A method, device and system for predicting nitrogen and phosphorus load trends in water areas

Abstract

The present invention relates to the technical field of water environment monitoring, and in particular to a method, device and system for predicting nitrogen and phosphorus load trends in water areas, comprising: obtaining at least one sewage discharge point in a preset area and obtaining multiple sampling points; determining a target sewage discharge point corresponding to a target sampling point among multiple sampling points; determining a first reference data set according to the target sewage discharge point and the target sampling point; calculating the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point in the first reference data set; performing data processing according to the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point to obtain a predicted reference weight and a target weight corresponding to any reference sampling point; obtaining a weighted nitrogen and phosphorus load mean value and a target actual nitrogen and phosphorus content value according to the predicted reference weight and the target weight corresponding to any reference sampling point; performing trend judgment according to the weighted nitrogen and phosphorus load mean value and the target actual nitrogen and phosphorus content value to obtain a nitrogen and phosphorus load trend.

Description

Technical Field

[0001] The present invention relates to the technical field of water environment monitoring, and in particular to a method, equipment and system for predicting nitrogen and phosphorus load trends in water areas. Background Art

[0002] The nitrogen and phosphorus load of water bodies refers to the total amount of dissolved and suspended nitrogen and phosphorus in water bodies, usually expressed as mass per unit area or per unit time. Nitrogen and phosphorus are key nutrients in water bodies, but excessive nitrogen and phosphorus input may lead to eutrophication of water bodies and cause environmental problems such as blue algae blooms.

[0003] Monitoring of nitrogen and phosphorus in water bodies usually relies on sensors to conduct real-time detection of nitrogen and phosphorus content in the water body, and then determine the probability of eutrophication in the water body and make corresponding compensatory measures; but relying solely on real-time detection of nitrogen and phosphorus content data cannot provide early warning. When the measured data has reached the warning threshold, problems such as blue-green algae blooms are already very serious. Therefore, it is necessary to predict the changes in nitrogen and phosphorus content data, and then provide early warning to reduce losses.

[0004] In the prior art, in the process of predicting the nitrogen and phosphorus content data, since the nitrogen and phosphorus load values ​​themselves have a large range of variation and since multiple sampling points are set up at different locations in the reservoir, when only the future change data is estimated based on the statistical nitrogen and phosphorus content at the discharge point without considering the degradation capacity of the water body itself, it is easy to cause the final prediction result to be distorted; at the same time, the degradation capacity of different sampling points is different, so when the overall nitrogen and phosphorus load trend of the reservoir area is finally obtained, direct overall acquisition is likely to lead to a decrease in the accuracy of the final prediction result. Summary of the invention

[0005] In order to solve the technical problem that the prediction results are distorted due to failure to consider the degradation capacity of the water body itself, the purpose of the present invention is to provide a method, device and system for predicting the trend of nitrogen and phosphorus loads in water areas. The technical solutions adopted are as follows:

[0006] In a first aspect, an embodiment of the present invention provides a method for predicting nitrogen and phosphorus load trends in water areas, which is used in a system for predicting nitrogen and phosphorus load trends in water areas. The method includes:

[0007] Acquire at least one sewage discharge point in a preset area and acquire a plurality of sampling points, wherein the sampling points are set up along the edge line of the preset area;

[0008] Determine a target sewage discharge point corresponding to a target sampling point among the multiple sampling points, wherein the target sewage discharge point is a sewage discharge point at a shortest distance between the at least one sewage discharge point and the target sampling point;

[0009] Determine a first reference data set according to the target sewage discharge point and the target sampling point, wherein the first reference data set includes a plurality of reference sampling points, and the reference sampling points include the target sampling point and a plurality of sampling points that meet a preset screening condition;

[0010] Calculate the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point in the first reference data set;

[0011] Performing data processing according to the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point to obtain a prediction reference weight and a target weight corresponding to any reference sampling point;

[0012] According to the predicted reference weight and the target weight corresponding to any reference sampling point, the weighted nitrogen and phosphorus load mean value and the target actual nitrogen and phosphorus content value corresponding to the preset area are obtained;

[0013] A trend judgment is performed based on the weighted nitrogen and phosphorus load mean value and the target actual nitrogen and phosphorus content value to obtain the nitrogen and phosphorus load trend corresponding to the preset area.

[0014] In combination with the first aspect, in a possible implementation method, the trend judgment is performed based on the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value to obtain the nitrogen and phosphorus load trend corresponding to the preset area, including: calculating the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value to obtain a target difference; when the target difference is greater than 0, the nitrogen and phosphorus load trend corresponding to the preset area is a downward trend; or, when the target difference is less than 0, the nitrogen and phosphorus load trend corresponding to the preset area is an upward trend; or, when the target difference is equal to 0, the nitrogen and phosphorus load trend corresponding to the preset area is a stable state.

[0015] In combination with the first aspect, in a possible implementation, determining a first reference data set based on the target sewage discharge point and the target sampling point includes: obtaining a first target straight line based on the target sampling point and the target sewage discharge point; and filtering the first target straight line and the multiple sampling points according to preset filtering conditions to obtain a first reference data set, wherein the first reference data set includes multiple reference sampling points, and the reference sampling points include the target sampling point and multiple sampling points that meet the preset filtering conditions.

[0016] In combination with the first aspect, in a possible implementation, the any reference sampling point includes a first reference sampling point, and the calculating of the spatial degradation trend, the temperature influence coefficient and the time degradation trend of any reference sampling point in the first reference data set includes: obtaining a first influence probability according to a first distance and a second distance from a vertical point corresponding to the first distance to the target sewage discharge point, the first distance being the distance between a first target straight line and the first reference sampling point, the first target straight line being obtained by the target sampling point and the target sewage discharge point; obtaining the spatial degradation trend of any reference sampling point according to the first influence probability and the second influence probability, the second influence probability being the influence probability of adjacent sampling points corresponding to the any reference sampling point at the same time; obtaining the temperature data and nitrogen and phosphorus content of any reference sampling point; obtaining the temperature influence coefficient of any reference sampling point according to the temperature data and the nitrogen and phosphorus content; and determining the time degradation trend of any reference sampling point according to the temperature influence coefficient and the spatial degradation trend.

[0017] In combination with the first aspect, in a possible implementation method, data processing is performed according to the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point to obtain the predicted reference weight and target weight corresponding to any reference sampling point, including: obtaining the predicted reference weight corresponding to any reference sampling point according to the spatial degradation trend and the historical spatial degradation trend of any reference sampling point at any historical moment; and taking the inverse calculation of the time degradation trend to obtain the target weight.

