Posts tagged ‘Data logger’

Feb 26

Data deep dive: When to doubt your measurements

Dr. Colin Campbell discusses why it’s important to “logic-check” your data when the measurements don’t make sense.

Wasatch Plateau

In the video below, he looks at weather data collected on the Wasatch Plateau at 10,000 feet (3000 meters) in the middle of the state of Utah.

Watch the video

Video transcript

My name is Colin Campbell, I’m a research scientist here at METER group. Today we’re going to spend time doing a data deep dive. We’ll be looking at some data coming from my research site on the Wasatch Plateau at 10,000 feet (3000 meters) in the middle of the state of Utah.

Right now, I’m interested in looking at the weather up on the plateau. And as you see from these graphs, I’m looking at the wind speeds out in the middle of three different meadows that are a part of our experiment. At 10,000 feet right now, things are not that great. This is a picture I collected today. If you look very closely, there’s an ATMOS 41 all-in-one weather station. It includes a rain gauge. And down here is our ZENTRA ZL6 logger. It’s obviously been snowing and blowing pretty hard because we’ve got rime ice on this post going out several centimeters, probably 30 to 40 cm. This is a stick that tells us how deep the snow is up on top.

One of the things we run into when we analyze data is the credibility of the data and one day someone was really excited as they talked to me and said, “At my research site, the wind speed is over 30 meters per second.” Now, 30 meters per second is an extremely strong wind speed. If it were really blowing that hard there would be issues. For those of you who like English units, that’s over 60 miles an hour. So when you look at this data, you might get confused and think: Wow, the wind speed is really high up there. And from this picture, you also see the wind speed is very high.

But the instrument that’s making those measurements is the ATMOS 41. It’s a three-season weather station, so you can’t use it in snow. It’s essentially producing an error here at 30 meters per second. So I’ll have to chop out data like this anemometer data at the summit where the weather station is often encrusted with snow and ice. This is because when snow builds up on the sonic anemometer reflection device, sometimes it simply estimates the wrong wind speed. And that’s what you’re seeing here.

This is why it’s nice to have ZENTRA cloud. It consistently helps me see if there’s a problem with one of my sensors. In this case, it’s an issue with my wind speed sensors. One of the other things I love about ZENTRA Cloud is an update about what’s going on at my site. Clearly, battery use is important because if the batteries run low, I may need to make a site visit to replace them. However, one of the coolest things about the ZL6 data logger is that if the batteries run out, it’s not a problem because even though it stops sending data over the cellular network, it will keep saving data with the batteries it has left. It can keep going for several months.

I have a mix of data loggers up here, some old EM60G data loggers which have a different voltage range than these four ZL6 data loggers. Three of these ZL6s are located in tree islands. In all of the tree islands, we’ve collected enough snow so the systems are buried and we’re not getting much solar charging. The one at the summit collects the most snow, and since late December, there’s been a slow decline in battery use. It’s down. This is the actual voltage on the batteries. The battery percentage is around 75%. The data loggers in the two other islands are also losing battery but not as much. The snow is just about to the solar charger. There’s some charging during the day and then a decrease at night.

So I have the data right at my fingertips to figure out if I need to make a site visit. Are these data important enough to make sure the data loggers call in every day? If so, then I can decide whether to send someone in to change batteries or dig the weather stations out of the snow.

I also have the option to set up target ranges on this graph to alert me whether the battery voltage is below an acceptable level. If I turn these on, it will send me an email if there’s a problem. So these are a couple of things I love about ZENTRA cloud that help me experiment better. I thought I’d share them with you today. If you have questions you want to get in contact me with me, my email is [email protected]. Happy ZENTRA clouding.

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Nov 7

How to get started with ZENTRA Cloud

Researchers need to optimize funding and maximize peer-reviewed paper output. ZENTRA Cloud’s powerful data management software works with the new ZL6 data logger to make it easier to succeed at both.

METER ZL6 Data Logger providing information to a researcher

ZENTRA Cloud reduces workload by speeding up analysis, streamlining workflow, and simplifying data sharing.

