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

<p>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.  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.  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.</p><p>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 km<sup>2</sup>), New Zealand.  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.  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.  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.  In total, over 400 model scenarios were tested.</p><p>Numerical mixture testing indicated that the dominant source can have a significant impact on model performance.  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.</p><p> </p>

Erosion modeling and tracing sediment sources at Guarda Mor catchment in southern Brazil

<p>Although sediment yield reflects a catchment’s erosive processes, material transfer from hillslopes to rivers depends on a series of phenomena occurring on variable and continuous range of scales. Physically based, distributed models can be used to evaluate erosion’s spatial variability within a catchment and to identify hotspots. Sediment fingerprinting allows source type discrimination based on sediment and soil properties. The analysis of these dynamic systems could be coupled by addressing hillslope processes with modeling, while fingerprinting enlightens the connection between them and the drainage network. We aimed to evaluate the erosive susceptibility and its spatial distribution in three environmentally fragile paired headwater catchments, nested within Guarda Mor catchment, located in the border of the volcanic plateau in southern Brazil. This catchment is characterized by intense agricultural use, diverse geology, and complex terrain. WATERSED model was used as a dynamic method to evaluate the spatial distribution of hydrologic and erosive fragility during rainfall events. WATERSED was parameterized for modeling surface runoff volume, sediment yield and interrill erosion, based on monitored data from a zero-order no-till catchment and literature data. Modeling results were analyzed for each land use. For fingerprinting, two sediment sampling strategies and source groupings were considered. One considered spatial sources, and the endmembers were the sub catchments, the other considered land use source types within each sub catchment. Deposited bed sediment samples were collected at the outlets of each sub catchment and the main outlet. Soil source samples were collected in crop fields, grasslands, stream channels, forests, and unpaved roads. Crop fields and grasslands compose the source type topsoil. Samples were analyzed by near-infrared spectroscopy. Artificial mixtures were made to calibrate the prediction models. Fifteen Support Vector Machine (SVM) models were built and independently trained. Modeled erosion indicates that the steepest areas and those near the drainage network can be the most susceptible to erosion and runoff. The spatial distribution of runoff-prone areas shows the connectivity from upper segments of these catchments increases with higher magnitude events. In fingerprinting, calibration results’ predictors show good performance by the models, validation results vary from poor to good. SVM models for unpaved roads and forest had the best validation performance. For sourcing tributaries, results and poor validation statistical results indicate the need to use different tracers, and to consider unsampled sources associated to soil and geological differences found downstream from the sub catchment’s outlets. As for the sub catchments, there is a variation among the main sediment sources and a significantly constant contribution from unpaved roads in all of them. Other important sources are topsoil and stream channels, while forests did not show significant contribution. These methodologies were useful in seeking a more holistic process understanding, as physical processes were addressed and later integrated with the resulting sediment yield. Despite the results are modelled, the complementation of their insights indicates that there is a possibility for validating the sediment fingerprinting technique once modelling is validated by monitored and measured data.</p>

Assessing the contribution of natural and anthropogenic processes on sediment dynamics in the Rio Santa (Peru) through sediment fingerprinting

<p>The combination of a changing climate and growing population poses a contemporary challenge for the water-food-energy security nexus in mountain regions, especially in glacier-fed catchments such as the Rio Santa in the Peruvian Andes. Soil erosion due to both natural processes and anthropogenic activities can exacerbate this challenge, with increased levels of sediment in river systems endangering crucial river functions, such as crop irrigation, drinking water, and hydroelectricity. Furthermore, sediment can act as a transport pathway for contaminants, in addition to being a source of contamination itself. Previous studies have suggested that soil erosion related to human activity vastly exceeds the rate of natural soil production in many Andean catchments, where research to date has primarily focused on larger eastern catchments. Smaller western catchments, however, are important for many major Andean cities reliant upon upstream water supplies. It is thus, important to identify sediment sources and better understand sediment dynamics to manage the threats to water supply.</p><p>Sediment fingerprinting approaches are one technique that can contribute to improved understanding of sediment sources and dynamics and the impact of soil erosion in a catchment, and thus contribute to water resource management at the catchment level. Taking a distributed approach along the Rio Santa, this study aims to improve understanding of natural and anthropogenic contributions to sediment production in this Andean system. Key sediment sources explored are glacial sediment potentially enhanced by retreat, agricultural land, forestry operations, land under natural vegetation, and mining. The distributed approach permits quantification of their dynamics throughout the catchment. All source and mixture samples were analysed using Wavelength Dispersive X-ray Fluorescence (WD XRF) to develop geochemical fingerprints and the MixSIAR mixing model was used to apportion sediment sources. While sediment sampling presents a number of challenges when working in remote, mountainous regions such as the Rio Santa catchment, sediment fingerprinting has the potential to help reduce environmental degradation when used to guide local resource management decisions.</p>

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

<p>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  sediment fingerprinting has focussed on the <63µm 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 63µm may form part of suspended sediment and/or occurs as relatively fast-moving fine bedload.  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.</p><p>This study explores this approach using <63µm, 63-125µm, 125-250 µm and 250-2000µm size fractions.  It focuses on the north-south flowing Ribeira dos Covões catchment (6.2 km<sup>2</sup>), 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. </p><p>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 ‘late-wet-season’ and ‘end-of-dry-season’ 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.  (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.  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.  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. </p>

Suitability of phytoliths as a quantitative process tracer for soil erosion studies

<p>Phytoliths are a plant microfossil commonly used as qualitative archive markers in archaeological and paleoecological studies. Their potential uniqueness to the vegetation cover, robustness to weathering, and lack of chemical alteration along the paths make them a potentially suitable tracer for quantitative erosion studies.<br>In this pilot study, we explore the potential of phytoliths in a sediment fingerprinting study in the Ceguera catchment (28 km2) in NE Spain. The phytolith concentrations and morphologies of four land cover classes (agricultural land, badland, forest, and shrubland) were analyzed, and their contributions to four sediment mixture samples along the river course were modelled. Phytoliths concentrations allowed us to discriminate sources sufficiently, albeit with limited sample size. The performance of the phytoliths as the tracer was tested by reproducing the sources of artificial sediment mixture samples with satisfactory recall ratio. Results identified badlands to be the main contributor, with 84–96% of the sediment load to the sinks, followed by shrublands (median 5%) and agricultural lands (median 2%). Additionally, an intensively used agricultural area in the SW of the catchment was well indicated. These major findings can be reproduced by other conventional erosion studies from this area, indicating that phytoliths are suited to quantifying erosion patterns in mesoscale catchments.</p>

From field to stream: Tracing streambed organic carbon origins at a catchment scale

<p>Quantifying organic carbon (OC) levels and the processes altering them is key in unlocking soils potential as a mediator of climate change through sequestration of atmospheric CO<sub>2</sub>. In areas of high soil erosion increased fluxes of OC across the terrestrial-aquatic interface are likely and understanding these fluxes is crucial in integrating lateral OC fluxes within the carbon cycle. For this study of a small UK catchment, OC mapping and Revised Universal Soil Loss Equation (RUSLE) based erosion modelling provided estimates of proportional soil OC loss coming from each land use. Sediment fingerprinting using <em>n</em>-alkane biomarkers and a Bayesian unmixing model provided a comparison of streambed OC proportions by land use to assess which processes were dominating OC input to streams. Results showed that RUSLE-based soil OC loss proportions exhibited disconnect with sediment fingerprinting OC composition and the river corridor and riparian environment were key zones in regulating terrestrial to aquatic fluxes of OC.</p>