Laboratory and field assessment of the capacitance sensors Decagon 10HS and 5TE for estimating the water content of irrigated soils

Visconti, Fernando; Paz, José Miguel de; Martínez, Delfina; Molina, M. J.

doi:10.1016/j.agwat.2013.10.005

Cited by 60 publications

(49 citation statements)

References 18 publications

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“…For the study presented, specific soil calibrations were not conducted; instead, the Decagon in‐house calibration for mineral soils was used. The accuracy range of ±1 unit of dielectric permittivity in ranges from 1 to 40 (soil range) and subsequently ±0.03 m 3 /m 3 VWC or ±3% VWC for soils with <10 dS/m (DecagonDevices, ; Visconti et al ., ) seemed sufficient for detecting trends throughout the sediment sequences and for correlation purposes intended in this study where contrast is the most essential factor. VWC is expressed as volume fraction: m 3 water per m 3 soil.…”

Section: Methodsmentioning

confidence: 96%

“…Decagon states the error margin at ±1 unit of apparent dielectric permittivity in ranges from 1 to 40 (soil range) and ±0.03 m 3 /m 3 VWC or ±3% VWC for soils with <10 dS/m (DecagonDevices, ). At this point it must be noted, however, that the accurate measurement of water content via dielectric methods is extremely complex and refinement of these methods including (soil specific) calibration equations and mixing models present an extensive area of research that is of particular importance in precision agriculture (Jacobsen & Schjønning, ; Roth, Malicki, & Plagge, ; Topp et al ., ; Tran, Ardekani, & Lambot, ; Visconti et al ., ; Wang & Schmugge, ). Temperature, salinity, bulk density and clay content as well as sensor technology used influence the estimation of water content.…”

Section: Methodsmentioning

confidence: 99%

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Geoarchaeological evaluation of ground penetrating radar and magnetometry surveys at the Iron Age burial mound Rom in Norway

Schneidhofer

Nau

McGraw

et al. 2017

Archaeological Prospection

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Following magnetometry and ground penetrating radar surveys, a geoarchaeological field evaluation was carried out at the Iron Age burial mound of Rom in Slagendalen, Vestfold County, Norway, in order to assess the accuracy of the geophysical data interpretation and to investigate specific questions that have arisen during data interpretation. The evaluation was conducted within the framework of an archaeological excavation campaign in 2013, which enabled direct access to the subsurface materials. The archaeological stratification was recorded by laser scanning using a three‐dimensional (3D) single‐surface approach, permitting a virtual reconstruction of the excavated part of the mound and facilitating the comparison between excavation and prospection data. Selected sediment sequences were targeted with in situ and laboratory‐based measurements for correlation purposes, including magnetic susceptibility, electrical conductivity and water content measurements. Here we present the methodological approach and the results of the geophysical prospection surveys, followed by a geoarchaeological evaluation and a discussion of the impact on the overall archaeological investigation.

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Section: Methodsmentioning

confidence: 96%

Section: Methodsmentioning

confidence: 99%

Geoarchaeological evaluation of ground penetrating radar and magnetometry surveys at the Iron Age burial mound Rom in Norway

Schneidhofer

Nau

McGraw

et al. 2017

Archaeological Prospection

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“…Most capacitance sensors use the manufacturer's calibration equations to convert readings to volumetric water content. Clay content, organic matter, salinity, bulk density, and temperature can affect the accuracy of capacitance sensors [36][37][38][39][40]. The effect of these factors on water content readings can vary in different soil types.…”

Section: Limitations Of Soil Moisture Sensors For Irrigation Schedulimentioning

confidence: 99%

New Approaches to Irrigation Scheduling of Vegetables

Cahn

Johnson

2017

Horticulturae

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Using evapotranspiration (ET) data for scheduling irrigations on vegetable farms is challenging due to imprecise crop coefficients, time consuming computations, and the need to simultaneously manage many fields. Meanwhile, the adoption of soil moisture monitoring in vegetables has historically been limited by sensor accuracy and cost, as well as labor required for installation, removal, and collection of readings. With recent improvements in sensor technology, public weather-station networks, satellite and aerial imaging, wireless communications, and cloud computing, many of the difficulties in using ET data and soil moisture sensors for irrigation scheduling of vegetables can now be addressed. Web and smartphone applications have been developed that automate many of the calculations involved in ET-based irrigation scheduling. Soil moisture sensor data can be collected through wireless networks and accessed using web browser or smartphone apps. Energy balance methods of crop ET estimation, such as eddy covariance and Bowen ratio, provide research options for further developing and evaluating crop coefficient guidelines of vegetables, while recent advancements in surface renewal instrumentation have led to a relatively low-cost tool for monitoring crop water requirement in commercial farms. Remote sensing of crops using satellite, manned aircraft, and UAV platforms may also provide useful tools for vegetable growers to evaluate crop development, plant stress, water consumption, and irrigation system performance.

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“…A cylindrical core sampler 12 cm in diameter and 6 cm in height was used to collect these undisturbed samples. The 0.5 height/diameter ratio of the cylinder used in this work prevented most of the usual soil compaction that usually occurs when using cylinders with a larger height/diameter ratio (Visconti et al 2014). …”

Section: Soil Samplingmentioning

confidence: 97%

A new methodology to assess the maximum irrigation rates at catchment scale using geostatistics and GIS

et al. 2015

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Soil hydraulic parameters are important for irrigation scheduling. In the domain of ''precision irrigation'', knowledge of the spatial distribution of these parameters is useful in determining the maximum irrigation rate for each field in a catchment. This study focuses on the development of a new methodology to assess the spatial distribution of the maximum irrigation rate depending on the available soil water holding capacity (ASWHC). This methodology combines geostatistical techniques with geographical information system (GIS) tools. A pilot zone of 12 400 ha in a Spanish Mediterranean area was selected to develop this methodology. The linear coregionalization model (LMCR), considering the percentage of sand, carbonates, and ASWHC at others soil depths as covariates, was the best option to model the ASWHC. Other required soil parameters were also spatially modeled. The percent of coarse fragments was modeled by regression kriging considering the soil map as an auxiliary variable. The bulk density was spatially modeled by LMCR, and extended to the rooting depth by linear regression. The spatial distributions modeled were implemented in a GIS with other spatial information layers of irrigation management parameters, such as the maximum allowable depletion of soil water content, the percent of wetted soil and the irrigation depth. The combination of these layers in the GIS was used to estimate the maximum irrigation rates for each field. A propagation error analysis was performed to know the uncertainties in the maximum irrigation rate estimation. Based on this information, the irrigation managers could optimize the irrigation rates for each field.

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Laboratory and field assessment of the capacitance sensors Decagon 10HS and 5TE for estimating the water content of irrigated soils

Cited by 60 publications

References 18 publications

Geoarchaeological evaluation of ground penetrating radar and magnetometry surveys at the Iron Age burial mound Rom in Norway

Geoarchaeological evaluation of ground penetrating radar and magnetometry surveys at the Iron Age burial mound Rom in Norway

New Approaches to Irrigation Scheduling of Vegetables

A new methodology to assess the maximum irrigation rates at catchment scale using geostatistics and GIS

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