Posts tagged ‘Soils’

Jul 31

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.

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.

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.

sand with plants poking out and a blue sky in the background

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.

Learn more

Soil moisture is more than just knowing the amount of water in soil. Learn basic principles you need to know before deciding how to measure it. In this 20-minute webinar, discover:

Water content: what it is, how it’s measured, and why you need it
Water potential: what it is, how it’s different from water content, and why you need it
Whether you should measure water content, water potential, or both
Which sensors measure each type of parameter

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.

Download the “Researcher’s complete guide to water potential”—>

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.

Take our Soil Moisture Master Class

Six short videos teach you everything you need to know about soil water content and soil water potential—and why you should measure them together. Plus, master the basics of soil hydraulic conductivity.

Watch it now—>

Download the “Researcher’s complete guide to soil moisture”—>

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Jul 24

Lessons from the Field – Sensor Installation Considerations

In the Midwest, government incentives are sometimes provided to convert marginal lands to switchgrass, a leading choice for bio-energy feedstock production. Michael Wine, a researcher at New Mexico Tech, wanted to investigate whether switchgrass’s deeper root systems would affect the water cycle both during and after crop establishment. In the first stages of his investigation, he learned that many factors need to be considered when determining the optimal location for sensor installation.

Image of Switchgrass in a field with a gray sky in the background

Switchgrass (Image: Plant and Soil Sciences E-library)

Aquifer Recharge

Wine used Gee passive capillary lysimeters to determine deep drainage under natural vegetation, wheat, and switchgrass in order to improve our understanding of both the baseline water cycle and the water budget associated with a switchgrass monoculture in Woodward, Oklahoma. He put the lysimeters and some soil moisture (capacitance) sensors into the Beaver-North Canadian River Alluvial Aquifer to look at recharge, but ran into challenges with sensor installation from the start.

Climate Considerations

One thing Wine learned was that biofuels aren’t very successful in his research location– there wasn’t enough water to support switchgrass. He says, “Most places here may have no precipitation recharge for a great many years. But there are sites, such as sub-humid environments, where you could get a whole lot of infiltration in a very short time.” In hindsight, Wine says he “would have increased his use of preliminary data to more efficiently determine the frequency of recharge events.”

Using Preliminary Data to help Site Instrumentation

Wine learned that it’s important to think about the time constant of your system when siting instrumentation and that preliminary data are crucial. He says, “Before sensor installation, I did a chloride mass balance which helped me determine where I should install the lysimeters.” He had been planning to put them at watersheds at the USDA-ARS Southern Plains Range Research Station, but the chloride mass balance showed there hadn’t been a recharge event at that site in the past 200 years. So he chose to install the lysimeters at the USDA-ARS Southern Plains Experimental Range, located in the Beaver-North Canadian River Alluvial Aquifer, a site with coarser soil and higher permeability.

Wine also thinks numerical modeling could have been useful in determining placement. “In siting the instruments, numerical modeling would’ve been a big help because we could have predicted the likelihood and frequency of recharge events. So I think preliminary data, numerical modeling, and environmental tracers can all help in terms of where to place these research devices.”

a baby calf walking towards the photographer with other cows, who are collectively walking through a field

After long absences, Wine often had to repair damage caused by cattle.

Proximity to Research Site

Another challenge was that the researchers were located in Stillwater, Oklahoma, far from their research site. The experiment was protected by fences, but after long absences, Wine often had to repair damage caused by cattle. “I really need to hand it to these instruments that can be trampled numerous times by cows and the battery compartment filled up with water,” Wine says. “They just needed to be dusted off, dried out, new batteries inserted, and they worked great.” Wine adds that researchers need to consider the distance between their office and their research site because in his case, the cows would have been less of an issue if it had been a fifteen-minute drive instead of three hours each way. He adds, “Selecting a nearby research site would have allowed us additional flexibility in our experimental methods; for example, with a nearby site we could have more easily conducted artificial rainfall simulations if a particular year turned out to be too dry for natural recharge events to occur.”

