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Little information exists on the potential of soil enzyme activities,which are sensitive to soil properties and management,for the characterization of sediment sources at the catchment scale.The objective of this study is to explore and evaluate enzyme activity as tracer for sediment fingerprinting in the Hiv catchment(55 km~2),Iran.Therefore,four enzymes were measured from 42 different sampling sites,covering three sediment source areas(rangeland/surface erosion,orchard/surface erosion,and streambank erosion),as well as from 12 sediment samples from reservoir check dams (sediment sinks).The results indicate that,based upon backward mode discriminant analysis,βglucosidase and dehydrogenase,allowed more than 95%of the samples to be correctly assigned to their source areas.These enzymes were selected as input data for a mixing-model to determine the relative contribution of the sampled sediment sources.The mean contributions from rangeland, orchard and streambank sources in the study area were estimated as 11.3%,15.1%and 73.7%, respectively.Using geochemical tracers,the mean contribution from rangeland,orchard and streambank sources was estimated as 14.1%,9.5%and 74.8%,respectively.Combined biochemical and geochemical tracers,similar values were obtained(18.7%,10.7%and 70.7%,respectively).Our results indicate that soil enzyme activity allows for a good characterization of sediment sources,and can provide a complementary tool to currently existing sediment fingerprinting approaches.However, the method should be also tested in other regions.
Little information exists on the potential of soil enzyme activities, which are sensitive to soil properties and management, for the characterization of sediment sources at the catchment scale. The objective of this study is to explore and evaluate enzyme activity as tracer for sediment fingerprinting in the Hiv catchment (55 km ~ 2), Iran.Therefore, four enzymes were measured from 42 different sampling sites, covering three sediment source areas (rangeland / surface erosion, orchard / surface erosion, and streambank erosion), as well as from 12 sediment samples from reservoir check dams (sediment sinks). The results indicate that, based upon backward mode discriminant analysis, βglucosidase and dehydrogenase, allowed more than 95% of the samples to be correctly assigned to their source areas. The enzymes were selected as input data for a mixing-model to determine the relative contribution of the sampled sediment sources. The mean contributions from rangeland, orchard and streambank sources in the study ar Ea were estimated as 11.3%, 15.1% and 73.7% respectively. Using geochemical tracers, the mean contribution from rangeland, orchard and streambank sources was estimated as 14.1%, 9.5% and 74.8% respectively. values were obtained (18.7%, 10.7% and 70.7%, respectively) .Our results that that soil enzyme activity allows for a good characterization of sediment sources, and can provide a complementary tool to currently available sediment fingerprinting approaches. However, the method should be also tested in other regions