Extensive boiling as a precipitation mechanism for precious and base metal ores, Bienaventurada Mine, Huancavelica, Perú

The Bienaventurada mine operates a polymetallic Ag-Pb-Zn (Cu, Au) vein system of the low sulphidation epithermal type. Fluid inclusions, FI, are abundant in quartz, sphalerite and adularia. FI petrography demonstrates typical primary growth zoning which occurs frequently in crystalline quartz, and defines the most common primary FI. These are usually very small, but several types of primary, P, and secondary, S, FI Assemblages (FIAs) comprising FI of measurable size (3 to > 100 μm) can also be identified through careful petrographic work. The fluids are aqueous and undersaturated, and no evidence of CO2 was found; the degree of fill is usually high (~70-80 %) in the L-rich inclusions, but extremely low in V-rich inclusions. The measured microthermometric values are very consistent in the FIAs selected; they are for the most part roughly similar in the P and S assemblages: the median is typically ~258ºC for total homogenization temperatures, Th, and -1.5 ºC for ice melting temperatures, Tm (corresponding to 2.57 wt% NaCl eq). The widespread occurrence of L-rich and V-rich FI in the same FIA and the consistent Th values point to an extensive boiling system along the vein. In these conditions, Th equals T of trapping, and the ores are assumed to have been precipitated from an aqueous low salinity boiling fluid, of likely meteoric origin, at some 250-280º C, under ~500 m hydrostatic head.

Spatial and temporal precipitation patterns of the Ebro River Basin, Spain

The Ebro River Basin, with around 85 000 km2 and located in NE Spain, is characterized by the high spatial heterogeneity of its geology, topography, climatology and land use. Rainfall is one of the most important climatic variables studied owing to its non-homogenous behaviour in event and intensity, which creates drought, water runoff and soil erosion with negative environmental and social consequences. In this work we characterized the rainfall variability pattern in the Ebro River Basin using universal multifractal (UM) analysis, which estimates the concentration of the data around the precipitation average (C1, codimension average), the degree of multiscaling behaviour in time (? index) and the maximum probable singularity in the rainfall distribution ( s). A spatial and temporal analysis of the UM parameters is applied to study the possible changes. With this porpoise, 60 daily rainfall series were selected from 132 synthetic series generated by Luna and Balairón (AEMet). These daily rainfall series present a length of 60 years, from 1950 to 2009. Each one of them was subdivided (1950?1970 and 1980?2009) to analyse the difference between the two periods. The range of variation of precipitation amounts and the frequency of dry events between both periods are discussed, as well as the evolution of the UM parameters through the years.

El programa ERHIN y la gestión de embalses en áreas con alta precipitación nival = The ERHIN programme and reservoir management in areas of high nival precipitation

El programa de Evaluación Recursos Hídricos procedentes de la Innivación (ERHIN) ha desarrollado un modelo hidrológico con subrutinas que contemplan el proceso de acumulación/fusión de nieve que permite el seguimiento del manto de nieve y su fusión , esencial para la previsión de avenidas en embalses cuyas cuencas vertientes recogen altos porcentajes de precipitación solida. En determinados sectores del territorio español (Pirineos, Cordilleras Cantábrica e Ibérica, Sistema Central y Sierra Nevada) la precipitación nival alcanza valores significativos durante el invierno, que conducen a espesores de nieve persistentes en las cuencas alimentadoras de numerosos embalses y a la fusión rápida de esta nieve en períodos cortos de tiempo, directamente relacionados con la elevación de la isoterma de cero grados en primavera. Estos procesos condicionan la gestión de los mencionados embalses.

Examining wheat yield sensitivity to temperature and precipitation changes for a large ensemble of crop models using impact response surfaces

Impact response surfaces (IRSs) depict the response of an impact variable to changes in two explanatory variables as a plotted surface. Here, IRSs of spring and winter wheat yields were constructed from a 25-member ensemble of process-based crop simulation models. Twenty-one models were calibrated by different groups using a common set of calibration data, with calibrations applied independently to the same models in three cases. The sensitivity of modelled yield to changes in temperature and precipitation was tested by systematically modifying values of 1981-2010 baseline weather data to span the range of 19 changes projected for the late 21st century at three locations in Europe.

Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces

This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to +9°C) and precipitation (-50 to +50%) was tested by modifying values of baseline (1981 to 2010) daily weather, with CO2 concentration fixed at 360 ppm. The IRS approach offers an effective method of portraying model behaviour under changing climate as well as advantages for analysing, comparing and presenting results from multi-model ensemble simulations. Though individual model behaviour occasionally departed markedly from the average, ensemble median responses across sites and crop varieties indicated that yields decline with higher temperatures and decreased precipitation and increase with higher precipitation. Across the uncertainty ranges defined for the IRSs, yields were more sensitive to temperature than precipitation changes at the Finnish site while sensitivities were mixed at the German and Spanish sites. Precipitation effects diminished under higher temperature changes. While the bivariate and multi-model characteristics of the analysis impose some limits to interpretation, the IRS approach nonetheless provides additional insights into sensitivities to inter-model and inter-annual variability. Taken together, these sensitivities may help to pinpoint processes such as heat stress, vernalisation or drought effects requiring refinement in future model development.