Evaluation of several calibration procedures for a portable soil moisture sensor

Rowlandson, Tracy; Berg, Aaron; Bullock, Paul; Ojo, E. RoTimi; McNairn, Heather; Wiseman, Grant; Cosh, Michael H.

doi:10.1016/j.jhydrol.2013.05.021

Cited by 89 publications

(70 citation statements)

References 23 publications

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“…The accuracy of calibration equations supplied by manufacturers of these sensors are usually between a range of ±4 -2% VMC when applied in non-saline soils [56]. Site-specific calibration equations which are developed by comparing the sensor output to gravimetrically derived soil moisture content can be applied when a higher level of accuracy is required [57]. In addition, for capacitance type probes, it is essential that the probe access tubes are fitted correctly without air gaps to ensure robust soil water measurements.…”

Section: Factors Affecting the Performance Of Dielectric Soil Moisturmentioning

confidence: 99%

Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

et al. 2017

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Globally, the irrigation of crops is the largest consumptive user of fresh water. Water scarcity is increasing worldwide, resulting in tighter regulation of its use for agriculture. This necessitates the development of irrigation practices that are more efficient in the use of water but do not compromise crop quality and yield. Precision irrigation already achieves this goal, in part. The goal of precision irrigation is to accurately supply the crop water need in a timely manner and as spatially uniformly as possible. However, to maximize the benefits of precision irrigation, additional technologies need to be enabled and incorporated into agriculture. This paper discusses how incorporating adaptive decision support systems into precision irrigation management will enable significant advances in increasing the efficiency of current irrigation approaches. From the literature review, it is found that precision irrigation can be applied in achieving the environmental goals related to sustainability. The demonstrated economic benefits of precision irrigation in field-scale crop production is however minimal. It is argued that a proper combination of soil, plant and weather sensors providing real-time data to an adaptive decision support system provides an innovative platform for improving sustainability in irrigated agriculture. The review also shows that adaptive decision support systems based on model predictive control are able to adequately account for the time-varying nature of the soil-plant-atmosphere system while considering operational limitations and agronomic objectives in arriving at optimal irrigation decisions. It is concluded that significant improvements in crop yield and water savings can be achieved by incorporating model predictive control into precision irrigation decision support tools. Further improvements in water savings can also be realized by including deficit irrigation as part of the overall irrigation management strategy. Nevertheless, future research is needed for identifying crop response to regulated water deficits, developing improved soil moisture and plant sensors, and developing self-learning crop simulation frameworks that can be applied to evaluate adaptive decision support strategies related to irrigation.

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Section: Factors Affecting the Performance Of Dielectric Soil Moisturmentioning

confidence: 99%

Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

et al. 2017

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“…In an effort to understand what soil physical property variable(s) is (are) best to use for calibration of SWC ground sensors (Rowlandson et al 2013;Ojo et al 2015) or to enter into remote-sensing algorithms to interpret the soil dielectric constant (Mladenova et al 2014;Manns et al 2015), it would be helpful to know the amount of variance that is expressed equally by all variables (same r value between any pairwise combinations) separately from the amount to which individual variables express unique variability in specific environmental conditions. The objective of this paper is to analyze the relationships among soil physical variables and in particular to assess the role of SOC as related to surface SWC when averaged over multiple fields and sampling times.…”

