Monitoring data compilations can be leveraged to highlight relationships between estuarine and watershed factors influencing eutrophication in estuaries.

Estuaries have been adversely impacted by increased nutrient loads. Eutrophication impacts from these loads include excess algal blooms and low oxygen conditions. In this study, we leveraged data from 28 monitoring programs in the northeastern US to explore the relationships between eutrophication response variables and watershed and estuarine variables. Extensive effort was needed to locate, harmonize, and assure the quality of the data. Random forest regression allowed us to identify the most important variables that could predict summer total nitrogen (TN), chlorophyll (chl), and bottom dissolved oxygen (DO). Several different summaries of the data were assessed. The best models for TN and chl used data summarized by estuary and year, explaining > 70% and > 60% of the variation, respectively. The best model for DO used data that were averaged by estuary across all years and explained > 55% of the variation. All models showed the importance of variables related to nutrient loading, such as population density and % development, and variables related to flushing rate, such as tidal range, length:width at mouth, and estuary openness. Future work will examine the impacts of climate on eutrophication response variables. This study demonstrates the utility of combining data from multiple unrelated routine monitoring programs to understand eutrophication impacts at regional scales.