In this brief 30-minute webinar, Dr. John Gammon, University of Alberta, teaches the basics of the Photochemical Reflectance Index (PRI).
He gives a introduction to the photochemical reflectance index and what it can tell researchers about xanthophyll cycle activity, carotenoid: chlorophyll pigment ratios, light-use efficiency, and plant stress. He also discusses remote sensing.
Time Domain Reflectometry (TDR) vs. capacitance is a common question for scientists who want to measure volumetric water content (VWC) of soil, but is it the right question? Dr. Colin S. Campbell, soil scientist, explains some of the history and technology behind TDR vs. capacitance and the most important questions scientists need to ask before investing in a sensor system. Read more…
Modern technology has made it possible to sample Normalized Difference Vegetation Index (NDVI) across a range of scales both in space and in time, from satellites sampling the entire earth’s surface to handheld small sensors that measure individual plants or even leaves. Read more…
Globally, the gap between the energy production and consumption is growing wider. To promote sustainability, University of California San Diego PhD candidate and ASCE GI Sustainability in Geotechnical Engineering committee member, Tugce Baser, Dr. John McCartney, Associate Professor, and their research team, Dr. Ning Lu, Professor at Colorado School of Mines and Dr. Yi Dong, Postdoctoral Researcher at Colorado School of Mines, are working on improving methods for borehole thermal energy storage (BTES), a system which stores solar heat in the soil during the summer months for reuse in homes during the winter. Read more…
Weather data, used for flight safety, disaster relief, crop and property insurance, and emergency services, contributes over $30 billion in direct value to U.S. consumers annually. Since the 1990’s in Africa, however, there’s been a consistent decline in the availability of weather observations. Read more…
Plants require nutrients to grow, and if we fail to supply the proper nutrients in the proper concentrations, plant function is affected. Fertilizer in too high concentration can also affect plant function, and sometimes is fatal. Read more…
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…
We were inspired by this Freakonomics podcast, which highlights the book, This Idea Must Die: Scientific Problems that are Blocking Progress, to come up with our own answers to the question: Which scientific ideas are ready for retirement? 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…
This week, guest author Dr. Michael Forster, of Edaphic Scientific Pty Ltd & The University of Queensland, writes about new research using irrigation curves as a novel technique for irrigation scheduling.
Growers do not have the time or resources to investigate optimal hydration for their crop. Thus, a new, rapid assessment is needed.
Measuring the hydration level of plants is a significant challenge for growers. Hydration is directly quantified via plant water potential or indirectly inferred via soil water potential. However, there is no universal point of dehydration with species and crop varieties showing varying tolerance to dryness. What is tolerable to one plant can be detrimental to another. Therefore, growers will benefit from any simple and rapid technique that can determine the dehydration point of their crop.
New research by scientists at Edaphic Scientific, an Australian-based scientific instrumentation company, and the University of Queensland, Australia, has found a technique that can simply and rapidly determine when a plant requires irrigation. The technique builds on the strong correlation between transpiration and plant water potential that is found across all plant species. However, new research applied this knowledge into a technique that is simple, rapid, and cost-effective, for growers to implement.
Current textbook knowledge of plant dehydration
The classic textbook values of plant hydration are field capacity and permanent wilting point, defined as -33 kPa (1/3 Bar) and -1500 kPa (15 Bar) respectively. It is widely recognized that there are considerable limitations with these general values. For example, the dehydration point for many crops is significantly less than 15 Bar.
Furthermore, values are only available for a limited number of widely planted crops. New crop varieties are constantly developed, and these may have varying dehydration points. There are also many crops that have no, or limited, research into their optimal hydration level. Lastly, textbook values are generated following years of intensive scientific research. Growers do not have the time, or resources, to completely investigate optimal hydration for their crop. Therefore, a new technique that provides a rapid assessment is required.
How transpiration varies with water potential
There is a strong correlation between transpiration and plant water potential: as plant water potential becomes more negative, transpiration decreases. Some species are sensitive and show a rapid decrease in transpiration; other species exhibit a slower decrease.
