Spatio-temporal statistical models for river monitoring networks
- Author
- Lieven Clement (UGent) , Olivier Thas (UGent) , Peter Vanrolleghem (UGent) and Jean-Pierre Ottoy (UGent)
- Organization
- Abstract
- When introducing new wastewater treatment plants (WWTP), investors and policy makers often want to know if there indeed is a beneficial effect of the installation of a WWTP on the river water quality. Such an effect can be established in time as well as in space. Since both temporal and spatial components affect the output of a monitoring network, their dependence structure has to be modelled. River water quality data typically come from a river monitoring network for which the spatial dependence structure is unidirectional. Thus the traditional spatio-temporal models are not appropriate, as they cannot take advantage of this directional information. In this paper, a state-space model is presented in which the spatial dependence of the state variable is represented by a directed acyclic graph, and the temporal dependence by a first-order autoregressive process. The state-space model is extended with a linear model for the mean to estimate the effect of the activation of a WWTP on the dissolved oxygen concentration downstream.
- Keywords
- parameter estimation, theory intervention analysis, water quality, space-time model
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-328421
- MLA
- Clement, Lieven, et al. “Spatio-Temporal Statistical Models for River Monitoring Networks.” WATER SCIENCE AND TECHNOLOGY, vol. 53, no. 1, 2006, pp. 9–15, doi:10.2166/wst.2006.002.
- APA
- Clement, L., Thas, O., Vanrolleghem, P., & Ottoy, J.-P. (2006). Spatio-temporal statistical models for river monitoring networks. WATER SCIENCE AND TECHNOLOGY, 53(1), 9–15. https://doi.org/10.2166/wst.2006.002
- Chicago author-date
- Clement, Lieven, Olivier Thas, Peter Vanrolleghem, and Jean-Pierre Ottoy. 2006. “Spatio-Temporal Statistical Models for River Monitoring Networks.” WATER SCIENCE AND TECHNOLOGY 53 (1): 9–15. https://doi.org/10.2166/wst.2006.002.
- Chicago author-date (all authors)
- Clement, Lieven, Olivier Thas, Peter Vanrolleghem, and Jean-Pierre Ottoy. 2006. “Spatio-Temporal Statistical Models for River Monitoring Networks.” WATER SCIENCE AND TECHNOLOGY 53 (1): 9–15. doi:10.2166/wst.2006.002.
- Vancouver
- 1.Clement L, Thas O, Vanrolleghem P, Ottoy J-P. Spatio-temporal statistical models for river monitoring networks. WATER SCIENCE AND TECHNOLOGY. 2006;53(1):9–15.
- IEEE
- [1]L. Clement, O. Thas, P. Vanrolleghem, and J.-P. Ottoy, “Spatio-temporal statistical models for river monitoring networks,” WATER SCIENCE AND TECHNOLOGY, vol. 53, no. 1, pp. 9–15, 2006.
@article{328421, abstract = {{When introducing new wastewater treatment plants (WWTP), investors and policy makers often want to know if there indeed is a beneficial effect of the installation of a WWTP on the river water quality. Such an effect can be established in time as well as in space. Since both temporal and spatial components affect the output of a monitoring network, their dependence structure has to be modelled. River water quality data typically come from a river monitoring network for which the spatial dependence structure is unidirectional. Thus the traditional spatio-temporal models are not appropriate, as they cannot take advantage of this directional information. In this paper, a state-space model is presented in which the spatial dependence of the state variable is represented by a directed acyclic graph, and the temporal dependence by a first-order autoregressive process. The state-space model is extended with a linear model for the mean to estimate the effect of the activation of a WWTP on the dissolved oxygen concentration downstream.}}, author = {{Clement, Lieven and Thas, Olivier and Vanrolleghem, Peter and Ottoy, Jean-Pierre}}, issn = {{0273-1223}}, journal = {{WATER SCIENCE AND TECHNOLOGY}}, keywords = {{parameter estimation,theory intervention analysis,water quality,space-time model}}, language = {{eng}}, location = {{Beijing, PR China}}, number = {{1}}, pages = {{9--15}}, title = {{Spatio-temporal statistical models for river monitoring networks}}, url = {{http://doi.org/10.2166/wst.2006.002}}, volume = {{53}}, year = {{2006}}, }
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