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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.

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.”  

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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)

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Vegetation in the Secchia River flood plain.

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.

soil 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 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.”

soil sensors

Researchers placed a 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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Soil Moisture: An Important Parameter in Weather Monitoring

CoCoRaHS and Weather Monitoring

Each time a rain, hail, or snow storm crosses over your area, volunteers are taking precipitation measurements that are then used to analyze situations ranging from water resource availability to severe storm warnings.  

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CoCoRaHS precipitation data is used by many high profile organizations.

CoCoRaHS (Community Collaborative Rain, Hail and Snow Network) is a non-profit community-based network of volunteers of all ages and backgrounds working together to measure and map precipitation (rain, hail and snow).  Their data is used by the National Weather Service, meteorologists, hydrologists, emergency managers, city utilities, USDA, engineers, farmers, and more.  The organization will soon add another layer to their weather-monitoring efforts:  soil moisture measurement.

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In 1997, a localized flooding event in Fort Collins, Colorado was not well-warned due to lack of high-density precipitation observation.

Why Soil Moisture?

CoCoRaHS originated as the brain child of Nolan Doesken, the state climatologist of Colorado,  in 1997 in response to a localized flooding event in Fort Collins, CO that was not well-warned due to lack of high-density precipitation observations.  Ten years ago the Colorado Climate Center began a partnership with the National Integrated Drought Information System to establish the first regional drought early warning system. This particular system would serve the Upper Colorado River Basin and eastern Colorado.

From the beginning, Nolan was thinking about soil moisture.  He says, “When we first started this project, we identified one weakness of the current climate monitoring systems as the inability to quantitatively assess soil moisture.  Soil moisture is critical as it affects both short term weather forecasts and long-term seasonal forecasts, which are important for drought early warning and avoiding the agricultural consequences of too much or too little soil moisture.”It wasn’t until years later in the drought of 2012, which developed rapidly in the mid and late spring across the intermountain west and central plains that Nolan began planning to use CoCoRaHS as a vehicle for improving the soil moisture aspect of drought early warning.

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The organization intends to measure soil moisture using the gravimetric method.

How Will Volunteers Measure Soil Moisture?

Historically, CoCoRaHS has had success using low-cost measurement tools, stressing training and education, and using an interactive web-site to provide the highest quality data, and soil moisture will be no different.  The organization intends to measure soil moisture using the gravimetric method, where the user will take samples using a soil ring, dry samples in their own oven, and measure sample weight with an electronic scale. Peter Goble, a research assistant at Colorado State, has developed the measurement protocols that volunteers will follow.  He says, “We have installed several different types of soil sensors and tried gravimetric techniques in a field next to the center, and our experience has helped us set up a protocol that gets observers as educated as they can be by the time they take their measurements. The coring device we use is something that came about through trial and error. We were trying to reconcile the fact that we really wanted deeper root zone measurements in order to satisfy drought early-warning-system users, and the need for an inexpensive set of standardized materials that we could send out to observers in a kit.”  Volunteers will take soil samples at each point in a grid pattern, both at the surface and at the 7-9 inch level near the root zone.

What will Happen to the Data?

Initially, while the program is in its test phase, the data will be put in a spreadsheet and shared. However, once CoCoRaHS has finished sending this protocol around the nation to a group of alpha testers, they’ll set up a website infrastructure enabling volunteers to enter their VWC data directly into the CoCoRaHS website.

The need for soil moisture measurement in weather monitoring will outweigh the volunteers’ ability to measure, but there is a solution.

The need for soil moisture measurement in weather monitoring will outweigh the volunteers’ ability to measure, but there is a solution.

Why the Gravimetric Method?

Nolan says the challenge of water content is that soil is highly variable across space.  And if you add issues like sensor performance, improper installation of sensors, problems with soil contact, changes in bulk density, and soil compaction, you end up with inconsistent data.  The gravimetric method will avoid inconsistencies in spatial measurements and ensure higher quality data.

An Overwhelming Task

Nolan says the need for soil moisture measurement in weather monitoring will outweigh the volunteers’ ability to measure, but there is a solution. “People who use soil moisture data in atmospheric applications need high resolution, gridded information in every square kilometer across the country, but it will happen through modeling.  The measurements we take of precipitation and soil moisture will help in the refinement of the weather modules the atmospheric scientists will use as input to their weather prediction models.”

