This repository contains links to personal GitHub repositories from (former) members of the Hydrology and Environmental Hydraulics Group at Wageningen University.
Collection of tools, software, instruction manuals and other materials for research and education.
- A (very) short introduction to R: A 1.5-hour (10 page) introduction to R and other self-study modules.
- Hydrology basics: Education material (knowledge clips, webapps and more) explaining basic hydrological concepts.
- R scripts for hydrological data analysis: Collection of R scripts that can be useful for data analysis.
- WALRUS: The Wageningen Lowland Runoff Simulator: a lumped rainfall-runoff model for catchments with shallow groundwater. See this publication by Brauer et al., Geosci. Model Dev., 2014.
- ADCP tools: Software to process ADCP data.
- dS2: The Distributed Simple Dynamical Systems Model. See this publication by Buitink et al., Geosci. Model Dev., 2020.
- RAINLINK: Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network. See this publication by Overeem et al., Atmos. Meas. Tech., 2016.
- Filtering personal weather station data: Quality control for crowdsourced personal weather stations to enable operational rainfall monitoring. See this publication by De Vos et al., Geophysical Research Letters, 2019.
- Salt intrusion forecasting model: Machine learning model for predicting salt concentrations in the Rhine-Meuse delta. See this publication by Wullems et al., Hydrol. Earth Syst. Sci., 2023.
- Meander analyses: Matlab scripts to study the multiscale structure of meandering planforms.
- Separating and identifying bedform scales: Tool to separate a bathymetric signal representing two or more bedform scales and identify bedforms based on zero-crossing.
- Loess filter: Matlab mex function to perform a locally weighted robust regression (loess filter).
- Processing NMEA data: Matlab toolbox to process NMEA data.
- morfacTide: MATLAB toolbox to create a repetitive tidal signal suited for upscaled morphodynamic models. See this publication by Schrijvershof et al., JGR. ES., 2023.
- Preprocessing KNMI radar data for hydrology: scripts (R and python), files and info to download and preprocess radar data from the Royal Netherlands Meteorological Institute (KNMI) for use in (catchment) hydrological studies.
- Spatial and temporal evaluation of radar rainfall nowcasting techniques on 1,533 Events: Code for this publication by Imhoff et al., Water Resour. Res., 2020.
- Rainfall Nowcasting Using Commercial Microwave Links: Code for this publication by Imhoff et al., Geophys. Res. Let., 2020.
