Evapotranspiration: Pitfalls to Avoid and Why It’s Easier Than You Think

Measuring evapotranspiration (ET) to understand water loss from a native or a managed ecosystem is easier than it looks, but you have to know what you’re doing.

Mistakes that kill your estimates

Measuring evapotranspiration (ET) to understand water loss from a native or a managed ecosystem is easier than it looks, but you have to know what you’re doing. If you can’t spend the time or money on a full eddy-covariance system, you’ll have to be satisfied with making some assumptions using equations such as Penman-Monteith.

Like any model, the accuracy of the output depends on the quality of the inputs, but do you know what measurements are critical for success? Plus, as your instrumentation gets more inaccurate, the errors get larger. If you’re not careful, you can end up with no idea what’s happening to the water in your system.

Get the right number every time

You don’t have to be a meteorologist or need incredibly expensive equipment to measure ET effectively. In this 30-minute webinar, Campbell Scientific application scientist Dr. Dirk Baker and METER research scientist Dr. Colin Campbell team up to explain:

  • The fundamentals of energy balance modeling to get ET
  • Assumptions that can simplify sensor requirements
  • What you must measure to get adequate ET estimates
  • Assumptions and common pitfalls
  • How accurate your equipment should be for good estimates
  • Causes and implications of uncertainty

Next steps


Our scientists have decades of experience helping researchers and growers measure the soil-plant-atmosphere continuum.

  • Blonquist Jr, J. M., R. G. Allen, and Bruce Bugbee. “An evaluation of the net radiation sub-model in the ASCE standardized reference evapotranspiration equation: Implications for evapotranspiration prediction.”Agricultural water management 97, no. 7 (2010): 1026-1038. (Article link)
  • Fuchs, Marcel, Ehud Dayan, David Shmuel, and Isaac Zipori. “Effects of ventilation on the energy balance of a greenhouse with bare soil.” Agricultural and Forest Meteorology 86, no. 3-4 (1997): 273-282. (Article link)
  • Ham, J. M. “Uncertainty analysis of the water balance technique for measuring seepage from animal waste lagoons.” Journal of environmental quality 31, no. 4 (2002): 1370-1379. (Article link)
  • Kimball, Bruce A., Kenneth J. Boote, Jerry L. Hatfield, Laj R. Ahuja, Claudio Stockle, Sotirios Archontoulis, Christian Baron et al. “Simulation of maize evapotranspiration: an inter-comparison among 29 maize models.” Agricultural and Forest Meteorology 271 (2019): 264-284. (Article link)


Dr. Dirk V. Baker has been with Campbell Scientific since 2011 and is an Application Research Scientist in the Environmental Group. Areas of interest include ecology, agriculture, and meteorology—among others. He has a bachelor’s degree in wildlife biology and a doctorate in weed science, both from Colorado State University. Dirk’s graduate and postdoctoral research centered around measuring and modeling wind-driven plant dispersal.

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.


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Hello everyone, and welcome to our combined Campbell Scientific and METER webinar, Evapotranspiration: Pitfalls to Avoid and Why It’s Easier Than You Think. Today’s presentation will be about 30 minutes, followed by about 10 minutes of Q&A with our presenters, Dirk Baker and Colin Campbell, whom I will introduce in just a moment. But before we start, we’ve got a couple of housekeeping items. First, we want this webinar to be interactive, so we encourage you to submit any and all questions in the questions pane. And we’ll be keeping track of these for the Q&A toward the end. Second, if you want us to go back or repeat something you’ve missed, don’t worry, we will be sending around a recording to the webinar via email within the next three to five business days along with a link to the slides. Alright, with all that out of the way, let’s get started. Today we’ll hear from doctors Dirk Baker and Colin Campbell, who will discuss fundamentals of evapotranspiration (ET), what types of errors to watch out for and what type of equipment is adequate for good ET estimates. Dirk Baker has been with Campbell Scientific since 2011 as an application research scientist in the environmental group. His areas of interest include ecology, agriculture, and meteorology, among others. He has a bachelor’s degree in wildlife biology and a doctorate in weed science, both from Colorado State University. Dirk’s graduate and postdoctoral research centered around measuring and modeling wind driven plant dispersal. Colin Campbell has been a research scientist at METER for 19 years following his PhD at Texas A&M University and soil physics. He is currently serving as Vice President of METER Environment. He is also adjunct faculty with the Department 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. Colin’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. So without further ado, I’ll hand it over to Colin to get us started.

