Analysis of peat soil organic carbon, total nitrogen, soil water content and basal respiration: Is there a ‘best’ drying temperature?

Abstract Background Soil organic carbon (SOC) plays a crucial role in the global carbon cycle and terrestrial ecosystem functions. It is widely known that climate change and soil water content (SWC) could influence the SOC dynamics; however, there are still debates about how climate change, especially climate warming, and SWC impact SOC. We investigated the spatiotemporal changes in SOC and its responses to climate warming and root-zone SWC change using the coupled hydro-biogeochemical model (SWAT-DayCent) and climate scenarios data derived under the three Representative Concentration Pathways (RCPs2.6, 4.5, and 8.5) from five downscaled Global Climate Models (GCMs) in a typical loess watershed––the Jinghe River Basin (JRB) on the Chinese Loess Plateau. Results The air temperature would increase significantly during the future period (2017–2099), while the annual precipitation would increase by 2.0–13.1% relative to the baseline period (1976–2016), indicating a warmer and wetter future in the JRB. Driven by the precipitation variation, the root-zone SWC would also increase (by up to 27.9% relative to the baseline under RCP4.5); however, the SOC was projected to decrease significantly under the future warming climate. The combined effects of climate warming and SWC change could more reasonably explain the SOC loss, and this formed hump-shaped response surfaces between SOC loss and warming-SWC interactions under both RCP2.6 and 8.5, which can help explain diverse warming effects on SOC with changing SWC. Conclusions The study showed a significant potential carbon source under the future warmer and wetter climate in the JRB, and the SOC loss was largely controlled by future climate warming and the root-zone SWC as well. The hump-shaped responses of the SOC loss to climate warming and SWC change demonstrated that the SWC could mediate the warming effects on SOC loss, but this mediation largely depended on the SWC changing magnitude (drier or wetter soil conditions). This mediation mechanism about the effect of SWC on SOC would be valuable for enhancing soil carbon sequestration in a warming climate on the Loess Plateau.

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Soil organic carbon as a factor in passive microwave retrievals of soil water content over agricultural croplands

Journal of Hydrology ◽

10.1016/j.jhydrol.2015.06.058 ◽

2015 ◽

Vol 528 ◽

pp. 643-651 ◽

Cited By ~ 8

Author(s):

Hida R. Manns ◽

Aaron A. Berg ◽

Andreas Colliander

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Passive Microwave

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Can a single dose of biochar affect selected soil physical and chemical characteristics?

Journal of Hydrology and Hydromechanics ◽

10.2478/johh-2018-0034 ◽

2018 ◽

Vol 66 (4) ◽

pp. 421-428 ◽

Cited By ~ 8

Author(s):

Dušan Igaz ◽

Vladimír Šimanský ◽

Ján Horák ◽

Elena Kondrlová ◽

Jana Domanová ◽

...

Keyword(s):

Organic Carbon ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Base Cations ◽

N Fertilization ◽

Exchange Capacity ◽

Organic Carbon Content ◽

Soil Sorption ◽

Linear Relationships

Abstract During the last decade, biochar has captured the attention of agriculturalists worldwide due to its positive effect on the environment. To verify the biochar effects on organic carbon content, soil sorption, and soil physical properties under the mild climate of Central Europe, we established a field experiment. This was carried out on a silty loam Haplic Luvisol at the Malanta experimental site of the Slovak Agricultural University in Nitra with five treatments: Control (biochar 0 t ha−1, nitrogen 0 kg ha−1); B10 (biochar 10 t ha−1, nitrogen 0 kg ha−1); B20 (biochar 20 t ha−1, nitrogen 0 kg ha−1); B10+N (biochar 10 t ha−1, nitrogen 160 kg ha−1) and B20+N (biochar 20 t ha−1, nitrogen 160 kg ha−1). Applied biochar increased total and available soil water content in all fertilized treatments. Based on the results from the spring soil sampling (porosity and water retention curves), we found a statistically significant increase in the soil water content for all fertilized treatments. Furthermore, biochar (with or without N fertilization) significantly decreased hydrolytic acidity and increased total organic carbon. After biochar amendment, the soil sorption complex became fully saturated mainly by the basic cations. Statistically significant linear relationships were observed between the porosity and (A) sum of base cations, (B) cation exchange capacity, (C) base saturation.

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Incorporation of globally available datasets into the roving cosmic-ray neutron probe method for estimating field-scale soil water content

Hydrology and Earth System Sciences ◽

10.5194/hess-20-3859-2016 ◽

2016 ◽

Vol 20 (9) ◽

pp. 3859-3872 ◽

Cited By ~ 27

Author(s):

William Alexander Avery ◽

Catherine Finkenbiner ◽

Trenton E. Franz ◽

Tiejun Wang ◽

Anthony L. Nguy-Robertson ◽

...

