• https://github.com/unpingco/Python-for-Signal-Processing - Notebooks for "Python for Signal Processing" book
• https://github.com/jnsebgosselin/gwhat - Ground-Water Hydrograph Analysis Toolbox
• https://github.com/AileenNielsen/TimeSeriesAnalysisWithPython -
• https://github.com/ResidentMario/missingno - Missing data visualization module for Python.
• https://github.com/jrmontag/STLDecompose - A Python implementation of Seasonal and Trend decomposition using Loess (STL) for time series data.
• https://github.com/lucashn/peakutils - utilities related to the detection of peaks on 1D data
• https://github.com/waterhackweek/tsdata_access - Data access and time-series statistics
• https://github.com/amacd31/phildb - Timeseries database
• https://github.com/TDAmeritrade/stumpy - computing a Matrix Profile, which can be used for a variety of time series data mining tasks
• https://github.com/johannfaouzi/pyts - A Python package for time series classification
• https://github.com/peterson-tim-j/HydroSight - A flexible statistical toolbox for deriving quantitative insights from groundwater data. (MATLAB)
• https://github.com/christurnadge/HydroSight - Python language version of the HydroSight Matlab toolbox
• https://github.com/arundo/adtk - Python toolkit for rule-based/unsupervised anomaly detection in time series
• https://github.com/blue-yonder/tsfresh - Automatic extraction of relevant features from time series
• https://github.com/deepcharles/ruptures - ruptures: change point detection in Python
• https://github.com/hildensia/bayesian_changepoint_detection - Methods to get the probability of a changepoint in a time series.
• https://github.com/nicodjimenez/lstm - Minimal, clean example of lstm neural network training in python, for learning purposes.
• https://github.com/kratzert/pangeo_lstm_example - Example notebook, showing how to use LSTMs for rainfall-runoff modeling
• https://github.com/quantumblacklabs/causalnex - helps data scientists to infer causation rather than observing correlation.
• https://github.com/mmhs013/pyMannKendall - A python package for non parametric Mann Kendall family of trend tests.
• https://github.com/pints-team/pints - Probabilistic Inference on Noisy Time Series
• https://github.com/fraunhoferportugal/tsfel - An intuitive library to extract features from time series
• https://github.com/hydrogeoscience/HydroGeoSines - Signal In the Noise Exploration Software for hydrogeological datasets
• https://github.com/HydroGeoSines/HydroGeoSines - Signal In the Noise Exploration Software for hydrogeological datasets
• https://github.com/bashtage/linearmodels - Add linear models including instrumental variable and panel data models that are missing from statsmodels.

• https://github.com/facebook/prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality
• https://github.com/pastas/pastas - open-source Python framework for the analysis of hydrological time series
• https://github.com/jxx123/fireTS - A python multi-variate time series prediction library working with sklearn
• https://github.com/aria-tools/ARIA-tools-docs - ARIA-tools and examples
• https://github.com/usbr/PyForecast - statistical modeling tool to predict seasonal inflows and streamflows.
• https://github.com/paulozip/arauto - An open-source tool for quick Time Series Analysis and Forecasting
• https://github.com/alkaline-ml/pmdarima - A statistical library designed to fill the void in Python's time series analysis capabilities
• https://github.com/facebookresearch/Kats - Kats, a kit to analyze time series data

