Temporal variability of suspended sediment sources in an alpine catchment combining river/rainfall monitoring and sediment fingerprinting

Sediment fingerprinting quantifies proportional contributions of catchment sediment sources to downstream sediment mixtures and deposits. While the sediment fingerprinting technique is well established it is still challenged by the coarse spatial resolution of sediment source discrimination which hinders understanding of catchment sediment dynamics and limits its usefulness for land management where finer resolution spatial information is required.Here, two conventional sediment fingerprinting datasets from New Zealand are used to show how spatial modelling of source loads can improve 1) the usefulness of sediment fingerprinting approaches and 2) visualization of results for end-users by combining source apportionment with terrain information and sediment budget modelling. The two case studies involve unmixing sediment source contributions to 1) overbank deposits within the Oroua River catchment, where six sediment sources (Mountain Range, Mudstone, Hill Subsurface, Hill Surface, Unconsolidated Sandstone, and Channel Bank) across two size fractions (<63 &#181;m and 125&#8211;300 &#181;m) were characterized using bulk geochemical and radionuclide tracers and 2) suspended sediment in the Manawatu catchment, where a similar six sources were characterized using bulk geochemical tracers to determine changes in source contributions to hourly suspended sediment samples during a 53hr storm event.The proportional source contributions for each case study are applied to modelled sediment loads and spatially distributed using terrain information for rock type, slope and channel network extent to produce specific sediment yield maps for both catchments and spatial visualization of sediment generation during the Manawatu catchment storm event. Integrating sediment fingerprinting results with spatial datasets and modelling can enhance interpretation of source apportionment results and improve the utility of this information for end-users focused on the spatial targeting of erosion sources for mitigation to reduce downstream sediment impacts.&#160; &#160;

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Exploring the potential for using hierarchical sediment fingerprinting as an urban management tool in monitoring changing sediment sources

10.5194/egusphere-egu2020-18003 ◽

2020 ◽

Author(s):

Rory Walsh ◽

Carla Ferreira ◽

William Blake ◽

Sam Higton ◽

Antonio Ferreira

Keyword(s):

Land Use ◽

Suspended Sediment ◽

Agricultural Land ◽

Management Tool ◽

Sediment Fingerprinting ◽

Storm Events ◽

Sediment Sources ◽

Wet Season ◽

Stream Network ◽

Urban Catchments

An ability to identify and quantify changes in sediment sources and erosion within catchments would be of great use for landscape managers and planners. This is particularly the case in peri-urban catchments, which are characterized by complex and dynamically changing land-use mosaics &#8211; and where today&#8217;s planning decisions may be crucial as regards avoiding or exacerbating erosional, water quality and flooding problems. This study explores the potential for a sediment fingerprinting approach to provide a cost-effective way of assessing changes in sediment sources within a small peri-urban catchment. The study focuses on the Ribeira dos Cov&#245;es catchment (6.2 km2), on the outskirts of Coimbra in central Portugal. The climate is humid Mediterranean and the geology is 56% sandstone, 41% marly limestone and 3% alluvium. Current land-use is 56% woodland, 4% agricultural and 40% urban (mainly residential, but also a recently constructed enterprise park (5%) and major highway (1%)). Recent urbanization has largely occupied former agricultural land. The study adopts a multi-proxy sediment fingerprinting approach, based on geochemical (elemental) characterization of fluvial fine bed-sediment and soil samples, using a Niton x-ray fluorescence elemental analyser. Sampling of fluvial sediment was carried out at 33 sites within the stream network (including all significant tributaries, downstream sites and the catchment outlet). Samples were collected in July 2018 and November 2018 following contrasting &#8216;late wet season&#8217; and &#8216;end of dry season&#8217; events. In addition, in July 2018 composite samples of potential sediment sources were collected, including (i) soil surface (0-2cm) samples at 64 representative locations, (ii) 17 samples from eroding channel margin sites, and (iii) 15 samples of road sediment. All samples were sieved to obtain <63&#181;m, 63-125&#181;m, 125-250 &#181;m and 250-2000&#181;m fractions, where the <63&#181;m fraction was taken to represent suspended sediment. The elemental geochemistry of each sample fraction was derived using the XRF analyser. Differences (and similarities) in geochemical signatures between the various tributaries and the various potential sources were assessed using a range of statistical techniques. Bayesian unmixing models were used in a hierarchical (confluence-based) fashion to assess the contributions of different sub-catchments to downstream sites including the catchment outlet. Modelling results were then compared with relative contributions for three previously analysed storm events of 2012-2015, at which time construction activities had been more active. Modelling results for the two 2018 events were also validated by comparing them with independent suspended sediment records collected at five locations on the principal tributaries and at the catchment outlet. Overall, the modelling was successful in indicating and quantifying significant changes in sediment sources through time within the catchment. Reasons as to why sediment fingerprinting was successful in this case are then examined and discussed, in part drawing comparisons with the findings from a parallel sediment fingerprinting study of changing sources in the dynamically changing partly logged rainforest, partly oil palm Brantian catchment in Sabah, Malaysian Borneo. The potential for a simple sediment fingerprinting methodology to be developed for more widespread use by urban/environmental managers and planners is then explored. &#160;