Plant physiologist refer to P50 as a value that clearly defines a species’ tolerance to dehydration. One definition of P50 is the plant water potential value at which transpiration is 50% of its maximum rate. P50 is also defined as the point at which hydraulic conductance is 50% of its maximum rate. Klein (2014) summarized the relationship between transpiration and plant water potential for 70 plant species (Figure 1). Klein’s research found that there is not a single P50 for all species, rather there is a broad spectrum of P50 values (Figure 1).
Figure 1. The relationship between transpiration (stomatal conductance) and leaf water potential for 70 plant species. The dashed red lines indicate the P80 and P50 values. The irrigation refill point can be determined where the dashed red lines intersect with the data on the graph. Image has been adapted from Klein (2014), Figure 1b.
Taking advantage of P50
The strong, and universal, relationship between transpiration and water potential is vital information for growers. A transpiration versus water potential relationship can be quickly, and easily, established by any grower for their specific crop. However, as growers need to maintain optimum plant hydration levels for growth and yield, the P50 value should not be used as this is too dry. Rather, research has shown a more appropriate value is possibly the P80 value. That is, the water potential value at the point that transpiration is 80% of its maximum.
Irrigation Curves – a rapid assessment of plant hydration
Research by Edaphic Scientific and University of Queensland has established a technique that can rapidly determine the P80 value for plants. This is called an “Irrigation Curve” which is the relationship between transpiration and hydration that indicates an optimal hydration point for a specific species or variety.
Once P80 is known, this becomes the set point at which plant hydration should not go beyond. For example, a P80 for leaf water potential may be -250 kPa. Therefore, when a plant approaches, or reaches, -250 kPa, then irrigation should commence.
P80 is also strongly correlated with soil water potential and, even, soil volumetric water content. Soil water potential and/or content sensors are affordable, easy to install and maintain, and can connect to automated irrigation systems. Therefore, establishing an Irrigation Curve with soil hydration levels, rather than plant water potential, may be more practical for growers.
Example irrigation curves
Irrigation curves were created for a citrus (Citrus sinensis) and macadamia (Macadamia integrifolia). Approximately 1.5m tall saplings were grown in pots with a potting mixture substrate. Transpiration was measured daily, between 11am and 12pm, with a SC-1 Leaf Porometer. Soil water potential was measured by combining data from an MPS-6 Matric Potential Sensor and WP4 Dewpoint Potentiometer. Soil water content was measured with a GS3 Water Content, Temperature and EC Sensor. Data from the GS3 and MPS-6 sensors were recorded continuously at 15-minute intervals on an Em50 Data Logger. When transpiration was measured, soil water content and potential were noted. At the start of the measurement period, plants were watered beyond field capacity. No further irrigation was applied, and the plants were left to reach wilting point over subsequent days.
Figure 2. Irrigation Curves for citrus and macadamia based on soil water potential measurements. The dashed red line indicates P80 value for citrus (-386 kPa) and macadamia (-58 kPa).
Figure 2 displays the soil water potential Irrigation Curves, with a fitted regression line, for citrus and macadamia. The P80 values are highlighted in Figure 2 by a dashed red line. P80 was -386 kPa and -58 kPa for citrus and macadamia, respectively. Figure 3 shows the results for the soil water content Irrigation Curves where P80 was 13.2 % and 21.7 % for citrus and macadamia, respectively.
Figure 3. Irrigation Curves for citrus and macadamia based on soil volumetric water content measurements. The dashed red line indicates P80 value for citrus (13.2 %) and macadamia (21.7 %).
From these results, a grower should consider maintaining soil moisture (i.e. hydration) above these values as they can be considered the refill points for irrigation scheduling.
Further research is required
Preliminary research has shown that an Irrigation Curve can be successfully established for any plant species with soil water content and water potential sensors. Ongoing research is currently determining the variability of generating an Irrigation Curve with soil water potential or content. Other ongoing research includes determining the effect of using a P80 value on growth and yield versus other methods of establishing a refill point. At this stage, it is unclear whether there is a single P80 value for the entire growing season, or whether P80 shifts depending on growth or fruiting stage. Further research is also required to determine how P80 affects plants during extreme weather events such as heatwaves. Other ideas are also being investigated.
