A method of evaluating the quality of water in a pipe network within a service area of a water supply

Abstract

The application discloses a kind of methods for evaluating the water quality of pipe network in the water supply area of water supply plant, comprising determining water quality turbidity and bacterial count in monitoring period after water source switching, treatment process or treatment parameter adjustment of water supply plant;Inquire turbidity and bacterial count in monitoring control period before water source switching, treatment process or treatment parameter adjustment;Then calculate the average value of turbidity and bacterial count in monitoring period and control period, calculate turbidity-bacterial colony weighted value;Then according to formula, the water quality score in monitoring period and monitoring control period is determined respectively;Finally, according to the difference between the water quality score of monitoring period and monitoring control period, as the judgment basis for the effect of water plant process parameter adjustment, process improvement, water source switching, provide accurate basis for water plant process parameter optimization, fine management, process improvement status, etc., achieve the goal of water plant process management with pipe network water quality as target.

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. 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 the water quality data of the same monitoring points in the same water supply area of ​​the same pipeline network to be evaluated before the water source switch, treatment process or treatment parameter adjustment of the water supply plant, at the same monitoring frequency within the monitoring control period, and use the water quality data of all monitoring points within the monitoring control period as the water quality control group data (also known as query data or query value), 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 monitoring control period, calculate the average turbidity of water samples from all pipeline monitoring points within the monitoring period and the monitoring control period, and record it as the total turbidity mean ZD.总均值 The average number of colonies, denoted as 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 water quality score of the pipe network in the water supply area during the monitoring period and the monitoring control period according to formula (4); the water quality score of the pipe network during the monitoring period is recorded as score2; the water quality score of the pipe network during the monitoring control period is recorded as score1.

[0013]

[0014] In formula (4):

[0015] `score` represents the regional network water quality score; `ZDi` represents the turbidity value (NTU) measured at the i-th monitoring point within the regional network, where i is 1-n; `JLi` represents the total bacterial count (CFU / mL) measured at the i-th monitoring point within the regional network, where i is 1-n; `n` represents the total number of selected monitoring points within the regional network; `m` represents the total number of water quality monitoring sessions within the monitoring or control period, where `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 colony correction coefficient.

[0016] 6) Calculate the water quality score difference Δscore between the monitoring period and the control period according to formula (5).

[0017] Δscore = score2 - score1 (5)

[0018] In formula (5):

[0019] score2 is the network water quality score during the monitoring period; score1 is the network water quality score during the monitoring control period.

[0020] 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.

[0021] 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.

[0022] 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.

[0023] In step 1), the number of water quality monitoring points selected is n≥10, preferably 20-40, and more preferably 30.

[0024] In particular, the sampling frequency of water samples collected at the selected pipeline water quality monitoring points is the same as the sampling frequency of water quality monitoring at the water plant.

[0025] 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.

[0026] 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.

[0027] In step 1), the monitoring period is ≥2 months, preferably 3-12 consecutive natural months, and more preferably 3-4 consecutive natural months.

[0028] 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.

[0029] In step 1), the water sample collection frequency f at each 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.

[0030] 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.

[0031] In step 2), the monitoring control period is the period of network water quality monitoring before the water source switch, water plant process or parameter adjustment, and is the same as the monitoring period duration; the natural month of monitoring is the same as the natural month of the monitoring period.

[0032] 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 collected at the same monitoring frequency within the monitoring control period as in step 1).

[0033] Among them, the water quality data retrieved in step 2) is called water quality query data or query value.

[0034] In particular, the water turbidity data that is consulted and retrieved is called the turbidity query value (turbidity query data); the water colony count data that is consulted and retrieved is called the colony query value (colony query data).

[0035] Query and retrieve water quality monitoring data from the same monitoring point in the same water supply area network of the water supply plant as the water quality monitoring point selected in step 1), within the monitoring control period before the water source switch or before the water treatment process and parameters are adjusted, at the same monitoring frequency, and use this data as the water quality monitoring control group.

[0036] The monitoring duration of the monitoring control period is the same as that of the monitoring period, which is a continuous natural month of the same duration. The monitoring control period is one year different from the monitoring period, and the monitoring control period is one year earlier than the monitoring period.