Proper Siting of Equipment Makes a Difference

Once Wine determined the correct placement of his instruments, he was finally able to get some interesting data. He says, “There are large pulses of focused recharge that do occur in certain places, and we quantified one of those pulses following a storm with one of the lysimeters. We’ve got about a year’s worth of data. Since we installed lysimeters at adjacent upland (diffuse recharge) and lowland (concentrated recharge) sites, we succeeded in observing large differences between the recharge fluxes at these nearby sites.” Wine’s plan is to see if he can replicate the results of the lysimeter experiment using numerical modeling, because he says, “the data look reasonable, but I’d like to confirm the measurements due to the cows playing havoc with our site.” Wine is excited as these lysimeters are yielding the first direct physical measurements of diffuse and concentrated groundwater recharge in the Beaver-North Canadian River Alluvial Aquifer, and he’s optimistic that his numerical modeling will match this unique time series of direct physical measurements of groundwater recharge.

Download the “Researcher’s complete guide to soil moisture”—>

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Jul 11

Great Science Reads: What our Scientists are Reading

We asked our scientists to share the great science reads they’ve perused recently. Here’s what they’ve been reading:

Letters to a Young Scientist by E.O. Wilson

Steve Garrity: E.O. Wilson is a leader in the science of biology. This book is a simple read. What I like most about it is that it very effectively conveys Dr. Wilson’s passion for science. His thoughts on what it takes to be a successful scientist resonated with me the most. In describing what it takes to be a successful scientist, E.O. Wilson says that being a genius, having a high IQ, and possessing mathematical fluency are all not enough. Instead, he says that success comes from hard work and finding joy in the processes of discovery. Dr. Wilson gets specific and says that the real key to success is the ability to rapidly perform numerous experiments. “Disturb nature,” he says, “and see if she reveals a secret.” Often she doesn’t, but performing rapid, and often sloppy, experiments increases the odds of discovering something new.

Out of the Scientist’s Garden by Richard Stirzaker

Lauren Crawford: “Richard Stirzaker is a scientist out of Australia committed to finding tools to make farming easier and more productive in third world countries. I love how he talks about what happens when he uses water from his washing machine on his garden and the unanticipated effects: what does the detergent do to the fertilizers and the soil properties? It’s a scientific view of how a garden works.”

Introduction to Water in California by David Carle

Chris Lund: “This is a great introduction to California’s water resources, from where the water comes from to how it is used….particularly relevant today given California’s ongoing drought and the hard choices California faces as a result.”

The Drunkard’s Walk: How Randomness Rules our Lives, by Leonard Mlodinow

Paolo Castiglione: “The Drunkard’s Walk’s beginning quote perfectly reflects the author’s thesis: “In God we trust. All others bring data!”. I enjoyed the author’s discussion on how the past century was strongly influenced by ideologies, in contrast to the present one, where data seems to shape people’s actions and beliefs.”

**Chapter 13 of An Introduction to Environmental Biophysics, by Gaylon Campbell**

Colin Campbell: “Because of teaching Environmental Biophysics class, all my focus has been on reading An Introduction to Environmental Biophysics. And, although I’ve read it too many times to count, I finally had a chance to study the human energy balance chapter (13) in depth, which was amazing. The way humans interact with our environment is something we deal with at every moment of every day; often not giving it much thought. In this chapter, we are reminded of the people of Tierra del Fuego (Fuegians) who were able to survive in an environment where temperatures approached 0 C daily, wearing no more than a loincloth. Using the principles of environmental biophysics and the equations developed in the chapter, we concluded that the Fuegian metabolic rate had to continuously run near the maximum of a typical human today. The food requirements to maintain that metabolic rate would be somewhere between the equivalent of 17 and 30 hamburgers per day (their diet was high in seal fat). You can read more about the Fuegians here.”

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May 15

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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.

Researcher Pointing to Something while Walking through a Forest

Dr. John Selker (Image: andrewsforest.oregonstateuniversity.edu)

What sparked your interest in science?

I was kind of an accidental scientist in a sense. I went into water resources having experienced the 1985 drought in Kenya. I saw that water was transformative in the lives of people there. I thought there were lots of things we could do to make a difference, so I wanted to become a water resource engineer. It was during my graduate degree process that I got excited about science.

What was the first sensor you developed?

I’ve been developing sensors for a long time. I worked at some national labs on teams developing sensors for physics experiments. The first one I developed myself was as an undergraduate student in physics. I was the lab instructor for the class, and I wanted to do something on my own while the students were busy. I made a non-contact bicycle speedometer which was much like an anemometer. I took an ultrasonic emitter, trained it on the tire, and I could get the beat frequency between emitted sound and the backscatter to get the bicycle speed.

