John J. Ramírez-Ávila

434 total citations
33 papers, 307 citations indexed

About

John J. Ramírez-Ávila is a scholar working on Water Science and Technology, Environmental Chemistry and Soil Science. According to data from OpenAlex, John J. Ramírez-Ávila has authored 33 papers receiving a total of 307 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Water Science and Technology, 15 papers in Environmental Chemistry and 15 papers in Soil Science. Recurrent topics in John J. Ramírez-Ávila's work include Hydrology and Watershed Management Studies (23 papers), Soil and Water Nutrient Dynamics (15 papers) and Soil erosion and sediment transport (14 papers). John J. Ramírez-Ávila is often cited by papers focused on Hydrology and Watershed Management Studies (23 papers), Soil and Water Nutrient Dynamics (15 papers) and Soil erosion and sediment transport (14 papers). John J. Ramírez-Ávila collaborates with scholars based in United States, Puerto Rico and Sweden. John J. Ramírez-Ávila's co-authors include Carl H. Bolster, R. Kröger, D. E. Radcliffe, Nathan O. Nelson, Deanna L. Osmond, Douglas R. Smith, Keith Reid, Wendy Francesconi, Mats Larsbo and Kristian Persson and has published in prestigious journals such as Journal of Hydrology, Journal of Environmental Quality and Agricultural Water Management.

In The Last Decade

John J. Ramírez-Ávila

27 papers receiving 290 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
John J. Ramírez-Ávila United States 8 197 189 147 56 45 33 307
Kristian Persson Sweden 6 236 1.2× 190 1.0× 138 0.9× 40 0.7× 46 1.0× 10 346
Vinayak S. Shedekar United States 12 184 0.9× 177 0.9× 154 1.0× 76 1.4× 63 1.4× 27 378
Stanley Livingston United States 10 216 1.1× 171 0.9× 175 1.2× 58 1.0× 40 0.9× 16 367
Nigel Fleming Australia 11 274 1.4× 187 1.0× 214 1.5× 34 0.6× 54 1.2× 24 385
Martha L. Villamizar United Kingdom 8 144 0.7× 175 0.9× 71 0.5× 44 0.8× 22 0.5× 9 266
Petr Fučík Czechia 12 96 0.5× 177 0.9× 99 0.7× 68 1.2× 31 0.7× 27 333
Ainis Lagzdiņš Latvia 11 270 1.4× 254 1.3× 145 1.0× 40 0.7× 40 0.9× 44 409
Lindsay Pease United States 11 377 1.9× 250 1.3× 253 1.7× 46 0.8× 68 1.5× 20 486
Hiroaki Somura Japan 11 123 0.6× 234 1.2× 84 0.6× 68 1.2× 34 0.8× 48 374
Noeleen McDonald Ireland 8 269 1.4× 223 1.2× 148 1.0× 36 0.6× 28 0.6× 14 369

Countries citing papers authored by John J. Ramírez-Ávila

Since Specialization
Citations

This map shows the geographic impact of John J. Ramírez-Ávila's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by John J. Ramírez-Ávila with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John J. Ramírez-Ávila more than expected).

Fields of papers citing papers by John J. Ramírez-Ávila

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John J. Ramírez-Ávila. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by John J. Ramírez-Ávila. The network helps show where John J. Ramírez-Ávila may publish in the future.

