John Ramirez Avila | Environmental Hydrology Award | Excellence in Research

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Dr. John Ramirez Avila | Environmental Hydrology Award | Excellence in Research

Dr. John Ramirez Avila, Mississippi State University, United States

Dr. John Ramirez Avila is an accomplished educator and researcher with expertise in water resources engineering. Holding a Ph.D. in Civil Engineering, he has served as an Associate Professor at Mississippi State University since 2016, prior to which he held various academic and research roles. With a focus on water quality assessment and management, Dr. Avila has taught a range of courses, mentored numerous students, and contributed significantly to advancing knowledge in hydrology and environmental engineering. His dedication to sustainable water use and pollution reduction reflects a commitment to addressing critical environmental challenges. 🌊📚

 

Publication Profile

Google Scholar

Education and Professional Experience 🎓

Dr. John Ramirez Avila holds a B.S. in Agricultural Engineering from Universidad Nacional de Colombia, an M.S. in Soils from the University of Puerto Rico, and a Ph.D. in Civil Engineering (Water Resources Engineering) from Mississippi State University. He currently serves as an Associate Professor at Mississippi State University, where he has contributed extensively through teaching, research, and service roles. With a career spanning various academic and research positions, Dr. Avila has amassed a wealth of experience in water resources management and environmental engineering.

Teaching 🌍

Beyond his academic responsibilities, Dr. Avila has been actively engaged in international teaching and workshops, imparting knowledge on topics like hydrology and watershed management. His commitment to sharing expertise globally underscores his dedication to addressing water resource challenges on a broader scale.

Honors and Achievements 🏆

Dr. Avila’s exemplary contributions have been recognized through numerous awards, including the prestigious Fellow of the Environmental and Water Resources Institute. He has also nurtured the talents of his mentees, guiding them to notable achievements in conferences and competitions, further solidifying his impact on the academic community.

Research Focus

Dr. John Ramirez-Avila’s research primarily focuses on assessing and mitigating nutrient and sediment losses in agricultural landscapes, with a particular emphasis on phosphorus management. Through his extensive work, he has explored the effectiveness of various best management practices (BMPs) such as low-grade weirs and grass filter strips in reducing nutrient runoff. His studies aim to enhance understanding of phosphorus transport mechanisms in drained fields and develop models for predicting phosphorus losses. Dr. Ramirez-Avila’s research contributes significantly to sustainable agricultural practices and water quality improvement, addressing crucial environmental challenges in agricultural regions. 🌱🔬

Publication Top Notes

  1. Applicability of models to predict phosphorus losses in drained fields: A review 📝 Cited by: 126 | Year: 2015
  2. Effectiveness of low-grade weirs for nutrient removal in an agricultural landscape in the Lower Mississippi Alluvial Valley 📝 Cited by: 42 | Year: 2014
  3. A field-scale investigation of nutrient and sediment reduction efficiencies of a low-technology best management practice: Low-grade weirs 📝 Cited by: 40 | Year: 2016
  4. Evaluation of the APEX Model to Simulate Runoff Quality from Agricultural Fields in the Southern Region of the United States 📝 Cited by: 29 | Year: 2017
  5. Southern Phosphorus Indices, water quality data, and modeling (APEX, APLE, and TBET) results: A comparison 📝 Cited by: 25 | Year: 2017
  6. Managing animal manure to minimize phosphorus losses from land to water
  7. Comparing an Annual and a Daily Time-Step Model for Predicting Field-Scale Phosphorus Loss
  8. Erosion and nutrient loss reduction with an alternative planting method for coffee (Coffea arabica)
  9. Transporte de sedimentos y fósforo en escorrentía bajo simulación de lluvia
  10. NRCS curve number method: comparison of methods for estimating the curve number from rainfall-runoff data