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Want to explore how ZENTRA Cloud works? Request access to a live test account.

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Sep 10

Data collection: 8 best practices to avoid costly surprises

Every researcher’s goal is to obtain usable field data for the entire duration of a study. A good data set is one a scientist can use to draw conclusions or learn something about the behavior of environmental factors in a particular application. However, as many researchers have painfully discovered, getting good data is not as simple as installing sensors, leaving them in the field, and returning to find an accurate record. Those who don’t plan ahead, check the data often, and troubleshoot regularly often come back to find unpleasant surprises such as unplugged data logger cables, soil moisture sensor cables damaged by rodents, or worse: that they don’t have enough data to interpret their results. Fortunately, most data collection mishaps are avoidable with quality equipment, some careful forethought, and a small amount of preparation.

Before selecting a site, scientists should clearly define their goals for gathering data.

Make no mistake, it will cost you

Below are some common mistakes people make when designing a study that cost them time and money and may prevent their data from being usable.

Site characterization: Not enough is known about the site, its variability, or other influential environmental factors that guide data interpretation
Sensor location: Sensors are installed in a location that doesn’t address the goals of the study (i.e., in soils, both the geographic location of the sensors and the location in the soil profile must be applicable to the research question)
Sensor installation: Sensors are not installed correctly, causing inaccurate readings
Data collection: Sensors and logger are not protected, and data are not checked regularly to maintain a continuous and accurate data record
Data dissemination: Data cannot be understood or replicated by other scientists

When designing a study, use the following best practices to simplify data collection and avoid oversights that keep data from being usable and ultimately, publishable.

IoT Technologies for Irrigation Water Management

Dr. Yossi Osroosh, Precision Ag Engineer in the Department of Biological Systems Engineering at Washington State University, discusses where and why IoT fits into irrigation water management. In addition, he explores possible price, range, power, and infrastructure road blocks.

Wireless sensor networks and irrigation lines in a field

Wireless sensor networks collect detailed data on plants in areas of the field that behave differently.

Studies show there is a potential for water savings of over 50% with sensor-based irrigation scheduling methods. Informed irrigation decisions require real-time data from networks of soil and weather sensors at desired resolution and a reasonable cost. Wireless sensor networks can collect data on plants in a lot of detail in areas of the field that behave differently. The need for wireless sensors and actuators has led to the development of IoT (Internet of Things) solutions referred to as Low-Power Wide-Area Networking or LPWAN. IoT simply means wireless communication and connecting to some data management system for further analysis. LPWAN technologies are intended to connect low-cost, low-power sensors to cloud-based services. Today, there are a wide range of wireless and IoT connectivity solutions available raising the question of which LPWAN technology best suits the application?

IoT Irrigation Management Scenarios

The following are scenarios for implementing IoT:

buying a sensor that is going to connect to a wireless network that you own (i.e., customer supplied like Wi-Fi, Bluetooth),
buying the infrastructure or at least pieces of it to install onsite (i.e., vendor managed LPWAN such as LoRaWAN, Symphony Link), and
relying on the infrastructure from a network operator LPWAN (e.g., LTE Cat-M1, NB-IOT, Sigfox, Ingenu, LoRWAN).

This is how cellular network operators or cellular IoT works. LPWAN technology fits well into agricultural settings where sensors need to send small data over a wide area while relying on batteries for many years. This distinguishes LPWAN from Bluetooth, ZigBee, or traditional cellular networks with limited range and higher power requirements. However, like any emerging technology, certain limitations still exist with LPWAN.

Individual weather and soil moisture sensor subscription fees in cellular IoT may add up and make it very expensive where many sensors are needed.

