River overflow pollution monitoring system and method
By dividing rain patterns and terrain states, collecting and analyzing river overflow pollution monitoring data, building a Markov chain model for concentration prediction, solving the problems of poor timeliness and lack of comprehensive monitoring of traditional monitoring methods, and achieving high-precision and high-frequency river overflow pollution monitoring.
Patent Information
- Application Number
- CN202510147181.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-11
- Publication Date
- 2025-05-30
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
Traditional river water quality monitoring methods have problems such as long monitoring cycle, poor timeliness, and inability to reflect pollution dynamics in real time, making it difficult to meet the high-precision, high frequency and real-time requirements of modern river environmental management for pollution monitoring. The existing river overflow pollution monitoring systems are mostly focused on monitoring a single water quality indicator, and lack comprehensive monitoring of the comprehensive characteristics of overflow pollution.
By dividing rain-type states according to precipitation and defining the terrain states according to land use type, overflow pollution monitoring data at the discharge outlets under different rain-type and terrain states are collected. The overflow pollutant concentration state is divided into multiple levels using historical concentration data, and a Markov chain model of overflow pollutant concentration state is constructed to conduct concentration prediction and overflow pollution intensity evaluation.
A comprehensive monitoring of the comprehensive characteristics of river overflow pollution is achieved, and the changes in overflow pollutant concentration can be accurately assessed based on the current pollutant level and weather conditions, and the timeliness and accuracy of pollution monitoring is improved.
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Figure CN120072098A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of river overflow pollution monitoring, and particularly relates to a river overflow pollution monitoring system and method. Background Art
[0002] With the rapid development of industrialization and urbanization, rivers, as important water resources and ecosystems, have attracted much attention for their pollution status. River overflow pollution is one of the important reasons for the deterioration of water quality. Especially during rainfall, the rain-sewage mixed water in the combined sewer system overflows into the river, carrying a large amount of pollutants, seriously affecting the ecological health of the river and the safety of human water use. How to monitor and warn river overflow pollution in real time is of great practical significance and urgent need for effectively protecting the river ecological environment and improving the water environment management level.
[0003] However, traditional river water quality monitoring methods mostly rely on manual sampling and laboratory analysis, which have problems such as long monitoring periods, poor timeliness, and inability to reflect pollution dynamics in real time, and are difficult to meet the high-precision, high-frequency, and real-time requirements of modern river environmental management for pollution monitoring. At present, although some river overflow pollution monitoring systems have adopted automatic monitoring equipment, most of them focus on the monitoring of single water quality indicators, such as chemical oxygen demand (COD), ammonia nitrogen, etc., lacking comprehensive monitoring of the comprehensive characteristics of overflow pollution and unable to accurately evaluate the change trend of overflow pollutant concentration. Therefore, we propose a river overflow pollution monitoring system and method. Summary of the Invention
[0004] The main purpose of the present invention is to provide a river overflow pollution monitoring system and method, which can effectively solve the problems in the background art.
[0005] To achieve the above purpose, the technical solution adopted by the present invention is as follows:
[0006] A river overflow pollution monitoring method includes:
[0007] Step 1: Divide the rainfall types in the area to be monitored into four categories: light rain, moderate rain, heavy rain, and rainstorm according to the precipitation, and define the rainfall type state of light rain as the rainfall type state of moderate rain as the rainfall type state of heavy rain as the rainfall type state of rainstorm as Obtain the rainfall type state set
[0008] The rainfall type division principle is:
[0009] When the precipitation is greater than 50 mm·d -1 then the rainfall type is rainstorm;
[0010] When the precipitation range is [25, 50) mm·d-1 When the precipitation is within the range, the rainfall type is heavy rain;
[0011] When the precipitation range is in [10, 25) mm·d -1 within the range, the rainfall type is moderate rain;
[0012] When the precipitation is less than 10, the rainfall type is light rain.
