Abstract
A sequential quantitative approach to sediment source ascription is presented based on mineral magnetic measurements. Rhode River catchment (USA) and Isabel II reservoir catchment (Spain) were taken as the examples for developing the magnetic diagnosis model. The multi-parameter cluster analysis was used to classify the sediment source with respect to their magnetic properties, multi-variable mixing model to link magnetic measurement of mixtures with their source component proportions, and linear programming to determine the sediment source components. It has been shown by these two experiments that the magnetic diagnosis model is successful for the quantitative sediment source ascription. The results correspond well with the relative environmental change proxy.
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References
Thompson, R., Oldfield, F.,Environmental Magnetism, London: Allen & Unwin, 1986, 112–119.
Oldfield, F., Environmental magnetism-personal perspective,Quaternary Science Review, 1991, 10: 73.
Yu, L., Oldfield, F., A multivariate mixing model for identifying sediment source from magnetic measurements,Quaternary Research, 1989, 32: 168.
Yu, L., Oldfield, F., Quantitative sediment source ascription using magnetic measurements in a reservoir-catchment system near Nijar, S.E. Spain,Earth Surface Processes and Land forms, 1993, 18: 441.
Oldfield, F., Maher, B. A., Donoghue, J.et al., Particle-size-related mineral magnetic source-sediment linkages in the Rhode River Catchment, Maryland, USA,Journal of Geology, 1985, 142: 1035.
Yu Lihong, Xu Yu, Zhang Weiguo, Mineral magnetic measurement on lake sediment and its environmental indications,Advances in Geophysics (in Chinese with English abstract), 1995, 10(1): 11.
Correll, D. L., An overview of the Rhode river watershed program, inWatershed Research in Eastern North America, Washington: Smithsonian Institution, 1977, 105–120.
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Yu, L., Zhang, W. Quantitative approach to sediment source identification by using magnetic diagnosis model. Chin.Sci.Bull. 44, 504–510 (1999). https://doi.org/10.1007/BF02885535
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DOI: https://doi.org/10.1007/BF02885535