Skip to content

Posts from the ‘Horticulture’ Category

Chalk talk: How to measure leaf transpiration

In his latest chalk talk video, Dr. Colin Campbell discusses why you can’t measure leaf transpiration with only a leaf porometer.

Image of the SC-1 Leaf Porometer which measures stomatal conductance
The SC-1 Leaf Porometer measures stomatal conducance

He teaches the correct way to estimate the transpiration from a single leaf and how a leaf porometer can be used to obtain one of the needed variables.

Watch the video

 

Video transcript

Hello, my name is Colin Campbell. I’m a senior research scientist here at METER Group. And today we’ll talk about how to estimate the transpiration from a single leaf. Occasionally we get this question: Can I estimate the transpiration from a leaf by measuring its stomatal conductance? Unfortunately, you can’t. And I want to show you why that’s true and what you’ll need to do to estimate the total conductance, and therefore, the evaporation of a leaf.

Image of a researcher Measuring stomatal conductance With an SC-1 Leaf Porometer
Researcher Measuring Stomatal
Conductance With an sc-1 Leaf Porometer

The calculation of transpiration (E) from a leaf is given by Equation 1 

Image of the equation used for the calculation of transpiration from a leaf
Equation 1

where gv is the total conductance of vapor from inside the leaf into the air, Cvs is the concentration of vapor inside the leaf and Cva is the concentration of vapor in the air.

Read more—>

Learn more about canopy measurements

Download the researcher’s complete guide to leaf area index—>

Questions?

Our scientists have decades of experience helping researchers measure the soil-plant-atmosphere continuum. Contact us for answers to questions about your unique application.

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

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

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.

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

Download “The researcher’s complete guide to water potential

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.

Watch the video

 

 

 

Learn more

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.

Chalk Talk: Intensive vs. Extensive Variables

Learn the difference between intensive and extensive variables and how they relate to soil water potential vs. soil water content in our new Chalk Talk whiteboard series. In this video series, Dr. Colin S. Campbell teaches basic principles of environmental biophysics and how they relate to measuring different parameters of the soil-plant-atmosphere continuum.

Watch the video

 

Learn more

To learn more about measuring water potential vs. water content read: Why soil moisture sensors can’t tell you everything.

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

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

Video transcript

Hello, my name is Colin Campbell. I’m a senior research scientist here at METER group. And I teach a class on environmental biophysics. Today I wanted to talk about something we teach in the class: the difference between extensive and intensive variables. I’d like to do this with the goal of relating it to the difference between volumetric water content and water potential. 

Here, I have a picture of a ship moving through the ice and some metal that’s been heated in a furnace. I think we would agree the ship has the highest amount of heat in it compared to this very small piece of metal. And if we placed that piece of metal onto the outside of the ship, despite the fact that there is more heat in the ship, we know the heat would not move from the high amount of heat (ship) to the low amount of heat (metal). It would actually move from the highest temperature to the lowest temperature. Why is that?

The reason is that heat moves because of temperature and not because of heat content or the amount of heat in something. Heat content defines an amount or an extent. And we generally term something that defines an extent or an amount as an extensive variable.An extensive variable depends broadly on the size of something or how much of something there is. 

This differs for temperature. Temperature doesn’t depend on size. The temperature could be the same in a very small room or a very large room, but the amount of heat or heat content in those rooms would be quite different. When we describe temperature, we talk about intensity, which is why we call these types of variables intensive variables. This is because they don’t depend on size or amount. 

Let’s talk about another example. Here’s your heating bill. Maybe it’s natural gas. What you’re paying for is the amount of heat you put into the house. But the question is, are you comfortable in the house? And from this bill, we can’t tell. Maybe you put in 200 heat units, whatever those might be. We can’t tell if that’s comfortable because we don’t know the size of the house or the type of insulation. All those things would influence whether you were comfortable. 

Alternatively, if the temperature is 71 F that’s quite comfortable. That’s equivalent to about 22 degrees Celsius. So the intensive variable, temperature, is different than the extensive variable, heat content, that tells us how much heat we put in. And that’s important because at the end of the day, that leads to cost. 

On this side, we don’t know how much we paid to keep it at 22 C because heat content doesn’t tell us anything about that. But the intensive variable temperature does tell us something about comfort. So both of these variables are critical to really understanding something about our comfort in the house. 

Now let’s talk about the natural environment. Specifically, we’re going to talk about soils. We’ll start with the extensive variable. When we talk about water in soil, the extensive variable is, of course, water content. Water content defines the amount of water. Why would we care about water content? Well, for irrigation or a water balance.

The intensive variable is called water potential. What does water potential tell us? It tells us if soil water is available and also predicts water movement. If this soil had a water content of 25% VWC and another soil was at 20% VWC, would the water move from the higher water content to the lower water content? Well, that would be like our example of the ship and the heated piece of metal. We don’t know if it would move. It may move. And if the soil on either side was exactly the same, we might presume that it would move from the higher water content to the lower water content, but we actually don’t know. Because the water content is an extensive variable, it only tells us how much there is. It won’t tell us if it will move. 

