Measuring soil surface water content in irrigated areas of southern Tunisia using full‐waveform inversion of proximal GPR data

Lambot, Sébastien; Slob, Evert; Chavarro, Diana; Lubczynski, M.; Vereecken, Harry

doi:10.3997/1873-0604.2008028

Cited by 65 publications

(30 citation statements)

References 41 publications

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“…Only two parameters are considered in the inversion, i.e., the soil dielectric permittivity ε and the antenna height above the soil h 0 , as the electromagnetic properties of the air layer are known (ε a = 1 and σ a = 0 S/m). This robust inversion procedure was used for soil moisture retrieval from GPR data in field conditions in [Weihermüller et al, 2007, Lambot et al, 2008b.…”

Section: One-layered Modelmentioning

confidence: 99%

“…The method resorts to fullwaveform forward and inverse modeling of the GPR signal, which inherently maximizes information retrieval capabilities from the radar data in terms of quantity and accuracy. Specific inversion strategies have been developed for the retrieval of soil surface dielectric permittivity and correlated water content [Lambot et al, 2006] and have been applied to field data [Lambot et al, 2008b]. In addition, this ground-based GPR can provide high-resolution soil moisture maps, bridging the scale gap between small-scale invasive measurement techniques and spaceborne sensors.…”

Section: Introductionmentioning

confidence: 99%

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Mapping shallow soil moisture profiles at the field scale using full-waveform inversion of ground penetrating radar data

et al. 2011

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Full-waveform inversions were applied to retrieve surface, two-layered and continuous soil moisture profiles from ground penetrating radar (GPR) data acquired in an 11-ha agricultural field situated in the loess belt area in central Belgium. The radar system consisted of a vector network analyzer combined with an off-ground horn antenna operating in the frequency range 200-2000 MHz. The GPR system was computer controlled and synchronized with a differential GPS for real-time data acquisition. Several inversion strategies were also tested using numerical experiments, which in particular demonstrated the potentiality to reconstruct simplified two-layered configurations from more complex, continuous dielectric profiles as prevalent in the environment. The surface soil moisture map obtained assuming a onelayered model showed a global moisture pattern mainly explained by the topography while local moisture patterns indicate a line effect. Two-layered and profile inversions provided consistent estimates with respect to each other and field observations, showing significant moisture increases with depth. However, some discrepancies were observed between the measured and modeled GPR data in the higher frequency ranges, mainly due to surface roughness effects which are not accounted for. The proposed GPR method and inversion strategies show great promise for high-resolution, realtime mapping of soil moisture at the field scale. * julien.minet@uclouvain.be

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Section: One-layered Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mapping shallow soil moisture profiles at the field scale using full-waveform inversion of ground penetrating radar data

et al. 2011

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“…Few studies have applied such an off-ground GPR approach for soil moisture sensing in field conditions (Chanzy et al, 1996;Redman et al, 2002;Or, 2003, 2005). Based on a full-waveform inversion of the GPR data and an accurate GPR system modeling, the off-ground GPR system developed by Lambot et al (2004Lambot et al ( , 2006b) has shown excellent potentialities for surface soil moisture sensing and mapping in field conditions (Weihermüller et al, 2007;Lambot et al, 2008;Jadoon et al, 2010a;Jonard et al, 2010;Minet et al, 2011). The method relies on an accurate radar model that, in particular, accounts for the antenna and antenna-soils interactions.…”

Section: Introductionmentioning

confidence: 99%

Validation of ground penetrating radar full-waveform inversion for field scale soil moisture mapping

