Posts tagged ‘Canopy’

Jan 23

Piñon Pine: Studying the Effects of Climate Change on Drought Tolerance

In the name of science, Henry Adams has killed a lot of trees. Adams, a PhD student at the University of Arizona, is studying the effect of climate change and drought on Piñon Pines. The Piñon Pine, a conifer with an extensive root system, grows at high elevations in the Southwest. Its root system makes the Piñon Pine remarkably drought tolerant, but in 2002- 03, an extended drought in combination with a bark beetle outbreak killed 12,000 hectares of the trees. It was a 100 year drought, the driest period on record, and interestingly it coincided with temperatures 2 to 3˚C above recorded averages.

Biosphere 2 glass dome where researchers study the effects of climate change

Biosphere 2. Image: wickipedia.org.

Research in Biosphere 2

Adams and his advisors wondered if increasing temperatures due to climate change might exacerbate the effects of drought and accelerate tree die-off. The University of Arizona has an unusual opportunity to test drought conditions and temperature change in its Biosphere 2 lab. Biosphere 2, a unique 3-acre enclosed “living laboratory” in the high Arizona desert, once hosted 8 people for two years of self-contained survival living. Now it hosts research projects, and Adams was able to use space inside to induce drought in two separate treatments of transplanted Piñon pines, one at ambient temperatures and one at temperatures 4˚C above ambient.

Sobering Outlook for the Piñon Pine

“Obviously, the warmer trees should die first,” says Adams. “But we want to test whether temperature change, independent of other factors, accelerates mortality.” If that acceleration in fact occurs, a shorter drought, the kind the Piñon Pine has historically been able to wait out, might cause a significant die-off.

Image of a close up on a Piñon Pine branch

Piñon Pine. Image: Naturesongs.com

Measuring Drought Response

Naturally, Adams and his colleagues did more than just watch how fast trees would die without water. They also studied the trees physiological response to drought, measuring gas exchange, water potential, and stomatal conductance. To measure stomatal conductance, they used a leaf porometer, making almost 9,000 separate measurements in sessions that lasted from sunup to sundown on one very long day once each week.

Stomatal Conductance in Conifers

There isn’t much guidance in the porometer manual for people who want to use it on conifers, so Adams “played around with it a little bit” on non-drought stressed trees before he started his study. He found that the best way to get good readings was to cover the aperture with a single layer of needles. “Needles are this three-dimensional thing,” he explains. “They have stomata on several sides, depending on the species. If you imagine that the fingers on your hand are needles sticking up from a branch, we just took those and pushed them together to make sure that there was just a one needle thick covering over the aperture. If you spread your fingers, that’s what it would be like if you didn’t totally cover the aperture-then you underestimate the conductance. We also found that if we stuck several layers in there, we could drive the conductance number up.

Next week: Find out how the researchers made comparisons at leaf level, transplanted the trees, and future implications for the Piñon Pine.

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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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Oct 10

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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.

Researchers measuring the NDVI of green plants in a greenhouse

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.”

Researchers measuring NDVI of petunias in a greenhouse

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.”

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.”

Six poinsettia plants with small flowers arranged with one in the middle and five around the middle one in a circle

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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Oct 3

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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.

Picture of green house full of bright red Poinsettia plants

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.

Sensor-controlled, automated irrigation system in a 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.

Green plants being monitored in a 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.”

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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Sep 12

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

Dr. Gaylon S. Campbell discusses how to measure light and photosynthesis (PAR) in canopies and why it’s helpful to researchers.

Dandelion with a bright sun shining on it

The source of all energy on earth is the sun.

The ultimate source of all energy on earth is the sun. Availability of this energy to most organisms occurs through photosynthesis, the conversion of CO₂ and H₂O to carbohydrates (stored energy) and O₂. Photosynthesis occurs when pigments in photosynthesizers absorb the energy of photons, initiating a chain of photochemical and chemical events. Where does this energy and material exchange occur? In plant canopies. The amount of photosynthesis that occurs in canopies depends on the amount of photosynthetically active radiation (PAR) intercepted by leaves in canopies.

In canopies, leaves function collectively.

