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Posts tagged ‘Field Capacity’

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 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.

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.

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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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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Environmental Biophysics: Top Five Blog Posts in 2015

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


Sunflower field in Hokkaido

Do the Standards for Field Capacity and Permanent Wilting Point Need to Be Reexamined?

We asked scientist, Dr. Gaylon S. Campbell, which scientific idea he thinks impedes scientific progress.  Here’s what he had to say.



Environmental Biophysics Lectures

During a recent semester at Washington State University, a film crew recorded all of the lectures given in the Environmental Biophysics course. The videos from each Environmental Biophysics lecture are posted here for your viewing and educational pleasure.



Sensor Data Improves Cherry Production

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


Maple leaf

What is the Future of Sensor Technology?

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



Sensors Validate California Groundwater Resource Management Techniques

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


Looking up at a tree canopy

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Water Potential/Water Content:  When to Use Dual Measurements

In a previous post, we discussed water potential as a better indicator of plant stress than water content.  However, in most situations, it’s useful to take dual measurements and measure both water content and water potential.  In a recent email, one of our scientist colleagues explains why: “The earlier article on water potential was excellent.  But what should be added is an explanation that the intensity measurement doesn’t translate directly into the quantity of water stored or needed. That information is also required when managing water through irrigation.  This is why I really like the dual measurement approach. I am excited about the possibilities of information that can be gleaned from the combined set of water content, water potential, and spectral reflectance data.”

dual measurements

Potato field irrigation

Managing Irrigation

The value of combined data can be illustrated by what’s been happening at the Brigham Young University Turf Farm, where we’ve been trying to optimize irrigation of turfgrass (read about it here). As we were thinking about how to control irrigation, we decided the best way was to measure water potential.  However, because we were in a sandy soil where water was freely available, we also guessed we might need water content. Figure 1 illustrates why.

dual measurements

Figure 1: Turf farm data: water potential only

Early water potential data looks uninteresting; it tells us there’s plenty of water most of the time, but doesn’t indicate if we’re applying too much.  In addition, if we zoom in to times when water potential begins to change, we see that it reaches a stress condition quickly.  Within a couple of days, it is into the stress region and in danger of causing our grass to go into dormancy.  Water potential data is critical to be able to understand when we absolutely need to water again, but because the data doesn’t change until it’s almost too late, we don’t have everything we need.

dual measurements

Figure 2: Turf farm data, volumetric water content only

Unlike water potential, the water content data (Figure 2) are much more dynamic. The sensors not only show the subtle changes due to daily water uptake but also indicate how much water needs to be applied to maintain the root zone at an optimal level. However, with water content data alone, we don’t know where that optimal level is. For example, early in the season, we observe large changes in water content over four or five days and may assume, based upon onsite observations, that it’s time to irrigate. But, in reality, we know little about the availability of water to the plant. Thus, we need to put the two graphs together (Figure 3).

dual measurements

Figure 3: Turfgrass data: both water potential and volumetric water content together.

In Figure 3, we have the total picture of what’s going on in the soil at the BYU turf farm. We see the water content going down and can tell at what percentage the plants begin to stress.  We also see when we’ve got too much water: when the water content is well above where our water potential sensors start to sense plant stress. With this information, we can tell that the turfgrass has an optimal range of 12% to 17% volumetric water content. Anything below or above that range will be too little or too much water.  

dual measurements

Figure 4: Turfgrass soil moisture release curve (black). Other colors are examples of moisture release curves for different types of soil.

Dual measurements will also allow you to make in situ soil moisture release curves like the one above (Figure 4), which detail the relationship between water potential and water content.  Scientists can evaluate these curves and understand many things about the soil, such as hydraulic conductivity and total water availability.

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Author Interview: Soil Physics with Python

The new book Soil Physics with Python: Transport in the Soil-Plant-Atmosphere System written by Dr. Marco Bitteli, Dr. Gaylon S. Campbell, and Dr. Fausto Tomei presents concepts and problems in soil physics as well as solutions using original computer programs.

