Quantification of the ferric/ferrous iron ratio in silicates by scanning transmission X-ray microscopy at the Fe L2,3 edges

Estimation of Fe³⁺/ΣFe ratios in materials at the submicrometre scale has been a long-standing challenge in the Earth and environmental sciences because of the usefulness of this ratio in estimating redox conditions as well as for geothermometry. To date, few quantitative methods with submicrometric resolution have been developed for this purpose, and most of them have used electron energy-loss spectroscopy carried out in the ultra-high vacuum environment of a transmission electron microscope (TEM). Scanning transmission X-ray microscopy (STXM) is a relatively new technique complementary to TEM and is increasingly being used in the Earth sciences. Here, we detail an analytical procedure to quantify the Fe³⁺/ΣFe ratio in silicates using Fe L_2,3-edge X-ray absorption near edge structure (XANES) spectra obtained by STXM, and we discuss its advantages and limitations. Two different methods for retrieving Fe³⁺/ΣFe ratios from XANES spectra are calibrated using reference samples with known Fe³⁺ content by independent approaches. The first method uses the intensity ratio of the two major peaks at the L₃-edge. This method allows mapping of Fe³⁺/ΣFe ratios at a spatial scale better than 50 nm by the acquisition of 5 images only. The second method employs a 2-eV-wide integration window centred on the L₂ maximum for Fe³⁺, which is compared to the total integral intensity of the Fe L₂-edge. These two approaches are applied to metapelites from the Glarus massif (Switzerland), containing micrometre-sized chlorite and illite grains and prepared as ultrathin foils by focused ion beam milling. Nanometre-scale mapping of iron redox in these samples is presented and shows evidence of compositional zonation. The existence of such zonation has crucial implications for geothermometry and illustrates the importance of being able to measure Fe³⁺/ΣFe ratios at the submicrometre scale in geological samples.     

Metasomatism and graphite formation at a lithological interface in Malaspina (Alpine Corsica, France)

Multiple pieces of geologic evidence suggest that interfaces between contrasted lithologies exert a strong control on the fate of volatiles in subduction zones. Here we present results from a contact between serpentinites and sediments, located in Corsica and metamorphosed in the blueschist facies during the alpine orogeny. It was shown previously that carbonates in the sediments have been reduced to graphitic carbonaceous material within a 5–10-cm-thick reaction zone at the contact with serpentinites. In an effort to investigate the mechanisms governing this unusual process, bulk rock geochemical analyses incorporating a statistical analysis of compositional data are presented. Observations show that the fate of C was decoupled from that of other elements such as O, H, and large-ion lithophile elements—e.g. K, Sr, Ba...,As—that were extensively leached from the reaction zone. Notably, Na is strongly enriched in the reaction zone and structurally linked to pectolite. Reducing conditions, manifested by the depletion of O in the reaction zone compared to the bulk metasediment, were likely maintained by the presence of Fe(II) in the serpentinite. Moreover, thermodynamic calculations show that the low solubility of carbon in COH fluids at high-pressure and low-temperature conditions was the main driver for graphite precipitation synchronously with carbonate destabilization. This may have been kinetically favored by the presence of already existing graphitized carbonaceous material and phengite in the metasediment. Limited lateral flow might have contributed as well to the geochemical and petrological patterns observed in these rocks.     

Modeling forest fire risk in the northeast of Iran using remote sensing and GIS techniques

Fire in forested areas can be regarded as an environmental disaster which is triggered by either natural forces or anthropogenic activities. Fires are one of the major hazards in forested and grassland areas in the north of Iran. Control of fire is difficult, but it is feasible to map fire risk by geospatial technologies and thereby minimize the frequency of fire occurrences and damages caused by fire. The fire risk models provide a suitable concept to understand characterization of fire risk. Some models are map based, and they combine effectively different forest fire–causing variables with remote sensing data in a GIS environment for identifying and mapping forest fire risk. In this study, Structural Fire Index, Fire Risk Index, and a new index called Hybrid Fire Index were used to delineate fire risk in northeastern Iran that is subjected to frequent forest fire. Vegetation moisture, slope, aspect, elevation, distance from roads, and vicinity to settlements were used as the factors influencing accidental fire starts. These indices were set up by assigning subjective weight values to the classes of the layers based on their sensitivity ratio to fire. Hot spots data derived from MODIS satellite sensor were used to validate the indices. Assessment of the indices with receiver operating characteristic (ROC) curves shows that 76.7 % accuracy of the HFI outperformed the other two indices. According to the Hybrid Fire Index, 57.5 % of the study area is located under high-risk zone, 33 % in medium-risk zone, and the remaining 9.5 % area is located in low-risk zone.     