What’s the future of sensor technology?

Communication

Right now one of the very exciting advances in technology is communication. Having sensors that can communicate back to the scientists immediately makes a huge difference in terms of knowing how things are going, making decisions on the fly, and getting good quality data. Oftentimes in the past, a sensor would fail and you wouldn’t know about it for months. Cell phone technology and the ability to run a station on a few AA batteries for years has been the most transformative aspect of technological development. The sensors themselves also continue to improve: getting smaller and using less energy, and that’s excellent progress as well.

A Picture of a Orange Maple Leaf in the middle of Fall

What often happens is that you install a solar sensor, and then a leaf or a dust grain falls on it, and you lose your accuracy.

Redundancy

I think the next big thing in sensing technology is how to use what we might call “semi-redundant” sensing. What often happens is that you install a solar sensor, and then a leaf or a dust grain falls on it, and you lose your accuracy. However, if you had a solar panel and a solar sensor, you could then do comparisons. Or if you were using a wind sensor and an accelerometer you could also compare data. We now have the computing capability to look at these things synergistically.

Accuracy

What I would say in science is that if we can get a few more zeros: a hundred times more accurate, or ten times more frequent measurements, then it would change our total vision of the world. So, what I think we’re going to have in the next few years, is another zero in accuracy. I think we’re going to go from being plus or minus five percent to plus or minus 0.5 percent, and we are going to do that through much more sophisticated intercomparisons of sensors. As sensors get cheaper, we can afford to have more and more related sensors to make those comparisons. I think we’re going to see this whole field of data assimilation become a critical part of the proliferation of sensors.

What are your thoughts on the future of sensor technology?

Get more information on applied environmental research in our

Download the “Researcher’s complete guide to soil moisture”—>

Take our Soil Moisture Master Class

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May 2

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Small Company, Big Mission: The Phoenix Mars Lander & TECP Sensor

On May 25, 2008 NASA’s Phoenix Lander successfully landed on the surface of Mars and used a robotic scoop arm to deliver regolith samples to the suite of instruments on the deck of the Lander—with one exception. The Thermal and Electrical Conductivity Probe (TECP), designed by a team of Decagon (now METER) research scientists, was mounted on the knuckle of the robotic arm and made direct contact with the regolith. It measured thermal conductivity, thermal diffusivity, electrical conductivity, and dielectric permittivity of the regolith, as well as vapor pressure of the air.

But, that’s starting at the end of the story. The fact is that TECP almost didn’t get started. After seeing a thermal properties needle at the American Geophysical Union meeting in San Francisco, Mike Hecht (project leader on the Mars Environmental Compatibility Assessment (MECA) instrument suite) encouraged his colleague Martin Buehler to call Decagon (now METER) to see if we’d be willing to participate in the Phoenix Lander project. When Martin called one Friday afternoon, announcing that he was from JPL and wondering if we would be willing to fly our sensor on the Phoenix Lander, I was instantly intimidated. I knew JPL was associated with NASA, and I couldn’t imagine why they would be calling Decagon. I always thought there was a fundamental relationship between NASA and Lockheed Martin, Northrop Grumman, and other major companies that did NASA work. I told him that Decagon, which was much smaller in those days, didn’t have the capacity to develop instrumentation for space flight. He suggested they come up for a visit and at least consult with us on what they would need to do to obtain this measurement. The following Monday, we were talking Martian science and inexorably hooked on the idea of joining the team.

I knew JPL was associated with NASA, and I couldn’t imagine why they would be calling Decagon.

Deciding to put one of our sensors on Mars did nothing to lessen the intimidation factor. But, working with Mike and his team at JPL/NASA taught us that doing amazing science can be an inspiring and collaborative effort. I’d always imagined NASA as a group of uber-scientists and engineers sitting in glass offices dreaming up and executing great projects that would be impossible for mere mortals. The reality is that sending something to Mars and having it do real science requires the combined effort of thousands of smart, dedicated people who are not that much different from the rest of us.

