University of Tehran Journal of Range and Watershed Managment 5044-2008 70 1 2017 05 22 Suspended sediment fingerprinting and uncertainty estimation (Case study: Zidasht-Fashandak sub-watershed in Taleghan) Suspended sediment fingerprinting and uncertainty estimation (Case study: Zidasht-Fashandak sub-watershed in Taleghan) 57 69 61966 10.22059/jrwm.2017.61966 FA Aboalhasan Fathabadi Ali Salajegheh Hamid Pezeshk Aliakbar Nazari Samani Hamed Rouhani Journal Article 2013 06 11 In order to manage and implement conservational activities in watershed successfully, it is necessary to determine the sediment sources. In recent years, sediment fingerpering techniques have been used for estimating sediment sources contribution. With respect to small source samples, having many answer as a result of over fitting, there are some uncertainties in estimated sources contribution. In this study, the uncertainty associated with the multivariate mixing model was estimated using Monte Carlo simulation and GLUE approach in Zidasht-Fashandak sub- watershed. The sediment and source samples were taken in the study area and then, 54 geochemistry and three organic characteristics were measured. 17 elements were also selected as optimum tracer composition using Kruskal–Wallis H-test and multivariate discriminate analysis. Meanwhile, sources contribution were estimated using multivariate mixing models. Results showed higher contribution of sub-surface sources than the surface resources. Also, the distance between lower and upper limits for all sources and resolutely uncertainty bands were high. In order to manage and implement conservational activities in watershed successfully, it is necessary to determine the sediment sources. In recent years, sediment fingerpering techniques have been used for estimating sediment sources contribution. With respect to small source samples, having many answer as a result of over fitting, there are some uncertainties in estimated sources contribution. In this study, the uncertainty associated with the multivariate mixing model was estimated using Monte Carlo simulation and GLUE approach in Zidasht-Fashandak sub- watershed. The sediment and source samples were taken in the study area and then, 54 geochemistry and three organic characteristics were measured. 17 elements were also selected as optimum tracer composition using Kruskal–Wallis H-test and multivariate discriminate analysis. Meanwhile, sources contribution were estimated using multivariate mixing models. Results showed higher contribution of sub-surface sources than the surface resources. Also, the distance between lower and upper limits for all sources and resolutely uncertainty bands were high. https://jrwm.ut.ac.ir/article_61966_4dec0a44c49ea2c4490d9d8cedc1240e.pdf