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Posts tagged ‘Soil Moisture Sensor’

How to analyze soil moisture data

CONTRIBUTORS

You’ve buried soil water content and water potential sensors in the ground, installed an ATMOS 41 in the field, and set up your ZL6 data logger. Your network of instruments has been collecting data for days, weeks, or even all season. Now what? Performing soil moisture data analysis for your research location is one thing. Knowing how to extrapolate meaningful inferences and conclusions to understand what is happening and troubleshoot issues is completely different.

In this article, we will step through multiple data sets to understand how soil water content, soil temperature, soil water potential, and atmospheric measurements can be used to discover the meaning behind the traces. Within this article you will learn how to identify the following events in your data:

  • Behavior of soil moisture sensors in different soil types
  • Infiltration
  • Flooding
  • Soil cracking
  • Freezing
  • Spatial variability
  • Temperature effects
  • Diurnal patterns due to hydraulic redistribution
  • Broken sensors
  • Installation problems

Each example will be represented by a graph. It is not necessary to understand every aspect of information within these graphs. Each one is used as an illustration of common soil moisture data patterns you might run into and how to extrapolate the most useful information possible from the patterns seen. Each graph will have a box in the upper right-hand side corner with the soil type and crop type so you have a better understanding of the variables at play.

All of the data provided was collected by data loggers, such as our ZL6 series, and uploaded to ZENTRA Cloud for remote viewing at the convenience of the user. All data sets are either from METER’s own instrumentation or are supplied by the data owner and are included with their permission.

A photograph of a ZL6 next to a tablet showing ZENTRA Cloud data
Figure 1. ZL6 Basic data logger with data collected and stored within the ZENTRA Cloud platform
Effects of soil types
A graph showing water content and water potential measurements for a turf grass in loamy sand in wet conditions
Figure 2. Water content and water potential measurements for a turf grass in loamy sand in wet conditions

In Figure 2 we see the data from an engineered loamy sand with a cover crop of turf grass. Our goal when executing our experiments in this example was to improve irrigation in turf grass. This grass had a fairly shallow root zone, the middle of which was about six cm deep and the bottom at about 10 cm. Over time, this example showed first relatively wet conditions to start through June and July, a fixed drying period condition in July and August, and drying until the cessation of water uptake in August and September.

This graph shows two soil moisture data types: volumetric water content on the left y-axis and matric potential, or water potential, on the right y-axis. Time is on the x-axis ranging from early summer to the start of fall. To understand what these data clusters can tell us, we must look at each data set individually.

Read the full article

How to analyze soil moisture data

CONTRIBUTORS

You’ve buried soil water content and water potential sensors in the ground, installed an ATMOS 41 in the field, and set up your ZL6 data logger. Your network of instruments has been collecting data for days, weeks, or even all season. Now what? Performing soil moisture data analysis for your research location is one thing. Knowing how to extrapolate meaningful inferences and conclusions to understand what is happening and troubleshoot issues is completely different.

Farm field
Learn how to identify and understand behavior of soil moisture sensors in different soil types

In this article, we will step through multiple data sets to understand how soil water content, soil temperature, soil water potential, and atmospheric measurements can be used to discover the meaning behind the traces. Within this article you will learn how to identify the following events in your data:

  • Behavior of soil moisture sensors in different soil types
  • Infiltration
  • Flooding
  • Soil cracking
  • Freezing
  • Spatial variability
  • Temperature effects
  • Diurnal patterns due to hydraulic redistribution
  • Broken sensors
  • Installation problems

Each example will be represented by a graph. It is not necessary to understand every aspect of information within these graphs. Each one is used as an illustration of common soil moisture data patterns you might run into and how to extrapolate the most useful information possible from the patterns seen. Each graph will have a box in the upper right-hand side corner with the soil type and crop type so you have a better understanding of the variables at play.

All of the data provided was collected by data loggers, such as our ZL6 series, and uploaded to ZENTRA Cloud for remote viewing at the convenience of the user. All data sets are either from METER’s own instrumentation or are supplied by the data owner and are included with their permission.

