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Posts from the ‘Hydrology’ Category

Feb 25

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Irrigation and Climate Impacts to the Water-Energy Balance of the WI Central Sands (Part II)

Due to controversy over the growing number of high capacity wells in the Wisconsin Central Sands, University of Wisconsin PhD student, Mallika Nocco, is researching how agricultural land use, irrigation, and climate change impact the region’s water-energy balance (see part I).  This week, read about her challenges installing lysimeters below the root zone, how she used a GPS system that can find the lysimeters within a half-inch of accuracy, and her surprising conclusions.

Irrigation sprinkler line set up in a grassy field

This relatively small ecological region has gone from 60 high capacity wells in 1960 to over 2,500 today.

Below the Root Zone

Nocco says getting the lysimeters below the root zone was a major challenge.  “We tried a couple of things, but we settled on installing all the lysimeters with an 18-inch auger that would drill a hole slightly bigger than the whole lysimeter.  We dug an 80 cm trench to the top of the monolith zone. Then, we pounded the drain gauge divergence control tube to 1.4 m to obtain an intact monolith, wherever it was possible to do so. We also stratified soil moisture sensors at 10, 20, 40, and 80 cm.  We used heavy equipment to slowly lift out the monolith, dig out the soil below, and place it back in, keeping  track of all of the different soil horizons, and backfilled as close to the bulk density as we could.”

Researcher filling a hole with dirt and a tube with dirt

Passive capillary lysimeter installation

Finding the Lysimeters with GPS

Typically, scientists bury lysimeters close to the edge of the field so they are easy to locate, but Nocco was concerned that they would prejudice their data due to the donut effect of center pivot irrigation: more irrigation hits the center of the field with less irrigation toward the edges. She comments, ”When I installed the first ten lysimeters, I had not yet come up with a way to find everything. Those instruments are all about 15 meters from the field edge so that I could triangulate measurements and find them during cultivation.  But then I met an extension scientist at the university who had access to an RTK GPS system, which can locate instrumentation within a half-inch of accuracy.  With his help and training, we were able to install the rest of the lysimeters at more random spots throughout the field.”

Irrigation sprinkler line set up in a pastor or field

Nocco was concerned that they would prejudice their data due to the donut effect of center pivot irrigation.

Surprising Conclusions

Nocco says that ET and differences in crop physiology do not explain or account for all of the variability that she saw in groundwater recharge.  Her team did a particle size analysis on the soils adjacent to the lysimeters, and she comments, “We thought that the greater the relative sand content in the soils, the more recharge we would have seen, but what we are seeing is the opposite.  The particle size analysis reveals a negative linear correlation between potential recharge and sand content. The more silt there is in these lysimeters, the more volume of recharge.  What I’m curious about now is if we’re seeing a greater volume of recharge in the siltier spots from flux convergence.  I’m trying to obtain the time series data from the pressure transducers to see if maybe the sandier areas had less potential recharge, but perhaps drained faster.  I have seen a correlation between antecedent soil moisture content and particle size (with no correlation based on crop type).  So it also looks like the siltier soils are holding more water when the rain comes through.”

What’s Next?

Eventually, Nocco plans to use field-generated estimates of groundwater recharge and ET to parameterize and validate a dynamic, agroecosystem model, Agro-IBIS, simulating hydrological responses to climate and land use changes over the past 60 years. Nocco will then share the water-energy budgets and water quantity/climate simulations with stakeholders in the Wisconsin Central Sands area.

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

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Feb 17

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Irrigation and Climate Impacts to the Water-Energy Balance of the WI Central Sands (Part I)

Due to controversy over the growing number of high capacity wells in the Wisconsin Central Sands, University of Wisconsin PhD student, Mallika Nocco, is researching how agricultural land use, irrigation, and climate change impact the region’s water-energy balance.  She and her team have uncovered some surprising results.

Fisher women leans in for a kiss with a class 1 trout she caught

A class 1 trout stream has sufficient natural reproduction to sustain populations of wild trout at or near carry capacity.

