In our latest podcast episode, Kevin Hyde, manager of the Montana Mesonet, discusses his views on predicting and mitigating the effects of flood and drought.
Montana’s large geographical area makes mesonet equipment maintenance a challenge.
He also shares how to build a robust weather network with high-quality data on a small budget, why setups should include other measurements such as soil moisture and NDVI, and the genius way he handles maintenance over such a large geographical area.
The views and opinions expressed in the podcast and on this posting are those of the individual speakers or authors and do not necessarily reflect or represent the views and opinions held by METER.
In his latest chalk talk, Dr. Colin Campbell, environmental scientist at METER Group, teaches how to model vertical variation in temperature and how to estimate sensible heat flux.
Video transcript
Hello, everyone. My name is Dr. Colin Campbell, and I’m a senior research scientist here at METER Group. For today’s chalk talk, we’ll be talking about modeling vertical variation in temperature. In Figure 1, I’ve put together a graph that shows the maximum and minimum temperature with height and depth in the soil at some snapshot in time at a particular place.
Figure 1. Maximum and minimum temperature with height and depth at a snapshot in time, in a particular place
It’s interesting to note that the change in temperature with depth in the soil is much faster than the change in temperature with height, whether we’re talking about a maximum or minimum. And the reason is that even though air is a good insulator, it also mixes really well. And that mixing is caused by eddies. And there’s a little more to that story. It depends specifically on surface heating by the sun through radiation and the cover type, whether it’s plants, rocks, boulders, straight soil, snow, or wind.
Equation 1
If we were going to model that, we would start by writing an equation (Equation 1) where a temperature at sun height, Z, above the surface (see variables noted in Figure 1), is equal to an aerodynamic surface temperature, T0, minus the sensible heat flux, divided by 0.4 times rho, CP, which is the volume specific heat of the air, times a variable called u*, which is the friction velocity. We multiply all that by the logarithm of z, the height above the surface minus d, which is the zero plane displacement, divided by z h, which is a roughness parameter. You might notice up here in the list of variables, that the zero plane displacement is 0.6 times H. H is the canopy height in meters. The rough roughness parameter can be estimated as 0.02 times the canopy height or times H. Now we have an equation that will help us model temperature with height.
However, often we don’t know things like H, our sensible heat flux, and u*, our friction velocity. One of the things that we notice about this equation is that it’s set up somewhat like a linear equation. As you know, an example of a linear equation is something like Equation 2.
Equation 2
Figure 1 isn’t written quite that way, but if we look closely at the example below (Equation 3), this value could be our b, and this value our m, and this value could be our x. And if we do that, we actually can get some use out of graphing temperature with height.
Equation 3
So we went out one day and measured this with a METER Group set of environmental sensors set up at certain heights above the surface. Here we placed sensors at 0.2 m, 0.4 m, 0.8 m, and 1.6 m above the ground.
Table 1
To visualize this, in Figure 2 we graphed height on the y axis and temperature on the x axis, similar to the graph in Figure 1.
Figure 2. Graph showing the relationship between height and temperature
We know from Equation 1 that the axes for temperature and height should be switched because temperature is the dependent variable, and height is the independent variable. So if we switch axes it would look like the graph in Figure 3.
Figure 3. Graph showing the relationship between height and temperature where temperature is the dependent variable and height is the independent variable.
Figure 3 is graphed with the independent variable on the x axis and height on the y axis. If we fit this curve with today’s calculators, it would be fairly easy to get a curve that would fit that. But since it’s a linear equation, we can take the temperature data from Table 1 and the In ((Z-d)/ZH) data from Table 1 and graph them together.
Figure 4. Relationship between temperature and In Z-d/zh
Figure 4 is a graph that shows what happens when we do that. Notice that, just like we suggested, it creates a linear equation (Equation 4).
Equation 4
We learned in Figure 1 the B value was equal to t0 (our aerodynamic surface temperature). Since we know our surface temperature is 34.5 degrees, we can estimate what the temperature is down here at the surface, even though we only measured down 0.2 m.
We also know from Equation 4 that our M value is equal to -2.01. And if we look at Equation 1, our slope value is below.
Equation 5 (the slope value from Equation 1)
So we can write
Equation 6
How to estimate sensible heat flux
Now, if we were interested in the sensible heat flux, which we often are, we can simply rearrange this equation to be
Equation 7
And in Figure 1, I forgot to give you this value, but for an air temperature of 20 degrees celsius,
Equation 8
And then finally, a typical unit for friction velocity, which should be measured in the field over the specific canopy you are in, is about 0.2 meters per second.
Equation 9
So if we did this calculation, we would learned that there’s about 193 watts per meter squared of sensible heat flux coming off that surface.
