Core Ideas A new technique for estimating the saturated hydraulic conductivity is developed. It uses a combination of hydrogeophysical and numerical methods. Electrical resistivity tomography and the instantaneous profile method are used. The technique is validated using simple and complex numerical hydrogeological models. Many hydrogeological and geophysical tools have been developed to determine subsoil properties, but they are often limited by sparse datasets and by the portability of the method from one site to another and often underestimate the complexity of the medium. We present a saturated hydraulic conductivity (Ks) estimation scheme, named the KES method, based on hydrogeophysical and numerical methods. The targeted medium of investigation is an unsaturated and heterogeneous soil. Estimation of Ks is accomplished by estimating the position of the wetting front and the distribution and velocity of flow lines during an infiltration test. Using numerical modeling, Ks is determined by minimizing the velocity difference between the measured flow lines and the modeled flow lines. Surface and buried electrodes are used as part of the electrical resistivity survey in determining the position of the wetting front. An instantaneous profile method is used to determine the water retention curve of the medium. The KES method has been tested and validated using data produced from simple and more complex geological models from published case studies. We obtained good reconstruction of the saturated hydraulic conductivity. We have found that the estimated value of Ks in log scale has a mean error <2.5%. Error increases along the boundaries of different hydrofacies.

In geophysical inverse problems, an a priori structured mesh is often used for inversion and mesh refinement is applied if needed by the user after observation of inversion results. We have developed a new intelligent self-adaptive unstructured finite-element meshing technique for electrical resistivity tomography inverse problems. This new approach uses Harris corner-and-edge detectors that are based on the local autocorrelation function of 2D distribution of pixels. This meshing technique optimizes the size of the inverse problem by refining areas where variations in the physical property structure are sensed to be important. The meshing technique also generates a more appropriate and optimum mesh for the inverse problem that is dependent on the problem itself. Tests on modeled data have demonstrated that the proposed intelligent meshing technique can reduce data misfit, produce a better reconstruction of the true physical properties, and minimize the size of the inverse problem. The synthetic model consists of a conductive dike in a resistive medium. By applying the proposed intelligent meshing technique, the inverse model of the dike is very similar to the inverse model produced using fine meshes, and it is also better reconstructed than the inverse model produced using conventional meshes. We have also applied the intelligent meshing technique to survey data collected for groundwater-saltwater mapping and characterizing the subsurface conductive structure with topography included. Our results indicate that the new meshing technique can produce solutions that are comparable with standard meshing and fine meshing techniques, while optimizing the size of the inverse problem.

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Side scan sonar, sub bottom profiling and electrical resistivity tomography (marine cables) were used to characterize the lake sediments (rock and soil) beneath the manmade Little Prairie Lake, central Missouri. Sub bottom profiling and electrical resistivity tomography (with marine cables) were used to determine variability in the lithology and thickness of sediments (soil and rock) beneath the lake, while side scan sonar was used to map the variations in the lithology/nature of exposed lake bed sediments.Analyses of the acquired data revealed the location and orientation of the original stream channel (prior to the construction of the earth fill dam). The side scan sonar was also used to map variations in the biomass at the bottom of the lake. AbstractSurvey efforts in complex areas present a challenge. This talk will explain the collection, processing and presentation of point cloud data collected underwater with multibeam sonar systems (RESON 7125 and BlueView 5000), as well as 3-D laser scanner collected above the water. Example data from mapping and inspections of dams, pipeline crossings, and cable routes will be presented in the form of integrated point clouds, digital terrain models (DTM), charts, solid models and movies. AbstractOver the past two years, the Wyoming Center for Environmental Hydrology and Geophysics (WyCEHG) has imaged the subsurface at five CZO's: Calhoun, Boulder Creek, Eel River, Reynolds Creek, and Southern Sierra. Techniques applied include seismic refraction, electrical resistivity, downhole logging, ground-penetrating radar, magnetic gradiometry, EMI, and surface NMR. We will present results from these sites that demonstrate the following: (1) The base of the Critical Zone may be defined as the depth to which fractures remain open (thus allowing pathways for meteoric water), and this depth is likely controlled by the near-surface stress distribution.(2) In areas characterized by regional compressive stresses, intact bedrock shows an inverted topography relative to surface topography, with bedrock "ridges" under stream valleys.(3) Seismic refraction velocities provide information on weathering zone thickness and can be inverted for estimates of bulk porosity that match measured porosities from coring. (4) Geophysical imaging provides a way to map the top of fractured bedrock (base of weathering) across landscapes. (5) Snow GPR data can provide estimates of snow-water equivalent over large mountain watersheds.

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