Rao S. Govindaraju
Environmental Science · Purdue University West Lafayette
Publications
318
Citations
8,585
Est. group size
~3
Recurring co-author estimate
Active years
42
Publishing since 1985
Rao S. Govindaraju's research focuses on hydrology, the study of water movement through watersheds, groundwater, and soil systems. Recent work applies machine learning and deep learning (including transformer-based models) to forecast hydrological and climate extremes, model harmful algal blooms in lakes, and evaluate hydrological models at sites with and without direct streamflow measurements. The work spans data-driven forecasting, environmental water quality, and methodological tools for testing model performance.
Publication output has fluctuated over the past decade with a notable peak in 2024, but overall activity has remained fairly steady with periodic surges rather than a clear long-term increase or decline.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Laboratory Study on Fate and Transport of Water-Borne eDNA: A Tale of Tempered Tails and Parafluvial Processes
Environmental Science & Technology · 2026
- EXtreFormer: a general deep learning framework for forecasting compound extreme events: experience with dry-hot extremes and vegetation response
Journal of Hydrology · 2026
- Evaluation of Sobol' Sensitivity Indices Conditioned on Model Performance
SSRN Electronic Journal · 2026
- Characterization and Modeling of Harmful Algal Blooms: A Review
Journal of Hydraulic Engineering · 2025
- Effect of Data Gaps on Harmful Algal Bloom Prediction Models for Inland Lakes
Journal of Hydrologic Engineering · 2025
- Enhancing Hydro-climatic and land parameter forecasting using Transformer networks
Journal of Hydrology · 2025
- Analyzing Compound Extremes in Hydrology: A Multivariate Approach Using Correlated Time Series
2025
- Corrigendum to “Enhancing Hydro-climatic and land parameter forecasting using Transformer networks” [J. Hydrol. 655 (2025) 132906]
Journal of Hydrology · 2025
- A framework for multivariate analysis of compound extremes based on correlated hydrologic time series
Journal of Hydrology · 2024
- Evaluation of hydrological models at gauged and ungauged basins using machine learning-based limits-of-acceptability and hydrological signatures
Journal of Hydrology · 2024
- Evaluating a conceptual hydrological model at gauged and ungauged basins using machine learning-based limits-of-acceptability and hydrological signatures
2024
- Evaluating a conceptual hydrological model at gauged and ungauged basins using machine learning-based limits-of-acceptability and hydrological signatures - 4
Zenodo (CERN European Organization for Nuclear Research) · 2024
- Evaluating a conceptual hydrological model at gauged and ungauged basins using machine learning-based limits-of-acceptability and hydrological signatures - 7
Zenodo (CERN European Organization for Nuclear Research) · 2024
- Evaluating a conceptual hydrological model at gauged and ungauged basins using machine learning-based limits-of-acceptability and hydrological signatures - 2
Zenodo (CERN European Organization for Nuclear Research) · 2024
- Evaluating a conceptual hydrological model at gauged and ungauged basins using machine learning-based limits-of-acceptability and hydrological signatures - 5
Zenodo (CERN European Organization for Nuclear Research) · 2024
- Zenodo (CERN European Organization for Nuclear Research)×20
- Journal of Hydrology×13
- Journal of Hydrologic Engineering×8
- Water×4
- Elsevier eBooks×4
- B. B. Wilson
Environmental Science · Purdue University West Lafayette
- Susmita Ghosh
Environmental Science · Purdue University West Lafayette
- Manal H. Askar
Environmental Science · The Ohio State University
- Marty D. Frisbee
Environmental Science · Purdue University West Lafayette
- K. P. Sudheer
Environmental Science · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile