In a continuation of our popular series inspired by the book, This Idea Must Die: Scientific Problems that are Blocking Progress, Dr. Gaylon S. Campbell relates a story to illustrate the filter paper method, a scientific concept he thinks impedes progress:
There are times when our independent verification turns out to be like the clock and the whistle, and we end up inadvertently chasing our tail.
I remember listening to a story about a jeweler who displayed a big clock in the front window of his store. He noticed that every day a man would stop in front of the store window, pull out a pocket watch, set the watch to the time that was on the large clock, and then continue on. One day, the jeweler decided to meet the man in order to see why he did that. He went out to the front of the store, intercepted the man, and said, “I noticed you stop here every day to set your watch.”
The man replied, “Yes, I’m in charge of blowing the whistle at the factory, and I want to make sure that I get the time exactly right. I check my watch every day so I know I’m blowing the whistle precisely at noon.”
Taken aback, the jeweler replied, “Oh, that’s interesting. I set my clock by the factory whistle.”
The Wrong Idea:
In science, we like to have independent verification for the measurements we make in order to have confidence that they are made correctly, but there are times when our independent verification turns out to be like the clock and the whistle, and we end up inadvertently chasing our tail. I’ve seen this happen to people measuring water potential (soil suction). They measure using a fundamental method like dew point or thermocouple psychrometry, but then they verify the method using filter paper. Filter paper is a secondary method—it was originally calibrated against the psychometric method. It’s ridiculous to use a secondary method to verify an instrument based on fundamental thermodynamics.
Geotechnical engineers use natural material such as soil and rock in combination with engineered material to design dams, tunnels, and foundations for all kinds of structures.
Where the Filter Paper Method Came From:
Before the development of modern vapor pressure measurements, field scientists needed an inexpensive, easy method to measure water potential. I.S. McQueen in the U.S. Geological Survey and some others worked out relationships between the water content of filter paper and water potential by equilibrating them over salt solutions. Later, other scientists standardized this method using thermocouple psychrometers so that there was a calibration. Filter paper was acceptable as a kind of a poor man’s method for measuring water potential because it was inexpensive, assuming you already had a drying oven and a balance. The thermocouple psychrometer and later the dew point sensor quickly supplanted filter paper in the field of soil physics. However, somewhere along the line, the filter paper technique was written into standards in the geotechnical area and the change to vapor methods never occurred. Consequently, a new generation of geotechnical engineers came to rely on the filter paper method. Humorously, when vapor pressure methods finally took hold, filter paper users became focused on verifying these new fundamental methods with the filter paper technique to see whether they were accurate enough to be used for water potential measurement of samples.
What Do We Do Now?
Certainly, there’s no need to get rid of the filter paper method. If I didn’t have anything else, I would use it. It will give you a rough idea of what the water potential or soil suction is. But the idea that I think has to die is that you would ever check your fundamental methods (dewpoint or psychrometer) against the filter paper method to see if they were accurate. Of course they’re accurate. They are based on first principles. The dew point or psychrometer methods are a check to see if your filter paper technique is working, which it quite often isn’t (watch this video to learn why).
Which scientific ideas do you think need to be revised?
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.
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.
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?
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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.
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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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.
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.
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.
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.
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.
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.
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.
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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Traveling around the world, I’ve seen many ways to install soil moisture sensors. Digging a trench to the required depth and inserting the sensors into the sidewall is certainly the most common technique. But using a shovel takes a lot of effort, especially in rocky soil. To solve this problem, I like to use an auguring tool because of its ability to dig through soil to deeper depths without taking a lot of time. Also, the footprint of an augured hole is also only a few inches, which makes for a much cleaner installation. Still, borrowing an auger from the lab next door and heading to the field may not be the best option. This is what we did on the Cook Farm project a few years back.
Standard bucket auger (image: www.atlanticsupply.com)
The Cook Agricultural Farm is a 37 Ha managed research site near Pullman, Washington where a combined team of Decagon and WSU scientists installed 150 water contentsensors over 30 sites a few years ago. At each site, we used the techniques outlined in METER’s installation video, which can be found here. However, the hardest thing about this installation was that we used some borrowed, standard bucket augers to bore the holes. These had a cutting surface along the bottom and an enclosed cylinder to hold the soil. Once we filled that bucket, we had a difficult time getting the soil out which really slowed the installation.
Ben digging soil out of the bucket auger during the Cook Farm Installation, 2009.
Recently while traveling to Germany, I learned about the Edelman Auger. The company that makes these (Eijkelkamp), says that most people in America use bucket augers to bore into fine soils which is needlessly time consuming. Edelman Augers, originally designed by the Army to dig latrines, will save time and labor.
Edelman auger.
At first, I was skeptical. It only had two cutting blades that ran up the auger in kind of loop; how would the soil lift out of the hole? However, when I tried one later in the day, the auger cut through the soil, making a 10 cm hole with very little effort, and as I removed it, the soil came out easily. It wasn’t hard to get the soil out from between the blades because there was no enclosed cylinder for the bucket. I wish I’d known about this auger when I was trying to install sensors at the Cook Farm.
So, here are a few tips about augers to help you pick the best one for your work:
The Eijkelkamp Edelman augers are best for silty soils to clay soils so pick this one if you’re working in sites with these types of soils. It’s also great for digging a quick latrine.
