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

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.

scholarly journals Drought stress tolerance of two wheat genotypes

2008 ◽  
Vol 3 (Special Issue No. 1) ◽  
pp. S95-S104 ◽  
Author(s):  
A. Lukács ◽  
G. Pártay ◽  
T. Németh ◽  
S. Csorba ◽  
C. Farkas
Keyword(s):  
Soil Moisture ◽  
Drought Stress ◽  
Water Balance ◽  
Water Content ◽  
Stress Tolerance ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Columns ◽  
Undisturbed Soil ◽  
Wheat Genotypes

Biotic and abiotic stress effects can limit the productivity of plants to great extent. In Hungary, drought is one of the most important constrains of biomass production, even at the present climatic conditions. The climate change scenarios, developed for the Carpathian basin for the nearest future predict further decrease in surface water resources. Consequently, it is essential to develop drought stress tolerant wheat genotypes to ensure sustainable and productive wheat production under changed climate conditions. The aim of the present study was to compare the stress tolerance of two winter wheat genotypes at two different scales. Soil water regime and development of plants, grown in a pot experiment and in large undisturbed soil columns were evaluated. The pot experiments were carried out in a climatic room in three replicates. GK Élet wheat genotype was planted in six, and Mv Emese in other six pots. Two pots were left without plant for evaporation studies. Based on the mass of the soil columns without plant the evaporation from the bare soil surface was calculated in order to distinguish the evaporation and the transpiration with appropriate precision. A complex stress diagnosis system was developed to monitor the water balance elements. ECH<sub>2</sub>O type capacitive soil moisture probes were installed in each of the pots to perform soil water content measurements four times a day. The irrigation demand was determined according to the hydrolimits, derived from soil hydrophysical properties. In case of both genotypes three plants were provided with the optimum water supply, while the other three ones were drought-stressed. In the undisturbed soil columns, the same wheat genotypes were sawn in one replicate. Similar watering strategy was applied. TDR soil moisture probes were installed in the soil at various depths to monitor changes in soil water content. In order to study the drought stress reaction of the wheat plants, microsensors of 1.6 mm diameter were implanted into the stems and connected to a quadrupole mass spectrometer for gas analysis. The stress status was indicated in the plants grown on partly non-irrigated soil columns by the lower CO<sub>2</sub> level at both genotypes. It was concluded that the developed stress diagnosis system could be used for soil water balance elements calculations. This enables more precise estimation of plant water consumption in order to evaluate the drought sensitivity of different wheat genotypes.

Laboratory calibration of different soil moisture sensors in various soil types

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

&lt;p&gt;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 5&lt;sup&gt;th&lt;/sup&gt; 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.&lt;/p&gt;

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

Water ◽  
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.

Comparison of Sensor-Based and Weather-Based Irrigation Scheduling

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.

scholarly journals Irrigation Scheduling Using Soil Moisture Sensors

2017 ◽  
Vol 10 (1) ◽  
pp. 1 ◽  
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.

Soil tillage systems to reduce the harmful effect of extreme weather and hydrological situations

Biologia ◽  
2009 ◽  
Vol 64 (3) ◽  
Author(s):  
Csilla Farkas ◽  
Márta Birkás ◽  
György Várallyay
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Structure ◽  
Water Regime ◽  
Harmful Effect ◽  
Soil Tillage ◽  
Catch Crop ◽  
Undisturbed Soil

AbstractSoil as the largest potential natural water reservoir in the Carpathian Basin has increasing importance under conditions of predicted climate change resulting in increase of probability of extreme hydrological events. Soil management changes soil structure and has a major effect on soil water, heat and nutrition regimes. In this study the effect of four tillage treatments in combination with catch crop management was studied on soil hydraulic properties and water regime under semi-arid conditions. Investigations were carried out in a long-term soil tillage experiment established on Calcic Chernozem soil in Hungary. Tillage variants comprised mouldboard ploughing, disking, loosening combined with disking and direct drilling. The crop sequence between September 2003 and September 2004 comprised maize (main crop), rye (catch crop) and pea (forage). In May 2004, disturbed samples and undisturbed soil cores were collected from each tillage treatment/catch crop combination. The main soil physical and hydrophysical properties were determined in laboratory. In each treatment, capacitive soil moisture probes were installed up to 80 cm depth to ensure continuous measurement of soil water content. Total soil water amounts of chosen soil layers and soil water content dynamics as a function of depth were evaluated for selected periods in order to quantify the effect of the studied management systems on soil water regime. The main conclusion from the experiment is that under such (or similar) ecological conditions, the uniform, „over-standardized“ adaptation of tillage methods for soil moisture conservation is rather risky, their application needs special care and the future is for site-specific precision technologies. These are, in combination with catch crop application can be efficient measures of environmental protection and soil structure and water conservation.

scholarly journals On the Accuracy of Factory-Calibrated Low-Cost Soil Water Content Sensors

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3101 ◽  
Author(s):  
Jesús María Domínguez-Niño ◽  
Heye Reemt Bogena ◽  
Johan Alexander Huisman ◽  
Bernd Schilling ◽  
Jaume Casadesús
Keyword(s):  
Dielectric Permittivity ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Solid Phase ◽  
Low Cost ◽  
Time Domain Reflectometry ◽  
Sensor Calibration ◽  
Undisturbed Soil ◽  
Calibration Approach