It’s More Complicated Than You Might Think

The rate at which photosynthesis occurs in one leaf might be calculated, but in canopies, leaves function collectively. Extrapolating photosynthesis from individual leaves to entire canopies is complex; the sheer numbers of leaves and their arrangement in the canopy structure can be overwhelming. Leaf area, inclination, and orientation all affect the degree to which light is captured and used in a canopy.

Tree canopy with sunlight breaking through the leaves

Average light level decreases exponentially downward through the canopy.

What Happens to Light in a Canopy?

Light varies dramatically both spatially and temporally through canopies. The average light level decreases more or less exponentially downward through the canopy, as the amount of leaf surface encountered increases. For some canopies, the greatest amount of leaf area occurs near the center. Therefore, canopy structure analysis becomes increasingly complex as one proceeds from a single plant to stands of the same plant, or to plant communities because of the variety of plants and growth forms.

Picture looking up from the ground at a tree canopy with sunlight breaking through the leaves

Photosynthesis depends on leaf orientation.

Absorption of radiation and resulting photosynthesis depend on leaf orientation, sun elevation in the sky, spectral distribution and multiple reflections of light, and the arrangement of leaves. Patterns of light and shaded areas can be complicated and change with the sun’s position. In addition, seasonality of foliage can result in fairly small canopy interception of PAR for much of the year. PAR might also be intercepted by non-photosynthetic parts of plants (bark, flowers, etc).

In two weeks: Dr. Campbell discusses the impact of leaf arrangement, measuring light in a canopy, and why we measure PAR.

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Sep 5

Can Canopy Measurements Determine Soil Moisture? (Part 2)

Dr. Y. Osroosh, now a researcher at Washington State University, believes that plants are the best soil moisture sensors (see part 1). He and his team have developed a new model for interpreting plant canopy signals to indirectly determine soil moisture in a Fuji apple orchard. Below are the results of their efforts and what he sees as the future of this research.

Could plants be the best indicators of soil moisture?

The Results

Osroosh says they expected to see correlations, but such strong relationships were unexpected. The team found that soil water deficit was highly correlated with thermal-based water stress indices in drip-irrigated apple orchard in the mildly-stressed range. The relationships were time-sensitive, meaning that they were valid only at a specific time of day. The measurements taken between 10:00am and 11:00am (late morning, time of maximum transpiration) were highly correlated with soil water deficit, but the “coefficient of determination” decreased quickly and significantly beyond this time window (about half in just one hour, and reached zero in the afternoon hours). Osroosh says this is a very important finding because researchers still think midday is the best time to measure canopy water stress index (CWSI). He adds, “The apple trees showed an interesting behavior which was nothing like what we are used to seeing in row crops. They regulate their stomata in a way that transpiration rate is intense late in the morning (maximum) and late in the afternoon. During the hot hours of afternoon, they close their stomata to minimize water loss.”

Researchers have found good relationships between CWSI and soil water content in the root zone near the end of the season at high soil water deficits in row crops.

Other Research

Osroosh points to other efforts which have tried to correlate remotely-sensed satellite-based thermal or NIR measurements to soil water content. He says, “The closest studies to ours have been able to find good relationships between CWSI and soil water content in the root zone near the end of the season at high soil water deficits in row crops. Paul Colaizzi, a research agricultural engineer did his PhD research in part on the relationship between canopy temperature, CWSI, and soil water status in Maricopa, Arizona; also motivated by Jackson et al. (1981). Steve Evett and his team at Bushland, Texas are continuing that research as they try to develop a relationship between CWSI and soil water status that will hold up. They are using a CWSI that is integrated over the daylight hours and have found good relationships between CWSI and soil water content in the root zone near the end of the season when plots irrigated at deficits begin to develop big deficits.”

Osroosh wants to study other apple cultivars, tree species, and perhaps even row crops, under other irrigation systems and climates.

What’s The Future?