• https://github.com/hydrogeog/hydro - Tools for quantitative analysis of the hydrologic system
• https://github.com/stijnvanhoey/hydropy - Analysis of hydrological oriented time series.
• https://github.com/jsignell/RatingCurve - Simple and fast watershed delineation in python.
• https://github.com/VForWaTer/hydrobox - hydrological preprocessing and analysis toolbox build upon pandas and numpy
• https://github.com/raoulcollenteur/Python-Hydrology-Tools - ist of open source Python packages interesting to Hydrologists
• https://github.com/waterhackweek/projects - links to waterhackweek project repositories
• https://github.com/stijnvanhoey/pybreach - Identification of temporal consistency in rating curve data: Bidirectional Reach
• https://github.com/spence97/Low_Flows - National Water Center Summer Institute project focused on low flow forecasting.
• https://github.com/reproducible-notebooks/national-water-model - process a year of hourly data on 2.7 million rivers in 1 minute
• https://github.com/USEPA/StreamCat - StreamCat Dataset summaries of natural and anthropogenic landscape features
• https://github.com/jsadler2/river-dl - Deep learning model for predicting environmental variables on river systems
• https://github.com/ThibHlln/hydroeval - An efficient evaluator for streamflow time series in Python
• https://github.com/gauchm/streamflow-ml - Machine Learning for Streamflow Prediction
• https://github.com/hidrokit/hidrokit - analisis hidrologi menggunakan python
• https://github.com/ThibHlln/eflowcalc - An Efficient Calculator of Ecological Streamflow Characteristics in Python
• https://github.com/USGS-R/HASP - Hydrologic AnalySis Package
• https://github.com/ArtesiaWater/hydropandas - Module for loading observation data into custom DataFrames
• https://github.com/ArtesiaWater/waterbalans - calculating water balances as developed by Maarten Ouboter
• https://github.com/waterhackweek/waterdata - Tuesday tutorials: data access, time series and spatial data analyses
• https://pygeoprocessing.readthedocs.io/en/latest/index.html - Flow routing

• https://github.com/aaren/wavelets - Python implementation of the wavelet analysis found in Torrence and Compo (1998)
• https://github.com/krischer/mtspec - Python library for multitaper spectral estimations
• https://github.com/pierre-rouanet/dtw - DTW (Dynamic Time Warping) python module
• https://github.com/duducosmos/PIWavelet - Python Interface for Wavelet Analises
• https://github.com/pckujawa/harmonic_analysis_of_time_series - Harmonic analysis of time series in python
• https://github.com/alsauve/scaleogram - Scaleogram plot for Continuous Wavelet Transform made easy
• https://github.com/gespinoza/hants - Harmonic ANalysis of Time Series (HANTS) applied to geographic data
• https://github.com/scikit-signal/tftb - time-frequency analysis
• https://github.com/christurnadge/05_Cardiff_and_Barrash_2015_solutions - calculate the sensitivity of the amplitude and phase of oscillatory signals to hydraulic parameters
• https://github.com/OverLordGoldDragon/ssqueezepy - Synchrosqueezing Toolbox ported to Python
• https://github.com/kymatio/kymatio - Wavelet scattering transforms in Python with GPU acceleration

• https://github.com/pwcazenave/tappy - Tidal Analysis Program in PYthon (TAPPY) uses the least squares optimization function from scipy to perform a harmonic analysis
• https://github.com/wesleybowman/UTide - Python re-implementation of the Matlab package UTide.
• https://github.com/hydrogeoscience/pygtide - A Python module and wrapper for ETERNA PREDICT to compute gravitational tides on Earth
• https://github.com/treverhines/PyGeoNS - Python-based Geodetic Network Strain software
• https://github.com/jrleeman/LongmanTide - Gravitational tide computation based on Longman 1959

• https://github.com/NumericalEnvironmental/Pumping_Test_Interpretation_with_Python - interpretation of aquifer pumping tests
• https://github.com/GeoStat-Framework/AnaFlow - analytical solutions for the groundwater flow equation
• https://github.com/GeoStat-Framework/welltestpy - package for handling well based field campaigns.

