Drs. Kim Novick and Jessica Guo team up to discuss the vital role water potential measurement plays in both plant and soil sciences and the work they are doing to establish the first-of-its-kind nationwide water potential network. Join their discussion to understand how a communal knowledge of these measurements could impact what we know about climate change and ecology as a whole.
Dr. Kim Novick is a professor, Paul H. O’Neill Chair, Fischer Faculty Fellow, and director of the Ph.D. Program in Environmental Sciences at Indiana University. She earned her bachelor’s and Ph.D. in environmental science at Duke University’s Nicholas School of the Environment. Her research areas span ecology and conservation, hydrology and water resources, and sustainability and sustainable development, with specific interests in land-atmosphere interactions, terrestrial carbon cycling, plant ecophysiology, and nature-based climate solutions.
Dr. Jessica Guo is a plant ecophysiologist and data scientist who studies plant-environment interactions under extreme climate conditions. She earned her bachelor’s in environmental biology from Columbia University and her Ph.D. in biological sciences from Northern Arizona University. She is currently at the University of Arizona, where she blends her passion for reproducible workflows, interactive visualizations, and hierarchical Bayesian models with her expertise in plant water relations.
Abiotic stress in plants: How to assess it the right way
As a plant researcher, you need to effectively assess crop performance, whether you’re selecting the best variety, trying to understand abiotic stress tolerance, studying disease resistance, or determining climate resilience. But if you’re only measuring weather data, you might be missing key performance indicators. Water potential is underutilized by plant researchers in abiotic stress studies even though it is the only way to assess true drought conditions when determining drought tolerance in plants. Learn what water potential is and how it can improve the quality of your plant study.
Quantitative genetics in plant breeding: why you need better data
If you’ve studied plant populations, you’re probably familiar with the simplified equation in Figure 1 that represents how we think about the impact of genetics and the environment on observable phenotypes.
This equation breaks down the observed phenotype (plant height, yield, kernel color, etc.) into the effects from the genotype (the plants underlying genetics) and the effects of the environment (rainfall, average daily temperature, etc.). You can see from this equation that the quality of your study directly depends on the kind of environmental data you collect. Thus, if you’re not measuring the right type of data, the accuracy of your entire study can be compromised.
Water potential: the secret to understanding water stress in plants
Drought studies are notoriously difficult to replicate, quantify, or even design. That’s because there is nothing predictable about drought timing, intensity, or duration, and it’s difficult to make comparisons across sites with different soil types. We also know that looking at precipitation alone, or even volumetric water content, doesn’t adequately describe the drought conditions that are occurring in the soil.
Soil water potential is an essential tool for quantifying drought stress in plant research because it allows you to make quantitative assessments about drought and provides an easy way to compare those results across field sites and over time. Let’s take a closer look to see why.
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.
Check out our latest podcast, where Dr. Richard Gill discusses his global research projects including climate change on the Wasatch Plateau, ranch sustainability in Colorado, reef studies in Samoa, and wildfires in the Mojave Desert.
He focuses on the connection between the ecology of a place and the communities of people that inhabit it, and how scientists can protect socially and ecologically vulnerable populations by collaborating equally with them. Unless they’re sharks. He found out they’re typically not open to collaboration.
Dr. Marco Bittelli, soil physics wizard and pretty much the most interesting guy we know, discusses his exciting research projects in Italy and Antarctica. Plus, he shares insights on cutting-edge measurement methods, climate change, jazz guitar music, and more.
Marco Bittelli, PhD, is an associate professor in the Department of Agricultural and Food Science at the University of Bologna in Italy.
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.
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.
Orchard growers today live in an exciting time where environmental data are becoming inexpensive and abundant. But going from a data-poor to a data-rich environment has its challenges. Big data can be so overwhelming that growers struggle with how to turn that data into actionable insight.
