Evaluation of methods for water and non-volatile LNAPL content measurement in porous media

Proper characterization of contaminants in subsurface helps to clean up effectively the contaminated sites. In this study, different methods were used to quantify non-volatile light non-aqueous phase liquid (LNAPL) and water from sample columns subjected to different water to LNAPL ratios. The objective of the study was to evaluate methods for porous media water and LNAPL contents analysis. The liquids were sampled from the sample columns using activated carbon pellets (ACP). Sample columns water content was also measured using soil moisture sensors. Dielectric mixing model (DMM) was evaluated for the estimation of LNAPL content after water and LNAPL contents of the sample columns were determined through gravimetric analysis method. The result shows that it was possible to sample both water and LNAPL using ACP proportionally but with high standard deviations. It also shows that more liquid was sampled from sample columns subjected to only one liquid compared to sample columns subjected to two liquids. On the other hand, analysis of water and LNAPL using gravimetric analysis method gave the best result although the presence of LNAPL resulted in underestimation of water content at higher LNAPL contents. Meanwhile, the presence of LNAPL modified the bulk relative permittivity (εa) of the sample columns and resulted in overestimation of water contents measured using soil moisture sensors at higher LNAPL content. The modification of εa was used for the estimation of LNAPL using DMM. The evaluation of the model with known water and LNAPL contents and in estimating the LNAPL content of the other sample columns shows that the model could be used for the proper estimation of LNAPL in porous media.

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Soil Structure and Texture Effects on the Precision of Soil Water Content Measurements with a Capacitance- Based Electromagnetic Sensor

Transactions of the ASABE ◽

10.13031/trans.13496 ◽

2020 ◽

Vol 63 (1) ◽

pp. 141-152

Author(s):

Jasreman Singh ◽

Derek M. Heeren ◽

Daran R. Rudnick ◽

Wayne E. Woldt ◽

Geng Bai ◽

...

Keyword(s):

Soil Moisture ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Sensor Calibration ◽

Soil Water Depletion ◽

Undisturbed Soil ◽

Water Depletion ◽

Soil Moisture Sensors ◽

Electromagnetic Sensor

HighlightsCapacitance-based electromagnetic soil moisture sensors were tested in disturbed and undisturbed soils.The uncertainty in estimation of soil water depth was lower using the undisturbed soil sample calibrations.The uncertainty in estimation of soil water depletion was lower than the uncertainty in volumetric water content.Undisturbed calibration of water depletion quantifies water demand with better precision and avoids over-watering.Abstract. The physical properties of soil, such as structure and texture, can affect the performance of an electromagnetic sensor in measuring soil water content. Historically, calibrations have been performed on repacked samples in the laboratory and on soils in the field, but little research has been done on laboratory calibrations with intact (undisturbed) soil cores. In this study, three replications each of disturbed and undisturbed soil samples were collected from two soil texture classes (Yutan silty clay loam and Fillmore silt loam) at a field site in eastern Nebraska to investigate the effects of soil structure and texture on the precision of a METER Group GS-1 capacitance-based sensor calibration. In addition, GS-1 sensors were installed in the field near the soil collection sites at three depths (0.15, 0.46, and 0.76 m). The soil moisture sensor had higher precision in the undisturbed laboratory setup, as the undisturbed calibration had a better correlation [slope closer to one, R2undisturbed (0.89) > R2disturbed (0.73)] than the disturbed calibrations for the Yutan and Fillmore texture classes, and the root mean square difference using the laboratory calibration (RMSDL) was higher for pooled disturbed samples (0.053 m3 m-3) in comparison to pooled undisturbed samples (0.023 m3 m-3). The uncertainty in determination of volumetric water content (?v) was higher using the factory calibration (RMSDF) in comparison to the laboratory calibration (RMSDL) for the different soil structures and texture classes. In general, the uncertainty in estimation of soil water depth was greater than the uncertainty in estimation of soil water depletion by the sensors installed in the field, and the uncertainties in estimation of depth and depletion were lower using the calibration developed from the undisturbed soil samples. The undisturbed calibration of soil water depletion would determine water demand with better precision and potentially avoid over-watering, offering relief from water shortages. Further investigation of sensor calibration techniques is required to enhance the applicability of soil moisture sensors for efficient irrigation management. Keywords: Calibration, Capacitance, Depletion, Irrigation, Precision, Sensor, Soil water content, Structure, Uncertainty.

