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Posts from the ‘Data Collection & Analysis’ Category

Data deep dive: why am I seeing diurnal changes in soil moisture?

In the video below, METER soil scientist Dr. Colin Campbell discusses an often-misdiagnosed water content signal that looks like typical diurnal temperature cycling but is actually due to a phenomenon called hydraulic redistribution. He shows how easily these patterns can be seen in ZENTRA Cloud data management software.

Watch the video

 

 

 

Learn more about measuring soil moisture. Download “The researcher’s complete guide to soil moisture“.

To understand how soil moisture and soil water potential work together, download “The researcher’s complete guide to water potential.”

Soil moisture sensors aid forensic science in time-of-death estimates

Extending time of death estimates

Forensic scientists are looking at better, more accurate ways of determining the post-mortem interval, or time of death. When a human body decomposes, microbes and nematodes become abundant in the soil surrounding the body. The types and maturity of these organisms may be a means of determining the time of death, but thus far most studies have focused on short post-mortem time frames.

Scientists look for ways to increase the accuracy of long-term post-mortem interval estimates

That’s why Stacy Taylor, her advisor, Dr. Jennifer DeBruyn, and their research team at the University of Tennessee are using cutting-edge molecular techniques and classical microscopic techniques to try and extend the time frames over which this approach could be used to determine how long it’s been since victims have died. 

Monitoring dramatic soil changes   

Taylor, a winner of the National Institute of Justice Graduate Research Fellowship in STEM, working in conjunction with the UT Anthropology Research Facility, is measuring biological and chemical changes in soil composition brought about by long-term human decomposition. She says, “We are looking at a combination of soil chemistry, microbial ecology, and some of the soil animals, particularly the nematodes, to get an entire food web approach in understanding all of the nutrient cycling that is occurring in these systems. We want to look at the soil chemistry patterns and microbial/nematode succession to see if these cross-inform each other.” 

Taylor explains some of the changes in soil composition that occur during both vertebrate and invertebrate decomposition, “Basically, any time you have a decomposition event that is not composed of plant litter, it creates what’s called a “hot spot” of nutrient enrichment. Unlike plant litter, which decomposes very slowly, with a vertebrate system you have a tremendous amount of protein and fat. You also have a lot of calcium, magnesium, sodium, and potassium. And when you put a large load of these things into the soil, you get a huge change in soil organic composition, nutrient availability, and soil moisture. So you’re essentially dealing with massive changes in a very localized soil environment.”

Decomposition also changes the soil water

Taylor and her adviser Dr. Debruyn had the fairly new idea to insert METER soil moisture, temperature and electrical conductivity sensors connected to data loggers into the soil in these hot spots, to see what kind of interesting data would turn up.

The TEROS 12 is an updated version of the sensor Taylor used in her research

She says they’ve been surprised at how informative and eye-opening this has been. She explains, “These hot spots change the ionic strength of the soil water. And that is highly correlated to electrical conductivity, which is measured by the soil moisture sensors. A change in ionic strength potentially impacts the salinity of the soil. Some of those changes have been shown to persist for well over a year, which is what these soil sensors are showing. I take an hourly reading, and the sensors are producing the most amazing data.”  

Taylor says the sensors were inserted into the soil surface, so they could measure the impact the decomposition produced immediately on the upper layer of soil. They took soil cores at 16 centimeters to measure soil pH and EC, and they also used RT-1 air temperature sensors to track accumulated degree days which are based on ambient air temperature and correlate with maggot growth and development rates. 

Identifying time markers

Taylor says that soil changes (in particular EC and temperature) are not just general deviations but show clear stages as decomposition progresses through time, indicating they might be useful as time markers. She explains, “We are tracking a succession of events. These events happen at particular time points and are associated with certain decomposition stages (i.e, bloat, active decay, advanced decay, or skeletonized remains). For example, you might see traces of increased electrical conductivity followed by a drop. If that drop happens at the same stage of decomposition, over and over, then you know that you have a time marker. And when you gradually accumulate some of these time markers, that can potentially inform some of the existing estimates of how long something has been there.”

