Method for evaluating water quality in a pipe network in a water supply area of a water supply plant

Abstract

The application discloses a water supply area pipe network water quality evaluation method, which comprises the following steps: determining turbidity and bacterial colony number in a monitoring period after water source switching, process or parameter adjustment; inquiring turbidity and bacterial colony number in a control period before water source switching, process or parameter adjustment; calculating turbidity-bacterial colony weighted value after determining turbidity and bacterial colony number average values in the two periods; drawing a month water supply amount-turbidity month average value working curve; bringing turbidity average values in the two periods into the working curve respectively to obtain turbidity working curve values in the two periods respectively, and calculating turbidity working curve difference value; calculating turbidity correction values of each monitoring point in the monitoring period, and calculating monitoring period water quality score according to the formula; calculating control period water quality score according to the formula; and calculating monitoring period and control period score difference, so as to take the score difference as a judgment basis for process, parameter adjustment and water source switching effect, provide precise guidance for process parameter optimization, fine management and process improvement, and achieve the goal of taking pipe network water quality as a target for water plant process management.

Description

Technical Field

[0001] This invention belongs to the field of safe distribution of pipe networks in drinking water treatment, and relates to a model and method for evaluating the water quality of regional pipe networks. In particular, it relates to an evaluation method that serves as a basis for judging the quality changes of pipe network water after the adjustment of water plant processes and parameters and the switching of water source water quality, providing a strong basis for the adjustment of water plant processes and parameters under the condition of integrated plant and network. Technical Background

[0002] With increasing societal awareness of environmental protection and healthy eating, people's demands for drinking water quality are also gradually rising. This necessitates continuous improvement of water supply plant processes, including the widespread introduction of new technologies such as advanced treatment processes, ultrafiltration, and nanofiltration, as well as the optimization and adjustment of existing process parameters. Some cities also resort to long-distance water transfer to address issues such as water shortages or substandard original water sources. Currently, water plants primarily aim to ensure that the quality indicators of the treated water meet drinking water hygiene standards. However, changes in water quality and quantity caused by the introduction of new processes, source switching, and adjustments to process parameters can significantly impact the water quality of the distribution network. Furthermore, when the sensitivity of treated water quality indicators to changes in processes and process parameters is lower than that of the distribution network, using treated water quality indicators as a reference would result in overly coarse adjustments to process parameters, thus failing to guarantee the safety of the distribution network's water quality. Therefore, to respond to and achieve integrated plant and network operations, water plant process adjustments must also take into account the water quality conditions of the distribution network.

[0003] Current methods for evaluating water quality in pipe networks mostly involve evaluating the water quality of a single point within the network, which is insufficient for water plants to use as a reference for process adjustments. This is because the impact of water quality changes on the pipe network after process adjustments is not immediately apparent; there is a time lag in network feedback. Furthermore, the extent of water quality changes is related to the characteristics of the pipe network. Some points are more sensitive to water quality changes, while others require a period of time before changes occur. This makes it difficult to accurately pinpoint the exact time when water quality changes occur after process adjustments, and it is also difficult to clearly determine the network's water quality changes caused by process adjustments based on the water quality of a single point. Therefore, accurately judging the impact of process adjustments on pipe network water quality based on a single sampling result at a single point is neither objective nor comprehensive. In other words, single-point water quality monitoring cannot serve as a standard for evaluating pipe network water quality, nor can a single water quality evaluation of a single point be used as a basis for judging the quality changes after adjustments to water plant processes and parameters, or changes in source water quality. In addition, water quality indicators in the pipe network of large cities, such as turbidity, will show certain patterns of change with the seasons. Therefore, when comparing the water quality of the pipe network in different seasons, eliminating the influence of seasonal changes is very important for the objectivity of the evaluation of the pipe network water quality. Summary of the Invention

[0004] In the process of promoting the integration of water treatment plants and water supply networks, strict control of water quality is required from the source to the tap. After leaving the water treatment plant, tap water undergoes a long pipeline transportation process. Therefore, water quality control includes both the process from the source to the treatment plant and the process from the treatment plant to the tap of residents. When the water treatment plant adjusts its processes or switches water sources, the quality of the water leaving the plant may change relatively little, but the pipeline network is more sensitive to changes in water quality. In particular, when the water source is switched, the change in water quality significantly alters the corrosiveness of the water in the pipeline network, resulting in a more noticeable change in the network's water quality. Therefore, using the evaluation of the pipeline network's water quality as an evaluation target for water treatment plant process and parameter adjustments and water source switching is more practically meaningful.

[0005] The purpose of this invention is to address the technical problems of existing methods that use the quality of treated water as the target for adjusting water plant processes and parameters, which cannot comprehensively reflect the water quality of the distribution network; and the inability of treated water quality to provide precise guidance for adjusting water plant processes and parameters. This invention provides a method for evaluating the water quality of the distribution network in the water supply area of ​​a water plant. It shifts the focus of the water plant to the water quality of the distribution network, using the water quality of multiple sampling points in the distribution network within the water supply area as the target, and combining this with the analysis of water plant process and parameter adjustments. This determines the impact of changes in water plant process parameters on the water quality of the distribution network, serving as a basis for judging the effectiveness of water plant process parameter adjustments, process improvements, and water source switching. This achieves the goal of water plant process management based on the water quality of the distribution network; it can also evaluate the water quality of the distribution network during a critical period.

[0006] To achieve the objectives of this invention, one aspect of this invention provides a method for evaluating the water quality of a water supply network within the water supply area of ​​a water supply plant, comprising the following steps:

[0007] 1) After the water source is switched, the treatment process or treatment parameters are adjusted at the water supply plant, n monitoring points are randomly selected from the water quality monitoring points in the water supply area of ​​the network to be evaluated. Water samples are collected at each selected monitoring point during the monitoring period (the collected water samples are the monitoring water samples). The water quality of the water samples is measured at the same time. The water quality data measured by all selected monitoring points during the monitoring period are used as the water quality monitoring group data, which is recorded as the monitoring group.

[0008] 2) Review and retrieve water quality data from the same monitoring points in the same pipeline network area of ​​the water supply plant before the water source switch, treatment process or treatment parameter adjustment, and at the same monitoring frequency within the control period. Use the water quality data of all monitoring points within the control period as the water quality control group data (also known as query data), and record it as the control group.

[0009] 3) Based on the water quality monitoring group data measured in step 1) within the monitoring period and the water quality control group data retrieved in step 2) within the control period, calculate the average turbidity of water samples from all pipeline monitoring points within the monitoring and control periods, i.e., the total average turbidity ZD. 总均值And the average number of colonies, i.e., the total colony mean JL 总均值 ;

[0010] 4) Calculate the turbidity-colony weighted value A according to formula (3).

[0011] A = Total mean turbidity / Total mean colony count (3)

[0012] 5) Measure the average turbidity for each monitoring month within the monitoring period and control period, i.e., the monthly average turbidity ZD. 月均值 ;

[0013] 6) Plot the monthly water supply-turbidity average monthly value working curve.

[0014] Queries and retrieves the monthly water supply volume Q of the water supply plant within the water supply area to be evaluated, during the monitoring and control periods. 月 ;

[0015] Based on monthly water supply Q 月 Using the X-axis as the x-axis, the monthly average turbidity ZD obtained in step 5) corresponding to the monthly water supply is... 月均值 Using the Y-axis, plot the monthly water supply-turbidity monthly average working curve, as shown in formula (5):

[0016] ZD 月均值 =k×Q 月 +b (5)

[0017] In formula (5), ZD 月均值 The monthly average turbidity is NTU; Q 月 denoted as monthly water supply (in millions of tons); k represents the slope of the monthly water supply-turbidity average working curve; b represents the intercept of the monthly water supply-turbidity average working curve.

[0018] 7) The average water supply Q of the groups during the monitoring period and the control period. 组均值 Substituting these values ​​into the monthly water supply-turbidity average working curve plotted in step 6), the group turbidity working curve values ​​for the monitoring period and control period are calculated, i.e., the group turbidity working value ZD. 组工作值 ;

[0019] 8) Calculate the difference between the turbidity working curve values ​​within the monitoring period and the control period according to formula (7), i.e., Δturbidity working difference, denoted as ΔZD;

[0020] ΔZD=ZD 监测-组工作值 -ZD 对照-组工作值 (7)

[0021] In formula (7):

[0022] ΔZD is the difference between the turbidity working curve values ​​within the monitoring period (monitoring group) and the control period (control group), denoted as Δturbidity working difference; ZD 对照-组工作值 The turbidity working curve value (i.e., the control group turbidity working value, ZD) is calculated based on the monthly average water supply-turbidity working curve during the control period (control group). 对照-组工作值 ZD 监测-组工作值 The turbidity working curve value (ZD) within the monitoring period (monitoring group) is calculated based on the monthly water supply-turbidity average working curve. 监测-组工作值 );

[0023] 9) Calculate the correction value of turbidity for all monitoring points and each measurement within the monitoring period according to formula (8), i.e., the turbidity correction value ZD. 修正 ;

[0024] ZD 修正 =ZD-ΔZD (8)

[0025] In formula (8):

[0026] ZD 修正 ZD is the correction value for the turbidity value measured at each monitoring point in the regional network during the monitoring period; ZD is the turbidity value of the water sample measured at each monitoring point in the regional network during the monitoring period, in NTU; ΔZD is the turbidity working difference, the difference between the turbidity working curve values ​​in the monitoring period and the control period, in NTU.

