99 results about "Surface water quality" patented technology

The invention discloses a drainage pipe network water quality monitoring, early warning and traceability system and method, and the system comprises the steps: arranging pipe network water quality monitoring stations, building pipe network water quality early warning monitoring stations, carrying out water quality early warning, building a traceability business platform, and building a water quality early warning traceability model. Constructing a water quality pollution traceability mechanism flow; the pipe network early-warning traceability supervision mechanism can quickly study and judge the water quality of the inlet of the pipe network, can track pollution sources of secret discharge, leakage discharge and excessive discharge, provides early warning for inlet water of a sewage treatment plant, reserves emergency disposal time, realizes early-warning traceability of the sewage pipe network, quickly and efficiently searches for the pollution sources, improves supervision efficiency, and ensures that the water quality of the inlet of the sewage treatment plant is ensured. Stable operation of a sewage treatment plant is guaranteed, and impact is effectively reduced; the development of the project provided by the invention plays a demonstration role in an environmental protection system, plays a leading role in improving the water quality of a sewage pipe network and surface water, and provides a scientific basis for water environment management.

The invention discloses a water quality change trend online identification and early warning method, system and device and a storage medium. The method comprises the following steps: acquiring historical water quality data and identifying periodic and seasonal fluctuations of the historical water quality data; constructing an off-line model group, performing trend identification, and outputting a trend identification result; performing normalization processing analysis on the trend identification result to obtain a trend analysis result, comparing the trend analysis result with a trend reference result, and optimizing the surface water quality trend identification offline model group; acquiring real-time water quality data and identifying periodic and seasonal fluctuations of the real-time water quality data; carrying out qualitative analysis on the water quality change trend; performing quantitative analysis on the water quality change trend by using the optimized offline model group to obtain a trend change index of each model; according to each model trend change index, calculating to obtain a comprehensive water quality change index; and quantifying the water quality change trend grade and generating corresponding early warning information. The real-time performance, the accuracy and the stability of water quality trend identification can be remarkably improved.

The invention relates to the field of water quality monitoring, and discloses a water quality on-line monitoring system based on full spectrum analysis, which comprises a full spectrum water quality analysis reference module, an equipment consistency correction module, a full spectrum water quality analysis derivative module and a quality monitoring module, wherein the reference module collects full-spectrum data through reference equipment to construct a water quality analysis reference model; the correction module uses the ResNet-C neural network to correct the spectral data difference of different devices; the derivative module combines the correction data and the reference model to realize water quality index prediction; the quality monitoring module calculates a quality evaluation coefficient through a multi-dimensional index and triggers early warning; the method is based on the Lambert-Beer theorem and the neural network architecture, solves the problems of high reagent consumption and poor equipment consistency in the traditional monitoring technology, and is suitable for real-time online monitoring of the surface water quality.

The invention discloses a water quality prediction method based on multi-source data, and constructs a water quality prediction model based on a long short-term memory network (LSTM) and a graph neural network (GNN) of multi-source data (surface water monitoring data, meteorological data, hydrological data and pollution source on-line monitoring data), so that short-term real-time on-line prediction of surface water quality factors can be realized. According to the method, on the basis of multi-source data such as section water quality monitoring data, historical meteorological data, forecast meteorological data, hydrological monitoring data, pollution source online monitoring data and upstream and downstream relations, multiple main water quality influence factors such as water quality, meteorology, hydrology, pollution sources and upstream and downstream section water quality are comprehensively considered; the LSTM or the graph neural network is adopted to establish a water quality prediction model, and the comprehensive influence of various influence factors and the time-space relationship on the water quality is simulated, so that the simulation result is more accurate and reliable.

The invention discloses a surface water quality parameter detection method, device and equipment, a medium and a product, and relates to the technical field of water quality monitoring. The method comprises the following steps: constructing sample data of each selected water quality parameter index according to ultraviolet-visible absorption spectrum data and water quality detection data of different surface water samples, sequentially determining a plurality of corresponding optimal water quality parameter estimation models and an optimal model fusion method on the basis of the corresponding sample data for each index, and calculating the optimal water quality parameter estimation model according to the optimal water quality parameter estimation model and the optimal model fusion method. Finally, the ultraviolet-visible absorption spectrum data, collected in real time, of the field surface water are imported into the optimal water quality parameter estimation models of all the indexes in real time, and the final index values of all the indexes of the field surface water are obtained by applying the optimal model fusion method of all the indexes. Therefore, the purpose of quickly, accurately and real-timely monitoring multiple parameters of the surface water quality can be achieved, and the method has the advantages of no reagent, no secondary pollution, real-time performance, high efficiency, multi-parameter monitoring capability and high robustness.

