Field Performance of Five Soil Moisture Instruments in Heavy Clay Soils

Ojo, E. RoTimi; Bullock, Paul; Fitzmaurice, John

doi:10.2136/sssaj2014.06.0250

Cited by 37 publications

(24 citation statements)

References 60 publications

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“…FDR is based on a unique relation between the volumetric water content and the dielectric constant of mineral soils. According to References [25,54,55], a Delta-T profile probe shows measurement difficulties in high clay soils; however, results are improved with site-specific calibration. In this study, site-specific calibrations were not conducted since the calibration of FDR sensors to tropical wetland soil conditions have been established by Reference [37], who approved their applicability with an error of 0.07 m 3 /m 3 .…”

Section: Soil Moisture and Groundwater Level Monitoringmentioning

confidence: 99%

“…Often, data gaps for the available soil moisture time series exist due to measurement constraints, device malfunctioning, or site inaccessibility during flooding periods. Moreover, during dry conditions, soil cracking affects the measuring moisture sensors and, therefore, data quality [25]. Statistical and data-driven methods are an option for filling in missing values in distributed soil moisture datasets.…”

Section: Introductionmentioning

confidence: 99%

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Modeling Spatial Soil Water Dynamics in a Tropical Floodplain, East Africa

Gabiri

Burghof

Diekkrüger

et al. 2018

Water

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Analyzing the spatial and temporal distribution of soil moisture is critical for ecohydrological processes and for sustainable water management studies in wetlands. The characterization of soil moisture dynamics and its influencing factors in agriculturally used wetlands pose a challenge in data-scarce regions such as East Africa. High resolution and good-quality time series soil moisture data are rarely available and gaps are frequent due to measurement constraints and device malfunctioning. Soil water models that integrate meteorological conditions and soil water storage may significantly overcome limitations due to data gaps at a point scale. The purpose of this study was to evaluate if the Hydrus-1D model would adequately simulate soil water dynamics at different hydrological zones of a tropical floodplain in Tanzania, to determine controlling factors for wet and dry periods and to assess soil water availability. The zones of the Kilombero floodplain were segmented as riparian, middle, and fringe along a defined transect. The model was satisfactorily calibrated (coefficient of determination; R 2 = 0.54-0.92, root mean square error; RMSE = 0.02-0.11) on a plot scale using measured soil moisture content at soil depths of 10, 20, 30, and 40 cm. Satisfying statistical measures (R 2 = 0.36-0.89, RMSE = 0.03-0.13) were obtained when calibrations for one plot were validated with measured soil moisture for another plot within the same hydrological zone. Results show the transferability of the calibrated Hydrus-1D model to predict soil moisture for other plots with similar hydrological conditions. Soil water storage increased towards the riparian zone, at 262.8 mm/a while actual evapotranspiration was highest (1043.9 mm/a) at the fringe. Overbank flow, precipitation, and groundwater control soil moisture dynamics at the riparian and middle zone, while at the fringe zone, rainfall and lateral flow from mountains control soil moisture during the long rainy seasons. In the dry and short rainy seasons, rainfall, soil properties, and atmospheric demands control soil moisture dynamics at the riparian and middle zone. In addition to these factors, depths to groundwater level control soil moisture variability at the fringe zone. Our results support a better understanding of groundwater-soil water interaction, and provide references for wetland conservation and sustainable agricultural water management.

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Section: Soil Moisture and Groundwater Level Monitoringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling Spatial Soil Water Dynamics in a Tropical Floodplain, East Africa

Gabiri

Burghof

Diekkrüger

et al. 2018

Water

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“…Others factors may influence on period measurements by means CS616 sensor, especially the clay content (Udawatta et al, 2011;Ojo et al, 2015). We observed that the soil moisture instrument calibrations developed by the manufacturers for a general proposing are not always adaptable for use under field conditions.…”

