Date

For Who

Topic

Presenter/Study TeamLink to Publication
August 2025Journal of HydrologyEvaluation of pre-fire, post-fire, and recovery conditions within a wildfire-prone southern California watershed

Avery Walters, Nawa Raj Pradhan, Ian Floyd, Venkataraman Lakshmi

https://doi.org/10.1016/j.ejrh.2025.102521

April 2025Journal of HydrologySnow Model Complexity Evaluation for Real-time Streamflow Forecasting

Wyatt Reiss, Jeremy Giovando, Mike Bartles , Travis Dahl, Avital Breverman 

November 2024Hydrologic ProcessesWildfire Impacts for Temperature Index Snowpack Model ParametersJeremy Giovando, PhD, PE

September 2024Journal of Hydrologic EngineeringBalancing Complexity, Parsimony, and Applicability in Hydrologic Modeling: A Comparative Evaluation of Four Infiltration Models across Parameterization ScenariosSara Rassa; Gerhard Schoener, Ph.D., A.M.ASCE; and Matthew Fleming, P.E.

July 2025Project Report

This study evaluates the performance of a leading deep learning model—Long Short-Term Memory (LSTM)—for rainfall–runoff modeling, comparing it with the U.S. Army Corps of Engineers' (USACE) process-based Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) model. Conducted in California’s Russian River watershed, the study developed and tested five model configurations: HEC-HMS, standalone LSTM, physics-informed LSTM (PILSTM), multi-timescale LSTM (MTS-LSTM), and physics-informed multi-timescale LSTM (MTS-PILSTM), using the open-source NeuralHydrology library recently updated by Google Research.

Bellugi, D. G., Khatri, K. B., Ruso, S.C., Sokolovskaya, N. L., Robert, E., Blaylock, M. C., Larsen, L. G., and Fleming, M. J.

July 2024Project ReportApplication of Machine Learning algorithms to predict snow accumulations and melt and reservoir inflow. Machine learning model results were compared to results from an HEC-HMS model.Dino Bellugi, Evan Roberts, Sumana Srivas, and Laurel Larsen from U.C. Berkeley, Chris Tennant from the Army Geospatial Center, and Matt Fleming and Natasha Sokolovskaya from HEC

November 2022ERDC Technical ReportDemonstrate a workflow that utilizes the existing Jython application programming interface (API) to batch run HEC-HMS simulations with Python. The workflow allows for gridded SMA HEC-HMS model sensitivity and calibration analyses to be conducted in a timely manner.Sean A. Matus and Daniel R. Gambill https://erdc-library.erdc.dren.mil/items/aad7c8f1-70bb-4fd5-981e-ee201a693b99
May 2015Journal of Hydrologic EngineeringModeling Surface Soil Erosion and Sediment Transport Processes in the Upper North Bosque River Watershed, TexasJang Hyuk Pak, Matthew Fleming, William Scharffenberg, Stanford Gibson, and Thomas Brauerhttps://ascelibrary.org/doi/10.1061/%28ASCE%29HE.1943-5584.0001205