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Apportionment of suspended sediment sources in an agricultural watershed using sediment fingerprinting

Geoderma ◽

10.1016/j.geoderma.2014.09.024 ◽

2015 ◽

Vol 239-240 ◽

pp. 25-33 ◽

Cited By ~ 38

Author(s):

Jasmeet Lamba ◽

K.G. Karthikeyan ◽

A.M. Thompson

Keyword(s):

Suspended Sediment ◽

Agricultural Watershed ◽

Sediment Fingerprinting ◽

Sediment Sources

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Multi-fractional sediment fingerprinting in monitoring sediment sources in a peri-urban Portuguese catchment

10.5194/egusphere-egu21-16224 ◽

2021 ◽

Author(s):

Rory Walsh ◽

Carla Ferreira ◽

William Blake ◽

Sam Higton ◽

Antonio Ferreira

Keyword(s):

Particle Size ◽

Suspended Sediment ◽

Agricultural Land ◽

Size Fraction ◽

Soil Samples ◽

Sediment Fingerprinting ◽

Bed Sediment ◽

Sediment Sources ◽

Geochemical Composition ◽

Size Fractions

This paper explores the potential for using multiple particle size fractions in a hierarchical geochemical sediment fingerprinting approach to the assessment of changes in sediment sources through time within a small Mediterranean peri-urban catchment. Conventional &#160;sediment fingerprinting has focussed on the <63&#181;m fraction of fine bed-sediment on the basis that this fraction represents suspended sediment, which in turn is considered dominant over bedload in catchment sediment budgets. In reality, however, coarser sediment than 63&#181;m may form part of suspended sediment and/or occurs as relatively fast-moving fine bedload.&#160; Furthermore, sediment sources vary in their particle size distribution and, as geochemical composition can vary with particle size, it is arguable that sediment fingerprinting studies should consider use of multiple size fractions.This study explores this approach using <63&#181;m, 63-125&#181;m, 125-250 &#181;m and 250-2000&#181;m size fractions.&#160; It focuses on the north-south flowing Ribeira dos Cov&#245;es catchment (6.2 km2), on the outskirts of Coimbra in central Portugal. The climate is humid Mediterranean. Catchment geology is 56% sandstone (in the east), 41 % marly limestone (in the west) and 3 % alluvium. Current land-use is 56% woodland, 4 % agricultural and 40% urban (mainly residential, but also including a recently constructed enterprise park (5%) and major highway (1%)). Recent urbanization has largely occupied former agricultural land.&#160;The study adopts a multi-proxy sediment fingerprinting approach to assessment of changes in sediment sources, based on geochemical (elemental) characterization of the four different size fractions of fluvial bed-sediment and soil samples, using a Niton x-ray fluorescence (XRF) elemental analyser. Sampling of fluvial sediment was carried out at 33 sites within the stream network (including all significant tributaries, downstream sites and the catchment outlet). Samples were collected in July 2018 and November 2018 following contrasting &#8216;late-wet-season&#8217; and &#8216;end-of-dry-season&#8217; events. In July 2018, samples of potential sediment sources were collected including: (i) soil surface (0-2cm) samples at 64 locations, (ii) 17 samples from eroding channel margin sites, and (iii) 15 samples of road sediment. All fluvial and soil samples were sieved to obtain the four target size fractions. The elemental geochemistry of each sample fraction at all fluvial and source sites was derived using the XRF analyser.&#160; (These results were added to similar datasets previously obtained on three occasions in 2012-15 in a period of enhanced urban constructional disturbance). Differences (and similarities) in geochemical signatures between the different size fractions at each survey date at and between each tributary and potential source site were assessed using a range of statistical techniques.&#160; Messages arising are discussed. For each size fraction and survey date, Bayesian unmixing models were used in a hierarchical (confluence-based) fashion to assess the contributions of sub-catchments to downstream sites and the catchment outlet. Modelling results for the two 2018 events were validated by comparing them with suspended sediment records collected at five tributary locations and at the catchment outlet.&#160; Although overall, the modelling was successful in indicating and quantifying significant changes in sediment sources through time within the catchment, uncertainties in interpretation of the multiple fractions are identified and discussed.&#160;

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Combining sediment fingerprinting and hydro-sedimentary monitoring to assess suspended sediment provenance in a mid-mountainous Mediterranean catchment

Journal of Environmental Management ◽

10.1016/j.jenvman.2021.113593 ◽

2021 ◽

Vol 299 ◽

pp. 113593

Author(s):

Julián García-Comendador ◽

Núria Martínez-Carreras ◽

Josep Fortesa ◽

Jaume Company ◽

Antoni Borràs ◽

...

