A Method and System for Dynamic Monitoring of Lake Salinity Stratification

Abstract

The present invention provides a method and system for dynamically monitoring the salinity stratification of lakes, which relates to the field of lake ecological technologies. The method includes the following steps: obtaining the geographical attribute data, hydrological characteristic data, and temperature data at different positions of the lake to be monitored, and performing layered division in the vertical direction of the lake to be monitored according to the hydrological characteristic data and temperature data to obtain the corresponding division result; constructing a corresponding water body salinity calculation model according to the division result, and obtaining the corresponding preliminary water body salinity value according to the water body salinity calculation model; judging whether it is necessary to correct the preliminary water body salinity value, and if so, correcting the preliminary water body salinity value to obtain the final estimated result of the lake water body salinity; the present invention realizes the effective monitoring and management of lake salinity, and provides strong support for lake protection and sustainable development.

Description

Technical Field

[0001] The present invention relates to the technical field of lake ecology, and more specifically, to a method and system for dynamically monitoring the salinity stratification of lakes. Background Art

[0002] At present, water salinity is one of the important parameters of lakes, which is a basic parameter for describing the physical and chemical properties of lake water bodies and plays an important role in the water ecology, hydrology, and water environment of lakes. Lake salinity is one of the important indicators for measuring lake water quality and is affected by various factors. By scientifically measuring and analyzing lake salinity, the water quality status and its changing trends of lakes can be understood, providing a scientific basis for lake protection and rational utilization.

[0003] However, in the prior art, the monitoring process for lake water salinity is relatively cumbersome. Many lakes cannot carry out on-site actual measurement surveys, and it is impossible to accurately evaluate the lake water salinity. Moreover, the relevant hydrological and physical characteristics of lake water at different water levels vary greatly and cannot be directly calculated equivalently, resulting in a problem of low calculation accuracy.

[0004] Therefore, how to provide a method for dynamically monitoring the salinity stratification of lakes that can solve the above problems is an urgent problem for those skilled in the art. Summary of the Invention

[0005] In view of this, the present invention provides a method and system for dynamically monitoring the salinity stratification of lakes, which realizes the effective monitoring and management of lake salinity through means such as precise stratified monitoring, dynamic salinity estimation, correction mechanism, prediction of environmental change trends, and intelligent water replenishment decision-making, providing strong support for lake protection and sustainable development.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for dynamically monitoring the salinity stratification of lakes, comprising the following steps:

[0008] Obtain the geographical attribute data, hydrological characteristic data, and temperature data at different positions of the lake to be monitored, and perform stratified division in the vertical direction of the lake to be monitored according to the hydrological characteristic data and temperature data to obtain the corresponding division result;

[0009] Construct a corresponding water salinity calculation model according to the division result, and obtain the corresponding preliminary water salinity value according to the water salinity calculation model;

[0010] Judge whether it is necessary to correct the preliminary water salinity value. If necessary, correct the preliminary water salinity value to obtain the final estimated result of the lake water salinity.

[0011] Preferably, the specific process of correcting the preliminary salinity value of the water body to obtain the final estimated result of the lake water body salinity includes:

[0012] Obtain the climate characteristic data and environmental emergency data of the location where the lake to be monitored is located through big data, and analyze the climate characteristic data and environmental emergency data to obtain the corresponding climate analysis result and environmental emergency analysis result;

[0013] Construct an analysis model, input the climate analysis result and environmental emergency analysis result into the analysis model for processing to obtain the corresponding analysis result, where the analysis model is a fusion model of a decision tree and a convolutional neural network;

[0014] Determine whether it affects the salinity of the lake to be monitored according to the analysis result. If it does not affect, no correction is made.

[0015] Preferably, the specific process of correcting the preliminary salinity value of the water body to obtain the final estimated result of the lake water body salinity further includes:

[0016] If there is an impact, construct a salinity prediction model, and input the climate analysis result, environmental emergency analysis result and the preliminary salinity value of the water body into the salinity prediction model for processing to obtain the corresponding salinity prediction value;

[0017] Perform weighted fusion on the salinity prediction value and the preliminary salinity value of the water body to obtain the final estimated result of the lake water body salinity.

[0018] Preferably, it further includes:

[0019] Use the estimated result of the lake water body salinity for inversion to obtain the environmental change trend of the lake to be monitored.