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Water Potential Instruments Try to Determine Where Alkali Bee Larvae Get their Water

Alkali bee beds are maintained by farmers near Touchet, Washington to pollinate fields of alfalfa, grown there for seed. The beds are typically a few acres in size and provide a nesting place for the bees, which can boost alfalfa seed production by as much as 70 percent.  Alkali bees are better than honeybees for pollinating alfalfa, as they don’t mind the “tripping” mechanism of the alfalfa flower, which releases pollen explosively.

Alkali Bee

Alkali Bee

USDA-ARS entomologist, Dr. Jim Cane, is trying to understand optimal bee-soil-water relations to ensure the bees will happily reproduce next year’s pollinators.  Dr. Gaylon S. Campbell recently worked with Dr. Cane to measure water relations in bee nesting beds.  Here’s what they found out:

Why Water Relations Matter

Alkali bees nest underground.  They prefer salty soil surfaces which retard evaporation and discourage plant growth. The soil has to be the right texture, density, and have the correct moisture levels for successful nesting. In addition, the water potential of the larval food provision mass has to be low so it does not mold.  Growers apply high levels of sodium chloride to the bee bed surface, and the soil is sub-irrigated to keep the salt near the surface and the subsurface soil moist.  

Alkali Bee

Bottom right: a white larvae on a gold colored provision mass inside one of the tunnels dug by the female.

The female digs a tunnel down to a favorable depth, typically 15-20 cm or more, hollows out a spheroidal shaped cell around 1 cm diameter, and carefully coats the inside of the cell with a special secretion that appears to form a hydraulic and vapor barrier between the soil and the nest contents.  She then builds a provision mass from pollen and nectar, shaped like a oblate spheroid with major axis around 6 mm and minor axis 3-4 mm.  One egg is laid on the provision mass (which provides food for the larva), and the mother bee then seals up the entrance to the cell and moves on to the next one.  

Alkali Bee

The female coats the inside of the cell with a special secretion that appears to form a hydraulic and vapor barrier between the soil and the nest contents.

Specialized Instruments for Each Measurement

In order to understand moisture relations between the soil, the larva, and the food provision mass, Dr. Cane carefully excavated three soil blocks from one of the bee beds, dissected them to find nests, and Dr. Campbell helped measure water potentials of the eggs, larvae, and provision masses.  They also measured matric and total water potentials of bee bed soils.  

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A sample chamber psychrometer

A  Sample Chamber Psychrometer is the only water potential device with a small enough sample chamber to be able to measure individual eggs and early-stage larvae, which it did.  The provision masses were too dry to measure with the psychrometer, so several provisions were combined (to provide sufficient sample size) and measured in a Dew Point Potentiameter, along with the soil samples.  Dr. Campbell measured measured matric potential of the highly saline soils using a tensiometer.  

Water Potential Seems Important to the Bees

Dr. Campbell thinks matric potential is important in determining physical condition of the soil (how easy it is for the bees to dig and paint the inside of the nest), but probably has little to do with bee or larva water relations. The water potentials of the eggs and larvae were low (dry), but within the range one sees in living organisms.  There was a consistent pattern of larva water potential decreasing with larval growth.  

alkali bee hiding

This alkali bee seeks shelter during the rain in a previously dug tunnel.

The exciting part of this experiment was the provision mass water potentials, which were so low that it is more convenient to talk about them in terms of water activity (another measure of the energy state of water in a system, widely used by food scientists).  The intact provision masses were drier than any of the soil water potentials and not in equilibrium with the soil.  Dr. Campbell says, “It’s interesting that all the provision masses were at water activities that would make them immune to degradation by almost all microbes, both bacteria and fungi.”

Another Interesting Observation  

Dr. Cane found one provision mass covered with mold.  Soil and plants are full of inoculum, so it is unlikely that the other provision masses lacked spores, but this one was wet enough to be compromised, and the others apparently weren’t.  Dr. Campbell says, “There are two possibilities.  Either it was put up too wet, or it got wet in the nest.  The really interesting question is why all of them don’t get that wet.  I think the hydrophobic coating of the nest eliminates all hydraulic contact from the soil to the provision mass, thus eliminating any liquid water flow, which would almost immediately wet the pollen balls.  I think it also drastically reduces the vapor conductance from the soil to the ball, making water uptake through the vapor phase slow enough that the provision mass can usually be consumed before its water activity gets high enough for mold to grow.”

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Tool the grower uses to punch holes in the nesting beds for the bees to tunnel into.

How Do Larvae Stay Hydrated?

