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  • 1
    Publication Date: 2022-09-22
    Description: Shallow earthquakes frequently disturb the hydrological and mechanical state of the subsurface, with consequences for hazard and water management. Transient post‐seismic hydrological behavior has been widely reported, suggesting that the recovery of material properties (relaxation) following ground shaking may impact groundwater fluctuations. However, the monitoring of seismic velocity variations associated with earthquake damage and hydrological variations are often done assuming that both effects are independent. In a field site prone to highly variable hydrological conditions, we disentangle the different forcing of the relative seismic velocity variations δv retrieved from a small dense seismic array in Nepal in the aftermath of the 2015 Mw 7.8 Gorkha earthquake. We successfully model transient damage effects by introducing a universal relaxation function that contains a unique maximum relaxation timescale for the main shock and the aftershocks, independent of the ground shaking levels. Next, we remove the modeled velocity from the raw data and test whether the corresponding residuals agree with a background hydrological behavior we inferred from a previously calibrated groundwater model. The fitting of the δv data with this model is improved when we introduce transient hydrological properties in the phase immediately following the main shock. This transient behavior, interpreted as an enhanced permeability in the shallow subsurface, lasts for ∼6 months and is shorter than the damage relaxation (∼1 yr). Thus, we demonstrate the capability of seismic interferometry to deconvolve transient hydrological properties after earthquakes from non‐linear mechanical recovery.
    Description: Plain Language Summary: Earthquake ground shaking damage the rocks in the subsurface of the Earth, altering their strength and their permeability. After the main shock, the rock properties slowly return to their pre‐earthquake state, but the duration of this recovery is poorly constrained. One way to investigate these time‐dependent changes is through the monitoring of seismic velocity inferred from ambient ground vibration recorded at seismic stations. Here, we constrain the evolution of seismic velocity following the large 2015 Mw 7.8 Gorkha earthquake in Nepal, in a field site characterized by seasonal groundwater fluctuations. We find that the velocity recoveries after the main shock and the aftershocks can be modeled with the same recovery timescale, independently from the initial shaking intensity. This suggests that earthquakes of different sizes activate the same geological structures and mechanisms during the recovery phase. Thanks to the unique hydrological setting of our field site and a model that links seismic velocity and groundwater level, we also show that this change of rock properties after the main shock is accompanied by a transient change in hydrological properties, an observation inferred for the first time with seismic measurement.
    Description: Key Points: We estimate a recovery time scale (〈1 yr) in seismic velocity changes after the Gorkha earthquake using ambient noise correlations. Velocity recoveries are modeled with relaxation functions characterized by a constant maximum relaxation timescale that is peak ground velocity‐independent. We highlight a transient enhanced permeability from the velocity changes in the first ∼6 months following the main shock.
    Description: GFZ HART program
    Description: https://doi.org/10.5880/GFZ.4.6.2021.002
    Description: https://doi.org/10.14470/KA7560056170
    Keywords: ddc:551.22
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2024-02-09
    Description: Tracing pathways and transformations of particulate organic carbon from landscape sources to oceanic sinks is commonly done using the isotopic composition or biomarker content of particulate organic matter (POM). However, similarity of source characteristics and complex mixing in rivers often preclude a robust deconvolution of individual contributions. Moreover, these approaches are limited in detecting organic matter transformations. This impedes understanding of carbon cycling. Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT‐ICR‐MS) can simultaneously identify many molecular formulas from mixtures of organic matter, and provide direct information on its compositional variability. Here, we investigate how FT‐ICR‐MS can give insight into POM dynamics on a landscape scale, focusing on the trans‐Himalayan Kali Gandaki River, Nepal. Using molecular information, we identify source tracers in the solvent extractable lipid fraction of riverine POM, finding up to 102 indicative molecular formulas for individual sources. Further, we assess molecular transformations of the lipid fraction of POM during its transfer from litter into topsoil, and onwards into the river. A large number of shared mass formulas and a well‐preserved isoprenoidal patterns suggest efficient incorporation of litter into topsoil. In contrast, we observe a selective loss of mass formulas and a preferential export of formulas with low double bond equivalents and a low nominal oxidation state of carbon after organic matter entrainment in the river. Our results demonstrate the potential of FT‐ICR‐MS for source‐to‐sink studies, allowing detailed organic matter source characterization and discrimination, and tracking of molecular transformations along organic matter pathways spanning different spatial and temporal scales.
