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Posts from the ‘Soils’ Category

Snapdragons and soil moisture sensors

Charles Bauers has been a hydroponic snapdragon grower for 17 years. He knows—in detail—how to produce a good snap. But five years ago, he needed a better way to measure water.

Soil sensors optimize irrigation for improved quality and profit

“We had no quantitative way to measure water. That was the limiting factor for me,” he explains. Other inputs, like fertilizer, were quantifiable, but Bauers still depended on “gut feel” for watering, and no matter how quickly he reacted to changes in the crop, he couldn’t consistently produce grade-one snapdragons.

He wanted a scale, a “recipe of numbers” that would let him produce a good crop all the time in all sections of the greenhouse.

“There are always areas that seem to produce good quality flowers, and then there are areas that are a bit more of a challenge. I installed METER soil moisture sensors in the good areas and the stressed areas and compared the two. Then I worked my stressed areas up to the same numbers.”

The TEROS 12 is well-suited for greenhouse applications

Snapdragons are very sensitive to moisture stress. “It’s a ten-week crop. If you don’t get the moisture right in the first two weeks, you can compromise that crop.”

Identifying irrigation set points

The soil moisture sensors made a huge difference in Bauers’s ability to get the moisture right.  “They give me, targeted set points that I can shoot for all the time, and if I hit the targeted set point, I know I’m going to have good quality snaps, barring any other type of stress.

Grade-one snapdragons are worth 40% more than grade twos, and the difference between the two is created by “incipient stress—water stress that you can’t measure with your fingers. You can’t see it, you can’t feel it, it’s stress at the root. There’s a difference between a 28% vwc [volumetric water content] and a 23% vwc. It’s only 5%, but one produces grade ones and one produces grade twos.”

Empowered with real-time information

Moisture sensors gave Bauers real-time information that helped him get the watering right in every part of the greenhouse.  “I became more consistent because I had a number to go at. Because we’re a hydroponic crop, we see the effects real quick, and I’d say ‘I just have to add a little more water here.’ But [before the sensors,] invariably we had areas that were stressed because you really never knew when you had enough water on that crop. With sensors, you can consistently put the right amount of water on all the time.”

Soil sensors helped identify and prevent irrigation problems

Bauers quickly became adept at using sensors to address his irrigation challenges. The sensors showed him where his irrigation system was broken or underperforming, helped him identify problems like a root growing into a drip tube, or an unplugged dripper. But as the sensors became part of his routine, he was surprised to discover a new opportunity.

“Besides giving me the real-time information, the sensors gave me the ability to look at trends…over a week or a month and be proactive if we started moving away from our set point. We could add more water, set shorter run times, or just make some changes in the irrigation system to get more in line with the set points. That was one of my biggest surprises, how well we were able to be proactive toward environmental changes using the trending of the charts. That was a bonus.”

Reducing production and labor costs

After five years of daily monitoring, Bauers is now ready to go to an even higher level. “The next huge area we see sensors in is as big, or bigger, than the actual growing of the plant itself. We’re going to use these sensors to guide us as we strip out all excess production costs, and that’s happening today. As an example, over the next five months we’ll be trimming our substrate use by 85%. Not only do we save on materials, but if you have 85% less substrate to work with or move, you reduce labor costs.”

In fact, the sensors have become an integral part of how Bauers does business. I asked him how he would feel if he lost them. “My gosh,” he said, “It would be like going back ten years. It would be like trying to measure the temperature in a room without a thermometer. We are totally dependent on them.”

Learn more

Watch: How to improve irrigation scheduling using soil moisture—>

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Webinar: Why Water Content Can’t Tell You Everything You Need to Know

Water content can leave you in the dark

Everybody measures soil water content because it’s easy. But if you’re only measuring water content, you may be blind to what your plants are really experiencing.

Soil moisture is more complex than estimating how much water is used by vegetation and how much needs to be replaced. If you’re thinking about it that way, you’re only seeing half the picture. You’re assuming you know what the right level of water should be—and that’s extremely difficult using only a water content sensor.

