Publications

Abstract not provided.

Southwest Solar Technologies Inc. is constructing a Solar-Fuel Hybrid Turbine energy system. This innovative energy system combines solar thermal energy with compressed air energy storage and natural gas fuel backup capability to provide firm, non-intermittent power. In addition, the energy system will have very little impact on the environment since, unlike other Concentrated Solar Power (CSP) technologies, it requires minimal water. In 2008 Southwest Solar Technologies received a Solar America Showcase award from the Department of Energy for Technical Assistance from Sandia National Laboratories. This report details the work performed as part of the Solar America Showcase award for Southwest Solar Technologies. After many meetings and visits between Sandia National Labs and Southwest Solar Technologies, several tasks were identified as part of the Technical Assistance and the analysis and results for these are included here.

This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

This report describes a model Transport Processes Investigation (TPI) where field-scale vadose zone flow and transport processes are identified and verified through a systematic field investigation at a contaminated DOE site. The objective of the TPI is to help with formulating accurate conceptual models and aid in implementing rational and cost effective site specific characterization strategies at contaminated sites with diverse hydrogeologic settings. Central to the TPI are Transport Processes Characterization (TPC) tests that incorporate field surveys and large-scale infiltration experiments. Hypotheses are formulated based on observed pedogenic and hydrogeologic features as well as information provided by literature searches. The field and literature information is then used to optimize the design of one or more infiltration experiments to field test the hypothesis. Findings from the field surveys and infiltration experiments are then synthesized to formulate accurate flow and transport conceptual models. Here we document a TPI implemented in the glacial till vadose zone at the Fernald Environmental Management Project (FEMP) in Fernald, Ohio, a US Department of Energy (DOE) uranium processing site. As a result of this TPI, the flow and transport mechanisms were identified through visualization of dye stain within extensive macro pore and fracture networks which provided the means for the infiltrate to bypass potential aquatards. Such mechanisms are not addressed in current vadose zone modeling and are generally missed by classical characterization methods.

Time domain reflectometry (TDR) operates by propagating a radar frequency electromagnetic pulse down a transmission line while monitoring the reflected signal. As the electromagnetic pulse propagates along the transmission line, it is subject to impedance by the dielectric properties of the media along the transmission line (e.g., air, water, sediment), reflection at dielectric discontinuities (e.g., air-water or water-sediment interface), and attenuation by electrically conductive materials (e.g., salts, clays). Taken together, these characteristics provide a basis for integrated stream monitoring; specifically, concurrent measurement of stream stage, channel profile and aqueous conductivity. Here, we make novel application of TDR within the context of stream monitoring. Efforts toward this goal followed three critical phases. First, a means of extracting the desired stream parameters from measured TDR traces was required. Analysis was complicated by the fact that interface location and aqueous conductivity vary concurrently and multiple interfaces may be present at any time. For this reason a physically based multisection model employing the S11 scatter function and Cole-Cole parameters for dielectric dispersion and loss was developed to analyze acquired TDR traces. Second, we explored the capability of this multisection modeling approach for interpreting TDR data acquired from complex environments, such as encountered in stream monitoring. A series of laboratory tank experiments were performed in which the depth of water, depth of sediment, and conductivity were varied systematically. Comparisons between modeled and independently measured data indicate that TDR measurements can be made with an accuracy of {+-}3.4x10{sup -3} m for sensing the location of an air/water or water/sediment interface and {+-}7.4% of actual for the aqueous conductivity. Third, monitoring stations were sited on the Rio Grande and Paria rivers to evaluate performance of the TDR system under normal field conditions. At the Rio Grande site (near Central Bridge in Albuquerque, New Mexico) continuous monitoring of stream stage and aqueous conductivity was performed for 6 months. Additionally, channel profile measurements were acquired at 7 locations across the river. At the Paria site (near Lee's Ferry, Arizona) stream stage and aqueous conductivity data were collected over a 4-month period. Comparisons drawn between our TDR measurements and USGS gage data indicate that the stream stage is accurate within {+-}0.88 cm, conductivity is accurate within {+-}11% of actual, and channel profile measurements agree within {+-}1.2 cm.