The utility model provides a modular artificial wetland water purification system, which comprises an adsorption sedimentation tank, a water distribution channel, a plurality of modular wetland units and a water collection channel in sequence along the flow direction of sewage; the modular artificial wetland water purification system of the invention solves the problems that the amount of urban tail water is large and the water quality is difficult to meet the surface water environmental quality standards, the wetland ecosystem is degraded and the water purification capacity is low, the ecological landscape pattern is fragmented, and the water ecosystem is fragile in the northern region under low temperature.

The invention provides a water quality sensor self-diagnosis method for surface water monitoring, which comprises the steps of water quality sensor setting, training data acquisition, training data analysis and real-time monitoring implementation, and is characterized in that based on a kernel principal component analysis method, water quality data acquired historically and monitored in real time is projected to a kernel principal component space for analysis; the comprehensive characteristics and the overall relation of water quality data are captured, whether the real-time monitoring abnormity is from the sensor or the water quality abnormity is effectively distinguished, self-diagnosis of the water quality sensor in the long-term application process is achieved, and therefore the water quality monitoring accuracy and the operation and maintenance efficiency of a surface water monitoring network are remarkably improved; and thus, the implementation level of surface water quality monitoring is comprehensively improved.

The invention discloses a migratable surface water quality prediction method based on representation learning, and the method comprises the steps: 1, obtaining historical monitoring data, so as to construct a data set in a multi-site sequence format, carrying out the mask processing of the historical monitoring data in the data set, so as to obtain mask data, forming a training test set by the historical monitoring data and the mask data; 2, selecting a Transform model framework with the same total number of source domains to construct a prediction network; step 3, training the prediction network to obtain a prediction model; and step 4, inputting the water quality data collected in the station and the meteorological data of the current day into the prediction model to obtain the water quality data of the source domain where the station is located. The invention further provides a device for predicting the water quality of the transferable surface water. According to the method provided by the invention, the key water quality index of the source domain river monitoring section is predicted through the change of the water quality information of each station in the source domain, and more accurate and comprehensive reference is provided for subsequent water quality management.

The utility model relates to a surface water sampling device, which is applied to the technical field of surface water quality monitoring, and comprises a sampling water inlet pipe, a sampling water outlet pipe, a sampling water outlet pipe, a vacuum water pump, a sampling water outlet pipe and a sampling water outlet pipe, and is characterized in that one end of the sampling water inlet pipe is provided with a sampling water inlet; a fixing part is arranged between the sampling water inlet pipe and the vertical line fixing arm, and the sampling water inlet pipe can be adjusted in position in the length direction of the vertical line fixing arm while the sampling water inlet pipe is fixed on the vertical line fixing arm by the fixing part; a connecting part is arranged between the vertical line fixing arm and the water surface floating device, and the vertical line fixing arm is fixed on the water surface floating device through the connecting part. According to the surface water sampling device, the depth of the sampling water inlet in water can be accurately controlled, that is, the position of a vertical line sampling point of the surface water can be accurately controlled, so that the surface water at the sampling point with the specified depth can be accurately sampled.

The utility model discloses a surface water quality monitoring device which comprises a box body, the front side of the box body is connected with a box door through a hinge, and the front side of the box door is provided with a hidden handle. When the surface water quality monitoring device is used, a container containing surface water is placed in a placing groove, and a first threaded rod can be driven to rotate by rotating a hand wheel; when a first servo motor is started to drive a second threaded rod to rotate, a detection head extends into the container for monitoring, a second servo motor drives a sleeve to rotate, the sleeve can rotate to drive a plurality of stirring blades to rotate, and thus surface water in the container can be stirred. The mounting plate is attached to the top of the container, water is prevented from overflowing when surface water is stirred, clockwise and anticlockwise rotation of the surface water can be achieved through work of the second servo motor, and then the defect that when the surface water is still in the container for monitoring, particulate matter precipitation causes inaccurate measurement data is overcome.