[0020] Preferably, the specific processing process after obtaining the environmental change trend of the lake to be monitored includes:

[0021] Determine the salinity threshold according to the environmental change trend, and compare the estimated result of the lake water body salinity with the salinity threshold;

[0022] When the estimated result of the lake water body salinity is greater than or equal to the salinity threshold, perform water replenishment treatment on the lake to be monitored.

[0023] Preferably, the specific processing process of comparing the estimated result of the lake water body salinity further includes:

[0024] When the estimated result of the lake water body salinity is less than the salinity threshold, determine whether water replenishment treatment is required for the lake to be monitored in combination with the hydrological characteristic data and environmental change trend of the lake to be monitored.

[0025] Preferably, the specific process of constructing the water body salinity calculation model includes:

[0026] Determine the water quality parameters related to the water body salinity;

[0027] Construct a water body salinity calculation model, input the water quality parameters into the water body salinity calculation model for processing, and obtain the corresponding preliminary water body salinity value.

[0028] Preferably, the specific process of constructing the water body salinity calculation model further includes:

[0029] Construct a water body salinity calculation model, where the water body salinity calculation model includes a Transformer-XGBoost hybrid model and a stacking generalization layer.

[0030] The present invention also provides a lake salinity stratification dynamic monitoring system, including:

[0031] A data acquisition and division module, configured to acquire the geographical attribute data, hydrological characteristic data of the lake to be monitored, and temperature data at different positions, and perform vertical stratification division on the lake to be monitored according to the hydrological characteristic data and temperature data, and obtain the corresponding division result;

[0032] A data processing module, configured to construct a corresponding water body salinity calculation model according to the division result, and obtain the corresponding preliminary water body salinity value according to the water body salinity calculation model;

[0033] A data judgment module, configured to judge whether it is necessary to correct the preliminary water body salinity value, and if so, correct the preliminary water body salinity value to obtain the final lake water body salinity estimation result.

[0034] Through the above technical solutions, compared with the prior art, the present invention discloses a lake salinity stratification dynamic monitoring method and system, which has the following beneficial effects:

[0035] 1. By acquiring the geographical attribute data, hydrological characteristic data of the lake, and temperature data at different positions, and performing vertical stratification division, the present invention makes the monitoring more accurate to the specific lake water body level, which helps to understand the vertical distribution of salinity inside the lake and is of great significance for lake ecology and water quality management.

[0036] 2. By constructing a water body salinity calculation model according to the stratification result and calculating the preliminary salinity value, the present invention realizes the dynamic estimation of lake salinity, can reflect the real-time change of lake salinity, and provides timely data support for lake management.

[0037] 3. The present invention obtains climate characteristic data and environmental emergency data through big data and analyzes them to determine whether these factors affect the lake salinity. If there is an impact, the salinity prediction model is used to correct the preliminary salinity value to obtain a more accurate salinity estimation result. This correction mechanism improves the accuracy and reliability of salinity estimation.

[0038] 4. The present invention uses the lake water salinity estimation result for inversion, and the environmental change trend of the lake can be obtained. This helps to predict the future ecological status of the lake and provides a scientific basis for lake protection and management.

[0039] 5. The present invention determines the salinity threshold based on the lake water salinity estimation result and the environmental change trend, and determines whether water replenishment treatment is required for the lake accordingly. This intelligent water replenishment decision-making mechanism helps to maintain the water quality balance and ecological balance of the lake. When deciding whether to replenish water, not only the salinity threshold is considered, but also the hydrological characteristic data and environmental change trend of the lake are comprehensively analyzed. This comprehensive consideration method makes the water replenishment decision more scientific and reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0041] Figure 1 It is the overall flowchart of a method for dynamically monitoring the lake salinity stratification provided by the present invention;

[0042] Figure 2 It is the structural principle block diagram of a system for dynamically monitoring the lake salinity stratification provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0044] See Figure 1 As shown, the embodiments of the present invention disclose a method for dynamically monitoring the lake salinity stratification, including the following steps:

[0045] Obtain the geographical attribute data, hydrological characteristic data, and temperature data at different locations of the lake to be monitored, and perform stratified division in the vertical direction of the lake to be monitored according to the hydrological characteristic data and temperature data to obtain the corresponding division results. The geographical attribute data can be the location data of the lake to be monitored, and the hydrological characteristic data can include the lake net flow of the water body, water quality data, and spectral data;

[0046] Construct a corresponding water body salinity calculation model according to the division results, and obtain the corresponding preliminary water body salinity value according to the water body salinity calculation model;

[0047] Judge whether it is necessary to correct the preliminary water body salinity value. If necessary, correct the preliminary water body salinity value to obtain the final estimated result of the lake water body salinity.

