Method and system for predicting evolution process of water quality of water body

Abstract

The invention relates to a method and a system for predicting a water quality evolution process of a water body. The method comprises the following steps: acquiring historical water quality data of a target water body at different moments in a historical monitoring period; respectively obtaining a historical dissolved oxygen average value, a historical oxidation-reduction potential average value and a historical turbidity average value based on the historical water quality data at the corresponding moments in the plurality of historical monitoring periods; acquiring current water quality data of a target water body at a moment corresponding to the historical water quality data; determining a sunny-day water quality evaluation coefficient and a rainy-day water quality evaluation coefficient; determining the water quality condition of the target water body in the sunny day according to the change trend of the sunny day water quality evaluation coefficient, the dissolved oxygen value deviation degree and the oxidation-reduction potential value deviation degree; and determining the water quality condition of the target water body in the rainy day according to the change trend of the rainy day water quality evaluation coefficient, the dissolved oxygen value deviation degree and the historical turbidity value deviation degree. The method can quickly and accurately predict and evaluate the black and odorous risk of the water body.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular to a method and system for predicting the evolution process of water quality of a water body. Background Art

[0002] Urban water bodies not only play an important role in urban landscape, but also carry the function of flood control and drainage. However, during rainfall, urban water bodies will deteriorate in water quality due to the influx of combined sewer overflow and separate sewer rainwater. When the water environment capacity of urban water bodies exceeds the limit, the water bodies may become black and smelly for a long time, seriously affecting the quality of life of urban residents and the urban environment. This phenomenon will not only reduce the landscape value of the water body, but also increase the cost of governance.

[0003] After the urban water bodies have undergone black and smelly treatment, the return to black and smelly has become the focus of water body management. The return to black and smelly water bodies will not only seriously affect the quality of life of the people, but also greatly reduce the initial investment and increase the subsequent management costs. At present, the water environment management of urban water bodies has basically been completed. The return to black and smelly water mainly includes two situations: persistent black and smelly water bodies and black and smelly water bodies after rainfall. In addition, the monitoring of water quality in urban water bodies selects different monitoring methods according to the local economic and technological level, and the results are different. Therefore, it is particularly important to select appropriate water quality monitoring indicators and establish a method to quickly and accurately predict and evaluate the risk of black and smelly water bodies, and take countermeasures. Summary of the invention

[0004] The present invention provides a method and system for predicting the evolution process of water quality of a water body. By combining historical monitoring data with real-time monitoring data and utilizing different water quality assessment coefficients under sunny and rainy conditions, the black and smelly risk of a water body can be accurately predicted.

[0005] In order to solve the above technical problems, the present invention provides a method for predicting the evolution process of water quality, comprising:

[0006] Acquire historical water quality data of the target water body at different times during a historical monitoring period, wherein the historical water quality data includes dissolved oxygen values, redox potential values, and turbidity values ​​at different historical times;

[0007] Based on the historical water quality data at corresponding moments in a plurality of historical monitoring periods, a historical average dissolved oxygen value, a historical average redox potential value and a historical average turbidity value are obtained respectively;

[0008] Acquire current water quality data of the target water body at the time corresponding to the historical water quality data, wherein the current water quality data includes dissolved oxygen values ​​at different times, redox potential values ​​at different times, and turbidity values ​​at different times;

[0009] Determine a sunny day water quality assessment coefficient according to the dissolved oxygen values ​​at different current moments, the historical dissolved oxygen average value, the redox potential values ​​at different current moments, and the historical redox potential average value; determine a rainy day water quality assessment coefficient according to the dissolved oxygen values ​​at different current moments, the historical dissolved oxygen average value, the turbidity values ​​at different current moments, and the historical turbidity average value;

[0010] The water quality of the target water body on a sunny day is determined according to the change trend of the sunny day water quality assessment coefficient, the dissolved oxygen value deviation and the redox potential value deviation; wherein the dissolved oxygen value deviation represents the degree of change in the numerical deviation between the dissolved oxygen values ​​at different current moments and the historical dissolved oxygen average value, and the redox potential value deviation represents the degree of change in the numerical deviation between the redox potential values ​​at different current moments and the historical redox potential average value;

[0011] The water quality of the target water body on rainy days is determined based on the changing trend of the rainy day water quality assessment coefficient, the dissolved oxygen value deviation and the historical turbidity value deviation; wherein the historical turbidity value deviation represents the degree of change in the numerical deviation between the turbidity values ​​at different current moments and the historical turbidity average value.

