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Feb 19

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.

Researcher holding a TEROS 12 soil sensor in front of a wheat field

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

 

Take our Soil Moisture Master Class

Six short videos teach you everything you need to know about soil water content and soil water potential—and why you should measure them together.  Plus, master the basics of soil hydraulic conductivity.

Watch it now—>

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

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

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Jan 11

Water holding and temperature patterns of canopy soil in an old-growth forest

The deadline is fast approaching to apply for the 2019 Grant A. Harris Fellowship. The fellowship awards $10,000 in METER research instrumentation to six U.S. or Canadian graduate students studying any aspect of agricultural, environmental, or geotechnical science.

Camila Tejo Haristoy using METER soil moisture and temperature sensors

(Image source: https://vimeo.com/69136931)

Camila Tejo Haristoy, former University of Washington grad student, was a Grant A. Harris Fellowship winner. She used METER soil moisture and temperature sensors to study the water holding and temperature patterns of canopy soil in an old-growth Sitka Spruce forest in Washington state. Sitka Spruce tree crowns contain large accumulations of organic matter known as “canopy soil”.  These accumulations provide substrate and habitat for a broad community of plants, insects, and other arboreal species. Using tree-climbing techniques, Camila installed soil moisture sensors in the canopy soils of spruce trees from an old-growth stand in the Olympic Peninsula, Washington.

This study characterized for the first time environmental conditions associated with soil mats within the crown of spruce trees, providing a framework for understanding the distribution and activity of epiphytic plants, nutrient dynamics, and associated canopy organisms.

Watch the documentary

Watch a fascinating 7-minute documentary of Camila’s interesting and exciting research. The documentary description: “Camila spends long rainy days climbing into treetops, taking temperature and moisture measurements, and collecting soil and plant samples. In the process, she interacts with a seldom seen, barely understood, and lushly beautiful environment.” (source https://vimeo.com/69136931)

Watch the video 

Recharge your research

Apply for the Grant A. Harris Fellowship today.

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

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

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Dec 11

What’s next for Fukushima?

Shortly after the Fukushima disaster, we donated environmental sensors to Dr. Masaru Mizoguchi, a scientist colleague at the University of Tokyo, to help him contrive a more environmentally friendly method to rid rice fields in the villages near Fukushima of the radioactive isotope cesium 137.

Fukushima rice patties

Scientists continue to search for ways to prevent the recontamination of the rice paddies.

Since then, his efforts, along with the efforts of a team of scientists and citizens, have made the rice grown in the paddies near the disaster site safe for human consumption. But questions and challenges remain. For instance, what will happen to the contaminated soil surrounding the decontaminated area? Will it settle in nearby stream beds, eventually contaminating the rice paddies? And what kind of erosion will come from the nearby tree-covered and clearcut hillslopes?

Recently, our scientists and videographers visited the villages near Fukushima to film some of the progress being made. Watch the video, and read the full story here.

See performance data for the ATMOS 41 weather station used in Fukushima research.

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

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

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Nov 7

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.

METER ZL6 Data Logger providing information to a researcher

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”—>

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Sep 10

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.

ZL6 Data Logger in a wheat field

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”—>

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

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Aug 7

5 ways site disturbance impacts your data—and what to do about it

Lies we tell ourselves about site disturbance

When it comes to measuring soil moisture, site disturbance is inevitable. We may placate ourselves with the idea that soil sensors will tell us something about soil water even if a large amount of soil at the site has been disturbed. Or we might think it doesn’t matter if soil properties are changed around the sensor because the needles are inserted into undisturbed soil.

Rolling farm fields

The key to reducing the impact of site disturbance on soil moisture data is to control the scale of the disturbance.

The fact is that site disturbance does matter, and there are ways to reduce its impact on soil moisture data. Below is an exploration of site disturbance and how researchers can adjust their installation techniques to fight uncertainty in their data.

