Towards understanding the dynamics of environmental sensitivity to climate change : introducing the DESC model
Barkwith, A.; Wang, L.; Jackson, C.; Ellis, M.. 2012 Towards understanding the dynamics of environmental sensitivity to climate change : introducing the DESC model. [Poster] In: European Geosciences Union General Assembly 2012, Vienna, Austria, 22-27 Apr 2012. European Geosciences Union.
Before downloading, please read NORA policies.Preview |
Text
EGU2012-11159.pdf Download (35kB) |
Abstract/Summary
The DESC model seeks to explore the interactions that exist between Earth systems at a range of spatio-temporal scales by coupling current landscape evolution modelling technologies to a host of new geo-processing modules. DESC currently uses the well established CAESAR model (Coulthard and Van De Wiel, 2006) as its kernel; a two-dimensional cellular automaton landscape evolution model which has a modular design and great versatility in the range of simulated spatio-temporal scales. Initial research focused on the loose coupling of CAESAR to the groundwater flow model ZOOMQ3D, investigating the role of groundwater on sediment transport at the catchment scale. The Eden Valley (Cumbria, UK) was selected as a test bed for the coupled model and results suggest that although the volume of sediment transport through the catchment is not altered, the distribution of sediment erosion and deposition in the simulation is perturbed by the interplay of baseflow conditions and storm intensity and frequency.
Item Type: | Publication - Conference Item (Poster) |
---|---|
Programmes: | BGS Programmes 2010 > Climate Change Science |
Additional Information. Not used in RCUK Gateway to Research.: | Vol. 14, EGU2012-11159, 2012 |
Additional Keywords: | GroundwaterBGS, Groundwater, Climate change |
NORA Subject Terms: | Computer Science Hydrology Earth Sciences |
Date made live: | 24 Jul 2012 13:48 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/18829 |
Actions (login required)
View Item |
Document Downloads
Downloads for past 30 days
Downloads per month over past year