Assistant Professor of Artificial Intelligence/Machine
Learning in Geological Sciences
University of Alabama, Tuscaloosa, AL (Fall 2024 - )
Faculty Fellow
Alabama Water Institute, Tuscaloosa, AL (Fall 2024 - 2027)
Doctor of Philosophy, 2022
University of Alabama
Major: Geological Sciences
Dissertation: “Deep Learning for Operational Streamflow
Forecasts: A Long Short-Term Memory Network Rainfall-Runoff Module for
The National Water Model”. Link
Master of Science, 2011
University of California, Irvine
Major: Civil Engineering - Hydrology and Water Resources
Bachelor of Science, 2010
California State University, Monterey Bay (CSUMB)
Major: Earth Systems Science, Technology and Policy
Minor: Mathematics
Honors Thesis: “An Integrated Surface Water-Groundwater
Interaction Model for the Carmel River”. Link
Frame et al., 2025, “Machine learning for a heterogeneous water modeling framework”. Journal of American Water Resources Association. DOI: 10.1111/1752-1688.70000
Frame et al., 2024, “Rapid inundation mapping using the U.S. National Water Model, satellite observations and convolutional neural networks”. Geophysical Research Letters. DOI
Frame et al., 2023, “On strictly enforced mass conservation constraints for modeling the rainfall runoff process”. Hydrological Processes. Link
Frame et al., 2022, “Deep learning rainfall-runoff predictions of extreme events”. Hydrology and Earth System Sciences. Link
Frame et al., 2021, “Post-processing the National Water Model with Long Short-Term Memory Networks for Streamflow Predictions and Model Diagnostics”. Journal of American Water Resources Association. Link
Ogden et al., 2025, "The NextGen Water Resources Modeling Framework: Community Innovation at the Intersection of Hydrologic, Data and Computer Sciences". In review for Journal of American Water Resources Association.
Ramirez Molina et al., 2025, "A Proof of Concept for Improving Estimates of Ungauged Basin Streamflow Via an LSTM-Based Synthetic Network Simulation Approach"Journal of Geophysical Research - Machine Learning and Computation. link
Abramowitz et al., 2024, "On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results". Biogeosciences. Link
Gholizadeh et al., 2023, “Long short-term memory models to quantify long-term evolution of streamflow discharge and groundwater depth in Alabama”. Science of the Total Environment.
Nearing et al., 2022, “Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks’’. Hydrology and Earth System Sciences. Link
Rahman et al., 2022, “Hydrology Research Articles are Becoming More Topically Diverse”. Journal of Hydrology. DOI
Wei et al., 2022. “A distributed domain model with coupled flow to quantify the impact of lateral hydrologic exchange on hydrograph patterns”. Journal of Hydrology. DOI
Zhang et al., 2021, “Hierarchical Fractional Advection-Dispersion Equation (FADE) to Quantify Anomalous Transport in River Corridor over a Broad Spectrum of Scales: Theory and Applications”. DOI
Brenner et al., 2021, “Predicting evapotranspiration using machine and deep learning methods”. Österreichische Wasser- und Abfallwirtschaft volume 73, pages 295–307 (2021). Link
Nearing et al., 2020, “What Role Does Hydrological Science Play in the Age of Machine Learning?”. Water Resources Research. DOI
Nair et al., 2022. “Deep Hydrology: Hourly, Gap-Free Flood Maps Through Joint Satellite and Hydrologic Modelling” Neural Information Processing Systems (NeurIPS) 2022. Link
Pellisier, Frame and Nearing, 2020, “Combining Parametric Land Surface Models with Machine Learning”. 2020 IEEE International Geoscience and Remote Sensing Symposium. Link
Nearing et al. 2019. “Physically Informed Machine Learning for Hydrological Modeling Under Climate Nonstationarity”. Science and Technology Infusion Climate Bulletin. NOAA’s National Weather Service. 44th NOAA Annual Climate Diagnostics and Prediction Workshop Durham, NC. Link
Frame et al., 2024, “Beyond catchment boundaries: extending geospatial context for local and large-domain hydrological predictions”. AGU Fall Meeting. December 2024. Washington D.C. Link
Frame et al., 2024, “Machine learning for a heterogeneous water modeling framework”. CIROH Developers Conference. May 2024. University of Utah. Link
Frame et al., 2024, “Rapid inundation mapping with machine learning”. Computational Modeling for Water Resources. October 2024. University of Arizona.
