11 research outputs found
A deconvolutional Bayesian mixing model approach for river basin sediment source apportionment
Increasing complexity in human-environment interactions at multiple watershed scales presents major challenges to sediment source apportionment data acquisition and analysis. Herein, we present a step-change in the application of Bayesian mixing models: Deconvolutional-MixSIAR (D-MIXSIAR) to underpin sustainable management of soil and sediment. This new mixing model approach allows users to directly account for the 'structural hierarchy' of a river basin in terms of sub-watershed distribution. It works by deconvoluting apportionment data derived for multiple nodes along the stream-river network where sources are stratified by sub-watershed. Source and mixture samples were collected from two watersheds that represented (i) a longitudinal mixed agricultural watershed in the south west of England which had a distinct upper and lower zone related to topography and (ii) a distributed mixed agricultural and forested watershed in the mid-hills of Nepal with two distinct sub-watersheds. In the former, geochemical fingerprints were based upon weathering profiles and anthropogenic soil amendments. In the latter compound-specific stable isotope markers based on soil vegetation cover were applied. Mixing model posterior distributions of proportional sediment source contributions differed when sources were pooled across the watersheds (pooled-MixSIAR) compared to those where source terms were stratified by sub-watershed and the outputs deconvoluted (D-MixSIAR). In the first example, the stratified source data and the deconvolutional approach provided greater distinction between pasture and cultivated topsoil source signatures resulting in a different posterior distribution to non-deconvolutional model (conventional approaches over-estimated the contribution of cultivated land to downstream sediment by 2 to 5 times). In the second example, the deconvolutional model elucidated a large input of sediment delivered from a small tributary resulting in differences in the reported contribution of a discrete mixed forest source. Overall D-MixSIAR model posterior distributions had lower (by ca 25-50%) uncertainty and quicker model run times. In both cases, the structured, deconvoluted output cohered more closely with field observations and local knowledge underpinning the need for closer attention to hierarchy in source and mixture terms in river basin source apportionment. Soil erosion and siltation challenge the energy-food-water-environment nexus. This new tool for source apportionment offers wider application across complex environmental systems affected by natural and human-induced change and the lessons learned are relevant to source apportionment applications in other disciplines
Capabilities and Choices: Do They Make Sen'Se for Understanding Objective and Subjective Well-Being?: An Empirical Test of Sen's Capability Framework on German and British Panel Data
Late Pleistocene Upwelling Variability on the Pacific Shelf of Baja California and in the Santa Barbara Basin
International audienceno abstrac
Machine-learning techniques for geochemical discrimination of 2011 Tohoku tsunami deposits
Varved glaciomarine clay in central Sweden before and after the Baltic Ice Lake drainage: a further clue to the drainage events at Mt Billingen
Does global warming favour the occurrence of extreme floods in European Alps? First evidences from a NW Alps proglacial lake sediment record
Diatom assemblage changes in lacustrine sediments from Isla de los Estados, southernmost South America, in response to shifts in the southwesterly wind belt during the last deglaciation
Climates of the last three interglacials in subtropical eastern Australia inferred from wetland sediment geochemistry
Records of Australian climate during Marine Isotope Stages 5 and 7 (130–71 and 243–191 ka) are rare, preventing detailed assessments of long-term climate, drivers and ecological responses across the continent over glacial-interglacial timescales. This study presents a geochemistry-based palaeoclimate record from Fern Gully Lagoon on North Stradbroke Island (also known as Minjerribah) in subtropical eastern Australia, which records climates in MIS 7a–c, MIS 5 and much of the Holocene, in addition to MIS 4 (71–57 ka), and parts of MIS 6, MIS 3 and MIS 2 (191–130, 57–29 and 29–14 ka). Indicators of inorganic sedimentation from a 9.5 m sediment core – focussed on high-resolution estimates of sediment geochemistry supported by x-radiography, inorganic content and magnetic susceptibility – were combined with a chronology consisting of six radiocarbon (14C) and thirteen single-grain optically stimulated luminescence (OSL) ages. Hiatuses occurred at ~178–153 ka, ~36–21 ka and ~7–2 ka and likely result from the wetland drying. Low values of locally sourced aeolian materials indicate a wet MIS 7a–c and early MIS 6 before a relatively dry MIS 5. Inorganic flux during the Holocene was up to four times greater than during MIS 5, consistent with long-term interglacial drying observed in other regions, most notably in central Australia. This study highlights the importance of employing a combination of multiple dating approaches and calibrated geochemical proxies to derive climate reconstructions and to identify depositional complexities in organic-rich wetland records.C.W. Kemp, J. Tibby, L.J. Arnold, C. Barr, P.S. Gadd, J.C. Marshall, G.B. McGregor, G.E. Jacobse