For more information on Irrigation Curves, or to become involved, please contact Dr. Michael Forster: firstname.lastname@example.org
Klein, T. (2014). The variability of stomatal sensitivity to leaf water potential across tree species indicates a continuum between isohydric and anisohydric behaviours. Functional Ecology, 28, 1313-1320. doi: 10.1111/1365-2435.12289
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Dr. Colin Campbell, METER soil scientist, explains soil sensor differences, pros, cons, and things to consider when choosing which sensor will best accomplish your research goals. Use the following considerations to help identify the perfect sensor for your research. Explore the links for a more in-depth look at each topic.
Scientists often measure soil moisture at different depths to understand the effects of soil variability and to observe how water is moving through the soil profile.
CHOOSE THE RIGHT MEASUREMENT
Volumetric Water Content: If a researcher wants to measure the rise and fall of the amount (or percentage) of water in the soil, they will need soil moisture sensors. Soil is made up of water, air, minerals, organic matter, and sometimes ice. As a component, water makes up a percentage of the total. To directly measure soil water content, one can calculate the percentage on a mass basis (gravimetric water content) by comparing the amount of water, as a mass, to the total mass of everything else. However, since this method is labor-intensive, most researchers use soil moisture sensors to make an automated volume-based measurement called Volumetric Water Content (VWC). METER soil moisture sensors use high-frequency capacitance technology to measure the Volumetric Water Content of the soil, meaning they measure the quantity of water on a volume basis compared to the total volume of the soil. Applications that typically need soil moisture sensors are watershed characterization, irrigation scheduling, greenhouse management, fertigation management, plant ecology, water balance studies, microbial ecology, plant disease forecasting, soil respiration, hydrology, and soil health monitoring.
Water potential: If you need an understanding of plant-available water, plant water stress, or water movement (if water will move and where it will go), a water potential measurement is required in addition to soil moisture. Water potential is a measure of the energy state of the water in the soil, or in other words, how tightly water is bound to soil surfaces. This tension determines whether or not water is available for uptake by roots and provides a range that tells whether or not water will be available for plant growth. In addition, water always moves from a high water potential to a low water potential, thus researchers can use water potential to understand and predict the dynamics of water movement.
Understand your soil type and texture
In soil, the void spaces (pores) between soil particles can be simplistically thought of as a system of capillary tubes, with a diameter determined by the size of the associated particles and their spatial association. The smaller the size of those tubes, the more tightly water is held because of the surface association.
Clay holds water more tightly than a sand at the same water content because clay contains smaller pores and thus has more surface area for the water to bind to. But even sand can eventually dry to a point where there is only a thin film of water on its surfaces, and water will be bound tightly. In principle, the closer water is to a surface, the tighter it will be bound. Because water is loosely bound in a sandy soil, the amount of water will deplete and replenish quickly. Clay soils hold water so tightly that water movement is slow. However, there is still available water.
Note: Use the PARIO soil texture analyzer to automate soil texture identification.
Two measurements are better than one
In all soil types and textures, soil moisture sensors are effective at measuring the percentage of water. Dual measurements—using a water potential sensor in addition to a soil moisture sensor—gives researchers the total soil moisture picture and are much more effective at determining when, and how much, to water. Water content data show subtle changes due to daily water uptake and also indicate how much water needs to be applied to maintain the root zone at an optimal level. Water potential data determine what that optimal level is for a particular soil type and texture.
University of Idaho graduate student and past Grant A. Harris Fellowship recipient, Adrianne Zuckerman, is taking a different approach to stream restoration than the traditional approach, channel manipulation, which often requires heavy equipment and major disruption to the riparian area.
Zuckerman set out to understand how vegetation lining the stream bank impacts habitat quality for anadromous salmon and steelhead in Washington’s Methow River, which flows through the eastern Cascades. Zuckerman wanted to know how tree species composition affects the amount of nutrients available to the benthic insect community, since they are a critical food source for young salmonid fish.
When Zuckerman began investigating methods for measuring leaf contribution to the stream, she found that leaf litter traps were the standard equipment. Leaf litter traps are time consuming to set and maintain, and data analysis consists of frequent visits to the field followed by extensive time in the lab processing leaf material.