[0018] In combination with the first aspect, in a possible implementation, the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value corresponding to the preset area are obtained according to the predicted reference weight and the target weight corresponding to any reference sampling point, including: obtaining the predicted nitrogen and phosphorus load value corresponding to any reference sampling point according to the predicted reference weight; weighting the predicted nitrogen and phosphorus load value according to the target weight to obtain the target weighted nitrogen and phosphorus load value corresponding to any reference sampling point; obtaining the weighted nitrogen and phosphorus load mean corresponding to the preset area according to the target weighted nitrogen and phosphorus load value and multiple weighted nitrogen and phosphorus load values, wherein the multiple weighted nitrogen and phosphorus load values ​​are obtained from multiple reference sampling points in the first reference data set; obtaining the target sampling time point of any reference sampling point and multiple actual nitrogen and phosphorus content values ​​at the target sampling time point, wherein the multiple actual nitrogen and phosphorus content values ​​correspond to multiple reference sampling points in the any reference data set; and performing data processing on the multiple actual nitrogen and phosphorus content values ​​according to the target weight to obtain the target actual nitrogen and phosphorus content value at the target sampling time point.

[0019] In combination with the first aspect, in a possible implementation method, the data processing of the multiple actual nitrogen and phosphorus content values ​​according to the target weight to obtain the target actual nitrogen and phosphorus content value at the target sampling time point includes: performing weighted calculation on each actual nitrogen and phosphorus content value of the multiple actual nitrogen and phosphorus content values ​​according to the target weight to obtain multiple weighted actual nitrogen and phosphorus contents; and performing weighted average calculation on the weighted actual nitrogen and phosphorus contents to obtain the target actual nitrogen and phosphorus content value at the target sampling time point.

[0020] In combination with the first aspect, in a possible implementation, obtaining multiple sampling points includes: obtaining any position on an edge line of a preset area; and selecting sampling points in a vertical direction of the any position according to a preset interval to obtain multiple sampling points.

[0021] In a second aspect, an embodiment of the present invention provides a system for predicting a trend of nitrogen and phosphorus loads in water areas, comprising a memory and a processor, wherein the memory is connected to the processor, and the processor is used to execute one or more computer programs stored in the memory. When the processor executes the one or more computer programs, the system for predicting a trend of nitrogen and phosphorus loads in water areas implements a method for predicting a trend of nitrogen and phosphorus loads in water areas as described in the first aspect.

[0022] In a third aspect, a computer device is provided, comprising a memory and a processor, wherein the memory is connected to the processor, and the processor is used to execute one or more computer programs stored in the memory. When the processor executes the one or more computer programs, the computer device implements a method for predicting nitrogen and phosphorus load trends in water areas as described in the first aspect.

[0023] In a fourth aspect, an embodiment of the present invention provides a water area nitrogen and phosphorus load trend prediction device, which is applied to a water area nitrogen and phosphorus load trend prediction system, and the device includes:

[0024] An acquisition unit, used for acquiring at least one sewage discharge point in a preset area and acquiring a plurality of sampling points, wherein the sampling points are set up along the edge line of the preset area;

[0025] a determination unit, configured to determine a target sewage discharge point corresponding to a target sampling point among the plurality of sampling points, wherein the target sewage discharge point is a sewage discharge point at a shortest distance between the at least one sewage discharge point and the target sampling point;

[0026] The determination unit is further used to determine a first reference data set according to the target sewage discharge point and the target sampling point, wherein the first reference data set includes a plurality of reference sampling points, and the reference sampling points include the target sampling point and a plurality of sampling points that meet a preset screening condition;

[0027] a calculation unit, used to calculate the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point in the first reference data set;

[0028] The determination unit is further used to perform data processing according to the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point to obtain the prediction reference weight and target weight corresponding to any reference sampling point;

[0029] The determination unit is further used to obtain the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value corresponding to the preset area according to the predicted reference weight and the target weight corresponding to any reference sampling point;

[0030] The determination unit is further used to perform trend judgment based on the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value to obtain the nitrogen and phosphorus load trend corresponding to the preset area.

[0031] In a fifth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes a method for predicting nitrogen and phosphorus load trends in water areas as described in the first aspect.

[0032] The present invention has the following beneficial effects: the present invention provides more accurate and real-time water quality monitoring data by accurately determining the sewage discharge point and the sampling points near the sewage discharge point in the preset area, and performing analysis based on the shortest distance between these sampling points and the sewage discharge point; further calculating the spatial degradation trend, taking into account the temperature influence coefficient and the time degradation trend, and comprehensively evaluating the water quality analysis, so as to better understand the complex process of water quality changes over time and space; using the predicted reference weight and target weight of each sampling point in the reference data set to calculate the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value, the nitrogen and phosphorus load trend of the preset area can be more accurately predicted and evaluated; further by monitoring and analyzing the water quality in the preset area, the method improves the prediction accuracy while providing timely and effective information for the management and protection of water bodies. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1A schematic flow chart of a method for predicting nitrogen and phosphorus load trends in water areas provided by one embodiment of the present invention;

[0035] Figure 2 A schematic diagram of the structure of a device for predicting nitrogen and phosphorus load trends in water areas provided by one embodiment of the present invention.

[0036] Figure 3 A schematic diagram of the structure of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of a method, device and system for predicting the trend of nitrogen and phosphorus loads in water areas proposed by the present invention, its specific implementation method, structure, features and effects, in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0038] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0039] The specific scheme of a method, device and system for predicting nitrogen and phosphorus load trends in water areas provided by the present invention is described in detail below in conjunction with the accompanying drawings.

[0040] See also Figure 1 , which shows a schematic flow chart of a method for predicting nitrogen and phosphorus load trends in water areas provided by an embodiment of the present invention, which is applied to a system for predicting nitrogen and phosphorus load trends in water areas, and the method comprises the following steps:

[0041] S10, obtaining at least one sewage discharge point in a preset area and obtaining a plurality of sampling points, wherein the sampling points are set up along the edge line of the preset area.

[0042] The preset area may be a water area to be detected, and the water area may be a reservoir or other area capable of storing water, which is not limited here.

[0043] The at least one sewage discharge point can be obtained by counting all industrial and agricultural sewage discharge points around the preset area.

[0044] Among them, the sampling points are set up along the edge line of the preset area, and this setting method can better reflect the overall situation of the water area.

[0045] The edge line may be the shoreline of a river or lake, or a specific geographical location, and is not limited here.

[0046] Optionally, the density of sampling points is determined according to the size and complexity of the preset area. The density of sampling points should be high enough to ensure that the changing trend of nitrogen and phosphorus loads can be accurately captured.

