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.

Selection of the suite subset of tracers, capable of discriminating Sediment sources, is the first and the most important step in the Sediment fingerprinting method. Selection of the suite subset is carried out by Discriminant function analysis. The presence of outliers affects the suite subset selection and prevents entering the important tracers into the model, hence reducing accurate classification percent of Discriminant function analysis. Therefore, the outliers must be detected and corrected or omitted, if enough evidences were present. In this study, different univariate and multivariate outlier detection methods were used to assess the presence of outliers in geochemical and organic elements and radionuclides of soil samples collected from Ghara aghaj watershed, Makoo township. According to four univariate outlier detection methods, no observations (samples) were outlier on a sufficient number of tracers. The [Median ± 3MAD] and box plot procedures showed better performance in outlier identification than the [Mean ± 3S] and Grubbs' test methods. Also, based on multivariate outlier detection methods, namely squared Mahalanobis distance, separate box plots of squared Mahalanobis distance for each of Sediment sources, principal component analysis and plot of the squared Mahalanobis distances against the quantiles of the chi-square distribution, no observations were detected as outlier. From perspectives of each of the two group methods, there was no sufficient information and demonstrable proof about true outlierness of any observation. The advantages of the approach adopted in this study are the simplicity and computability of the selected outlier detection methods with commonly used statistical softwares, and the condition that an observation is regarded as outlier if its uniqueness is confirmed with several methods.

Suspended Sediments originated from nonpoint sources in the fluvial and the catchment which they are different on spatial and temporal scales. fingerprinting of Sediment process focuses on the methods which researchers able to discriminate Sediment sources using composite and extracted Sediment and surface and subsurface of soil samples from nonpoint resources using tracers and mixing models. Using this method as a Sediment and soil technique and as well as complementary of classic methods of water erosion to identifying of Sediment sources, Sediment delivery in the river at various spatial and temporal scale and estimation of soil erosion using existing tracers in the soil and Sediment has been increased in latest decades. This research is reviewing the comprehensive background of erosion and Sediment studies, emphasis on the used techniques and methods, mixing model and utilities of various tracers in the erosion and Sediment studies and various sampling methods in different studies, introduce the Sediment fingerprinting in the world and Iran. This research introduces the new technologies (patents) in Iran which they are related to Sediment and soil erosion studies. The results of review research showed that cohesive studies of soil and Sediment with regarding to new methodology started since 60th decade and continued large, medium, small scale basin, hillslope, plot and experimental scale with techniques such as radionuclide decay, earth rare element, magnetic properties of soils, other tracers and fingerprinting. Also the mixing models of Hughs, Landvehr, Slattery and motha, MixSIAR, Bayesian and Monte carlo were used in more researches related to fingerprinting and Hughs and Collins models are the best predictive one for replication in data and correct factor in its data respectively.

An important and significant issue in applied research for the management of watersheds is to know integrated drainage Sediment yield process to recognize hill slopes and fluvial system. In erosion and Sediment study, investigation of form and land form evolution was the earth science study core in the long time. So determination of landform contribution in Sediment and erosion yield can utilize for erosion and Sediment process in watershed. In recently two decades, Sediment fingerprinting method was proven as a key method for contribution of Sediment proportion. The purpose of this study was to determine the geomorphic landforms in Sediment yield in Chehel-Chaye catchment in Golestan province. By using Topography Position Index, four landforms including concave and convex slope, narrow valleys and slope between concave and convex slope were recognized. In eight flood events suspended Sediment sampling was done in March to April 2020. By using XRF instrument, 23 geochemical traces was analysis. After bracket, kruskal-wallis and discernment function analysis, Ba، Ni،Pb، V، Mgo، Mno and Cao had the most discernment percentage in all of tracers. Based of Bayesian mixing model, in first concave slopes 60/9 and in second 28/5 percentage of Sediment yield. Result of virtual Sediment modeling show that root mean squared error are in 0.6 and 8/4 and mean absolute error 1/7 and 23 evaluated.

In order to develop management plans for water and soil conservation, it is necessary to determine the sources of Sediment production in watersheds. During the past three decades fingerprinting technique has been used extensively in determining the contribution of different sources of Sediment. In this study, was carried out Sediments fingerprinting and determine the contribution of each source to Sediment production of the Toulbane watershed in Golestan province. To this end, 44 source samples were collected from forest, pasture, agriculture and bank erosion. Also 8 Sediment samples were collected using Philips time-integrated Sediment sampler. Afterward, the concentration of 34 geochemical properties was examined in the laboratory using the ICP device. Next, the optimal composite tracers were determined to discriminate Sediment sources by using statistical tests including mass conservation test and Kruskal-Wallis. The contribution of different sources to Sediment production was determined using the multivariate mixing model. Finally, the uncertainty in the case of a low number of data, was examined using the Monte Carlo method. As a result, after statistical tests, 12 tracers were selected as the optimal composite fingerprints. The bank erosion was main source to Sediment production with 52. 18% and the forest had the lowest contribution to Sediment production with 4. 39%. The contribution of agriculture and pasture was 33. 23% and 10. 21%, respectively. According to the uncertainty analysis, bank erosion is the most significant source to Sediment production. Also, the high difference between the upper and the lower boundaries in different sources indicates high uncertainty.

