The secondary products of a lightning strike include electromagnetic pulses, electrostatic pulses, and earth current transients.
Surge suppression components typically perform their suppression function by temporarily short circuiting the voltage between two wires, several devices, or ground.
Electromagnetic pulses are created by the strong magnetic field that is formed by the short term current flow taking place in the lightning strike. With current flows as high as 510kA per microsecond, these currents create very large magnetic fields. These short-term magnetic fields then induce voltages onto wires and cables.
Electrostatic pulses are created by electrostatic fields that accompany a thunderstorm. Any cable suspended above the earth during a thunderstorm is immersed in the electrostatic field and will be electrically charged. Quick changes in the charges stored in both the clouds and earth take place whenever there is a lightning strike. The charge on the cable must now be discharged or neutralized. Unable to find a path to ground (earth), it breaks down insulation and component in its efforts to return to earth.
Earth current transients are the direct result of the neutralization process that immediately follows the end of lightning strike. Neutralization is accomplished by the movement or redistribution of charge along or near the earth’s surface from all the points where the charge had been initially induced to the point where the lightning strike has just terminated. Earth current transients create a shift in potential across a ground plan, often called a “ground bounce”.
Patterns of water replenishment and use give rise to large spatial variations in soil moisture over the depth of the soil profile. Accurate measurements of profile water content are therefore the basis of any water budget study. When monitored accurately, profile measurements show the rates of water use, amounts of deep percolation, and amounts of water stored for plant use.
Three common challenges to making high-quality volumetric water content measurements are:
making sure the probe is installed in undisturbed soil,
minimizing disturbance to roots and biopores in the measurement volume, and
eliminating preferential water flow to, and around, the probe.
All dielectric probes are most sensitive at the surface of the probe. Any loss of contact between the probe and the soil or compaction of soil at the probe surface can result in large measurement errors. Water ponding on the surface and running in preferential paths down probe installation holes can also cause large measurement errors.
Installing soil moisture sensors will always involve some digging. How do you accurately sample the profile while disturbing the soil as little as possible? Consider the pros and cons of five different profile sampling strategies.
Preferential flow is a common issue with commercial profile probes
Profile probes are a one-stop solution for profile water content measurements. One probe installed in a single hole can give readings at many depths. Profile probes can work well, but proper installation can be tricky, and the tolerances are tight. It’s hard to drill a single, deep hole precisely enough to ensure contact along the entire surface of the probe. Backfilling to improve contact results in repacking and measurement errors. The profile probe is also especially susceptible to preferential-flow problems down the long surface of the access tube. (NOTE: The new TEROS Borehole Installation Tool eliminates preferential flow and reduces site disturbance while allowing you to install sensors at depths you choose.)
Trench installation is arduous
Installing sensors at different depths through the side wall of a trench is an easy and precise method, but the actual digging of the trench is a lot of work. This method puts the probes in undisturbed soil without packing or preferential water-flow problems, but because it involves excavation, it’s typically only used when the trench is dug for other reasons or when the soil is so stony or full of gravel that no other method will work. The excavated area should be filled and repacked to about the same density as the original soil to avoid undue edge effects.
Digging a trench is a lot of work.
Augur side-wall installation is less work
Installing probes through the side wall of a single augur hole has many of the advantages of the trench method without the heavy equipment. This method was used by Bogena et al. with EC-5 probes. They made an apparatus to install probes at several depths simultaneously. As with trench installation, the hole should be filled and repacked to approximately the pre-sampling density to avoid edge effects.
An augered borehole disturbs the soil layers, but the relative size of the impact to the site is a fraction of what it would be with a trench installation. A trench may be about 60 to 90 cm long by 40 cm wide. A borehole installation performed using a small hand auger and the TEROS Borehole Installation Tool creates a hole only 10 cm in diameter—just 2-3% of the area of a trench. Because the scale of the site disturbance is minimized, fewer macropores, roots, and plants are disturbed, and the site can return to its natural state much faster. Additionally, when the installation tool is used inside a small borehole, good soil-to-sensor contact is ensured, and it is much easier to separate the horizon layers and repack to the correct soil density because there is less soil to separate.