Water Use Debate

There are class 1 trout streams in the Central Sands region, and some people worry that the increasing number of high capacity wells used for agriculture will reduce the water levels in those streams.  “Lake Huron has lost about 11 feet of water since 2000,” says one resident of the Central Sands area, “and water levels are continuing to drop.” In 2008, the small well he used to pump drinking water went dry, and he blames the high capacity wells.” (Aljazeera America)  On the other side of the debate, agriculture irrigated by these wells is extremely valuable to the state, and growers have taken quite a bit of time to understand the water cycle and their role in it. You can read about their water management goals and accomplishments here.

Updating Former Research

Irrigated agriculture wasn’t prevalent or profitable in the Wisconsin Central Sands until groundwater irrigation with high capacity wells became feasible in the 1950s.  Since then, this relatively small ecological region has gone from 60 high capacity wells in 1960 to over 2,500 today.

Mallika Nocco is studying potential groundwater recharge from irrigated cropping systems that use the wells, hoping to understand if the irrigation water is lost or returned to the groundwater.  She says, “Until now, we’ve been relying on models validated by two lysimeters in the 1970s. Champ Tanner (one of the fathers of environmental biophysics) designed the weighing lysimeters, and they were very accurate, but we wanted to do a larger scale study with multiple crops to get a handle on interannual variability and to improve our understanding of recharge in the region so we can do a better job of managing irrigation and groundwater.”

Lysimeter installation into a dirt and a field

Lysimeter installation into actively managed fields presented challenges that the research team had to overcome.

Measuring Recharge

Nocco used twenty-five drain gauge lysimeters to capture vadose zone flux under potato and maize cropping systems.  She monitored soil water (and temperature) flux by stratifying water content sensors from the soil surface to a depth of 1.4 meters.  She also estimated evapotranspiration (ET) using a porometer to measure stomatal conductance, in addition to obtaining micrometeorology, leaf area index, and gas exchange measurements.

Nocco and her team had to put their sensors in to avoid cultivation, so they extended the drain gauge PVC that comes up to the soil surface and removed it any time there was major fieldwork, whether it was tillage or planting, so that the area over the lysimeter got the same treatment as the rest of the agricultural fields.

Below the Root Zone

Nocco says getting the lysimeters below the root zone was a challenge.  Next week, read about how she solved that challenge, how she used a GPS system to find the lysimeters within a half-inch of accuracy, and about her surprising conclusions.

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

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Jan 7

Using The Salt Balance Approach to Measure Soil Drainage

Understanding the amount of drainage that comes out of the bottom of the root zone and infiltrates into groundwater recharge is a very difficult measurement to do well. Drain gauges do a good job of it but on a small scale. Large lysimeters do an even better job, but are extremely expensive and complex.  There is an economical alternative, however, called the salt balance approach to measuring drainage.

Soil profile underneath canola

Soil profile underneath canola

The Salt Balance Approach

Since the majority of non-fertilizer salts in the soil solution don’t get taken up by plants, this salt can be used in soil as a conservative tracer.  This means that whatever salt is applied to the soil through rainfall or irrigation water is either stored in the soil or leaches through the profile with the soil water, enabling us to use conservation of mass in our salt balance analysis. The electrical conductivity of water (ECw) is directly proportional to the salt concentration, so ECw can be used in place of salt concentration in this analysis.  If you measure the EC of the water that’s applied to the soil, either through irrigation or precipitation,  as well as the EC of the water that’s coming out of the bottom of your profile, then you can calculate what fraction of the applied water is being transpired by the plants, and what fraction is draining out of the bottom.  This method is useful for measuring water balance at field sites.

To illustrate this concept, let’s work through a simple example.  A particular field received 40 cm of water through precipitation and irrigation.  The average ECw of the precipitation and irrigation water is 0.5 dS/m.  Measurements of ECw draining from the soil profile below the root zone indicate an ECw of 2.0 dS/m.  The drainage or leaching fraction can be easily calculated as :

ECw(applied) / ECw(drained) = 0.5 dS/m / 2.0 dS/m = 0.25

The amount of water drained can also be easily calculated as:

Leaching fraction * applied water = 0.25 * 40 cm = 10 cm

Measuring Pore Water EC (ECw)

One challenge to this approach is the measurement of water electrical conductivity itself.  Bulk EC is a relatively simple measurement, and several types of soil water content sensors measure it as a basic sensor output.  However, the electrical conductivity of water, called pore water EC (ECw), is more complex.  Pore water EC requires that it be either estimated from the bulk EC and soil water content or that a sample of pore water be pulled from the soil matrix and measured.  When estimated, pore water EC can contain considerable error.  In addition, removing a water sample and measuring the pore water EC is not easy. 