[0012] In one embodiment of the present invention, the method further comprises:

[0013] Dividing the target water body into different areas according to water flow pattern, water depth, water surface width and water quality targets;

[0014] One or more water quality monitoring sensors for dissolved oxygen, redox potential and turbidity are respectively arranged in the different areas.

[0015] In one embodiment of the present invention, the calculation of the sunny day water quality assessment coefficient is as follows:

[0016]

[0017] Among them, Q is the water quality assessment coefficient on sunny days;

[0018] DO ti is the dissolved oxygen value at different times;

[0019] is the historical average dissolved oxygen value;

[0020] ORP ti is the redox potential value at different times;

[0021] is the historical average redox potential;

[0022] α and β are weight coefficients, and α+β=1;

[0023] n is the number of simultaneous moments in a certain period of time in the past.

[0024] In one embodiment of the present invention, the rainy day water quality assessment coefficient is calculated as follows:

[0025]

[0026] Among them, Y is the water quality assessment coefficient on rainy days;

[0027] DO ti is the dissolved oxygen value at different times;

[0028] is the historical average dissolved oxygen value;

[0029] NTU ti is the turbidity value at different times;

[0030] is the historical turbidity average;

[0031] α and β are weight coefficients, and α+β=1;

[0032] n is the number of simultaneous moments in a certain period of time in the past.

[0033] In one embodiment of the present invention, the water quality of the target water body on a sunny day is determined according to the change trend of the sunny day water quality assessment coefficient, the dissolved oxygen value deviation and the oxidation-reduction potential value deviation, including:

[0034] When the sunny day water quality assessment coefficient continues to increase and the dissolved oxygen value deviation and the oxidation-reduction potential value deviation both continue to increase, it is determined that the water quality of the target water body on sunny days is optimized;

[0035] When the sunny day water quality assessment coefficient continues to decrease and the dissolved oxygen value deviation and the oxidation-reduction potential value deviation continue to increase, it is determined that the water quality of the target water body on sunny days has deteriorated.

[0036] In one embodiment of the present invention, the water quality of the target water body on rainy days is determined according to the change trend of the rainy day water quality assessment coefficient, the dissolved oxygen value deviation and the historical turbidity value deviation, including:

[0037] When the rainy day water quality assessment coefficient continues to increase and the dissolved oxygen value deviation and the historical turbidity value deviation both continue to increase, it is determined that the water quality of the target water body on rainy days has not deteriorated;

[0038] When the rainy day water quality assessment coefficient continues to decrease and the dissolved oxygen value deviation and the historical turbidity value deviation continue to increase, it is determined that the water quality of the target water body on rainy days has deteriorated.

[0039] In one embodiment of the present invention, the method further comprises:

[0040] Preset the black and odor threshold of the water quality assessment coefficient of the water body on sunny days, the black and odor threshold of the water quality assessment coefficient of the water body on rainy days, the dissolved oxygen threshold, the redox potential threshold and the turbidity threshold;

[0041] In response to the current dissolved oxygen value and the current redox potential value continuously decreasing and correspondingly falling to the dissolved oxygen threshold and the redox potential threshold, and the sunny day water quality assessment coefficient is less than the sunny day water body water quality assessment coefficient black and odor threshold, it is determined that the target water body has a black and odor risk;

[0042] In response to the current dissolved oxygen value and the current redox potential value both increasing continuously, and the sunny day water quality assessment coefficient increasing continuously and the difference between the sunny day water quality assessment coefficient and the black and odor threshold value increasing, it is determined that the target water body has no black and odor risk;

[0043] In response to the dissolved oxygen value at the current moment continuously decreasing and falling to the dissolved oxygen threshold value or the turbidity value at the current moment continuously increasing and rising to the turbidity threshold value, and the rainy day water quality assessment coefficient is less than the black and odor threshold value of the rainy day water body water quality assessment coefficient and the difference between the black and odor threshold value of the rainy day water body water quality assessment coefficient and the rainy day water body water quality assessment coefficient increases, it is determined that the target water body has a black and odor risk;

[0044] In response to the current moment dissolved oxygen value continuously decreasing or the current moment turbidity value continuously increasing and rising to a stable range, and the rainy day water quality assessment coefficient is not less than the rainy day water body black and smelly threshold, it is determined that the target water body does not have a black and smelly risk.

