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Quantifying fine-grained sediment sources in the River Axe catchment, southwest England: application of a Monte Carlo numerical modelling framework incorporating local and genetic algorithm optimisation

A.L Collins, Y Zhang, D.E Walling, S.E Grenfell, P Smith, J Grischeff, A Locke, A Sweetapple, D Brogden, Suzanne Grenfell

Hydrological Processes, Volume: 26, Issue: 13, Pages: 1962 - 1983

Swansea University Author: Suzanne Grenfell

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DOI (Published version): 10.1002/hyp.8283

Published in: Hydrological Processes
ISSN: 0885-6087
Published: 2012
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URI: https://cronfa.swan.ac.uk/Record/cronfa13112
first_indexed 2013-07-23T12:09:29Z
last_indexed 2018-02-09T04:43:39Z
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spelling 2013-06-13T09:55:00.8767729 v2 13112 2012-10-18 Quantifying fine-grained sediment sources in the River Axe catchment, southwest England: application of a Monte Carlo numerical modelling framework incorporating local and genetic algorithm optimisation 605a22a02be0744a23bca3bf65a4d2df Suzanne Grenfell Suzanne Grenfell true false 2012-10-18 BGPS Journal Article Hydrological Processes 26 13 1962 1983 0885-6087 31 12 2012 2012-12-31 10.1002/hyp.8283 COLLEGE NANME Biosciences Geography and Physics School COLLEGE CODE BGPS Swansea University 2013-06-13T09:55:00.8767729 2012-10-18T14:03:47.9070351 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Biosciences A.L Collins 1 Y Zhang 2 D.E Walling 3 S.E Grenfell 4 P Smith 5 J Grischeff 6 A Locke 7 A Sweetapple 8 D Brogden 9 Suzanne Grenfell 10
title Quantifying fine-grained sediment sources in the River Axe catchment, southwest England: application of a Monte Carlo numerical modelling framework incorporating local and genetic algorithm optimisation
spellingShingle Quantifying fine-grained sediment sources in the River Axe catchment, southwest England: application of a Monte Carlo numerical modelling framework incorporating local and genetic algorithm optimisation
Suzanne Grenfell
title_short Quantifying fine-grained sediment sources in the River Axe catchment, southwest England: application of a Monte Carlo numerical modelling framework incorporating local and genetic algorithm optimisation
title_full Quantifying fine-grained sediment sources in the River Axe catchment, southwest England: application of a Monte Carlo numerical modelling framework incorporating local and genetic algorithm optimisation
title_fullStr Quantifying fine-grained sediment sources in the River Axe catchment, southwest England: application of a Monte Carlo numerical modelling framework incorporating local and genetic algorithm optimisation
title_full_unstemmed Quantifying fine-grained sediment sources in the River Axe catchment, southwest England: application of a Monte Carlo numerical modelling framework incorporating local and genetic algorithm optimisation
title_sort Quantifying fine-grained sediment sources in the River Axe catchment, southwest England: application of a Monte Carlo numerical modelling framework incorporating local and genetic algorithm optimisation
author_id_str_mv 605a22a02be0744a23bca3bf65a4d2df
author_id_fullname_str_mv 605a22a02be0744a23bca3bf65a4d2df_***_Suzanne Grenfell
author Suzanne Grenfell
author2 A.L Collins
Y Zhang
D.E Walling
S.E Grenfell
P Smith
J Grischeff
A Locke
A Sweetapple
D Brogden
Suzanne Grenfell
format Journal article
container_title Hydrological Processes
container_volume 26
container_issue 13
container_start_page 1962
publishDate 2012
institution Swansea University
issn 0885-6087
doi_str_mv 10.1002/hyp.8283
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Biosciences{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Biosciences
document_store_str 0
active_str 0
published_date 2012-12-31T04:41:08Z
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score 11.096913

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