Influence of Stage Discharge Relationship on the Annual Maximum Discharge Statistics

Discharge data are traditionally derived from measures of watersurface levels using stage-discharge relationships. Astage-discharge relation is obtained from direct dischargemeasurements for a set of water surface levels by fitting anempirical relationship to the data set. Since discharge measuresare made only for low flow conditions, the historicalstage-discharge relationships can give rise to severemisinterpretation for high flow values. The present work analysisthe influence on discharge statistics of the rating curve errorsfor the Liguria region. The work shows that historicalstage-discharge relations are highly uncertain when used for theestimation of annual maximum discharge. Moreover, data produced bythe traditional stage discharge relationships when compared withdata derived from more reliable theoretical stage-dischargerelationships, have statistically important biases. The findinghighlights a new problem in the use of historical data for floodrisk assessment.     

Monte Carlo Studies of Relations between Fractal Dimensions in Monofractal Data Sets

—Within the fractal approach to studying the distribution of seismic event locations, different fractal dimension definitions and estimation algorithms are in use. Although one expects that for the same data set, values of different dimensions will be different, it is usually anticipated that the direction of fractal dimension changes among different data sets will be the same for every fractal dimension.¶Mutual relations between the three most popular fractal dimensions, namely the capacity, cluster and correlation dimensions, have been investigated in the present work. The studies were performed on the Monte Carlo generated data sets. The analysis has shown that dependence of the fractal dimensions on epicenter distribution, and relations among the fractal dimensions, are complex and variable. Neither values nor even inequalities among dimension estimates are preserved when different fractal dimensions are used. The correlation and the capacity dimensions seem to be good tools to trace collinear tendencies of eipicenters while the cluster dimension is more appropriate to studying uniform clustering of points.     

Modeling a Ground Water Circulation Well Alternative

Ground water circulation wells (GCWs) provide an appealing alternative to typical pump-and-treat ground water remediation systems because of the inherent resource-conservative nature of the GCW systems. GCW performance prediction is challenging because the consideration of extraction and recharge in a single well is unusual for most practitioners, the technology is relatively new, and a meaningful body of literature has not been published. A three-part evaluation process using state-of-the-practice numerical ground water flow and mass transport models was developed for application during GCW pilot studies at the former Nebraska Ordnance Plant site. A small-scale ground water flow model was developed during the pilot study planning process to predict the system performance and to locate performance-measuring monitoring wells. Key predictions included the capture zone predicted to develop upgradient of the GCW, the downgradierit GCW recharge zone, and the circulation zone centered on the GCW. The flow model was subsequently verified using ground water elevation data and contaminant concentration data collected during pilot study operation. Aquifer parameters were reestimated as a result of the verification process. Those parameter values were used as input to a larger scale model, which was used to develop a remedial alternative consisting of multiple GCW systems.     

The abandoned Pb-Zn mine of Ingurtosu, Sardinia (Italy)

The Ingurtosu Pb-Zn mine, situated in the southwestern part of Sardinia, has been in production from the beginning of the last century up to 1968. The orebody consists of galena/sphalerite/barite/siderite veins in Ordovician arenaceous and phyllitic sediments, near the contact with a Hercynian batholith.

Abundant tailings were collected in a pond from which they were discharged during the winter months into the sea via the Rio Naracauli stream. Today this area of outstanding scenic beauty, is degraded by tailings and waste rock scattered all along the stream.

Material derived from mining activities was studied for grain size, mineralogical and geochemical composition. The Rio Naracauli was sampled over a length of ten kilometers at regular intervals.

The results can be summarized as follows: (a) tailings contain a varying, but often quite high, percentage of Pb; lower percentages were found for Zn and Cd; (b) a sharp increase in dissolved Zn, Cd and Pb was observed in the Rio Naracauli where it leached the tailings; and (c) tailings and waste rocks should be recycled or revegetated.     

The helium abundance and ΔY/ΔZ in lower main-sequence stars

We use nearby K dwarf stars to measure the helium-to-metal enrichment ratio  Δ Y /Δ Z   , a diagnostic of the chemical history of the solar neighbourhood. Our sample of K dwarfs has homogeneously determined effective temperatures, bolometric luminosities and metallicities, allowing us to fit each star to the appropriate stellar isochrone and determine its helium content indirectly. We use a newly computed set of Padova isochrones which cover a wide range of helium and metal content.
Our theoretical isochrones have been checked against a congruous set of main-sequence binaries with accurately measured masses, to discuss and validate their range of applicability. We find that the stellar masses deduced from the isochrones are usually in excellent agreement with empirical measurements. Good agreement is also found with empirical mass-luminosity relations.
Despite fitting the masses of the stars very well, we find that anomalously low helium content (lower than primordial helium) is required to fit the luminosities and temperatures of the metal-poor K dwarfs, while more conventional values of the helium content are derived for the stars around solar metallicity.
We have investigated the effect of diffusion in stellar models and the assumption of local thermodynamic equilibrium (LTE) in deriving metallicities. Neither of these is able to resolve the low-helium problem alone and only marginally if the cumulated effects are included, unless we assume a mixing-length which is strongly decreasing with metallicity. Further work in stellar models is urgently needed.
The helium-to-metal enrichment ratio is found to be  Δ Y /Δ Z = 2.1 ± 0.9  around and above solar metallicity, consistent with previous studies, whereas open problems still remain at the lowest metallicities. Finally, we determine the helium content for a set of planetary host stars.     

