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Posts from the ‘Water Potential sensors’ Category

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.

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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.

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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).

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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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Measuring Water Potential in Concrete

Trevor Dragon, a former METER Research and Development Engineer, was pouring concrete at his Beeville, Texas, farm one day and wondered if he could measure moisture in concrete with a matric potential sensor instead of the more traditionally used volumetric water content sensor (VWC) to get more accurate readings.  Dragon says, “We had about five concrete trucks come in that day, and we poured five different slabs.  Every truck had a different amount of water added.  One particular batch of concrete was really wet and soupy, and I became curious to measure it and compare it to the other slabs.”

Concrete slab drying down at Trevor's Texas farm.

Concrete slab drying down at Trevor’s Texas farm.

Why Measure Moisture in Concrete?

As concrete hardens, portland cement reacts with water to form new bonds between the components of the concrete.  This chemical process, known as hydration, gives concrete its characteristic rock-like structure.  Too much or too little water can reduce the strength of the concrete.  Adding excess water can lead to excessive voids in concrete while providing too little water can inhibit the cement hydration reaction. Thus, when you pour a slab in south Texas, where it’s exposed to high wind and intense heat, sufficient water must be added, and precautions must be taken to minimize evaporation of water from the slab surface as the concrete hardens.

Better Readings:

Dragon chose the matric potential sensor because he wondered if it would be more accurate than a VWC measurement.  He says, “I knew that VWC sensors were calibrated for soil, and because of that they would lack accuracy.  But the water potential sensor is calibrated for the ceramic it contains.  I figured it would be closer to the real thing without having to do a custom calibration.”

Moisture in concrete has been difficult to measure because the high electrical conductivity early in the hydration process throws off water content sensor calibration. So, Dragon was surprised when his data turned out to be really good.  He comments, “The dry down curve of the matric potential sensor was a perfect curve. There was a nice knee (drop from saturation) after about 200 minutes, and it just went down from there.  We’re kind of stumped because we are trying to understand why the data came out so well and why the curve looks so good.”  

MPS2 Water Potential in Concrete

Water Potential in Concrete

The scientists at METER sent the drydown curve to Dr. Spencer Guthrie, a civil engineering professor, to see what he thought.  He explains, “I suspect that the concrete is experiencing initial set at around 200 minutes.  This is a very normal time frame by which finishing operations need to be complete.  At this stage in cement hydration, the concrete becomes no longer moldable.  A rigid capillary structure is forming, and individual pores are taking shape.  As hydration continues, the pores become smaller and smaller, which may explain the decrease in matric potential.”

New Methods:

One theory Dragon and his colleague Dr. Colin Campbell came up with was that perhaps Dragon’s unique method of inserting the sensors made a difference in the measurements.  He explains, “The first thing I did was look for the rebar in the concrete, and I placed the sensors in the exact center of one of the squares to avoid the influence of metal on the sensor electromagnetic field.  Also, I didn’t insert the sensors the same way you would insert them into soil.  In soil, you put the sensors in vertically; I placed the water potential sensor horizontally because in this case, I was not interested in how water was moving in the slab but how it was being used over time.

What Does It Mean for the Future?

The behavior of the water potential sensor embedded in the concrete clearly indicated a drying process where water becomes less available over time. However, the implications are still unknown.  Can the quality of the concrete be determined from the speed or extent of water becoming less available?  Hopefully, this opportunistic experiment by Dragon will lead to more tests to show whether this approach is useful to others.  

Dr. Guthrie agrees the idea should be explored further and comments, “The matric potential measurements were not redundant with the water content measurements.  Instead, they offered additional, interesting information about the early hydration characteristics of the concrete.  In the context of construction operations, the water potential data indicated what is normally determined by observing the impression left in the concrete surface from the touch of a finger.  In the context of research, however, the use of a water potential sensor may yield helpful information about how certain admixtures, for example, influence the development of hydration products in concrete over time.

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Measuring Frozen Water Potential: How and Why?