Multiple-hole installation protects against failures
Digging a separate access hole for each depth ensures that each probe is installed into undisturbed soil at the bottom of its own hole. As with all methods, take care to assure that there is no preferential water flow into the refilled augur holes, but a failure on a single hole doesn’t jeopardize all the data, as it would if all the measurements were made in a single hole.
The main drawback to this method is that a hole must be dug for each depth in the profile. The holes are small, however, so they are usually easy to dig.
Single-hole installation is least desirable
It is possible to measure profile moisture by auguring a single hole, installing one sensor at the bottom, then repacking the hole, while installing sensors into the repacked soil at the desired depths as you go. However, because the repacked soil can have a different bulk density than it had in its undisturbed state and because the profile has been completely altered as the soil is excavated, mixed, and repacked, this is the least desirable of the methods discussed. Still, single-hole installation may be entirely satisfactory for some purposes. If the installation is allowed to equilibrate with the surrounding soil and roots are allowed to grow into the soil, relative changes in the disturbed soil should mirror those in the surroundings.
Bogena, H. R., A. Weuthen, U. Rosenbaum, J. A. Huisman, and H. Vereecken. “SoilNet-A Zigbee-based soil moisture sensor network.” In AGU Fall Meeting Abstracts. 2007. Article link.
In an update to our previous blog, “Soil Moisture Sensors in a Tree?”, we highlight two current research projects using soil moisture sensors to measure volumetric water content (VWC) in tree stems and share why this previously difficult-to-obtain measurement will change how we look at tree water usage.
Researchers explore the feasibility of inserting capacitance soil sensors in tree stems as a real-time measurement.
Soil Moisture Sensors in Tree Stems?
In a recent research project, Ph.D. candidate Ashley Matheny of the University of Michigan used soil sensors to measure volumetric water content in the stems of two species of hardwood trees in a northern Michigan forest: mature red oak and red maple. Though both tree types are classified as deciduous, they have different strategies for how they use water. Oak is anisohydric, meaning the species doesn’t control their stomata to reduce transpiration, even in drought conditions. Isohydric maples are more conservative. If the soil starts to dry out, maple trees will maintain their leaf water potential by closing their stomata to conserve water. Ashley and her research team wanted to understand the different ways these two types of trees use stem water in various soil moisture scenarios.
Historically, tree water storage has been measured using dendrometers and sap flow data, but Ashley’s team wanted to explore the feasibility of inserting a capacitance-type soil sensor in the tree stems as a real-time measurement. They hoped for a practical way to make this measurement to provide more accurate estimations of transpiration for use in global models.
Scientists measured volumetric water content in the stems of two species of hardwood trees in a northern Michigan forest: mature red oak and red maple.
Ashley and her team used meteorological, sap flux, and stem water content measurements to test the effectiveness of capacitance sensors for measuring tree water storage and water use dynamics in one red maple and one red oak tree of similar size, height, canopy position and proximity to one another (Matheny et al. 2015). They installed both long and short soil moisture probes in the top and the bottom of the maple and oak tree stems, taking continuous measurements for two months. They calibrated the sensors to the density of the maple and oak woods and then inserted the sensors into drilled pilot holes. They also measured soil moisture and temperature for reference, eventually converting soil moisture measurements to water potential values.
Results Varied According to Species
The research team found that the VWC measurements in the stems described tree storage dynamics which correlated well with average sap flux dynamics. They observed exactly what they assumed would be the anisohydric and isohydric characteristics in both trees. When soil water decreased, they saw that red oak used up everything that was stored in the stem, even though there wasn’t much available soil moisture. Whereas in maple, the water in the stem was more closely tied to the amount of soil water. After precipitation, maple trees used the water stored in their stem and replaced it with more soil water. But, when soil moisture declined, they held onto that water and used it at a slower rate.
Researchers want to figure out the appropriate level of detail for tree water-use strategy in a global model.