Looking for an alternative method, she discovered the LP-80 ceptometer: a lightweight, field-portable instrument for measuring leaf area index. Using the LP-80, Zuckerman was able to rapidly assess the leaf area contribution of each tree species along the riparian corridor. Using this information, it was relatively straightforward for her to estimate the contribution of each tree species to the stream food web.
Zuckerman’s research will help land managers and other researchers understand the importance of riparian vegetation for maximizing the food available to salmonid fish species. Improvement and maintenance of optimal stream-side vegetation composition should ultimately help to enhance salmon populations in the Pacific Northwest.
Receive $10,000 in METER research instrumentation
The Grant A. Harris Fellowship awards $40,000 in research instrumentation (four $10,000 awards) annually to graduate students studying any aspect of agricultural, environmental, or geotechnical science. METER is now accepting applications for the 2018 award. Learn more about how to apply for the Grant A. Harris Fellowship here.
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Water potential is the most fundamental and essential measurement in soil physics because it describes the force that drives water movement.
Water potential helps researchers determine how much water is available to plants.
Making good water potential measurements is largely a function of choosing the right instrument and using it skillfully. In an ideal world, there would be one instrument that simply and accurately measured water potential over its entire range from wet to dry. In the real world, there is an assortment of instruments, each with its unique personality. Each has its quirks, advantages, and disadvantages. Each has a well-defined range.
Below is a comparison of water potential instruments and the ranges they measure.
A comparison of water potential instrument ranges
To learn more about measuring water potential, see the articles or videos below:
In an effort to find sustainable energy solutions for heating and cooling buildings, many homeowners, companies, and university campuses are turning to ground-source heat exchange systems (GSHE) to reduce energy usage and greenhouse gas emissions. GSHE systems are designed to take advantage of the moderate and nearly constant temperatures in the ground as the exchange medium for space heating and cooling and to heat water for domestic use.
Some universities are exploring the development of GHSE systems.
In these systems, water or specially formulated geothermal fluid is circulated through plastic pipes (i.e., ground loops) installed in vertical boreholes. In the winter, geothermal loops tap heat from the ground, while in the summer, heat from the surface is transferred into the ground. Currently, the application of ground-source heat exchange systems reduces overall carbon emissions by up to 50%, and according to the U.S. Department of Energy, they are up to 4 times more efficient than gas furnaces.
But are GSHE systems as efficient as they claim to be? The answer, according to researchers at the University of Illinois at Urbana-Champaign (UIUC), is that it depends. Drs. Yu-Feng Forrest Lin and Andrew Stumpf and their associates at the Illinois State Geological Survey (a division of the Prairie Research Institute) at the UIUC and their collaborator, Dr. James Tinjum from the University of Wisconsin–Madison (UWM), are working on a project funded by the UIUC Student Sustainability Committee (SSC) to improve the efficiency of GSHE systems. They also hope to show that ground-source heat exchange systems systems could be included in the University’s multifaceted sustainability plan to reduce carbon emissions on campus to zero by 2050. Members of their research team are trying to determine whether GSHE systems would be feasible for heating and cooling buildings on campus with the existing subsurface geologic conditions.
Diagram showing ~50% reduction of energy using GHSEs (from USEPA)
The UIUC is not the first university to explore the development of GSHE systems. For example, Ball State University recently replaced its coal-powered heating and cooling system on campus with a large district-scale GSHE system. Other universities with similar systems include the Missouri Institute of Science and Technology and the University of Notre Dame. These ground-source heat exchange systems are specifically designed to meet future energy needs. However, as Dr. Stumpf notes, “Historically, quite a few large district-scale systems have not achieved their projected efficiencies. Some systems have even overheated the ground, forcing them to go off-line. We’re trying to come up with a way to make borehole fields more efficient and prevent these hazards from occurring.”
Why do some ground-source heat exchange systems not meet their efficiency targets?
Dr. Stumpf explains that many times, the contractors that install ground-source heat exchange systems do a single conductivity measurement in the borehole. Or they run a thermal response test (TRT) and then use these calculations to determine the conductivity of the geologic materials at the proposed site. In many cases, however, especially for district-scale GSHE systems with multiple large borefields and a complex geology, this information does not adequately characterize the site conditions. He states, “Because only limited measurements are taken, many systems have developed problems and are unable to keep up with the thermal demands.”
