/KWR_Aa_project

Python scripts to develop a deep learning model to forecast the groundwater table height and the river level in the Drenthe province, The Netherlands

Primary LanguageJupyter NotebookOtherNOASSERTION

Project @ KWR, 2021: Deep learning model for hydrological values prediction

Still in progress

Author: Paolo Colombo, Supervisor: Xin Tian

Python scripts to develop a deep learning model to forecast hydrological variables in the Drenthe province, The Netherlands.

The model will be used to predict, for 2 weeks ahead:

  • Water table depth in Aa river's region
  • Aa river's discharge

The main code is organized in Main folder as written below:

  • main_GW_dp.py: data pre-processing procedures to clean the groundwater (GW) data and obtain 20 stations with a good amount of data where to predict the water table depth. Then, SSA time series decomposition to obtain the important components of the time series
  • main_R_dp.py: data pre-processing procedures applied to the river (R) data. Then, SSA time series decomposition to obtain the important components of the time series.
  • main_model.py: model construction

Also, other folders are present:

  • Supporting_scripts: experiments doen that were crucial in defining information and data used in the main scripts
  • non_organized_and_old_scripts: various drafts and experiments done throughout the project progresses, kept just in case
  • Code_examples: other codes/projects that have been useful in the study phase

All the sources of pieces of code not written directly by me are cited in the scripts.