scholarly journals Imaging Rhizosphere CO2 and O2 Concentration to Localize Respiration Hotspots Linked to Root Type and Soil Moisture Dynamics

2021 ◽  
Author(s):  
Sarah Bereswill ◽  
Nicole Rudolph-Mohr ◽  
Sascha E Oswald
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Lateral Roots ◽  
Lupinus Albus ◽  
Spatiotemporal Variability ◽  
Cluster Roots ◽  
Small Scale

Abstract PurposeRhizosphere respiration strongly affects CO2 concentration within vegetated soils and resulting fluxes to the atmosphere. Respiration in the rhizosphere exhibits high spatiotemporal variability that may be linked to root type, but also to small-scale variation of soil water content altering gas transport dynamics in the soil. We address spatiotemporal dynamics of CO2 and O2 concentration in the rhizosphere via non-invasive in-situ imaging.MethodsOptodes sensitive to CO2 and O2 were applied to non-invasively measure in-situ rhizosphere CO2 and O2 concentration of white lupine (Lupinus albus) grown in slab-shaped glass rhizotrons. We monitored CO2 concentration over the course of 16 days at constant water content and also performed a drying-rewetting experiment to explore sensitivity of CO2 and O2 concentration to soil moisture changes. ResultsHotspots of respiration formed around cluster roots and CO2 concentration locally increased to > 20 % pCO2 (CO2 partial pressure). After rewetting the soil, cluster roots consumed available O2 significantly faster compared to non-cluster lateral roots. In wet soil, CO2 accumulation zones extended up to 9.5 mm from the root surface compared to 0.3-1 mm in dry soil.ConclusionResults from this imaging experiment indicate that respiratory activity differs substantially within the root system of a plant individual and that cluster roots are hotspots of respiration. As rhizosphere CO2 and O2 concentration was strongly sensitive to soil water content and its variation, we recommend monitoring the soil water content prior and during the measurement of rhizosphere respiration.

Spatiotemporal Variability of Soil Moisture under Different Agroforestry Landscape in Jinghe River

2012 ◽  
Vol 212-213 ◽  
pp. 3-9
Author(s):  
Qi Rui Wang ◽  
Jun Gao
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Fractal Dimensions ◽  
Spatiotemporal Variability ◽  
Cover Soil ◽  
Rain Season ◽  
Landscape Types ◽  
Jinghe River

Measured the cover soil water content in soil layer 0~30cm of different agroforestry landscape types in Jinghe river with TDR, the landscape types including sloping cropland, apple orchard, apple-clover system, land under forest and grass changed from grain crop and black locust forest. Analyze the distribution characteristic and spatiotemporal variability of the cover soil water. The result showed that the soil water has renewed in a certain extent after a rain period in 1.5 m soil profile; the soil water content is gradually increased from the top of to the bottom of the slope under the affection of the slope location and plant category. The theory model of semivariogram for cover soil water content before rain season and after season, the value of nugget is changed no obviously , and they are 0.25 and 0.30; ranges is 99.7 m and 87.6 m. And the results indicated that soil moisture exhibited high fractal dimensions and clear spatial autocorrelation. The fractal dimensions are 1.71 and 1.74, variogram is main autocorrelation. During rain season the theory semivariogram model is linear, the spatiotemporal variability of soil water content becomes higher with the increase in distance, and its fractal dimension is 1.40.

scholarly journals Estimating Soil Water Retention Curve by Inverse Modelling from Combination of In Situ Dynamic Soil Water Content and Soil Potential Data

Soil Systems ◽  
2018 ◽  
Vol 2 (4) ◽  
pp. 55 ◽  
Author(s):  
Pinnara Ket ◽  
Chantha Oeurng ◽  
Aurore Degré
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Water Retention ◽  
Inverse Modelling ◽  
Soil Water Retention ◽  
Moisture Dynamics ◽  
Hydrus 1D