    Description: Plain Language Summary: The transfer of organic matter (OM) by rivers from landscape sources into the ocean followed by its burial in marine sediments is an important carbon sink. Therefore, OM is often traced along this journey using its isotopic or biomarker composition. But contributions of OM sources to river sediments can be difficult to estimate because of similar source characteristics, mixing of many sources and changes of the molecular composition along the way. Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT‐ICR‐MS) is a novel method able to identify many molecular formulas from OM mixtures at once providing direct information about their molecular composition. Here, we investigate how FT‐ICR‐MS contributes to understanding the transport and transformation of particulate OM focusing on a Himalayan river in Nepal. We use the molecular information to identify tracers for individual OM sources in the landscape. We then assess molecular transformations during the transfer of litter into topsoil, and onwards into the river. Our data suggest efficient incorporation of litter into topsoil, but we observe a selective loss of molecular formulas upon entrainment of sources into the river. Our results reveal that FT‐ICR‐MS is useful for detailed source characterization and tracking of molecular transformations along OM pathways.
    Description: Key Points: Organic matter sourcing and transformations in a Himalayan river studied by FT‐ICR‐MS measurements of solvent extractable lipids. Identification of up to 102 indicator mass formulas for different organic matter sources in the landscape using indicator species analysis. Mass formulas preserved during incorporation of litter into topsoil but selectively lost during entrainment of sources into the river.
    Description: Helmholtz Impuls und Vernetzungsfond
    Description: GFZ expedition funding
    Description: http://doi.org/10.5880/GFZ.4.6.2022.002
    Keywords: ddc:551 ; particulate organic carbon ; solvent extractable lipids ; FT‐ICR‐MS ; Himalaya ; carbon cycling ; indicator species analysis
    Language: English
    Type: doc-type:article
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  • 3
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] The erosion of mountain belts controls their topographic and structural evolution and is the main source of sediment delivered to the oceans. Mountain erosion rates have been estimated from current relief and precipitation, but a more complete evaluation of the controls on erosion rates ...
    Type of Medium: Electronic Resource
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  • 4
    Publication Date: 2023-06-21
    Description: To document distinct sources of particulate organic carbon (POC) to the Río Bermejo, we collected 15 soil and 13 leaf litter samples from the local floodplain, and 10 bedrock (predominantly outcroppings of fine-grained sedimentary bedrock) and 2 soil samples from the Río Bermejo headwaters. Leaf litter and soil were oven-dried at 40°C for 〉48 hours. We shredded leaf litter in an industrial blender, homogenized soil samples in an agate mortar and manually removed root and plant debris 〉1 cm, and pulverized bedrock samples to 〈63 µm.
    Keywords: AR15DS-001; AR15DS-005a; AR15DS-005b; AR15DS-008; AR15DS-010b; AR15DS-013; AR15DS-015; AR15DS-016; AR15DS-018; AR15DS-021; AR15DS-045-S; AR15DS-052-S; AR17MR-18; AR17MR-37; AR17MR-38; AR17MR-48; AR17MR-49; Argentina; biogeochemistry; Bucket, plastic; Calculated; Carbon, organic, total; Carbon, organic/Nitrogen, total ratio; DATE/TIME; DEPTH, sediment/rock; Distance; El Colgado; Element analyser (EA); Element analyser isotope ratio mass spectrometer (EA-IRMS); Element analyzer coupled to an accelerator mass spectrometer (EA-AMS); Event label; Fraction modern carbon; Latitude of event; Longitude of event; meandering river; Median, grain size; Nitrogen, total; Nitrogen, total/Carbon, organic ratio; organic carbon (OC); Particle size analyser (Retsch/Horiba LA-950V2); PLV_LL11032018; Puerto lavalle; Reserva Natural Formosa; river sediment; RNF_LL12_3_18; RSF-RB confluence; Sample comment; Sample ID; Sample type; ST15-52; ST15-71; StRATEGy; StRATEGy international research training group; SZ_LL12_3_18; Villa Rio Bermejito; WB; δ13C, organic carbon
    Type: Dataset
    Format: text/tab-separated-values, 222 data points
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  • 5
    Publication Date: 2023-06-21