Soil Physics with Python

Soil Physics with Python

In contrast to the majority of the literature on soil physics, this text focuses on solving, not deriving, differential equations for transport. Numerical methods convert differential equations into algebraic equations, which can be solved using conventional methods of linear algebra.  Here, Dr. Campbell interviews about this update to his classic book Soil Physics with BASIC.

Why did you write the first book, Soil Physics with BASIC?

Soil physics classes were always frustrating for me because you would spend time writing fancy equations on the chalkboard, and in the end, you couldn’t do anything with them.  You couldn’t solve any of the problems because, even though they involved difficult mathematics, the math was still so simplified that it didn’t apply to anything that went on in nature.

When I taught my first graduate soil physics class, I determined that we were going to be able to do something by the time we finished.  Luckily, in the mid-1970s, personal computers were being developed, and I realized this was the answer to my problem.  Numerical methods could solve any problem with any geometry in it.  It wasn’t limited to problems that fit the assumptions needed to derive a complex differential equation.  I could write computer programs that simplified the mathematics for the students and teach them how to solve those problems using numerical methods.  By the end of the semester, my students would have a set of tools that they could use to solve problems in the real world.  

Did this book come from class notes or some other source?  

I wrote two textbooks and they both came the same way.  When I first started teaching, I had a textbook that was inadequate, so I began writing notes of my own and handing them out to the students.   After two years, I turned these notes into An Introduction to Environmental Biophysics.  Soil Physics with BASIC came about by the same process, but I enlisted the help of my daughter, Julia, to type it up. It was in the early days of word processing so entering equations was quite difficult.  It all went well for her until chapter eight, which was a nightmare of greek symbols. After she finished slogging for days through the material, we somehow lost the chapter.  She retyped it, and we lost it again, making her type it three times!  We didn’t have spreadsheets then either, so the figures were all hand-drawn by my daughter, Karine.

soil physics with python

Marco [Bitteli] has added two and three-dimensional flow problems, so you can model whole landscapes and water behavior in an entire terrain.

What does Soil Physics with Python add to the conversation?

First, it updates the programming language.  BASIC was a language invented at Dartmouth and intended to be a simple teaching language.  It was never supposed to be a scientific computer language.  Python (13:26.) is a newer language, and there are many open source programs for it, making it a better language to use for science.

Secondly, the old book had one-dimensional flow problems in it for the most part, but Marco [Bitteli] has added two and three-dimensional flow problems, so you can model whole landscapes and water behavior in an entire terrain.

In addition, Dr. Bitteli describes the process and analysis of soil treated as fractals as well as soil image analysis.  There are a lot of extensions and updates that weren’t in the original book.  

Will it be accessible across all disciplines?

To some extent, different disciplines speak different languages.  A soil physicist talks about water potential, and a geotechnical engineer talks about soil suction. Thus, there may be some translation of discipline-specific terms, but it’s intended to be a book that people in the plant sciences can use along with people in the soil sciences.

Dr. Marco Bitteli earned his PhD at Washington State University and was Dr. Campbell’s former student.  This book is a product of their continued collaboration. Dr. BBitteli is now a professor at University of Bologna, the oldest university in operation in the world.  Soil Physics with Python  is available at

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Do the Standards for Field Capacity and Permanent Wilting Point Need to Be Reexamined?

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 METER 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:

field capacity

A layered soil, a soil that has a fine-textured horizon on top of a coarse-textured soil, will hold twice as much water as you’ll predict from the -⅓ bar value.


The phrase, “this idea must die,” is probably too strong a phrase, but certainly some scientific ideas need to be reexamined, for instance the standard of -⅓ bar (-33 kPa) water potential for field capacity and -15 bars (-1500 kPa or -1.5 MPa) for permanent wilting point.

