The 30 Day Chart Challenge with the USGS VizLab
A collection of data viz for the 2023 30 Day Chart Challenge
Data visualization practitioners around the world participated in the 30-Day Chart Challenge by creating new charts daily throughout the month of April. The challenge, hosted on Twitter, is a month-long open-participation opportunity that encourages anyone to share compelling data visualizations based on pre-organized themes. Participants create charts to fit into daily themes which are neatly separated into five categories: comparisons, distributions, relationships, timeseries, and uncertainties.
We enjoyed participating in this challenge for the third year in a row, as it’s a fun and engaging way for us to share our water science while learning new data visualization skills along the way. Throughout the month we shared thirty new charts featuring the work of hydrologists, data scientists, and science communicators at USGS as well as some of our Department of the Interior colleagues at United States Fish and Wildlife Service. A big thank you to all our contributors!
Scroll to see all our contributions to the chart challenge. We’ve documented the code behind these charts on github at https://github.com/DOI-USGS/vizlab-chart-challenge-23. Follow @USGS_DataSci on Twitter to see future data visualizations, and check out the USGS VizLab portfolio.
Day 1, Comparisons: Part-to-Whole by Mandie Carr
Most saline water is stored in oceans but can also be found in lakes, wetlands, and parts of aquifers.
— USGS Data Science (@USGS_DataSci) April 1, 2023
Only 2-3% of all water on Earth is freshwater.
💪 Kicking off DAY 1 of #30DayChartChallenge with #DataViz by Mandie Carr 🎉 pic.twitter.com/XoJSkpVKpM
Day 2, Comparisons: Waffle by Elmera Azadpour
Waffle charts show regional patterns of 4 common drinking water contaminants. @USGS well data: https://t.co/f9Eyeks1hj
— USGS Data Science (@USGS_DataSci) April 2, 2023
Learn more about contaminant concentrations at: https://t.co/T3uVhXKbtB#30DayChartChallenge 📅 #rstats
Day 2 Waffle by Elmera Azadpour pic.twitter.com/CAocXGsohP
Day 2, Comparisons: Waffle by Hayley Corson-Dosch
As of 2015, total DAILY U.S. water use was 322 billion gallons.
— USGS Data Science (@USGS_DataSci) April 2, 2023
Thermoelectric power used 133 billion gallons daily (41%) to generate electricity with steam-driven turbine generators.
Day 2 of #30DayChartChallenge 📅 #DataViz by Hayley Corson-Dosch #rstats pic.twitter.com/rVNWzrxPLz
Day 3, Comparisons: Fauna/flora by Cee Nell
Spring is coming! Comparing current spring leaf out timing to the 30-year average with data from @USANPN for #Day3 of #30DayChartChallenge 📅 flora #rstats pic.twitter.com/5BfWT5Yrej
— USGS Data Science (@USGS_DataSci) April 3, 2023
Day 3, Comparisons: Fauna/flora by Althea Archer
Urban trees provide important services such as energy & water savings through shade & increased infiltration
— USGS Data Science (@USGS_DataSci) April 3, 2023
This #DataViz used a combo of hand-drawn illustrations #rstats to take an #art approach to the chart challenge
Day 3 of #30DayChartChallenge 📅 by Althea Archer#SciComm pic.twitter.com/8bfIbdMZfu
Day 4, Comparisons: Historical by Althea Archer
Not your parents’... streamflow 💧
— USGS Data Science (@USGS_DataSci) April 4, 2023
Using 100 years of @USGS #streamgage data, we show minimum annual streamflow across generations. How does today compare to the “Silent Generation" across #CONUS?#Day4 | #30DayChartChallenge Historic 📅 | #DataViz by Althea Archer pic.twitter.com/GpqDzPjM30
Day 4, Comparisons: Historical by Elmera Azadpour & Cee Nell
March #streamflow conditions across the U.S.🌧☀ compared to the historical record
— USGS Data Science (@USGS_DataSci) April 4, 2023
Storms brought wetter than normal conditions across much of the U.S., while Northwest & Northern Plains remain dry.#Day4 of #30DayChartChallenge 📅 Historical #rstats pic.twitter.com/6mpxaV4uxS
Day 6, Comparisons: OWID Data by Hayley Corson-Dosch
Historic events stand out in the record of lives lost:
— USGS Data Science (@USGS_DataSci) April 6, 2023
- 1980 heat wave
- 1980 Mt. Saint Helens eruption
- 2005 Hurricane Katrina
- 2014 Oso Mudslide
- 2018 Camp Fire
Charts on the right show events by disaster type.#Day6 #30DayChartChallenge 📅 #rstats pic.twitter.com/8zZqfxAHXr
Day 7, Distributions: Hazards by Matt Conlon
Using gage height data, we created an animated inundation map to show flooding of the Schuylkill River due to Hurricane Ida.#DataViz made with #rayshader, which allows for 2- and 3D rendering of geospatial data.#Day7 | hazards | #30DayChartChallenge 📅 #rstats pic.twitter.com/SNAbTWou33
— USGS Data Science (@USGS_DataSci) April 7, 2023
Day 8, Distributions: Humans by Hayley Corson-Dosch
How are we using water? 💧
— USGS Data Science (@USGS_DataSci) April 8, 2023
We show eight water use categories across #CONUS, where western water is largely used for irrigation, and eastern water is primarily used for public supply & industry. #Day8 | #30DayChartChallenge Humans 📅| #DataViz by Hayley Corson-Dosch #rstats pic.twitter.com/W4selTSqjo
Day 9, Distributions: High/low by Althea Archer
A tale of two winters ❄️
— USGS Data Science (@USGS_DataSci) April 9, 2023
Map of #CONUS coupled with lollipop charts show high snow across much of the West and low snow across the East in February.#Day9 | high/low | #30DayChartChallenge 📅 by Althea Archer #rstats#OpenData from @NSIDC https://t.co/rxxkQzoqgP pic.twitter.com/tIGuJtvFjQ
Day 11, Distributions: Circular by Jay Hariharan
When you think ‘lake’ you might envision a circular body of water 🔵, but #DYK that most lakes aren’t very circular?