    Description: These data were collected from the Río Bermejo in northern Argentina. To determine the seasonal variability in the particulate organic carbon composition of exported river sediment, we collected weekly suspended sediment samples (March 2016 to March 2018) at the Puente Lavalle (PLV) monitoring site, ~870 river km downstream of the mountain front (-25.655°S, -60.130°W). Surface water samples were collected from a bridge using a river-rinsed bucket and were filtered through a 0.22 µm polyethersulfone membrane. Samples were stored on site at ambient temperatures for up to one year, transferred to Germany and subsequently stored at ~4°C until processing. Suspended sediment was rinsed from filters into pre-combusted glass evaporating dishes using ultra-pure (18.2 M) water, oven-dried at 40°C for 〉48 hr, and homogenized in an agate mortar without crushing. Geochemical and grain size analyses required 0.8 g sediment; for samples 〈0.8 g, we combined consecutive weekly samples to create a new bulk sample of 〉0.8 g (Table S1). We split sediment samples into aliquots for grain size analysis via laser diffraction and geochemical analyses. Sediment particle size distributions were measured on ~0.2 g aliquots using a laser diffraction particle size analyzer (Retsch/Horiba LA-950V2). Aliquots for geochemical analyses were ground to 〈63 µm. The homogenized suspended sediment, bedrock, soil and leaf litter aliquots were further split for total nitrogen measurement (TN, wt%) and organic carbon analyses including total organic carbon (TOC, wt%), stable carbon isotope composition (δ13COC), and radiocarbon fraction modern (Fm). We decarbonated the aliquots for POC measurements using a liquid HCl leach following Galy et al., (2007). TOC and TN measurements were split between facilities at the German Research Centre for Geosciences (GFZ), Durham University, and University of Nevada Reno (UNR) using an elemental analyzer (EA). δ13COC was measured with a coupled EA-isotope ratio mass spectrometer (EA-IRMS). All isotopic compositions are reported using standard delta (δ) notation in per mil (‰) relative to Vienna PeeDee Belemnite (VPDB). Calibration and accuracy were monitored through analyses of in-house standards (Glutamic Acid, 40.82% C, 9.52% N at Durham; Boden3, HEKATECH at GFZ), which were calibrated against international standards (e.g., USGS 40, USGS 24, IAEA 600, IAEA CH3, IAEA CH7, IAEA N1, IAEA N2). Radiocarbon content was measured for a subset of 29 samples at ETH Zürich using a combined EA and accelerator mass spectrometer (EA-AMS) (Ruff et al. 2010; McIntyre et al., 2017). All 14C /12C ratios are reported as fraction modern (Fm, equivalent to F14C as defined by Reimer et al. (2004)) relative to 95% of the 14C activity of NBS Oxalic Acid II in 1950 (δ13COC = -17.8‰) and normalized to δ13COC = -25‰ of VPDB.\n\nThis geochemical dataset is supported by hydrologic measurements of daily water discharge at the El Colorado gauging station (river km 1086, SNIH, https://snih.hidricosargentina.gob.ar/) collected between 2016 and 2018.
    Keywords: biogeochemistry; Bucket, plastic; Calculated; Carbon, organic, total; Carbon, organic/Nitrogen, total ratio; DATE/TIME; Element analyser (EA); Element analyser isotope ratio mass spectrometer (EA-IRMS); Element analyzer coupled to an accelerator mass spectrometer (EA-AMS); Event label; Fraction modern carbon; Latitude of event; Longitude of event; meandering river; Median, grain size; Nitrogen, total; Nitrogen, total/Carbon, organic ratio; organic carbon (OC); Particle size analyser (Retsch/Horiba LA-950V2); PLV_01042016; PLV_01062016; PLV_01062017; PLV_01122017; PLV_02012018; PLV_02092016; PLV_02122016; PLV_04052017; PLV_06012017; PLV_06052016; PLV_06072016; PLV_06082016; PLV_07022018; PLV_07042017; PLV_07102016; PLV_08042016; PLV_08052017; PLV_08122016; PLV_09062017; PLV_09082017; PLV_09112017; PLV_10062016; PLV_11122017; PLV_12012018; PLV_12042016; PLV_12062017; PLV_12072016; PLV_12072017; PLV_12082016; PLV_13012017; PLV_14042017; PLV_14052016; PLV_16022018; PLV_16092016; PLV_16122016; PLV_17062016; PLV_18012017; PLV_18032016; PLV_19012018; PLV_19052017; PLV_19082016; PLV_20052016; PLV_20122017; PLV_21022018; PLV_21042017; PLV_22042016; PLV_22072016; PLV_23122016; PLV_24012018; PLV_24032016; PLV_24032017; PLV_24062016; PLV_24102016; PLV_24112016; PLV_26072017; PLV_26082016; PLV_27012017; PLV_27052016; PLV_27062016; PLV_28042017; PLV_28062017; PLV_28122017; PLV_29042016; PLV_29072016; PLV_29092017; PLV_30032017; PLV_30122016; PLV_31012018; PLV_31082017; Puerto lavalle; River discharge, daily; river sediment; Sample comment; Sample ID; Sampling date; Season; StRATEGy; StRATEGy international research training group; WB; δ13C, organic carbon
