Upscaling linear chemical reactions in porous and fractured media with a continuous time random walk framework
Abstract
The exchange of surface and subsurface waters plays an important role in understanding and predicting large scale transport processes in streams and rivers. Faithfully representing the influence of small-scale physical and chemical processes associated with the subsurface on exchange is necessary for developing reliable upscaled predictive models at the reach scale and beyond. In this work, we introduce a novel continuous time random walk model to predict transport in an open channel system with hyporheic exchange and linear reactive processes in the subsurface. The methodology uses particle trajectory data from direct numerical simulations of a turbulent channel. We study the influence of chemical species properties (via Damkohler numbers) and subsurface bed depth influence emergent large-scale transport behavior in the surface.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFM.H45J1285S