Reservoir source raw water quality abnormity simulation early warning and auxiliary decision-making method and system

Abstract

The invention provides a reservoir source raw water quality abnormity simulation early warning and auxiliary decision-making method and system, and relates to the technical field of water quality monitoring, and the method specifically comprises the following steps: obtaining key water quality parameters, calculating a turbidity index according to a turbidity value, and calculating an environmental influence index and a nutrition state index; and constructing a comprehensive evaluation model according to the turbidity index, the environmental influence index and the nutrition and health index, generating a water quality abnormal risk index, comparing the water quality abnormal risk index with a risk evaluation threshold value, and making a decision suggestion according to a comparison result. Through comprehensive analysis of the turbidity index, the nutrition state index and the environmental influence index, the water quality abnormity risk is accurately evaluated, and scientific decision suggestions are provided. According to the method, the water quality monitoring efficiency is improved, and countermeasures can be taken quickly when the water quality is reduced, so that the safety of a water source is effectively guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of water quality monitoring, and in particular to a method and system for simulating and warning abnormal water quality of a reservoir source raw water and assisting in decision-making. Background Art

[0002] As an important water source, reservoirs undertake multiple functions such as water supply, irrigation and flood control. However, with the acceleration of industrialization and the increase in population, reservoir water sources are facing increasingly severe pollution challenges. Numerous factors such as the use of agricultural fertilizers, industrial wastewater discharge and urban sewage inflow have led to water quality indicators such as turbidity, ammonia nitrogen and total phosphorus exceeding the standard, which not only affects the safety of drinking water, but also poses a serious threat to the aquatic ecosystem. In addition, existing water quality monitoring technologies often focus on the detection of a single or a small number of water quality indicators, resulting in an inability to fully reflect the true condition of the water body when the water quality changes. This single monitoring method makes it impossible for regulatory authorities to capture abnormal changes in water quality in a timely and accurate manner, thus missing the best time to take intervention measures.

[0003] Traditional water quality monitoring methods also have limitations in data collection and analysis. First, conventional monitoring usually relies on regular manual sampling and laboratory analysis, which has a long cycle and slow response, making it difficult to meet the needs of real-time monitoring. Second, the lack of a systematic model for comprehensive analysis of multiple parameters often results in an inability to fully consider the interactions between various factors when assessing water quality risks. This approach not only has a negative impact on the timeliness and effectiveness of water quality management, but also increases the cost of water quality management. Furthermore, existing technologies are also insufficient in abnormal water quality early warning mechanisms. The lack of scientific threshold settings and corresponding decision-making systems has resulted in the failure of water quality monitoring results to form an effective feedback mechanism, thereby affecting the management efficiency and decision-making level of reservoirs. Therefore, there is an urgent need for an innovative technical solution to address the many shortcomings in current reservoir water quality monitoring and management to ensure the safety of water sources and the health of the ecological environment.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and system for simulating and warning abnormal water quality of reservoir source raw water and assisting decision making, so as to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The method for simulating and warning abnormal water quality of reservoir source water and assisting decision-making includes the following specific steps:

[0008] Step 1: Monitor and analyze reservoir water sources to obtain key water quality parameters, including pH, turbidity, dissolved oxygen concentration, ammonia nitrogen concentration, total phosphorus concentration, biological oxygen demand, chemical oxygen demand, conductivity, and temperature. Calculate the turbidity index based on the turbidity value.

[0009] Step 2: Calculate the environmental impact index based on the dimensionless pH, biological oxygen demand, chemical oxygen demand, conductivity, and temperature data; calculate the nutrient status index based on the dimensionless ammonia nitrogen concentration, total phosphorus concentration, and dissolved oxygen concentration data;

[0010] Step 3: Construct a comprehensive assessment model based on the turbidity index, environmental impact index, and nutritional health index of the reservoir to be assessed. Use the analytic hierarchy process to generate the weights within the comprehensive assessment model, and use the comprehensive assessment model to generate the water quality abnormality risk index of the reservoir to be assessed.

[0011] Step 4: Compare the water quality abnormality risk index with the preset risk assessment threshold. Based on the comparison results, the water quality of the reservoir to be assessed is divided into three levels. For different levels, corresponding decision recommendations are formulated.

[0012] Furthermore, a certain amount of water sample is collected, and the pH value, dissolved oxygen concentration, turbidity value, conductivity and temperature value of the water sample are collected through sensors;

[0013] The turbidity index is calculated according to the following formula:

[0014]

[0015] Among them, TI is the turbidity index, Tur is the turbidity value of the current water sample, Tur max is the maximum turbidity threshold for the water area, determined based on historical data and regulatory standards;

[0016] The specific logic for obtaining the ammonia nitrogen concentration of the reservoir is as follows:

[0017] Use a clean water sampler to collect 500 ml of water sample, filter the water sample to remove suspended matter, dilute the filtered water sample, and use an ammonia ion selective electrode for measurement: insert the ammonia ion selective electrode into the water sample and let it soak for 1-2 minutes to ensure full contact between the electrode and the water sample. Read the electrode potential and establish a calibration curve with the potential of the standard ammonia concentration;

[0018] The Nernst equation is used to establish the relationship between the standard potential and the measured potential:

[0019]

[0020] Where, E is the measured potential, E 0is the standard potential, i.e., the electrode potential under standard conditions, obtained from relevant literature and data tables; R is the gas constant, which is 8.314 J / (mol·K); T is the absolute temperature of the water sample; n is the number of electron transfers, n=1, because the ammonia molecule transfers one electron in the reaction; F is the Faraday constant; [NH3] is the concentration of ammonia in the sample to be tested, [NH3] ref is the reference ammonia concentration;

