EGRET
An R-package for the analysis of long-term changes in water quality and streamflow, including the water-quality method Weighted Regressions on Time, Discharge, and Season (WRTDS). https://doi-usgs.github.io/EGRET/
Install / Use
/learn @DOI-USGS/EGRETREADME
EGRET <img src="man/figures/egret-02.png" alt="EGRET" style="width:90px;height:auto;" align="right" class="logo" />
Exploration and Graphics for RivEr Trends (EGRET): An R-package for
the analysis of long-term changes in water quality and streamflow,
including the water-quality method Weighted Regressions on Time,
Discharge, and Season (WRTDS).
Look for new and improved documentation here: https://doi-usgs.github.io/EGRET/
The link for the official USGS publication user guide is here:
https://pubs.usgs.gov/tm/04/a10/
A companion package EGRETci
implements a set of approaches to the analysis of uncertainty associated
with WRTDS trend analysis.
If you are familiar with the traditional EGRET workflow, check out the
[Overview and
Updates](https://doi-usgs.github.io/EGRET/articles/Overview.html to
see how all the latest updates relate.
Recent introduction to WRTDS and the EGRET package at the 12th
National Monitoring Conference April 19, 2021:
Package Installation
To install the EGRET package, you must be using R 3.0 or greater and run the following command:
install.packages("EGRET")
Background:
Evaluating long-term changes in river conditions (water quality and
discharge) is an important use of hydrologic data. To carry out such
evaluations, the hydrologist needs tools to facilitate several key steps
in the process: acquiring the data records from a variety of sources,
structuring it in ways that facilitate the analysis, routines that will
process the data to extract information about changes that may be
happening, and graphical techniques that can display findings about
change. The R package EGRET (Exploration and Graphics for RivEr
Trends) was developed for carrying out each of these steps in an
integrated manner. It is designed to accept easily data from three
sources: U.S. Geological Survey hydrologic data, Water Quality Portal
Data (currently including U.S. Environmental Protection Agency (EPA)
STORET data, and USDA STEWARDS data), and user-supplied flat files. The
EGRET package has components oriented towards the description of
long-term changes in streamflow statistics (high flow, average flow, and
low flow) as well as changes in water quality. For the water-quality
analysis, it uses Weighted Regressions on Time, Discharge and Season
(WRTDS) to describe long-term trends in both concentration and flux.
EGRET also creates a wide range of graphical presentations of the
water-quality data and of the WRTDS results. The following report serves
as a user guide, providing detailed guidance on installation and use of
the software, documentation of the analysis methods used, as well as
guidance on some of the kinds of questions and approaches that the
software can facilitate.
EGRET includes statistics and graphics for streamflow history, water
quality trends, and the statistical modeling algorithm Weighted
Regressions on Time, Discharge, and Season (WRTDS). Please see the
official EGRET User Guide for more information on the EGRET package:
https://doi.org/10.3133/tm4A10 The best ways to learn about the WRTDS approach is to read the User Guide and two journal articles. These articles are available, for free, from the journals in which they were published. The first relates to nitrate and total phosphorus data for 9 rivers draining to Chesapeake Bay. The URL is:
https://onlinelibrary.wiley.com/doi/full/10.1111/j.1752-1688.2010.00482.x.
The second is an application to nitrate data for 8 monitoring sites on the Mississippi River or its major tributaries. The URL is:
https://pubs.acs.org/doi/abs/10.1021/es201221s
For a thorough discussion of the generalized flow normalization method implemented in the EGRET enhancements, see the paper: “Tracking changes in nutrient delivery to western Lake Erie: Approaches to compensate for variability and trends in streamflow” (doi:10.1016/j.jglr.2018.11.012).
