A Bayesian Network Model And Its Application On Ecological Environment Vulnerability Assessment

The Yellow River delta(YRD)is a typical coastal wetland in northern China with rich natural resources,unique habitats and landscapes.On the other hand,it is the important relay stations,wintering habitat and breeding place for migrating birds in eastern Asia.In recent years,the eco-environment in Yellow River delta became more and more vulnerable due to intensive human innervations and natural variability.Therefore,it is necessary and urgent to fully assess the ecological and environmental vulnerability and clearly identifying the driving factors.In this thesis,a Bayesian network(BN)model was constructed and utilized to assess and predict the ecological and environmental vulnerability in YRD.Firstly,based on previous studies about ecological and environmental vulnerability in this area,an assessment framework has been proposed including 8 factors criteria layerindices and 11 factors index level indices,where all indices were carefully screened and selected.Secondly,a Bayesian network model was constructed based on the index system.BN model is an uncertain knowledge representation model based on probability theory and graph theory,which plays an important role in uncertain reasoning.Cross validation was also applied to select the optimal model,with which both the current status of vulnerability was assessed.Specifically,the spatial distribution and causes of ecological and environmental vulnerability was reasoned using BN model.Moreover,the sensitivity analysis showed that NDVI,land use and vegetation types were the three primary factors that determine ecological and environmental vulnerability significantly.Finally,different scenarios about human activities,climate change and NDVI change were set and predict the evaluation of ecological and environmental vulnerability in YRD by considering the local economy and social developments so that suggestions were proposed to solve the ecological and environmental problems.The analysis of the current situation shows that the study area is dominated by slight vulnerability and mild vulnerability,which accounts for about 2/3 of the total area,and the moderate vulnerability is about 2/15,and the severe vulnerability and extreme vulnerability are about 1/5 of the total area.Through the performance analysis of the model,a good model with an error rate of only 17.35% is selected,which lays the foundation for the scenario analysis.A series of scenario analysis shows that the uncertain knowledge representation of ecological vulnerability prediction is an effective method based on Bayesian network,which provides a new idea for the prediction of ecological vulnerability in the Yellow River delta.In summary,the Bayesian network model can integrate various ecological environment information,and it can effectively fusion these information,besides it can infer a causal relationship between each factor,which provides a new idea for wetland ecological environment vulnerability prediction.