A photograph of a ZL6 next to a tablet showing ZENTRA Cloud data
Figure 1. ZL6 Basic data logger with data collected and stored within the ZENTRA Cloud platform
Effects of soil types
A graph showing water content and water potential measurements for a turf grass in loamy sand in wet conditions
Figure 2. Water content and water potential measurements for a turf grass in loamy sand in wet conditions

In Figure 2 we see the data from an engineered loamy sand with a cover crop of turf grass. Our goal when executing our experiments in this example was to improve irrigation in turf grass. This grass had a fairly shallow root zone, the middle of which was about six cm deep and the bottom at about 10 cm. Over time, this example showed first relatively wet conditions to start through June and July, a fixed drying period condition in July and August, and drying until the cessation of water uptake in August and September.

This graph shows two soil moisture data types: volumetric water content on the left y-axis and matric potential, or water potential, on the right y-axis. Time is on the x-axis ranging from early summer to the start of fall. To understand what these data clusters can tell us, we must look at each data set individually.

Read the full article here: https://metergroup.com/measurement-insights/how-to-analyze-soil-moisture-data/

Office Hours Episode 11: Soil Moisture

There’s a lot to consider when collecting soil moisture measurements.

Get your soil moisture questions answered in our Office Hours series.

Join Environment Support Manager, Chris Chambers, and Director of Science Outreach, Leo Rivera, as they discuss submitted questions all about getting the best soil moisture measurements.

In the full episode, they discuss: 

  1. How difficult is the calibration of dielectric sensors? 
  2. How does soilless media affect the operation of dielectric sensors? 
  3. How much can organic soil amendments influence soil moisture? 
  4. Is it possible to determine the soil hydraulic properties from soil water content? 
  5. Why volumetric water content instead of gravimetric water content? 
  6. What is the best way to correct for the temperature sensitivity of sensors? 
  7. And more. 

Watch the full episode now: https://metergroup.com/office-hours-qa/office-hours-11-soil-moisture-measurements/

Combining in situ soil moisture with satellite data for improved irrigation recommendations

Improving irrigation requires smart data gathering to help growers make better choices in the field. Measuring in situ creates high-resolution, temporal data enabling us to see clearly what’s happening over time—but only at a single point. Satellites show data across a large spatial scale but are hampered by revisit frequencies, clouds, and resolution limits.

Often we see information in a silo, looking at one type of data or another. The challenge to researchers is how to connect across these scales and combine the information to make better irrigation decisions. In this webinar, Dr. Colin Campbell explores the future of irrigation and research he’s been doing with collaborators at Brigham Young University. Learn:

  • How researchers are combining in situ, drone, and satellite measurements to extract key information
  • How these data can be connected across scales 

Watch it now

 

3 Insider Strategies for a More Accurate Soil Moisture Picture (part 2)

Different readings in soil moisture sensors are caused by spatial variation in water content (see part 1). These readings provide researchers with valuable information about soil texture, watering patterns, and water use. This week, learn two more strategies to keep in mind when trying to understand the varying patterns of soil moisture at your research or irrigation site.

Tree standing in a green field

In some crop studies, it may be important to account for horizontal variation.

Strategy #2: Crop Studies—Representing Variation in a Homogeneous Environment

In some research projects, it will be important to account for horizontal variation. How variable is the water content across a field? We did an experiment in which we set out a transect across a field of bare, tilled soil. Using a METER EC-5 soil moisture sensor connected to Procheck meter, we sampled water content at one-meter intervals over a 58-meter distance. The individual readings are shown in Figure 1.

Soil volumetric water content and measurement number chart

Figure 1. You can determine how many samples are necessary to characterize a homogeneous area in about an hour using an EC-5 soil moisture sensor and a ProCheck.

