Advances in lithium analysis in solids by means of laser-induced breakdown spectroscopy: an exploratory study

Lithium is an important geochemical tracer for fluids or solids. However, because the electron microprobe cannot detect Li, variations of Li abundance at the micrometric scale are most often estimated from bulk analyses. In this study, the Li intense emission line at 670.706 nm in optical emission spectroscopy was used to perfect the analysis of Li at the micrometric scale by means of laser-induced breakdown spectroscopy (LIBS). To estimate lithium content for different geological materials, LIBS calibration of the emission line at 670.706 nm was achieved by use of synthetic glasses and natural minerals. The detection limit for this method is ∼5 ppm Li. Three applications to geological materials show the potential of LIBS for lithium determination, namely for Li-bearing minerals, melt inclusions, quartz, and associated fluid inclusions.For spodumene and petalite from granite pegmatite dikes (Portugal), the Li₂O concentrations are 7.6 ± 1.6 wt% and 6.3 ± 1.3 wt%, respectively, by use of LIBS. These values agree with ion microprobe analyses, bulk analyses, or both. For eucryptite crystals, the Li concentrations are scattered because grain size is smaller than the LIBS spatial resolution (6 to 8 μm). Lithium concentrations of melt inclusions from the Streltsovka U deposit (Siberia) are in the range of 2 to 6.2 wt% (Li₂O) for Li-rich daughter minerals. Lithium estimations on silicate glasses display values between 90 and 400 ppm.Lithium was also analyzed as a trace element in quartz. Transverse profiles were performed in hydrothermal barren quartz veins from the Spanish Central System (Sierra de Guadarrama). The highest Li concentrations (250 to 370 ppm) were found in specific growth bands in conjunction with the observed variation in optical cathodoluminescence intensity. Considering the fluid inclusion analysis, the source of fluid responsible to the Li enrichment in quartz is probably high-salinity fluids derived from sedimentary basins.     

Green water overtopping analyzed with a SPH model

Wave overtopping on the decks of offshore platforms and ships can cause severe damage due to the high forces generated by the water. This phenomenon is analyzed within the framework of the Smoothed Particle Hydrodynamics (SPH) method. The presence of a fixed horizontal deck above the mean water level modifies strongly the wave kinematics. In particular, the flow in the wave crest is split into two, showing a different behavior above and below the deck. Numerical results generated by the SPH method are compared to laboratory experiments. The formation of a jet in the rear of the deck after overtopping is observed under extreme conditions.     

The Use of Geographically Weighted Regression for Spatial Prediction: An Evaluation of Models Using Simulated Data Sets

Increasingly, the geographically weighted regression (GWR) model is being used for spatial prediction rather than for inference. Our study compares GWR as a predictor to (a) its global counterpart of multiple linear regression (MLR); (b) traditional geostatistical models such as ordinary kriging (OK) and universal kriging (UK), with MLR as a mean component; and (c) hybrids, where kriging models are specified with GWR as a mean component. For this purpose, we test the performance of each model on data simulated with differing levels of spatial heterogeneity (with respect to data relationships in the mean process) and spatial autocorrelation (in the residual process). Our results demonstrate that kriging (in a UK form) should be the preferred predictor, reflecting its optimal statistical properties. However the GWR-kriging hybrids perform with merit and, as such, a predictor of this form may provide a worthy alternative to UK for particular (non-stationary relationship) situations when UK models cannot be reliably calibrated. GWR predictors tend to perform more poorly than their more complex GWR-kriging counterparts, but both GWR-based models are useful in that they provide extra information on the spatial processes generating the data that are being predicted.     