[0047] It can be seen that this embodiment can better reflect the nitrogen and phosphorus load trend of the entire water area by determining at least one sewage discharge point in the preset area and establishing multiple sampling points along the edge line of the preset area. The sampling points are usually located at key positions for pollutant input and output, and can capture the diffusion and migration of pollutants in the water area, ensuring that the direct or indirect impacts from the sewage discharge point can be fully monitored. Furthermore, by establishing sampling points on the edge line, the entire area can be effectively covered, thereby obtaining more comprehensive data to evaluate and monitor water quality.

[0048] In one embodiment, obtaining a plurality of sampling points includes: obtaining any position on an edge line of a preset area; and selecting sampling points in a vertical direction of the any position according to a preset interval to obtain a plurality of sampling points.

[0049] Among them, any position means selecting a starting point on the edge line of the preset area. This point can be any position in the preset area, which is determined according to actual needs and monitoring objectives.

[0050] Among them, the above-mentioned preset interval can be determined according to a preset distance. This distance may be set according to factors such as the depth, width, and monitoring purpose of the water area, and is not a sole limitation here.

[0051] Among them, at each vertical interval, a sampling point is selected according to the preset interval, and the sampling point can be fixed or adjustable to meet different monitoring needs.

[0052] The number of sampling points in the plurality of sampling points may be 3, 4, 5, etc., which is not limited here. The sampling points are distributed in the waters of the entire preset area to form a sampling network.

[0053] It can be seen that this embodiment can more accurately capture the distribution and changes of pollutants in the water area by selecting multiple sampling points on the edge line of the preset area and performing sampling in the vertical direction at preset intervals, thereby improving monitoring accuracy; the sampling points on the edge line can better reflect the overall characteristics of the water area and the transmission path of pollutants, which helps to understand the source and impact range of pollutants.

[0054] S20. Determine a target sewage discharge point corresponding to a target sampling point among the multiple sampling points, wherein the target sewage discharge point is a sewage discharge point that is at the shortest distance between the at least one sewage discharge point and the target sampling point.

[0055] The target sampling point may be any sampling point among the multiple sampling points.

[0056] Among them, for each target sampling point, the distance between it and all surrounding sewage discharge points is calculated, and the shortest distance between each target sampling point and the surrounding sewage discharge points is determined. The position corresponding to this distance is the target sewage discharge point.

[0057] Among them, the shortest distance between the target sampling point and the target sewage discharge point indicates the fastest path for pollutants to reach the sampling point from the discharge point, and the degree of pollution on this path may be the highest.

[0058] It can be seen that in this embodiment, by determining the target sewage discharge point corresponding to the target sampling point, the complexity of the monitoring work can be reduced and the monitoring efficiency can be improved. That is, the target sewage discharge point is the point on the fastest path for pollutants to reach the sampling point from the discharge point, reflecting the actual transmission path of the pollutants. Based on the shortest distance between the target sewage discharge point and the target sampling point, the diffusion and degradation process of pollutants in the water area can be more accurately predicted, thereby improving the accuracy of nitrogen and phosphorus load prediction.

[0059] S30. Determine a first reference data set according to the target sewage discharge point and the target sampling point, wherein the first reference data set includes multiple reference sampling points, and the reference sampling points include the target sampling point and multiple sampling points that meet preset screening conditions.

[0060] The first reference data set is obtained by data processing based on the target sewage discharge point and the target sampling point. The data processing may be to first obtain a straight line between the target sewage discharge point and the target sampling point, and then screen the straight line between the two points and the plurality of sampling points to obtain a plurality of reference sampling points; and then aggregate the plurality of reference sampling points and the target sampling point to obtain the first reference data set. It should be noted that the first reference data set must include the target sampling point because it is the starting point of the prediction analysis.

[0061] Among them, the preset screening conditions include two types of conditions. The first type is other sampling points on the straight line between the target sewage discharge point and the target sampling point, which are sampling points that meet the preset screening conditions; the second type is sampling points that are not on the straight line between the target sewage discharge point and the target sampling point. It is necessary to perform data screening on the sampling points that are not on the straight line. The process of data screening is: assuming that the straight line between the target sewage discharge point and the target sampling point is the first target straight line, obtain the vertical distance from the sampling point that is not on the straight line to the first target straight line. , use the norm function to normalize the vertical distance The sampling points whose corresponding normalized values ​​are less than the preset empirical value are divided into the first reference data set, that is, the sampling points that meet the preset screening conditions are obtained. Note that the preset empirical value may include but is not limited to 0.3 and may be set manually.

[0062] The first reference data set also includes the distance between the intersection of the vertical line of each reference sampling point and the first target straight line and the target sewage discharge point. , Represents any other sampling point in the first reference data set.

[0063] The vertical distance It usually represents the shortest distance from the sampling point to the reference line. It should be noted that if the sampling point is exactly on the line, then this perpendicular distance should be zero, because there is no perpendicular separation between the sampling point and the line. In this case, the perpendicular distance It is set to a very small positive number to avoid the problem of zero. At the same time, this small positive number also indicates that the point is very close to the line and has a great influence on its weight.

[0064] It can be seen that in this embodiment, by constructing a data set including a target sampling point and multiple sampling points that meet the screening conditions for the prediction and analysis of nitrogen and phosphorus load trends, the accuracy of the prediction is improved.

[0065] In one embodiment, determining a first reference data set based on the target sewage discharge point and the target sampling point includes: obtaining a first target straight line based on the target sampling point and the target sewage discharge point; and filtering the first target straight line and the multiple sampling points according to preset filtering conditions to obtain a first reference data set, wherein the first reference data set includes multiple reference sampling points, and the reference sampling points include the target sampling point and multiple sampling points that meet the preset filtering conditions.

[0066] Among them, in the specific implementation of obtaining the first target straight line according to the target sampling point and the target sewage discharge point, a coordinate system can be established to locate the target sampling point and the target sewage discharge point in the coordinate system, and the equation of the straight line connecting the two points is calculated according to the coordinates of the target sampling point and the target sewage discharge point. This straight line is called the first target straight line.

[0067] The above-mentioned preset screening conditions are described in S30 and will not be described again here.

[0068] It can be seen that in this embodiment, by constructing a data set including a target sampling point and multiple sampling points that meet the screening conditions for the prediction and analysis of nitrogen and phosphorus load trends, the accuracy of the prediction is improved.

[0069] S40, calculating the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point in the first reference data set.

[0070] The any reference sampling point includes a first reference sampling point, that is, the first reference sampling point represents any point among any reference sampling points.