Frame et al., 2023, “On the spontaneous synchronization of hydrologic processes and hydrologic modeling”. AGU Fall Meeting. Link
Frame et al., 2023, “On strictly enforced mass conservation constraints for modeling the rainfall-runoff process”. AGU Fall Meeting. Link
Frame et al., 2023, ML-based, hydrologically-informed, large-scale, flood inundation mapping for near real time flood response: case study from the California 2023 flood season. HydroML Symposium.
Frame et al., 2022, “Deep learning sub-seasonal predictions of flooded area in South Sudan”. AGU Fall Meeting
Frame et al., 2022, “Flood maps across CONUS using the U.S. National Water Model, satellite observations and convolutional neural networks”. AGU Fall Meeting. Link
Frame et al., 2022, “Intelligent flood maps: combining satellite observations with hydrologic modeling for high temporal resolution flood maps”, Frontiers in Hydrology. Link
Frame et al., 2021, “Deep learning for the Next Generation U.S. National Water Model” American Geophysical Union, Fall meeting. Link
Frame et al., 2021, “Data-driven streamflow simulations of extreme (high flow) events”. The 3rd NOAA workshop on Leveraging AI in Environmental Sciences. Link
Frame et al., 2020, “Post processing the U.S. National Water Model with long short-term memory networks”. American Geophysical Union, Fall meeting. Link
Frame 2020, “Improving US Gulf Region Streamflow Predictions from the US National Water Model with Machine Learning”, AAPG GeoGulf.
Frame, Pellisier, and Nearing, 2019, “Toward Global Terrestrial Hydrology with Theory Guided Machine Learning”. American Geophysical Union, Fall meeting.
Frame, Guzman and Watson, 2009, “Watershed Simulation Model with Application to the Carmel Watershed in California”. Western Society of Naturalists Annual Meeting.
Snow Hydrology. NASA snow water equivalent data analysis for deep learning-based water resources forecasting. Rockie Mountains, USA
Groundwater supply analysis. Local groundwater model for analyzing sustainable yield and potential for expanded use of aquifer for housing development projects. Santa Barbara, CA.
Storm Surge Flooding. Large scale storm surge simulations for compound flood inundation mapping. Coastal Cities, USA
Flood prediction. Deep learning modeling, statistics and probability of flood risks/impacts at multiple scales. South Sudan
Flood damage predictions. Near-real time and early warning flood damage prediction system for Silicon Valley Innovation Program (SVIP) in partnership with the Federal Emergency Management Agency (FEMA) and Federal Insurance and Mitigation Administration (FIMA).
Deep learning and data assimilation for land surface modeling. Noah land surface hydrology model augmented with a Gaussian process for improving model simulations of soil moisture.
Coastal flooding prevention infrastructure. Hydrology and hydraulics analysis and design of flood protection infrastructure for Bayfront Canal, Redwood City, California.
Sediment transport system design. Surface water conveyance design to improve sediment transport efficiency for the Santa Clara River, Ventura County, California.
Watershed water yield analysis. Analysis of flooding, surface water-groundwater interactions, and water resources management for Griffith Park, Los Angeles, California.
Stream restoration and stabilization. Design of bank stabilization, water retention, and fish passage facilities for Mission Creek, Santa Barbara, California.
Sewer risk mitigation. Flood frequency analysis and treatments to protect sewer facilities and resources at Upper Truckee Marsh, South Lake Tahoe, California.
