Feasibility of estimating heavy metal contaminations in floodplain soils using laboratory-based hyperspectral data—A case study along Le’an River, China

Geo-spatial Information Science - Tập 14 - Trang 10-16 - 2011
Yaolin Liu1,2, Wei Li3, Guofeng Wu1,2, Xinguo Xu1
1School of Resource and Environmental Science, Wuhan University, Wuhan, China
2Key Laboratory of Geographic Information System, Ministry of Education, Wuhan University, Wuhan, China
3Sichuan Zhongshui-chengkanyuan Surveying and Mapping Engineering Company, Chengdu, China

Tóm tắt

It is necessary to estimate heavy metal concentrations within soils for understanding heavy metal contaminations and for keeping the sustainable developments of ecosystems. This study, with the floodplain along Le’an River and its two branches in Jiangxi Province of China as a case study, aimed to explore the feasibility of estimating concentrations of heavy metal lead (Pb), copper (Cu) and zinc (Zn) within soils using laboratory-based hyperspectral data. Thirty soil samples were collected, and their hyperspectral data, soil organic matters and Pb, Cu and Zn concentrations were measured in the laboratory. The potential relations among hyperspectral data, soil organic matter and Pb, Cu and Zn concentrations were explored and further used to estimate Pb, Cu and Zn concentrations from hyperspectral data with soil organic matter as a bridge. The results showed that the ratio of the first-order derivatives of spectral absorbance at wavelengths 624 and 564 nm could explain 52% of the variation of soil organic matter; the soil organic matter could explain 59%, 51% and 50% of the variation of Pb, Cu and Zn concentrations with estimated standard errors of 1.41, 48.27 and 45.15 mg·kg−; and the absolute estimation errors were 8%–56%, 12%–118% and 2%–22%, and 50%, 67% and 100% of them were less than 25% for Pb, Cu and Zn concentration estimations. We concluded that the laboratory-based hyperspectral data hold potentials in estimating concentrations of heavy metal Pb, Cu and Zn in soils. More sampling points or other potential linear and non-linear regression methods should be used for improving the stabilities and accuracies of the estimation models.

Tài liệu tham khảo

Wild A (1993) Soils and the environment: an introduction [M]. New York: Cambridge University Press Alloway B J (1994) Heavy metals in soils [M]. Berlin: Springer Kishe M A, Machiwa J F (2003) Distribution of heavy metals in sediments of Mwanza Gulf of Lake Victoria, Tanzania[J]. Environment International, 28(7): 619–625 Ozmen H, Kulahci F, Cukurovali A, et al. (2004) Concentrations of heavy metal and radioactivity in surface water and sediment of Hazar Lake (Elazig, Turkey)[J]. Chemosphere, 55(3): 401–408 UNESCO (1996) Ecological effects of heavy-metal pollution in the Dexing copper mine region (Jian Xi province, China)[R]. The United nations Educational, Scientific and Cultural Organization. Clevers, Kooistra, Salas (2004) Study of heavy metal contamination in river floodplains using the red-edge position in spectroscopic data[J]. International Journal of Remote Sensing, 25(19): 3883–3895 Dauvalter V, Rognerud S (2001) Heavy metal pollution in sediments of the Pasvik River drainage[J]. Chemosphere, 42(1): 9–18 Kemper T, Sommer S (2002) Estimate of heavy metal contamination in soils after a mining accident using reflectance spectroscopy[J]. Environmental Science & Technology, 36(12): 2742–2747 Choe E, van der Meer F, van Ruitenbeek F, et al. (2008) Mapping of heavy metal pollution in stream sediments using combined geochemistry, field spectroscopy, and hyperspectral remote sensing: a case study of the Rodalquilar mining area, SE Spain[J]. Remote Sensing of Environment, 112(7): 3222–3233 Demattê J A M, Campos R C, Alves M C, et al. (2004) Visible-NIR reflectance: A new approach on soil evaluation[ J]. Geoderma, 121(1–2): 95–112 Kooistra L, Wanders J, Epema G F, et al. (2003) The potential of field spectroscopy for the assessment of sediment properties in river floodplains[J]. Analytica Chimica Acta, 484(2): 189–200 Melendez-Pastor I, Navarro-Pedreño J, Gómez I, et al. (2008) Identifying optimal spectral bands to assess soil properties with VNIR radiometry in semi-arid soils[J]. Geoderma, 147(3–4): 126–132 Kooistra L, Wehrens R, Leuven R S, et al. (2001) Possibilities of visible-near-infrared spectroscopy for the assessment of soil contamination in river floodplains[J]. Analytica Chimica Acta, 446(1–2): 97–105 Liu W X, Coveney R M, Chen J L (2003) Environmental quality assessment on a river system polluted by mining activities[J]. Applied Geochemistry, 18(5): 749–764 Zeng F, Xiao H, Zhou W (2007) Spatial and temporal variations and their source analysis of Copper, Lead and Zinc in river-waters and sediments of the Le’an River (in Chinese)[J]. Research of Environmental Sciences, 20(6): 14–20 He M, Wang Z, Tang H (1998) The chemical, toxicological and ecological studies in assessing the heavy metal pollution in Le An River, China[J]. Water Research, 32(2): 510–518 Walkley A L, Black A (1947) A critical examination of a rapid method for determination of organic carbon in soils-effect of variations in digestion conditions and of inorganic soil constituents[J].Soil Science, 63: 251–163 Krishnan P, Alexander J D, Butler B J, et al.(1980) Reflectance technique for predicting soil organic matter[J]. Soil Science, 44(6): 1282–1285 Efron B(1979) Bootstrap methods: another look at the Jackknife[J]. Annals of Statistics, 7(1): 1–26 Lu Y, Bai Y, Yang L, et al. (2007) Prediction and validation of soil organic matter content based on hyperspectrum (in Chinese) [J]. Scientia Agricultura Sinica, 40(9): 1989–1995 Wang J, Huang C P, Allen H E, et al. (1999) Effects of dissolved organic matter and pH on heavy metal uptake by sludge particulates exemplified by Copper (II) and Nickel (II): three-variable model [J]. Water Environment Research, 71: 139–147 Middelkoop H (1997) Embanked floodplains in the Netherlands: geomorphological evolution over various time scales [D]. Universiteit Utrecht