Non-disturbance methods don’t measure up—yet

During a soil moisture sensor installation, it’s important to generate the least amount of soil disturbance possible in order to obtain a representative measurement. Non-disturbance methods do exist, such as satellite, ground-penetrating radar, and COSMOS. However, these methods face challenges that make them impractical as a single approach to water content. The satellite has a large footprint, but generally measures the top 5-10 cm of the soil, and the resolution and measurement frequency is low. Ground-penetrating radar has great resolution, but it’s expensive, and data interpretation is difficult when a lower boundary depth is unknown. COSMOS is a ground-based, non-invasive neutron method that measures continuously and reaches deeper than a satellite over an area up to 800 meters in diameter. But it is cost-prohibitive in many applications and sensitive to both vegetation and soil, so researchers have to separate the two signals. These methods aren’t yet ready to displace soil moisture sensors, but they work well when used in tandem with the ground truth data that soil moisture sensors can provide.

Read more…

Get more info on applied environmental research in our

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

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

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Jun 25

Double Ring vs. SATURO: Two Infiltrometers Go Head to Head

The SATURO and the double-ring infiltrometer are both ring infiltrometers that infiltrate water from the surface into soils. Overall, they compare fairly well (see comparison). The main difference is how they deal with three-dimensional flow in the Kfs calculation. The SATURO uses the multiple-ponded head analysis approach to get a more direct estimation of alpha, which is used to determine how the soil pulls the water laterally. The double-ring infiltrometer uses a larger outer ring to act as a buffer from three-dimensional flow. This requires more water, and literature suggests that it doesn’t perform well. Also, with a double-ring infiltrometer, there is still a need to estimate alpha in the equations. This is typically done from a look-up table based on soil type and often results in error.

SATURO Infiltrometer which uses multiple-ponded head analysis approach

The SATURO is an automated infiltrometer which uses the multiple-ponded head analysis approach.

How do SATURO readings compare to double-ring infiltrometer readings?

We compared the SATURO with a 6-inch (15.24 cm) inner ring diameter against a double-ring infiltrometer with a 6-inch (15.24 cm) inner ring diameter and an outer ring with a 12-inch (30.48 cm) diameter.

See the results

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

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

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May 18

Hydrology 301: What a Hydraulic Conductivity Curve Tells You & More

Hydraulic conductivity is the ability of a porous medium (soil for instance) to transmit water in saturated or nearly saturated conditions. It’s dependent on several factors: size distribution, roughness, tortuosity, shape, and degree of interconnection of water-conducting pores. A hydraulic conductivity curve tells you, at a given water potential, the ability of the soil to conduct water.

Researcher measuring with the HYPROP balance

One factor that affects hydraulic conductivity is how strong the structure is in the soil you’re measuring.

For example, as the soil dries, what is the ability of water to go from the top of a sample [or soil layer in the field] to the bottom. These curves are used in modeling to illustrate or predict what will happen to water moving in a soil system during fluctuating moisture conditions. Researchers can combine hydraulic conductivity data from two laboratory instruments, the KSAT and the HYPROP, to produce a full hydraulic conductivity curve (Figure 1).

Hydraulic conductivity curve

Figure 1. Example of hydraulic conductivity curves for three different soil types. The curves go from field saturation on the right to unsaturated hydraulic conductivity on the left.  They illustrate the difference between a well-structured clayey soil to a poorly structured clayey soil and the importance of structure to hydraulic conductivity especially at, or near, saturation.

In Hydrology 301, Leo Rivera, Research Scientist at METER, discusses hydraulic conductivity and the advantages and disadvantages of methods used to measure it.

Watch the webinar below.

 

Get more info on applied environmental research in our

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

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

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Apr 21

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.

Tractor moving soil around

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”—>

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Apr 3

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.

Grapes being irrigated

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

Fruit on a tree branch

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 sensor technology. The main problem they have is that developing good sensors is hard. Most of these companies will fail before the batteries of their sensors die. Few will survive or prevail in the very competitive IoT market. Larger companies that 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 computers or smartphones, 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.

IoT Technologies Chart

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

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

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

Get more info on applied environmental research in our

Learn more

Download the “Complete guide to irrigation management”—>

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