| Maintainer: | Sam Albers, Sam Zipper, Ilaria Prosdocimi |
| Contact: | sam.albers at gmail.com |
| Version: | 2022-03-02 |
| URL: | https://CRAN.R-project.org/view=Hydrology |
| Source: | https://github.com/cran-task-views/Hydrology/ |
| Contributions: | Suggestions and improvements for this task view are very welcome and can be made through issues or pull requests on GitHub or via e-mail to the maintainer address. For further details see the Contributing guide. |
| Citation: | Sam Albers, Sam Zipper, Ilaria Prosdocimi (2022). CRAN Task View: Hydrological Data and Modeling. Version 2022-03-02. URL https://CRAN.R-project.org/view=Hydrology. |
| Installation: | The packages from this task view can be installed automatically using the ctv package. For example, ctv::install.views("Hydrology", coreOnly = TRUE) installs all the core packages or ctv::update.views("Hydrology") installs all packages that are not yet installed and up-to-date. See the CRAN Task View Initiative for more details. |
This task view contains information about packages broadly relevant to hydrology , defined as the movement, distribution and quality of water and water resources over a broad spatial scale of landscapes. Packages are broadly grouped according to their function; however, many have functionality that spans multiple categories. We also highlight other, existing resources that have related functions - for example, statistical analysis or spatial data processing. See also Riccardo Rigon’s excellent list of hydrology-related R tools and resources. Some Python-related resources can be found here and here.
If you have any comments or suggestions for additions or improvements for this task view, go to GitHub and submit an issue, or make some changes and submit a pull request. If you can’t contribute on GitHub, send Sam Albers an email. If you have an issue with one of the packages discussed below, please contact the maintainer of that package.
dataRetrieval: Collection of functions to help retrieve U.S. Geological Survey (USGS) and U.S. Environmental Protection Agency (EPA) water quality and hydrology data from web services.
dbhydroR: Client for programmatic access to the South Florida Water Management District’s ‘DBHYDRO’ database at https://www.sfwmd.gov/science-data/dbhydro, with functions for accessing hydrologic and water quality data.
iemiscdata: Miscellaneous data sets [Engineering Economics, Environmental/Water Resources Engineering, US Presidential Elections].
ie2miscdata: A collection of Irucka Embry’s miscellaneous USGS data sets (USGS Parameter codes with fixed values, USGS global time zone codes, and US Air Force Global Engineering Weather Data). Irucka created these data sets while a Cherokee Nation Technology Solutions (CNTS) United States Geological Survey (USGS) Contractor and/or USGS employee.
dbhydroR: Client for programmatic access to the South Florida Water Management District’s DBHYDRO database, with functions for accessing hydrologic and water quality data.
echor: An R interface to United States Environmental Protection Agency (EPA) Environmental Compliance History Online (‘ECHO’). Provides functions to locate facilities with discharge permits and download discharge records.
FedData: Functions to Automate Downloading Geospatial Data Available from Several Federated Data Sources.
hydroscoper: R interface to the Greek National Data Bank for Hydrological and Meteorological Information. It covers Hydroscope’s data sources and provides functions to transliterate, translate and download them into tidy dataframes (tibbles).
isoWater: R interface to the Waterisotopes Database. Provides functions to query and obtain stable H and O isotope data from water samples collected at >60,000 sites worldwide.
kiwisR: Wrapper for retrieving data from KISTERS WISKI databases via the KiWIS API.
metScanR (archived): A tool for locating, mapping, and gathering environmental data and metadata from over 157,000 environmental monitoring stations among 219 countries/territories and >20 networks/organizations,
nhdR: Tools for working with the National Hydrography Dataset, with functions for querying, downloading, and networking both the NHD and NHDPlus datasets.
rnrfa: Utility functions to retrieve data from the UK National River Flow Archive. There are functions to retrieve stations falling in a bounding box, to generate a map and extracting time series and general information.
tidyhydat: Provides functions to access historical and real-time national ‘hydrometric’ data from Water Survey of Canada data sources ( http://dd.weather.gc.ca/hydrometric/csv/ and http://collaboration.cmc.ec.gc.ca/cmc/hydrometrics/www/) and then applies tidy data principles.
washdata: Urban water and sanitation survey dataset from survey conducted in Dhaka, Bangladesh, part of a series of surveys to be conducted in various cities including Accra, Ghana; Nakuru, Kenya; Antananarivo, Madagascar; Maputo, Mozambique; and, Lusaka, Zambia.
waterData: Imports U.S. Geological Survey (USGS) daily hydrologic data from USGS web services, plots the data, addresses some common data problems, and calculates and plots anomalies.
