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André Revil

Publications and source records attributed to André Revil.

2 recordsLinked to original sources

Comparison of soil thickness in a zero-order basin in the Oregon Coast Range using a soil probe and electrical resistivity tomography

Accurate estimation of the soil thickness distribution in steepland drainage basins is essential for understanding ecosystem and subsurface response to infiltration. One important aspect of this characterization is assessing the heavy and antecedent rainfall conditions that lead to shallow landsliding. In this paper, we investigate the direct current (DC) resistivity method as a tool for quickly estimating soil thickness over a steep (33–40°) zero-order basin in the Oregon Coast Range, a landslide prone region. Point measurements throughout the basin showed bedrock depths between 0.55 and 3.2 m. Resistivity of soil and bedrock samples collected from the site was measured for degrees of saturation between 40 and 92%. Resistivity of the soil was typically higher than that of the bedrock for degrees of saturation lower than 70%. Results from the laboratory measurements and point-depth measurements were used in a numerical model to evaluate the resistivity contrast at the soil-bedrock interface. A decreasing-with-depth resistivity contrast was apparent at the interface in the modeling results. At the field site, three transects were surveyed where coincident ground truth measurements of bedrock depth were available, to test the accuracy of the method. The same decreasing-with-depth resistivity trend that was apparent in the model was also present in the survey data. The resistivity contour of between 1,000 and 2,000 Ωm that marked the top of the contrast was our interpreted bedrock depth in the survey data. Kriged depth-to-bedrock maps were created from both the field-measured ground truth obtained with a soil probe and interpreted depths from the resistivity tomography, and these were compared for accuracy graphically. Depths were interpolated as far as 16.5 m laterally from the resistivity survey lines with root mean squared error (RMSE) = 27 cm between the measured and interpreted depth at those locations. Using several transects and analysis of the subsurface material properties, the direct current (DC) resistivity method is shown to be able to delineate bedrock depth trends within the drainage basin.

Oregon

Improved hydrogeophysical characterization and monitoring through parallel modeling and inversion of time-domain resistivity andinduced-polarization data

Electrical geophysical methods have found wide use in the growing discipline of hydrogeophysics for characterizing the electrical properties of the subsurface and for monitoring subsurface processes in terms of the spatiotemporal changes in subsurface conductivity, chargeability, and source currents they govern. Presently, multichannel and multielectrode data collections systems can collect large data sets in relatively short periods of time. Practitioners, however, often are unable to fully utilize these large data sets and the information they contain because of standard desktop-computer processing limitations. These limitations can be addressed by utilizing the storage and processing capabilities of parallel computing environments. We have developed a parallel distributed-memory forward and inverse modeling algorithm for analyzing resistivity and time-domain induced polar-ization (IP) data. The primary components of the parallel computations include distributed computation of the pole solutions in forward mode, distributed storage and computation of the Jacobian matrix in inverse mode, and parallel execution of the inverse equation solver. We have tested the corresponding parallel code in three efforts: (1) resistivity characterization of the Hanford 300 Area Integrated Field Research Challenge site in Hanford, Washington, U.S.A., (2) resistivity characterization of a volcanic island in the southern Tyrrhenian Sea in Italy, and (3) resistivity and IP monitoring of biostimulation at a Superfund site in Brandywine, Maryland, U.S.A. Inverse analysis of each of these data sets would be limited or impossible in a standard serial computing environment, which underscores the need for parallel high-performance computing to fully utilize the potential of electrical geophysical methods in hydrogeophysical applications.

Geophysics