scholarly journals Temporal stability of electrical conductivity in a sandy soil

2016 ◽  
Vol 30 (3) ◽  
pp. 349-357 ◽  
Author(s):  
Aura Pedrera-Parrilla ◽  
Eric C. Brevik ◽  
Juan V. Giráldez ◽  
Karl Vanderlinden
Keyword(s):  
Electrical Conductivity ◽  
Spatial Variability ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Precision Agriculture ◽  
Temporal Stability ◽  
Principal Component ◽  
Model Parameters ◽  
Soil Spatial Variability

Abstract Understanding of soil spatial variability is needed to delimit areas for precision agriculture. Electromagnetic induction sensors which measure the soil apparent electrical conductivity reflect soil spatial variability. The objectives of this work were to see if a temporally stable component could be found in electrical conductivity, and to see if temporal stability information acquired from several electrical conductivity surveys could be used to better interpret the results of concurrent surveys of electrical conductivity and soil water content. The experimental work was performed in a commercial rainfed olive grove of 6.7 ha in the ‘La Manga’ catchment in SW Spain. Several soil surveys provided gravimetric soil water content and electrical conductivity data. Soil electrical conductivity values were used to spatially delimit three areas in the grove, based on the first principal component, which represented the time-stable dominant spatial electrical conductivity pattern and explained 86% of the total electrical conductivity variance. Significant differences in clay, stone and soil water contents were detected between the three areas. Relationships between electrical conductivity and soil water content were modelled with an exponential model. Parameters from the model showed a strong effect of the first principal component on the relationship between soil water content and electrical conductivity. Overall temporal stability of electrical conductivity reflects soil properties and manifests itself in spatial patterns of soil water content.

scholarly journals The spatial variability of soil water content in a potato field before and after spray irrigation in arid northwestern China

2020 ◽  
Vol 20 (3) ◽  
pp. 860-870 ◽  
Author(s):  
Tao Li ◽  
Jian-feng Zhang ◽  
Si-yuan Xiong ◽  
Rui-xi Zhang
Keyword(s):  
Spatial Variability ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Precision Agriculture ◽  
Field Experiments ◽  
Soil Layer ◽  
Northwestern China ◽  
Potato Field ◽  
Arid Northwestern China

Abstract Assessing the spatial variability of soil water content is important for precision agriculture. To measure the spatial variability of the soil water content and to determine the optimal number of sampling sites for predicting the mean soil water content at different stages of the irrigation cycle, field experiments were carried out in a potato field in northwestern China. The soil water content was measured in 2016 and 2017 at depths of 0–20 and 20–40 cm at 116 georeferenced locations. The average coefficient of variation of the soil water content was 20.79% before irrigation and was 16.44% after irrigation at a depth of 0–20 cm. The spatial structure of the soil water content at a depth of 20–40 cm was similar throughout the irrigation cycle, but at a depth of 0–20 cm a relatively greater portion of the variation in the soil water content was spatially structured before irrigation than after irrigation. The autocorrelation of soil water contents was influenced by irrigation only in the surface soil layer. To accurately predict mean soil moisture content, 40 and 20 random sampling sites should be chosen with errors of 5% and 10%, respectively.

scholarly journals Analyzing spatial and temporal variability of soil water content

Bragantia ◽  
2008 ◽  
Vol 67 (2) ◽  
pp. 463-469 ◽  
Author(s):  
Sidney Rose Vieira ◽  
Célia Regina Grego ◽  
George Clarke Topp
Keyword(s):  
Spatial Variability ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Spatial Dependence ◽  
Temporal Variability ◽  
Temporal Stability ◽  
Water Evaporation ◽  
Spatial And Temporal Variability ◽  
Statistical Parameters

During the last two decades geoestatistical methods have been intensively used for in-depth descriptions of spatial variability. The objective of this study was to assess the spatial and temporal variability of soil water content. The measurements were taken with a TDR equipment to a 20 cm depth, in a nearly flat 1.2 ha field at the Central Experimental Farm of the Agriculture Canada, Ottawa. The soil classified as a Rideau soil series, is a clay loam soil. A square grid with 10 m spacing was laid out, resulting in 164 sampling points at which two TDR rods were installed to measure the water content down to 20 cm depth. Measurements were taken on 33 dates during the frost free months in 1987, 1988 and 1989. The spatial variability was analyzed examining the scaled semivariograms, the statistical parameters and the parameters of the models fit to individual semivariograms as a function of time. It was concluded that spatial dependence decreases as the soil gets drier and that results from one year connect almost continuously to other years. The topography and structure of topsoil horizon was the primary cause for the repeating spatial pattern of soil water content in successive samplings. The places where the mean value occurred in the field were more stable in time when there was spatial dependence. As the soil gets dryer the temporal stability of the spatial distribution tends to disappear due to the hydraulic conductivity controlling the water evaporation over the field