[0013] Step 2: Classify the terrain in the area to be monitored into six categories: roads, grasslands, forests, buildings, bare soil, and water bodies according to the land use type, and define the terrain states as λ 1 , λ 2 ,..., λ 6 , and obtain the terrain state set λ = {λ 1 , λ 2 ,..., λ 6};
[0014] Step 3: Collect the overflow pollution monitoring data of the outfall when a precipitation event occurs in the area to be monitored under the corresponding rainfall type state and terrain state λ g , and obtain the time series of the overflow pollutant concentration data of the outfall where h = 1, 2, 3, 4; g = 1, 2,..., 6;
[0015] Step 4: According to the collected historical concentration data of the overflow pollutants at the outfall, divide the concentration state of the overflow pollutants at the outfall into k levels, denoted as s k , and obtain the set of the concentration states of the overflow pollutants at the outfall S = {s 1 , s 2 ,..., s k};
[0016] The classification process of the pollutant concentration state includes the following steps:
[0017] Obtain the historical concentration data of the r-th type of overflow pollutant at the outfall, and use the data to construct a concentration data sample set, denoted as which represents the n-th data of the r-th type of overflow pollutant collected;
[0018] Calculate the mean and standard deviation in the concentration data sample set, and use the formula: Perform standardization processing on the q-th data point in the concentration data sample set, where is the standard parameter, and σ and μ are the variance and mean of the data in the sample set respectively; q ∈ n;
[0019] The standard parameters are mapped and adjusted to the range of [0, 1] using the Sigmoid function, and the Sigmoid function values of the standard parameters are used. Classify the data points into grades, specifically as follows:
[0020] When it is the first grade;
[0021] When it is the second grade;
[0022] When it is the third grade;
[0023] And so on,
[0024] When it is the k-th grade;
[0025] where are the minimum and maximum values of the Sigmoid function values of the standard parameters respectively;
[0026] According to the grade classification situation, determine the concentration status of the overflow pollutants at the outfall, specifically as follows:
[0027] When is the first grade, the corresponding overflow pollutant concentration status is the first grade;
[0028] When is the second grade, the corresponding overflow pollutant concentration status is the second grade;
[0029] When is the third grade, the corresponding overflow pollutant concentration status is the third grade;
[0030] And so on,
[0031] When is the k-th grade, the corresponding overflow pollutant concentration status is the k-th grade.
[0032] Step Five: Use the obtained time series to construct a Markov chain model for the concentration status of the overflow pollutants at the outfall. The model is defined as: where represents the probability that when the rainfall type state is and the terrain state is λ g the concentration of the overflow pollutants at the outfall transfers from state i to state j in one step; X t+1Denoted as the state of the pollutant concentration in the outfall overflow at time t+1; X t Denoted as the state of the pollutant concentration in the outfall overflow at time t; i, j ∈ S;
[0033] Step Six: According to the constructed Markov chain model, calculate the next sampling period at the current moment, and the predicted value C' of the concentration of the r-th type of overflow pollutant at the outfall in the area to be monitored r , and the specific process includes the following steps:
[0034] Step S61: Determine the rain type state topographic state of the outfall position at the current time t t , the concentration state X of the r-th type of overflow pollutant at the outfall t ;
[0035] Step S62: According to the rain type state and the topographic state select the time series calculate the state transition probability of the outfall overflow pollutant concentration construct the state transition probability matrix of the outfall overflow pollutant concentration In the formula, is the frequency of the concentration of the outfall overflow pollutant in the time series changing from state i to state j in one step when the rain type state is g and the topographic state is λ ;
[0036] Step S63: According to the concentration state X t , generate a random number x 1 that follows a uniform distribution, and use the random number x 1 to determine the state X of the outfall overflow pollutant concentration at time t+1 t+1 ;
[0037] Step S64: According to the concentration state X t+1 , generate another random number x 1 that follows a uniform distribution and is independent of x 2 , and use the generated random number x 2 to determine the predicted value C' of the concentration of the r-th type of overflow pollutant at the outfall in the area to be monitored at time t+1 r , and the calculation formula is: In the formula, is the upper limit of the pollutant concentration interval corresponding to the concentration state X t+1 ; is the lower limit of the pollutant concentration interval corresponding to the concentration state X t+1 ;
[0038] The state X of the concentration of pollutants overflowing from the drainage outlet at time t+1 t+1 The determination principle is as follows:
[0039] If then the state X t+1 is the first level;
[0040] If then the state X t+1 is the (M+1)th level;
[0041] where M, M+1 ∈ S; are the cumulative probabilities of the Mth step and the (M+1)th step under the transition probability matrix respectively, and m ∈ S.