Taylor’s study is about bringing better justice and more peace to the families of crime victims.

What’s the future?

Taylor says the implications of this study will help nail down many of the intrinsic controls on the decomposition process. And once they understand that, they’ll have a better idea how to employ these estimates of post mortem interval, which will bring better justice and more peace to the families of crime victims. About the future of the research, she says, “This is the kind of study that you want to replicate at other human decomposition facilities that vary by altitudes, weather, soils, and more. You need to be able to look at a variety of environments just to see what happens.”

You can read more about Stacy’s project here.

To learn more about measuring soil moisture, download “The researcher’s complete guide to soil moisture“.

To understand how soil moisture and soil water potential work together, download “The researcher’s complete guide to water potential.”

Freshwater shrimp grown in Korean rice paddy boost grower income

In South Korea, falling rice prices threaten the livelihood of many rice growers. Recently our Korean reps told us about an experiment performed in Jinju city, Gyeongsangnam-do, South Korea, by GNARES (Gyeongsangnam-do Agricultural Research & Extension Services) to increase grower income through simultaneous freshwater shrimp, lotus plant, and rice cultivation in a paddy field.

RT-1 water temperature sensors were installed along with METER data loggers to monitor the water temperature, ensuring it was optimal for shrimp growth. Through this experiment, GNARES found that environmental conditions were good for cultivating freshwater shrimp in this area. 

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

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

Engineers Without Borders alleviates Panamanian village water security issues

Engineers Without Borders (EWB) at Washington State University in Pullman, WA has partnered with a small indigenous village located in the Comarca Ngäbe-Buglé region of Panama. The relationship between this village and EWB at WSU began in 2016 when WSU alumna Destry Seiler began living in the village as a Peace Corps volunteer hoping to help solve the community’s water security needs.

A view of the Comarca Ngäbe-Buglé taken from the village in Panama.

During the rainy season in this village, approximately 20 households have access to water through a two-inch PVC pipe that operates by gravity. It runs approximately 1.5 kilometers through the jungle from a spring source higher in the mountain to small hose spickets located close to the homes on the distribution line. The other ~80 households do not have access to the distribution line and walk to the closest river or creek up to five times a day to find water. However, during the dry season, most spring sources dry up, leaving all households in the community to walk to the diminished supply of rivers to find their water.

A view of the water line currently serving ~20 homes in the village during the rainy season.

The village initially requested assistance from the Peace Corps in order to find a year-round source of clean water. But, after living in the village for 1.5 years, Ms. Seiler could not locate spring sources that both survived through the dry season and could also reach the homes in need through a gravity fed system.

Then Ms. Seiler began thinking of groundwater as a possible new water source for the community. Unfortunately, groundwater data for the Comarca Ngäbe-Buglé was not available from the local government agency. So she decided to reach out to WSU professor, Dr. Karl Olsen, to ask for assistance with a groundwater research project, and the EWB club was formed.

The club visited the village for the first time along with Ms. Seiler and faculty mentor Dr. Karl Olsen in August 2018 to do an initial survey of water use and needs, as well as to create a first-ever map of the area. EWB will return to Panama this June 2019 to implement a solar-powered water pump requested by a section of the community to deliver water from a spring source to approximately 20 homes on the nearest ridgeline. The club will also install latrines in a nearby community. They will continue the groundwater survey of the area through more extensive mapping and perform a more advanced analysis with the support of a local hydrologic company.

EWB members and WSU students Patrick Roubicaud, Kristy Watson, Destry Seiler, Perri Piller, Rene McMinn, and Kevin Allen during their visit to Panama, August 2018.