Sample Workflow
WRTDS on the Choptank River at Greensboro MD, for Nitrate:
library(EGRET)
############################
# Gather discharge data:
siteID <- "01491000" #Choptank River at Greensboro, MD
startDate <- "" #Gets earliest date
endDate <- "2011-09-30"
# Gather sample data:
parameter_cd<-"00631" #5 digit USGS code
Sample <- readNWISSample(siteID,parameter_cd,startDate,endDate)
#Gets earliest date from Sample record:
#This is just one of many ways to assure the Daily record
#spans the Sample record
startDate <- min(as.character(Sample$Date))
# Gather discharge data:
Daily <- readNWISDaily(siteID,"00060",startDate,endDate)
# Gather site and parameter information:
# Here user must input some values for
# the default (interactive=TRUE)
INFO<- readNWISInfo(siteID,parameter_cd)
INFO$shortName <- "Choptank River at Greensboro, MD"
# Merge discharge with sample data:
eList <- mergeReport(INFO, Daily, Sample)
library(EGRET)
# Sample data included in package:
eList <- Choptank_eList
boxConcMonth(eList)
boxQTwice(eList)
plotConcTime(eList)
plotConcQ(eList)
multiPlotDataOverview(eList)
# Run WRTDS model:
eList <- modelEstimation(eList)
#>
#> first step running estCrossVal may take about 1 minute
#> estCrossVal % complete:
#> 0 1 2 3 4 5 6 7 8 9 10
#> 11 12 13 14 15 16 17 18 19 20
#> 21 22 23 24 25 26 27 28 29 30
#> 31 32 33 34 35 36 37 38 39 40
#> 41 42 43 44 45 46 47 48 49 50
#> 51 52 53 54 55 56 57 58 59 60
#> 61 62 63 64 65 66 67 68 69 70
#> 71 72 73 74 75 76 77 78 79 80
#> 81 82 83 84 85 86 87 88 89 90
#> 91 92 93 94 95 96 97 98 99
#> Next step running estSurfaces with survival regression:
#> Survival regression (% complete):
#> 0 1 2 3 4 5 6 7 8 9 10
#> 11 12 13 14 15 16 17 18 19 20
#> 21 22 23 24 25 26 27 28 29 30
#> 31 32 33 34 35 36 37 38 39 40
#> 41 42 43 44 45 46 47 48 49 50
#> 51 52 53 54 55 56 57 58 59 60
#> 61 62 63 64 65 66 67 68 69 70
#> 71 72 73 74 75 76 77 78 79 80
#> 81 82 83 84 85 86 87 88 89 90
#> 91 92 93 94 95 96 97 98 99
#> Survival regression: Done
#eList:
plotConcTimeDaily(eList)
#> plotGenConc = TRUE requires running WRTDSKalman
#> on eList. Switching to WRTDS concentration.
plotFluxTimeDaily(eList)
#> plotGenFlux = TRUE requires running WRTDSKalman
#> on eList. Switching to WRTDS concentration.
plotConcPred(eList)
plotFluxPred(eList)
plotResidPred(eList)
plotResidQ(eList)
plotResidTime(eList)
boxResidMonth(eList)
boxConcThree(eList)
plotConcHist(eList)
plotFluxHist(eList)
# Multi-line plots:
date1 <- "1985-09-01"
date2 <- "1997-09-01"
date3 <- "2010-09-01"
qBottom<-0.2
qTop<-10
plotConcQSmooth(eList, date1, date2, date3, qBottom, qTop,
concMax=2,legendTop = 0.85)
q1 <- 2
q2 <- 10
q3 <- 20
centerDate <- "07-01"
yearEnd <- 1980
yearStart <- 2010
plotConcTimeSmooth(eList, q1, q2, q3, centerDate, yearStart, yearEnd, legendTop = 0.55, legendLeft = 1990)
# Multi-plots:
fluxBiasMulti(eList)
#Contour plots:
clevel<-seq(0,2,0.5)
yearStart <- 1980
yearEnd <- 2010
plotContours(eList, yearStart,yearEnd,qBottom=0.5,
qTop = 20, contourLevels = clevel)
plotDiffContours(eList, year0 = 1990,
year1 = 2010,
qBottom = 0.5,
qTop = 20,
maxDiff = 0.6)
Sample workflow for a flowHistory application for the entire record
library(EGRET)
# Flow history analysis
# Gather discharge data:
siteID <- "01491000" #Choptank River at Greensboro, MD
startDate <- "" # Get earliest date
endDate <- "" # Get latest date
Daily <- readNWISDaily(siteID, "00060", startDate, endDate)
#> GET: https://waterservices.usgs.gov/nwis/dv/?site=01491000&format=rdb%2C1.0&ParameterCd=00060&StatCd=00003&startDT=1851-01-01
#> There are 28235 data points, and 28235 days.
# Gather site and parameter information:
# Here user must input some values for
# the default (interactive=TRUE)
INFO <- readNWISInfo(siteID, "00060")
#> GET: https://waterservices.usgs.gov/nwis/site/?siteOutput=Expanded&format=rdb&site=01491000
#> Your site for streamflow data is:
#> 01491000 .
#> Your site name is CHOPTANK RIVER NEAR GREENSBORO, MD
#> but you can modify this to a short name in a style you prefer.
#> This na