[0045] In one embodiment of the present invention, the method further comprises:

[0046] In different areas of the target water body, obtaining assessment data including sunny day water quality assessment coefficients and rainy day water quality assessment coefficients;

[0047] Perform cluster analysis on the assessment data to identify abnormal points or outliers and determine the corresponding risk thresholds;

[0048] Obtain the sunny day water quality assessment coefficient and rainy day water quality assessment coefficient of each area in the target water body in real time, and compare them with the corresponding risk thresholds respectively. If the sunny day water quality assessment coefficient or rainy day water quality assessment coefficient of the area exceeds the corresponding risk threshold, it is confirmed that the area is at risk;

[0049] If the proportion of risky areas to all areas exceeds a preset ratio threshold or the number of risky areas exceeding the risk threshold exceeds a predetermined number of times, an early warning signal is triggered.

[0050] The present invention also provides a system for predicting the evolution of urban water quality, including:

[0051] A historical water quality data acquisition module is used to acquire historical water quality data of the target water body at different times during a historical monitoring period, wherein the historical water quality data includes dissolved oxygen values, redox potential values, and turbidity values ​​at different historical times;

[0052] An average value acquisition module, used to obtain the historical average value of dissolved oxygen, the historical average value of redox potential and the historical average value of turbidity based on the historical water quality data at corresponding moments in multiple historical monitoring periods;

[0053] A current water quality data acquisition module is used to acquire the current water quality data of the target water body at the time corresponding to the historical water quality data, wherein the current water quality data includes the dissolved oxygen value at different times, the redox potential value at different times, and the turbidity value at different times;

[0054] A module for determining water quality assessment coefficients for sunny and rainy days, for determining a water quality assessment coefficient for sunny days according to the dissolved oxygen values ​​at different current moments, the historical average dissolved oxygen values, the redox potential values ​​at different current moments, and the historical average redox potential values, and for determining a water quality assessment coefficient for rainy days according to the dissolved oxygen values ​​at different current moments, the historical average dissolved oxygen values, the turbidity values ​​at different current moments, and the historical average turbidity values;

[0055] A module for determining water quality on sunny days, for determining the water quality of a target water body on sunny days according to the change trend of the sunny day water quality assessment coefficient, the dissolved oxygen value deviation and the redox potential value deviation; wherein the dissolved oxygen value deviation represents the degree of change in the value deviation between the dissolved oxygen value at different current moments and the historical dissolved oxygen average value, and the redox potential value deviation represents the degree of change in the value deviation between the redox potential value at different current moments and the historical redox potential average value;

[0056] The rainy day water quality determination module is used to determine the water quality of the target water body on rainy days based on the changing trend of the rainy day water quality assessment coefficient, the dissolved oxygen value deviation and the historical turbidity value deviation; wherein the historical turbidity value deviation represents the degree of change in the numerical deviation between the turbidity values ​​at different current moments and the historical turbidity average value.

[0057] The above technical solution of the present invention has the following advantages compared with the prior art:

[0058] The method and system for predicting the evolution of water quality in a water body described in the present invention can accurately predict the future trend of water quality changes by real-time monitoring of conventional water quality indicators such as dissolved oxygen (DO), oxidation-reduction potential (ORP) and turbidity (NTU), combined with historical monitoring data and current monitoring data. By setting the water quality assessment coefficients for sunny and rainy days, it is possible to effectively judge the optimization or deterioration of water quality, thereby achieving accurate prediction of water quality and facilitating taking measures in advance to avoid water quality deterioration. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to make the contents of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments of the present invention in conjunction with the accompanying drawings.

[0060] Figure 1 It is a schematic diagram of the prediction framework of the water quality evolution process of the water body of the present invention. DETAILED DESCRIPTION

[0061] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0062] In the present invention, "several" means one or more, "multiple" means more than two, "greater than", "less than", "exceed" and the like are understood to exclude the number itself; "above", "below", "within" and the like are understood to include the number itself. In the description of the present invention, if there is a description of "first" or "second", it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0063] Example 1

[0064] Reference Figure 1 As shown, a method for predicting the evolution of water quality in a water body according to this embodiment is as follows:

[0065] This method predicts the blackness and odor of water by monitoring conventional water quality indicators. By regularly monitoring representative points in the water body, conventional water quality indicators including dissolved oxygen (DO), oxidation-reduction potential (ORP) and turbidity (NTU) (or total suspended solids TSS) are selected. Based on the changing patterns of water quality indicators monitored in the past time period and the current water quality indicator values, the changing trends of water quality indicators in the future period are predicted.

