A new method for fingerprinting sediment source contributions using distances from discriminant function analysis

Liu, Bing; Storm, Daniel E.; Zhang, X. C.; Cao, Wenda; Duan, Xingwu

doi:10.1016/j.catena.2016.06.039

Cited by 20 publications

(8 citation statements)

References 29 publications

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“…To assess the uncertainty in the extent to which the average fingerprinting properties concentration of each source category in the mixing model reflects the true value, a Monte-Carlo simulation approach was used. This technique involved solving the mixing model by removing one sample from each source group for 1000 iterations; following this process, the mean relative source contributions were determined for each site [59,66].…”

Section: Goodness-of-fit and Uncertainty Analysismentioning

confidence: 99%

Fingerprinting Suspended Sediment Sources in an Urbanized Watershed

Malhotra

Lamba

Srivastava

et al. 2018

Water

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The elevated supply of fine-grained sediment to a river system negatively impacts the water quality and ecosystem health. Therefore, quantification of the relative contribution from different sources to in-stream sediment is of major interest to target sediment mitigation best management practices (BMPs). The objective of this study was to determine the relative contribution from different sources of suspended sediment in an urbanized watershed (31 km2) located in the eastern part of Alabama, USA. Estimates of relative contributions from individual source types were assessed for two different particle size fractions, 63–212 μm (fine sand) and <63 μm (silt and clay). Results of this study indicate that the construction sites were the dominant source of suspended sediment in this watershed. The average annual subwatershed-level surface runoff determined using the Soil and Water Assessment Tool (SWAT) model varied from 2.3 to 11,980 mm ha−1 year−1. Areas that generate high surface runoff have the potential to contribute disproportionately high amounts of sediment to streams and therefore should be targeted for BMPs. The results of this study show that it is important to consider spatial and temporal variability in suspended sediment sources in order to develop and target sediment control management strategies. The sources of suspended sediment and sediment deposited on the stream bed might not necessarily be the same. Therefore, sampling both suspended sediment and stream bed sediment will improve our knowledge of watershed-level sediment transport processes.

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Section: Goodness-of-fit and Uncertainty Analysismentioning

confidence: 99%

Fingerprinting Suspended Sediment Sources in an Urbanized Watershed

Malhotra

Lamba

Srivastava

et al. 2018

Water

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“…Navarro-Hevia et al, 2015) and sediment fences (e.g. Shakesby et al, 2015), but fingerprinting techniques have been increasingly applied worldwide (Carter et al, 2003;Walling, 2005;Liu et al, 2016). The approach is based on the assumption that one or more physical and/or biogeochemical properties of downstream sediments will reflect their sources, and therefore can be used diagnostically to identify the origin(s) of the sediments (Koiter et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…The behaviour of each tracer in the erosion and transport process must be conservative (Devereux et al, 2010), and usually more than one tracer is used (composite fingerprint) for better discrimination of a wide range of potential sources (Collins & Walling, 2002;. After establishing the composite fingerprints, the importance of different potential sources can be assessed by the subsequent application of a multivariate mixing model (Carter et al, 2003;Nosrati et al, 2014;Franz et al, 2014;Liu et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Temporal Dynamics of Sediment Sources in an Urbanizing Mediterranean Catchment

et al. 2017

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The identification of sediment sources is important for catchment management, but few studies have been performed in Mediterranean areas. This study uses a multiproxy sediment fingerprinting approach to explore sources and dynamics of fluvial sediments in a rapidly urbanizing Portuguese peri‐urban catchment. X‐ray fluorescence was used to characterize the elemental geochemistry of sediments collected within the stream network after three storm events in 2012 and 2015. A range of statistical techniques, including hierarchical cluster analysis, was used to identify discriminant sediment properties and similarities between fine bed sediment samples of tributaries and downstream sites. Quantification of sediment supply from upstream sub‐catchments was undertaken using established sediment fingerprinting approaches. The geochemistry of the sediments was found to be influenced by both lithology and land‐use changes. In 2012, the sandstone sub‐catchment provided 75% of the <63 μm and 94% of the 63–125 and 125–2000 μm sediment, mostly from an Enterprise Park site undergoing deforestation and construction (covering 5% of the catchment area), with most of the remaining sediment deriving from the construction of a major road (1% of the catchment) in the limestone sub‐catchment. In 2015, planned and accidental retention basins below the Enterprise Park and major road sites, respectively, prevented some sediment from reaching the stream network, thereby reducing their importance as sediment sources. Sediment mobilization in urban areas with paved roads was small in comparison, but characterized by high heavy metal concentrations. The sediment fingerprinting approach adopted shows promise in identification of the main sources of sediments, necessary to underpin improved peri‐urban management strategies. Copyright © 2017 John Wiley & Sons, Ltd.

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“…Two principal data processing frameworks are widely used to quantify the uncertainties associated with sediment fingerprinting results. Many studies (e.g., Franks and Rowan 2000;Collins et al 2013aCollins et al , b, 2014Stone et al 2014;Liu et al 2016b;Pulley and Collins 2018;Habibi et al 2019) have used a frequentist approach incorporating a Monte Carlo framework for uncertainty analysis. Alternatively, Bayesian approaches have also been used to evaluate uncertainties associated with the results generated by sediment fingerprinting (Nosrati et al 2018;Gholami et al 2017b;Cooper et al 2014Cooper et al , 2015Abban et al 2016;Cooper and Krueger 2017;Habibi et al 2019).…”

Section: Selection Of Final Composite Fingerprints For Terrestrial Somentioning

confidence: 99%