In this data set, the samples are not spatially correlated. The variation is apparent. The mean water content of the data set is 0.198 m3m-3. The standard deviation is 0.023 m3m-3 . The coefficient of variation is 12%. Using some simple geostatistics, we determined that three carefully placed sites would adequately represent the variation present in this very homogeneous environment. Of course, in some environments, samples will not be independent. If a semivariogram indicates that some underlying spatial factor influences soil moisture variability, you will have to consider that in your experimental design.

Forest of trees

By taking into account the major relevant sources of soil moisture variation, you can plan enough sampling locations to draw conclusions from your data.

Strategy #3: Ecology Studies—Heterogeneous Environments

On a forested hillside, horizontal variation in soil moisture will obviously be significant. Determining how many sensors to use and where to place them is not at all trivial. Stratified sampling—systematically sampling from more uniform subgroups of a heterogeneous population—may be a better way to deal with this kind of variety. The researcher classifies the site into strata (eg., forested canopy, brush, hillside, valley) and evaluates the number of samples needed to statistically represent the variation present within each stratum.

Many people allow for the variation in soil moisture values that come from the slope, orientation, vegetation, and canopy cover. Some fail to consider the important soil-level variations that come from soil type and density. By taking into account the major relevant sources of soil moisture variation, you can plan enough sampling locations to draw reasonable conclusions from your data. Choose too few locations, and you run the risk of missing the patterns that will lead to higher-level understanding. Choose too many, and not only will you be unable to afford your experiment, but you may also miss the patterns altogether as your experiment overflows with random abundance.

Image is an example of a heterogeneous research area with different slopes and vegetation

Sometimes researchers want to compare dissimilar sites.

Comparing Data from Different Sites or Strata

Comparing absolute water content numbers can give confusing results. Both measurements are volumetric water content, but 35% here vs. 15% there actually tells us very little. Was the site in sand or clay, or something in between? If conditions at the two sites are virtually identical, the comparison may make some sense. But often, researchers want to compare dissimilar sites.

Volumetric water content and depth in a chart

Figure 2. Changes in VWC with depth (convention: negative values indicate depths below soil surface) for the same time period at Site 1.

Water potential measurements determined by converting absolute volumetric water content to soil water potential using a moisture characteristic curve specific to each soil type can be used to compare results across sites. Comparing relative values—quantities of water used in centimeters for example—can also be both useful and valid.

Figure 3 below illustrates an experiment we performed in a dryland field where water content measurements were made over a growing season at 30, 60, 90, 120, and 150 cm below a wheat crop.  The graph of soil moisture data shows how water is taken up from successively deeper layers. By subtracting one profile from another and summing over the layers where change occurs (for instance, in Figure 2 above, subtract the far left line from the far-right line to see how much water was used from May 10th to August 21st), you can determine the amount of water used by the plants over a particular period.  If similar data were taken at different sites or in different strata, these relative values, in terms of quantified water use, could form the basis of solid comparison studies.

Soil water content in winter wheat

Figure 3. Soil water content in winter wheat measured at 30 cm increments

Read more about accurate soil moisture:  Can you sample the profile without a profile probe?  Find out.

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

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

3 Insider Strategies for a More Accurate Soil Moisture Picture (Part 1)

How Do you Know You’re Getting Accurate Soil Moisture?

Researchers and irrigators may wonder if their soil moisture sensors are accurate because probes at different locations in the same field have different water content readings. Different readings in soil moisture sensors are caused by spatial variation in water content. These readings provide researchers valuable information about soil texture, watering patterns, and water use. Here are some ideas and strategies to keep in mind when trying to understand the varying patterns of soil moisture at your research or irrigation site. Click the links for more in-depth information about accurate soil moisture.

Grapes on the vines down isles

One irrigator noticed a few sensors indicating low water content after a heavy rain that had uniformly wetted his vineyard.

Horizontal vs. Vertical Variation

It’s helpful to distinguish variation in the vertical from variation in the horizontal. Most people expect strong vertical variation due to wetting and drying patterns, soil horizonation, and compaction. Water content can vary drastically over distances of only a few centimeters, especially near the soil surface. Horizontal variation is typically less pronounced in a bare or uniformly planted field, and at a given depth, it might be quite small. But surprisingly large variations can exist, indicating isolated patches of sand or clay or differences in topography. One irrigator noticed a few sensors indicating low water content after a heavy rain that had uniformly wetted his vineyard. Knowing that sand has a low field capacity water content, he surmised (correctly) that he had found the sandy areas in the vineyard.