epanetReader: Reads water network simulation data in ‘Epanet’ text-based ‘.inp’ and ‘.rpt’ formats into R. Also reads results from ‘Epanet-msx’. Provides basic summary information and plots. The README file has a quick introduction. See https://www.epa.gov/water-research/epanet. for more information on the Epanet software for modeling hydraulic and water quality behavior of water piping systems.
noaastormevents: Allows users to explore and plot data from the National Oceanic and Atmospheric Administration (NOAA) Storm Events database through R for United States counties. Functionality includes matching storm event listings by time and location to hurricane best tracks data. This work was supported by grants from the Colorado Water Center, the National Institute of Environmental Health Sciences (R00ES022631) and the National Science Foundation (1331399).
frostr: An API to Norway’s ‘Frost’ API to retrieve data as data frames. The ‘Frost’ API, and the underlying data, is made available by the Norwegian Meteorological Institute (MET Norway).
climate: Automatize downloading of meteorological and hydrological data from publicly available repositories: OGIMET, University of Wyoming - atmospheric vertical profiling data, and Polish Institute of Meterology and Water Management - National Research Institute. T
clifro: A web portal to the New Zealand National Climate Database of around 6,500 climate stations. See https://cliflo.niwa.co.nz/ for more information.
getMet (archived): Functions for sourcing, formatting, and editing meteorological data for hydrologic models.
GSODR: Provides automated downloading, parsing, cleaning, unit conversion and formatting of Global Surface Summary of the Day (GSOD) weather data from the from the USA National Centers for Environmental Information (NCEI) for use in R.
MODISTools: Programmatic Interface to the MODIS Land Products Subsets Web Services. Allows for easy downloads of ‘MODIS’ time series.
nasapower: Client for NASA’s Prediction of Worldwide Energy Resource (POWER) project data API Web Services. Data available include daily meteorology, interannual and 30 year climatology. Functionality for specifying geolocation and downloading data, which have global coverage at 1/2 by 1/2 arc-degree gridded resolution from 1983 to near-current are provided. Over 140 different parameters are offered including temperature (max/min/mean/dew), relative humidity, precipitation, wind speed and more.
metR: metR packages several functions and utilities that make R better for handling meteorological data in the tidy data paradigm. Extends ‘ggplot2’ for better plotting of scalar and vector fields and provides commonly used analysis methods in the atmospheric sciences.
prism: This package allows users to access and visualize data from the Oregon State PRISM project. Data are all in the form of gridded rasters for the continental US at 4 different temporal scales: daily, monthly, annual, and 30 year normals.
rdwd: Handle climate data from the German DWD (‘Deutscher Wetterdienst’).
RNCEP: Contains functions to retrieve, organize, and visualize weather data from the NCEP/NCAR Reanalysis and NCEP/DOE Reanalysis II datasets.
rnoaa: Client for many NOAA data sources including the NCDC climate API, with functions for each of the API endpoints: data, data categories, data sets, data types, locations, location categories, and stations. Includes interface NOAA sea ice data, severe weather inventory, Historical Observing Metadata Repository (‘HOMR’), storm data via ‘IBTrACS’, tornado data via the NOAA storm prediction center, and more.
rpdo: Get Monthly Pacific Decadal Oscillation (PDO) index values from January 1900 to present. See also rsoi for downloading Southern Oscillation Index, Oceanic Nino Index and North Pacific Gyre Oscillation data.
rwunderground: Tools for getting historical weather information and forecasts from wunderground.com. Historical weather and forecast data includes, but is not limited to, temperature, humidity, windchill, wind speed, dew point, heat index. Additionally, the weather underground weather API also includes information on sunrise/sunset, tidal conditions, satellite/webcam imagery, weather alerts, hurricane alerts and historical high/low temperatures.
smapr: Acquisition and Processing of NASA Soil Moisture Active-Passive (SMAP) Data. Facilitates programmatic access to search for, acquire, and extract NASA Soil Moisture Active Passive (SMAP) data.
stationaRy: Acquire hourly meteorological data from stations located all over the world. The available data is automatically downloaded from a data repository and processed into a ‘tibble’ for the exact range of years requested.
worldmet: Functions to import data from more than 30,000 surface meteorological sites around the world managed by the National Oceanic and Atmospheric Administration (NOAA) Integrated Surface Database (ISD).
agromet: agrometeorological functions to calculate climatic and hydrological indices and statistics from tidy data.
driftR: A tidy implementation of equations that correct for instrumental drift in continuous water quality monitoring data using one or two standard reference values. The equations implemented are from Hasenmueller (2011).
climdex.pcic: PCIC Implementation of Climdex Routines PCIC’s implementation of Climdex routines for computation of extreme climate indices.
climatol: Functions for the quality control, homogenization and missing data infilling of climatological series and to obtain climatological summaries and grids from the results. Also functions to draw wind-roses and Walter&Lieth climate diagrams.
getMet (archived): Functions for sourcing, formatting, and editing meteorological data for hydrologic models.
htsr: Functions for the management and treatment of hydrology and meteorology time-series stored in a ‘Sqlite’ data base.
