Using Sensors and Cross-Disciplinary Teams to Quickly Understand Complex Ecosystems

Publish Date: Feb 17, 2009 | 0 Ratings | 0.00 out of 5 |  PDF

Overview

In early 2008, Dr. Tom Harmon, professor of engineering at the University of California, Merced, and his cross-disciplinary team of environmental engineers, biologists, computer scientists, hydrologists, and electrical engineers set out for four days to document the microbial biodiversity on a uniquely variable chain of five inland lakes in rural Argentina. With this research, Harmon and his team aimed to determine how quickly and accurately they can use today’s observational technologies such as sensors, actuators, the global positioning system (GPS), computer models, wireless Internet, and off-grid energy sources to characterize complex ecosystems under stress. Techniques like those used in this research are under test for implementation in situations where it is important to quickly monitor and model water quality, such as when tsunamis, hurricanes, or other natural disasters strike.

Table of Contents

  1. Addressing Global Problems with Global Teams
  2. Quick Win: Follow-Up Collaborative Field Research Project
  3. The First PASEO Project: Characterize a Chain of Argentinean Lakes
  4. Deploying Distributed Sensors Requires a Cross-Disciplinary Skill Set
  5. Understanding Complex Environmental Problems
  6. Results of the PASEO Project
  7. Creating a National Network for Monitoring Lakes and Wetlands in Argentina

1. Addressing Global Problems with Global Teams

The National Science Foundation (NSF) recognizes that American researchers need to have a global perspective, which is why it created the Office of International Science and Engineering (OISE). Because of Harmon’s experience in using distributed sensors and his role in founding the Center for Embedded Network Sensing (CENS), which is an NSF-sponsored science and technology center hosted at the University of California, Los Angeles (UCLA), OISE asked him to organize a workshop to foster collaborative environmental research in South America.


Dr. Thomas C. Harmon

 

Harmon and Harold Stolberg, the NSF director of the OISE, made a reconnaissance trip to Buenos Aires in September 2006 to meet with the Pan-American Sensors for Environmental Observatories (PASEO) workshop co-organizer, Daniel Lupi, at the Instituto Nacional de Tecnología Industrial (INTI). They met with a group of environmental scientists at several research agencies, all of whom agreed to support the collaboration.

This workshop was very successful, and the participants quickly determined a set of research principles and challenges and began to identify common research initiatives. The scientists agreed that they could establish comparative environmental test beds in North and South America to study lakes, estuaries, and water resource management. These research projects could be used to train graduate students in the application of new observational technologies as well as international collaboration.

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2. Quick Win: Follow-Up Collaborative Field Research Project

Harmon still had some funding from the workshop project. “I told our NSF sponsors, ‘I could send this money back to you or we could actually do something we had talked about at the workshop. Let’s get some students down there and do a project together.’” Harmon then formed a research team of a dozen professors and graduate students from three U.S. universities and 14 professors and graduate students from several Argentinean research institutions.

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3. The First PASEO Project: Characterize a Chain of Argentinean Lakes

Within three months, the NSF instructed Harmon to undertake the first follow-up research project to study the Encadenadas del Oeste, a chain of inland lakes in Argentina. The northernmost lake in the chain is moderately salty while the southernmost lake in the chain is nearly as salty as the Dead Sea.

A Google Earth map showing the one-time “Pearls of the Pampas” – a string of shallow lakes: Alsina, Cochicó, del Monte and Epecuén, and ending in Del Venado. The salinity of these lakes increases as the water flows from north to south.

Harmon explained that these lakes all have the same weather and are surrounded by the same vegetation, yet there is a big change in salinity from the lakes at the top of the chain to the very salty ones at the bottom of the chain. The researchers wanted to see if they could characterize the lakes, measure the necessary parameters, and grab samples in just four days.

“Engineers love to try to describe systems with math,” Harmon explained. “We think we know what a lake is going to do. We can simulate it using physics-based models. The water flows from the high end to the low end, and we can use hydrodynamic equations to model how the water will move around.”

These models are complex with many parameters and interrelated changes in time and space. Until recently, such lake modeling in real time has been an ill-posed problem because scientists did not have the streams of data needed to build and test their models. “The old approach was to put on your hip waders and grab your clipboard and collect samples,” Harmon said. “It can take years to see a trend that way.”

Dr. Gerardo Perillo, vice director of the Instituto Argentino de Oceanografía (IADO) in Bahia Blanca, south of Buenos Aires, was excited about the project because he had been trying to mobilize a group of hydrologists and environmentalists to look at this area. He explained that there are a lot of excellent scientists in Argentina, but they have a hard time getting funding for instruments and gear.

Together, their goal was to study the relationship between water salinity and the biodiversity reflected in the bacteria and phytoplankton across the chain of lakes, and to use observational sensors to document the lakes’ water quality and mixing conditions. Additionally, an equally important goal was to give students and researchers the opportunity to plan and execute a challenging international scientific collaboration to gain a more global perspective about their research.

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4. Deploying Distributed Sensors Requires a Cross-Disciplinary Skill Set

 

Participants in the PASEO Workshop

To develop and deploy new cutting-edge environmental observation technology, Harmon explained, “You can’t just leave it to the technology people. You need ‘application people,’ environmental engineers and ecologists who work in the field since they create the models and know what to monitor. But you also need electrical engineers and computer scientists to design and refine the technology.”

