CN114548754A - Wetland buffer area water ecological health evaluation method based on trend judgment - Google Patents
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Abstract
The invention discloses a wetland buffer area water ecological health evaluation method based on trend judgment, which comprises the following steps: s1: determining influence factors based on Meta analysis: setting search keywords to collect experimental observation data of potential influence factors, obtaining key influence factors of water ecological health through environmental factor correlation analysis, and calculating influence factor weight; s2: collecting index data; s3: establishing a prediction model based on machine learning; s4: and (3) trend judgment: and inputting the predicted values of the key influence factors and the influence weights of different influence factor types into the water ecological health evaluation model to obtain the water ecological health status n years later, and taking the water ecological health status as the prediction evaluation of the current water ecological health status. The method can obtain the influence factors with strong correlation and sensitive influence, furthest eliminates the limitation caused by regional scale investigation, evaluates the current water ecological health at a future view angle, and can better reflect the development trend and the current state of the current water ecological health state.
Description
Technical Field
The invention belongs to the field of water ecological health evaluation, and mainly relates to a wetland buffer zone water ecological health evaluation method based on trend judgment.
Background
The wetland refers to an area where the wetland organisms grow due to over-wet or frequent water accumulation on the ground surface. The wetland ecosystem is a unified whole consisting of wetland plants, animals inhabiting the wetland, microorganisms and the environment thereof. The wetland has multiple functions: protecting biological diversity, regulating runoff, improving water quality, regulating microclimate, providing food and industrial raw materials, providing tourist resources and the like. The water quality evaluation refers to that according to an evaluation target, corresponding water quality parameters, water quality standards and evaluation methods are selected to evaluate the water quality utilization value and the water treatment effect. The water quality evaluation is a basic work for reasonably developing, utilizing and protecting water resources. And adopting corresponding water quality standards according to different evaluation types. Evaluating the water environment quality by adopting a ground water environment quality standard; evaluating the quality of the aquaculture water body by adopting a fishery water quality standard; evaluating the water quality of a water source of a centralized domestic drinking water taking point, and using the ground water sanitary standard; evaluating the water for farmland irrigation, and adopting the water quality standard of farmland irrigation. Generally, various water quality standards issued by national or local governments are used as evaluation standards.
Most current evaluation methods are based on-site monitoring sampling and evaluation of the water ecological health status of the monitored space-time, which is not prospective. In the aspect of evaluation factor selection, single type influence is mostly considered, and the overall water ecological health evaluation has one-sided influence, however, for multi-factor selection, due to the spatial and temporal limitation of sampling, corresponding weight cannot be determined according to the actual influence degree, and the loss of parameter information expression is caused. In addition, machine learning is an advanced and efficient means in predicting forecasts, but a general problem with machine learning is that its predictions are often not based on physical meaning. That is, the algorithm simply looks for a correlation between input and output, but sometimes this correlation may be "false" or may give erroneous results, which when used directly in an assessment of water ecology, may result in the algorithm model failing to handle the results when the relationship between input and output changes.
Disclosure of Invention
The invention aims to provide a wetland buffer area water ecological health evaluation method based on trend judgment aiming at the problems in the prior art.
The invention aims to realize the purpose, and the method for evaluating the ecological health of the water in the wetland buffer area based on the trend judgment is characterized by comprising the following steps of:
s1: determining influence factors based on Meta analysis: setting retrieval keywords, carrying out literature investigation in an academic database, collecting experimental observation data of different types of potential influence factors, and obtaining key influence factors of water ecological health through environmental factor correlation analysis; obtaining influence weights of different factor types and influence weights of different influence factors in the same type through weight analysis;
s2: collecting index data: collecting a multi-year dataset of key influencing factors of the target area;
s3: establishing a prediction model based on machine learning: dividing a multi-year data set of key influence factors into a training set and a prediction set according to different time sliding windows, and respectively establishing prediction models corresponding to the key influence factors by a machine learning method;
s4: and (3) trend judgment: the collected overall data of the key influence factors are used as a prediction basis, and the corresponding prediction model is input to obtain the predicted value of the key influence factors n years later; after the predicted values of the key influence factors are graded, the predicted values are matched with the different influence factor types and the influence weights corresponding to the different influence factors and input into a water ecological health evaluation model, and the water ecological health condition n years later is obtained and is used as the prediction evaluation of the current water ecological health condition.
Preferably, the keywords are "phytoplankton", "zooplankton", "diversity", "aquatic ecohealth".
Preferably, the weight analysis in S1 is a variance analysis.
Preferably, the environmental factor correlation analysis in S1 is to calculate the direct correlation between the influencing factor and the water ecological health assessment index by using a maximum information coefficient MIC, which is calculated as follows:
in the formula, X, Y are respectively an environmental impact factor and a water ecological health evaluation index; b is variable, and is generally selected to be 0.6 power of the data volume.
Preferably, the water ecological health evaluation model in S4 is a water ecological health index model, wherein the water ecological health index M is calculated as follows:
in the formula, KjAs classification weight of the j-th class index, GjiIs the index weight of the ith index in the jth index class, XjiAnd assigning scores to the indexes of the ith index in the jth index.
Preferably, the scoring system assigned by the index can refer to the water ecological health assessment technical specification DB 11/T1722-2020.