[0027] 10) Calculate the water quality score2 of the water supply area network of the water supply plant within the monitoring period according to formula (9).

[0028]

[0029] In equation (9),

[0030] score2 is the water quality score within the regional pipeline network monitoring period; ZD i修正 NTU is the turbidity correction value for the i-th monitoring point in the regional network within the monitoring period; JLi is the total bacterial count measured at the i-th monitoring point in the regional network within the monitoring period, CFU / mL; n is the total number of monitoring points in the regional network; m is the total number of water quality monitoring times within the monitoring or control period, m = G × f, where G is the number of natural months in the monitoring or control period; f is the monitoring frequency; A is the turbidity-colony weighted value, which is the ratio of the total turbidity mean to the total bacterial count mean; B is the turbidity correction coefficient; C is the total bacterial count correction coefficient.

[0031] 11) Calculate the water quality score1 of the water supply area network of the water supply plant within the control period according to formula (10).

[0032]

[0033] In formula (10),

[0034] score1 represents the water quality score within the regional network control period; ZDi represents the turbidity value (NTU) of the i-th monitoring point within the regional network within the control period; JLi- 对照 , where is the total bacterial count (CFU / mL) at the i-th monitoring point in the regional network during the control period; n is the total number of monitoring points in the regional network; in this example, n = 30; m is the total number of water quality monitoring sessions during the monitoring or control period, m = G × f, where G is the number of natural months in the monitoring or control period; f is the monitoring frequency; A is the turbidity-colony weighted value, which is the ratio of the total turbidity mean to the total bacterial count mean; B is the turbidity correction factor; C is the total bacterial count correction factor.

[0035] 12) Calculate the water quality score difference Δscore between the monitoring period and the control period according to formula (11).

[0036] Δscore=score2-score1 (11)

[0037] If Δscore is greater than 0, then switching water sources or adjusting water treatment processes and parameters will improve the water quality of the pipe network.

[0038] If Δscore is less than 0, then switching water sources or adjusting water treatment processes and parameters will have a negative impact on the water quality of the pipe network.

[0039] If Δscore equals 0, then switching water sources or adjusting water treatment processes and parameters will have no impact on the water quality of the pipe network.

[0040] In step 1), the number of water quality monitoring points selected is n≥10, preferably 20-40, and more preferably 30.

[0041] In particular, the water sample collection frequency at the selected water quality monitoring points is the same as the sampling frequency for water quality monitoring at the water plant.

[0042] In particular, the determination of water quality in step 1) refers to the determination of turbidity (ZD) and colony count (JL) of the water sample.

[0043] In particular, the turbidity was determined by the scattering method in the "Standard Examination Methods for Drinking Water - Sensory Characteristics and Physical Indicators", and the turbidity unit was NTU; the total bacterial count was determined by the plate counting method in the "Standard Examination Methods for Drinking Water - Microbiological Indicators", and the bacterial count unit was CFU / mL.

[0044] In step 1), the monitoring period is ≥3 months, preferably 3-12 consecutive natural months, and more preferably 3-4 consecutive natural months.

[0045] To eliminate the impact of the time lag in water quality changes in the pipeline network, the monitoring period is usually ≥3 months, preferably 3-12 months, and more preferably 3 months.

[0046] In step 1), the water sample collection frequency f at each water quality monitoring point during the monitoring period is at least 2 times / month, preferably 2-4 times / month, and more preferably 2 times / month. That is, during the monitoring period, water samples are collected and water quality is measured at each water quality monitoring point at least 2 times per natural month, preferably 2-4 times.

[0047] The sampling frequency for water quality monitoring at the water plant is at least twice a month, preferably twice a month, and even more preferably twice a month. That is, water quality monitoring is conducted at the monitoring points 2-4 times per month.

[0048] In step 2), the control period is the period of network water quality monitoring before the water source switch, water plant treatment process or treatment parameter adjustment, and is the same as the monitoring period.

[0049] In particular, the reference period is 1-12 calendar months before the time node for water source switching, treatment process or treatment parameter adjustment of water supply plant, preferably 2-3 calendar months, and more preferably 3 calendar months.

[0050] Using the time point of water source switching, treatment process or treatment parameter adjustment as the reference period, the query starts from the time point 1-12 months before the adjustment time point, preferably 3-12 months, and more preferably 3-4 months.

[0051] If the water source switch, treatment process, or treatment parameter adjustment time point is May 2015, then the control period is the period of 1-6 calendar months before May 2015, usually April and the months before April. For example, if the monitoring period is 3 months, then the control period is February, March, and April; if the adjustment time point is August, then the control period is May, June, and July.

[0052] In particular, the water sample sampling frequency and water quality monitoring frequency were the same during the control period and monitoring period.

[0053] In particular, the months corresponding to the control period and the monitoring period are different.

[0054] In particular, in step 2), the turbidity and colony count data of the same water quality monitoring points in the same water supply area of ​​the same pipeline network to be evaluated in the water supply plant are retrieved and reviewed, and are obtained at the same monitoring frequency within the control period as in step 1).

[0055] Among them, the water quality data retrieved in step 2) is called the water quality query value.

[0056] In particular, the water turbidity data that is consulted and retrieved is called the turbidity query value; the water colony count data that is consulted and retrieved is called the colony query value.

[0057] Query and retrieve water quality monitoring data from the same water quality monitoring point in the same water supply area network of the water supply plant, which is the same as the water quality monitoring point selected in step 1), and the water quality monitoring data at the same monitoring frequency during the control period before the water source switch or the water treatment process and parameter adjustment node, and use this data as the water quality monitoring control group.

[0058] The monitoring duration of the control period is the same as the monitoring period, and the control period is a continuous natural month with the same duration as the monitoring period before the water source switch or before the water treatment process and parameter adjustment node.

[0059] In particular, the monitoring period is a continuous natural month before the water source switch or after the water treatment process and parameter adjustment node, with the month corresponding to the adjustment node as the starting month of the monitoring period; the control period is a continuous natural month before the water source switch or before the water treatment process and parameter adjustment node, with the month preceding the month corresponding to the adjustment node as the starting month of the control period.

[0060] The monitoring months for the control period and the monitoring period are different. For example, if the adjusted time point is July 2019 and the monitoring period is July-September 2019, then the control period is April-June 2019; if the monitoring period is July-October 2019, then the control period is March-June 2019; or if the monitoring period is August-October 2019, then the control period is April-June 2019.

[0061] Within the same water supply network, before the water source switch or the adjustment of water treatment processes or parameters, water quality monitoring data with the same monitoring frequency are collected within a consecutive natural month period with the same monitoring cycle duration. This data serves as the water quality control group. The control period differs from the monitoring period in terms of the natural month, but the monitoring duration is the same. In other words, within the network water quality data before the water source switch or the adjustment of water treatment processes and parameters, the network water quality monitoring data of the same water quality monitoring point as in step 1) are retrieved within a time period with the same monitoring cycle duration, counting backwards from the month preceding the month corresponding to the water source switch or the adjustment of water treatment processes or parameters, and are used as the water quality control group.

[0062] Among them, the monthly average turbidity (ZD) mentioned in step 5) 月均值 () represents the monthly average turbidity value for each month within the monitoring and control periods.

[0063] In particular, the monthly average turbidity (ZD) for each month within the monitoring and control periods is calculated according to formula (4). 月均值 ),

[0064] ZD 月均值 = Sum of turbidity monitoring or query values ​​of all pipeline monitoring points in each natural month / (n×f) (4)

[0065] In formula (4), ZD 月均值 t is the monthly average turbidity value in NTU; n is the number of monitoring points in the pipeline network; f is the monthly water quality monitoring frequency in the pipeline network, times / month.

[0066] In step 7), the average water supply Q of the group during the monitoring period will be used. 监测-组均值 Substituting the data into the monthly water supply-turbidity average working curve plotted in step 6), the average turbidity of the monitoring group (i.e., the average turbidity of the monitoring group ZD) within the monitoring period is calculated. 监测-组均值 The average water supply Q of the control group during the control period. 对照-组均值 Substituting the monthly water supply-turbidity average working curve plotted in step 6), the average turbidity value of the control group (i.e., the average turbidity value ZD of the control group) within the control period is calculated. 对照-组均值 ).

[0067] In particular, the average water supply (i.e., Q) of the monitoring group and the control group was calculated according to formula (6) during the monitoring period (monitoring group) and the control period (control group). 对照-组均值 Q 监测-组均值 ),

[0068] Q 组均值 =Monthly water supply Q in each natural month within the monitoring or control period 月 Sum of G (6)

[0069] In formula (6):

[0070] Q 组均值 G represents the average water supply volume of the monitoring group (monitoring group) or control group (control group) within the monitoring period (monitoring group) or control period, in millions of tons; G represents the number of natural months within the pipeline monitoring period or control period.