The team will use a METER-donated ATMOS 41 weather station along with a ZL6 data logger and ZENTRA Cloud software to assist in the data collection necessary to begin mapping groundwater in the area. The weather station will record precipitation, solar radiation, vapor pressure, temperature, wind, and relative humidity data that will enable EWB to begin to quantify environmental conditions and available water supply. When combined with streamflow data from rivers in the area, groundwater availability can also begin to be estimated. Because of ZENTRA Cloud, EWB will be able to view this information near-real time as well as share it with the village to help guide their design decisions. EWB plans to install the ATMOS 41 at a nearby village school to ensure weather station security and to provide an opportunity for local students to learn about their surrounding environment in a way they have not been able to do before.

To learn more about the Panamanian village or the work EWB from WSU is doing, visit ewb.wsu.edu.

See performance data for the ATMOS 41 weather station.

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

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

Why mesonets make weather prediction more accurate

The staggering cost of Montana’s “flash drought”

Some people figured it was climate change. One statistician said it was a part of a cyclical trend for poor crop years. Whatever the cause, the 2017 flash drought that parched the entire state of Montana and most of South Dakota, severely impacted the profitability of ranchers and farmers. In western Montana, fires burned some of the largest acreages in recent history. It resulted in one of the biggest wildfire incident reports (over one-million acres) and caused virtually 100% crop loss in northeastern Montana. The U.S. Dept. of Agriculture estimated the crop loss to be in the hundreds of millions of dollars, and one question was on everybody’s mind—why did no one see it coming?

Figure 1. Montana drought conditions August 2017 (Source: Montana State Library website: https://mslservices.mt.gov/Geographic_Information/Maps/drought/)

Getting the right weather data

The 2017 Montana Dept. of Natural Resources and Conservation spring drought report indicated plenty of water: “By the end of the month, almost all drought concern was removed from the state, with the exception of Wibaux and Fallon Counties….As of May 9, 2017, Montana was 98.45% drought free.” But in late May, an abrupt shift in weather conditions led to one of the hottest, driest summers on record.

The problem, says Kevin Hyde, Montana State Mesonet Coordinator, lies not only in the need for more weather data but in obtaining the right kind of data. He says, “One of the reasons drought was missed was because we’re still thinking you measure drought by snowpack and how much water is in the river, which is really great if you’ve got water rights. But we’ve got a lot of dryland out there.”

In addition to weather monitoring, Hyde is a big proponent of adding soil moisture and NDVI measurements to each of the Montana Mesonet stations he oversees. He says, “The conventional weather station only measures atmospheric conditions. But ultimately, to make any decisions, we’ve got to know not just how much water comes into the system, but how much goes into the soil. And even that’s not enough…because what we really need to know is how the water situation is going to affect plants.”

Hyde says more data are needed to warn growers and ranchers about upcoming weather risks. He points to the fact that increasing evapotranspiration got missed leading up to the summer of 2017. “We realized that if we were looking carefully at reference ET, we might have seen it about a month earlier. What would people have done? They would have changed their calf purchases. They would have figured out what kind of forage they needed to buy. These are the types of decisions people can make if they know the information sooner.”

Was the drought over? Soil moisture illuminates the bigger picture

Heavy rains came mid-September of 2017, which led some people to believe the drought was over. However, changes in soil moisture told a different story. Very little of the rain made it into the soil. “At the Havre, MT station you can see we had some heavy precipitation events. Then we had early October snows. So people expected good soil water recharge. But at the end of the day, we didn’t get it. On Sept.15th, soil moisture sensors showed a big soil moisture response at the surface but only a marginal response at 8 inches.” The melt of early October snows onto the soil, still damp from the September rain, drained to 20 inches or more. But as the snowmelt dissipated, there was minimal net gain going into the winter.