University of Illinois campus.
To assist contractors and other groups involved in designing and installing ground-source heat exchange systems, the UIUC research team is studying the thermal conditions in a shallow geoexchange system and collecting data from geologic samples from a 100-m-deep borehole located on the UIUC Energy Farm. A fiber-optic distributed temperature sensing (FO-DTS) system is being used to collect detailed temperature measurements in this borehole during and after a TRT. The FO-DTS system is an emerging technology that utilizes laser light to measure temperature along the entire length of a standard telecommunications fiber-optic cable. By analyzing the laser’s backscattered energy, the team can estimate temperatures along the entire sensor cable as a continuous profile. The ground temperature can be measured every 15 seconds, in every meter along the cable, with a resolution from 0.1 to 0.01 °C (depending on the measurement integration time). These data can be integrated with the TRT results, ultimately providing a better understanding of the subsurface thermal profile, which will lead to increasing the efficiency of the GSHE system.
Continuous core collected from the 100-m borehole was subsampled to measure the thermal properties of the subsurface geologic units, and testing was performed at the UWM with a thermal properties analyzer. The resulting information will provide a better understanding of how thermal energy is stored and transported in the subsurface.
Geologic and geophysical logs from the borehole at the UIUC Energy Farm
How is the UIUC Energy Farm site unique?
Dr. Stumpf states that the ground under the UIUC Energy Farm includes various geologic materials that conduct heat differently and require some additional design considerations. He explains, “The upper 60 m of the borehole was drilled into glacial sediment, including till, outwash (sand and gravel), and lake sediment (silt and clay), which have different thermal conductivities. Flowing groundwater in the sand and gravel units also increases the thermal transport. Conversely, the bottom 40 m of the borehole penetrated Pennsylvanian-age bedrock, mostly shale and siltstone, which included layers of coal. Unlike the other lithologies, coal has a very low thermal conductivity and is therefore not optimal for a GSHE system. The most efficient GSHE systems avoid low-conductivity geologic units and are optimized to take advantage of flowing groundwater.
Soil moisture release curves have always had two weak areas: a span of limited data between 0 and -100 kPa and a gap around field capacity where no instrument could make accurate measurements.
Using HYPROP with the redesigned WP4C, a skilled experimenter can now make complete high resolution moisture release curves.
Between 0 and -100 kPa, soil loses half or more of its water content. If you use pressure plates to create data points for this section of a soil moisture release curve, the curve will be based on only five data points.
And then there’s the gap. The lowest tensiometer readings cut out at -0.85 MPa, while historically the highest WP4 water potential meter range barely reached -1 MPa. That left a hole in the curve right in the middle of plant-available range.
The conversion of light energy and atmospheric carbon dioxide to plant biomass is fundamentally important to both agricultural and natural ecosystems.
The detailed biophysical and biochemical processes by which this occurs are well understood. At a less-detailed level, however, it is often useful to have a simple model that can be used to understand and analyze parts of an ecosystem. Such a model has been provided by Monteith (1977). He observed that when biomass accumulation by a plant community is plotted as a function of the accumulated solar radiation intercepted by the community, the result is a straight line. Figure 1 shows Monteith’s results.
Figure 1. Total dry matter produced by a crop as a function of total intercepted radiation (from Monteith, 1977).
The PHYTOS 31 Leaf Wetness Sensor was designed to measure the presence and duration of water on leaf surfaces. However, Dr. Bruce Bugbee, professor of Crop Physiology at Utah State University, noticed that his leaf wetness sensor revealed interesting phenomena associated with some precipitation events. Here is what he observed on a recent day at the USU Environmental Observatory in Logan, Utah
It is possible to have a day with numerous 0.1 mm increments of rain, followed by some evaporation, in which a rain gauge would not record any rain during the day.
“Recent data from our weather station provided two examples of the offset in measurement associated with tipping bucket rain gauges. It started raining on campus last night at exactly 20:00 hours, as indicated by the response of the leaf wetness sensor (Figure 1). The first 0.1 mm tip of the rain gauge occurred about 25 minutes later (Figure 2). The resolution for most high-quality tipping bucket rain gauges is listed as 0.1 mm, but this is not the resolution for the first 0.1 mm of rain.