Abstract
Agricultural runoff from the Mississippi-Atchafalaya River Basin delivers nitrogen (N) and phosphorus (P) to the Gulf of Mexico, causing hypoxia, and climate drives interannual variation in nutrient loads. Climate phenomena such as El Niño–Southern Oscillation may influence nutrient export through effects on river flow, nutrient uptake, or biogeochemical transformation, but landscape variation at smaller spatial scales can mask climate signals in load or discharge time series within large river networks. We used multivariate autoregressive state-space modeling to investigate climate signals in the long-term record (1979–2014) of discharge, N, P, and SiO2 loads at three nested spatial scales within the Mississippi-Atchafalaya River Basin. We detected significant signals of El Niño–Southern Oscillation and land-surface temperature anomalies in N loads but not discharge, SiO2, or P, suggesting that large-scale climate phenomena contribute to interannual variation in nutrient loads through biogeochemical mechanisms beyond simple discharge-load relationships.
| Original language | English |
|---|---|
| Pages (from-to) | 3791-3801 |
| Number of pages | 11 |
| Journal | Geophysical Research Letters |
| Volume | 46 |
| Issue number | 7 |
| DOIs | |
| State | Published - Apr 16 2019 |
Funding
Data used in this analysis are available online through the following U.S. government agencies: USGS, NOAA, and USDA. We thank the National Science Foundation (grant DEB-1354867) for funding the Stream Resiliency Research Coordination Network and the National Socio-Environmental Synthesis Center for hosting the working group where many of these ideas were developed. A.P.A. was partly supported by the USGS Office of Water Information. N.A.G. was partially supported by the U.S. Department of Energy's Office of Science, Biological and Environmental Research and Environmental Management Programs. Data used in this analysis are available online through the following U.S. government agencies: USGS, NOAA, and USDA. We thank the National Science Foundation (grant DEB‐ 1354867) for funding the Stream Resiliency Research Coordination Network and the National Socio‐ Environmental Synthesis Center for hosting the working group where many of these ideas were developed. A.P.A. was partly supported by the USGS Office of Water Information. N.A.G. was partially supported by the U.S. Department of Energy's Office of Science, Biological and Environmental Research and Environmental Management Programs.
Keywords
- climate
- multivariate autoregressive state space models
- nitrogen
- phosphorous
- rivers
- time series analysis