points. S2. Water quality monitoring sensor groups are deployed at horizontal monitoring points in the upstream and downstream slow-release zones to acquire water quality monitoring data groups at each horizontal monitoring point. The water quality monitoring data groups are then preprocessed and standardized to obtain standardized water quality monitoring data groups. S3. Install flow meters at longitudinal monitoring points in the upstream and downstream slow-release zones to obtain water flow velocity data sets at the longitudinal monitoring points in the upstream and downstream slow-release zones. Calculate the average value of the water flow velocity data sets at the longitudinal monitoring points in the upstream and downstream slow-release zones respectively, and perform standardization processing to obtain a standardized average water flow velocity. S4. Use the standardized average water flow velocity to perform correlation analysis on the standardized water quality monitoring data set, obtain the influence coefficient of water flow velocity on each water quality monitoring data, and construct a water quality monitoring model based on water flow velocity to predict water quality monitoring data.

[0005] Furthermore, step S1 specifically includes: The upstream and downstream slow-release zones of the target watershed in the study area were selected, and monitoring points were set at equal intervals in the horizontal and vertical directions of the upstream and downstream slow-release zones, respectively, to obtain the horizontal and vertical monitoring points.

[0006] Furthermore, step S2 specifically includes: S21. Water quality monitoring sensor groups are set up at the horizontal monitoring points in the upstream and downstream slow release zones. The water quality sensor groups include water temperature sensors, pH sensors, dissolved oxygen sensors, conductivity sensors and turbidity sensors to obtain water quality monitoring data groups containing water temperature, pH value, dissolved oxygen, conductivity and turbidity. S22. The trispline interpolation method is used to preprocess the water quality monitoring data set for outliers and missing values, and the preprocessed water quality monitoring data set is then standardized to obtain a standardized water quality monitoring data set.

[0007] Furthermore, step S3 specifically includes: S31. Deploy flow meters at longitudinal monitoring points in the upstream slow-release zone to obtain a set of water flow velocity data at these points, namely:

[0008] in, This represents the water flow velocity data set at the longitudinal monitoring points in the upstream slow-release zone. This indicates the number of longitudinal monitoring points in the upstream slow-release zone. This indicates the number of water flow velocities monitored at each longitudinal monitoring point in the upstream slow-release zone. This indicates the flow velocity at the first longitudinal monitoring point in the upstream slow-release zone. This indicates the first longitudinal monitoring point in the upstream slow-release zone. The water flow velocity, The first term representing the upstream slow-release zone The first water flow velocity at the longitudinal monitoring point, The first term representing the upstream slow-release zone The first of the longitudinal monitoring points The water flow velocity; S32. Deploy flow meters at longitudinal monitoring points in the downstream slow-release zone to obtain a set of water flow velocity data at the longitudinal monitoring points in the downstream slow-release zone, namely:

[0009] in, This represents the water flow velocity data set at the longitudinal monitoring points in the downstream slow-release zone. This indicates the number of longitudinal monitoring points in the downstream slow-release zone. This indicates the number of water flow velocities monitored at each longitudinal monitoring point in the downstream slow-release zone. This indicates the flow velocity at the first longitudinal monitoring point in the downstream slow-release zone. This indicates the first longitudinal monitoring point in the downstream slow-release zone. The water flow velocity, The downstream sustained-release zone is represented by the first The first water flow velocity at the longitudinal monitoring point, The downstream sustained-release zone is represented by the first The first of the longitudinal monitoring points The water flow velocity; S33. Calculate the average value of the water flow velocity data sets at the longitudinal monitoring points in the upstream slow-release zone and the average value of the water flow velocity data sets at the longitudinal monitoring points in the downstream slow-release zone, respectively:

[0010] in, This represents the average value of the water flow velocity data set at the longitudinal monitoring points in the upstream slow-release zone. This represents the average value of the water flow velocity data set at the longitudinal monitoring points in the downstream slow-release zone. S34. Calculate the average water flow velocity based on the average value of the water flow velocity data sets from the longitudinal monitoring points in the upstream slow-release zone and the average value of the water flow velocity data sets from the longitudinal monitoring points in the downstream slow-release zone, i.e.:

[0011] in, Indicates the average water flow velocity; S35. The average water flow velocity is standardized to obtain the standardized average water flow velocity, i.e.:

[0012] in, This represents the standardized average water flow velocity. This indicates the maximum value of the water flow velocity. This represents the minimum water flow velocity.