[0042] The method further includes:
[0043] According to the obtained predicted value C' of the concentration of pollutants overflowing from the drainage outlet r calculate the overflow pollution intensity in the area to be monitored, and evaluate the degree of overflow pollution by using the calculation result of the overflow pollution intensity. The calculation formula of the overflow pollution intensity is:
[0044]
[0045] In the formula, RPI r represents the overflow pollution intensity of the rth type of overflow pollutant at the drainage outlet in the area to be monitored; C' rmax represents the maximum value within the hour of the predicted value C' of the concentration of the rth type of overflow pollutant r ; represents the standard value of the concentration of the rth type of overflow pollutant.
[0046] A river overflow pollution monitoring system includes:
[0047] A rain type state definition module, which is used to divide the rain type in the area to be monitored into four categories: light rain, moderate rain, heavy rain, and rainstorm according to the precipitation, and define the rain type state of light rain as the rain type state of moderate rain as the rain type state of heavy rain as the rain type state of rainstorm as to obtain the rain type state set
[0048] A terrain state definition module, which is used to divide the terrain in the area to be monitored into six categories: road, grassland, forest, building, bare soil, and water body according to the land use type, and define the terrain states as λ 1 、λ 2 、...、λ 6 in turn, and obtain the terrain state set λ = {λ1 , λ 2 ,..., λ 6};
[0049] A historical data acquisition module, configured to collect the overflow pollution monitoring data of the outfall when a precipitation event occurs in the area to be monitored, corresponding to the rain type state and the terrain state λ g at that time, and obtain the time series sequence of the overflow pollutant concentration data of the outfall;
[0050] A pollutant concentration state definition module, configured to divide the overflow pollutant concentration state of the outfall into k levels according to the collected historical concentration data of the overflow pollutants of the outfall, and obtain the set S of the overflow pollutant concentration states of the outfall = {s 1 , s 2 ,..., s k};
[0051] A model construction module, configured to construct a Markov chain model of the overflow pollutant concentration state of the outfall by using the obtained time series sequence;
[0052] A pollutant concentration prediction module, configured to calculate the predicted value C' of the r-th type of overflow pollutant concentration of the outfall in the area to be monitored in the next sampling period at the current moment according to the constructed Markov chain model r ;
[0053] An overflow pollution degree evaluation module, configured to calculate the overflow pollution intensity in the area to be monitored according to the obtained predicted value C' of the overflow pollutant concentration of the outfall r , and evaluate the overflow pollution degree by using the calculation result of the overflow pollution intensity.
[0054] The system further includes a memory, a processor, and a computer program stored on the memory and executable on the processor.
