[1] Arsenic concentrations measured by graphite furnace atomic absorption range from < 5 to 900 mg/L in groundwater pumped from 6000 wells within a 25 km 2 area of Bangladesh. The proportion of wells that exceed the Bangladesh standard for drinking water of 50 mg/L arsenic increases with depth from 25% between 8 and 10 m to 75% between 15 and 30 m, then declines gradually to less than 10% at 90 m. Some villages within the study area do not have a single well that meets the standard, while others have wells that are nearly all acceptable. In contrast to the distribution of arsenic in the 8-30 m depth range which does not follow any obvious geological feature, the arsenic content of groundwater associated with relatively oxic Pleistocene sand deposits appears to be consistently low. The depth of drilling necessary to reach these low-As aquifers ranges from 30 to 120 m depth within the study area.

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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.