Soil water retention curves (SWRCs) are crucial for characterizing soil moisture dynamics, and are particularly relevant in the context of irrigation management. Inverse modelling is one of the methods used to parameterize models representing these curves, which are closest to the field reality. The objective of this study is to estimate the soil hydraulic properties through inverse modelling using the HYDRUS-1D code based on soil moisture and potential data acquired in the field. The in situ SWRCs acquired every 30 min are based on simultaneous soil water content and soil water potential measurements with 10HS and MPS-2 sensors, respectively, in five experimental fields. The fields were planted with drip-irrigated lettuces from February to March 2016 in the Chrey Bak catchment located in the Tonlé Sap Lake region, Cambodia. After calibration of the van Genuchten soil water retention model parameters, we used them to evaluate the performance of HYDRUS-1D to predict soil moisture dynamics in the studied fields. Water flow was reasonably well reproduced in all sites covering a range of soil types (loamy sand and loamy soil) with root mean square errors ranging from 0.02 to 0.03 cm3 cm−3.

A simple method for soil moisture calculation using data from ELBARA III passive radiometer and thermal inertia

2020 ◽  
Author(s):  
Mateusz Lukowski ◽  
Lukasz Gluba ◽  
Anna Rafalska-Przysucha ◽  
Kamil Szewczak ◽  
Bogusław Usowicz
Keyword(s):  
Heat Capacity ◽  
Soil Moisture ◽  
Brightness Temperature ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Thermal Inertia ◽  
Time Domain Reflectometry ◽  
L Band

<p>The soil is a heterogonous substance consists of three phases: solid, gas and liquid, where the latter is mainly water – the natural solvent with very high heat capacity. Due to this physical property and the fact that water is a common substance on our planet, it has a significant impact for stability of the climate on Earth. Another water property, the dielectric constant much higher than in other soil ingredients, is often used to determine soil water content. As an example, the Time Domain Reflectometry (TDR) technique for in situ soil moisture measurements may be mentioned. For soil moisture assessments at global scale, the satellite-based instruments were designed and launched into space, e.g. Soil Moisture and Ocean Salinity (SMOS) or Soil Moisture Active Passive (SMAP). Those satellites are measuring brightness temperature of soil in microwave (L-band) domain. The algorithms that retrieve soil moisture from L-band measurements by nonlinear optimisation engage several parameters such as soil temperature, its roughness and vegetation cover. In the presented work, we introduce a much simpler method that base on three facts: i) a high water heat capacity cause that, during the diurnal night/day cycle, the soil with higher water content cools down and heats up slower than dry soil. This phenomenon was quantified by thermal inertia; ii) brightness temperature is related to the effective temperature of the surface and iii) plants are generally semi-transparent for L-band microwaves, what gives a possibility for probing soil properties underneath vegetation. Due to iii) we assumed that L-band soil albedo (needed in thermal inertia computations) is constant. The proposed approach seems to be reasonable, as both variables, brightness temperature and thermal inertia, strongly depend on soil water content. The method was evaluated using ELBARA (European Space Agency L-band Radiometer) instrument operating at Bubnow test site in Poland. The ELBARA is a directional receiver at 1.4 GHz frequency (the same as received by SMOS satellite), installed on the Earth’s surface, at 6-meter tower. In the years 2016-2019, we conducted 16 field campaigns – we measured surface soil moisture in situ using TDR, and interpolate it to semi-continuous grid using geostatistics. Then, the driest and the wettest points (in space and time) were chosen and assigned to, respectively, maximum and minimum thermal inertia. Basing on that, the model retrieving soil moisture was built, and the other measurements served as validation assembly. Simple regression methods revealed good or moderately good agreement between modelled and measured data. Some outliers, probably induced by meteorological phenomena disturbing stable soil cooling and heating such as rain or wind, have been noticed.</p><p>Research was partially conducted under the project “Water in soil - satellite monitoring and improving the retention using biochar” no. BIOSTRATEG3/345940/7/NCBR/2017 which was financed by Polish National Centre for Research and Development in the framework of “Environment, agriculture and forestry” – BIOSTRATEG strategic R&D programme.</p>

scholarly journals Relating surface backscatter response from TRMM Precipitation Radar to soil moisture: results over a semi-arid region