    Type: Dataset
    Format: text/tab-separated-values, 696 data points
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  • 6
    Publication Date: 2023-06-21
    Description: To determine the depositional age and the long-term delivery of meteoric 10Be (10Bem) to the Rio Bermejo floodplain (northern Argentina), we collected floodplain sediment samples at four locations identified as point bars of abandoned Rio Bermejo channels. We used a stainless-steel hand auger to collect sediment down to a maximum depth of ~5 m, or until refusal. For 10Bem and 9Bereac analysis, we extracted samples that integrated material from 0-20 cm below the surface, 20-50 cm, and regularly spaced 40 cm intervals for lower depths. We homogenized the material prior to packing into clean plastic bags. Sediment particle size distributions were measured on ~10 mg aliquots using a laser diffraction particle size analyzer (Horiba LA-950). The total reactive phase, including amorphous oxyhydroxides and crystalline oxide grain coatings, was extracted from the sediment samples using a procedure adapted from Wittmann et al. (2012, doi:10.1016/j.chemgeo.2012.04.031). 10Be was purified from the extracted material, spiked with a 9Be carrier solution containing 150 µg of 9Be, and packed into targets for AMS measurement at the University of Cologne Centre for Accelerator Mass Spectrometry (Cologne, Germany). 10Be/9Be measurements were normalized to the KN01-6-2 and KN01-5-3 standards (Dewald et al., 2013, doi:10.1016/j.nimb.2012.04.030) that are consistent with a 10Be half-life of 1.36 ± 0.07 x10 yrˉ¹ (Nishiizumi et al., 2007, doi:10.1016/j.nimb.2007.01.297). 10Bem was calculated from the normalized and blank-corrected 10Be/9Be ratios. The reported 1σ uncertainties include counting statistics and the uncertainties of both standard normalization and blank correction. Stable 9Be concentrations were measured on a separate aliquot of the sample solution using inductively coupled plasma optical emission spectroscopy (ICP-OES). Uncertainty of ICP-OES measurements was 5%. We used coarse quartz grain OSL analysis to determine depositional ages for each floodplain core. For OSL analysis, we collected light-sealed samples by driving an opaque tube into our floodplain cores at two select depths in each core. OSL measurements were performed using a Risø DA 15 OSL/TL reader equipped with a 90Sr beta irradiator (4.9 Gy/min). OSL signals were stimulated with blue LEDs (470 nm, 50 s, 125 ºC) and detected through an optical filter (U 340 Hoya). For each sample, 40 aliquots were measured using the single-aliquot regenerative dose (SAR) protocol (Murray and Wintle, 2000, doi:10.1016/S1350-4487(03)00053-2) for equivalent dose determination.
    Keywords: Accelerator mass spectrometry (AMS); Age, error; Age, maximum/old; Age, minimum/young; Age, optical stimulated luminescence (OSL); Age, soil; ALTITUDE; Beryllium-10; Beryllium-10, standard deviation; Beryllium-10/Beryllium-9; Beryllium-10/Beryllium-9, standard deviation; Beryllium-9; Beryllium-9, standard deviation; Clay minerals; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Dose recovery test; Event label; Gas sorption analyszer (Quantachrome NOVAtouch LX) and BET-method (Brunauer et al., 1938); Grain Size; HADR; Hand auger (drill); LATITUDE; LONGITUDE; Mass; Median, grain size; meteoric 10Be; Number of subsamples; OSL; Paleodose; Paleodose, standard deviation; Profile; river sediment; Sample ID; Skewness; SP_1; SP_2; SP_3; SP_4; Specific surface area
    Type: Dataset
    Format: text/tab-separated-values, 482 data points
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  • 7
    Publication Date: 2023-06-21