[0037] The monitoring period and the monitoring control period have the same monitoring months, and the monitoring control period is one year apart from the monitoring period. For example, if the monitoring period is July-September 2019, then the monitoring control period is July-September 2018.

[0038] This refers to water quality monitoring data within the same water supply network, collected at the same frequency and within the corresponding time range of the monitoring cycle one year prior to the water source switch or adjustment of the water treatment process or parameters. This data serves as the water quality monitoring control group. The control group is one year apart from the monitoring cycle, and the control group and monitoring cycle have the same natural months and monitoring duration. In other words, from the network water quality data before the water source switch or adjustment of the water treatment process and parameters, the network water quality monitoring data of water samples collected at the same monitoring points in step 1) under the same natural month, monitoring duration, and monitoring frequency are retrieved and used as the water quality monitoring control group. The water quality monitoring cycle of the control group is defined as the monitoring control cycle, which is one year apart from the monitoring cycle. For example, if the monitoring cycle is March-May 2022, then the monitoring control cycle is March-May 2021.

[0039] The turbidity correction factor B mentioned in step 5) is determined according to the following method:

[0040] 5A) 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 average ZD. 总均值 The number of times the turbidity monitoring data in the monitoring group is less than the overall turbidity mean;

[0041] 5B) In step 2), among the turbidity values ​​of water samples from the same water quality monitoring points selected within the monitoring period that were retrieved and consulted during the statistical step, the turbidity data retrieved was 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;

[0042] 5C) Calculate the turbidity correction factor B for the monitoring period and the monitoring control period according to formula (1).

[0043] B = Number of times the turbidity monitoring data or turbidity query data is less than the total turbidity mean / (n×m) (1)

[0044] 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 = G × f, where G 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.

[0045] The turbidity correction factor is the number of times the measured turbidity data or the turbidity query data within the monitoring period is less than the total turbidity mean, divided by (n×m).

[0046] The colony correction factor C in step 5) is determined according to the following method:

[0047] 5-1) 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;

[0048] 5-2) In step 2), among the water samples from the same water quality monitoring points selected within the monitoring control period, the colony count data retrieved and consulted showed that the colony count was less than the total colony mean. 总均值 Quantity;

[0049] 5-3) Calculate the colony correction factor C for the monitoring period and the monitoring control period according to formula (2).

[0050] C = Number of times the colony monitoring data or colony query data is less than the total colony mean / (n×m) (2)

[0051] 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 = G × f, where G 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.

[0052] The colony correction factor is the number of times the colony count data measured within the monitoring period or the colony count query data within the monitoring control period is less than the total colony mean, divided by (n×m).

[0053] 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.

[0054] 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.

[0055] 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 lower 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 monitoring control period to the total number of pipeline network monitoring times.

[0056] 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 colony mean, relative to 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 colony mean in all colony total data of the regional pipeline network monitoring point within the monitoring period or monitoring control period to the total number of pipeline network monitoring times.

[0057] In the water quality evaluation method of the present invention, the higher the score obtained according to formula (4), the better the water quality of the pipeline network.

[0058] When evaluating the impact of water source switching, treatment process adjustments, or parameter changes 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 pipe network monitoring points. If Δscore > 0, it indicates that the water quality at that monitoring point is better than before the adjustment after the water source switching or treatment process / parameter adjustment. If the improvement is due to the water source switching, it means that the new 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 is necessary to be aware of the risk of fluctuations in pipe network water quality caused by the switch. If the improvement in pipe network water quality is due to the adjustment of the water treatment process or 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 make the adjustment range more precise. 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.

[0059] This invention provides a method for judging the adjustment of water plant processes and parameters based on the water quality of the pipe network. 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.

[0060] 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.

[0061] Compared with the prior art, the present invention has the following advantages and benefits:

[0062] 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.

[0063] 2. 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.

[0064] 3. 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. Detailed Implementation

[0065] 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.

[0066] Example 1

[0067] Taking the water treatment process and treatment parameters of a water supply plant adjusted in July 2019 as an example, the water quality of the pipe network in the water supply area was monitored and evaluated.