Due to successes of fingerprinting method in producing rapid and low-cost information of Sediment sources, in this research this method was used in three sub-cathments of Chasht-Khoran Basin in Semnan Province: Amrovan, Atari and Ali-Abad. Samples below 63 mm were separated and 15 fingerprinting propertis was measured. In the first stage comparison of means and differentiation analysis were used for determination of the characteristics that can differentiate Sediment source as well as possible. In second stage, by minimizing composite multivariate model by optimization methods, the share of each source was determined. The results shown that, in Amrovan Catchment, For properties consisting of Co, Ph, Kaolinite and K were recognized as optimum composition of Sediment tracers which could differentiate Sediment source completely. In Atary Catchment, the optimum composition of tracers are Na, Co, XLF and kaolinite which differentiate source by %91.7. In Ali-Abad Catchment five parameters were recognized as optimum composite which are:Na, XLF, Ca, Co and smectit which completely differentiated Sediment sources. The results of calculated composite multivariate model have shown that Upper Red formation in Amrovan, Atari and Ali-Abad Sub-Catchment has the highest share in Sediment production. The Sediment production in these three sub catchment are as follows:35.9, 23.53 and 86.64% respectively. Therefore Sediment management and control strategies should be performed on these sources.

Soil erosion is the most serious and irreversible threat to sustainable development. According to the increasing rate of soil erosion and Sediment yield, the current study aimed to determine relative contribution of Sediment sources in Ziarat catchment in fall, winter and spring seasons using Sediment fingerprinting technique. In this regard, 43 samples from Sediment sources including rangeland and cultivated land as surface erosion and stream bank and road verges as sub-surface erosion as well as 14 samples of suspended Sediment at outlet of catchment were collected and concentration of geochemical tracers, organic carbon and 137Cs were measured. The optimum set of tracers was selected using the Kruskal-Wallis H test and discriminant function analysis. Finally, the relative contribution of Sediment sources was determined through mixing model in different seasons. The results showed that the maximum relative contribution was related to surface erosion in winter and spring seasons. Sub-surface erosion in spring season with 60. 4% also caused a large amount of Sediment yield. The results of this study can be used to select the management strategies in soil erosion and Sediment control of Ziarat catchment in different seasons.

Because of many problems associated with traditional procedures for identifying Sediment sources, fingerprinting techniques, based on physical, chemical and organic properties of Sediment and source materials, are increasingly being used as a valuable and effective alternative approach to assembling such information. In this method, a suitable composite (set) of diagnostic properties and a multivariate mixing model are employed to estimate the relative contribution of Sediment sources to Sediments transported to basin outlet. In this study, using suitable composites of geochemical elements, radionuclides, organic Carbon, Nitrogen and Phosphorous, capable of discriminating subbasins of the study basin, and a multivariate mixing model were used to determine contributions of that subbasins to Sediment yield. The suitable composite fingerprints (elements) were obtained using discriminant analysis. The study basin is known as Margan, located in Pouldasht district, Makoo Township, Western Azarbaijan province. This basin has six subbasins. The suitable composite fingerprints having capability to distinguish the above mentioned subbasins include: Tl and Ce for the subbasins of 1 and 2, W, V, and Pb for the subbasins of 3 and 4, and Ni, Mn and Ce for the subbasins of 5 and 6. Mean contributions from the subbasins of 1, 2, 3, 4, 5 and 6 were to be estimated as 89.14, 10.86, 20.86, 79.14, 67.10 and 32.90% respectively. Low mean absolute errors (less than 11%) show high degree of correspondence between measured and predicted properties. High model efficiencies (greater than 0.99) confirm the goodness of fit of the mixing models. Also it is argued that fingerprinting estimates for Sediment sources are consistent with field observations. Then although a number of limitations must be recognized, the fingerprinting approach to source ascription has high efficiency to determine relative importance of Sediment sources (subbasins) in the study basin.

Sediment tracing method has been proven as a successful and effective method to determining Sediment sources contribution in Sediment yield in recent two decades. Ziarat drainage basin in Golestan province is one of the water supply resources in Gorgan city. The main lithological formations in the study area are Gorgan Schists, Quaternary alluvial deposits, Shemshak and Khosh yeylagh Formation which could have an important role in erosion and Sediment yield. For tracing Sediment, 14 samples of suspended Sediment from catchment outlet during precipitation events and 43 representative samples of geologic formations (as Sediment sources) from the soil surface (depth of 0-5 cm) were collected and geochemical elements, 137Cs and organic carbon were measured in the samples as tracers. The optimum set of tracers was selected by using Kruskal-Wallis test and discriminate function analysis. The results of this study indicate that the tracers including OC, 137Cs and Cu have the most potential to discriminate the Sediment sources. The result of the Sediment fingerprinting mixing model showed that Shemshak formation, fluvial deposition, Khosh yeylagh and Shist formation have 42, 31/9 and 23/7, 1. 6% of the Sediment contributions in Sediment yield, respectively.

Determining the relative contribution of Sediment sources is the first step in planning for soil conservation programs. This study aimed to compare two methods of water Sediment source tracing (including fingerprint technique and field measurements of erosion) in Vartavan catchment. Discriminant analysis and multivariate mixing model were used for determining the optimum combination of tracers and contribution of Sediment sources. Sediment trapper was also used for measuring the erosion of various lithological units. The result showed that the contributions of Sedimentary, calcareous and volcanic sources in the outlet Sediments were equal to 47. 6, 37. 4 and 15. 1 % respectively and the relative importance of these sources (in terms of specific Sediment) were equal to 1. 58, 1. 04 and 0. 48, respectively. The average of minimum and maximum weight of accumulated Sediments in trappers were also 2/13 and 6/221 gr for orbitolina and plagioclase limestone. respectively. In total و the results and efficacy of fingerprinting, was approved by field measurements. As well, differences between the results of direct and indirect methods are due to the differences in the area of units and the lack of spatial and filtering resistances in the indirect methods.