This idea was really brought home when we finally visited JPL. Although the things they were doing were amazing and on a much grander scale, they weren’t that much different from the things we do at Decagon. They had testing facilities, development facilities, production facilities, and support personnel all working together on projects, just like us. However, the projects were pretty amazing. We watched the robot arm being tested in a lab for the ability to dig martian soil analogs. We observed an ice probe working in a 55-gallon drum trying to prove it could melt its way down through the thick Martian polar ice caps. We were mesmerized by prototypes of Mars rovers being programmed and executing maneuvers on Martian surface analogs.

It was fun to discover who the Jet Propulsion Lab is and how enjoyable it is to collaborate with people that are thinking about new applications of technology. This collaboration also benefitted METER’s thermal properties instrument because the mathematical models we developed for Mars made this sensor much more accurate and effective. The Mars project expanded both the depth of our understanding and the breadth of our perspective. Even so, it was fun to find out that scientists who work at JPL have to put their pants on one leg at a time, just like all of us.

Watch this virtual seminar where Dr. Mike Hecht talks Mars, poetry, and Decagon’s (now METER’s) involvement in the Mars Phoenix Lander Mission.

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Apr 22

The Scientific Instrumentation Museum of Horrors

Chris Chambers is the primary technical support scientist at METER. Deep within the recesses of his office, there is a collection of scientific instrumentation we like to call the “Museum of Horrors”. It showcases the many instruments that have been mangled and destroyed over the years by insects, animals, or the environment.

This serial cable melted when it got too close to a sample heating oven.

We get a few instruments back every year that are burned up in a fire, chewed up by rodents, and occasionally we get one that’s been exploded by lightning. We interviewed Chris to find out how to prevent scientific instrumentation from being damaged or destroyed by these types of natural disasters.

Soil Moisture Sensor that got Eaten by Ants

Beware of ant hills. This soil moisture sensor got eaten by ants.

Animals and insects:

The single most important thing you can do to prevent damage from animals is to protect your cables. You can protect your cables with cable armor, electrical conduit, or PVC pipe. Even better is to place cables in some type of conduit and then bury it. Keeping things tidy around the data logger and avoiding exposed cables as much as possible will go a long way toward preventing animals and insects from ruining your experiment.

An ECH2010 Laying in Dirt and Chipped by a Shovel

A retired ECH2O10 that was hit by a shovel.

Lightning:

Lightning is not as big of a danger on METER loggers as it is with third party loggers (read about logger grounding here). Where we typically see people run into problems with lightning is when they have long lengths of cable between the data logger and sensor. Long cable runs act like lightning harvesting antennae. The best thing to do is to keep the cables shorter and do not spread them out in lots of different directions.

TEROS12 with a Bent Needle from Being Pushed into a Rock

This soil moisture sensor was pushed into a rock.

Wildfire:

We have a few instruments every year that get burned up in fires, but there is not much you can do about this hazard except for watching for reports of encroaching fires that may be in your surrounding area and evacuating important instrumentation.

Data Logger that was Struck by Lightning Laying in Bark

A data logger that was struck by lighting.

Flooding:

The worst killer of data loggers is flooding. We have a lot of customers that try and bury their loggers, and that’s generally a terrible idea. Unless you can guarantee the logger will be waterproofed and put some desiccant inside the box, it will probably end badly. There are a few scientists out there that have done a really good job of waterproofing, but they generally spend almost as much effort and money waterproofing as they do purchasing the actual logger.

There’s always going to be some risk to your scientific instrumentation because you’re installing it outside, but hopefully, these tips will help you avoid disaster and keep your system out of the museum of horrors.

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Apr 16

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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:

Canola Field right next to an eroded soil cliff

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.

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.

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.”

Harness the power of soil moisture

Researchers measure evapotranspiration and precipitation to understand the fate of water—how much moisture is deposited, used, and leaving the system. But if you only measure withdrawals and deposits, you’re missing out on water that is (or is not) available in the soil moisture savings account. Soil moisture is a powerful tool you can use to predict how much water is available to plants, if water will move, and where it’s going to go.

In this 20-minute webinar, discover:

Why soil moisture is more than just an amount
Water content: what it is, how it’s measured, and why you need it
Water potential: what it is, how it’s different from water content, and why you need it
Whether you should measure water content, water potential, or both
Which sensors measure each type of parameter

Take our Soil Moisture Master Class

Watch it now—>

Download the “Researcher’s complete guide to soil moisture”—>

Download the “Researcher’s complete guide to water potential”—>

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Apr 12

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.