[0048] Specifically, in the process of dividing the lake to be monitored in the vertical direction, it is achieved through multiple preset temperature threshold ranges.

[0049] In the process of establishing the water body salinity calculation model, the embodiments of the present invention can first, according to the division results in the vertical direction of the lake, use the correlation analysis method to study the relationship between different water quality parameters and water body salinity, and screen out the water quality parameters that have a significant correlation with salinity. The water quality parameters screened here are: conductivity, water body temperature, runoff data; construct a water body salinity calculation model, where the water body salinity calculation model includes a Transformer-XGBoost hybrid model and a stacking generalization layer (stacking layer). The Transformer model is used as a feature extractor to capture complex features in the data, and then these features are provided as inputs to the XGBoost model for processing. The stacking generalization layer can use the prediction results of multiple models as input features to generate the final result, improve the data processing ability of the model, and at the same time improve the calculation accuracy.

[0050] In a specific embodiment, the specific process of correcting the preliminary water body salinity value to obtain the final estimated result of the lake water body salinity includes:

[0051] Obtain the climate characteristic data and environmental emergency data at the location of the lake to be monitored through big data, and analyze the climate characteristic data and environmental emergency data to obtain the corresponding climate analysis results and environmental emergency analysis results. The climate characteristic data can include climate data such as rainfall and evaporation that may affect the water body, and the environmental emergency data can include data such as pollution leakage data that may affect water quality;

[0052] Construct an analysis model, input the climate analysis results and environmental emergency analysis results into the analysis model for processing to obtain the corresponding analysis results;

[0053] Determine whether it affects the salinity of the lake to be monitored according to the analysis result. If it does not affect, no correction is made.

[0054] Specifically, the analysis model can be a fusion model of a decision tree and a convolutional neural network, which can be used to comprehensively analyze various factors and their interactions in environmental emergency data, and improve the analysis ability.

[0055] In a specific embodiment, the specific process of correcting the initial salinity value of the water body to obtain the final estimated result of the lake water body salinity further includes:

[0056] If there is an impact, construct a salinity prediction model, and input the climate analysis result, environmental emergency analysis result, and the initial salinity value of the water body into the salinity prediction model for processing to obtain the corresponding salinity prediction value, where the salinity prediction model can be a convolutional neural network model;

[0057] Perform weighted fusion on the salinity prediction value and the initial salinity value of the water body to obtain the final estimated result of the lake water body salinity.

[0058] In a specific embodiment, it further includes:

[0059] Use the estimated result of the lake water body salinity for inversion to obtain the environmental change trend of the lake to be monitored.

[0060] In a specific embodiment, the specific processing process after obtaining the environmental change trend of the lake to be monitored includes:

[0061] Determine the salinity threshold according to the environmental change trend, and compare the estimated result of the lake water body salinity with the salinity threshold;

[0062] When the estimated result of the lake water body salinity is greater than or equal to the salinity threshold, perform water replenishment treatment on the lake to be monitored.

[0063] In a specific embodiment, the specific processing process of comparing the estimated result of the lake water body salinity further includes:

[0064] When the estimated result of the lake water body salinity is less than the salinity threshold, determine whether the lake to be monitored needs water replenishment treatment in combination with the hydrological characteristic data and the environmental change trend of the lake to be monitored.

[0065] See Figure 2 As shown, the embodiment of the present invention further provides a system using the lake salinity stratification dynamic monitoring method according to any one of the above embodiments, including:

[0066] A data acquisition and division module, configured to acquire the geographical attribute data, hydrological characteristic data, and temperature data at different positions of the lake to be monitored, and perform vertical stratification division on the lake to be monitored according to the hydrological characteristic data and the temperature data to obtain the corresponding division result;

[0067] A data processing module, configured to construct a corresponding water body salinity calculation model according to the division result, and obtain a corresponding preliminary water body salinity value according to the water body salinity calculation model;

[0068] A data judgment module, configured to judge whether it is necessary to correct the preliminary water body salinity value. If so, correct the preliminary water body salinity value to obtain a final estimated result of the lake water body salinity.