[0013] Furthermore, step S4 specifically includes: S41. Based on the Pearson coefficient method, correlation analysis is performed on the standardized water quality monitoring data set using the standardized average water flow velocity, and the influence coefficient of water flow velocity on each water quality monitoring data is calculated, i.e.:

[0014] in, This represents the coefficient indicating the influence of water temperature on water flow velocity. This indicates the number of rows representing the horizontal monitoring points between the upstream and downstream slow-release zones. Indicates the first The first horizontal monitoring point A water temperature value, This represents the standardized average water flow velocity. This represents the coefficient indicating the influence of pH value on water flow velocity. Indicates the first The first horizontal monitoring point A pH value, This represents the coefficient indicating the influence of dissolved oxygen on water flow velocity. Indicates the first The first horizontal monitoring point Dissolved oxygen value, This represents the coefficient indicating the influence of conductivity value on water flow velocity. Indicates the first The first horizontal monitoring point Each conductivity value, This represents the coefficient indicating the influence of turbidity on water flow velocity. Indicates the first The first horizontal monitoring point One turbidity value; S42. Based on the calculated influence coefficient of water flow velocity on various water quality monitoring data, establish a water quality monitoring model based on water flow velocity, namely:

[0015] in, This represents the predicted water quality monitoring data. This indicates a selector, meaning that the corresponding water quality monitoring data is selectively output based on the input water flow velocity.

[0016] The present invention has the following beneficial effects: 1. The present invention proposes a method for monitoring the water quality of natural drinking water resources in plateau areas. By acquiring the upstream and downstream slow-release zones of the target watershed and setting up monitoring points in both horizontal and vertical directions, the method makes full use of the influence of the slow-release zones on water quality monitoring data and improves the accuracy of water quality monitoring data collection. 2. Collect the water flow velocity at the longitudinal monitoring points in the upstream slow-release zone and the downstream slow-release zone respectively, taking into full account the large variation in water flow velocity between the upstream and downstream areas, thereby reducing the water flow velocity error in the target watershed; 3. The correlation analysis between water flow velocity and various water quality monitoring data is carried out using the Pearson coefficient method, thereby establishing a water quality monitoring model based on water flow velocity to predict water quality monitoring data, improve the accuracy of water quality monitoring prediction and reduce labor costs. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a method for monitoring the quality of natural drinking water resources in plateau regions, as proposed in this invention. Detailed Implementation

[0018] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0019] like Figure 1 As shown, a method for monitoring the water quality of natural drinking water resources in plateau areas includes the following steps: S1. Obtain the upstream and downstream slow-release zones of the target watershed. Set up several monitoring points in the horizontal and vertical positions of the upstream and downstream slow-release zones of the target watershed to obtain the horizontal and vertical monitoring points.

[0020] In this embodiment, a plateau region was selected as the study area, and the target watershed of the study area was used to set up monitoring points. Among them, the upstream and downstream slow-release zones of the target watershed were selected for the experiment. The purpose is that water quality monitoring of slow-release zones, also known as buffer zones, is usually more important and effective than that of unprotected river sections or river sections without slow-release zones, for example: (1) Slow-release zones can filter pollutants from farmland, urban and industrial areas, including nutrients, sediments and chemicals, through the action of vegetation, soil and microorganisms; therefore, water quality monitoring in these areas can help assess the effectiveness of these natural filtration processes. (2) Slow-release zones are an important part of river ecosystems, providing habitats for many aquatic and terrestrial organisms; by monitoring the water quality of slow-release zones, the health status of the ecosystem can be understood, and potential problems can be identified and resolved in a timely manner. (3) Slow-release zones help to slow down flood flow and absorb floodwater, reducing the impact of floods on downstream areas; in water quality monitoring, water quality changes during floods can be considered to assess the effectiveness of slow-release zones in flood control. (4) The slow-release zone can promote the conversion of surface water into groundwater, which helps to replenish groundwater resources; by monitoring the water quality of the slow-release zone, the water quality changes during the groundwater replenishment process can be assessed.