Get it right every time

Water content is only one side of a critical two-sided coin. To understand when to water or plant water stress, you need to measure both water content and water potential.

TEROS 21 water potential sensor

In this 30-minute webinar, METER soil physicist, Dr. Colin Campbell, discusses how and why scientists combine both types of sensors for more accurate insights. Discover:

  • Why the “right water level” is different for every soil type
  • Why soil surveys aren’t sufficient to type your soil for full and refill points
  • Why you can’t know what a water content “percentage” means to growing plants
  • How assumptions made when only measuring water content can reduce crop yield and quality
  • Water potential fundamentals
  • How water potential sensors measure “plant comfort” like a thermometer
  • Why water potential is the only accurate way to measure drought stress
  • Why visual cues happen too late to prevent plant-water problems
  • Case studies that show why both water content and water potential are necessary to understand the condition of soil water in your experiment or crop

WATCH IT NOW—>

Presenter

Dr. Colin Campbell has been a research scientist at METER for 20 years following his Ph.D. at Texas A&M University in Soil Physics. He is currently serving as Vice President of METER Environment. He is also adjunct faculty with the Dept. of Crop and Soil Sciences at Washington State University where he co-teaches Environmental Biophysics, a class he took over from his father, Gaylon, nearly 20 years ago. Dr. Campbell’s early research focused on field-scale measurements of CO2 and water vapor flux but has shifted toward moisture and heat flow instrumentation for the soil-plant-atmosphere continuum.

Learn more

Download the “Complete guide to irrigation management”—>

How to Use Plant-Water Relations and Atmospheric Demand for Simplified Water Management

Going by soil moisture data alone?

Soil moisture data are useful, but they can’t tell you everything. Other strategies for growers and researchers, like plant and weather monitoring, can inform water management decisions.

Researcher using the SC-1 leaf porometer to measure stomatal conductance
Researcher using the SC-1 leaf porometer to measure stomatal conductance

In this webinar, world-renowned soil physicist, Dr. Gaylon Campbell shares his newest insights and explores options for water management beyond soil moisture. Learn the why and how of scheduling irrigation using plant or atmospheric measurements. Understand canopy temperature and its role in detecting water stress in crops. Plus, discover when plant water information is necessary and which measurement(s) to use. Find out:

  • Why the Penman-Monteith equation, with the FAO 56 procedures, gives a solid, physics-based method for determining potential evapotranspiration of a crop
  • How the ATMOS 41 microenvironment monitor combined with the ZL6 logger and ZENTRA Cloud give easy access to crop ET data
  • How assimilate partitioning can be controlled by manipulating plant water potential using appropriate irrigation strategies
  • Why combining monitoring soil water potential with deficit irrigation based on ET estimates provide an efficient and precise method for controlled water stress management
  • And more…

REGISTER NOW—>

Presenter

Dr. Gaylon S. Campbell has been a research scientist and engineer at METER for over 20 years, following nearly 30 years on faculty at Washington State University. Dr. Campbell’s first experience with environmental measurement came in the lab of Sterling Taylor at Utah State University making water potential measurements to understand plant water status.

Dr. Campbell is one of the world’s foremost authorities on physical measurements in the soil-plant-atmosphere continuum. His book written with Dr. John Norman on Environmental Biophysics provides a critical foundation for anyone interested in understanding the physics of the natural world. Dr. Campbell has written three books, over 100 refereed journal articles and book chapters, and has several patents.

Learn more

Download the “Complete guide to irrigation management”—>

Soil Hydraulic Properties—8 Ways You Can Unknowingly Compromise Your Data

Avoid costly surprises

Measuring soil hydraulic properties like hydraulic conductivity and soil water retention curves is difficult to do correctly. Measurements are affected by spatial variability, land use, sample prep, and more.

Image of a research using the SATURO infiltrometer in the field
Leo Rivera teaches soil hydraulic properties measurement best practices

Getting the right number is like building a house of cards. If one thing goes wrong—you wind up with measurements that don’t truly represent field conditions. Once your data are skewed in the wrong direction, your predictions are off, and erroneous recommendations or decisions could end up costing you a ton of time and money. 