[0068] 1. Set up regional pipeline water quality monitoring points and conduct water quality testing.

[0069] 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.

[0070] 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.

[0071] 1B. After adjusting the water treatment process parameters at the water supply plant, collect water samples at each selected monitoring point in the pipeline network and determine the water quality of the collected samples (water quality indicators include turbidity (ZD) and total bacterial count (JL)); among which:

[0072] Turbidity was determined by the scattering method in the "Standard Examination Methods for Drinking Water - Sensory Characteristics and Physical Indicators", and the unit of turbidity was NTU.

[0073] The total colony count was determined according to the plate count method in "Standard Examination Methods for Drinking Water - Microbiological Indicators", and the colony count unit is CFU / mL;

[0074] Water sampling and water quality monitoring (i.e., monitoring cycle) shall be for at least 3 consecutive calendar months (usually 3-12 calendar months, preferably 3 consecutive calendar months);

[0075] 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, each monitoring point collects water samples and measures water quality at least 2 times per month;

[0076] 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 month, and the turbidity and colony count of the water samples are measured.

[0077] 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 designated as monitoring group data, i.e., water quality data of all monitored group water samples are designated as monitoring group water quality data, and are recorded as monitoring group; the monitoring period is any consecutive 3-12 calendar months after the water source of the water supply plant is switched or the water treatment process and treatment parameters are adjusted, preferably any consecutive 3 months.

[0078] In this embodiment, the monitoring frequency of the sampling points is taken as 2 times / month as an example. Other frequencies of 2-4 times / month are also applicable to this invention. The monitoring cycle duration is described using 3 months as an example. Usually, the monitoring cycle duration is at least 3 consecutive months, typically 3-12 consecutive months, and preferably 3 months.

[0079] In this embodiment, the water sample collection and water quality monitoring period (monitoring calendar month) is July, August, and September 2019. The monitoring period is 3 months, and the monitoring frequency f is 2 times / month; the water quality monitoring results are shown in Tables 1 and 2.

[0080] 2. Review and retrieve water quality data from regional pipeline network monitoring points during the monitoring control period.

[0081] Review and retrieve water quality (turbidity and total bacterial count) data of water samples collected from the same pipeline monitoring points in the year prior to the water source switch or water treatment process and process parameter adjustment, under the same natural month, same monitoring duration, and same monitoring frequency corresponding to the monitoring cycle. Use the retrieved data as the control group data and record it as the control group.

[0082] In other words, the water quality data of water samples collected from the same pipeline monitoring points as the monitoring group within the monitoring control period are used as the control group data. The monitoring control period is the same natural month as the monitoring period in the year preceding the monitoring period. That is, the monitoring duration of the monitoring control period is the same as that of the monitoring period, which is the same month as the consecutive natural month corresponding to the monitoring period. The monitoring control period is one year different from the monitoring period, and the monitoring control period is one year earlier than the monitoring period, and the natural month is the same as that of the monitoring period.

[0083] The water quality (turbidity and total bacterial count) data of water samples collected from the same monitoring points in the same pipeline network and under the same monitoring frequency within the same natural month and monitoring duration one year prior to the monitoring cycle when the water source was switched or the water treatment process and process parameters were adjusted. In other words, the water samples collected by the water supply plant in the same water supply area one year prior to the adjustment of the water treatment process and treatment parameters, within the same monitoring natural month and monitoring duration, and under the same monitoring frequency, were used as control group water samples. The water quality data of the control group water samples were used as control group data.

[0084] The monitoring control month is the same natural month in the year before the water source switch or the adjustment of water treatment process and parameters, when the water supply plant conducts water sample monitoring at the same monitoring point in the same pipeline network. For example, if the monitoring month is July, August, and September 2019, then the monitoring control month is July, August, and September 2018; if the monitoring month is April, May, June, and July 2020, then the monitoring control month is April, May, June, and July 2019. And so on.

[0085] The monitoring period is the duration of a calendar month. The monitoring control period is the duration of a calendar month. The monitoring control period is the same as the monitoring period, but the monitoring control period differs from the monitoring period by one year. For example, if the monitoring months are July, August, and September 2019, the monitoring period is 3 consecutive months; the monitoring control period is also 3 months, from July to September 2018, lasting 3 months, and the monitoring period is 1 year apart from the monitoring control period.