[0021] Specifically, step S1 includes: The upstream and downstream slow-release zones of the target watershed in the study area were selected, and monitoring points were set at equal intervals in the horizontal and vertical directions of the upstream and downstream slow-release zones, respectively, to obtain the horizontal and vertical monitoring points.

[0022] In this embodiment, a method is set at the lateral position between the upstream and downstream sustained-release zones. , each line set Several monitoring points were set up longitudinally in the upstream slow-release zone. Columns, each column has Each monitoring point is used for data collection. The water flow velocity; set at the longitudinal position of the downstream slow-release zone. Columns, each column has Each monitoring point is used for data collection. The water flow velocity; among which .

[0023] S2. Water quality monitoring sensor groups are deployed at horizontal monitoring points in the upstream and downstream slow-release zones to acquire water quality monitoring data sets at each horizontal monitoring point. The water quality monitoring data sets are then preprocessed and standardized to obtain standardized water quality monitoring data sets.

[0024] Specifically, step S2 includes S21-S22: S21. Water quality monitoring sensor groups are deployed at horizontal monitoring points in the upstream and downstream slow-release zones. The water quality sensor groups include water temperature sensors, pH sensors, dissolved oxygen sensors, conductivity sensors, and turbidity sensors to obtain water quality monitoring data sets containing water temperature, pH value, dissolved oxygen, conductivity, and turbidity.

[0025] In this embodiment, only some important monitoring indicators from water quality monitoring data were selected for subsequent water quality monitoring. Water temperature is a fundamental indicator for evaluating surface water quality. Changes in surface water temperature have a significant negative impact on the growth and development of aquatic plants and animals, affecting their growth, development, and reproductive time and efficiency. Sustained high temperatures can alter the physicochemical properties of water, resulting in water quality deterioration, blackening, odor, and algal blooms. Therefore, selecting water temperature to assess the water quality of the target watershed is necessary. pH is an indicator reflecting the acidity or alkalinity of water. National standards stipulate that the pH of urban drinking water should be between 6.5 and 8.5, and that of rural drinking water should be between 6.5 and 9.5. Excessive pH fluctuations indicate severe external pollution, possibly caused by the discharge of industrial wastewater with high acidity or alkalinity. pH also primarily affects the self-purification capacity of water bodies; excessive pH changes reduce this capacity, leading to water quality deterioration. Therefore, selecting pH value to assess water quality is also necessary. Dissolved oxygen is the oxygen dissolved in water, primarily consumed by the respiration of aquatic plants and animals and by microorganisms decomposing organic matter. Dissolved oxygen is an important indicator for surface water monitoring, reflecting the water body's self-purification capacity. Therefore, monitoring dissolved oxygen is essential. Conductivity primarily measures the electrical conductivity of water, used to monitor ion concentration. Conductivity is mainly determined by various conductive substances present in water, such as chemical substances, heavy metals, and impurities. Therefore, water conductivity can reflect the impurity content in water to a certain extent. Thus, monitoring conductivity is also necessary. Turbidity measures the amount of suspended solids in water. Suspended solids hinder the photosynthesis and respiration of aquatic organisms and also affect the aesthetics of the water. Therefore, monitoring turbidity is also necessary.

[0026] S22. The trispline interpolation method is used to preprocess the water quality monitoring data set for outliers and missing values, and the preprocessed water quality monitoring data set is then standardized to obtain a standardized water quality monitoring data set.

[0027] In this embodiment, the purpose of data preprocessing is to improve the accuracy of water quality monitoring data collection, and the purpose of standardization is to unify the dimensions.

[0028] S3. Install flow meters at longitudinal monitoring points in the upstream and downstream slow-release zones to obtain water flow velocity data sets at the longitudinal monitoring points in the upstream and downstream slow-release zones. Calculate the average value of the water flow velocity data sets at the longitudinal monitoring points in the upstream and downstream slow-release zones respectively, and perform standardization processing to obtain a standardized average water flow velocity.