SWTools: Functions to speed up work flow for hydrological analysis. Focused on Australian climate data (SILO climate data), hydrological models (eWater Source) and in particular South Australia (https://water.data.sa.gov.au hydrological data).
openSTARS: An open source implementation of the ‘STARS’ toolbox (Peterson & Ver Hoef, 2014, doi:10.18637/jss.v056.i02) using ‘R’ and ‘GRASS GIS’. It prepares the *.ssn object needed for the ‘SSN’ package. A Digital Elevation Model (DEM) is used to derive stream networks (in contrast to ‘STARS’ that can clean an existing stream network).
waterquality: The main purpose of waterquality is to quickly and easily convert satellite-based reflectance imagery into one or many well-known water quality algorithms designed for the detection of harmful algal blooms or the following pigment proxies: chlorophyll-a, blue-green algae (phycocyanin), and turbidity. Johansen et al. (2019) doi:10.21079/11681/35053.
RWDataPlyr: A tool to read and manipulate data generated from ‘RiverWare’(TM) http://www.riverware.org/ simulations. ‘RiverWare’ and ‘RiverSMART’ generate data in “rdf”, “csv”, and “nc” format. This package provides an interface to read, aggregate, and summarize data from one or more simulations in a ‘dplyr’ pipeline.
reasonabletools: Functions for cleaning and summarising water quality data for use in National Pollutant Discharge Elimination Service (NPDES) permit reasonable potential analyses and water quality-based effluent limitation calculations. Procedures are based on those contained in the “Technical Support Document for Water Quality-based Toxics Control”, United States Environmental Protection Agency (1991).
baseflow (archived): Computes hydrograph separation using the conceptual automated process from Pelletier and Andreassian (2019).
biotic: Calculates a range of UK freshwater invertebrate biotic indices including BMWP, Whalley, WHPT, Habitat-specific BMWP, AWIC, LIFE and PSI.
EcoHydRology (archived): This package provides a flexible foundation for scientists, engineers, and policy makers to base teaching exercises as well as for more applied use to model complex eco-hydrological interactions, including some SWAT calibration functions.
ecoval: Functions for evaluating and visualizing ecological assessment procedures for surface waters containing physical, chemical and biological assessments in the form of value functions.
EflowStats: Calculates a suite of ecological flow statistics and fundamental properties of daily streamflow for a given set of data. GitHub only package.
EGRET: Exploration and Graphics for RivEr Trends (EGRET): analysis of long-term changes in water quality and streamflow, including the water-quality method Weighted Regressions on Time, Discharge, and Season (WRTDS).
EGRETci: A bootstrap method for estimating uncertainty of water quality trends.
FAdist: Probability distributions that are sometimes useful in hydrology.
fasstr: Functions to tidy, summarize, analyze, trend, and visualize streamflow data. This package summarizes continuous daily mean streamflow data into various daily, monthly, annual, and long-term statistics, completes annual trends and frequency analyses, in both table and plot formats.
FlowScreen: Screens daily streamflow time series for temporal trends and change-points. This package has been primarily developed for assessing the quality of daily streamflow time series. It also contains tools for plotting and calculating many different streamflow metrics.
grwat: Automatic hydrograph separation and daily runoff time series analysis. This package provides various filters to separate baseflow and quickflow. Implements advanced separation technique by Rets et al. (2022) which involves meteorological data to reveal genetic components of the runoff: ground, rain, thaw, and spring (seasonal thaw). High-performance C++17 computation, annual statistics, and supplementary functions for plotting and generating reports.
hydropeak: Detect and characterize sub-daily flow fluctuations based on a framework introduced in Greimel et al. (2016).
hydroroute: Implements the “PeakTrace” method which allows to trace longitudinal hydropeaking waves based on an approach proposed and validated in Greimel et al. (2022).
hydrostats: Calculates a suite of hydrologic indices for daily time series data that are widely used in hydrology and stream ecology.
hydroTSM: Functions for management, analysis, interpolation and plotting of time series used in hydrology and related environmental sciences. In particular, this package is highly oriented to hydrological modelling tasks.
lfstat (archived): Functions to compute and plot statistics described in the “Manual on Low-flow Estimation and Prediction”, published by the World Meteorological Organisation (WMO).