[0021] According to the Nernst equation, the ammonia concentration of the water sample is calculated using the measured potential and the standard potential:

[0022]

[0023] Calculate the ammonia nitrogen concentration of the water sample through the ammonia concentration:

[0024] [NH3-N]=[NH3]×14.007g / mol×1000mg / g

[0025] Where [NH3-N] is the ammonia nitrogen concentration in the reservoir, and [NH3] is the ammonia concentration;

[0026] The specific logic for obtaining the total phosphorus concentration of the reservoir is as follows:

[0027] Use a clean water sampler to collect 500 ml of water sample, filter the water sample to remove suspended matter, mix the filtered water sample with ammonium molybdate color developer to form a blue complex, use a spectrophotometer to measure the absorbance at a wavelength of 880 nm, and calculate the total phosphorus concentration using the following formula:

[0028]

[0029] Where [TP] is the total phosphorus concentration, A is the measured absorbance, ∈ is the molar extinction coefficient of the developer, and l is the optical path length;

[0030] The specific logic for obtaining the biological oxygen demand of the reservoir is as follows:

[0031] Use a clean water sampler to collect 500 ml of water sample, filter the water sample to remove suspended matter, dilute the filtered water sample, place the water sample in a sealed BOD bottle, measure its initial dissolved oxygen concentration, place the bottle in an incubator at 20°C, and measure its final dissolved oxygen concentration after 5 days of incubation;

[0032] The biological oxygen demand is calculated using the following formula:

[0033] BOD5=DO0-DO5

[0034] Among them, BOD5 is the biological oxygen demand of the reservoir, DO0 is the initial dissolved oxygen concentration, and DO5 is the final dissolved oxygen concentration;

[0035] The specific logic for obtaining the chemical oxygen demand of the reservoir is as follows:

[0036] A 500 ml water sample is collected using a clean water sampler. The water sample is filtered to remove suspended matter and added to a digestion flask containing potassium dichromate, sulfuric acid, and silver sulfate (as a catalyst). The reaction flask is placed in a digester and heated at 150°C for 2 hours to fully oxidize the organic matter. After digestion, the sample is cooled and the unreacted potassium dichromate is determined by titration using sodium thiosulfate as a reducing agent until the titration reaction reaches a complete reaction state, at which point the color change of the indicator indicates the end of the reaction.

[0037] The chemical oxygen demand is calculated according to the following formula:

[0038]

[0039] Where COD is the chemical oxygen demand of the reservoir, C1 is the concentration of sodium thiosulfate when the titration is completed, V1 is the volume of sodium thiosulfate consumed when the titration is completed, C2 is the initial concentration of potassium dichromate, V2 is the volume of potassium dichromate consumed, and V s is the volume of the water sample.

[0040] Furthermore, the pH value of the current reservoir to be evaluated is compared with the preset pH threshold. If it exceeds the threshold range, the difference between the current pH value of the reservoir and the preset threshold is calculated and recorded as ΔpH; if it does not exceed the threshold range, it will not be included in the subsequent calculation of the environmental impact index;

[0041] Compare the current temperature value of the reservoir to be evaluated with the preset temperature assessment threshold. If it exceeds the threshold range, calculate the difference between the current reservoir temperature and the preset threshold, which is recorded as ΔT; if it does not exceed the threshold range, it will not be included in the subsequent calculation of the environmental impact index;

[0042] The environmental impact index of the reservoir to be assessed is calculated according to the following formula:

[0043]

[0044] Among them, WQI is the environmental impact index, pH is the pH value of the reservoir, and pH ref is the pH threshold, T is the temperature of the reservoir water source, T ref is the temperature threshold, BOD5 is the biological oxygen demand of the reservoir, COD is the chemical oxygen demand of the reservoir, CON is the conductivity, ω1, ω2 and ω3 are the preset proportional coefficients, and ω1>ω2>ω3>0; a and b are denominator adjustment constants, when |pH-pH ref |or|TT refWhen | is zero, the corresponding denominator adjustment constant is 1. When |pH-pH ref |or|TT ref When | is not zero, the corresponding denominator adjustment constant is 0;

[0045] The trophic status index of the reservoir to be assessed is calculated according to the following formula:

[0046]

[0047] Among them, NSI is the nutrient status index, [NH3-N] is the ammonia nitrogen concentration of the reservoir, [TP] is the total phosphorus concentration, DIS is the dissolved oxygen concentration, μ, is the preset scaling factor, and

[0048] Furthermore, a comprehensive assessment model is constructed based on the turbidity index, environmental impact index and nutritional health index of the reservoir to be assessed. The model expression is as follows:

[0049]

[0050] Among them, QS is the water quality abnormality risk index, TI is the turbidity index, WQI is the environmental impact index, NSI is the nutrient status index, and α, β, and γ are proportional coefficients.