[0071] The turbidity correction coefficient B mentioned in steps 10) and 11) is determined according to the following method:

[0072] B-1) Among the turbidity monitoring values ​​of water samples collected from all water quality monitoring points within the statistical monitoring period, the measured turbidity value is less than the overall turbidity mean ZD. 总均值The number of times the turbidity monitoring data in the monitoring group is less than the overall turbidity mean;

[0073] B-2) In the statistical step 2), among the turbidity values ​​of water samples from the same water quality monitoring points selected within the monitoring period as those retrieved during the monitoring control period, the turbidity data retrieved is less than the overall turbidity mean ZD. 总均值 The number of times the turbidity query data in the control group is less than the overall turbidity mean;

[0074] B-3) Calculate the turbidity correction factor B for the monitoring period and the monitoring control period according to formula (1), respectively.

[0075] B = Number of times the turbidity monitoring data or turbidity query data is less than the total turbidity mean / (n×m) (1)

[0076] In formula (1), B is the turbidity correction coefficient; m is the total number of water quality monitoring times within the monitoring cycle or monitoring control cycle, m = J × f, where J is the number of natural months in the monitoring cycle or monitoring control cycle; f is the monitoring frequency; and n is the number of network monitoring points selected within the regional network.

[0077] The colony correction coefficient C mentioned in steps 10) and 11) is determined according to the following method:

[0078] C-1) Among the colony counts of water samples collected from all water quality monitoring points within the statistical monitoring period, the colony count was less than the total colony mean. 总均值 The number of times the colony count in the monitoring group is less than the total average colony count;

[0079] C-2) In step 2), among the water samples from the same water quality monitoring points selected within the monitoring control period that were retrieved and consulted during the statistical step, the colony count data was less than the total colony mean. 总均值 Quantity;

[0080] C-3) Calculate the colony correction coefficient C for the monitoring period and the monitoring control period according to formula (2), respectively.

[0081] C = Number of times the colony monitoring data or colony query data is less than the total colony mean / (n×m) (2) In formula (2), C is the colony correction coefficient; m is the total number of water quality monitoring times within the monitoring period or monitoring control period, m = J × f, where J is the number of natural months in the monitoring period or monitoring control period; f is the monitoring frequency; and n is the number of network monitoring points selected within the regional network.

[0082] Total mean turbidity (ZD) 总均值 This refers to the average turbidity value of all monitoring points in the pipeline network, including both the control and monitoring groups.

[0083] Total average colony count (JL) 总均值 This includes the mean total number of bacterial colonies at all monitoring points in the pipeline network within both the control and monitoring groups.

[0084] The turbidity correction factor B represents the probability that the turbidity value in the water quality monitoring data of the regional pipeline network monitoring point is lower than the total turbidity mean out of the total number of pipeline network monitoring times; that is, the ratio of the number of times the turbidity value is lower than the total turbidity mean in all turbidity data of the regional pipeline network monitoring point within the monitoring period or control period to the total number of pipeline network monitoring times.

[0085] The colony correction factor C represents the probability that the total number of colonies in the water quality monitoring data of the regional pipeline network monitoring point is less than the total average number of colonies out of the total number of pipeline network monitoring times; that is, the ratio of the number of times the total number of colonies is lower than the total average number of colonies in all the total number of colonies data of the regional pipeline network monitoring point within the monitoring period or control period to the total number of pipeline network monitoring times.

[0086] In the water quality evaluation method of the present invention, the higher the score obtained according to formula (9), the better the water quality of the pipeline network.

[0087] When evaluating the impact of water source switching, treatment process, and parameter adjustments on the water quality of the pipe network, the score difference Δscore (adjusted score - unadjusted score) is calculated by comparing the score changes before and after the adjustment. The Δscore is used to determine the water quality changes at the monitoring points in the pipe network. If Δscore > 0, it indicates that the water quality at that point is better than before the change, even with the original water source or process. If the change is due to a water source switching, it means the water source is less corrosive to the pipe network in that area, and the water quality has improved. However, when switching back to the original water source, it's necessary to be aware of the risk of fluctuations in water quality. If the improvement is due to adjustments in the water treatment process and parameters, it indicates that the direction of the adjustment is correct. The water plant can adopt the adjusted process or parameters, or continue to adjust them to refine the adjustment range. Conversely, if Δscore < 0, it indicates that after the water source switch or adjustment of the water treatment process and parameters at the water plant, the water quality of the pipeline network at that point has deteriorated compared to the previous water source or process conditions. This suggests that the water source switch plan needs further adjustment, such as gradually increasing the proportion of the new water source to ensure that the pipeline network gradually adapts to the changes in the quality of the new water source; or it indicates that the direction or method of the process or parameter adjustment is not conducive to improving the pipeline network water quality, and the water plant needs to adjust the parameters in the opposite direction. For example, if the water plant increases the prechlorination dosage, causing the pipeline network water quality to deteriorate, then the prechlorination dosage needs to be reduced based on the adjusted prechlorination dosage, and then the pipeline network water quality should be evaluated again to achieve the goal of precise prechlorination dosage management based on the pipeline network water quality standard. If Δscore = 0, it indicates that the process or parameter adjustment has no significant impact on the pipeline network water quality, and the water plant can adjust the plan and other parameters to achieve the goal of optimizing the pipeline network water quality.

[0088] This invention provides a method for judging the adjustment of water plant processes and parameters, using the water quality of the pipe network as the target. The method includes first selecting several pipe network monitoring points within the water supply area of ​​the plant and conducting water quality monitoring at these points 2-4 times per month. To eliminate the impact of the time lag in pipe network water quality changes, a sampling period of 3-12 months is recommended. It should be noted that water supply in large cities typically exhibits seasonal cyclical changes, manifested as annual turbidity variations in pipe network water, with lower turbidity in summer and higher turbidity in winter. Different cities have different water supply volumes and pipe network characteristics, making it difficult to standardize the degree of turbidity variation caused by water supply volume. Therefore, when comparing pipe network water quality before and after process and parameter adjustments, it is necessary to use the same pipe network monitoring points, maintain the same monitoring frequency at the same monitoring points, and compare data within a one-year period or the same monthly period.

[0089] This invention eliminates the impact of significant seasonal variations in water supply on turbidity by introducing a turbidity correction method. This removes time constraints from network water quality assessment, eliminating the need to select a network with similar water supply from the previous year in the same season as a control. Therefore, the selection of the control period is more flexible. This flexibility allows monitoring to begin immediately after process or parameter adjustments, enabling faster assessment of the effectiveness of these adjustments. Furthermore, conducting water quality assessments before and after adjustments, due to the short time interval, allows for more precise identification of the specific operations causing changes in network water quality, better aligning with the expected results of applying this model in practical network water quality assessment.

[0090] This invention focuses on multiple monitoring points within a water supply area, involving numerous monitoring points and a large volume of data. Among the extensive water quality monitoring data, turbidity not only reflects the quality of the treated water but also largely reflects the feedback of the pipeline network to changes in water quality and quantity. For example, changes in water quality and quantity can lead to increased corrosion or impact on the pipeline network, resulting in the release of iron and manganese, and the shedding of bacterial colonies, thus causing changes in turbidity. Therefore, this model should adhere to the principle of simplicity and ease of calculation, using turbidity and total bacterial count as the primary reference indicators.

[0091] Compared with the prior art, the present invention has the following advantages and benefits:

[0092] 1. This invention evaluates the water quality of multiple pipe network monitoring points within a water supply area, and provides feedback on water plant process or parameter adjustments and water source switching based on the water quality of the non-point source pipe network. This has a wider range of applications than the current single-point, single-time pipe network water quality evaluation. Furthermore, combined with the analysis of water plant processes and parameters, it can provide more accurate basis for optimizing water plant process parameters and evaluating the improvement status of water plant processes year by year.

[0093] 2. This invention takes into account the seasonal variation of turbidity in the pipeline network with an annual cycle, and makes the monitoring cycle for data selection more flexible during application by correcting the turbidity value.

[0094] 3. The integration of water treatment plants and water supply networks is an inevitable requirement for smart water management, optimized scheduling, and further ensuring the safety of tap water quality. Using the water quality of the water supply network as the evaluation target is more in line with the general trend of promoting the integration of water treatment plants and water supply networks.

[0095] 4. Currently, most large urban water supply plants adopt advanced water treatment processes, and the quality of the water leaving the plant is significantly better than the national drinking water standards. Adjustments to process parameters may not be significantly reflected in the quality of the water leaving the plant, resulting in a wide range of process parameter adjustments. However, the pipe network is more sensitive to changes in water quality. Therefore, using changes in pipe network water quality as a reference target for adjusting water treatment processes or parameters can make the adjustment range more precise, which is conducive to achieving refined management of water plants and can also promote energy conservation and consumption reduction in water plants. Attached Figure Description

[0096] Figure 1 The working curves show the monthly water supply and the monthly average turbidity. Detailed Implementation

[0097] The present invention will be further illustrated below with reference to specific embodiments, and the advantages and features of the present invention will become clearer as the description proceeds. However, these embodiments are merely exemplary and do not constitute any limitation on the scope of the present invention. Those skilled in the art should understand that modifications or substitutions can be made to the details and form of the technical solutions of the present invention without departing from the spirit and scope of the present invention, but all such modifications and substitutions fall within the protection scope of the present invention.

[0098] When conducting actual pipeline water quality assessments, especially when managers want to determine whether the direction of water plant process and parameter adjustments is correct based on changes in pipeline water quality, managers prefer to obtain analysis results as soon as possible. However, it may be difficult to find relevant data from the previous year, or the water plant's situation may have changed significantly during the same period of the previous year, making comparison difficult.