IDF: Intensity-duration-frequency (IDF) curves are a widely used analysis-tool in hydrology to assess extreme values of precipitation [e.g. Mailhot et al., 2007, doi:10.1016/j.jhydrol.2007.09.019]. The package ‘IDF’ provides functions to estimate IDF parameters for given precipitation time series on the basis of a duration-dependent generalized extreme value distribution [Koutsoyiannis et al., 1998, doi:10.1016/S0022-1694(98)00097-3].
hydraulics: Functions for basic hydraulic calculations related to water flow in circular pipes both flowing full (under pressure), and partially full (gravity flow), and trapezoidal open channels. For pressure flow this includes friction loss calculations by solving the Darcy-Weisbach equation for head loss, flow or diameter, plotting a Moody diagram, matching a pump characteristic curve to a system curve, and solving for flows in a pipe network using the Hardy-Cross method. The Darcy-Weisbach friction factor is calculated using the Colebrook (or Colebrook-White equation), the basis of the Moody diagram, the original citation being Colebrook (1939) doi:10.1680/ijoti.1939.13150. For gravity flow, the Manning equation is used, again solving for missing parameters. The derivation of and solutions using the Darcy-Weisbach equation and the Manning equation are outlined in many fluid mechanics texts such as Finnemore and Franzini (2002, ISBN:978-0072432022). For the Manning equation solutions, this package uses modifications of original code from the ‘iemisc’ package by Irucka Embry.
RiverLoad: Implements several of the most popular load estimation procedures, including averaging methods, ratio estimators and regression methods. The package provides an easy-to-use tool to rapidly calculate the load for various compounds and to compare different methods. The package also supplies additional functions to easily organize and analyze the data.
Evapotranspiration: Functions to calculate potential evapotranspiration (PET) and actual evapotranspiration (AET) from 21 different formulations including Penman, Penman-Monteith FAO 56, Priestley-Taylor and Morton models.
humidity: Functions for calculating saturation vapor pressure (hPa), partial water vapor pressure (Pa), relative humidity (%), absolute humidity (kg/m^3), specific humidity (kg/kg), and mixing ratio (kg/kg) from temperature (K) and dew point (K). Conversion functions between humidity measures are also provided.
MBC: Multivariate Bias Correction of Climate Model Outputs. Calibrate and apply multivariate bias correction algorithms for climate model simulations of multiple climate variables.
meteoland: Functions to estimate weather variables at any position of a landscape.
musica: Multiscale Climate Model Assessment. Provides function to compare and analyse time series.
openair: Tools to analyse, interpret and understand air pollution data. Many functions can also be applied to other data, including meteorological and traffic data.
qmap: Empirical adjustment of the distribution of variables originating from (regional) climate model simulations using quantile mapping.
Rainmaker: Instantaneous rainfall data processing for defining event periods, determination of antecedent rainfall conditions and X-hr intensities. GitHub only package.
RGENERATEPREC: The method ‘generate()’ is extended for spatial multi-site stochastic generation of daily precipitation. It generates precipitation occurrence in several sites using logit regression (Generalized Linear Models) and the approach by D.S. Wilks (1998) doi:10.1016/S0022-1694(98)00186-3.
IETD: Computes characteristics of independent rainfall events (duration, total rainfall depth, and intensity) extracted from a sub-daily rainfall time series based on the inter-event time definition (IETD) method. To have a reference value of IETD, it also analyzes/computes IETD values through three methods: autocorrelation analysis, the average annual number of events analysis, and coefficient of variation analysis. Ideal for analyzing the sensitivity of IETD to characteristics of independent rainfall events. Adams B, Papa F (2000) <ISBN: 978-0-471-33217-6>. Joo J et al. (2014) doi:10.3390/w6010045. Restrepo-Posada P, Eagleson P (1982) doi:10.1016/0022-1694(82)90136-6.
berryFunctions: Draw horizontal histograms, color scattered points by 3rd dimension, enhance date- and log-axis plots, zoom in X11 graphics, trace errors and warnings, use the unit hydrograph in a linear storage cascade, convert lists to data.frames and arrays, fit multiple functions.
dssrip: rJava wrapper to HEC-DSSVue to read hydrologic timeseries from HEC-DSS files. Github and Windows only package, due to dependency on HEC-DSS libraries.
GWSDAT: Shiny application for the analysis of groundwater monitoring data, designed to work with simple time-series data for solute concentration and ground water elevation, but can also plot non-aqueous phase liquid (NAPL) thickness if required.
hydrogeo: Contains one function for drawing Piper diagrams (also called Piper-Hill diagrams) of water analyses for major ions.
hydrotoolbox: Read, plot, manipulate and process hydro-meteorological data records (with special features for Argentina and Chile data-sets).
kitagawa: Provides tools to calculate the theoretical hydrodynamic response of an aquifer undergoing harmonic straining or pressurization. There are two classes of models here: (1) for sealed wells, based on the model of Kitagawa et al (2011), and (2) for open wells, based on the models of Cooper et al (1965), Hsieh et al (1987), Rojstaczer (1988), and Liu et al (1989).
