Advances in Ground Penetrating Radar application for estimating soil hydraulic properties: A mini review.

For water dynamics investigation in unsaturated (vadose) zones, ground penetrating radar is a popular hydro-geophysical method because it is non-invasive for soil, has high resolution and the results have a direct link with water content. Soil water content and soil hydraulic properties are two key factors for describing the water dynamics in vadose zones. There has been tremendous progress in soil water content and soil hydraulic properties estimation with ground penetrating radar. The purpose of this paper is to provide an overview of the application of ground penetrating radar for soil water dynamics studies. This paper first summarizes various methods for the determination of soil water content. including traditional methods in the surveys of surface ground penetrating radar, borehole ground penetrating radar, and off-ground ground penetrating radar, as well as relatively new methods, such as full waveform inversion, the average envelope amplitude method, and the frequency shift method. This paper further provides a review for estimating soil hydraulic properties with GPR according to the types of ground penetrating radar data. We hope that this review can provide a reference for the application of ground penetrating radar in soil water dynamics studies in the future.

Incorporating biochar (BC) as a soil amendment has become a prominent agricultural management practice since it has many advantages. Most soils amended with BC have shown improvements in soil physical and hydraulic properties, including bulk density, soil porosity, water retention, field capacity, and permanent wilting point. Ground-penetrating radar (GPR) is a non-destructive geophysical technique that is used to study soil properties and state variables. Yet, there is a lack of research studying the influence of amendments on soil hydrology using GPR.  Therefore, this study was aimed at evaluating the ability of GPR in assessing the effect of BC on soil hydrology. The experiment was conducted under laboratory conditions using plastic containers measuring 28.6 cm in length, 20 cm in width and 16.4 cm in height. These plastic containers were filled up to 14 cm height with three different treatments (T); T1 (100% Sand+0% BC), T2 (99.5% Sand+0.5% BC), and T3 (98% Sand+2% BC) on a mass basis. Soil moisture sensors were placed horizontally at 2, 7, and 12 cm depths while packing the containers. The GPR data were collected using 1000 MHz center frequency transducers by keeping transmitter and receiver on opposite sides of the container (zero-offset profiling survey) at 20 cm antenna offset. Data were collected before, during, and after the wetting process over a one-hour timeframe. A 204 mL of water was applied every 4 min (13 times) to increase the soil water content at each time by 2% from initial water content. The GPR data were processed, and radargrams were prepared to observe the wetting front movement. Soil water contents were estimated utilizing the travel time of the GPR direct wave through the treatment media. GPR travel time and moisture sensor data were compared in each treatment. The GPR estimated soil water contents correlated well with moisture sensor data (correlation coefficient (r)>0.93) in all three treatments. Results have shown that the travel time of GPR direct wave responded differently for three treatments. The rate of change in GPR estimated soil water content over time exhibits an increase with the percentage of BC (T1

Brazil is the world’s largest sugarcane producer with projections for expanding the current area by 30% in the coming years, mainly in areas previously occupied by pastures. We assess soil water changes induced by land-use change (LUC) for sugarcane expansion in the central-south region of Brazil. For that purpose, soil samples were collected in a typical LUC sequence (native vegetation–pasture–sugarcane) in two contrasting soil textures (i.e., sandy and clayey). Soil hydro-physical properties such as pores size distribution, bulk density, soil water content, water tension, and drainage time at field capacity, plant-available water, and S-index were analyzed. Our data showed that long-term LUC from native vegetation to extensive pasture induced severe degradation in soil physical quality and soil water dynamics. However, conventional tillage used during conversion from pasture to sugarcane did not cause additional degradation on soil structure and soil water dynamics. Over time, sugarcane cultivation slightly impaired soil water and physical conditions, but only in the 10–20 cm layer in both soils. Therefore, we highlight that sustainable management practices to enhance soil physical quality and water dynamics in sugarcane fields are needed to prevent limiting conditions to plant growth and contribute to delivering other ecosystem services.

Information on the spatiotemporal variability of soil properties and states within the agricultural landscape is vital to identify management zones supporting precision agriculture (PA). Ground-penetrating radar (GPR) and electromagnetic induction (EMI) techniques have been applied to assess soil properties, states, processes, and their spatiotemporal variability. This paper reviews the fundamental operating principles of GPR and EMI, their applications in soil studies, advantages and disadvantages, and knowledge gaps leading to the identification of the difficulties in integrating these two techniques to complement each other in soil data studies. Compared to the traditional methods, GPR and EMI have advantages, such as the ability to take non-destructive repeated measurements, high resolution, being labor-saving, and having more extensive spatial coverage with geo-referenced data within agricultural landscapes. GPR has been widely used to estimate soil water content (SWC) and water dynamics, while EMI has broader applications such as estimating SWC, soil salinity, bulk density, etc. Additionally, GPR can map soil horizons, the groundwater table, and other anomalies. The prospects of GPR and EMI applications in soil studies need to focus on the potential integration of GPR and EMI to overcome the intrinsic limitations of each technique and enhance their applications to support PA. Future advancements in PA can be strengthened by estimating many soil properties, states, and hydrological processes simultaneously to delineate management zones and calculate optimal inputs in the agricultural landscape.

