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Title: The importance of considering shifts in seasonal changes in discharges when prediciting future phosphorus loads in streams

Author
item LABEAU, MERIDITH - Michigan Technological University
item MAYER, ALEX - Michigan Technological University
item GRIFFIS, VERONICA - Michigan Technological University
item WATKINS, DAVID - Michigan Technological University
item ROBERTSON, DALE - Us Geological Survey (USGS)
item Gyawali, Rabi

Submitted to: Biogeochemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/10/2015
Publication Date: 10/30/2015
Citation: Labeau, M., Mayer, A., Griffis, V., Watkins, D., Robertson, D., Gyawali, R. 2015. The importance of considering shifts in seasonal changes in discharges when prediciting future phosphorus loads in streams. Biogeochemistry. 126:153-172.

Interpretive Summary: This research demonstrates the use of climate data to develop statistical relationships between Phosphorus concentrations and streamflow in 14 Great Lakes watersheds. It was found out that seasonal models are important to understand the effects of future climate change on nutrient loads.

Technical Abstract: In this work, we hypothesize that phosphorus (P) concentrations in streams vary seasonally and with streamflow and that it is important to incorporate this variation when predicting changes in P loading associated with climate change. Our study area includes 14 watersheds with a range of land uses throughout the U.S. Great Lakes Basin. We develop annual seasonal load-discharge regression models for each watershed and apply these models with simulated discharges generated for future climate scenarios to simulate future P loading patterns for two periods: 2046–2065 and 2081–2100. We utilize output from the Coupled Model Intercomparison Project phase 3 downscaled climate change projections that are input into the Large Basin Runoff Model to generate future discharge scenarios, which are in turn used as inputs to the seasonal P load regression models. In almost all cases, the seasonal load-discharge models match observed loads better than the annual models. Results using the seasonal models show that the concurrence of nonlinearity in the load-discharge model and changes in high discharges in the spring months leads to the most significant changes in P loading for selected tributaries under future climate projections. These results emphasize the importance of using seasonal models to understand the effects of future climate change on nutrient loads.