To learn more about measuring EC, read our EC app guide.

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

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Nov 9

Screening for Drought Tolerance

Screening for drought tolerance in wheat species is harder than it seems.  Many greenhouse drought screenings suffer from confounding issues such as soil type and the resulting soil moisture content, bulk density, and genetic differences for traits like root mass, rooting depth, and plant size. In addition, because it’s so hard to isolate drought stress, some scientists think finding a repeatable screening method is next to impossible. However, a recent pilot study done by researcher Andrew Green may prove them wrong.

An automatic irrigation setup with green plants sticking out

Automatic Irrigation Setup

The Quest for Repeatability

Green says, “There have been attempts before of intensively studying drought stress, but it’s hard to isolate drought stress from heat, diseases, and other things.”  Green and his advisors, Dr. Gerard Kluitenberg and Dr. Allan Fritz, think monitoring water potential in the soil is the only quantifiable way to impose a consistent and repeatable treatment. With the development of a soil-moisture retention curve for a homogeneous growth media, they feel the moisture treatment could be maintained in order to isolate drought stress.  Green says, “Our goal is to develop a repeatable screening system that will allow us to be confident that what we’re seeing is an actual drought response before the work of integrating those genes takes place, since that’s a very long and tedious process.”

Why Hasn’t This Been Done Before?

Andrew Green, as a plant breeder, thinks the problem lies in the fact that most geneticists aren’t soil scientists. He says, “In past experiments, the most sophisticated drought screening was to grow the plants up to a certain point, stop watering them, and see which ones lived the longest. There’s never been a collaborative approach where physiologists and soil scientists have been involved.  So researchers have imposed this harsh, biologically irrelevant stress where it’s basically been an attrition study.” Green says he hopes in his research to use the soil as a feedback mechanism to maintain a stress level that mimics what exists in nature.

Data acquisition a cabinet setup for green's expanded experiment

Data Acquisition Cabinet setup for Green’s expanded experiment.

The Pilot Study

Green used volumetric water content sensors, matric potential sensors, as well as column tensiometers to monitor soil moisture conditions in a greenhouse experiment using 182 cm tall polyvinyl chloride (PVC) growth tubes and homogenous growth media. Measurements were taken four times a day to determine volumetric water content, soil water potential, senescence, biomass, shoot, root ratio, rooting traits, yield components, leaf water potential, leaf relative water content, and other physiological observations between moisture limited and control treatments.  

Soil Media:  Advantages and Disadvantages

To solve the problem of differing soil types, Andrew and his team chose a homogeneous soil amendment media called Profile Greens Grade, which has been extensively studied for use in space and other applications.  Green says, “It’s a very porous material with a large particle size.  It’s a great growth media because at the end of the experiment you can separate the roots of the plant from the soil media, and those roots can be measured, imaged, and studied in conjunction with the data that is collected.”   Green adds, however, that working with soil media isn’t perfect: there have been hydraulic conductivity issues, and the media must be closely monitored.

What’s Unique About this Study?

Green believes that because the substrate was very specific and his water content and water potential sensors were co-located, it allowed him to determine if all of his moisture release curves were consistent.  He says, “We try to pack these columns to a uniform bulk density and keep an eye on things when we’re watering, hoping it’s going to stay consistent at every depth.  So far it’s been working pretty well: the water content and the water potential are repeatable in the different columns.”

Irrigation setup for the expanded study with research data cabinet

Entire Irrigation setup for the expanded study.