[0066] The method comprises:

[0067] S1. Obtain historical water quality data of the target water body at different times in a historical monitoring period, wherein the historical water quality data includes dissolved oxygen values, redox potential values, and turbidity values ​​at different historical times.

[0068] In this embodiment, one day is set as a historical monitoring cycle. It can be understood that "different times" refer to different time points in a historical monitoring cycle (such as one day), such as 10:00, 14:00, etc. every day.

[0069] In this embodiment, the basic water quality and hydrodynamic information of the water body are first obtained, and the target water body is divided into different areas according to the flow state, water depth, water surface width and water quality target of the water body. Water quality monitoring sensors of dissolved oxygen (DO), oxidation-reduction potential (ORP) and turbidity (NTU) (or total suspended solids TSS) are set in different areas of the target water body. One or more monitoring points can be set in each area, with a total of N monitoring points, to ensure that the water quality data obtained is representative. By collecting DO, ORP and NTU data at different times, the data are uploaded to the central processing system.

[0070] S2. Based on the historical water quality data at corresponding moments in multiple historical monitoring periods, obtain the historical average dissolved oxygen value, the historical average redox potential value and the historical average turbidity value respectively.

[0071] By monitoring the water quality including dissolved oxygen, redox potential and turbidity at the monitoring points, the dissolved oxygen values, redox potential values ​​and turbidity values ​​corresponding to different times are obtained, as well as the historical average dissolved oxygen values, historical average redox potential values ​​and historical average turbidity values ​​at different times after multiple historical monitoring cycles are generated.

[0072] It is understandable that the “corresponding time” refers to the same time point in each historical monitoring cycle (such as a day), such as 10:00, 14:00, etc. every day.

[0073] S3. Obtain current water quality data of the target water body at the time corresponding to the historical water quality data, wherein the current water quality data includes dissolved oxygen values ​​at different current times, redox potential values ​​at different current times, and turbidity values ​​at different current times.

[0074] S4. Determine the sunny day water quality assessment coefficient based on the dissolved oxygen values ​​at different current moments, the historical average dissolved oxygen value, the redox potential values ​​at different current moments, and the historical average redox potential value; determine the rainy day water quality assessment coefficient based on the dissolved oxygen values ​​at different current moments, the historical average dissolved oxygen value, the turbidity values ​​at different current moments, and the historical average turbidity value.

[0075] The sunny day water quality assessment coefficient can be used to judge the changes in water quality by the redox potential value and dissolved oxygen value on sunny days, and the rainy day water quality assessment coefficient can be used to judge the changes in water quality by the turbidity value and dissolved oxygen value on rainy days.

[0076] Specifically, the calculation of the sunny day water quality assessment coefficient is as follows:

[0077]

[0078] Among them, Q is the water quality assessment coefficient on sunny days;

[0079] DO ti is the dissolved oxygen value at different times;

[0080] is the historical average dissolved oxygen value, which corresponds to the DO at the same time ti ;

[0081] ORP ti is the redox potential value at different times;

[0082] is the historical average redox potential, which corresponds to the ORP at the same time ti for;

[0083] α and β are weight coefficients, and α+β=1; the values ​​of α and β are determined by the hierarchical analysis method according to the characteristics and conditions of different water bodies.

[0084] n is the number of times at the same moment in a certain period of time in the past. The period or number of times is set according to the required prediction accuracy and monitoring frequency, such as 30 days.

[0085] Specifically, the calculation of the rainy day water quality assessment coefficient is as follows:

[0086]

[0087] Among them, Y is the water quality assessment coefficient on rainy days;

[0088] DO ti is the dissolved oxygen value at different times;

[0089] is the historical average dissolved oxygen value; it corresponds to DO at the same time ti ;

[0090] NTU ti is the turbidity value at different times;

[0091] is the historical average turbidity value, which corresponds to the NTU at the same time ti ;

[0092] α and β are weight coefficients, and α+β=1; the values ​​of α and β are determined by the hierarchical analysis method according to the characteristics and conditions of different water bodies.

[0093] n is the number of times at the same moment in a certain period of time in the past. The period or number is set according to the required prediction accuracy and monitoring frequency.

[0094] The water quality assessment coefficient is formed by the cubic projection of the standard cube deviation of all values ​​in the same period and the mean of the indicator.

