Estimating Nutrient and Organic Carbon Loads to Water-Supply Reservoir Using Semiparametric Models
Publication: Journal of Environmental Engineering
Volume 142, Issue 8
Abstract
This study investigated the impact of model form and flexibility on estimates of constituent loads to a water-supply reservoir. A series of load-estimation regression models were calibrated and used to predict nutrient (nitrate-nitrogen and total phosphorus) and organic carbon loads from three major tributaries of a water-supply reservoir. These models included traditional linear models (LMs) as well as semiparametric generalized additive models (GAMs). The relative performance of each model was determined using cross-validation. GAMs, which employ more flexible model structures, outperformed LMs in most cases, explaining an additional 2% of load variance and 5% of concentration variance in validation data on average. Resulting point load estimates from the 1.5-year study period were similar between the two modeling approaches, yielding overlapping 95% confidence intervals in all nine cases modeled. A novel graphical method was developed to present relative agreement between the two model types as a function of the time interval over which the load is estimated. This revealed relative differences between the two modeling approaches in excess of 100% depending on the time interval of the load estimate. The time-dependent disagreement between similarly well-performing models highlights an aspect of model uncertainty not visible in more structurally restrictive modeling approaches.
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Acknowledgments
This work was funded by the Massachusetts Department of Conservation and Recreation (MassDCR). The authors would like to thank Ms. Patricia Austin, Mr. Lawrence Pistrang, and Mr. Steve Sulprizio at MassDCR for providing the data and their review for this paper.
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Published In
Journal of Environmental Engineering
Volume 142 • Issue 8 • August 2016
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Feb 19, 2015
Accepted: Oct 23, 2015
Published online: Mar 2, 2016
Published in print: Aug 1, 2016
Discussion open until: Aug 2, 2016
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