Thanks, Brad. It’s a pleasure to be with all of you today, and especially a pleasure to join with my friend and colleague, Dirk Baker from Campbell Scientific. In our first joint seminar together as partner companies, it’s great to be able to start giving some of the combined knowledge we have of the scientists to all of you. And today it’s my special pleasure to talk about something that that I consider really important in our research: evapotranspiration. And the reason we titled it “why it’s easier than you think” is that for me, personally, I’ve often kind of shied away from using evapotranspiration because I’ve worried that it may be too difficult, or there’s too many parameters that I need to know to be able to actually use this in my studies.

Now something that I learned as a young graduate student studying rice in South Texas was that every day, a well water crop, like rice loses between seven and 10 millimeters of water. Of course, it has to be a nice, clear day. But that’s an amazing amount of water to be lost during just a single day growing period. Now knowing exactly how much water a canopy is losing is vital. And there are a lot of different reasons one may want to to know this. These are a few that I thought up. But you probably can think of a bunch more things like how much water do we need to replenish with irrigation. After that it’s lost during a day for a crop, we might want to explore different phenotypic water use based on different plants that we’re growing. It also can be an indicator of drought, it can be a surrogate of biomass production and growth models depend on this kind of analysis to estimate how much growth we have day after day.

Now, why is evapotranspiration or ET so complicated? Well, I’m not sure that it is, but it certainly has that reputation. And one of the reasons is that because of the different ways you have to go about finding it. First, and probably the most complex is measuring it directly. And I have a system here from Campbell Scientific and Eddy covariance system that can measure the up and down Eddys moving above a system that we’re interested in. And using the system we can figure out how much water vapor or co2 or trace gases are moving into and out of that ecosystem we’re interested in, and we can be quite accurate with the system. But there are problems. The cost of the system is often such that many struggle to put in a system like this. And the maintenance and effort involved trying to make sure you get good data and that you get great data over time is also pretty intensive. So many have focused on measuring ET indirectly, which is basically using the residual of an energy balance or energy budget analysis. This comes with lower cost. And we’ll talk about some of the benefits in a moment, but it has associated assumptions that limit its accuracy. And we’re going to talk about that in my my portion of the seminar.

So as I thought about trying to estimate water loss from a canopy, the first thing that comes to my mind is the thought that well, if we really wanted to just measure this value, E the evaporation, we’re gonna do it the simplest way possible. And there is an equation and I teach this in that environmental biophysics class that was mentioned earlier, that just says, to get evaporation, we need to know the ability of water vapor to move from the starting point to the ending point basically, inside the leaves in this canopy to the atmosphere, and the difference in concentration inside the leaf and in the atmosphere. So this would make a very simple analysis, if we just use this equation, but there is a major problem with this. It involves this conductance to vapor, and that in turn, the conductance of vapor over here depends both on the conductance in vapor in the air, which we get with a turbulent transport equation, but we can calculate that, but also this conductance to paper of the surface or that canopy, and we don’t know the canopy conductance, in fact, we know that it actually changes quite a bit over time, depending on several factors that cause domains to open and close. And so the simple approach that would allow us to get evaporation from a plant canopy and require us to only need to know the ability of water vapor to leave the canopy and go into the atmosphere, and also require us to know the leaf temperature, this is actually very difficult, because we don’t know, often the leaf temperature, there are better ways to do that now than there have been. But it’s still a difficult way to analyze this. And we struggle calculating that canopy conductance accurately. So we needed a better solution.

So there’s a connection that most people understand which ties together evaporation from a surface and what we call the continuity equation, or an energy balance that just says that the net radiation coming into a system Rn minus all the sources or sinks of radiation in that system, sensible heat flux H, latent heat flux, lambda e and soil heat flux G, all of that should sum to zero. And because in that equation, we have that evaporation. If we rearrange it, we actually have this again, pretty simple equation that says the evaporation should be related to the net radiation sensible heat flux. So heat flux divided by the latent heat of vaporization lambda. So that would be easy, except for the fact that we have a lot of things going on with that radiation term that are fairly difficult to calculate. And in the end, we have to know if something of the radiation coming into our system we’re interested in, but also and very importantly, the radiation that’s given off or emitted by that system if it’s a canopy, for example. So again, the basic assumption in evapotranspiration is that energy and mass flow are connected. And if we know all other forms of energy movement, latent heat flux is the residual and therefore we can solve for evaporation. Now, this is a little more complex than this summary kind of gets us to. And this was understood back many years ago by a man named Howard Penman who worked at the Rothamsted Research Station in the United Kingdom.

