groundwater

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

MODFLOW 6 Repository

Groundwater Time Series Modeling Challenge

Groundwater timeseries analysis of hydrographs

Module for loading observation data into custom DataFrames

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

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

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

Python code to process, build and visualize MODFLOW models in the Netherlands. Model data is stored in a xarray Datasets and geopandas GeoDataFrames.

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;

A package for audio-frequency magnetotellurics

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

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

Multivariate timeseries analysis using dynamic factor modelling.

🍝 🏪 Tools for managing timeseries and Pastas models

R interface to the South Florida Water Management District's DBHYDRO Database 💦 🌴

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.