In China recently, a fellow scientist asked Dr. Colin Campbell if matric potential sensors work in frozen soils.  His answer? Sort of. In this blog, he explains what he meant by his enigmatic reply: When water freezes in the soil, most matric potential sensors won’t work accurately because frozen water essentially disappears to the measurement. For example, in a dielectric measurement circuit, most of the water that was polarized in the electromagnetic field solidifies in the ice matrix. Thus, because dielectric measurements determine the charge that is stored when water is polarized, ice is not measured. But, many matric potential sensors contain a component that will measure frozen water potential: the temperature sensor.

frozen water potential

Horseshoe prints in frozen soil.

How Does Temperature Measure Water Potential?  

The temperature of a frozen matrix like soil has a fundamental thermodynamic relationship to the energy state of that water. For every one degree C below freezing, the water potential decreases by 1.2 MPa. For example, if the soil drops down to -4 C, the soil water potential will be -4.8 MPa. However, one thing many people don’t understand is that there is still liquid water in frozen soils.

Where is the Liquid Water in a Frozen Soil?

Some liquid water will always be associated with soil surfaces because water, as a polar molecule, is attracted by opposite surface charges. Ice is a collection of water molecules that have slowed enough that they are arranged in a crystal-like structure. When ice arranges in that structure, it will attract and use all those water molecules that are available but will have difficulty stealing away water bound to soil surfaces. That water will remain liquid. As soil temperature drops, water layers closer and closer to soil particle surfaces will slow and join the ice structure.

Why Worry about Frozen Water Potential?

Previously, we’ve discussed the importance of water potential in determining the availability of water for plant growth. But below freezing, plants are either dormant or expired, so why measure frozen water potential?

There are a couple of reasons frozen soil water potential may be interesting to scientists. Liquid water in frozen soil still has the possibility to move. So, knowing soil temperature will allow models to predict water flow.  

Even more interesting is what could be done with a temperature sensor and a measurement of water content using dielectric permittivity. As we mentioned earlier, ice essentially disappears to a dielectric measurement.  Thus, a dielectric sensor water content measurement should provide the amount of liquid water in the soil. Using the temperature sensor to infer water potential (assuming the soil begins wet enough that its pre-frozen state has not reduced WP significantly), we can combine the WP and VWC measurements over a range of temperatures to generate an in situ moisture release curve. This idea was developed into a prototype instrument that appeared to have promise as a new laboratory technique to obtain moisture release curves.

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Water Content helps Turf Growers find Water/Nutrient Balance

Many athletes don’t like artificial turf. They say it’s hot, uncomfortable to run on, causes burns when you slide or fall on it, and changes the way a ball moves.  Professional women’s soccer players even started a lawsuit over FIFA’s decision to use artificial turf in the 2015 Women’s World Cup.

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Soccer players on natural turf.

Some universities—including Brigham Young University—have responded to athlete concerns by using natural turf fields for practice and in their stadiums. But the challenge is to develop plants and management practices for natural turf that help it stand up to frequent use and allow it to perform well even during the difficult fall months. It’s a perfect research opportunity.

BYU turf professor and manager of BYU sports turf, Bryan Hopkins and his colleagues in the Plant and Wildlife Department, have been able to set up a new state-of-the-art facility to study plants and soil in both greenhouse and natural conditions. The facility includes a large section of residential and stadium turfgrass.  

Before Soil Sensors

Initially, BYU maintained the turf farm grass on a standard, timer-based irrigation control system, but over time they realized that understanding the performance of their turf relative to moisture content and nutrient load is crucial. Last year during Memorial Day weekend their turf farm irrigation system stopped working when no one was around to notice.  During those four days temperatures rose to 40 C (100 F), and the grass in the field slipped into dormancy due to heat stress. In response, Dr. Hopkins began imagining a system of soil moisture sensors to constantly monitor the performance of the turf grass.  He wanted not only to make sure the turf never died but also to really understand the elements of stress so they could do a better job growing healthy turf.

Sensors Give a Clear Picture

Soon afterward, a team of scientists, including fellow professor Dr. Neil Hansen, installed volumetric water content (VWC) and matric potential sensors at two different sites: one in the sports turf and one in a residential turf plot.  Each plot had two installations of sensors at 6 cm and 15 cm, along with VWC only at 25 cm, to measure water moving beyond the root zone. Combining these measurements, they could clearly see when the grass was reaching stress conditions and how quickly the turf went from the beginning of stress (in terms of water content and time) to permanent wilting point. In addition, ancillary measurements of temperature and electrical conductivity provide an opportunity for modeling surface and root zone temperature as well as fertilizer concentration dynamics.