Trees use different strategies at the species level
The ability to make a stem water content measurement was important to these researchers because much of their work deals with global models representing forests in the broadest sense possible. They want to figure out the appropriate level of detail for tree water-use strategy in a global model. Both oak and the maple are classified as broadleaf deciduous, and in a global model, they’re lumped into the same category. But this study illustrates that if you’re interested in hydrodynamics (the way that trees use water), deciduous trees use different strategies at the species level. Thus, there is a need to treat them differently to produce accurate models.
Reference: Matheny, A. M., G. Bohrer, S. R. Garrity, T. H. Morin, C. J. Howard, and C. S. Vogel. 2015. Observations of stem water storage in trees of opposing hydraulic strategies. Ecosphere 6(9):165. http://dx.doi.org/10.1890/ES15-00170.1
Next week: Learn about more research being done using soil moisture sensors to measure volumetric water content in tree stems.
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Salt in soil comes from the fertilizer we apply but also from irrigation water and dissolving soil minerals. If more salt is applied in the irrigation water than is leached or taken off in harvested plants, the soil becomes more saline and eventually ceases to support agricultural production (see part 1). This week, learn an effective way to measure electrical conductivity (EC) in soil.
How to Measure Electrical Conductivity of the Soil Solution
As mentioned above, the earliest measurements of solution conductivity were made on soil samples, but it was found to be more reliable to extract the soil solution and make the measurements on it. When values for unsaturated soils are needed, those are calculated based on the saturation numbers and conjecture about how the soil dried to its present state. Obviously a direct measurement of the soil solution conductivity would be better if it could be made reliably.
Two approaches have been made to this measurement. The first uses platinum electrodes embedded in ceramic with a bubbling pressure of 15 bars. Over the plant growth range the ceramic remains saturated, even though the soil is not saturated, allowing a measurement of the solution in the ceramic. As long as there is adequate exchange between the ceramic and the soil solution, this measurement will be the EC of the soil solution, pore water EC.
Salt in soil comes from the fertilizer we apply, irrigation water and dissolving soil minerals.
The other method measures the conductivity of the bulk soil and then uses empirical or theoretical equations to determine the pore water EC. The ECH2O 5TE uses the second method. It requires no exchange of salt between soil and sensor and is therefore more likely to indicate the actual solution electrical conductivity. The following analysis shows one of several methods for determining the electrical conductivity of the saturation extract from measurements of the bulk soil electrical conductivity.
Mualem and Friedman (1991) proposed a model based on soil hydraulic properties. It assumes two parallel conduction paths: one along the surface of soil particles and the other through the soil water. The model is
Here σb is the bulk conductivity which is measured by the probe, σs is the bulk surface conductivity, σw is the conductivity of the pore water, θ is the volumetric water content, θs is the saturation water content of the soil and n is an empirical parameter with a suggested value around 0.5. If, for the moment, we ignore surface conductivity, and use eq. 1 to compute the electrical conductivity of a saturated paste (assuming n = 0.5 and θs = 0.5) we obtain σb = 0.35σw. Obviously, if no soil were there, the bulk reading would equal the electrical conductivity of the water. But when soil is there, the bulk conductivity is about a third of the solution conductivity. This happens because soil particles take up some of the space, decreasing the cross section for ion flow and increasing the distance ions must travel (around particles) to move from one electrode of the probe to the other. In unsaturated soil these same concepts apply, but here both soil particles and empty pores interfere with ion transport, so the bulk conductivity becomes an even smaller fraction of pore water conductivity.
When water evaporates at the soil surface, or from leaves, it is pure, containing no salt, so evapotranspiration concentrates the salts in the soil.
Our interest, of course, is in the pore water conductivity. Inverting eq. 1 we obtain
In order to know pore water conductivity from measurements in the soil we must also know the soil water content, the saturation water content, and the surface conductivity. The 5TE measures the water content. The saturation water content can be computed from the bulk density of the soil
Where ρb is the soil bulk density and ρs is the density of the solid particles, which in mineral soils is taken to be around 2.65 Mg/m3 . The surface conductivity is assumed to be zero for coarse-textured soil. Therefore, using the 5TE allows us to quantify pore water EC through the use of the above assumptions. This knowledge has the potential to be a very useful tool in fertilizer scheduling.
