Big problems call for big data: reporting back from the CUAHSI Biennial Colloquium

CUAHSI recently hosted its Biennial Colloquium at the National Conservation Training Center in Shepherdstown, West Virginia. This year’s symposium focused around the theme of “Finding your place in big data: using observations to understand hydrologic processes for predicting a changing world.” More on that in a moment, but first: CUAHSI.

What is CUAHSI?

CUAHSI stands for Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. CUAHSI is funded by NSF, governed by a community of expert water resource scientists and researchers, and serves as a collective voice for over 100 universities and organizations on subjects related to water science. Generally speaking, CUAHSI aims to support the advancement of water science in the United States. This goal is operationalized through workshops, conferences, the coordination of initiatives that assist water researchers (i.e., HydroClient and Hydroshare, which simplify data download and sharing), and more.

CUAHSI’s Biennial Colloquium

The Biennial Colloquium aims to host an event with content that lands between “super specialized and only for a select group of experts” and “broadly appealing to all environmental/biosystems scientists and engineers.” This year’s program addressed all things “big data” within the context of water science – big compute, large-scale modeling, tools and sensors that collect loads of data, and case studies of big data analyses – by including a variety of talks by distinguished lecturers, concurrent sessions on specialized topics, workshops, water-related field trips, and a poster symposium.

Students setting up for the poster symposium at the CUAHSI Biennial Colloquium

Rather than detail all of the interesting experiences had over the few days of the colloquium, I’ll focus on two workshops that I participated in: (1) Do-It-Yourself, Open-Source Wireless Environmental Data Logging, and (2) CUAHSI Data-Driven Education.

EnviroDIY Mayfly: fun, open-source, inexpensive, wireless environmental monitoring

At the “Do-It-Yourself, Open-Source Wireless Environmental Data Logging” workshop, my geekiness reigned as I tinkered with the Arduino-based EnviroDIY Mayfly data logger. The workshop was directed by the brains behind the Mayfly, Steve Hicks (Research Engineer) and Dr. Anthony Aufdenkampe (Associate Research Scientist) of the Stroud Water Research Center. The Mayfly was born from the desire to create an extensive network of sensors that monitored various environmental variables, but on a tight budget. The EnviroDIY Mayfly logger board is based on Arduino, an open-source platform that uses simple and user-friendly hardware and software to translate inputs (i.e., a digital signal, button push, sensor trigger, or even a Twitter message!) into useful information based on user-programmed instructions.

Getting trained on use of the EnviroDIY Mayfly logger by the folks @StroudCenter. Awesome low-cost tech! #CUAHSI pic.twitter.com/nOho1E3bFl

— Natalie Nelson (@natnels) July 26, 2016

At first glance, the Mayfly looks like a simple circuit board with a few additional components. These components include an atomic clock, microSD memory card slot, several input pins (i.e., 8-bit Analog-to-Digital, 16-bit ADC), microUSB port, Bee socket (allows for wireless capability), and solar panel connector. For a full list of Mayfly features, check out their website. All of these components allow for data to be collected from several solar- or battery-powered sensors, and logged on the microSD card that the user has plugged into the Mayfly. Users program the Mayfly using open-source software that is both Mac OS X and Windows compatible. The code is easy to write, and the creators of the Mayfly have created an online community called EnviroDIY that includes blog posts and forums on all things open-source + environmental monitoring. On this website, Mayfly users can download and contribute other open-source codes, making this technology very accessible for those of us who lack experience in Arduino. Have I convinced you that it’s awesome yet? If not, maybe the price will: you can buy a complete EnviroDIY Mayfly loggerstarter kit on Amazon for $90.

The Mayfly data logger and relevant accessories for implementation in environmental monitoring hardware systems. Images from envirodiy.org.

Teaching Hydrology with Data

The second workshop I attended focused on Data and Model Driven Hydrology Education. Participants were asked to create a data-driven hydrology assignment prior to attending the workshop. These assignments were then contributed to the Science Education Resource Center (SERC), which is a NSF-funded venture with the mission of improving "education in the Earth sciences and beyond." The SERC website includes several different modules with user-contributed earth science assignments that target K12 through higher education students, making this online platform a wonderful resource for any and all educators working in natural sciences and engineering. If you ever find yourself needing to create an educational exercise, save yourself some time and check out the brilliant assignments on SERC!