[0095] S5. Determine the water quality of the target water body on a sunny day according to the change trend of the sunny day water quality assessment coefficient, the dissolved oxygen value deviation and the redox potential value deviation; wherein the dissolved oxygen value deviation represents the degree of change in the value deviation between the dissolved oxygen value at different times and the historical dissolved oxygen average value, that is, The oxidation-reduction potential value deviation represents the degree of change in the value deviation between the current oxidation-reduction potential value at different moments and the historical oxidation-reduction potential average value, that is,

[0096] The water quality of the target water body on rainy days is determined according to the change trend of the rainy day water quality assessment coefficient, the dissolved oxygen value deviation and the historical turbidity value deviation; wherein the historical turbidity value deviation represents the degree of change in the numerical deviation between the current turbidity value at different times and the historical turbidity average value, that is,

[0097] Specifically, in step S5, when the sunny day water quality assessment coefficient continues to increase and the dissolved oxygen value deviation and the oxidation-reduction potential value deviation both continue to increase, it is determined that the water quality of the target water body on a sunny day is optimized;

[0098] When the sunny day water quality assessment coefficient continues to decrease and the dissolved oxygen value deviation and the oxidation-reduction potential value deviation continue to increase, it is determined that the water quality of the target water body on sunny days has deteriorated.

[0099] Specifically, in step S5, when the rainy day water quality assessment coefficient continues to increase and the dissolved oxygen value deviation and the historical turbidity value deviation both continue to increase, it is determined that the water quality of the target water body on rainy days has not deteriorated;

[0100] When the rainy day water quality assessment coefficient continues to decrease and the dissolved oxygen value deviation and the historical turbidity value deviation continue to increase, it is determined that the water quality of the target water body on rainy days has deteriorated.

[0101] Specifically, according to the actual water quality conditions of the target water body and the water quality targets, the black and odor threshold of the water quality assessment coefficient of the sunny water body, the black and odor threshold of the water quality assessment coefficient of the rainy water body, the dissolved oxygen threshold, the redox potential threshold and the turbidity threshold are preset.

[0102] During sunny days, the water quality of urban water bodies gradually deteriorates due to the release of pollutants from bottom sediments to overlying water bodies, lack of hydrodynamics in water bodies, the presence of floating objects and garbage on the water surface, and sewage outflow from outlets. As microorganisms consume a large amount of oxygen in the water, the ORP and DO values ​​decrease.

[0103] In response to the current dissolved oxygen value and the current redox potential value continuously decreasing and correspondingly falling to the dissolved oxygen threshold and the redox potential threshold, and the sunny day water quality assessment coefficient is less than the sunny day water body water quality assessment coefficient black and odor threshold, it is determined that the target water body has a black and odor risk, and when the water body optimizes the water quality due to measures such as enhancing hydrodynamics, improving the growth state of bank protection aquatic plants, and appropriate water replenishment, the DO value and the ORP value gradually increase to a certain stable range;

[0104] In response to the current dissolved oxygen value and the current redox potential value both increasing, and the sunny water quality assessment coefficient increasing and the difference with the black and odor threshold of the sunny water quality assessment coefficient increasing, it is determined that the target water body has no black and odor risk. Generally speaking, the ORP and DO values ​​of urban water bodies are not too high, the highest ORP value is generally between 400 and 600, and the highest DO value is generally between 17 and 18.

[0105] During rainy days, urban water bodies receive surface runoff, combined sewer overflow and separate rainwater from rainfall, which introduces a certain amount of pollutants into the water. Since pollutants are mostly introduced by attaching to the surface of particles, relatively few pollutants are dissolved, so dissolved oxygen (DO) and turbidity (NTU) (or total suspended solids TSS) are selected as monitoring indicators for water quality prediction and black and odor warning. Outlets and surface runoff into rivers cause the water quality to gradually deteriorate. The introduction of pollutants and a large amount of reducing substances consumes oxygen in the water, causing the NTU to increase and the DO value to decrease.

[0106] In response to the dissolved oxygen value at the current moment continuously decreasing and falling to the dissolved oxygen threshold value or the turbidity value at the current moment continuously increasing and rising to the turbidity threshold value, and the rainy day water quality assessment coefficient is less than the black and odor threshold value of the rainy day water body water quality assessment coefficient and the difference between the black and odor threshold value of the rainy day water body water quality assessment coefficient and the rainy day water body water quality assessment coefficient increases, it is determined that the target water body has a black and odor risk;

[0107] In response to the current moment dissolved oxygen value continuously decreasing or the current moment turbidity value continuously increasing and rising to a stable range, and the rainy day water quality assessment coefficient is not less than the rainy day water body black and smelly threshold, it is determined that the target water body does not have a black and smelly risk.