2009 ◽  
Vol 6 (5) ◽  
pp. 6425-6454
Author(s):  
H. Stephen ◽  
S. Ahmad ◽  
T. C. Piechota ◽  
C. Tang
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Arid Regions ◽  
Vegetation Index ◽  
Temporal Trends ◽  
Model Parameters ◽  
Precipitation Radar ◽  
Semi Arid

Abstract. The Tropical Rainfall Measuring Mission (TRMM) carries aboard the Precipitation Radar (TRMMPR) that measures the backscatter (σ°) of the surface. σ° is sensitive to surface soil moisture and vegetation conditions. Due to sparse vegetation in arid and semi-arid regions, TRMMPR σ° primarily depends on the soil water content. In this study we relate TRMMPR σ° measurements to soil water content (ms) in Lower Colorado River Basin (LCRB). σ° dependence on ms is studied for different vegetation greenness values determined through Normalized Difference Vegetation Index (NDVI). A new model of σ° that couples incidence angle, ms, and NDVI is used to derive parameters and retrieve soil water content. The calibration and validation of this model are performed using simulated and measured ms data. Simulated ms is estimated using Variable Infiltration Capacity (VIC) model whereas measured ms is acquired from ground measuring stations in Walnut Gulch Experimental Watershed (WGEW). σ° model is calibrated using VIC and WGEW ms data during 1998 and the calibrated model is used to derive ms during later years. The temporal trends of derived ms are consistent with VIC and WGEW ms data with correlation coefficient (R) of 0.89 and 0.74, respectively. Derived ms is also consistent with the measured precipitation data with R=0.76. The gridded VIC data is used to calibrate the model at each grid point in LCRB and spatial maps of the model parameters are prepared. The model parameters are spatially coherent with the general regional topography in LCRB. TRMMPR σ° derived soil moisture maps during May (dry) and August (wet) 1999 are spatially similar to VIC estimates with correlation 0.67 and 0.76, respectively. This research provides new insights into Ku-band σ° dependence on soil water content in the arid regions.

Root effects on soil water and hydraulic properties

Biologia ◽  
2007 ◽  
Vol 62 (5) ◽  
Author(s):  
Horst Gerke ◽  
Rolf Kuchenbuch
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Water Content ◽  
Bulk Density ◽  
Soil Water ◽  
Soil Water Content ◽  
Hydraulic Properties ◽  
Soil Hydraulic Properties ◽  
Soil Hydraulic ◽  
Root Effects

AbstractPlants can affect soil moisture and the soil hydraulic properties both directly by root water uptake and indirectly by modifying the soil structure. Furthermore, water in plant roots is mostly neglected when studying soil hydraulic properties. In this contribution, we analyze effects of the moisture content inside roots as compared to bulk soil moisture contents and speculate on implications of non-capillary-bound root water for determination of soil moisture and calibration of soil hydraulic properties.In a field crop of maize (Zea mays) of 75 cm row spacing, we sampled the total soil volumes of 0.7 m × 0.4 m and 0.3 m deep plots at the time of tasseling. For each of the 84 soil cubes of 10 cm edge length, root mass and length as well as moisture content and soil bulk density were determined. Roots were separated in 3 size classes for which a mean root porosity of 0.82 was obtained from the relation between root dry mass density and root bulk density using pycnometers. The spatially distributed fractions of root water contents were compared with those of the water in capillary pores of the soil matrix.Water inside roots was mostly below 2–5% of total soil water content; however, locally near the plant rows it was up to 20%. The results suggest that soil moisture in roots should be separately considered. Upon drying, the relation between the soil and root water may change towards water remaining in roots. Relations depend especially on soil water retention properties, growth stages, and root distributions. Gravimetric soil water content measurement could be misleading and TDR probes providing an integrated signal are difficult to interpret. Root effects should be more intensively studied for improved field soil water balance calculations.