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Installing water content sensors at the BYU turf farm.

Errors Revealed

What the researchers learned was that they were using too much water. Dr. Colin Campbell, a METER research scientist who worked with BYU on sensor installation, comments, “We found in the first year that the plants never got stressed at all. So this year, the researchers allowed the water potential (WP) at 6 cm to drop into the stress range (~ -500 kPa) while observing WP at 15 cm (-50 kPa to -60 kPa). We hope this approach will reduce irrigation inputs while creating some stress in the grass in order to push the roots deeper.”

What’s happening with the water?

Dr. Campbell’s favorite part of the sensor data was the detailed picture it gave of what was happening with the water in the sandy soil (Figure 1). He says, “Most people believe that they have an intuitive feel for water availability in soil.  If we were only using water content sensors, seeing a typical value of 20% would lead us to believe we were comfortably in the middle of the plant available range (A).  But in this study, using our colocated soil water content and soil water potential sensors, the data showed readings over 15% VWC were too wet to affect the WP (B). However, once WP visibly changed, it quickly moved toward critical stress levels (C, -1500 kPa is permanent wilting point); it only took two days for the water potential to change from -8 kPa to -1000 kPa.  A subsequent dry period (D) shows similar behavior, but this time the 15 cm WP drops to near -1000 kPa.”

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Figure 1

The plant stress levels were reached surprisingly quickly in this soil because its sand composition has a lot of large pores and not very many small ones (Figure 2). Campbell explains, “The large pores store water that is not held tightly due to low surface area, so the water is freely available. But at around 10% VWC all the water from the large pores is used up. As the soil dries beyond that, the water is held tightly in small pores and becomes increasingly unavailable. This is clear in the moisture release curve.  We see almost no change in water potential as the soil dried to 16% VWC, but from 10% down to 7%, the water potential reached permanent wilting point, and it happened in just over a day.”

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Figure 2

What the Future Holds:

The researchers wanted to make sure that if they went down to certain stress levels, they wouldn’t cause harm to the plants, so this year, they installed a weather station to monitor evapotranspiration and calculate irrigation application rates.  They also began measuring spectral reflectance to monitor changes in leaf area (NDVI) and photosynthesis (PRI).  This will enable them to see the impact on the plants as the turf is drying down.  “In the future,” says Campbell, “we hope that both commercial and residential turf growers will be able to more effectively control their irrigation and nutrients based on what we find in this study.”

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Low Impact Design: Sensors Validate California Groundwater Resource Management

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.

Low impact design

Can Low Impact Design Structures store rainwater?

Low Impact Design Structures

Global groundwater resources in urban, coastal environments are highly vulnerable to increased human pressures and climate variability. Impervious surfaces, such as buildings, roads, and parking lots prevent infiltration, reduce recharge to underlying aquifers, and increase contaminants in surface runoff that often overflow sewage systems. To mitigate these effects, cities worldwide are adopting low impact design (LID) approaches to direct runoff into natural vegetated systems such as rain gardens that reduce, filter, and slow stormwater runoff. LID hypothetically increases infiltration and recharge rates to aquifers.

low impact design

Infiltration and Recharge

Michelle and the team at San Francisco State University, advised by Dr. Jason Gurdak, realized that the effects of LID on recharge rates and quality were unknown, particularly during intense precipitation events for cities along the Pacific coast in response to inter-annual variability of the El Niño Southern Oscillation (ENSO). Using water potential and water content sensors she was able to quantify the current and projected rates of infiltration and recharge to the California Coastal Westside Basin aquifer system. The team compared a LID infiltration trench surrounded by a rain garden with a traditional turf-lawn setting in San Francisco.  She says, “Cities like San Francisco are implementing these LID structures, and we wanted to test the quantity of water that was going through them.  We were interested specifically in different climate scenarios, like El Niño versus La Niña, because rain events are much more intense during El Niño years and could cause flash flooding or surface pollutant overflow problems.”

