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Posts from the ‘Irrigation’ Category

Apr 16

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”—>

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Apr 6

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—>


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Mar 17

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

 

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Feb 26

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—>

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Feb 7

Soil sensors help solve putting green water distribution issues

Distribution of soil water in high-sand-content putting greens is a major concern for golf course superintendents. Gravel is commonly used as a component of a sand-based root zone to increase moisture retention, but due to gravity, the contour and slope of a putting green significantly affect moisture retention. Coarse-textured soils often become too dry in higher elevations and too wet in lower elevations. This hampers performance and increases water and labor inputs. 

Image of a golfer putting on a putting green at a golf course
The contour of a putting green affects moisture retention


To fix this problem, Thomas Green, a graduate student at Michigan State University, and a team of researchers are assessing the impact of gravel layer particle size and slope on soil water content in a variable-depth, high-sand content root zone.  He says, “Due to lack of published research and the USGA’s wide-ranged specification for gravel selection based on the root zone material, determining the optimal bridging, filtering, permeability, and uniformity factors capable of increasing root zone soil moisture uniformity is critical.”

Validating previous turfgrass experiments

Green and his team set out to validate previous turf experiments done at MSU which showed that increasing the particle size difference between the gravel and root zone (sand) layers, in combination with a variable-depth root zone (shallower at the slope apex, deeper at the slope base) would improve soil moisture uniformity. 

He says, “We wanted to retain this moisture consistently throughout the whole profile over the entire green. Our experiments decreased the root zone depth in relation to our gravel layer. So at the peak, we reduced the root zone, and in the valleys, we increased the root zone to eliminate wet spots where water accumulates.”

Water potential is the key

Green says the goal was to manipulate the “head” (or water potential) in the peaks and valleys. He explains, “We tested particle size differences between a high-sand, root-zone mix and the gravel layer. Past studies show that the greater the difference between the root zone particle size and the gravel particle size, the more water is retained at the interface. Essentially in the valleys, we increased the depth of the sand layer to create (in physics terms) a large head that forced more water to drain. At the top of the green, we did the opposite and made a thin layer of sand so more water was available. Basically, it was all about manipulating the water potential or tension on the water to retain the right level of moisture.”

The diagrams below illustrate the physics of how this works:

Diagram of sand and gravel layers in a putting green
Figure 1. Diagram of sand and gravel layers in a putting green

In Figure 1, the gravel provides a textural barrier where pores must be saturated for water to move into the gravel.

Close up diagram of tall sand layers in the valley
Figure 2. Closeup of tall sand layer in the valley

Figure 2 is a closeup of the tall layer. Cohesion of water molecules together and adhesion to soil particles ties water together and exerts downward force or tension on water at the top of the profile. The larger the height from the top of the profile to the saturated surface, the more tension on the water (lower water potential).

Close up diagram of short sand layer at the peak
Figure 3. Closeup of short sand layer at the peak

Figure 3 is a closeup of the short sand layer. Shorter height above the saturation zone reduces the tension in the top layer of soil (higher water potential). Thus, the high part of the green with the thinnest sand layer will have less tension and more water than the thick layer in the lower part of the green. To visualize what soil tension is like, think of people hanging on people (Figure 4). The more people there are, the more “pull” will be exerted on the top person.

Diagram of a comparison of soil tension to people hanging on people
Figure 4. Soil tension is like people hanging on people. The more people, the more pull exerted on the top person.

Eliminating edge effects

Green used METER soil moisture and temperature sensors at three different depths along with METER data loggers to validate that the water was in the right place. He inserted the sensors into an enormous box that mimicked a putting green. “I created a 4-ft x 4-ft module to simulate a sloping green. I had to figure out how large it should be to eliminate edge effects (water preferentially moving toward the container edges). The soil moisture sensor helped me determine just how large this box had to be to get accurate measurements.”

Green says the surface measurements were the most important, “I was interested in that top depth because in a golf setting, that’s where you need to control moisture. In a putting green, turfgrass roots aren’t very deep because the grass is so short.”

USGA has adopted the new method

Green says the results turned out as expected. “We expected that if we increased the gravel particle size difference and reduced sand depth, we would see increased water retention in our root zone profile, and that’s exactly what happened. The great thing is the USGA has now somewhat adopted these new recommendations. More and more golf courses are going to this construction method. It’s good for the industry because they’re conserving water.”

In the future, Green says he’d like to explore some research done by F.W. Taylor in the early 1900s. Taylor thought about using a vertical sand or gravel strip contoured on a slope to form a barrier to water moving downhill instead of plastic or polyethylene. This idea is illustrated beautifully in the classic 1950s era film by Dr. Walter Gardner.