And his understanding of the link between energy balance and evaporation led him to write this paper. I just threw up a picture of the first page of that paper. It’s very famous, from 1948 on natural evaporation from open water, bare soil, and grass. And he produced an equation based on this energy balance or energy budget that was able to analyze evaporation based on those other parts of the energy balance. But one of the problems with this paper was that included in empiricism, an F value that tried to take into account the things that he couldn’t solve for in the equation. And essentially, that made that equation work quite well for Rothamsted, and a few other areas. But it wasn’t universally applicable. One cool note about Dr. Penman was that to get measurements from his research, he used to spend the night at the little experiment station they had there in the shed, in his sleeping bag waking up every hour when his alarm clock rang to remember to take different measurements. I think that’s one of the best recommendations I have for why it’s so wonderful to have data loggers these days.

So a critical step forward was made by a man named John Monteith many years later. He recognized the importance of having heat and vapor conductance in the equations that Dr. Penman put together. Nowadays, when I learned this equation, I didn’t realize that no one knew that fact, since we have learned the conductances first, and having them in the Penman Monteith equation just made so much sense I didn’t realize that, at some point, people didn’t recognize the importance of understanding the ability of water vapor to move from inside the leaf to the outside of the leaf and outside a leaf into into the the atmosphere. And also the same way from heat to move from the canopy, sensible heat to move from the canopy to the air. So what he did was put together these ideas of vapor conductance so that in the the canopy and the boundary layer, the air, and the conductance of heat to the boundary layer, in a couple of terms inside this equation, where there’s that GV the conductance of vapor in the upper right hand of the Penman Monteith equation, and then this gamma star equation that not only recognized so the original, just gamma, this was the the heat capacity over the latent heat of vaporization. Now, we’re multiplying that by a ratio of the conductance to heat to the conductance of vapor, and this gave our psychrometer constant now, a star, so gamma star, and that recognized the the adjustments we have to make when those things are out of a unity proportion. So John Monteith understood the importance of this heat and vapor conductance. And this new equation was really exciting because it removed the empiricism, that Penman’s original equation had in it, and became a practical solution for a broad set of locations. Now, the arguments continue today, does this equation fit everywhere? And as Dirk will start talking about in his presentation, well, we need some some simplifications for this. But it actually is applicable across a very broad range of things. But there is a problem here in that there are some things that we may not have values for and we’re going to have to make estimates. Now I put up a picture of John Monteith here. And I have to say, as I talk about him, I got to meet John when I was a seven year old boy, and my father was going for a sabbatical in England with Dr. Monteith, at the University of Nottingham. And he was described to be by many as I’ve gotten older as a classic Scottish gentleman, but I knew him as the nice white haired man that sat me on his lap from Heathrow Airport to Nottingham, and just talked with me and asked me questions the whole way, a wonderful man and who is truly missed in our science.

Now let’s talk about some of these practical aspects of Penman Monteith that I mentioned before and I said I’d get back to. So if we’re going to do this indirect method, this energy balance method of getting our evapotranspiration, we’ve got to recognize there are some good things and some bad things about this. Some of the positives are that we’re going to spend a lot less money on the solution. For example, the ATMOS 41 or ClimaVUE50 is much lower cost than these other systems, they’re easier to maintain and even like, for example, that ATMOS 41, ClimaVUE50 is very fast to deploy. We can do it in just a few minutes. But there are some negatives about this. And I’ve drawn this into my diagram here on the right hand side, there are some assumptions that may lead to some inaccuracies. One thing is that for example, the ClimaVUE50, ATMOS 41 just measures solar radiation coming in. But as I’ve tried to draw here, while it is going to collect the solar diffuse radiation, things like the solar reflected, and all these black arrows coming out here that I’m trying to draw in the long wave radiation both downwelling and uploading, it’s not going to capture. So then we’re going to have to make an assumption about that, that I’ll show you in just a moment. It also requires an ongoing canopy assessment of your particular canopy, because as I’ll mention in a moment, we’re not going to actually get the ET from our canopy, we’re gonna get the supposed ET from a reference canopy, and then convert it over to our canopy using what we call a crop coefficient. And unfortunately, we can only make hourly or daily assessments, another thing that Dirk will talk about in a moment. So what do we need to gather from Penman Monteith to estimate that maybe just a little beyond what we’re going to be able to measure with a typical weather station? Well, there is a net radiation, there we’ve got to convert over from a solar radiation also soil heat flux, which we don’t mention a lot in our presentation here. Over a day, we’re just going to assume that it’s going to be zero, but we could maybe be more accurate if we had an actual measurement of that, and canopy conductance. So let’s talk about some of these measurements here.

