Research data supporting the manuscript “A machine learning framework for reliable prediction of open channel flow depth and velocity for hydraulic engineering applications”
Abstract
This dataset contains the input and output variables, processed data, and model-ready datasets used to develop and validate machine learning models for reliable prediction of open channel flow depth and velocity in hydraulic engineering applications. The data supports the manuscript entitled “A machine learning framework for reliable prediction of open channel flow depth and velocity for hydraulic engineering applications” submitted to Catena. All files are organized and described in the accompanying Machine learning optimized data and results file.
Fields of Study & Subjects
Hydraulic flow and structures
Hydrological Forecasting Using AI
Hydrology and Sediment Transport Processes
Publication details
- Journal / source
- Mendeley Data
- Publication date
- 19 January 2026
- Document type
- Dataset