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.

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.

Researcher squatting letting sand fall through his fingers

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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Apr 4

Double Ring Infiltrometers Versus DualHead Infiltrometers

Several years ago I had the chance to work at the USDA ARS Research Watershed in Riesel, Texas. The goal of my research was to look at the effects of land use and landscape position on water infiltration. Within the research watershed there is preserved and maintained native prairie, improved pasture, and conventional tilled areas, which have been in existence for 75 years. Thus we were able to use infiltrometers to study the long-term effects of those different land uses, along with the effect of landscape position within the same soil type.

Texas Infiltrometer setup

My research focused on the Houston Black Soil Series, which is a clay-rich soil with a high shrink-swell capacity. This soil type has key economic importance, as it is present in much of Texas’ USDA prime farmland. To achieve our objectives, we began by mapping soil bulk electrical conductivity using an EM38 device (electromagnetic geo-surveying instrument). The maps we created allowed us to look for areas of variability in water content, depth to parent material, clay content, and salinity. Then we randomly selected three zones within the catinas (full hill slope including summit, back slope, and front slope) and flagged them with GPS points. Our goal was to make infiltration measurements at all of the landscape positions on the slope and compare them to the same landscape positions within each land use type.

We found that the native prairie had the highest infiltration rates because the soil maintained its strong structure and macropores which allowed water to conduct well through the soil. We also found some differences by landscape position that were consistent within the different catinas. As water would run down the catina, erosion would transport soil and organic matter off the shoulder and back slope and deposit it on the foot slopes. Even though they were mapped as the same soil type, the differences in erosion and reduction of organic matter affected the ability of these different positions to transport water.

We chose to customize existing double ring infiltrometers to make these measurements because there wasn’t anything automated on the market. If I was going to conduct my research in a reasonable amount of time, I had to come up with a system where I could run a lot of measurements relatively easily. As a result, we bought three double-ring infiltrometers and modified them with pressure sensors and some larger controlled ports. The resulting setup was huge; the outer ring on each infiltrometer was 60 cm in diameter and the entire instrument was very heavy. We were constantly refilling the instrument water reservoirs. In fact, this setup required so much water that we had to pull a 1,900-liter water tank on a trailer wherever we were taking measurements.

Our goal was to save time by running all three infiltrometers concurrently, but it still took a LONG time. Even though we had automated the instruments, they required a lot of monitoring; sometimes I had to fill our 1,900-liter water tank twice in a day. One measurement at one site took anywhere from 1.5 hours to 3 hours depending on when we reached steady state. We spent so much time out in the field that we were actually caught on film in one of the Google Maps picture flyovers! Even after all this field time, the data analysis was overwhelming, despite a relatively seamless approach to handle it all.

Our huge setup caught on google maps

I often dreamed of making a tool that would be a lot easier for me and others to use. When I joined Decagon (now METER), it gave me an opportunity to do just that. Our design goals were to make an infiltrometer that required less water and simplified the data analysis. We rejected the double ring design in favor of a single ring approach because research has shown that the outer ring doesn’t buffer three-dimensional flow like it’s supposed to. (Swartzendruber D. and T.C. Olson. “Sand-model study of buffer effects in the double-ring infiltrometer” Soil Sci. Soc. Am. Proc. 25 (1961), 5-8)

We also wanted to simplify the analysis of three-dimensional flow. With a constant head control in a single ring, there are equations that you use to correct for it. But you have to guess at things like soil type and structure which leads to inaccuracies. Multi-head analysis has been around for decades. It involves establishing constant water heights (heads) at multiple levels and looking at the difference in the infiltration rates to calculate the sorptivity. Thus, parameters that are normally estimated from a table can actually be measured, and infiltration results will be independent of users.

Still, there can be problems with the multiple head approach. Increasing the water height when infiltrating into a really low conductivity soil may take 1 to 2 hours to drain back to the original height. We didn’t want to make this measurement take longer than necessary, so instead of using additional water, we used air pressure to simulate higher water levels which can be added or removed very quickly.

