TETIS Runtime Predictor

This repository hosts the validated Machine Learning (ML) predictive tool developed to estimate the computational performance (runtime) of the TETIS v9.1 hydrological model.

The package contains the trained Random Forest (RF) regression models and the associated Python scripts required for execution. This tool enables researchers and end-users to predict the execution time of two critical processes:

1. Topolco.sds generation (Parallel process)

2. Hydrological Simulation execution (Serial process)

This resource is vital for planning large ensemble experiments, optimizing resource allocation, and improving the operational reliability of TETIS software.

Cite the associated article when using this predictive tool:

[UNDER REVIEW]

DOI: [UNDER REVIEW]