The DOI matches its Crossref record.
AGNPS: A nonpoint-source pollution model for evaluating agricultural watersheds
Abstract
A computer model to analyze nonpoint-source pollution and to prioritize potential water quality problems in rural areas is described. The event-based model uses geographic cells of data units at resolutions of 0.4 to 16 ha to represent upland and channel conditions. Within the framework of the cells, runoff characteristics and transport processes of sediment, nutrients, and chemical oxygen demand are simulated for each cell and routed to the outlet. This permits the flow at any point in the watershed to be examined. Upland sources contributing to a potential problem can be identified and prioritized where remedial measures could be initiated to improve water quality most efficiently.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China
Yang, J., Reichert, P., Abbaspour, K. C., Xia, J., & Yang, H. (2008) · Journal of Hydrology · doi:10.1016/j.jhydrol.2008.05.012 · Cited by 800
Using the USLE: Chances, challenges and limitations of soil erosion modelling
Alewell, C., Borrelli, P., Meusburger, K., & Panagos, P. (2019) · International Soil and Water Conservation Research · doi:10.1016/j.iswcr.2019.05.004 · Cited by 804
Evaluating Hydrologic Response of an Agricultural Watershed for Watershed Analysis
Jha, M. K. (2011) · Water · doi:10.3390/w3020604 · Cited by 61
Powers, S. E. (2005) · doi:10.2172/15016223 · Cited by 30
Metadata
- Authors
- Young, R. A., Onstad, C. A., Bosch, D. D., & Anderson, W. P.
- Venue
- Journal of Soil and Water Conservation
- Publisher
- Informa UK Limited
- Published
- 1989-03
- Volume
- 44
- Issue
- 2
- Pages
- 168-173
- ISSN
- 0022-4561 (ISSN-L)
- 1941-3300
- OpenAlex
- W1839261311
- Cited by
- 932
- References
- 0
- FWCI
- 10.00
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: AGNPS: A nonpoint-source pollution model for evaluating agricultural watersheds. https://app.cochat.ai/papers/10.1080/00224561.1989.12456304
- The paper
- Young, R. A., Onstad, C. A., Bosch, D. D., & Anderson, W. P. (1989). AGNPS: A nonpoint-source pollution model for evaluating agricultural watersheds. Journal of Soil and Water Conservation. https://doi.org/10.1080/00224561.1989.12456304
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.