Groundwater travel time in the freshwater lenses of Samborombón Bay,Argentina

Abstract

The Samborombón Bay area (Argentina) is a coastal plain environment that contains groundwater resources with high salinity. In addition, there are local freshwater lenses associated with shell ridges and sand sheets in the region. In this work, the groundwater travel time in these freshwater lenses is estimated based on their geological conditions, which include hydraulic conductivity, recharge, morphology and discharge to surface freshwater or to saline groundwater. Groundwater travel times in the freshwater lenses were calculated from the equations developed by Chesnaux and Allen. The travel times estimated for the different scenarios were relatively short. The results indicate that the groundwater flow tends to be strongly dependent on the recharge conditions, with an excess of water in the water balance. The results can be applied to help design sustainable management methods to exploit this water resource system and also to assess the impact of contaminant plumes on this groundwater resource.

Citation Carol, E., Kruse, E. & Roig, A. (2010) Groundwater travel time in the freshwater lenses of Samborombón Bay, Argentina. Hydrol. Sci. J. 55(5), 754–762.     

Assessment of possible peak accelerations through stochastic variations

A method is presented for the estimation of possible maximum accelerations, as well as of other accelerogram or seismogram characteristics, based on the stochastic variation of the spectral phase of pulses from an observed time series of interest, possibly the ‘design earthquake’. For a seismic source with the same spectral amplitude the variations are caused by slight differences in source time function, source or receiver location, etc. A large number of variations define the range of possible time series, as well as clear and stable relationships between the standard deviations of phase variation distributions (here considered Gaussian) and possible values of the studied features, as well as their distributions and probabilities.     

An Analysis of Polar Coronal Hole Evolution: Relations to Other Solar Phenomena and Heliospheric Consequences

We use observations of the green corona low-brightness regions to construct a time series of a polar coronal hole area from 1939 to 1996, covering 5 solar cycles. We then perform a power-spectral analysis of the monthly data time series. Several persistent significant periodicities appear in the spectra, which are related with those found in solar magnetic flux emergence, geomagnetic storm sudden commencements and cosmic-ray flux at Earth. Of particular importance are the peak at around 1.6–1.8 yr recently found in cosmic-ray intensity fluctuations, and the peak at around 1 yr, also identified in coronal hole magnetic flux variations. Additional interesting features are the peaks close to 5 yr, 3 yr and the possible peak at around 30 yr, that were also found in other solar and interplanetary phenomena. Our results stress the physical connection between the solar magnetic flux emergence and the interplanetary medium dynamics, in particular the importance of coronal hole evolution in the structuring of the heliosphere.     

shinyNORRRM: A Cross-Platform Software to Calculate the CIPW Norm

In this paper, a novelty-free software to assess an efficient CIPW Norm (± 0.006 wt.% in differences between input and output data) is presented. The package is available in the official repository for user-contributed R packages (CRAN: Comprehensive R Archive Network). The software is able to handle big data sets and considers minor and trace element compositions. The algorithm can calculate odd minerals in igneous rocks, such as cancrinite and calcite, adjust the Fe⁺³/Fe⁺² ratio in different standard approaches, and recalculate the compositions of the rocks in an anhydrous basis (100 ± 0.003 wt.% volatile-free adjusted). Furthermore, the package calculates several petrological parameters, and the graphical outputs are displayed following IUGS scheme standards. The prime aspect of shinyNORRRM is the symbiosis of native R functions with the R package’s shiny (Web Application Framework for R) to run the norm in a user-friendly interface. shinyNORRRM can be executed in any operating system and requires no previous programming knowledge, thus promising to be the universal computational program in this matter. The output data are printed in the standard comma-separated values (*.csv) format, which is highly compatible with general spreadsheet editors. In this work, the algorithm of our program is validated using already compiled whole-rock geochemical databases.

     

New insights into geochemical behaviour in ancient marine carbonates (Upper Jurassic Ammonitico Rosso): Novel proxies for interpreting sea‐level dynamics and palaeoceanography

Elemental concentrations in Phanerozoic sea water are known to fluctuate both in time and space. With regard to carbonates precipitated from marine fluids, elemental concentrations in the carbonate crystal lattice are affected by a complex array of equilibrium and non‐equilibrium as well as post‐depositional alteration processes. To assess the potential of carbonate elemental chemostratigraphy, seven Upper Jurassic sections were investigated along a proximal to distal transect across the south‐east Iberian palaeomargin. The aim was to explore stratigraphic and spatial variations in calcium, strontium, magnesium, iron and manganese elemental abundances. The epicontinental geochemical record is influenced by the combination of continental runoff and a significant diagenetic overprint. In contrast, the epioceanic geochemical record agrees with reconstructed open marine sea water values, reflecting a moderate degree of syn‐depositional to early marine pore water diagenesis. Establishing a fair degree of preservation of matrix micrite, a thorough statistical approach was applied and elemental associations tested for their environmental significance. Principal component and hierarchical cluster analyses revealed a persistent relation between carbonate magnesium, iron and strontium abundances. Processes related to early diagenetic nodulation in Ammonitico Rosso facies most probably account for the incorporation of these elements in the calcium carbonate lattice. The clear decoupling of carbonate manganese abundance with respect to the remaining elements is documented and related to high sea floor spreading rates and hydrothermal activity during the Late Jurassic. The investigation of potential time‐fluctuation of geochemical patterns was approached through variogram computation. The observed temporal behaviour is most likely to be forced by relative sea‐level dynamics, reflecting Late Jurassic palaeoceanographic conditions and potential planetary interactions. The data obtained in this study highlight the utility of elemental data from carbonate matrix micrites as geochemical proxies for studying the influence of remote trigger factors.     

