A nice series of video tutorial on R was just posted by the Google Developers Group, on youTube, here.
Recently many resources were added for hydrologists, which I list below with a little comment.
New: Now we also have a very informative paper at HESSD: "Using R in hydrology: a review of recent developments and future directions" by Slate et al., 2019. It is a pity they do not cite this blog, but we cannot pretend too much!
- DonwscaleR is an R package for empirical-statistical downscaling focusing on daily data and covering the most popular approaches and techniques (quantile mapping, analogs, regression, generalized regression, neural networks). This package has been conceived to work in the framework of both seasonal forecasting and climate change studies and is part of the climate4R framework, formed by
- bigleaf (version 0.6.5), an open source toolset for the derivation of meteorological, aerodynamic, and physiological ecosystem properties from eddy covariance (EC) flux observations and concurrent meteorological measurements.
- rtop is a package for geostatistical interpolation of data with irregular spatial support such as runoff related data or data from administrative units.
- The boussinesq package is a collection of functions implementing the one-dimensional Boussinesq Equation (ground-water).
- dynatopmodel is a native R implementation and enhancement of the Dynamic TOPMODEL, Beven and Freers’ (2001) extension to the semi-distributed hydrological model TOPMODEL (Beven and Kirkby, 1979).
RclimTool. It was designed with the aim of facilitating users in statistical analysis for quality control, filling of missing data, homogeneity analysis and calculation of indicators for daily weather series for temperature (maximum and minimum) and precipitation.
- LumpR a tool for HRU delineations (the reference paper is here).
- Cropwat FAO model (it is a decision support system developed by the Land and Water Development Division of FAO for planning and management of irrigation) translated into R.
- Two socio-hydrological models of human-flood interactions that were recently developed. The two models are similar, but based on different socio-economic variables (wealth and human proximity to rivers VS relative population density). A full description of the two models can be found in the following two papers: HESS (2013), https://www.hydrol-earth-syst-sci.net/17/3295/2013/hess-17-3295-2013.pdf; WRR (2015), http://onlinelibrary.wiley.com/doi/10.1002/2014WR016416/full
- RWater: A Cyber-enabled Data-driven Tool for Enhancing Hydrology Education
- airGR: Hydrological modelling tools developed at Irstea-Antony (HBAN Research Unit, France). The package includes several conceptual rainfall-runoff models , a snowmelt module and the associated functions for their calibration and evaluation
- airGRteaching:“It is an add-on package to the 'airGR' package that simplifies its use and is aimed at being used for teaching hydrology. The package provides 1) three functions that allow to complete very simply a hydrological modelling exercise 2) plotting functions to help students to explore observed data and to interpret the results of calibration and simulation of the GR ('Génie rural') models 3) a 'Shiny' graphical interface that allows for displaying the impact of model parameters on hydrographs and models internal variables.“
- lumpR. A tool facilitating landscape discretisation for hillslope-based hydrological models. It is described in a paper on GMDD
- HydroGOF and HydroTSM by Mauricio Zambrano-Bigiarini. The first provides functions implementing both statistical and graphical goodnes-of-fit measures between observed and simulated values, mainly oriented to be used during the calibration, validation, and application of hydrological models. The second provides functions for management, analysis, interpolation and plotting of time series used in hydrology and related environmental sciences. Mauricio also had a poster at EGU 2010 general assembly on the topic.
- Jasper Vrugt's DREAM calibration method
- RMWAGEN by Emanuele Cordano which is a weather generator, a package that contains functions for spatial multi-site stochastic generation of daily timeseries of temperature and precipitation. A presentation can be found here.
- Other stochastic generators of precipitation can be found here. Do not forget to explore the links in that page, and particularly the presentations given at the Roscoff's Workshop on stochastic generators, where many examples are in R
- The RHydro which included TOPMODEL (apparently not anymore supported), tools for DEM analysis (this last type of tools however are also available through the work by R. Bivand, E.J. Pebesma and V. Gomez-Rubio ), an implementation of the FUSE by Clark et al (2008) methodology, and many other tools for hydrological analysis. These were initially promoted by Wouter Buytaert and Dominik Reusser who also gave a nice tutorial at EGU a few years ago.
- Hydromad: It provides a modelling framework for environmental hydrology: water balance accounting and flow routing in spatially aggregated catchments. It supports simulation, estimation, assessment and visualisation of flow response to time series of rainfall and other drivers
- TUWmodel is a lumped conceptual rainfall-runoff model, following the structure of the HBV model. The model runs on a daily time step and consists of a snow routine, a soil moisture routine and a flow routing routine. See Parajka, J., R. Merz, G. Bloeschl (2007) Uncertainty and multiple objective calibration in regional water balance modelling: case study in 320 Austrian catchments, Hydrological Processes, 21, 435-446
- Sean Turner's and Stefano Galelli's, reservoir package, Tools for Analysis, Design, and Operation of Water Supply Storages
- R Code: Handy routines for Hydrologists by Dan Moore and others.
- Hydrosanity: It provides a graphical user interface for exploring hydrological time series. It is designed to work with catchment surface hydrology data (mainly rainfall and streamflow time series at a set of locations). There are functions to import from a database or files; summarise and visualise the dataset in various ways; estimate areal rainfall; fill gaps in rainfall data; and estimate the rainfall-runoff relationship. Probably the most useful features are the interactive graphical displays of a spatial set of time series. (This project seems actually being abandoned).
- aqp: Algorithms for quantitative pedology. A collection of algorithms related to modeling of soil resources, soil classification, soil profile aggregation, and visualization by Dylan Beaudette and Pierre Roudier. A paper talking about it is given here. And a presentation is not missing.