[0055] The present invention has the following beneficial effects
[0056] Compared with the prior art, by defining the rain type state according to the precipitation, obtaining the set of rain type states Define the terrain state according to the land use type, obtain the terrain state set λ, collect the time series sequence of the overflow pollution monitoring data of the outfall under each rain type state and terrain state when a precipitation event occurs in the area to be monitored, divide the outfall overflow pollutant concentration state into k levels according to the collected historical concentration data of the outfall overflow pollutants, obtain the outfall overflow pollutant concentration state set S, use the obtained time series sequence to construct a Markov chain model of the outfall overflow pollutant concentration state, calculate the next sampling period at the current moment, the predicted values of various overflow pollutant concentrations and the overflow pollution intensity of the outfall in the area to be monitored, and use the calculation result of the overflow pollution intensity to evaluate the overflow pollution degree, so as to comprehensively monitor the comprehensive characteristics of the overflow pollution, accurately evaluate the change trend of the overflow pollutant concentration according to the current pollutant level and weather state, and improve the timeliness and accuracy of pollution monitoring. BRIEF DESCRIPTION OF THE DRAWINGS
[0057] Figure 1 It is a schematic flow chart of a method for monitoring river overflow pollution according to the present invention;
[0058] Figure 2 It is a schematic structural diagram of a river overflow pollution monitoring system according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0059] The following further describes the present invention in conjunction with the specific embodiments. Among them, the drawings are only for illustrative purposes, showing only schematic diagrams, not physical diagrams, and should not be construed as a limitation to the present invention. In order to better illustrate the specific embodiments of the present invention, some components in the drawings will be omitted, enlarged or reduced, and do not represent the dimensions of the actual product.
[0060] The specific implementation process of the technical solution of the present invention includes the following steps:
[0061] Step 1: Divide the rain types in the area to be monitored into four categories: light rain, moderate rain, heavy rain, and rainstorm according to the precipitation, and define the rain type state of light rain as The rain type state of moderate rain is The rain type state of heavy rain is The rain type state of rainstorm is Obtain the rain type state set
[0062] Among them, the rain type division principle is:
[0063] When the precipitation is greater than 50 mm·d -1 , the rain type is rainstorm;
[0064] When the precipitation range is in the interval of [25, 50) mm·d -1 , the rain type is heavy rain;
[0065] When the precipitation range is within [10, 25) mm·d -1 interval, the rainfall type is moderate rain;
[0066] When the precipitation is less than 10, the rainfall type is light rain;
[0067] The corresponding rainfall type status classification principle is as follows:
[0068] When the precipitation is greater than 50 mm·d -1 then, the rainfall type status is
[0069] When the precipitation range is within [25, 50) mm·d -1 interval, the rainfall type status is
[0070] When the precipitation range is within [10, 25) mm·d -1 interval, the rainfall type status is
[0071] When the precipitation is less than 10, the rainfall type status is
[0072] Step 2: Classify the terrain in the area to be monitored into six categories: roads, grasslands, forests, buildings, bare soil, and water bodies according to the land use type, and define the terrain status as λ 1 , λ 2 ,..., λ 6 , and obtain the terrain status set λ = {λ 1 , λ 2 ,..., λ 6}.
[0073] Step 3: Collect the overflow pollution monitoring data of the outfall when a precipitation event occurs in the area to be monitored under the corresponding rainfall type status and terrain status λ g , and obtain the time series sequence of the overflow pollutant concentration data of the outfall where h = 1, 2, 3, 4; g = 1, 2,..., 6.
[0074] Step 4: According to the collected historical concentration data of the overflow pollutants at the outfall, classify the overflow pollutant concentration status of the outfall into k levels, denoted as s k , and obtain the overflow pollutant concentration status set S = {s 1 , s 2 ,..., s k};
[0075] The classification process of the pollutant concentration status includes the following steps:
[0076] Step S41: Obtain the historical concentration data of the r-th type of overflow pollutants at the drainage outlet, and use the data to construct a concentration data sample set, denoted as which represents the n-th data of the r-th type of overflow pollutants collected;
[0077] Step S42: Calculate the mean and standard deviation in the concentration data sample set, using the formula: Perform standardization processing on the q-th data point in the concentration data sample set. In the formula, is the standard parameter of, and σ and μ are the variance and mean of the data in the sample set respectively; q ∈ n;
[0078] Step S43: Map and adjust the standard parameter to the range [0, 1] using the Sigmoid function, and use the Sigmoid function value of the standard parameter to classify the level of the data point Specifically:
[0079] When then is the first level;
[0080] When then is the second level;
[0081] When then is the third level;
[0082] And so on,
[0083] When then is the k-th level;
[0084] where are the minimum and maximum values of the Sigmoid function value of the standard parameter respectively;
[0085] Step S44: Determine the concentration status of the overflow pollutants at the drainage outlet according to the level classification situation of. Specifically:
[0086] When is the first level, the corresponding overflow pollutant concentration status is the first level;
[0087] When is the second level, the corresponding overflow pollutant concentration status is the second level;
[0088] When is the third level, the corresponding overflow pollutant concentration status is the third level;
[0089] And so on,
[0090] When is at the k-th level, the corresponding concentration state of the overflow pollutants is at the k-th level.