Electrical Conductivity is Temperature Dependent
Electrical conductivity of solutions or soils changes by about 2% per Celsius degree. Because of this, measurements must be corrected for temperature in order to be useful. Richards (1954) provides a table for correcting the readings taken at any temperature to readings at 25 °C. The following polynomial summarizes the table
where t is the Celsius temperature. This equation is programmed into the 5TE, so temperature corrections are automatic.
Soil salinity has been measured using electrical conductivity for more than 100 years.
Units of Electrical Conductivity
The SI unit for electrical conductance is the Siemen, so electrical conductivity has units of S/m. Units used in older literature are mho/cm (mho is reciprocal ohm), which have the same value as S/cm. Soil electrical conductivities were typically reported in mmho/cm so 1 mmho/cm equals 1 mS/cm. Since SI discourages the use of submultiples in the denominator, this unit is changed to deciSiemen per meter (dS/m), which is numerically the same as mmho/cm or mS/cm. Occasionally, EC is reported as mS/m or µS/m. 1 dS/m is 100 mS/m or 105 µS/m.
Richards, L. A. (Ed.) 1954. Diagnosis and Improvement of Saline and Alkali Soils. USDA Agriculture Handbook 60, Washington D. C.
Rhoades, J. D. and J. Loveday. 1990. Salinity in irrigated agriculture. In Irrigation of Agricultural Crops. Agronomy Monograph 30:1089-1142. Americal Society of Agronomy, Madison, WI.
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Dr. Colin S. Campbell discusses whether TDR vs. capacitance (see part 1) is the right question, the challenges facing soil moisture sensor technology, and the correct questions to ask before investing in a sensor system.
It’s easy to overlook the obvious question: what is being measured?
What are You Trying to Measure?
When considering which soil water content sensor will work best for any application, it’s easy to overlook the obvious question: what is being measured? Time Domain Reflectometry (TDR) vs. capacitance is the right question for a researcher who is looking at the dielectric permittivity across a wide measurement frequency spectrum (called dielectric spectroscopy). There is important information in these data, like the ability to measure bulk density along with water content and electrical conductivity. If this is the desired measurement, currently only one technology will do: TDR. The reflectance of the electrical pulse that moves down the conducting rods contains a wide range of frequencies. When digitized, these frequencies can be separated by fast fourier transform and analyzed for additional information.
The objective for the majority of scientists, however, is to simply monitor soil water content instantaneously or over time, with good accuracy. There are more options if this is the goal, yet there are still pitfalls to consider.
Considerable research has been devoted to determining which soil moisture sensors meet expectation.
Each Technology Has Challenges
Why would a scientist pay $100+ for a soil volumetric water content (VWC) sensor, when there are hundreds of soil moisture sensors online costing between $5 and $15? This is where knowing HOW water content is measured by a sensor is critical.
Most sensors on home and garden websites work based on electrical resistivity or conductivity. The principle is simple: more water will allow more electrons to flow. So conductivity will change with soil water content. But, while it’s possible to determine whether water content has changed with this method, absolute calibration is impossible to achieve as salts in the soil water will change as the water content changes. A careful reading of sensor specs will sometimes uncover the measurement method, but sometimes, price is the only indication.
Somewhere between dielectric spectroscopy and electrical resistance are the sensors that provide simple, accurate water content measurement. Considerable research has been devoted to determining which of these meet expectation, and the results suggest that Campbell Scientific, Delta-T, Stevens, Acclima, Sentek, and METER (formerly Decagon Devices), provide accurate sensors vetted by soil scientists. The real challenge is installing the sensors correctly and connecting them to a system that meets data-collection and analysis needs.
Installation Techniques Affect Accuracy
Studies show there is a difference between mid-priced sensor accuracy when tested in laboratory conditions. But, in the field, sensor accuracy is shown to be similar for all good quality probes, and all sensors benefit from site-specific soil calibration. Why? The reason is associated with the principle upon which they function. The electromagnetic field these sensors produce falls off exponentially with distance from the sensor surface because the majority of the field is near the electrodes. So, in the lab, where test solutions form easily around sensor rods, there are differences in probe performance. In a natural medium like soil, air gaps, rocks, and other detritus reduce the electrode-to-soil contact and tend to reduce sensor to sensor differences. Thus, picking an accurate sensor is important, but a high-quality installation is even more critical.