Co-authorship network of co-authors of John J. Ramírez-Ávila

This figure shows the co-authorship network connecting the top 25 collaborators of John J. Ramírez-Ávila. A scholar is included among the top collaborators of John J. Ramírez-Ávila based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John J. Ramírez-Ávila. John J. Ramírez-Ávila is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ramírez-Ávila, John J., et al.. (2025). Toward a better understanding of curve number and initial abstraction ratio values from a large sample of watersheds perspective. Journal of Hydrology. 655. 132941–132941. 2 indexed citations
2.
Ramírez-Ávila, John J., et al.. (2025). Comparing Frequency-Matched and Natural Data Approaches for Estimating the Curve Number from Rainfall-Runoff Data. Journal of Hydrologic Engineering. 30(3).
3.
Bonta, J. V., David A. Chin, Michael S. Johnson, et al.. (2025). The Curve Number’s Initial Abstraction and Physical Hydrology: ASCE-EWRI CN Hydrology Committee Synthesis. Journal of Irrigation and Drainage Engineering. 151(4).
4.
Brooks, John P., et al.. (2024). Short-Term Contribution of Conservation Practice Implementation to Water Quality Impairments in Small Streams. Water. 16(2). 261–261. 1 indexed citations
5.
Ramírez-Ávila, John J., et al.. (2024). High-resolution Annual Dynamic dataset of Curve Number from 2008 to 2021 over Conterminous United States. Scientific Data. 11(1). 207–207. 4 indexed citations
6.
Ramírez-Ávila, John J., et al.. (2024). Evaluating the Effects of Initial Abstraction Ratio on Curve Number Accuracy. 1535–1548. 4 indexed citations
7.
Ramírez-Ávila, John J., et al.. (2023). Advancing Watershed Modeling for TMDL and Holistic Watershed Management Including Climate Change Impacts. 1227–1241. 2 indexed citations
8.
Quinn, Nigel W.T., John J. Ramírez-Ávila, Huilin Gao, et al.. (2022). Applications of GIS and remote sensing in public participation and stakeholder engagement for watershed management. Socio-Environmental Systems Modeling. 4. 18149–18149. 10 indexed citations
9.
Moglen, Glenn E., et al.. (2022). NRCS Curve Number Method: Comparison of Methods for Estimating the Curve Number from Rainfall-Runoff Data. Journal of Hydrologic Engineering. 27(10). 17 indexed citations
10.
Bolster, Carl H., Claire Baffaut, Nathan O. Nelson, et al.. (2019). Development of PLEAD: A Database Containing Event‐based Runoff Phosphorus Loadings from Agricultural Fields. Journal of Environmental Quality. 48(2). 510–517. 3 indexed citations
11.
Ramírez-Ávila, John J., et al.. (2019). Barrier Island Restoration: A Literature Review. 310–319.
12.
Osmond, Deanna L., Carl H. Bolster, Andrew N. Sharpley, et al.. (2017). Southern Phosphorus Indices, Water Quality Data, and Modeling (APEX, APLE, and TBET) Results: A Comparison. Journal of Environmental Quality. 46(6). 1296–1305. 22 indexed citations
13.
Bolster, Carl H., Aaron R. Mittelstet, D. E. Radcliffe, et al.. (2017). Comparing an Annual and a Daily Time‐Step Model for Predicting Field‐Scale Phosphorus Loss. Journal of Environmental Quality. 46(6). 1314–1322. 15 indexed citations
14.
Ramírez-Ávila, John J., et al.. (2017). Runoff Curve Number Estimation for Agricultural Systems in the Southern Region of USA. 353–366. 5 indexed citations
15.
16.
Radcliffe, D. E., Keith Reid, Karin Blombäck, et al.. (2015). Applicability of Models to Predict Phosphorus Losses in Drained Fields: A Review. Journal of Environmental Quality. 44(2). 614–628. 100 indexed citations
17.
Kröger, R., et al.. (2013). Effectiveness of low-grade weirs for nutrient removal in an agricultural landscape in the Lower Mississippi Alluvial Valley. Agricultural Water Management. 131. 79–86. 31 indexed citations
18.
Ramírez-Ávila, John J., et al.. (2011). Phosphorus in runoff from two highly weathered soils of the tropics. Canadian Journal of Soil Science. 91(2). 267–277. 2 indexed citations
19.
Sotomayor‐Ramírez, David, et al.. (2009). Caribbean Phosphorus Index Validation and Management Practices Evaluation on Fields under Manure Applications. 2009 Reno, Nevada, June 21 - June 24, 2009.
20.
Sotomayor‐Ramírez, David, et al.. (2008). Eficacia de franjas filtrantes para la reducción de nutrientes en escorrentía de pasturas enmendadas con efluentes de vaquerías.. The Journal of Agriculture of the University of Puerto Rico. 92(1-2). 1–14. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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