NDLI: Assessing the Relative Importance of Nitrogen-Retention Processes in a Large Reservoir Using Time-Series Modeling

Content Provider	Springer Nature Link
Author	Hansen, Elizabeth Chan, Kung Sik Jones, Christopher S. Schilling, Keith
Copyright Year	2015
Abstract	Nitrogen (N) removal within reservoirs can be substantial, but few studies have reported the relative importance of various N-retention pathways. Assessing N-removal processes in reservoirs is important for quantifying the impacts of reservoirs on downstream water quality. In this study, we used a time-series approach to quantify the relative importance of various N-removal processes in the Saylorville Reservoir in Iowa. Dynamic regression modeling of upstream–downstream changes in key water-quality surrogates (pH, hardness, alkalinity, and suspended solids) and their relation to N concentration changes were used to estimate the relative importances of denitrification, N assimilation by algal uptake, and sedimentation of N on N retention in the reservoir. Assuming that decreasing N concentrations in the reservoir are the sum of these three processes, we estimate that denitrification is the dominant N removal process (60.9 %) followed by algal assimilation (37.9 %) and sedimentation (1.2 %). Our approach represents a new method of establishing the relative importance of N-removal processes in reservoirs and quantifying the impacts of reservoirs on downstream water quality.
Starting Page	152
Ending Page	169
Page Count	18
File Format	PDF
ISSN	10857117
Journal	Journal of Agricultural, Biological, and Environmental Statistics
Volume Number	21
Issue Number	1
e-ISSN	15372693
Language	English
Publisher	Springer US
Publisher Date	2015-11-30
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Nitrate–nitrogen Reservoirs Time-series modeling Denitrification Assimilation Statistics for Life Sciences, Medicine, Health Sciences Agriculture Environmental Monitoring/Analysis Biostatistics
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty

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