Research on ecological environment impact assessment based on PSR and cloud theory in Dari county, source of the Yellow River

In order to reasonably evaluate the ecological environment of Dari County in the source region of the Yellow River, the characteristics and actual conditions of Dari County’s ecological environment are taken into account, and the principles of representativeness, scientificity, operability and systematicness of index are followed. An evaluation index system is established for Dari County based on the Pressure-State-Response (PSR) conceptual framework. Combining the Analytic Hierarchy Process (AHP) with the cloud model, an ecological environment evaluation model for Dari County is established, and the ecological environment of Dari County is quantitatively evaluated. The model organically combines the ambiguity and randomness of the uncertainty concept. It not only describes the ambiguity of the evaluation level with a membership function, but also considers the randomness of the membership itself using the concept of superentropy, which is more in line with the actual evaluation object. The results indicate that the ecological situation of Dari County is in a ‘general’ state that should be urgently protected for sustainable development, and land degradation is the most important factor affecting the ecological environment of Dari County.


INTRODUCTION
The source region of the Yellow River is located in southwest Qinghai Province, the hinterland of the Qinghai-Tibet Plateau. It is an important water conservation area and ecological barrier of the Yellow River, as well as one of the most special and fragile areas in China. With the influence of climate change and human activity, the ecological environment in parts of the source Yellow River areas have suffered damage in recent years. To protect the ecological environment, it is necessary to know and quantitatively evaluate the current state of the regional ecological environment.
The difficulty is how to select the corresponding evaluation index system according to the regional characteristics and make a reasonable quantitative analysis. In view of this, assessing the state of the ecological environment in the river source area is of great significance for its protection and restoration. This paper selects the 'Pressure-State- River region, such as the uneven spatial and temporal distribution of climate and rainfall, grassland degradation, land desertification, and human activities, and its ecological impacts. Based on the latest research results, this paper attempts to put forward the PSR framework ecoenvironmental impact assessment index system in Dari County, the source region of the Yellow River.
In the existing researches, the domestic ecological environment assessment of river basins, plateau regions or eco-environment impacts of projects are mainly focused at home, while ecological impact assessments from certain The fuzzy comprehensive method divides the fuzzy classification boundary of indexes, but the calculated membership degree is easily disturbed by subjective conditions. The system dynamics method is to build a model around the problem; results will vary greatly because of different models for same problem. In summary, the existing quantitative evaluation methods and models can obtain regional ecological environment impact level, but cannot explain the level con-

STUDY AREA AND DATA SOURCE Study area
Dari County is located in the Sanjiangyuan District ( Figure 1). The source area of the river is located in the southwest of Qinghai Province in the hinterland of the Qinghai-Tibet Plateau and is the source of the Yangtze, Yellow and Lancang Rivers. It is an ecological barrier for the ecological environment and regional sustainable development of the middle and lower reaches of China's rivers and Southeast Asian countries. Dari County is the core area of the Sanjiangyuan, and its ecological location is very important. It is of great significance for ensuring the safety of the ecological environment of the Sanjiangyuan and promoting the development of the regional ecological environment (He et al. ). In recent years, regional climate change and intensified human activities have caused a decrease in precipitation, which has reduced water conservation functions, reduced water production, and reduced forest and grass coverage. Regional socio-economic development has had a serious impact (details in Table 1).

Data source
The basic data used in this paper is collected from According to the PSR model framework, pressure index refers to the interference and pressure factors from external conditions in the evaluation index system constructed, state index is used to reflect the ecological environment, and the response category refers to the impact of the ecosystem under the current ecological environment pressure (Long et al. ). Interconnect the three aspects of pressure-stateresponse to build the framework of the ecological environment impact assessment system, and select specific indicators to form a three-level indicator system.

Evaluation index system for Dari County
The construction of an assessment index system is the basis for conducting an ecological environment impact assessment. But considering that different regions have different characteristics, a specific research indicator system and evaluation model need to be carried out for the study area, based on its ecological environment characteristics and actual conditions. Details of the eco-environmental impact assessment index system of Dari County are in Table 2.
Apart from the influence of water resources, mainly climate factors, grassland degradation and land desertification are major factors that cause ecological and environmental    Table 3.