MBSStools: Suite of tools for data manipulation and calculations for Maryland DNR MBSS program. GitHub only package.
MODIStsp: Suite of tools to automate the Download and Preprocessing of MODIS Land Products Data. Allows automating the creation of time series of rasters derived from MODIS Satellite Land Products data. It performs several typical preprocessing steps such as download, mosaicking, reprojection and resize of data acquired on a specified time period.
lulcc: Classes and methods for spatially explicit land use change modelling.
wql: Functions to assist in the processing and exploration of data from environmental monitoring programs. Intended for programs that sample approximately monthly, quarterly or annually at discrete stations, a feature of many legacy data sets. Most of the functions should be useful for analysis of similar-frequency time series regardless of the subject matter.
WRTDStidal: An adaptation for estuaries (tidal waters) of weighted regression on time, discharge, and season to evaluate trends in water quality time series.
soilhypfit: Provides functions for efficiently estimating properties of the Van Genuchten-Mualem model for soil hydraulic parameters from possibly sparse soil water retention and hydraulic conductivity data by multi-response parameter estimation methods (Stewart, W.E., Caracotsios, M. Soerensen, J.P. (1992) “Parameter estimation from multi-response data” doi:10.1002/aic.690380502). Parameter estimation is simplified by exploiting the fact that residual and saturated water contents and saturated conductivity are conditionally linear parameters (Bates, D. M. and Watts, D. G.
iemisc: A collection of Irucka Embry’s miscellaneous functions (Engineering Economics, Civil & Environmental/Water Resources Engineering, Geometry, Statistics, GNU Octave length functions, Trigonometric functions in degrees, etc.).
ie2misc: A collection of Irucka Embry’s miscellaneous USGS functions (processing .exp and .psf files, statistical error functions, “+” dyadic operator for use with NA, creating ADAPS and QW spreadsheet files, calculating saturated enthalpy). Irucka created these functions while a Cherokee Nation Technology Solutions (CNTS) United States Geological Survey (USGS) Contractor and/or USGS employee.
The CRAN Spatial task view gives an overview of packages to be used in R to read, visualise, and analyse spatial data. See also the rOpenSci MapTools listing.
lumpR: Functions for a semi-automated approach of the delineation and description of landscape units and partition into terrain components. It can be used for the pre-processing of semi-distributed large-scale hydrological and erosion models using catena-representation (WASA-SED, CATFLOW). GitHub only package.
lakemorpho: Lake morphometry metrics are used by limnologists to understand, among other things, the ecological processes in a lake. The ‘lakemorpho’ package provides the tools to calculate a typical suite of these metrics from an input elevation model and lake polygon.
nhdR: Tools for working with the National Hydrography Dataset, with functions for querying, downloading, and networking both the NHD and NHDPlus datasets.
somspace: somspace is an R package for spatial classification of time series. somspace provides the tools to generate meaningful representations that capture the main spatial patterns of the analyzed time series.
nhdplusTools: Tools for accessing and working with the NHDPlus. Offers utilities for calculating NHDPlus attributes, network navigation, and indexing data to any hydrographic network.
riverdist: Reads river network shape files and computes network distances. Also included are a variety of computation and graphical tools designed for fisheries telemetry research, such as minimum home range, kernel density estimation, and clustering analysis using empirical k-functions with a bootstrap envelope. Tools are also provided for editing the river networks, meaning there is no reliance on external software.
gsw: Provides an interface to the Gibbs ‘SeaWater’ (‘TEOS-10’) C library, version 3.05 (commit ‘f7bfebf44f686034636facb09852f1d5760c27f5’, dated 2021-03-27, available at https://github.com/TEOS-10/GSW-C, which stems from ‘Matlab’ and other code written by members of Working Group 127 of ‘SCOR’/‘IAPSO’ (Scientific Committee on Oceanic Research / International Association for the Physical Sciences of the Oceans).
OCNet: Generate and analyze Optimal Channel Networks (OCNs): oriented spanning trees reproducing all scaling features characteristic of real, natural river networks. As such, they can be used in a variety of numerical experiments in the fields of hydrology, ecology and epidemiology. See Carraro et al. (2020) doi:10.1002/ece3.647. for a presentation of the package; Rinaldo et al. (2014) doi:10.1073/pnas.1322700111 for a theoretical overview on the OCN concept; Furrer and Sain
SBN: Generate Stochastic Branching Networks (‘SBNs’). Used to model the branching structure of rivers.
gwavr: Provides methods to Get Water Attributes Visually in R (‘gwavr’). This allows the user to point and click on areas within the United States and get back hydrological data, e.g. flowlines, catchments, basin boundaries, comids, etc.
epanet2toolkit: Enables simulation of water piping networks using ‘EPANET’. The package provides functions from the ‘EPANET’ programmer’s toolkit as R functions so that basic or customized simulations can be carried out from R. The package uses ‘EPANET’ version 2.2 from Open Water Analytics https://github.com/OpenWaterAnalytics/EPANET/releases/tag/v2.2.