• https://github.com/NASA-DEVELOP/METRIC - For estimating daily evapotranspiration from Landsat data
• https://github.com/adamhsparks/EddyCleanR - Fills gaps and removes outliers in eddy covariance data.
• https://github.com/bgctw/REddyProc - Processing data from micrometeorological Eddy-Covariance systems
• https://github.com/usda-ars-ussl/fluxpart - Python module for partitioning eddy covariance flux measurements.
• https://github.com/June-Spaceboots/EddyCovarianceProcessing - A collection of code used to processess Eddy Covaraince Data
• https://github.com/sunxm19/Planetary_boundary_height_for_FFP - extracting boundary height within North America from NOAA regional data
• https://github.com/UofM-CEOS/flux_capacitor - https://github.com/UofM-CEOS/flux_capacitor
• https://github.com/wsular/EasyFlux-DL-CR3000 - CR3000 datalogger program for Campbell open-path eddy-covariance systems
• https://github.com/woodcrafty/PyETo - Python package for calculating reference/potential evapotranspiration (ETo).
• https://github.com/cgmorton/RefET-GEE - ASCE Standardized Reference Evapotranspiration Functions for Google Earth Engine (GEE)
• https://github.com/usbr/et-demands - Dual crop coefficient crop water demand model
• https://github.com/kratzert/pyTSEB - two Source Energy Balance model for estimation of evapotranspiration with remote sensing data
• https://github.com/spizwhiz/openet-ssebop-beta - Earth Engine SSEBop ET Model
• https://github.com/pblankenau2/openet-core-beta - OpenET Core Components
• https://github.com/jnelson18/ecosystem-transpiration - Code and examples of how to estimate transpiration from eddy covariance data.
• https://github.com/bgctw/REddyProc - Processing data from micrometeorological Eddy-Covariance systems
• https://github.com/Open-ET/flux-data-qaqc - Energy Balance Closure Analysis and Eddy Flux Data Post-Processing
• https://github.com/tomchor/pymicra - A Python tool for Micrometeorological Analysis

• https://github.com/ulmo-dev/ulmo - clean, simple and fast access to public hydrology and climatology data.
• https://github.com/aleaf/pydrograph - Get and process stream flows and groundwater levels from NWIS.
• https://github.com/NWQMC/WQP-WQX-Services - The core data services for Water Quality Portal
• https://github.com/mroberge/hydrofunctions - A suite of convenience functions for working with hydrology data in an interactive Python session.
• https://github.com/ODM2/WOFpy - A server-side implementation of CUAHSI's Water One Flow service stack in Python.
• https://github.com/mesowx/MesoPy - A Python wrapper for the MesoWest environmental data API
• https://github.com/hydroshare/hydroshare - HydroShare is a collaborative website for better access to data and models in the hydrologic sciences.
• https://github.com/tethysplatform/tethys - The Tethys Platform main Django website project repository.
• https://github.com/heigeo/climata - Python library for loading and iterating over climate and flow time series data
• https://github.com/NWQMC/pywqp - client for downloading datasets from the USGS/EPA Water Quality Portal
• https://github.com/kapadia/usgs - Client library for interfacing with USGS datasets
• https://github.com/Unidata/MetPy - reading, visualizing and performing calculations with weather data.
• https://github.com/gunnarleffler/getSnotel - This program gets snotel data and metadata from the NRCS webservice
• https://github.com/ACWI-SOGW/well_registry_management - Application for management of groundwater monitoring locations.
• https://github.com/USGS-python/dataretrieval - Tools for downloading hydrologic and climate data.
• https://github.com/catalyst-cooperative/pudl - The Public Utility Data Liberation Project
• https://github.com/cheginit/pynhd - A part of Hydrodata software stack that provides access to NHD+ V2 data through NLDI and Waterdata web services

• https://github.com/mattjenkins3/SinglePlant_Irrigation_DataTool - CR3000 datalogger program for Campbell open-path eddy-covariance systems
• https://github.com/kitplummer/PyPak - Communication with Campbell Scientific Dataloggers
• https://github.com/frankohanlon/DataPro - Simple Automated Data Processing / QA-QC engine for Campbell Scientific data loggers
• https://github.com/koffertfisk/campbellsciparser - Utility for parsing and exporting data collected by Campbell Scientific's CR-type dataloggers.
• https://github.com/jsignell/campbellsci-tools - Tools for reading ascii files using the campbellsci TOA5 long header
• https://github.com/nationalparkservice/hobo-py - reading Onset HOBO data logger data