The soil offers numerous challenges to life residing in its porous environment. One of these challenges are fluctuations in soil water content which are accompanied by shifts in soil hydraulic properties. In order to avoid undesirable alterations and optimise growth conditions, plants and bacteria engineer their local environment by release of mucilage and EPS (extracellular polymeric substances). So far, modifications of soil properties were mainly attributed to the intrinsic properties of these highly polymeric blends. In this work, we focused on deriving a mechanistic understanding of how mucilage and EPS interact with the soil pore space and how these interactions impact soil hydraulic properties and water dynamics in the rhizosphere and other biological hotspots in soils. Mucilage and EPS are capable of absorbing large volumes of water, increase the viscosity of the soil solution and decrease its surface tension. Upon drying, mucilage turns water repellent. Here, we proposed a conceptual model linking the intrinsic physical properties of mucilage to their impact on soil hydrology. The increase in viscosity is related to the high content of polymers which can form an interconnected network. As the soil dries, mucilage and EPS become increasingly concentrated, the viscosity of the soil solution locally increases and its surface tension decreases. When a critical viscosity is reached and parts of the polymer network are adsorbed to drying surfaces, the retreat of the liquid front is delayed and its break-up due to capillary forces is prevented. This concept is confirmed by microscopy imaging and high resolution X-ray CT, which revealed that mucilage and EPS form filaments and two-dimensional structures in this process. Upon drying in porous media, mucilage at low concentrations (mass of dry gel per mass of dry soil) resulted in the formation of filaments. With increase in initial mucilage concentration, two-dimensional surfaces formed when the water content was relatively high and the liquid phase connected. Complementary measurements of soil hydraulic properties of mucilage amended soils showed how the formation of these continuous two-dimensional structures impacts soil physical properties, such as soil hydraulic conductivity, soil water retention and vapour diffusion. The maintained liquid connectivity in drying soils, which is caused by the high viscosity, low surface tension and interaction of the polymer network with the soil porous matrix, explains why the hydraulic conductivity of a mucilage amended sandy loam was higher at low soil water content when compared to its control, as shown in evaporation experiments. Additionally, the delayed retreat of the liquid phase at a critical mucilage concentration creates an additional matric (capillary) potential and enhances soil water retention. To separate and quantify this matric (capillary) effect from the intrinsic property of the polymer network to absorb water remains an open task. Furthermore, upon severe soil drying, the network of two-dimensional…

ABSTRACTTo investigate transient dynamics of soil water redistribution during infiltration, we conducted horizontal borehole and surface ground penetrating radar measurements during a 4‐day infiltration experiment at the rhizontron facility in Selhausen, Germany. Zero‐offset ground penetrating radar profiling in horizontal boreholes was used to obtain soil water content information at specific depths (0.2, 0.4, 0.6, 0.8 and 1.2 m). However, horizontal borehole ground penetrating radar measurements do not provide accurate soil water content estimates of the top soil (0–0.1 m depth) because of interference between direct and critically refracted waves. Therefore, surface ground penetrating radar data were additionally acquired to estimate soil water content of the top soil. Due to the generation of electromagnetic waveguides in the top soil caused by infiltration, a strong dispersion in the ground penetrating radar data was observed in 500 MHz surface ground penetrating radar data. A dispersion inversion was thus performed with these surface ground penetrating radar data to obtain soil water content information for the top 0.1 m of the soil. By combining the complementary borehole and surface ground penetrating radar data, vertical soil water content profiles were obtained, which were used to investigate vertical soil water redistribution. Reasonable consistency was found between the ground penetrating radar results and independent soil water content data derived from time domain reflectometry measurements. Because of the improved spatial representativeness of the ground penetrating radar measurements, the soil water content profiles obtained by ground penetrating radar better matched the known water storage changes during the infiltration experiment. It was concluded that the combined use of borehole and surface ground penetrating radar data convincingly revealed spatiotemporal soil water content variation during infiltration. In addition, this setup allowed a better quantification of water storage, which is a prerequisite for future applications, where, for example, the soil hydraulic properties will be estimated from ground penetrating radar data.