So if we had a complete suite of instruments, we wouldn’t have too much of a problem estimating ET, someone who’s long been messing around with energy balance may be arguing with me here that we still have a consistent problem that closed and complete energy balance is something that we haven’t quite done yet. So I’m not arguing that we would be able to do that completely with the instruments I’m showing. But especially with something like this four band net radiometer. So we’re collecting both upwelling and downwelling, shortwave radiation and long wave radiation in this device, then we get a long ways toward at least getting an accurate measurement of our net radiation, a big piece of this analysis. We could also put things like a soil heat flux plate shown here, this is a red device into the soil, and then we can get estimates of soil heat flux across a day, we can even step a little further and get a canopy temperature, this is not something that was very easily done certainly back in the days of John Monteith. But even when I was a brand new graduate student, I remember kind of talking about some of these instrumentation and my professor rolling out a $10,000 instrument that we could measure the infrared temperature of individual leaves in a canopy. Now we can do that much more easily. But the science is advancing pretty quickly. So instead of that, our typical weather station wall only have some of these parameters. And so here’s the ATMOS 41 or the ClimaVUE50. We have total solar radiation here, we have wind speed here. Up inside here, we’ve got a temperature measurement that’s accurately corrected for solar radiation and wind speed. We’ve got humidity and several other measurements that we’re able to do this analysis of ET. But in there, we’re forced to make some assumptions. So as Dirk will mention, there are a couple of ways to estimate ET.

One is FAO 56. And I chose this particular one, just to talk about how we’ve simplified some of the things with the Penman Monteith equation. So here as I mentioned earlier, we’re going to estimate our own ET from a reference ET of an idealized canopy. Now there are two types of canopies. I’m only going to focus on grass but Dirk will mention alfalfa as well. So grass that we’re going to idealize here, it’s 12 centimeters high, it’s well watered. And if we do that, we can then use some of the simplifications I’ve shown here on the right hand side, instead of using our turbulent transport equation. If we mount our weather station at two meters, then these two conductances, the boundary layer conductances, to heat and to vapor, just turn into a multiplier constant of .2 multiplied by the wind speed.

The conductance to vapor is also simplified. Here we’re going to assume that the canopy conductance is about .6 mols per meter square per second. Now that’s higher than an individual leaf conductance. I’ve measured those many many times. They’re typically for a well watered leaf around .2 mols per meter square per second. But there’s a rule of thumb we can multiply by three and get a canopy conductance. Now you see some of these empiricism coming in. And then we just have the conductance to vapor that includes the canopy conductance and the boundary layer conductance. We combine them together in this equation to get an overall gv just as a function of again, the wind speed. Same thing for the psychrometer constant gamma star, we have a multiplier here that just includes the wind speed. So the other piece that we have to estimate is the net radiation and errors to the net radiation are going to be in Dirk’s talk. But I’ll mention here that if we only have solar radiation, we have a constant that we’re going to multiply our solar radiation by. And then we’re going to subtract from it things related to the average temperature, the vapor pressure, and in a function of cloudiness. So this side of the equation actually takes into account our long wave radiation portion, and is based on lots of experiments to tie the net radiation to the total incoming solar radiation. But it is a simplification. So why does this work? Well, we multiply this by our crop coefficient to adjust it to our specific need. And then using this specific surface, this idealized surface is 12 centimeter grass. We can and other things like the canopy conductance and the net radiation, we can make this estimate of ET. And now I’m going to turn the time over to Dirk who’s going to continue our discussion.

Thank you, Colin. And thanks everybody for joining us. And it’s a real pleasure to be able to collaborate with METER and Colin, and I look forward to future collaborations as well. So this is another version or another way to write the Penman Monteith equation. And I won’t go into a lot of detail because Colin’s covered a lot of this already. But there’s a couple of things that if you’re like me, they’d stick out very quickly. First, we have this strange constant of 0.408. Now, if you remember from Colin’s talk, there’s usually you’d see, or you would see the the lambda in the denominator. So one over Lambda, or the latent heat of vaporization is simply that .408. And then the other two that are so clearly described there in that list of parameters are the Cn and Cd or the numerator constant and the denominator constant. So the strange descriptive there aside, these are really just relating to a lot of the canopy simplifications that Colin’s talked about. And so these are dependent. These are basically a lookup table of values that would be used for either if you’re using a short or tall reference, and then if it’s an hourly calculation, then whether it’s day or night time. Okay.