IoT Strengths and Limitations

The average data rate in cellular IoT can be 20 times faster than LoRa or Symphony Link, making it ideal for applications that require higher data rates. LTE Cat-M1 (aka LTE-M), for example, is like a Ferrari in terms of speed compared to other IoT technologies. At the same time, sensor data usage is the most important driver of the cost in using cellular IoT. Individual sensor subscription fee in cellular IoT may add up and make it very expensive where many sensors are needed. This means using existing wireless technologies like traditional cellular or ZigBee to complement LPWAN. One-to-many architecture is a common approach with respect to wireless communication and can help save the most money. Existing wireless technologies like Bluetooth LE, WiFi or ZigBee can be exploited to collect in-field data. In this case, data could be transmitted in-and-out of the field through existing communication infrastructure like a traditional cellular network (e.g., 3G, 4G) or LAN. Alternatively, private or public LPWAN solutions such as LoRaWAN gateways or cellular IoT can be used to push data to the cloud. Combination of Bluetooth, radio or WiFi with cellular IoT means you will have fewer bills to pay. It is anticipated that, with more integrations, the IoT market will mature, and costs will drop further.

Many of LPWAN technologies currently have a very limited network coverage in the U.S. LTE Cat-M1 by far has the largest coverage. Ingenu, which is a legacy technology, Sigfox and NB-IOT have very limited U.S. coverage. Some private companies are currently using subscription-free, crowd-funded LoRaWAN networks to provide service to U.S. growers: however, with a very limited network footprint. Currently, cellular IoT does not perform well in rural areas without strong cellular data coverage.

In two weeks: Dr. Osroosh continues to discuss IoT strengths and limitations in part 2.

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Jan 2

Lysimeters Determine if Human Waste Composting can be More Efficient

In Haiti, untreated human waste contaminating urban areas and water sources has led to widespread waterborne illness. Sustainable Organic Integrated Livelihoods (SOIL) has been working to turn human waste into a resource for nutrient management by turning solid waste into compost. Read more…

Estimating Relative Humidity in Soil: How to Stop Doing it Wrong

Estimating the relative humidity in soil? Most people do it wrong…every time. Dr. Gaylon S. Campbell shares a lesson on how to correctly estimate soil relative humidity from his new book, Soil Physics with Python, which he recently co-authored with Dr. Marco Bittelli. Read more.…

How Many Soil Moisture Sensors Do You Need?

“How many soil moisture sensors do I need?” is a question that we get from time to time. Fortunately, this is a topic that has received substantial attention by the research community over the past several years. So, we decided to consult the recent literature for insights. Here is what we learned.

Data loggers: To Bury, or Not To Bury

Globally, the number one reason for data loggers to fail is flooding. Yet, scientists continue to try to find ways to bury their data loggers to avoid constantly removing them for cultivation, spraying, and harvest. Chris Chambers, head of Sales and Support at Decagon Devices always advises against it. Read more…

Founders of Environmental Biophysics: Champ Tanner

Image: http://soils.wisc.edu/people/history/champ-tanner/

We interviewed Gaylon Campbell, Ph.D. about his association with one of the founders of environmental biophysics, Champ Tanner. Read more…

And our three most popular blogs of all time:

Do the Standards for Field Capacity and Permanent Wilting Point Need to Be Reexamined?

We asked scientist, Dr. Gaylon S. Campbell, which scientific idea he thinks impedes progress. Here’s what he had to say about the standards for field capacity and permanent wilting point. Read more…

Environmental Biophysics Lectures

During a recent semester at Washington State University, a film crew recorded all of the lectures given in the Environmental Biophysics course. The videos from each Environmental Biophysics lecture are posted here for your viewing and educational pleasure. Read more…

Soil Moisture Sensors In a Tree?

Soil moisture sensors belong in the soil. Unless, of course, you are feeling creative, curious, or bored. Then maybe the crazy idea strikes you that if soil moisture sensors measure water content in the soil, why couldn’t they be used to measure water content in a tree? Read more…

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Dec 5

Data Logger Dilemma: To Bury, or Not to Bury—An Update

Recently, we wrote about scientists who were burying their data loggers (read it here). Radu Carcoana, research specialist and Dr. Aaron Daigh, assistant professor at North Dakota State University, used paint cans to completely seal their data loggers before burying them in the fall of 2015.