Look in the time-series modeling section for time-series specific models

• https://github.com/UMN-Hydro/GSFLOW_pre-processor - GSFLOW pre-processing scripts, for Andes project
• https://github.com/gsflow/gsflow-arcpy - GSFlow ArcPy Tools
• https://github.com/pygsflow/pygsflow - Python package to Create, Read, Write, Edit, and Visualize GSFLOW models
• https://github.com/UMN-Hydro/GSFLOW-GRASS - Generates inputs for and runs the coupled groundwater-surface water model "GSFLOW"
• https://github.com/usgs/gw-general-models
• https://github.com/VUB-HYDR/QSWAT_Automated_Workflow = automated workflow for setting up SWAT Models presented in Chawanda et al., 2019 EMS
• https://github.com/simpeg/discretize - Discretization tools for finite volume and inverse problems.
• https://github.com/nschloe/meshio - input/output for many mesh formats
• https://github.com/apryet/Qgridder - Qgis python plugin for building 2D grids for finite difference numerical modeling
• https://github.com/GeospatialPython/voronoi-py3 - Voronoi module ported to Python 3
• https://github.com/driftingtides/hyvr - A package for simulating hydrogeological virtual realities.
• https://github.com/djdahlstrom/modeling-tools - Tools and utilities to facilitate groundwater flow and contaminant transport modeling.
• https://github.com/Ouranosinc/raven - Hydrological modeling and calibration WPS services
• https://github.com/usgs/linesink-maker - Rapidly build GFLOW models from GIS hydrography data
• https://github.com/usgs/sfrmaker - Rapid construction of MODFLOW SFR Package input from hydrography data.

See Optimization for PEST-related packages

• https://github.com/modflowpy/flopy A Python package to create, run, and post-process MODFLOW-based models.
• https://github.com/MODFLOW-USGS/executables - MODFLOW and related program executables for Windows, Mac, and Linux
• https://github.com/modflowpy/pymake - Python package for compiling MODFLOW-based applications
• https://github.com/jlarsen-usgs/HydrographTools - A small set of tools for creating hydrographs from MODFLOW--HOBS and HYDMOD outputs
• https://github.com/mwtoews/surface-water-network - Creates surface water network, which can be used to create MODFLOW's SFR.
• https://github.com/MODFLOW-USGS/modflow6 - MODFLOW 6 Repository
• https://github.com/Deltares/xmipy - BMI python wrapper for MODFLOW 6 (and some more)
• https://github.com/jlarsen-usgs/mf2web - A collection of tools to export MODFLOW models for web display using netcdf
• https://github.com/MODFLOW-USGS/modflow6-examples - Collection of MODFLOW 6 example models
• https://github.com/langevin-usgs/mf6flopy2019_classrepo - Class repository for the MODFLOW 6 / Flopy workshop held in Delft
• https://github.com/jdhughes-usgs/MM2019_FloPy - MODFLOW and More 2019 FloPy Short Course Repository
• https://github.com/rniswon/mfnwt - MODFLOW-NWT - Version: 1.1.0 Newton Formulation for MODFLOW-2005

• https://github.com/Applied-Groundwater-Modeling-2nd-Ed - GW modeling teaching/supporting material provided by the community
• https://github.com/NMTHydro/Recharge - Python code to model recharge and ET
• https://github.com/usgs/gw-res-time - Groundwater Residence Time Distributions
• https://github.com/peckhams/topoflow - Spatial hydrologic model (D8-based, fully BMI-compliant)
• https://github.com/mbakker7/timml - An analytic element model for steady multi-layer flow
• https://github.com/Hugovdberg/QgsTIM - QGIS frontend for TimML library
• https://github.com/drainagequickscan/drainagequickscan - Using TimML for geohydrological modelling of dike cross-sections
• https://github.com/mbakker7/maqtides - Mulit-layer analytic solutions for tidal propagation in coastal aquifers
• https://github.com/smwesten-usgs/swb2_examples - This repository contains three working examples for use with the SWB version 2.0 code.
• https://github.com/WilcoTerink/SPHY - Spatial Processes in HYdrology (SPHY) model
• https://github.com/DHI-GRAS/qgis-processing-swat - QGIS Processing provider for SWAT based hydrological modelling.
• https://github.com/Project-Platypus/Rhodium - Python Library for Robust Decision Making and Exploratory Modelling
• https://github.com/PRMS-Python/PRMS-Python - A Python package for the PRMS hydrologic model
• https://github.com/stijnvanhoey/pyfuse - creating and running lumped hydrological models
• https://github.com/sahg/PyTOPKAPI - TOPKAPI Hydrological model
• https://github.com/pysal/mgwr - Multiscale Geographically Weighted Regression (MGWR)
• https://github.com/umn-earth-surface/bucket-hydrology - Simple reservoir-based hydrological model
• https://github.com/UVAdMIST/Norfolk_Groundwater_Model - scripts to model and forecast shallow groundwater table level in Norfolk, VA ANN
• https://github.com/jfzhang95/LSTM-water-table-depth-prediction - Developing a Long Short-Term Memory (LSTM) based Model for Predicting Water Table Depth in Agricultural Areas
• https://github.com/OpenWaterAnalytics/pyswmm - Python Wrapper for Stormwater Management Model (SWMM5)
• https://github.com/paknorton/pyPRMS - A Python library for working with the Precipitation-Runoff Modeling System (PRMS)