So, as Colin alluded to, there are a couple of formulations of Penman Monteith that are at least the most commonly used in the world. One is that FAO 56. It’s the Food and Agriculture Organization, it’s part of the UN. And the other is the ASCE standardized reference. And this is the American Society of Civil Engineers. And there’s links there at the bottom to both of these, you can get the full versions for no cost. So the difference between these is really not there. In fact, if you wanted to look, I think it’s in the appendices of the ASCE standardized reference, there are some comparisons of these two and as well as a couple other methods of calculating ET using Penman Monteith. METER uses or provides a daily calculation based on FAO 56 in their ZENTRA Cloud. And Campbell Scientific has the ASCE hourly calculation. Now the difference between daily and hourly is really pretty small most of the time, the only time you’d see significant variation or significant differences is if you have substantial variation in less than a day in one or more of the measurements. And I have heard of some efforts to do even shorter time intervals. But again, I think that relates to whether or not and it could be done, I just don’t know that you’d gain a lot because you’d have to have significant variation in one or more of the measurements at that timescale for that to make much of a difference.

And coming back to this equation now I’ve added the list of measurements that we would use, either with FAO 56, or ASCE against the list of parameters, and the first thing that sticks out is that there’s only two of these parameters that are directly measured, and that’s temperature and wind speed. And so the rest of these are modeled to one degree or another And so things like the saturation vapor pressure and the vapor pressure, these are pretty straightforward relationships just based on temperature and relative humidity. But especially net radiation is heavily modeled to get to that. So then the question becomes which of these measurements are the most important, which ones do we want to be most concerned about the accuracy?

And so here’s an attempt to render what amounts to be about six different dimensions, if you will, into two dimensions. So bear with me for a moment while I explain this. So this figure holds the four, the three measurements constant, while varying one other. And then there’s the other two dimensions that are held constant for all of these. And those are just the time and the location of the measurement. And location just matters for solar angle. And so what’s held constant for all of these figures here is the location which is mid latitude and the time, which is a mid day on a summer day. And so, the short of this is that the steeper the slope, the more sensitive the calculation of ET is to that measurement. And I won’t go into you can, this will be provided as a recording, so if you want to spend more time with it, it does, it took me a little bit to get my head around all of the interactions here. But so you can glance at this quickly at least, and see that the steepest slope there is that incoming radiation, as measured by a pyranometer. And so that is the most important measurement. Now because these do interact, there’s some other generalizations that we can make. So one is this idea that if wind decreases, or relative humidity increases, then the radiation is that much more important. And the other is if radiation decreases than wind speed has larger influence on that calculation of ET. Now going into a little bit more detail on radiation, this on the left is the same figure I just showed.

So this is the sensitivity of the calculation in an arbitrary evapotranspiration to incoming radiation versus the net radiation, which again, has all of that modeling to get to net radiation from incoming radiation and temperature. And so you can see that that’s an even steeper slope. So it’s even more sensitive to net radiation. Okay, so one of my interests is in understanding better how uncertainty and especially measurement uncertainty, what implications there are for that uncertainty for various decisions or inference that we might make in either decision making or in research. So this is one way that’s part of a white paper that I’m working on, it’s one way to try to get at the combined uncertainty from all of the sensors that are being used to come up with an ET calculation. So this is data from a seven day period as totalized, ET over that seven day period at a site in southern Utah. So the blue columns are from the measurements, so they’re just calculated directly from the measurements from the weather station for that period. And then the error bars, the red error bars are a combined uncertainty that differ in a sort of a hypothetical set of sensors. And so these represent a high medium and low measurement uncertainty. And then it also shows the data for both a short and a tall reference. And so the short, we haven’t talked about this much, but the short is again, what Colin mentioned, it’s the short grass often thought of like a turf grass. And the tall is an alfalfa. And so either one of those are used as references for various applications. And so the shorter the interpretation here is that while these errors would accumulate over time, the contribution of the sensor itself to uncertainty in the calculation of ET is relatively small.

Okay, so there are some simplifications and improvements and there’s a lot of research in this area. One that I’ll mention is there are alternatives to Penman Monteith that use fewer measurements. Now the short of this is that we would generally not recommend it because we’re doing even more modeling to come up with a calculation of ET. And so if you can avoid that, I would go with as many measurements as you can do, as you can afford. And as Colin mentioned, the simplest improvement here is to directly measure the net radiation that gets rid of all that modeling and assumptions about what’s going on in it with net radiation. So but that can be an added expense. And so adding a four component net radiometer would also mean that with either the easily done calculation from either METER or Campbell Scientific, then there would be some additional work to do that calculation since both of those equations, the ASCE and the FAO 56 are assuming a incoming radiation not net radiation as the input. And then, of course, the more direct measurement is a full Eddy covariance suite, or even more so it would be a lysimeter, which we haven’t talked about, but that’s that much more intensive and expensive and interesting to maintain. So the place where we have the greatest opportunity as users of an FAO 56 or ASCE calculation is in the siting of the weather station, the installation, and its maintenance.