Figure 2. Soil moisture traces at the Havre, MT weather station

Predictive models need more coverage to be effective

Typically in the U.S., the National Weather Service (a division of NOAA) puts out a network of weather monitoring stations spaced out across the country, and that data gets fed into forward-looking models that help predict the weather. Dr. Doug Cobos, research scientist at METER says, “What people are finding out is that putting in a sparse network of very expensive systems has done really well. It’s been a good thing. But the spatial gaps in those networks are a problem, especially for agriculture producers and ranchers. They need to know what’s happening where they are.”

Hyde agrees, adding that we need better predictive tools that help growers and ranchers make practical decisions based on data rather than guessing. “January 1st is when the decision has to be made—do I buy cows? Do I sell cows? Do I need more pasture? But many predictions start on April 1st. As one rancher puts it, ‘We don’t bother with Las Vegas. We sit around the dining room table at the beginning of the year and put a million dollars on one shot.’”

Mesonets improve spatial distribution

Mesonets present a practical solution for the need to fill in data gaps between large, complex weather stations. The Montana Mesonet currently has 57 stations interspersed throughout the state, and through partnerships with both the public and private sector, they’re adding more stations every year.

Figure 3. Map of MT Mesonet weather stations (source: http://climate.umt.edu/mesonet/)

At each location, the Montana Mesonet team installs METER all-in-one weather stations, soil moisture sensors, NDVI sensors and data loggers that integrate with ZENTRA Cloud: an easy-to-use web software that seamlessly integrates into third-party applications through an API. He says the system enables better spatial distribution and reliability. “When we were deciding on equipment we asked ourselves: What kind of technology should we use? It had to provide high data integrity. It had to be easy to deploy and maintain. And it had to be cost effective. There’s not a lot of people in that sector. METER systems are low profile, they’re affordable, and the reliability is there. I look at some other mesonets, and they cannot afford to build out further because they are relying on large, complex, expensive systems. That’s where the METER system comes into play.”

Figure 4. Montana Mesonet station setup (Photo credit: Kevin Hyde)

Betting on the future

The Mesonet team and its partners are excited to see how their data will mesh with the available predictive tools to be the most useful and practical for growers and ranchers throughout the state, and they realize that there is still much work to do. “It’s not enough just to get the instrumentation out there. The overall crux is: how do we build the information network, and how do we build a relationship with the producers so that we can have an iterative and interactive conversation?” says Hyde. “We know there needs to be an education in how to use and interpret the data. For example: what is NDVI, and what can we learn from it? A lot of what we need to do is translate science into practical terms.” But he adds that it doesn’t need to be perfect. “What the farmers have said to us is, ‘We don’t need exact numbers. We’re gamblers. Give us probability. Teach us what it means, and we’ll make the decision.’”

Find more information on the Montana Mesonet here.

See performance data for the ATMOS 41 weather station.

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

Why does my soil moisture sensor read negative?

How is a negative number possible?

METER soil moisture sensors measure the dielectric constant of the substrate in which they are installed. They are designed to measure soil, which has a dielectric constant of around 5.

METERTEROS 12 soil moisture sensor

Water has a dielectric of approximately 80, so if we assume that a dry soil has a dielectric of 5 (VWC = 0.00 m3/m3), then changes to the bulk dielectric read by the soil moisture sensor will be attributable to changes in water content. If you read a METER sensor in air, which has a dielectric constant of 1, you will quite naturally get a negative number.   

Improving accuracy of dielectric soil moisture sensors

There are two common causes for negative readings on a METER soil moisture sensor:  

1) Poor contact with the soil resulting from improper installation or disturbance

Air gaps next to a sensor will contribute the lower dielectric of air to the measurement resulting in an underestimation of VWC. Air gaps can arise if enough care is not taken to pack soil around the sensor body to approximate native bulk density. Sensors that have been disturbed, such as having a cable tripped over, can also develop air gaps that can result in negative results in dry soils. (To reduce the possibility of air gaps when installing METER sensors, use the new TEROS borehole installation tool

2) A calibration that is inappropriate for the soil in which the sensor is installed

If the standard mineral calibration is used, an error of ~ 3-4% can be expected in METER sensor readings. Negative numbers can be observed in oven-dry soils (by definition a VWC of 0.0 m3/m3) down to ~ – 0.02 m3/m3 with no malfunction of the sensor. The dielectric constant of the soil is assumed to be 5 and this is a valid assumption in the majority of soils of primarily mineral composition. If your soil has a different dielectric constant, such as can occur in soils with high organic matter content, then the uncertainty in your measurements will increase. This is not a large problem because METER sensors can be calibrated to match a given soil with very little investment in resources.