[0099] The turbidity of urban pipe network water is not stable or fluctuates randomly throughout the year, but rather varies cyclically with the seasons. Water supply is high in summer, resulting in low turbidity, while water supply is relatively low in winter, leading to high turbidity. If water plants adjust their processes during the natural months of October to December, and the pipe network water quality from July to September is used as a control, with October to December as the monitoring period, even without any process adjustments, the turbidity of the pipe network water during the monitoring period will be significantly higher than the control group. Therefore, if the reference period and the monitoring period fall in different seasons, the influence of seasonal variations in turbidity must be eliminated before comparison. The method of this invention evaluates pipe network water quality considering the influence of seasonal variations in pipe network turbidity.

[0100] Example 1

[0101] A water supply plant adjusted its water treatment process and parameters in early October of a certain year. In this embodiment of the invention, the water treatment process and parameters of the water supply plant were adjusted in early October of a certain year. The water quality of the pipe network in the water supply area was monitored, and the water quality of the pipe network in a certain area was evaluated.

[0102] 1. Set up regional pipeline water quality monitoring points and conduct water quality testing.

[0103] 1A. Randomly select any 30 water quality monitoring points (i.e., n = 30, where n is the number of monitoring points) from the numerous water quality monitoring points that the water supply plant has set up in advance to monitor the water quality of the pipeline network during the water supply process within the water supply area of ​​the water supply plant. Mark them as D1-D30 respectively, and mark the i-th monitoring point as Di, where i is 1-30.

[0104] In this embodiment, n=30 pipeline monitoring points are used as an example; other monitoring points with n≥10 are also applicable to this invention. Water quality pipeline monitoring points are water sample collection points pre-set by the water supply plant during the water supply process to monitor the water quality of the pipeline network.

[0105] 1B. After adjusting the water treatment process and parameters at the water supply plant, water samples are collected at each selected monitoring point in the pipeline network, and the water quality of the collected water samples is measured, i.e., the water quality of the monitored water samples includes turbidity (ZD) and total bacterial count (JL); among which:

[0106] Turbidity was determined by the scattering method in "Standard Examination Methods for Drinking Water - Sensory Characteristics and Physical Indicators", and the unit of turbidity was NTU; total bacterial count was determined by the plate counting method in "Standard Examination Methods for Drinking Water - Microbiological Indicators", and the unit of bacterial count was CFU / mL.

[0107] The water sampling and water quality monitoring period (i.e., monitoring cycle, L) is 3 consecutive natural months (usually 2-5 natural months, preferably 3 consecutive natural months);

[0108] The sampling frequency (or monitoring frequency, f) at each monitoring point is at least 2 times / month (usually 2-4 times / month, preferably 2 times / month), that is, water samples are collected and water quality is measured twice a month at each monitoring point;

[0109] The sampling intervals are basically the same. For example, if f = 2 times / month, the sampling interval is 14-16 days, usually in the first and second ten days of each month. In this example, water samples are collected on the 1st and 16th of each natural month, and the turbidity and colony count of the water samples are measured.

[0110] Water samples collected from all selected pipeline monitoring points within the monitoring period are designated as monitoring group water samples; water quality measurement values ​​of all selected pipeline monitoring points within the monitoring period are used as water quality monitoring group data, i.e., the water quality data of all monitored group water samples are the monitoring group water quality data, denoted as the monitoring group; the monitoring period is any consecutive 3-12 calendar months after the water supply plant source switch or water treatment process / parameter adjustment, preferably any consecutive 3 months, and more preferably a consecutive 3 months after the adjustment node. Preferably, the monitoring period starts from the month corresponding to the water supply plant source switch or water treatment process / parameter adjustment node, and is a consecutive 3-12 months, more preferably 3 months.

[0111] In this embodiment, the water sample collection and water quality monitoring frequency f at the monitoring point is taken as 2 times / month. Other frequencies of 2-4 times / month are also applicable to this invention. The monitoring cycle duration L is taken as 3 months. Usually, the monitoring cycle duration is at least 3 consecutive months, usually 3-12 consecutive months, preferably 3 months.

[0112] In this embodiment, the water sample collection and water quality monitoring time (monitoring calendar month) are October, November and December 2019 as examples; the monitoring period L is 3 months and the monitoring frequency f is 2 times / month; the water quality monitoring results are shown in Table 1 and Table 2.

[0113] 2. Review and retrieve water quality data from regional pipeline network monitoring points within the control period to obtain water quality query data.

[0114] Before the water source switching or water treatment process or process parameter adjustment, the water quality (turbidity and total bacterial count) data of water samples collected from the same pipeline monitoring points within the same monitoring duration and at the same monitoring frequency as the monitoring cycle were reviewed and retrieved. The retrieved data was used as the control group data and recorded as the control group.

[0115] That is, the water quality data of water samples collected from the same pipeline monitoring points as the monitoring group within the control period are used as the control group data. The control period is the pipeline water sample collection and water quality monitoring period with the same duration as the monitoring period before the water source switch or water treatment process or process parameter adjustment node of the water supply plant. The control period is at least 3 consecutive natural months.

[0116] Review and retrieve water quality (turbidity and total bacterial count) data from water samples collected at the same monitoring points within the same monitoring period, prior to any water source switch, water treatment process, or process parameter adjustment. In other words, use water samples collected by the water supply plant within the same water supply area, prior to any water source switch, water treatment process, or process parameter adjustment, at the same monitoring points within the same monitoring period, as control group water samples. The water quality data from these control group water samples will then be used as control group data.

[0117] The water quality data queried is called the query value; the water turbidity data queried and retrieved is called the turbidity query value; the water colony count data queried and retrieved is called the colony query value.

[0118] The control period is the time period for collecting water samples from the pipeline network and monitoring water quality before the water source switch or water treatment process or process parameter adjustment at the water supply plant, and the duration is the same as the monitoring period.

[0119] The natural months of the control period and the monitoring period can be the same or different.

[0120] The month preceding the month corresponding to the water source switch or water treatment process / treatment parameter adjustment node of the water supply plant is taken as the starting time of the control period, and the consecutive months preceding it are 3-12 months, further preferably 3-6 months, and preferably 3 months.

[0121] The control period is 1-12 consecutive calendar months before the water source switch or water treatment process or process parameter adjustment at the water supply plant, preferably 3-12 consecutive calendar months, and more preferably 3 consecutive calendar months. For example, if the monitoring period is 3 months, the control period is also 3 months. If the adjustment point is October of a certain year, then the specific time of the control period is July, August, and September of that year, which are 3 consecutive calendar months before October. If the control period is 5 months, then the specific time of the control period is May, June, July, August, and September of that year, which are 5 consecutive calendar months before October.

[0122] The monitoring period is the time period for water sample collection and water quality measurement (i.e., the length of a calendar month). The control period is the length of a calendar month for monitoring and control. The length of the control period is the same as that of the monitoring period. The control period and the monitoring period are usually 3-6 months before and after the water source switch or water treatment process or process parameter adjustment at the water supply plant, preferably 3 months.

[0123] For example: The water supply plant adjusted its water treatment process and parameters in early October 2019. The adjustment time was early October 2019, and the monitoring period (monitoring calendar months) was October, November, and December 2019, three consecutive calendar months; the monitoring period L was three months long; the monitoring period was the same as the control period; the control period was July, August, and September 2019, three calendar months, or it could be May, June, and July 2019, three calendar months. Alternatively, the monitoring period could be November, December 2019, and January 2020, a total of 3 calendar months, with the control period being July, August, and September 2019, also a total of 3 calendar months, or June, July, and August 2019, also a total of 3 calendar months; or the water source switching time at the water supply plant could be early May 2020, in which case the monitoring period (monitoring calendar months) would be May, June, July, and August 2020, a total of 3 calendar months, with the control period (calendar months) being January, February, March, and April 2020, and so on.

[0124] The control period is usually 3-6 months before the water source switch or water treatment process or process parameter adjustment at the water supply plant, preferably 3 months; the monitoring period is usually 3-6 months after the water source switch or water treatment process or process parameter adjustment at the water supply plant, preferably 3 months.

[0125] Water samples collected from all selected pipeline monitoring points within the monitoring period are designated as monitoring group water samples, and the water quality data of the monitoring group water samples are designated as monitoring group data, denoted as the monitoring group. Water samples collected from the same pipeline monitoring points selected during the control period are designated as control group water samples, and the water quality data of the control group water samples are designated as control group data, denoted as the control group. In other words, before the water source switch or water treatment process or process parameter adjustment, the water quality (turbidity and total bacterial count monitoring data) data of water samples collected from the same pipeline monitoring points under the same monitoring duration and frequency as the monitoring period are used as the control group.

[0126] This embodiment uses water quality data from water samples collected at the same monitoring frequency from the same pipeline monitoring points at the water supply plant in July, August, and September 2019 (control period, 3 months) before the water source switch or the water treatment process and parameter adjustment node (early October 2019) as the control group water quality data (denoted as the control group). The measurement data of turbidity and colony count of the control group water samples are shown in Table 1 and Table 2, respectively.

[0127] Table 1. Turbidity (NTU) at monitoring points in the regional pipeline network during the monitoring and control periods.

[0128]

[0129]

[0130] Table 2. Colony counts (CFU / mL) at monitoring points in the regional pipeline network during the monitoring and control periods.