[0086] Water samples collected from all 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 within the monitoring 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. Specifically, the water quality (turbidity and total bacterial count monitoring data) of water samples collected from the same pipeline monitoring points within the same monitoring natural month and monitoring frequency as the year prior to the water source switch or water treatment process and process parameter adjustment is used as the control group.

[0087] In this embodiment, all water samples collected in July, August, and September 2018 (the monitoring control months, with a monitoring control period of 3 months) at the same monitoring points in the same pipeline network and at the same monitoring frequency were used as control group water samples; the water quality data of the control group water samples were used as control group data (denoted as control group). The turbidity and colony count data of the control group water samples are shown in Tables 1 and 2.

[0088] Table 1. Turbidity (NTU) of water at monitoring points in the regional pipe network during the monitoring and control periods.

[0089]

[0090]

[0091] Table 2. Number of bacterial colonies (CFU / mL) in water at monitoring points in the regional pipe network during the natural month of the monitoring period and the monitoring control period.

[0092]

[0093]

[0094] 3. Measure the total mean turbidity of the water (i.e., ZD). 总均值 )

[0095] 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., 3 calendar months of monitoring control) was calculated and recorded as the total turbidity mean (ZD). 总均值 The calculation results are shown in Table 1.

[0096] Total mean turbidity (ZD) 总均值 The turbidity value refers to the average turbidity of water samples from all pipeline monitoring points within the monitoring period and the monitoring control period, i.e., the average turbidity value of all pipeline monitoring points within the control group and the monitoring group.

[0097] For example, in this embodiment, the turbidity data of 180 water samples collected from 30 pipeline monitoring points numbered 1-30 within the monitoring control period (July, August, and September 2018) and the average turbidity data of 180 water samples collected from 30 pipeline monitoring points numbered 1-30 within the monitoring period (July, August, and September 2019) are used to obtain the total average turbidity ZD of the pipeline water quality. 总均值 It is 0.34 NTU.

[0098] 4. Measure the total bacterial count (JL) of the water. 总均值 )

[0099] 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., 3 calendar months of monitoring control) was calculated and recorded as the total colony mean (i.e., JL). 总均值 The calculation results are shown in Table 2.

[0100] 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 period and the monitoring control period, i.e., the average bacterial count of all pipeline monitoring points within the control group and the monitoring group.

[0101] For example, in this embodiment, the average of the colony data of 180 water samples collected from 30 pipeline monitoring points numbered 1-30 within the monitoring control period (July, August, and September 2018) and the average of the colony data of 180 water samples collected from 30 pipeline monitoring points numbered 1-30 within the monitoring period (July, August, and September 2019), i.e., the average of the colony count data of the 30 pipeline monitoring points numbered 1-30 over 6 months, is used to obtain the total average colony count JL of the pipeline water quality. 总均值 It was 1.74 CFU / mL.

[0102] 5. Calculate the turbidity correction factor B

[0103] 5A. Among the turbidity monitoring values ​​of all monitoring points and water samples collected during the monitoring period and the monitoring 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.

[0104] For example, in the two monitoring sessions in July 2018 within the monitoring control period, the measured turbidity data from monitoring points 1-30 in the first monitoring session of July 2018 showed values ​​lower than the overall turbidity mean (0.34 NTU) 16 times, meaning 16 out of 30 measured turbidity values ​​were lower than the overall turbidity mean. The second monitoring session showed 19 such values, and so on. The statistical results are shown in Table 3. Similarly, in the two monitoring sessions in July 2019 within the monitoring period, the measured turbidity data from monitoring points 1-30 in the first monitoring session of July 2019 showed 22 such values, meaning 22 out of 30 measured turbidity values ​​were lower than the overall turbidity mean. The second monitoring session showed 16 such values, and so on. The statistical results are shown in Table 3.