The invention discloses a wetland buffer area water ecological health evaluation method based on trend judgment, which has the following advantages: (1) potential influence factors of water ecological health are collected by integrating the existing research, and key influence factors are judged on a global scale based on Meta analysis, so that influence factors with stronger correlation and more sensitive influence are obtained, and the limitation caused by regional scale investigation is eliminated to the maximum extent; (2) based on the time series data set of the existing key influence factors, the future key influence factors are predicted through machine learning, and the prediction precision is improved; (3) by evaluating the future prediction data of the key influence factors, the current water ecological health evaluation under the future visual angle is obtained, and the evaluation can better reflect the development trend and the health state of the current water ecological health state.
Drawings
Fig. 1 is a schematic diagram of the trend judgment-based wetland buffer area water ecological health evaluation method.
Detailed Description
A wetland buffer zone water ecological health evaluation method based on trend judgment is characterized by comprising the following steps:
s1: determining influence factors based on Meta analysis: setting phytoplankton, zooplankton, diversity and water ecological health as retrieval keywords, performing literature investigation in an academic database, collecting experimental observation data of different types of potential influence factors, and obtaining influence weights of different factor types and influence weights of different influence factors in the same type through variance decomposition analysis; obtaining key influence factors of water ecological health through correlation analysis of environmental factors;
the environmental factor correlation analysis is to calculate the direct correlation between the influence factors and the water ecological health evaluation indexes through the maximum information coefficient, and the calculation mode of the maximum information coefficient MIC is as follows:
in the formula, X, Y are respectively an environmental impact factor and a water ecological health evaluation index; b is a variable, and the power of 0.6 of the data volume is generally selected.
S2: collecting index data: collecting a multi-year dataset of key influencing factors of the target area;
s3: establishing a prediction model based on machine learning: dividing a multi-year data set of key influence factors into a training set and a prediction set according to different time sliding windows, and respectively establishing prediction models corresponding to the key influence factors by a machine learning method;
s4: and (3) trend judgment: the collected overall data of the key influence factors are used as a prediction basis, and the corresponding prediction model is input to obtain the predicted value of the key influence factors n years later; inputting the predicted values of the key influence factors and the influence weights of different influence factor types into a water ecological health evaluation model to obtain the water ecological health condition n years later, and taking the water ecological health evaluation model as the prediction evaluation of the current water ecological health condition, wherein the water ecological health evaluation model is a water ecological health index model, and the calculation mode of the water ecological health index M is as follows:
M＝∑Kj(ΣGjiXji)
in the formula, KjAs a classification weight for the j-th class index, GjiIs the index weight of the ith index in the jth index class, XjiAnd assigning scores to the indexes of the ith index in the jth index. The scoring system for the index assignment can refer to the water ecological health evaluation technical specification DB 11/T1722-2020.
Claims (6)
1. A wetland buffer zone water ecological health evaluation method based on trend judgment is characterized by comprising the following steps:
s1: determining influence factors based on Meta analysis: setting retrieval keywords, carrying out literature investigation in an academic database, collecting experimental observation data of different types of potential influence factors, and obtaining key influence factors of water ecological health through environmental factor correlation analysis; obtaining influence weights of different factor types and influence weights of different influence factors in the same type through weight analysis;
s2: collecting index data: collecting a multi-year dataset of key influencing factors of the target area;
s3: establishing a prediction model based on machine learning: dividing a multi-year data set of key influence factors into a training set and a prediction set according to different time sliding windows, and respectively establishing prediction models corresponding to the key influence factors by a machine learning method;
s4: and (3) trend judgment: the collected overall data of the key influence factors are used as a prediction basis, and the corresponding prediction model is input to obtain the predicted value of the key influence factors n years later; after the predicted values of the key influence factors are graded, the predicted values are matched with the different influence factor types and the influence weights corresponding to the different influence factors and input into a water ecological health evaluation model, and the water ecological health condition n years later is obtained and is used as the prediction evaluation of the current water ecological health condition.
2. The trend judgment based wetland buffer area water ecological health evaluation method according to claim 1, characterized in that: the keywords are phytoplankton, zooplankton, diversity and aquatic ecological health.
3. The trend judgment based wetland buffer area water ecological health evaluation method according to claim 1, characterized in that: the weight analysis in S1 is a variance decomposition analysis.
4. The trend judgment based wetland buffer area water ecological health evaluation method according to claim 1, characterized in that: in the S1, the environmental factor correlation analysis is to calculate a direct correlation between the influencing factor and the water ecological health assessment indicator through a maximum information coefficient MIC, and the maximum information coefficient MIC is calculated as follows:
in the formula, X, Y are respectively an environmental impact factor and a water ecological health evaluation index; b is variable, and is generally selected to be 0.6 power of the data volume.
5. The trend judgment based wetland buffer area water ecological health evaluation method according to claim 1, characterized in that: the water ecological health evaluation model in the S4 is a water ecological health index model, wherein the water ecological health index M is calculated in the following manner:
M＝∑Kj(ΣGjiXji)
in the formula, KjAs a classification weight for the j-th class index, GjiIs the index weight of the ith index in the jth index class, XjiAssigning a score to an indicator of an ith indicator of the jth indicator。
6. The trend judgment based wetland buffer area water ecological health evaluation method according to claim 5, characterized in that: the scoring system for the index assignment can refer to the water ecological health evaluation technical specification DB 11/T1722-2020.
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