[0051] Furthermore, the specific logic of generating the weights in the comprehensive evaluation model through the hierarchical analysis method is as follows:

[0052] The three indicators of turbidity index, environmental impact index and nutritional health index are marked, and the relative importance between them is determined by the nine-scale method to construct a judgment matrix, in which the index of turbidity index is marked as 1, the index of environmental impact index is marked as 2, and the index of nutritional health index is marked as 3. The constructed judgment matrix is:

[0053]

[0054] Among them, f and v both represent the index of the exponential, and f∈[1,3], v∈[1,3], b fv Indicates the importance of the index f relative to the index v, and b ff =1,

[0055] Each element value in the judgment matrix is ​​divided by the sum of its columns to obtain the normalized normalized judgment matrix. The mean of the element values ​​in each row of the normalized judgment matrix is ​​calculated, and the mean of the element values ​​in the first row is used as the weight of the turbidity index, the mean of the element values ​​in the second row is used as the weight of the environmental impact index, and the mean of the element values ​​in the third row is used as the weight of the nutritional health index. With the constraint that the sum of the scaled values ​​is equal to 1, the three weights are scaled equally, and the scaled weights are used as the proportional coefficients of the corresponding indices.

[0056] Furthermore, the water quality abnormality risk index is compared with the preset risk assessment threshold:

[0057] If QS<0.5QS threshold , then the current reservoir water quality is judged to be low risk level, indicating that the water quality is good, and the existing water quality management measures should be maintained and regular inspections should be carried out;

[0058] If 0.5QS threshold ≤QS <QS threshold , the current reservoir water quality is judged to be at a medium risk level, and the monitoring frequency should be increased, the causes of water quality changes should be analyzed, emergency plans should be formulated, and water quality treatment should be carried out if necessary;

[0059] If QS ≥ QS threshold , the current reservoir water quality is judged to be at a high-risk level, and water quality improvement measures are immediately taken, water use is restricted, and a comprehensive water quality survey is conducted;

[0060] Among them, QS is the water quality abnormal risk index, QS threshold is the risk assessment threshold.

[0061] The present invention further provides a reservoir water source raw water quality abnormality simulation early warning and auxiliary decision-making system, which is used to execute the above-mentioned reservoir water source raw water quality abnormality simulation early warning and auxiliary decision-making method, including:

[0062] The data acquisition system is used to monitor and analyze reservoir water sources and obtain key water quality parameters, including pH, turbidity, dissolved oxygen concentration, ammonia nitrogen concentration, total phosphorus concentration, biological oxygen demand, chemical oxygen demand, conductivity, and temperature. The turbidity index is calculated based on the turbidity value.

[0063] The data processing module calculates the environmental impact index based on dimensionless pH, biological oxygen demand, chemical oxygen demand, conductivity, and temperature data; and calculates the nutrient status index based on dimensionless ammonia nitrogen concentration, total phosphorus concentration, and dissolved oxygen concentration data. The model construction module is used to construct a comprehensive assessment model based on the turbidity index, environmental impact index, and nutrient health index of the reservoir to be assessed, generate weights within the comprehensive assessment model through the hierarchical analysis method, and use the comprehensive assessment model to generate the water quality abnormality risk index of the reservoir to be assessed.

[0064] The comprehensive assessment module is used to compare the water quality abnormality risk index with the preset risk assessment threshold. Based on the comparison results, the water quality of the reservoir to be assessed is divided into three levels, and corresponding decision-making recommendations are formulated for different levels.

[0065] Compared with the prior art, the present invention has the following beneficial effects:

[0066] By establishing a systematic water quality monitoring and assessment model, the present invention achieves comprehensive monitoring and abnormal warning of reservoir water quality. Through comprehensive analysis of the turbidity index, nutrient status index, and environmental impact index, the risk of water quality anomalies can be more accurately assessed, and scientific decision-making recommendations can be made on this basis. This method not only improves the efficiency of water quality monitoring, but also allows for rapid response measures when water quality deteriorates, reducing the impact of water quality deterioration on the environment and humans, thereby effectively ensuring water source safety. In addition, the weight coefficients determined by the hierarchical analysis method ensure the operability and applicability of the model, making reservoir water quality management more scientific and systematic, and promoting the sustainable development of the ecological environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 Schematic diagram of the overall method flow of the present invention;

[0068] Figure 2 It is a schematic diagram of the overall system module of the present invention. DETAILED DESCRIPTION

[0069] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to specific embodiments.

[0070] It should be noted that, unless otherwise defined, the technical or scientific terms used in the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative position relationships. When the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0071] Example:

[0072] See also Figure 1 , the present invention provides a technical solution:

[0073] The method for simulating and warning abnormal water quality of reservoir source water and assisting decision-making includes the following specific steps:

[0074] Step 1: Monitor and analyze reservoir water sources to obtain key water quality parameters, including pH, turbidity, dissolved oxygen concentration, ammonia nitrogen concentration, total phosphorus concentration, biological oxygen demand, chemical oxygen demand, conductivity, and temperature. Calculate the turbidity index based on the turbidity value.

[0075] In this embodiment, a certain amount of water sample is collected, and the pH value, dissolved oxygen concentration, turbidity value, conductivity and temperature value of the water sample are collected through the sensor;

[0076] The turbidity index is calculated according to the following formula:

[0077]

[0078] Among them, TI is the turbidity index, Tur is the turbidity value of the current water sample, Tur max is the maximum turbidity threshold for the water area, determined based on historical data and regulatory standards;

[0079] The specific logic for obtaining the ammonia nitrogen concentration of the reservoir is as follows:

[0080] Use a clean water sampler to collect 500 ml of water sample, filter the water sample to remove suspended matter, dilute the filtered water sample, and use an ammonia ion selective electrode for measurement: insert the ammonia ion selective electrode into the water sample and let it soak for 1-2 minutes to ensure full contact between the electrode and the water sample. Read the electrode potential and establish a calibration curve with the potential of the standard ammonia concentration;