The embodiment of the invention discloses a water resource quality detection method and device applied to a water diversion project and electronic equipment. A specific implementation mode of the method comprises the following steps: performing water quality detection on a water area where a water diversion project is located to obtain an earth surface water quality data set and an underground water quality data set; constructing an earth surface data structure network according to a pre-constructed water area simulation model and an earth surface water quality data set; constructing an underground data structure network; performing water pollution detection on the water area to generate an earth surface water quality detection result set and an underground water quality detection result set; performing correlation analysis on the surface water resources and the underground water resources of the water area to generate water pollution correlation characteristics; determining a surface water pollution area and an underground water pollution area of the water area; and determining the surface water quality detection result set, the underground water quality detection result set, the surface water pollution area, the underground water pollution area and the water pollution correlation characteristics as water resource quality detection results. According to the embodiment, the accuracy of the water area overall quality detection result can be improved.

The invention relates to the technical field of surface water quality evaluation, in particular to a water quality sampling and evaluating method and device, electronic equipment and a storage medium. Secondly, for each section, constructing a detection data matrix by using a plurality of corresponding detection data vectors according to a time node sequence, and performing dimension transformation on the detection data matrix to obtain section vectors; finding a plurality of similar vectors from the plurality of water quality classes according to each section vector, and constructing the plurality of similar vectors into a reference vector group; and finally, determining the water quality grade of each section according to the reference vector group, and determining the water quality grade of the water body according to the water quality grades of the plurality of sections. According to the method, detection data of a plurality of detection items, a plurality of time nodes and a plurality of sections of the water body are integrated, the water quality of the water body is reflected objectively, few samples are needed, the construction process is simple, and the output result is more accurate and reliable.

The invention relates to the field of surface water quality safety evaluation, in particular to a CRITIC method-based physical and chemical index water environment quality evaluation method, which comprises the following steps of: determining a quality evaluation index based on a water body type; according to the selected quality evaluation index, calculating the condition of the quality evaluation index and then assigning a score; an original index data matrix is constructed to store assigned scores of the quality evaluation indexes, and nondimensionalization is carried out on data values in the original index data matrix; calculating the standard deviation of data values in the original index data matrix, and calculating the conflict of the evaluation indexes; calculating the information amount of the quality evaluation index, and calculating the weight of the quality evaluation index; and calculating a comprehensive index, and rating the water environment quality according to the comprehensive index. The method has the effects of improving the accuracy of a calculation result and improving the accuracy of a water environment quality evaluation result in the water environment quality evaluation process.

The invention discloses an offshore water quality multi-parameter monthly dynamic monitoring method based on a remote sensing image and a random forest algorithm, which is used in the field of offshore water quality remote sensing monitoring research, and comprises the following steps: obtaining hydrometric station data and remote sensing image data of a monitoring area, and sequentially carrying out preprocessing and space-time fusion matching operation, obtaining a month-by-month water quality data set; constructing a monthly water quality monitoring model based on a random forest algorithm; training a monthly water quality monitoring model by using the monthly water quality data set to obtain a monthly water quality monitoring inversion model; and performing inversion on the remote sensing satellite image of each month by using the monthly water quality monitoring inversion model to obtain a water quality inversion spatial distribution diagram of each month. According to the method, long-time sequence, revisit, large-range and efficient dynamic monitoring can be realized, the prediction precision is high, the generalization ability is strong, and a business unit can be served to carry out related businesses such as monthly surface water quality drawing, monitoring and evaluation.

The utility model discloses a surface water quality monitoring device which comprises a base, the base comprises an L-shaped equipment platform, one end of the L-shaped equipment platform is fixedly connected with the inner wall of a weight box, the other end of the L-shaped equipment platform extends out of the weight box, a pulling mechanism is arranged at the top of the L-shaped equipment platform, and the other end of the L-shaped equipment platform is fixedly connected with a connecting seat. The other end of the rotating arm is connected with a hoisting mechanism, a floating mark is arranged at the bottom of the hoisting mechanism, and a detection mechanism is arranged on the side, away from the hoisting mechanism, of the floating mark. The utility model solves the problem in the prior art that the water quality monitoring and data acquisition are influenced because an engine or a paddle stirs and mixes substances at each level in water in the ship taking sampling and monitoring process.

