Gabriel Perez

Postdoctoral Research Associate

Dr. Perez is a postdoctoral research associate in the Watershed System Modeling Group at the Climate Change Science Institute at ORNL. His research combines numerical modeling of physical-based hydrological processes with stochastic processes theory, with the main goal of dissecting the roles of rainfall and land surface process interactions in producing surface and subsurface flow at a wide range of temporal and spatial scales. He is interested in high-performance computing, hydroclimate impact assessment, flood frequency analysis, stochastic modeling, remote sensing, machine learning, groundwater modeling, and hyporheic exchange modeling.

Before joining ORNL, Dr. Perez worked as a postdoctoral scholar at Vanderbilt University. He received his Ph.D. in Hydraulics and Water Resources from the University of Iowa, an M.S. in Water Resources, and a B.S. in Civil Engineering from the National University of Colombia at Medellin.

Papers Published in Refereed Journals

  1. Perez, G., Gomez-Velez, J. D., & Grant, S. B. (2023). The sanitary sewer unit hydrograph model: A comprehensive tool for wastewater flow modeling and inflow-infiltration simulations. Water Research, 120997.
  2. Perez, G., Gomez-Velez, J. D., Chen, X., & Scheibe, T. (2023). The directional unit hydrograph model: Connecting streamflow response to storm dynamics. Journal of Hydrology, 627, 130422.
  3. Krajewski, W. F., Otto, L., Vishwakarma, S., Perez, G. (2023). Revisiting Turcotte’s approach: flood frequency analysis. Stochastic Environmental Research and Risk Assessment, 37(5).
  4. Grant, S.B; Rippy, M; Birkland, T; Schenk, T; Rowles, K; Aminpour, P; Kaushal, S; Vikesland, P; Berglund, E; Gomez-Velez, J; Hotchkiss, E; Perez, G; Zhang, H; Armstrong, K; Bhide, S; Krauss, L; Maas, C; Mendoza, K; Shipman, C; Zhang, Y; Zhong, Y. (2022) “Can Common Pool Resource theory catalyze stakeholder-driven solutions to the freshwater salinization syndrome?” Environmental Science & Technology,
  5. Perez, G., Gomez‐Velez. JD., Chen, X., Scheibe, T., Chen, Y., Bao, J. (2021) Identification of Characteristic Spatial Scales to Improve the Performance of Analytical Spectral Solutions to the Groundwater Flow Equation. Water Resources Research, 57(12)  
  6. Perez, G., Gomez‐Velez, JD., Mantilla, R., Wright, D., Li, Z. (2021) The Effect of Storm Direction on Flood Frequency Analysis. Geophysical Research Letters, 48(9):1–10.
  7. Quintero, F., Krajewski, W. F., Muste, M., Rojas, M., Perez, G., Johnson, S. J., Anderson, A., Hunemuller, T., Cappuccio., B., & Zogg, J. (2021). Development of synthetic rating curves: A case study in Iowa. Journal of Hydrologic Engineering, 1–12.  
  8. Perez, G., Mantilla, R., Krajewski, W. F., & Quintero, F. (2019). Examining Observed Rainfall, Soil Moisture, and River Network Variabilities on Peak Flow Scaling of Rainfall‐Runoff Events with Implications on Regionalization of Peak Flow Quantiles. Water Resources Research, 2019WR026028. .
  9. Perez, G., Mantilla, R., Krajewski, W. F., & Wright, D. B. (2019). Using Physically Based Synthetic Peak Flows to Assess Local and Regional Flood Frequency Analysis Methods. Water Resources Research, 2019WR024827. .
  10. Perez, G., Mantilla, R., & Krajewski, W. F. (2018). Estimation of Historical-Annual and Historical-Monthly Scale-Invariant Flow Duration Curves with Implementation for Iowa. Journal of Hydrologic Engineering, 23(12), 05018021. .
  11. Perez, G., Mantilla, R., & Krajewski, W. F. (2018). The Influence of Spatial Variability of Width Functions on Regional Peak Flow Regressions. Water Resources Research, 54(10), 7651–7669

Book Chapters

  1. Perez, G., Mantilla, R., & Krajewski, W. F. (2018). Spatial patterns of peak flow quantiles based on power-law scaling in the Mississippi River basin. In A. A. Tsonis (Ed.), Thirty Years of Nonlinear Dynamics in Geosciences. Springer.