And so one thing to consider is the height and especially the wind speed. And so these equations of Penman Monteith assume that that measurement height is at two meters. So that conflicts with a lot of weather station needs which put that light wind speed measurement up at about 10 meters. So these equations do do an adjustment. So you can input the height of the measurement height of the sorry, of the wind speed sensor, and then it will do an adjustment based on a log width and profile to that to make it as if it were at two meters. So there’s an additional level of modeling with some potential for error there. Temperature, radiation shielding is always important. And even passive shields can introduce some error if you have a lot of incoming solar radiation, and not much wind. But given the lower sensitivity of the calculation of ET to temperature, the addition of something like an aspirated shield probably isn’t necessarily worth the investment at the maintenance cost. Unless you need a high accuracy temperature measurement for another purpose. And so coming again to the solar, this is where the the biggest opportunity to make sure you’re getting good measurements is. And so making sure that solar sensor is mounted well, it’s clean and stays clean and is level. So even some dust let alone bird deposits are going to cause some substantial error in solar input, leading to an underestimate of ET. And so in low level would cause a bias a time bias. And so depending on which direction that solar sensor is that higher numbers is pointing, it could be, you know, if it’s pointed east or west, and you’re given the time of day, it would be higher or lower than it should be. And especially for solar, we recommend calibrating it every couple of years. Now talking a little bit about the influence or how large of a geographic area set of sensors is relating to versus how high it is. So the higher a sensor is mounted, the greater the geographic extent is its area of influence. And that’s why in a lot of cases, weather stations are mounted higher. So it’s not just local conditions that it’s relevant to. However, that doesn’t mean that if those especially upwind conditions differ strongly from those of interest, then you’d introduce that much more uncertainty and bias potentially into the ET calculation. So mounting it lower, which is why the two meter height is a general rule of thumb, depending on canopy height. Now if you’re measuring a forest, that’s going to be really challenging because that’s a very tall canopy and getting measurements above that canopy is obviously a real challenge logistically. However or if you’re measuring a tall crop then the measurement height above that, say it’s corn then you just need to make sure that your measurements are above the highest corn cut canopy.

Okay, just a few summary points. We’ve kind of harped on this, but that net radiation is the most important parameter. So though it is largely modeled, so the simplest improvement is to directly measure that net radiation. But the key part is to make sure your sighting installation and maintenance are kept up. And these are more important than sensor uncertainty. Given a certain the data that I showed did assume a certain level of sensor quality and accuracy. These are what kinds of sensors you’d get from either METER or Campbell Scientific, not real low end sensors. And then crop coefficients which we’ve also not really addressed here, it’s a big topic. And that’s how you go from this reference ET to your crop of interest or your system of interest. It can be very challenging and error prone to estimate these crop coefficients. Some are more widely available and better estimated than others. But it might be better depending on your system and how you’re using ET which is definitely something we’re interested in hearing from you is how you’re using it. It might be better in a lot of cases just to use the reference ET as an index, not necessarily a direct number. But that would be an interesting thing to hear more from you about what you’re interested in, as in ET, and how you’re using it or how you’d like to use it. And with that, I’ll close and thank you very much for your time. And we look forward to any questions you have. All right.

Thanks a bunch, Dirk. Thank you, Colin, we do have a few minutes for Q&A. Before we start the Q&A section, we are going to post a quick poll just to see your thoughts yes or no on how this webinar had helped or possibly changed your perspective on ET. So I’m going to start that poll. I’ll leave it up for a few seconds, just to get enough people to answer and get a good sample size there. And while you’re answering that poll, I did want to let you know that you can still enter your questions in the Questions pane. And like I said, we’ll take a few minutes, we’ll see how far we get. We do have a bunch of questions that have come in already. And I just want to warn everybody, we will not be able to get to everybody’s question. But we do have them recorded. And so if we do not, so feel free to to submit your question, if we do not get to it either Colin or Dirk or somebody else from our METER Environment or Campbell Scientific teams will be able to get back to individually via the email that you registered with to answer your question. So please feel free to ask any and all questions that you have.

All right. Okay, thank you for everybody who responded to that poll. I think your participation has been valuable. Thank you. All right. So questions here. This first question is asking, and again, this is open to Colin or Dirk, or both of you. What percent of the water given based on daily ET is really used for the plant? I’m assuming this depends on the plant. In many ways, right?

Yeah, so I can take a shot of that and Dirk, you can too. So this really depends on a lot of things. One is the soil wetness, the surface wetness of the soil, as well as the canopy closure. And so it’s difficult to actually say how much that would be. But let’s say we have a completely closed canopy, something like I was showing that first picture of a beautiful potato canopy. If it’s fully closed, then the percentage of water given I mean, some is gonna evaporate off leaves, if you’ve got like a center pivot irrigation laying the water down. But in general, if we just talk about the water that actually makes it into the soil, whether they’re accessed by the roots, it can be up toward 90% of the water given that’s actually used in evapotranspiration (ET), that’s what I understand Dirk, do you have a different number?