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

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

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Jan 20

Founders of Environmental Biophysics: Walter Gardner

Visualizing water flow in soil

This week, in our “Founders” series, we highlight a soil physicist.

Image of soil being held in a researchers hand

Water movement in soil defies intuition

When Dr. Walter Gardner passed away in June (2015), many viewed the film Water Movement in Soils as one of the main accomplishments of a remarkable career. Dr. Gardner and Jack Hsieh made the film in 1959 at Washington State University. The technology they used was impressive—it was years before advanced electronics would make time lapse movies routine—but Dr. Gaylon Campbell finds the ideas behind the experiments even more remarkable.

“Once you’ve seen the film, you can go back to the unsaturated flow theory and see how it would work,” Campbell says, “but the ideas aren’t really obvious. I wish I knew how he thought of doing that.”

At one point in the film, Gardner himself says that the phenomena he illustrates in the film can be seen in nature “if one observes carefully.” It’s possible that some of these careful observations were made in the fields around Washington State University, where farmers often turned the surface layer of soil over using a moldboard plow. This created a layer of surface soil with a layer of straw underneath it—exactly the conditions Gardner describes in the film as leading to erosion, reduced water in the root zone, and damage to the soil in the plow zone.

Though agriculture was the obvious target of the film, for a while it was also a big hit with the US Golf Association. Golf greens are mown short and get a lot of abuse. They need to be watered and fertilized heavily, but how do you keep enough water on the plants between irrigations without leaching nutrients out of the root zone? Water Movement in Soils provides a perfect answer. Gardner consulted for the USGA and used his film to train people who designed and constructed the greens.

Water movement in soil defies intuition

Our intuitions about how water moves in soil are often wrong. More than fifty years after it was made, this classic film still has the power to help people understand what’s really going on.

Watch the video

 

Learn more

Download “The researcher’s complete guide to soil moisture”

Download “The researcher’s complete guide to water potential”

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Jan 8

Best of 2019: Environmental Biophysics

In case you missed them, here are our most popular educational webinars of 2019. Watch any or all of them at your convenience.

Lab vs. In Situ Water Characteristic Curves

Image of a researcher running hand across wheat

Researcher Running A Hand Across Wheat

Lab-produced soil water retention curves can be paired with information from in situ moisture release curves for deeper insight into real-world variability.

Watch it here—>

Hydrology 101: The Science Behind the SATURO Infiltrometer

Image of a fallen tree being supported off the ground by many other trees

A Forest With Fallen Trees

Dr. Gaylon S. Campbell teaches the basics of hydraulic conductivity and the science behind the SATURO automated dual head infiltrometer.

Watch it here—>

Publish More. Work Less. Introducing ZENTRA Cloud

Image of a researcher collecting information from a ZL6 data logger

Researcher is Collecting Data from the ZL6 Data Logger

METER research scientist Dr. Colin Campbell discusses how ZENTRA Cloud data management software simplifies the research process and why researchers can’t afford to live without it.

Watch it here—>

Soil Moisture 101: Need-to-Know Basics

Soil moisture is more than just knowing the amount of water in soil. Learn basic principles you need to know before deciding how to measure it.

Watch it here—>

Soil Moisture 201: Moisture Release Curves—Revealed

Image of rolling hills of farm land

Rolling Hills of Farm Land

A soil moisture release curve is a powerful tool used to predict plant water uptake, deep drainage, runoff, and more.

Watch it here—>

Soil Moisture 301: Hydraulic Conductivity—Why You Need It. How to Measure it.

Image of a researcher measuring with the HYPROP balance

Researcher measuring with the HYPROP balance

If you want to predict how water will move within your soil system, you need to understand hydraulic conductivity because it governs water flow.

Watch it here—>

Soil Moisture 102: Water Content Methods—Demystified

Image of a researcher holding a TEROS 12 in front of a field

Modern Sensing is more than just a Sensor

Dr. Colin Campbell compares measurement theory, the pros and cons of each method, and why modern sensing is about more than just the sensor.

Watch it here—>

Soil Moisture 202: Choosing the Right Water Potential Sensor

Image of a dirt plowed field being used for electrical conductivity

Electrical Conductivity

METER research scientist Leo Rivera discusses how to choose the right field water potential sensor for your application.

Watch it here—>

Water Management: Plant-Water Relations and Atmospheric Demand

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.