[0091] Step 5: Use the obtained time series to construct a Markov chain model for the concentration state of the overflow pollutants at the outfall, and the model is defined as: where, represents the probability that when the rainfall type state is and the terrain state is λ g , the concentration of the overflow pollutants at the outfall transfers from state i to state j in one step; X t+1 represents the state of the concentration of the overflow pollutants at the outfall at time t + 1; X t represents the state of the concentration of the overflow pollutants at the outfall at time t; i, j ∈ S;
[0092] Step 6: According to the constructed Markov chain model, calculate the predicted value C' of the concentration of the r-th type of overflow pollutants at the outfall in the next sampling period at the current moment for the area to be monitored, and the specific process includes the following steps: r Specifically, the process includes the following steps:
[0093] Step S61: Determine the rainfall type state terrain state concentration state X of the r-th type of overflow pollutants at the outfall t , concentration C of the r-th type of overflow pollutants at the outfall t ;
[0094] Step S62: According to the rainfall type state and the terrain state select the time series calculate the state transition probability of the concentration of the overflow pollutants at the outfall construct the state transition probability matrix of the concentration of the overflow pollutants at the outfall In the formula, is the frequency that when the rainfall type state is and the terrain state is λ g , the concentration of the overflow pollutants at the outfall in the time series transfers from state i to state j in one step;
[0095] Step S63: According to the concentration state X t , generate a random number x 1 that follows a uniform distribution, and use the random number x 1 to determine the state X t+1 of the concentration of the overflow pollutants at the outfall at time t + 1, and the determination principle is:
[0096] If then the state X t+1 is the first level;
[0097] If then the state X t+1 is the (M + 1)-th level;
[0098] wherein, M, M + 1 ∈ S; are respectively the cumulative probabilities of the M-step and the (M + 1)-step under the transition probability matrix m ∈ S;
[0099] Step S64: According to the concentration state X t+1 , generate another random number x that follows a uniform distribution and is independent of x 1 , and use the generated random number x 2 to determine the predicted value C' of the concentration of the r-th type of overflow pollutant at the outfall in the area to be monitored at time t + 1 2 , and the calculation formula is: r In the formula, wherein, is the upper limit of the pollutant concentration interval corresponding to the concentration state X t+1 ; is the lower limit of the pollutant concentration interval corresponding to the concentration state X t+1 .
[0100] Step 7: According to the obtained predicted value C' of the outfall overflow pollutant concentration r , calculate the overflow pollution intensity in the area to be monitored, and use the calculation result of the overflow pollution intensity to evaluate the overflow pollution degree. The calculation formula of the overflow pollution intensity is:
[0101]
[0102] In the formula, RPI r represents the overflow pollution intensity of the r-th type of overflow pollutant at the outfall in the area to be monitored; C' rmax represents the maximum value within the hour of the predicted value C' of the r-th type of overflow pollutant concentration r ; represents the standard value of the r-th type of overflow pollutant concentration.
[0103] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.