[0069] In the present specification, the various embodiments are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The same or similar parts among the various embodiments can be referred to each other. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0070] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A dynamic monitoring method for lake salinity stratification, characterized in that, Including the following steps: Obtain the geographical attribute data, hydrological characteristic data, and temperature data at different locations of the lake to be monitored, and perform layered division in the vertical direction of the lake to be monitored according to the hydrological characteristic data and temperature data to obtain the corresponding division result; Construct a corresponding water body salinity calculation model according to the division result, and obtain the corresponding preliminary water body salinity value according to the water body salinity calculation model; Judge whether it is necessary to correct the preliminary water body salinity value. If necessary, correct the preliminary water body salinity value to obtain the final estimated result of the lake water body salinity. The specific process includes: Obtain the climate characteristic data and environmental emergency data at the location of the lake to be monitored through big data, and analyze the climate characteristic data and environmental emergency data to obtain the corresponding climate analysis result and environmental emergency analysis result; Construct an analysis model, input the climate analysis result and environmental emergency analysis result into the analysis model for processing to obtain the corresponding analysis result, where the analysis model is a fusion model of a decision tree and a convolutional neural network; Determine whether it affects the salinity of the lake to be monitored according to the analysis result. If it does not affect, no correction is performed; If there is an impact, construct a salinity prediction model, and input the climate analysis result, environmental emergency analysis result, and the preliminary water body salinity value into the salinity prediction model for processing to obtain the corresponding salinity prediction value; Perform weighted fusion on the salinity prediction value and the preliminary water body salinity value to obtain the final estimated result of the lake water body salinity.

2. The dynamic monitoring method for lake salinity stratification according to claim 1, characterized in that, It also includes: Use the estimated result of the lake water body salinity for inversion to obtain the environmental change trend of the lake to be monitored.

3. The dynamic monitoring method for lake salinity stratification according to claim 2, wherein The specific processing process after obtaining the environmental change trend of the lake to be monitored includes: Determine the salinity threshold according to the environmental change trend, and compare the estimated result of the lake water body salinity with the salinity threshold; When the estimated result of the lake water body salinity is greater than or equal to the salinity threshold, perform water replenishment treatment on the lake to be monitored.

4. The dynamic monitoring method for lake salinity stratification according to claim 3, characterized in that, The specific processing process of comparing the estimated result of the lake water body salinity with the salinity threshold also includes: When the estimated result of the lake water body salinity is less than the salinity threshold, determine whether water replenishment treatment is required for the lake to be monitored in combination with the hydrological characteristic data and environmental change trend of the lake to be monitored.

5. A method for dynamically monitoring the salinity stratification of a lake according to claim 1, characterized in that, The specific process of constructing the water body salinity calculation model includes: Determine the water quality parameters related to the water body salinity; Construct a water body salinity calculation model, input the water quality parameters into the water body salinity calculation model for processing to obtain the corresponding preliminary water body salinity value.

6. The dynamic monitoring method for lake salinity stratification according to claim 5, wherein The specific process of constructing the water body salinity calculation model also includes: Construct a water body salinity calculation model, where the water body salinity calculation model includes a Transformer-XGBoost hybrid model and a stacking generalization layer.

7. A system using the method for dynamically monitoring the lake salinity stratification according to any one of claims 1-6, characterized in that, Including: A data acquisition and division module, which is used to acquire the geographical attribute data, hydrological characteristic data of the lake to be monitored, and temperature data at different positions, and perform layered division in the vertical direction of the lake to be monitored according to the hydrological characteristic data and the temperature data, so as to obtain the corresponding division result; A data processing module, which is used to construct a corresponding water body salinity calculation model according to the division result, and obtain a corresponding initial water body salinity value according to the water body salinity calculation model; A data judgment module, which is used to judge whether it is necessary to correct the initial water body salinity value. If necessary, the initial water body salinity value is corrected to obtain the final estimated result of the lake water body salinity.

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