• https://github.com/pypr/pysph - A framework for Smoothed Particle Hydrodynamics in Python
• https://github.com/pmgbergen/porepy - Python Simulation Tool for Fractured and Deformable Porous Media
• https://github.com/python-hydro/pyro2 - A framework for hydrodynamics explorations and prototyping
• https://github.com/PMEAL/OpenPNM - A Python package for performing pore network modeling of porous media
• https://github.com/PMEAL/porespy - A set of tools for characterizing and analying 3D images of porous materials

• https://github.com/pytorch/pytorch - Tensors and Dynamic neural networks
• https://github.com/josephmisiti/awesome-machine-learning - list of awesome Machine Learning frameworks, libraries and software.
• https://github.com/trekhleb/homemade-machine-learning - Python examples of popular machine learning algorithms
• https://github.com/donnemartin/data-science-ipython-notebooks - Data science Python notebooks
• https://github.com/openai/gym - A toolkit for developing and comparing reinforcement learning algorithms.
• https://github.com/keras-team/keras - Deep Learning for humans

• https://github.com/thouska/spotpy - A Statistical Parameter Optimization Tool
• https://github.com/PESTools/pestools - PESTools is a Python package for processing and visualizing information associated with the parameter estimation software PEST and PEST++
• https://github.com/JamesSample/water_balance_model - MCMC calibration code for a spatially distributed water balance model
• https://github.com/pypest/pyemu - model-independent uncertainty analyses, data-worth analyses, and interfacing with PEST(++)
• https://github.com/Project-Platypus/Platypus - A Free and Open Source Python Library for Multiobjective Optimization
• https://github.com/mehmetbercan/NSGA-II_Python_for_SWAT_model - Multi-Site and -Objective calibration method for SWAT model

• https://github.com/micha-silver/WRF-Hydro - Scripts for managing data from WRF-Hydro model
• https://github.com/brclark-usgs/NHGtools - Scripts to develop sub-National grids based on the National Hydrogeologic Grid
• https://github.com/hzambran/SWAT2R - Input/Output functions for pre- and post-processing SWAT
• https://github.com/spence97/SWAT_viewer - SWAT output viewer application
• https://github.com/DigitalAgricultureDiscovery/swat-tools - four applications designed to assist with your analysis of SWAT model data.
• https://github.com/yt-project/yt - analyzing and visualizing volumetric data
• https://github.com/snowmodel-tools/postprocess_python - post processing of output from SnowModel / HydroFlow

• https://github.com/YoJimboDurant/pyNADA - attempt to create python version of R package NADA
• https://github.com/CamDavidsonPilon/lifelines - Survival analysis in Python
• https://github.com/jkall/qgis-midvatten-plugin - Midvatten plugin for QGIS
• https://github.com/marcharper/python-ternary - Ternary plotting library for python with matplotlib
• https://github.com/Geosyntec/wqio - Water quality analysis
• https://github.com/flashliquid/PiperPython - Plot Piper waterquality diagrams using python
• https://github.com/morganjwilliams/pyrolite - A set of tools for getting the most from your geochemical data.
• https://github.com/bjodah/chempy - A package useful for chemistry written in Python