Claims
1. A method for monitoring river overflow pollution, characterized in that: include: Step 1: According to the precipitation, the rainfall type in the monitored area is divided into four categories: light rain, moderate rain, heavy rain, and rainstorm. The rainfall type state of light rain is defined as The rain type of moderate rain is The rain type of heavy rain is The rain type of heavy rain is Get the rain type status collection Step 2: According to the land use type, the terrain in the monitored area is divided into six categories: road, grassland, forest, building, bare soil, and water body, and the terrain state is defined as λ1, λ2, ..., λ6 in sequence, and the terrain state set λ = {λ1, λ2, ..., λ6} is obtained; Step 3: Collect the data of the outlet in the corresponding rain type state when a precipitation event occurs in the monitored area. and terrain state λ g The overflow pollution monitoring data at the time of discharge is obtained to obtain the time series of the discharge port overflow pollutant concentration data. Among them, h=1,2,3,4; g=1,2,...,6; Step 4: Based on the collected historical concentration data of the discharge outlet overflow pollutants, the discharge outlet overflow pollutant concentration state is divided into k levels, recorded as s k , obtain the discharge outlet overflow pollutant concentration state set S = {s1, s2, ..., s k }; Step 5: Using the acquired time series A Markov chain model of the pollutant concentration state of the outfall overflow is constructed, and the model is defined as: in, It means when the rain type is And the terrain state is λ g When the discharge port overflow pollutant concentration is transferred from state i to state j in one step, X t+1 It is expressed as the state of the overflow pollutant concentration at the time t+1; X t It is represented by the state of the discharge outlet overflow pollutant concentration at time t; i, j∈S; Step 6: According to the constructed Markov chain model, calculate the predicted value C' of the rth overflow pollutant concentration at the outlet in the monitored area in the next sampling period at the current moment r .
2. A river overflow pollution monitoring method according to claim 1, characterized in that: The method further comprises: Step 7: Based on the predicted value C' of the discharge overflow pollutant concentration r , calculate the overflow pollution intensity in the monitored area, and use the calculation result of the overflow pollution intensity to evaluate the overflow pollution degree. The calculation formula of the overflow pollution intensity is: Where, RPI r It is expressed as the overflow pollution intensity of the rth type of overflow pollutants discharged from the outlet in the area to be monitored; C' rmax Expressed as the predicted value C' of the rth type of overflow pollutant concentration r The maximum value within the hour; Expressed as the standard value of the rth type overflow pollutant concentration.
3. A river overflow pollution monitoring method according to claim 1, characterized in that: The principles for rain type classification are: When the precipitation is greater than 50 mm·d -1 When the rain type is heavy rain; When the precipitation range is [25, 50) mm·d -1 When it is within the interval, the rain type is heavy rain; When the precipitation range is [10, 25) mm·d -1 When it is within the interval, the rain type is moderate rain; When the precipitation is less than 10, the rain type is light rain.
4. A river overflow pollution monitoring method according to claim 1, characterized in that: The process of classifying the pollutant concentration status of the outfall overflow includes the following steps: Obtain the historical concentration data of the rth type of overflow pollutants at the outlet and use the data Construct a concentration data sample set, denoted as It is represented as the nth data collected for the rth type of overflow pollutant; Calculate the mean and standard deviation of a sample set of concentration data using the formula: For the qth data point in the concentration data sample set After standardization, for The standard parameters of , σ, μ are the variance and mean of the data in the sample set respectively; q∈n; Adjust the standard parameter to [0,1] using the Sigmoid function mapping, and use the Sigmoid function value of the standard parameter For data points The levels are classified as follows: when hour, is the first level; when hour, is the second level; when hour, is the third level; And so on. when hour, is the kth level; in, They are the minimum and maximum values of the Sigmoid function of the standard parameters respectively; Step s25: According to The pollutant concentration state of the discharge outlet is determined according to the grade classification, which is as follows: when When it is the first level, the corresponding overflow pollutant concentration state is the first level; when When it is the second level, the corresponding overflow pollutant concentration state is the second level; when When it is the third level, the corresponding overflow pollutant concentration state is the third level; And so on. when When it is the kth level, the corresponding overflow pollutant concentration state is the kth level.