One grower on the Washington Tree Fruit Research Commission recently commented that he uses no less than 19 data apps for making decisions. Steve Mantle, founder of innov8.ag, says, “It’s just overwhelming to a grower to consolidate all of this data together. We need to figure out how to help them with actual insights that impact either their yield quality / quantity—and just as importantly—their costs: particularly on labor, chemical/nutrients, and irrigation.” That’s why in 2020, Mantle and his team approached the Tree Fruit Research Commission’s technology committee to see if they could bring their capabilities, ingesting data from many different data silos and sensor providers into one place, with the goal of providing actionable insights for growers in the apple orchard space. Thus, the idea of a “smart orchard” was born.
Turning big data into a solution
In March, Innov8.ag began piloting a smart orchard project in collaboration with researchers from Washington State University & Oregon State University at Chiawana Orchards in Washington state. Their goal was to “sensorize” an orchard from multiple hardware providers, bringing together growers, data, and researchers to create a sustainable, “smart” orchard with insights that impacted a grower’s bottom line. To do this they combined data from on-farm and off-farm, online and offline sources including satellites, drones, weather providers, telemetry from IoT devices such as soil moisture probes and leaf wetness sensors, and more.” Mantle adds, “We’re trying to see how the sensors at different price points and from different vendors compare against each other in terms of accuracy. But the biggest goal is to get more granularity around and prove the value in canopy, soil, and weather measurements. Then we tie that in with yield, quality, and profit.”
Installing sensors so that comparisons are valid
The smart orchard consists of 100 rows of Gala apple trees spaced out over two 20-acre blocks. A number of different sensor/instrumentation providers, including METER Group, have their sensors deployed at this smart orchard measuring parameters such as weather, irrigation, soil water and nutrients, chemicals, disease, pests, crop health, labor, and drone/satellite imagery. All these data are aggregated and organized on a regular basis to try and enable growers to better understand weather and climate change to make precise, informed decisions and better manage their water usage, labor, equipment, and chemical usage.
Smart Orchard team member and researcher, Harmony Liu, says one challenge they face is making sure the comparisons are valid. “We are careful to install the same sensor types at the same heights so we are making “apple-to-apple” comparisons.”
Liu says in addition to sensing, they collect soil samples every week throughout the season and send them out to two different labs for nutrient testing so they can look at how that data compares with the soil nutrient sensors. They sample at five different locations at three different depths to match the sensors. She adds, “We have the dendrometer, soil nutrient data, soil moisture data, and canopy data all being collected within the same zone. It’s part of our intent to show this data all connecting with each other.” The team also measures irrigation line pressure with a sensor as opposed to using an irrigation switch. Liu says, “We want to know what the pressure signature is as everything turns on and activates so we can understand what that signature looks like and start to identify when there are abnormalities in how the irrigation system fills.” Additionally, they’re using METER NDVI and PRI sensors as well as a pyranometer for ground truthing the drone imagery that they’re doing at a 7 centimeters per pixel resolution.
Data cleanup is time-consuming
Liu says getting the smart orchard up and running was not without its challenges. “The first challenge was gaining access to some of the data from grower owned instruments because those instruments are not all grouped together.” Liu says that challenge made data cleanup time consuming, but they worked their way through it. She adds, “Overall, having this density of data is difficult because it’s a lot to wade through. But at the same time, it’s been really helpful. Data has been reliable coming in across the board.”
In-farm vs. outside-farm measurements
Liu says one thing they are interested in is accurately measuring temperature and humidity within the orchard because these parameters are critical for apple disease modeling. She says, “When people are modeling disease, they take the inputs from weather forecasts into the disease model for risk calculations. But there are some differences in environmental conditions inside vs. outside the orchard where evapotranspiration will cause temperatures in the canopy to be cooler compared to outside-farm temperatures while the vapor pressure is higher. So that’s one thing we use METER group instruments for. We have outside-orchard, above-orchard, and in-canopy ATMOS 41 weather stations and ATMOS 14 temperature and relative humidity sensors. We use these to compare the temperature and relative humidity difference. By using an instrument from the same provider, we eliminate the systematic bias vs. if we were to compare temp and RH from different providers. We also set up a vertical profile by installing sensors on the same pole at different heights and could see how the temperature and humidity changed across height for that location.”