Improper installation is the largest barrier to accuracy.
Which Capacitance Sensor Works Best?
Sensor choice should be based on how sensors will be installed, the nature of the research site, and the intended collection method. Some researchers prefer a profile sensor, which allows instruments to be placed at multiple depths in a single hole. This may facilitate fast installation, but air gaps in the auger pilot hole can occur, especially in rocky soils. Fixing this problem requires filling the hole with a slurry, resulting in disturbed soil measurements. Still, profile sensor installation must be evaluated against the typical method of digging a pit and installing sensors into a sidewall. This method is time consuming and makes it more difficult to retrieve sensors.
New technology that allows sensor installation in the side of a 10 cm borehole may give the best of both worlds, but still requires backfill and has the challenge of probe removal at the end of the experiment.
The research site must also be a consideration. If the installation is close to main power or easily reached with batteries and solar panels, your options are open: all sensors will work. But, if the site is remote, picking a sensor and logging system with low power requirements will save time hauling in solar panels or the frustration of data loggers running out of batteries.
Often times it comes down to convenience.
Data Loggers Can Be a Limitation
Many manufacturers design data loggers that only connect to the sensors they make. This can cause problems if the logging system doesn’t meet site needs. All manufacturers mentioned above have sensors that will connect to general data loggers such as Campbell Scientific’s CR series. It often comes down to convenience: the types of sensor needed to monitor a site, the resources needed to collect and analyze the data, and site maintenance. Cost is an issue too, as sensors range from $100 to more than $3000.
Successfully Measure Water Content
The challenge of setting up and monitoring soil water content is not trivial, with many choices and little explanation of how each type of sensor will affect the final results. There are a wealth of papers that review the critical performance aspects of all the sensors discussed, and we encourage you to read them. But, if soil water content is the goal, using one of the sensors from the manufacturers named above, a careful installation, and a soil-specific calibration, will ensure a successful, accurate water content measurement.
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.
TDR began as a technology the power industry used to determine the distance to a break in broken power lines.
In the late 1970s, Clarke Topp and two colleagues began working with a technology the power industry used to determine the distance to a break in broken power lines. Time Domain Reflectometers (TDR) generated a voltage pulse which traveled down a cable, reflected from the end, and returned to the transmitter. The time required for the pulse to travel to the end of the cable directed repair crews to the correct trouble spot. The travel time depended on the distance to the break where the voltage was reflected, but also on the dielectric constant of the cable environment. Topp realized that water has a high dielectric constant (80) compared to soil minerals (4) and air (1). If bare conductors were buried in soil and the travel time measured with the TDR, he could determine the dielectric constant of the soil, and from that, its water content. He was thus able to correlate the time it took for an electromagnetic pulse to travel the length of steel sensor rods inserted into the soil to volumetric water content. Despite his colleagues’ skepticism, he proved that the measurement was consistent for several soil types.
TDR sensors consume a lot of power. They may require solar panels and larger batteries for permanent installations.
TDR Technology is Accurate, but Costly
In the years since Topp et al.’s (1980) seminal paper, TDR probes have proven to be accurate for measuring water content in many soils. So why doesn’t everyone use them? The main reason is that these systems are expensive, limiting the number of measurements that can be made across a field. In addition, TDR systems can be complex, and setting them up and maintaining them can be difficult. Finally, TDR sensors consume a lot of power. They may require solar panels and larger batteries for permanent installations. Still, TDR has great qualities that make these types of sensors a good choice. For one thing, the reading is almost independent of electrical conductivity (EC) until the soil becomes salty enough to absorb the reflection. For another, the probes themselves contain no electronics and are therefore good for long-term monitoring installations since the electronics are not buried and can be accessed for servicing, as needed. Probes can be multiplexed, so several relatively inexpensive probes can be read by one set of expensive electronics, reducing cost for installations requiring multiple probes.
Many modern capacitance sensors use high frequencies to minimize effects of soil salinity on readings.