Soil water content (SWC) monitoring is often used to optimize agricultural irrigation. Commonly, capacitance sensors are used for this task. However, the factory calibrations have been often criticized for their limited accuracy. The aim of this paper is to test the degree of improvement of various sensor- and soil-specific calibration options compared to factory calibrations by taking the 10HS sensor as an example. To this end, a two-step sensor calibration was carried out. In the first step, the sensor response was related to dielectric permittivity using calibration in media with well-defined permittivity. The second step involved the establishment of a site-specific relationship between permittivity and soil water content using undisturbed soil samples and time domain reflectometry (TDR) measurements. Our results showed that a model, which considered the mean porosity and a fitted dielectric permittivity of the solid phase for each soil and depth, provided the best fit between bulk permittivity and SWC. Most importantly, it was found that the two-step calibration approach (RMSE: 1.03 vol.%) provided more accurate SWC estimates compared to the factory calibration (RMSE: 5.33 vol.%). Finally, we used these calibrations on data from drip-irrigated almond and apple orchards and compared the factory calibration with our two-step calibration approach.

scholarly journals Effects of soil water depletion on the water relations in tropical kudzu

1999 ◽  
Vol 34 (7) ◽  
pp. 1151-1157
Author(s):  
Adaucto Bellarmino de Pereira-Netto ◽  
Antonio Celso Novaes de Magalhães ◽  
Hilton Silveira Pinto
Keyword(s):  
Water Stress ◽  
Stomatal Conductance ◽  
Water Content ◽  
Soil Water ◽  
Cover Crop ◽  
Soil Water Depletion ◽  
Pueraria Phaseoloides ◽  
Water Depletion ◽  
Relative Water ◽  
Dry Soil

Tropical kudzu (Pueraria phaseoloides (Roxb.) Benth., Leguminosae: Faboideae) is native to the humid Southeastern Asia. Tropical kudzu has potential as a cover crop in regions subjected to dryness. The objective of this paper was to evaluate the effect of soil water depletion on leaflet relative water content (RWC), stomatal conductance (g) and temperature (T L) in tropical kudzu. RWC of waterstressed plants dropped from 96 to 78%, following a reduction in SWC from 0.25 to 0.17 g (H2O).g (dry soil)-1.Stomatal conductance of stressed plants decreased from 221 to 98 mmol.m-2.s-1, following the reduction in soil water content (SWC). The day after re-irrigation, g of water stressed plants was 15% lower than g of unstressed plants. Differences in T L between waterstressed and unstressed plants (deltaT L) rose linearly from 0.1 to 2.2ºC following progressive water deficit. RWC and T L of waterstressed plants paralled RWC and T L of unstressed plants the day after reirrigation. The strong decrease in SWC found in this study only induced moderate water stress in tropical kudzu. In addition, tropical kudzu recover rapidly from the induced water stress after the re-irrigation.

scholarly journals Relating surface backscatter response from TRMM Precipitation Radar to soil moisture: results over a semi-arid region

2009 ◽  
Vol 6 (5) ◽  
pp. 6425-6454
Author(s):  
H. Stephen ◽  
S. Ahmad ◽  
T. C. Piechota ◽  
C. Tang
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Arid Regions ◽  
Vegetation Index ◽  
Temporal Trends ◽  
Model Parameters ◽  
Precipitation Radar ◽  
Semi Arid

Abstract. The Tropical Rainfall Measuring Mission (TRMM) carries aboard the Precipitation Radar (TRMMPR) that measures the backscatter (σ°) of the surface. σ° is sensitive to surface soil moisture and vegetation conditions. Due to sparse vegetation in arid and semi-arid regions, TRMMPR σ° primarily depends on the soil water content. In this study we relate TRMMPR σ° measurements to soil water content (ms) in Lower Colorado River Basin (LCRB). σ° dependence on ms is studied for different vegetation greenness values determined through Normalized Difference Vegetation Index (NDVI). A new model of σ° that couples incidence angle, ms, and NDVI is used to derive parameters and retrieve soil water content. The calibration and validation of this model are performed using simulated and measured ms data. Simulated ms is estimated using Variable Infiltration Capacity (VIC) model whereas measured ms is acquired from ground measuring stations in Walnut Gulch Experimental Watershed (WGEW). σ° model is calibrated using VIC and WGEW ms data during 1998 and the calibrated model is used to derive ms during later years. The temporal trends of derived ms are consistent with VIC and WGEW ms data with correlation coefficient (R) of 0.89 and 0.74, respectively. Derived ms is also consistent with the measured precipitation data with R=0.76. The gridded VIC data is used to calibrate the model at each grid point in LCRB and spatial maps of the model parameters are prepared. The model parameters are spatially coherent with the general regional topography in LCRB. TRMMPR σ° derived soil moisture maps during May (dry) and August (wet) 1999 are spatially similar to VIC estimates with correlation 0.67 and 0.76, respectively. This research provides new insights into Ku-band σ° dependence on soil water content in the arid regions.

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