Data logger in a paint can with sensor cords, being prepared by researchers to be buried

Paint can setup for buried data logger.

They drilled ports for the sensor cables, sealed them up, and when they needed to collect data, they dug up the cans, retrieved the instruments, and downloaded the data in a minute or less.

Here Radu gives an update of what happened when he dug up his buried instruments in the spring.

Results of the Paint Can Experiment

In May of this year, we dug up eighteen units (one data logger and four soil moisture sensors per unit) left in the field since November 2015—over six months.

Did moisture get into the paint cans? —We found only three cans with water in them, purely due to installation techniques used for that specific unit. The other fifteen units were bone dry, although total precipitation for the month of April only amounted to 3.63 inches, plus the snow melt.

How was data recording and recovery? —For six months, every 30 minutes the soil moisture sensors took readings, the data logger recorded, and we retrieved all of the data, complete and unaltered.

Image of a METER Data Logger in a can with water in it, which was a result of a faulty burying installation

Only three cans with water in them, due to installation techniques.

What about power consumption? The batteries were good —over 90% did not need replacement. The power budget provided by five AA batteries was more than enough for reading four soil moisture sensors at 30-minute intervals.

What Happens Now?

In the spring of this year, we installed 18 more units in the third farm field, right after planting soya. We now have 36 individual units (~$1,000 value each unit) buried in the ground in the middle of a field planted with corn or soybean, since the beginning of May.

On October 13-14 (after 5 months), we accessed the first twelve units (Farm A). All 30 minutes of data was read, recorded, and downloaded (since May). The batteries and the other accessories were replaced, and then we sealed and reburied the cans. Only one unit out of twelve had an issue and was replaced: the battery exploded in the can (editor’s note: battery explosion is usually caused by a manufacturing defect and the risk can be lessened by purchasing higher quality batteries, although all types are susceptible to some degree). Since battery leakage will often corrode everything the acid touches, the data logger had to be sent back for repair and there may be partial data loss. The other 24 units (Farm B and C) will be accessed next week, weather permitting.

METER Data Logger open on top of an experimental burying site

Over 90% of batteries did not need replacement.

Is the Paint Can Method Worth it?

We will continue to monitor and retrieve the data from the buried data loggers (We don’t use data loggers suited for wireless communication, because several factors guided us not to). The paint can system works very well if the installation is done correctly, with great attention to detail, and it costs only $2.00/can. However, there are improvements that could be made in order to have this method become a standard in soil research. For instance, though we are still using paint cans and other common materials, advancements in the design of waterproof containers and sturdiness would be a huge step forward. This is just a well thought out concept – a prototype. It proves that burying electronics for a longer period of time can be done if properly executed.

Note: METER’s (formerly Decagon) official position is that you should never bury your data logger. But we couldn’t resist sharing a few stories of scientists who have figured out some innovative methods which may or may not be successful, if tried at other sites.

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Nov 28

Soil Sensors Help Thousand-Year-Old Levees Protect Residents of the Secchia River Valley

In Italy, on January of 2014, one of the Secchia river levees failed, causing millions of dollars in flood damage and two fatalities. Concerned with preventing similar disasters, scientists and geotechnical engineers are using soil sensors to investigate solutions in a project called, INFRASAFE (Intelligent monitoring for safe infrastructures) funded by the Emilia Romagna Region (Italy) on European Funds.

Secchia river in Italy (Image: visitsassuolo.it)

Professor Alberto Lamberti, Professor Guido Gottardi, Department of Civil, Chemical, Environmental, and Materials Engineering, University of Bologna, along with Prof. Marco Bittelli, University of Bologna professor of Soil and Environmental Physics, installed soil sensors along some transects of the Secchia river to monitor water potential and piezometric pressure. They want to study properties of the compacted levee “soil”, during intense flooding. Bittelli comments, “Rainfall patterns are changing due to climate change, and we are seeing more intense floods. There is a concern about monitoring levees so that we can, through studying the process, eventually create a warning system.”

