Publication: A predictive model of the impact of urbanization on bacterial loads in watersheds
4
Issued Date
2021-05-15
Resource Type
ISSN
09596526
Other identifier(s)
2-s2.0-85102976673
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Cleaner Production. Vol.297, (2021)
Suggested Citation
Chantima Piyapong, Nitcha Chamroensaksri, Sayam Aroonsrimorakot, Lawan Eyosawat, Surasak Khankhum, Sunirat Rattana, Nuchsupha Sunthamala, Panya Warapetcharayut, Emmanuel Paradis A predictive model of the impact of urbanization on bacterial loads in watersheds. Journal of Cleaner Production. Vol.297, (2021). doi:10.1016/j.jclepro.2021.126704 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/76445
Research Projects
Organizational Units
Authors
Journal Issue
Thesis
Title
A predictive model of the impact of urbanization on bacterial loads in watersheds
Other Contributor(s)
Mahidol University
Burapha University
CNRS Centre National de la Recherche Scientifique
Thailand National Science and Technology Development Agency
Mahasarakham University
Ministry of Natural Resources and Environment
Ministry of Natural Resources and Environment
Ministry of Natural Resources and Environment
Burapha University
CNRS Centre National de la Recherche Scientifique
Thailand National Science and Technology Development Agency
Mahasarakham University
Ministry of Natural Resources and Environment
Ministry of Natural Resources and Environment
Ministry of Natural Resources and Environment
Abstract
Bacterial concentration is one of the most important aspects of water quality. Many regions in the world are affected by increasing urbanization and a potential increase in bacterial concentrations in waters. We used long-term data from 68 stations in eight watersheds in Eastern Thailand to quantify the temporal and geographical variation in total and fecal coliform bacteria. Descriptive statistics showed considerable seasonal, inter-annual, and geographical variation. In order to quantify this multi-level variation, we built a predictive model of bacterial loads. Using fixed- and mixed-effects regression models, we built a model including the effects of urbanization and other significant variables. The best model, fitted by restricted maximum likelihood, included the effects of season, year, urbanization as fixed effects, and of watershed and station as nested, random effects. Temporal variation was related to seasonal and annual variations. Spatial variation had a very significant impact on the bacterial concentrations. Urbanization was an important factor controlling concentrations of bacteria in rivers: we found that the proportion of urban area around a station had a statistically significant effect on log-transformed total coliform bacterial concentration with a slope equal to 1.3 (SE = 0.3), and on log-transformed fecal coliform bacterial concentration with a slope equal to 1.4 (SE = 0.3). Our model predicts that bacterial concentrations would be multiplied by 20 if land is transformed from non-urban to fully urban.