The invention belongs to the technical field of surface water quality monitoring. The invention provides a surface water quality multi-parameter online monitor. The surface water quality multi-parameter online monitor comprises a vertical motor, a vertical sliding table, a horizontal motor, a horizontal sliding table, a multi-parameter probe, a probe bracket, a measuring pool, a cleaning pipe interface, a checking pool and a checking bin, the checking pool and the measuring pool are arranged side by side; checking bins in one-to-one correspondence with the multi-parameter probes are arranged in the checking pool; the checking bin comprises a pH value probe checking bin, a dissolved oxygen probe checking bin, a conductivity probe checking bin and a turbidity probe checking bin; the side part of the checking bin is provided with a sample inlet and the bottom is provided with a drain valve; a stirring device is arranged at the bottom of the turbidity probe checking bin. According to the scheme, silt or algae in complex surface water with high turbidity, high nutrition and the like can be prevented from being attached to the pond body to influence the accuracy of calibration and checking data.

The invention relates to the technical field of water quality detection, in particular to a rapid surface water quality detection device and method.The rapid surface water quality detection device comprises a shell, a water storage container, a detection container, a water pumping pipe, a first water pumping part, a three-way adjusting valve and a second water pumping part, the three-way adjusting valve is inserted into the shell, one end of the three-way adjusting valve penetrates through the water storage container, and the other end of the three-way adjusting valve penetrates through the detection container; and the other two ends are respectively communicated with the two ends of the water pumping pipe, which are positioned on the outer side of the water storage container, and are opposite in opening degree. In the use process, the three-way regulating valve is determined to be in a closed / opened state according to whether the temperature of the surface water is within the measurement range of the water quality detection sensor and whether the surface water needs to be diluted; according to the temperature difference between the surface water and the pure water in the water storage container, the opening degree of the communicating position of the three-way regulating valve and the water pumping pipe located at the water outlet end of the outer side of the water storage container is determined, so that the treatment mode can be reasonably selected according to the condition of the surface water, the operation is simple, and the detection efficiency is high.

The invention discloses a surface water resource quality dynamic prediction and early warning method. The method comprises the following steps: step 1, water quality prediction and early warning index selection; 2, classifying water quality prediction and early warning indexes; 3, dynamically predicting A-class water quality prediction and early warning indexes; 4, dynamically predicting B-type water quality prediction and early warning indexes; and 5, determining a water quality comprehensive early warning grade. According to the invention, by integrating multi-dimensional information, key water quality indexes for prediction and early warning aiming at different evaluation sections are screened out, differentiated early warning thresholds and grades aiming at different types of water quality prediction and early warning indexes are set, a modeling scheme of classified implementation is put forward, a model parameter dynamic optimization mechanism of rolling correction is established, and the accuracy of early warning is improved. A comprehensive water quality dynamic prediction and early warning method system is formed, and the core problems of poor pertinence, poor timeliness and insufficient adaptability in current surface water quality prediction and early warning are solved. And an important supporting effect is achieved on reasonable utilization and optimal configuration of water resources.

The application discloses a surface water quality prediction method based on a self-attention mechanism coupled KAN network, and steps include: S1, integrating multi-source heterogeneous water environment data of a target basin, pre-processing and multi-granularity feature engineering are performed, and a three-dimensional space-time feature tensor is constructed; S2, a composite base function library is constructed, and an optimized base function set is obtained through double sparse screening; S3, the feature tensor is divided according to three feature channels, a space-time attention network is constructed, and a global attention weight matrix is calculated; S4, the base function set and the weight matrix are fused, a KAN network is constructed and is sparsified, and an Att-KAN coupled model is formed; S5, a multi-objective loss function is established, and the coupled model is optimized and trained in stages; S6, water quality space-time prediction is completed by inputting pre-processed target data, and attribution analysis and uncertainty evaluation are carried out. The application adopts the above method, fuses the advantages of the self-attention network and the KAN network, and realizes the unity of water quality prediction precision and model transparency.

The invention relates to the technical field of surface water supervision, in particular to a water quality monitoring management platform which comprises a monitoring network and a management module. The monitoring network comprises shooting equipment deployed at each water recession path node, and planktons sensitive to pollutant response are arranged on the water recession path nodes; the monitoring network is used for acquiring plankton characteristic data on the corresponding water recession path nodes through the shooting devices; and the management module is used for outputting a pollution diffusion path probability graph according to the plankton characteristic data, generating a water quality management scheme according to the pollution diffusion path probability graph, and realizing real-time monitoring and accurate management of the surface water quality.