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Water Content ◽

Bulk Density ◽

Soil Water Content ◽

Cosmic Ray ◽

Soil Bulk Density ◽

Local Soil ◽

Calibration Parameters

Abstract. The need for accurate, real-time, reliable, and multi-scale soil water content (SWC) monitoring is critical for a multitude of scientific disciplines trying to understand and predict the Earth's terrestrial energy, water, and nutrient cycles. One promising technique to help meet this demand is fixed and roving cosmic-ray neutron probes (CRNPs). However, the relationship between observed low-energy neutrons and SWC is affected by local soil and vegetation calibration parameters. This effect may be accounted for by a calibration equation based on local soil type and the amount of vegetation. However, determining the calibration parameters for this equation is labor- and time-intensive, thus limiting the full potential of the roving CRNP in large surveys and long transects, or its use in novel environments. In this work, our objective is to develop and test the accuracy of globally available datasets (clay weight percent, soil bulk density, and soil organic carbon) to support the operability of the roving CRNP. Here, we develop a 1 km product of soil lattice water over the continental United States (CONUS) using a database of in situ calibration samples and globally available soil taxonomy and soil texture data. We then test the accuracy of the global dataset in the CONUS using comparisons from 61 in situ samples of clay percent (RMSE  =  5.45 wt %, R2  =  0.68), soil bulk density (RMSE  =  0.173 g cm−3, R2  =  0.203), and soil organic carbon (RMSE  =  1.47 wt %, R2  =  0.175). Next, we conduct an uncertainty analysis of the global soil calibration parameters using a Monte Carlo error propagation analysis (maximum RMSE ∼  0.035 cm3 cm−3 at a SWC  =  0.40 cm3 cm−3). In terms of vegetation, fast-growing crops (i.e., maize and soybeans), grasslands, and forests contribute to the CRNP signal primarily through the water within their biomass and this signal must be accounted for accurate estimation of SWC. We estimated the biomass water signal by using a vegetation index derived from MODIS imagery as a proxy for standing wet biomass (RMSE  <  1 kg m−2). Lastly, we make recommendations on the design and validation of future roving CRNP experiments.

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Effects of biotic and abiotic indices on soil water content in a decade-long grassland biodiversity experiment

10.5194/egusphere-egu2020-10981 ◽

2020 ◽

Author(s):

Christine Fischer ◽

Sophia Leimer ◽

Christiane Roscher ◽

Janneke Ravenek ◽

Hans de Kroon ◽

...

Keyword(s):

Species Richness ◽

Soil Moisture ◽

Organic Carbon ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Functional Groups ◽

Plant Species ◽

Plant Species Richness

Soil moisture is the dynamic link between climate, soil and vegetation and the dynamics and variation are affected by several often interrelated factors such as soil texture, soil structural parameters (soil organic carbon) and vegetation parameters (e.g. belowground- and aboveground biomass). For the characterization of soil moisture, including its variability and the resulting water and matter fluxes, the knowledge of the relative importance of these factors is of major challenge. Because of the spatial heterogeneity of its drivers soil moisture varies strongly over time and space. Our objective was to assess the spatio-temporal variability of soil moisture and factors which could explain that variability, like soil properties and vegetation cover, in in a long term biodiversity experiment (Jena Experiment).The Jena Experiment consist 86 plots on which plant species richness (0, 1, 2, 4, 8, 16, and 60) and functional groups (legumes, grasses, tall herbs, and small herbs) were manipulated in a factorial design Soil moisture measurements were performed weekly April to September 2003-2005 and 2008-2013 in 0.1, 0.2, 0.3, 0.4, and 0.6 m soil depth using Delta T theta probe.The analysis showed that both plant species richness and the presence of particular functional groups affected soil water content, while functional group richness per se played no role. Plots containing grasses was consistently drier than average at the soil surface in all observed years while plots containing legumes comparatively moister, but only up to the year 2008.Interestingly, plant species richness led to moister than average subsoil at the beginning of the experiment (2003 and 2004), which changed to lower than average up to the year 2010 in all depths.Shortly after establishment, increased topsoil water content was related to higher leaf area index in species&#8208;rich plots, which enhanced shading. In later years, higher species richness increased topsoil organic carbon, likely improving soil aggregation. Improved aggregation, in turn, dried topsoils in species&#8208;rich plots due to faster drainage of rainwater.Our decade&#8208;long experiment shows that besides abiotic factors like texture, soil water patterns are consistently affected by biotic factors such as species diversity and plant functional types, but also properties that originate from biotic-abiotic interactions such as soil structure. Especially the effect of plant species richness propagated to deeper soil layers 8 years after the establishment of the experiment, and while originally caused by shading it was later related to altered soil physical characteristics in addition to modification of water uptake depth. Functional groups affected soil water distribution, likely due to plant traits affecting root water uptake depths, shading, or water&#8208;use efficiency. Our results highlight the role of vegetation composition for soil processes and emphasize the need for long-term experiments to discover diversity effects in slow reacting systems like soil.

