In this episode of the Sprinkler Nerd Show, Andy Humphrey shares his experiences and insights from Salt Lake City, Utah, where he visits OptConnect and spends quality time with his son at the University of Utah. He looks forward to enjoying St. Paddy's Day weekend activities, including drinking green beer and skiing. Amidst his travels, Andy seizes the opportunity to engage in a thoughtful discussion on the topic of soil moisture sensing technology, its applications, and the broader implications of experimenting in life and business.
Andy underscores the podcast's mission to assist irrigation professionals, regardless of their experience level, in leveraging technology to enhance their services and gain competitive advantages. He passionately discusses the experimental nature of life, encouraging listeners to embrace trial and error in both personal and professional contexts. Andy advocates for a mindset of continuous learning and experimentation, particularly in the realm of soil moisture sensing, to better understand and optimize irrigation practices.
Highlighting recent conversations on soil moisture sensing, Andy delves into the practical benefits and transformative potential of this technology. He emphasizes the importance of data collection and analysis to validate assumptions about soil conditions, which can lead to more informed decision-making in irrigation management. Through a series of anecdotal insights, Andy illustrates how soil moisture sensors can reveal the nuanced behaviors of soil under various conditions, offering a more scientific approach to irrigation that challenges traditional assumptions and practices.
Andy encourages his listeners to adopt an experimental approach when utilizing new technologies, viewing them as tools for discovery and improvement. He stresses the significance of observing and interpreting data over time to gain deeper insights into soil moisture levels and their impact on irrigation efficiency. By promoting an inquisitive and open-minded attitude towards technology, Andy hopes to inspire irrigation professionals to explore new possibilities, question established norms, and ultimately, enhance their expertise.
Concluding the episode, Andy extends an invitation for feedback and engagement, emphasizing his openness to connecting with the audience and sharing knowledge. He leaves his listeners with a message of encouragement to remain curious, willing to experiment, and committed to advancing their skills in the ever-evolving field of irrigation.
[00:00:00] Welcome back to The Sprinkler Nerd Show. I'm your host Andy Humphrey coming to you from the city of Salty Lakes.
[00:00:08] Salty Lakes City, USA, the city of Slut. Slut, USA, SLC, Salt Lake City, Utah. Just landed here today and I'm going to make a quick trick up.
[00:00:23] Quick trip up to visit op connect and then spend some time with my son, Google City University.
[00:00:30] A Utah hang out with my good buddy Chris Wright, VP of sales for baseline. Have a fun St. Paddy's Day weekend drink some green beer. Perhaps go skiing.
[00:00:39] In any case, I've got a few minutes here while driving north on I-15 and just thought I would do a little brain share.
[00:00:46] Kind of just share some thoughts that are on my mind this week particularly because I've had some fun conversations as it relates to soul moisture sensing and new technology and collecting data and what it can do for us.
[00:00:58] So let's roll the intro and get right into the episode.
[00:01:01] If you are an irrigation professional, old or new who designs, installs or maintains high end residential commercial or municipal properties and you want to use technology to improve your business to get a leg up on your competition.
[00:01:21] Even if you're an old school irrigator from the days of hydraulic systems this show is for you.
[00:01:29] This whole thing is just it's kind of just a big old experiment. This whole thing of life, this game of life, this whole thing of business, your job, what you do every day.
[00:01:44] Kind of just a big old experiment. Is there a right way to do something? Is there a wrong way to do something? Are there many ways to do something?
[00:01:55] Do you think that what you know is what you know? I would agree that what you know is what you know. So how do you change what it is that you know?
[00:02:11] Maybe experiment, maybe for ice something. This whole thing is just an experiment and those are some of the kind of top level high thoughts that come to my mind as it relates to both technology but more importantly sort of the specifics of soil moisture sensing.
[00:02:35] And I've had a lot of really interesting conversations recently about soil moisture sensing and it's very fun for me because what I like most, I think about using soil moisture sensors is being able to connect the dots as it relates to trying something new.
[00:02:58] I'm changing that runtime from 28 minutes to 35 minutes does it make a difference, a measurable difference without being able to have eyes in the soil. There's no other way to know.
[00:03:18] And so some of the conversations I've had recently in regards to soil moisture sensing have really been about understanding what, what the data is telling us how quickly a soil dries out or the exact opposite.
[00:03:34] How much moisture or water does a soil hold and after a significant rain event, what does that look like in the soil? If the moisture doesn't rise significantly after a significant rain event, then perhaps the soil is already at the limits of what they can hold.
[00:03:59] And so sometimes we have a, we have a thought in our mind of what we think is happening. What we think is happening during the rain event or after the rain events and without being able to have any data to close the loop and validate our assumptions.
