Regional Patterns and Drivers of Total Nitrogen Trends in the Chesapeake Bay Watershed
Insights from machine learning approaches and management implications.
Description
Anthropogenic nutrient inputs have led to nutrient enrichment in many waterbodies worldwide, including the Chesapeake Bay. River water quality integrates the spatial and temporal changes of watersheds and forms the foundation for disentangling the effects of anthropogenic inputs. This study, published in Water Research, demonstrates with the Chesapeake Bay Non-Tidal Monitoring Network that machine learning approaches (i.e., hierarchical clustering and random forest classification) can be combined to better understand the regional patterns and drivers of total nitrogen trends in large monitoring networks, resulting in information useful for watershed management.
Citation
Zhang, Q., J.T. Bostic and R.D. Sabo, 2022. “Regional patterns and drivers of total nitrogen trends in the Chesapeake Bay watershed: Insights from machine learning approaches and management implications”, Water Research, 218:118443, doi: 10.1016/j.watres.2022.118443.
Category: Report