The water activity of the larvae were around 0.99, much higher than either the soil or the provision mass, inspiring the scientists to wonder how they stay hydrated.  Dr. Campbell speculates, “They have a water source from their metabolism, since water is a byproduct of respiration (Campbell and Norman, p. 205).   It is also possible for biological systems to take up water against a potential gradient by expending energy.  There are reports of a beetle which can take up water from a drop of saturated NaCl (water activity 0.75), so it is possible that the larva gets water from the environment that way.  There appears to be no shortage of energy available.  On the other hand, it would seem like the larval cuticle would need to be pretty impermeable to maintain water balance since the salty soil, and especially the provision mass, are so much drier than the larva.”  Dr. Cane notes that,”For a few exemplar bee species, mature larvae weigh 30-40% more than the provision they ate, with the possibility that the provision undergoes a controlled hydration by the soil atmosphere through the uncoated soil cap of the nest cell.”

In the future, Dr. Campbell is hoping to see more experiments that will answer some of the questions raised, such as measuring individual provision masses to determine why there is some variation in water potential.  Dr. Cane will be undertaking experiments to measure moisture weight gain of new provisions exposed to the soil atmosphere of the Touchet nest bed soil.

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References

Campbell, G. S. 1985. Soil Physics with BASIC: Transport Models for Soil-Plant Systems.  Elsevier, New York.

Campbell, G. S. and J. M. Norman. 1998. An Introduction to Environmental Biophysics. Springer Verlag, N. Y.

Rawlins, S. L. and G. S. Campbell. 1986. Water potential: thermocouple psychrometry. In Methods of Soil Analysis, Part 1. Physical and Mineralogical Methods – Agronomy Monograph 9, 2nd edition.

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.

Mesh Wireless Sensor Network

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

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.

Mesh Wireless Sensor Network

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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Mesh Wireless Sensor Networks: Will Their Potential Ever Be Realized?

Although the idea of mesh wireless sensor networks is not new, the realization of their many benefits have gone largely unrealized. The low success rate of most wireless systems makes the accomplishments of this Johns Hopkins group unique.

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Soil moisture and temperature are major drivers of seasonal dynamics, soil respiration, carbon cycling, biogeochemical functions, and even the types of species living in a certain area.

The ability to measure soil moisture and temperature is vital to ecologists who work in heterogeneous environments because these parameters are major drivers of seasonal dynamics, soil respiration, carbon cycling, biogeochemical functions, and even the types of species living in a certain area.  But ecologists’ scientific understanding of environmental conditions is hindered when soil moisture measurements disturb the research site, or when field measurements are not collected at biologically significant spatial or temporal granularities. Soil ecologist Dr. Kathy Szlavecz and her husband and computer scientist, Dr. Alex Szalay, both at Johns Hopkins University, are working to solve this dilemma by testing a wireless sensor network (WSN; Mesh Sensor Network), developed by Dr. Szalay, his colleague, computer scientist Dr. Andreas Terzis, and their graduate students. These generate thousands of measurements monthly from wireless sensors. The husband/wife team says that WSN have the potential to revolutionize soil ecology by generating a previously impossible spatial resolution.

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Architecture of an end-to-end mesh network data collection system. (Image: lifeunderyourfeet.org)

What is  a Mesh Network?

In a mesh wireless sensor network, specially designed radio units (nodes) use proprietary or open communications protocols to self-organize and can pass measurement information back to central units called gateways. Different from star networks where each node communicates directly to the gateway, mesh networks pass data to each other, acting as repeater for other nodes when necessary.

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These are the 37 sampling locations at the Smithsonian Environmental Research Center (SERC) in Edgewater, MD. Data from this deployment is aimed at understanding the effect of forest age, leaf litter input, and earthworm abundance on soil carbon cycling. (Image: lifeunderyourfeet.org)

With low power and reliability as their goal, they are deployed in dense networks to automatically measure conditions such as temperature and soil moisture. These node measurements are taken every few hours over several months. The data are then uploaded onto computers, where it can be maintained and searched. Kathy explains “Without an autonomous sensor system, experiments in need of accurate information about a multitude of environmental parameters on various spatial and temporal scales require a superhuman effort. The inexpensive nature of these sensors enable scientists to place a high-resolution grid of sensors in the field, and get frequent readouts.  This provides an extremely rich data set about the correlations and subtle differences among many parameters, allowing ecologists to design experiments that study not only the gross effects of environmental variables, but also the subtle relations between gradients and small temporal changes.”

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Without an autonomous sensor system, experiments in need of accurate information about a multitude of environmental parameters on various spatial and temporal scales require a superhuman effort.

