Fill Missing Precipitation Data with Artificial Intelligence (Python Keras) - Tutorial
Evaluation of hydrological processes as evapotranspiration, runoff, routing and infiltration require data as precipitation, flow, temperature and radiation on a daily basis. Required data for the hydrological modeling need to be accurate and must be completed over the period of study. Many times historical data from hydrological stations are incomplete and present many gaps that can be filled by the use of Artificial Intelligence tools as the Keras library in Python.
This tutorial show the procedure to run a complete script for the filling of missing precipitation in one station by the use of data from 2 nearby stations. The Python script is done on a Jupyter Notebook.
Input Data
You can download the input data here:
https://www.hatarilabs.com/ih-en/fill...
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