A 25-kyr record of East African monsoon variability: Insights from grain-size distributions and end-member modeling of siliciclastic sediments from Lake Chala

2020 ◽  
Author(s):  
Inka Meyer ◽  
Maarten Van Daele ◽  
Niels Thange ◽  
Dirk Verschuren ◽  
Marc De Batist
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
East Africa ◽  
Grain Size Distribution ◽  
Transport Processes ◽  
Monsoon Circulation ◽  
East African ◽  
African Monsoon ◽  
Sediment Fraction ◽  
End Members

<p>Terrigenous particles deposited in all kinds of sedimentary records (terrestrial, marine and lacustrine) have proven to yield valuable information for reconstruction of paleo-climate and paleo-environments. Natural sediments typically represent a mixture of deposits of diverse provenance, potentially supplied by different transport processes, expressed in a bi-or poly-modal grain-size distribution. Recently, complex mathematical-statistical end-member models have been developed to disentangle the different sub-populations within one grain-size distribution, which are then assumed to represent a distinct sediment fraction that has a single provenance and/or was transported by the same process to the site of deposition.</p><p>Here we present end-member modeling results of the terrigenous sediment fraction in a 25-kyr sediment sequence from Lake Chala (Kenya/Tanzania), revealing valuable information on climate and environmental change in equatorial East Africa since the Last Glacial Maximum (LGM). Calculated end members could be related to distinct source areas and transport processes, namely to fine aeolian dust, fine-grained soil runoff, coarser aeolian dust from proximal sources and coarse erosive material originating from the crater rim surrounding the lake. Variations in the occurrence of distal versus proximal dust is suggested to be a reliable indicator for changes in East African monsoon circulation. During Northern Hemisphere cold periods, such as the LGM and Younger Dryas (YD), wind systems associated with the Intertropical Convergence Zone (ITCZ) were pushed southward, causing a more intense influence of the NE monsoon at Lake Chala. This resulted in high amounts of fine dust originating from the Horn of Africa region. At the same time, SE monsoon circulation was diminished due to a reduced atmospheric pressure gradient between the Asian/Indian continent and the Indian Ocean. Influx of coarse dust from proximal sources, which are mostly located east of Lake Chala, was impossible due to the weaker SE monsoon circulation. After termination of the YD, rapid reestablishment of the SE monsoon in the Early Holocene is recorded by an abrupt increase in the influx of coarse dust.</p><p>Lake Chala sediments contain one of the few continuous and high-resolution climate records in East Africa spanning the past 25 kyr, providing detailed information on long-term climate variation in an area highly sensitive to hydrological variations. Subdividing the clastic sediment fraction into statistically robust end members produces multiple quantitative and independent proxies to help reconstruct this region’s climate and environmental history.</p>

scholarly journals Passive acoustic measurement of bedload grain size distribution using self-generated noise

2018 ◽  
Vol 22 (1) ◽  
pp. 767-787 ◽  
Author(s):  
Teodor Petrut ◽  
Thomas Geay ◽  
Cédric Gervaise ◽  
Philippe Belleudy ◽  
Sebastien Zanker
Keyword(s):  
Grain Size ◽  
Sediment Transport ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Measurement Techniques ◽  
Bedload Transport ◽  
Transport Processes ◽  
Signal Spectrum ◽  
Inversion Method ◽  
Passive Acoustic

Abstract. Monitoring sediment transport processes in rivers is of particular interest to engineers and scientists to assess the stability of rivers and hydraulic structures. Various methods for sediment transport process description were proposed using conventional or surrogate measurement techniques. This paper addresses the topic of the passive acoustic monitoring of bedload transport in rivers and especially the estimation of the bedload grain size distribution from self-generated noise. It discusses the feasibility of linking the acoustic signal spectrum shape to bedload grain sizes involved in elastic impacts with the river bed treated as a massive slab. Bedload grain size distribution is estimated by a regularized algebraic inversion scheme fed with the power spectrum density of river noise estimated from one hydrophone. The inversion methodology relies upon a physical model that predicts the acoustic field generated by the collision between rigid bodies. Here we proposed an analytic model of the acoustic energy spectrum generated by the impacts between a sphere and a slab. The proposed model computes the power spectral density of bedload noise using a linear system of analytic energy spectra weighted by the grain size distribution. The algebraic system of equations is then solved by least square optimization and solution regularization methods. The result of inversion leads directly to the estimation of the bedload grain size distribution. The inversion method was applied to real acoustic data from passive acoustics experiments realized on the Isère River, in France. The inversion of in situ measured spectra reveals good estimations of grain size distribution, fairly close to what was estimated by physical sampling instruments. These results illustrate the potential of the hydrophone technique to be used as a standalone method that could ensure high spatial and temporal resolution measurements for sediment transport in rivers.