See also the r-hydro project on R-Forge and the Astagneau et al. (2021, HESS) paper discussing R packages for Hydrology modelling.
airGR: Hydrological modelling tools developed at INRAE-Antony (HYCAR Research Unit, France). The package includes several conceptual rainfall-runoff models (GR4H, GR5H, GR4J, GR5J, GR6J, GR2M, GR1A) that can be applied either on a lumped or semi-distributed way. A snow accumulation and melt model (CemaNeige) and the associated functions for their calibration and evaluation.
airGRdatassim: Add-on to the ‘airGR’ package which provides the tools to assimilate observed discharges in daily GR hydrological models using the Ensemble Kalman filter or the Particle filter as described in Piazzi et al. (2021).
airGRteaching: Add-on to the ‘airGR’ package that simplifies its use and is aimed at being used for teaching hydrology. A Shiny GUI is embedded into the package (demo available on sunshine.irstea.fr.
airGRiwrm: Semi-distributed Precipitation-Runoff Modelling based on ‘airGR’ package models integrating human infrastructures and their managements.
bigleaf: Calculation of physical (e.g. aerodynamic conductance, surface temperature), and physiological (e.g. canopy conductance, water-use efficiency) ecosystem properties from eddy covariance data and accompanying meteorological measurements. Calculations assume the land surface to behave like a ‘big-leaf’ and return bulk ecosystem/canopy variables.
boussinesq (archived): Collection of functions for the One-Dimensional Boussinesq Equation (ground-water).
Brook90_R: an R implementation of the 1D-SVAT model Brook90. GitHub only package.
Ecohydmod: Simulates the soil water balance (soil moisture, evapotranspiration, leakage and runoff), rainfall series by using the marked Poisson process and the vegetation growth through the normalized difference vegetation index (NDVI). See Souza et al. (2016).
EcoHydRology (archived): Flexible foundation for scientists, engineers, and policy makers to base teaching exercises as well as for more applied use to model complex eco-hydrological interactions, including some SWAT calibration functions.
geotopbricks: An R Plug-in for the Distributed Hydrological Model GEOtop. The package analyzes raster maps and other information as input/output files from the Hydrological Distributed Model GEOtop.
hydromad: Hydrological Model Assessment and Development - website. GitHub only package.
hydroPSO: Particle Swarm Optimisation (PSO) algorithm for the calibration of environmental and other real-world models that need to be executed from the system console. hydroPSO is model-independent, allowing the user to easily interface any computer simulation model with the PSO calibration engine.
HBV.IANIGLA: This package contains the HBV hydrological model but in modules, allowing the user to build his/her own HBV model. HBV.IANIGLA incorporates routines for clean and debris covered glacier melt simulations. See Toum et al. 2021
kwb.hantush: Calculation groundwater mounding beneath an infiltration basin based on the Hantush (1967) equation. The correct implementation is shown with a verification example based on a USGS report ( page 25).
LWFBrook90R: Simulate Evapotranspiration and Soil Moisture with the SVAT Model LWF-Brook90. See paper Schmidt-Walter et al. (2020).
loadflex: Models and Tools for Watershed Flux Estimates. See paper. GitHub only package.
RavenR: Utilities for processing input and output files associated with the Raven Hydrological Modelling Framework. Includes various plotting functions, model diagnostics, reading output files into xts format, and support for writing Raven input files (rvt, rvh, rvc, etc.).
reservoir: Tools for Analysis, Design, and Operation of Water Supply Storages. Measure 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; generate inflow replicates using parametric and non-parametric models; evaluate inflow persistence using the Hurst coefficient.
RHMS: Hydrologic modelling system is an object oriented tool which enables R users to simulate and analyze hydrologic events. The package proposes functions and methods for construction, simulation, visualization, and calibration of hydrologic systems.
RSAlgaeR: Builds Empirical Remote Sensing Models of Water Quality Variables and Analyzes Long-Term Trends. Assists in processing reflectance data, developing empirical models using stepwise regression and a generalized linear modeling approach, cross- validation, and analysis of trends in water quality conditions (specifically chl-a) and climate conditions using the Theil-Sen estimator.
streamDepletr: Analytical depletion functions used to calculate the impacts of groundwater pumping on one or more streams.
streamMetabolizer: Estimate aquatic photosynthesis and respiration (collectively, metabolism) from time series data on dissolved oxygen, water temperature, depth, and light via inverse modeling. The package assists with data preparation, handles data gaps during modeling, and provides tabular and graphical reports of model outputs. GitHub only package.
swmmr: Functions to connect the widely used Storm Water Management Model (SWMM) of the United States Environmental Protection Agency (US EPA) to R.
telemac: An R interface to the TELEMAC suite for modelling of free surface flow. This includes methods for model initialisation, simulation, and visualisation. So far only the TELEMAC-2D module for 2-dimensional hydrodynamic modelling is implemented.
topmodel: Set of hydrological functions including the hydrological model TOPMODEL, which is based on the 1995 FORTRAN version by Keith Beven. From version 0.7.0, the package is put into maintenance mode.