[0108] Specifically, the method further includes:

[0109] In different areas of the target water body, assessment data including sunny day water quality assessment coefficients and rainy day water quality assessment coefficients are obtained; specifically, the Q value and Y value of the water body are continuously collected from multiple monitoring points of the target water body.

[0110] Cluster analysis is performed on the assessment data to identify abnormal points or outliers and determine the corresponding risk thresholds; the algorithm divides the data into K clusters, each of which contains similar monitoring data points. The cluster analysis process identifies similar data points by minimizing the distance between the data points and the cluster center. When the distance between some data points of Q value or Y value and the cluster center is significantly greater than that of other data points, these points can be identified as outliers or abnormal points. According to the distribution of outliers or abnormal points, the risk thresholds of water quality assessment coefficients Q and Y are set.

[0111] Obtain the sunny day water quality assessment coefficient and rainy day water quality assessment coefficient of each area in the target water body in real time, and compare them with the corresponding risk thresholds respectively. If the sunny day water quality assessment coefficient or rainy day water quality assessment coefficient of the area exceeds the corresponding risk threshold, it is confirmed that the area is at risk;

[0112] If the proportion of areas at risk to all areas exceeds a preset threshold (such as 30%) or the number of times the areas at risk exceed the risk threshold exceeds a predetermined number of times (such as 3 times), it means that the water body as a whole already has a greater risk of being black and smelly, and the corresponding water body information will be used as early warning information to issue an early warning signal, thereby facilitating timely processing.

[0113] In addition, the average value of water quality indicators will fluctuate during long-term monitoring due to factors such as water temperature, water depth and surrounding environment. The water quality indicator values ​​that cause the water quality assessment coefficients Y and Q to exceed the risk threshold will be eliminated, and the historical average value of water quality indicators will be dynamically adjusted.

[0114] Through the above method, different monitoring methods and forecasting and early warning methods are selected according to weather conditions in order to reduce monitoring costs and reduce forecasting operations. Without obtaining weather conditions, two forecasting methods are used to monitor and forecast water quality in the same way as the above steps. This method is applied to computer forecasting models to quickly identify and predict water quality trends and issue early warning signals for black and smelly water phenomena.

[0115] Example 2

[0116] Based on the same inventive concept, this embodiment provides a system for predicting the evolution process of water quality of urban water bodies. The principle of solving the problem is similar to that of the method for predicting the evolution process of water quality of urban water bodies, and the repeated parts will not be repeated.

[0117] This embodiment provides a system for predicting the evolution of urban water quality, including:

[0118] A historical water quality data acquisition module is used to acquire historical water quality data of the target water body at different times during a historical monitoring period, wherein the historical water quality data includes dissolved oxygen values, redox potential values, and turbidity values ​​at different historical times;

[0119] An average value acquisition module, used to obtain the historical average value of dissolved oxygen, the historical average value of redox potential and the historical average value of turbidity based on the historical water quality data at corresponding moments in multiple historical monitoring periods;

[0120] A current water quality data acquisition module is used to acquire the current water quality data of the target water body at the time corresponding to the historical water quality data, wherein the current water quality data includes the dissolved oxygen value at different times, the redox potential value at different times, and the turbidity value at different times;

[0121] A module for determining water quality assessment coefficients for sunny and rainy days, for determining a water quality assessment coefficient for sunny days according to the dissolved oxygen values ​​at different current moments, the historical average dissolved oxygen values, the redox potential values ​​at different current moments, and the historical average redox potential values, and for determining a water quality assessment coefficient for rainy days according to the dissolved oxygen values ​​at different current moments, the historical average dissolved oxygen values, the turbidity values ​​at different current moments, and the historical average turbidity values;

[0122] A module for determining water quality on sunny days, for determining the water quality of a target water body on sunny days according to the change trend of the sunny day water quality assessment coefficient, the dissolved oxygen value deviation and the redox potential value deviation; wherein the dissolved oxygen value deviation represents the degree of change in the value deviation between the dissolved oxygen value at different current moments and the historical dissolved oxygen average value, and the redox potential value deviation represents the degree of change in the value deviation between the redox potential value at different current moments and the historical redox potential average value;

[0123] The rainy day water quality determination module is used to determine the water quality of the target water body on rainy days based on the changing trend of the rainy day water quality assessment coefficient, the dissolved oxygen value deviation and the historical turbidity value deviation; wherein the historical turbidity value deviation represents the degree of change in the numerical deviation between the turbidity values ​​at different current moments and the historical turbidity average value.

