Literature DB >> 24407033

The use of composite fingerprints to quantify sediment sources in a wildfire impacted landscape, Alberta, Canada.

M Stone1, A L Collins2, U Silins3, M B Emelko4, Y S Zhang5.   

Abstract

There is increasing global concern regarding the impacts of large scale land disturbance by wildfire on a wide range of water and related ecological services. This study explores the impact of the 2003 Lost Creek wildfire in the Crowsnest River basin, Alberta, Canada on regional scale sediment sources using a tracing approach. A composite geochemical fingerprinting procedure was used to apportion the sediment efflux among three key spatial sediment sources: 1) unburned (reference) 2) burned and 3) burned sub-basins that were subsequently salvage logged. Spatial sediment sources were characterized by collecting time-integrated suspended sediment samples using passive devices during the entire ice free periods in 2009 and 2010. The tracing procedure combines the Kruskal-Wallis H-test, principal component analysis and genetic-algorithm driven discriminant function analysis for source discrimination. Source apportionment was based on a numerical mass balance model deployed within a Monte Carlo framework incorporating both local optimization and global (genetic algorithm) optimization. The mean relative frequency-weighted average median inputs from the three spatial source units were estimated to be 17% (inter-quartile uncertainty range 0-32%) from the reference areas, 45% (inter-quartile uncertainty range 25-65%) from the burned areas and 38% (inter-quartile uncertainty range 14-59%) from the burned-salvage logged areas. High sediment inputs from burned and the burned-salvage logged areas, representing spatial source units 2 and 3, reflect the lasting effects of forest canopy and forest floor organic matter disturbance during the 2003 wildfire including increased runoff and sediment availability related to high terrestrial erosion, streamside mass wasting and river bank collapse. The results demonstrate the impact of wildfire and incremental pressures associated with salvage logging on catchment spatial sediment sources in higher elevation Montane regions where forest growth and vegetation recovery are relatively slow.
Copyright © 2013 Elsevier B.V. All rights reserved.

Keywords:  Genetic algorithm; Sediment source fingerprinting; Uncertainty analysis; Wildfire

Mesh:

Year:  2014        PMID: 24407033     DOI: 10.1016/j.scitotenv.2013.12.052

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


  4 in total

1.  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

2.  Fingerprinting sub-basin spatial sediment sources in a large Iranian catchment under dry-land cultivation and rangeland farming: Combining geochemical tracers and weathering indices.

Authors:  Zeinab Mohammadi Raigani; Kazem Nosrati; Adrian L Collins
Journal:  J Hydrol Reg Stud       Date:  2019-08

3.  Sediment source fingerprinting: benchmarking recent outputs, remaining challenges and emerging themes.

Authors:  Adrian L Collins; Martin Blackwell; Pascal Boeckx; Charlotte-Anne Chivers; Monica Emelko; Olivier Evrard; Ian Foster; Allen Gellis; Hamid Gholami; Steve Granger; Paul Harris; Arthur J Horowitz; J Patrick Laceby; Nuria Martinez-Carreras; Jean Minella; Lisa Mol; Kazem Nosrati; Simon Pulley; Uldis Silins; Yuri Jacques da Silva; Micheal Stone; Tales Tiecher; Hari Ram Upadhayay; Yusheng Zhang
Journal:  J Soils Sediments       Date:  2020-09-16       Impact factor: 3.308

4.  Fingerprinting the spatial sources of fine-grained sediment deposited in the bed of the Mehran River, southern Iran.

Authors:  Atefe Fatahi; Hamid Gholami; Yahya Esmaeilpour; Aboalhasan Fathabadi
Journal:  Sci Rep       Date:  2022-03-10       Impact factor: 4.996

  4 in total

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