scholarly journals Passive Acoustic Measurement of Bedload Grain Size Distribution using the Self-Generated Noise

2017 ◽  
Author(s):  
Teodor I. Petrut ◽  
Thomas Geay ◽  
Cédric Gervaise ◽  
Philippe Belleudy ◽  
Sebastien Zanker
Keyword(s):  
Grain Size ◽  
Sediment Transport ◽  
Power Spectrum ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Bedload Transport ◽  
Transport Processes ◽  
Signal Spectrum ◽  
Inversion Method ◽  
Passive Acoustic

Abstract. Monitoring sediment transport processes in rivers is of particular interest to engineers and scientists to assess the stability of rivers and hydraulic structures. Various methods for sediment transport processes description were proposed using conventional or surrogate measurement techniques. This paper addresses the topic of the passive acoustic monitoring of bedload transport in rivers and especially the estimation of the bedload grain size distribution from self-generated noise. It discusses the feasibility of linking the acoustic signal spectrum shape to bedload-grain sizes involved in elastic impacts with the bed river treated as a massive slab. Bedload grain size distribution is estimated by a regularized algebraic inversion scheme fed with the power spectrum density of river noise estimated from one hydrophone. The inversion methodology relies upon a physical model which predicts the acoustic field generated by the collision between rigid bodies. Here it is proposed an analytic model of the acoustic power spectrum generated by the impacts between a sphere and a slab. The proposed model is written as linear system of analytic power spectra weighted by the grain size distribution. The algebraic system of equations is then solved by least square optimization and solution regularization methods. The result of inversion leads directly to the estimation of the bedload grain size distribution. The inversion method was applied on real acoustic data from passive acoustics experiments realized on the Isère River, in France. The inversion of in situ measured spectra reveals good estimations of grain size distribution, fairly close to what was estimated by physical sampling instruments. These results illustrate the potential of the hydrophone technique to be used as a standalone method that could ensures high spatial and temporal resolution measurements for sediment transport in rivers.

A new easy-to-use tool for grain size distribution analysis

2020 ◽  
Author(s):  
Yuming Liu ◽  
Xingxing Liu ◽  
Youbin Sun
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Quaternary Geology ◽  
Distribution Analysis ◽  
Lacustrine Deposits ◽  
Mean Grain Size ◽  
Different Types ◽  
Geological Information ◽  
End Members

<p>Grain size distribution (GSD) data have been widely used in Earth sciences, especially Quaternary Geology, due to its convenience and reliability. However, the usages of GSD are still oversimplified. The geological information contained in GSD is very abundant, but only some simplified proxies (e.g. mean grain size) are widely used. The most important reason is that GSD data are hard to interpret and visualize directly.</p><p>To overcome this, some researchers have developed the methods to unmix the mixed multi-modal GSD to some components to make the interpretation and visualization easier. These methods can be divided into two routes. One is end-member analysis (EMA) which takes a batch of samples for the calculation of the end-members. Another is called single-specimen unmixing (SSU) (Sun et al., 2002) which treats each sample as an individual. The key difference between the two routes is that whether the end-members of a batch of samples are consistent. EMA believes that the end-members between different samples are consistent, the variations of GSD are only caused by the changing of fractions of the end-members. On the contrary, SSU has no assumption on the end-members, i.e. it admits that the end-members may vary between different samples. Some mature tools (Paterson and Heslop, 2015; Dietze and Dietze, 2019) taking the EMA route have appeared, but there is no available public and easy-to-use tool for SSU.</p><p>Here we introduce a free and open-source GUI tool which is called QGrain, it can help researchers to analyze the GSD data easily and bring new insights for the interpretation of GSD. QGrain is based on SSU but applied some algorithms (e.g. data preprocessing and global optimization) to improve its precision and robustness. It supports Lognormal or Weibull as the base distribution and it is easy to add more base distributions. QGrain can handle different types of sediments (e.g. aeolian, fluvial and lacustrine deposits). QGrain can export all detailed data and generate the charts automatically.</p>

scholarly journals Identifying sediment transport mechanisms from grain size-shape distributions

2019 ◽  
Author(s):  
Johannes Albert van Hateren ◽  
Unze van Buuren ◽  
Sebastiaan Martinus Arens ◽  
Ronald Theodorus van Balen ◽  
Maarten Arnoud Prins
Keyword(s):  
Grain Size ◽  
Spatial Distribution ◽  
Sediment Transport ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Grain Shape ◽  
Transport Processes ◽  
Transport Mechanisms ◽  
Aeolian Transport ◽  
Transport Mode