Image of a white van parked on a road next to a trench built for burying sensor cables

Trench for burying sensor cables.

What Are The Levees Made Of?

Amazingly, some of these levees are very old, built at the beginning of the second millennium to protect the Secchia valley population from floods. “These rudimentary barrages were the starting point of the huge undertakings, aiming at the regulation and stabilization of the river, which were gradually developed and expanded in the following centuries…building up a continuous chain all along the river.” (Marchii et. al., 1995)

Vegetation in the Secchia River floodplain.

Unlike natural soil with horizons, the soil that makes up the levees is made up of extremely compact clay and other materials, which will pose challenges to the research team in terms of sensor installation. The team will use soil sensors to determine when the compacted material that makes up the levees gets so saturated it becomes weak. Bittelli says, “We are looking at the mechanical properties of the levees, but mechanical properties are strongly dependent on hydraulic properties, particularly soil water potential (or soil suction). A change in water potential changes the mechanical properties and weakens the structure.” This can happen either when a soil dries below an optimal limit or wets above it; the result is a weakened barrier that can fail under load.

Image of a research team using an installation tool to install water content sensors

Here the team uses an installation tool to install water content sensors.

Soil Sensors Present Installation Challenges

To solve the installation problems, the team will use a specialized installation tool to insert their water content sensors. Bittelli says, “Our main challenge is to install sensors deep into the levees without disturbing the soil too much. It’s very important to have this tool because clearly, we cannot dig out a levee; we might be the instigator of a flood. So it was necessary for us to be able to install the sensors in a relatively small borehole.” The researchers will install the sensors farther down than the current tool allows, so they are modifying it to go down to eight or ten meters. Bittelli explains, “We used a prototype installation tool which is two meters long. We modified it in the shop and extended it to six meters to be able to install water content sensors at further depths.”

Another challenge facing the research team is how to install water potential sensors without disturbing the levee. Marco explains, “We placed an MPS-6 (now called TEROS 21) into a cylinder of local soil prepared in the lab. A sort of a muffin made of soil with an MPS-6 inside. Then we lowered the cylinder into the borehole, installed the sensor inside, and then slid it down into the hole. Our goal is to try and keep the structure of the soil intact. Since the cylinder is made of the same local soil, and it is in good contact with the borehole walls, hydraulic continuity will be established.”

Image researcher placing an MPS-6 into a cylinder of soil

Researchers placed an MPS-6 into a cylinder of local soil prepared in the lab.

Unlike installing water content sensors, matric potential sensors don’t need to be installed in undisturbed soil but only require good contact between the sensor and the bulk soil so liquid water can easily equilibrate between the two. The researchers are also contemplating using a small camera with a light so they can see from above if the installation is successful.

Find Out More

The researchers will collect data at two experimental stations, one on the Po river, and one on the Secchia River. So far, the first installation was successfully performed, and data are collected from the website. Bitteli says the first installation included water content, temperature, and electrical conductivity sensors, water potential sensors, and tensiometers connected to a wireless network that will transmit all the data to a central office for analysis.

You can read more about this project and how it’s progressing here.

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Nov 7

Mesh Wireless Sensor Networks: Will Their Potential Ever Be Realized? (Part 2)

Soil ecologist Dr. Kathy Szlavecz and her husband, computer scientist, Dr. Alex Szalay, both at Johns Hopkins University, are testing a wireless sensor network (WSN; Mesh Sensor Network), developed by Dr. Szalay, his colleague, computer scientist Dr. Andreas Terzis, and their graduate students (read part 1). Mesh networks generate thousands of measurements monthly from wireless sensors. The husband/wife team says that WSN’s have the potential to revolutionize soil ecology by generating a previously impossible spatial resolution. This week, read about the results of their experiments.

Overall, the experiments were a scientific success, exposing variations in the soil microclimate not previously observed.

