Characterization and quantification of suspended sediment sources to the Manawatu River, New Zealand.

Autor: Vale SS; Institute of Agriculture and Environment, Massey University, Palmerston North, New Zealand; Soils and Landscapes, Landcare Research, Palmerston North, New Zealand. Electronic address: s.vale@massey.ac.nz., Fuller IC; Institute of Agriculture and Environment, Massey University, Palmerston North, New Zealand., Procter JN; Institute of Agriculture and Environment, Massey University, Palmerston North, New Zealand., Basher LR; Soils and Landscapes, Landcare Research, Nelson, New Zealand., Smith IE; School of Environment, University of Auckland, Auckland, New Zealand.
Jazyk: angličtina
Zdroj: The Science of the total environment [Sci Total Environ] 2016 Feb 01; Vol. 543 (Pt A), pp. 171-186. Date of Electronic Publication: 2015 Nov 12.
DOI: 10.1016/j.scitotenv.2015.11.003
Abstrakt: Knowledge of sediment movement throughout a catchment environment is essential due to its influence on the character and form of our landscape relating to agricultural productivity and ecological health. Sediment fingerprinting is a well-used tool for evaluating sediment sources within a fluvial catchment but still faces areas of uncertainty for applications to large catchments that have a complex arrangement of sources. Sediment fingerprinting was applied to the Manawatu River Catchment to differentiate 8 geological and geomorphological sources. The source categories were Mudstone, Hill Subsurface, Hill Surface, Channel Bank, Mountain Range, Gravel Terrace, Loess and Limestone. Geochemical analysis was conducted using XRF and LA-ICP-MS. Geochemical concentrations were analysed using Discriminant Function Analysis and sediment un-mixing models. Two mixing models were used in conjunction with GRG non-linear and Evolutionary optimization methods for comparison. Discriminant Function Analysis required 16 variables to correctly classify 92.6% of sediment sources. Geological explanations were achieved for some of the variables selected, although there is a need for mineralogical information to confirm causes for the geochemical signatures. Consistent source estimates were achieved between models with optimization techniques providing globally optimal solutions for sediment quantification. Sediment sources was attributed primarily to Mudstone, ≈38-46%; followed by the Mountain Range, ≈15-18%; Hill Surface, ≈12-16%; Hill Subsurface, ≈9-11%; Loess, ≈9-15%; Gravel Terrace, ≈0-4%; Channel Bank, ≈0-5%; and Limestone, ≈0%. Sediment source apportionment fits with the conceptual understanding of the catchment which has recognized soft sedimentary mudstone to be highly susceptible to erosion. Inference of the processes responsible for sediment generation can be made for processes where there is a clear relationship with the geomorphology, but is problematic for processes which occur within multiple terrains.
(Copyright © 2015 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
Externí odkaz: