Quantifying field-scale soil moisture using electrical resistivity imaging

Schwartz, Benjamin; Schreiber, Madeline E.; Yan, Tingting

doi:10.1016/j.jhydrol.2008.08.027

Cited by 100 publications

(70 citation statements)

References 29 publications

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“…The proper understanding of the drivers of SWC distribution dynamics is therefore crucial for accurate modelling (Western et al, 2003). Yet, quantifying soil moisture in unsaturated environments is difficult due to the complexity of unsaturated hydrologic systems and problems associated with obtaining accurate and spatially representative measurements of soil moisture in a heterogeneous environment (Schwartz et al, 2008). It is therefore challenging to quantify the SWC variability at the field scale.…”

Section: Introductionmentioning

confidence: 99%

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Three-dimensional monitoring of soil water content in a maize field using Electrical Resistivity Tomography

Beff

Günther

Vandoorne

et al. 2013

Hydrol. Earth Syst. Sci.

124

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Abstract.A good understanding of the soil water content (SWC) distribution at the field scale is essential to improve the management of water, soil and crops. Recent studies proved that Electrical Resistivity Tomography (ERT) opens interesting perspectives in the determination of the SWC distribution in 3 dimensions (3-D). This study was conducted (i) to check and validate how ERT is able to monitor SWC distribution in a maize field during the late growing season; and (ii) to investigate how maize plants and rainfall affect the dynamics of SWC distribution. Time Domain Reflectometry (TDR) measurements were used to validate ERT-inverted SWC values. Evolution of water mass balance was also calculated to check whether ERT was capable of giving a reliable estimate of soil water stock evolution. It is observed that ERT was able to give the same average SWC as TDR (R 2 = 0.98). In addition, ERT gives better estimates of the water stock than TDR thanks to its higher spatial resolution. The high resolution of ERT measurements also allows for the discrimination of SWC heterogeneities. The SWC distribution showed that alternation of maize rows and inter-rows was the main influencing factor of the SWC distribution. The drying patterns were linked to the root profiles, with drier zones under the maize rows. During short periods, with negligible rainfall, the SWC decrease took place mainly in the two upper soil horizons and in the inter-row area. In contrast, rainfall increased the SWC mostly under the maize rows and in the upper soil layer. Nevertheless, the total amount of rainfall during the growing season was not sufficient to modify the SWC patterns induced by the maize rows. During the experimental time, there was hardly any SWC redistribution from maize rows to inter-rows. Yet, lateral redistribution from inter-rows to maize rows induced by potential gradient generates SWC decrease in the inter-row area and in the deeper soil horizons.

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Section: Introductionmentioning

confidence: 99%

“…However, more recently, a few studies tried to obtain the actual SWC distribution validated with TDR probes. Brunet et al (2010) and Schwartz et al (2008) inferred 2-D SWC maps along transects. Garré et al (2012) developed a methodology to measure the SWC dynamics in a cropped field.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional monitoring of soil water content in a maize field using Electrical Resistivity Tomography

Beff

Günther

Vandoorne

et al. 2013

Hydrol. Earth Syst. Sci.

124

View full text Add to dashboard Cite

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“…Soil-water status sensors such as tensiometers, capacitive sensors, or neutron scattering may be used to monitor the performance and uniformity of irrigation systems. Such methods, though, are 1-dimensional and smallscale, since they provide information within a region of a few centimetres from the probe; therefore, they poorly cover the (Schwartz et al, 2008). Furthermore, soil sensors cannot discern whether water has been drained, up-taken by plants, or redistributed within the root zone and thus it is difficult to translate this kind of data into irrigation decisions.…”