Watch it here—>

How to Improve Irrigation Scheduling Using Soil Moisture

Image of a crop field

Capacitance

Dr. Gaylon Campbell covers the different methods irrigators can use to schedule irrigation and the pros and cons of each.

Watch it here—>

Next up:

Soil Moisture 302: Hydraulic Conductivity—Which Instrument is Right for You?

Image of plants growing out of the sand

Leo Rivera, research scientist at METER teaches which situations require saturated or unsaturated hydraulic conductivity and the pros and cons of common methods.

Watch it here—>

Image of grapes growing off of a tree

Predictable Yields using Remote and Field Monitoring

New data sources offer tools for growers to optimize production in the field. But the task of implementing them is often difficult. Learn how data from soil and space can work together to make the job of irrigation scheduling easier.

Watch it here—>

Learn more

Download “The researcher’s complete guide to soil moisture”

Download “The researcher’s complete guide to water potential”

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Dec 19

Chalk talk: How to calculate absolute humidity

In this video, Dr. Colin Campbell discusses how to use air temperature and relative humidity to calculate absolute humidity, a value you can use to compare different sites, calculate fluxes, or calculate how much water is actually in the air.

Depicting vapor and humidity coming off of the ground

Vapor density tells you how much water is actually in the air.

Watch the video to find out how to calculate absolute humidity and how to avoid a common error in the calculation.

 

Video transcript: Absolute humidity

Hello, I’m Dr. Colin Campbell, a senior research scientist here at METER Group, and also an adjunct faculty at Washington State University where I teach a class in environmental physics. Today we’re going to talk about absolute humidity. In a previous lecture, we discussed how relative humidity was a challenging variable to use in environmental studies. So, I’m going to show the right variable to use as we talk about humidity. 

Absolute humidity can be talked about in terms of vapor pressure, which is what I’m used to, or in terms of vapor density. Whatever we use, we usually start by calculating this from a relative humidity value and a knowledge of air temperature. In my relative humidity lecture, I said that Hr (or the relative humidity) was equal to the vapor pressure divided by the saturation vapor pressure. And in most field studies, we’d typically get a report of the air temperature and the relative humidity. So how do we take those two values and turn them into something we could use to compare different sites, calculate fluxes, or calculate how much water is actually in the air? We’ll need to work through some equations to get there. I’m going to take you through it and give you an example so that you know how to do that calculation.

Vapor pressure

First, we’ll talk about absolute humidity in terms of vapor pressure or Ea. If we rearrange this equation here (very simple math), the relative humidity times the saturation vapor pressure will give us our vapor pressure. And that vapor pressure is now an absolute humidity. How would we do this? Well, let’s first talk about an example in terms of vapor pressure. 

Let’s say a weather report said the air temperature was 25 degrees Celsius and the relative humidity was 28% or 0.28. First, we’d use Teten’s formula which I talked about in the previous lecture. We’d say the saturation vapor pressure at the air temperature is equal 0.611 kPa times the exponential of a constant times the air temperature divided by another constant plus the air temperature. So in our case, the air temperature is 25 degrees, which we’ll add here. Remember saturation vapor pressure is a function of 25. So 0.611 kPa times the exponential of 17.502. In the previous lecture, I showed you that b value times 25 degrees divided by the c value 240.97. And then we add to that 25 degrees (this is for liquid water, of course, it’s 25 degrees Celsius because nothing’s frozen). If you were working over ice, these constants would be different. So we put this into our calculator or into a spreadsheet, and we easily calculate the saturation vapor pressure at 25 degrees C is 3.17 kPa. But we’re not done yet. 

We have to go back to this equation that says the vapor pressure is equal to the relative humidity times the saturation vapor pressure. When we plug our data in, the relative humidity 0.28 times the saturation vapor pressure that we calculated right here, we get a vapor pressure of 0.89 kPa. And if we were calculating fluxes (we’ll talk about that in another lecture), this is typically the value we would use. But there are other things we can do with the absolute humidity values that might be useful.

Vapor density

So let’s talk about vapor density. If we had a certain volume of air, and we wanted to know how much water was in that volume of air (for example, if we were going to try to condense it out) we’d more typically use this vapor density value. But how do we get from a vapor pressure that we can easily calculate from a weather report to a vapor density that would allow me to know how much water was actually in the air? 

This is our equation that says the vapor pressure times the molecular weight of water divided by the universal gas constant times the kelvin temperature of the air will give us the vapor density. So I’ll take you through an example here, just continue on the one we’ve already done, just so you can see how to calculate it and to avoid a pretty common misstep. 