Cloud model
The cloud model (Lujun & Yaping ) is an uncertainty model proposed by Academician Li Deyi that can be used to represent both a certain qualitative concept and its quantitative concept. It shows an advantage in the analysis of the randomness and ambiguity of the thing itself for unified analysis. The model is a new mathematical model, which is characterized by a combination of normal distribution and >5,000 2,500-5,000 1,000-2,500 <1,000 (1) As the boundary of each level, x ij belongs to both the previous level and the next level, so the boundary value is equal to the membership degree of the upper and lower levels, thereby obtaining the entropy value: (2) The size of He is generally obtained based on the entropy value and experience, which mainly reflects the thickness of the cloud layer, which is 0.01 here: Ecological environment impact assessment model based on cloud model In the process of quantitatively measuring the regional ecological environment, the quantitative description of its evaluation indicators has both ambiguity and randomness.
If only the ambiguity or randomness of the objects in the regional ecological environment evaluation is considered, then an accurate evaluation result is expected. The purpose is difficult to achieve, so it is necessary to introduce a model method that can take into account both ambiguity and randomness. This study builds on the normal cloud model theory and builds a comprehensive evaluation model based on the normal cloud. The construction of the evaluation model is mainly divided into the following parts: ( Figure 2).
• Evaluate each index in the system and establish a fuzzy matrix R. The element rij in R represents the degree of membership of the i-th element in the system.
• Take the quantitative value rij of each index as the input for the cloud generator to get a set of cloud drops (a, y).
Execute the cloud generator multiple times, and determine the cloud membership matrix Z ¼ (Z ij ) n * m .
Cloud generator algorithm: First set Ex as the expected value and He as the standard deviation to generate a normal random number En ', and then set Ex as the expected value and En' as the standard deviation to generate a normal random number a. After the degree of certainty is calculated by using the (Equation (4)) N cloud droplets are generated by repeating N times. The calculation principle is shown in Figure 3.

Determination of indicator weights
In the process of regional eco-environmental assessment, the degree of influence of different evaluation factors on the evaluation results is different. Therefore, it is first necessary to determine the degree of influence (weight) of each evaluation factor on the evaluation results. Hierarchical analysis method (AHP) is used to determine the weight of each evaluation index in the ecological environment evaluation index system. According to the steps of the analytic hierarchy process, first construct a hierarchical hierarchy structure, namely the target layer, the criterion layer and the factor layer of the evaluation index system, and then compare the two elements in turn to construct a judgment matrix, and then calculate the relative weights, and then make it consistent. The sex test is terminated after passing the test. (Changyu et al. ).
After the largest eigenvalue λ and the eigenvector w are calculated by the sum-product method, the weights of each index are acquired. And then a consistency check for each index is conducted. If the judgment matrix meets check, the calculated weight is available for use. The calculation steps are as follows: • Normalize the vector • Normalize • Calculate the largest eigenvalue λ CR ¼ CI RI (10)

Evaluation process
The AHP method is a combination of qualitative and quantitative methods for seeking weights. It can test and reduce the influence of subjective factors, making the analysis and evaluation more objective and scientific. At the same time, the cloud model can reduce the impact of ambiguity and randomness in the evaluation process. Coupling the AHP method with the cloud model can take advantage of the two and apply it to the evaluation of uncertain systems.
The evaluation process is as follows.  Table 2 is represented as a normal cloud, as shown in Table 4.
According to the evaluation standards of each index, the forward cloud generator model is used to obtain the standard normal cloud model parameters of each index by calculating Ex, En, and He of each index corresponding to different evaluation levels ( which reflects the fuzzy uncertainty between the index value and the level to be determined ( Figure 5).
The cloud certainty of each index is calculated through forward cloud generator to form a membership matrix based on the preliminary calculating results, as shown in Table 6.
The weight of each index in the ecological environment impact assessment is calculated by the above-mentioned   (11).
The four levels' comprehensive membership of ecological environment assessment in Dari County is calculated based on the formula. According to the maximum value determination method, the evaluation level belongs to 'general' (

CONCLUSIONS
This paper evaluates the ecological and environmental impacts in Dari County. The evaluation results intuitively reflect the ecological environment. The following conclusions are mainly drawn.
• As can be seen in the evaluation results, the ecological environment in Dari County is in a 'general' state. It urgently needs to be improved to reach a sustainable development state.
• As can be seen in the PSR index system, the land degradation rate in Dari County is particularly serious. In future work, the prevention of 'black soil beach' and the improvement of vegetation coverage, such as forest rate, in Dari County should be paid more attention, the problems of soil erosion, land salinization should be concerned, and the pressure on the local ecosystem due to human activities should be effectively controlled.