[0131]

[0132]

[0133] 3. Measure the total mean turbidity of the water (i.e., ZD). 总均值 )

[0134] The average turbidity of water samples from all monitoring points in the monitoring group (i.e., the monitoring period, 3 calendar months) and the control group (i.e., the control period, 3 calendar months) was calculated and recorded as the total turbidity mean (ZD). 总均值 The calculation results are shown in Table 1.

[0135] Total mean turbidity (ZD) 总均值 The turbidity value refers to the average turbidity of water samples from all monitoring points in the pipeline network within the monitoring and control periods, i.e., the average turbidity value of all monitoring points in the control and monitoring groups.

[0136] For example, in this embodiment, the turbidity data of 180 water samples collected from 30 pipeline monitoring points numbered 1-30 within the control period (July, August, and September 2019) and the average turbidity data of 180 water samples collected from 30 pipeline monitoring points numbered 1-30 within the monitoring period (October, November, and December 2019) are compared with the average turbidity data of 180 water samples collected from 30 pipeline monitoring points numbered 1-30 over 6 months to obtain the total average turbidity ZD of the pipeline water quality. 总均值 It is 0.39 NTU.

[0137] 4. Measure the total bacterial count (JL) of the water. 总均值 )

[0138] The average colony count of water samples from all monitoring points in the monitoring group (i.e., the monitoring period, 3 calendar months) and the control group (i.e., the control period, 3 calendar months) was calculated and recorded as the total colony mean (i.e., JL). 总均值 The calculation results are shown in Table 2.

[0139] Total average colony count (JL) 总均值 The value refers to the average bacterial count of water samples from all pipeline monitoring points within the monitoring and control periods, i.e., the average bacterial count of all pipeline monitoring points within the control and monitoring groups.

[0140] For example, in this embodiment, the average colony count of 180 water samples collected from 30 pipeline monitoring points numbered 1-30 within the control period (July, August, and September 2019) and the average colony count of 180 water samples collected from 30 pipeline monitoring points numbered 1-30 within the monitoring period (October, November, and December 2019) is used to obtain the total average colony count of the pipeline water quality JL. 总均值 The concentration was 1.64 CFU / mL.

[0141] 5. Calculate the turbidity correction factor B

[0142] 5A. Among the turbidity monitoring data of all monitoring points and water samples collected during the monitoring period and control period, the measured turbidity values ​​were less than the overall turbidity average (ZD). 总均值 The number (i.e., frequency) of ) is shown in Table 3.

[0143] For example, in the two monitoring sessions in July 2019 within the control period, the measured turbidity data from the pipeline monitoring points numbered 1-30 in the first monitoring session in July 2019 showed 26 instances where the turbidity was less than the total turbidity mean (0.39 NTU), meaning that 26 out of 30 measured turbidity values ​​were less than the total turbidity mean. The second monitoring session showed 21 instances where the turbidity was less than the total turbidity mean, and so on. The statistical results are shown in Table 6. Similarly, in the two monitoring sessions in October 2019 within the monitoring period, the measured turbidity data from the pipeline monitoring points numbered 1-30 in the first monitoring session in October 2019 showed 24 instances where the turbidity was less than the total turbidity mean (0.39 NTU), meaning that 24 out of 30 measured turbidity values ​​were less than the total turbidity mean. The second monitoring session showed 22 instances where the turbidity was less than the total turbidity mean, and so on. The statistical results are shown in Table 6.

[0144] 5B. Calculate the correction value B (i.e., turbidity correction coefficient) for the turbidity measurement of the monitoring group (all turbidity measurement data within the monitoring period) and the control group (all turbidity measurement data within the control period) according to formula (1).

[0145] B = Number of times the turbidity monitoring / query data in the monitoring group or control group is less than the total turbidity average / (n×m) (1) In formula (1): B is the correction value of turbidity measurement during turbidity monitoring, the turbidity correction coefficient; m is the total number of water quality monitoring times in the monitoring cycle or monitoring control cycle, m = G×f, where G is the number of natural months in the monitoring cycle or monitoring control cycle; f is the monitoring frequency; in this embodiment, G is 3; f is 2; m is 6; n is the number of monitoring points in the pipeline network, in this embodiment n = 30.

[0146] The turbidity correction factor B represents the probability that the number of times the turbidity value in the water quality monitoring data of the regional pipeline network monitoring point is less than the total turbidity mean relative to the total number of pipeline network monitoring times; that is, the ratio of the number of times the turbidity value is lower than the total turbidity mean in all turbidity data of the regional pipeline network monitoring point within the monitoring period or control period to the total number of pipeline network monitoring times; the turbidity correction factor B of the monitoring group and the control group were calculated according to formula (1), and the measurement results are shown in Table 6.

[0147] For example: Control group: Turbidity correction coefficient B1 = (26+21+24+24+23+24) / (30×6) = 0.79 for 30 pipeline monitoring points and a total of 6 monitoring sessions during the 3-month control period from July to September 2019; Monitoring group: Turbidity correction coefficient B2 = (24+22+19+9+8+6) / (30×6) = 0.49 for 30 pipeline monitoring points and a total of 6 monitoring sessions during the 3-month monitoring period from October to December 2019.

[0148] Table 3 Correction coefficients for turbidity and colony count

[0149]

[0150]

[0151] 6. Calculate the colony count correction factor C.

[0152] 6A. In the monitoring data of colony counts of all monitoring points and water samples collected during the monitoring period and control period, the measured value of the colony count was less than the total average colony count (JL). 总均值 The number (i.e., frequency) of ) is shown in Table 6.

[0153] For example, in the two monitoring sessions in July 2019 within the control period, the number of colony counts at the pipeline monitoring points numbered 1-30 in the first monitoring session in July 2019 was less than the total colony mean (1.64 CFU / mL) 26 times, meaning that 26 out of the 30 measured colony counts were less than the total colony mean of 1.64 CFU / mL; the number of colony counts less than the total colony mean was 26 times in the second monitoring session, and so on. The statistical results are shown in Table 6. In the two monitoring sessions in October 2019 during the monitoring period, the number of colony counts at the pipeline monitoring points numbered 1-30 in the first monitoring session in October 2019 was less than the total colony mean (1.64 CFU / mL) 28 times, meaning that 28 out of the 30 measured colony counts were less than the total colony mean of 1.64 CFU / mL; in the second monitoring session, the number of colony counts was less than the total colony mean 26 times, and so on. The statistical results are shown in Table 3.

[0154] 6B. Calculate the correction coefficient C for colony count determination of the monitoring group (all colony count data within the monitoring period) and the control group (all colony count data within the control period) according to formula (2), i.e., the colony correction coefficient; C = the number of times the colony monitoring / query data in the monitoring group or control group is less than the total colony mean / (n×m) (2) In formula (2): C is the correction coefficient for colony determination during colony monitoring, the colony correction coefficient; m is the total number of water quality monitoring in the monitoring period or monitoring control period, m = G×f, where G is the number of natural months in the monitoring period or monitoring control period; f is the monitoring frequency; in this embodiment, G is 3; f is 2; m is 6; n is the number of monitoring points in the pipeline network, in this embodiment n = 30.

[0155] The colony correction factor C represents the probability that the total number of colonies in the water quality monitoring data of the regional pipeline network monitoring point is less than the total average number of colonies out of the total number of pipeline network monitoring times; that is, the ratio of the number of times the total number of colonies is lower than the total average number of colonies in all colony total data of the regional pipeline network monitoring point within the monitoring period or control period to the total number of pipeline network monitoring times. The results of calculating the colony correction factor C of the monitoring group and the control group according to formula (2) are shown in Table 3.

[0156] For example: Control group: During the 3-month control period from July to September 2019, the colony correction coefficient C1 for 30 monitoring points in the pipeline network and a total of 6 monitoring sessions was (26+26+29+28+27+27) / (30×6) = 0.91; that is, the colony correction coefficient C1 for the control group during the 3-month control period from July to September 2019 was 0.91.

[0157] The colony correction coefficient C2 for the monitoring group during the 3-month monitoring period from October to December 2019, consisting of 30 pipeline monitoring points and a total of 6 monitoring sessions, is (28+26+30+30+29+29) / (30×6)=0.96; that is, the colony correction coefficient C2 for the monitoring group during the 3-month monitoring period from October to December 2019 is 0.96.

[0158] 7. Calculate the turbidity-colony weighted value A

[0159] Calculate the turbidity-colony weighted value A according to formula (3).

[0160] A = ZD 总均值 / JL 总均值 (3)

[0161] In formula (3), ZD 总均值 The total mean turbidity is NTU; JL 总均值 The total average colony count is expressed in CFU / mL.

[0162] In this embodiment, the total mean turbidity is ZD. 总均值 The mean total colony count was 0.39; JL 总均值 =1.64; A = 0.2378

[0163] The total mean turbidity is measured in NTU; the total mean colony count is measured in CFU / mL. The weighting is dimensionless. Both turbidity and total mean colony count are calculated using the data corresponding to their respective units.

[0164] 8. Measure the average turbidity (i.e., monthly average turbidity, ZD) for each natural month within the monitoring and control periods. 月均值 )

[0165] Monthly average turbidity (ZD) 月均值 The average turbidity value (ZD) within the water supply area of ​​the water supply plant for each natural month is calculated according to formula (4) for each month in the monitoring group and the control group. 月均值 The measurement results are shown in Table 4; ZD 月均值 = Sum of turbidity monitoring or query values ​​of all pipeline monitoring points in each natural month / (n×f) (4) In formula (4): ZD 月均值is the average turbidity of all water samples collected from all pipeline monitoring points within each natural month; n is the number of pipeline monitoring points, n = 30 in this embodiment; f is the frequency of pipeline water quality monitoring within each month, times / month, f = 2 times / month in this embodiment.