Plans for the Future

Green’s pilot study was completed in the spring, and he’s getting ready for the expanded version of the project:  a replicated trial with wild relatives of wheat. He’s hoping to use soil moisture sensors to make automatic irrigation decisions: i.e. the water potential of the columns will activate twelve solenoid valves which will disperse water to keep the materials in their target stress zone, or ideal water potential.

The Ultimate Goal

The ultimate goal of Green’s research is to breed wild species of wheat into productive forms that can be used as farmer-grown varieties. He is optimistic about the results of his pilot study.  He says, “Based on the very small unreplicated data that we have so far, I think it is going to be possible to develop a repeatable method to screen these materials.  With the data that we’re seeing now, and the information that we’re capturing about what’s going on below ground, I think being able to hold these things in a biologically relevant stress zone is going to be possible.”

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Sep 19

Assessing Erosion Risk after Forest Fires

As forest fires throughout the Northwest die down, one scientist’s work is just beginning.  An article from our archives details the important research that takes place in the aftermath of the flames:

Forest on fire with sun shining through the smoke

In 2015, over eight million acres of forest burned in the United States. Major fires burned in five northwestern states: Washington, Idaho, Montana, Oregon, and California.

Flagstaff, Arizona is typically a dry place. But in August 2010, churning rivers flowed down roadways and around—and through—homes in the Flagstaff area. The floods were caused by a fire—the 15,000 acre Shultz fire that raged around Flagstaff from April to July, 2010.

One might not ordinarily think of a fire causing a flood, but to Forest Service research engineer Dr. Peter Robichaud, the setup is classic. “After a fire, you’ve changed the hydrology of the hillside,” he says. “Normally in an unburned area, rain gets soaked up by forest floor material on the ground and then it soaks into the soil. After a fire goes through, there’s no forest floor material to soak up the water and the soil may become water repellent due to heat from the fire.”

Reduced infiltration means increased runoff and erosion. As Robichaud explains, “If you have a steep slope and high velocities, along with very erodible soil, things converge rather quickly and you can generate debris flows and mudslides.  It’s not just a 100% increase. It’s orders of magnitude increase.”

Burned trees standing in a swampy area covered in water

After a fire, soil commonly becomes hydrophobic, just one factor in increased runoff.

One of Robichaud’s research interests is in designing a model for post-fire erosion. The model helps land managers and assessment teams in the field to evaluate the risks such erosion might pose. “It lets them see what might be affected if they have an erosion event,” he says.

“Is it going to affect the municipal water supply, affect a road crossing, an interstate highway, a school that happens to be at the mouth of a canyon? Once they can estimate the amount of erosion that might occur, they can use the model to help pick treatments to reduce the risk.”

Often practitioners will use the model to establish an early warning system to areas that will be affected.

Along with developing the model, Robichaud has also looked for ways to help postfire assessment teams gauge the water repellency of the soil after a fire. Historically, soil in a burned area was evaluated using the water drop penetration time test, or WDPT. Team members would place a drop of water on the surface of the soil and time how long it took to be absorbed. This seventies-era test was easy to do in the field, but Robichaud wanted something more representative.

Trees and a street covered in a pool of water

One of Robichaud’s research interests is in designing a model for post-fire erosion to help land managers and assessment teams in the field evaluate the risks such erosion might pose.

“I’ve always felt we could do a better job of characterizing the changes in soil condition,” he says. “[The WDPT] doesn’t really represent the physical process of the water infiltrating, because you put a single drop of water on the surface… The ideal method is a rainfall simulator, but it’s not practical in the field. [You] can’t expect every assessment team after a fire to set up a rainfall simulator for a couple of weeks.”

As he looked for alternatives, Robichaud started using a Mini Disk Infiltrometer. Practitioners all over the world use infiltration measurements along with Robichaud’s model of post-fire erosion to assess the impacts of a fire, predict erosion, and make plans to manage and reduce the associated risks. Robichaud’s online Erosion Risk Management Tool allows researchers and assessment teams alike to use scientifically solid analysis. He’s currently involved in refining and validating the model, improving assessment techniques, using remote sensing technology to perform assessments, and looking at alternative post-fire treatment options to reduce erosion risk, among other things.

