Preface
I Background
1
Motivation and objectives
1.1
Motivation
1.2
Objectives
2
R statistical program
2.1
R
2.2
Functions & packages
2.2.1
Function
2.2.2
Arguments
2.2.3
Package
2.3
Documentation
3
GitHub
3.1
DWQ GitHub organization
3.2
DWQ R packages
4
IR process outline
II Demonstration
5
Options for running demos
5.1
Preferred method: R-Studio Cloud
5.2
Local install of R & DWQ packages
5.3
Running Shiny applications via remote server
6
Packages & data downloads
6.1
Install & import DWQ’s R packages
6.2
Download and import data
6.2.1
Data download
6.2.2
Data imports
7
Site validation
7.1
Auto site validation & use and assessment unit assignments
7.2
Manual site validation
8
Data processing
8.1
Data validation
8.1.1
Update detection condition / limit name tables
8.1.2
Determine detection conditions and fill NDs
8.1.3
Update lab/activity & media tables
8.1.4
Apply screening tables
8.1.5
Subset data to desired flag types
8.2
Data prep
8.2.1
Update parameter translation tables
8.2.2
Apply parameter translation table
8.2.3
Subset data to ACCEPT parameters
8.2.4
Criteria & unit assigments
8.2.5
Final data prep step
8.2.6
Write processed data
9
Assessments
9.1
Conventionals (rivers & streams, non-ALU lake surface)
9.1.1
Count exceedances
9.1.2
Assess exceedances
9.2
Toxics
9.2.1
Count exceedances
9.2.2
Assess exceedances
9.3
Lake profiles
9.4
E.coli (not run)
9.5
HFDO (not run)
9.6
Group assessments
10
Rollup
11
Write out assessments
12
Assessment map
III Applications
13
Review and visualization applications
13.1
Assessment review tools
13.1.1
Pre-assessment site validation applications
13.1.2
Assessment & data dashboard
13.1.3
Lake profile dashboard
13.1.4
High frequency DO dashboard
13.2
Examples from other programs
13.2.1
Utah Lake Data Explorer
13.2.2
Great Salt Lake Data Explorer
Utah DWQ’s irTools R package: An automated approach to state-wide water quality assessment
12
Assessment map
https://bookdown.org/jakevl/assessment-map/assessment-map.html