Equation 10
So if we can measure temperature at a few heights, we can estimate what the heat flux is coming off the surface assuming we know something about our canopy. Learn more about measuring and modeling environmental parameters at metergroup.com/environment. If you have any questions feel free to email Dr. Campbell at [email protected].
In our latest podcast, Dr. Neil Hansen, BYU professor of environmental science, discusses water conservation, the latest research on getting more crop per drop, exciting applications of remote sensing, and the challenges we face trying to meet changing water demands in a growing population.
The views and opinions expressed in the podcast and on this posting are those of the individual speakers or authors and do not necessarily reflect or represent the views and opinions held by METER.
Advances in sensor technology and software now make it easy to understand what’s happening in your soil, but don’t get stuck thinking that only measuring soil water content will tell you what you need to know.
Water content is only one side of a critical two-sided coin. To understand when to water, plant-water stress, or how to characterize drought, you also need to measure water potential.
Better data. Better answers.
Soil water potential is a crucial measurement for optimizing yield and stewarding the environment because it’s a direct indicator of the availability of water for biological processes. If you’re not measuring it, you’re likely getting the wrong answer to your soil moisture questions. Water potential can also help you predict if soil water will move, and where it’s going to go. Join METER soil physicist, Dr. Doug Cobos, as he teaches the basics of this critical measurement. Learn:
What is water potential?
Why water potential isn’t as confusing as it’s made out to be
Common misconceptions about soil water content and water potential
Dr. Cobos is a Research Scientist and the Director of Research and Development at METER. He also holds an adjunct appointment in the Department of Crop and Soil Sciences at Washington State University where he co-teaches Environmental Biophysics. Doug’s Masters Degree from Texas A&M and Ph.D. from the University of Minnesota focused on field-scale fluxes of CO2 and mercury, respectively. Doug was hired at METER to be the Lead Engineer in charge of designing the Thermal and Electrical Conductivity Probe (TECP) that flew to Mars aboard NASA’s 2008 Phoenix Scout Lander. His current research is centered on instrumentation development for soil and plant sciences.
What was the life of a scientist like before modern measurement techniques? In our latest podcast, Campbell Scientific’s Ed Swiatek and METER’s Dr. Gaylon Campbell discuss their association with three pioneers of environmental measurement.
Learn what it was like to practice science on the cutting edge. Discover the creative lengths they went to and what crazy things they cobbled together to get the measurements they needed.
In our latest We Measure the World podcast, we interview Oregon State University researcher Dalyn McCauley
about her experience developing a site-specific decision support tool for on-farm management of crop damaging weather events—and techniques she used to help the grower implement changes for quality and yield improvements.
When you irrigate in a greenhouse or growth chamber, you need to get the most out of your substrate so you can maximize the yield and quality of your product.
But if you’re lifting a pot to gauge how much water is in the substrate, it’s going to be difficult—if not impossible—to achieve your goals. To complicate matters, soil substrates and potting mixes are some of the most challenging media in which to get the water exactly right.
Without accurate measurements or the right measurements, you’ll be blind to what your plants are really experiencing. And that’s a problem, because irrigating incorrectly will reduce yield, derail the quality of your product, deprive the roots of oxygen, and increase the risk of disease.
Supercharge yield, quality—and profit
At METER, we’ve been measuring soil moisture for over 40 years. Join Dr. Gaylon Campbell, founder, soil physicist, and one of the world’s foremost authorities on soil, plant, and atmospheric measurements, for a series of irrigation webinars designed to help you correctly control your crop environment to achieve maximum results. In this 30-minute webinar, learn:
Why substrates hold water differently than normal soil
How the properties of different substrates and potting mixes compare
Why it’s difficult if not impossible to irrigate correctly without accurately measuring the amount of water in the substrate
The fundamentals of measuring soil moisture: specifically water content and electrical conductivity
How measuring soil moisture helps you get the most out of the substrate you choose, so you can improve your product
Easy tools you can use to measure soil water in a greenhouse or growth chamber to maximize yields and minimize inputs
Irrigation management: Why it’s easier than you think
Years ago, we received an irrigation management call from a couple of scientists, Drs. Bryan Hopkins and Neil Hansen, about the sports turfgrass they were growing in cooperation with the Certified Sports Field Managers at Brigham Young University (BYU) and their turfgrass research and education programs. They wanted to optimize performance through challenging situations, such as irrigation controller failure and more. Together, we began intensively examining the water in the root zone.
BYU researchers are zeroing in on irrigation management best practices leading to better outcomes that are easier to achieve.