• https://github.com/ethoms-usgs/Cross-Section - Geoprocessing tools for working with geologic cross-sections in ArcGIS
• https://github.com/cgre-aachen/gempy - GemPy is an open-source, Python-based 3-D structural geological modeling software
• https://github.com/agile-geoscience/welly - Welly is a family of classes to facilitate the loading, processing, and analysis of subsurface wells and well data
• https://github.com/agile-geoscience/geotransect - Tool for visualizing subsurface data along 2D transects.
• https://github.com/brendonhall/facies_classification - demonstration of using a machine learning algorithm (support vector machine) to assign facies to well log data
• https://github.com/fr1ll/ras2las - Well log digitalization
• https://github.com/petroGG/Basic-Well-Log-Interpretation - Basic Well Log Interpretation with python, pandas, matplotlib
• https://github.com/tomvansteijn/xsboringen - plot borehole data in cross-sections
• https://github.com/kinverarity1/well-schematics - matplotlib code for drawing borehole schematic diagrams
• https://github.com/dfitzgerald3/AutomatedWellLogCorrelation - Framework for correlating two or more well logs using feature vectors generated from CNN's in Pytorch
• https://github.com/peterson-tim-j/HydroMap - Spatial interpolation of groundwater level for realistic flow dynamics

• https://github.com/UWSEDS/LectureNotes - Lecture content for UW Software Engineering for Data Scientists
• https://github.com/goodalljl/hydroinformatics_class - Sample Python scripts provided to students in a Hydroinformatics course
• https://github.com/tjfulle/fem-with-python - Materials for introductory Finite Element course
• https://github.com/jakevdp/PythonDataScienceHandbook - Python Data Science Handbook: full text in Jupyter Notebooks
• https://github.com/wenzeslaus/geospatial-modeling-course-jupyter - NCSU Geospatial Modeling and Analysis course
• https://github.com/barbagroup/CFDPython - A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/
• https://github.com/ncsu-geoforall-lab/open-science-course-notebook - Notebook for Tools for Open Geospatial Science Course
• https://github.com/PacktPublishing/Learning-Geospatial-Analysis-with-Python-Third-Edition - Learning Geospatial Analysis with Python
• https://github.com/rasbt/python-machine-learning-book-2nd-edition - Python Machine Learning
• https://github.com/uwescience/Online-Educational-Resources - Online resources for data science education
• https://github.com/giswqs/qgis-earthengine-examples - A collection of 290+ Python examples for using Google Earth Engine in QGIS
• https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers - An introduction to Bayesian methods + probabilistic programming

• https://github.com/ibab/python-mle A Python package for performing Maximum Likelihood Estimates
• https://github.com/tommyod/KDEpy - Kernel Density Estimation in Python
• https://github.com/rouseguy/intro2stats - Introduction to Statistics using Python
• https://github.com/ecosme38/Data-Assimilation-Notebooks - data assimilation
• https://github.com/ctgk/bayesnet - Bayesian method library for Python

• https://github.com/ucd-cws/arcpy_metadata - Python metadata editing classes for ArcGIS feature classes
• https://github.com/python-visualization/folium - Python Data. Leaflet.js Maps.
• https://github.com/JamesRamm/archook - Searches the system for arcgis and makes arcpy available to python
• https://github.com/Esri/arcgis-python-api - Documentation and samples for ArcGIS API for Python
• https://github.com/GeospatialPython/pyshp - This library reads and writes ESRI Shapefiles in pure Python.
• https://github.com/schwanksta/python-arcgis-rest-query - A simple util to download a layer from ArcGIS web servers
• https://github.com/jkeifer/arcpy-extensions - Extensions and helpers for the ArcGIS python interface arcpy.
• https://github.com/knu2xs/geoai-tutorials - Tutorials on how to merge the capabilities of ArcGIS and Machine Learning
• https://github.com/openaddresses/pyesridump - Scrapes an ESRI MapServer REST endpoint to spit out more generally-usable geodata.
• https://github.com/R-ArcGIS/r-bridge-install - Install the R ArcGIS Tools
• https://github.com/knu2xs/esri-netx-hydro - Perform hydrology tracing using NetworkX against NHD flow line data.