Results and Challenges:

About the performance of the network, Kathy says, “Overall, our experiments were a scientific success, exposing variations in the soil microclimate not previously observed. However, we encountered a number of challenging technical problems, such as the need for low-level programming to get the data from the sensor into a usable database, calibration across space and time, and cross-reference of measurements with external sources.

The ability of mesh networks that generate so much data also presents a data management challenge. Kathy explains, “We didn’t always have the resources or personnel who could organize the data. We needed a dedicated research assistant who could clean, handle, and organize the data. And the software wasn’t user-friendly enough. We constantly needed computer science expertise, and that’s not sustainable.”

The team also faced setbacks stemming from inconsistencies generated by new computer science students beginning work on the project as previous students graduated. This is why the team is wondering if a commercial manufacturer in the industrial sector would be a better option to help finish the development of the mesh network.

Mesh Wireless Sensor Network on rocks in the Atacama desert

This deployment is located in the Atacama desert in Chile. Atacama is one of the highest, driest places on Earth. These sensors are co-located with the Atacama Cosmological Telescope. The goal of this deployment is to understand how the hardware survives in an extreme environment. In addition to the cold, dry climate, the desert is exposed to high UV radiation. These boxes are collecting soil temperature, soil moisture and soil CO2 data. (Image: lifeunderyourfeet.org)

What’s Next?

Kathy and Alex say that mesh sensor network design has room for improvement. Through their testing, the research team learned that, contrary to the promise of cheap sensor networks, sensor nodes are still expensive. They estimated the cost per mote including the main unit, sensor board, custom sensors, enclosure, and the time required to implement, debug and maintain the code to be around $1,000. Kathy says, “The equipment cost will eventually be reduced through economies of scale, but there is clearly a need for standardized connectors for connecting external sensors and in general, a need to minimize the amount of custom hardware work necessary to deploy a sensor network.” The team also sees a need for the development of network design and deployment tools that will instruct scientists where to place gateways and sensor relay points. These tools could replace the current labor-intensive trial and error process of manual topology adjustment that disturbs the deployment area.

Image of deployment locations in fields of the farming systems

This deployment is located in the fields of the farming system project at BARC. Soil temperature and moisture probes are placed at various locations of a corn-soybean-wheat rotation. The goal is to understand and explain soil heterogeneity and to provide background data for trace gas measurements. (Image: Lifeunderyourfeet.org)

Future Requirements:

According to Kathy, wireless sensor networks promise richer data through inexpensive, low-impact collection—an attractive alternative to larger, more expensive data collection systems. However, to be of scientific value, the system design should be driven by the experiment’s requirements rather than technological limitations. She adds that focusing on the needs of ecologists will be the key to developing a wireless network technology that will be truly useful. “While the computer science community has focused attention on routing algorithms, self-organization, and in-network processing, environmental monitoring applications require quite a different emphasis: reliable delivery of the majority of the data and metadata to the scientists, high-quality measurements, and reliable operation over long deployment cycles. We believe that focusing on this set of problems will lead to interesting new avenues in wireless sensor network research.” And, how to package all the data collected into a usable interface will also need to be addressed in the future.

You can read about Kathy’s experiments in detail at Lifeunderyourfeet.org.

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Oct 24

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Unraveling the Effects of Dams in Costa Rica (Part 2)

Dr. Rafael Muñoz-Carpena, Professor and University of Florida Water Institute Faculty Fellow and his research team are performing environmental studies on the Palo Verde National Park wetlands, trying to unravel the effects of the dams and how to revert some of the damage (see part one). This week, find out how the researchers established connectivity in such a remote area, some of the problems associated with the research, and how the team has addressed some unusual research issues.