As we gathered irrigation and performance data over time, we discovered new critical best practices for managing irrigation in turfgrass and other crops, including measuring “soil water potential”. We combined soil water potential sensors with traditional soil water content sensors to reduce the effort it took to keep the grass performance high while saving water costs and reducing disease potential and poor aeration. We also reduced fertilization costs by minimizing leaching losses out of the root zone due to overwatering.
Supercharge yield, quality and profit in any crop with soil moisture-led irrigation management
This article uses turfgrass and potatoes to show how to irrigate using both water potential and water content sensors, but these best practices apply to any type of crop grown by irrigation scientists, agronomists, crop consultants, outdoor growers, or greenhouse growers. By adding water potential sensors to his water content sensors, one Idaho potato grower cut his water use by 38%. This reduced his cost of water (pumping costs) per 100 lbs. of potatoes, saving him $13,000 in one year.But that’s not even the best part. His yield increased by 8% and he improved his crop quality—the rot he typically sees virtually disappeared.
What is soil water potential?
In simple terms, soil water potential is a measure of the energy state of water in the soil. It has a complicated scientific definition, but you don’t have to understand what soil water potential is to use it effectively. Think of it as a type of plant thermometer that indicates “plant comfort”—just as a human thermometer indicates human comfort (and health). Here’s an analogy that explains the concept of soil water potential in terms of optimizing irrigation.
Two researchers show easier methods conform to standards
If you’re measuring saturated hydraulic conductivity with a double ring infiltrometer, you’re lucky if you can get two tests done in a day. For most inspectors, researchers, and geotechs—that’s just not feasible. Historically, double ring methods were the standard, however the industry is now more accepting of faster single ring methods with the caveat that enough locations are tested. But how many locations are enough?
Triple the tests you run in a day
Drs. Andrea Welker and Kristin Sample-Lord, researchers at Villanova University, are changing the way infiltration measurements are captured while keeping the standards of measurement high. They ran many infiltration tests with three types of infiltrometers with a variety of sizes and soil types. In this 30-minute webinar, they’ll discuss what they found to be the acceptable statistical mean for a single rain garden. Plus, they’ll reveal the pros and cons of each infiltrometer type and which ones were the most practical to use. Learn:
What types of sites were tested
How the spot measurements compared with infiltration rates over the whole rain garden
Pros and cons of each infiltrometer and how they compared for practicality and ease of use
What is an acceptable number of measurements for an accurate assessment
Dr. Andrea Welker, PE, F.ASCE, ENV SP, is a Professor of Civil and Environmental Engineering and the Associate Dean for Academic Affairs at Villanova University. She joined Villanova after obtaining her PhD at the University of Texas at Austin. Her research focuses on the geotechnical aspects of stormwater control measures (SCMs) and the effectiveness of SCMs at the site and watershed scale.
Dr. Kristin Sample-Lord, P.E., is an Assistant Professor of geotechnical and geoenvironmental engineering in the Civil and Environmental Engineering Department at Villanova University. She received her PhD and MS from Colorado State University. Her research includes measurement of flow and transport in soils, with specific focus on green infrastructure and hydraulic containment barriers.
The environment plays a large role in any plant study. Ensuring you’re capturing weather and other environmental parameters in the best way allows you to draw better conclusions. To accurately assess plant stress tolerance, you must first characterize all environmental stressors. And you can’t do that if you’re only looking at above-ground weather data.
For example, drought studies are notoriously difficult to replicate and quantify. Knowing what kind of soil moisture data to capture can help you quantify drought, allowing you to accurately compare data from different years and sites.
Get better, more accurate conclusions
It’s important for your environmental data to accurately represent the environment of your site. That means not only capturing the right parameters but choosing the right tools to capture them. In this 30-minute webinar, application expert Holly Lane discusses how to improve your current data and what data you may not be collecting that will optimize and improve the quality of your plant study. Find out:
How to know if you’re asking the right questions
Are you using the right atmospheric measurements? And are you measuring weather in the right location?
Which type of soil moisture data is right for the goals of your research or variety trial
How to improve your drought study, why precipitation data is not enough, and why you don’t need to be a soil scientist to leverage soil data
How to use soil water potential
How accurate your equipment should be for good estimates
Key concepts to keep in mind when designing a plant study in the field
What ancillary data you should be collecting to achieve your goals
Holly Lane has a BS in agricultural biotechnology from Washington State University and an MS in plant breeding from Texas A&M, where she focused on phenomics work in maize. She has a broad range of experience with both fundamental and applied research in agriculture and worked in both the public and private sectors on sustainability and science advocacy projects. Through the tri-societies, she advocated for agricultural research funding in DC. Currently, Holly is an application expert and inside sales consultant with METER Environment.