[0081] The Nernst equation is used to establish the relationship between the standard potential and the measured potential:

[0082]

[0083] Where, E is the measured potential, E 0 is the standard potential, i.e., the electrode potential under standard conditions, obtained from relevant literature and data tables; R is the gas constant, which is 8.314 J / (mol·K); T is the absolute temperature of the water sample; n is the number of electron transfers, n=1, because the ammonia molecule transfers one electron in the reaction; F is the Faraday constant; [NH3] is the concentration of ammonia in the sample to be tested, [NH3] ref is the reference ammonia concentration;

[0084] According to the Nernst equation, the ammonia concentration of the water sample is calculated using the measured potential and the standard potential:

[0085]

[0086] Calculate the ammonia nitrogen concentration of the water sample through the ammonia concentration:

[0087] [NH3-N]=[NH3]×14.007g / mol×1000mg / g

[0088] Where [NH3-N] is the ammonia nitrogen concentration in the reservoir, and [NH3] is the ammonia concentration;

[0089] The specific logic for obtaining the total phosphorus concentration of the reservoir is as follows:

[0090] Use a clean water sampler to collect 500 ml of water sample, filter the water sample to remove suspended matter, mix the filtered water sample with ammonium molybdate color developer to form a blue complex, use a spectrophotometer to measure the absorbance at a wavelength of 880 nm, and calculate the total phosphorus concentration using the following formula:

[0091]

[0092] Where [PT] is the total phosphorus concentration, A is the measured absorbance, ∈ is the molar extinction coefficient of the color developer, which refers to the proportional relationship between absorbance and concentration at a certain concentration. The higher the value, the stronger the color-developing ability of the substance. Its specific value is determined by the laboratory based on the color developer and reaction conditions; l is the optical path length, usually 1 cm;

[0093] The specific logic for obtaining the biological oxygen demand of the reservoir is as follows:

[0094] Use a clean water sampler to collect 500 ml of water sample, filter the water sample to remove suspended matter, dilute the filtered water sample, place the water sample in a sealed BOD bottle, measure its initial dissolved oxygen concentration, place the bottle in an incubator at 20°C, and measure its final dissolved oxygen concentration after 5 days of incubation;

[0095] The biological oxygen demand is calculated using the following formula:

[0096] BOD5=DO0-DO5

[0097] Among them, BOD5 is the biological oxygen demand of the reservoir, DO0 is the initial dissolved oxygen concentration, and DO5 is the final dissolved oxygen concentration;

[0098] The specific logic for obtaining the chemical oxygen demand of the reservoir is as follows:

[0099] A 500 ml water sample is collected using a clean water sampler. The water sample is filtered to remove suspended matter and added to a digestion flask containing potassium dichromate, sulfuric acid, and silver sulfate (as a catalyst). The reaction flask is placed in a digester and heated at 150°C for 2 hours to fully oxidize the organic matter. After digestion, the sample is cooled and the unreacted potassium dichromate is determined by titration using sodium thiosulfate as a reducing agent until the titration reaction reaches a complete reaction state, at which point the color change of the indicator indicates the end of the reaction.

[0100] The chemical oxygen demand is calculated according to the following formula:

[0101]

[0102] Where COD is the chemical oxygen demand of the reservoir, C1 is the concentration of sodium thiosulfate when the titration is completed, V1 is the volume of sodium thiosulfate consumed when the titration is completed, C2 is the initial concentration of potassium dichromate, V2 is the volume of potassium dichromate consumed, and V s is the volume of the water sample.

[0103] The advantage of Step 1 lies in its comprehensive monitoring and analysis of key water quality parameters, providing a data foundation for subsequent water quality assessments. This process not only covers multiple important indicators such as pH, turbidity, dissolved oxygen, total phosphorus, biological oxygen demand, chemical oxygen demand, conductivity, and temperature, but also provides a more comprehensive picture of water pollution through the calculation of the turbidity index. Compared to existing technologies that rely on the detection of a single or limited number of indicators, the multi-parameter monitoring in Step 1 can more accurately capture the dynamics of water quality changes, promptly identify potential water quality anomalies, and provide objective data support for water quality management.

[0104] In this patented solution, the implementation of Step 1 provides a solid foundation of data for the overall plan, facilitating the development and calculation of environmental impact models and nutrient status assessment models in subsequent steps. Systematic monitoring ensures that the subsequent comprehensive assessment model generates a more reliable water quality risk index. This multi-dimensional data integration and analysis not only enhances the scientific nature and accuracy of decision-making but also provides a clear basis for reservoir management and the formulation of remediation measures, effectively improving the efficiency of water quality monitoring and management.

[0105] Step 2: Calculate the environmental impact index based on the dimensionless pH, biological oxygen demand, chemical oxygen demand, conductivity, and temperature data; calculate the nutrient status index based on the dimensionless ammonia nitrogen concentration, total phosphorus concentration, and dissolved oxygen concentration data;

[0106] In this embodiment, the environmental impact index of the reservoir to be evaluated is calculated according to the following formula:

[0107]