low impact design

Sensors Tell the Story

The research team looked at the differences in the quantity of water that LID structures could allow to pass through.  Michelle says. ”The sensors yielded data proving LID areas were effective at capturing the water, infiltrating it more slowly, and essentially storing it in the aquifer.”  The team tested how a low-impact development-style infiltration trench compared to an irrigated lawn and found that the recharge efficiency of the infiltration trench, at 58% to 79%, was much higher than that of the lawn, at 8% to 33%.

low impact design

Rain Gauges Yield Surprises

Though it wasn’t part of the researchers’ original plan, they used rain gauges to measure precipitation, which yielded some surprising data.  Michelle comments, “We were just going to use the San Francisco database, but it became necessary to use the rain gauges because of all the fog.  The fog brought a lot of precipitation with it that didn’t come in the form of raindrops.  As it condensed on the leaves, it provided a substantial portion of the water in the budget, and that was surprising to me.  The rain gauge captured the condensate on the funnel of the instrument, so we were able to see that a certain quantity of water was coming in that is typically neglected in many studies.”

Future El Niño Precipitation

Michelle also found some really interesting results regarding El Niño and La Niña.  She says, “I did a historical analysis to establish baselines for frequency, intensity, and duration of precipitation events during El Niño and La Niña years.  I then ran projected climate data through a Hydrus-2D model, and the models showed that with future El Niño intensities, recharge rates were effectively higher for a given precipitation event. During these events, in typical urban settings, water runs off so fast that only these rain gardens and trenches would be able to capture the rain that would otherwise be lost to the ocean. This contrasts with a La Niña climate scenario where there’s typically less rain that is more diffuse. Most of that rain may eventually be lost to evaporation during dry years.  So using sensors and 2D modeling we have validated the hypothesis that LID structures provide a service for storing water, particularly during El Niño years where there are more intense rainstorms.”

Michelle’s research received some press online and also was featured in the AGU EOS Editor’s spotlight.   Her results are published in the journal Water Resources Research.

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Water Potential Versus Water Content

Dr. Colin Campbell, soil physicist, shares why he thinks measuring soil water potential can be more useful than measuring soil water content.

A horsetail plant showing possible signs of guttation where the water potential in the soil overnight is high enough to force water out of the stomates in the leaves.

A horsetail plant showing possible signs of guttation where the water potential in the soil overnight is high enough to force water out of the stomates in the leaves.

I know an ecologist who installed an extensive soil water content (VWC) sensor network to study the effect of slope orientation on plant available water.  He collected good VWC data, but ultimately he was frustrated because he couldn’t tell how much of the water was available to plants.

He’s not alone in his frustration. Accurate, inexpensive soil moisture sensors have made soil VWC a justifiably popular measurement, but as many people have discovered, a good hammer doesn’t make every soil water problem a nail. I like to compare water potential to temperature because both are considered “intensive” variables that define the intensity of something.

People often try to quantify their own environment, because those measurements define comfort and happiness.  Long ago, they discovered they could make an enclosed glass tube, put mercury inside, and infer this intensive variable called temperature from the changes in the mercury’s volume. This was an obvious way to define the comfort level of a human being.

water potential

People discovered they could make an enclosed glass tube, put mercury inside, and infer an intensive variable called temperature.

They could have measured the heat content of their surroundings.  But they would have discovered that while heat content would be higher in a larger room and lower in a smaller room, you would feel the same comfort level in both rooms.  The temperature measurement helps you know whether or not you’d be comfortable without any other variables entering into the equation.

Similar to heat content, water content is an amount. It’s an extensive variable.  It changes with size and situation. Consider the following paradoxes:

  • A soil with fairly low volumetric water content can have plenty of plant-available water and a soil with high water content can have almost none.
  • Gravity pulls water down through the profile, but water moves up into the soil from a water table.
  • Two adjacent patches of soil at equilibrium can have significantly different water content.

In these and many other cases, water content data can be confusing because they don’t predict how water moves.  Water potential measures the energy state of water and thus explains realities of water movement that otherwise defy intuition. Like temperature, water potential defines the comfort level of a plant.   Similar to the room size analogy for temperature, if we know the water potential, we can know whether plants will grow well or be stressed in any environment.

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Soil, clay, sand, potting soil, and other media, all hold water differently.