Concurrent temporal stability of the apparent electrical conductivity and soil water content

2017 ◽  
Vol 544 ◽  
pp. 319-326 ◽  
Author(s):  
Aura Pedrera-Parrilla ◽  
Yakov A. Pachepsky ◽  
Encarnación V. Taguas ◽  
Sergio Martos-Rosillo ◽  
Juan V. Giráldez ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Temporal Stability ◽  
Apparent Electrical Conductivity

scholarly journals Using Multivariate Geostatistics to Assess Patterns of Spatial Dependence of Apparent Soil Electrical Conductivity and Selected Soil Properties

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Glécio Machado Siqueira ◽  
Jorge Dafonte Dafonte ◽  
Montserrat Valcárcel Armesto ◽  
Ênio Farias França e Silva
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Clay Content ◽  
Data Sets ◽  
Soil Electrical Conductivity ◽  
Multivariate Geostatistics ◽  
Northwestern Spain

The apparent soil electrical conductivity (ECa) was continuously recorded in three successive dates using electromagnetic induction in horizontal (ECa-H) and vertical (ECa-V) dipole modes at a 6 ha plot located in Northwestern Spain. One of the ECadata sets was used to devise an optimized sampling scheme consisting of 40 points. Soil was sampled at the 0.0–0.3 m depth, in these 40 points, and analyzed for sand, silt, and clay content; gravimetric water content; and electrical conductivity of saturated soil paste. Coefficients of correlation between ECaand gravimetric soil water content (0.685 for ECa-V and 0.649 for ECa-H) were higher than those between ECaand clay content (ranging from 0.197 to 0.495, when different ECarecording dates were taken into account). Ordinary and universal kriging have been used to assess the patterns of spatial variability of the ECadata sets recorded at successive dates and the analyzed soil properties. Ordinary and universal cokriging methods have improved the estimation of gravimetric soil water content using the data of ECaas secondary variable with respect to the use of ordinary kriging.

scholarly journals Using an inverse modelling approach to evaluate the water retention in a simple water harvesting technique

2009 ◽  
Vol 6 (3) ◽  
pp. 4265-4306 ◽  
Author(s):  
K. Verbist ◽  
W. M. Cornelis ◽  
D. Gabriels ◽  
K. Alaerts ◽  
G. Soto
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Water Retention ◽  
Measurement Techniques ◽  
Inverse Modelling ◽  
Model Parameters ◽  
Arid Zones ◽  
Water Harvesting ◽  
Data Set

Abstract. In arid and semi-arid zones runoff harvesting techniques are often applied to increase the water retention and infiltration on steep slopes. Additionally, they act as an erosion control measure to reduce land degradation hazards. Nevertheless, few efforts were observed to quantify the water harvesting processes of these techniques and to evaluate their efficiency. In this study a combination of detailed field measurements and modelling with the HYDRUS-2D software package was used to visualize the effect of an infiltration trench on the soil water content of a bare slope in Northern Chile. Rainfall simulations were combined with high spatial and temporal resolution water content monitoring in order to construct a useful dataset for inverse modelling purposes. Initial estimates of model parameters were provided by detailed infiltration and soil water retention measurements. Four different measurement techniques were used to determine the saturated hydraulic conductivity (Ksat) independently. Tension infiltrometer measurements proved a good estimator of the Ksat value and a proxy for those measured under simulated rainfall, whereas the pressure and constant head well infiltrometer measurements showed larger variability. Six different parameter optimization functions were tested as a combination of soil-water content, water retention and cumulative infiltration data. Infiltration data alone proved insufficient to obtain high model accuracy, due to large scatter on the data set, and water content data were needed to obtain optimized effective parameter sets with small confidence intervals. Correlation between observed soil water content and simulated values was as high as R2=0.93 for ten selected observation points used in the model calibration phase, with overall correlation for the 22 observation points equal to 0.85. Model results indicate that the infiltration trench has a significant effect on soil water storage, especially at the base of the trench.

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.

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