[0108] Among them, WQI is the environmental impact index, pH is the pH value of the reservoir, and pH ref is the pH threshold, T is the temperature of the reservoir water source, T ref is the temperature threshold, BOD5 is the biological oxygen demand of the reservoir, CON is the chemical oxygen demand of the reservoir, CON is the conductivity, ω1, ω2 and ω3 are preset proportional coefficients, and ω1>ω2>ω3>0. This is because the pH value and temperature of the reservoir water quality have an important impact on the health and biological activity of the aquatic ecosystem. The pH value is an important parameter that determines the acidity and alkalinity of the water body, affecting the solubility of substances in the water and the survival of organisms. Temperature directly affects the solubility of oxygen in the water and the metabolic rate of organisms. Therefore, the weight ω1 of pH and temperature is set high, reflecting the significance of their impact on the environment. Conductivity is an indicator of ion concentration in water and has a relatively weak impact on water quality. Therefore, the weight ω3 is set to the lowest. Although conductivity can reflect the degree of dissolved salts in the water body, its direct impact on the water ecology is not as significant as pH, temperature, BOD5 and COD. a and b are denominator adjustment constants. When |pH-pH ref |or|TT ref When | is zero, the corresponding denominator adjustment constant is 1. When |pH-pH ref |or|TT ref When \ is not zero, the corresponding denominator adjustment constant is 0;

[0109] When | pH-pH ref When | increases, it means that the pH of the water body deviates further from the ideal state, which may threaten the survival of aquatic organisms and the environmental impact index WQI will decrease; when |TT refWhen | increases, it indicates that the water temperature deviates further from the ideal state, which will affect the survival and reproduction of aquatic organisms, and the environmental impact index WQI will decrease; BOD5 reflects the concentration of organic matter in the water and the degree of water pollution. The higher the BOD5, the more organic matter there is in the water and the worse the water quality; COD value is also an important indicator for assessing water pollution. A higher COD value indicates a high concentration of oxidizable substances in the water and worse water quality; an increase in the conductivity CON value may indicate a change in the salinity of the water or an increase in pollutants; that is, | pH-pH ref |、|TT ref |, BOD5, CON, CON and environmental impact index WQI were negatively correlated.

[0110] The trophic status index of the reservoir to be assessed is calculated according to the following formula:

[0111]

[0112] Among them, NSI is the nutrient status index, [NH3-N] is the ammonia nitrogen concentration of the reservoir, [TP] is the total phosphorus concentration, DIS is the dissolved oxygen concentration, μ, is the preset scaling factor, and This is because ammonia nitrogen and total phosphorus are important nutrients in water bodies. Nitrogen and phosphorus are the main nutrients that promote the growth of aquatic plants and algae. In eutrophic water bodies, increased concentrations of nitrogen and phosphorus lead to the rapid reproduction of plants and algae. Therefore, the influence of ammonia nitrogen and total phosphorus is given greater weight in the calculation of the trophic status index.

[0113] Increased ammonia nitrogen concentrations generally indicate eutrophication, especially during the decomposition of organic matter, where ammonia nitrogen increases as a byproduct, leading to higher nitrogen concentrations in the water. Therefore, when [NH3-N] increases, the NSI increases. Total phosphorus concentration is a key indicator for assessing eutrophication. Phosphorus is a limiting nutrient for algal growth, and increased concentrations generally promote algal reproduction. Therefore, when [TP] increases, the NSI increases. Increased dissolved oxygen concentrations generally indicate healthy water bodies capable of supporting aquatic life. Therefore, when DIS increases, the NSI decreases. This indicates that [NH3-N], [TP], and NSI are positively correlated, while DIS and NSI are negatively correlated.

[0114] The advantage of step 2 is that it uses dimensionless water quality data to establish an environmental impact model and a nutrient status assessment model, thereby obtaining an environmental impact index and a nutrient status index. This process eliminates the differences between different water quality parameters, facilitating comprehensive analysis and comparison. Compared with existing technologies, traditional methods that usually only focus on a single water quality indicator are difficult to comprehensively assess the ecological and environmental status of water bodies. However, this step, through the combination of multiple parameters, can more accurately quantify the environmental impact of the reservoir and its nutrient status, helping to fully understand the trends and causes of water quality changes, thereby improving the scientific nature of monitoring and management.

[0115] In this patented solution, the implementation of step 2 provides the necessary basic indicators for the construction of a comprehensive assessment model, making subsequent risk assessments more accurate and systematic. The resulting environmental impact index and nutrient status index provide more comprehensive data support for the calculation of the water quality anomaly risk index, further enhancing the reliability of the model. This step not only improves the overall effectiveness of the solution but also ensures multi-dimensional analysis of water quality monitoring, helping managers make decisions based on comprehensive and scientific data, thereby effectively responding to abnormal reservoir water quality.

[0116] Step 3: Construct a comprehensive assessment model based on the turbidity index, environmental impact index, and nutritional health index of the reservoir to be assessed. Use the analytic hierarchy process to generate the weights within the comprehensive assessment model, and use the comprehensive assessment model to generate the water quality abnormality risk index of the reservoir to be assessed.

[0117] In this embodiment, a comprehensive assessment model is constructed based on the turbidity index, environmental impact index, and nutritional health index of the reservoir to be assessed. The model expression is as follows:

[0118]

[0119] Among them, QS is the water quality abnormality risk index, TI is the turbidity index, WQI is the environmental impact index, NSI is the nutrient status index, and α, β, and γ are proportional coefficients.

[0120] Turbidity is an indicator of water pollution and water quality deterioration. An increase in turbidity usually means an increase in suspended matter or pollutants in the water. Therefore, when TI increases, the water quality abnormality risk index QS increases. NSI reflects the degree of eutrophication of the water body. An increase in NSI usually means an increase in the concentration of nitrogen and phosphorus in the water body, which may lead to algae reproduction and water quality deterioration. Therefore, an increase in NSI will lead to an increase in QS, indicating an increased risk of water quality abnormality. An increase in WQI generally means that the water quality has improved or maintained in a good state. This shows that TI, NSI and QS are positively correlated, and WQI and QS are negatively correlated.