Section: Resultsmentioning

confidence: 99%

Electrical resistivity tomography to delineate greenhouse soil variability

Rossi¹,

Amato²,

Bitella³

et al. 2013

International Agrophysics

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Appropriate management of soil spatial variability is an important tool for optimizing farming inputs, with the result of yield increase and reduction of the environmental impact in field crops. Under greenhouses, several factors such as non-uniform irrigation and localized soil compaction can severely affect yield and quality. Additionally, if soil spatial variability is not taken into account, yield deficiencies are often compensated by extra-volumes of crop inputs; as a result, over-irrigation and overfertilization in some parts of the field may occur. Technology for spatially sound management of greenhouse crops is therefore needed to increase yield and quality and to address sustainability. In this experiment, 2D-electrical resistivity tomography was used as an exploratory tool to characterize greenhouse soil variability and its relations to wild rocket yield. Soil resistivity well matched biomass variation (R2=0.70), and was linked to differences in soil bulk density (R2=0.90), and clay content (R2=0.77). Electrical resistivity tomography shows a great potential in horticulture where there is a growing demand of sustainability coupled with the necessity of stabilizing yield and product quality.

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“…Time domain reflectometry (TDR) and capacitance probes are commonly used to measure soil moisture in shallow soils (Schwartz et al, 2008;Calamita et al, 2012;Beff et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Vegetation Effects on Soil Moisture and Groundwater Recharge in Subtropical Coastal Sand Dunes

Fan¹

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Vegetation can potentially have a strong influence on the water budget and hydrological processes in vegetated ecosystems due to canopy rainfall interception and the partitioning of rainfall into throughfall and stemflow, as well as root water uptake from the vadose zone or groundwater table. This study aims to explore the potential effects of vegetation on soil moisture dynamics and groundwater recharge in a subtropical coastal area of eastern Australia. This area is characterized by highly permeable sands, intense summer rainfall events and three typical vegetation covers (exotic pine plantation, native woodland and grassland).First of all, the spatial variability of both throughfall and stemflow at the soil surface was investigated in a 12-year-old managed pine plantation over one year on Bribie Island using tipping-bucket rain gauges. Rainfall loss by canopy interception and subsequent evaporation from this pine plantation and a native banksia woodland were also quantified and compared using field measurements and two analytical models of rainfall interception.In addition, the potential hydrological impacts of changes in vegetation cover in this shallow sandy groundwater system (depth to water table < 2 m) was evaluated by estimating groundwater recharge and discharge by evapotranspiration (ET g ) under the three contrasting vegetation covers over a 2-year period using the water table fluctuation method and the White method, respectively.To further monitor the actual water percolation processes in deep sand dune profiles (depth to water table > 10 m), spatial patterns and seasonal dynamics of root-zone soil moisture were quantified under three contrasting vegetation covers on North StradbrokeIsland by combining two geophysical techniques: surface electric resistivity tomography (surface ERT) and spatial time domain reflectometry (spatial TDR). Based on the field investigations of rainfall and root distributions at the under-canopy and inter-canopy zones, spatial distributions of vadose zone soil moisture and deep drainage in this subtropical coastal forest overlying deep sand dunes were finally simulated using HYDRUS models.On the Bribie Island sites, the highest throughfall was found on the east side of the tree trunks (~85% of gross rainfall) and the lowest in the midway between tree rows (~68% of gross rainfall) in the pine plantation. These spatial patterns persist for around 84% of recorded rainfall events. This is explained by canopy interception of the inclined rainfall resulting from the prevailing easterly wind direction throughout the experiment. Annual ii rainfall interception loss in the banksia woodland was lower (~16% of gross rainfall) than that in the pine plantation (~23% of gross rainfall) due to the lower canopy storage capacity and higher aerodynamic resistance of the banksia woodland. The RGAM and WiMo models predicted the interception losses from these forest stands reasonably well.The average annual gross recharge was largest at the sparse grassland site, followed by the exotic...

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Quantifying field-scale soil moisture using electrical resistivity imaging

Cited by 100 publications

References 29 publications

Three-dimensional monitoring of soil water content in a maize field using Electrical Resistivity Tomography

Three-dimensional monitoring of soil water content in a maize field using Electrical Resistivity Tomography

Electrical resistivity tomography to delineate greenhouse soil variability

Vegetation Effects on Soil Moisture and Groundwater Recharge in Subtropical Coastal Sand Dunes

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