- A package for plotting soil water retention curves and hydraulic conductivity by Emanuele Cordano, Fabio Zottele and Daniele Andreis is soilwater.
- soilDB, of the same authors of aqp, is useful to access some soil databases.
- soiltexture: Functions for soil texture plot, classification and transformation by Jules Moeys
- Hydrome: This package estimates the parameters in infiltration and water retention models by curve-fitting method.
- SoilWater address to a couple of packages for estimating Soil Water Retention Curves and some Pedotransfer Functions
- hydropso: This package implements a state-of-the-art version of the Particle Swarm Optimisation (PSO) algorithm, with a special focus on the calibration of environmental models.
- Evapotranpiration: by Dan Lu Guo and Seth Westra. This package estimates Potential and Actual Evapotranspiration with multiple models (see also the paper here).
- EcoHydRology developed by DR. Fuka, MT Walter, JA Archibald, TS Steenhuis, and ZM Easton which presents a community modeling foundation for Eco-Hydrology.
- Claudia Vitolo's Curve Number (Curve Number!) and other R stuff, including some tools for data discovery. Claudia also manages a Google+ group, R4Hydrology.
- nsRFA: this is collection of statistical tools for objective (non-supervised) applications of the Regional Frequency Analysis methods in hydrology made by Alberto Viglione. The package refers to the index-value method and, more precisely, helps the hydrologist to: (1) regionalize the index-value; (2) form homogeneous regions with similar growth curves; (3) fit distribution functions to the empirical regional growth curves.
- Wasim: Helpful tools for data processing and visualisation of results of the hydrological model WASIM-ETH.
- Geotopbricks by Emanuele Cordano, analyses raster maps and other information as input/output files from the Hydrological Distributed Model GEOtop
- hddtools by Claudia Vitolo is a tool for hydrological data discovery.
- waterData is a USGS Package for Retrieval, Analysis, and Anomaly Calculation of Daily Hydrologic Time Series Data
- Lmoments and Lmomco are two packages for the estimation of the L-moments of a distribution.
- The SPEI R Package by Santiago Begueria which includes a set of functions for computing potential evapotranspiration and several widely used drought indices including the Standardized Precipitation-Evapotranspiration Index (SPEI).
- The USGS-R packages at github
- Alessio Pugliese and Attilio Castellarin pREC: a package for the regionalisation of some hydrological variables.
- Alberto Montanari version of Hymod: here.
- Emanuele Cordano work in connecting R with JGrasstools, here, to do geomorphological analysis (slides in Italian here, and in English here) within R.
- meteo package by Kilibarda, Sekulic, Hengl, Pebesma and Graeler, A package for spatio-temporal geostatistical mapping of meteorological data. Global spatio-temporal models calculated using publicly available data are stored in package.
- The reservoir package by Sean Turner [aut, cre], Jia Yi Ng [aut], Stefano Galelli [aut]. It measures single-storage water supply system performance using resilience, reliability, and vulnerability metrics; assess storage-yield-reliability relationships; determine no-fail storage with sequent peak analysis; optimize release decisions for water supply, hydropower, and multi-objective reservoirs using deterministic and stochastic dynamic programming; evaluate inflow persistence using the Hurst coefficient. A companion paper for this tool is available.
- The scripts and data I use in my short mini-classes on R inside my Hydrology and Hydraulic Constructions classes. The include a quick introduction to R, plotting a treating a time serie of rainfall data read from a file, reading and plotting discharges data from a file, estimating the idf curves of rainfall from a standard (Italian standard) set of maxima of annual precipitation, with interpolation of Gumbel probabilities with various methods.
- The TSA package contains R functions and datasets detailed in the book "Time Series Analysis with Applications in R (second edition)" by Jonathan Cryer and Kung-Sik Chan
- Here James B. Elsner and Thomas H. Jagger wrote a tutorial for using R for Climate Research.
- Here tools for visualising California snow cover data are provided.
- A visualisation of the Bayesian search of a distribution stimulated by Climate Research.
- Simulating wind speed with R.
- Visualising droughts.
- Visualising NCEP global data
- Resources for Spatial Analysis
- Analysis of Dutch Rainfall data
- extRemes [for Windows users (I do not like the packages linked to a platform!!!)]
Frankly I did not test them all: but usually CRAN packages are really good.
Finally, Mauricio Zambrano suggested also a series of other CRAN R packages that could be useful:
- Geostatistics: gstat, automap, geoR, fields, RandomFields
- GIS: spgrass6, RSAGA, rgdal, sp, proj4, raster, mapproj, maptools, RGoogleMaps, RArcInfo, RpyGeo,
- Flood frequency: POT, evd, nsRFA, extremes, lmomco
- Optimization: pso, DEoptim,
- High Performance Computing: parallel, snowfall, multicore, jit, nws, Rmpi, snow, taskPR
- Spreadsheets & DB: RPostgreSQL, RMySQL, RSQLite, RNetCDF, RexcelInstaller, xlsReadWrite
- Bayesian statistics: BAS, BLR, ensembleBMA, evdbayes, LearnBayes,
- ramps, spBayes,...
- Latex: xtable, Sweave
- Wavelets: wavelets; wavethresh, wmtsa, Rwave
- Data Mining: Rweka, rattle, party, RandomForest, ...
- Machine Learning tools (in Java with R connection)
If you arrived here and you never used R, you can start from here.
Finally, you also would like to know why it is so hard to learn R. This blogpost clarify it, and also why I am using other languages for real model development.