Application of Grain-Size End-Member Modelling in Bed Sediments of the
Brahmaputra River
Abstract
Superimposed signatures of grain size effect, lithology and chemical
processes on fluvial sediments need to be resolved to answer the
profound research questions related to sediment provenance and
processes. Hydraulic forces sort the sediments into different grain size
classes in the river water column. The finest fraction is transported as
the suspended sediments which have different sediment composition than
the bed sediments. Thus, suspended sediment may provide additional
information about earth surface processes, such as chemical weathering.
Hydraulically sorted river bed sediments may or may not provide this
information, as bulk sample may be depleted in finer grains by hydraulic
processes. Bed sediments that are easily sampled from the sand bars and
river banks are often investigated to study the weathering intensity and
sediment provenance. It is thus crucial to identify and quantify the
specific grain size classes in the bulk sample to be investigated for
the research question at hand. End Member Modelling Algorithms (EMMA)
for grain size distribution is a useful tool to unmix the grain size
population into geological meaningful end members. We applied
Hierarchical alternating least squares nonnegative matrix factorization
(HALS-NMF) algorithm to unmix the grain size data (62 samples) of river
bed sediments collected from the freshly exposed sand bars of the
Brahmaputra river over a stretch of 550km. The grain size distribution
of the finest end member (mean=18µm) is closely approximated to be of
the surface sediment grain size distribution reported previously for the
Brahmaputra river. Thus, we were able to quantify the relative
contribution of suspended sediment to the bed sediment of the
Brahmaputra trunk. Results show that the contribution of the suspended
sediments in the bed sediment is higher at the lower reaches of the
river near floodplain outlet, possibly due to the reduced flow energy in
downstream regions. The findings may also be used to select samples and
grain size classes for additional geochemical and mineralogical study in
order to interpret signals of weathering, provenance and physical
processes in the Brahmaputra’s large dynamic floodplains at a finer
spatial scale.