We present an analysis of fault hydraulic architecture, based on Ͼ700 spatially distributed ground and geothermal spring temperature measurements taken in an active fault zone. Geostatistical simulations were used to extrapolate the measured data over an 800 ؋ 100 m area and develop a high-resolution image of temperatures in the fault. On the basis of the modeled temperatures, a simple analytical model of convective heat transport was used to infer a probability distribution function for hydraulic conductivities in a twodimensional plane parallel to the land surface, and the partitioning of flow between flow paths of different conductivities was calculated as a fraction of the total flux. The analysis demonstrates the existence of spatially discrete, high-permeability flow paths within the predominantly lower-permeability fault materials. Although the existence of fast-flow paths in faults has been hypothesized for Ͼ10 yr, their prevalence and contribution to the total flow of fluid in a fault zone are debated. On the basis of our findings, we conclude that the flux transmitted by an individual fast-flow path is significantly greater than that of an average flow path, but the total flux transported in fast-flow paths is a negligible fraction of the total flux transmitted by the fault.

[1] This study presents a description of permeability in an active fault zone located in the Great Basin extensional province. The fault hydraulic structure is inferred from geostatistical analysis of temperatures in 143 geothermal springs, located along a fault trace in the Alvord Basin of southeast Oregon. Based on this analysis, we conclude that the fault zone is predominately low permeability, interspersed with relatively few, spatially-discrete, highpermeability channels. The conceptual model presented is in agreement with the findings of other investigators, but extends their work by offering a representation of fault properties at the tens to hundreds of meters scale.

With the increasing accessibility of terrestrial light detection and ranging scanners (LiDAR), generating tools to elicit meaningful information from high-density point cloud data has become of paramount importance. Surface roughness is one metric that has gained popularity, largely due to the accuracy and density of LiDAR-derived point cloud data. Surface roughness is typically defined as a spread of point distances from a reference datum, the standard deviation of point distances from a model surface being a commonly employed model. Unfortunately, a recent literature review has found that existing surface roughness models are far from standardized and may be prone to error resulting from underlying surface topography. In the research presented here, we develop a surface roughness model that is robust to underlying topographic variability by segmenting the point cloud with a three-dimensional regular grid, establishing local (grid cell) reference planes by orthogonal distance regression, and estimating the surface roughness of each grid cell as the standard deviation of orthogonal point-to-plane distances. This surface roughness model is employed to identify fracture and rubble zone distributions within a terrestrial LiDAR scan from a basalt outcrop in southeast Idaho, and the results are compared to a more common model based on ordinary least-squares plane fitting. Results indicate that the orthogonal regression model is robust to outcrop orientation and that the ordinary least-squares model systematically overestimates surface roughness by contaminating estimates with spatially correlated errors that increase with decreasing grid size.

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[1] Faults are often assumed to be either barriers or conduits for subsurface fluid flow, although they may act as both, depending on the hydraulic architecture of the fault and the direction of flow with respect to the fault plane. Here we use high-resolution (5 Â 5 m spacing) ground temperature measurements to track geothermal discharge in the step-over region of an active échelon normal fault in southeast Oregon. Our analysis demonstrates that the fault acts as a combination conduit-barrier system and reveals complex, 3-dimensional circulation patterns in the area of the fault step-over. Although complex flow circulation patterns are likely to be present in most fault-controlled flow systems, they are generally neglected in conceptual and numerical models. Improved understanding of this aspect of subsurface fluid flow is essential for developing better models of fault hydrology.