To see what Dr. Robichaud’s been up to recently, read his 2014 paper, The temporal evolution of wildfire ash and implications for post-fire infiltration, published in the International Journal of Wildland Fire.   Find out more about Robichaud’s research, methods for use of the Mini Disk Infiltrometer for changes in infiltration characteristics after fire, or access the Erosion Risk Management Tool, by visiting the Moscow Forest Sciences Laboratory website.

Learn more about wildfire and soil moisture

See how soil moisture information could improve assessments of wildfire probabilities and fuel conditions, resulting in better fire danger ratings here.

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Sep 4

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Examining Plant Stress using Water Potential and Hydraulic Conductivity

Many scientists rely on water potential alone to measure plant water stress.  Leo Rivera, a METER soil scientist, shows how a two-pronged approach, using hydraulic conductivity as well as water potential, can make those measurements more powerful.  

Green tomato plant with three bright red tomatoes

Measuring hydraulic conductivity in nursery plants shows why plants are stressed.

Soil moisture release curves can give you incredible detail about water movement, allowing you to understand not only that plants are stressed, but WHY they are not getting the water they need.

Recently, we ran into a mystery where this method was useful.  Growers at a Georgia nursery noticed that plants growing in a particular soilless substrate were beginning to show signs of stress at about -10 kPa water potential, which is still really wet. They wanted to know why.

We decided to create the unsaturated hydraulic conductivity and soil moisture release curves  for the substrate (using the Wind Schindler technique [HYPROP lab instrument]) and found that it had a dual porosity curve: essentially, a curve with a “stair step” in it. The source of the “stair step” can be explained by considering the substrate, which was made up of bark mixed with some other fine organic materials. In the bark material there were a lot of large and small pores, but no medium-sized pores (this is called a “gap-graded” pore size distribution).  This gap in the pore size distribution reduced the unsaturated hydraulic conductivity and caused the stress. Even though there was available water in the soil, it couldn’t flow to the plant roots.

Blue crates with lots of green nursery seedlings in each crate

Nursery seedlings

That would have been pretty hard to understand without detailed hydraulic conductivity and soil moisture release curves—curves with more detail than most traditional techniques can provide.  Our measurements showed that unsaturated hydraulic conductivity can have a major effect on how available water is to plants.  Our theory about the soilless substrate was that as the roots were taking up water, they dried the soil around them pretty quickly. In a typical mineral soil, the continuous pore size distribution would allow water to flow along a water potential gradient from the surrounding area to the soil adjacent to the roots. In the bark, the roots dried the area around them in the same way, but the gap in pore size distribution created low hydraulic conductivity and prevented water from moving into the soil adjacent to the roots. This caused plants to start stressing even though the substrate was still quite wet. 

We were pretty excited about this discovery. It shows that water potential, though critical, may not always tell the whole story. Using technology to measure the full soil moisture release curve and the hydraulic conductivity in one continuous test, we discovered the real reason plants were wilting even when surrounded by water. In the past, it took three or four different instruments and several months to take these measurements.  We can now do it in a week. For more information about creating these kinds of curves, check out the app guide:  “Tools and Tips for Measuring the Full Soil Moisture Release Curve.”

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

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

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Jul 24

Lessons from the Field – Sensor Installation Considerations

In the Midwest, government incentives are sometimes provided to convert marginal lands to switchgrass, a leading choice for bio-energy feedstock production.  Michael Wine, a researcher at New Mexico Tech, wanted to investigate whether switchgrass’s deeper root systems would affect the water cycle both during and after crop establishment.  In the first stages of his investigation, he learned that many factors need to be considered when determining the optimal location for sensor installation.

Aquifer Recharge

Wine used Gee passive capillary lysimeters to determine deep drainage under natural vegetation, wheat, and switchgrass in order to improve our understanding of both the baseline water cycle and the water budget associated with a switchgrass monoculture in Woodward, Oklahoma.  He put the lysimeters and some soil moisture (capacitance) sensors into the Beaver-North Canadian River Alluvial Aquifer to look at recharge, but ran into challenges with sensor installation from the start.