• https://github.com/DiffusionMapsAcademics/pyDiffMap - Library for diffusion maps
• https://github.com/cjohnson318/geostatsmodels - This is a collection of geostatistical scripts written in Python
• https://github.com/GeoStat-Framework/PyKrige - Kriging Toolkit for Python
• https://github.com/whimian/pyGeoStatistics - Geostatistics in Python
• https://github.com/GeostatsGuy/GeostatsPy - Reimplementation of GSLIB, Spatial Data Analytics and Geostatistics
• https://github.com/pysal/esda - Methods for testing for global and local autocorrelation in areal unit data.
• https://github.com/GeoStat-Framework/GSTools - A geostatistical toolbox: random fields, variogram estimation, covariance models, kriging
• https://github.com/fatiando/verde - Processing and interpolating spatial data with a twist of machine learning
  • https://github.com/fatiando/transform2020 - Material for the Verde tutorial at Transform 2020
• https://github.com/GeostatsGuy/PythonNumericalDemos - A collection of Python demos for geostatistical methods.
• https://github.com/GeostatsGuy/GeostatsPy_Intro_Course - Introduction to spatial data analytics and machine learning with GeostatsPy Python package
• https://github.com/MuellerSeb/GSTools-EGU2020 - EGU2020 Presentation for GSTools
• https://github.com/pysal/tobler - Areal interpolation
• https://github.com/szymon-datalions/pyinterpolate - Geostatistics

• https://github.com/aleaf/GIS_utils - some functions for working with the Python GIS toolchain (fiona, shapely, pyproj, etc.)
• https://github.com/sshuair/awesome-gis - Awesome GIS is a collection of geospatial related sources
• https://github.com/HPCGISLab/pcml - the parallel cartographic modeling language (PCML) is a multi-institutional collaborative project
• https://github.com/jazzband/geojson - Python bindings and utilities for GeoJSON
• https://github.com/perrygeo/python-rasterstats - Summary statistics of geospatial raster datasets based on vector geometries.
• https://github.com/NCAR/esmlab - Earth System Model Lab (esmlab)
• https://github.com/ColCarroll/ridge_map - Ridge plots of ridges
• https://github.com/awickert/GRASS-GIS-for-geomorphologists - Introductory guide to using GRASS GIS for drainage networks,
• https://github.com/fmaussion/salem Add geolocalised subsetting, masking, and plotting operations to xarray
• https://github.com/amacd31/catchment_tools - Tools for doing calculations related to hydrological catchments.
• https://github.com/corteva/rioxarray - geospatial xarray extension powered by rasterio
• https://github.com/RoboDonut/awesome-spatial - A list of awesome spatial repositories.
• https://github.com/earthlab/OpenTopoDL - Programmatic access to OpenTopography data via Python

• https://github.com/lucadelu/pyModis - python library to work with MODIS data
• https://github.com/tomquisel/snow_melt - This is a project by Jeff Dozier to estimate the amount of snow water equivalent (SWE) in a mountainous region based on satellite imagery.
• https://github.com/pytroll/pyresample - Geospatial image resampling in Python
• https://github.com/mdbartos/pysheds - Simple and fast watershed delineation in python.
• https://github.com/sahandha/eif - Extended Isolation Forest for Anomaly Detection
• https://github.com/dshean/snowtools - Utilities for working with snow data
• https://github.com/rspies/USGS_nexrad - Comparison of NEXRAD Multisensor Precipitation Estimates to Raingage Observations
• https://github.com/hydrogo/rainymotion - radar-based precipitation nowcasting based on optical flow techniques
• https://github.com/whigg/natural_disaster_pred - Using CNNs and Sentinel-2 satellite data to predict landslides
• https://github.com/ornldaac/modis_global_tool_batch_order - MODIS Global Subset Tool orders via the MODIS Web Service
• https://github.com/atedstone/modis_tools
• https://github.com/pangeo-data/awesome-open-climate-science - Awesome Open Atmospheric, Ocean, and Climate Science
• https://github.com/mortcanty/CRC4Docker - Image Analysis, Classification and Change Detection in Remote Sensing, Fourth Revised Edition
• https://github.com/giswqs/Awesome-GEE - A curated list of Google Earth Engine resources
• https://github.com/jhamman/scikit-downscale - Statistical climate downscaling in Python

