Research On Prediction Of Soil Heavy Metal Pollution And Evaluation-early Warning Of Ecological Risk

Soil,as one of the living natural resources that humans depend on,plays an important role in the survival and development of human beings.However,in recent years with the intensification of soil heavy metal pollution,the environmental quality has further deteriorated,constantly threatening the sustainable development of the soil.With the rapid development of social progress and industrialization,the impact of heavy metal pollution in the soil has become more obvious.The reasonable and accurate prediction and early warning of soil heavy metals can provide technical support for scientific management decisions of farmland and safe production of agricultural products.Therefore,predicting the heavy metal content in the soil and evaluating and early warning of the ecological pollution caused by it is a top priority.In this paper,the Binzhou demonstration area of the Yellow River Delta is selected as a research area,and the soil environment of the farmland in this area is taken as the analysis object.A short-term prediction model for heavy metal content in soil based on a time-series exponential smoothing model and a mid-to-long term prediction model for soil heavy metals based on a grey model are established and ecological risk warning is carried out.The main works of the thesis are as follows:(1)Exponential smoothness prediction model.A time-series index smoothing prediction model was established,the error data corresponding to six soil heavy metal content prediction models for lead,mercury,copper and so on can be calculated through accuracy analysis error monitoring.(2)Gray prediction model.According to the residual error test,the average relative error of model fitting is obtained,and the residual of Cd is less than 0.2 on average and meets the general requirements,which can make less accurate predictions.The prediction of the remaining heavy metals is less than 0.1,which meets the higher requirements,and can also make accurate predictions.Through the model residual test after the combination of the inspection error test index level criteria,we can see that the model has reached a good prediction level.(3)Based on the method of geoaccumulation index and Hakanson potential ecological risk index,the evaluation of regional soil heavy metal ecological risk was conducted.Calculation results show that the Hg metal in the study area contributes the most to soil pollution,and its potential ecological risk index is relatively high which is at medium potential ecological risk.The potential ecological risks of six soil heavy metals are at a low potential ecological risk and will not cause serious environmental pollution in the short term.According to the ecological risk warning index method,it can be seen from the proportion of sampling points that the overall ecological environment of the study area is good,but Hg and Cd reach the light police level at some sampling points.Therefore,it is still necessary to intensify monitoring to prevent heavy metals from threatening the ecological environment in the study area.(4)The system uses Visual Studio 2015 from Microsoft and AcrGIS Server 10.0 from ESRI as a development platform,and uses C language as a development language.It realizes prediction of heavy metal content in agricultural soil and ecological risk assessment and early warning of heavy metals in soil.