Concentrations of Iron (Fe), As, and Cu in soil samples from the fields near the Baoshan Mine in Hunan Province, China, were analyzed and soil spectral reflectance was measured with an ASD FieldSpec FR spectroradiometer (Analytical Spectral Devices, Inc., USA) under laboratory condition. Partial least square regression (PLSR) models were constructed for predicting soil metal concentrations. The data pre-processing methods, first and second derivatives (FD and SD), baseline correction (BC), standard normal variate (SNV), multiplicative scatter correction (MSC), and continuum removal (CR), were used for the spectral reflectance data pretreatments. Then, the prediction results were evaluated by relative root mean square error (RRMSE) and coefficients of determination (R 2 ). According to the criteria of minimal RRMSE and maximal R 2 , the PLSR models with the FD pretreatment (RRMSE = 0.24, R 2 = 0.61), SNV pretreatment (RRMSE = 0.08, R 2 = 0.78), and BC-pretreatment (RRMSE = 0.20, R 2 = 0.41) were considered as the final models for predicting As, Fe, and Cu, respectively. Wavebands at around 460, 1 400, 1 900, and 2 200 nm were selected as important spectral variables to construct final models. In conclusion, concentrations of heavy metals in contaminated soils could be indirectly assessed by soil spectra according to the correlation between the spectrally featureless components and Fe; therefore, spectral reflectance would be an alternative tool for monitoring soil heavy metals contamination.
REN Hong-YanZHUANG Da-FangA. N. SINGHPAN Jian-JunQIU Dong-ShengSHI Run-He
Wind erosion is one of the major environmental problems in semi-arid and arid regions. Here we es- tablished the Tariat-Xilin Gol transect from northwest to southeast across the Mongolian Plateau, and selected seven sampling sites along the transect. We then estimated the soil wind erosion rates by using the ^(137)Cs tracing technique and examined their spatial dynamics. Our results showed that the ^(137)Cs inventories of sampling sites ranged from 265.63±44.91 to 1279.54±166.53 Bq·m^(-2), and the wind erosion rates varied from 64.58 to 419.63 t·km^(-2)·a^(-1) accordingly. In the Mongolia section of the transect (from Tariat to Sainshand), the wind erosion rate increased gradually with vegetation type and climatic regimes; the wind erosion process was controlled by physical factors such as annual precipitation and vegetation coverage, etc., and the impact of human activities was negligible. While in the China section of the transect (Inner Mongolia), the wind erosion rates of Xilin Hot and Zhengxiangbai Banner were thrice as much as those of Bayannur of Mongolia, although these three sites were all dominated by typical steppe. Besides the physical factors, higher population density and livestock carrying level should be responsible for the higher wind erosion rates in these two regions of Inner Mongolia.
LIU JiYuanSHI HuaDingQI YongQingZHUANG DaFangHU YunFeng
土壤风蚀是北方干旱和半干旱地区土地沙化和沙尘暴灾害的首要环节和主要动力过程之一.选取影响内蒙古自治区土壤风蚀演化的相关指标,运用GIS技术提取各指标数据,构建径向基函数神经网络(Radial Basis Function Network,RBFN);根据不同风蚀危险程度标准,选取12个市、县(旗)相关数据进行训练,确定网络模型参数,进而对内蒙古自治区88个市、县(旗)的土壤风蚀危险度进行了评价.结果表明:内蒙古自治区西部为土壤风蚀发生的极强危险区,西北为强危险区,中部为中度危险区,而东部为轻度危险区;利用其他研究对该评价结论进行对比验证,结果较为理想.