So, thanks to the instrument hardships I endured in my past efforts to obtain infiltration measurements, we now have an easy-to-use dual-head infiltrometer (now called the SATURO), that can do the analysis of infiltration rates and saturated hydraulic conductivity on the instrument itself (it gives sorptivity and alpha, based on the soil type and structure, and makes the correction onboard). Thus, if a scientist needs a value right away, it’s there. But, if like me, they wanted to dig deeper through the data, all the measured values can still be downloaded for more careful analysis. Together, it’s a simple tool for both scientists and consultants who need to make these measurements. And they won’t get caught on Google Maps like me, because they’ve had to spend their whole life in the field taking measurements.

Below is a video of the dual-head infiltrometer in action.

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Mar 23

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What Does SMAP Mean for In Situ Soil Water Content Measurement?

With the recent news coverage of the SMAP (Soil Moisture Active Passive) satellite launch, researchers may wonder: what does remote sensing mean for the future of in situ measurements? We asked two scientists, Drs. Colin Campbell and Chris Lund, for answers to this complex question. Here’s what they had to say:

Image: www.jpl.nasa.gov

What is SMAP?

SMAP is an orbiting earth observatory that estimates soil moisture content in the top 5 cm of soil over the entire earth. The mission is three years long with measurements taken every 2-3 days. This will allow seasonal changes around the world to be observed over time, improving our ability to manage water resources and better parameterize land surface models. SMAP determines the amount of water found between the minerals, rocky material, and organic particles found in soil by measuring the ability of radar to penetrate the soil. The wetter the soil is, the less the radar will penetrate. SMAP has two different sensors on the platform: an L band aperture radar with a resolution of about a kilometer when it’s looking straight down (the pixel size is about 1 km by 1 km), combined with a passive radiometer with about 40 km of resolution. This combination creates a synthetic product that takes advantage of the sensitivity of the radiometer.

What does SMAP mean for in situ soil water content measurement?

It’s all about scale: In some ways, comparing in situ to SMAP measurements is like comparing apples to…well…mountain-sized apples. The two forms of measurement use vastly different scales. In situ soil moisture sensors measure water content at the volume of several liters of soil, maximum. Even the sensor with the largest field of sensitivity, the neutron probe, can only integrate a volleyball-sized volume. On the other hand, SMAP measures at a resolution of 1 km2, which is larger than the size of a quarter section, a large field for many farmers. Global soil moisture maps will allow scientists using SMAP to look at big picture applications like weather, climate and hydrological forecasting, drought, and flooding, while more detailed in situ measurements will tell a farmer when it’s time to water, or help researchers discover exactly why plants are growing in one location versus another. The difference in spatial scale makes the two forms of measurement useful for very different research purposes and applications. However, there are applications where the two measurements can be complementary. Most notably, in situ measurements are often temporally rich while being spatially poor. But, SMAP can be used to scale in situ measurements to areas where in situ measurements are absent. In situ measurements can also be used as a source of validation data for SMAP-derived values for any location where both in situ and SMAP measurements overlap. Thus, there is opportunity for synergy when pairing SMAP and in situ measurements.

Satellite image in Winter.

What can SMAP do that in situ measurement can’t?

Scientists say they’ve seen a relationship between the top 5 cm of soil moisture and some factors related to climate change and weather. Because in situ soil sensors sample across a spatial footprint of a few meters, it can be very difficult to use their data to say anything about processes occurring across broad spatial scales; two liters of soil is not going to tell you anything about weather or flooding. SMAP can help us better understand the interaction between the land surface and atmosphere, improving our understanding of the global water cycle as well as regional and global climate. This will help with forecasting crop yield, pest pressure, and disease…that’s big picture research.

The productivity of a forest also may depend on the general soil moisture measured by SMAP. For instance, if we got an idea of the soil moisture and greenness of a forest, we could tie together the approximate water availability and the resulting biomass accumulation with incoming solar radiation. Better biomass accumulation models could lead to better validation of global carbon cycle models.

SMAP will also be able to detect dry areas across the U.S. and challenges they might present. Surface runoff that leads to flooding could also be predicted as scientists will be able to see where soils reach saturated conditions.

In other applications, people working on global water or energy budgets have to parameterize the land surface in terms of how wet or dry it is. That’s the big advantage of SMAP’s relatively new data sets. Any time you’re running a regional climate model you have to parameterize what the soil moisture is in order to partition surface heat flux into sensible and latent heat flux. If there’s a lot of available water, it’s weighted more toward evaporation and less toward sensible heat flux. In areas where there’s little available water and low evaporation, you get high surface temperatures and sensible heat flux. So SMAP will be important for model parameterization as we haven’t had a good global data set for soil moisture until now.