The SERC webpage on Data and Model Driven Hydrology Education created in collaboration with CUAHSI.

CUAHSI researchers successfully received funding to create a module within SERC that includes problem sets for training the next generation of water scientists and engineers. I created and submitted an assignment on dissolved oxygen (DO) trends in the Lower St. Johns River. For this exercise, students download data from three locations along the Lower St. Johns (estuarine, transitional, upstream), and evaluate how the combination of hydrology and system biology produce distinct DO behavior at each of these three river reaches. Data are downloaded with CUAHSI’s HydroClient and evaluated using a Python-enabled Jupyter notebook that I created specifically for this assignment. If you’re interested in including this assignment as part of your curriculum, check out the assignment’s webpage and/or reach out to me! I’m happy to help implement the assignment, or directly teach it to your class. There are also other fantastic assignments included on the Data and Model Driven Hydrology Education webpage that I’m sure you will find useful and/or inspiring.

Snapshot of the Jupyter notebook created as part of a Data and Model Driven Hydrology Education assignment.

All in all, I found that the CUAHSI Biennial Colloquium provided several unique learning experiences, and opportunities for interactions with leaders in the field of hydrology. Whether you’re a student like me, or an experienced water professional, you should strongly consider venturing to the wilds of West Virginia to participate in this conference in 2018! If you don’t want to wait that long, there will also be a Hydroinformatics conference coming up in July of 2017 in Logan, UT. Hope to see you there!

ASABE AIM 2016: Ag and Bio Engineering in the Happiest Place on Earth

Last month marked one of the high points of every summer for our UF/IFAS group – ASABE’s Annual International Meeting (AIM). As an added treat this year’s meeting was held in Orlando so travel was markedly easier for us. Further, I was offered the opportunity to don my digital comms hat and attend.

ASABE’s AIM is an excellent venue for staying abreast of the latest research in Ag & Bio engineering on the local, national and international level. Presentations ranged from food processing to biofuels to landscape irrigation to precision ag and robotics - essentially all the disciplines of the field.

Familiar faces on Sunday morning: UF ABE PhD Students Joe Sagues and Natalie Nelson

It’s quite the slate of events, often running concurrently. In addition, students have a prominent role at AIM, as volunteers, as presenters (talks and posters) and as competitors in various events.

Getting the Story

For me, AIM began in early July when I learned I would be covering the Fountain Wars student competition. Fountain Wars is an AIM staple that challenges student teams to devise ways of using water and engineering to accomplish specific tasks. 

Putting in work: Mike and Lexi of UF ABE's Fountain Wars squad

I was able to connect with the UF ABE team as they made final preparations for competition. This allowed me to both learn about the event and begin the documentation process early, should UF be victorious. See more about the 2016 competition's tasks in the short video below.

My other assignment was robotics. Each year student teams are given a task around which to construct robots that will fulfill the challenge. 

Picking it up and delivering: Clemson Edisto's robots came to win

This year the theme was citrus and the robots had to pick up items, separate them by color and deliver them to one another and then a final location. I did not have the luxury of touching base with the UF ABE team outside of AIM so I had to get the team and event story on site. Following a long absence, the UF ABE robotics team returned to competition again in 2016. 

Team member Amanda DeCanio with one of UF ABE robotics' mean machines

Bringing Home Gold

Two of our closest collaborators won big at AIM 2016. Dr. Michael Dukes was awarded the John Deere Gold Medal for excellence in the application of science and art to the soil. 

.@UF_IFAS expert Dr. Michael Dukes reflects on receiving @ASABEorg's John Deere Gold Medal #ASABEaim16 pic.twitter.com/3pR9EIUkeC

— UF/IFAS IrriGator (@IrriGatorUF) July 20, 2016

And Dr. Kati Migliaccio was recognized for outstanding associate editor.

A Plethora of Resources

If you were not at AIM 2016 or wish to revisit one of the many excellent presentations, all are available here. You can also relive the events as they happened on Twitter. And finally watch for two videos about the student competitions mentioned above to be released in August.