Researcher holding an ECHO EC-5 in front of soil

Soil moisture sensors sometimes measure unexpected things.

Unexpected Readings

Because properly installed dielectric soil moisture sensors lie in undisturbed (and therefore unanalyzed) soil, they sometimes measure unexpected things. One researcher buried a probe in what appeared to be a very dry location and was startled to measure 25 to 30% volumetric water content. Those readings made the soil appear saturated, but obviously, it wasn’t. She dug down to the sensor and found a pocket of clay. As she discovered, it is impossible to get much information from an absolute water content measurement without knowing what type of soil the sensor is in.

Since we expect variation, how do we account for it? How many probes are needed to adequately characterize the water content in an application or experiment? There is no simple answer to this question. The answer will be affected by your site, your goals, and how you plan to analyze your data. Here are some things you might consider as you plan.

Sun rising behind a wheat field

If a field will be irrigated as a unit, it should be monitored as a unit at one representative spot.

Strategy #1: Irrigation—Use Soil Moisture as an Indicator

What information do you have when you know a field’s volumetric water content? That number independently tells an irrigator very little. Soil moisture can be used like a gauge to show when a field is full and when it needs to be refilled, but the “full” and “empty” are only meaningful in context.

The goals of irrigation are to keep root zone water within prescribed limits and to minimize deep drainage. Understanding and monitoring the vertical variation lets you correlate a real-time graph of water use data with above-ground field conditions and plant water needs. It makes sense to place probes both within and below the root zone.

By contrast, measuring horizontal variation—placing sensors at different spots in the field—is not very helpful. If a field will be irrigated as a unit, it should be monitored as a unit at one representative spot. Because there’s no way to adjust water application in specific spots, there’s no benefit to quantifying spatial variation in the horizontal. Like a float in a gas tank, a set of soil moisture sensors in the right spot will adequately represent the changing soil moisture condition of the whole field.

We recommend a single probe location in each irrigation zone with a minimum of one probe in the root zone and one probe below it. Additional probes at that site, within and below the root zone, will increase the reliability of the information for the irrigation manager, at minimal additional cost.

In two weeks: Learn two more techniques researchers use in crop studies and ecology studies to account for variability in order to obtain an accurate soil moisture picture.

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

Which Soil Sensor Should I Choose?

Dr. Colin Campbell, METER soil scientist, explains soil sensor differences, pros, cons, and things to consider when choosing which sensor will best accomplish your research goals. Use the following considerations to help identify the perfect sensor for your research.  Explore the links for a more in-depth look at each topic.

Researcher Holding a TEROS 12

Scientists often measure soil moisture at different depths to understand the effects of soil variability and to observe how water is moving through the soil profile.

CHOOSE THE RIGHT MEASUREMENT

  • Volumetric Water Content:  If a researcher wants to measure the rise and fall of the amount (or percentage) of water in the soil, they will need soil moisture sensors. Soil is made up of water, air, minerals, organic matter, and sometimes ice.  As a component, water makes up a percentage of the total.  To directly measure soil water content, one can calculate the percentage on a mass basis (gravimetric water content) by comparing the amount of water, as a mass, to the total mass of everything else.  However, since this method is labor-intensive, most researchers use soil moisture sensors to make an automated volume-based measurement called Volumetric Water Content (VWC). METER soil moisture sensors use high-frequency capacitance technology to measure the Volumetric Water Content of the soil, meaning they measure the quantity of water on a volume basis compared to the total volume of the soil.  Applications that typically need soil moisture sensors are watershed characterization, irrigation schedulinggreenhouse management, fertigation management, plant ecology, water balance studies, microbial ecology, plant disease forecasting, soil respiration, hydrology, and soil health monitoring.
  • Water potential:  If you need an understanding of plant-available water, plant water stress, or water movement (if water will move and where it will go), a water potential measurement is required in addition to soil moisture. Water potential is a measure of the energy state of the water in the soil, or in other words, how tightly water is bound to soil surfaces. This tension determines whether or not water is available for uptake by roots and provides a range that tells whether or not water will be available for plant growth. In addition, water always moves from a high water potential to a low water potential, thus researchers can use water potential to understand and predict the dynamics of water movement.

