SACRAMENTO RIVER FLOW RECONSTRUCTED TO A.D. 869 FROM TREE RINGS1

ABSTRACT: A time series of annual flow of the Sacramento River, California, is reconstructed to A.D. 869 from tree rings for a long‐term perspective on hydrologic drought. Reconstructions derived by principal components regression of flow on time‐varying subsets of tree‐ring chronologies account for 64 to 81 percent of the flow variance in the 1906 to 1977 calibration period. A Monte Carlo analysis of reconstructed n‐year running means indicates that the gaged record contains examples of drought extremes for averaging periods of perhaps = 6 to 10 years, but not for longer and shorter averaging periods. For example, the estimated probability approaches 1.0 that the flow in A.D. 1580 was lower than the lowest single‐year gaged flow. The tree‐ring record also suggests that persistently high or low flows over 50‐year periods characterize some parts of the long‐term flow history. The results should contribute to sensible water resources planning for the Sacramento Basin and to the methodology of incorporating tree‐ring data in the assessment of the probability of hydrologic drought.     

Risk on the ramble: The international transfer of risk and vulnerability

In this paper the purpose is to discuss a concept of technology that can explain how the transfer of technology implies the risk of new failures, misuse, accidents and unhealthy workplaces. Production technologies are often transformed through a steady stream of incremental changes appropriate to their social context, and the technology will therefore gradually acquire some contextually dependent preconditions for use. These preconditions will most probably be revealed when a technology is transferred from one context to another. Thus, a technology transfer project may trigger a long process of re-innovations just to make the technology fully operational in its new context. In a transfer process, technological risks may arise due to incomplete transfer of mastering capacity; mismatch between transferred technology and the environment; transfer of latent conditions for failure; and the transformation of latent conditions or known risks when the technology is installed in a new environment. Longitudinal data from the Norwegian petroleum industry indicates that the first phases in a transfer process will create high technological risks. It will take many years before the transferred technologies are adapted to the new context and the risk level has been normalised.     

Evaluation and ranking of restoration strategies for radioactively contaminated sites.

An international project, whose aim was the development of a transparent and robust method for evaluating and ranking restoration strategies for radioactively contaminated sites (RESTRAT), was carried out under the Fourth Framework of the Nuclear Fission Safety Programme of the EU. The evaluation and ranking procedure used was based on the principles of justification and optimisation for radiation protection. A multi-attribute utility analysis was applied to allow for the inclusion of radiological health effects, economic costs and social factors. Values of these attributes were converted into utility values by applying linear utility functions and weighting factors, derived from scaling constants and expert judgement. The uncertainties and variabilities associated with these utility functions and weighting factors were dealt with by a probabilistic approach which utilised a Latin Hypercube Sampling technique. Potentially relevant restoration techniques were identified and their characteristics determined through a literature review. The methodology developed by this project has been illustrated by application to representative examples of different categories of contaminated sites; a waste disposal site, a uranium tailing site and a contaminated freshwater river.     

Batch sorption dynamics and equilibrium for the removal of lead ions from aqueous phase using activated carbon developed from coffee residue activated with zinc chloride

Lignocellulosic materials are good precursors for the production of activated carbon. In this work, coffee residue has been used as raw material in the preparation of powder activated carbon by the method of chemical activation with zinc chloride for the sorption of Pb(II) from dilute aqueous solutions.The influence of impregnation ratio (ZnCl₂/coffee residue) on the physical and chemical properties of the prepared carbons was studied in order to optimize this parameter. The optimum experimental condition for preparing predominantly microporous activated carbons with high pore surface area (890 m²/g) and micropore volume (0.772 cm³/g) is an impregnation ratio of 100%. The developed activated carbon shows substantial capability to sorb lead(II) ions from aqueous solutions and for relative impregnation ratios of 75 and 100%, the maximum uptake is practically the same. Thus, 75% represents the optimal impregnation ratio.Batch experiments were conducted to study the effects of the main parameters such as contact time, initial concentration of Pb(II), solution pH, ionic strength and temperature. The maximum uptake of lead(II) at 25 °C was about 63 mg/g of adsorbent at pH 5.8, initial Pb(II) concentration of 10 mg/L, agitation speed of 200 rpm and ionic strength of 0.005 M. The kinetic data were fitted to the models of pseudo-first order and pseudo-second order, and follow closely the pseudo-second order model. Equilibrium sorption isotherms of Pb(II) were analyzed by the Langmuir, Freundlich and Temkin isotherm models. The Freundlich model gives a better fit than the others.Results from this study suggest that activated carbon produced from coffee residue is an effective adsorbent for the removal of lead from aqueous solutions and that ZnCl₂ is a suitable activating agent for the preparation of high-porosity carbons.     