How to avoid a common error

Again, molecular weight of water is 18.02 g/mol. The universal gas constant R is 8.31 J/mol K. And here’s the kelvin temperature of the air. I’ve scribbled this in a little bit. That’s how I note the difference between something like this, which would be air temperature in Celsius and this air temperature in kelvin. So let’s go ahead and plug all these into our equation. There’s our vapor pressure. We’re just dragging that over here. There’s our molecular weight of water. There’s our universal gas constant. And here is the kelvin temperature of the air. So as we look at this, you immediately say, how do I cancel these units? The kilopascals and the joules are certainly not going to cancel as they are. But there are conversions we can use. A Pascal is equal to an Nm-2, and a joule is equal to an Nm.

So if we change this joule to an Nm, we change this Pascal to Nm-2, we have to pay attention here as we’re doing it that the kilo right there, don’t forget that because that can mess you up. So I’m circling that to make sure that we’ve got this. Now we cancel our N’s, and combining together we get a m-3. That’s what we’re hoping for on the bottom. The grams come out on top, they don’t cancel, but everything else does. The mols cancel mols, the kelvin cancels the kelvin there, and the N cancels the N. 

And we come out with just what we were looking for, save one thing, which is a kg/m-3. And this calculation gives us point 0065. But since we actually want to do this in grams, because that’s more typical of what you find in how much water there is in air. It’s not a kg of water, but more in terms of g/m-3 of water, we get 6.5 g/m-3. 

Check your calculation

One way you can check this calculation (just as a rule of thumb), is if we had a pressure of the air of 100 kPa and a temperature of 20 degrees Celsius, the multiplier to get from your vapor pressure to your vapor density is about 7.4 or so. We’ll just say around 7.0. And we’ll do a quick mental calculation, 0.89 times 7, that should give us something around 6.0. So our answer should be around 6.0, and it is. It’s certainly no orders of magnitude off. So we’ve got at least close to the right answer, by doing a mental check, and we can say this conversion works. 

If you want to learn more about instrumentation to measure all kinds of atmospheric parameters, please come to our website, www.metergroup.com or you can email me to chat more about this: colin.campbell@metergroup. com. 

Download “The researcher’s complete guide to LAI”

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—>

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Nov 18

Chalk Talk: Why is Humidity Relative?

Dr. Colin Campbell, a senior research scientist at METER Group, as well as adjunct faculty at Washington State University teaches about relative humidity.

Image of a forest with clouds and fog everywhere
Comparing RH at different research sites can be a challenge

Watch the video to find out why we use the term relative humidity and why comparing RH at different research sites can be a challenge.

 

Video transcript

Why is humidity relative?

Hi, I’m Dr. Colin Campbell. I’m a senior research scientist here at METER Group, as well as adjunct faculty up at Washington State University. And I teach a class in environmental biophysics. And today, we’re going to be talking about relative humidity. Have you ever looked at a weather report and wondered, what do they mean by the term relative? Why aren’t we talking about absolute things? And so today I’m going to talk about what is relative humidity? Well, relative humidity we’re going to define here as just hr. And hr is equal to the partial pressure of water vapor in air divided by the saturation vapor pressure or the maximum possible partial pressure of water in air as a function of temperature. So this is relative because anytime we have a partial pressure of water vapor, we’re always dividing it by the maximum possible water vapor that could be in the air at any point.

Comparing RH at different sites is a challenge

So, why would relative humidity be such a challenge for us as scientists to use in comparing different sites? I wanted to talk about that so we can focus in here on this saturation vapor pressure. Over here we have Tetens equation. This says that the saturation vapor pressure, which is a function of air temperature is equal to 0.611 kPa times the exponential of a constant “b” times the air temperature divided by another constant “c” plus the air temperature. So at any point, depending on the air temperature, we can calculate the saturation vapor pressure, and then we can put it back into this equation and get our relative humidity. There are two situations we might think about for calculating our saturation vapor pressure. The most typical is this one: where that constant “b” is 17.502 degrees C. And the constant “c” is 240.97 degrees C (the units on this are degrees C, so these will cancel). If we’re over ice, those constants will be different: “b” would be 21.87 degrees C and “c” would be 265.5 degrees C. 