In the future, Osroosh hopes to study the limitations of this approach and to find a better way to monitor a large volume of soil in the root zone in real-time (as reference). He says, “We would like to see how universal these equations can be. Right now, I suspect they are crop and soil-specific, but by how much we don’t know. We want to study other apple cultivars, tree species, and perhaps even row crops, under other irrigation systems and climates. We need to monitor crops for health, as well, to make sure what we are measuring is purely a water stress signal. One of our major goals is to develop a sensor-based setup which, after calibration, can be used for “precise non-contact sensing of soil water content” and “stem water potential” in real-time by measuring canopy temperature and micrometeorological parameters.”

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Aug 29

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Can Canopy Measurements Determine Soil Moisture?

As a young university student, Dr. Y. Osroosh, now a researcher at Washington State University, wanted to design the most accurate soil moisture sensor. Over the years, however, he began to realize the complexity and difficulty of the task. Inspired by the work of Jackson et al. (1981) and researchers in Bushland, TX, he now believes that plants are the best soil moisture sensors. He and his team developed a new model for interpreting plant canopy signals to indirectly determine soil moisture.

The team measured microclimatic data in an apple orchard.

How Can Plants Indicate Water in Soil?

Osroosh and his team wanted to use plant stress instead of soil sensors to make irrigation decisions in a drip-irrigated Fuji apple tree orchard. But, the current practice of using the crop water stress index (CWSI) for detecting water stress presented some problems, Osroosh comments, “Currently, scientists use either an empirical CWSI or a theoretical one developed using equations from FAO-56, but the basis for FAO-56 equations is alfalfa or grass, which isn’t similar to apple trees.” One of the main differences between grass and apple trees is that apple tree leaves are highly linked to atmospheric conditions. They control their stomata to avoid water loss.

There is high degree of coupling between apple leaves and the humidity of the surrounding air.

So Osroosh borrowed a leaf porometer to measure the stomatal conductance of apple trees, and he developed his own crop water stress index, based on what he found. He explains, “We developed a new theoretical crop water stress index specifically for apple trees. It accounts for stomatal regulations in apple trees using a canopy conductance sub-model. It also estimates average actual and potential transpiration rates for the canopy area which is viewed by a thermal infrared sensor (IRT).”

Fuji open air apple orchard (Roza Farm, Prosser, WA).

Fuji apple orchard (Roza Farm, Prosser, WA) where Osroosh performed his research.

What Data Was Used?

Osroosh says they established their new “Apple Tree” CWSI based on the energy budget of a single apple leaf, so “soil heat flux” was not a component in their modeling. He and his team measured soil water deficit using a neutron probe in the top 60 cm of the profile, and they collected canopy surface temperature data using thermal infrared sensors. The team also measured microclimatic data in the orchard.

Neutron probes were problematic, as they did not allow collection of data in real time.

Osroosh comments, “The accuracy of this approach greatly depends on the accuracy of reference soil moisture measurement methods. To establish a relationship between CWSI and soil water, we needed to measure soil water content in the root zone precisely. We used a neutron probe, which provides enough precision and volume of influence to meet our requirements. However, it was a labor and time intensive method which did not allow for real-time measurements, posing a serious limitation.”

Next week: Learn the results of Dr. Osroosh’s experiments, the future of this research, and about other researchers who are trying to achieve similar goals.

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Jul 8

Improving Drought Tolerance in Soybean

Limited water availability is a significant issue threatening the agricultural productivity of soybean, reducing yields by as much as 40 percent. Due to climate change, varieties with improved drought tolerance are needed, but phenotyping drought tolerance in the field is challenging, mainly because field drought conditions are unpredictable both spatially and temporally. This has led to the genetic mechanisms governing drought tolerance traits to be poorly understood. Researcher Clinton Steketee at the University of Georgia is trying to improve soybean drought tolerance by using improved screening techniques for drought tolerance traits, identifying new drought tolerant soybean germplasm, and clarifying which genomic regions are responsible for traits that help soybeans cope with water deficit.

Researchers are trying to improve soybean drought tolerance by using better screening techniques for drought tolerance traits.

Which Traits Are Important?

