Hydrogen diffusion in clinopyroxene: dehydration experiments

Hydrogen diffusivity of one clinopyroxene megacryst from Nüshan, eastern China parallel to [001]* crystallographic direction was measured by high-temperature sequential dehydration experiments at 950℃ and 850℃, which was (6.5± 1.5)×10-12(m2/s) and (1.8± 0.7)×10-12(m2/s) respectively. From these results and the previous published data, it seems that the correlation between hydrogen diffusivity and Fe content suggested by Dyar et al. (1996) possibly does not exist. Clinopyroxene megacrysts from alkali basalts appear to be possible reliable samples for the study of the water evolution and hydrogen isotope compositions of the upper mantle.     

Data assimilation in groundwater modelling: ensemble Kalman filter versus ensemble smoothers

Groundwater modelling calls for an effective and robust data integrating method to fill the gap between the model and observation data. The ensemble Kalman filter (EnKF), a real‐time data assimilation method, has been increasingly applied in multiple disciplines such as petroleum engineering and hydrogeology. In this approach, a groundwater model is updated sequentially with measured data such as hydraulic head and concentration. As an alternative to the EnKF, the ensemble smoother (ES) has been proposed for updating groundwater models using all the data together, with much less computational cost. To further improve the performance of the ES, an iterative ES has been proposed for continuously updating the model by assimilating measurements together. In this work, we compare the performance of the EnKF, the ES, and the iterative ES using a synthetic example in groundwater modelling. Hydraulic head data modelled on the basis of the reference conductivity field are used to inversely estimate conductivities at unsampled locations. Results are evaluated in terms of the characterization of conductivity and groundwater flow predictions. It is concluded that (a) the iterative ES works better than the standard ES because of its continuous updating and (b) the iterative ES could achieve results comparable with those of the EnKF, with less computational cost. These findings show that the iterative ES should be paid much more attention for data assimilation in groundwater modelling.     

Estimation of water saturation dependence of dispersion in unsaturated porous media: experiments and modelling analysis

In the dispersion theory, a linear relationship has been verified between the coefficient of hydrodynamic dispersion and water velocity, both in saturated and in unsaturated porous media. But for unsaturated soils the variability of flow directions and microscopic velocities can be larger than in saturated soils because of the lower degree of water saturation. This leads to an increased dispersion. Therefore, relationships between water content and relative water velocity fluctuations and water content together with the coefficient of dispersivity in unsaturated porous media respectively have been investigated systematically by displacement experiments in glass beads and coarse-textured sandy soil columns. The breakthrough curves (BTCs) of chloride showed that an increase of solute mixing with a decrease of water content was caused by an increase of flow velocity fluctuations for different pathways. In order to explain the observed tailing effect in unsaturated flow, two mathematical models were used to fit theoretically derived nonlinear functions of water content dependent dispersivities for both porous media. The close agreement between the observed and computed results suggests that the theoretical model of hydrodynamic dispersion can be extended to transport in unsaturated porous media, providing that BTCs of the effluent water are used to estimate representative dispersivity parameters of soils.     

Local erosion rates versus active tectonics: cosmic ray exposure modelling in Provence (south-east France)

Over the past decade, in situ-produced cosmogenic nuclides have revolutionised the study of landscape evolution. In particular, numerous studies have demonstrated that, in active tectonic settings, cosmic ray exposure dating of deformed or displaced geomorphic features makes it possible to quantify long-term deformation rates. In western European countries, erosion due to climatically driven processes and human activities is probably the factor that most limits the accuracy of exposure ages and landscape modification rates. In this study, we present the results of a depth-profiling technique applied to alluvial terraces located along the Rhône and the Moyenne Durance rivers. The expected decrease with depth of the measured ¹⁰Be concentrations has been modelled using a χ² inversion method in order to constrain the exposure history of the alluvial sediments. The results suggest that: (1) over the Quaternary, the local surface erosion rates including both regional uplift and climatically driven processes acting on landforms are on the order of 30 m/Myr in southeastern France, and (2) providing a fairly good bracketing of the exposure age, the modelled abandonment age of alluvial terraces affected by the Moyenne Durance Fault allows estimating incision rates, comparing the alluvial terrace elevations with topographic river profiles, and a minimum vertical slip rate value of roughly 0.02 mm/yr for the southern segment of the Moyenne Durance Fault.     

A bivariate stochastic Gamma diffusion model: statistical inference and application to the joint modelling of the gross domestic product and CO2 emissions in Spain

This paper examines the use of a bivariate stochastic Gamma diffusion model to represent the co-evolution of the stochastic variables CO₂ emission and gross domestic product (GDP) in Spain. These variables were selected in view of the strong correlation between them. We compare the results obtained to those provided by the Gamma one-dimensional process with exogenous factors, taking CO₂ emission as an endogenous variable and GDP as the exogenous factor. This methodology was applied to a real case, with two dependent variables: firstly, GDP and CO₂ emission from the combustion of fossil fuels (gas, liquid and solid fuels) and cement manufacture in Spain. And secondly, with GDP and CO₂ emission from the consumption and flaring of natural gas in Spain. The joint dynamic evolution of these factors is represented by the proposed model. In addition, a comparison is made with results obtained from fitting the data using the Gamma diffusion process with external factors, in which GDP is the variable containing the external information. This implementation was carried out on the basis of annual observations of the variables over the periods 1986–2008 and 1986–2009, respectively.     

Improving the estimation of hydrological states in the SWAT model via the ensemble Kalman smoother: Synthetic experiments for the Heihe River Basin in northwest China

Data assimilation as a method to predict variables, reduce uncertainties and explicitly handle various sources of uncertainties has recently received widespread attention and has been utilized to combine in situ and remotely sensed measurements with hydrological models. However, factors that significantly influence the capability of data assimilation still need testing and verifying. In this paper, synthetic surface soil moisture data are assimilated into the Soil and Water Assessment Tool (SWAT) model to evaluate their impact on other hydrological variables via the ensemble Kalman smoother (EnKS), using data from the Heihe River Basin, northwest China. The results show that the assimilation of surface soil moisture can moderately improve estimates of deep layer soil moisture, surface runoff and lateral flow, which reduces the negative influences of erroneous forcing and inaccurate parameters. The effects of the spatially heterogeneous input data (land cover and soil type) on the performance of the data assimilation technique are noteworthy. Moreover, the approaches including inflation and localization are specifically diagnosed to further extend the capability of the EnKS.