Effective application of monitoring information: the case of San Francisco Bay

The San Francisco Estuary Regional Monitoring Program (RMP) for Trace Substances is an innovative partnership among a regulatory agency, more than 70 regulated entities, and an independent scientific organization. The institutional arrangement behind the RMP has made the regulatory system increasingly responsive to emerging management needs, particularly with regard to the development of total maximum daily loads and ecosystem impairment assessment. Through multi-agency partnerships within and outside the RMP institutional structure, major information gaps for several pollutants of concern have been narrowed, resulting in a successful consensus-based regulatory approach to managing copper and nickel mass inputs into the Estuary. Short-term research efforts, based upon monitoring results, helped identify the most cost-effective control and remediation options for various bioaccumulative substances. Additionally, adaptive changes to the monitoring program documented the existence of widespread aquatic toxicity in the Estuary that is apparently due to pesticide runoff from agricultural and urban areas. One of the most important contributions of this collaborative monitoring program is the deliberate and systematic adjustment of management and research questions that serve to influence and add relevance to the overall research agenda related to San Francisco Estuary ecosystem assessment.     

Nonparametric Monte Carlo Simulation for Flood Frequency Curve Derivation: An Application to a Korean Watershed1

Abstract: A mix of causative mechanisms may be responsible for flood at a site. Floods may be caused because of extreme rainfall or rain on other rainfall events. The statistical attributes of these events differ according to the watershed characteristics and the causes. Traditional methods of flood frequency analysis are only adequate for specific situations. Also, to address the uncertainty of flood frequency estimates for hydraulic structures, a series of probabilistic analyses of rainfall‐runoff and flow routing models, and their associated inputs, are used. This is a complex problem in that the probability distributions of multiple independent and derived random variables need to be estimated to evaluate the probability of floods. Therefore, the objectives of this study were to develop a flood frequency curve derivation method driven by multiple random variables and to develop a tool that can consider the uncertainties of design floods. This study focuses on developing a flood frequency curve based on nonparametric statistical methods for the estimation of probabilities of rare floods that are more appropriate in Korea. To derive the frequency curve, rainfall generation using the nonparametric kernel density estimation approach is proposed. Many flood events are simulated by nonparametric Monte Carlo simulations coupled with the center Latin hypercube sampling method to estimate the associated uncertainty. This study applies the methods described to a Korean watershed. The results provide higher physical appropriateness and reasonable estimates of design flood.     

A statistical approach for the assessment and redesign of the Nile Delta drainage system water-quality-monitoring locations

There are several deficiencies in the statistical approaches proposed in the literature for the assessment and redesign of surface water-quality-monitoring locations. These deficiencies vary from one approach to another, but generally include: (i) ignoring the attributes of the basin being monitored; (ii) handling multivariate water quality data sequentially rather than simultaneously; (iii) focusing mainly on locations to be discontinued; and (iv) ignoring the reconstitution of information at discontinued locations. In this paper, a methodology that overcomes these deficiencies is proposed. In the proposed methodology, the basin being monitored is divided into sub-basins, and a hybrid-cluster analysis is employed to identify groups of sub-basins with similar attributes. A stratified optimum sampling strategy is then employed to identify the optimum number of monitoring locations at each of the sub-basin groups. An aggregate information index is employed to identify the optimal combination of locations to be discontinued. The proposed approach is applied for the assessment and redesign of the Nile Delta drainage water quality monitoring locations in Egypt. Results indicate that the proposed methodology allows the identification of (i) the optimal combination of locations to be discontinued, (ii) the locations to be continuously measured and (iii) the sub-basins where monitoring locations should be added. To reconstitute information about the water quality variables at discontinued locations, regression, artificial neural network (ANN) and maintenance of variance extension (MOVE) techniques are employed. The MOVE record extension technique is shown to result in a better performance than regression or ANN for the estimation of information about water quality variables at discontinued locations.     

Use of beetroot fibers to clean water contaminated with heavy metals,to soften hard water,and to desalinate seawater

In this article we describe the use of beetroot fibers in treating water contaminated with heavy metals, in softening hard water, and in desalinating seawater. The study was carried out with either beetroot fibers or powdered fibers using a laboratory column with a fixed bed. The effectiveness of the method and the effect of the pH on it were monitored by atomic absorption spectrometry, infrared spectroscopy, conductivity measurements, and a volumetric method. The optimum pH range for all the treatment was found to be between 6.0 and 6.6. The heavy metals included in this study were lead, copper, nickel, and zinc. The amount of heavy metals retained by the fibers or the powder was significant in each case. The retention capacity was the strongest for lead and the weakest for nickel. In the case of hard water and seawater studies, our experiments revealed a dramatic decrease in total dissolved solids (TDS), indicating the potential of the method as an aid or an alternative to conventional methods.     

Quaternary adsorption equilibria from aqueous systems onto decolourizing activated carbon

An experimental study has been conducted to obtain the adsorption isotherms of four typical pollutants from quaternary aqueous systems onto decolourizing activated carbon. The four materials investigated are: Phenol, 1,4-dihydroxybenzene, 4-amino-l-naphthalene sulfonic acid-sodium salt and Benzoic acid. The study has concentrated on the dilute region of concentrations which range from 10 to 165 ppm (mg/L) at an operating temperature of 30 °C.

The quaternary adsorption equilibria have been modeled using the extended Langmuir predictive model and the ideal adsorbed solution (IAS) theory. In employing these models for the prediction of multicomponent adsorption equilibria, the single-solute isotherms are needed. These isotherms have been fitted to Langmuir, Freundlich, and Dubinin models and the resulting model parameters, which are needed for the prediction of multicomponent adsorption equilibria, are reported. Predictions obtained from the extended Langmuir predictive model and the ideal adsorbed solution (IAS) model are in agreement, however, they deviate to an appreciable extent from experimental observations.     

Atmospheric nitrous oxide: patterns of global change during recent decades and centuries

Data from weekly global measurements of nitrous oxide from 1981 to the end of 1996 are presented. The results show that there is more N2O in the northern hemisphere by about 0.7 +/- 0.04 ppbv, and the Arctic to Antarctic difference is about 1.2 +/- 0.1 ppbv. Concentrations at locations influenced by continental air are higher than at marine sites, showing the existence of large land-based emissions. For the period studied, N2O increased at an average rate of about 0.6 ppbv/year (approximately 0.2%/year) although there were periods when the rates were substantially different. Using ice core data, a record of N2O can be put together that goes back about 1000 years. It shows pre-industrial levels of about 287 +/- 1 ppbv and that concentrations have now risen by about 27 ppbv or 9.4% over the last century. The ice core data show that N2O started increasing only during the 20th century. The data presented here represent a comprehensive view of the present global distribution of N20 and its historical and recent trends.