ATMOS 41 Weather Station in Palo Verde National Park Wetlands

Surface water elevation gauge station at the Bebedero river. Photo credit: Marco Pazmino Antonio

The Data Challenges of Remote Locations

The team began collecting data, as part of a joint effort with the Organization of Tropical Studies (OTS) research station. However, typical sensors require constant supervision and frequent visits, which imposed a burden on the station staff. There was also the risk of losing data if a sensor malfunction went undetected between monthly visits. Rafael says, “Sometimes access was not possible due to floods or scheduling issues, so there was a high risk of losing information. To fix the problem (thanks to a National Science Foundation grant awarded to OTS) we integrated the sensors into a system that gives us remote access on a daily basis. This allows us to see the status of the instrumentation in near real-time, and thus coordinate with OTS to replace sensors if needed.”

Glimpse of the fauna in Palo Verde. Photo credit: Alice Alonso

Connectivity Issues

The team had a difficult time finding internet connectivity because the area is so remote. After trying several solutions, they finally built their own cell towers. The stations are now outfitted with cellular-enabled data loggers in conjunction with rain gauges and soil moisture and salinity sensors. The stations also include a standing well to measure surface and river water levels and monitor flooding stages. These are coupled with shallow water table wells, installed below the surface at 3-5 meters. Rafael says, “These are tidal rivers, so we get a lot of activity up and down. We look at river data in conjunction with inland responses to try and get an idea of the influence of the river on the shallow groundwater nearby. All these data feed into a database that researchers and stakeholders can look at.”

Composite image contrasting the Palo Verde wetland in the 1986 and the wetland in recent days (2012) during the wet seasons. It highlights the encroachment of vegetation and Typha domingensis (cattail), closing the patches of open water and reducing biodiversity and sites for birds feeding and nesting.

Internal Drivers

Dr. Muñoz-Carpena says because of the lag in the environmental response, it is not immediately clear to the general public that the wetland behavior is the result of what is happening upstream. People fail to see a connection. Therefore unraveling the data in a way that is clear is the first challenge of the project. He adds, “There are also internal drivers such as park management changes that compound the effects of the dams. Originally park managers tried invasive plant control with fire and cattle. Now they control the invasive with blade-rigged tractors that mow the cattail. But this is a highly expensive and temporary measure with recurrent costs, which provides no definitive solution to the cattail invasion. It’s important to understand the changes are not just the result of what’s happening locally. We need to find permanent solutions by tracking down the root of the problem.”

Endangered Jabiru birds in the trees in Palo Verde National Park

Endangered Jabiru in the Palo Verde National Park. Photo credit: Alice Alonso

Plants are Not the Only Invasives

Cattails are not the only invaders that plague the wetlands. Rafael explains, “The other problem is that there is trafficking going on in the park. The men see these data logger boxes with silver antennas, and they think it’s a camera, so they break off the antennas. We are now putting up signs that say, ‘This is not the government watching you. This is research to protect your environment,’ but we are afraid the next time they will break the boxes and everything that goes with them. We won’t have the manpower or the financial resources to go down there and fix the data loggers for another six months.”

Image of a typical monitoring station set up in a more dry area

Example of a typical monitoring station: Surface and subsurface water elevation and EC monitoring wells, and soil moisture and EC at 30 and 60 cm depths. Sensors connected to a wireless cellular data logger for near-real-time data access. Photo taken during the dry season. Photo credit: Alice Alonso

What’s Next?

Over the last three years the team has collected a high-resolution database of fifteen to thirty minute timed steps, with over 100 sensors deployed in twelve spatially-distributed monitoring stations around the park. With that data, Rafael’s team is conducting exploratory types of analysis to study not only potential drivers of change, but also the cause of the drivers. They want to understand potential initiatives they could introduce to make the system more sustainable. Rafael says, “Once we develop integrated hydrological models and test them for the conditions in Costa Rica, hopefully we can understand the behavior in the past and forecast some different scenarios for the future.” Because many regions in the world suffer the impacts of interbasin water transfer, this research can inform future research policy at a broader scale.

Monkeys hang from a tree branch in Palo Verde National park

Glimpse of the fauna in Palo Verde. Photo credit: Alice Alonso

See a map of the instrumentation network within the Palo Verde National Park.

Conceptual representation of the Palo Verde National Park in the context of the Tempisque watershed system.

