MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1

Abstract: We proposed a step‐by‐step approach to quantify the sensitivity of ground‐water discharge by evapotranspiration (ET) to three categories of independent input variables. To illustrate the approach, we adopt a basic ground‐water discharge estimation model, in which the volume of ground water lost to ET was computed as the product of the ground‐water discharge rate and the associated area. The ground‐water discharge rate was assumed to equal the ET rate minus local precipitation. The objective of this study is to outline a step‐by‐step procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground‐water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation in each subbasin. The specific goal is to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground‐water discharge estimates. The influential independent variables to be included in the sensitivity analysis are first selected based on the physical characteristics and model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables are calculated using the results from sampling‐based Monte Carlo simulations. Results illustrate that, while as many as 630 independent variables potentially contribute to the calculation of the total annual ground‐water discharge for the case study area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground‐water discharge. Results indicate that the variability of ET rate for moderately dense desert shrubland contributes to about 75% of the variance in the total ground‐water discharge estimates. These results point to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground‐water discharge. While the approach proposed here uses a basic ground‐water discharge model taken from an earlier study, the procedure of quantifying uncertainty and sensitivity can be generalized to handle other types of environmental models involving large numbers of independent variables.     

Assessment Tools for Urban Catchments: Defining Observable Biological Potential1

Abstract: Urbanization represents a strong and increasingly more prevalent impact on stream quality worldwide. One of the characteristic effects of increased urbanization is a consistent decline in biological stream condition. The characterization of this biological degradation with increasing urbanization presents a number of advantages for the study and management of urban streams and catchments. In this paper, the limitation of biological condition with urbanization, called observed biological potential, is characterized. Using an urban intensity index and a biological index developed specifically for urban systems in the Baltimore, Maryland; Cleveland, Ohio; and San Jose, California regions, two principal techniques were compared (quantile regression and bin regression) to define observed biological potential along urban gradients. Quantile regression was selected as the preferable tool for describing observed biological potential given the consistency with which it can be applied and its statistical efficiency, however, bin quantile regression performed similarly. Having identified a numeric approximation of observed biological potential, two methods for identifying factors related to distance from potential as a way of identifying critical environmental factors affecting biological condition in urban areas were explored. The results of this work can be used for identifying benchmarks for urban stream biological condition, identifying limiting catchment characteristics, and prioritizing urban stream management efforts.     

Conversion of a Missouri River Dam and Reservoir to a Sustainable System: Sediment Management1

Abstract: A present and future challenge for water resources engineers is to extend the useful life of our dams and reservoirs. Ongoing reservoir sedimentation in impoundments must be addressed; sedimentation in many reservoirs already limits project benefits and effective project life. Sustainability requires that incoming sediment be moved downstream past the impounding dam. We use Lewis and Clark Lake, the most downstream of the six Missouri River main stem reservoirs, to demonstrate how a reservoir in advanced stages of its project life could be converted to a sustainable system with local benefits exceeding costs by a factor of 1.5. Full consideration of benefits would further enhance project justification. The proposed strategy involves four phases that will take about 50 years to complete. Cost estimates for this potential project range from the quantitative to the plausible, but it is clear that the results justify a full engineering, environmental, and economic study of this model project. If implemented, the project will create scientific knowledge and develop technologies useful for achieving sustainability at many other reservoirs in the Mississippi River basin and beyond.     

Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation1

Young, Charles A., Marisa I. Escobar‐Arias, Martha Fernandes, Brian Joyce, Michael Kiparsky, Jeffrey F. Mount, Vishal K. Mehta, David Purkey, Joshua H. Viers, and David Yates, 2009. Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation. Journal of the American Water Resources Association (JAWRA) 45(6):1409‐1423. Abstract: The rainfall‐runoff model presented in this study represents the hydrology of 15 major watersheds of the Sierra Nevada in California as the backbone of a planning tool for water resources analysis including climate change studies. Our model implementation documents potential changes in hydrologic metrics such as snowpack and the initiation of snowmelt at a finer resolution than previous studies, in accordance with the needs of watershed‐level planning decisions. Calibration was performed with a sequence of steps focusing sequentially on parameters of land cover, snow accumulation and melt, and water capacity and hydraulic conductivity of soil horizons. An assessment of the calibrated streamflows using goodness of fit statistics indicate that the model robustly represents major features of weekly average flows of the historical 1980‐2001 time series. Runs of the model for climate warming scenarios with fixed increases of 2°C, 4°C, and 6°C for the spatial domain were used to analyze changes in snow accumulation and runoff timing. The results indicated a reduction in snowmelt volume that was largest in the 1,750‐2,750 m elevation range. In addition, the runoff center of mass shifted to earlier dates and this shift was non‐uniformly distributed throughout the Sierra Nevada. Because the hydrologic model presented here is nested within a water resources planning system, future research can focus on the management and adaptation of the water resources system in the context of climate change.     