Do mixing models with different input requirement yield similar streamflow source contributions? Case study: A tropical montane catchment

Hydrogeochemical based mixing models have been successfully used to investigate the composition and source identification of streamflow. The applicability of these models is limited due to the high costs associated with data collection and the hydrogeochemical analysis of water samples. Fortunately, a variety of mixing models exist, requiting different amount of data as input, and in data scarce regions it is likely that preference will be given to models with the lowest requirement of input data. An unanswered question is if models with high or low input requirement are equally accurate. To this end, the performance of two mixing models with different input requirement, the mixing model analysis (MMA) and the end-member mixing analysis (EMMA), were verified on a tropical montane headwater catchment (21.7 km²) in the Ecuadorian Andes. Nineteen hydrogeochemical tracers were measured on water samples collected weekly during 3 years in streamflow and eight potential water sources or end-members (precipitation, lake water, soil water from different horizons and springs). Results based on 6 conservative tracers, revealed that EMMA (using all tracers) and MMA (using pair-combinations out of the 6 conservative ones), identified the same end-members: rainfall, soil water and spring water., as well as, similar contribution fractions to streamflow from rainfall 21.9% and 21.4%, soil water 52.7% and 52.3%, and spring water 26.1% and 28.7%, respectively. Our findings show that a hydrogeochemical mixing model requiring a few tracers can provide similar outcomes than models demanding more tracers as input data. This underlines the value of a preliminary detailed hydrogeochemical characterization as basis to derive the most cost-efficient monitoring strategy.     

Water transport and tracer mixing in volcanic ash soils at a tropical hillslope: A wet layered sloping sponge

Andosol soils formed in volcanic ash provide key hydrological services in montane environments. To unravel the subsurface water transport and tracer mixing in these soils we conducted a detailed characterization of soil properties and analyzed a 3-year data set of sub-hourly hydrometric and weekly stable isotope data collected at three locations along a steep hillslope. A weakly developed (52–61 cm depth), highly organic andic (Ah) horizon overlaying a mineral (C) horizon was identified, both showing relatively similar properties and subsurface flow dynamics along the hillslope. Soil moisture observations in the Ah horizon showed a fast responding (few hours) “rooted” layer to a depth of 15 cm, overlying a “perched” layer that remained near saturated year-round. The formation of the latter results from the high organic matter (33–42%) and clay (29–31%) content of the Ah horizon and an abrupt hydraulic conductivity reduction in this layer with respect to the rooted layer above. Isotopic signatures revealed that water resides within this soil horizon for short periods, both at the rooted (2 weeks) and perched (4 weeks) layer. A fast soil moisture reaction during rainfall events was also observed in the C horizon, with response times similar to those in the rooted layer. These results indicate that despite the perched layer, which helps sustain the water storage of the soil, a fast vertical mobilization of water through the entire soil profile occurs during rainfall events. The latter being the result of the fast transmissivity of hydraulic potentials through the porous matrix of the Andosols, as evidenced by the exponential shape of the water retention curves of the subsequent horizons. These findings demonstrate that the hydrological behavior of volcanic ash soils resembles that of a “layered sponge,” in which vertical flow paths dominate.     

Processes affecting groundwater temperature patterns in a coastal aquifer

The temperature depth profiles of six wells in the Motril-Salobren～a aquifer were used as a basis for a comparative analysis involving various parameters to determine their relations and factors influencing the different trends. There is a clear influence of ambient temperature on all the profiles, with a lag time of two to five months. Nevertheless, there are clear differences in the temperature depth profile patterns that can be accounted for by other factors. First, there is a greater influence of localized recharge; Guadalfeo River as opposed to diffuse recharge; irrigation return flow and rainfall. Three of the wells located near the riverbed of the Guadalfeo River have extremely variable temperature-depth profiles and show clear river influence. In springtime, during the highest flood stages of the river due to cold melt water from the Sierra Nevada, the groundwater falls in temperature. During secondary peaks in river flow rates during the autumn due to rainfall, the warm water increases groundwater temperature. The effect of the river recharge decreases with distance from the course since there is less mixing with water from the Guadalfeo River. In addition, there are two temperature-depth profiles in which temperature variations remain shallow and follow a pattern that cannot be attributed to the influence of either of the above two parameters. Among these two cases, the most influential factor is the groundwater flow pattern typical of a discharge zone, characterized by vertical-flow components.     