Plants don’t understand the concept of a content in terms of “comfort” because soil, clay, sand, potting soil, and other media, all hold water differently.  Imagine a sand with 30% water content. Due to its low surface area, the sand will be too wet for optimal plant growth, threatening a lack of aeration to the roots, and flirting with saturation.  Now consider a fine textured clay at that same 30% water content. The clay may appear only moist and be well below optimum “comfort” for a plant due to the surface of the clay binding the water and making it less available to the plant.

Water potential measurements clearly indicate plant available water, and, unlike water content, there is an easy reference scale. We know that plant optimal runs from about -2-5 kPa which is on the very wet side, to about -100 kPa, at the drier end of optimal.  Below that plants will be in deficit, and past -1000 kPa they start to suffer.  Depending on the plant, water potentials below -1000 to -2000 kPa cause permanent wilting.

So, why would we want to measure water potential? Water content can only tell you how much water you have.  If you want to know how fast water can move, you need to measure hydraulic conductivity.  If you want to know whether water will move and where it’s going to go, you need water potential.

Many questions about water availability and movement are best answered by measuring water potential.  To find out more, watch any of the virtual seminars below, or visit our new water potential website.

Water Potential 101: Making Use of an Important Tool

Water Potential 201:  Choosing the Right Instrument

Water Potential 301: How to Push Your Instruments Past their Specifications

Water Potential 401: Advances in Field Water Potential

Find out when you should measure both water potential and water content.

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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.

Idea:

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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Thoughts on Soil Sensor Installation from a German Precisionist

Many researchers carefully choose the right instrumentation for their projects, but when it comes to installing the soil sensor into the soil, they are less than careful about the process. Researchers need to know how to install sensors in a way that will allow them to get the most accurate data the instruments are capable of.

soil sensor

Georg von Unold

Georg von Unold has almost two decades of experience installing all types of soil sensors and a German eye for precision that is unmatched in our experience. As the president and founder of UMS (now METER Ag), a German company that develops and manufactures precision soils instrumentation, and a close friend, we thought there would be no one better to share a couple of ideas on careful installation.  Here’s what he had to say:

Pick the Right Place to Install your Sensors

When we develop research instrumentation we look at the accuracy and the resolution of our instruments from a technical point of view.  However, the heterogeneity of research sites can be so vast that we have to take care to select a research site that is representative from a scientific point of view of the results we would like to publish.  We do this first by analyzing the biosphere above the soil that is visible to us, and then perhaps doing some auguring into the soil at various sites to investigate what might be going on in different areas of the field.  If you are researching on a farm, it is important to ask the grower where he’s had good and bad harvest results, where he’s needed to irrigate, and where he’s had problems with erosion.  Always interview people who know the history and specifics of the sites first, because if the sites are flooded or at risk for landslides, it will be a bad choice for long-term monitoring.  Investigating the right place for your sensors before you install will save you time and help you obtain the most applicable and accurate data for your research.

soil sensor

We knew that gravel would have bad capillary contact because the stones would have holes between them.

Be Careful with the Way you Install Sensors

One of our research projects used tensiometers to try and determine how water flowed through gravel.  We knew that gravel would have bad capillary contact because the stones would have holes between them. So we decided to make a slurry of fine material from this gravel soil and put it in the installation hole so that the tensiometer would have better capillary contact.  It was a good idea, but it led to misleading results.  What we ended up with was a kind of water reservoir with fine material around the tensiometer which had nothing to do with the true moisture situation in the gravel.  The tensiometer gave us wonderful readings: very constant but with no dynamics that would have been typical for a gravel soil.  When we took it into the lab to investigate, we realized we’d built an artificial soil around our tensiometer.  We weren’t measuring the gravel but were measuring our artificial error which we had created so carefully.  The other thing we found is that over the course of time our slurry would move away from the tensiometer, and within a few years, the tensiometer would be simply hanging in a big gap.  This project also contained fine, heavy soils. Eventually, we realized that we needed an auguring tool that would not push the soil away or compact the soil where we placed the tensiometer because compaction would mean different hydraulic behavior.  So we asked our friends at a Dutch company to make us an auger that was shaped in a form that wouldn’t change the natural soil density that we wanted to measure.