[0105] 5B. Calculate the correction value B (i.e., turbidity correction coefficient) for turbidity measurement in the monitoring group (all turbidity measurement data within the monitoring period) and the control group (all turbidity measurement data within the monitoring control period) according to formula (1); B = the number of times the turbidity monitoring / query data in the monitoring group or control group is less than the total turbidity mean / (n×m) (1)

[0106] In formula (1),

[0107] B is the correction value for turbidity measurement during turbidity monitoring, i.e., the turbidity correction coefficient;

[0108] m is the total number of water quality monitoring times within 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, m is 6;

[0109] n represents the number of pipeline monitoring points selected within the regional pipeline network; in this embodiment, n = 30.

[0110] 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 lower 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 the monitoring control period to the total number of pipeline network monitoring times. The turbidity correction factor B for the monitoring group and the control group were calculated according to formula (1), and the measurement results are shown in Table 3.

[0111] For example: Control group: Turbidity correction coefficient B1 = (16+19+14+16+16+9) / (30×6) = 0.50 for 30 pipeline monitoring points and a total of 6 monitoring sessions during the 3-month monitoring control period from July to September 2018; Monitoring group: Turbidity correction coefficient B2 = (22+16+17+20+20+25) / (30×6) = 0.67 for 30 pipeline monitoring points and a total of 6 monitoring sessions during the 3-month monitoring control period from July to September 2019.

[0112] Table 3 Correction coefficients for turbidity and colony count

[0113]

[0114] 6. Calculate the colony correction factor C

[0115] 6A. Among the colony counts of all monitoring points and water samples collected during the monitoring period and the monitoring control period, the measured colony counts were less than the total average colony count (JL). 总均值 The number (i.e., frequency) of ) is shown in Table 3.

[0116] For example, in the two monitoring sessions in July 2018 within the monitoring control period, the number of colony counts at monitoring points 1-30 in the first monitoring session in July 2018 was less than the total colony mean (1.74 CFU / mL) 26 times, meaning that 26 out of the 30 measured colony counts were less than the total colony mean of 1.74 CFU / mL. In the second monitoring session, the number of colony counts less than the total colony mean was 27 times, and so on. The statistical results are shown in Table 3. Similarly, in the two monitoring sessions in July 2019 within the monitoring period, the number of colony counts at monitoring points 1-30 in the first monitoring session in July 2019 was less than the total colony mean (1.74 CFU / mL) 26 times, and so on. The statistical results are shown in Table 3.

[0117] 6B. Calculate the correction coefficient C for colony count in the monitoring group (all colony count data within the monitoring period) and the control group (all colony count data within the monitoring control period) according to formula (2).

[0118] C = 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)

[0119] In formula (2),

[0120] C is the correction factor for colony determination during colony monitoring, i.e., the colony correction factor;

[0121] m is the total number of water quality monitoring times within 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, m is 6;

[0122] n represents the number of pipeline monitoring points selected within the regional pipeline network; in this embodiment, n = 30.

[0123] The colony correction coefficient 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 of colonies relative to 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 of colonies in all the total number of colonies data of the regional pipeline network monitoring point within the monitoring period or the monitoring control period to the total number of pipeline network monitoring times is calculated according to formula (2) for the colony number monitoring of the monitoring group and the control group respectively. The measurement results are shown in Table 3.

[0124] For example: Control group: The colony correction coefficient C1 for 30 pipeline monitoring points and a total of 6 monitoring sessions during the 3-month monitoring period from July to September 2018 was (26+27+0+25+28+24) / (30×6)=0.72; Control group: The colony correction coefficient C1 for the control group during the 3-month monitoring period from July to September 2018 was 0.72; Monitoring group: The colony correction coefficient C2 for 30 pipeline monitoring points and a total of 6 monitoring sessions during the 3-month monitoring period from July to September 2019 was (26+26+29+28+27+27) / (30×6)=0.91; Monitoring group: The colony correction coefficient C2 for the monitoring group during the 3-month monitoring period from July to September 2019 was 0.91.

[0125] 7. Calculate the turbidity-colony weighted value A

[0126] Calculate the turbidity-colony weighted value A according to formula (3).

[0127] A = ZD 总均值 / JL 总均值 (3)

[0128] 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.