[0166] For example, in the two monitoring sessions conducted in July 2019 within the control period (i.e., the first and second monitoring sessions in July 2019), the sum of the two measured turbidity data from monitoring points numbered 1-30 was 19.88 ZD. 月均值 =19.88 / (30×2) = 0.33 NTU, meaning the monthly average turbidity in July 2019 was 0.33 NTU; In the two monitoring sessions in October 2019 (i.e., the first and second monitoring sessions in October 2019), the sum of the two measured turbidity data from monitoring points numbered 1-30 was 20.23 NTU. 月均值 =20.23 / (30×2) =0.34NTU, that is, the monthly average turbidity in July 2019 was 0.34NTU.

[0167] The turbidity of the piped water is strongly correlated with the water supply. Specifically, as the water supply decreases, the turbidity of the piped water tends to increase even without adjustments to the water treatment process at the water plant. This is mainly manifested in the summer when the water supply is highest and the turbidity is lowest, and in the winter when the water supply is lowest and the turbidity is highest. Therefore, even without adjustments to the water plant's processes or parameters, the turbidity of the piped water exhibits a pattern of lower turbidity in summer and higher turbidity in winter. That is, from summer to autumn and then to winter, the turbidity of the piped water gradually increases, and from winter to spring and then back to summer, the turbidity gradually decreases. Therefore, to evaluate the piped water quality in different seasons, it is necessary to consider the reasons for these seasonal changes. These reasons include: firstly, the significant differences in water supply across seasons leading to variations in turbidity; and secondly, the changes in piped water quality caused by adjustments to the water plant's processes or parameters. For example, if the process or parameters are adjusted in the fall, the water quality of the pipeline network in summer before the adjustment and the water quality of the pipeline network in winter after the adjustment are compared and scored. Since the difference in water supply between winter and summer is the greatest, the water supply will have the most significant impact on the turbidity of the pipeline network. Therefore, it is necessary to first eliminate the impact of seasonal changes in water supply on the turbidity of the pipeline network in order to more accurately judge the impact of the water plant's process or parameter adjustment on the pipeline network water quality.

[0168] To eliminate the problem of the impact of seasonal water supply differences on the turbidity of the pipe network water, the method of the present invention corrects the turbidity within the monitoring period to overcome the changes in pipe network water turbidity caused by changes in water supply.

[0169] Table 4. Water supply and average monthly turbidity from July to December 2019

[0170]

[0171] 9. Plot the monthly water supply-turbidity average monthly value working curve.

[0172] Queries and retrieves the monthly water supply volume Q of the water supply plant within the water supply area to be evaluated, during the monitoring and control periods. 月 The query results are shown in Table 4.

[0173] The monthly water supply and average turbidity values ​​for each natural month of the control group and the monitoring group are listed separately. Then, the monthly water supply and average turbidity data groups are rearranged in ascending order of monthly water supply. Then, the monthly water supply and average turbidity working curve is plotted with monthly water supply as the X-axis and the corresponding monthly turbidity as the Y-axis. The specific plotting method is as follows: The monthly water supply and average turbidity are plotted with monthly water supply as the X-axis and the corresponding monthly turbidity as the Y-axis, and the monthly water supply is plotted in ascending order of monthly water supply. Then, the scatter plot is linearly fitted to obtain the corresponding trend line equation. That is, the monthly water supply and average turbidity working curve is shown in formula (5). The monthly water supply and average turbidity working curve is as follows:

[0174] ZD 月均值 =k×Q 月 +b (5)

[0175] In formula (5), ZD 月均值 The monthly average turbidity is NTU; Q 月 denoted as monthly water supply (in millions of tons); k represents the slope of the monthly water supply-turbidity average working curve; and b represents the intercept of the monthly water supply-turbidity average working curve.

[0176] In this embodiment, k = -0.0337; b = 1.7855; the monthly water supply-turbidity average working curve is shown below. Figure 1 As shown.

[0177] like Figure 1 As shown, the obtained trend line equation is the working curve of monthly water supply and turbidity. In this embodiment, through correlation analysis, the correlation coefficient between monthly water supply and monthly average turbidity is -0.5283, indicating that the monthly average turbidity is negatively correlated with the monthly water supply, that is, the monthly average turbidity of the pipe network is correlated with the monthly water supply, and decreases as the monthly water supply increases.

[0178] 10. Calculate the average water supply Q of the group during the monitoring period and the control period. 组均值

[0179] Calculate the average water supply (Q) of the monitoring group and the control group within the monitoring period (monitoring group) and control period (control group) respectively according to formula (6). 对照-组均值 Q 监测-组均值 )

[0180] Q 组均值=Monthly water supply Q in each natural month within the monitoring or control period 月 Sum of G (6)

[0181] In formula (6):

[0182] Q 组均值 G represents the average water supply volume of the monitoring group (monitoring group) or control group (control group) within the monitoring period (monitoring group) or control period, in millions of tons; G is the number of natural months within the pipeline monitoring period or control period, and in this embodiment, G = 3.

[0183] In this embodiment, the control period (July-September 2019) and the monitoring period (October-December 2019) involve 3 months for both the control and monitoring groups, therefore the value of G is 3.

[0184] Q 对照-组均值 = (43,651,400 + 42,761,600 + 41,702,500) / 3 = 42,705,166.67 tons = 42.71 million tons

[0185] Q 监测-组均值 = (39,336,900 + 40,577,100 + 39,932,700) / 3 = 39,948,900 tons = 39.95 million tons

[0186] 11. Calculate the group turbidity working curve values ​​(referred to as group turbidity working values, i.e., ZD) for the control period (control group) and monitoring period (monitoring group) according to formula (5) (i.e., the monthly water supply-turbidity monthly average working curve). 组工作值 ZD 对照-组工作值 ZD 监测-组工作值 )

[0187] To eliminate turbidity variations caused by changes in monthly water supply, the turbidity working curve values ​​(ZD) for the control group and monitoring group were calculated based on the working curve (5) of monthly water supply versus monthly average turbidity. 对照-组工作值 ZD 监测-组工作值 ),

[0188] That is, the average water supply Q of the control group and the monitoring group respectively. 组均值 Substituting into formula (5), the turbidity working curve values ​​(ZD) within the control period (control group) and monitoring period (monitoring group) are calculated. 对照-组工作值 ZD 监测-组工作值 ).

[0189] In this embodiment, the turbidity working curve values ​​(ZD) within the monitoring period (monitoring group) and control period (control group) are as follows: 组工作值 )as follows:

[0190] ZD 对照-组工作值 = -0.0337 × Q对照-组均值 +1.7855 = -0.0337 × 42.71 + 1.7855 = 0.3463

[0191] ZD 监测-组工作值 = -0.0337 × Q 监测-组均值 +1.7855 = -0.0337 × 39.95 + 1.7855 = 0.4392

[0192] 12. Calculate the difference between the turbidity working curve values ​​of the monitoring period (monitoring group) and the control period (control group) according to formula (7), and record it as Δturbidity working difference (i.e. ΔZD);

[0193] ΔZD=ZD 监测-组工作值 -ZD 对照-组工作值 (7)

[0194] In formula (7): ΔZD is the difference between the turbidity working curve values ​​within the monitoring period (monitoring group) and the control period (control group), where Δ is the turbidity working difference; ZD 对照-组工作值 The turbidity working curve value (i.e., the control group turbidity working value, ZD) is calculated based on the monthly water supply-turbidity average working curve during the control period (control group). 对照-组工作值 ZD 监测-组工作值 The turbidity working curve value (ZD) within the monitoring period (monitoring group) is calculated based on the monthly water supply-turbidity average working curve. 监测-组工作值 ).

[0195] In this embodiment, ΔZD = 0.4392 - 0.3462 = 0.0929.

[0196] 13. Calculate the correction value (i.e., turbidity correction value, ZD) for all monitoring points and each measurement within the monitoring period according to formula (8). 修正 )

[0197] To eliminate the impact of monthly water supply on turbidity, the turbidity of the monitoring group needs to be corrected to obtain the turbidity correction value (ZD). 修正 The calculation method is as shown in formula (8).

[0198] ZD 修正 =ZD-ΔZD (8)

[0199] In formula (8): ZD 修正 (i.e., turbidity correction value) is the correction value for the turbidity value measured at each monitoring point in the regional network during the monitoring period; ZD (i.e., turbidity value) is the turbidity value of the water sample measured at each monitoring point in the regional network during the monitoring period, in NTU; ΔZD is the turbidity working difference, the difference between the turbidity working curve values ​​of the monitoring period (monitoring group) and the control period (control group), in NTU;

[0200] In this embodiment, the correction values ​​for turbidity measured at each pipeline monitoring point during the monitoring period (monitoring group, October-December 2019) are shown in Table 5.

[0201] Table 5. Turbidity Correction Values ​​(ZD) for October-December 2019 修正 (NTU)

[0202]

[0203]

[0204] 14. Determine the water quality score (score2) within the regional pipeline network monitoring cycle.

