Are you part of the network? : characterizing process couplings and feedbacks in a river delta using information theory
| dc.contributor.advisor | Passlacqua, Paola | en |
| dc.contributor.committeeMember | Gilbert, Robert | en |
| dc.creator | Sendrowski, Alicia Paige | en |
| dc.date.accessioned | 2015-10-19T18:43:07Z | en |
| dc.date.accessioned | 2018-01-22T22:28:30Z | |
| dc.date.available | 2015-10-19T18:43:07Z | en |
| dc.date.available | 2018-01-22T22:28:30Z | |
| dc.date.issued | 2015-05 | en |
| dc.date.submitted | May 2015 | en |
| dc.date.updated | 2015-10-19T18:43:07Z | en |
| dc.description | text | en |
| dc.description.abstract | River deltas are highly interconnected systems consisting of channels and inter-channel islands. They result from complex interactions between fluxes of water, sediment, nutrients, energy, and biota. Given the importance of deltas in a social, economic, and ecological context, the understanding of delta function and evolution is of utmost importance. This work aims to use statistical methods to gain insights into delta system processes across spatial and temporal scales. Specifically, understanding the effect of discharge, wind, and tidal forcing on delta variables is a key question. An information theoretic approach was used to identify environmental controls on island and channel inundation, and channel turbidities, in Wax Lake Delta, a naturally prograding delta in coastal Louisiana, USA. Continuous water level data were collected on the islands during summer 2014 and in the channels during winter 2014. Channel turbidities were also collected in winter 2014. Information theory statistics, such as transfer entropy and mutual information, were calculated for all variables to characterize controls on depth and turbidity in terms of strength, direction, and scale. Discharge, wind, and tidal forcing were found to be very dependent on spatial location in the delta. The more upstream locations see increasing influence from discharge in both islands and channels, with tidal influence increasing downstream. Channels are less affected by tides than islands. Wind influence is more complex and varies across space and time for both water level and turbidity. Recalculating information theory metrics under conditions of low and high discharge reveals a higher tidal influence in low flows and a higher wind influence during high flows. The implications for this work are the future construction of a process network, which will show the major flow paths of energy, water, sediments, and nutrients through the system, leading to enhanced metrics that aid in delta system restoration. | en |
| dc.description.department | Civil, Architectural, and Environmental Engineering | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier | doi:10.15781/T2H03V | en |
| dc.identifier.uri | http://hdl.handle.net/2152/31782 | en |
| dc.language.iso | en | en |
| dc.subject | Delta | en |
| dc.subject | Information theory | en |
| dc.subject | Networks | en |
| dc.title | Are you part of the network? : characterizing process couplings and feedbacks in a river delta using information theory | en |
| dc.type | Thesis | en |