Get the right numbers—every time

For 10 years, METER research scientist, Leo Rivera, has helped thousands of customers make saturated and unsaturated hydraulic conductivity measurements and retention curves to accurately understand their unique soil hydraulic properties. In this 30-minute webinar, he’ll explain common mistakes to avoid and best practices that will save you time, increase your accuracy, and prevent problems that could reduce the quality of your data. Learn:

  • Sample collection best practices
  • Where to make your measurements
  • How many measurements you need
  • Field mapping tools
  • How to get more out of your instruments
  • How to use the LABROS suite to fully characterize soils (i.e., full retention curves and hydraulic conductivity curves)
  • Best practices for measuring field hydraulic conductivity using SATURO

Watch it now—>

Water potential sensors improve peanuts, cotton, and corn irrigation

Ron Sorensen, a researcher at the National Peanut Research Laboratory in Georgia, is working to help small-scale peanut, corn, and cotton farmers in Georgia optimize irrigation.

Image of a cotton field in southern U.S

Cotton field in southern U.S.

Shallow subsurface drip irrigation is a very economical alternative for these farmers. “If you can put in a pivot, most of those are already in,” says Sorensen. What he’s working with are “small, irregularly shaped fields that go around swamps or in trees or backwoods where they might have 10 to 15 acres that used to be an old farmstead.”

Sorensen helps revitalize these old farmsteads by revamping old wells and plowing in drip tape. In many cases, farmers can have water running the same day they start the project.

Subsurface drip offers significant benefits to these farmers. “What I like about drip is that…I can fill up the soil profile, and I know I can fill it up. With the pivot, I’m putting out water today, and I may be coming back two days later and doing it again,” Sorensen says. “And I’m putting all this water on the leaves, creating the incidence for disease… With cotton, you can actually wash the pollen out of the flowers, and you won’t set a boule. There you’re losing yield. Whereas with drip, you can turn it on, you’re never wetting leaves, you’re getting full pollination… I’m an advocate for drip on small irrigated fields.

Image of a tractor plowing a field

“Irrigating down here [using diesel-powered irrigation pumps] is upwards of $11 an acre any time the farmer turns it on. So if he can wait a day, he’s saved that irrigation.”

“I love pivots on big fields, but we have to manage the water correctly. Farmers are starting to see that. We can save the farmer money, save him time, save him labor. Those…are all side benefits of irrigating correctly,” says Sorensen.

As farmers begin to see the benefits of efficient irrigation, Sorensen’s challenge is to help them know when to water and how much water to put on.

Sorensen is at the end of his third year gathering data with METER water potential sensors. He buries sensors at 10- and 20-inch depths in three separate plots, then irrigates when the average water potential reaches -40, -60, and -80 kPa respectively.

“We started in corn, because we know it has a shallow root system, and when you don’t irrigate corn, you don’t get any yield.” Initially, they allowed the profile to dry out to -120 kPa, but “we discovered it doesn’t work. We weren’t ever irrigating, and we had really bad yields. -120 was much too dry, and we cut back to -40, -60, and -80.”

The researchers used water potential readings with moisture release curves to determine how much water to add to bring the profile to field capacity.

Image of a researcher using a TEROS 21 sensor

METER TEROS 21 water potential sensor

They found that allowing the soil to dry to -60 allowed them to save water without impacting yields in corn. Cotton and peanuts are a different—and more complex—story.  “Both cotton and peanut, if you don’t get any rain or water, they just hunker down, and when you do get a rainstorm, they flourish. When the rainfall comes at a funny time, it changes everything,” Sorensen explains.

Take this year, for example. Until the first of June, Sorensen’s plots got very little rain. Then from June to the end of July, he got 24 – 26 inches. “All the differences between our plots are just gone. Irrigated is the same as the non-irrigated because by the time we started to irrigate, it started raining.”