Advances in Electronics Enable Capacitance Technology
Dielectric constant of soil can also be measured by making the soil the dielectric in a capacitor. One could use parallel plates, as in a conventional capacitor, but the measurement can also be made in the fringe field around steel sensor rods, similar to those used for TDR. The fact that capacitance of soil varies with water content was known well before Topp and colleagues did their experiments with TDR. So, why did the first attempt at capacitance technology fail, while TDR technology succeeded? It all comes down to the frequency at which the measurements are made. The voltage pulse used for TDR has a very fast rise time. It contains a range of frequencies, but the main ones are around 500 MHz to 1 GHz. At this high frequency, the salinity of the soil does not affect the measurement in soils capable of growing most plants.
Like TDR, capacitance sensors use a voltage source to produce an electromagnetic field between metal electrodes (usually stainless steel), but instead of a pulse traveling down the rods, positive and negative charges are briefly applied to them. The charge stored is measured and related to volumetric water content. Scientists soon realized that how quickly the electromagnetic field was charged and discharged was critical to success. Low frequencies led to large soil salinity effects on the readings. This new understanding, combined with advances in the speed of electronics, meant the original capacitance approach could be resurrected. Many modern capacitance sensors use high frequencies to minimize effects of soil salinity on readings.
NASA used capacitance technology to measure water content on Mars.
Capacitance Today is Highly Accurate
With this frequency increase, most capacitance sensors available on the market show good accuracy. In addition, the circuitry in them can be designed to resolve extremely small changes in volumetric water content, so much so, that NASA used capacitance technology to measure water content on Mars. Capacitance sensors are lower cost because they don’t require a lot of circuitry, allowing more measurements per dollar. Like TDR, capacitance sensors are reasonably easy to install. The measurement prongs tend to be shorter than TDR probes so they can be less difficult to insert into a hole. Capacitance sensors also tend to have lower energy requirements and may last for years in the field powered by a small battery pack in a data logger.
In two weeks: Learn about challenges facing both types of technology and why the question of TDR vs. Capacitance may not be the right question.
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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.
Figure 1: NDVI is sensitive to the amount of vegetation cover that is present across the earth’s surface.
NDVI – Global
The broadest way to think of NDVI is data obtained from an earth orbiting satellite. In the figure above, you can see highly vegetated areas that have high NDVI values represented by dark green colors across the globe. Conversely, areas of low vegetation have low NDVI values, which look brown. NDVI is sensitive to the amount of vegetation cover that is present across the earth’s surface.
NDVI – Local
How might NDVI be useful at the plot level? Figure 2 below shows a successional gradient where time zero is a bare patch of soil, or a few forbs or annual grasses. If we leave that patch of ground for enough time, the vegetation will change: shrubs may take over from grasses and eventually we might see a forest. Across a large area, we may also move from grasslands to forest. In an agricultural system, there is yearly turnover of vegetation—from bare field to plant emergence, maturity, and senescence. This cycle repeats itself every year. Within these growth cycles NDVI helps to quantify the canopy growth that occurs over time as well as the spatial dynamics that occur across landscapes.
Figure 2: Seasonal growth plotted against spatiotemporal variation
Spectral Reflectance Data
So where does NDVI come from? In Figure 3, the x-axis plots wavelength of light within the electromagnetic spectrum; 450 to 950 nm covers both the visible region and a portion of the near infrared. On the y-axis is percent reflectance. This is a typical reflectance spectrum from green vegetation.
The green hyperspectral line is what we would expect to get from a spectral radiometer. Reflectance is typically low in the blue region, higher in the green region, and lower in the red region. It shifts dramatically as we cross from the visible to the near infrared. The two vertical bars labeled NDVI give you an idea of where a typical NDVI sensor measures within the spectrum. One band is in the red region and the other is in the near-infrared region.
NDVI capitalizes on the large difference between the visible region and the near infrared portion of the spectrum. Healthy, growing plants reflect near-infrared strongly. The two images on the right of the figure above are of the same area. The top image is displayed in true color, or three bands–blue, green and red. The image below is a false color infrared image. The three bands displayed are blue, green, and in place of red, we used the near infrared. The bright red color indicates a lot of near infrared reflectance which is typical of green or healthy vegetation.
