عنوان مقاله [English]
نویسنده [English]چکیده [English]
Knowledge of source of sediment and determination of relative contributions of sediment sources are required for watershed management strategies as soil and sediment erosion control methods that have important effect on soil and water quality and quantity. Uncertainty confidence levels ascertaining is needed in sediment fingerprinting mixing models but it has not yet been fully incorporated in these models. The objective of this study is to apply a Bayesian-mixing model to assess the uncertainty estimation in sediment fingerprinting in the Zidasht catchment, Iran. In view of this, 28 tracers were measured in 42 different sampling sites from four sediment sources and 14 sediment samples. Backward discriminant analysis provided an optimum composite of seven tracers viz. B, C, K, Mo, P, Pb and Tl that afforded more than 97% correct assignations in discriminating between the sediment sources in the study area. Sediment source fingerprinting was used to explore the uncertainty in the contributions of sediment from the four sources. In the study area, the relative contributions associated with Bayesian uncertainty from rangeland/sheet erosion, crop field/sheet erosion, stream bank and dry-land farming/sheet erosion sources ranged between 13 (8-20), 7.5 (0-10), 59 (45-75) and 20.5 (10-30) percent, respectively. These results can be useful as a scientific basis for selecting proper soil conservation and sediment control methods and integrated watershed management.