Now, if we knew that this soil water potential was -20 kPa and this soil water potential over here was -15 kPa, we would know something about where the water would move, and it would do something different than we might think. It would move from the higher water potential to the lower water potential against the gradient in water content, which is pretty interesting but nonetheless true. Water always moves from the highest water potential to the lowest water potential.

This helps us understand these variables in terms of plant comfort. We talked about the temperature being related to human comfort. We know at what temperatures we are most comfortable. With plants, we know exactly the same thing, and we always turn to the intensive variable, water potential, to define plant comfort.

For example, if we have an absolute scale like water potential for a particular plant, let’s say -15 kPa is the upper level for plant comfort, and -100 kPa is the lower level of comfort, we could keep our water potential in this range. And the plant would be happy all the time. Just like if we kept our temperature between 21 and 23 Celsius, that would be comfortable for humans. But of course, we humans are different. Some people think that temperature is warm, and some think it’s cold. And it’s the same for plants. So this isn’t a hard and fast rule. But we can’t say the same thing with water content. There’s no scale where we can say at 15% water content up to 25% water content you’ll have a happy plant That’s not true.If we know something about the soil, we can infer it. But soil is unique. And we’d have to derive this relationship between the water content and the water potential to know that. 

So why would we ever think about using water content when we measure water in the soil? One reason is it’s the most familiar to people. And it’s the simplest to understand. It’s easy to understand an amount. But more importantly, when we talk about things like how much we’re going to irrigate, we might need to put on 10 millimeters of water to make the plants happy. And we’d need to measure that. Also if we want to know the fate of the water in the system, how much precipitation and irrigation we put on versus how much is moving down through the soil into the groundwater, that also relates to an amount.  

But when we want to understand more about plant happiness or how water moves, it’s going to be this intensive variable, water potential that makes the biggest difference. And so with that, I’ll close. I’d love for you to go check out our website www.metergroup.com to learn a little bit more about these measurements in our knowledge base. And you’re also welcome to email me about this at [email protected] group.com.

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—>

Soil moisture: ECH20 vs. TEROS, which is better?

See how the new TEROS soil moisture sensor line compares with METER’s trusted ECH20 sensor line.

Image of TEROS 12 moisture sensor in front of wheat
TEROS 12 soil moisture sensor

Volumetric water content—defined

To evaluate the performance of any water content sensor, you need to first understand its technology. In order to do this, it’s necessary to understand how volumetric water content (VWC) is measured. Volumetric water content is the volume of water divided by the volume of soil (Equation 1) which gives the percentage of water in a soil sample.

Equation to measure volumetric water content

So, for instance, if a volume of soil (Figure 1) was made up the following constituents: 50% soil minerals, 35% water, and 15% air, that soil would have a 35% volumetric water content.

Diagram depicting soil constituents

The percentage of water by mass (wm) can be measured directly using the gravimetric method, which involves subtracting the oven-dry soil mass (md) from the mass of moist soil (giving the mass of water, mw) and dividing by md (Equation 2).

Gravimetric method to measure the percentage of water by mass

The resulting gravimetric water content can be converted to volumetric by multiplying by the dry bulk density of the soil (b) (Equation 3).

Gravimetric water content converted to volumetric by multiplying by the dry bulk density of the soil

Why capacitance technology works

Volumetric water content can also be measured indirectly: meaning a parameter related to VWC is measured, and a calibration is used to convert that amount to VWC. All METER soil moisture sensors use an indirect method called capacitance technology. In simple terms, capacitance technology uses two metal electrodes (probes or needles) to measure the charge-storing capacity (or apparent dielectric permittivity) of whatever is between them.

Diagram depicting how capacitance sensors use two probes to form an electromagnetic field

Table 1 illustrates that every common soil constituent has a different charge-storing capacity. In a soil, the volume of most of these constituents will stay constant over time, but the volume of air and water will fluctuate.

Charge storing capacity of common soil constituents

Since air stores almost no charge and water stores a large charge, it is possible to measure the change in the charge-storing ability of a soil and relate it to the amount of water (or VWC) in that soil. (For a more detailed explanation of capacitance technology watch our Soil Moisture: methods/applications webinar.

Capacitance today is highly accurate

When capacitance technology was first used to measure soil moisture in the 1970s, scientists soon realized that how quickly the electromagnetic field was charged and discharged was critical to success. Low frequencies led to large soil salinity effects on the readings. Over time, this new understanding, combined with advances in the speed of electronics, enabled the original capacitance approach to be adjusted for success. Modern capacitance sensors, such as METER sensors, use high frequencies (70 MHz) to minimize effects of soil salinity on readings.