Snowpack precipitation forecasting. Support vector machine model for forecasting precipitation using atmospheric variables and seasonal climatology in the Eastern Sierra Mountains, California.
Coastal flooding joint probability analysis. Joint probability analysis of tidal surge, wave height, meteorological, and oceanographic variables in the Strait of Georgia, Canada.
Flood and reservoir dynamics modeling. Maximum probable flood estimation and reservoir temperature dynamics modeling for South Fork Tolt Reservoir, Washington.
FEMA flood mapping. Hydrology, hydraulics, and base flood elevation calculations for a FEMA Letter of Map Revision in Puyallup, Washington.
Channel stabilization design. Hydrologic analysis, flood estimates, and hydraulics modeling for Kaloi Channel, Honolulu, Hawaii.
Urban river restoration. Geospatial analysis, GIS mapping, risk assessments, and community engagement for urban river restoration programs.
Environmental modeling framework development. Contributed to the Tarsier environmental modeling framework’s development and application.
Elk habitat hydrology analysis. Hydrologic and geographic characterization of Gibbon, Firehole, and Madison Rivers in Yellowstone National Park, Wyoming.
DERWA Recycled Water Treatment Plant Expansion. Modeled hydraulic transients in a multi-material pressure zone network with surge protection recommendations. Dublin/San Ramon, CA.
Coloma Pump Station. Developed surge control strategies for a 4.5 MGD wastewater force main, including controlled venting and pressurized surge tank alternatives. Sausalito-Marin City, CA.
Rim Rock Pump Station. Simulated transients for a pump station network of asbestos cement, PVC, and ductile iron pipes. Laguna Beach, CA.
EL 47.5 Irrigation Delivery System. Modeled transients in a 9-mile, 54-inch steel and PVC irrigation pipeline system, recommending surge tanks and staged valve closures. Warden, WA.
Tesoro Viejo Water and Wastewater Treatment. Developed surge control strategies for an upgraded agricultural pump station and transmission pipeline. Fresno, CA.
Pinole/Hercules WPCP Upgrades. Modeled transients for a 14.2 MGD effluent pump station and 4-mile outfall pipeline, recommending surge tanks and controlled venting valves. Pinole, CA.
Hinds Pumping Plant. Analyzed transient conditions in a 1800 cfs aqueduct pump station with complex discharge and suction configurations. Colorado River Aqueduct, CA.
SEPA Sewer Pump Station. Modeled transient impacts for a dual-force main system conveying wastewater to an interceptor. Sacramento, CA.
Ridgewood View Reservoir Pump Station. Simulated transient conditions in an 11 MGD pump station and recommended surge tank placement. Beaverton, OR.
La Granada Pump Station. Performed surge analyses for potable water distribution, recommending surge tanks and check valve buffering. Thousand Oaks, CA.
Long Beach Lateral Service Connections. Assisted in pressure surge analysis of 12- to 84-inch steel and concrete pipelines. Long Beach, CA.
Twin Oaks Valley WTP Expansion. Compiled data and developed a surge model for 22,000 ft of large-diameter pipelines. San Diego, CA.
Jim Miller Pump Station. Modeled hydraulic transients for an 18-mile, 84/90-inch PCCP transmission main and developed surge control strategies. Dallas, TX.
Westlake Filtration Plant Pump Station. Simulated transients in a 36-inch steel suction pipeline and proposed a surge protection system. Calabasas, CA.
East High Pressure & Pleasant Grove Intermediate Zones. Simulated transient behavior in a 24- and 45-square-mile potable water network. Dallas, TX.
Camp Pendleton Potable Water Conveyance. Modeled transient impacts and recommended surge control measures for a 14-inch, 2.8-mile HDPE pipeline. Camp Pendleton, CA.
Elm Fork Pump Station. Performed transient analyses for a 100 MGD and 180 MGD pump station network. Dallas, TX.