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Posts from the ‘Greenhouse’ Category

Soil Moisture Sensors: Which Installation Method is Best?

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.

How to avoid measurement errors

Three common challenges to making high-quality volumetric water content measurements are:

  1. making sure the probe is installed in undisturbed soil,
  2. minimizing disturbance to roots and biopores in the measurement volume, and
  3. 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.

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.

soil moisture sensors

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.

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.

Read more soil moisture sensor installation tips.

Electrical Conductivity of Soil as a Predictor of Plant Response (Part 2)

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.

Electrical conductivity

Salt in irrigation water reduces its water potential, making it less available to the plant.

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

Equation 1

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.

Electrical 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

Equation 2

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

Electrical conductivity

Equation 3

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.

Electrical conductivity

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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Soil Moisture Sensors: Why TDR VS. Capacitance May Be Missing the Point (Part 2)

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 side-wall. 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.

For an in-depth comparison of TDR versus capacitance technology, read: Dielectric Probes Vs. Time Domain Reflectometers

For an understanding of how capacitance sensors compare to other major contemporary sensor technologies, watch our Soil Moisture 201 webinar.

Soil Moisture Sensors: Why TDR vs. Capacitance May Be Missing the Point

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 vs. Capacitance

TDR began as a technology the power industry used to determine the distance to a break in broken power lines.

Clarke Topp

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 vs. Capacitance

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.  

TDR vs. Capacitance

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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Top Five Blog Posts in 2016

In case you missed them the first time around, here are the most popular Environmental blog posts in 2016.

Lysimeters Determine if Human Waste Composting can be More Efficient

Top five blog posts Environmental biophysics

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

Top five blog posts Environmental biophysics

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?

Top five blog posts Environmental biophysics

“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

Top five blog posts Environmental biophysics

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

Top five blog posts Environmental biophysics


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?

Top five blog posts Environmental biophysics

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

Top five blog posts Environmental biophysics

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?

Top five blog posts Environmental biophysics

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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How to Measure Water Potential

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.

How to measure water potential

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.

How to Measure Water Potential

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.

Secondary Methods

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.

Limited Range

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.

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 at

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Water Potential: The Science Behind the Measurement (Part 2)

In the second part of this month’s water potential  series (see part 1), we discuss the separate components of a water potential measurementThe total water potential is the sum of four components: matric potential, osmotic potential, gravitational potential, and pressure potential.  Below is a description of each component.

Matric Potential

Matric potential arises because water is attracted to most surfaces through hydrogen bonding and van der Waals forces. This water droplet is pure but no longer free. The matric forces that bind it to the plastic have lowered its potential and you would have to use some energy to remove it from the surface and take it to a pool of pure, free water.

Soil is made up of small particles, providing lots of surfaces that will bind water. This binding is highly dependent on soil type. For example, sandy soil has large particles which provide less surface binding sites, while a silt loam has smaller particles and more surface binding sites.

The following figure showing moisture release curves for three different types of soil demonstrates the effect of surface area. Sand containing 10% water has a high matric potential, and the water is readily available to organisms and plants. Silt loam containing 10% water will have a much lower matric potential, and the water will be significantly less available.

Matric potential is always negative or zero, and is the most significant component of soil water potential in unsaturated conditions.

matric potential

Osmotic Potential

Osmotic potential describes the dilution and binding of water by solutes that are dissolved in the water. This potential is also always negative.

Osmotic potential only affects the system if there is a semi-permeable barrier that blocks the passage of solutes. This is actually quite common in nature. For example, plant roots allow water to pass but block most solutes. Cell membranes also form a semi-permeable barrier. A less-obvious example is the air-water interface, where water can pass into air in the vapor phase, but salts are left behind.

You can calculate osmotic potential from the following equation if you know the concentration of solute in the water.



Where C is the concentration of solute (mol/kg), ɸ is the osmotic coefficient (-0.9 to 1 for most solutes), v is the number of ions per mol (NaCl = 2, CaCl2 = 3, sucrose = 1), R is the gas constant, and T is the Kelvin temperature.

Osmotic potential is always negative or zero, and is significant in plants and some salt-affected soils.