I don’t have a number. The first thing I think of as kind of from the ecologist standpoint, or the natural system standpoint is there’s going to be a tremendous amount of variation based on what types of plants or community of plants are of interest. You know, desert ecosystems especially, are very well adapted to close domains or have a waxy surface to minimize water loss. And so it’s really and that’s why we do reference ET for a variety of other reasons as well. But that’s what the first thing I thought about. All right.

Another question here, can we implement FAO 56 equations using conductances derived from Eddy covariance?

Gonna let Derek answer that one.

Well, I sense I think that would take some work. I guess I’m not. It would take some time digging into the equations to see how that would work. I think that just off the cuff it would it might be more something that you’d put into something analogous to a crop coefficient. Colin do you have?

Yeah. That’s interesting. Interesting thought, I think. I mean, first of all, why are you doing this? If you’ve got Eddy covariance, you could do it. But maybe the question is hey, if we put an Eddy covariance system out in the field, and used it for a while to try to get at a canopy conductance, could we then use a weather station after that to insert maybe a better estimate of the canopy conducted to that .6? And so from my point of view, sure, improve upon that. That’s a solid number as is on the equation constant. So what are your thoughts on that? Does that change your view there?

No, no, I think that’s kind of where I was going is that if or my assumption was kind of what you’re saying is that they had to have the opportunity to maybe get the estimates from another location or short term deployment of an ET status station. So that’s how they were able to get some of these better estimates. So yeah, definitely opportunities for improvement. It would just take the work of digging into those equations and seeing where you can make those improvements. I kind of well, I won’t go into digressions. I’ll stop there.

All right. Next question. Where do you recommend installing the weather station to use this type of ET method in an agricultural crop?

Yeah, I can jump in there. And Dirk, I’ll step first because that was what I was messing around with last summer quite a bit. And Dirk mentioned this of locating your weather station in an area with appropriate fetch. That means that the area with which that is kind of with the prevailing wind or the wind that’s blowing, that’s actually moving the eddies of the surface that you’re interested in. So we compared a weather station that was just regional, it was about six or seven kilometers away from our field, we call it I don’t know, regional weather station that’s almost semi local to one that we actually installed out in the field where we had our canopy or our plants of interest. And it’s interesting how different those values were. And so you know, getting it in the location that you’re interested in learning about is critical, but I want to see what Dirk says, because he really covered this in his presentation.

Yeah, that’s the same kind of thing I was thinking of, and there you know just be aware of that no matter you know, depending on say, you know, the worst case kind of scenario is a small irrigated crop in the middle of a desert. No matter where you mount or install your station, you’re going to have some influence to that surrounding station and surrounding area, but you know, being aware of that fetch, where the prevailing winds are coming from, and making sure you mount your sensors, as you know at that two meters, or at least close to wherever the maximum canopy height is going to be. And either on the downwind side, or kind of in the center of the field, I guess, would be the general recommendations I would have.

A couple more questions here. This next one, so adding the four component net radiometer can improve accuracy of the reference ET. But then it breaks inner comparability of those calculated values with the standard Penman Monteith calculations. Would this invalidate the use of published crop coefficients?

Oh man, I’m going to Dirk again.

Ah, that’s an interesting question. I know this is done. So people have done this. And it’s not necessarily my area of expertise. There’s some good work. Some papers which sorry, I’m not remembering off the top of my head the titles or published dates, but I know our colleague over at Apogee, Mark Longlist, has spent quite a bit of time with evapotranspiration. And he’s done some work with colleagues on evaluating some of these using a direct measure of net radiation, as opposed to the model version that’s in the standard implementation of FAO 56 or ASCE. So you know, that’s something where I started to go into a digression. I’ll try to minimize my time here. But I kind of get a little bit circular in these because all these estimates there’s a lot of kind of empiricism in these equations. And so once you start tweaking with some of the measurements, does that then start breaking down the rest of the calculations? And I think that’s a valid question. It’s not something I spent a lot of time in literature. So there might be people, even in the audience that have a better answer than I do. So that’s kind of a non answer, but Colin I don’t know if you have other thoughts there. Yeah, I

think that was just an excellent answer. And just kind of what I was thinking as well. It’s great if you have that four component, as we’ve talked about you make big strides and getting closer to the right answer from the perspective of a Penman Monteith equation, remember that original equation I talked about was, you know, there we could directly estimate the evapotranspiration from a specific crop. So once you get a four component, net radiometer out there, if you can go a little bit further and close off some of these other questions like a canopy temperature measurement to try to estimate canopy conductance, you may be not in line for a reference ET, but in line to actually get your actual ET from the field. So or you can go, you know, so you can either go with crop coefficients and maybe adjust them, maybe making like an eddy covariance measurement on the field just for some validations initially to learn whether you’re doing it right, or you can go straight to an ET calculation once you’ve got a few of these other pieces.