— USGS Data Science (@USGS_DataSci) April 11, 2023
The circularity of named lakes in the U.S. are shown here. Lake Cumberland? Def not a circle 😅#Day11 circular #30DayChartChallenge 📅 by Jay Hariharan #python pic.twitter.com/rZnHgMyKbt
Day 13, Distributions: Pop Culture by Anthony Martinez
Wildfires can degrade water quality in watersheds that provide public water supplies.
— USGS Data Science (@USGS_DataSci) April 13, 2023
From 2000-2020, watersheds supplying as many 2 million consumers were affected by wildfires.#Day13 | pop culture | #30DayChartChallenge 📅 by Anthony Martinez #rstats chart inspired by Tron pic.twitter.com/l6cHFF05lU
Day 13, Distributions: Pop Culture by Elmera Azadpour
Thirty years of daily average streamflow in cubic feet per second on the Rio Grande River, New Mexico, inspired by the style of a classic album cover.#Day13 | pop culture | #30DayChartChallenge 📅 by Elmera Azadpour #rstats#OpenData from @USGS: https://t.co/DESoOW5Msf pic.twitter.com/jN5bNbJOax
— USGS Data Science (@USGS_DataSci) April 13, 2023
Day 14, Relationships: New Tool by Elmera Azadpour
Using @GoogleColab & #geemap, we created a split-panel map for inspecting timeseries images of @USGSLandsat and #NLCD from 2001-2016 for Great Salt Lake#Day14 | new tool | #30DayChartChallenge 📅 by Elmera Azadpour
— USGS Data Science (@USGS_DataSci) April 14, 2023
View notebook here: https://t.co/k54CC7Ndhn pic.twitter.com/rCWx1qMqdr
Day 15, Relationships: Positive/negative by Althea Archer
We’re half-way through the #30DayChartChallenge!
— USGS Data Science (@USGS_DataSci) April 15, 2023
In March, the western U.S. remained snowier than normal (positive), while the eastern U.S. continued to stay less snowy than normal (negative).
Day 15 | Positive/Negative #DataViz #rstats by Althea Archer pic.twitter.com/1ZARcVCWq6
Day 17, Relationships: Networks by Hayley Corson-Dosch
#DYK that river networks are mostly made up of small, first-order streams? These headwater streams provide critical habitat and play an important role in nutrient cycling.#Day17 | Networks | #30DayChartChallenge 📅#DataViz by Hayley Corson-Dosch #RStats pic.twitter.com/BHHxhJhHXG
— USGS Data Science (@USGS_DataSci) April 18, 2023
Day 19, Timeseries: Anthropocene by Margaret Jaenicke
Glen Canyon Dam was constructed between 1956-66 on the Colorado River north of the Grand Canyon, changing streamflow & the landscape.
— USGS Data Science (@USGS_DataSci) April 19, 2023
See historical streamflow in the Grand Canyon ⬇️#Day19 | Anthropocene | #30DayChartChallenge 📅#Highcharts #DataViz by Margaret Jaenicke pic.twitter.com/CwxVWffkqD
Day 20, Timeseries: Correlation by Althea Archer
Many fish, like brook trout, rely on optimal water temperatures 🐟💧
— USGS Data Science (@USGS_DataSci) April 20, 2023
This relationship between air & stream temperature is critical for fish habitat health.#Day20 | Correlation | #30DayChartChallenge 📅#rstats #DataViz by Althea Archer
Data from: https://t.co/wbK0rjfs3H pic.twitter.com/FmoYRDf0bq
Day 21, Timeseries: Down/Upwards by Althea Archer
Ocean currents cycle between warmer (el Niño) and cooler (la Niña) periods.
