Geophysical methods can provide three-dimensional (3D), spatially continuous estimates of soil moisture. However, point-to-point comparisons of geophysical properties to measure soil moisture data are frequently unsatisfactory, resulting in geophysics being used for qualitative purposes only. This is because (1) geophysics requires models that relate geophysical signals to soil moisture, (2) geophysical methods have potential uncertainties resulting from smoothing and artifacts introduced from processing and inversion, and (3) results from multiple geophysical methods are not easily combined within a single soil moisture estimation framework. To investigate these potential limitations, an irrigation experiment was performed wherein soil moisture was monitored through time, and several surface geophysical datasets indirectly sensitive to soil moisture were collected before and after irrigation: ground penetrating radar, electrical resistivity tomography (ERT), and frequency domain electromagnetics (FDEM). Data were exported in both raw and processed form, and then snapped to a common 3D grid to facilitate moisture prediction by standard calibration techniques, multivariate regression, and machine learning. A combination of inverted ERT data, raw FDEM, and inverted FDEM data was most informative for predicting soil moisture using a random regression forest model (one-thousand 60/40 training/test cross-validation folds produced root mean squared errors ranging from 0.025-0.046 cm/cm). This cross-validated model was further supported by a separate evaluation using a test set from a physically separate portion of the study area. Machine learning was conducive to a semi-automated model-selection process that could be used for other sites and datasets to locally improve accuracy.

Contamination of vadose-zone systems by chlorinated solvents is widespread, and poses significant potential risk to human health through impacts on groundwater quality and vapor intrusion. Soil vapor extraction (SVE) is the presumptive remedy for such contamination, and has been used successfully for innumerable sites. However, SVE operations typically exhibit reduced mass-removal effectiveness at some point due to the impact of poorly accessible contaminant mass and associated mass-transfer limitations. Assessment of SVE performance and closure is currently based on characterizing contaminant mass discharge associated with the vadose-zone source, and its impact on groundwater or vapor intrusion. These issues are addressed in this overview, with a focus on summarizing recent advances in our understanding of the transport, characterization, and remediation of chlorinated solvents in the vadose zone. The evolution of contaminant distribution over time and the associated impacts on remediation efficiency will be discussed, as will the potential impact of persistent sources on groundwater quality and vapor intrusion. In addition, alternative methods for site characterization and remediation will be addressed.

Most current vapor-intrusion screening models employ the assumption of a subsurface homogenous source distribution, and groundwater data obtained from nearby monitoring wells are usually taken to reflect the source concentration for several nearby buildings. This practice makes it necessary to consider the possible influence of lateral source-building separation. In this study, a new way to estimate subslab (nonbiodegradable) contaminant concentration is introduced that includes the influence of source offset with the help of a conformal transform technique. Results from this method are compared with those from a three-dimensional numerical model. Based on this newly developed method, a possible explanation is provided here for the great variation in the attenuation factors of the soil vapor concentrations of groundwater-to-subslab contaminants found in the EPA vapor-intrusion database.

When using the eddy covariance (EC) method for measuring the ecosystem-atmosphere exchange of sensible and latent heat, it is not uncommon to find that these two energy fluxes fall short of available energy by 20-30 %. As the causes for the energy imbalance are still under discussion, it is currently not clear how the energy balance should be closed. The objective of the present paper is to use independent measurements of evapotranspiration (ET) for empirically devising on how to best close the energy balance. To this end ET of a temperate mountain grassland was quantified during two measurement campaigns using both an open- and a closed-path EC system, lysimeters and an approach scaling up leaf-level stomatal conductance to canopy level transpiration. Our study showed that both EC systems underestimated ET measured independently by lysimeters and the up-scaling approach. Best correspondence to independently measured ET was achieved by assigning the entire energy imbalance to ET and by adjusting ET according to the average energy balance ratio during the first and second measurement campaign, respectively. Due to a large spatial variability in ET during the first measurement campaign and given large differences in spatial scale between the EC and the independent methods, we are more confident with the comparison of approaches during the second measurement campaign and thus recommend forcing energy balance closure by adjusting for the average energy balance ratio.

Naturally occurring biodegradation of petroleum hydrocarbons in the vadose zone depends on the physical soil environment influencing field-scale gas exchange and pore-scale microbial metabolism. In this study, we evaluated the effect of soil physical heterogeneity on biodegradation of petroleum vapors in a 16-m-deep, layered vadose zone. Soil slurry experiments (soil/water ratio 10:30 w/w, 25°C) on benzene biodegradation under aerobic and well-mixed conditions indicated that the biodegradation potential in different textured soil samples was related to soil type rather than depth, in the order: sandy loam > fine sand > limestone. Similarly, O(2) consumption rates during in situ respiration tests performed at the site were higher in the sandy loam than in the fine sand, although the difference was less significant than in the slurries. Laboratory and field data generally agreed well and suggested a significant potential for aerobic biodegradation, even with nutrient-poor and deep subsurface conditions. In slurries of the sandy loam, the biodegradation potential declined with increasing in situ water saturation (i.e., decreasing air-filled porosity in the field). This showed a relation between antecedent undisturbed field conditions and the slurry biodegradation potential, and suggested airfilled porosity to be a key factor for the intrinsic biodegradation potential in the field.

Recently, we have developed a two-dimensional analytical petroleum vapor intrusion model, PVI2D (petroleum vapor intrusion, two-dimensional), which can help users to easily visualize soil gas concentration profiles and indoor concentrations as a function of site-specific conditions such as source strength and depth, reaction rate constant, soil characteristics, and building features. In this study, we made a full comparison of the results returned by PVI2D and those obtained using Abreu and Johnson's three-dimensional numerical model (AJM). These comparisons, examined as a function of the source strength, source depth, and reaction rate constant, show that PVI2D can provide similar soil gas concentration profiles and source-to-indoor air attenuation factors (within one order of magnitude difference) as those by the AJM. The differences between the two models can be ascribed to some simplifying assumptions used in PVI2D and to some numerical limitations of the AJM in simulating strictly piecewise aerobic biodegradation and no-flux boundary conditions. Overall, the obtained results show that for cases involving homogenous source and soil, PVI2D can represent a valid alternative to more rigorous three-dimensional numerical models.