Want more details?  

Watch our webinar titled Why Does My Sensor Read Negative below. This webinar is designed for those who use electromagnetic sensors (capacitance/TDR/FDR) to measure soil water content. Learn about the theory behind the measurements. Dr. Doug Cobos discusses:

  • What is volumetric water content?
  • Dielectric measurement theory basics
  • Dielectric mixing models
  • Why might a sensor read a negative VWC?
  • Can a sensor really have 2% VWC accuracy for all soils?
  • Sources of error in dielectric measurement methods
  • Improving accuracy of dielectric measurements

 

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

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

How to get started with ZENTRA Cloud

Researchers need to optimize funding and maximize peer-reviewed paper output. ZENTRA Cloud’s powerful data management software works with the new ZL6 data logger to make it easier to succeed at both.

ZENTRA Cloud reduces workload by speeding up analysis, streamlining workflow, and simplifying data sharing.

Try ZENTRA Cloud now

Want to explore how ZENTRA Cloud works? Request access to a live test account.

Take a ZENTRA Cloud guided tour

Get a comprehensive look at ZENTRA Cloud’s capabilities and learn how to get started here.

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

Data collection: 8 best practices to avoid costly surprises

Every researcher’s goal is to obtain usable field data for the entire duration of a study. A good data set is one a scientist can use to draw conclusions or learn something about the behavior of environmental factors in a particular application. However, as many researchers have painfully discovered, getting good data is not as simple as installing sensors, leaving them in the field, and returning to find an accurate record. Those who don’t plan ahead, check the data often, and troubleshoot regularly often come back to find unpleasant surprises such as unplugged data logger cables, soil moisture sensor cables damaged by rodents, or worse: that they don’t have enough data to interpret their results. Fortunately, most data collection mishaps are avoidable with quality equipment, some careful forethought, and a small amount of preparation.

Before selecting a site, scientists should clearly define their goals for gathering data.

Make no mistake, it will cost you

Below are some common mistakes people make when designing a study that cost them time and money and may prevent their data from being usable.

  • Site characterization: Not enough is known about the site, its variability, or other influential environmental factors that guide data interpretation
  • Sensor location: Sensors are installed in a location that doesn’t address the goals of the study (i.e., in soils, both the geographic location of the sensors and the location in the soil profile must be applicable to the research question)
  • Sensor installation: Sensors are not installed correctly, causing inaccurate readings
  • Data collection: Sensors and logger are not protected, and data are not checked regularly to maintain a continuous and accurate data record
  • Data dissemination: Data cannot be understood or replicated by other scientists

When designing a study, use the following best practices to simplify data collection and avoid oversights that keep data from being usable and ultimately, publishable.

Read more

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

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

Lab versus in situ soil water characteristic curves—a comparison

The HYPROP and WP4C enable fast, accurate soil moisture release curves (soil water characteristic curves-SWCCs), but lab measurements have some limitations: sample throughput limits the number of curves that can be produced, and curves generated in a laboratory do not represent their in situ behavior. Lab-produced soil water retention curves can be paired with information from in situ moisture release curves for deeper insight into real-world variability.

soil water characteristic curves

Soil water characteristic curves help determine soil type, soil hydraulic properties, and mechanical performance and stability

Moisture release curves in the field? Yes, it’s possible.