Understand your soil type and texture

In soil, the void spaces (pores) between soil particles can be simplistically thought of as a system of capillary tubes, with a diameter determined by the size of the associated particles and their spatial association.  The smaller the size of those tubes, the more tightly water is held because of the surface association.

Clay holds water more tightly than a sand at the same water content because clay contains smaller pores and thus has more surface area for the water to bind to. But even sand can eventually dry to a point where there is only a thin film of water on its surfaces, and water will be bound tightly.  In principle, the closer water is to a surface, the tighter it will be bound. Because water is loosely bound in a sandy soil, the amount of water will deplete and replenish quickly.  Clay soils hold water so tightly that water movement is slow. However, there is still available water.

Note: Use the PARIO soil texture analyzer to automate soil texture identification.

Two measurements are better than one

In all soil types and textures, soil moisture sensors are effective at measuring the percentage of water. Dual measurements—using a water potential sensor in addition to a soil moisture sensor—gives researchers the total soil moisture picture and are much more effective at determining when, and how much, to water.  Water contendata show subtle changes due to daily water uptake and also indicate how much water needs to be applied to maintain the root zone at an optimal level.  Water potential data determine what that optimal level is for a particular soil type and texture.

Get the big picture with moisture release curves  

Dual measurements of both water content and water potential also enable the creation of in situ soil moisture release curves (or soil water characteristic curves) like the one below (Figure 1), which detail the relationship between water potential and water content.  Scientists and engineers can evaluate these curves in the lab or the field and understand many things about the soil, such as hydraulic conductivity and total water availability.

Turf-grass Soil Moisture Release Curve

Figure 1. Turfgrass soil moisture release curve (black). Other colors are examples of moisture release curves for different types of soil.

Read the full article

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

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

Get more information on applied environmental research in our

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—>

How to Protect your Soil Moisture Sensors from Lightning Surge

We occasionally see soil moisture sensors damaged by lightning.  Here’s what to do to protect them.

The secondary products of a lightning strike include electromagnetic pulses, electrostatic pulses, and earth current transients.

Lighting striking

Surge suppression components typically perform their suppression function by temporarily short circuiting the voltage between two wires, several devices, or ground.

Electromagnetic pulses are created by the strong magnetic field that is formed by the short term current flow taking place in the lightning strike. With current flows as high as 510kA per microsecond, these currents create very large magnetic fields. These short-term magnetic fields then induce voltages onto wires and cables.

Electrostatic pulses are created by electrostatic fields that accompany a thunderstorm. Any cable suspended above the earth during a thunderstorm is immersed in the electrostatic field and will be electrically charged. Quick changes in the charges stored in both the clouds and earth take place whenever there is a lightning strike. The charge on the cable must now be discharged or neutralized. Unable to find a path to ground (earth), it breaks down insulation and component in its efforts to return to earth.

Earth current transients are the direct result of the neutralization process that immediately follows the end of lightning strike. Neutralization is accomplished by the movement or redistribution of charge along or near the earth’s surface from all the points where the charge had been initially induced to the point where the lightning strike has just terminated. Earth current transients create a shift in potential across a ground plan, often called a “ground bounce”.

Read more

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

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

Soil Moisture Sensors: Which Installation Method is Best?

Patterns of water replenishment and use give rise to large spatial variations in soil moisture over the depth of the soil profile. Accurate measurements of profile water content are therefore the basis of any water budget study. When monitored accurately, profile measurements show the rates of water use, amounts of deep percolation, and amounts of water stored for plant use.