[0121] The specific logic of generating weights in the comprehensive evaluation model through the analytic hierarchy process is as follows:

[0122] The three indicators of turbidity index, environmental impact index and nutritional health index are marked, and the relative importance between them is determined by the nine-scale method to construct a judgment matrix, in which the index of turbidity index is marked as 1, the index of environmental impact index is marked as 2, and the index of nutritional health index is marked as 3. The constructed judgment matrix is:

[0123]

[0124] Among them, f and v both represent the index of the exponential, and f∈[1,3], v∈[1,3], b fv Indicates the importance of the index f relative to the index v, and b ff =1,

[0125] Each element value in the judgment matrix is ​​divided by the sum of its columns to obtain the normalized normalized judgment matrix. The mean of the element values ​​in each row of the normalized judgment matrix is ​​calculated, and the mean of the element values ​​in the first row is used as the weight of the turbidity index, the mean of the element values ​​in the second row is used as the weight of the environmental impact index, and the mean of the element values ​​in the third row is used as the weight of the nutritional health index. With the constraint that the sum of the scaled values ​​is equal to 1, the three weights are scaled equally, and the scaled weights are used as the proportional coefficients of the corresponding indices.

[0126] The advantage of step 3 is that it generates an abnormal water quality risk index by constructing a comprehensive assessment model, combining the turbidity index, environmental impact index, and nutritional health index. This method comprehensively analyzes multiple key water quality indicators, reflecting the complexity and diversity of water quality changes, thereby improving the ability to identify abnormal water quality phenomena. Compared with existing technologies, traditional methods often focus on monitoring a single indicator and lack comprehensive considerations, which can easily lead to misjudgments or omissions of water quality risks. This step, however, assigns appropriate weights to each indicator through the hierarchical analysis method, ensuring that the assessment results are more comprehensive and objective, thereby more effectively reflecting the true state of water quality.

[0127] In this patented solution, the implementation of Step 3 provides critical support for the accuracy and scientific nature of the overall solution. By generating a water quality anomaly risk index, managers can more intuitively understand the health of reservoir water quality and formulate appropriate monitoring and management strategies accordingly. This comprehensive assessment model not only enhances the scientific nature of decision-making but also provides a basis for subsequent risk grading and response measures, effectively enhancing the flexibility and responsiveness of reservoir water quality management, ensuring water source safety and ecological balance.

[0128] Step 4: Compare the water quality abnormality risk index with the preset risk assessment threshold. Based on the comparison results, the water quality of the reservoir to be assessed is divided into three levels. For different levels, corresponding decision recommendations are formulated;

[0129] In this embodiment, the water quality abnormality risk index is compared with a preset risk assessment threshold:

[0130] If QS<0.5QS threshold , then the current reservoir water quality is judged to be low risk level, indicating that the water quality is good, and the existing water quality management measures should be maintained and regular inspections should be carried out;

[0131] If 0.5QS threshold ≤QS <QS threshold , the current reservoir water quality is judged to be at a medium risk level, and the monitoring frequency should be increased, the causes of water quality changes should be analyzed, emergency plans should be formulated, and water quality treatment should be carried out if necessary;

[0132] If QS ≥ QS threshold , the current reservoir water quality is judged to be at a high-risk level, and water quality improvement measures are immediately taken, water use is restricted, and a comprehensive water quality survey is conducted;

[0133] Among them, QS is the water quality abnormal risk index, QS threshold is the risk assessment threshold.

[0134] The advantage of step 4 is that it enables hierarchical management of reservoir water quality by comparing the water quality anomaly risk index with the preset risk assessment threshold. This method can clearly divide water quality conditions into three risk levels: low, medium, and high. This not only makes it easier for managers to quickly identify water quality risks, but also allows them to formulate appropriate decision-making measures based on different risk levels. Compared with existing technologies, traditional water quality monitoring often lacks systematic risk assessment, resulting in ambiguity and lag in management measures. However, this step, through a clear grading mechanism, makes water quality management more scientific and efficient, enabling the timely implementation of necessary countermeasures.

[0135] In this patented solution, the implementation of Step 4 provides a clear decision-making framework for the overall plan, enhancing the timeliness and effectiveness of water quality management. By grading the risks of abnormal water quality, managers can quickly take appropriate countermeasures based on different risk scenarios, thereby reducing the potential risk of water quality deterioration. This mechanism not only improves reservoir management efficiency but also helps ensure water source safety and ecological health, providing strong support for the sustainable use of water resources.

[0136] See also Figure 2 ,A reservoir water source raw water quality abnormality simulation early warning and auxiliary decision-making system, including:

[0137] Data acquisition system, used to monitor and analyze reservoir water sources, obtain key water quality parameters, including pH, turbidity, dissolved oxygen, total phosphorus concentration, biological oxygen demand, chemical oxygen demand, conductivity, and temperature, and calculate the turbidity index based on the turbidity value;

[0138] The data processing module calculates the environmental impact index based on dimensionless pH, biological oxygen demand, chemical oxygen demand, conductivity, and temperature data; and calculates the nutrient status index based on dimensionless ammonia nitrogen concentration, total phosphorus concentration, and dissolved oxygen concentration data. The model construction module is used to construct a comprehensive assessment model based on the turbidity index, environmental impact index, and nutrient health index of the reservoir to be assessed, generate weights within the comprehensive assessment model through the hierarchical analysis method, and use the comprehensive assessment model to generate the water quality abnormality risk index of the reservoir to be assessed.

