Curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome

Pastas is an open-source Python framework for the analysis of groundwater time series.

Python library for reading and writing well data using Log ASCII Standard (LAS) files

USGS Modular Hydrologic Model

A simple Python package to calculate and visualize some popular drought indices such as the SPI, SPEI and SGI.

Groundwater Time Series Modeling Challenge

Module for loading observation data into custom DataFrames

Groundwater timeseries analysis of hydrographs

Python package to build, run and visualize MODFLOW 6 groundwater models in the Netherlands.

Python package to Create, Read, Write, Edit, and Visualize GSFLOW models

A package for audio-frequency magnetotellurics

Tools used to manipulate hydrograph data; Solinst xles to pandas dataframe; hydrograph analysis; hydrology; Gannt Charts; Piper diagrams; hydrogeology; wells; groundwater; USGS data; WQP data;

SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn.

Source codes for groundwater pumping prediction using integrated remote sensing datasets and machine learning

12 baseflow separation methods with automatic parameter calibration

Multivariate timeseries analysis using dynamic factor modelling.

Hydrologic AnalySis Package. See official source code: https://doi-usgs.github.io/HASP/

🍝 🏪 Tools for managing timeseries and Pastas models

Mapping of groundwater level for realistic flow flowpaths using semi-automated kriging.

pumpingtest is a R package designed for the analysis and evaluation of aquifer tests in wells. The package includes the most common analytical solutions used to describe groundwater flow in different types of aquifers around wells.