[0071] The specific calculation process may be: in one embodiment, the any reference sampling point includes a first reference sampling point, and the calculation of the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point in the first reference data set includes: obtaining a first influence probability according to a first distance and a second distance from a vertical point corresponding to the first distance to the target sewage discharge point, the first distance being the distance between a first target straight line and the first reference sampling point, the first target straight line being obtained by the target sampling point and the target sewage discharge point; obtaining the spatial degradation trend of any reference sampling point according to the first influence probability and the second influence probability, the second influence probability being the influence probability of adjacent sampling points corresponding to any reference sampling point at the same time; obtaining the temperature data and nitrogen and phosphorus content of any reference sampling point; obtaining the temperature influence coefficient of any reference sampling point according to the temperature data and the nitrogen and phosphorus content; determining the time degradation trend of any reference sampling point according to the temperature influence coefficient and the spatial degradation trend.

[0072] Among them, the first distance is the distance between the first target straight line and the first reference sampling point, and the distance is a vertical distance. The first target straight line is obtained by the target sampling point and the target sewage discharge point.

[0073] The second distance represents the distance between the intersection point of the perpendicular line of the first reference sampling point and the first target straight line and the target sewage discharge point.

[0074] Among them, in obtaining the first impact probability according to the first distance and the second distance from the vertical point corresponding to the first distance to the target sewage discharge point, the first impact probability can be obtained according to the following preset first formula:

[0075] ;

[0076] Where: Indicates any current sampling point. It is represented as the first reference sampling point, and the first reference sampling point is any other sampling point in the first reference data set. represents the second distance, represents the first distance, represents the first impact probability, which represents the The probability that the nitrogen and phosphorus data at a certain moment corresponding to the sampling point are affected by the emission point due to the change in distance.

[0077] in, The bigger, The greater the probability that the nitrogen and phosphorus data at a certain moment corresponding to the sampling point will be affected by the emission point due to the change in distance.

[0078] Among them, in the formula of the first impact probability, It is set to a very small positive number to avoid the problem of zero. For a specific explanation, please refer to the description in the above S30, which will not be repeated here.

[0079] Among them, in the process of obtaining the spatial degradation trend of any reference sampling point according to the first influence probability and the second influence probability, the second influence probability is the influence probability of the adjacent sampling points corresponding to any reference sampling point at the same time, and the calculation of the second influence probability can be obtained by referring to the above-mentioned preset first formula.

[0080] Among them, in the specific implementation of obtaining the spatial degradation trend of any reference sampling point according to the first impact probability and the second impact probability, the any reference sampling point (assuming that ) spatial degradation trend:

[0081] ;

[0082] Where: Indicates the current The total number of sampling points in the first reference data set corresponding to the sampling point (including itself), Indicates the current The influence probability of the rth sampling point in the first reference data set corresponding to the sampling point. Indicates the current sampling point The corresponding influence probability of the r+1th sampling point in the first reference data set, Indicates the current The sampling time of the rth sampling point in the first reference data set corresponding to the sampling point, Indicates the current sampling point The sampling time of the r+1th sampling point in the corresponding first reference data set.

[0083] In the preset second formula, the summation starts from the first sample point (i.e., r=1) until the sampling points, that is, the termination condition should be when the variable r reaches When all sampling points are traversed, the summation operation ends.

[0084] Among them, since all sampling points in the data set are traversed, we get ,therefore Used as a loop variable or index to iterate over all sample points in the dataset.

[0085] in, Indicates the current Spatial degradation trend of the sampling points. The larger the value, the higher the degradation trend.

[0086] In obtaining the temperature data and nitrogen and phosphorus content of any reference sampling point, corresponding data may be obtained according to different sensors, and no sole limitation is made here.

[0087] Among them, in obtaining the temperature influence coefficient of any reference sampling point according to the temperature data and the nitrogen and phosphorus content, the Pearson correlation coefficient is used for calculation to obtain the temperature influence coefficient between the temperature data and the nitrogen and phosphorus load data. The value range of the temperature influence coefficient is [-1,1], where 1 represents a complete positive correlation, -1 represents a complete negative correlation, and 0 represents no linear correlation. At this time, the absolute value is used, thereby obtaining , so that its range becomes [0,1].

[0088] The temperature data and nitrogen and phosphorus content obtained at any reference sampling point may be time series data, reflecting changes in temperature and nitrogen and phosphorus loads over a period of time.

[0089] In determining the time degradation trend of any reference sampling point according to the temperature influence coefficient and the spatial degradation trend, the specific process can be calculated according to a preset third formula, and the preset third formula is calculated to obtain Time degradation trend of sampling points:

[0090] ;

[0091] Where: express Temporal degradation trend of sampling points, express The variance of the spatial degradation trend delay series of the sampling points, express The mean of the spatial degradation trend delay series of the sampling points, For the current The temperature influence coefficient of the sampling point. The larger the value, the greater the influence of temperature on the water body corresponding to the sampling point. It also means that the change of the load data obtained at the current sampling point is more obviously affected by the temperature, that is, the seasonal characteristics are more obvious. It also means that the spatial degradation trend calculated above in the time series of the sampling point has a higher reference value.

[0092] in, The larger the value is, the smaller the seasonal impact on the current sampling point is, and the greater its temporal degradation trend is.

[0093] It can be seen that in this embodiment, by calculating the spatial degradation trend, the spatial distribution and changes of nitrogen and phosphorus pollutants can be more accurately predicted, thereby improving the accuracy of predicting changes in water environment quality. Further, by combining the first impact probability and the second impact probability, it is helpful to understand the transmission mechanism of pollutants from the sewage discharge point to the sampling point. By calculating the temperature influence coefficient, the impact of temperature changes on nitrogen and phosphorus loads can be quantified. By combining the spatial degradation trend and the temperature influence coefficient, the temporal degradation trend can be determined, and the changing trend of nitrogen and phosphorus pollutants over time can be comprehensively evaluated. The predictive ability of the temporal degradation trend can be used to establish an early warning system, forecast possible water quality deterioration in advance, and provide preparation time for emergency response.

[0094] S50, performing data processing according to the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point to obtain a prediction reference weight and a target weight corresponding to any reference sampling point.

[0095] In one embodiment, the data processing is performed according to the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point to obtain the predicted reference weight and target weight corresponding to any reference sampling point, including: obtaining the predicted reference weight corresponding to any reference sampling point according to the spatial degradation trend and the historical spatial degradation trend of any reference sampling point at any historical moment; and obtaining the target weight by taking the inverse of the time degradation trend.