Climate Considerations

One thing Wine learned was that biofuels aren’t very successful in his research location– there wasn’t enough water to support switchgrass.  He says, “Most places here may have no precipitation recharge for a great many years. But there are sites, such as sub-humid environments, where you could get a whole lot of infiltration in a very short time.” In hindsight, Wine says he “would have increased his use of preliminary data to more efficiently determine the frequency of recharge events.”

Using Preliminary Data to help Site Instrumentation

Wine learned that it’s important to think about the time constant of your system when siting instrumentation and that preliminary data are crucial. He says, “Before sensor installation, I did a chloride mass balance which helped me determine where I should install the lysimeters.”  He had been planning to put them at watersheds at the USDA-ARS Southern Plains Range Research Station, but the chloride mass balance showed there hadn’t been a recharge event at that site in the past 200 years. So he chose to install the lysimeters at the USDA-ARS Southern Plains Experimental Range, located in the Beaver-North Canadian River Alluvial Aquifer, a site with coarser soil and higher permeability.

Wine also thinks numerical modeling could have been useful in determining placement. “In siting the instruments, numerical modeling would’ve been a big help because we could have predicted the likelihood and frequency of recharge events.  So I think preliminary data, numerical modeling, and environmental tracers can all help in terms of where to place these research devices.”

a baby calf walking towards the photographer with other cows, who are collectively walking through a field

After long absences, Wine often had to repair damage caused by cattle.

Proximity to Research Site

Another challenge was that the researchers were located in Stillwater, Oklahoma, far from their research site. The experiment was protected by fences, but after long absences,  Wine often had to repair damage caused by cattle.  “I really need to hand it to these instruments that can be trampled numerous times by cows and the battery compartment filled up with water,” Wine says. “They just needed to be dusted off, dried out, new batteries inserted, and they worked great.”  Wine adds that researchers need to consider the distance between their office and their research site because in his case, the cows would have been less of an issue if it had been a fifteen-minute drive instead of three hours each way. He adds, “Selecting a nearby research site would have allowed us additional flexibility in our experimental methods; for example, with a nearby site we could have more easily conducted artificial rainfall simulations if a particular year turned out to be too dry for natural recharge events to occur.”

Proper Siting of Equipment Makes a Difference

Once Wine determined the correct placement of his instruments, he was finally able to get some interesting data.  He says, “There are large pulses of focused recharge that do occur in certain places, and we quantified one of those pulses following a storm with one of the lysimeters.  We’ve got about a year’s worth of data. Since we installed lysimeters at adjacent upland (diffuse recharge) and lowland (concentrated recharge) sites, we succeeded in observing large differences between the recharge fluxes at these nearby sites.”  Wine’s plan is to see if he can replicate the results of the lysimeter experiment using numerical modeling, because he says, “the data look reasonable, but I’d like to confirm the measurements due to the cows playing havoc with our site.”  Wine is excited as these lysimeters are yielding the first direct physical measurements of diffuse and concentrated groundwater recharge in the Beaver-North Canadian River Alluvial Aquifer, and he’s optimistic that his numerical modeling will match this unique time series of direct physical measurements of groundwater recharge.

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Apr 4

Double Ring Infiltrometers Versus DualHead Infiltrometers

Several years ago I had the chance to work at the USDA ARS Research Watershed in Riesel, Texas. The goal of my research was to look at the effects of land use and landscape position on water infiltration.  Within the research watershed there is preserved and maintained native prairie, improved pasture, and conventional tilled areas, which have been in existence for 75 years. Thus we were able to use infiltrometers to study the long-term effects of those different land uses, along with the effect of landscape position within the same soil type.

Double Ring Lysimeters

Texas Infiltrometer setup

My research focused on the Houston Black Soil Series, which is a clay-rich soil with a high shrink-swell capacity. This soil type has key economic importance, as it is present in much of Texas’ USDA prime farmland.  To achieve our objectives, we began by mapping soil bulk electrical conductivity using an EM38 device (electromagnetic geo-surveying instrument).  The maps we created allowed us to look for areas of variability in water content, depth to parent material, clay content, and salinity.  Then we randomly selected three zones within the catinas (full hill slope including summit, back slope, and front slope) and flagged them with GPS points.  Our goal was to make infiltration measurements at all of the landscape positions on the slope and compare them to the same landscape positions within each land use type.

