Open source reporting tools for the PEP Monitoring Collaborative: Beach Pathogens and Dissolved Oxygen

# Open source reporting tools for the PEP Monitoring Collaborative: Beach Pathogens and Dissolved Oxygen
### <a href="mailto:mbeck@tbep.org">Dr. Marcus Beck</a> • <a href="https://twitter.com/fawda123">@fawda123</a> • <a href="https://twitter.com/hashtag/TampaBayOpenSci?src=hashtag_click">#TampaBayOpensci</a>
### Peconic Estuary WQ Monitoring Collaborative, Tampa Bay Estuary Program
### 1/29/2021

---

1. Brief review of PEP reporting tools: `peptools` R package

1. Development of beach pathogen reporting

1. Development of dissolved oxygen reporting

---

1. Vibe check: do we like these approaches?

1. Discuss decision points on pathogen reporting

1. Discuss decision points on dissolved oxygen reporting

---

## `peptools` R PACKAGE

---

## `peptools` R PACKAGE

---

* Consider existing LTM datasets that can be used to assess progress in attaining CCMP goals (*Goal: Clean Waters*)
--

* Spatial divisions of Peconic Estuary for applying numeric thresholds
--

* Relevant thresholds and how to quantify (median vs. mean)

--
* Stoplight graphic for public-facing documents, update annually

---

```r
library(peptools)
dat <- read_pepwq('data/currentdata.xlsx')
show_thrpep(dat, bay_segment = "Western", param = "chla")
```

---

* All segment annual values based on medians, account for censored data (secchi on bottom)

```r
medpep <- anlz_medpep(dat)
medpep$ann
```

```
## # A tibble: 792 x 5
## bay_segment yr val est var 
## <fct> <dbl> <dbl> <chr> <chr>
## 1 Western 2019 3.03 lwr.ci chla 
## 2 Western 2019 4.22 medv chla 
## 3 Western 2019 6.26 upr.ci chla 
## 4 Western 2018 3.89 lwr.ci chla 
## 5 Western 2018 4.82 medv chla 
## 6 Western 2018 6 upr.ci chla 
## 7 Western 2017 3.58 lwr.ci chla 
## 8 Western 2017 5.29 medv chla 
## 9 Western 2017 7.04 upr.ci chla 
## 10 Western 2016 3.14 lwr.ci chla 
## # ... with 782 more rows
```

---

* Provisional targets ([Suffolk Co 2019 SWP](https://suffolkcountyny.gov/Departments/Health-Services/Environmental-Quality#SubWWPlan)) for water clarity and secchi depth

```r
peptargets
```

```
## # A tibble: 3 x 4
## bay_segment name sd_thresh chla_thresh
## <fct> <chr> <dbl> <dbl>
## 1 Western Western 6.5 5.5
## 2 Central Central 6.5 5.5
## 3 Eastern Eastern 6.5 5.5
```

---

* Apply targets to annual medians

```r
anlz_attainpep(medpep)
```

```
## # A tibble: 132 x 4
## bay_segment yr chla_sd outcome
## <fct> <dbl> <chr> <chr> 
## 1 Western 2019 2_3 red 
## 2 Western 2018 2_3 red 
## 3 Western 2017 2_3 red 
## 4 Western 2016 0_3 yellow 
## 5 Western 2015 0_2 yellow 
## 6 Western 2014 0_0 green 
## 7 Western 2013 1_1 yellow 
## 8 Western 2012 1_2 yellow 
## 9 Western 2011 1_2 yellow 
## 10 Western 2010 3_3 red 
## # ... with 122 more rows
```

---

* Annual categories depend on both a __duration__ and __magnitude__ of exceedance
* Jointly considers chlorophyll and water clarity endpoints
--

.center[
.footnote[[TBEP tech report #04-00](https://drive.google.com/file/d/1juhfptqA4R-Bq_XfW6nOhqFxJSorGkfq/view?usp=drivesdk)]
]

---

* Annual categories depend on both a __duration__ and __magnitude__ of exceedance
* Jointly considers chlorophyll and water clarity endpoints

.center[
.footnote[[TBEP tech report #04-00](https://drive.google.com/file/d/1juhfptqA4R-Bq_XfW6nOhqFxJSorGkfq/view?usp=drivesdk)]
]

---

* Translate segment water quality conditions into annual reporting categories to inform/prioritize management actions towards CCMP goals
--

* In Tampa...

__Stay the Course__: Continue planned projects. Report data via annual progress reports and Baywide Environmental Monitoring Report.