[0096] Among them, in obtaining the prediction reference weight corresponding to any reference sampling point according to the spatial degradation trend and the historical spatial degradation trend of any reference sampling point at any historical moment, the prediction reference weight can be obtained by calculating through the preset fourth formula :

[0097] ;

[0098] In the formula, express The predicted reference weight of the actual nitrogen and phosphorus load value at the sampling point, That is to say The sampling time points of the sampling points correspond to the spatial degradation trends obtained. That is, it represents the spatial degradation trend of any moment q in history. By making the difference between the two, we can get , the smaller the value is, the more similar the historical moment is to the current time point, and the higher its reference weight is; That is, the historical sampling time point q to The time difference between the sampling time points of the sampling points. The larger the value, the smaller the reference weight. Therefore, it is expressed in fractions. For the spatial degradation trend of the current sampling time point, The larger the value, the higher the reference weight of the nitrogen and phosphorus load value to be predicted for that historical moment. In order to avoid the influence of the above difference on the weight value when it is 0, the Euclidean norm is used to combine the above two characteristic factors, and the fraction is used to express them. Based on the sum normalization , thus obtaining The larger the value is, the higher the predicted reference weight of the actual nitrogen and phosphorus load value at any historical sampling moment.

[0099] In the specific implementation of taking the inverse of the time degradation trend to obtain the target weight, it can be expressed as the following formula:

[0100] ;

[0101] in, express Temporal degradation trend of sampling points, express The target weight of the sampling point.

[0102] It can be seen that in this embodiment, the prediction reference weight is determined by comparing the current spatial degradation trend with the historical spatial degradation trend, so that the value of the historical monitoring data is maximized, providing a historical basis for current and future environmental management, and the dynamic adjustment of the prediction reference weight can enable the prediction model to better adapt to environmental changes; further taking the inverse of the time degradation trend to calculate the target weight can better reflect the rate of change of pollutants over time, enhance the accuracy of time series analysis, and thus improve the accuracy and reliability of the prediction of nitrogen and phosphorus load trends in waters.

[0103] S60. Obtain the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value corresponding to the preset area according to the predicted reference weight and the target weight corresponding to any reference sampling point.

[0104] In a specific implementation, the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value corresponding to the preset area are obtained according to the predicted reference weight and the target weight corresponding to any reference sampling point, including: obtaining the predicted nitrogen and phosphorus load value corresponding to any reference sampling point according to the predicted reference weight; weighting the predicted nitrogen and phosphorus load value according to the target weight to obtain the target weighted nitrogen and phosphorus load value corresponding to any reference sampling point; obtaining the weighted nitrogen and phosphorus load mean corresponding to the preset area according to the target weighted nitrogen and phosphorus load value and multiple weighted nitrogen and phosphorus load values, wherein the multiple weighted nitrogen and phosphorus load values ​​are obtained from multiple reference sampling points in the first reference data set; obtaining the target sampling time point of any reference sampling point and multiple actual nitrogen and phosphorus content values ​​at the target sampling time point, wherein the multiple actual nitrogen and phosphorus content values ​​correspond to multiple reference sampling points in the any reference data set; performing data processing on the multiple actual nitrogen and phosphorus content values ​​according to the target weight to obtain the target actual nitrogen and phosphorus content value at the target sampling time point.

[0105] Among them, in the specific implementation of obtaining the predicted nitrogen and phosphorus load value corresponding to any reference sampling point according to the predicted reference weight, the actual nitrogen and phosphorus measurement values ​​of each sampling point are weighted using the predicted reference weight, that is, each actual nitrogen and phosphorus measurement is multiplied by the predicted reference weight to obtain the predicted nitrogen and phosphorus load value corresponding to any reference sampling point.

[0106] Therefore, the predicted value of nitrogen and phosphorus load at the current sampling point is obtained according to the predicted reference weight, and then the overall nitrogen and phosphorus load status of the water body is evaluated and predicted.

[0107] Among them, in the specific process of weighting the predicted nitrogen and phosphorus load values ​​according to the target weight to obtain the target weighted nitrogen and phosphorus load value corresponding to any reference sampling point, the predicted nitrogen and phosphorus load value corresponding to any reference sampling point is multiplied by the target weight to obtain the target weighted nitrogen and phosphorus load value corresponding to any reference sampling point.

[0108] In the specific implementation process of obtaining the weighted nitrogen and phosphorus load mean corresponding to the preset area according to the target weighted nitrogen and phosphorus load value and a plurality of weighted nitrogen and phosphorus load values, the weighted nitrogen and phosphorus load values ​​of all reference sampling points in the first reference data set are summed to obtain the total weighted nitrogen and phosphorus load value, and then the total weighted nitrogen and phosphorus load value is divided by the weight The sum of the weighted nitrogen and phosphorus loads is obtained.

[0109] Among them, in the specific process of performing data processing on the multiple actual nitrogen and phosphorus content values ​​according to the target weight to obtain the target actual nitrogen and phosphorus content value at the target sampling time point, the data processing can be weighted processing of the data, weighted average processing, etc.

[0110] It can be seen that in this embodiment, by using the prediction reference weight to determine the predicted nitrogen and phosphorus load value corresponding to each reference sampling point, the pollution degree of each sampling point can be more accurately reflected, and by performing target weighting processing on the predicted nitrogen and phosphorus load value, those areas with more serious pollution or greater environmental impact can be more targeted to identify, and further obtain multiple actual nitrogen and phosphorus content values ​​at the target sampling time point, and perform weighted processing, which is helpful to quickly and accurately evaluate the actual pollution status at the target time point. Therefore, the prediction error can be reduced and the prediction ability of the trend prediction of nitrogen and phosphorus load in waters can be improved.

[0111] In one embodiment, the data processing of the multiple actual nitrogen and phosphorus content values ​​according to the target weight to obtain the target actual nitrogen and phosphorus content value at the target sampling time point includes: performing weighted calculation on each actual nitrogen and phosphorus content value of the multiple actual nitrogen and phosphorus content values ​​according to the target weight to obtain multiple weighted actual nitrogen and phosphorus contents; and performing weighted average calculation on the weighted actual nitrogen and phosphorus contents to obtain the target actual nitrogen and phosphorus content value at the target sampling time point.

[0112] Among them, the target actual nitrogen and phosphorus content value can be obtained by dividing the sum of the weighted actual nitrogen and phosphorus contents of all reference sampling points by the sum of the weights of all reference sampling points.

[0113] Among them, the target actual nitrogen and phosphorus content value reflects the value of the overall nitrogen and phosphorus load status in the preset area at the current sampling time point, that is, the target actual nitrogen and phosphorus content value takes into account the differences in contributions of different sampling points to the overall load.

[0114] It can be seen that through weighted calculation in this embodiment, it can be ensured that the nitrogen and phosphorus content data of each sampling point more accurately reflects its importance in the overall environmental load, and the target actual nitrogen and phosphorus content value obtained by weighted average calculation can more accurately assess the environmental pollution risk and provide a reliable basis for risk management.