[0029] Specifically, step S3 includes S31-S35: S31. Deploy flow meters at longitudinal monitoring points in the upstream slow-release zone to obtain a set of water flow velocity data at these points, namely:

[0030] in, This represents the water flow velocity data set at the longitudinal monitoring points in the upstream slow-release zone. This indicates the number of longitudinal monitoring points in the upstream slow-release zone. This indicates the number of water flow velocities monitored at each longitudinal monitoring point in the upstream slow-release zone. This indicates the flow velocity at the first longitudinal monitoring point in the upstream slow-release zone. This indicates the first longitudinal monitoring point in the upstream slow-release zone. The water flow velocity, The first term representing the upstream slow-release zone The first water flow velocity at the longitudinal monitoring point, The first term representing the upstream slow-release zone The first of the longitudinal monitoring points The water flow velocity.

[0031] S32. Deploy flow meters at longitudinal monitoring points in the downstream slow-release zone to obtain a set of water flow velocity data at the longitudinal monitoring points in the downstream slow-release zone, namely:

[0032] in, This represents the water flow velocity data set at the longitudinal monitoring points in the downstream slow-release zone. This indicates the number of longitudinal monitoring points in the downstream slow-release zone. This indicates the number of water flow velocities monitored at each longitudinal monitoring point in the downstream slow-release zone. This indicates the flow velocity at the first longitudinal monitoring point in the downstream slow-release zone. This indicates the first longitudinal monitoring point in the downstream slow-release zone. The water flow velocity, The downstream sustained-release zone is represented by the first The first water flow velocity at the longitudinal monitoring point, The downstream sustained-release zone is represented by the first The first of the longitudinal monitoring points The water flow velocity.

[0033] S33. Calculate the average value of the water flow velocity data sets at the longitudinal monitoring points in the upstream slow-release zone and the average value of the water flow velocity data sets at the longitudinal monitoring points in the downstream slow-release zone, respectively:

[0034] in, This represents the average value of the water flow velocity data set at the longitudinal monitoring points in the upstream slow-release zone. This represents the average value of the water flow velocity data set at the longitudinal monitoring points in the downstream slow-release zone.

[0035] S34. Calculate the average water flow velocity based on the average value of the water flow velocity data sets from the longitudinal monitoring points in the upstream slow-release zone and the average value of the water flow velocity data sets from the longitudinal monitoring points in the downstream slow-release zone, i.e.:

[0036] in, This indicates the average water flow velocity.

[0037] S35. The average water flow velocity is standardized to obtain the standardized average water flow velocity, i.e.:

[0038] in, This represents the standardized average water flow velocity. This indicates the maximum value of the water flow velocity. This represents the minimum water flow velocity.

[0039] In this embodiment, since the water flow velocities upstream and downstream are different, the water flow velocity at the longitudinal monitoring point in the upstream slow-release zone is collected, and the water flow velocity at the longitudinal monitoring point in the downstream slow-release zone is also collected. By calculating the average value of the water flow velocity at the longitudinal monitoring water level, the water flow velocity error is reduced, so that the water flow velocity can be used to analyze the water quality monitoring data in the future.

[0040] S4. Use the standardized average water flow velocity to perform correlation analysis on the standardized water quality monitoring data set, obtain the influence coefficient of water flow velocity on each water quality monitoring data, and construct a water quality monitoring model based on water flow velocity to predict water quality monitoring data.

[0041] In this embodiment, by calculating the influence coefficient of water flow velocity on various water quality monitoring data, a water quality monitoring model based on water flow velocity is established. When water flow velocities at different locations are collected, the water quality monitoring data can be analyzed using this model.