The reason NDVI is formulated with red and near infrared is because red keys in on chlorophyll absorption, and near infrared is sensitive to canopy structure and the internal cellular structure of leaves. As we add leaves to a canopy, there’s more chlorophyll and structural complexities, thus we can expect decreasing amounts of red reflectance and higher amounts of near-infrared reflectance.
How Do We Calculate the NDVI?
The Normalized Difference Vegetation Index takes into account the amount of near-infrared (NIR) reflected by plants.It is calculated by dividing the difference between the reflectances (Rho) in the near-infrared and red by the sum of the two. NDVI values typically range between negative one (surface water) and one (full, vibrant canopy). Low values (0.1 – 0.4) indicate sparse canopies, while higher values (0.7 – 0.9) suggest full, active canopies.
The way we calculate the percent reflectance is to quantify both the upwelling radiation (the radiation that’s striking the canopy and then reflected back toward our sensor) as well as the total amount of radiation that’s downwelling (from the sky) on a canopy. The ratio of those two give us percent reflectance in each of the bands.
Next Week:Learn about NDVI applications, limitations, and how to correct for those limitations.
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In Germany, scientists are measuring the effects of tomorrow’s climate change with a vast network of 144 large lysimeters (see part 1). This week, read about the intense precision required to move the soil-filled lysimeters, how problems are prevented, and how the data is used by scientists worldwide.
Moving the lysimeters
Moving the Lysimeters is not Easy
As noted previously, one TERENO lysimeter weighs between 2.5 and 3.5 tons depending on the soil and the water saturation, so the problem of transporting it without compacting the soil or causing cracks in the soil column caused Georg many sleepless nights. He explains, “We found a truck with an air venting system, which could prevent vibrations in a wide range. We made a wooden support structure, bought 100 car springs, and loaded the lysimeter on this frame. After some careful preparation and design adjustments, I told the truck driver, ‘take care, I’m recording the entire drive with my acceleration sensor and data logger so I can see if you are driving faster than I allow.” Each lysimeter soil surface level was marked to check if the lysimeter was rendered useless due to transport, and the truck was not allowed to go over a railway or a bump in the road faster than 2 km per hour to avoid the consequences of compaction and cracking.
Understanding the water potential inside the intact lysimeter core is not trivial. Georg and his team use maintenance-free tensiometers, which overcome the typical problem of cavitation in dry conditions as they don’t need to be refilled. Still, this parameter is so critical they installed 3 of them and took the median, which can be weighed in case one of the sensors is not working. Georg says, “There is a robust algorithm behind measuring the true field situation with tensiometers.”
What Happens With the Data?
Georg hopes that many researchers will take advantage of the TERENO lysimeter network data (about 4,000 parameters stored near-continuously on a web server). He says, “Researchers have free access to the data and can publish it. It’s wonderful because it’s not only the biggest project of its kind, each site is well-maintained, and all measurements are made with the same equipment, so you can compare all the data.” (Contact Dr. Thomas Puetz for access). Right now, over 400 researchers are working with those data, which has been used in over 200 papers.
Lysimeter plant with CO2 fumigation facility in Austria.
What’s the Future?
Georg thinks 40,000 data points arriving every minute will give scientists plenty of information to work on for years to come. Each year, more TERENO standard lysimeters are installed to enlarge the database. The ones in TERENO have a 1 m2 surface area, which is fine for smaller plants like wheat or grass, but is not a good dimension for big plants like trees and shrubs. Georg points out that you have to take into account effort versus good data. Larger lysimeters present exponentially larger challenges. He admits that, “With the TERENO project, they had to make a compromise. All the lysimeters are cut at a depth of 1.5 m. If there is a mistake, it is the same with all the lysimeters, so we can compare on climate change effects.” He adds, “After six years, we now have a standard TERENO lysimeter design installed over 200 times around the world, where data can be compared through a database, enhancing our understanding of water in an era of climate change.”
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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 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 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.
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…
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 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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In the conclusion of our 3-part water potential series (see part 1), we discuss how to measure water potential—different methods, their strengths, and their limitations.