[00:04:16] I guess really that's what, that's what some of these new sensors are able to do is validate our assumptions without validating our assumptions. Our assumptions may or may not be accurate and it seems that or could be that oftentimes we operate from a set of assumptions that could possibly not be true but because we have no way of actually measuring them, understanding them, seeing them
[00:04:44] that we over time sort of begin to convince ourselves that certain, even certain ways of doing things might be the right way of doing something because there isn't anything else that's come across that we've tried that could convince us otherwise.
[00:05:00] And my first sort of thought as it relates to soil moisture sensing, well those two parts. Number one is that somebody's first thought generally is okay great, this soil moisture sensor. Now how do I get it to automatically adjust the controller?
[00:05:16] And it's interesting that that's a first thought that people have and I think it's because we live in the sort of the box of irrigation.
[00:05:26] And I would say that yes, that would be great and there are many ways you can use the soil moisture data to adjust in control or start or stop or pause or suspend an irrigation system. However, there's more, there's more that the data can teach us
[00:05:45] to make us all better irrigators than just looking for the quick answer of suspending the irrigation system or controlling a zone.
[00:05:56] And so my recommendation to people who are just getting started with soil moisture sensors is to put them in the ground, look at the data and not only look at the data let's say right now in this instance and what it is telling us right now.
[00:06:15] But what does it tell us over time because the data point all by itself is rather, it doesn't actually tell us much all by itself. We have to compare data over time we have to look at the frequency of the data over time to understand what is telling us. So for instance, if the soil moisture sensor tells us 33%
[00:06:43] we actually don't know what that means. You can make some possible generalizations if you know things like the soil type and the structure and the compaction and the old incapacity, et cetera, et cetera without any other information.
[00:07:01] So just the value of 33% all by itself is not very relevant. Now if you were to look at it's 33% today and next week at the same time, the value is 45%.
[00:07:22] Now 33% is relevant. 33% can now be compared to 45%. So now we know, oh, last week when the measure was 33%, that was drier than 45%.
[00:07:38] Interesting. I wonder how high the value, I wonder how much moisture this soil can hold and now the values become relevant to each other based on the holding capacity or based on the soils ability to hold water and what that upper value looks like.
[00:07:59] And you can look at it the opposite way. If it's 33% today and we came back in a week and we took another measurement and it was 25%. Now we know the soil can be drier than 33%.
[00:08:15] And it must have been fairly wet when I took the first reading. So with that in mind, my first sort of observation with soil moisture sensing is to look at the data over time. One day's not enough.
[00:08:31] Let me take that back. It could be enough if you know your soil is dry and you put a moisture sensor in the ground and then you pour a bucket of water over it and you wait a few hours. Okay, that might be might be relevant but you need to wait even longer.
[00:08:48] So if you were to watch and look at the data over at least one week and you know that the area in which it's place has had time to both dry out and it is also had water applied to it, either from an irrigation system or from rain mother nature.
[00:09:09] If you've had wet and dry over a week or two, now you can look at what that data what that looks like over time on a graph. And that information looking at the pattern of the soil moisture is in a pretty significant observation.
[00:09:30] They can tell you quite quite a bit. And I think that kind of looking at the data like an experiment, you know this is all just as I kind of started out this is all just an experiment that having have an experiment having an experimental mind sets can be helpful because it can keep you in a place of wondering and curiosity.
[00:09:59] Versus being in a place of I don't understand. I don't think this is working. This is a pain in my ass. I don't want to do this anymore. That that is one approach that people can have instead of saying, huh, I wonder why after this significant rain event.
[00:10:18] Why why why didn't the moisture go up like I thought it would huh. That's interesting and just keeping thoughts like that in the back of your mind.
[00:10:30] Or the front of your mind, wherever wherever you can keep it where you won't forget where you can use it to learn. I feel is is really important because these types of tools, although they have they have been around a long time accessing access to the data really hasn't been available in the way that it is today.
[00:10:50] So if you were to put a slow moisture sensor in the ground today, you can now have readily available access to the data.
[00:10:58] Potentially down to the minute if you wanted or at least by the hour and you can look at it over a day, a week, a month. You can look at it over the same irrigation cycle.
[00:11:11] What does a 45 minutes cycle look like? And it doesn't always look the same. And having these tools to sort of complete the complete the loop and compare the data is a really really good.
[00:11:28] And I kind of like to look at it. I was messaging with the messaging with a friend of the show actually here today and what first came to my mind he was asking me some great questions in this regard. He's got one of our
[00:11:45] one of our hex sensors, one of our hexes in the ground and you know I think there was an air pocket when he first installed it so it wasn't quite reading accurately because there were some air gaps around the sensor.
