Remote Sensing Monitoring And Pollution Evaluation Of Heavy Metals In Winter Wheat Growing Area In Northern Plain Of Longkou City

In recent years,frequent heavy metal pollution events have made people pay more attention to the heavy metal pollution in grain growing areas in China.After the soil environment is polluted by heavy metals,heavy metals are difficult to transform and decompose in the soil environment,and easy to accumulate,which is very harmful to the soil and very lasting,and cannot guarantee the safe and stable agricultural production.In addition,heavy metals can be absorbed by crops and then converted into compounds more harmful to human beings,posing a threat to human survival.Therefore,it is particularly important to effectively monitor heavy metals in grain-growing areas.To develop an efficient,economical and rapid heavy metal monitoring method and to explore the heavy metal pollution situation in grain planting areas,the winter wheat growing area in the northern plain of Longkou City,the main grain producing area in Jiaodong,Shandong Province,is taken as the research area.Under the support of the National Natural Science Foundation of China(NSFC)project "Remote sensing monitoring research on farmland ecological security in farmland area based on surface parameters"(No.41371395),61 winter wheat samples and 125 soil samples were collected systematically,and the canopy reflectance spectra and soil reflectance spectra of winter wheat were measured on the spot with ground object spectrometer.A variety of spectral estimation models of 8 heavy metals(As,Cd,Cr,Cu,Hg,Ni,Pb,and Zn)in soil and winter wheat leaves were established based on the field measured soil reflectance spectra,canopy spectral data of winter wheat and laboratory heavy metal test data,and geostatistics and multivariate analysis combined with multi-source data were used to analyze the sources,spatial distribution and pollution status of various heavy metals.The main research results were as follows:(1)In the estimation of soil heavy metal content by field measured soil spectra,back propagation neural network(BPNN)model had the strongest estimation ability for eight kinds of heavy metals,followed by geographically weighted regression(GWR)model and partial least squares(PLSR)model,and the stepwise multiple linear regression(SMLR)model had the worsteffect.At the same time,the estimation ability of soil original reflectance spectra(R)had been improved to some extent after spectral transformation and information extraction.The establishment of neural network model with first-order derivative of reflectivity(FDR)as independent variable was the optimal estimation model of As,Cu,Hg,Ni,Pb,and Zn.The BPNN model with second-order derivative of reflectivity(SDR)as independent variable was the optimal model of heavy metal Cd and Cr.(2)When estimating the heavy metal content in winter wheat leaves,it was found that the BPNN model had the strongest ability to estimate the heavy metal content in winter wheat leaves.The BPNN model established with the SDR as the independent variable was the optimal estimation model of Cd and Zn.For As,Ni,Hg,and Pb,the best estimation effect was achieved by establishing the BPNN model with the FDR as the independent variable.The BPNN model established with spectral parameters of the three sides(SPs)as independent variables was the optimal model of Cr and Cu.(3)Cr,Ni,and As had similar spatial distribution,with a low content in the northwest,a high content in the northeast and a high content in the south.It mainly came from the parent material of the granite and was greatly affected by topography.For heavy metal Hg,traffic emissions and industrial pollution,as well as the lower terrain in the north and west,led to the concentration of Hg in the central urban area,the north and parts of the west.Soil parent material,industrial and agricultural activities had an impact on the enrichment of heavy metal Zn,so that it was mainly distributed in the northwest and the south.Pb agglomeration occurred in the southwest and northeast,mainly from industrial and agricultural activities,but little influenced by the geological background.Cd was mainly distributed in the central and southern part of the study area,which was greatly affected by industry and elevation.For Cu,it was mainly distributed in the northwest and southeast,and was greatly affected by industrial and agricultural activities.(4)According to the results of single factor pollution index,comprehensive pollution index evaluation and potential ecological risk evaluation,the pollution level of heavy metals in the soil in this study area was Cd>Pb>Hg>Cu>Ni>Zn>Cr>As,successively.Nearly half of the sampling points were below the pollution warning value,some sampling sites exceeded slight pollutionlevel,only a few of the sites reached moderate pollution levels.The level of ecological risk in most areas of the study area was low,and only the western and northeastern regions were mainly at the moderate level of ecological risk.Therefore,great attention should be paid to the soil environmental quality in these areas.