[0115] S70. Perform trend judgment based on the weighted nitrogen and phosphorus load mean value and the target actual nitrogen and phosphorus content value to obtain the nitrogen and phosphorus load trend corresponding to the preset area.

[0116] Among them, the above trend judgment can be based on the difference calculation between the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value, and the target difference is obtained to make a trend judgment. The positive and negative numbers of the target difference show that the nitrogen and phosphorus load in the current preset area is in an upward or downward stage, and the absolute value of the target difference shows the amplitude of the increase or decrease of the nitrogen and phosphorus load. The larger the absolute value, the more significant the amplitude of the trend change.

[0117] Specifically, the difference can be calculated according to the following formula:

[0118] Target difference = weighted nitrogen and phosphorus load mean - target actual nitrogen and phosphorus content value, where the target difference can be positive or negative.

[0119] Optionally, the nitrogen and phosphorus load trends may be output in the form of a report, including a trend graph, predicted values, and predicted errors, etc., which are not limited here.

[0120] In one embodiment, the trend judgment is performed based on the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value to obtain the nitrogen and phosphorus load trend corresponding to the preset area, including: calculating the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value to obtain a target difference; when the target difference is greater than 0, the nitrogen and phosphorus load trend corresponding to the preset area is a downward trend; or, when the target difference is less than 0, the nitrogen and phosphorus load trend corresponding to the preset area is an upward trend; or, when the target difference is equal to 0, the nitrogen and phosphorus load trend corresponding to the preset area is a stable state.

[0121] Among them, when the target difference is greater than 0, it means that the actually measured nitrogen and phosphorus content is lower than the expected (or weighted average) nitrogen and phosphorus content, that is, the nitrogen and phosphorus load may be decreasing, and the nitrogen and phosphorus pollution in the water area has decreased. Therefore, the nitrogen and phosphorus load trend corresponding to the preset area is a downward trend.

[0122] Among them, when the target difference is less than 0, it means that the actually measured nitrogen and phosphorus content is higher than the expected nitrogen and phosphorus content, indicating that the nitrogen and phosphorus load may be increasing and the nitrogen and phosphorus pollution in the water area is aggravating. Therefore, the nitrogen and phosphorus load trend corresponding to the preset area is an upward trend.

[0123] Among them, when the target difference is equal to 0, it means that the actually measured nitrogen and phosphorus content is equal to the expected nitrogen and phosphorus content, and there is no upward or downward trend. Therefore, the nitrogen and phosphorus load trend corresponding to the preset area is in a stable state.

[0124] Optionally, the target difference and its positive and negative signs and absolute values ​​are used to describe the trend of nitrogen and phosphorus loads in the current preset area.

[0125] For example, if the target difference = 5, it means that the expected nitrogen and phosphorus content is 5 units higher than the actually measured nitrogen and phosphorus content, indicating that the nitrogen and phosphorus load has a downward trend; if the target difference = -3, it indicates that the nitrogen and phosphorus load has an upward trend with an amplitude of 3 units.

[0126] It can be seen that in this embodiment, a quantitative indicator is obtained to describe the trend of nitrogen and phosphorus loads, which helps decision makers or researchers understand the dynamic changes of nitrogen and phosphorus loads in the reservoir area and take corresponding management measures.

[0127] The present invention has the following beneficial effects: the present invention accurately determines the sewage discharge point and the sampling points near the sewage discharge point in the preset area, and analyzes based on the shortest distance between these sampling points and the sewage discharge point, thereby providing more accurate and real-time water quality monitoring data; further calculates the spatial degradation trend, and considers the temperature influence coefficient and the time degradation trend at the same time, and comprehensively evaluates the water quality analysis, which can better understand the complex process of water quality changes over time and space; uses the predicted reference weight and target weight of each sampling point in the reference data set to calculate the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value, which can more accurately predict and evaluate the nitrogen and phosphorus load trend of the preset area; further, by monitoring and analyzing the water quality of the preset area, this method improves the prediction accuracy while providing target abnormal state parameters for the management and protection of water bodies, and can evaluate the performance quality of the large current terminal to be detected, thereby ensuring the quality and reliability of the product.

[0128] It should be noted that the sequence of the above embodiments of the present invention is for description only and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0129] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0130] As another aspect of the embodiment of the present application, the embodiment of the present application provides a device for predicting the trend of nitrogen and phosphorus loads in water areas. The device for predicting the trend of nitrogen and phosphorus loads in water areas can be a software module, which includes several instructions stored in a memory, and the processor can access the memory and call the instructions for execution to complete a method for predicting the trend of nitrogen and phosphorus loads in water areas described in the above-mentioned embodiments.

[0131] See also Figure 2 , Figure 2 Schematic diagram of a device for predicting nitrogen and phosphorus load trends in water areas provided in an embodiment of the present application. Figure 2 As shown, the device 200 for predicting nitrogen and phosphorus load trends in water areas includes:

[0132] An acquisition unit 201 is used to acquire at least one sewage discharge point in a preset area and acquire multiple sampling points, wherein the sampling points are set up along the edge line of the preset area;

[0133] A determination unit 202 is used to determine a target sewage discharge point corresponding to a target sampling point among the multiple sampling points, wherein the target sewage discharge point is a sewage discharge point that is at the shortest distance between the at least one sewage discharge point and the target sampling point;

[0134] The determining unit 202 is further configured to determine a first reference data set according to the target sewage discharge point and the target sampling point, wherein the first reference data set includes a plurality of reference sampling points, and the reference sampling points include the target sampling point and a plurality of sampling points that meet a preset screening condition;

[0135] A calculation unit 203 is used to calculate the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point in the first reference data set;

[0136] The determination unit 202 is further used to perform data processing according to the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point to obtain the prediction reference weight and target weight corresponding to any reference sampling point;

[0137] The determining unit 202 is further configured to obtain a weighted nitrogen and phosphorus load mean value and a target actual nitrogen and phosphorus content value corresponding to the preset area according to the predicted reference weight and the target weight corresponding to any reference sampling point;

[0138] The determination unit 202 is further configured to perform trend judgment based on the weighted nitrogen and phosphorus load mean value and the target actual nitrogen and phosphorus content value to obtain the nitrogen and phosphorus load trend corresponding to the preset area.