Lay concepts on CCS deployment in Switzerland based on qualitative interviews

Laypeople's acceptance and perception of Carbon Dioxide Capture and Storage (CCS) can have an influence on its political feasibility. It is important, therefore, to study how laypeople perceive CCS and which cognitions they hold with respect to this technique. We conducted in-depth interviews with laypeople (N = 16) to explore their mental concepts of CCS. Little knowledge about CCS was detected among laypeople. We also found that laypeople fear that a deployment of CCS could create incentives that would hinder a sustainable development of the energy economy. A misunderstanding of the concepts of hydro- and geostatic pressure, as well as a lack of knowledge about the physical–chemical properties of carbon dioxide seemed to trigger fundamental rejection of CCS among some laypeople. This qualitative study identifies concepts that underlie CCS perception, and these should be objects of future studies. We provide some suggestions for risk management and communication about CCS.     

Investigations on CO2 storage capacity in saline aquifers—Part 2: Estimation of storage capacity coefficients

Many studies on geological carbon dioxide (CO₂) storage capacity neglect the influence of complex coupled processes which occur during and after the injection of CO₂. Storage capacity is often overestimated since parts of the reservoirs cannot be reached by the CO₂ plume due to gravity segregation and are thus not accessible for storage. This work investigates the effect of reservoir parameters like depth, temperature, absolute and relative permeability, and capillary pressure on the processes during CO₂ injection and thus on estimates of effective storage capacity. The applied statistical characteristics of parameters are based on a large reservoir parameter database. Different measured relative permeability relations are considered. The methodology of estimating storage capacity is discussed. Using numerical 1D and 3D experiments, detailed time-dependent storage capacity estimates are derived. With respect to the concept developed in this work, it is possible to estimate effective CO₂ storage capacity in saline aquifers. It is shown that effective CO₂ mass stored in the reservoir varies by a factor of 20 for the reservoir setups considered. A high influence of the relative permeability relation on storage capacity is shown.     

Enrichment of the metallic components from waste printed circuit boards by a mechanical separation process using a stamp mill

Printed circuit boards incorporated in most electrical and electronic equipment contain valuable metals such as Cu, Ni, Au, Ag, Pd, Fe, Sn, and Pb. In order to employ a hydrometallurgical route for the recycling of valuable metals from printed circuit boards, a mechanical pre-treatment step is needed. In this study, the metallic components from waste printed circuit boards have been enriched using a mechanical separation process. Waste printed circuit boards shredded to <10mm were milled using a stamp mill to liberate the various metallic components, and then the milled printed circuit boards were classified into fractions of <0.6, 0.6-1.2, 1.2-2.5, 2.5-5.0, and >5.0mm. The fractions of milled printed circuit boards of size <5.0mm were separated into a light fraction of mostly non-metallic components and a heavy fraction of the metallic components by gravity separation using a zig-zag classifier. The >5.0mm fraction and the heavy fraction were subjected to two-step magnetic separation. Through the first magnetic separation at 700 Gauss, 83% of the nickel and iron, based on the whole printed circuit boards, was recovered in the magnetic fraction, and 92% of the copper was recovered in the non-magnetic fraction. The cumulative recovery of nickel-iron concentrate was increased by a second magnetic separation at 3000 Gauss, but the grade of the concentrate decreased remarkably from 76% to 56%. The cumulative recovery of copper concentrate decreased, but the grade increased slightly from 71.6% to 75.4%. This study has demonstrated the feasibility of the mechanical separation process consisting of milling/size classification/gravity separation/two-step magnetic separation for enriching metallic components such as Cu, Ni, Al, and Fe from waste printed circuit boards.