Just-Accepted Journal Articles

Just-Accepted Articles are peer-reviewed, accepted manuscripts that have been assigned Digital Object Identifiers (DOIs) and undergo the normal publication process (copy editing, page composition, proofing by author, and finalization). A Just-Accepted article listing includes an abstract and the DOI (scroll).  The article is removed when the final version of the manuscript is ready and assigned to a Journal of Environmental & Engineering Geophysics (JEEG) issue, becoming the official version of the article. The Just Accepted article has the same DOI that appears on the official version of the article; therefore, citations made to an article during the Just-Accepted stage will continue to link to the article's official version.  EEGS Members can access the full, preliminary article via this "member-only" link:  Just-Accepted Articles with full article PDF

Applications and Analytical Methods of Ground Penetrating Radar for Soil Characterization in a Silvopastoral System
Authors:  Harrison Wakefield Smith; Phillip Owens; Amanda Ashworth

DOI: 10.32389/JEEG22-001

ABSTRACT: The use of ground penetrating radar (GPR) for soil characterization has grown rapidly in recent years due to substantial increases in computer processing power and advances in GPR methodologies. However, few studies have focused on applied GPR analysis for soil characterization and decision making in agricultural systems. In this study, we explored applications of some common qualitative and quantitative methods for GPR analysis and characterization of subsurface conditions in a silvopasture system. We analyzed GPR results using traditional visual interpretation methods to delineate depth to bedrock, clay layers, and other important soil features. Estimates of depth to bedrock correlated well with values measured in the field (r_s=0.61,p<0.01), and estimates of depth to clay layers were marginally correlated with observed values (r_s=047,p=0.09). We also extracted attributes from GPR images to train a random forest regression model to predict coarse fragment percentage and percent clay content. GPR attributes were found to be good predictors of soil coarse fragments, with an R2 value of 0.81 and root mean square error (RMSE) of 18.82 for test data. Our results demonstrate GPR can provide valuable information on subsurface features in silvopastoral systems. These results also suggest a strong potential for machine learning algorithms in GPR data analytics. Data generated using these methods could be integrated with or used to validate existing digital soil mapping methods and contribute to better understanding of subsurface characteristics for optimized soil management in silvopastoral systems.

Keywords: ground penetrating radar; soil characterization; agriculture; random forest; modeling


Integrated Agrogeophysical Approach for Investigating Soil Pipes in Agricultural Fields
Authors:  Md Abdus Samad; Leti T. Wodajo; Parsa Bakhtiari Rad; Md Lal Mamud; Craig J. Hickey

DOI: 10.32389/JEEG22-007

ABSTRACT: Soil erosion is one of the most significant challenges for soil management and agri-food production threatening human habitat and livelihood. Although soil erosion due to surficial processes is well-studied, erosion due to subsurface processes such as internal soil pipes has often been overlooked. Internal soil pipes directly contribute to the total soil loss in agricultural fields and impede agricultural sustainability. Locating, measuring, and mapping internal soil pipes and their networks are vital to assessing the total soil loss in agricultural fields. Their hidden and uncorrelated nature of subsurface occurrences constricts the applicability of manual and remote sensing-based detection techniques. Non-invasive agrogeophysical methods can overcome these limitations with detailed subsurface pictures and high spatial resolution. In this study, the applicability of three agrogeophysical methods including seismic refraction tomography (SRT), electrical resistivity tomography (ERT), and ground-penetrating radar (GPR) was tested at Goodwin Creek, an experimental field site with established internal soil pipes. SRT showed low P and S wave velocities anomalies in soil pipe-affected zones. ERT results indicated the location of soil pipes with high resistivity anomalies. However, both SRT and ERT lack resolution to identify individual soil pipes. GPR diffraction hyperbolas and their apexes however effectively-identified individual soil pipes. The agrogeophysical anomalies for soil pipes were compared with the low penetration resistance of the cone penetrologger (CPL) results. Correspondence between low PR in CPL and agrogeophysical anomalies verify the locations of internal soil pipe-affected zones. Moreover, the fragipan layer is identified below the soil pipe-affected zone by all three methods.

Keywords: Soil erosion Soil pipes Seismic refraction tomography Electrical resistivity tomography GPR