[0139] The comprehensive assessment module is used to compare the water quality abnormality risk index with the preset risk assessment threshold. Based on the comparison results, the water quality of the reservoir to be assessed is divided into three levels, and corresponding decision-making recommendations are formulated for different levels.

[0140] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0141] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software depends on the specific application and design constraints of the technical solution.

[0142] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, and may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment as needed.

[0143] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A method for simulating and warning abnormal water quality of reservoir source raw water and assisting decision making, characterized in that: The specific steps include: Step 1: Monitor and analyze the reservoir water source to obtain key water quality parameters, including pH, turbidity value, dissolved oxygen concentration, ammonia nitrogen concentration, total phosphorus concentration, biological oxygen demand, chemical oxygen demand, conductivity and temperature, and calculate the turbidity index based on the turbidity value; Step 2: Calculate the environmental impact index based on the dimensionless pH value, biological oxygen demand, chemical oxygen demand, conductivity and temperature data; calculate the nutrient status index based on the dimensionless ammonia nitrogen concentration, total phosphorus concentration and dissolved oxygen concentration data; Step 3: Construct a comprehensive assessment model based on the turbidity index, environmental impact index and nutritional health index of the reservoir to be assessed, generate the weights in the comprehensive assessment model through the analytic hierarchy process, and use the comprehensive assessment model to generate the water quality abnormality risk index of the reservoir to be assessed; Step 4: Compare the water quality abnormality risk index with the preset risk assessment threshold. According to the comparison results, the water quality of the reservoir to be assessed is divided into three levels, and corresponding decision-making recommendations are formulated for different levels.

2. The method for simulating, warning and assisting decision-making of abnormal water quality of reservoir water source according to claim 1, characterized in that: Collect a certain amount of water samples, and use sensors to collect the pH value, dissolved oxygen concentration, turbidity value, conductivity and temperature of the water samples; The turbidity index is calculated according to the following formula: Among them, TI is the turbidity index, Tur is the turbidity value of the current water sample, and Tur max is the maximum turbidity threshold for the water area, determined based on historical data and regulatory standards; The specific logic for obtaining the ammonia nitrogen concentration of the reservoir is as follows: Use a clean water sampler to collect 500 ml of water sample, filter the water sample to remove suspended matter, dilute the filtered water sample, and use an ammonia ion selective electrode for measurement: insert the ammonia ion selective electrode into the water sample and let it soak for 1-2 minutes to make the electrode fully contact with the water sample, read the electrode potential, and establish a calibration curve with the potential of the standard ammonia concentration; The Nernst equation is used to establish the relationship between the standard potential and the measured potential: Where, E is the measured potential, E 0 is the standard potential, i.e. the electrode potential under standard conditions, obtained from relevant literature and data tables; R is the gas constant, R is 8.314 J / (mol·K), T is the absolute temperature of the water sample, n is the number of electron transfers, n=1, because the ammonia molecule transfers one electron in the reaction; F is the Faraday constant, [NH3] is the concentration of ammonia in the sample to be tested, [NH3] ref is the reference ammonia concentration; According to the Nernst equation, the ammonia concentration of the water sample is calculated by the measured potential and the standard potential: Calculate the ammonia nitrogen concentration of the water sample through the ammonia concentration: [NH3-N]=[NH3]×14.007g / mol×1000mg / g Where [NH3-N] is the ammonia nitrogen concentration in the reservoir, and [NH3] is the ammonia concentration; The specific logic for obtaining the total phosphorus concentration of the reservoir is as follows: Use a clean water sampler to collect 500 ml of water sample, filter the water sample to remove suspended matter, mix the filtered water sample with ammonium molybdate color developer to form a blue complex, use a spectrophotometer to measure the absorbance at a wavelength of 880 nm, and use the following formula to calculate the total phosphorus concentration: Where [TP] is the total phosphorus concentration, A is the measured absorbance, ∈ is the molar extinction coefficient of the developer, and l is the optical path length; The specific logic for obtaining the biological oxygen demand of the reservoir is as follows: Use a clean water sampler to collect 500 ml of water sample, filter the water sample to remove suspended matter, dilute the filtered water sample, put the water sample into a sealed BOD bottle, measure its initial dissolved oxygen concentration, place the bottle in an incubator at 20°C, and measure its final dissolved oxygen concentration after 5 days of incubation; The biological oxygen demand is calculated using the following formula: BOD5=DO0-DO5 Among them, BOD5 is the biological oxygen demand of the reservoir, DO0 is the initial dissolved oxygen concentration, and DO5 is the final dissolved oxygen concentration; The specific logic for obtaining the chemical oxygen demand of the reservoir is as follows: Use a clean water sampler to collect 500 ml of water sample, filter the water sample to remove suspended matter, add it to a digestion bottle containing potassium dichromate, sulfuric acid and silver sulfate (as a catalyst), place the reaction bottle in the digester, and heat it at 150°C for 2 hours to fully oxidize the organic matter; after digestion, cool it down, and determine the unreacted potassium dichromate by titration, using sodium thiosulfate as a reducing agent to titrate until the titration reaction reaches a state of complete reaction, at which time the color change of the indicator indicates the end of the reaction; The chemical oxygen demand is calculated according to the following formula: Where COD is the chemical oxygen demand of the reservoir, C1 is the concentration of sodium thiosulfate when the titration is completed, V1 is the volume of sodium thiosulfate consumed when the titration is completed, C2 is the initial concentration of potassium dichromate, V2 is the volume of potassium dichromate consumed, and V s is the volume of the water sample.