[0124] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0125] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0126] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0127] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0128] Finally, it should be noted that the above specific implementation methods are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to examples, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A method for predicting the evolution of water quality, characterized in that: include: Acquire historical water quality data of the target water body at different times during a historical monitoring period, wherein the historical water quality data includes dissolved oxygen values, redox potential values, and turbidity values ​​at different historical times; Based on the historical water quality data at corresponding moments in a plurality of historical monitoring periods, a historical average dissolved oxygen value, a historical average redox potential value and a historical average turbidity value are obtained respectively; Acquire current water quality data of the target water body at the time corresponding to the historical water quality data, wherein the current water quality data includes dissolved oxygen values ​​at different times, redox potential values ​​at different times, and turbidity values ​​at different times; Determine a sunny day water quality assessment coefficient according to the dissolved oxygen values ​​at different current moments, the historical dissolved oxygen average value, the redox potential values ​​at different current moments, and the historical redox potential average value; determine a rainy day water quality assessment coefficient according to the dissolved oxygen values ​​at different current moments, the historical dissolved oxygen average value, the turbidity values ​​at different current moments, and the historical turbidity average value; The water quality of the target water body on a sunny day is determined according to the change trend of the sunny day water quality assessment coefficient, the dissolved oxygen value deviation and the redox potential value deviation; wherein the dissolved oxygen value deviation represents the degree of change in the numerical deviation between the dissolved oxygen values ​​at different current moments and the historical dissolved oxygen average value, and the redox potential value deviation represents the degree of change in the numerical deviation between the redox potential values ​​at different current moments and the historical redox potential average value; The water quality of the target water body on rainy days is determined based on the changing trend of the rainy day water quality assessment coefficient, the dissolved oxygen value deviation and the historical turbidity value deviation; wherein the historical turbidity value deviation represents the degree of change in the numerical deviation between the turbidity values ​​at different current moments and the historical turbidity average value.

2. The method for predicting the evolution of water quality according to claim 1, characterized in that: The method further comprises: Dividing the target water body into different areas according to water flow pattern, water depth, water surface width and water quality targets; One or more water quality monitoring sensors for dissolved oxygen, redox potential and turbidity are respectively arranged in the different areas.

3. The method for predicting the evolution of water quality according to claim 1, characterized in that: The calculation of the sunny day water quality assessment coefficient is as follows: Among them, Q is the water quality assessment coefficient on sunny days; DO ti is the dissolved oxygen value at different times; is the historical average dissolved oxygen value; ORP ti is the redox potential value at different times; is the historical average redox potential; α and β are weight coefficients, and α+β=1; n is the number of simultaneous moments in a certain period of time in the past.

4. The method for predicting the evolution of water quality according to claim 1, characterized in that: The calculation of the rainy day water quality assessment coefficient is as follows: Among them, Y is the water quality assessment coefficient on rainy days; DO ti is the dissolved oxygen value at different times; is the historical average dissolved oxygen value; NTU ti is the turbidity value at different times; is the historical turbidity average; α and β are weight coefficients, and α+β=1; n is the number of simultaneous moments in a certain period of time in the past.

5. The method for predicting the evolution of water quality according to claim 1, characterized in that: According to the change trend of the sunny day water quality assessment coefficient, the deviation of the dissolved oxygen value and the deviation of the redox potential value, the water quality of the target water body on a sunny day is determined, including: When the sunny day water quality assessment coefficient continues to increase and the dissolved oxygen value deviation and the oxidation-reduction potential value deviation both continue to increase, it is determined that the water quality of the target water body on sunny days is optimized; When the sunny day water quality assessment coefficient continues to decrease and the dissolved oxygen value deviation and the oxidation-reduction potential value deviation continue to increase, it is determined that the water quality of the target water body on sunny days has deteriorated.

6. The method for predicting the evolution of water quality according to claim 1, characterized in that: Determining the water quality of the target water body on rainy days according to the change trend of the rainy day water quality assessment coefficient, the dissolved oxygen value deviation and the historical turbidity value deviation, including: When the rainy day water quality assessment coefficient continues to increase and the dissolved oxygen value deviation and the historical turbidity value deviation both continue to increase, it is determined that the water quality of the target water body on rainy days has not deteriorated; When the rainy day water quality assessment coefficient continues to decrease and the dissolved oxygen value deviation and the historical turbidity value deviation continue to increase, it is determined that the water quality of the target water body on rainy days has deteriorated.