Despite this setback, Sorensen is confident that the data will ultimately help produce a reliable irrigation tool for farmers. His goal is to add a drip irrigation module to Irrigator Pro, a computer program currently used by pivot irrigators.

He is working with several farmers who already use sensors in conjunction with the Irrigator Pro model. “They can use the computer model as a guess to get close, and then they can use a sensor to really get down to the exact day,” he says. And in Georgia, the exact day can matter quite a bit.

“What it comes down to is: Do I need to turn the pump on or not?” he explains. “Irrigating down here [using diesel-powered irrigation pumps] is upwards of $11 an acre any time the farmer turns it on. So if he can wait a day, and if we have one of these gulf storms come through, and the farmer gets 3/4 inch of rain, he’s saved that irrigation.

“And if you can save two, three, maybe four irrigations a year, we’re conserving water, we’re making the farmer more sustainable, and he can take that money and reinvest it into his farm, or into his children, or wherever he wants to put it. And that makes it so we have food on the table, clothes on our backs, cotton, corn, or peanuts, we’ve got food to eat.”

Learn more

Download the “Complete guide to irrigation management”—>

Discover METER water potential sensors

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

Soil Moisture—6 Common Oversights That Might Be Killing Your Accuracy

Your decisions are only as good as your data

If you rely on soil moisture data to make decisions, understand treatment effects, or make predictions, then you need that data to be accurate and reliable. But even one small oversight, such as poor installation, can compromise accuracy by up to +/-10%. How can you ensure your data represent what’s really happening at your site?

Image of a researcher digging an installation site for a sensor
Chris Chambers discusses how people unknowingly compromise their soil moisture data.

Best practices you need to know

Over the past 10 years, METER soil moisture expert Chris Chambers has pretty much seen it all. In this 30-minute webinar, he’ll discuss 6 common ways people unknowingly compromise their data and important best practices for higher-quality data that won’t cause you future headaches. Learn:

  • Are you choosing the right type of sensor or measurement for your particular needs?
  • Are you sampling in the right place?
  • Why you must understand your soil type
  • How to choose the right number of sensors to deal with variability
  • At what depths you should install sensors 
  • Common installation mistakes and best practices
  • Soil-specific calibration considerations
  • How cable management can make or break a study
  • Factors impacting soil moisture you should always record as metadata
  • Choosing the right data management platform for your unique application

Watch it now—>

How to interpret soil moisture data

Surprises that leave you stumped

Soil moisture data analysis is often straightforward, but it can leave you scratching your head with more questions than answers. There’s no substitute for a little experience when looking at surprising soil moisture behavior. 

Image of orange, yellow, and white flowers in a green house
Join Dr. Colin Campbell April 21st, 9am PDT as he looks at problematic and surprising soil moisture data.

Understand what’s happening at your site

METER soil scientist, Dr. Colin Campbell has spent nearly 20 years looking at problematic and surprising soil moisture data. In this 30-minute webinar, he discusses what to expect in different soil, environmental, and site situations and how to interpret that data effectively. Learn about:

  • Telltale sensor behavior in different soil types (coarse vs. fine, clay vs. sand)
  • Possible causes of smaller than expected changes in water content 
  • Factors that may cause unexpected jumps and drops in the data
  • What happens to dielectric sensors when soil freezes and other odd phenomena
  • Surprising situations and how to interpret them
  • Undiagnosed problems that affect plant-available water or water movement
  • Why sensors in the same field or same profile don’t agree
  • Problems you might see in surface installations

Watch it now

Learn more

Download the “Complete guide to irrigation management”—>

Degradation of soil-applied herbicides under limited irrigation

Soil-applied herbicides are important for controlling weeds in many crops because they offer a broadened control spectrum and chemical diversity. But if soil-applied herbicides persist in the soil too long, there is risk for damage to susceptible rotational crops in succeeding years. Since herbicide degradation in the soil is highly dependent on water, imminent needs to reduce agricultural water use in the future could lead to limited herbicide degradation and a greater risk for carryover.