Water-Saving Sensors Go Toe-to-Toe? The Winner Will Surprise You

By Bernard Cardenas

Ever suspect that some of your neighbors apply too much water to their lawns? In some cases you might be right. To remediate this issue, the irrigation industry has developed products to reduce the amount of water wasted during landscape irrigation. 

Water waste adds up (via EPA WaterSense)

Among these technologies are rain sensors and soil moisture sensors (SMS). Rain sensors detect when sufficient rain has fallen and then bypass the irrigation timer’s schedule. Likewise, SMS can detect if the soil is moist enough (so that the lawn can withstand some extra days without watering) and then prevent scheduled irrigation events. 

Sensor vs. Sensor

In a recently published study researchers at UF evaluated the water savings potential of rain sensors and SMS in homes for more than two years. They compared their results to homes only equipped with irrigation timers. They also compared those results to homes that were provided both a rain sensor and educational materials. 

To evaluate if the homes in the study were applying the right amount of water, the researchers also estimated the water applied by the different technologies compared to a theoretical requirement (calculated using a daily soil water balance).

Palm Harbor, FL - where we lay our scene

The Location

In the vicinity of Palm Harbor, FL, a total of 64 homes supplied with reclaimed water for irrigation were selected for this study. Dedicated irrigation flowmeters were installed in every home to measure the amount of water applied. The 64 homes were divided in 4 treatments with 16 homes each. Treatments were: MO (monitored only), SMS, rain sensor, and rain sensor plus educational materials. 

The Results

By the end of the study, SMS-equipped homes were the only group significantly different to the MO homes. This means that the homes equipped with a rain sensor, or a rain sensor plus educational materials, did not save a significant amount of water compared to the MO homes.

Further, the homes equipped with a SMS reduced the average number of irrigation events per week, compared to the MO homes (1.7 vs. 2.7 events/week, respectively), decreased the depth of the weekly irrigation (22 vs. 42 mm, respectively), and applied 44% less water, over the 32 months of data collection. These savings were achieved with no adverse effects to turf quality.

These results indicate that the tested SMS can save a significant amount of reclaimed water, compared to the other methods/technologies investigated.

This paper is part of a series. Read part one here. And if you are attending the ASABE International Meeting in Orlando this month, the studies will be presented in session 138 on 7/18, 2:30pm - 5pm. Follow all our Orlando coverage on Twitter. 

Say "Hello, world!" with Google Earth Engine

See what I did there? For those of you who may not have taken a programming course before, you might not be familiar with “hello, world” – it’s the first program that essentially all coders learn how to write. It’s also how I felt while attending the Google Earth Engine User Summit at Google Headquarters in Mountain View, CA, after discovering that the world (in the form of satellite imagery) is at my fingertips!

Engineers, scientists, researchers, and practitioners from all over the globe congregated in Mountain View, CA, for the 2016 Google Earth Engine User Summit.

Access to satellite data has historically been limited due to the tremendous computational power needed for data download and processing. But the tide is turning. For the past few years, the Google Earth team has been uploading massive amounts of satellite data to the cloud. Google engineers created an online platform, called Google Earth Engine, to give researchers, engineers, geographers, and earth scientists a way to work with these cloud-based data.

Check out this video on "A Planetary Perspective: With Landsat and Google Earth Engine" for a visual overview of Google Earth Engine.

 

Making sense of satellite data

In addition to providing quick and easy access to decades of satellite data, the Google Earth Engine platform includes a suite of tools for data processing. In this case, “processing” means “writing simple code” for the purpose of extracting useful information from the historical record of satellite images. In true Google fashion, the tools are openly available to non-commercial users.

Just a few lines of code in the Earth Engine platform allows users to calculate the "Normalized Difference Vegetation Index" (NDVI), which serves as a measure of vegetation "greenness." Above, NDVI across Florida for January-March, 2016. 

Case studies: from Antarctic sea ice to cropland

Researchers and practitioners are using Google Earth Engine to address a wide variety of important issues. For example, researchers at the European Commission Joint Research Centre are using Google Earth Engine for large-scale crop monitoring to identify fallow land and farms with failed crops. These observations can be coupled with on-the-ground measurements to evaluate the efficacy of management practices, such as those related to irrigation. Imagine the possibilities! 