[0129] In this embodiment, the total mean turbidity is ZD. 总均值 =0.34; mean total colony count JL 总均值 =1.74; A = 0.1954

[0130] The total mean turbidity is measured in NTU; the total mean colony count is measured in CFU / mL. The weighting is dimensionless. Both the total mean turbidity and the total mean colony count are calculated using the data corresponding to their respective units.

[0131] 8. Determine the water quality score within the monitoring cycle and control cycle of the regional pipeline network.

[0132] According to formula (4), calculate the monitoring control period and the water quality score within the monitoring period of the water supply area network of the water supply plant.

[0133]

[0134] In equation (4),

[0135] The score represents the water quality rating of the regional pipe network.

[0136] ZDi (i.e., turbidity value i) is the water turbidity value measured at the i-th monitoring point in the regional pipe network, in NTU;

[0137] JLi (i.e., colony count i) is the total number of colonies measured at the i-th monitoring point in the regional pipeline network, in CFU / mL;

[0138] n is the total number of monitoring points in the regional pipeline network; in this embodiment, n = 30.

[0139] m is the total number of water quality monitoring times within the water quality monitoring cycle or the monitoring control cycle, m = G × f, where G is the number of natural months in the monitoring cycle or the monitoring control cycle; f is the monitoring frequency; in this embodiment, m = 6;

[0140] In the process of measuring the total mean turbidity, the total mean colony count, the turbidity correction factor, and the colony count correction factor, m was always 6.

[0141] i represents the marking order of water quality monitoring points within the same regional pipeline network monitoring points, and the value of i is between 1 and n;

[0142] j represents the order of the number of monitoring sessions within the water quality monitoring cycle, and the value of j is between 1 and m;

[0143] A is the turbidity-colony weighted value, which is the ratio of the total turbidity mean to the total colony mean.

[0144] B is the turbidity correction coefficient, which represents the probability of 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 relative to the total number of water quality monitoring data in the pipeline network; that is, the ratio of the number of times the turbidity is lower than the total turbidity mean in all turbidity data within the monitoring period or monitoring control period of the regional pipeline network monitoring point to the total number of water quality monitoring data in the pipeline network.

[0145] C is the correction factor for total colony count, which represents the probability that the total colony count in the water quality monitoring data of the regional pipeline network monitoring point is less than the total colony mean, 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 always lower than the total colony mean in all colony count data of the regional pipeline network monitoring point within the monitoring period or monitoring control period to the total number of pipeline network water quality monitoring times.

[0146] The water quality score for the control group (i.e., the monitoring control period) is score 1; the water quality score for the monitoring group (i.e., the monitoring period) is score 2.

[0147] According to formula (4), the water quality score of the pipeline network during the monitoring control period is obtained, which is the water quality score of the pipeline network for the three months from July to September 2018 (i.e., the water quality evaluation score of the pipeline network). The score is 714.

[0148] According to formula (4), the water quality score of the pipeline network during the monitoring period is obtained as score2, which is the water quality score of the pipeline network for the three months from July to September 2019 (i.e., the water quality evaluation score of the pipeline network). The score2 is 983.

[0149] 9. Calculate the water quality score difference Δscore, which is the difference in water quality scores between the monitoring period and the control period.

[0150] The difference in water quality scores between the monitoring period and the control monitoring period is calculated according to formula (5).

[0151] Δscore = score2 - score1 (5)

[0152] A score difference Δscore greater than 0 indicates that the water quality in the pipe network from July to September 2019 was better than that from July to September 2018.

[0153] Improved water quality in the pipe network is usually related to the following: 1) water supply pipeline upgrades; 2) water source switching at water plants; 3) water treatment process and parameter adjustments at water plants.

[0154] In this embodiment, the water supply area of ​​the water plant did not undergo pipeline renewal during the 2018-2019 network water quality assessment period, and the water source remained the same. Therefore, the improved network water quality during this period was related to the adjustment of the water plant's processes and parameters. The water quality score measured by the method of this invention during the network monitoring period was higher than that during the monitoring control period, indicating that the adjustment of the treatment process and parameters during the water plant monitoring period improved the water quality in the network, demonstrating that the adjustment of the treatment process and parameters is beneficial to improving the network water quality.