Colocating water potential sensors and soil moisture sensors in situ add many more moisture release curves to a researcher’s knowledge base. And, since it is primarily the in-place performance of unsaturated soils that is the chief concern to geotechnical engineers and irrigation scientists, adding in situ measurements to lab-produced curves would be ideal.

In this brief 20-minute webinar, Dr. Colin Campbell, METER research scientist, summarizes a recent paper given at the Pan American Conference of Unsaturated Soils. The paper, “Comparing in situ soil water characteristic curves to those generated in the lab” by Campbell et al. (2018), illustrates how well in situ generated SWCCs using the TEROS 21 calibrated matric potential sensor and METER’s GS3 water content sensor compare to those created in the lab.

Watch the webinar below:

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

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

IoT Technologies for Irrigation Water Management (Part 2)

Dr. Yossi Osroosh, Precision Ag Engineer in the Department of Biological Systems Engineering at Washington State University, continues (see part 1) to discuss the strengths and limitations of  IoT technologies for irrigation water management.

Informed irrigation decisions require real-time data from networks of soil and weather sensors at desired resolution and a reasonable cost.

LoRaWAN (a vendor-managed solution see part 1) is ideal for monitoring applications where sensors need to send data only a couple of times per day with very high battery life at very low cost. Cellular IoT, on the other hand, works best for agricultural applications where sensors are required to send data more frequently and irrigation valves need to be turned on/off. Low-Power Wide-Area Networking (LPWAN) technologies need gateways or base stations for functioning. The gateway uploads data to a cloud server through traditional cellular networks like 4G. Symphony Link has an architecture very similar to LoRaWAN with higher degree of reliability appropriate for industrial applications. The power budget of LTE Cat-M1 9 (a network operator LPWAN) is 30% higher per bit than technologies like SigFox or LoRaWAN, which means more expensive batteries are required. Some IoT technologies like LoRa and SigFox only support uplink suited for monitoring while cellular IoT allows for both monitoring and control. LTE-M is a better option for agricultural weather and soil moisture sensor applications where more data usage is expected.

NB-IoT is more popular in EU and China and LTE Cat-M1 in the U.S. and Japan. T-Mobile is planning to deploy NB-IoT network in the U.S. by mid-2018 following a pilot project in Las Vegas. Verizon and AT&T launched LTE Cat-M1 networks last year and their IoT-specific data plans are available for purchase. Verizon and AT&T IoT networks cover a much greater area than LoRa or Sigfox. An IoT device can be connected to AT&T’s network for close to $1.00 per month, and to Verizon’s for as low as $2 per month for 1MB of data. A typical sensor message generally falls into 10-200 bytes range. With the overhead associated with protocols to send the data to the cloud, this may reach to 1KB. This can be used as a general guide to determine how much data to buy from a network operator.

Studies show there is a potential for over 50% water savings using sensor-based irrigation scheduling methods.

What the future holds

Many startup companies are currently focused on the software aspect of IoT, and their products lack the sensor technology. The main problem they have is that developing good sensors is hard. Most of these companies will fail before batteries of their sensors die. Few will survive or prevail in the very competitive IoT market. Larger companies who own sensor technologies are more concerned with the compatibility and interoperability of these IoT technologies and will be hesitant to adopt them until they have a clear picture. It is going to take time to see both IoT and accurate soil/plant sensors in one package in the market.  

With the rapid growth of IoT in other areas, there will be an opportunity to evaluate different IoT technologies before adopting them in agriculture. As a company, you may be forced to choose specific IoT technology. Growers and consultants should not worry about what solution is employed to transfer data from their field to the cloud and to their computer or smart phones, as long as quality data is collected and costs and services are reasonable. Currently, some companies are using traditional cellular networks. It is highly likely that they will finally switch to cellular IoT like LTE Cat-M1. This, however, may potentially increase the costs in some designs due to the higher cost of cellular IoT data plans.

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

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

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