Keyword(s):

Suspended Sediment ◽

Sediment Provenance ◽

Sediment Fingerprinting

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Suspended sediment sources and transport distances in the Yellowstone River basin

Geological Society of America Bulletin ◽

10.1130/b25623.1 ◽

2005 ◽

Vol 117 (3) ◽

pp. 515 ◽

Cited By ~ 53

Author(s):

Peter J. Whiting ◽

Gerald Matisoff ◽

William Fornes ◽

Frederick M. Soster

Keyword(s):

Suspended Sediment ◽

River Basin ◽

Sediment Sources ◽

Yellowstone River

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Evaluation of suspended-sediment sources in the Yeongsan River using Cs-137 after major human impacts

Quaternary International ◽

10.1016/j.quaint.2014.05.033 ◽

2014 ◽

Vol 344 ◽

pp. 64-74 ◽

Cited By ~ 3

Author(s):

Young Shin Lim ◽

Jin Kwan Kim ◽

Jong Wook Kim ◽

Sei Sun Hong

Keyword(s):

Suspended Sediment ◽

Human Impacts ◽

Sediment Sources

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Evaluating the effects of tracer selection, source dominance and source number on the accuracy and sensitivity of source apportionment using sediment fingerprinting.

10.5194/egusphere-egu21-13691 ◽

2021 ◽

Author(s):

Simon Vale ◽

Andrew Swales ◽

Hugh Smith ◽

Greg Olsen ◽

Ben Woodward

Keyword(s):

Land Cover ◽

Source Apportionment ◽

Model Performance ◽

Common Source ◽

Native Forest ◽

Test Model ◽

Sediment Fingerprinting ◽

Sediment Sources ◽

Dominant Source ◽

The Impact

Sediment fingerprinting is a technique for determining the proportional contributions of sediment from erosion sources delivered to downstream locations. It involves selecting tracers that discriminate sediment sources and determining contributions from those sources using tracers.&#160; These tracers can include geochemical, fallout radionuclides, magnetic properties, and compound specific stable isotope (CSSI) values of plant-derived biotracers that label of soils and sediment. &#160;A range of tracer applications and developments in source un-mixing have been demonstrated in the literature and, while the basis for discriminating sediment sources is reasonably well understood, research has drawn increasing attention to limitations and uncertainties associated with source apportionment. Numerical mixtures provide a way to test model performance using idealized mixtures with known source proportions. Although this approach has been applied previously, it has not been used to test and compare model performance across a range of tracer types with varied source contribution dominance and number of sources.We used numerical mixtures to examine the ability of two different tracer sets (geochemical and CSSI), each with two tracer selections, to discriminate sources using a common source dataset. Sources were sampled according to erosion process and land cover in the Aroaro catchment (22 km2), New Zealand.&#160; Here we sampled top-soils and sub-soils from pasture (n = 12 sites), harvested pine (12), kanuka scrub (7) and native forest (4) locations. Composite soil samples were collected at 0-2 and 40-50 cm depth increments to represent surface and shallow landslide (subsoil) erosion sources. Stream sediment (11) samples were also collected for initial unmixing. &#160;Here, we focus on using numerical mixtures with geochemical and CSSI tracers for an increasing number of sources (3 to 6) where each individual and pairwise combination of sources were systematically set as the dominant source. &#160;Since mixing models for CSSI tracers produce source contributions based on isotopic proportions (Isotopic%) instead of soil contributions (Soil%), CSSI numerical mixtures were created for Isotopic% and Soil% to assess the impact this correction factor may have on model performance. &#160;In total, over 400 model scenarios were tested.Numerical mixture testing indicated that the dominant source can have a significant impact on model performance. &#160;If the dominant source is well discriminated, then the model performs well but accuracy declines significantly as discrimination of the dominant source reduces. This occurs more frequently with an increasing number of sources. The geochemical dataset performed well for erosion-based sources while both tracer sets produced larger apportionment errors for land cover sources. CSSI model performance was generally poorer for Soil% than Isotopic%, indicating high sensitivity to the percent soil organic carbon in each source, especially when there are large differences in organic matter between sources.&#160;

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