Geophysics provides a multidimensional suite of investigative methods that are transforming our ability to see into the very fabric of the subsurface environment, and monitor the dynamics of its fluids and the biogeochemical reactions that occur within it. Here we document how geophysical methods have emerged as valuable tools for investigating shallow subsurface processes over the past two decades and offer a vision for future developments relevant to hydrology and also ecosystem science. The field of “hydrogeophysics” arose in the late 1990s, prompted, in part, by the wealth of studies on stochastic subsurface hydrology that argued for better field-based investigative techniques. These new hydrogeophysical approaches benefited from the emergence of practical and robust data inversion techniques, in many cases with a view to quantify shallow subsurface heterogeneity and the associated dynamics of subsurface fluids. Furthermore, the need for quantitative characterization stimulated a wealth of new investigations into petrophysical relationships that link hydrologically relevant properties to measurable geophysical parameters. Development of time-lapse approaches provided a new suite of tools for hydrological investigation, enhanced further with the realization that some geophysical properties may be sensitive to biogeochemical transformations in the subsurface environment, thus opening up the new field of “biogeophysics.” Early hydrogeophysical studies often concentrated on relatively small “plot-scale” experiments. More recently, however, the translation to larger-scale characterization has been the focus of a number of studies. Geophysical technologies continue to develop, driven, in part, by the increasing need to understand and quantify key processes controlling sustainable water resources and ecosystem services.

/pdf/the-emergence-of-hydrogeophysics-for-improved-understanding-1kxmx4m0xa.pdf

The emergence of hydrogeophysics for improved understanding of subsurface processes over multiple scales.

Changes in climate patterns are dramatically influencing some agricultural areas. Arid, semi‐arid and coastal agricultural areas are especially vulnerable to climate change impacts on soil salinity. Inventorying and monitoring climate change impacts on salinity are crucial to evaluate the extent of the problem, to recognize trends and to formulate irrigation and crop management strategies that will maintain the agricultural productivity of these areas. Over the past three decades, Corwin and colleagues at the U.S. Salinity Laboratory (USSL) have developed proximal sensor and remote imagery methodologies for assessing soil salinity at multiple scales. The objective of this paper is to evaluate the impact climate change has had on selected agricultural areas experiencing weather pattern changes, with a focus on the use of proximal and satellite sensors to assess salinity development. Evidence presented in case studies for Californiaʼs San Joaquin Valley (SJV) and Minnesotaʼs Red River Valley (RRV) demonstrates the utility of these sensor approaches in assessing soil salinity changes due to changes in weather patterns. Agricultural areas are discussed where changes in weather patterns have increased root‐zone soil salinity, particularly in areas with shallow water tables (SJV and RRV), coastal areas with seawater intrusion (e.g., Bangladesh and the Gaza Strip) and water‐scarce areas potentially relying on degraded groundwater as an irrigation source (SJV and Murray‐Darling River Basin). Trends in salinization due to climate change indicate that the infrastructure and protocols to monitor soil salinity from field to regional to national to global scales are needed. HIGHLIGHTS: Climate change will have a negative impact on agriculture, particularly in arid regions. Proximal/remote sensors are useful to assess climate change impact on soil salinity across scales. Salt‐water intrusion, shallow water tables and degraded water reuse will increase soil salinity. Infrastructure and protocols to monitor soil salinity across multiple scales are needed.

Climate change impacts on soil salinity in agricultural areas

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=2462&context=usdaarsfacpub

The use of electromagnetic induction techniques in soils studies

During the past 80 years, ground-penetrating radar (GPR) has evolved from a skeptically received glacier sounder to a full multicomponent 3D volume-imaging and characterization device. The tool can be calibrated to allow for quantitative estimates of physical properties such as water content. Because of its high resolution, GPR is a valuable tool for quantifying subsurface heterogeneity, and its ability to see nonmetallic and metallic objects makes it a useful mapping tool to detect, localize, and characterize buried objects. No tool solves all problems; so to determine whether GPR is appropriate for a given problem, studying the reasons for failure can provide an understanding of the basics, which in turn can help determine whether GPR is appropriate for a given problem. We discuss the specific aspects of borehole radar and describe recent developments to become more sensitiveto orientation and to exploit the supplementary information in different components in polarimetric uses of radar data. Multicomponent GPR data contain more diverse geometric information than single-channel data, and this is exploited in developed dedicated imaging algorithms. The evolution of these imaging schemes is discussed for ground-coupled and air-coupled antennas. For air-coupled antennas, the measured radiated wavefield can be used as the basis for the wavefield extrapolator in linear-inversion schemes with an imaging condition, which eliminates the source-time function and corrects for the measured radiation pattern. A handheld GPR system coupled with a metal detector is ready for routine use in mine fields. Recent advances in modeling, tomography, and full-waveform inversion, as well as Green's function extraction through correlation and deconvolution, show much promise in this field.