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Oct 17

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Unraveling the Effects of Dams in Costa Rica

Thirty years ago, in Costa Rica’s Palo Verde National Park, the wetlands flooded regularly and eco-tourists could view thousands of waterfowl. Today, invasive cattail plants cover portions of the wetland which has subsequently dried up and become colonized by hardwoods. Consequently, the number of birds has fallen dramatically.

The number of birds on Palo Verde National Park has fallen dramatically. (Image: anywherecostarica.com)

Some people blame the dams built in the 1970s which introduced hydrological power and created a large irrigation district in the remote region. Dr. Rafael Muñoz-Carpena, Professor and University of Florida Water Institute Faculty Fellow and his research team are performing environmental studies on the wetlands, trying to unravel the effects of the dams and how to revert some of the damage. Rafael explains, “We have a situation where modern engineering brought about social improvements, helpful renewable resources, and irrigation for abundant food production. But the resulting environmental degradation threatens a natural region in a country that depends on eco-tourism.”

Birds in a river at Palo Verde National Park

“A vast network of mangrove-rich swamp, lagoons, marshes, grassland, limestone outcrops, and forests comprise the 32,266 acre Palo Verde National Park.” (Image and text: anywherecostarica.com)

Are The Dams Responsible?

Dr. Muñoz-Carpena says because of lack of historical data it’s difficult to untangle and separate all the factors that have caused the environmental degradation. He adds, “Thirty years ago Palo Verde National Park was part of a large wetland system which was important to all of Central America because it contained many endangered species and was a wintering ground for migratory birds from North America. The Palo Verde field station on the edge of the wetland, operated by the Organization of Tropical Studies (OTS), attracted birdwatchers and wetland scientists from all over the world.”

In the 1970’s, with international funding, a dam was built in the mountains to collect water from the humid side of Costa Rica in order to generate hydroelectric power. It was clean, abundant, and strategically important. With the water transferred to the dry side of the country, a large irrigation district was created to not only produce important crops to the region like rice and beans, but to distribute the land among small parcel settlers.

Flock of birds in the grasslands at Palo Verde National Park

“Birding is the principal draw of visitors to the park.” (Image and text: anywherecostarica.com)

Over the years, however, the wetland area slowly degraded to the point where its Ramsar Convention wetland classification is under question. Rafael says that understanding the causes of the degradation, the impacts of the human system, and how the natural and human systems are linked, is the big question of his research, and there are many factors to consider. “The release of the water, ground and surface water (over)use, agriculture, human development, and a larger population are all factors that could contribute to this degradation. Everything compounds in the downstream coastal wetlands. In collaboration with OTS and other partner organizations and universities, we are trying to disentangle these different drivers.”

Grasslands and swamps with mountains in the background

Understanding the causes of the degradation, the impacts of the human system, and how the natural and human systems are linked, is the big question of this research. (Image: anywherecostarica.com)

A Lack of Historical Data

One of the challenges the researchers face is to gather a sufficient amount of temporal and spatial information about what happened in the past forty years. There are no public repositories of data to tap, and the information is spotty and hard to access. Rafael says, “Thanks to the collaboration of many local partners, we have been able to gather enough information to stitch together a large database out of a collection of non-systematic studies. The biggest challenge is to harmonize data that has been collected by different people in non-consistent ways.” This large database now contains the best long-term record possible for key hydrologic variables: river flow, groundwater stage, precipitation, and evapotranspiration.

The team is also using remote sensing sources to try to obtain time-series data for land-use and vegetation change, and will have those data ground-truthed through instruments that are collecting similar time-series data. Rafael says, “The idea is to build a network that will allow us to overlap some of the previous data sources with our own, validate and upscale the ground data with remote sensing sources, enabling us to put together a detailed picture of what happened.”

Next Week: Find out how the researchers established connectivity in such a remote area, some of the problems associated with the research, and how the team has addressed those issues.

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See a map of the instrumentation network within the Palo Verde National Park.

Are The Dams Responsible?

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