We need to be aware of soil moisture sensors limitations, and learn how to interpret sensor data before using in decision making. It is possible to make better irrigation decisions by combining soil data that is not perfect with crop models, algorithms and optimization techniques (Kelly et al., 2021). This is, however, a topic of discussion for another article, and we are obligated to continue our efforts on developing technologies that can measure soil water content accurately. In addition, no decision support system exists today that can make good recommendations or automatic decisions based on “bad” sensor data. Emerging technologies in agriculture such as wireless sensor networks, Internet of Things (IoT) and artificial intelligence (AI) are useless without “good sensors” and “good” sensor data.
Over the last few decades, soil moisture sensors have been shrinking in size for a number of reasons:
Smaller sensor means less materials used and less manufacturing cost.
Smaller sensor makes in-soil installation easier and decreases wobble.
Smaller sensors are easier to install in rockwool blocks or pots.
Some sensor manufacturers falsely claim higher sphere of influence (SI) can compensate for smaller sensor size, so they have reduced the sensor size and increased the SI instead.
Some sensor manufacturers have no idea what an optimum size for a sensor should be.
Those who have experience with soil moisture sensors, know that sensor installation is extremely important and that they should avoid air gaps (void spaces between sensor and soil) due to installation at any cost. Air gaps can also happen or disappear due to expansion or compaction in the substate such as in coco coir or in swelling soils. Air gaps between the sensor blade, prong or rods and the substrate can result in highly erroneous moisture measurements. The question is how smaller sensors, especially with all the interest in indoor growing, have been dealing with the air gap problem?
In the following paragraphs, we will see how the sensor size and its shape can affect soil moisture sensor sensitivity to air gaps.
Smaller sensors are more sensitive to air gaps
We cannot measure the size of air gaps or their effect on sensor measurements easily. We can define air gaps in an area unit, such as cm2. This would help compare how two sensors with different dimensions are affected by air gaps. To make the comparison easier to understand, we are going to make simplifying assumptions and define a value called “air gaps fraction” as the following:
Af = Ag / Sa (1)
Where, Ag is the air gaps area (cm2), and Sa is the sensor surface area (cm2). The sensor surface area is the part of the sensor surface that is in direct contact with the soil or substrate after installation. The ideal is to have Af = 0 (Ag = 0).
It is clear that the smaller the value of Sa, the higher the value of Af, and naturally the higher the effect of air gaps on sensor measurements accuracy. A comparison between the surface areas (calculated based on the size of their sensing elements, not the sensor head that usually contains electronics) of two commercial sensors can be seen in Fig. 1. The green sensor on the left has a surface area (Sa1) that is about four times that of the white sensor on the right (Sa2). This means the same degree of air gaps between the sensor surface and the soil can potentially result in much higher water content measurement error in the sensor with smaller surface area (Sa2).
Figure 1. A comparison between the surface areas of two commercial sensors. The green sensor on the left has a surface area (Sa1) that is about four times that of the sensor on the right (Sa2). This means the same degree of air gaps between the sensor surface and the soil can potentially result in much higher water content measurement error in the sensor with smaller surface area (Sa2).
Sensor shape
A misunderstanding with soil moisture sensors is that they can be used for spot measurements by inserting them into the soil or substrate whenever needed. Unfortunately, we are limited by the technologies we have and they might not provide acceptable accuracy if used for spot measurements. Extensive field experiments using various soil moisture sensors have shown systemic underestimates in moisture measurements specially in coarse soils. This is caused by air gaps which are created when the sensor is inserted into the soil. The shape of the sensor and the material it is made from can play an important role here. Low profile probes (smaller), which are also sharper and narrower can minimize the air gaps due to installation. This is where we need to work on optimizing the design of the sensor (shape and size) and find a good balance. If the probe gets too small, we might actually increase the sensitivity to air gaps, and if it is too long/big, we will create more air gaps. Please note that even the type of sensors that come with access tube (profile probes) are sensitive to air gaps (Kafarski et al., 2019). The sensors in Fig. 1 are made up of two different materials: the green sensor is narrow with sharp tip made up of PCB, and the white sensor relies on stainless steel rods to sense moisture. Both sensors have a low profile, so the assumption is that installation introduces minimum disturbance (same degree of air gaps). However, as discussed earlier the white sensor is too small, and a higher degree of inaccuracy is expected with this type of sensor in both soil and soilless media (especially in coco coir) due to air gaps.
Calibrate sensors or give time to air gaps to disappear
If we assume that air gaps caused by installation are going to stay the same (during the time a sensor is being used) and that they have a uniform distribution, we may be able to get away with the problem through individual sensor calibration. However, sensor calibration is time- and labor-intensive. In addition, air gaps around permanent sensor installations will disappear over time (Reeves and Smith, 1992), which will render the calibration useless. Please also note that in-lab sensor calibrations by the sensor manufacturer is not helpful in anyway, because of the nature of this problem. So do not waste your money on that. A better approach is to bury the sensor (recommend in soil and coco coir) and give the soil time (sometimes a growing season) to settle and then start taking measurements. The problem with air gaps is more pronounced if a small sensor (especially with short steel rods) is used to monitor coco coir moisture. Coco coir tends to have a fluctuating density (as a result of expansion, contraction etc. following hydration/dehydration cycles), so the sensor can quickly lose its contact with the substrate (air gaps?). Small sensor also means that it is more sensitive to the moisture distribution non-uniformity and it might read very dry (might be true in that part of the soil), while most of the substrate is very wet. If the sensor is too small, sensor burial might not improve moisture measurements accuracy. A sensor with a larger surface area is more accurate under the same conditions.