We found that the native prairie had the highest infiltration rates because the soil maintained its strong structure and macropores which allowed water to conduct well through the soil.  We also found some differences by landscape position that were consistent within the different catinas.  As water would run down the catina, erosion would transport soil and organic matter off the shoulder and back slope and deposit it on the foot slopes.  Even though they were mapped as the same soil type, the differences in erosion and reduction of organic matter affected the ability of these different positions to transport water.

Double ring infiltrometer chart

We chose to customize existing double ring infiltrometers to make these measurements because there wasn’t anything automated on the market.  If I was going to conduct my research in a reasonable amount of time, I had to come up with a system where I could run a lot of measurements relatively easily.  As a result, we bought three double-ring infiltrometers and modified them with pressure sensors and some larger controlled ports.  The resulting setup was huge; the outer ring on each infiltrometer was 60 cm in diameter and the entire instrument was very heavy.  We were constantly refilling the instrument water reservoirs. In fact, this setup required so much water that we had to pull a 1,900-liter water tank on a trailer wherever we were taking measurements.

Our goal was to save time by running all three infiltrometers concurrently, but it still took a LONG time.  Even though we had automated the instruments, they required a lot of monitoring; sometimes I had to fill our 1,900-liter water tank twice in a day. One measurement at one site took anywhere from 1.5 hours to 3 hours depending on when we reached steady state. We spent so much time out in the field that we were actually caught on film in one of the Google Maps picture flyovers!   Even after all this field time, the data analysis was overwhelming, despite a relatively seamless approach to handle it all.

One huge infiltrometer setup

Our huge setup caught on google maps

I often dreamed of making a tool that would be a lot easier for me and others to use. When I joined Decagon (now METER), it gave me an opportunity to do just that.  Our design goals were to make an infiltrometer that required less water and simplified the data analysis.  We rejected the double ring design in favor of a single ring approach because research has shown that the outer ring doesn’t buffer three-dimensional flow like it’s supposed to. (Swartzendruber D. and T.C. Olson.  “Sand-model study of buffer effects in the double-ring infiltrometer” Soil Sci. Soc. Am. Proc. 25 (1961), 5-8)

We also wanted to simplify the analysis of three-dimensional flow.  With a constant head control in a single ring, there are equations that you use to correct for it.  But you have to guess at things like soil type and structure which leads to inaccuracies.  Multi-head analysis has been around for decades. It involves establishing constant water heights (heads) at multiple levels and looking at the difference in the infiltration rates to calculate the sorptivity. Thus, parameters that are normally estimated from a table can actually be measured, and infiltration results will be independent of users.

Still, there can be problems with the multiple head approach. Increasing the water height when infiltrating into a really low conductivity soil may take 1 to 2 hours to drain back to the original height. We didn’t want to make this measurement take longer than necessary, so instead of using additional water, we used air pressure to simulate higher water levels which can be added or removed very quickly.

So, thanks to the instrument hardships I endured in my past efforts to obtain infiltration measurements, we now have an easy-to-use dual-head infiltrometer (now called the SATURO), that can do the analysis of infiltration rates and saturated hydraulic conductivity on the instrument itself (it gives sorptivity and alpha, based on the soil type and structure, and makes the correction onboard).  Thus, if a scientist needs a value right away, it’s there. But, if like me, they wanted to dig deeper through the data, all the measured values can still be downloaded for more careful analysis.  Together, it’s a simple tool for both scientists and consultants who need to make these measurements.  And they won’t get caught on Google Maps like me, because they’ve had to spend their whole life in the field taking measurements.

Below is a video of the dual-head infiltrometer in action.

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Feb 23

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Are Arduinos Practical and Cost Effective?