Bucket augers are best for sandy soils because of the enclosed cylinder will help lift the loose sand out of the borehole.
If you’re trying to install your soil moisture sensors in very rocky soils, try a stony soil auger. It has big blades to help move small rocks and lift them out of the hole.
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 situsensors 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).
Both the amount and the availability of water in soil is important to plant roots and soil-dwelling organisms. To describe the amount of water in the soil we use the term water content. To describe the availability we talk of water potential. In thermodynamics, the water content would be referred to as the extensive variable and the water potential as the intensive variable. Both are needed to correctly describe the state of water in soil and plants.
In addition to describing the state of water in the soil, it may also be necessary to know how fast water will move in the soil. For this, we need to know the hydraulic conductivity. Other important soil parameters are the total pore space, the drained upper limit for soil water, and the lower limit of available water in a soil. Since these properties vary widely among soils, it would be helpful to establish correlations between these very useful parameters and easily measured properties such as soil texture and bulk density. This paper will present the information needed for simple models of soil water processes.
METER’s founder, Dr. Gaylon S. Campbell was born in Blackfoot, Idaho, and grew up on a dry farm in Juniper, Idaho. He went to school in Logan, Utah, finally attending Utah State University where he received a B. S. in Physics in 1965 and an M. S. in Soil Physics in 1966. He was granted a Ph. D. in Soil Physics from Washington State University in 1968. He became an officer in the U. S. Army in 1969, doing meteorological research at White Sands Missile Range, New Mexico. In 1971 he returned to Washington State University as Assistant Professor of Biophysics and Assistant Soil Scientist. There he taught and did research in Environmental Biophysics and Soil Physics until 1998. Since 1998 he has worked as vice president, engineer, and scientist at Decagon Devices, Inc (now METER). He has written three books, over 100 refereed journal articles and book chapters, and has several patents. Today we are interviewing him about his book, An Introduction to Environmental Biophysics.
Dr. Campbell is the author of An Introduction to Environmental Biophysics
Where did you get the knowledge to write the book?
I was hired to teach Environmental Biophysics at Washington State University in 1971, and when I looked around for a textbook to go with the class, there weren’t any that fit very well. I knew what I wanted to teach in the class, and some of the principles were in books that were available, but a lot weren’t. So I started writing up notes to hand out to the students and then improved them over time.
One of the important sources of knowledge for my book was John Montieth’s book, Principles of Environmental Physics. Its first edition came out in 1973. It’s a wonderful book. I didn’t know about it until one of my students brought it into class and let me borrow it overnight.
I went home and started reading it. I read it all night, and by morning I’d finished it. I have read some novels that could keep me awake all night, but that’s the only science book I ever read that could do it.
I was really excited about his approach because it was perfect for what I wanted to do in the class. However, it was at a different level than I needed, so I went ahead and developed my own notes, but his book certainly was an important source.
I started writing up notes to hand out to the students and then improved them over time.
How difficult was it to understand the theory behind what you were writing about?
When I’d take a class in school, I felt like I never understood what was in that class until I attended the next class. Then when I got a bachelor’s degree, I thought, I hope nobody expects me to know something just because I have this degree, because I don’t feel like I know anything. I hoped when I earned a masters degree that it would be better, but I got there and thought, oh boy, I still don’t know anything. It was probably when I took my prelim exam that I finally felt confident enough that I could be a soil physicist if I had to.
But I was wrong about that. I really didn’t understand physics very well, even then. It was when I had to teach it that the real understanding came. When I understood it well enough to lecture about it was when I felt like I had really mastered the theories and understood them at the level that I wanted to.
I suppose that came one piece at a time. In the beginning, I certainly didn’t understand things as well as I did later on. And that still happens today. I learn things that I hadn’t understood before. So I guess when you ask how hard it was: it was an ongoing process. Even when somebody’s already laid it out for you, it doesn’t mean you’re going to understand it. But when you lecture about it and write about it, those are the processes that help to deepen your knowledge and understanding.
When you lecture about a subject and write about it, those are the processes that help to deepen your knowledge and understanding.
The subject is extremely complicated, but people are always saying how easy it is to understand environmental biophysics from your book. How did you bring it down to the level of the students?
When I was in the Army, the philosophy they had was, “If the student hasn’t learned, the teacher hasn’t taught.” That was not the philosophy that you normally encountered at the university. Many professors complained often about how lousy their students were. I never found it to be that way. I always thought my students were getting better and better.
I think it comes down, to some extent, to the philosophy the teacher has. We often see teachers come in and fill the board with equations and wonder why their students don’t understand them. But it’s likely the teacher hasn’t looked at it from the standpoint of the students. The student is going to gain understanding by the same path the teacher did. Professors work and work to put together a wonderful picture of things, and once they have that wonderful picture, they tend to want to dump the whole thing on the student. But students can’t assimilate the whole picture all at once. They have to go step by step too.
If people wanted to learn from your book, what is the best way to get the principles down?
It’s no accident that there are lots of both worked examples and problems for students to solve. I don’t think you can learn physics without solving problems, and so the best way to do it is to look through the ones that we’ve solved in the book and then look through the problems we give at the end of the chapters and solve them. That, I think, is the best way to get there.