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Response of Two Inexpensive Commercially Produced Soil Moisture Sensors to Changes in Water Content and Soil Texture

Agricultural Sciences ◽

10.4236/as.2015.610110 ◽

2015 ◽

Vol 06 (10) ◽

pp. 1148-1163 ◽

Cited By ~ 1

Author(s):

Tyson B. Raper ◽

Christopher G. Henry ◽

Leo Espinoza ◽

Mukhammadzakhrab Ismanov ◽

Derrick M. Oosterhuis

Keyword(s):

Soil Moisture ◽

Water Content ◽

Soil Texture ◽

Soil Moisture Sensors

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Hydrotropic Root Behavior in Water-Saving Cultivation: A High-Resolution Monitoring Study of Soil Water Dynamics

10.21203/rs.3.rs-526684/v1 ◽

2021 ◽

Author(s):

Qichen Li ◽

Toshiaki Sugihara ◽

Sakae Shibusawa ◽

Minzan Li

Keyword(s):

Soil Moisture ◽

High Resolution ◽

Water Content ◽

Root System ◽

Soil Water ◽

Water Saving ◽

Water Dynamics ◽

Soil Water Dynamics ◽

Soil Moisture Sensors ◽

Wet Zone

Abstract BackgroundSubsurface irrigation has been confirmed to have high water use efficiency due to it irrigating only the crop root zone. Hydrotropism allows roots to grow towards higher water content areas for drought avoidance, which has research interests in recent years. However, most hydrotropism studies focused on a single root and were conducted in air or agar systems. The performance of hydrotropism in subsurface irrigation is not clear. ResultsWe developed a method to observe and analyze hydrotropism in soil under water-saving cultivation. A wet zone was produced around the whole root system based on using subsurface irrigation method and micro soil water dynamics were observed using high-resolution soil moisture sensors. This method enabled the observation and analysis of plant water absorption activities and the hydrotropic response of the root system. In the analysis, we first applied a high-pass filter and fast Fourier transform to the soil water dynamics data. The results indicated that the plant’s biological rhythm of photosynthetic activities can be identified from the soil moisture data. We then observed root growth in response to the dynamics of soil water content in the wet zone. We quantified root distribution inside and outside the wet zone and observed the shape of the root system from the cross-section of the wet zone. The results showed that the root hydrotropic response is not uniform for all roots of an individual plant. ConclusionsThis study verified the feasibility of using high-resolution soil moisture sensors to study root hydrotropic responses in soil during water-saving cultivation. To further evaluate a plant’s hydrotropic ability, it is necessary to use statistical analysis and/or a non-deterministic approach. Future studies may also explore developing an automated experimental system and robotic manipulations for getting steady repeatable observation of hydrotropism in water-saving cultivation.

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Laboratory calibration of soil moisture sensors in porous media (repacked soils) v1 (protocols.io.pjidkke)

protocols.io ◽

10.17504/protocols.io.pjidkke ◽

2018 ◽

Author(s):

Soham Adla ◽

Neeraj Rai ◽

K Sri ◽

Shivam Tripathi ◽

Markus Disse ◽

...

Keyword(s):

Porous Media ◽

Soil Moisture ◽

Soil Moisture Sensors ◽

Laboratory Calibration

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Laboratory calibration of different soil moisture sensors in various soil types

10.5194/egusphere-egu2020-5956 ◽

2020 ◽

Author(s):

Urša Pečan ◽

Damijana Kastelec ◽

Marina Pintar

Keyword(s):

