Staffordshire University logo
STORE - Staffordshire Online Repository

Deglaciation controls on sediment yield: towards capturing spatio-temporal variability

Carrivick, Jonathan L. and TWEED, Fiona (2021) Deglaciation controls on sediment yield: towards capturing spatio-temporal variability. Earth-Science Reviews, 221 (Oct). ISSN 00128252

[img]
Preview
Text
Carrivick_and_Tweed_ESR_accepted_9Sept2021.pdf - AUTHOR'S ACCEPTED Version (default)
Available under License Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).

Download (3MB) | Preview

Abstract or description

Accelerated glacier and ice sheet retreat and thinning in recent decades has profound consequences for catchment sediment supply with attendant repercussions for nutrient cycling, carbon fluxes and natural resource management. This paper evaluates the impacts of deglaciation on sediment yields from glaciated, deglaciating and recently-deglaciated catchments. It summarises the key characteristics of sediment yields from glaciated catchments to be that they span five orders of magnitude, vary with latitude and are greatest in high-relief and tectonically-active regions. We review the available quantitative data on sediment yields from glaciated catchments and we comment extensively on spatio-temporal variability to understand global to local and inter- and intracatchment controls. Significant gaps in the available sediment yield data and also in our knowledge of sediment sources, pathways and sinks are identified. We constrain a set of novel approaches by which these gaps could be addressed. In particular, we suggest that the opportunities presented by emerging datasets and analytical methods enabling landcover changes, Digital Elevation Model (DEM) change detection, analyses of connectivity and analyses of sediment plumes are exciting and these approaches should become practical tools for understanding intra- and inter-catchment sediment yields from deglaciating landscapes. We showcase preliminary studies utilising these datasets and they are used to formulate hypotheses designed to stimulate further research.

Item Type: Article
Faculty: School of Digital, Technologies and Arts > Engineering
Depositing User: Fiona TWEED
Date Deposited: 15 Sep 2021 15:46
Last Modified: 12 Apr 2023 08:26
URI: https://eprints.staffs.ac.uk/id/eprint/7016

Actions (login required)

View Item View Item

DisabledGo Staffordshire University is a recognised   Investor in People. Sustain Staffs
Legal | Freedom of Information | Site Map | Job Vacancies
Staffordshire University, College Road, Stoke-on-Trent, Staffordshire ST4 2DE t: +44 (0)1782 294000