[0042] Specifically, step S4 includes S41-S42: S41. Based on the Pearson coefficient method, correlation analysis is performed on the standardized water quality monitoring data set using the standardized average water flow velocity, and the influence coefficient of water flow velocity on each water quality monitoring data is calculated, i.e.:

[0043] in, This represents the coefficient indicating the influence of water temperature on water flow velocity. This indicates the number of rows representing the horizontal monitoring points between the upstream and downstream slow-release zones. Indicates the first The first horizontal monitoring point A water temperature value, This represents the standardized average water flow velocity. This represents the coefficient indicating the influence of pH value on water flow velocity. Indicates the first The first horizontal monitoring point A pH value, This represents the coefficient indicating the influence of dissolved oxygen on water flow velocity. Indicates the first The first horizontal monitoring point Dissolved oxygen value, This represents the coefficient indicating the influence of conductivity value on water flow velocity. Indicates the first The first horizontal monitoring point Each conductivity value, This represents the coefficient indicating the influence of turbidity on water flow velocity. Indicates the first The first horizontal monitoring point One turbidity value.

[0044] S42. Based on the calculated influence coefficient of water flow velocity on various water quality monitoring data, establish a water quality monitoring model based on water flow velocity, namely:

[0045] in, This represents the predicted water quality monitoring data. This indicates a selector, meaning that the corresponding water quality monitoring data is selectively output based on the input water flow velocity.

[0046] This invention proposes a method for monitoring the quality of natural drinking water resources in plateau areas. By acquiring the upstream and downstream slow-release zones of the target watershed and setting up monitoring points both horizontally and vertically, the method effectively utilizes the influence of the slow-release zones on water quality monitoring data, thereby improving the accuracy of data acquisition. Simultaneously, it collects the water flow velocity at both the upstream and downstream longitudinal monitoring points, fully considering the significant variations in flow velocity between upstream and downstream areas, thus reducing the error in water flow velocity within the target watershed. Furthermore, this invention uses the Pearson coefficient method to perform correlation analysis between water flow velocity and various water quality monitoring data, thereby establishing a water quality monitoring model based on water flow velocity for predicting water quality monitoring data, improving the accuracy of water quality prediction, and reducing labor costs.

[0047] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

[0048] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A method for monitoring the water quality of natural drinking water resources in plateau areas, characterized in that, Includes the following steps: S1. Obtain the upstream and downstream slow-release zones of the target watershed, and set up several monitoring points in the horizontal and vertical positions of the upstream and downstream slow-release zones of the target watershed to obtain the horizontal monitoring points and the vertical monitoring points. S2. Water quality monitoring sensor groups are deployed at horizontal monitoring points in the upstream and downstream slow-release zones to acquire water quality monitoring data groups at each horizontal monitoring point. The water quality monitoring data groups are then preprocessed and standardized to obtain standardized water quality monitoring data groups. S3. Install flow meters at longitudinal monitoring points in the upstream and downstream slow-release zones to obtain water flow velocity data sets at the longitudinal monitoring points in the upstream and downstream slow-release zones. Calculate the average value of the water flow velocity data sets at the longitudinal monitoring points in the upstream and downstream slow-release zones respectively, and perform standardization processing to obtain a standardized average water flow velocity. S4. Use the standardized average water flow velocity to perform correlation analysis on the standardized water quality monitoring data set, obtain the influence coefficient of water flow velocity on each water quality monitoring data, and construct a water quality monitoring model based on water flow velocity to predict water quality monitoring data.

2. The method for monitoring the water quality of natural drinking water resources in plateau areas according to claim 1, characterized in that, Step S1 specifically includes: The upstream and downstream slow-release zones of the target watershed in the study area were selected, and monitoring points were set at equal intervals in the horizontal and vertical directions of the upstream and downstream slow-release zones, respectively, to obtain the horizontal and vertical monitoring points.

3. The method for monitoring the water quality of natural drinking water resources in plateau areas according to claim 1, characterized in that, Step S2 specifically includes: S21. Water quality monitoring sensor groups are set up at the horizontal monitoring points in the upstream and downstream slow release zones. The water quality sensor groups include water temperature sensors, pH sensors, dissolved oxygen sensors, conductivity sensors and turbidity sensors to obtain water quality monitoring data groups containing water temperature, pH value, dissolved oxygen, conductivity and turbidity. S22. The trispline interpolation method is used to preprocess the water quality monitoring data set for outliers and missing values, and the preprocessed water quality monitoring data set is then standardized to obtain a standardized water quality monitoring data set.