__Caution__: Review monitoring data and nitrogen loading estimates. Begin/continue TAC and Management Board development of specific management recommendations.

__On Alert__: Finalize development and implement appropriate management actions to get back on track.

---

```r
show_matrixpep(dat, asreact = TRUE, nrows = 8)
```

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---

```r
show_plotlypep(rawdat, bay_segment = 'Western')
```

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(length)","type":"scatter","mode":"lines","line":{"width":0.377952755905512,"color":"rgba(0,0,0,1)","dash":"solid"},"fill":"toself","fillcolor":"rgba(255,0,0,1)","hoveron":"fills","name":"red","legendgroup":"red","showlegend":false,"xaxis":"x","yaxis":"y2","hoverinfo":"text","frame":null},{"x":[2014.5,2015.5,2015.5,2014.5,2014.5,null,2003.5,2004.5,2004.5,2003.5,2003.5,null,2001.5,2002.5,2002.5,2001.5,2001.5,null,2000.5,2001.5,2001.5,2000.5,2000.5,null,1998.5,1999.5,1999.5,1998.5,1998.5,null,1993.5,1994.5,1994.5,1993.5,1993.5],"y":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],"text":"Result: 2, Exceedance: small (size), long 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3, Exceedance: large (size), long (length)","type":"scatter","mode":"lines","line":{"width":0.377952755905512,"color":"rgba(0,0,0,1)","dash":"solid"},"fill":"toself","fillcolor":"rgba(255,0,0,1)","hoveron":"fills","name":"red","legendgroup":"red","showlegend":false,"xaxis":"x","yaxis":"y2","hoverinfo":"text","frame":null},{"x":[2017.5,2018.5,2018.5,2017.5,2017.5,null,2016.5,2017.5,2017.5,2016.5,2016.5],"y":[0.5,0.5,1.5,1.5,0.5,null,0.5,0.5,1.5,1.5,0.5],"text":"Result: 3, Exceedance: large (size), NA 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---

* 28 swimming/bathing beaches in the Peconic Estuary
--

* *Enterococcus* concentrations monitored by SCDHS
--

* Beaches are closed if concentrations are high
--

* Data can be summarized to understand __relative risk__ of exposure
--

.center[
.footnote[[https://tbep-tech.github.io/peptools/articles/pathogens.html](https://tbep-tech.github.io/peptools/articles/pathogens.html)]
]

---

* Data are available as a spreadsheet [here](https://gisportal.suffolkcountyny.gov/gis/home/item.html?id=025cb4dadb57413980dbd7e760b94da8)

---

* Import the data with [`read_pepent()`](https://tbep-tech.github.io/peptools/reference/read_pepent.html)

```r
path <- system.file('extdata', 'enterodata.xlsx', 
 package = 'peptools')
entdat <- read_pepent(path)
head(entdat)
```

```
## # A tibble: 6 x 5
## Name FieldNum Date value status
## <chr> <chr> <dttm> <dbl> <chr> 
## 1 Alberts Landing Beach EH7 2010-06-29 09:47:00 4 "<" 
## 2 Alberts Landing Beach EH7 2010-07-27 09:49:00 4 "<" 
## 3 Alberts Landing Beach EH7 2010-08-13 09:18:00 28 "" 
## 4 Alberts Landing Beach EH7 2011-06-22 10:21:00 4 "<" 
## 5 Alberts Landing Beach EH7 2011-07-20 10:57:00 4 "<" 
## 6 Alberts Landing Beach EH7 2011-08-17 11:14:00 4 "<"
```

---

* Summarize the data with [`anlz_entpep()`](https://tbep-tech.github.io/peptools/reference/anlz_entpep.html)
* This creates a count of exceedances in each 24 hour period for each year and each beach
--

```r
entsum <- anlz_entpep(entdat)
head(entsum)
```

```
## # A tibble: 6 x 5
## Name yr samples exceedances proexceedances
## <chr> <dbl> <int> <int> <dbl>
## 1 Alberts Landing Beach 2010 3 0 0
## 2 Alberts Landing Beach 2011 3 0 0
## 3 Alberts Landing Beach 2012 4 0 0
## 4 Alberts Landing Beach 2013 3 0 0
## 5 Alberts Landing Beach 2014 4 0 0
## 6 Alberts Landing Beach 2015 3 0 0
```

---

* Plot the results with [`show_entmatrix()`](https://tbep-tech.github.io/peptools/reference/show_entmatrix.html)

```r
show_entmatrix(entdat)
```

---

* This plot communicates exposure risk, NOT beach closures
--

* Exceedances based on concentrations above 104 cfu/100 mL
--

* We can change this...