How to avoid measurement errors

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

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

All dielectric probes are most sensitive at the surface of the probe. Any loss of contact between the probe and the soil or compaction of soil at the probe surface can result in large measurement errors. Water ponding on the surface and running in preferential paths down probe installation holes can also cause large measurement errors.

Installing soil moisture sensors will always involve some digging. How do you accurately sample the profile while disturbing the soil as little as possible?  Consider the pros and cons of five different profile sampling strategies.

Preferential flow is a common issue with commercial profile probes

Profile probes are a one-stop solution for profile water content measurements. One probe installed in a single hole can give readings at many depths. Profile probes can work well, but proper installation can be tricky, and the tolerances are tight. It’s hard to drill a single, deep hole precisely enough to ensure contact along the entire surface of the probe. Backfilling to improve contact results in repacking and measurement errors. The profile probe is also especially susceptible to preferential-flow problems down the long surface of the access tube.  (NOTE: The new TEROS Borehole Installation Tool eliminates preferential flow and reduces site disturbance while allowing you to install sensors at depths you choose.)

Trench installation is arduous

Installing sensors at different depths through the side wall of a trench is an easy and precise method, but the actual digging of the trench is a lot of work. This method puts the probes in undisturbed soil without packing or preferential water-flow problems, but because it involves excavation, it’s typically only used when the trench is dug for other reasons or when the soil is so stony or full of gravel that no other method will work. The excavated area should be filled and repacked to about the same density as the original soil to avoid undue edge effects.

Researcher is holding an ECHO EC-5 in front of soil

Digging a trench is a lot of work.

Augur side-wall installation is less work

Installing probes through the side wall of a single augur hole has many of the advantages of the trench method without the heavy equipment. This method was used by Bogena et al. with EC-5 probes. They made an apparatus to install probes at several depths simultaneously. As with trench installation, the hole should be filled and repacked to approximately the pre-sampling density to avoid edge effects.

An augered borehole disturbs the soil layers, but the relative size of the impact to the site is a fraction of what it would be with a trench installation. A trench may be about 60 to 90 cm long by 40 cm wide. A borehole installation performed using a small hand auger and the TEROS Borehole Installation Tool creates a hole only 10 cm in diameter—just 2-3% of the area of a trench. Because the scale of the site disturbance is minimized, fewer macropores, roots, and plants are disturbed, and the site can return to its natural state much faster. Additionally, when the installation tool is used inside a small borehole, good soil-to-sensor contact is ensured, and it is much easier to separate the horizon layers and repack to the correct soil density because there is less soil to separate.

Multiple-hole installation protects against failures

Digging a separate access hole for each depth ensures that each probe is installed into undisturbed soil at the bottom of its own hole. As with all methods, take care to assure that there is no preferential water flow into the refilled augur holes, but a failure on a single hole doesn’t jeopardize all the data, as it would if all the measurements were made in a single hole.

The main drawback to this method is that a hole must be dug for each depth in the profile. The holes are small, however, so they are usually easy to dig.

Single-hole installation is least desirable

It is possible to measure profile moisture by auguring a single hole, installing one sensor at the bottom, then repacking the hole, while installing sensors into the repacked soil at the desired depths as you go. However, because the repacked soil can have a different bulk density than it had in its undisturbed state and because the profile has been completely altered as the soil is excavated, mixed, and repacked, this is the least desirable of the methods discussed. Still, single-hole installation may be entirely satisfactory for some purposes. If the installation is allowed to equilibrate with the surrounding soil and roots are allowed to grow into the soil, relative changes in the disturbed soil should mirror those in the surroundings.

Reference

Bogena, H. R., A. Weuthen, U. Rosenbaum, J. A. Huisman, and H. Vereecken. “SoilNet-A Zigbee-based soil moisture sensor network.” In AGU Fall Meeting Abstracts. 2007. Article link.

Read more soil moisture sensor installation tips.