Gravitational Potential

Gravitational potential arises because of water’s location in a gravitational field. It can be positive or negative depending on where you are in relation to the specified reference of pure, free water at the soil surface. Gravitational potential is then:



Where G is the gravitational constant (9.8 m s-2) and H is the vertical distance from the reference height to the soil surface (the specified height).

matric potential

You can feel positive pressure as you swim down into a lake or pool.

Pressure Potential

Pressure potential is a hydrostatic or pneumatic pressure being applied to or pulled on the water.  It is a more macroscopic effect acting throughout a larger region of the system.

There are several examples of positive pressure potential in the natural environment.

For example, there is a positive pressure present below the surface of any groundwater. You can feel this pressure yourself as you swim down into a lake or pool. Similarly, a pressure head or positive pressure potential develops as you move below the water table.

Turgor pressure in plants and blood pressure in animals are two more examples of positive pressure potential.

Pressure potential can be calculated from:



Where P is the pressure (Pa) and P_W is the density of water.

Though pressure potential is usually positive, there are important cases where it is not. One is found in plants, where a negative pressure potential in the xylem draws water from the soil up through the roots and into the leaves.

Next Week: Learn the different methods for measuring water potential and their strengths and limitations.

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Secrets of Water Potential: Learn the Science Behind the Measurement

This month in a 3 part series, we will explore water potential –the science behind it and how to measure it effectively.

water potential

To understand water potential, compare the water in a soil sample to water in a drinking glass.

Definition of Water Potential

Water potential is the energy required, per quantity of water, to transport an infinitesimal quantity of water from the sample to a reference pool of pure free water. To understand what that means, compare the water in a soil sample to water in a drinking glass. The water in the glass is relatively free and available; the water in the soil is bound to surfaces, diluted by solutes, and under pressure or tension. In fact, the soil water has a different energy state from “free” water. The free water can be accessed without exerting any energy. The soil water can only be extracted by expending energy. Water potential expresses how much energy you would need to expend to pull that water out of the soil sample.

Water potential is a differential property. For the measurement to have meaning, a reference must be specified. The reference typically specified is pure, free water at the soil surface. The water potential of this reference is zero. Water potential in the environment is almost always less than zero, because you have to add energy to get the water out.

water potential

You can’t tell by measuring heat content whether or not heat will be transferred to another object if the two touch each other.

Extensive vs. Intensive Variables

Water movement in the environment is really a physics problem, and to understand it, we have to distinguish between intensive and extensive variables. The extensive variable describes the extent or amount of matter or energy. The intensive variable describes the intensity or quality of matter or energy. For example, the thermal state of a substance can be described in terms of both heat content and temperature.

The two variables are related, but they are not the same. Heat content depends on mass, specific heat, and temperature. You can’t tell by measuring heat content whether or not heat will be transferred to another object if the two touch each other. So you also don’t know if the object is hot or cold, or whether it will be safe to touch.

These questions are much easier to answer if you know the intensive variable–temperature. In fact, though it can be important to measure both intensive and extensive variables, often the intensive variable gives you more useful information.

In terms of water, the extensive variable is water content, and it tells you the extent, or amount, of water in plant tissue or soil. The intensive variable is water potential, and it describes the intensity or quality of water in plant tissue or soil.  Water content can only tell you how much water you have. If you want to know how fast it can move, you need to measure hydraulic conductivity. If you want to know whether it will move and where it’s going to go, you need water potential.

water potential

If you want to know whether water will move and where it’s going to go, you need water potential.

Two Key Water Potential Questions:

1. Where will water move? Water will always flow from high potential to low potential. This is the second law of thermodynamics—energy flows along the gradient of the intensive variable.

2. What is the availability of water to plants? Liquid water moves from soil to and through roots, through the xylem of plants, to the leaves, and eventually evaporates in the substomatal cavities of the leaf. The driving force for this flow is a water potential gradient. In order for water to flow, therefore, the leaf water potential must be lower than the soil water potential.

Next week learn about the four components of water potential– osmotic potential, gravitational potential, matric potential, and pressure potential.

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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.


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.”


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.”  


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

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

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

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Measuring NDVI in a Greenhouse Presents Challenges

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


Greenhouse 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.  


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.  


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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