Guido Lemoine, European Commission’s JRC, speaking on how #GIS can help w #foodsecurity analysis #EEUS #copernicus pic.twitter.com/cPfT9J6h0D

— GoogleEarth Outreach (@earthoutreach) June 14, 2016

Beyond big data

The User Summit not only afforded me the opportunity to learn about the utility and potential of Google Earth Engine, but also gave me a glimpse into the future of satellite image collection. Luc Vincent, Director of Google Geo Imagery, discussed Google's “Terra Bella” division, which designs and manufactures low-cost satellites. Google will be sending enough of these cost-efficient satellites to capture global snapshots 2-3 times per day! At the moment, attaining global coverage with satellite imagery takes approximately 16 days, making Google's vision for satellite data collection particularly impressive (a 3200% improvement in temporal resolution!).

ICYMI: Here's a quick look at our new episode about @terra_bella's small imaging satellites https://t.co/wDDpNZD4Lj pic.twitter.com/8l8vNzSERe

— Nat and Lo (@NatAndLo) April 14, 2016

So you want to learn more about Earth Engine? Here are some resources:

• Google Earth Engine documentation, tutorials, and videos
• Alice Alonso, PhD Candidate in the Agricultural and Biological Engineering Department at UF, recently had an article accepted for publication in Transactions of ASABE that highlights the potential of Google Earth Engine as a tool for Agricultural and Biological Engineers. It's currently in press, but will be published soon! 
• Alonso, A., R. Muñoz-Carpena, K. Robert and C. Murcia. 2016. Wetland landscape spatio-temporal degradation dynamics using the new Google Earth Engine cloud-based platform: opportunities for non-specialists in remote sensing. Trans. ASABE
• In partnership with Science, an educational lab assignment based in Google Earth Engine was created, which also makes for a fun and easy introduction to the platform.
• There are also a lot of web apps that use Google Earth Engine to highlight specific issues, such as deforestation, climate, wildlife conservation, and more!

If you're interested in learning more about Google Earth Engine or the User Summit, reach out to me by email or on Twitter. Until next time!

Whether using reclaimed or potable, overwatering in the landscape is easily preventable

By Bernard Cardenas

Some homeowners with automatic irrigation systems are over-watering their lawns in Florida without even knowing it. To cope with this issue, researchers at UF have been testing different soil moisture sensors, a promising technology that can potentially reduce waste of irrigation water.

Examples of widely available soil moisture sensor devices

Purple Pipes Among Us

In Florida, an important number of homes use reclaimed water to irrigate their landscape. Using soil moisture sensors in this context could present a problem because reclaimed water may contain more salts than potable water, and these salts could alter sensor readings when measuring the soil water content.

Therefore, irrigation specialists evaluated the functionality of four soil moisture sensor brands under both reclaimed and potable water, and quantified their potential irrigation savings. They also analyzed the consistency of each brand to control irrigation and, finally, they compared the brands to see if all of them were effective, or not.

Research Mode

The study was carried out in Gainesville in turfgrass plots irrigated with potable water and reclaimed water (2009 and 2010 respectively). Four soil moisture sensor brands were tested and were compared to a treatment that had no sensor feedback, which is the most common situation in Florida.

All the soil moisture sensors tested applied significantly less water than the comparison treatment (which had no sensor feedback). This was a consequence of the soil moisture sensors not allowing irrigation when soil was wet enough.  

The water savings ranged from 46% to 78% under potable water, and from 45% to 68% under reclaimed water. This means that the tested soil moisture sensors could be used under reclaimed or potable water conditions. Even more promising: these important water savings were obtained during a mostly dry period.

Also important to mention is that these water savings were attained without compromising the turf quality, which always rated good or higher, during the 2 year study.

The Bottom Line

From these results, which are comparable to those achieved in other similar experiments, it is clear that soil moisture sensors can be a useful tool for conserving water on turfgrass irrigated with either potable or reclaimed water.

(Adapted from a recently published research article available here.)