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Performance of Soil Water Content Using Ground Penetrating Radar with Different Antenna Frequencies

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.29.14263 ◽

2018 ◽

Vol 7 (2.29) ◽

pp. 815

Author(s):

Nurul Izzati Abd Karim ◽

Samira Albati Kamaruddin ◽

Rozaimi Che Hasan

Keyword(s):

Dielectric Permittivity ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Ground Penetrating Radar ◽

Peat Soil ◽

Relative Dielectric Permittivity ◽

Depth Of Penetration ◽

Engineering Research ◽

Ground Penetrating

Accurate measurements of Soil Water Content (SWC) with applicable and relevant support are essential in many fields of earth and soil engineering research. Ground Penetrating Radar (GPR) is a geophysical tool that measures and provides accurate results for determination of the SWC. To prove the accuracy of SWC measurement using GPR, a field survey was performed in peat soil. This paper presents a fieldwork survey with the aim of assessing the SWC measurement using GPR. The survey work was conducted at Johor Bharu using different antenna frequencies (250 and 700 MHz). Five profiles, which is 5m by 5m in length, were scanned along an east-west direction with a common offset at an equal spacing of 1m. To measure the SWC using GPR, the researchers used the velocity from the GPR’s signal from the receiving antenna to the soil. Statistical analysis was carried out based on the dielectric permittivity and SWC. Schaap’s equation and Roth’s equation were used to distinguish the relative dielectric permittivity of the soil to SWC. The results of this study show the linear function, for the measured SWC. The validation graph shows that at a frequency of 250 MHz, the depth of penetration was greater compared to the frequency of 750 MHz. These results, suggest that a higher frequency will give higher resolution but lower depth penetration.

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A near infrared index to assess effects of soil texture and organic carbon content on soil water content

European Journal of Soil Science ◽

10.1111/ejss.12725 ◽

2018 ◽

Vol 70 (1) ◽

pp. 151-161 ◽

Cited By ~ 3

Author(s):

I. Soltani ◽

Y. Fouad ◽

D. Michot ◽

P. Bréger ◽

R. Dubois ◽

...

Keyword(s):

Organic Carbon ◽

Carbon Content ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Soil Texture ◽

Near Infrared ◽

Organic Carbon Content

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Incorporation of globally available datasets into the cosmic-ray neutron probe method for estimating field scale soil water content

10.5194/hess-2016-92 ◽

2016 ◽

Author(s):

William Alexander Avery ◽

Catherine Finkenbiner ◽

Trenton E. Franz ◽

Tiejun Wang ◽

Anthony L. Nguy-Robertson ◽

...

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Water Content ◽

Bulk Density ◽

Soil Water Content ◽

Cosmic Ray ◽

Soil Bulk Density ◽

Local Soil ◽

Calibration Parameters

Abstract. The need for accurate, real-time, reliable, and multi-scale soil water content (SWC) monitoring is critical for a multitude of scientific disciplines trying to understand and predict the earth's terrestrial energy, water, and nutrient cycles. One promising technique to help meet this demand is fixed and roving cosmic-ray neutron probes (CRNP). However, the relationship between observed low-energy neutrons and SWC is affected by local soil and vegetation calibration parameters. This effect may be accounted for by a calibration equation based on local soil type and the amount of standing biomass. However, determining the calibration parameters for this equation is labor and time intensive, thus limiting the full potential of the roving CRNP in large surveys and long transects, or its use in novel environments. In this work, our objective is to develop and test the accuracy of using globally available datasets (clay weight percent, soil bulk density, and soil organic carbon) to support the operability of the CRNP. Here, we develop a 1 km product of soil lattice water over the CONtinental United States (CONUS) using a database of in-situ calibration samples and globally available soil taxonomy and soil texture data. We then test the accuracy of the global dataset in the CONUS using comparisons from 61 in-situ samples of clay percent (RMSE = 5.45 wt. %, R2 = 0.68), soil bulk density (RMSE = 0.173 g/cm3, R2 = 0.203), and soil organic carbon (RMSE = 1.47 wt. %, R2 = 0.175). Next, we conduct an uncertainty analysis of the global soil calibration parameters using a Monte Carlo error propagation analysis (maximum RSME ~0.035 cm3/cm3 at a SWC = 0.40 cm3/cm3). In terms of vegetation, fast growing crops (i.e. maize and soybeans) contribute to the CRNP signal primarily through the water within their biomass and this signal must be minimized for accurate estimation of SWC. We estimated the biomass water signal by using a vegetation index derived from MODIS imagery as a proxy for standing wet biomass (RMSE < 1 kg/m2). Lastly, we make recommendations on the design and validation of future roving CRNP experiments.

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