Jump to Main Content
Linking terrestrial phosphorus inputs to riverine export across the United States
- Metson, Genevieve S., Lin, Jiajia, Harrison, John A., Compton, Jana E.
- Water research 2017 v.124 pp. 177-191
- agricultural land, algal blooms, aquatic ecosystems, crops, data collection, detergents, eutrophication, fertilizers, humans, hypoxia, mechanistic models, monitoring, phosphorus, pollution load, prediction, runoff, sewage, variance, watersheds, waterways, United States
- Humans have greatly accelerated phosphorus (P) flows from land to aquatic ecosystems, causing eutrophication, harmful algal blooms, and hypoxia. A variety of statistical and mechanistic models have been used to explore the relationship between P management on land and P losses to waterways, but our ability to predict P losses from watersheds often relies on small scale catchment studies, where detailed measurements can be made, or global scale models that that are often too coarse-scaled to be used directly in the management decision-making process. Here we constructed spatially explicit datasets of terrestrial P inputs and outputs across the conterminous U.S. (CONUS) for 2012. We use this dataset to improve understanding of P sources and balances at the national scale and to investigate whether well-standardized input data at the continental scale can be used to improve predictions of hydrologic P export from watersheds across the U.S. We estimate that in 2012 agricultural lands received 0.19 Tg more P as fertilizer and confined manure than was harvested in major crops. Approximately 0.06 Tg P was lost to waterways as sewage and detergent nationally based on per capita loads in 2012. We compared two approaches for calculating non-agricultural P waste export to waterways, and found that estimates based on per capita P loads from sewage and detergent were 50% greater than Discharge Monitoring Report Pollutant Loading Tool. This suggests that the tool is likely underestimating P export in waste the CONUS scale. TP and DIP concentrations and TP yields were generally correlated more strongly with runoff than with P inputs or P balances, but even the relationships between runoff and P export were weak. Including P inputs as independent variables increased the predictive capacity of the best-fit models by at least 20%, but together inputs and runoff explained 40% of the variance in P concentration and 46–54% of the variance in P yield. By developing and applying a high-resolution P budget for the CONUS this study confirms that both hydrology and P inputs and sinks play important roles in aquatic P loading across a wide range of environments.