Landscape Studies Benefit from Mesh Networks

Kathy and Alex have deployed mesh wireless sensor networks at several study areas around the state of Maryland.  Kathy says, “Once we record the measurements, we can combine that information with observations of soil organisms to better understand how soil organisms and the soil environment interact. This means we can make better predictions about how human activities will affect the soil environment.” In one urban landscape study, Kathy and her team deployed over 100 nodes around a CO2 flux tower looking at the two major landscape covers in an urban environment: grass and forest.  She explains, “We collected data from nodes connected to soil moisture and temperature sensors for over two years at these sites, and the system worked quite well. We collected about 180 million data points, and that’s no small feat.”

Next week: Learn the results of this research group’s mesh network testing and what Kathy thinks the future holds for this technology.

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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.

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.

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

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.”

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

Example of a typical monitoring station: Surface and sub-surface water elevation and EC monitoring wells, and soil moisture and EC at 30 and 60 cm depths. Sensors connected to 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.

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

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.

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

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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.

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

Some people blame the dams built in the 1970’s 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.”

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“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 says, “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.

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“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.”

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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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Measuring NDVI in a Greenhouse Presents Challenges (Part 2)

University of Georgia researcher, Shuyang Zhen, wanted to find out if she could optimize greenhouse irrigation with reference evapotranspiration calculated from environmental factors and a crop coefficient, using NDVI measurements to adjust for canopy size (see part 1). Learn the results of the experiment and how fast growth and flowering caused problems with the NDVI measurement.

setup-1

Shuyang’s experimental setup.

Fast Growth Causes Problems

Shuyang says because the plants grew so large, the canopy filled in beyond what the sensor could see.  That meant there was additional leaf area that participated in vapor loss which wasn’t identified by the NDVI sensor.  As the canopies approached moderate-to-high canopy densities, Shuyang observed that the NDVI readings became less responsive to increases in canopy size. To work around this problem, Shuyang tried to calculate a vegetation index called the Wide Dynamic Range Vegetation index with the spectral reflectance outputs of the two wavebands measured by the NDVI sensor. Shuyang says, “This index was supposed to improve the sensitivity at higher canopy density, so I transformed all my data and was surprised that it actually improved the sensitivity when the canopy density was lower.  But at a higher canopy density it wasn’t as effective.”

setup-2

The red flowers reflected a lot of red light compared to the leaves, which confused the NDVI measurement.

Plant flowering also caused problems with the NDVI measurement.   Shuyang explains, “We had one cultivar of petunia with red flowers which formed on top of the canopy. The red flowers reflected a lot of red light compared to the leaves, which confused the NDVI measurement.  The NDVI value gradually decreased when the plants started to flower. There was no way I could get around that issue, so in some of the replicates, I removed the flowers, and in some I kept the flowers so I could compare the different responses and characterize why it happened.”

NDVI

The NDVI was very sensitive to the increase in crop size when the canopy was relatively small, but when you reach a certain canopy size and the canopy closure was nearly complete, then the sensitivity decreased.

Summary and Future Studies

During the early stages of growth, the research team saw a linear relationship between NDVI and crop coefficient. However, when the crop coefficient reached higher values, the response leveled off.  Shuyang says, “The response failed to change with further increases in the crop coefficient. The NDVI was very sensitive to the increase in crop size when the canopy was relatively small, but when you reach a certain canopy size and the canopy closure was nearly complete, then the sensitivity decreased.”  

NDVI

Lack of NDVI sensitivity during canopy closure and flowering translated to a problem with under-irrigation,

Shuyang adds that the lack of NDVI sensitivity during canopy closure and flowering translated to a problem with under-irrigation, so the team is thinking about developing separate models for different canopy stages.  She explains, “When the canopy reaches high canopy closure we may have to add an additional coefficient to compensate for that underestimation, but it’s difficult to evaluate what kind of coefficient we should use without more data. We need to do more studies to get an idea of what kind of adjustments will make the prediction more precise.”

Learn more about Shuyang’s work on the University of Georgia horticulture blog.

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Measuring NDVI in a Greenhouse Presents Challenges

Greenhouse growers need irrigation strategies to maintain high plant quality, but it’s difficult to obtain quantitative information on exactly how much water will produce the highest-quality growth.

Greenhouse

Greenhouse plant canopies are highly variable.

Estimating irrigation needs by using reference evapotranspiration calculated from environmental factors and a crop coefficient is standard for controlling field crop irrigation, but in a greenhouse this method can be challenging.  Greenhouse plant canopies are highly variable, and there’s limited information on the crop coefficient values for ornamental crops.  

greenhouse

Researchers used a sensor-controlled automated irrigation system with soil moisture sensors.

