Elayouty, A., Scott, M. , Miller, C. , Waldron, S. and Franco-Villoria, M. (2016) Challenges in modeling detailed and complex environmental data sets: a case study modeling the excess partial pressure of fluvial CO2. Evironmental and Ecological Statistics, 23(1), pp. 65-87. (doi: 10.1007/s10651-015-0329-4)
|
Text
108829.pdf - Published Version Available under License Creative Commons Attribution. 2MB |
Abstract
Advances in sensor technology enable environmental monitoring programmes to record and store measurements at a high temporal resolution, enhancing the capacity to detect and understand short duration changes that would not have been apparent in the past with monthly, fortnightly or even daily sampling. However, there are various challenges in terms of the processing and analysis of these environmental high-frequency data due to their complex behavior over the different timescales and the strong correlation structure that persists over a large number of lags. Here, we explore the complexities of modeling high-frequency data which arise from environmental applications. With increasing understanding of the importance of surface waters as a source of atmospheric CO2 we consider a high-resolution sensor-generated time series of the over-saturation of CO2, EpCO2, in a small order river system. We will present advanced statistical approaches to analyze and model the data, which include visualization tools for exploratory analysis, wavelets and additive models. These methods reveal the complex dynamics of EpCO2 over different timescales, and the multivariate relationships of EpCO2 with hydrology and temporal autocorrelation structures, which are time and scale dependent.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Waldron, Professor Susan and Scott, Professor Marian and Elayouty, Amira and Miller, Professor Claire |
| Authors: | Elayouty, A., Scott, M., Miller, C., Waldron, S., and Franco-Villoria, M. |
| College/School: | College of Science and Engineering > School of Geographical and Earth Sciences College of Science and Engineering > School of Mathematics and Statistics College of Science and Engineering > School of Mathematics and Statistics > Statistics |
| Journal Name: | Evironmental and Ecological Statistics |
| Publisher: | Springer |
| ISSN: | 1352-8505 |
| ISSN (Online): | 1573-3009 |
| Published Online: | 11 September 2015 |
| Copyright Holders: | Copyright © 2015 The Authors |
| First Published: | First published in Evironmental and Ecological Statistics 23(1): 65-87 |
| Publisher Policy: | Reproduced under a Creative Commons License |
University Staff: Request a correction | Enlighten Editors: Update this record
Altmetric
Altmetric