---

* Changing the default arguments...

```r
show_entmatrix(entdat, thr = 35)
```

---

* Two continuous USGS monitoring stations in Peconic Estuary
--

* Peconic River (01304562) and Orient Harbor (01304200)
--

* Data can be summarized to understand hypoxia frequency/duration
--

.center[
.footnote[[https://tbep-tech.github.io/peptools/articles/dissolvedoxygen.html](https://tbep-tech.github.io/peptools/articles/dissolvedoxygen.html)]
]

---

* Data can be downloaded directly from USGS data source with [`read_pepdo()`](https://tbep-tech.github.io/peptools/reference/read_pepdo.html)

```r
exdat <- read_pepdo(site = c('01304562', '01304200'), 
 nms = c('Peconic R.', 'Orient Harbor'), 
 startDate = '2013-01-01', endDate = '2020-06-30')
head(exdat)
```

```
##            site            DateTime do_mgl
## 1 Orient Harbor 2013-01-01 00:00:00   11.2
## 2 Orient Harbor 2013-01-01 00:06:00   11.2
## 3 Orient Harbor 2013-01-01 00:12:00   11.2
## 4 Orient Harbor 2013-01-01 00:18:00   11.2
## 5 Orient Harbor 2013-01-01 00:24:00   11.2
## 6 Orient Harbor 2013-01-01 00:30:00   11.2
```

---
class: left, top

---
class: left, top

---

* DO data have diurnal and seasonal variation, how can we summarize this to quantify hypoxia stress?
--

* Hypoxia can have both acute and chronic impacts, how can we summarize the DO data to express magnitude and duration of hypoxia?

---

* Summarize the data with [`anlz_domopep()`](https://tbep-tech.github.io/peptools/reference/anlz_domopep.html)
--

* Gets the following for each month:
     * Mean daily DO
     * Proportion of days with low DO (magnitude)
     * Max run of days with low DO (duration)

---

* Summarize the data with [`anlz_domopep()`](https://tbep-tech.github.io/peptools/reference/anlz_domopep.html)

```r
anlz_domopep(dodat, thr = 3)
```

```
## # A tibble: 189 x 6
## site yr mo do_mgl below_ave below_maxrun
## * <fct> <dbl> <ord> <dbl> <dbl> <dbl>
## 1 Peconic River 2013 Jan 11.6 0 0
## 2 Peconic River 2013 Feb 11.9 0 0
## 3 Peconic River 2013 Mar 11.7 0 0
## 4 Peconic River 2013 Apr 9.55 0 0
## 5 Peconic River 2013 May 7.90 0 0
## 6 Peconic River 2013 Jun 5.73 0.3 5
## 7 Peconic River 2013 Jul 3.12 1 27
## 8 Peconic River 2013 Aug 3.13 1 24
## 9 Peconic River 2013 Sep 4.81 0.655 6
## 10 Peconic River 2013 Oct 6.03 0.348 7
## # ... with 179 more rows
```

---

* Plot the results with [`show_domatrix()`](https://tbep-tech.github.io/peptools/reference/show_domatrix.html)

```r
show_domatrix(dodat, thr = 3, show = 'below_ave')
```

---

* Plot the results with [`show_domatrix()`](https://tbep-tech.github.io/peptools/reference/show_domatrix.html)

```r
show_domatrix(dodat, thr = 3, show = 'below_maxrun')
```

---

* Plot the results with [`show_domatrix()`](https://tbep-tech.github.io/peptools/reference/show_domatrix.html)

```r
show_domatrix(dodat, thr = 4.8, show = 'below_ave')
```

---

* The summaries show relative hypoxia stress between locations, with stress quantified as magnitude or duration
--

* What is the relevance of the threshold to a meaningful endpoint? 
--

* Are there breakpoints we need to consider?
--

* What can we reasonably say about the spatial extent of hypoxia?

---

* Pathogens vignette: [link](https://tbep-tech.github.io/peptools/articles/pathogens.html)
* Dissolved oxygen vignette: [link](https://tbep-tech.github.io/peptools/articles/dissolvedoxygen.html)
* Package overview vignette: [link](https://tbep-tech.github.io/peptools/articles/Introduction.html)
* `peptools` package website: [link](https://tbep-tech.github.io/peptools/)
* `peptools` GitHub source: [link](https://github.com/tbep-tech/peptools)

---

1. Vibe check: do we like these approaches?

1. Discuss decision points on pathogen reporting

1. Discuss decision points on dissolved oxygen reporting