Impact of past mining activity on the quality of groundwater in SW Sardinia (Italy)

Hydrogeochemical surveys were carried out in SW Sardinia (Italy) to investigate the impact of past mining activities on the quality of groundwater. The chemistry of waters from flooded galleries, adits and dumps has been compared with that of springs and wells in the same area at sites relatively far from any mine legacy. A feature, common to all waters, is the circumneutral pH, since the carbonate formations in the area neutralise the acidity produced by the oxidation of Fe-bearing sulphide minerals in the mine impacted water. However, groundwater interacting with mine workings is degraded in quality; it shows high dissolved SO₄, Zn, Cd and Pb contents. In some cases groundwater exceeds the limit established by the guidelines of the World Health Organization for Pb content in drinking water, so that groundwater is mixed before entering the local aqueducts. Results from this study suggest that more attention needs to be paid to the impact on the streams from contaminated water flowing out from some mine areas because during the dry season these streams are only fed by mine groundwater. We recommend focusing efforts to reduce the chemical contamination prior to discharge.     

GRIDA3—a shared resources manager for environmental data analysis and applications

GRIDA3 (Shared Resources Manager for Environmental Data Analysis and Applications) is a multidisciplinary project designed to deliver an integrated system to forge solutions to some environmental challenges such as the constant increase of polluted sites, the sustainability of natural resources usage and the forecast of extreme meteorological events. The GRIDA3 portal is mainly based on Web 2.0 technologies and EnginFrame framework. The portal, now at an advanced stage of development, provides end-users with intuitive Web-interfaces and tools that simplify job submission to the underneath computing resources. The framework manages the user authentication and authorization, then controls the action and job execution into the grid computing environment, collects the results and transforms them into an useful format on the client side. The GRIDA3 Portal framework will provide a problem-solving platform allowing, through appropriate access policies, the integration and the sharing of skills, resources and tools located at multiple sites across federated domains.     

Sequence stratigraphy of a Mesozoic carbonate platform-to-basin system in western Sicily

Sequence stratigraphic studies of the Triassic through Paleogene carbonate successions of platform, slope and basin in western Sicily (Palermo and Termini Imerese Mountains) have identified a sedimentary cyclicity mostly caused by relative oscillations of sea level. The stratigraphic successions of the Imerese and Panormide palaeogeographic domains of the southern Tethyan continental margin were studied with physical-stratigraphy and facies analysis to reconstruct the sedimentary evolution of this platform-to-basin system. The Imerese Basin is characterized by a carbonate and siliceous-calcareous succession, 1200–1400m thick, Late Triassic to Eocene in age. The strata display a typical example of a carbonate platform margin, characterized by resedimented facies with progradational stacking patterns. The Panormide Carbonate Platform is characterized by a carbonate succession, 1000–1200 m thick, Late Triassic to Late Eocene, mostly consisting of shallow-water facies with periodic subaerial exposure. The cyclic arrangement has been obtained by the study of the stratigraphic signatures (unconformities, facies sequences, erosional surfaces and stratal geometries) found in the slope successions. The recognized pattern has been compared with coeval facies of the shelf. This correlation provided evidence of sedimentary evolution, influenced by progradation and backstepping of the shelf deposits. The stratigraphic architecture of the platform-to-basin system is characterized by four major transgressive/regressive cycles during the late Triassic to late Eocene. These cycles, framed in a chronostratigraphic chart, allows the correlation of the investigated shelf-to-basin system with the geological evolution of the African continental margin during the Mesozoic, showing tectono-eustatic cycles. The first cycle, encompassing the late Triassic to early Jurassic, appears to be related to the late syn-rift stage of the continental margin evolution. The following three cycles, spanning from the Jurassic to Eocene, can be related to the post-rift evolution and to thermal subsidence changes.     

Improvement of HVSR technique by self-organizing map (SOM) analysis

Data interpretation is one of the most important and thorny tasks in geosciences. Difficulties occur especially in non-invasive geophysical techniques and/or when the data that have to be analyzed are multidimensional, non-linear and highly noisy. Another important task is to ensure an efficient automatic data analysis, in order to allow a data interpretation as independent as possible from any a priori knowledge. This paper describes the post-processing application of a kind of neural network (self-organizing map, SOM) to the identification of the fundamental HVSR frequency of a given site. SOM results can be represented as two-dimensional maps, with a non-parametric mapping that projects the high dimensional original dataset in a fashion that provides both an unsupervised clustering and a highly visual representation of the data relationships. This innovative application of the SOM algorithm is presented with a case study related to the characterization of a mineral deposit.