This is why CENS was created in 2002. “We marry environmental engineers with computer scientists and/or electrical engineers in true collaboration,” Harmon said. There are now 35 principal investigators from five universities who are associated with CENS, including a mix of electrical engineers, computer scientists, environmental engineers, geologists, and biologists.

The team used 14 different sensors to characterize each of the lakes and surrounding soil. Team members monitored weather effects on the lakes, including the amount of water mixing that occurred because of the wind. “We were lucky. We arrived during a windstorm, so the water was pretty thoroughly mixed throughout our four-day stay,” Harmon said.

Arriving at the shores of the first lake, the project team launched a boat to start taking measurements on the lake.

The team used a Vaisala weather station to gather high-quality, real-time data and an NI CompactRIO system to control and log the data for the weather station in a compact unit that could be easily transported and used in remote locations.

One of the most significant challenges for this type of research is the large amount of configuration and sensor expertise typically required to set up a system. Traditional data loggers collect data from environmental sensors, but they cannot be programmed for any kind of real-time analysis. Typically, the data is collected and then analyzed at the lab. Some sensors, such as those that measure water turbidity, are difficult to set up and have to be configured, perf

 

 ectly calibrated, and correctly located to collect accurate and useful samples. Without near real-time analysis, poor quality or less useful data often results.

With NI LabVIEW graphical programming software, Harmon and his team created a customized program that runs on the CompactRIO measurement system, performs analysis on the data as it is collected, and provides real-time feedback on whether the sensors are configured correctly. With this breakthrough in embedded intelligence, water quality measurement systems can be sent all over the world and configured with simple instructions.

In addition to providing the embedded real-time analysis and feedback, LabVIEW simplified the development of the water quality monitoring application, so domain experts such as environmental engineers and hydrologists can customize programs for their specific needs.

“The key advantage is the combination of field-ready NI hardware and the processing capability of LabVIEW,” Harmon said. “This integrated system provides an excellent platform for the integrated measurement-modeling sensor system envisioned here.”

To conduct their research, team members met in Buenos Aires, traveled 11 hours to the lake site, deployed sensors to take measurements, performed their analysis, created simulations, and then uploaded the information to the Internet for other scientists around the world to share feedback with colleagues. When they returned to their labs at the end of the week, they were able to further analyze and document their findings.

In the past, a research project of this scope would have taken months of manual sampling and analysis. By using sensors to analyze the air, soil, water, wind, and weather, and by analyzing phytoplankton and bacteria from lake to lake, the research team characterized the ecology of these inland lakes in four days, except for the biological samples, which will take more time to prepare and process.

 

CompactRIO was used to capture the weather data gathered at each point. It was windy all four days which was good for gathering water samples that were well mixed.

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5. Understanding Complex Environmental Problems

Harmon said that it is difficult to understand many environmental problems because the environment is constantly changing, and it is expensive to constantly observe the changes to understand their patterns.

This is why today’s distributed and networked sensors are critical to the success of environmental engineering. Harmon is an advocate for distributed sensing systems because he believes if affordable, distributed observation systems can be made available to environmental scientists and environmental engineers, and then those scientists and engineers can detect important patterns much more quickly. “Think of how much earlier we could have documented global warming if we had had dense arrays of temperature sensors logging data all over the globe for the past 50 years,” Harmon said.

The team members were able to monitor the validity of the samples they were collecting to make sure that the sensors were working and everything was correctly calibrated. The home-made pontoon boat had several sensors suspended underneath.

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6. Results of the PASEO Project

“The range in salinity we found was terrific,” Harmon reported. “It ranged from less salty (1 µS/cm) to very salty (80 µS/cm).”

Mary Cynthia Piccolo, director of the IADO and one of the principal investigators of this study, described the benefits derived from using 14 different sensors and monitoring four lakes in the same week. “With the equipment the U.S. team brought, we were able to collect new data and perform comparisons between each of the lakes simultaneously, since it makes no sense to measure one lake and, after a month, measure another lake.”

The researchers involved in this project are hopeful that this kind of environmental monitoring can soon be carried out by local practitioners who may not be environmental engineers or computer scientists. The researchers hope these practitioners will be able to quickly deploy low-cost sensors, collect data, and stream it onto the Internet for remote analysis and modeling.

“If we could create some systems that nonscientists could replicate around the world, the result would be dramatic. We would have fewer water-borne diseases as well as better allocation of resources to critical areas in developing countries. In the more developed nations, more real-time environmental data gathering and real-time analysis would lead to better policy making, like in situations in which you’re advising people such as farmers about best management practices.”

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7. Creating a National Network for Monitoring Lakes and Wetlands in Argentina

Perhaps the most important result of the PASEO workshop and the week’s worth of follow-up field work is a new commitment from Argentinean researchers to create a national network for modeling all of the lakes, estuaries, and wetlands in the country.

Based on the success of the first PASEO workshop and the hands-on research project at the lakes, the NSF has funded PASEO II, a more hands-on study and training institute for 50 early-career scientists from both the U.S. and Latin America for spring 2009. This training session will combine theory and field practice using the same mix of computer scientists and application scientists from two different cultures.

Learn about more work being done by CENS in the Costa Rican rainforest. 

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