So as I mentioned, relative humidity is a challenging variable to use in research because while vapor pressure (ea) (the vapor pressure of the air) is somewhat conservative across a day, the saturation vapor pressure (with respect to air temperature), this changes slowly with temperature across the day. So if we graphed temperature on one axis and the relative humidity on the other axis, we might during a typical day have a temperature range that looks somewhat like this. And even if the actual vapor pressure “ea” wasn’t changing, we’d see a relative humidity trend that looked like this: only changing because of air temperature. And because of that, if we wondered how do I compare the water in the air at one research site, for example, with the water in the air at another research site? We might be inclined to average them. But because of this trend, the average of the relative humidity at any site tends to be around 0.60 to 0.65 and therefore will be totally irrelevant in the literature. 

So we need to speak in absolutes, and in my next lecture, I’m going to go into what we can do to calculate that absolute relative humidity. If you want to know more about making measurements in the atmosphere, go to metergroup.com, look at our atmospheric instrumentation, and you can learn more from there.

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Oct 16

Data deep dive: why am I seeing diurnal changes in soil moisture?

In the video below, METER soil scientist Dr. Colin Campbell discusses an often-misdiagnosed water content signal that looks like typical diurnal temperature cycling but is actually due to a phenomenon called hydraulic redistribution. He shows how easily these patterns can be seen in ZENTRA Cloud data management software.

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Learn more about measuring soil moisture. Download “The researcher’s complete guide to soil moisture“.

To understand how soil moisture and soil water potential work together, download “The researcher’s complete guide to water potential.”

Video transcript

Hello, my name is Colin Campbell. I’m a research scientist here at METER Group. And today we’re going to be digging into some water content data that I collected over the last summer. This is a field that’s planted in spring wheat, it’s about 700 meters across. And we’ve set up six measurement sites. At each one of these sites, we’re making several measurements, but the ones we’re going to talk about today are just water content. And while we’ve installed water content sensors at 15, 45, and 65 centimeters, we’re just going to focus on the 65-centimeter water content sensors. These sensors are the METER TEROS 12 soil moisture sensors, so they also measure electrical conductivity and temperature, and we’re going to look at temperature as well because that figures into this discussion. 

So this field was planted in April of 2019. And not a lot interesting goes on at the 65-centimeter depth through April, May, and June. But as we get into July, the wheat is reaching maturity, and they essentially are going to cut off the irrigation water here on July 22. So up to July 22, there’s really not a lot of movement in the water content. One of the sites decreases a little bit, but each line is flat. What I noticed as I was looking at this particular graph is after this long period of very flat data, after June 22 when the irrigation was cut off, we start to see some movement in the water content at this depth Not only is there movement down, but there’s a daily movement of the actual water content signals, all but this top light green line. And it made me wonder, what’s going on? 

Image of a field of wheat

Diurnal water content fluctuations are not always due to temperature.

Initially, whenever you see a diurnal movement, you suspect that it’s caused by temperature. It’s been said that every sensor is probably a temperature sensor first, and a sensor of whatever we’re really interested in second. In this case, we can look to see what the temperature is doing at that depth. Here’s soil temperature, at 65 centimeters, and even though there’s just a little bobble in the line, the line is almost completely flat. We see the seasonal trends in temperature, but really no diurnal temperature cycling. And this scale is also fairly small. So back to our 65-centimeter water content. If it’s not temperature that’s affecting these lines, then what is it? 

I’ve seen this before in an experiment that I did years ago in a non-irrigated wheat field. We were measuring down at  150 centimeters, and when the water had been used up in the upper levels of the soil profile, the roots of the wheat plant just simply went down to 150 centimeters and started taking water up. So this is what I assume is also happening here. The wheat has extended its roots down to 65 centimeters, since its irrigated wheat. That’s not too deep, but wheat doesn’t necessarily need to get its roots down super deep. And as the wheat accesses that water, we’re seeing these daily drops in water. But then we’re seeing just a slight increase in water. Here on July 28, we’re seeing that water go up slightly. And so why is this happening? We might understand how the water is being taken out of the soil, but why do we see a slight increase in the water content (just a few tenths of a percent)? 

What I think is happening, in this case, is that it’s not temperature, but actually, roots are growing down into this area, and they’re probably growing around the sensor. As we change from day to night, we see a release in the elasticity of the water in the xylem, and maybe just a little bit more water down in the roots as they’re the transpiration pull of the day is lessened and stops overnight. The stomates are closed, and we see just a little bit of water coming back into the roots and possibly into the soil. 

Now there was a big discussion many years ago about whether this was something called hydraulic lift where trees could take up water from deep in the soil profile and essentially give it back to plants near the surface. And although it was a great debate, it was never proven that this actually happened: water being spread from deeper locations to more shallow locations by roots. But this is probably hydraulic redistribution where we just have roots filling with water, and when they are filled, we see a little bit in the water content sensor.

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