3. The method for simulating, warning and assisting decision-making of abnormal water quality of reservoir water source raw water according to claim 1, characterized in that: The environmental impact index of the reservoir to be assessed is calculated according to the following formula: Among them, WQI is the environmental impact index, pH is the pH value of the reservoir, and pH ref is the pH threshold, T is the temperature of the reservoir water source, T ref is the temperature threshold, BOD5 is the biological oxygen demand of the reservoir, COD is the chemical oxygen demand of the reservoir, CON is the conductivity, ω1, ω2 and ω3 are the preset proportional coefficients, and ω1>ω2>ω3>0; a and b are the denominator adjustment constants, when |pH-pH ref |or|TT ref When | is zero, the corresponding denominator adjustment constant is 1. ref |or|TT ref |When it is not zero, the corresponding denominator adjustment constant is 0; The trophic status index of the reservoir to be evaluated is calculated according to the following formula: Among them, NSI is the nutrient status index, [NH3-N] is the ammonia nitrogen concentration of the reservoir, [TP] is the total phosphorus concentration, DIS is the dissolved oxygen concentration, μ, is the preset scaling factor, and 4. The method for simulating early warning and assisting decision-making of abnormal water quality of reservoir water source according to claim 1, characterized in that: A comprehensive assessment model is constructed based on the turbidity index, environmental impact index and nutritional health index of the reservoir to be assessed. The model expression is as follows: Among them, QS is the water quality abnormality risk index, TI is the turbidity index, WQI is the environmental impact index, NSI is the nutrient status index, and α, β, and γ are proportional coefficients.

5. The method for simulating early warning and assisting decision-making of abnormal water quality of reservoir water source according to claim 1, characterized in that: The specific logic of generating weights in the comprehensive evaluation model through the hierarchical analysis method is: The three indicators of turbidity index, environmental impact index and nutritional health index are marked, and the relative importance between them is determined by the nine-scale method to construct a judgment matrix, in which the index of turbidity index is marked as 1, the index of environmental impact index is marked as 2, and the index of nutritional health index is marked as 3. The constructed judgment matrix is: Where f and v both represent indexes of the exponent, and f∈[1,3], v∈[1,3], b fv represents the importance of the index f relative to the index v, and b ff =1, Each element value in the judgment matrix is ​​divided by the sum of its columns to obtain a normalized judgment matrix. The mean of the element values ​​in each row of the normalized judgment matrix is ​​calculated, and the mean of the element values ​​in the first row is used as the weight of the turbidity index, the mean of the element values ​​in the second row is used as the weight of the environmental impact index, and the mean of the element values ​​in the third row is used as the weight of the nutritional health index. With the constraint that the sum of the scaled values ​​is equal to 1, the three weights are scaled in equal proportions, and the scaled weights are used as the proportional coefficients of the corresponding indexes.

6. The method for simulating, warning and assisting decision-making of abnormal water quality of reservoir water source according to claim 1, characterized in that: Compare the water quality abnormality risk index with the preset risk assessment threshold: If QS<0.5QS threshold , then the current reservoir water quality is judged to be at a low risk level, indicating that the water quality is good, and the existing water quality management measures should be maintained and regular inspections should be carried out; If 0.5QS threshold ≤QS <QS threshold , the current reservoir water quality is judged to be at a medium risk level, the monitoring frequency is increased, the causes of water quality changes are analyzed, emergency plans are formulated, and water quality treatment is carried out when necessary; If QS ≥ QS threshold , the current reservoir water quality is judged to be at a high risk level, and water quality improvement measures are immediately taken, water use is restricted, and a comprehensive water quality survey is conducted; Among them, QS is the water quality abnormal risk index, QS threshold is the risk assessment threshold.

7. The abnormal water quality simulation warning and auxiliary decision-making system of reservoir water source raw water is characterized by: The reservoir water source raw water quality abnormal simulation early warning and auxiliary decision-making system is used to execute the reservoir water source raw water quality abnormal simulation early warning and auxiliary decision-making method according to any one of claims 1 to 6, comprising: The data acquisition system is used to monitor and analyze the reservoir water source and obtain key water quality parameters, including pH, turbidity value, dissolved oxygen concentration, ammonia nitrogen concentration, total phosphorus concentration, biological oxygen demand, chemical oxygen demand, conductivity and temperature, and calculate the turbidity index based on the turbidity value; The data processing module calculates the environmental impact index based on the dimensionless pH value, biological oxygen demand, chemical oxygen demand, conductivity and temperature data; the nutrient status index is calculated based on the dimensionless ammonia nitrogen concentration, total phosphorus concentration and dissolved oxygen concentration data; the model building module is used to build a comprehensive evaluation model based on the turbidity index, environmental impact index and nutritional health index of the reservoir to be evaluated, generate the weights in the comprehensive evaluation model through the hierarchical analysis method, and use the comprehensive evaluation model to generate the water quality abnormality risk index of the reservoir to be evaluated; The comprehensive assessment module is used to compare the water quality abnormality risk index with the preset risk assessment threshold. According to the comparison results, the water quality of the reservoir to be assessed is divided into three levels, and corresponding decision-making recommendations are formulated for different levels.

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