Measuring Crop Size

University of Georgia researcher, Shuyang Zhen, wanted to find out if she could solve this problem for greenhouse growers using NDVI measurements to adjust for canopy size. In a greenhouse setting, she and her team planted four types of fast growing herbaceous plants in small containers on top of greenhouse benches.  They set up a small weather station to monitor environmental parameters and used that data to calculate reference evapotranspiration.  

greenhouse

NDVI measurements are a non-destructive, continuous monitoring method to get information as to how big a crop is.

Using a sensor-controlled automated irrigation system with soil moisture sensors, the team determined the amount of water the plants used, which allowed them to calculate a crop coefficient on a daily basis.  They then used NDVI measurements to monitor crop size.  Shuyang says, “It’s easy to monitor environmental factors such as light, temperature, relative humidity, and wind speed, but it’s much harder to determine how big the crop is because many methods are destructive and time-consuming.  We chose NDVI measurements as a non-destructive, continuous monitoring method to get information as to how big our crop was. We were specifically interested in looking at how NDVI changes with the crop coefficient and how those two parameters correlate with each other.”

greenhouse

Some species were more upward growing and some more sprawling.

Shuyang mounted multiple NDVI sensors on top of the benches, approximately four feet from the plants. Each sensor had a field of view of about .6 square meters and tracked the changes in plant size and NDVI values for over 8 weeks.  Shuyang says, “Each species had different growth habits.  Some species were more upward growing and some more sprawling. They also had different leaf chlorophyll content. Over the course of my study, three species reached reproductive stages, producing flowers. All of these factors had an effect on the NDVI measurements.”

Next week: Learn the results of the experiment and how fast growth and flowering caused problems with the measurement.

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Measuring Light and Photosynthesis (PAR): Complicated, but Worth It (Part 2)

In part 2 of our PAR Measurement Series (read part 1), Dr. Gaylon S. Campbell discusses the impact of leaf arrangement, measuring light in a canopy, and why we measure PAR.

PAR

Vertical leaves absorb less radiation when the sun is at a high angle, and more radiation when the sun is at a low angle; the converse is true for horizontal leaves.

Leaf Arrangement

Leaf display (angular orientation) affects light interception. Strictly vertical or horizontally oriented leaves are extreme cases, but a large range of angles occurs. Vertical leaves absorb less radiation when the sun is at a high angle, and more radiation when the sun is at a low angle; the converse is true for horizontal leaves. The greatest photosynthetic capacity can be achieved by a change from nearly vertical to nearly horizontal leaves lower down. This arrangement leads to effective beam penetration and a more even distribution of light.

PAR

The highest LAI’s usually occur in coniferous forests.

Leaf area index (LAI), a measure of the foliage in a canopy, is the canopy property that has most effect on interception of radiation. LAI usually ranges between 1 and 12. Values of 3-4 are typical for horizontal-leafed species such as alfalfa; values of 5-10 occur in vertical leafed species such as grasses and cereals, or in plants with highly clumped leaves, such as spruce. The highest LAI’s usually occur in coniferous forests, which have overlapping generations of leaves. These forests have a photosynthetic advantage due to longevity of individual needles.

PAR

PAR must be measured at a number of locations and then averaged.

Measuring Light in a Canopy

Variability of leaf distribution in canopies results in wide variations in light. To determine light at any height in the canopy, PAR must be measured at a number of locations and then averaged. Direct methods of measurement include using the horizontal line sensors whose output is the spatial average over the sensor length. The appropriate sensor length or number of sampling points depends on plant spacing.

Indirect methods for measuring canopy structure rely on the fact that canopy structure and solar position determine the radiation within the canopy. Because it’s hard to measure three dimensional distribution of leaves in a canopy, models for light interception and tree growth often assume random distribution throughout the canopy; however, leaves are generally aggregated or grouped.

PAR

Models for light interception and tree growth often assume random distribution throughout the canopy; however, leaves are generally aggregated or grouped.

Why Measure Photosynthesis or PAR?

The ability to measure PAR assists with understanding the unique spatial patterns that different plants have for displaying photosynthetic surfaces. Since effective use of PAR influences plant production, knowledge of the structural diversity of canopies aids research on plant productivity. One result: researchers can use information about different plants’ abilities to intercept and use PAR to engineer canopy structure modifications that significantly improve crop yield.

View our LAI application guide, or learn more about how researchers and growers use PAR measurement to improve crop yields.

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