TUWmodel: Lumped Hydrological Model for Education Purposes: a lumped conceptual rainfall-runoff model, following the structure of the HBV model. The model runs on a daily or shorter time step and consists of a snow routine, a soil moisture routine and a flow routing routine.
VICmodel: Implementation of the Variable Infiltration Capacity (VIC) model, a macroscale hydrologic model that solves full water and energy balances, originally developed by Xu Liang at the University of Washington (UW)
WRSS: Water resources system simulator is a tool for simulation and analysis of large-scale water resources systems. ‘WRSS’ proposes functions and methods for construction, simulation and analysis of primary water resources features (e.g. reservoirs, aquifers, and etc.) based on Standard Operating Policy (SOP).
DWBmodelUN: A tool to hydrologic modelling using the Budyko framework and the Dynamic Water Balance model with Dynamical Dimension Search algorithm to calibrate the model and analyze the outputs from interactive graphics. It allows to calculate the water availability in basins and also some water fluxes represented by the structure of the model. See Zhang, L., N., Potter, K., Hickel, Y., Zhang, Q., Shao (2008) DOI:10.1016/j.jhydrol.2008.07.021 “Water balance modeling over variable time scales based on the Budyko framework - Model development and testing”, Journal of Hydrology, 360, 117–131. See Tolson, B., C., Shoemaker (2007) DOI:10.1029/2005WR004723 “Dynamically dimensioned search algorithm for computationally efficient watershed model calibration”, Water Resources Research, 43, 1–16.
dynatop: An R implementation and enhancement of the Dynamic TOPMODEL semi-distributed hydrological model originally proposed by Beven and Freer (2001) doi:10.1002/hyp.252. The ‘dynatop’ package implements code for simulating models which can be created using the ‘dynatopGIS’ package.
dynatopGIS: A set of algorithms based on Quinn et al.
baytrends: Enable users to evaluate long-term trends using a Generalized Additive Modeling (GAM) approach. The model development includes selecting a GAM structure to describe nonlinear seasonally-varying changes over time, incorporation of hydrologic variability via either a river flow or salinity, the use of an intervention to deal with method or laboratory changes suspected to impact data values, and representation of left- and interval-censored data. The approach has been applied to water quality data in the Chesapeake Bay, a major estuary on the east coast of the United States to provide insights to a range of management- and research-focused questions. Methodology described in Murphy (2019) doi:10.1016/j.envsoft.2019.03.027.
Raquifer: Generate a table of cumulative water influx into hydrocarbon reservoirs over time using un-steady and pseudo-steady state models. Van Everdingen, A. F. and Hurst, W.
swmmr: Functions to connect the widely used Storm Water Management Model (SWMM) of the United States Environmental Protection Agency (US EPA) https://www.epa.gov/water-research/storm-water-management-model-swmm to R with currently two main goals: (1) Run a SWMM simulation from R and (2) provide fast access to simulation results, i.e. SWMM’s binary ‘.out’-files. High performance is achieved with help of Rcpp. Additionally, reading SWMM’s ‘.inp’ and ‘.rpt’ files is supported to glance model structures and to get direct access to simulation summaries.
transfR: A geomorphology-based hydrological modelling for transferring streamflow measurements from gauged to ungauged catchments. Inverse modelling enables to estimate net rainfall from streamflow measurements following Boudhraâ et al. (2018) doi:10.1080/02626667.2018.1425801. Resulting net rainfall is then estimated on the ungauged catchments by spatial interpolation in order to finally simulate streamflow following de Lavenne et al. (2016) doi:10.1002/2016WR018716.
smnet: Fits flexible additive models to data on stream networks, taking account of flow-connectivity of the network. Models are fitted using penalised least squares.
curvenumber: This package is an implementation of the Curve Number, a well established method for the estimation of direct runoff from storm rainfall.