It is important to be careful when you install sensors. For example, if you have a clay soil and you auger a bigger hole than your tensiometer, you will have a water tube around your sensor.  If your soil flooded, the water would flow down your shaft to where your tensiometer is placed, and then what are you measuring?  Thus it is necessary to seal the shaft or to prevent access of surface water to a deeper horizon.

soil sensor

You need to remember that if you want to measure temperature at a depth of one meter below the surface, the thermal conductivity is strongly dependent on the kind of soil and the moisture of the soil.

Beware of Simple Mistakes

You can also make simple mistakes with other types of soil sensors, such as temperature probes.  You need to remember that if you want to measure temperature at a depth of one meter below the surface, the thermal conductivity is strongly dependent on the kind of soil and the moisture of the soil.  If, for example, you put a temperature probe wired with copper wires in a dry sand or gravel, you will get an average value of the temperature of the sunlight exposed hot cable. The reason is that the copper is leading the temperature down to where you measure and has a much higher conductivity compared to dry, coarse soil.  Thus it is important to think through your installation processes because it is likely you will have a different installation method in a clay soil versus a gravel soil.

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The History and Future of Water Potential

I often hear researchers complain about the accuracy of our TEROS 21 water potential sensors.  We still have room to improve, but we’ve certainly come a long way! People have been attempting to make water potential measurement in the field for over 100 years. The following is a brief overview of the evolution and history of water potential measurements over that time.

history

Pre-MPS-1 prototype.

Livingston Discs

The Livingston disc, developed in 1908, was one of the first attempts at determining water potential in the field.  The Livingston Disc was actually a primitive, manual version of the technology used in our MPS6 ceramic disc.  Here is how it worked:  first, you’d weigh the dry disk, then put it in the soil and let it equilibrate.  After that, you would dig it up and weigh it again.  Using the water retention curve of the disc, you could then determine the water potential.

Gypsum block

In the 1940s gypsum block sensors were invented as the first solid matrix equilibrium technique for water potential.  This method tried to continuously sense water potential with a simple electrical conductivity measurement in a solid porous (and naturally occurring) gypsum matrix.  However, because naturally occurring gypsum doesn’t have a consistent pore size distribution and it degrades over time, the instrument was not very accurate.

history

In the 1940’s gypsum block sensors were invented as the first solid matrix equilibrium technique for water potential. Image: www.soilmoisture.com

Tensiometers

In the 1960’s a liquid equilibration technique called tensiometry was discovered that allowed water potential measurement with good accuracy even in the presence of positive pore water pressures.   Tensiometers work extremely well in wetter soils with water potentials between 0 and -80 kPa and should be the choice for all wet soil applications, especially above -9 kPa where the MPS6 will not work (the air entry value for its ceramic is -9 kPa).  However, when the soil dries out the water under tension in the tensiometer eventually cavitates, causing the output to be useless until they are refilled.  Thus solid equilibrium techniques like the TEROS 21 are the best choice across the dry range.

history

Tensiometers are the most accurate way to measure water potential in the field in the wet range, but are limited to the plant optimal range of about -100 kPa and above.

The Evolution of Ceramic Discs

We learned with the gypsum blocks that one of the challenges in solid matrix water potential measurement is finding a material that will create the same water retention curve every time. In quest of this goal, the ceramic discs in sensors like the TEROS 21 have taken years of development.  Because of the limited range of the tensiometer, we wanted to develop a water potential sensor that could measure over a larger range.  The hardest part about developing that ceramic was getting a variety of pore sizes so the instrument could read said wide range of water potentials.  This started years ago in the lab of Dr. Gaylon Campbell at Washington State University where his technician, Kees Calisendorf, experimented over a long period of time to come up with the perfect recipe.

history

The MPS1 was our original matric potential sensor released in 2001. It allowed for long-term monitoring in the field because, unlike gypsum, the ceramic did not degrade over time.