/pdf/surface-and-borehole-ground-penetrating-radar-developments-2qckwgquor.pdf

Surface and borehole ground-penetrating-radar developments

SUMMARY A meaningful interpretation of geophysical measurements requires an assessment of the space of models that are consistent with the data, rather than just a single, ‘best’ model which does not convey information about parameter uncertainty. For this purpose, a trans-dimensional BayesianMarkovchainMonteCarlo(MCMC)algorithmisdevelopedforassessingfrequencydomain electromagnetic (FDEM) data acquired from airborne or ground-based systems. By sampling the distribution of models that are consistent with measured data and any prior knowledge, valuable inferences can be made about parameter values such as the likely depth to an interface, the distribution of possible resistivity values as a function of depth and non-unique relationships between parameters. The trans-dimensional aspect of the algorithm allows the number of layers to be a free parameter that is controlled by the data, where models with fewer layers are inherently favoured, which provides a natural measure of parsimony and a significant degree of flexibility in parametrization. The MCMC algorithm is used with synthetic examples to illustrate how the distribution of acceptable models is affected by the choice of prior information, the system geometry and configuration and the uncertainty in the measured system elevation. An airborne FDEM data set that was acquired for the purpose of hydrogeological characterization is also studied. The results compare favourably with traditional least-squares analysis, borehole resistivity and lithology logs from the site, and also provide new information about parameter uncertainty necessary for model assessment.

/pdf/a-trans-dimensional-bayesian-markov-chain-monte-carlo-3m3l1zstwg.pdf

A trans-dimensional Bayesian Markov chain Monte Carlo algorithm for model assessment using frequency-domain electromagnetic data

Agricultural Geophysics Overview General Considerations for Geophysical Methods Applied to Agriculture, Allred et al. Past, Present, and Future Trends of Soil Electrical Conductivity Measurement Using Geophysical Methods, Corwin History of Ground-Penetrating Radar Applications in Agriculture, Collins Agricultural Geophysics Measurements and Methods Theoretical Insight on the Measurement of Soil Electrical Conductivity, Corwin et al. Resistivity Methods, Allred et al. Electromagnetic Induction Methods, Daniels et al. Ground Penetrating Radar Methods, Daniels et al. Magnetometry, Self-Potential, and Seismic: Additional Geophysical Methods Having Potentially Significant Future Use in Agriculture, Allred et al. The Global Positioning System and Geographic Information Systems Integration of the Global Positioning System (GPS) to Agricultural Geophysics, Grejner-Brzezinska Integration of Geographic Information Systems (GIS) to Agricultural Geophysics, Merry Agricultural Geophysics Application Examples Resistivity and Electromagnetic Induction Case Histories Introduction to Resistivity and Electromagnetic Case Histories, Allred and Ehsani. Apparent Electrical Conductivity for Delineating Spatial Variability in Soil Properties, Wienhold and Doran Dependence of Soil Apparent Electrical Conductivity (ECa) Upon Soil Texture and Ignition Loss at Various Depths in Two Morainic Loam Soils in SE Norway, Korsaeth Relations Between a Commercial Soil Survey Map Based on Soil Apparent Electrical Conductivity (ECa) and Measured Soil Properties on a Morainic Soil in SE Norway, Korsaeth et al. Mapping Pesticide Partition Coefficients by Electromagnetic Induction, Jaynes Can Apparent Soil Electrical Conductivity Be Used to Map Soil-Herbicide Partition Coefficients? A Case Study in Three Colorado Fields, Shaner et al. Delineating Site-Specific Management Units Using Geospatial Apparent Soil Electrical Conductivity (ECa) Measurements, Corwin et al. Mapping of Soil Drainage Classes Using Topographical Data and Soil Electrical Conductivity, Kravchenko Productivity Zones Based on Bulk Soil Electrical Conductivity: Applications for Dryland Agriculture and Research, Johnson et al. A Four Year Summary of the Use of Soil Conductivity as a Measure of Soil and Crop Status, Eigenberg Mapping of Apparent Soil Electrical Conductivity (ECa) Helps Establish Research Plots at a New Research and Extension Center, Farahani et al. Mapping Golf-Course Features with Electromagnetic Induction, with Examples from Dublin, Ohio, Taylor Comparison of Geoelectrical Instruments in Different Soilscapes, Gebbers and Luck Ground Penetrating Radar Case Histories Introduction to Ground Penetrating Radar Case Histories, Allred. Ground Penetrating Radar Surveys Across a Prototype Surface Barrier to Determine Temporal and Spatial Variations in Soil Moisture, Clement and Ward Soil Water Content Measurement Using the Ground- Penetrating Radar Surface Reflectivity Method, Redman Assessing Spatial and Temporal Soil Water Content Variations with Ground Penetrating Radar, Lennartz et al. Ground Penetrating Radar Mapping of Near-Surface Preferential Flow, Freeland An Application of Ground Penetrating Radar in Golf Course Management, Boniak et al. Ground Penetrating Radar Investigation of a Golf Course Green: Computer Processing and Field Survey Set-Up Considerations, Allred et al. Agricultural Drainage Pipe Detection Using Ground Penetrating Radar, Allred and Daniels Using Ground Penetrating Radar to Estimate Tree Root Mass: Comparing Results from Two Florida Surveys, Butnor at al. Glossary Index

Handbook of Agricultural Geophysics

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Handbook of Agricultural Geophysics