Literature DB >> 22119027

Sediment source tracing in a lowland agricultural catchment in southern England using a modified procedure combining statistical analysis and numerical modelling.

A L Collins1, Y Zhang, D McChesney, D E Walling, S M Haley, P Smith.   

Abstract

Catchment erosion, soil losses and resulting sediment pressures continue to represent cause for concern with respect to the ecological vitality and amenity value of riverine systems, including those in the agricultural catchments of southern England. Given that the sources of fine-grained sediment are typically diffuse in nature, it is essential to adopt a catchment-wide perspective to corresponding management strategies and sediment source tracing procedures have proved useful in assisting such planning. There remains, however, scope for further refining sediment sourcing procedures and on that basis, a recent study in the upper River Kennet (~214 km(2)) catchment in southern England, provided an opportunity for designing and testing a refined statistical procedure for sediment source discrimination with composite fingerprints using Genetic Algorithm (GA)-driven Discriminant Function Analysis, the Kruskal-Wallis H-test and Principal Components Analysis. The revised statistical verification of composite signatures was combined with numerical mass balance modelling using recent refinements including a range of tracer weightings and both local and GA optimisation. Comparison of the local and global optimisation increased confidence in the outputs of local optimisation and the goodness-of-fit for the predicted source contributions using the optimum composite signatures selected from the revised statistical testing ranged from 0.914 to 0.965. Overall relative frequency-weighted average median source type contributions were estimated to be 4% (agricultural topsoils; predicted deviate median inputs 1-19%), 55% (unmetalled farm track surfaces; predicted deviate median inputs 9-91%), 6% (damaged road verges; predicted deviate median inputs 4-42%), 31% (channel banks/subsurface sources; predicted deviate median inputs 5-41%) and 4% (urban street dust; predicted deviate median inputs 0-20%). The study provides further evidence of the importance of eroding farm tacks as a catchment scale sediment source and confirms the utility of tracing for assembling information on sediment inputs from both the agricultural and urban sectors.
Copyright © 2011 Elsevier B.V. All rights reserved.

Mesh:

Year:  2011        PMID: 22119027     DOI: 10.1016/j.scitotenv.2011.10.062

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  6 in total

1.  Fingerprinting sub-basin spatial suspended sediment sources by combining geochemical tracers and weathering indices.

Authors:  Kazem Nosrati; Zeynab Fathi; Adrian L Collins
Journal:  Environ Sci Pollut Res Int       Date:  2019-08-02       Impact factor: 4.223

2.  Monte Carlo fingerprinting of the terrestrial sources of different particle size fractions of coastal sediment deposits using geochemical tracers: some lessons for the user community.

Authors:  Hamid Gholami; Ebrahim Jafari TakhtiNajad; Adrian L Collins; Aboalhasan Fathabadi
Journal:  Environ Sci Pollut Res Int       Date:  2019-03-26       Impact factor: 4.223

Review 3.  A review of source tracking techniques for fine sediment within a catchment.

Authors:  Zhuo Guan; Xiang-Yu Tang; Jae E Yang; Yong Sik Ok; Zhihong Xu; Taku Nishimura; Brian J Reid
Journal:  Environ Geochem Health       Date:  2017-04-28       Impact factor: 4.609

4.  The representation of sediment source group tracer distributions in Monte Carlo uncertainty routines for fingerprinting: An analysis of accuracy and precision using data for four contrasting catchments.

Authors:  Simon Pulley; Adrian L Collins; J Patrick Laceby
Journal:  Hydrol Process       Date:  2020-03-10       Impact factor: 3.565

5.  Investigating the importance of recreational roads as a sediment source in a mountainous catchment using a fingerprinting procedure with different multivariate statistical techniques and a Bayesian un-mixing model.

Authors:  Kazem Nosrati; Adrian L Collins
Journal:  J Hydrol (Amst)       Date:  2019-02       Impact factor: 5.722

6.  Tracing catchment fine sediment sources using the new SIFT (SedIment Fingerprinting Tool) open source software.

Authors:  S Pulley; A L Collins
Journal:  Sci Total Environ       Date:  2018-04-24       Impact factor: 7.963

  6 in total

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