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A B ayesian hierarchical approach to model seasonal algal variability along an upstream to downstream river gradient
Author(s) -
Cha YoonKyung,
Soon Park Seok,
Won Lee Hye,
Stow Craig A.
Publication year - 2016
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2015wr017327
Subject(s) - eutrophication , environmental science , phytoplankton , chlorophyll a , context (archaeology) , upstream and downstream (dna) , hydrology (agriculture) , seasonality , algal bloom , abundance (ecology) , upstream (networking) , ecology , nutrient , geography , biology , computer science , geology , computer network , botany , geotechnical engineering , archaeology
Modeling to accurately predict river phytoplankton distribution and abundance is important in water quality and resource management. Nevertheless, the complex nature of eutrophication processes in highly connected river systems makes the task challenging. To model dynamics of river phytoplankton, represented by chlorophyll a (Chl a ) concentration, we propose a Bayesian hierarchical model that explicitly accommodates seasonality and upstream‐downstream spatial gradient in the structure. The utility of our model is demonstrated with an application to the Nakdong River (South Korea), which is a eutrophic, intensively regulated river, but functions as an irreplaceable water source for more than 13 million people. Chl a is modeled with two manageable factors, river flow, and total phosphorus (TP) concentration. Our model results highlight the importance of taking seasonal and spatial context into account when describing flow regimes and phosphorus delivery in rivers. A contrasting positive Chl a ‐flow relationship across stations versus negative Chl a ‐flow slopes that arose when Chl a was modeled on a station‐month basis is an illustration of Simpson's paradox, which necessitates modeling Chl a ‐flow relationships decomposed into seasonal and spatial components. Similar Chl a ‐TP slopes among stations and months suggest that, with the flow effect removed, positive TP effects on Chl a are uniform regardless of the season and station in the river. Our model prediction successfully captured the shift in the spatial and monthly patterns of Chl a .