Large volume of influence cannot compensate for small sensor size
A soil moisture sensor’s sphere of influence (SI) is simply the volume of soil that is sensed using the electromagnetic field (EM) produced by the sensor. The influence of this field decreases with distance from the probe surface. Some sensor manufacturers claim that they have solved the so-called “air gaps problem” by increasing the sensor's SI, but this is a false claim. Increased sensor SI cannot compensate for decreased sensor length or solve the air gaps problem. In fact, air gaps can easily make the larger SI useless. If there are air gaps, most of the electromagnetic wave (no matter how powerful the EM) will not be able to penetrate the substrate (abrupt change in relative dielectric permittivity can reflect EM energy) and the higher the sensor working frequency (the case in sensors with larger SI) the worse the problem. It is interesting to note that the same principle is used in ground penetrating radars to map geological structures and distribution of porosity and fluids.
A dielectric soil moisture sensor is an antenna that is installed in the soil rather than in the air. The [inexpensive] sensor cable can act as the extension of this antenna, interfere with the sphere of influence, and therefore cause fluctuations in sensor readings (referred to as “cable noise”). The sensor cable can sense moisture, and a larger volume of influence means the cable is going to interfere with the readings even more. We need to reduce EM interference (EMI) for FCC regulatory compliance, so there is a limit to how much radiation the sensor is emitting (or how large its volume of influence can be). In addition, it is desirable to keep the power consumption of the sensor low, which translates into a smaller volume of influence. Noisy soil moisture readings due to cable interference may appear mysterious and cause a lot of headaches. In recent years, some manufactures have added snap-on ferrite core to the sensor cable (sometime as big as the sensor itself) to minimize the noise caused by the aforementioned sources. Unfortunately, most manufactures and their customers are not even aware of this problem and the sensors lack any type of noise suppressors.
Famous TDR does not perform better than FDR sensors
Whenever there is a talk of soil moisture sensors, you might hear someone saying “TDR is the best!” If you ask them why, they might simply answer “everybody says so!” Interestingly enough, there are so many publications that point at the many weaknesses of TDR such as sensitivity to temperature (Osroosh, 2020a) and air gaps, on the top of being an expensive soil moisture measurement device. TDR as a tool for soil moisture measurements is at least 40 years old and we have had more than enough time to inspect it from every possible angle.
There is an extensive literature on the severity of air gaps effect on TDR water content sensor measurements. Just a few publications are listed in the references section as examples (Kafarski, et al., 2019; Reeves and Smith, 1992; Siddiqui and Drnevich, 1995; Sakaki, 2011; Perrson and Berndtsson, 1998). Numerical analysis by Persson and Dahlin (2010) has shown that 90% of the TDR sensor measurement area only extended to about 10 mm from the probe surface, meaning that TDR was very sensitive to air gaps (close to the sensor surface) forming during the installation. In an experiment by Sakaki (2011), longitudinal air gaps caused up to 71% underestimation in the dielectric constant (K) for a typical air gap of up to only ~0.3 mm!
Conclusions
optimized sensor size and shape. During the last forty years, a myriad of soil moisture sensors in different shapes and sizes have been introduced to agriculture. However, the literature is still reporting the same air gaps problem with soil moisture sensors. It is clear that soil moisture sensor manufacturers must revisit their designs and work closely with scientist and universities to solve this problem. The size and shape of soil moisture sensors need optimization that leads to a larger probe surface area that maximizes contact with the substrate and less sensitivity to air gaps.
Alternative approaches to soil sensors. We also need to take alternative approaches for soil moisture estimations and irrigation scheduling more seriously. Automatic plant-based methods such as proximal remote sensing using thermal IR sensors have been promising (Osroosh, 2020b) and has the potential to even be used in controlled environment agriculture. However, like soil moisture sensors, thermal sensors come with their own limitations and need to be combined with robust crop models and algorithms.
References
Kafarski, M., Majcher, J., Wilczek, A., Szyplowska, A., Lewandowski, A., Zackiewicz, A., Skierucha, W., 2019. Penetration Depth of a Soil Moisture Profile Probe Working in Time-Domain Transmission Mode. Sensors, 19(24): 5485.
Kelly, T.D., Foster, T., Schultz, D.M., Mieno, T., 2021. The Effect of Soil-moisture Uncertainty on Irrigation Water Use and Farm Profits. Advances in Water Resources 154(7): 103982.
Osroosh, Y., 2020a. Why Soil Temperature Fluctuations Result in Inaccurate Soil Moisture Measurements? Duruntashlab.com/blog, Mar 22.
Osroosh, Y., 2020b. Can Plant Measurements Accurately Determine Available Soil Moisture in the Root Zone? Duruntashlab.com/blog, Aug 29.
Perrson, M., Berndtsson, R., 1998. Noninvasive water content and electrical conductivity laboratory measurements using time domain reflectometry. Soil Science Society of America J., 62: 1471–1476.
Persson, M., Dahlin, T., 2010. A profiling TDR probe for water content and electrical conductivity measurements of soils. Eur. J. Soil Sci. 61: 1106–1112.
Reeves, T.L., Smith, M.A., 1992. Time domain reflectometry for measuring soil water content in range surveys. J. Range Manage. 45: 412–414.
Siddiqui, S.I., Drnevich, V.P., 1995. A new method of measuring density and moisture content of soil using the technique of time domain reflectometry. Technical Report No. FHWA/IN/JHRP-95/09, Purdue University, USA.
Sakaki, T., 2011. Effect of gaps around a TDR probe on water content measurement: Experimental verification of analytical and numerical solutions. Environmental Science and Engineering Division, Colorado School of Mines, Golden, Colorado, U.S.A.