    Description: To test the potential of meteoric 10Be (10Bem) as a river sediment transit time proxy, we measured 10Bem concentrations in river suspended sediment of the Rio Bermejo (northern Argentina), which is a river with a ~1300 km lowland flowpath void of tributaries. We collected fluvial suspended sediment in vertical depth profiles at five sampling locations along the length of the Rio Bermejo (northern Argentina) during near-bankfull conditions, when discharge varied between 675 and 1080 m**3/s and banks were actively eroding. Additionally, we collected one depth profile from Rio San Francisco (RSF) and one from the Rio Bermejo 10 km upstream of the RSF confluence. Combining these profiles and weighting them by the relative proportions of their total sediment load input to the mainstem Bermejo serves as an integrated headwater depth profile. In the thalweg, we collected water and suspended sediment from a boat using a weighted 8-liter horizontal sampling bottle (Wildco Beta Plus bottle) with an attached pressure transducer to measure sampling depth. We separated sediment from the water using a custom-built 5-liter pressurized filtration unit with a 293 mm diameter, 0.2 µm polyethersulfone filter. In the laboratory, we rinsed sediment off the filters directly into an evaporating dish with ultrapure 18.2 MΩ water (pH~7; when needed, we added NH3 solution to the water to maintain pH~7). Samples were dried in an oven at 40ºC, and subsequently homogenized. Sediment particle size distributions were measured on ~10 mg aliquots using a laser diffraction particle size analyzer (Horiba LA-950). Specific surface area (SSA) of bulk sediment samples was measured on ~4 g aliquots using a Quantachrome NOVAtouch LX gas sorption analyzer and the Brunauer, Emmett, and Teller (BET) theory (Brunauer et al., 1938). The total reactive phase, including amorphous oxyhydroxides and crystalline oxide grain coatings, was extracted from the sediment samples using a procedure adapted from Wittmann et al. (2012, doi:10.1016/j.chemgeo.2012.04.031). 10Bem was purified from the extracted material, spiked with a 9Be carrier solution containing 150 µg of 9Be, and packed into targets for AMS measurement at the University of Cologne Centre for Accelerator Mass Spectrometry (Cologne, Germany). 10Be /9Be measurements were normalized to the KN01-6-2 and KN01-5-3 standards (Dewald et al., 2013, doi:10.1016/j.nimb.2012.04.030) that are consistent with a 10Be half-life of 1.36 ± 0.07 x10^6 yrˉ¹ (Nishiizumi et al., 2007, doi:10.1016/j.nimb.2007.01.297). [10Be]m was calculated from the normalized and blank-corrected 10Be/9Be ratios. The reported 1σ uncertainties include counting statistics and the uncertainties of both standard normalization and blank correction. Stable 9Be concentrations were measured on a separate aliquot of the sample solution using inductively coupled plasma optical emission spectroscopy (ICP-OES). Uncertainty of ICP-OES measurements was 5%.
    Keywords: Accelerator mass spectrometry (AMS); AR17DS-001; AR17MR-05; AR17MR-06; AR17MR-07; AR17MR-08; AR17MR-11; AR17MR-12; AR17MR-13; AR17MR-14; AR17MR-24; AR17MR-25; AR17MR-26; AR17MR-27; AR17MR-30; AR17MR-31; AR17MR-32; AR17MR-33; AR17MR-34; AR17MR-35; AR17MR-36; AR17MR-42; AR17MR-43; AR17MR-44; AR17MR-45; AR17MR-46; Beryllium-10; Beryllium-10, standard deviation; Beryllium-10/Beryllium-9; Beryllium-10/Beryllium-9, standard deviation; Beryllium-9; Beryllium-9, standard deviation; Calculated/normalized; CONFLUENCE; DEPTH, water; Distance; El Colgado; ELEVATION; Embarcacion; Event label; Gas sorption analyszer (Quantachrome NOVAtouch LX) and BET-method (Brunauer et al., 1938); General Mansilla; Grain Size; integrated; LATITUDE; LONGITUDE; Median, grain size; meteoric 10Be; OSL; pH; Puerto lavalle; Reserva Natural Formosa; Rio San Francisco; river sediment; Sample ID; Scattering Particle Size Distribution Analyzer LA-950 (Horiba); Size fraction 〈 0.063 mm, mud, silt+clay; Specific surface area; Suspended sediment concentration
    Type: Dataset
    Format: text/tab-separated-values, 401 data points
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  • 8
    Publication Date: 2023-06-21
    Description: These data were collected from the Río Bermejo in northern Argentina. To determine the seasonal variability in the particulate organic carbon composition of exported river sediment, we collected weekly suspended sediment samples (March 2016 to March 2018) at the Puente Lavalle (PLV) monitoring site, ~870 river km downstream of the mountain front (-25.655°S, -60.130°W). Surface water samples were collected from a bridge using a river-rinsed bucket and were filtered through a 0.22 µm polyethersulfone membrane. Samples were stored on site at ambient temperatures for up to one year, transferred to Germany and subsequently stored at ~4°C until processing. To document distinct sources of particulate organic carbon (POC) to the Río Bermejo, we collected 15 soil and 13 leaf litter samples from the local