[00:11:59] And in any case what it reminded me of when we were talking was that there's this kind of you know if you keep a keep an open mind where it's not it's working, it's not working or it's black or it's white or it's this or it's that.
[00:12:15] And you sort of approach these new tools and you approach new technology and you approach new data. And you use them to make some observations just no different than being in the laboratory and using doing an experiment and using something to measure the experiment, you can make some observations.
[00:12:35] You can wonder what are you observing is it what you thought you would observe you can kind of you can kind of ponder the observation and make some potentially make some theories about why it is that you're seeing what you're seeing.
[00:12:51] And you could try to make some changes and you could observe again and then you can learn again, then you could try again and occasionally in this process you have some aha moments.
[00:13:04] And give you one example. Let's say you you were going to use a soil moisture sensor to start watering at exactly the same threshold doesn't matter what the number is, you're going to start watering at exactly the same depth and the analogy I would say is that it would be similar to filling up your vehicle when the light comes on if you have it when you gallon tank and you fill up exactly when the light comes on.
[00:13:33] You know within a few miles you'll generally put in about the same amount of fuel. Let's just say 20 gallons because this star point was the same it was when the tank was empty.
[00:13:44] So let's just say that that was like running a 45 minute cycle when the soil was dry.
[00:13:53] Well, what if the 45 minute cycle on some days only gets the soil half as wet as a 45 minute cycle on other days and this is this is real shit.
[00:14:05] This is how it works. 45 minutes doesn't always apply the same amount of water.
[00:14:13] Why why is that? Well maybe it's windy.
[00:14:19] If it is very windy and it happens to be windy right now I'm driving north on I 15 actually going to visit op connect.
[00:14:26] This is the second podcast I've recorded in a vehicle driving to visit op connect and there's a high wind warning which made me think of this example if there's a high wind warning and your sprinklers come on that precipitation will not reach the soil moisture sensor the same way it does if there is no wind.
[00:14:42] Same amount of runtime different amounts of water hit the sensor and when you look at that data.
[00:14:47] You can clearly see how wet the soil became after that cycle and it wouldn't it wouldn't match up.
[00:14:57] So that's just one example of seeing data that you might not expect trying to understand what could be going on making a making an observation thinking about it wondering about it making a theory testing it trying to get in having a good time.
[00:15:11] And without these types of tools and without this type of data.
[00:15:17] This wouldn't be you couldn't do this you could make some theories but you wouldn't be able to prove your theories to see if what if the observation and what your theory is about the observation is true because there's no way to measure it.
[00:15:34] And so to me the first step the single greatest opportunity with these tools is to learn is to use them like an experiment for you.
[00:15:47] To learn and grow and improve let's just say in this case improve as an irrigator and there's probably many many examples we could take outside of the irrigation world but hey this is the sprinkler podcast so my first thought is okay what would it look like if every year
[00:16:02] or in the United States or in the world tomorrow how to soil moisture sensor and they went and stuck it out in the landscape and they set a watering schedule like they normally do.
[00:16:16] And they came back here what they didn't you have to come back they looked at the results after two weeks I guarantee you everybody would learn something the speed at which we can learn and become better irrigators would improve so rapidly if we just say that we can't do anything.
[00:16:31] So if we just started deploying these tools not to immediately connect to a control or automate the system because it's kind of like in order to do that first you sort of have to know what you're doing because these tools are just they're not magic ones you don't put a magic
[00:16:48] or moisture sensor in the ground and press a button and that it just magically works kind of have to know what you're looking at and the only way to know what you're looking at and how it works is to start playing with it or experimenting with it so I think that's really what I wanted to share with you today is just my thoughts on using technology and these tools that are becoming available.
[00:17:11] Use them in their business in your business but use them as an experiment to try to learn something so that you can understand how they work and how to make that tool work for you.
[00:17:23] And I think that if we can make technology affordable and readily available so that it can be easily obtained and deployed by every irrigator the rate at which we would improve even just our basic schedule.
[00:17:40] We would never see the rate of improvement like we would if we started deploying these tools right away and learning so that's all I have guys thanks again for listening to the sprinkler nerd show.
[00:17:56] I appreciate connecting with all of you if you feel like you want to reach out my cell phone is always open you're welcome to send me a text message my number is 208 908 3229 and love connecting with you guys thanks so much for all the fantastic questions that you asked for being curious and inquisitive willing to learn experiment take a few risks and improve what you're doing.
[00:18:23] That having awesome weekend will catch you next week on another episode of the sprinkler nerd show bye bye.