[0205] The water quality score (score2) for the water supply area network of the water supply plant during the monitoring period is calculated according to formula (9).

[0206]

[0207] In equation (9): score2 is the water quality score during the regional pipeline network monitoring period; ZD i修正 (i.e., turbidity value) i修正 ) represents the turbidity correction value (NTU) of the i-th monitoring point in the regional network within the monitoring period (monitoring group); JLi (i.e., total bacterial count i) represents the total bacterial count (CFU / mL) measured at the i-th monitoring point in the regional network within the monitoring period (monitoring group); n represents the total number of monitoring points in the regional network; in this embodiment, n = 30; m represents the total number of water quality monitoring times within the monitoring period or control period, m = G × f, where G is the number of natural months in the monitoring period or control period; f is the monitoring frequency; in this embodiment, G is 3; f is 2; m is 6; where m is 6 throughout the process of measuring the total turbidity mean, total bacterial count mean, turbidity correction coefficient, and bacterial count correction coefficient. i represents the labeling order of water quality monitoring points within the same regional pipeline network monitoring point, with a value between 1 and n; j represents the order of the number of monitoring times within the water quality monitoring cycle / control cycle, with a value between 1 and m; A is the turbidity-colony weighted value, which is the ratio of the total turbidity mean to the total colony mean; B is the turbidity correction coefficient, which represents the probability that the number of times the turbidity is less than the total turbidity mean in the water quality monitoring data of the regional pipeline network monitoring point is relative to the total number of pipeline network water quality monitoring times; that is, the ratio of the number of times the turbidity value is lower than the total turbidity mean in all turbidity data within the monitoring cycle of the regional pipeline network monitoring point to the total number of pipeline network water quality monitoring times; C is the total colony count correction coefficient, which represents the probability that the total colony count is less than the total colony mean in the water quality monitoring data of the regional pipeline network monitoring point is relative to the total number of pipeline network water quality monitoring times; that is, the ratio of the number of times the total colony count is lower than the total colony mean in all total colony count data within the monitoring cycle of the regional pipeline network monitoring point to the total number of pipeline network water quality monitoring times.

[0208] 15. Measure the water quality score (score1) of the regional pipe network during the control period.

[0209] The water quality score (score1) of the water supply area network of the water supply plant during the control period is calculated according to formula (10).

[0210]

[0211] In formula (10): score1 is the water quality score within the regional network control period; ZDi (i.e., turbidity value i) is the water turbidity value (NTU) at the i-th monitoring point in the regional network within the control period; JLi- 对照 (i.e., colony count i) is the total number of colonies at the i-th monitoring point in the regional network during the control period, in CFU / mL; n is the total number of monitoring points in the regional network; in this embodiment, n = 30; m is the total number of water quality monitoring times during the monitoring period or control period, m = G × f, where G is the number of natural months in the monitoring period or monitoring control period; f is the monitoring frequency; in this embodiment, G = 3; f = 2; m = 6; where m is 6 throughout the determination of the total mean turbidity, total mean colony count, turbidity correction factor, and colony count correction factor. i represents the labeling order of water quality monitoring points within the same regional pipeline network monitoring point, with i values ​​ranging from 1 to n; j represents the order of monitoring times within the water quality monitoring cycle / control cycle, with j values ​​ranging from 1 to m; A represents the turbidity-colony weighted value, which is the ratio of the total turbidity mean to the total colony mean; B represents the turbidity correction coefficient, which indicates the probability that the number of times the turbidity is less than the total turbidity mean in the water quality monitoring data of the regional pipeline network monitoring point is relative to the total number of pipeline network water quality monitoring points; that is, the ratio of the number of times the turbidity value is lower than the total turbidity mean in all turbidity data within the monitoring cycle or control cycle of the regional pipeline network monitoring point to the total number of pipeline network water quality monitoring points; C represents the total colony count correction coefficient, which indicates the probability that the total colony count is less than the total colony mean in the water quality monitoring data of the regional pipeline network monitoring point is relative to the total number of pipeline network water quality monitoring points; that is, the ratio of the number of times the total colony count is lower than the total colony mean in all total colony count data within the monitoring cycle or control cycle of the regional pipeline network monitoring point to the total number of pipeline network water quality monitoring points.

[0212] The water quality score of the control group (i.e., the monitoring control period) is score1; the water quality score of the monitoring group (i.e., the monitoring period) is score2. The water quality score of the pipeline network during the control period is calculated according to formula (10), which is the water quality score of the pipeline network for the three months from July to September 2019 (i.e., the pipeline network water quality evaluation score), and score1 is 1546;

[0213] The network water quality score score2 within the monitoring period is calculated according to formula (9), which is the network water quality score (i.e., network water quality evaluation score) for the three months from October to December 2019. The score2 is 1501.

[0214] 15. Calculate the water quality score difference Δscore, which is the difference in water quality scores between the monitoring period and the control period.

[0215] The difference in water quality scores between the monitoring period and the control period is calculated according to formula (11).

[0216] Δscore=score2-score1 (11)

[0217] A score difference Δscore greater than 0 indicates that switching water sources, treatment processes, or adjusting treatment parameters have an improving effect on the water quality of the pipe network; a score less than 0 indicates that switching water sources, treatment processes, or adjusting treatment parameters have a negative impact on the water quality of the pipe network; a score equal to 0 indicates that switching water sources, processes, and adjusting parameters have no impact on the water quality of the pipe network.

[0218] In this embodiment, the water supply area of ​​the water plant did not undergo pipeline updates during the water quality evaluation period from April 2019 to January 2020, and the water source remained the same. Therefore, the deterioration of the water quality in the pipeline during this period was related to the adjustment of the water plant's processes and parameters.

[0219] In this embodiment, the score difference Δscore is -45, indicating that the water quality in October, November, and December 2019 was slightly worse than the network water quality in July, August, and September 2019. However, the difference is not particularly large. If the two scores are correlated with the water plant's process or parameter adjustments, it can be seen that the process parameter adjustments have a slight negative impact on the network water quality. The water plant needs to revise the adjustment plan, increasing the adjustment range in the opposite direction. The specific operations to guide the water plant in making process adjustments are as follows:

[0220] For example: if the water plant's process adjustment involves increasing the dosage of coagulants, flocculants, or pre-oxidants, and the quality of the treated water does not change significantly and remains better than the national drinking water standards, but the water quality in the distribution network does not improve, then the water plant should adjust the dosage of these chemicals to be reduced. If the process adjustment involves reducing the dosage of these chemicals, and the water quality in the distribution network does not change significantly, then a balance can be found between reducing the dosage of chemicals and improving water quality, achieving the goal of energy conservation and consumption reduction. If the process adjustment involves adjusting a certain parameter, and the quality of the treated water does not change significantly and remains better than the national drinking water standards, but the water quality in the distribution network improves, then the parameter needs to be adjusted in this direction, and then the water quality in the distribution network should be evaluated again. This will allow the process parameters and dosage to be controlled within a relatively precise range, providing practical guidance for the water plant's process adjustment and promoting the integration of the plant and the distribution network or the coordinated operation of the plant and the distribution network.

[0221] Since water plant processes and parameters are not frequently adjusted, the method of this invention can accurately pinpoint the causes of changes in water quality in the pipe network, providing strong and scientific guidance for adjusting water plant processes and parameters.

[0222] Furthermore, this evaluation method allows for targeted optimization of water plant processes and parameters. For example, if the water quality at the current water plant is already excellent and significantly better than the national drinking water standards, and the introduction of new processes such as ultrafiltration or nanofiltration, or adjustments to some process parameters, does not significantly change the water quality—for instance, due to the advanced technology, the turbidity of the effluent before adjustment was around 0.3 NTU and the bacterial count was undetectable; after adjustment, the turbidity is around 0.25 NTU and the bacterial count is still undetectable—it is difficult to determine the necessity and accuracy of the process or water quality adjustment based solely on the change in water quality. In other words, there is no clear reference indicator for judging the direction of new process or parameter adjustments based on the effluent quality, leaving the water plant's process and parameter adjustments in a relatively crude manner. However, the pipe network is relatively more sensitive and more sensitive to adjustments in water plant processes and parameters, making the direction and scope of these adjustments clearer and more precise. This also aligns with the integrated plant-network concept required by the new national drinking water standards.

[0223] Compared to single-point water quality assessments at pipeline monitoring points, this method expands the monitoring cycle and scope, extending from one-dimensional, single-point, single-time assessments to three-dimensional, multi-point, long-term assessments. It eliminates problems such as pipeline feedback lag and inaccurate assessments caused by differences in pipeline characteristics (e.g., pipe age, material, scale composition) leading to varying sensitivity at different pipeline points. This makes the assessment results more reliable and accurate. It also establishes a link between water source switching, process and parameter adjustments at water treatment plants and pipeline water quality, providing direction for precise adjustments to water treatment plant processes.

[0224] The lag in pipe network development can also be attributed to the different characteristics of pipe networks, which lead to different sensitivities to changes in water quality. Some pipe networks with long service life and loose scale may quickly show yellow water and deteriorate water quality when water quality changes. On the other hand, some pipe networks with short service life and stainless steel pipes may not show obvious changes in water quality at first, and it may take some time for the changes to become apparent.