Section: Introductionmentioning

confidence: 99%

Evidence of a union between organic carbon and water content in soil

2016

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Soil organic matter, comprising ∼58% soil organic carbon (SOC), is attributed with increased water holding capacity in the surface horizon of agricultural soil. This paper addresses the role of SOC as a component of a common functional unit in soil from analysis within a single field and over multiple fields. Soil data measured on the fields during the SMAPVEX12 satellite prelaunch algorithm development campaign exhibited high correlation among SOC, field-mean soil water content (SWC), bulk density, and soil texture. The analysis extended over a wide range of soil texture and wetness in the top 5 cm of soil over 50 agricultural fields covering ∼400 km 2 of southern Manitoba. Data collected over a much smaller area from Ontario silt loam soils at the Elora Research Centre demonstrated a similar correlation between SOC and SWC in intensive field sampling. This intercorrelation of SOC and SWC is examined with partial least-squares regression, principal component analysis, and geostatistical semivariograms. A model is proposed to interpret the feedback process between SOC and SWC to explain the persistent correlation. Further work to substantiate the strengths and limits of the relationship between SOC and SWC may be beneficial for estimating SWC for remote sensing, agriculture, hydrology, and ecosystem function.Key words: soil organic carbon, soil water content, organic matter molecule, partial least-squares analysis, carbon feedback.Résumé : On estime que la matière organique, qui se compose d'environ 58 % de carbone organique (CO), retient l'eau davantage dans l'horizon superficiel des sols agricoles. Cet article examine le rôle du CO en tant que composante d'une unité fonctionnelle commune du sol d'après l'analyse du sol d'un ou de plusieurs terrains agricoles. Les données relevées au champ lors du développement de l'algorithme SMAPVEX12 avant le lancement du satellite montrent qu'il existe une étroite corrélation entre le CO, la teneur en eau moyenne du sol (TEM) au champ, la masse volumique apparente et la texture du sol. L'analyse a porté sur un large éventail de textures et de concentrations d'eau dans la couche supérieure de 5 cm d'une cinquantaine de parcelles cultivées couvrant une superficie de ∼400 km 2 dans le sud du Manitoba. Les données recueillies sur une superficie plus modeste constituée de loams limoneux, au centre de recherche d'Elora, en Ontario, montraient une corrélation analogue entre le CO et la TEM pour les parcelles échantillonnées, cultivées intensivement. Les auteurs examinent la corrélation entre le CO et la TEM du sol au moyen de la méthode de régression partielle par les moindres carrés, de l'analyse en composantes principales et de semivariogrammes en géostatistique. Ils proposent un modèle permettant d'interpréter les mécanismes de rétroaction entre le CO et la TEM en vue d'expliquer cette corrélation tenace. Des recherches plus poussées pour étoffer les forces et les limites du lien entre le CO et la TEM du sol auraient leur utilité pour estimer la TEM en vue de son util...

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“…These can be better combined with data assimilation [21][22][23], especially for the estimation of the root zone soil moisture using SMOS [24,25] and SMAP [26,27]. By combining our dielectric mixing model with the radiative transfer models, the TB can be obtained more accurately in the microwave spectral region, which is of course beneficial not only for the data assimilation scheme but also the field campaign for the calibration and validation such as SMOSREX [28] or SMAPVEX [29].…”

Section: Introductionmentioning

confidence: 99%

New Approach for Calculating the Effective Dielectric Constant of the Moist Soil for Microwaves

et al. 2017

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Microwave remote sensing techniques are used, among others, for temporally and spatially highly-resolved observations of land-surface properties, e.g., for the management of agricultural productivity and water resource, as well as to improve the performances of numerical weather prediction and climate simulations with soil moisture data. In this context, the effective dielectric constant of the soil is a key variable to quantify the land surface properties. We propose a new approach for the effective dielectric constant of the multiphase soil that is based on an arithmetic average of the dielectric constants of the land-surface components with damping. The results show, on average, better agreement with experimental data than previous approaches. Furthermore, the proposed new model overcomes the theoretical limitation of previous models in the incorporation of non-physical parameters to simulate measured data experimentally with satisfactory accuracy. For microwave remote sensing such as SMAP (Soil Moisture Active Passive), SMOS (Soil Moisture and Ocean Salinity) and AMSR-E (Advanced Microwave Scanning Radiometer for EOS), the physical-based model in our study showed a 23-35% RMSE (root-mean-square error) reduction compared to the most prevalent refractive mixing model in the prediction of the dielectric constant for the real and imaginary part, respectively. Furthermore, in radiowave bands used in portable soil sensors such as TDR (time-domain reflectometer) and GPR (ground-penetrating radar) the new dielectric mixing model reduced RMSE by up to 53% in the prediction of the dielectric constant. We found that the permittivity over the saturation point (porosity of dry soil) has a very different and varying pattern compared to that measured in the unsaturated condition. However, in our study, this pattern was mathematically derived from the same mixing rule applied for the unsaturated condition. It is expected that the new dielectric mixing model might help to improve the accuracy of flood monitoring by satellite.

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Evaluation of several calibration procedures for a portable soil moisture sensor

Cited by 89 publications

References 23 publications

Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

Evidence of a union between organic carbon and water content in soil

New Approach for Calculating the Effective Dielectric Constant of the Moist Soil for Microwaves

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