Effect of water on common lambsquarters (Chenopodium album L.) and barnyardgrass [Echinochloa crus-galli (L.) Beauv.] seedling emergence in corn

2002 ◽  
Vol 82 (4) ◽  
pp. 855-859 ◽  
Author(s):  
M. L. Leblanc ◽  
D. C. Cloutier ◽  
C. Hamel
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Chenopodium Album ◽  
Seedling Emergence ◽  
Field Capacity ◽  
Emergence Period ◽  
Common Lambsquarters ◽  
Weed Emergence

A 2-year field study was conducted in corn to determine the influence of rainfall, irrigation and soil water content on common lambsquarters and barnyardgrass emergence. Rainfall or irrigation had no influence on the final weed density and little on the pattern of weed emergence because the soil water content was at or greater than field capacity during the main weed emergence period. Irrigation may hasten the first weed emergence by warming the soil when temperature is limiting for germination. In southwestern Quebec, temperature appears to be the most important factor regulating germination in the spring since soil moisture is normally at field capacity for a long period, in part because of the melting of snow. Key words: Irrigation, weed emergence, soil moisture

scholarly journals On the scaling characteristics of observed and simulated spatial soil moisture fields

2009 ◽  
Vol 16 (1) ◽  
pp. 141-150 ◽  
Author(s):  
M. Gebremichael ◽  
R. Rigon ◽  
G. Bertoldi ◽  
T. M. Over
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Spatial Correlation ◽  
Hydrologic Model ◽  
Invariance Property ◽  
Spatial Average ◽  
Hydrologic Models ◽  
Model Simulations

Abstract. By providing continuous high-resolution simulations of soil moisture fields, distributed hydrologic models could be powerful tools to advance the scientific community's understanding of the space-time variability and scaling characteristics of soil moisture fields. However, in order to use the soil moisture simulations from hydrologic models with confidence, it is important to understand whether the models are able to represent in a reliable way the processes regulating soil moisture variability. In this study, a comparison of the scaling characteristics of spatial soil moisture fields derived from a set of microwave radiometer observations from the Southern Great Plains 1997 experiment and corresponding simulations using the distributed hydrologic model GEOtop is performed through the use of generalized variograms. Microwave observations and model simulations are in agreement with respect to suggesting the existence of a scale-invariance property in the variograms of spatial soil moisture fields, and indicating that the scaling characteristics vary with changes in the spatial average soil water content. However, observations and simulations give contradictory results regarding the relationship between the scaling parameters (i.e. spatial organization) and average soil water content. The drying process increased the spatial correlation of the microwave observations at both short and long separation distances while increasing the rate of decay of correlation with distance. The effect of drying on the spatial correlation of the model simulations was more complex, depending on the storm and the simulation examined, but for the largest storm in the simulation most similar to the observations, drying increased the long-range correlation but decreased the short-range. This is an indication that model simulations, while reproducing correctly the total streamflow at the outlet of the watershed, may not accurately reproduce the runoff production mechanisms. Consideration of the scaling characteristics of spatial soil moisture fields can therefore serve as a more intensive means for validating distributed hydrologic models, compared to the traditional approach of only comparing the streamflow hydrographs.

An in situ probe-spacing-correction thermo-TDR sensor to measure soil water content accurately

2018 ◽  
Vol 69 (6) ◽  
pp. 1030-1034 ◽  
Author(s):  
M. M. Wen ◽  
G. Liu ◽  
R. Horton ◽  
K. Noborio
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Probe Spacing
Sign in / Sign up

Export Citation Format

Share Document