Minet

Bogaert

Vanclooster

et al. 2012

Journal of Hydrology

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Ground penetrating radar (GPR) is an efficient method for soil moisture mapping at the field scale, bridging the scale gap between small-scale invasive sensors and large-scale remote sensing instruments. Nevertheless, commonly-used GPR approaches for soil moisture characterization suffer from several limitations and the determination of the uncertainties in GPR soil moisture sensing has been poorly addressed. Herein, we used an advanced proximal GPR method based on full-waveform inversion of ultra-wideband radar data for mapping soil moisture and uncertainties in the soil moisture maps were evaluated by three different methods. First, GPRderived soil moisture uncertainties were computed from the GPR data inversion, according to measurements and modeling errors and to the sensitivity of the electromagnetic model to soil moisture. Second, the reproducibility of the soil moisture mapping was evaluated. Third, GPR-derived soil moisture was compared with ground-truth measurements (soil core sampling). The proposed GPR method appeared to be highly precise and accurate, with spatially averaged GPR inversion uncertainty of 0. and an uncertainty of 0.0233 m 3 m −3 when compared with ground-truth measurements. These uncertainties were mapped and appeared to be related to some local model inadequacies and to small-scale variability of soil moisture. In a soil moisture mapping framework, the interpolation was found to be the determinant source of the observed uncertainties. The proposed GPR method was proven to be largely reliable in terms of accuracy and precision and appeared to be highly efficient for soil moisture * julien.minet@uclouvain.be mapping at the field scale.

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“…The GPR method for soil moisture retrieval was widely validated in laboratory conditions (Lambot et al, 2004(Lambot et al, , 2006Minet et al, 2010) and applied to field conditions (Weihermüller et al, 2007;Lambot et al, 2008b;Jadoon et al, 2010;Minet et al, 2011). The GPR-derived soil moisture uncertainty was quantified in Jadoon et al (2010) and a RMSE of 0.025 in terms of volumetric water content between TDR and GPR estimates was found.…”

Section: Sensing Of Soil Moisture By Ground Penetrating Radarmentioning

confidence: 99%

“…In that respect, GPR has shown great potential to accurately characterise soil moisture at the field scale with high resolution (Serbin and Or, 2005;Weihermüller et al, 2007;Lambot et al, 2008b;Minet et al, 2011). As pointed out by Western et al (1999), high-resolution soil moisture datasets are required to readily assess the effect of antecedent soil moisture conditions, rather than relying on few point values that may not capture the real soil moisture patterns.…”

Section: Introductionmentioning

confidence: 99%

Effect of high-resolution spatial soil moisture variability on simulated runoff response using a distributed hydrologic model

Minet

Laloy

Lambot

et al. 2011

Hydrol. Earth Syst. Sci.

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Abstract. The importance of spatial variability of antecedent soil moisture conditions on runoff response is widely acknowledged in hillslope hydrology. Using a distributed hydrologic model, this paper aims at investigating the effects of soil moisture spatial variability on runoff in various field conditions and at finding the structure of the soil moisture pattern that approaches the measured soil moisture pattern in terms of field scale runoff. High spatial resolution soil moisture was surveyed in ten different field campaigns using a proximal ground penetrating radar (GPR) mounted on a mobile platform. Based on these soil moisture measurements, seven scenarios of spatial structures of antecedent soil moisture were used and linked with a field scale distributed hydrological model to simulate field scale runoff. Accounting for spatial variability of soil moisture resulted in general in higher predicted field scale runoff as compared to the case where soil moisture was kept constant. The ranges of possible hydrographs were delineated by extreme scenarios where soil moisture was directly and inversely modelled according to the topographic wetness index (TWI). These behaviours could be explained by the sizes and locations of runoff contributing areas, knowing that runoff was generated by infiltration excess over a certain soil moisture threshold. The most efficient scenario for modelling the within field spatial structure of soil moisture appeared to be when soil moisture is directly arranged according to the TWI, especially when measured soil moisture and TWI were correlated. The novelty of this work is to benefit from a large set of high-resolution Correspondence to: J. Minet (julien.minet@uclouvain.be) soil moisture measurements allowing to model effectively the within field distribution of soil moisture and its impact on the field scale hydrograph. These observations contributed to the current knowledge of the impact of antecedent soil moisture spatial variability on field scale runoff.

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Measuring soil surface water content in irrigated areas of southern Tunisia using full‐waveform inversion of proximal GPR data

Cited by 65 publications

References 41 publications

Mapping shallow soil moisture profiles at the field scale using full-waveform inversion of ground penetrating radar data

Mapping shallow soil moisture profiles at the field scale using full-waveform inversion of ground penetrating radar data

Validation of ground penetrating radar full-waveform inversion for field scale soil moisture mapping

Effect of high-resolution spatial soil moisture variability on simulated runoff response using a distributed hydrologic model

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