4. The method for monitoring the water quality of natural drinking water resources in plateau areas according to claim 1, characterized in that, Step S3 specifically includes: S31. Deploy flow meters at longitudinal monitoring points in the upstream slow-release zone to obtain a set of water flow velocity data at these points, namely: in, This represents the water flow velocity data set at the longitudinal monitoring points in the upstream slow-release zone. This indicates the number of longitudinal monitoring points in the upstream slow-release zone. This indicates the number of water flow velocities monitored at each longitudinal monitoring point in the upstream slow-release zone. This indicates the flow velocity at the first longitudinal monitoring point in the upstream slow-release zone. This indicates the first longitudinal monitoring point in the upstream slow-release zone. The water flow velocity, The first term representing the upstream slow-release zone The first water flow velocity at the longitudinal monitoring point, The first term representing the upstream slow-release zone The first of the longitudinal monitoring points The water flow velocity; S32. Deploy flow meters at longitudinal monitoring points in the downstream slow-release zone to obtain a set of water flow velocity data at the longitudinal monitoring points in the downstream slow-release zone, namely: in, This represents the water flow velocity data set at the longitudinal monitoring points in the downstream slow-release zone. This indicates the number of longitudinal monitoring points in the downstream slow-release zone. This indicates the number of water flow velocities monitored at each longitudinal monitoring point in the downstream slow-release zone. This indicates the flow velocity at the first longitudinal monitoring point in the downstream slow-release zone. This indicates the first longitudinal monitoring point in the downstream slow-release zone. The water flow velocity, The downstream sustained-release zone is represented by the first The first water flow velocity at the longitudinal monitoring point, The downstream sustained-release zone is represented by the first The first of the longitudinal monitoring points The water flow velocity; S33. Calculate the average value of the water flow velocity data sets at the longitudinal monitoring points in the upstream slow-release zone and the average value of the water flow velocity data sets at the longitudinal monitoring points in the downstream slow-release zone, respectively: in, This represents the average value of the water flow velocity data set at the longitudinal monitoring points in the upstream slow-release zone. This represents the average value of the water flow velocity data set at the longitudinal monitoring points in the downstream slow-release zone. S34. Calculate the average water flow velocity based on the average value of the water flow velocity data sets from the longitudinal monitoring points in the upstream slow-release zone and the average value of the water flow velocity data sets from the longitudinal monitoring points in the downstream slow-release zone, i.e.: in, Indicates the average water flow velocity; S35. The average water flow velocity is standardized to obtain the standardized average water flow velocity, i.e.: in, This represents the standardized average water flow velocity. This indicates the maximum value of the water flow velocity. This represents the minimum water flow velocity.

5. The method for monitoring the water quality of natural drinking water resources in plateau areas according to claim 1, characterized in that, Step S4 specifically includes: S41. Based on the Pearson coefficient method, correlation analysis is performed on the standardized water quality monitoring data set using the standardized average water flow velocity, and the influence coefficient of water flow velocity on each water quality monitoring data is calculated, i.e.: in, This represents the coefficient indicating the influence of water temperature on water flow velocity. This indicates the number of rows representing the horizontal monitoring points between the upstream and downstream slow-release zones. Indicates the first The first horizontal monitoring point A water temperature value, This represents the standardized average water flow velocity. This represents the coefficient indicating the influence of pH value on water flow velocity. Indicates the first The first horizontal monitoring point A pH value, This represents the coefficient indicating the influence of dissolved oxygen on water flow velocity. Indicates the first The first horizontal monitoring point Dissolved oxygen value, This represents the coefficient indicating the influence of conductivity value on water flow velocity. Indicates the first The first horizontal monitoring point Each conductivity value, This represents the coefficient indicating the influence of turbidity on water flow velocity. Indicates the first The first horizontal monitoring point One turbidity value; S42. Based on the calculated influence coefficient of water flow velocity on various water quality monitoring data, establish a water quality monitoring model based on water flow velocity, namely: in, This represents the predicted water quality monitoring data. This indicates a selector, meaning that the corresponding water quality monitoring data is selectively output based on the input water flow velocity.

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