5. A river overflow pollution monitoring method according to claim 1, characterized in that: The specific process of step six includes the following steps: Step S61: Determine the rain pattern state at the outlet position at the current time t Terrain status The concentration state of the rth overflow pollutant at the outlet is X t , the discharge outlet r type overflow pollutant concentration C t ; Step S62: According to the rain type and terrain status Selecting a Timing Sequence Calculate the probability of state transition of the discharge overflow pollutant concentration Constructing the state transition probability matrix of the outfall overflow pollutant concentration In the formula, When the rain type is And the terrain state is λ g Time, timing sequence The frequency of the pollutant concentration of the overflow outlet transferring from state i to state j in one step; Step S63: According to the concentration state X t , generate a random number x1 that follows a uniform distribution, and use the random number x1 to determine the state X of the discharge outlet overflow pollutant concentration at time t+1 t+1 ; Step S64: According to the concentration state X t+1 , generate another random number x2 that obeys uniform distribution and is independent of x1, and use the generated random number x2 to determine the predicted value C' of the rth overflow pollutant concentration at the outlet in the monitored area at time t+1 r , the calculation formula is: In the formula, is the concentration state X t+1 The corresponding upper limit of the pollutant concentration range; is the concentration state X t+1 The corresponding lower limit of the pollutant concentration range.
6. A river overflow pollution monitoring method according to claim 5, characterized in that: The state of the discharge outlet overflow pollutant concentration at time t+1 is X t+1 The principles for determining are: like Then state X t+1 is the first level; like Then state X t+1 It is the M+1th level; Among them, M, M+1∈S; They are the transition probability matrices The cumulative probability of M steps and M+1 steps under m∈S.
7. A river overflow pollution monitoring system, characterized in that: The system is used to implement the steps of a river overflow pollution monitoring method according to any one of claims 1 to 6, including: The rain type state definition module is used to classify the rain type in the monitored area into four categories: light rain, moderate rain, heavy rain, and rainstorm according to the precipitation. The rain type state of light rain is defined as The rain type of moderate rain is The rain type of heavy rain is The rain type of heavy rain is Get the rain type status collection A terrain state definition module is used to classify the terrain in the monitored area into six categories according to the land use type: road, grassland, forest, building, bare soil, and water body, and define the terrain state as λ1, λ2, ..., λ6 in sequence, and obtain the terrain state set λ = {λ1, λ2, ..., λ6}; The historical data acquisition module is used to collect the data of the outlet in the corresponding rain type state when a precipitation event occurs in the monitored area. and terrain state λ g The overflow pollution monitoring data at that time is used to obtain the time series of the discharge port overflow pollutant concentration data; The pollutant concentration state definition module is used to classify the discharge port overflow pollutant concentration state into k levels according to the collected discharge port overflow pollutant historical concentration data, and obtain the discharge port overflow pollutant concentration state set S = {s1, s2, ..., s k }; A model building module is used to build a Markov chain model of the concentration state of the outfall overflow pollutants using the acquired time series; The pollutant concentration prediction module is used to calculate the predicted value C' of the rth overflow pollutant concentration at the outlet in the monitored area in the next sampling period at the current moment according to the constructed Markov chain model. r ; Overflow pollution degree assessment module, used to obtain the predicted value C' of the discharge port overflow pollutant concentration r , calculate the overflow pollution intensity in the area to be monitored, and use the calculation result of the overflow pollution intensity to evaluate the overflow pollution degree.
8. A river overflow pollution monitoring system according to claim 7, characterized in that: The system also includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor can implement the steps of a river overflow pollution monitoring method described in any one of claims 1-6 when executing the program.