floodplain, and 10 bedrock (predominantly outcroppings of fine-grained sedimentary bedrock) and 2 soil samples from the Río Bermejo headwaters. Suspended sediment was rinsed from filters into pre-combusted glass evaporating dishes using ultra-pure (18.2 M) water, oven-dried at 40°C for 〉48 hr, and homogenized in an agate mortar without crushing. Leaf litter and soil were oven-dried at 40°C for 〉48 hours. We shredded leaf litter in an industrial blender, homogenized soil samples in an agate mortar and manually removed root and plant debris 〉1 cm, and pulverized bedrock samples to 〈63 µm. Geochemical and grain size analyses required 0.8 g sediment; for samples 〈0.8 g, we combined consecutive weekly samples to create a new bulk sample of 〉0.8 g (Table S1). We split sediment samples into aliquots for grain size analysis via laser diffraction and geochemical analyses. Sediment particle size distributions were measured on ~0.2 g aliquots using a laser diffraction particle size analyzer (Retsch/Horiba LA-950V2). Aliquots for geochemical analyses were ground to 〈63 µm. The homogenized suspended sediment, bedrock, soil and leaf litter aliquots were further split for total nitrogen measurement (TN, wt%) and organic carbon analyses including total organic carbon (TOC, wt%), stable carbon isotope composition (δ13COC), and radiocarbon fraction modern (Fm). We decarbonated the aliquots for POC measurements using a liquid HCl leach following Galy et al. (2007, doi:10.1111/j.1751-908X.2007.00864.x)). TOC and TN measurements were split between facilities at the German Research Centre for Geosciences (GFZ), Durham University, and University of Nevada Reno (UNR) using an elemental analyzer (EA). δ13COC was measured with a coupled EA-isotope ratio mass spectrometer (EA-IRMS). All isotopic compositions are reported using standard delta (δ) notation in per mil (‰) relative to Vienna PeeDee Belemnite (VPDB). Calibration and accuracy were monitored through analyses of in-house standards (Glutamic Acid, 40.82% C, 9.52% N at Durham; Boden3, HEKATECH at GFZ), which were calibrated against international standards (e.g., USGS 40, USGS 24, IAEA 600, IAEA CH3, IAEA CH7, IAEA N1, IAEA N2). Radiocarbon content was measured for a subset of 29 samples at ETH Zürich using a combined EA and accelerator mass spectrometer (EA-AMS) (Ruff et al. (2010, doi:10.1017/S003382220005637X); McIntyre et al. (2017, doi:10.1017/RDC.2016.68)). All 14C /12C ratios are reported as fraction modern (Fm, equivalent to F14C as defined by Reimer et al. (2004)) relative to 95% of the 14C activity of NBS Oxalic Acid II in 1950 (δ13COC = -17.8‰) and normalized to δ13COC = -25‰ of VPDB. This geochemical dataset is supported by hydrologic measurements of daily water discharge at the El Colorado gauging station (river km 1086, SNIH, https://snih.hidricosargentina.gob.ar/) collected between 2016 and 2018.
    Keywords: biogeochemistry; meandering river; organic carbon (OC); river sediment; StRATEGy; StRATEGy international research training group
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 9
    Publication Date: 2023-06-21
    Description: To study the transformation of organic carbon through long distance transport in rivers, we measured the composition of bulk organic carbon in river suspended sediment of the Rio Bermejo (northern Argentina). This river has a ~1300 km lowland flowpath with no significant tributaries. We collected fluvial suspended sediment in vertical depth profiles at five sampling locations along the length of the Rio Bermejo (northern Argentina) during near-bankfull conditions, when discharge varied between 675 and 1080 m3/s and banks were actively eroding. Additionally, we collected one depth profile from the Rio San Francisco (RSF) and one from the Rio Bermejo 10 km upstream of the RSF confluence. Combining these profiles and weighting them by the relative proportions of their total sediment load input to the mainstem Bermejo serves as a depth profile representing the headwaters. At each depth profile location, we collected water and suspended sediment from the channel thalweg by boat. We used a weighted 8-liter horizontal sampling bottle (Wildco Beta Plus bottle) with an attached pressure transducer to measure sampling depth. We separated sediment from the water using a custom-built 5-liter pressurized filtration unit with a 293 mm diameter, 0.2 µm polyethersulfone filter. In the laboratory, we rinsed sediment off the filters directly