The invention provides a water quality fuzzy comprehensive evaluation method and system based on the game theory and empowerment, and relates to the technical field of water quality comprehensive evaluation, and the method comprises the steps: obtaining a plurality of water quality indexes of a to-be-evaluated water sample; performing correlation analysis on each water quality index; according to a correlation analysis result, under the condition that highly-collinear water quality indexes exist, principal component analysis is carried out on all the water quality indexes, and a water quality evaluation index set is determined; dividing water quality grades according to a surface water quality evaluation standard; calculating a membership degree matrix of each evaluation index; determining a subjective weight value of each evaluation index in combination with a single pollution index algorithm and an analytic hierarchy process algorithm; determining an objective weight value of each evaluation index through an entropy weight algorithm; calculating a fusion weight matrix of each evaluation index relative to different water quality levels in the water quality evaluation index set by taking Nash equilibrium as a target based on a game theory; and generating the water quality grade of the to-be-evaluated water sample in combination with the membership matrix and the fusion weight matrix.

This application discloses a water quality assessment method and apparatus based on the quantitative grading of non-quantitative environmental pollution indicators. The method includes: screening surface water quality indicators and classifying them into direct and indirect water quality indicators; determining the assessment section and assessment period, and obtaining raw water quality concentration data for different times and sections within the assessment period; screening a predetermined number of direct water quality indicators related to indirect water quality indicators; performing PLSR regression and calculating the regression quantitative grading standard for each indirect water quality indicator; standardizing the raw detection data, the national grading standard for direct water quality indicators, and the regression quantitative grading standard for indirect water quality indicators into dimensionless values; performing PCA analysis according to the assessment period and assessment section to determine the achieved water quality environmental functional zone category; and obtaining typical water quality indicators for the section based on the PCA analysis. This method and apparatus can comprehensively consider the relationship between quantitative and non-quantitative environmental pollution indicators and the contribution of indirect indicators, making the assessment results more comprehensive and objective.

The invention discloses a self-lifting surface water sampling system and method, which are used for solving the problems of inaccurate sampling depth control and easy interference in the environments of large surge peak valley change and fast water flow rate in the existing sampling technology. Comprising the steps that the water depth is monitored in real time through a liquid level sensor on a sampling probe, and a controller dynamically controls an electric winch to collect and release a sampling cable according to the deviation between an actually measured sampling probe depth value and a preset sampling depth value, so that the probe is stabilized at the preset water depth; after the sampling depth is stable, water sample collection and water quality monitoring are performed. The system comprises a self-lifting control module, a sampling probe module, a composite cable type composite sampling pipe and a power supply communication module, wherein the self-lifting control module comprises an electric capstan, a liquid level sensor and a controller, and the sampling probe module is integrated with a surface water quality conventional five-parameter sensor module including PH, water temperature, turbidity, conductivity and dissolved oxygen. Through closed-loop feedback control, surge fluctuation and impact of high water flow speed are actively resisted, and high-precision fixed-depth sampling is ensured to be realized under complex hydrological conditions.

The invention discloses a surface reflectance and temperature fused water quality inversion method in the technical field of water environment remote sensing. The method comprises the following steps: acquiring a remote sensing image of a monitoring station within a space-time range of measured data of surface water; performing preprocessing such as atmospheric correction on the remote sensing image, extracting index data such as reflectivity and surface temperature, and establishing a basic data set of water quality remote sensing inversion; data cleaning and space-time matching are carried out on actually measured and remote sensing data, and correlation verification is carried out on remote sensing surface temperature data and actually measured water temperature data of a monitoring station; constructing a surface water environment quality inversion model and verifying the surface water environment quality inversion model based on data such as actually measured water quality indexes, reflectivity and temperature; simulating surface water quality parameters by adopting the constructed remote sensing inversion model, and visualizing a simulation result; according to the invention, by fully excavating the surface temperature information of the remote sensing satellite, higher surface water quality inversion precision is realized, and the uncertainty of water environment remote sensing is effectively reduced.