[0139] The present invention has the following beneficial effects: the present invention accurately determines the sewage discharge point and the sampling points near the sewage discharge point in the preset area, and analyzes based on the shortest distance between these sampling points and the sewage discharge point, thereby providing more accurate and real-time water quality monitoring data; further calculates the spatial degradation trend, and considers the temperature influence coefficient and the time degradation trend at the same time, and comprehensively evaluates the water quality analysis, which can better understand the complex process of water quality changes over time and space; uses the predicted reference weight and target weight of each sampling point in the reference data set to calculate the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value, which can more accurately predict and evaluate the nitrogen and phosphorus load trend of the preset area; further, by monitoring and analyzing the water quality of the preset area, this method improves the prediction accuracy while providing target abnormal state parameters for the management and protection of water bodies, and can evaluate the performance quality of the large current terminal to be detected, thereby ensuring the quality and reliability of the product.

[0140] In one embodiment, in traversing the state parameter set to obtain abnormal state parameters and the first detection order corresponding to the abnormal state parameters, the determination unit 202 is further used to: calculate the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value to obtain a target difference; when the target difference is greater than 0, the nitrogen and phosphorus load trend corresponding to the preset area is a downward trend; or, when the target difference is less than 0, the nitrogen and phosphorus load trend corresponding to the preset area is an upward trend; or, when the target difference is equal to 0, the nitrogen and phosphorus load trend corresponding to the preset area is a stable state.

[0141] In one embodiment, in determining the first reference data set according to the target sewage discharge point and the target sampling point, the determination unit 202 is further used to: obtain a first target straight line according to the target sampling point and the target sewage discharge point; and filter the first target straight line and the multiple sampling points according to preset filtering conditions to obtain a first reference data set, wherein the first reference data set includes multiple reference sampling points, and the reference sampling points include the target sampling point and multiple sampling points that meet the preset filtering conditions.

[0142] In one embodiment, the any reference sampling point includes a first reference sampling point. In the calculation of the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point in the first reference data set, the calculation unit 203 is further used to: obtain a first influence probability according to a first distance and a second distance from a vertical point corresponding to the first distance to the target sewage discharge point, the first distance being the distance between a first target straight line and the first reference sampling point, the first target straight line being obtained by the target sampling point and the target sewage discharge point; obtain the spatial degradation trend of the any reference sampling point according to the first influence probability and the second influence probability, the second influence probability being the influence probability of adjacent sampling points corresponding to the any reference sampling point at the same time; obtain the temperature data and nitrogen and phosphorus content of the any reference sampling point; obtain the temperature influence coefficient of the any reference sampling point according to the temperature data and the nitrogen and phosphorus content; and determine the time degradation trend of the any reference sampling point according to the temperature influence coefficient and the spatial degradation trend.

[0143] In one embodiment, in the process of performing data processing according to the spatial degradation trend, the temperature influence coefficient and the time degradation trend of any reference sampling point to obtain the predicted reference weight and the target weight corresponding to the any reference sampling point, the determining unit 202 is further used to: obtain the predicted reference weight corresponding to the any reference sampling point according to the spatial degradation trend and the historical spatial degradation trend of the any reference sampling point at any historical moment; and obtain the target weight by taking the inverse of the time degradation trend.

[0144] In one embodiment, in obtaining the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value corresponding to the preset area according to the predicted reference weight and the target weight corresponding to any reference sampling point, the determining unit 202 is further used to: obtain the predicted nitrogen and phosphorus load value corresponding to any reference sampling point according to the predicted reference weight; perform weighted processing on the predicted nitrogen and phosphorus load value according to the target weight to obtain the target weighted nitrogen and phosphorus load value corresponding to any reference sampling point; obtain the weighted nitrogen and phosphorus load mean corresponding to the preset area according to the target weighted nitrogen and phosphorus load value and multiple weighted nitrogen and phosphorus load values, wherein the multiple weighted nitrogen and phosphorus load values ​​are obtained from multiple reference sampling points in the first reference data set; obtain the target sampling time point of any reference sampling point and multiple actual nitrogen and phosphorus content values ​​at the target sampling time point, wherein the multiple actual nitrogen and phosphorus content values ​​correspond to multiple reference sampling points in the any reference data set; perform data processing on the multiple actual nitrogen and phosphorus content values ​​according to the target weight to obtain the target actual nitrogen and phosphorus content value at the target sampling time point.

[0145] In one embodiment, in performing data processing on the multiple actual nitrogen and phosphorus content values ​​according to the target weight to obtain the target actual nitrogen and phosphorus content value at the target sampling time point, the determination unit 202 is further used to: perform weighted calculation on each actual nitrogen and phosphorus content value in the multiple actual nitrogen and phosphorus content values ​​according to the target weight to obtain multiple weighted actual nitrogen and phosphorus contents; and perform weighted average calculation on the weighted actual nitrogen and phosphorus contents to obtain the target actual nitrogen and phosphorus content value at the target sampling time point.

[0146] In one embodiment, in the step of acquiring multiple sampling points, the acquisition unit 201 is further used to: acquire any position in the edge line of a preset area; and select sampling points in a vertical direction of the any position according to a preset interval to obtain multiple sampling points.

[0147] It should be noted that the above-mentioned device for predicting the trend of nitrogen and phosphorus loads in water areas can execute a method for predicting the trend of nitrogen and phosphorus loads in water areas provided in the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not fully described in the embodiment of the device for predicting the trend of nitrogen and phosphorus loads in water areas, please refer to a method for predicting the trend of nitrogen and phosphorus loads in water areas provided in the embodiment of the present application.

[0148] See also Figure 3 , Figure 3 Schematic diagram of the structure of a computer device provided in an embodiment of the present application. Figure 3As shown, the computer device 300 includes a processor 301 and a memory 302. The processor 301 is in communication connection with the memory 302.

[0149] The processor 301 is configured to support the computer device to perform the corresponding functions in a method for predicting the trend of nitrogen and phosphorus loads in waters in the above method embodiment. The processor 301 can be a central processing unit (CPU), a network processor (NP), a hardware chip or any combination thereof. The above hardware chip can be an application specific integrated circuit (ASIC), a programmable logic device (PLD) or a combination thereof. The above PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL) or any combination thereof.

[0150] Specifically, the processor 301 may include a sending card, a receiving card and a driving chip.

[0151] The memory 302 is used to store program codes, etc. The memory 302 may include a volatile memory (VM), such as a random access memory (RAM); the memory 302 may also include a non-volatile memory (NVM), such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD); the memory 302 may also include a combination of the above-mentioned types of memories.

[0152] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. The computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes a method for predicting nitrogen and phosphorus load trends in water areas as described in the above embodiments.

[0153] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0154] The above disclosure is only a preferred embodiment of the present application, and certainly cannot be used to limit the scope of rights of the present application. Therefore, equivalent changes made according to the present application are still within the scope covered by the present application.