[0225] The above embodiments of the present invention are merely exemplary and do not constitute any limitation on the scope of the present invention. Those skilled in the art should understand that modifications or substitutions can be made to the details and form of the technical solutions of the present invention without departing from the spirit and scope thereof, but all such modifications and substitutions fall within the protection scope of the present invention.

Claims

1. A method for evaluating the quality of water in a pipe network in a water supply area of a water supply plant, characterized by, Includes the following steps: 1) After the water supply plant switches its water source, adjusts its treatment process or treatment parameters, n monitoring points are randomly selected from the water quality monitoring points in the water supply area to be evaluated. Water samples are collected at each selected monitoring point during the monitoring period, and the water quality of the samples is measured. The water quality data of all selected monitoring points within the monitoring period are used as the water quality monitoring group data, which is recorded as the monitoring group. The water quality of the measured water samples refers to the turbidity and colony count of the measured water samples. 2) Review and retrieve water quality data from the same monitoring points in the same pipeline network area of ​​the water supply plant before the water source switch, treatment process or treatment parameter adjustment, and at the same monitoring frequency within the control period. Use the water quality data of all monitoring points within the control period as the water quality control group data, and record it as the control group. 3) Based on the water quality monitoring group data measured in step 1) within the monitoring period and the water quality control group data retrieved in step 2) within the control period, calculate the average turbidity of water samples from all pipeline monitoring points within the monitoring and control periods, i.e., the total average turbidity ZD. 总均值 And the average number of colonies, i.e., the total colony mean JL 总均值 ; 4) Calculate the turbidity-colony weighted value A according to formula (3). A = Total mean turbidity / Total mean colony count (3); 5) determination of the turbidity mean value for each monitoring natural month within the monitoring period, i.e. the turbidity monthly mean value ZD 月均值 ; 6) Plot the monthly water supply-turbidity average monthly value working curve. Query and call the monthly water supply quantity Q of the water supply plant in the water supply area to be evaluated water quality in the monitoring period, the control period 月 ; Based on monthly water supply Q 月 Using the X-axis as the x-axis, the monthly average turbidity ZD obtained in step 5) corresponding to the monthly water supply is... 月均值 Using the Y-axis, plot the working curve of monthly water supply - monthly average turbidity, as shown in formula (5): ZD 月均值 = k x Q 月 + b (5) In formula (5), ZD 月均值 is the monthly average turbidity, NTU; Q 月 is the monthly water supply, million tons; k is the slope of the monthly water supply-monthly average turbidity working curve; and b is the intercept of the monthly water supply-monthly average turbidity working curve. 7) the group turbidity working value ZD in the monitoring period and the control period is calculated respectively by bringing the monthly average water supply-turbidity working curve drawn in step 6) into the group water supply average Q in the monitoring period and the control period respectively. 组均值 ; and 组工作值 ; 8) Calculate the difference between the turbidity working curve values ​​within the monitoring period and the control period according to formula (7), i.e., Δturbidity working difference ΔZD; ΔZD = ZD 监测-组工作值 - ZD 对照-组工作值 (7) In formula (7): ΔZD is the difference between the turbidity working curve values ​​within the monitoring period and the control period; Δ is the turbidity working difference. 对照-组工作值 The turbidity working curve value for the control period is calculated based on the monthly water supply-turbidity average working curve, i.e., the turbidity working value ZD of the control group. 对照-组工作值 ZD 监测-组工作值 The turbidity working curve value (ZD) is calculated based on the monthly water supply-turbidity average working curve during the monitoring period, i.e., the turbidity working value of the monitoring group. 监测-组工作值 ; 9) Calculate the correction value of turbidity for all monitoring points and each determination in the monitoring period according to formula (8), that is, the turbidity correction value ZD 修正 ; ZD 修正 = ZD - ΔZD (8) In formula (8): ZD 修正 ΔZD is the turbidity working difference value, the difference value of the turbidity working curve value in the monitoring period and the control period, NTU; 10) Calculate the water quality score2 of the water supply area network of the water supply plant within the monitoring period according to formula (9). （9） In equation (9), score2 is the water quality score within the regional pipeline network monitoring period; ZD i修正 , NTU, represents the turbidity correction value at the i-th monitoring point within the regional network during the monitoring period; JLi represents the total bacterial count at the i-th monitoring point within the regional network during the monitoring period, CFU / mL; n represents the total number of monitoring points within the regional network; m represents the total number of water quality monitoring sessions during the monitoring or control period, m = G × f, where G is the number of natural months in the monitoring or control period; f is the monitoring frequency; A is the turbidity-colony weighted value; B is the turbidity correction coefficient; C is the colony correction coefficient. 11) Calculate the water quality score (score1) of the water supply area network of the water supply plant within the control period according to formula (10). （10） In formula (10), score1 represents the water quality score within the regional network control period; ZDi represents the turbidity value (NTU) of the i-th monitoring point within the regional network within the control period; JLi- 对照 denoted as CFU / mL, it represents the total bacterial count (CFU / mL) at the i-th monitoring point within the regional pipe network during the control period; n represents the total number of monitoring points within the regional pipe network; m represents the total number of water quality monitoring sessions during the monitoring or control period, where m = G × f, and G is the number of natural months in the monitoring or control period; f is the monitoring frequency; A is the turbidity-colony weighted value; B is the turbidity correction factor; C is the colony correction factor; where... The turbidity correction factor B is determined according to the following method: B-1) Among the turbidity monitoring values of the water samples collected at all water quality monitoring points in the statistical monitoring period, the actual turbidity monitoring value is less than the total average turbidity ZD 总均值 , that is, the number of times that the turbidity monitoring data in the monitoring group is less than the total average turbidity. B-2) In the statistical step 2), among the turbidity values ​​of water samples from the same water quality monitoring points selected within the monitoring period as the control period, those turbidity values ​​retrieved from the same water quality monitoring points within the monitoring period, are less than the overall turbidity mean ZD. 总均值 The number of times the turbidity query data in the control group is less than the overall turbidity mean; B-3) Calculate the turbidity correction coefficient B for the monitoring period and the control period according to formula (1), respectively. B = Number of times the turbidity monitoring data or turbidity query data is less than the total turbidity average / (n×m) (1) In formula (1), B is the turbidity correction coefficient; m is the total number of water quality monitoring times within the monitoring period or control period, m = G × f, where G is the number of natural months in the monitoring period or control period; f is the monitoring frequency; and n is the number of network monitoring points selected within the regional network. The colony correction factor C was determined according to the following method: C-1) Among the colony counts of water samples collected from all water quality monitoring points within the statistical monitoring period, the colony count was less than the total colony mean. 总均值 The number of times the colony count in the monitoring group is less than the total average colony count; C-2) In the control period, the number of times that the colony count query data is less than the total colony average JL, i.e., the number of times that the colony count query data is less than the total colony average in the control group 总均值 of the same water quality monitoring points selected in the monitoring period, and the colony count query data is less than the total colony average JL C-3) Calculate the colony correction coefficient C for the monitoring period and the control period according to formula (2), respectively. C = Number of times the colony monitoring data or colony query data is less than the total colony mean / (n×m) (2) In formula (2), C is the colony correction coefficient; m is the total number of water quality monitoring times within the monitoring period or control period, m = G × f, where G is the number of natural months in the monitoring period or control period; f is the monitoring frequency; and n is the number of network monitoring points selected within the regional network. 12) Calculate the water quality score difference Δscore between the monitoring period and the control period according to formula (11). Δscore = score2- score1 (11) If Δscore is greater than 0, then switching water sources or adjusting water treatment processes and parameters will improve the water quality of the pipe network. If Δscore is less than 0, then switching water sources or adjusting water treatment processes and parameters will have a negative impact on the water quality of the pipe network. If Δscore equals 0, then switching water sources or adjusting water treatment processes and parameters will have no impact on the water quality of the pipe network.

2. The method of claim 1 wherein, The number of water quality monitoring points selected in step 1) is n≥10.

3. The method of claim 1 wherein, The number of water quality monitoring points n selected in step 1) is 20-40.

4. The method of claim 1 wherein, The number of water quality monitoring points selected in step 1) is n, which is 30.

5. The method of claim 1 wherein, The turbidity was determined by the scattering method in "Standard Examination Methods for Drinking Water - Sensory Characteristics and Physical Indicators"; the total bacterial count was determined by the plate counting method in "Standard Examination Methods for Drinking Water - Microbiological Indicators".

6. The method of claim 1 or 2, wherein, The monitoring period described in step 1) is ≥ 3 consecutive natural months.

7. The method of claim 1 or 2, wherein, The monitoring period described in step 1) is 3-12 consecutive calendar months.

8. The method of claim 1 or 2, wherein, The monitoring period described in step 1) is 3-4 consecutive calendar months.

9. The method of claim 1 or 2, wherein, In step 1), the water sample monitoring frequency at each water quality monitoring point is at least 2 times per month during the monitoring period. That is, during the monitoring period, water samples are collected and water quality is measured at each water quality monitoring point at least 2 times per natural month.

10. The method of claim 1 or 2, wherein, In step 1), the water sample monitoring frequency at each water quality monitoring point is 2-4 times per month during the monitoring period. That is, during the monitoring period, water samples are collected and water quality is measured at each water quality monitoring point 2-4 times per natural month.

11. The method of claim 1 or 2, wherein, The control period and the monitoring period mentioned in step 2) are the same in length.

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