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Using Multi-media Modeling to Investigate Conditions Leading to Harmful Algal Blooms
Abstract
We used linked and coupled physical models to identify relationships among environmental variables across multiple sources and pathways to examine the impact of nitrogen loadings on chlorophyll α concentrations.
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The occurrence of high cyanotoxin concentrations can severely impair the use of a waterbody for drinking water and recreational purposes. Cyanotoxins are likely to occur under specific environmental conditions, and so identifying these conditions can facilitate management of the waterbody to reduce the likelihood of high cyanotoxin concentrations.
We analysed data collected from lakes across the contiguous United States to identify environmental variables that are strongly associated with occurrence of high concentrations of a common cyanotoxin, microcystin ( MC ).
Since many different environmental variables covary and are associated with high MC , we used least absolute shrinkage and selection operator ( LASSO ) regression to identify a few variables that provided accurate predictions of high MC (≥1 μg L ⁻¹ ).
Our analysis indicated that total nitrogen ( TN ) and chlorophyll a (chl a ) concentrations yielded a parsimonious model that accurately predicted the occurrence of high MC . Based on this model, we identified management thresholds for TN and chl a that would maintain the probability of high MC at or below 10 and 5%.
Evaluation of a regional air-quality model with bidirectional NH3 exchange coupled to an agroecosystem model
- J O Bash
- JO Bash