The Salamón gold deposit (León, Spain)

Located 55 km NE of the provincial capital León, Salamón deposit, discovered in 1985, is located on the southern slope of the Cantabrian Mountains, in the north of the Iberian Peninsula. The deposit is located on the León fault, which is a late-Variscan, E–W trending, deep structure extending for more than 100 km. The León fault has a complex history, and many mines and occurrences are located near it. The deposit is also close to small stocks and dykes of igneous rocks with intermediate to basic composition to which the mineralisation is related. The mineralisation is hosted mainly by the limestones and bituminous shales of the Lena Group (Namurian–Westphalian). There is also some mineralisation in other stratigraphic units of the Upper Carboniferous, such as the Maraña Group or the Stephanian B sediments.Apart from local and regional exploration, a detailed mineralogical and metallogenic research has been carried out. The epithermal mineralisation of Salamón was developed in two phases: an early dominant and extensive stage, with very fine crystalline gold-bearing sulphides, mainly pyrite, arsenic-bearing pyrite and arsenopyrite, in a matrix of quartz–chalcedony (jasperoid) and dolomite, and a later stage, of a larger crystal size, which occurs replacing the early stage or in pockets and veins, with greater mineralogical variety. Last of all there is a stage of supergene mineralisation, a product of the oxidant action of meteoric waters over the previous minerals. The hydrothermal alterations of the host rocks related to the orebodies are fundamentally decarbonatisation–dolomitisation, silicification and argillitisation. The early stages of mineralisation were produced in a temperature of 148–241°C, while that in the later stages occurred at 86–123°C. The early stage has been dated as 269±5 Ma, and this agrees with the ages of the other deposits of the district, which lay between 292 and 263 Ma, and the igneous rocks of the Peña Prieta stock (277±1 Ma), all which are of Permian age.The results of the studies carried out until now lead to the conclusion that Salamón is a Carlin-type gold deposit.     

Wavelet analyses of neural networks based river discharge decomposition

The problem of discharge forecasting using precipitation as input is still very active in Hydrology, and has a plethora of approaches to its solution. But, when the objective is to simulate discharge values without considering the phenomenology behind the processes involved, Artificial Neural Networks, ANN give good results. However, the question of how the black box internally solve this problem remains open. In this research, the classical rainfall-runoff problem is approached considering that the total discharge is a sum of components of the hydrological system, which from the ANN perspective is translated to the sum of three signals related to the fast, middle and slow flow. Thus, the present study has two aims (a) to study the time-frequency representation of discharge by an ANN hydrologic model and (b) to study the capabilities of ANN to additively decompose total river discharge. This study adds knowledge to the open problem of the physical interpretability of black-box models, which remains very limited. The results show that total discharge is adequately simulated in the time frequency domain, although less power spectrum is evident during the rainy seasons in the ANN model, due to fast flow underestimation. The wavelet spectrum of discharge represents well the slow, middle and fast flow components of the system with transit times of 256, 12–64 and 2–12 days, respectively. Interestingly, these transit times are remarkably similar to those of the soil water reservoirs of the studied system, a small headwater catchment in the tropical Andes. This result needs further research because it opens the possibility of determining MMT on a fraction of the cost of isotopic based methods. The cross-power spectrum indicates that the error in the simulated discharge is more related to the misrepresentation of the fast and the middle flow components, despite limitations in the recharge period of the slow flow component. With respect to the representation of individual signals of the slow, middle and fast flows components, the three neurons were uncapable to individually represent such flows. However, the combination of pairs of these signals resemble the dynamics and the spectral content of the aforementioned flows signals. These results show some evidence that signal processing techniques may be used to infer information about the hydrological functioning of a basin.