Even after we found a consistent ceramic, there were still outliers.  So creating a calibration method was essential to making an accurate sensor.  The first challenge was to be able to store calibration points in the sensor, which required a microprocessor.  The second, and more difficult task, was to establish a method to calibrate large numbers of sensors at once.  We tried many different approaches like pressure plate, equilibration over salt solutions, and even centrifugal force, but nothing worked.  Finally, in a discussion with our partner, UMS, we discovered the key.  We now can accurately calibrate 50 sensors at a time in only 12 hours.  Still, even with these advanced techniques, we only have a sensor with an accuracy of plus or minus 10%, but considering the history of how hard it’s been to develop consistent ceramic, this accuracy is exciting for the range that we can get.

history

The MPS 2 was our second matric potential sensor which offered two-point calibration and a temperature sensor, improving accuracy.

What’s Next?

Now that we’ve created a reliable calibration method, we can turn our attention toward further improving the sensor measurement range as well as its accuracy.  Testing different ceramics, or other porous media, may hold the key to a solid equilibrium technique sensor reading all the way to 0 kPa, eventually replacing the need for tensiometers in the field.

history

The two key innovations in the MPS6 (now called TEROS 21), released in 2014, are the addition of a microprocessor to the sensor and fast, accurate equilibration at multiple points.

 

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Despite Drawbacks, Scientific Collaboration Pays Off

Though collaboration can fuel innovation and increase the relevance and complexity of the scientific questions we study, I’ve noticed it does have its ups and downs.  The highs and lows we’ve run into on our research projects may help others avoid some of the pitfalls we experienced as many diverse groups tried to learn how to work together.

collaboration

Researchers discussing science at the Lytle Ranch Preserve, a remarkable desert laboratory located at the convergence of the Great Basin, Colorado Plateau, and Mojave Desert biogeographical regions.

There can be bumps in the road when collaborating with companies who want to test their product. Being at the forefront of innovation means that untested sensors may require patience as you work out all the bugs together. But from my perspective, this is part of the fun.  If we are late adopters of technology, we wouldn’t get to have a say in creating the sensors that will best fit our projects as scientists.

Collaborating scientists can also sometimes run into problems in terms of the stress of setting up an experiment in the time frame that is best for everyone.  During our experiment on the Wasatch Plateau, we had six weeks to get together soil moisture and water potential sensors, but our new GS3 water content, temperature, and EC sensors had never been outside of the lab. In addition, we planned to use an NDVI sensor concept that came out of a workshop idea my father Gaylon had.  We’d made ONE, and it seemed to work, but that is a long way from the 20 we needed for a long-term experiment in a remote location at 3000 meters elevation. In the end, it all worked out, but not without several late nights and a bit of luck.  I remember students holding jackets over me to protect me from the rain as I raced to get the last sensor working.  Then we shut the laptop and ran down the hill, trying to beat a huge thunderstorm that started to pelt the area.

collaboration

Desert-FMP Researchers at the Lytle Ranch Preserve

Other challenges of scientific collaboration present organizational hardships.  One of the interesting things about the interdisciplinary science in the Desert FMP project is the complexity of the logistics, and maybe that’s a reason why some people don’t do interdisciplinary projects.  We are finding in order to get good data on the effects of small mammals and plants you need to coordinate when you are sampling small mammals and when you’re sampling plants.  Communicating between four different labs is complicated.  Each of the rainout shelters we use cover an area of approximately 1.5 m2 .  That’s not a lot of space when we have two people interested in soil processes and two people interested in plants who all need to know what’s going on underneath the shelter.  Deciding who gets to take a destructive sample and who can only make measurements that don’t change the system is really hard.  The interesting part of the project where we’re making connections between processes has required a lot of coordination, collaboration, and forward-thinking.

In spite of the headaches, my colleague and I continue to think of ways we can help each other in our research.  Maybe we’re gluttons for punishment, but I think the benefits far outweigh the trouble we’ve had.  For instance, in the above-mentioned Desert FMP project we’ve been able to discover that small mammals are influential in rangeland fire recovery (read about it here).  We only discovered that piece of the puzzle because scientists from differing disciplines are working together.  In our Wasatch Plateau project, my scientist colleague said it was extremely helpful for him to be working with an instrumentation expert who could help him with setup and technical issues.  Also, we’ve been able to secure some significant grants in our Cook Farm Project (you can read about it in an upcoming post) and answer some important questions that wouldn’t have occurred to either one of us, if we hadn’t been working together.  In addition, solving problems that have cropped up in our projects has spurred us on to a new idea for analyzing enormous streams of data in near-real time.  (read about it here).

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