ReviewACS environmental Au2025
Effective Nutrient Management of Surface Waters in the United States Requires Expanded Water Quality Monitoring in Agriculturally Intensive Areas.
Review in ACS environmental Au, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Accounting for legacy nitrogen stores does not improve the accuracy of riverine nitrate load model predictions.Environmental research. Water · 2025Article
- Linking agricultural conservation to water quality outcomes in the United States at multiple scales: Do we have the information we need?Journal of environmental qualityReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The U.S. Clean Water Act is believed to have driven widespread decreases in pollutants from point sources and developed areas, but has not substantially affected nutrient pollution from agriculture. Today, the highest nutrient concentrations in surface waters are often associated with agricultural production. In this Perspective, we explore whether challenges stemming from the Clean Water Act's inability to mitigate agricultural nutrient pollution are also exacerbated by coarse nutrient monitoring. We evaluate the current state of nutrient monitoring in surface waters of the contiguous U.S. relative to agricultural nutrient inputs to assess how monitoring effort varies across agriculturally intensive areas. The locations of nutrient monitoring stations with approximately seasonal sampling frequency (4 samples per year, on average) from 2012 to 2021 were compiled from the U.S. Water Quality Portal. Monitoring station locations were then compared to watershed-scale (HUC-8) nutrient inventory estimates for agricultural fertilizer and livestock manure inputs. From this assessment, we found that many, but not all, of the nation's most agriculturally intensive areas are under-monitored, and often unmonitored. While it is well-known that the Midwest is the epicenter of agricultural production in the U.S., our results reveal it is poorly monitored relative to its agricultural nutrient inputs. Other regions, like the California Central Valley and parts of the southeastern Coastal Plain were also coarsely monitored relative to nutrient inputs. Conversely, some agriculturally intensive watersheds were moderately-to-well monitored (e.g., western Lake Erie basin, eastern North Carolina, and the Delmarva Peninsula), with these basins largely having established Total Maximum Daily Loads and discharging to prominent waterways. In closing, we argue that sparse monitoring across many of the nation's most agriculturally intensive areas motivate a need to re-envision nutrient monitoring networks, and that increased resources and advanced technologies are likely required to enable effective nutrient source identification throughout the nation.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.