Last spring my daughter, Sarah, needed a project for the science fair, and since she has always been interested in scientific measurements, we decided to try and figure out when it was time to water her mother’s plants. Since we’ve fielded a lot of calls from customers asking about using Arduinos (user-programmable microprocessors) lately, I thought I would kill two birds with one stone and give one a try. My preference would have been the speed and simplicity of a METER data logger, but I was curious about how practical and cost-effective this method might be for taking measurements.

Young Girl Concentrating on Helping with the Soldering

Arduino Science Project with my daughter

The Arduino is an inexpensive, user-programmable microprocessor on a circuit board that has exposed analog inputs for measuring voltages and digital ports for measuring incoming digital signals. It can also run displays and is programmed by an Arduino IDE running on your computer.

I purchased a book called Arduino Recipes that taught us the basics of Arduino programming, which was pretty straightforward. The Arduino board itself has rows of pinheaders, so I brought some of the male pinheaders from work and soldered all the wires to them, in preparation to attach the water content sensor. It looked medusa-like with all the wires coming off the pinheaders, but we could then just hook up kid-friendly snap circuits and try some elementary tests to get used to the system.

We hooked up Decagon’s (now METER) analog water content sensor (EC5)  first and started measuring. It has a really nice calibration equation supplied by METER, so we used that for a while to measure water content. We took one of mom’s dry plants and measured before and after watering and used the readings to make a linear relationship between the reading on the sensor when it was dry and the reading on the sensor when it was wet.

Small Cactus in the Window

Our biggest challenge was that Sarah wanted to display this to mom to make sure she knew when to water the plants. So she and I then had to figure out how to integrate an LCD display.

Sarah was excited to get the digital soil moisture sensor integrated because we could then measure water content AND electrical conductivity (EC) to get an idea of the fertilizer in the soil. We used my work colleague’s code to read the digital sensor output, which worked quite well.  It only took a few minutes to insert his piece in the code into our program and start reading water content. Our biggest challenge was that Sarah wanted to display this to mom to make sure she knew when to water the plants. So she and I then had to figure out how to integrate an LCD display. Luckily, all the details were on the Arduino website.  We just cut and pasted the code into our program and then did all the wiring.

Finally, we had it all put together, and we inserted the 5TE digital sensor into the pot. It worked, but the device was large and unwieldy. Mom wasn’t happy that we were putting it right in the middle of her clean living room, but Sarah pointed out that we have to make sacrifices for science, so we put the sensors in the soil, set up the display, and ran it for about a week. Sarah took water content data morning and night and watered it when it reached our “dry” point. She took the finished system to the science fair and was excited to find a few future customers.

Close up on a circuit board

The biggest challenge would be all the details in the system. We’d need a circuit board, a power supply, a data logging interface board, and a box to put it in, and if we were going to set it outside, that box would have to be waterproof.

Are Arduinos practical for use in your experiments?

It depends. Sarah and I found out that it just doesn’t take a lot to integrate a sensor into the Arduino system and be able to make measurements. However, if we were to try the above experiment long-term, the biggest challenge would be all the details in the system. We’d need a circuit board, a power supply, a data logging interface board, and a box to put it in, and if we were going to set it outside, that box would have to be waterproof. We’d also need ways to connect the sensor to the circuitry, and all these things take time and resources. For me, the take-home message was that Arduinos are a lot of fun, and might fit your application exactly the way you want. However, you’ll need time (often a lot of it) to spend making sure it’s waterproof, doing all the programming, writing a code durable enough to fit your field applications, and getting the hardware prepped. In fact, Decagon support staff take calls every week from frustrated do-it-yourselfers who’ve found this is not as easy as it seems. Thus, in my opinion, an EM50 or Campbell Scientific data logger are more practical options than an Arduino-like microprocessor.

Are Arduinos cost effective?

A lot of scientists want to make measurements out in the field with small budgets. I am certainly one of those. Arduinos are $85 versus a complete data logger that costs several hundred dollars. However, people tend to forget that things like labor even cost discrepancies.

So, if you have plenty of time, want the versatility, and you love this stuff, go ahead and make an Arduino sensor, but at the end of the day, the cost shouldn’t be a driver, because there are data loggers that can do the job of an Arduino more simply and quickly, without all the hassle.

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

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

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

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