Numerical analysis of water and solute transport in variably-saturated fractured clayey till

This study numerically investigates the influence of initial water content and rain intensities on the preferential migration of two fluorescent tracers, Acid Yellow 7 (AY7) and Sulforhodamine B (SB), through variably-saturated fractured clayey till. The simulations are based on the numerical model HydroGeoSphere, which solves 3D variably-saturated flow and solute transport in discretely-fractured porous media. Using detailed knowledge of the matrix, fracture, and biopore properties, the numerical model is calibrated and validated against experimental high-resolution tracer images/data collected under dry and wet soil conditions and for three different rain events. The model could reproduce reasonably well the observed preferential migration of AY7 and SB through the fractured till, although it did not capture the exact depth of migration and the negligible impact of the dead-end biopores in a near-saturated matrix. A sensitivity analysis suggests fast flow mechanisms and dynamic surface coating in the biopores, and the presence of a plough pan in the till.     

A Multilevel Model of the Impact of Farm‐Level Best Management Practices on Phosphorus Runoff1

Abstract: Multilevel or hierarchical models have been applied for a number of years in the social sciences but only relatively recently in the environmental sciences. These models can be developed in either a frequentist or Bayesian context and have similarities to other methods such as empirical Bayes analysis and random coefficients regression. In essence, multilevel models take advantage of the hierarchical structure that exists in many multivariate datasets; for example, water quality measurements may be taken from individual lakes, lakes are located in various climatic zones, lakes may be natural or man‐made, and so on. The groups, or levels, may effectively yield different responses or behaviors (e.g., nutrient load response in lakes) that often make retaining group membership more effective when developing a predictive model than when working with either all of the data together or working separately with the individuals. Here, we develop a multilevel model of the impact of farm level best management practices (BMPs) on phosphorus runoff. The result of this research is a model with parameters which vary with key practice categories and thus may be used to evaluate the effectiveness of these practices on phosphorus runoff. For example, it was found that the effect of fertilizer application rate on farm‐scale phosphorus loss is a function of the application method, the hydrologic soil group, and the land use (crop type). Further, results indicate that the most effective method for controlling fertilizer loss is through soil injection. In summary, the resultant multilevel model can be used to estimate phosphorus loss from farms and hence serve as a useful tool for BMP selection.     

Estimating human exposure to transport noise in central Dublin, Ireland

This paper reports on research conducted to determine estimates of the extent of environmental noise exposure from road transport on residents and workers in central Dublin, Ireland. The Harmonoise calculation method is used to calculate noise values for the study area while a Geographical Information System (GIS) is utilised as a platform upon which levels of noise exposure are estimated. Residential exposure is determined for L(den) and L(night) while worker exposure is determined for L(den). In order to analyse the potential of traffic management as a noise abatement measure, traffic was redirected from the main residential areas to alternative road links and the revised exposure levels were determined. The results show that the extent of noise exposure in Dublin is considerable, and in relative terms, it is worse for the night-time period. In addition, the results suggest also that traffic management measures have the potential to lead to significant reductions in the level of noise exposure provided that careful consideration is given to the impact of traffic flows on residential populations.     

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.