Future smart orchard goals
Mantle says their most important goal is understanding in-canopy weather and how they can work with WSU and other institutions on adapting models for disease, pests, and ultimately informing spray management. Liu adds, “We also want to understand data comparison and unification. We want to bring together soil moisture measurements like volumetric water content and data from the METER TEROS 21 matric potential sensor. What we found is that, although they’re looking at soil moisture from different perspectives, unifying the two measurements will be critical for people working on irrigation scheduling.” The team also plans on working with WSU professors to create an evapotranspiration map that blends together some of the sensor telemetry and the view from a drone.
See the webinar
Want to learn more? METER soil physicist, Dr. Colin Campbell and Washington State University soil scientist Dr. Dave Brown discuss the smart orchard project in a METER Group webinar.
Everybody measures soil water content because it’s easy. But if you’re only measuring water content, you may be blind to what your plants are really experiencing.
Soil moisture is more complex than estimating how much water is used by vegetation and how much needs to be replaced. If you’re thinking about it that way, you’re only seeing half the picture. You’re assuming you know what the right level of water should be—and that’s extremely difficult using only a water content sensor.
Get it right every time
Water content is only one side of a critical two-sided coin. To understand when to water or plant water stress, you need to measure both water content and water potential.
In this 30-minute webinar, METER soil physicist, Dr. Colin Campbell, discusses how and why scientists combine both types of sensors for more accurate insights. Discover:
Why the “right water level” is different for every soil type
Why soil surveys aren’t sufficient to type your soil for full and refill points
Why you can’t know what a water content “percentage” means to growing plants
How assumptions made when only measuring water content can reduce crop yield and quality
Water potential fundamentals
How water potential sensors measure “plant comfort” like a thermometer
Why water potential is the only accurate way to measure drought stress
Why visual cues happen too late to prevent plant-water problems
Case studies that show why both water content and water potential are necessary to understand the condition of soil water in your experiment or crop
Dr. Colin Campbell has been a research scientist at METER for 20 years following his Ph.D. at Texas A&M University in Soil Physics. He is currently serving as Vice President of METER Environment. He is also adjunct faculty with the Dept. of Crop and Soil Sciences at Washington State University where he co-teaches Environmental Biophysics, a class he took over from his father, Gaylon, nearly 20 years ago. Dr. Campbell’s early research focused on field-scale measurements of CO2 and water vapor flux but has shifted toward moisture and heat flow instrumentation for the soil-plant-atmosphere continuum.
Soil moisture data are useful, but they can’t tell you everything. Other strategies for growers and researchers, like plant and weather monitoring, can inform water management decisions.
In this webinar, world-renowned soil physicist, Dr. Gaylon Campbell shares his newest insights and explores options for water management beyond soil moisture. Learn the why and how of scheduling irrigation using plant or atmospheric measurements. Understand canopy temperature and its role in detecting water stress in crops. Plus, discover when plant water information is necessary and which measurement(s) to use. Find out:
Why the Penman-Monteith equation, with the FAO 56 procedures, gives a solid, physics-based method for determining potential evapotranspiration of a crop
How the ATMOS 41 microenvironment monitor combined with the ZL6 logger and ZENTRA Cloud give easy access to crop ET data
How assimilate partitioning can be controlled by manipulating plant water potential using appropriate irrigation strategies
Why combining monitoring soil water potential with deficit irrigation based on ET estimates provide an efficient and precise method for controlled water stress management
Dr. Gaylon S. Campbell has been a research scientist and engineer at METER for over 20 years, following nearly 30 years on faculty at Washington State University. Dr. Campbell’s first experience with environmental measurement came in the lab of Sterling Taylor at Utah State University making water potential measurements to understand plant water status.
Dr. Campbell is one of the world’s foremost authorities on physical measurements in the soil-plant-atmosphere continuum. His book written with Dr. John Norman on Environmental Biophysics provides a critical foundation for anyone interested in understanding the physics of the natural world. Dr. Campbell has written three books, over 100 refereed journal articles and book chapters, and has several patents.