[1] A cross-hole tracer test involving the simultaneous injection of two nonsorbing solute tracers with different diffusion coefficients (bromide and pentafluorobenzoate) and a weakly sorbing solute tracer (lithium ion) was conducted in a fractured granite near an underground nuclear test cavity in central Nevada. The test was conducted to (1) test a conceptual radionuclide transport model for the site and (2) obtain transport parameter estimates for predictive modeling. The differences between the responses of the two nonsorbing tracers (when normalized to injection masses) are consistent with a dualporosity transport system in which matrix diffusion is occurring. The large concentration attenuation of the sorbing tracer relative to the nonsorbing tracers suggests that diffusion occurs primarily into matrix pores, not simply into stagnant water within the fractures. The relative responses of the tracers at late times suggest that the diffusion-accessible matrix pore volume is possibly limited to only half the total volume of the flow system, implying that the effective retardation factor due to matrix diffusion may be as small as 1.5 for nonsorbing solutes in the system. The lower end of the range of possible sorption K d values deduced from the lithium response is greater than the upper 95% confidence bound of K d values measured in laboratory sorption tests using crushed granite from the site. This result suggests that the practice of using laboratory sorption data in field-scale transport predictions of cation-exchanging radionuclides, such as 137 Cs + and 90 Sr ++ , should be conservative for the SHOAL site.

[1] Streambed seepage can be predicted using an analytical solution to the one-dimensional heat transport equation to take advantage of the relationship between streambed thermal properties, seepage flux, and the amplitude ratio and phase shift associated with streambed temperature signals. This paper explores the accuracy of streambed-seepage velocity estimates from this method when uncertainty in input parameters exists. Uncertainty in sensor spacing, thermal diffusivity, and the accuracy of temperature sensors were examined both individually and in combination using Monte Carlo analysis. The analytical solution correctly reproduced known thermal front velocities above 1.25 m d À1 , using both the amplitude-ratio and phase-shift methods, despite introduced uncertainty in any of the variables. Noise in temperature measurements (because of sensor accuracy) caused erroneous prediction of velocity for gaining stream conditions using both the amplitude ratio and phase shift. Uncertainty in the thermal diffusivity and sensor spacing resulted in incorrect velocity, primarily under gaining conditions, when using the amplitude ratio and near-zero velocity using the phase shift. For a sensor accuracy of 0.15 C, we present combinations of parameters for which the resulting signal amplitude is sufficiently large for use with the Stallman equation.

[1] Given increasing demands on finite water supplies, accurate estimates of evapotranspiration (LE) from arid shrublands of the Southwestern United States are needed to develop or refine basin water budgets. In this work, a novel approach to estimating the equilibrium (or wet environment) surface temperature (T e ) and LE from regionally extensive phreatophyte shrublands is tested using complementary theory and micrometeorological data collected from five eddy correlation stations located in eastern Nevada. A symmetric complementary relationship between the potential LE (LE p ) and actual LE is extremely attractive because it is based on general feedback mechanisms where detailed knowledge of the complex processes and interactions between soil, vegetation, and the near-surface boundary layer can be avoided. Analysis of computed LE p and eddy correlation-derived LE indicates that there is unequivocal evidence of a complementary relationship between LE p and LE, where the measured and normalized complementary relationship is symmetric when T e is utilized to compute the wet environment LE (LE w ). Application of a modified Brutsaert and Stricker advection-aridity (AA) model, where T e is utilized to compute LE w as opposed to the measured air temperature, indicates an improvement in prediction accuracy over the standard Brutsaert and Stricker AA model. Monthly and annual predictions of LE using the modified AA model are within the uncertainty of the measurement accuracy, making the application of this approach potentially useful for estimating regional LE in arid shrubland environments. Our observational evidence supports the idea of a symmetric complementary relationship yielding an approach with standard parameters, making it simple to apply with satisfactory accuracy. To our knowledge, this work presents the first application and evaluation of the complementary relationship in phreatophyte shrublands while utilizing the T e with comparisons to actual LE via flux measurements.

This study evaluates alternative groundwater models with different recharge and geologic components at the northern Yucca Flat area of the Death Valley Regional Flow System (DVRFS), USA. Recharge over the DVRFS has been estimated using five methods, and five geological interpretations are available at the northern Yucca Flat area. Combining the recharge and geological components together with additional modeling components that represent other hydrogeological conditions yields a total of 25 groundwater flow models. As all the models are plausible given available data and information, evaluating model uncertainty becomes inevitable. On the other hand, hydraulic parameters (e.g., hydraulic conductivity) are uncertain in each model, giving rise to parametric uncertainty. Propagation of the uncertainty in the models and model parameters through groundwater modeling causes predictive uncertainty in model predictions (e.g., hydraulic head and flow). Parametric uncertainty within each model is assessed using Monte Carlo simulation, and model uncertainty is evaluated using the model averaging method. Two model-averaging techniques (on the basis of information criteria and GLUE) are discussed. This study shows that contribution of model uncertainty to predictive uncertainty is significantly larger than that of parametric uncertainty. For the recharge and geological components, uncertainty in the geological interpretations has more significant effect on model predictions than uncertainty in the recharge estimates. In addition, weighted residuals vary more for the different geological models than for different recharge models. Most of the calibrated observations are not important for discriminating between the alternative models, because their weighted residuals vary only slightly from one model to another.

[1] Discrete fracture network (DFN) and stochastic continuum (SC) are two common modeling approaches used for simulating fluid flow and solute transport in fractured media. Fracture continuum approaches combine the merits of each approach; details of the fracture network are preserved, and a computationally efficient grid is utilized for the solution of fluid flow by assigning a conductivity contrast between the grid cells representing the rock matrix and those representing fractures. In this paper, we propose a fracture continuum approach for mapping individual fractures onto a finite-difference grid as conductivity fields. We focus on several issues that are associated with this approach, such as enhanced connectivity between fractures that would otherwise not be in connection in a DFN simulation and the influence of grid cell size. To addresses these issues, both DFN and the proposed approach are used to solve for fluid flow through two-dimensional, randomly generated fracture networks in a steady-state, single-phase flow system. The DFN flow solution is used as a metric to evaluate the robustness of the method in translating discrete fractures onto grid cell conductivities on four different regularly spaced grids: 1 Â 1 m, 2 Â 2 m, 5 Â 5 m, and 10 Â 10 m. Two correction factors are introduced to ensure equivalence between the total flow of the grid and the original fracture network. The first is dependent on the fracture alignment with the grid and is set to account for the difference between the length of the flow path on the grid and that of the fracture. The other correction is applied for areas in the grid with high fracture density and accounts for the artificial degree of connectivity that exists on the grid but not in the DFN. Fifteen different cases are studied to evaluate the effect of fracture statistics on the results of the proposed approach and by taking average results of 100 realizations in each case in a stochastic Monte Carlo framework. The flow equation is solved for the DFN, and total flow is obtained. The flow is also solved separately for the four-grid resolution levels, and comparisons between the DFN and the grid total flows are made for the different cases and the different grid resolution levels. The approach performed relatively well in all cases for the fine-grid resolution, but an overestimation of grid flow is observed in the coarse-grid resolution, especially for cases wherein the network connectivity is controlled by small fractures. This overestimation shows minor variation from one realization to another within the same case. This allowed us to develop an approach that depends on solving limited number of DFN simulations to obtain this overestimation factor. Results indicate that the proposed approach provides improvements over existing approaches and has a potential to provide a link between DFN and SC models.