Vapor pressure methods work in the dry range.
How to measure water potential
Essentially, there are only two primary measurement methods for water potential—tensiometers and vapor pressure methods. Tensiometers work in the wet range—special tensiometers that retard the boiling point of water (UMS) have a range from 0 to about -0.2 MPa. Vapor pressure methods work in the dry range—from about -0.1 MPa to -300 MPa (0.1 MPa is 99.93% RH; -300 MPa is 11%).
Historically, these ranges did not overlap, but recent advances in tensiometer and temperature sensing technology have changed that. Now, a skilled user with excellent methods and the best equipment can measure the full water potential range in the lab.
There are reasons to look at secondary measurement methods, though. Vapor pressure methods are not useful in situ, and the accuracy of the tensiometer must be paid for with constant, careful maintenance (although a self-filling version of the tensiometer is available).
Here, we briefly cover the strengths and limitations of each method.
Vapor Pressure Methods:
The WP4C Dew Point Hygrometer is one of the few commercially available instruments that currently uses this technique. Like traditional thermocouple psychrometers, the dew point hygrometer equilibrates a sample in a sealed chamber.
WP4C Dew Point Hygrometer
A small mirror in the chamber is chilled until dew just starts to form on it. At the dew point, the WP4C measures both mirror and sample temperatures with 0.001◦C accuracy to determine the relative humidity of the vapor above the sample.
The most current version of this dew point hygrometer has an accuracy of ±1% from -5 to -300 MPa and is also relatively easy to use. Many sample types can be analyzed in five to ten minutes, although wet samples take longer.
At high water potentials, the temperature differences between saturated vapor pressure and the vapor pressure inside the sample chamber become vanishingly small.
Limitations to the resolution of the temperature measurement mean that vapor pressure methods will probably never supplant tensiometers.
The dew point hygrometer has a range of -0.1 to -300 MPa, though readings can be made beyond -0.1 MPa using special techniques. Tensiometers remain the best option for readings in the 0 to-0.1 MPa range.
Water content tends to be easier to measure than water potential, and since the two values are related, it’s possible to use a water content measurement to find water potential.
A graph showing how water potential changes as water is adsorbed into and desorbed from a specific soil matrix is called a moisture characteristic or a moisture release curve.
Example of a moisture release curve.
Every matrix that can hold water has a unique moisture characteristic, as unique and distinctive as a fingerprint. In soils, even small differences in composition and texture have a significant effect on the moisture characteristic.
Some researchers develop a moisture characteristic for a specific soil type and use that characteristic to determine water potential from water content readings. Matric potential sensors take a simpler approach by taking advantage of the second law of thermodynamics.
Matric Potential Sensors
Matric potential sensors use a porous material with known moisture characteristic. Because all energy systems tend toward equilibrium, the porous material will come to water potential equilibrium with the soil around it.
Using the moisture characteristic for the porous material, you can then measure the water content of the porous material and determine the water potential of both the porous material and the surrounding soil. Matric potential sensors use a variety of porous materials and several different methods for determining water content.
Accuracy Depends on Custom Calibration
At its best, matric potential sensors have good but not excellent accuracy. At its worst, the method can only tell you whether the soil is getting wetter or drier. A sensor’s accuracy depends on the quality of the moisture characteristic developed for the porous material and the uniformity of the material used. For good accuracy, the specific material used should be calibrated using a primary measurement method. The sensitivity of this method depends on how fast water content changes as water potential changes. Precision is determined by the quality of the moisture content measurement.
Accuracy can also be affected by temperature sensitivity. This method relies on isothermal conditions, which can be difficult to achieve. Differences in temperature between the sensor and the soil can cause significant errors.
All matric potential sensors are limited by hydraulic conductivity: as the soil gets drier, the porous material takes longer to equilibrate. The change in water content also becomes small and difficult to measure. On the wet end, the sensor’s range is limited by the air entry potential of the porous material being used.
TS1 Smart Tensiometer
Tensiometers and Traditional Methods
Read about the strengths and limitations of tensiometers and other traditional methods such as gypsum blocks, pressure plates, and filter paper here.
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