The utility model belongs to the field of water quality monitoring, and particularly relates to a surface water quality monitoring device which comprises a device main body, a filtering and sampling component and a hose, the top end of the filtering and sampling component is in threaded connection with an end cover, the bottom end of the hose is sleeved with a fixing sleeve, a clamping mechanism is arranged in the end cover and comprises a long groove, the long groove is formed in the bottom end of the fixing sleeve, a rotating rod is rotationally connected to the long groove, the top end of the rotating rod abuts against a sliding groove, and the top end of the rotating rod is in threaded connection with the sliding groove. The sliding groove is formed in the bottom end of the end cover, a fixing ring is fixedly connected to the fixing sleeve, the bottom end of the fixing ring makes contact with a supporting ring, two first springs are fixedly connected to the bottom end of the supporting ring, the bottom ends of the first springs are fixedly connected to clamping blocks, and the clamping blocks are rotationally connected to the interiors of the clamping grooves. And through the structural design of the clamping mechanism, the function of conveniently taking down the hose from the filtering and sampling component is realized.

This invention relates to an intelligent continuous flow system and method for deep nitrogen and phosphorus removal from wastewater treatment plant effluent with low-activity sludge concentration. Belonging to the technical field of wastewater treatment system purification, the system is designed based on the denitrification phosphorus removal principle. It consists of a nitrification tank, three anaerobic tanks, three anoxic tanks, one aerobic tank, and a sedimentation tank. By measuring the nitrate nitrogen concentration in the effluent and precisely adding an organic carbon source, the system controls the endpoints of nitrification and denitrification reactions online. Due to its short hydraulic retention time, the system can operate at high speed and efficiency, produces no byproducts, and avoids secondary pollution. The purified water meets or exceeds Class III standards of my country's surface water quality standards. This invention provides a better technical solution for addressing the secondary eutrophication pollution caused by surface discharge of effluent from existing wastewater treatment plants and the challenges of upgrading existing wastewater treatment plants. It also has significant implications for the restoration of water quality in water source protection areas and eutrophic water bodies.

The invention relates to the technical field of environmental engineering, and particularly discloses a surface water quality improvement effect evaluation method after comprehensive treatment of a water environment, and the method comprises the steps: S1, obtaining the basic condition of a project associated with surface water, and determining an evaluation object in combination with project partitioning; s2, determining the effect of a newly built or repaired pollutant treatment system on reducing the amount of surface water pollutants by analyzing the content and implementation condition of the evaluation object; s3, analyzing and comparing the environment quality condition of the coverage area where the newly built or repaired pollutant treatment system is located to determine the environment change caused by pollutant treatment; according to the method, the implementation effect of the treatment project is determined by analyzing the pollutant reduction amount and environmental change cleaning, the surface water quality improvement condition is determined through the model, the primary and secondary pollutants in the water body are reasonably determined, and the two are combined to analyze and determine the treatment measures to improve the surface water quality. And the reasonable effect objective evaluation work can be better carried out on the comprehensive treatment of the water resource.

A surface water quality monitoring method based on a high spatial resolution satellite includes: step 1. building standard surface water quality pools by mixing natural water bodies with clean water in different proportions to obtain surface water quality data; step 2. obtaining high spatial resolution remote sensing images for processing; step 3. identifying remote sensing bands with higher correlation through correlation analysis by presetting ratio values of remote sensor data bands and the standard surface water quality pools; step 4. building a water quality parameter retrieval model, and comparing and retrieving the remote sensing bands with higher correlation and the surface water quality data to obtain water quality data; and step 5. identifying abnormal points of the water quality based on the water quality data and water quality data threshold of the surface water.

The invention provides a water quality index annual standard reaching early warning method based on a target margin and a trend line. The method comprises the following steps: firstly, collecting historical month-by-month water quality monitoring data of a section, calculating upper and lower limit extreme value lines of the same month, and drawing a multi-year monthly mean value trend line after removing outliers; calculating a target margin according to a water quality target, predicting a month-by-month index concentration early warning value after the ith month by using a trend line, and introducing parameters to calculate a comprehensive pressure index of the section. And finally, risk early warning is carried out through standard reaching condition three-level research and judgment. The method overcomes the defects that a traditional method does not consider seasonal fluctuation of water quality, lacks a dynamic correction mechanism and depends on experience judgment, comprehensively evaluates the risk that the water quality reaches the standard from multiple dimensions, enables early warning to be more scientific and accurate, can effectively assist surface water quality management decision, and improves reliability and effectiveness of water quality early warning.