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

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

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—>

Stem Water Content Changes Our Understanding of Tree Water Use (Part 2)

This week, we continue highlighting the second of two current research projects (see part one) which use soil moisture sensors to measure volumetric water content in tree stems and why this previously difficult to obtain measurement will change how we look at tree water use.

Image of Tamarisk tree in Sudan

Tamarisk tree: an invasive species dominant in Sudan and arid parts of the United States. (Photo credit: biolib.cz)

Determining Tree Stem Water Content in Drought Tolerant Species

Tadaomi Saito and his research team were interested in using dielectric soil moisture sensors to measure the tree stem volumetric water content of mesquite trees and tamarisk, two invasive species dominant in Sudan and arid parts of the United States. Mesquite is a species that can access deep groundwater sources using their taproots which is how they compete with native species. Tamarisk, on the other hand, uses shallow, saline groundwater to survive.  The team wanted to see if dielectric probes were useful for real-time measurement of plant water stress in these drought-tolerant species and if these measurements could illuminate differing tree water-use patterns.  These sensors could then potentially be used for precision irrigation strategies to assist in agricultural water management.  

Temperature Calibration Was Essential

After calibrating the soil moisture sensors to the wood types in a lab, the team inserted probes into the stems of both trees.  They also monitored groundwater and soil moisture content to try and infer whether or not the trees were plugged into a deep source of water.  Interestingly, Saito found that, unlike soil, where temperature fluctuation is buffered, tree stems are subject to large variations in temperature throughout the course of the day.  This temperature fluctuation interfered with the soil moisture probes’ ability to accurately measure VWC.   The team came up with a simple method for accounting for temperature variability and were then able to obtain accurate VWC measurements.  

Image of a Mesquite tree on a desert mountain slope

Photo credit: desertusa.com

Water Use Depended on Landscape Position

Saito’s results were similar to Ashley Matheny’s study (see part 1), in that they found a lot of different patterns, even in trees of the same species.  Water-use depended on where the trees were on the landscape.  Some of them were tapped into groundwater, and the stem water storage didn’t change no matter how dry the soil became.  Whereas others, depending on their position in the landscape, were very dependent on soil moisture conditions.  

You can read the full study details here.

Implications

Saito’s study illustrates that we see everything about a tree that’s above ground, but we may have no sense of what’s going on below ground.   We can put a soil moisture sensor in the ground and decide there’s plenty of moisture available.  Or if conditions are dry, we may decide the tree is under drought stress, but we don’t know if that tree is tapped into a more permanent source of groundwater.   

Other researchers have put soil moisture sensors in orchards looking at stem water storage from a practical standpoint for irrigation management.  Their data didn’t work out so well because of cable sensitivity where water on the cable created false readings.  However, the data they were able to obtain showed that some of the trees were plugged into water sources that were independent of the soil.  Those trees were able to withstand drought and needed less irrigation, whereas other trees were much more sensitive to soil moisture.  

If we had an inexpensive, easy to deploy measurement device plugged into every tree in an orchard, we could irrigate tree by tree, give them precisely what they needed, and account for their unique situation.

What Does it All Mean?

The interesting thing about using soil moisture sensors in a tree is that stem water content is a difficult-to-obtain piece of information that has now been made easier.  Historically, we’ve focused on measuring sap flow, but that’s just how much water is flowing past the sensor. We’ve measured what’s in the soil: a pool of moisture that’s available to the tree. But some trees are huge in size, such as ones along the coast of California. They’re able to store vast amounts of water above-ground in their tissue.  Understanding how a tree can use that water to buffer or get through periods of drought is a unique research topic that has had very little attention. With these kinds of sensors, we can start to investigate those questions.

Reference: Saito T., H. Yasuda, M. Sakurai, K. Acharya, S. Sueki, K. Inosako, K. Yoda, H. Fujimaki, M. Abd Elbasit, A. Eldoma and H. Nawata , Monitoring of stem water content of native/invasive trees in arid environments using GS3 soil moisture sensor , Vadose Zone Journal , vol.15 (0) (p.1 – 9) , 2016.03

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

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

Get more information on applied environmental research in our