VIC5: The Variable Infiltration Capacity (VIC) model is a macroscale hydrologic model that solves full water and energy balances, originally developed by Xu Liang at the University of Washington (UW). The version of VIC source code used is of 5.0.1 on https://github.com/UW-Hydro/VIC/, see Hamman et al. (2018). Development and maintenance of the current official version of the VIC model at present is led by the UW Hydro (Computational Hydrology group) in the Department of Civil and Environmental Engineering at UW. VIC is a research model and in its various forms it has been applied to most of the major river basins around the world, as well as globally http://vic.readthedocs.io/en/master/Documentation/References/. References: “Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges (1994), A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99(D7), 14415-14428, doi:10.1029/94JD00483”; “Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y. (2018), The Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements for new applications and reproducibility, Geosci. Model Dev., 11, 3481-3496, doi:10.5194/gmd-11-3481-2018”.
DeductiveR: Apply the Deductive Rational Method to a monthly series of flow or precipitation data to fill in missing data. The method is as described in: Campos, D.F., (1984, ISBN:9686194444).
The Environmetrics task view gives an overview of packages used in the analysis of environmental data, encompassing hydrological data, including many statistical approaches used in the ecological sciences. Additionally, packages that help model datasets with extreme values are discussed in the ExtremeValue task view.
CityWaterBalance (archived): Retrieves data and estimates unmeasured flows of water through the urban network. Any city may be modeled with preassembled data, but data for US cities can be gathered via web services using this package and dependencies geoknife and dataRetrieval.
CoSMoS: is an implementation of Papalexiou 2018. CoSMoS generates univariate/multivariate non-Gaussian time series and random fields for environmental and hydroclimatic processes such as precipitation, streamflow, relative humidity, temperature and beyond.
dream: DiffeRential Evolution Adaptive Metropolis (DREAM). Efficient global MCMC even in high-dimensional spaces. R-Forge only package.
fuse: An R package implementing the Framework for Understanding Structural Errors cvitolo.github.io/fuse/. GitHub only package.
hydroApps (archived): Package providing tools for hydrological applications and models developed for regional analysis in Northwestern Italy focused on Flood Frequency Analysis.
hydroGOF: S3 functions implementing both statistical and graphical goodness-of-fit measures between observed and simulated values, mainly oriented to be used during the calibration, validation, and application of hydrological models.
HydroMe: Estimates the parameters in infiltration and water retention models by curve-fitting method. The models considered are those that are commonly used in soil science.
hyfo: Focuses on data processing and visualization in hydrology and climate forecasting. Main function includes data extraction, data downscaling, data resampling, gap filler of precipitation, bias correction of forecasting data, flexible time series plot, and spatial map generation. It is a good pre- processing and post-processing tool for hydrological and hydraulic modellers.
isoWater: Bayesian inference of the source isotope composition or source mixing ratios for water samples that may have experienced evaporation, after Bowen et al. 2018.
NEON-stream-discharge: NEON Stage-Discharge Rating Curve. Instructions to set up a docker container which calculates the stage-discharge rating curve for a site and water year, developed using a Bayesian modeling technique. GitHub only package.
NPRED: Partial informational correlation (PIC) is used to identify the meaningful predictors to the response from a large set of potential predictors. Details of methodologies used in the package can be found in Sharma & Mehrotra (2014), Sharma et al. (2016), and Mehrotra & Sharma (2006).
LPM: Apply Univariate Long Memory Models, Apply Multivariate Short Memory Models To Hydrological Dataset, Estimate Intensity Duration Frequency curve to rainfall series.
meteo: Spatio-temporal geostatistical mapping of meteorological data.
nsRFA: A collection of statistical tools for objective (non-supervised) applications of the Regional Frequency Analysis methods in hydrology.
RMAWGEN: Functions for spatial multi-site stochastic generation of daily time series of temperature and precipitation.
rtop: Interpolation of Data with Variable Spatial Support Geostatistical interpolation of data with irregular spatial support such as runoff related data or data from administrative units.
SCI: Functions for generating Standardized Climate Indices (SCI). SCI is a transformation of (smoothed) climate (or environmental) time series that removes seasonality and forces the data to take values of the standard normal distribution. SCI was originally developed for precipitation. In this case it is known as the Standardized Precipitation Index (SPI).
soilwater: Implements parametric formulas of soil water retention or conductivity curve. At the moment, only Van Genuchten (for soil water retention curve) and Mualem (for hydraulic conductivity) were implemented.
synthesis: Generate synthetic time series from commonly used statistical models, including linear, nonlinear and chaotic systems.
SPEI: A set of functions for computing potential evapotranspiration and several widely used drought indices including the Standardized Precipitation-Evapotranspiration Index (SPEI).
WASP: A wavelet-based variance transformation method is used for system modelling and prediction. It refines predictor spectral representation using Wavelet Theory, which leads to improved model specifications and prediction accuracy. Details of methodologies used in the package can be found in Jiang, Sharma, et al. (2020), Jiang, Rashid, et al. (2020), and Jiang, Sharma, et al. (2021).