I think we’ve got time for one more question. And I’m going to cheat and squish a bunch together. Other people are asking about the various applications, specific applications that are a bit off of the normal from what we’ve discussed here today. So what are some suggestions you might have for those trying to measure ET in say, for instance, open water or greenhouses or vineyards or along those lines?

So I’m going to integrate Dirk in here maybe with thoughts. But as I came in here several of you sent in great questions beforehand talking about hey, what do we do with potted plants? For example what do we do with forest canopies? You know, what do we do about different things and one of the amazing things about ET is that it’s one of the most intensely studied topics in literature. So there’s a lot of great literature on each one of these, and I by no means am an expert on ET. But I do know kind of where to point some people and some articles, and it may be something that you’ll have to look into more there’s a great open water article, I think it was by one of my friends, Jay Ham, put something together on that maybe we can leak that when we send this out if I can find it for greenhouses. A good friend of mine, Marcel Fuchs, a colleague of my father’s who was a visiting professor when I was really young, did some work on greenhouses, and maybe we could point you to some of that work. I’m not super familiar with vineyards. But I’m going to turn it over to Dirk to give some thoughts on some of these two.

Yeah, so my first thought for, which would be I would hesitate to actually recommend this, but when it’s over water, then the transpiration component of evapotranspiration kind of goes away unless you have a lot of sleek floating plants and that kind of thing. That’s my first thought. And so what you’re really looking at is evaporation. And so there is something called an evaporation pan. That’s a measurement directly of evaporation. There’s even ways of turning that into, which I’m not that familiar with. But there are ways of using an evaporation pan to get at evapotranspiration. They’re high maintenance. They’re kind of challenging to work with. So that’s why I hesitated a little bit to recommend it. But if it’s open water, then my first thought is that you’re more interested in in evaporation than the transpiration component. But I may be missing something in that equation or in that question. I have not spent time looking at this. It seems like it would be really complicated to try to do this in a closed system like a greenhouse, but that’s just my first thought. I would be interested in those references too Colin. So that’s kind of my first thought there. What am I missing other parts of that question?

Vineyard, it was discussed, I think, I mean, my experience is that that’s been well worked on. Do you know any references for that?

I don’t but, yeah, I would think that I’m sure that there’s work there. I think that the key part of that is that what you’d use as a reference, and how much you know, whether they’re using how much you’d have bare soil coming into versus a closed canopy, seems like that would be the key part of it.

And, you know, maybe if I can add Brad, just as a last comment, because it reminded me of one of the questions that came in from our pre webinar email. The question really related how to tie evaporation to in soil measurements, and I think we have another virtual seminar that we maybe link for that question, but one of the things that we see as a critical step forward in the future is tying evapotranspiration, the stuff we talked about today, within soil measurements. So water potential we can see how the plants are doing in the soil. We can see what’s lost through at how the plants are doing with the soil, in the soil, and things like some remote sensing tied in, we’re using satellite data to locate where we should put sensors and to evaluate stress. On a field scale, these things are getting tied together. So I don’t want people to come away from the seminar thinking, okay, it is the only tool that I have in my toolbox to be able to assess plant health.

There’s some really cool work in using drones as supplemental to this or even the primary measurement. Not to undermine us, but the the same kind of thing as satellite or aerial imagery can really be informative there. And that’s not something I have necessarily expertise, but it’s interesting stuff. All right.

Thanks Dirk. Thanks Colin, that’s gonna wrap it up for us today. We’ve gone over thank you for everybody who has stayed on and listening to this. We hope you have enjoyed this discussion as much as we have. And again, thank you for all of your great questions. We have dozens and dozens over 100 questions here have been submitted. And so we definitely did not get to all of them. But again, somebody from our team whether Colin or Dirk or somebody else from our teams will be able to get back to you to answer your questions. Also, please consider answering the short survey that will appear after this webinar is finished just to tell us what types of webinars you’d like to see in the future. And for more information on what you’ve seen today, please visit metergroup.com and campbellsci.com. And finally, look for the recording of today’s presentation in your email. And stay tuned for future METER webinars. Thanks again, stay safe, and have a great day.

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