Clinton and his colleagues are evaluating a genetically diverse panel of 211 soybean lines in two different states, Kansas and Georgia, for over two years to help him accomplish his research objectives. These 211 lines come from 30 countries and were selected from geographical areas with low annual precipitation and newly developed soybean lines with enhanced drought-related traits, along with drought susceptible checks. The researchers are looking at traits such as canopy wilting. Some plants will take a few days longer to wilt, allowing these plants to continue their photosynthetic ability to produce biomass for seed production. Other traits that he is interested in evaluating are stomatal conductance, canopy temperature with thermal imaging, relative water content, and carbon isotope discrimination.

The scientists want to monitor traits such as canopy wilting.

Use of Microclimate Stations to Monitor Environmental Conditions

Clinton says to make selection of drought-tolerant lines easier and more predictable, knowledge of field environmental conditions is critical. He says, “You can phenotype all you want, but you need the true phenotype of the plant to be observed under real drought conditions so you can discover the genes for drought tolerance and improve resistance down the line in a breeding program.”

In addition to soil moisture sensors, the team used microclimate weather stations to help monitor water inputs at their two field research sites and determine ideal time periods for phenotyping drought-related traits. Steketee says, “We put microenvironment monitors in the field next to where we were growing our experimental materials. Both locations use those monitors to keep an eye on weather conditions throughout the growing season, measuring temperature, humidity, and precipitation. Since we could access the data remotely, we used that information to help us determine when it was time to go out to the field and look at the plots. We wanted to see big differences between soybean plants if possible, especially in drought conditions. By monitoring the conditions we could just go back to our weather data to show we didn’t get rain for 3 weeks before we took this measurement, proving that we were actually experiencing drought conditions.”

The team identified some lines that performed well.

Results So Far

Though 2015 wasn’t a great year for drought in Georgia, Clinton says there was a period in late July when he was able to measure canopy wilting, and they identified some lines that performed well. He says, “We compared our data to the data collected by our collaborator in Kansas, and there are a few lines that did well in both locations. Hopefully, another year of data will confirm that these plants have advantageous drought tolerance traits, and we’ll be able to probe the advantageous traits out of those lines and integrate them into our breeding program.”

Future Plans

The team will use what’s called a genome-wide association study approach to identify genomic regions responsible for drought tolerance traits of interest. This approach uses phenotypic information collected from the field experiments along with DNA markers throughout the soybean genome to see if that marker is associated with the trait they are interested in. If the scientists find the spot in the genome that is associated with the desired trait, they will then develop genomic tools to be used for selection, integrate that trait into elite germplasm, and ultimately improve the drought tolerance of soybeans.

See weather sensor performance data for the ATMOS 41 weather station.

Explore which weather station is right for you.

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Jan 22

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The Quest for Accurate Air Temperature (Part 1)

Mark Blonquist, chief scientist at Apogee Instruments and air temperature measurement expert, explains the difficulties of obtaining accurate air temperature.

Air Temperature gauge at the foot of a tree

The accuracy of air temperature has come a long way.

Accurate air temperature measurements are challenging, despite decades of research and development aimed at improving instruments and methods. People assume that they can use a static louvered radiation shield along with a temperature sensor and start measuring accurate air temperature. That assumption is good if you are at a site where the wind blows all the time (roughly greater than 3 m/s). However, if the wind at your field site is below that, you’re going to see errors due to solar heating (See Figure 1).

Figure 1: Passive Shield Error: Data for 3 different models are graphed.

Challenge 1: Accurate Sensors

Over the years, thermocouples, thermistors, and platinum resistance thermometers (PRTs) have been used for air temperature measurement, each with associated advantages and disadvantages. PRTs have the reputation as the preferred sensor for air temperature measurement due to high accuracy and stability. However, thermistors have high signal-to-noise ratio, are easy to use and low cost, and have similar accuracy and stability to PRTs. Thermocouples are becoming less commonly used for air temperature measurement because of the requirement of accurate measurement of reference temperature (i.e., meter temperature, data logger panel temperature).

