groundwater
There are 18 repositories under groundwater topic.
softwareunderground / awesome-open-geoscience
Curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome
- pastas
pastas / pastas
Pastas is an open-source Python framework for the analysis of groundwater time series.
Language:Python 365 kinverarity1 / lasio
Python library for reading and writing well data using Log ASCII Standard (LAS) files
Language:Lasso 344- Language:Fortran 255
martinvonk / SPEI
A simple Python package to calculate and visualize some popular drought indices such as the SPI, SPEI and SGI.
Language:Python 72- Language:Jupyter Notebook 58
ArtesiaWater / hydropandas
Module for loading observation data into custom DataFrames
Language:Python 56- HydroSight
peterson-tim-j / HydroSight
Groundwater timeseries analysis of hydrographs
Language:MATLAB 44 gwmod / nlmod
Python package to build, run and visualize MODFLOW 6 groundwater models in the Netherlands.
Language:Python 35- pygsflowLanguage:Python 33
earthai-tech / pycsamt
A package for audio-frequency magnetotellurics
Language:Python 26utah-geological-survey / WellApplication
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;
Language:Python 24- skbel
robinthibaut / skbel
SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn.
Language:Python 22 - HydroMST
montimaj / HydroMST
Source codes for groundwater pumping prediction using integrated remote sensing datasets and machine learning
Language:Python 21 - Language:Python 21
- Language:Python 21
DOI-USGS / HASP
Hydrologic AnalySis Package. See official source code: https://doi-usgs.github.io/HASP/
Language:R 16:spaghetti: :convenience_store: Tools for managing timeseries and Pastas models
Language:Python 16Mapping of groundwater level for realistic flow flowpaths using semi-automated kriging.
Language:R 15khaors / pumpingtest
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.
Language:R 13ropensci-archive / dbhydroR
R interface to the South Florida Water Management District's DBHYDRO Database :sweat_drops: :palm_tree:
Language:R 12- python-flopy-parser
bdestombe / python-flopy-parser
Convert MODFLOW input files to Python
Language:BASIC 11 inkenbrandt / Peeters_Piper
From Peeters 2014 in Groundwater; ArcGIS Python Toolbox; Piper Diagram; Water Chemistry
Language:Python 10lhalloran / COMPEST
An interface connecting COMSOL Multiphysics and PEST to solve inverse modelling problems using forward finite element models (paper here: http://doi.org/10.1016/j.cageo.2019.02.001)
Language:Java 10Groundwater pumping estimation in Arizona using remote sensing datasets and machine learning
Language:Python 10rniswon / gsflow_v2
Integrated surface water and groundwater model for simulating hydrology in watersheds
Language:Fortran 10jobar8 / subsurface_hackathon_2017
Three notebooks to jump start a data science project
Language:Jupyter Notebook 9- Language:Julia 9
ThoReimann / HydroTeaching
Material for teaching hydro-related subjects
Language:Jupyter Notebook 9A tool for conversion between Δg and groundwater storage changes. https://doi.org/10.1016/j.envsoft.2022.105340
Language:Python 8- Language:R 7
- Language:C++ 7
dhanush-2501 / hydro-analyzer
Hydro Analyser is is a first ever open source tool designed for hydrogeologists, engineers, and other professionals in the water resources industry to accurately analyze and optimize groundwater pumping tests
Language:Python 6- Language:R 6
:mortar_board: Repository to hold public articles or presentations on Pastas.
rhkarls / sondera
sondera is a python package providing clients for accessing Swedish hydrology and meteorology related open data. Data sources currently include SMHI open data API and SGU groundwater API.
Language:Python 4
