基于地理最优相似性的土壤重金属镉含量空间预测

Spatial prediction of soil heavy metal cadmium content based on geographically optimal similarity

以地理相似性定律为基础,利用野外采集的40个土壤样本数据,结合环境辅助变量构建地理最优相似性(GOS)模型,对研究区域重金属镉含量及其空间分布进行预测研究,并将预测结果与偏最小二乘回归(PLSR)、随机森林(RF)和通用克里格(UK)模型的结果进行对比分析。研究结果表明:研究区内土壤样本镉质量分数均值(0.432 mg/kg)比背景值大,接近中度污染水平(污染指数为2.18),区域土壤生态环境受到一定的威胁;GOS预测结果的决定系数为0.668,均方根误差和平均绝对误差分别为0.096和0.080,在4个预测模型中表现最佳;区域重金属Cd质量分数从东北部向西南部递减,高值分布于河流沿岸和人类活动密集区域,反映出人类活动是导致研究区内土壤重金属分异的主要因素。

Based on the law of geographic similarity,40 soil samples collected in the field were used to construct a geographically optimal similarity(GOS)model by combining environmental auxiliary variables to predict the heavy metal cadmium content and its spatial distribution in the study area,and the prediction results were compared and analyzed with those of partial least squares regression(PLSR),random forest(RF)and universal kriging(UK)models.The results show that the mean cadmium content of soil samples in the study area(0.432 mg/kg)is greater than the background value,close to the moderate pollution level(pollution index of 2.18),and the regional soil ecology is under some threat.The GOS prediction results have a coefficient of determination of 0.668,and the root-mean-square error and the mean absolute error are 0.096 and 0.080,which are the best among the four prediction models.The spatial prediction results of the GOS show that the regional content of the heavy metal Cd decreases from the northeast to southwest,and the high values are distributed along rivers and in areas with intensive human activities,reflecting that human activities are the main factors leading to soil heavy metal differentiation in the study area.