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Long-Term Mississippi River Trends Expose Shifts in the River Load Response to Watershed Nutrient Balances Between 1975 and 2017
Excess nutrients transported by the Mississippi River (MR) contribute to hypoxia in the Gulf of Mexico. Nutrient balances are key drivers to river nutrient loads and represent inputs (fertilizer, manure, deposition, wastewater, N-fixation, and weathering) minus outputs (nutrient uptake and removal i...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9983731/ https://www.ncbi.nlm.nih.gov/pubmed/36875793 http://dx.doi.org/10.1029/2021wr030318 |
Sumario: | Excess nutrients transported by the Mississippi River (MR) contribute to hypoxia in the Gulf of Mexico. Nutrient balances are key drivers to river nutrient loads and represent inputs (fertilizer, manure, deposition, wastewater, N-fixation, and weathering) minus outputs (nutrient uptake and removal in harvest, and N emissions). Here, we quantified annual changes in nitrogen (N) and phosphorus (P) river loads and nutrient balances at the MR Outlet and documented that the river load response to watershed nutrient balances shifted between 1975 and 2017. Annual nutrient balances and river loads were positively correlated between 1975 and 1985, but after, a disconnect between both the N and P balances and river loads emerged, and the subsequent river load patterns were different for N versus P. We evaluated the relative impacts of legacy nutrients and other latent factors, for which data were not available, on river nutrient load trends. Our analysis showed that in the case of N, latent factors were potentially just as important in explaining changes in river nutrient loads over time as N balances, and in the case of P, they were even more important. We hypothesized that these factors included implementation of best management practices, changes in watershed buffering capacity, the effects of tile drainage, or increased precipitation. Our analytical approach shows promise for the investigation of drivers of water quality trends that are not well-represented in typical national scale geospatial datasets. |
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