• https://github.com/jackjamieson/GE-3-point-problem-solver - Uses the Google Earth JS API to interactively plot geological symbols and planes by solving the 3 point problem.
• https://github.com/zsylvester/meanderpy - Simple model of meander migration
• https://github.com/dandrino/terrain-erosion-3-ways - Three Ways of Generating Terrain with Erosion Features
• https://github.com/utah-geological-survey/RuffSurfFinder - Set of codes built by Matthew Morriss to measure surface roughness
• https://github.com/awickert/gFlex - methods to solve elastic plate flexure
• https://github.com/hrmartens/LoadDef - LoadDef: A Python-based toolkit to model elastic deformation caused by surface mass loading
• https://github.com/softwareunderground/awesome-open-geoscience - repositories that make our lives as geoscientists, hackers and data wranglers easier
• https://github.com/usgs/shakemap - Near-real-time maps of ground motion and shaking intensity
• https://github.com/usgs/groundmotion-processing - Parsing and processing ground motion data
• https://github.com/insarlab/MintPy - Miami InSAR time-series software in Python
• https://github.com/isce-framework/isce2 - InSAR Scientific Computing Environment version 2
• https://github.com/GeoscienceAustralia/PyRate - estimating velocity and time-series from Interferometric Synthetic Aperture Radar
• https://github.com/cossatot/culpable - quantitative analysis of faulting in slip rate/history estimation and paleoseismology
• https://github.com/geodynamics/pylith_installer - Installer code for PyLith, a finite-element code for dynamic and quasistatic simulations of crustal deformation
• https://github.com/SciTools/iris - A powerful, format-agnostic, and community-driven Python package for analysing and visualising Earth science data
• https://github.com/yohanesnuwara/open-geoscience-repository - Open geoscience computing of open geoscience datasets available in open databases
• https://github.com/alainmuls/pyRTKLib - Processing / plotting of RINEX based GPS & Galileo data
• https://github.com/bpurinton/GNSS-Correction-RTKLIB - GNSS Collection and Post-Processing with RTKLIB
• https://github.com/usgs/gems-tools-arcmap - Tools for working with the GeMS geologic map database schema in ArcGIS
• https://github.com/usgs/gems-tools-pro - GeMS Tools for ArcGIS Pro
• https://github.com/softwareunderground/subsurface - Core library for subsurface science and engineering

• https://github.com/opengrav/gmeterpy - Processing gravity measurements with Python

• https://github.com/smarnach/pyexiftool a Python library to communicate with an instance of Phil Harvey's excellent ExifTool command-line application.
• https://github.com/citation-style-language/styles - Official repository for Citation Style Language (CSL) citation styles.
• https://github.com/zotero/zotero - zotero
• https://github.com/wp-plugins/zotpress WordPress.org Plugin Mirror
• https://github.com/urschrei/pyzotero Pyzotero: a Python client for the Zotero API

• https://github.com/datalyze-solutions/pandas-qt - Utilities to use pandas (the data analysis / manipulation library for Python) with Qt.
• https://github.com/dmnfarrell/tkintertable - A pure python library for adding tables to a Tkinter application
• https://github.com/dmnfarrell/pandastable - Table analysis in Tkinter using pandas DataFrames.
• https://github.com/draperjames/qtpandas - Qt Meets Pandas
• https://github.com/mherrmann/fbs-tutorial - Tutorial for creating Python/Qt GUIs with fbs
• https://github.com/alejandroautalan/pygubu - A simple GUI designer for the python tkinter module
• https://github.com/ragardner/tksheet - Python 3.6+ tkinter table widget for displaying tabular data
• https://github.com/jarvisteach/appJar - Simple Tkinter GUIs in Python
• https://github.com/adamerose/pandasgui - A GUI for analyzing Pandas DataFrames.
• https://github.com/bluenote10/tabloo - Minimalistic dashboard app for visualizing tabular data