The circuitry in capacitance sensors can be designed to resolve extremely small changes in volumetric water content, so much so, that NASA used METER’s capacitance technology to measure water content on Mars. Capacitance soil moisture sensors are easy to install and tend to have low power requirements. They may last for years in the field powered by a small battery pack in a data logger.   

TEROS and ECH20: same trusted technology

Both TEROS and ECH20 soil moisture sensors use the same trusted, high-frequency (70 MHz) capacitance technology that is published in thousands of peer-reviewed papers. Figure 3 shows the calibration data for the ECH20 5TE and TEROS 12.

Read the full article….

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

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

Just released: ATMOS 41 comparison testing data

Climate parameters such as precipitation, air temperature, and wind speed can change considerably across short distances in the natural environment. However, most weather observations either sacrifice spatial resolution for scientific accuracy or research-grade accuracy for spatial resolution.

Researcher setting up an ATMOS 41 all-in-one weather station

ATMOS 41 all-in-one weather station

The ATMOS 41 represents an optimization of both. It was carefully engineered to maximize accuracy at a price point that allows for spatially distributed observations. Additionally, because many researchers need to avoid frequent maintenance and long setup times, the ATMOS 41 weather station was designed to reduce complexity and withstand long-term deployment in harsh environments. To eliminate breakage, it contains no moving parts, and it only requires recalibration every two years. Since all 14 measurements are combined in a single unit, it can be deployed quickly and with almost no effort. Its only requirement is to be mounted and leveled on top of a pole with an unobstructed view of the sky.

Comparison testing and sensor-to-sensor variability data

METER released the ATMOS 41 in January 2017 after extensive development and testing with partnerships across the world, in Africa, Europe, and the US. We performed comparison testing with high-quality, research-grade non-METER sensors and conducted time-series testing for sensor-to-sensor variability.

See weather sensor performance data for the ATMOS 41 weather station.

Explore which weather station is right for you.

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

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

Data collection: 8 best practices to avoid costly surprises

Every researcher’s goal is to obtain usable field data for the entire duration of a study. A good data set is one a scientist can use to draw conclusions or learn something about the behavior of environmental factors in a particular application. However, as many researchers have painfully discovered, getting good data is not as simple as installing sensors, leaving them in the field, and returning to find an accurate record. Those who don’t plan ahead, check the data often, and troubleshoot regularly often come back to find unpleasant surprises such as unplugged data logger cables, soil moisture sensor cables damaged by rodents, or worse: that they don’t have enough data to interpret their results. Fortunately, most data collection mishaps are avoidable with quality equipment, some careful forethought, and a small amount of preparation.

ZL6 Data Logger in a wheat field

Before selecting a site, scientists should clearly define their goals for gathering data.

Make no mistake, it will cost you

Below are some common mistakes people make when designing a study that cost them time and money and may prevent their data from being usable.

  • Site characterization: Not enough is known about the site, its variability, or other influential environmental factors that guide data interpretation
  • Sensor location: Sensors are installed in a location that doesn’t address the goals of the study (i.e., in soils, both the geographic location of the sensors and the location in the soil profile must be applicable to the research question)
  • Sensor installation: Sensors are not installed correctly, causing inaccurate readings
  • Data collection: Sensors and logger are not protected, and data are not checked regularly to maintain a continuous and accurate data record
  • Data dissemination: Data cannot be understood or replicated by other scientists

When designing a study, use the following best practices to simplify data collection and avoid oversights that keep data from being usable and ultimately, publishable.

Read more

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

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

Download the “Researcher’s complete guide to SDI-12″—>

Hydrology 301: What a Hydraulic Conductivity Curve Tells You & More

Hydraulic conductivity is the ability of a porous medium (soil for instance) to transmit water in saturated or nearly saturated conditions. It’s dependent on several factors: size distribution, roughness, tortuosity, shape, and degree of interconnection of water-conducting pores. A hydraulic conductivity curve tells you, at a given water potential, the ability of the soil to conduct water.

Researcher measuring with the HYPROP balance

One factor that affects hydraulic conductivity is how strong the structure is in the soil you’re measuring.

For example, as the soil dries, what is the ability of water to go from the top of a sample [or soil layer in the field] to the bottom. These curves are used in modeling to illustrate or predict what will happen to water moving in a soil system during fluctuating moisture conditions. Researchers can combine hydraulic conductivity data from two laboratory instruments, the KSAT and the HYPROP, to produce a full hydraulic conductivity curve (Figure 1).

Hydraulic conductivity curve

Figure 1. Example of hydraulic conductivity curves for three different soil types. The curves go from field saturation on the right to unsaturated hydraulic conductivity on the left.  They illustrate the difference between a well-structured clayey soil to a poorly structured clayey soil and the importance of structure to hydraulic conductivity especially at, or near, saturation.

In Hydrology 301, Leo Rivera, Research Scientist at METER, discusses hydraulic conductivity and the advantages and disadvantages of methods used to measure it.

Watch the webinar below.

 

Get more info on applied environmental research in our

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

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