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Using in situ UV‐Visible spectrophotometer sensors to quantify riverine phosphorus partitioning and concentration at a high frequency
Author(s) -
Vaughan Matthew C. H.,
Bowden William B.,
Shanley James B.,
Vermilyea Andrew,
Wemple Beverley,
Schroth Andrew W.
Publication year - 2018
Publication title -
limnology and oceanography: methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.898
H-Index - 72
ISSN - 1541-5856
DOI - 10.1002/lom3.10287
Subject(s) - turbidity , phosphorus , environmental science , water quality , watershed , dissolved organic carbon , nutrient , environmental chemistry , land cover , hydrology (agriculture) , chemistry , land use , ecology , geotechnical engineering , organic chemistry , machine learning , computer science , engineering , biology
Accurate riverine phosphorus concentration measurements are often critical to meet watershed management goals. Phosphorus monitoring programs often rely on proxy variables such as turbidity and discharge and have limited ability to accurately estimate concentrations of dissolved phosphorus fractions that are most bioavailable. Optical water quality sensors can make subhourly measurements and have been shown to reduce uncertainty in load estimates and reveal high‐frequency storm dynamics for nitrate and dissolved organic carbon. We evaluated the utility of in situ UV‐Visible spectrophotometers to predict total, dissolved, and soluble reactive phosphorus concentrations in streams draining agricultural, urban, and forested land use/land covers. We present the first statistically validated application of optical water quality sensors to demonstrate how sensors may perform in predicting phosphorus fraction concentrations through training set models. Total phosphorus predictions from UV‐Visible spectra were optimal when models were site‐specific, and the proportion of variance explained was generally as high as or higher than the results of other studies that rely only on discharge and turbidity. However, root mean square errors for total phosphorus models were relatively high compared to the median concentrations at each site. Models to predict dissolved and soluble reactive phosphorus concentrations explained a greater proportion of the variance than any other known proxy variable technique, and results varied by land use/land cover. Though accuracy limitations remain, this approach has potential to predict concurrent total, dissolved, and soluble reactive phosphorus concentrations at a high frequency for many applications in water quality research and management communities.