FORECAST SKILL OF DISSOLVED ORGANIC MATTER CONCENTRATIONS DECREASES DURING STRATIFIED CONDITIONS

Dissolved organic matter (DOM) is a valuable metric of ecosystem functioning and water quality in freshwater systems. Despite its importance for biogeochemical cycling, ecosystem metabolism, as well as drinking water management, we are unaware of any forecasts (i.e., predictions of future conditions with specified uncertainty) that have been developed for DOM dynamics. To improve our understanding of DOM cycling and water quality, we developed the first 1-16-day ahead forecasts of epilimnetic fluorescent DOM (fDOM) in a small eutrophic, dimictic reservoir in Vinton, Virginia, USA. Our forecasts use a time series model based on forecasted water temperature and meteorology that is updated daily from high-frequency fDOM sensor data that are wirelessly transmitted to the cloud for data assimilation. We found that our forecasts were able to capture observed dynamics over a year. Forecast skill varied across seasons, with a higher RMSE in the summer stratified period (RMSE=4.2 quinine sulfate units (QSU)) compared to other seasons (RMSE=3.2 QSU). Over the 1-16-day forecast horizon, forecast RMSE increased from 1.3 to 5.6 QSU. Uncertainty (contributed by model parameters, driver data, model structure, and initial conditions) increased over the forecast horizon (standard deviation increasing from 3.2 to 5.3 QSU over the 16-day horizon), and was greatest during summer. These forecasts can help guide water managers as well as improve our understanding of the predictability of DOM in freshwater ecosystems. 

Primary Presenter: Dexter Howard, Virginia Tech (dwh1998@vt.edu)

Authors:

Dexter Howard, Virginia Tech  (dwh1998@vt.edu)

Adrienne Breef-Pilz, Virginia Tech  (abreefpilz@vt.edu)

Austin Delany, Virginia Tech  (addelany@vt.edu)

Mary Lofton, Virginia Tech  (melofton@vt.edu)

Quinn Thomas, Virginia Tech  (rqthomas@vt.edu)

Cayelan Carey, Virginia Tech  (cayelan@vt.edu)