Soil Moisture ◽

Water Content ◽

Bulk Density ◽

Soil Water ◽

Soil Water Content ◽

Soil Bulk Density ◽

Soil Samples ◽

Soil Types ◽

Soil Moisture Sensors ◽

Dry Soil

Measurements of soil water content are particularly useful for irrigation scheduling. In optimal conditions, field data are obtained through a dense grid of soil moisture sensors. Most of the currently used sensors for soil water content measurements, measure relative permittivity, a variable which is mostly dependant on water content in the soil. Spatial variability of soil characteristics, such as soil texture and mineralogy, organic matter content, dry soil bulk density and electric conductivity can also alter measurements with dielectric sensors. So the question arises, whether there is a need for a soil specific calibration of such sensors and is it dependant on the type of sensor? This study evaluated the performance of three soil water content sensors (SM150T, Delta-T Devices Ltd, UK; TRIME-Pico 32, IMKO micromodultechnik GmbH, DE; MVZ 100, Eltratec trade, production and services d.o.o., SI) in nine different soil types in laboratory conditions. Our calibration approach was based on calibration procedure developed for undisturbed soil samples (Holzman et al., 2017). Due to possible micro location variability of soil properties, we used disturbed and homogenized soil samples, which were packed to its original dry soil bulk density. We developed soil specific calibration functions for each sensor and soil type. They ranged from linear to 5th order polynomial. We calculated relative and actual differences in sensor derived and gravimetrically determined volumetric soil water content, to evaluate the errors of soil water content measured by sensors which were not calibrated for soil specific characteristics. We observed differences in performance of different sensor types in various soil types. Our results showed measurements conducted with SM150T sensors were within the range of manufacturer specified measuring error in three soil types for which calibration is not necessary but still advisable for improving data quality. In all other cases, soil specific calibration is required to obtain relevant soil moisture data in the field.

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Optimizing the Positioning of Soil Moisture Monitoring Sensors in Winter Wheat Fields

Water ◽

10.3390/w10121707 ◽

2018 ◽

Vol 10 (12) ◽

pp. 1707

Author(s):

Xiaojun Shen ◽

Jing Liang ◽

Ketema Zeleke ◽

Yueping Liang ◽

Guangshuai Wang ◽

...

Keyword(s):

Soil Moisture ◽

Winter Wheat ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Soil Profile ◽

Root Distribution ◽

Soil Surface ◽

Soil Moisture Sensors ◽

Total Average

Collecting accurate real-time soil moisture data in crop root zones is the foundation of automated precision irrigation systems. Soil moisture sensors (SMSs) have been used to monitor soil water content (SWC) in crop fields for a long time; however, there is no generally accepted guideline for determining optimal number and placement of soil moisture sensors in the soil profile. In order to study adequate positioning for the installation of soil moisture sensors in the soil profile, six years of field experiments were carried out in North China Plain (NCP). Soil water content was measured using the gravimetric method every 7 to 10 days during six growing seasons of winter wheat (Triticum aestivum L), and root distribution was measured using a soil core method during the key periods of winter wheat growth. The results from the experimental data analysis show that SWC at different depths had a high linear correlation. In addition, the values of correlation coefficients decreased with increasing soil depth; the coefficient of variation (CV) of SWC was higher in the surface layers than in the deeper layers (depths were 0–40 cm, 0–60 cm, and 0–100 cm during the early, middle, and last stages of winter wheat, respectively); wheat roots were mainly distributed in the surface layer. According to an analysis of CV for SWC and root distribution, the depths of planned wetted layers were determined to be 0–40 cm, 0–60 cm, and 0–100 cm during the sowing to reviving stages (the early stage of winter wheat), returning green and jointing stages (the middle stage of winter wheat), and heading to maturity stage (the last stage of winter wheat), respectively. The correlation and R-cluster analyses of SWC at different layers in the soil profile showed that SMSs should be installed 10 and 30 cm below the soil surface during the winter wheat growing season. The linear regression model can be built using SWC at depths of 10 and 30 cm to predict total average SWC in the soil profile. The results of validation showed that the developed model provided reliable estimates of total average SWC in the planned wetted layer. In brief, this study suggests that suitable positioning of soil moisture sensors is at depths of 10 and 30 cm below the soil surface.

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Comparison of Sensor-Based and Weather-Based Irrigation Scheduling

Applied Engineering in Agriculture ◽

10.13031/aea.13678 ◽

2020 ◽

Vol 36 (3) ◽

pp. 375-386

Author(s):

Ruixiu Sui ◽

Earl D. Vories

Keyword(s):

Soil Moisture ◽

Water Balance ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Soil Texture ◽