Section: Resultsmentioning

confidence: 95%

Laboratory temperature-compensating calibration procedure for soil water content determination by reflectometry

et al. 2018

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The water content reflectometer allows a temporal and spatial assessment in soil water dynamic. This work aimed to study the behavior of the sensor (CS616) for the period measurement in function to the temperature and soil water content. The tests were conducted at State University of Mato Grosso, Tangara da Serra municipality. We used PVC (polymerizing vinyl chloride) pipe to make six recipients (0.1 m diameter and 0.4 m height) and filled them with soil. For each one of them a sensor CS616 and temperature sensor (K type) were allocate in a central position. The soil water content for each recipient were fitted to 0.00; 0.06; 0.11; 0.16; 0.22; 0.27 m 3 m -3 , and the samples were submitted to temperature gradient from 1.0 up to 40.0 °C. Data of temperature, and period response were recorded in a data logger. Notice that the temperature provides changes for period response values (μs), and as greater the soil water content, as greater the temperature influence. From collected data, two models were fitted (linear and quadratic), and compared with manufacturer standard equations. For conditions in that study, the fitted quadratic model provide the best approach for the water soil content prediction.Additional keywords: CS616, sensor, time domain reflectometry. ResumoOs sensores de reflectometria permitem a avaliação temporal e contínua da dinâmica da água no solo. O objetivo deste trabalho foi avaliar a leitura (período) do sensor (CS616) em função do teor de água e da temperatura do solo, para a predição da umidade do solo. O estudo foi realizado na Universidade do Estado de Mato Grosso, no Câmpus Universitário de Tangará da Serra. Foram construídos seis tubos de PVC, nos quais foram acondicionados solo em seus interiores, sendo que em cada tubo foi instalado um sensor CS616 e um sensor de temperatura tipo "K". Posteriormente, condicionou-se o solo de cada tubo nas umidades volumétricas 0,00; 0,06; 0,11; 0,16; 0,22 e 0,27 m 3 m -3 , submetendo-os a um gradiente de temperatura de 1,0 até 40,0 °C. Os valores de temperatura e do período foram registrados e armazenados em um sistema de aquisição de dados. Observou-se que a temperatura influencia nas mensurações do período (µs), tendo maior influência à medida que se aumenta a umidade do solo. Uma vez constatada a referida influência, ajustou-se um modelo linear e outro quadrático que representassem o comportamento dos dados, comparando-os com as equações fornecidas pelo fabricante do sensor utilizado. Para as condições estudadas, a equação quadrática gerada neste trabalho gerou melhores resultados de predição da umidade volumétrica do solo em relação às demais.Palavras-chave adicionais: CS616, reflectometria no domínio do tempo, sensor.

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“…The performance of EM soil water sensors under various soil conditions has been investigated extensively (Geesing et al, 2004;Mittelbach et al, 2012;Singh et al, 2018;Varble and Chávez, 2011;Vaz et al, 2013), and some studies have proposed correcting for non-water influences on  v by developing soil-specific calibrations. For soil moisture sensors based on capacitance and frequency domain technology, the sensor response over a large  v range has been captured in the laboratory (Adeyemi et al, 2016;Goswami et al, 2019;Ojo et al, 2015;Provenzano et al, 2016;Santhosh et al, 2017) and in the field (Datta et al, 2018;Huang et al, 2017;Lea-Cox et al, 2018;Ojo et al, 2014;Rudnick et al, 2015;Sui, 2017).…”

mentioning

confidence: 99%

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

Singh

Heeren²,

Rudnick³

et al. 2020

Transactions of the ASABE

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Collection HIGHLIGHTS Capacitance-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 in situ 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, R 2 undisturbed (0.89) > R 2 disturbed (0.73)] than the disturbed calibrations for the Yutan and Fillmore texture classes, and the root mean square difference using the laboratory calibration (RMSD L ) was higher for pooled disturbed samples (0.053 m 3 m -3 ) in comparison to pooled undisturbed samples (0.023 m 3 m -3 ). The uncertainty in determination of volumetric water content ( v ) was higher using the factory calibration (RMSD F ) in comparison to the laboratory calibration (RMSD L ) 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.

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Field Performance of Five Soil Moisture Instruments in Heavy Clay Soils

Cited by 37 publications

References 60 publications

Modeling Spatial Soil Water Dynamics in a Tropical Floodplain, East Africa

Modeling Spatial Soil Water Dynamics in a Tropical Floodplain, East Africa

Laboratory temperature-compensating calibration procedure for soil water content determination by reflectometry

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

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