Comparison of soil water content estimation equations using ground penetrating radar

Soil moisture prediction of bare soil profiles using diffuse spectral reflectance information and vadose zone flow modeling

The appropriate of petrophysical relationship is needed for Soil Water Content (SWC) estimation especially when using Ground Penetrating Radar (GPR). Ground penetrating radar is a geophysical tool that provides indirectly the parameter of SWC. This paper examines the performance of few published petrophysical relationships to obtain SWC estimates from in-situ GPR common-offset survey measurements with gravimetric measurements at peat soil area. Gravimetric measurements were conducted to support of GPR measurements for the accuracy assessment. Further, GPR with dual frequencies (250MHhz and 700MHz) were used in the survey measurements to obtain the dielectric permittivity. Three empirical equations (i.e. Roth’s equation, Schaap’s equation and Idi’s equation) were selected for the study, used to compute the soil water content from dielectric permittivity of the GPR profile. The results indicate that Schaap’s equation provides strong correlation with SWC as measured by GPR data sets and gravimetric measurements.

Dynamics of profile soil water vary with terrain, soil, and plant characteristics. The objectives addressed here are to quantify dynamic soil water content over a range of slope positions, infer soil profile water fluxes, and identify locations most likely influenced by multidimensional flow. The instrumented 56 ha watershed lies mostly within a dryland (rainfed) wheat field in semiarid eastern Colorado. Dielectric capacitance sensors were used to infer hourly soil water content for approximately 8 years (minus missing data) at 18 hillslope positions and four or more depths. Based on previous research and a new algorithm, sensor measurements (resonant frequency) were rescaled to estimate soil permittivity, then corrected for temperature effects on bulk electrical conductivity before inferring soil water content. Using a mass‐conservation method, we analyzed multitemporal changes in soil water content at each sensor to infer the dynamics of water flux at different depths and landscape positions. At summit positions vertical processes appear to control profile soil water dynamics. At downslope positions infrequent overland flow and unsaturated subsurface lateral flow appear to influence soil water dynamics. Crop water use accounts for much of the variability in soil water between transects that are either cropped or fallow in alternating years, while soil hydraulic properties and near‐surface hydrology affect soil water variability across landscape positions within each management zone. The observed spatiotemporal patterns exhibit the joint effects of short‐term hydrology and long‐term soil development. Quantitative methods of analyzing soil water patterns in space and time improve our understanding of dominant soil hydrological processes and provide alternative measures of model performance.

Soil water content (SWC) estimation is important for many areas including hydrology, agriculture, soil science, and environmental science. Ground penetrating radar (GPR) is a promising geophysical method for SWC estimation. However, at present, most of the studies are based on partial information of GPR, like travel time or amplitude information, to invert the SWC. Full waveform inversion (FWI) can use the information of the entire waveform, which can improve the accuracy of parameter estimation. This study proposes a novel SWC estimation scheme by using the FWI of GPR, optimized by the grey wolf optimizer (GWO) algorithm. The proposed scheme includes a petrophysical relationship to link the SWC with the relative dielectric permittivity, 1D GPR forward modeling, and a GWO optimization algorithm. First, numerical modeling was carried out, and the proposed scheme was applied to both noise‐free and noisy data to verify its applicability. Then, the proposed method was applied to data collected from a field experimental site. These results, derived from both synthetic and real datasets, show that the proposed inversion scheme resulted in a good match between the observed and calculated GPR data. In the numerical modeling, it was observed that the SWC could be inverted accurately, even when noise was present in the data. These demonstrate that the GWO method can be applied for the quantitative interpretation of GPR data. The proposed scheme shows potential for SWC estimation by using GPR full waveform data.

Despite the widely held assumption that trees negatively affect the local water budget in densely planted tree plantations, we still lack a clear understanding of the underlying processes by which canopy cover influences local soil water dynamics in more open, humid tropical ecosystems. In this study, we propose a new conceptual model that uses a combination of stable isotope and soil moisture measurements throughout the soil profile to assess potential mechanisms by which evaporation (of surface soil water and of canopy‐intercepted rainfall) affects the relationship between surface soil water isotopic enrichment (lc‐excess) and soil water content. Our conceptual model was derived from soil water data collected under deciduous and evergreen plants in a shade grown coffee agroforestry system in Costa Rica. Reduced soil moisture under shade trees during the “drier” season, coinciding when these trees were defoliated, was largely the result of increase soil water evaporation as indicated by the positive relationship between soil water content and lc‐excess of surface soil water. In contrast, the evergreen coffee shrubs had a higher leaf area index during the “drier” season, leading to enhanced rainfall interception and a negative relationship between lc‐excess and soil water content. During the wet season, there was no clear relationship between soil water content and between lc‐excess of surface soil water. Greater surface soil water under coffee during the dry season may, in part, explain greater preferential flow under coffee compared with under trees in conditions of low rainfall intensities. However, with increasing rainfall intensities during the wet season, there was no obvious difference in preferential flow between the two canopy covers. Results from this study indicate that our new conceptual model can be used to help disentangling the relative influence of canopy cover on local soil water isotopic composition and dynamics, yet also stresses the need for additional measurements to better resolve the underlying processes by which canopy structure influences local water dynamics.