Abstract. The way in which sediment is transported (creep, saltation, suspension), is traditionally interpreted from grain size distribution characteristics. However, the grain size range associated with transitions from one transport mode to the other is highly variable because it depends on the amount of transport energy available. In this study we present a novel methodology for determination of the sediment transport mode based on grain size and shape data from dynamic image analysis. The data are integrated into grain size-shape distributions and primary components are determined using end-member modelling. In real-world datasets, primary components can be interpreted in terms of different transport mechanisms and/or sediment sources. Accuracy of the method is assessed using artificial datasets with known primary components that are mixed in known proportions. The results show that the proposed technique accurately identifies primary components with the exception of those primary components that only form minor contributions to the samples (highly mixed components). The new method is also tested on sediment samples from an active aeolian system in the Dutch coastal dunes. Aeolian transport processes and geomorphology of these type of systems are well known and can therefore be linked to the spatial distribution of end members to assess the physical significance of the method's output. The grain size-shape distributions of the dune dataset are unmixed into three primary components. The spatial distribution of these components is constrained by geomorphology and reflects the three dominant aeolian transport processes known to occur along a beach-dune transect: bedload on the beach and in notches that were dug by man through the shore-parallel foredune ridge, modified saltation on the windward and leeward slope of the intact foredune, and suspension in the vegetated hinterland. The three transport modes are characterised by distinctly different trends in grain shape with grain size: with increasing size, bedload shows a constant grain regularity, modified saltation a minor decrease in grain regularity and suspension a strong decrease in grain regularity. These trends, or in other words, the shape of the grain size-shape distributions, can be used to determine the transport mode responsible for a sediment deposit. Results of the method are therefore less ambiguous than those of traditional grain-size distribution end-member modelling, especially if multiple transport modes occur or if primary components overlap in terms of grain size but differ in grain shape.

scholarly journals Identifying sediment transport mechanisms from grain size–shape distributions, applied to aeolian sediments

2020 ◽  
Vol 8 (2) ◽  
pp. 527-553
Author(s):  
Johannes Albert van Hateren ◽  
Unze van Buuren ◽  
Sebastiaan Martinus Arens ◽  
Ronald Theodorus van Balen ◽  
Maarten Arnoud Prins
Keyword(s):  
Grain Size ◽  
Spatial Distribution ◽  
Sediment Transport ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Grain Shape ◽  
Transport Processes ◽  
Transport Mechanisms ◽  
Aeolian Transport ◽  
Transport Mode

Abstract. The way in which sediment is transported (creep, saltation, suspension), is traditionally interpreted from grain size distribution characteristics. However, the grain size range associated with transitions from one transport mode to the other is highly variable because it depends on the amount of transport energy available. In this study we present a novel methodology for determination of the sediment transport mode based on grain size and shape data from dynamic image analysis. The data are integrated into grain size–shape distributions, and primary components are determined using endmember modelling. In real-world datasets, primary components can be interpreted in terms of different transport mechanisms and/or sediment sources. Accuracy of the method is assessed using artificial datasets with known primary components that are mixed in known proportions. The results show that the proposed technique accurately identifies primary components, with the exception of those primary components that only form minor contributions to the samples (highly mixed components). The new method is tested on sediment samples from an active aeolian system in the Dutch coastal dunes. Aeolian transport processes and geomorphology of these type of systems are well known and can therefore be linked to the spatial distribution of endmembers to assess the physical significance of the method's output. The grain size–shape distributions of the aeolian dune dataset are unmixed into three primary components. The spatial distribution of these components is constrained by geomorphology and reflects the three dominant aeolian transport processes known to occur along a beach–dune transect: bedload on the beach and in notches that were dug by man through the shore-parallel foredune ridge, modified saltation on the windward and leeward slope of the intact foredune, and suspension in the vegetated hinterland. The three transport modes are characterised by distinctly different trends in grain shape with grain size: with increasing size, bedload shows a constant grain regularity, modified saltation a minor decrease in grain regularity, and suspension a strong decrease in grain regularity. These trends, or in other words, the shape of the grain size–shape distributions, can be used to determine the transport mode responsible for an aeolian sediment deposit. Results of the method are therefore less ambiguous than those of traditional grain size distribution endmember modelling, especially if multiple transport modes occur or if primary components overlap in terms of grain size but differ in grain shape.

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