into an evaporating dish with ultrapure 18.2 MΩ water (pH~7). Samples were dried in an oven at 40ºC, and subsequently homogenized. Sediment particle size distributions were measured on ~10 mg aliquots using a laser diffraction particle size analyzer (Horiba LA-950). Specific surface area (SSA) of bulk sediment samples was measured on ~4 g aliquots using a Quantachrome NOVAtouch LX gas sorption analyzer and the Brunauer, Emmett, and Teller (BET) theory (Brunauer et al., 1938). Aliquots for organic carbon measurements were first treated with 4% HCl solution to remove inorganic carbon, following Galy et al. (2007, doi:10.1111/j.1751-908X.2007.00864.x). Total organic carbon (TOCPOC) and δ13C of POC was measured in duplicate at Durham University using a Costech elemental analyzer (EA) coupled to a CONFLO III and Thermo Scientific Delta V Advantage isotope ratio mass spectrometer (IRMS). Radiocarbon content was measured using an EA coupled to an accelerator mass spectrometer (EA-AMS) at ETH Zurich. We report 14C content as fraction modern (F14C), by normalizing measurements to 95% of the 1950 NBS Oxalic Acid II standard (δ13C = -17.8‰) and correcting for mass-dependent fractionation using a common δ13C value of -25‰. OC loading is the mass of organic carbon in a sample normalized by the sample's specific surface area (SSA). Reactive metals in the amorphous oxyhydroxide and crystalline oxide grain coatings, were extracted from the sediment samples using a procedure adapted from Wittmann et al. (2012, doi:10.1016/j.chemgeo.2012.04.031). The extracted oxyhydroxides and oxides were dried down and diluted in 3M HNO3. A 100 μl aliquot was taken for measurement of metal concentrations. Al, Fe, Mg, and Mn concentrations were measured using inductively coupled plasma optical emission spectroscopy (ICP-OES). Uncertainty of ICP-OES measurements was 〈5%. All depth-integrated values are calculated as a function of the suspended sediment concentration relative to the depth-averaged suspended sediment concentration.
    Keywords: Aluminium, reactive; AR17MR-05; AR17MR-06; AR17MR-07; AR17MR-08; AR17MR-11; AR17MR-12; AR17MR-13; AR17MR-14; AR17MR-24; AR17MR-25; AR17MR-26; AR17MR-27; AR17MR-30; AR17MR-31; AR17MR-32; AR17MR-33; AR17MR-34; AR17MR-35; AR17MR-36; AR17MR-42; AR17MR-43; AR17MR-44; AR17MR-45; AR17MR-46; Carbon, organic, loading; Carbon, organic, loading, standard error; Carbon, organic, total; Carbon, organic, total, standard error; CONFLUENCE; DATE/TIME; Depth, relative; Depth comment; Distance; El Colgado; Element analyser CHN (Costech) coupled to a CONFLO III and Thermo Scientific Delta V Advantage isotope ratio mass spectrometer (IRMS); Element analyzer coupled to an accelerator mass spectrometer (EA-AMS); ELEVATION; Embarcacion; Event label; Fraction modern carbon; Fraction modern carbon, standard error; Gas sorption analyszer (Quantachrome NOVAtouch LX) and BET-method (Brunauer et al., 1938); General Mansilla; Grain Size; ICP-OES, Inductively coupled plasma - optical emission spectrometry; Iron, reactive; LATITUDE; LONGITUDE; Magnesium, reactive; Manganese, reactive; Median, grain size; Normalized; oxyhydroxide; Particulate organic carbon; Puerto lavalle; radiocarbon; Reactive minerals, total; Reserva Natural Formosa; Rio San Francisco; river sediment; Sample ID; Scattering Particle Size Distribution Analyzer LA-950 (Horiba); Sediment transit time; Sediment transit time, uncertainty; Size fraction 〈 0.030 mm; Specific surface area; surface area; Suspended sediment concentration; TOC; Weighted average; δ13C; δ13C, standard error
    Type: Dataset
    Format: text/tab-separated-values, 528 data points
    Location Call Number Limitation Availability
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  • 10
    Publication Date: 2023-10-13
    Description: Additionally, we employed a local resident to collect surface water suspended sediment samples at river km 865 throughout the 2017-2018 water year. These samples were collected in a bucket, the sediment was allowed to settle, and then the water was decanted off the top. Recovered sediment was stored in sterile Whirlpak bags, and then dried in an oven at 40°C. We homogenized and disaggregated the dry sediment using a mortar and pestle, and removed coarse plant material 〉1 mm. For each sample, we weighed an aliquot of sediment and loaded the material into aluminum cells for lipid extraction. Total lipid extracts (TLE) were recovered using an accelerated solvent