WATex: A machine learning library in hydro-geophysics

WATex is a Python package for reducing numerous losses during hydro-geophysical exploration projects. Its mission is to bring a piece of solution in a wide program of WATER4ALL such as participating in Sustanaible Development Goa… and Africa Agenda 2063 N1 achievements. It's mainly focused on the field of groundwater exploration. It encompasses the DC-resistivity ( Electrical profiling (ERP) & vertical electrical sounding (VES)), short periods EM, geology, and hydrogeology methods combined with the machine learning approaches to:

• right locate the drilling operations,
• reduce the cost of permeability coefficient (k) data collection during the hydro-geophysical engineering projects,
• predict the water content in the well such as the groundwater flow rate, and the level of water inrush, ...
• etc.

It contributes to minimizing the numerous unsuccessful drillings, and unsustainable boreholes thereby saving money for funders, state governments, and geophysical and drilling ventures.

Visit the package website for more resources watex.readthedocs.io. You can also quickly browse the software API reference (watex.readthedocs.io) and flip through the examples page (watex.readthedocs.io) to see some of the expected results. Furthermore, the step-by-step guide (watex.readthedocs.io) is elaborated for real-world engineering problems such as computing DC parameters and predicting the k-parameter. A tangible example using watex can be found in the published case history paper (agupubs.onlinelibrary.wiley…).