Measuring soil water content through volume/mass replacement using a constant volume container

Ying, Ma; Qu, Liqin; Wang, Wei; Yang, Xin; Lei, Tingwu

doi:10.1016/j.geoderma.2016.02.003

Cited by 21 publications

(11 citation statements)

References 34 publications

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Section: Methodsmentioning

confidence: 99%

“…This measurement was repeated after all irrigation treatments and major precipitation events. Both methods (volumetric measurements and oven-drying) were used to measure total soil moisture as described by Ma et al (2016). For soil N content, soil sampling was done from each subplot at the depth of 0-20, 20-40, 40-60, 60-80, and 80-100 cm for the estimation of before sowing soil N contents.…”

Section: Estimation Of Soil Moisture N Contents Biomass and Yield Rmentioning

confidence: 99%

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Assessment of Water and Nitrogen Use Efficiencies Through UAV-Based Multispectral Phenotyping in Winter Wheat

Yang

Hassan

et al. 2020

Front. Plant Sci.

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Unmanned aerial vehicle (UAV) based remote sensing is a promising approach for nondestructive and high-throughput assessment of crop water and nitrogen (N) efficiencies. In this study, UAV was used to evaluate two field trials using four water (T0 = 0 mm, T1 = 80 mm, T2 = 120 mm, and T3 = 160 mm), and four N (T0 = 0, T1 = 120 kg ha −1 , T2 = 180 kg ha −1 , and T3 = 240 kg ha −1) treatments, respectively, conducted on three wheat genotypes at two locations. Ground-based destructive data of water and N indictors such as biomass and N contents were also measured to validate the aerial surveillance results. Multispectral traits including red normalized difference vegetation index (RNDVI), green normalized difference vegetation index (GNDVI), normalized difference red-edge index (NDRE), red-edge chlorophyll index (RECI) and normalized green red difference index (NGRDI) were recorded using UAV as reliable replacement of destructive measurements by showing high r values up to 0.90. NGRDI was identified as the most efficient non-destructive indicator through strong prediction values ranged from R 2 = 0.69 to 0.89 for water use efficiencies (WUE) calculated from biomass (WUE.BM), and R 2 = 0.80 to 0.86 from grain yield (WUE.GY). RNDVI was better in predicting the phenotypic variations for N use efficiency calculated from nitrogen contents of plant samples (NUE.NC) with high R 2 values ranging from 0.72 to 0.94, while NDRE was consistent in predicting both NUE.NC and NUE.GY by 0.73 to 0.84 with low root mean square errors. UAV-based remote sensing demonstrates that treatment T2 in both water 120 mm and N 180 kg ha −1 supply trials was most appropriate dosages for optimum uptake of water and N with high GY. Among three cultivars, Zhongmai 895 was highly efficient in WUE and NUE across the water and N treatments. Conclusively, UAV can be used to predict time-series WUE and NUE across the season for selection of elite genotypes, and to monitor crop efficiency under varying N and water dosages.

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Section: Methodsmentioning

confidence: 99%

Section: Estimation Of Soil Moisture N Contents Biomass and Yield Rmentioning

confidence: 99%

Assessment of Water and Nitrogen Use Efficiencies Through UAV-Based Multispectral Phenotyping in Winter Wheat

Yang

Hassan

et al. 2020

Front. Plant Sci.

View full text Add to dashboard Cite

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“…These techniques are widely used and their accuracy depends largely on the experience of the user, careful calibration and different soil properties. The thermo-gravimetric method can be a good tool to calibrate these devices, although due to the time and oven requirements, the calibration process is slow but extremely accurate (Ma et al, 2016;Placidi et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Calibration of an Arduino-based low-cost capacitive soil moisture sensor for smart agriculture

Kulmány

Bede‐Fazekas

Beslin

et al. 2022

Journal of Hydrology and Hydromechanics

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Agriculture faces several challenges to use the available resources in a more environmentally sustainable manner. One of the most significant is to develop sustainable water management. The modern Internet of Things (IoT) techniques with real-time data collection and visualisation can play an important role in monitoring the readily available moisture in the soil. An automated Arduino-based low-cost capacitive soil moisture sensor has been calibrated and developed for data acquisition. A sensor- and soil-specific calibration was performed for the soil moisture sensors (SKU:SEN0193 - DFROBOT, Shanghai, China). A Repeatability and Reproducibility study was conducted by range of mean methods on clay loam, sandy loam and silt loam soil textures. The calibration process was based on the data provided by the capacitive sensors and the continuously and parallelly measured soil moisture content by the thermogravimetric method. It can be stated that the response of the sensors to changes in soil moisture differs from each other, which was also greatly influenced by different soil textures. Therefore, the calibration according to soil texture was required to ensure adequate measurement accuracy. After the calibration, it was found that a polynomial calibration function (R2 ≥ 0.89) was the most appropriate way for modelling the behaviour of the sensors at different soil textures.

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“…Actually, researchers only collected partial runoff due to the tedious work, which inevitably resulted in errors caused by changes in sediment concentrations. More speculatively, drying period varied from one soil to another due to different implementations of the gravimetric method could favor the dynamic of relative errors (Ban et al., 2017; Ma et al., 2016). The relative error for sediment concentrations between the two methods averaged 4.82%, suggesting that the averaged accuracy of the instrument was greater than 95%.…”

Section: Resultsmentioning

confidence: 99%

An Instrument With Constant Volume Approach for In Situ Measurement of Surface Runoff and Suspended Sediment Concentration

Zhan

Jing

Zhu‐Barker

et al. 2021

Water Resources Research

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There is an increasing demand for reliable methods to measure soil loss in order to get a better understanding of sediment movement and to develop process‐based sediment transport models. This study described the design, calibration, and practical application of an instrumented technique that automatically characterized surface flow in situ fields. The instrument consisted of a sampling assembly, a measuring assembly, and a management platform. The special design combined with a volume‐mass conversion relationship was used to determine the exact volume and mass of the sediment‐laden water, thereby allowing the implementation of real‐time measurement and synchronous calculation of runoff rate and sediment concentration. Calibration results showed that normal distributions and an average error of −3.67% were obtained for the target sediment concentrations of 2–1,000 g/L. Compared with the gravimetric method, the average error of the new technique for sediment concentration was 4.82%, and the highest precision was 98.50%. The high repeatability and accuracy of the technique suggest that it can be used with confidence to give satisfactory results in fields. A field experiment under natural rainfall showed that a grass‐covered plot had 18.94% less runoff rate and 42.92% lower sediment concentration than a bare soil plot, illustrating the impact of vegetation cover on reducing soil loss. This uniquely designed instrument provides a new approach to real‐time sediment detection in surface flow. It will be beneficial for rigorously evaluating runoff and sedimentation and for in‐depth research regarding water and soil loss processes.

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Measuring soil water content through volume/mass replacement using a constant volume container

Cited by 21 publications

References 34 publications

Assessment of Water and Nitrogen Use Efficiencies Through UAV-Based Multispectral Phenotyping in Winter Wheat

Assessment of Water and Nitrogen Use Efficiencies Through UAV-Based Multispectral Phenotyping in Winter Wheat

Calibration of an Arduino-based low-cost capacitive soil moisture sensor for smart agriculture

An Instrument With Constant Volume Approach for In Situ Measurement of Surface Runoff and Suspended Sediment Concentration

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