Where it came from:

In the early days of soil physics, a lot of work was done in order to establish the upper and lower limit for plant available water.  The earliest publication on the lower limit experiments was by Briggs and Shantz in 1913. They planted sunflowers in small pots under greenhouse conditions, letting the plants use the water until they couldn’t recover overnight, after which they carefully measured the water content (WC).  The ability to measure water potential came along quite a bit later in the 1930s using pressure plates.  As those measurements started to become available, a correlation was found between the 15 bar pressure plate WCs and the WCs that were determined by Briggs and Shantz’s earlier work.  Thus -15 bars (-1.5 MPa) was established as the lower limit of plant available water.  The source of the field capacity WC data that established a fixed water potential for the upper limit is less clear, but the process, apparently, was similar to that for the lower limit, and -⅓ bar was established as the drained upper limit water potential in soil.

field capacity

Briggs and Shantz planted sunflowers in small pots under greenhouse conditions, letting the plants use the water until they couldn’t recover overnight, after which they carefully measured the water content (WC).

Damage it does:  

In practice, using -15 bars to calculate permanent wilting point probably isn’t a bad starting point, but in principle, it’s horrible. Over the years we have set up experiments like Briggs and Shantz did and measured water potential. We have also measured field soils after plants have extracted all the water they can.  Permanent wilting point never once came out at -15 bars or -1.5 MPa.  For things like potatoes, it was approximately -10 bars (-1 MPa), and for wheat it was approximately -30 bars (-3 MPa).  We found that the permanent wilting point varies with the species and even with soil texture to some extent.

Of course, in the end it doesn’t matter much as the moisture release curve is pretty steep on the dry end, and whether you predict it to be 10 or 12% WC, it doesn’t make a huge difference in the size of the soil water reservoir that you compute.

However, on the field capacity end of the scale, it matters a lot.  If you went out and made measurements of the water potentials in soils a few days after a rain, it would be an absolute accident if any of them were ever -⅓ bar (-33 kPa).  I’ve never seen it.  A layered soil, a soil that has a fine-textured horizon on top of a coarse-textured soil, will hold twice as much water as you’ll predict from the -⅓ bar value.  On the other hand, if you’re getting pretty frequent rains or irrigation, that field capacity number becomes irrelevant. Thus, -⅓ bar may be a useful starting point for determining field capacity, but it’s only a starting point.

Why it’s wrong:

Field capacity and permanent wilting point are dynamic properties.  They depend on the rate at which the water is being extracted or the rate at which it’s being applied.  They also depend on the time you wait to sample after irrigation. Think of the soil as a leaky bucket.  If you were trying to carry water in a leaky bucket and you walked slowly, the bucket would be empty by the time you get the water where you want it. However, if you run fast, there will still be some water left in the bucket.  Similarly, if a plant can use water up rapidly, most of it will be intercepted, but if a plant is using water slowly, the water will move down past the root zone and out the bottom of the soil profile before the plant can use it.  These are dynamic phenomena that you are trying to describe with static variables.  And that’s where part of the problem comes.  We need a number to do our calculations with, but it’s important to understand the factors that affect that number.

field capacity

Rye field

What do we do now:

What I hope we can do is better educate people. We should teach that we need a value we call field capacity or permanent wilting point, but it’s going to be a dynamic property.  We can start out by saying: our best guess is that it will be -⅓ bar for finer-textured soils and -1/10 bar (-10 kPa) for coarser-textured soils. But when we dig a hole and find out there is layering in the profile or textural discontinuities, we’d better adjust our number.  If we’re dealing with irrigated farmland, the adjustment will always be up, and if we’re dealing with dryland or rain-fed agriculture where the time between water additions is longer, we’ll use a lower number.

Some Ideas Never Die:

One of the contributors to the book, This Idea Must Die, Dr. Steve Levitt, had this to say about outdated scientific ideas, and we agree:  “I love the idea of killing off bad ideas because if there’s one thing that I know in my own life, it’s that ideas that I’ve been told a long time ago stick with me,  and you often forget whether they have good sources or whether they’re real. You just live by them. They make sense. The worst kind of old ideas are the ones that are intuitive. The ones that fit with your worldview, and so, unless you have something really strong to challenge them, you hang on to them forever.”

What scientific ideas do you think need to be reexamined?

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