Accurate characterization of near-surface soil water content is vital for guiding agricultural management decisions and for reducing the potential negative environmental impacts of agriculture. Characterizing the near-surface soil water content can be difficult, as this parameter is often both spatially and temporally variable, and obtaining sufficient measurements to describe the heterogeneity can be prohibitively expensive. Understanding the spatial correlation of near-surface soil water content can help optimize data acquisition and improve understanding of the processes controlling soil water content at the field scale. In this study, ground penetrating radar (GPR) methods were used to characterize the spatial correlation of water content in a three acre field as a function of sampling depth, season, vegetation, and soil texture. GPR data were acquired with 450 MHz and 900 MHz antennas, and measurements of the GPR groundwave were used to estimate soil water content at four different times. Additional water content estimates were obtained using time domain reflectometry measurements, and soil texture measurements were also acquired. Variograms were calculated for each set of measurements, and comparison of these variograms showed that the horizontal spatial correlation was greater for deeper water content measurements than for shallower measurements. Precipitation and irrigation were both shown to increase the spatial variability of water content, while shallowly-rooted vegetation decreased the variability. Comparison of the variograms of water content and soil texture showed that soil texture generally had greater small-scale spatial correlation than water content, and that the variability of water content in deeper soil layers was more closely correlated to soil texture than were shallower water content measurements. Lastly, cross-variograms of soil texture and water content were calculated, and co-kriging of water content estimates and soil texture measurements showed that geophysically-derived estimates of soil water content could be used to improve spatial estimation of soil texture.

Estimating Soil Water Content (SWC) for peat soil is fundamental parameters that are essential for quality of soil especially during drying periods. Transformations and subsequent losses to groundwater or atmosphere are mediated by moisture conditions in the soil. Success or failure of food, fiber, and energy production from agricultural crops depends on soil water storage between rainfall and/or irrigation events. Despite this importance, predicting soil water dynamics especially during dry and wet season remains a major challenge in hydrology, environmental science, agriculture, and engineering. Hence this study aims to determine the mathematical model for the site-specific of petrophysical relationship for wet and dry season between dielectric permittivity and water content of the peat soil. Field survey measurements and laboratory measurements were conducted at peat soil area. Soil samples were collected from 0 to 1.0m layer for 20 point. Dielectric permittivity values were determined using 2D adjusted of parallel plate capacitor. The oven-drying process was conducted for soil water content estimation. Linear and polynomial models were adjusted for the peat soil between dielectric permittivity and water content. From the results shows that the modeled of site-specific of petrophysical relationship gives better correlation for dry season (R2=0.9812) and wet season (R2=0.9441). The comparisons of GPR-derived estimates of water content to gravimetric measurements showed that GPR measurements using the modeled site-specific petrophysical relationships for both season had a root mean square error of 0.017 (wet season) and 0.25 (dry season). This indicates that the modeled equations can be used to estimate the water content of the peat soil when measured it by using GPR. Besides, through verifying the model of site-specific of petrophysical relationship using ground penetrating radar (GPR) along with three proposed model (Roth equation, Schaap equation and Idi equation) where the season was taken as consideration, the adjusted models provide sufficient accuracy to determine soil water content of peat soil for wet and dry season.

Ground-Penetrating Radar (GPR) is a non-invasive electromagnetic geophysical method, which is sensitive to variations of subsurface dielectric properties. With this, GPR has become a versatile tool in various fields of geophysics and the soil science. In particular the determination of field-scale soil water content has drawn considerable research interest over the past decade. However, the quantifiability of achieved results remains often contested. In this thesis, three approaches for a quantitative use of GPR in soil hydrology are presented. First, a new calibration approach is developed for quantifying near-surface soil water contents with GPR and its applicability is demonstrated in field applications. Second, the ability of GPR methods for monitoring soil water dynamics is tested in well-controlled field experiments featuring imbibition into and drainage from a known subsurface structure. Finally, GPR applications are demonstrated in the broader context of developing monitoring schemes at a set of representative sites in a highly structured watershed.