Image of a sunflower in a sunflower field facing the sun
Some crops don’t have a wide variety of post-emergent herbicide options, so growers are dependent on soil-applied herbicides for weed control.

Recently Daniel Adamson and a research team at the University of Wyoming, under the guidance of Dr. Gustavo Sbatella, investigated the effects of soil-applied herbicides under limited irrigation conditions. They wanted to understand how limited irrigation affects the efficacy and carryover of soil-applied herbicides in Wyoming’s irrigated crop rotations. A two-part field study was undertaken by applying four soil-applied herbicides to dry beans and four soil-applied herbicides to corn. 

Soil microbe activity matters

Describing his research site, Adamson says, “Wyoming is not a huge farming state but there’s a pocket of farm ground near the Powell/Cody area with a unique rotation. The main crop is sugar beets, and they also grow dry, edible beans, sunflowers and malt barley. Some of these crops don’t have a wide variety of post-emergent herbicide options, so growers are dependent on soil-applied herbicides for weed control. However, they need to balance weed control with timely dissipation so sensitive rotational crops won’t be injured.

Adamson says that soil-applied herbicides tend to be fairly long-lived in the soil, which is advantageous for weed control. Importantly, the herbicides dissipate through degradation by soil microbes, and soil microbes are highly influenced by how much water is in soil. When the soil is moist and warm, microbes are more active, and they degrade the herbicides faster. Thus, his team hypothesized that if future climate change effects led to limited availability of surface water for irrigation, these herbicides may not degrade as quickly and possibly injure crops planted successionally.

Assessing herbicide damage

During the first year, the research team applied three irrigation treatments to each crop: 100%, 85%, and 70% of crop evapotranspiration. Both crops and soil moisture were monitored using METER data loggers and soil moisture sensors. Adamson recalls, “The sensors were our means of tracking what was happening in the soil in terms of volumetric water content. Some of the areas were chronically dry, so the sensors enabled us to confirm that the treatments were applied correctly and should theoretically affect how the herbicides were performing. The volumetric soil water content of the three irrigation treatments averaged 24%, 18%, and 16% throughout the growing season, and crop yield decreased as irrigation was reduced.” 

Over the course of the second year, the team collected soil samples at regular intervals following herbicide application. They analyzed the samples for herbicide level and used them to perform a greenhouse bioassay to determine crop response to residual herbicide. Also during the second year, crop response was evaluated in the field when sugar beet, sunflower, and dry bean or corn was planted over the original plots and assessed for herbicide damage.

Crops planted in a field assessed for herbicide damage
The results of the experiment were surprising.

Hurdles and challenges

Adamson said timing was the major difficulty in terms of applying irrigation treatments. He said, “There were no differences in irrigation timing for the various treatments. The way we irrigated was not representative of a typical deficit irrigation strategy because we were tied to a sprinkler with other projects on it. So we irrigated based on when the full water treatment would normally be irrigated. Other treatments had smaller nozzles so the amount of water was physically reduced.”

Adamson said they also weren’t prepared to track how some of the herbicides would behave in the soil. “Some of the herbicides degrade into metabolites that are phytotoxic in the soil, and it was hard to analyze for all molecules that were plant active. So that was challenging.”

Surprising results

Adamson said the results of the experiment were surprising. He says, “It was a good result for growers because we found there were no differences in the fields, statistically or visually, between how the herbicides carried over in the really dry soil versus the normally irrigated soil. So that was surprising, but from a practical standpoint for farmers, it was important information. They now know if they do have to start applying less water, it isn’t something to be overly concerned about.”

More research is needed

Adamson says more work is needed in this area of research. He adds, “There’s a tremendous amount of information within the weed science community about what herbicides do in the soil and things that influence that. But relatively few studies look at changing irrigation rates in a practical sense. A lot of the current studies are done in rain-fed systems where the amount of rain changes (i.e., a normal year vs. a drought year). In irrigated systems, you might reduce the amount of water, but it’s not a drastic reduction like a rain-fed system might experience. There’s not a huge amount of research looking at how different irrigation rates affect herbicide management, so I do think it would be worth exploring in the future.”

