Quantitative Assessment of the Ecological Vulnerability of Baiyangdian Wetlands in the North China Plain

Quantitative assessment of vulnerability is a core aspect of wetland vulnerability research. Taking Baiyangdian (BYD) wetlands in the North China Plain as a study area and using the ‘cause-result’ model, 23 representative indicators from natural, social, sci-tech and economic elements were selected to construct an indicator system. A weight matrix was obtained by using the entropy weight method to calculate the weight value for each indicator. Based on the membership function in the fuzzy evaluation model, the membership degrees were determined to form a fuzzy relation matrix. Finally, the ecological vulnerability was quantitatively assessed based on the comprehensive evaluation index calculated by using a composite operator to combine the entropy weight matrix with the fuzzy relation matrix. The results showed that the ecological vulnerability levels of the BYD wetlands were comprehensively evaluated as Grade II, Grade Ⅲ, Grade IV, and Grade Ⅲ in 2010, 2011-2013, 2014, and 2015-2017, respectively. The ecological vulnerability of the BYD wetlands increased from low fragility in 2010 to general fragility in 2011-2013, and to high fragility in 2014, reflecting the fact that the wetland ecological condition was degenerating from 2010 to 2014. The ecological vulnerability status then turned back into general fragility during 2015-2017, indicating that the ecological situation of the BYD wetlands was starting to improve. However, the ecological status of the BYD wetlands on the whole is relatively less optimistic. The major factors affecting the ecological vulnerability of the BYD wetlands were found to be industrial smoke and dust emission, wetland water area, ammonia nitrogen, total phosphorus, rate of industrial solid wastes disposed, GDP per capita, etc. This illustrates that it is a systematic project to regulate wetland vulnerability and to protect regional ecological security, which may offer researchers and policy-makers specific clues for concrete interventions.