[0155] Since water plant processes and parameters are not frequently adjusted, the method of this invention can accurately pinpoint the causes of improved water quality in the pipe network, providing strong and scientific guidance for adjusting water plant processes and parameters. Furthermore, this evaluation method allows for targeted optimization of water plant processes and parameters.

[0156] Under the current technological conditions of water supply plants, the quality of the effluent is already quite good, significantly exceeding the national drinking water standards. Even after introducing new technologies such as ultrafiltration and nanofiltration membranes, or adjusting some process parameters, the change in effluent quality is not significant, and it remains better than the national drinking water standards. For example, due to the advanced technology of the water plant, before the adjustment, the turbidity of the effluent was around 0.3 NTU, and the bacterial count was undetectable. After the process or parameter adjustment, the turbidity of the effluent is around 0.25 NTU, and the bacterial count is still undetectable. Therefore, with such small changes in effluent quality, it is difficult to determine the necessity and accuracy of the direction of the process or water quality adjustment based on the change in water quality. In other words, there is no clear reference indicator for judging the direction of the new process or parameter adjustment based on the effluent quality, leaving the water plant's process and parameter adjustments in a relatively crude state. However, the pipe network is relatively more sensitive and more sensitive to adjustments in the water plant's process and parameters, making the direction and scope of the adjustments clearer and more precise. This also aligns with the integrated plant-network concept required by the new national drinking water standards.

[0157] 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.

[0158] 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.

[0159] 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 water quality of a water supply network within the water supply area of ​​a water supply plant, characterized in that, 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 collected during the monitoring period are used as the water quality monitoring group data, which is recorded as the monitoring group. The measured water quality of the samples is the turbidity and colony count of the water samples. 2) Review and retrieve the water quality data of the same monitoring points in the same water supply area of ​​the same pipeline network to be evaluated before the water source switch, treatment process or treatment parameter adjustment of the water supply plant, at the same monitoring frequency within the control period, and use the water quality data of all monitoring points within the control period as the water quality control group data, which is recorded 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, and record it as the total turbidity mean ZD. 总均值 The average number of colonies, denoted as 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) Measure the water quality score of the pipe network in the water supply area during the monitoring period and the control period according to formula (4); （4） In formula (4): The score represents the water quality rating of the regional pipe network. ZDi is the turbidity value of the water measured at the i-th water quality monitoring point in the regional pipe network, in NTU; JLi represents the total bacterial count (CFU / mL) measured at the i-th water quality monitoring point within the regional pipe network. n represents the total number of water quality monitoring points selected within the regional pipe network; m is the total number of water quality monitoring times within the monitoring cycle or control cycle, m = G × f, where G is the number of natural months in the monitoring cycle or control cycle; f is the monitoring frequency. A is the turbidity-colony weighted value; B is the turbidity correction factor; C is the colony correction factor; Wherein: the turbidity correction coefficient B is determined according to the following method: 5A) 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 average ZD. 总均值 The number of times the turbidity monitoring data in the monitoring group is less than the overall turbidity mean; 5B) In step 2), among the turbidity values ​​of water samples from the same water quality monitoring points selected during the monitoring period and retrieved in the 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; 5C) Calculate the turbidity correction factor 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: 5-1) 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; 5-2) In step 2), among the water samples from the same water quality monitoring points selected during the monitoring period and the control period retrieved, the colony count data were less than the total colony mean. 总均值 The number of times the colony count in the control group is less than the total average colony count; 5-3) 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. 6) Calculate the water quality score difference Δscore between the monitoring period and the control period according to formula (5). Δscore = score2 - score1 (5) In formula (5): score2 is the network water quality score during the monitoring period; score1 is the network water quality score during the control period. 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 as described in claim 1, characterized in that, The number of water quality monitoring points selected in step 1) is n≥10.

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

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

5. The method as described in claim 1, characterized in that, 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 as described in claim 1 or 2, characterized in that, The monitoring period described in step 1) is ≥ 2 consecutive natural months.

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

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

9. The method as described in claim 1 or 2, characterized in that, 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 as described in claim 1 or 2, characterized in that, 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 as described in claim 1 or 2, characterized in that, The control period and monitoring period mentioned in step 2) are the same in length and in calendar months.

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