extraction system (Dionex ASE) with 9:1 v/v dichloromethane: methanol. We added exactly 10 µg of internal standard (5-a-Androstane) to the TLE for unknown compound quantification. We then separated the TLE into three fractions using silica gel column chromatography with hexane (alkanes), 1:1 v/v hexane: dichloromethane (ketones), and 1:1 v/v dichloromethane: methanol (alcohols + acids) (Rach et al., 2020; doi:10.1016/j.orggeochem.2020.103995). Unsaturated compounds were removed from the alkane fraction using AgNO3-silica gel column chromatography with n-hexane (saturated n-alkanes) and DCM (unsaturated n-alkanes). n-alkanes were identified and quantified using an Agilent gas chromatograph (GC 7890-A) with flame ionization detection (FID) coupled to a single quadrupole mass spectrometer (MS 5975-C). We quantified n-alkane concentrations relative to the peak response of the internal standard, and then normalized the abundance to the sediment mass. We measured n-alkane d13C via GC-C-IRMS (gas chromatography/combustion/isotope-ratio mass spectrometry) with helium as a carrier gas (Agilent 7890N, ThermoFisher Delta V Plus). All compounds were measured in triplicate with a standard deviation of =0.5‰. Measurement quality was checked regularly by measuring n-alkane standards (nC15, nC20, nC25) with known isotopic composition (provided by Campro Scientific, Germany). d13C values were normalized to the Vienna Pee Dee Belemnite (VPDB) standard. We measured n-alkane d2H via GC-IRMS using a ThermoFisher Scientific Trace GC 1310 coupled to a Delta-V isotope ratio mass spectrometer. All d2H measurements were made in duplicate, and measurement quality was checked with d2H values were normalized to the Vienna Standard Mean Ocean Water (VSMOW) standard using an n-alkane standard mix with known d2H values (nC16 - nC30, from A. Schimmelman/Indiana University).
    Keywords: Accelerated Solvent Extraction (Dionex ASE); Average chain length; Biomarker; Bucket, plastic; Carbon, organic, total; Carbon Preference Index; Compound-specific Isotopes; Date/Time of event; Date/Time of event 2; Distance; Event label; Fraction modern carbon, organic; Fraction modern carbon, organic, error; Gas chromatography (Agilent GC 7890-A) with flame ionization detection (FID) coupled to a single quadrupole mass spectrometer (MS 5975-C); Gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) with helium as a carrier gas (Agilent 7890N, ThermoFisher Delta V Plus); Gas chromatography - Isotope ratio mass spectrometer (GC-IRMS) (ThermoFisher Scientific Trace GC 1310) coupled to a Delta-V isotope ratio mass spectrometer; Latitude of event; Longitude of event; Median, grain size; n-Alkane, (C31+C33)/(C27+C29) ratio; n-Alkane, sum, per unit mass total organic carbon; n-Alkane, total per unit sediment mass; n-Alkane C16, per unit sediment mass; n-Alkane C17, per unit sediment mass; n-Alkane C18, per unit sediment mass; n-Alkane C19, per unit sediment mass; n-Alkane C20, per unit sediment mass; n-Alkane C21, per unit sediment mass; n-Alkane C22, per unit sediment mass; n-Alkane C23, per unit sediment mass; n-Alkane C24, per unit sediment mass; n-Alkane C25, per unit sediment mass; n-Alkane C26, per unit sediment mass; n-Alkane C27, per unit sediment mass; n-Alkane C27, δ13C; n-Alkane C27, δ13C, standard deviation; n-Alkane C27, δD; n-Alkane C27, δD, standard deviation; n-Alkane C28, per unit sediment mass; n-Alkane C29, per unit sediment mass; n-Alkane C29, δ13C; n-Alkane C29, δ13C, standard deviation; n-Alkane C29, δD; n-Alkane C29, δD, standard deviation; n-Alkane C30, per unit sediment mass; n-Alkane C31, per unit sediment mass; n-Alkane C31, δ13C; n-Alkane C31, δ13C, standard deviation; n-Alkane C31, δD; n-Alkane C31, δD, standard deviation; n-Alkane C32, per unit sediment mass; n-Alkane C33, per unit sediment mass; n-Alkane C33, δ13C; n-Alkane C33, δ13C, standard deviation; n-Alkane C33, δD; n-Alkane C33, δD, standard deviation; n-Alkane C34, per unit sediment mass; n-Alkane C35, per unit sediment mass; n-alkanes; n-Alkanes, total mass; PLV_01062017; PLV_07092017; PLV_09072017; PLV_11122017; PLV_12012018; PLV_12062017; PLV_16032018; PLV_21022018; Puerto lavalle; River discharge; river sediment; Sample ID; Sample mass; Sampling date; Size fraction 〈 0.030 mm; WB; δ13C, organic carbon
    Type: Dataset
    Format: text/tab-separated-values, 423 data points
    Location Call Number Limitation Availability
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