Irrigation Scheduling ◽

Cotton Field ◽

List Type ◽

Soil Moisture Sensors

HighlightsSensor-based irrigation scheduling methods (SBISM) were compared with computerized water balance scheduling.Number and time of irrigation events scheduled using the SBISM were often different from those predicted by the computerized method.The highly variable soils at the Missouri site complicated interpretation of the sensor values.Both SBISM and computerized water balance scheduling could be used for irrigation scheduling with close attention to soil texture and effective rainfall or irrigation.Abstract. Sensor-based irrigation scheduling methods (SBISM) measure soil moisture to allow scheduling of irrigation events based on the soil-water status. With rapid development of soil moisture sensors, more producers have become interested in SBISM, but interpretation of the sensor data is often difficult. Computer-based methods attempt to estimate soil water content and the Arkansas Irrigation Scheduler (AIS) is one example of a weather-based irrigation scheduling tool that has been used in the Mid-South for many years. To aid producers and consultants interested in learning more about irrigation scheduling, field studies were conducted for two years in Mississippi and a year in Missouri to compare SBISM with the AIS. Soil moisture sensors (Decagon GS-1, Acclima TDR-315, Watermark 200SS) were installed in multiple locations of a soybean field (Mississippi) and cotton field (Missouri). Soil water contents of the fields were measured hourly at multiple depths during the growing seasons. The AIS was installed on a computer to estimate soil water content and the required data were obtained from nearby weather stations at both locations and manually entered in the program. In Mississippi, numbers and times of the irrigation events triggered by the SBISM were compared with those that would have been scheduled by the AIS. Results showed the number and time of irrigation events scheduled using the SBISM were often different from those predicted by the AIS, especially during the 2018 growing season. The highly variable soils at the Missouri site complicated the interpretation of the sensor values. While all of the sites were within the Tiptonville silt loam map unit, some of the measurements appeared to come from sandier soils. The AIS assumed more water entered the soil than the sensors indicated from both irrigations and rainfalls less than 25 mm. While the irrigation amounts were based on the pivot sprinkler chart, previous testing had confirmed the accuracy of the charts. Furthermore, the difference varied among sites, especially for rainfall large enough to cause runoff. The recommendations based on the Watermark sensors agreed fairly well with the AIS in July after the data from the sandiest site was omitted; however, the later irrigations called for by the AIS were not indicated by the sensors. Both the sensor-based irrigation scheduling method and the AIS could be used as tools for irrigation management in the Mid-South region, but with careful attention to soil texture and the effective portion of rainfall or irrigation. Keywords: Irrigation scheduling, Soil moisture sensor, Soil water content, Water management.

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Effect of soil moisture dynamics on dense nonaqueous phase liquid (DNAPL) spill zone architecture in heterogeneous porous media

Journal of Contaminant Hydrology ◽

10.1016/j.jconhyd.2006.09.007 ◽

2007 ◽

Vol 90 (3-4) ◽

pp. 159-183 ◽

Cited By ~ 8

Author(s):

Hongkyu Yoon ◽

Albert J. Valocchi ◽

Charles J. Werth

Keyword(s):

Porous Media ◽

Soil Moisture ◽

Heterogeneous Porous Media ◽

Nonaqueous Phase Liquid ◽

Soil Moisture Dynamics ◽

Dense Nonaqueous Phase Liquid ◽

Phase Liquid ◽

Moisture Dynamics

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Irrigation Scheduling Using Soil Moisture Sensors

Journal of Agricultural Science ◽

10.5539/jas.v10n1p1 ◽

2017 ◽

Vol 10 (1) ◽

pp. 1 ◽

Cited By ~ 6

Author(s):

Ruixiu Sui

Keyword(s):

Soil Moisture ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Management Practices ◽

Root Zone ◽

Weighted Average ◽

Irrigation Scheduling ◽

Time Interval ◽

Soil Moisture Sensors

Irrigation is required to ensure crop production. Practical methods of use sensors to determine soil water status are needed in irrigation scheduling. Soil moisture sensors were evaluated and used for irrigation scheduling in humid region of the Mid-South US. Soil moisture sensors were installed in soil at depths of 15 cm, 30 cm, and 61 cm belowground. Soil volumetric water content was automatically measured by the sensors in a time interval of an hour during the crop growing season. Soil moisture data were wirelessly transferred onto internet through a wireless sensor network (WSN) so that the data could be remotely accessed online. Soil water content measured at the three depths were interpreted using a weighted average method to reflect the status of soil water in plant root zone. A threshold to trigger an irrigation event was determined with sensor-measured soil water content. An antenna mounting device was developed for operation of the WSN. Using the antenna mounting device, the soil moisture measurement was not be interrupted by crop field management practices.

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