7. The method for predicting the evolution of water quality according to claim 1, characterized in that: The method further comprises: Preset the black and odor threshold of the water quality assessment coefficient of the water body on sunny days, the black and odor threshold of the water quality assessment coefficient of the water body on rainy days, the dissolved oxygen threshold, the redox potential threshold and the turbidity threshold; In response to the current dissolved oxygen value and the current redox potential value continuously decreasing and correspondingly falling to the dissolved oxygen threshold and the redox potential threshold, and the sunny day water quality assessment coefficient is less than the sunny day water body water quality assessment coefficient black and odor threshold, it is determined that the target water body has a black and odor risk; In response to the current dissolved oxygen value and the current redox potential value both increasing continuously, and the sunny day water quality assessment coefficient increasing continuously and the difference between the sunny day water quality assessment coefficient and the black and odor threshold value increasing, it is determined that the target water body has no black and odor risk; In response to the dissolved oxygen value at the current moment continuously decreasing and falling to the dissolved oxygen threshold value or the turbidity value at the current moment continuously increasing and rising to the turbidity threshold value, and the rainy day water quality assessment coefficient is less than the black and odor threshold value of the rainy day water body water quality assessment coefficient and the difference between the black and odor threshold value of the rainy day water body water quality assessment coefficient and the rainy day water body water quality assessment coefficient increases, it is determined that the target water body has a black and odor risk; In response to the current moment dissolved oxygen value continuously decreasing or the current moment turbidity value continuously increasing and rising to a stable range, and the rainy day water quality assessment coefficient is not less than the rainy day water body black and smelly threshold, it is determined that the target water body does not have a black and smelly risk.

8. The method for predicting the evolution of water quality according to claim 1, characterized in that: The method further comprises: In different areas of the target water body, obtaining assessment data including sunny day water quality assessment coefficients and rainy day water quality assessment coefficients; Perform cluster analysis on the assessment data to identify abnormal points or outliers and determine the corresponding risk thresholds; Obtain the sunny day water quality assessment coefficient and rainy day water quality assessment coefficient of each area in the target water body in real time, and compare them with the corresponding risk thresholds respectively. If the sunny day water quality assessment coefficient or rainy day water quality assessment coefficient of the area exceeds the corresponding risk threshold, it is confirmed that the area is at risk; If the proportion of risky areas to all areas exceeds a preset ratio threshold or the number of risky areas exceeding the risk threshold exceeds a predetermined number of times, an early warning signal is triggered.

9. A system for predicting the evolution of urban water quality, characterized in that: include: A historical water quality data acquisition module is used to acquire historical water quality data of the target water body at different times during a historical monitoring period, wherein the historical water quality data includes dissolved oxygen values, redox potential values, and turbidity values ​​at different historical times; An average value acquisition module, used to obtain the historical average value of dissolved oxygen, the historical average value of redox potential and the historical average value of turbidity based on the historical water quality data at corresponding moments in multiple historical monitoring periods; A current water quality data acquisition module is used to acquire the current water quality data of the target water body at the time corresponding to the historical water quality data, wherein the current water quality data includes the dissolved oxygen value at different times, the redox potential value at different times, and the turbidity value at different times; A module for determining water quality assessment coefficients for sunny and rainy days, for determining a water quality assessment coefficient for sunny days according to the dissolved oxygen values ​​at different current moments, the historical average dissolved oxygen values, the redox potential values ​​at different current moments, and the historical average redox potential values, and for determining a water quality assessment coefficient for rainy days according to the dissolved oxygen values ​​at different current moments, the historical average dissolved oxygen values, the turbidity values ​​at different current moments, and the historical average turbidity values; A module for determining water quality on sunny days, for determining the water quality of a target water body on sunny days according to the change trend of the sunny day water quality assessment coefficient, the dissolved oxygen value deviation and the redox potential value deviation; wherein the dissolved oxygen value deviation represents the degree of change in the value deviation between the dissolved oxygen value at different current moments and the historical dissolved oxygen average value, and the redox potential value deviation represents the degree of change in the value deviation between the redox potential value at different current moments and the historical redox potential average value; The rainy day water quality determination module is used to determine the water quality of the target water body on rainy days based on the changing trend of the rainy day water quality assessment coefficient, the dissolved oxygen value deviation and the historical turbidity value deviation; wherein the historical turbidity value deviation represents the degree of change in the numerical deviation between the turbidity values ​​at different current moments and the historical turbidity average value.

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