Challenge 2: Housing Air Temperature Sensors

The challenge of accurate air temperature measurement is far greater than having an accurate sensor, as temperature measured by an air temperature sensor is not necessarily equal to air temperature. Temperature sensors must be kept in thermal equilibrium with air through proper shielding in order to provide accurate measurements. To do this, housings should minimize heat gains and losses due to conduction and radiation, and enhance coupling to air via convective currents. They must shield it from shortwave (solar) radiant heating and longwave radiant cooling. A temperature sensor should also be thermally isolated from the housing to minimize heat transport to and from the sensor by conduction. The housing should provide ventilation so the temperature sensor is in thermal equilibrium with the air. Also, the housing should keep precipitation off the sensor, which is necessary to minimize evaporative cooling of the sensor. Conversely, condensation on sensors can cause warming. When condensed water subsequently evaporates, it cools the sensor via removal of latent heat (evaporational cooling).

Challenge 3: Size of Sensor

The magnitude of wind speed effects on air temperature measurement in passive shields is highly dependent on the thermal mass (size) of the sensor. Many weather stations have combined relative humidity and temperature sensors, which are much larger than a stand-alone air temperature sensor. Air temperature errors from larger probes are greater than those from smaller sensors. One study, Tanner (2001), reported results where a common temperature/RH probe was approximately 0.5 degrees C warmer than a common thermistor in a weather-proof housing.

Thermal mass of temperature sensors also has a major impact on sensor response time. Sensors with small thermal mass equilibrate and respond to changes quicker and are necessary for applications requiring high-frequency air temperature measurements.

Challenge 4: Proper Shielding

In addition to an accurate sensor, accurate air temperature measurement requires proper shielding and ventilation of the sensor. Active, fan aspiration improves accuracy under conditions of low wind but requires power to operate the fan. Passive, natural aspiration minimizes power use but can reduce accuracy in conditions of high solar load or low wind speed. Radiation shields for air temperature sensors should be placed in an environment where air temperature is representative. For example, air temperature sensors and radiation shields should not be deployed on the tops of buildings or in areas where they will be shaded by structures or trees. Conditions in microenvironments have that potential to be very different from surrounding conditions. Typical mounting heights for air temperature sensors are 1.2 to 2.0 meters above the ground. Typically, radiation shields should be mounted over vegetation.

Up next: Mark Blonquist explains the complexities of some of the proposed solutions to the above challenges in part 2.

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Jan 1

Environmental Biophysics: Top Five Blog Posts in 2015

In case you missed our best blogs, below are the five most-viewed Environmental Biophysics posts in 2015.

Sunflower field in Hokkaido

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 scientific progress. Here’s what he had to say.

Conifer

Environmental Biophysics Lectures

Cherries

Sensor Data Improves Cherry Production

Dr. Khot and his postdoc, Dr. Jianfeng Zhou, are using leaf wetness sensors to determine if and how long water is present on cherry tree canopies after a rain event. Dr. Khot hopes that data from these sensors will help growers decide whether or not it makes sense to fly helicopters in order to dry the canopies.

Maple leaf

What is the Future of Sensor Technology?

Dr. John Selker, hydrologist at Oregon State University and one of the scientists behind the Trans African Hydro and Meteorological Observatory (TAHMO) project, gives his perspective on the future of sensor technology.

Riverbank

Sensors Validate California Groundwater Resource Management Techniques

Michelle Newcomer, a PhD candidate at UC Berkeley, (previously at San Francisco State University), recently published research using rain gauges, soil moisture, and water potential sensors to determine if low impact design (LID) structures such as rain gardens and infiltration trenches are an effective means of infiltrating and storing rainwater in dry climates instead of letting it run off into the ocean.

Looking up at a tree canopy

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Measuring and Modeling the Environment

Posts tagged ‘Canopy’

Research in Biosphere 2

Sobering Outlook for the Piñon Pine

Measuring Drought Response

Stomatal Conductance in Conifers

And our three most popular blogs of all time:

Fast Growth Causes Problems

Summary and Future Studies

Measuring Crop Size

It’s More Complicated Than You Might Think

What Happens to Light in a Canopy?

The Results

Other Research

What’s The Future?

How Can Plants Indicate Water in Soil?

What Data Was Used?

Which Traits Are Important?

Use of Microclimate Stations to Monitor Environmental Conditions

Results So Far

Future Plans

Challenge 1: Accurate Sensors

Challenge 2: Housing Air Temperature Sensors

Challenge 3: Size of Sensor

Challenge 4: Proper Shielding