In situ sensors show how much water is lost from the root zone and what is still left.

What can in situ sensors do that SMAP can’t?

In irrigated agriculture, farmers need to know when and how much to irrigate. In situ sensors give them this information by showing how much water was lost from the root zone and what is still left. SMAP is unable to tell you what’s down in the root zone; it only reaches to 5 cm. Additionally, 1 km resolution is larger than most irrigation blocks. These factors mean that it will be difficult to make irrigation decisions from SMAP alone.

Scientists using in situ sensors are concerned with the soil moisture available in a local area because their time resolution is excellent and they have the ability to resolve what’s happening in particular conditions related to crops or natural systems. Natural systems are often heterogeneous, meaning there may be adjacent areas with different types of vegetation including trees, shrubs, and grass. Tree roots may grow deep while grass roots are shallow. Being able to look over all these different areas without averaging them together, as SMAP does, is critical in some applications.

What about geotechnical applications? Literature suggests SMAP output can help predict landslides. It is more likely that it can only see when the soil is generally saturated and generate a warning. But in slopes that are at risk of landslides, in situ monitoring with sensors such as tensiometers to measure positive pore water pressure may be more useful for determining when a slide is imminent.

SMAP, like in situ water content measuring systems, is also limited by the fact that it measures the amount, not the availability, of water. If it measures 23% water content in a certain area, that measurement may not tell us what we want to know. A clay soil at 23% VWC will be close to wilting point while a sand would be above the plant optimal range. SMAP doesn’t measure the energy status of water (water potential), so even if SMAP tells us a field has water content, that water might not be readily available. Water availability must be determined through a pedo-transfer function or moisture release curve appropriate for a specific soil type (It is possible to overlay SMAP data on soil type data to estimate energy state, but this might not be fine enough resolution to be useful).

Complementary Technology

How do SMAP and in situ instruments work together? The key is ground truthing in situ soil moisture measurements with SMAP type satellites and vice versa. Ground-based measurements at specific locations can be matched with satellite information to extrapolate over a field and gain confidence in the small continuous scale alongside the larger infrequent scale. It’s analogous of a video camera recording one plant continuously while a single shot camera snaps whole-field pictures every day. With the SMAP “single-shot” we can say, something changed from time A to time B, but we don’t know what happened in the middle (rain event, etc.). In situ measurements will tell us the details of what happened in between each snapshot. Putting both data sets together and matching trends, we can show correlation and complete the soil moisture picture. Basically, In situ measurements provide temporally rich information about soil moisture from a postage stamp-sized area of earth’s surface (driven by highly localized conditions), whereas SMAP gives us the ability to monitor broad scale spatiotemporal patterns across all of earth’s surface (driven by synoptic conditions).

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Measuring and Modeling the Environment

Posts tagged ‘Soils’

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Take our Soil Moisture Master Class

Aquifer Recharge

Climate Considerations

Using Preliminary Data to help Site Instrumentation

Proximity to Research Site

Proper Siting of Equipment Makes a Difference

Letters to a Young Scientist by E.O. Wilson

Out of the Scientist’s Garden by Richard Stirzaker

Introduction to Water in California by David Carle

The Drunkard’s Walk: How Randomness Rules our Lives, by Leonard Mlodinow

Chapter 13 of An Introduction to Environmental Biophysics, by Gaylon Campbell

What sparked your interest in science?

What was the first sensor you developed?

What’s the future of sensor technology?

Take our Soil Moisture Master Class

Animals and insects:

Lightning:

Wildfire:

Flooding:

Idea:

Where it came from:

Damage it does:

Why it’s wrong:

What do we do now:

Some Ideas Never Die:

Harness the power of soil moisture

Take our Soil Moisture Master Class

Pick the Right Place to Install your Sensors

Be Careful with the Way you Install Sensors

Beware of Simple Mistakes

What is SMAP?

What does SMAP mean for in situ soil water content measurement?

What can SMAP do that in situ measurement can’t?

What can in situ sensors do that SMAP can’t?

Complementary Technology

**Chapter 13 of An Introduction to Environmental Biophysics, by Gaylon Campbell**