— USGS Data Science (@USGS_DataSci) April 21, 2023
In the U.S., el Niño causes wetter weather in the south and la Niña causes wetter weather in the north.#Day21 | Down/Upwards |#30DayChartChallenge 📅#rstats #watercolor #DataViz by Althea Archer pic.twitter.com/86Cx3upeIF
Day 21, Timeseries: Down/Upwards by Natalie Schmer
#DYK water temperature influences biological and chemical activity in stream ecosystems?
— USGS Data Science (@USGS_DataSci) April 21, 2023
Long-term monitoring allows us to identify changes and effectively manage our water resources.#Day21 | Down/Upwards |#30DayChartChallenge 📅#rstats #DataViz by Natalie Schmer pic.twitter.com/tr54RQ3O9C
Day 22, Timeseries: Green Energy by Mandie Carr
As of 2020, wind power has overtaken hydropower as the leading renewable energy source in the U.S. 💨
— USGS Data Science (@USGS_DataSci) April 22, 2023
Bioenergy and geothermal energy generation did not change much from 2000-2022. #Day22 | Green energy | #30DayChartChallenge 📅 #rstats #DataViz by Mandie Carr #EarthDay pic.twitter.com/cx1M0kz8rh
Day 23, Timeseries: Tiles by Hayley Corson-Dosch
The nation’s water use has declined since 1985 💧, but patterns of use vary by state. Read more about trends in water use here: https://t.co/EUcpFnnZM7 #Day23 | Tiles | #30DayChartChallenge 📅 #rstats #DataViz by Hayley Corson-Dosch pic.twitter.com/GtWqTLjirM
— USGS Data Science (@USGS_DataSci) April 23, 2023
Day 25, Uncertainties: Global Change by Katie Nuessly
Once spanning 600 million acres, the Central Grasslands are the world’s most imperiled ecosystem. Due to land use change, invasives, & climate change, grasslands are being lost at fast rate @USFWS #Day25| Global Change | #30DayChartChallenge 📅#rstats #DataViz by Katie Nuessly pic.twitter.com/207mGwDlAJ
— USGS Data Science (@USGS_DataSci) April 25, 2023
Day 26, Uncertainties: Local change by Ellie White
How will #ClimateChange affect the timing of fish spawning? 🐟
— USGS Data Science (@USGS_DataSci) April 26, 2023
Charts show projected impact of four @IPCC_CH scenarios on spawn timing of American Shad & Striped Bass. Data: Hudson River Estuary#Day26 | local change | #30DayChartChallenge 📅#rstats #DataViz by Ellie White pic.twitter.com/hRRKCpCF32
Day 28, Uncertainties: Trend by Julie Padilla
In 2023, ice cover on the Great Lakes was 59% lower than the average over the last 50 years.
— USGS Data Science (@USGS_DataSci) April 28, 2023
Lake Superior was 67% below average while Lake Ontario was 45% below.#Day28 | trend | #30DayChartChallenge 📅 #rstats #DataViz by Julie Padilla pic.twitter.com/f3CDzFdJ4K
Day 28, Uncertainties: Trend by Elmera Azadpour
Forest area compared to the 35-year mean across CONUS 🌳
— USGS Data Science (@USGS_DataSci) April 28, 2023
Much of the U.S. have seen drops in forest area magnitude in recent years, while the Northern Plains have seen slight increases.#Day28 | trend | #30DayChartChallenge 📅 #rstats #DataViz by Elmera Azadpour pic.twitter.com/S2pL9QIzmO
Day 28, Uncertainties: Trend by Margaux Sleckman
What does streamflow into Lake Tahoe look like this snowmelt season?
— USGS Data Science (@USGS_DataSci) May 2, 2023
Check out the daily streamflow at 9 streamgages surrounding the lake from Mar 2023 to present as compared to the historical record.#Day28 | Trend | #30DayChartChallenge 📅 #rstats #DataViz by Margaux Sleckman pic.twitter.com/rFoTIN2jA9
Day 29, Uncertainties: Monochrome by Merritt Harlan
@USGS is improving water monitoring by combining ground data with satellite data on water extent & elevation, which can be used together to estimate streamflow in rivers like the Tanana in AK 🛰💧#Day29 | Monochrome | #30DayChartChallenge 📅 #rstats #DataViz by Merritt Harlan pic.twitter.com/hZYvJnXQkS
— USGS Data Science (@USGS_DataSci) April 29, 2023
Day 30, Uncertainties: Worldbank by Jay Hariharan
Present-day industrial freshwater withdrawals in the U.S. have decreased since 1990, but overall freshwater withdrawals are similar to those in 1990.
— USGS Data Science (@USGS_DataSci) April 30, 2023
Data used for this #DataViz comes from the Worldbank.#Day30 | Worldbank | #30DayChartChallenge 📅 by Jay Hariharan #rstats pic.twitter.com/bR3vrf99W9
The code behind these charts is available on github at https://github.com/DOI-USGS/vizlab-chart-challenge-23.
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