Download the researcher’s complete guide to soil moisture—>

Download the researcher’s complete guide to water potential—>


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

 

Data deep dive: When to doubt your measurements

Dr. Colin Campbell discusses why it’s important to “logic-check” your data when the measurements don’t make sense.

Image of the Wasatch Plateau

Wasatch Plateau

In the video below, he looks at weather data collected on the Wasatch Plateau at 10,000 feet (3000 meters) in the middle of the state of Utah.

Watch the video

 

Video transcript

My name is Colin Campbell, I’m a research scientist here at METER group. Today we’re going to spend time doing a data deep dive. We’ll be looking at some data coming from my research site on the Wasatch Plateau at 10,000 feet (3000 meters) in the middle of the state of Utah. 

Right now, I’m interested in looking at the weather up on the plateau. And as you see from these graphs, I’m looking at the wind speeds out in the middle of three different meadows that are a part of our experiment. At 10,000 feet right now, things are not that great. This is a picture I collected today. If you look very closely, there’s an ATMOS 41 all-in-one weather station. It includes a rain gauge. And down here is our ZENTRA ZL6 logger. It’s obviously been snowing and blowing pretty hard because we’ve got rime ice on this post going out several centimeters, probably 30 to 40 cm. This is a stick that tells us how deep the snow is up on top. 

One of the things we run into when we analyze data is the credibility of the data and one day someone was really excited as they talked to me and said, “At my research site, the wind speed is over 30 meters per second.” Now, 30 meters per second is an extremely strong wind speed. If it were really blowing that hard there would be issues. For those of you who like English units, that’s over 60 miles an hour. So when you look at this data, you might get confused and think: Wow, the wind speed is really high up there. And from this picture, you also see the wind speed is very high. 

But the instrument that’s making those measurements is the ATMOS 41. It’s a three-season weather station, so you can’t use it in snow. It’s essentially producing an error here at 30 meters per second. So I’ll have to chop out data like this anemometer data at the summit where the weather station is often encrusted with snow and ice. This is because when snow builds up on the sonic anemometer reflection device, sometimes it simply estimates the wrong wind speed. And that’s what you’re seeing here. 

This is why it’s nice to have ZENTRA cloud. It consistently helps me see if there’s a problem with one of my sensors. In this case, it’s an issue with my wind speed sensors. One of the other things I love about ZENTRA Cloud is an update about what’s going on at my site. Clearly, battery use is important because if the batteries run low, I may need to make a site visit to replace them. However, one of the coolest things about the ZL6 data logger is that if the batteries run out, it’s not a problem because even though it stops sending data over the cellular network, it will keep saving data with the batteries it has left. It can keep going for several months. 

I have a mix of data loggers up here, some old EM60G data loggers which have a different voltage range than these four ZL6 data loggers. Three of these ZL6s are located in tree islands. In all of the tree islands, we’ve collected enough snow so the systems are buried and we’re not getting much solar charging. The one at the summit collects the most snow, and since late December, there’s been a slow decline in battery use. It’s down. This is the actual voltage on the batteries. The battery percentage is around 75%. The data loggers in the two other islands are also losing battery but not as much. The snow is just about to the solar charger. There’s some charging during the day and then a decrease at night. 

So I have the data right at my fingertips to figure out if I need to make a site visit. Are these data important enough to make sure the data loggers call in every day? If so, then I can decide whether to send someone in to change batteries or dig the weather stations out of the snow. 

I also have the option to set up target ranges on this graph to alert me whether the battery voltage is below an acceptable level. If I turn these on, it will send me an email if there’s a problem. So these are a couple of things I love about ZENTRA cloud that help me experiment better. I thought I’d share them with you today. If you have questions you want to get in contact me with me, my email is [email protected]. Happy ZENTRA clouding.

Download the researcher’s complete guide to soil moisture—>

Download the researcher’s complete guide to water potential—>