2007
Barnes, E. A.; Power, M. E.; Foufoula-Georgiou, E.; Hondzo, M.; Dietrich, W. E.
Upscaling river biomass using dimensional analysis and hydrogeomorphic scaling Journal Article
In: Geophysical Research Letters, vol. 34, no. 24, 2007.
Abstract | Links | BibTeX | Tags: biomass, dimensional analysis, multi-resolution
@article{Barnes2007,
title = {Upscaling river biomass using dimensional analysis and hydrogeomorphic scaling},
author = {E. A. Barnes and M. E. Power and E. Foufoula-Georgiou and M. Hondzo and W. E. Dietrich},
url = {https://angelo.berkeley.edu/wp-content/uploads/sites/59/Barnes_2007_GeophyResLet.pdf},
doi = {10.1029/2007GL031931},
year = {2007},
date = {2007-12-11},
journal = {Geophysical Research Letters},
volume = {34},
number = {24},
abstract = {We propose a methodology for upscaling biomass in a river using a combination of dimensional analysis and hydro-geomorphologic scaling laws. We first demonstrate the use of dimensional analysis for determining local scaling relationships between Nostoc biomass and hydrologic and geomorphic variables. We then combine these relationships with hydraulic geometry and streamflow scaling in order to upscale biomass from point to reach-averaged quantities. The methodology is demonstrated through an illustrative example using an 18 year dataset of seasonal monitoring of biomass of a stream cyanobacterium (Nostoc parmeloides) in a northern California river.},
keywords = {biomass, dimensional analysis, multi-resolution},
pubstate = {published},
tppubtype = {article}
}
We propose a methodology for upscaling biomass in a river using a combination of dimensional analysis and hydro-geomorphologic scaling laws. We first demonstrate the use of dimensional analysis for determining local scaling relationships between Nostoc biomass and hydrologic and geomorphic variables. We then combine these relationships with hydraulic geometry and streamflow scaling in order to upscale biomass from point to reach-averaged quantities. The methodology is demonstrated through an illustrative example using an 18 year dataset of seasonal monitoring of biomass of a stream cyanobacterium (Nostoc parmeloides) in a northern California river.