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index.Rmd
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---
title: "Meta-repository for Turner et al., 2021 / 'Comparison of potential drinking water source contamination across one hundred U.S. cities'"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
**Comparison of potential drinking water source contamination across one hundred U.S. cities**
Sean W. D. Turner<sup>1\*</sup>, Jennie S. Rice<sup>1\*</sup>, Kristian D. Nelson<sup>1\*</sup>, Chris R. Vernon<sup>1\*</sup>, Ryan McManamay<sup>2\*</sup>, Kerim Dickson<sup>3\*</sup>, Landon Marston<sup>4\*</sup>
<sup>1 </sup> PNNL
<sup>2 </sup> Baylor
<sup>3 </sup> Kansas State
<sup>4 </sup> Virginia Tech
\* corresponding author: sean.turner@pnnl.gov
### Article
Turner, S.W.D., Rice, J., Nelson, K., Vernon, C., McManamay, R., Dickson, K., and Marston, L. (2021). Comparison of potential drinking water contamination across one hundred U.S. cities, *Nature Communications* **12**, 7254. https://doi.org/10.1038/s41467-021-27509-9
### Contributing modeling software
| model | Version | Repository Link | DOI |
|:------|:--------|:----------------|:----|
| `gamut` | 0.1.0 | immm-sfa.github.io/gamut/ | [](https://doi.org/10.5281/zenodo.5590217) |
### Input data
| Dataset | Version | DOI |
|:------|:--------|:----------------|
| UWSCatCH | 1.0 | [](https://doi.org/10.5281/zenodo.4315195)|
| Geospatial Input Datasets for Urban Teleconnections Analysis | 1.0 | [](https://doi.org/10.5281/zenodo.4662993)|
### Results: PPCS metrics and water supply contributions for 116 cities
[](https://doi.org/10.5281/zenodo.5813878)
## Example: use `gamut` to compute PPCS and other metrics
To download the `gamut` tool, use:
```{r, eval=FALSE}
devtools::install_github('IMMM-SFA/gamut')
```
If you have any trouble installing, please the instructions here: https://github.com/IMMM-SFA/gamut. Still no luck? Open an [issue](https://github.com/IMMM-SFA/gamut/issues).
Next download the input data linked above ("Geospatial Input Datasets for Urban Teleconnections Analysis") and save to a local directory of your choice.
```{r}
my_gamut_data_dir <- "my_directory/Geospatial_Input_Datasets"
```
```{r, show = FALSE, echo = FALSE}
my_gamut_data_dir <- "../../../../Large data files/Geospatial_Input_Datasets/"
```
Here's an example for two cities:
(Due to the high resolution of some of the geospatial data used in `gamut`, this may take several minutes!)
```{r, warning = FALSE}
library(gamut)
count_watershed_teleconnections(
data_dir = my_gamut_data_dir,
cities = c("Portland | OR", "New York | NY")
) -> city_metrics
head(city_metrics)
```
Check [here](https://github.com/IMMM-SFA/gamut) for definitions of each metric.