Effects of Amazon basin deforestation on regional atmospheric circulation and water vapor transport towards tropical South America

The water cycle over the Amazon basin is a regulatory mechanism for regional and global climate. The atmospheric moisture evaporated from this basin represents an important source of humidity for itself and for other remote regions. The deforestation rates that this basin has experienced in the past decades have implications for regional atmospheric circulation and water vapor transport. In this study, we analyzed the changes in atmospheric moisture transport towards tropical South America during the period 1961–2010, according to two deforestation scenarios of the Amazon defined by Alves et al. (Theor Appl Climatol 100(3-4):337–350, 2017). These scenarios consider deforested areas of approximately 28% and 38% of the Amazon basin, respectively. The Dynamic Recycling Model is used to track the transport of water vapor from different sources in tropical South America and the surrounding oceans. Our results indicate that under deforestation scenarios in the Amazon basin, continental sources reduce their contributions to northern South America at an annual scale by an average of between 40 and 43% with respect to the baseline state. Our analyses suggest that these changes may be related to alterations in the regional Hadley and Walker cells. Amazon deforestation also induces a strengthening of the cross-equatorial flow that transports atmospheric moisture from the Tropical North Atlantic and the Caribbean Sea to tropical South America during the austral summer. A weakening of the cross-equatorial flow is observed during the boreal summer, reducing moisture transport from the Amazon to latitudes further north. These changes alter the patterns of precipitable water contributions to tropical South America from both continental and oceanic sources. Finally, we observed that deforestation over the Amazon basin increases the frequency of occurrence of longer dry seasons in the central-southern Amazon (by between 29 and 57%), depending on the deforestation scenario considered, as previous studies suggest.     

Potential for small scale added value of RCM’s downscaled climate change signal

In recent decades, the need of future climate information at local scales have pushed the climate modelling community to perform increasingly higher resolution simulations and to develop alternative approaches to obtain fine-scale climatic information. In this article, various nested regional climate model (RCM) simulations have been used to try to identify regions across North America where high-resolution downscaling generates fine-scale details in the climate projection derived using the “delta method”. Two necessary conditions were identified for an RCM to produce added value (AV) over lower resolution atmosphere-ocean general circulation models in the fine-scale component of the climate change (CC) signal. First, the RCM-derived CC signal must contain some non-negligible fine-scale information—independently of the RCM ability to produce AV in the present climate. Second, the uncertainty related with the estimation of this fine-scale information should be relatively small compared with the information itself in order to suggest that RCMs are able to simulate robust fine-scale features in the CC signal. Clearly, considering necessary (but not sufficient) conditions means that we are studying the “potential” of RCMs to add value instead of the AV, which preempts and avoids any discussion of the actual skill and hence the need for hindcast comparisons. The analysis concentrates on the CC signal obtained from the seasonal-averaged temperature and precipitation fields and shows that the fine-scale variability of the CC signal is generally small compared to its large-scale component, suggesting that little AV can be expected for the time-averaged fields. For the temperature variable, the largest potential for fine-scale added value appears in coastal regions mainly related with differential warming in land and oceanic surfaces. Fine-scale features can account for nearly 60 % of the total CC signal in some coastal regions although for most regions the fine scale contributions to the total CC signal are of around ～5 %. For the precipitation variable, fine scales contribute to a change of generally less than 15 % of the seasonal-averaged precipitation in present climate with a continental North American average of ～5 % in both summer and winter seasons. In the case of precipitation, uncertainty due to sampling issues may further dilute the information present in the downscaled fine scales. These results suggest that users of RCM simulations for climate change studies in a delta method framework have little high-resolution information to gain from RCMs at least if they limit themselves to the study of first-order statistical moments. Other possible benefits arising from the use of RCMs—such as in the large scale of the downscaled fields– were not explored in this research.     

Nonparametric analysis of high wind speed data

In this paper, nonparametric curve estimation methods are applied to analyze time series of wind speeds, focusing on the extreme events exceeding a chosen threshold. Classical parametric statistical approaches in this context consist in fitting a generalized Pareto distribution (GPD) to the tail of the empirical cumulative distribution, using maximum likelihood or the method of the moments to estimate the parameters of this distribution. Additionally, confidence intervals are usually computed to assess the uncertainty of the estimates. Nonparametric methods to estimate directly some quantities of interest, such as the probability of exceedance, the quantiles or return levels, or the return periods, are proposed. Moreover, bootstrap techniques are used to develop pointwise and simultaneous confidence intervals for these functions. The proposed models are applied to wind speed data in the Gulf Coast of US, comparing the results with those using the GPD approach, by means of a split-sample test. Results show that nonparametric methods are competitive with respect to the standard GPD approximations. The study is completed generating synthetic data sets and comparing the behavior of the parametric and the nonparametric estimates in this framework.     

Optical Spectroscopy of Comet C/2000 WM1 (LINEAR) at the Guillermo Harro Astrophysical Observatory in Mexico

We present a preliminary analysis of medium resolution optical spectra of comet C/2000 WM1 (LINEAR) obtained on 22 November 2001. Theemission lines of the molecules C₂, C₃, CN, NH₂,H₂O⁺ and presumably CO (Asundi and triplet bands) and C₂ ^-were identified in these spectra. By analysing the brightnessdistributions of the C₂, C₃, CN emission lines along theslit of the spectrograph we determined some physical parameters of theseneutrals, such as their lifetimes and expansion velocities inthe coma. The Franck–Condon factors for the CO Asundi bands and C₂ ^- bands were calculated using a Morse potential model.