Claims

1. A method for predicting nitrogen and phosphorus load trends in water areas, characterized in that: Applied to a water body nitrogen and phosphorus load trend prediction system, the method comprises: Acquire at least one sewage discharge point in a preset area and acquire a plurality of sampling points, wherein the sampling points are set up along the edge line of the preset area; Determine a target sewage discharge point corresponding to a target sampling point among the multiple sampling points, wherein the target sewage discharge point is a sewage discharge point at a shortest distance between the at least one sewage discharge point and the target sampling point; Determine a first reference data set according to the target sewage discharge point and the target sampling point, wherein the first reference data set includes a plurality of reference sampling points, and the reference sampling points include the target sampling point and a plurality of sampling points that meet a preset screening condition; Calculate the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point in the first reference data set; Performing data processing according to the spatial degradation trend, temperature influence coefficient and time degradation trend of any reference sampling point to obtain a prediction reference weight and a target weight corresponding to any reference sampling point; According to the predicted reference weight and the target weight corresponding to any reference sampling point, the weighted nitrogen and phosphorus load mean value and the target actual nitrogen and phosphorus content value corresponding to the preset area are obtained; Performing trend judgment according to the weighted nitrogen and phosphorus load mean value and the target actual nitrogen and phosphorus content value to obtain the nitrogen and phosphorus load trend corresponding to the preset area; Among them, the method for obtaining the predicted reference weight and target weight corresponding to any reference sampling point is: according to the spatial degradation trend and the historical spatial degradation trend of any reference sampling point at any historical moment, the predicted reference weight corresponding to any reference sampling point is obtained; the inverse calculation of the time degradation trend is performed to obtain the target weight.

2. The method for predicting nitrogen and phosphorus load trends in water areas according to claim 1, characterized in that: The performing trend judgment according to the weighted nitrogen and phosphorus load mean value and the target actual nitrogen and phosphorus content value to obtain the nitrogen and phosphorus load trend corresponding to the preset area includes: Calculating the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value to obtain a target difference; When the target difference is greater than 0, the nitrogen and phosphorus load trend corresponding to the preset area is a downward trend; or, When the target difference is less than 0, the nitrogen and phosphorus load trend corresponding to the preset area is an upward trend; or, When the target difference is equal to 0, the nitrogen and phosphorus load trend corresponding to the preset area is obtained to be in a stable state.

3. The method for predicting nitrogen and phosphorus load trends in water areas according to claim 1, characterized in that: The step of determining a first reference data set according to the target sewage discharge point and the target sampling point includes: Obtaining a first target straight line according to the target sampling point and the target sewage discharge point; According to the preset screening conditions, the first target straight line and the multiple sampling points are screened to obtain a first reference data set, wherein the first reference data set includes multiple reference sampling points, and the reference sampling points include the target sampling point and multiple sampling points that meet the preset screening conditions.

4. The method for predicting nitrogen and phosphorus load trends in water areas according to claim 1, characterized in that: The any reference sampling point includes a first reference sampling point, and the calculating of the spatial degradation trend, the temperature influence coefficient and the time degradation trend of any reference sampling point in the first reference data set includes: A first impact probability is obtained according to a first distance and a second distance from a vertical point corresponding to the first distance to the target sewage discharge point, wherein the first distance is a distance between a first target straight line and the first reference sampling point, and the first target straight line is obtained by the target sampling point and the target sewage discharge point; According to the first influence probability and the second influence probability, a spatial degradation trend of any reference sampling point is obtained, wherein the second influence probability is an influence probability of an adjacent sampling point corresponding to any reference sampling point at the same time; Obtaining temperature data and nitrogen and phosphorus content of any reference sampling point; According to the temperature data and the nitrogen and phosphorus contents, a temperature influence coefficient of any reference sampling point is obtained; The time degradation trend of any reference sampling point is determined according to the temperature influence coefficient and the spatial degradation trend.

5. The method for predicting nitrogen and phosphorus load trends in water areas according to claim 1, characterized in that: The step of obtaining the weighted nitrogen and phosphorus load mean and the target actual nitrogen and phosphorus content value corresponding to the preset area according to the predicted reference weight and the target weight corresponding to any reference sampling point includes: According to the predicted reference weight, the predicted nitrogen and phosphorus load value corresponding to any reference sampling point is obtained; Performing weighted processing on the predicted nitrogen and phosphorus load values ​​according to the target weights to obtain a target weighted nitrogen and phosphorus load value corresponding to any reference sampling point; Obtaining a weighted nitrogen and phosphorus load mean corresponding to the preset area according to the target weighted nitrogen and phosphorus load value and a plurality of weighted nitrogen and phosphorus load values, wherein the plurality of weighted nitrogen and phosphorus load values ​​are obtained from a plurality of reference sampling points in the first reference data set; Obtaining a target sampling time point of any reference sampling point and a plurality of actual nitrogen and phosphorus content values ​​at the target sampling time point, wherein the plurality of actual nitrogen and phosphorus content values ​​correspond to a plurality of reference sampling points in any reference data set; The multiple actual nitrogen and phosphorus content values ​​are processed according to the target weights to obtain the target actual nitrogen and phosphorus content value at the target sampling time point.

6. The method for predicting nitrogen and phosphorus load trends in water areas according to claim 5, characterized in that: The performing data processing on the multiple actual nitrogen and phosphorus content values ​​according to the target weight to obtain the target actual nitrogen and phosphorus content value at the target sampling time point includes: Performing weighted calculation on each of the multiple actual nitrogen and phosphorus content values ​​according to the target weight to obtain multiple weighted actual nitrogen and phosphorus contents; The weighted actual nitrogen and phosphorus contents are weighted averaged to obtain the target actual nitrogen and phosphorus content value at the target sampling time point.

7. The method for predicting nitrogen and phosphorus load trends in water areas according to claim 1, characterized in that: The obtaining of multiple sampling points comprises: Get any position of the edge line of the preset area; In the vertical direction of any of the positions, sampling points are selected according to preset intervals to obtain a plurality of sampling points.

8. A system for predicting nitrogen and phosphorus load trends in water areas, characterized in that: It includes a memory and a processor, the memory is connected to the processor, the processor is used to execute one or more computer programs stored in the memory, and when the processor executes the one or more computer programs, the water body nitrogen and phosphorus load trend prediction system implements the water body nitrogen and phosphorus load trend prediction method as described in any one of claims 1-7.

9. A computer device, characterized in that: It includes a memory and a processor, wherein the memory is connected to the processor, and the processor is used to execute one or more computer programs stored in the memory. When the processor executes the one or more computer programs, the computer device implements the method for predicting the trend of nitrogen and phosphorus loads in water areas as described in any one of claims 1 to 7.

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