Implementation of method of lines to predict water levels due to a storm along the coastal region of Bangladesh

In this study, the method of lines (MOL) has been applied to solve two-dimensional vertically integrated shallow water equations in Cartesian coordinates for the prediction of water levels due to a storm surge along the coast of Bangladesh. In doing so, the partial derivatives with respect to the space variables were discretized by the finite difference (central) method to obtain a system of ordinary differential equations (ODEs) with time as independent variable. The classical fourth-order Runge–Kutta method was used to solve the obtained system of the ODEs. We used a nested finite difference scheme, where a high resolution fine grid model (FGM) capable of incorporating all major islands along the coastal region of Bangladesh was nested into a coarse grid model (CGM) covering up to 15°N latitude of the Bay of Bengal. The boundaries of the coast and islands were approximated through proper stair step. Appropriate tidal condition over the model domain was generated by forcing the sea level to be oscillatory with the constituent M ₂ along the southern open boundary of the CGM omitting wind stress. Along the northeast corner of the FGM, the Meghna River discharge was taken into account. The developed model was applied to estimate water levels along the coast of Bangladesh due to the interaction of tide and surge associated with the April 1991 storm. We also computed our results employing the standard finite difference method (FDM). Simulated results show the MOL performs well in comparison with the FDM with regard to CPU time and stability, and ensures conformity with observations.     

FAO 56 Model and Remote Sensing for the Estimation of Crop-Water Requirement in Main Branch Canal of the Bhadra Command area, Karnataka State

Remote sensing and FAO 56 crop water model are used for estimating crop water requirement for paddy crop located in the main branch canal of Bhadra Command Area in Karnataka, India. The estimation of crop-water requirement depends on the meteorological factors, soil type and crop coefficients. The result obtained showed that water requirements of rabi crops higher than those of the kariff crops. The total irrigated area estimated from the IRS image is 29,353 ha. It is found that the total paddy crop acreage is 18,257 ha covering 62 % in the total irrigated area of the command area, Arecanut 20 %, coconut 15 % and sugarcane with other crops 3 %. The water requirement for paddy is 1180.4 mm for its entire growth period. The total water requirement for irrigation supply for crops in the entire command area is 5,790 at a demand of 0.10501 cusecs per ha.     

A wavelet-neural network hybrid modelling approach for estimating and predicting river monthly flows

Abstract

A wavelet-neural network (WNN) hybrid modelling approach for monthly river flow estimation and prediction is developed. This approach integrates discrete wavelet multi-resolution decomposition and a back-propagation (BP) feed-forward multilayer perceptron (FFML) artificial neural network (ANN). The Levenberg-Marquardt (LM) algorithm and the Bayesian regularization (BR) algorithm were employed to perform the network modelling. Monthly flow data from three gauges in the Weihe River in China were used for network training and testing for 48-month-ahead prediction. The comparison of results of the WNN hybrid model with those of the single ANN model show that the former is able to significantly increase the prediction accuracy.

Editor D. Koutsoyiannis; Associate editor H. Aksoy

Citation Wei, S., Yang, H., Song, J.X., Abbaspour, K., and Xu, Z.X., 2013. A wavelet-neural network hybrid modelling approach for estimating and predicting river monthly flows. Hydrological Sciences Journal, 58 (2), 374–389.     

Adaptive time series compensator for delay compensation of servo‐hydraulic actuator systems for real‐time hybrid simulation

Hydraulic actuators are typically used in a real‐time hybrid simulation to impose displacements to a test structure (also known as the experimental substructure). It is imperative that good actuator control is achieved in the real‐time hybrid simulation to minimize actuator delay that leads to incorrect simulation results. The inherent nonlinearity of an actuator as well as any nonlinear response of the experimental substructure can result in an amplitude‐dependent behavior of the servo‐hydraulic system, making it challenging to accurately control the actuator. To achieve improved control of a servo‐hydraulic system with nonlinearities, an adaptive actuator compensation scheme called the adaptive time series (ATS) compensator is developed. The ATS compensator continuously updates the coefficients of the system transfer function during a real‐time hybrid simulation using online real‐time linear regression analysis. Unlike most existing adaptive methods, the system identification procedure of the ATS compensator does not involve user‐defined adaptive gains. Through the online updating of the coefficients of the system transfer function, the ATS compensator can effectively account for the nonlinearity of the combined system, resulting in improved accuracy in actuator control. A comparison of the performance of the ATS compensator with existing linearized compensation methods shows superior results for the ATS compensator for cases involving actuator motions with predefined actuator displacement histories as well as real‐time hybrid simulations. Copyright © 2013 John Wiley & Sons, Ltd.     

Numerical modelling: a useful tool to simulate collapsing volcanoes

Since the nineteenth century scientists have tried to reproduce natural events in order to study and understand them through the technique of modelling. However, technology has evolved rapidly in the past two decades and now sophisticated numerical models are widely used to reproduce past events or simulate new scenarios. These models are particularly useful to reproduce the large scale and complexity of geological events. To illustrate the use and potential of numerical modelling in geological sciences, we describe a simulation of a large debris avalanche caused by the collapse of the north flank of the Taranaki volcano in New Zealand and the value of this information in the context of disaster planning.     

Accuracy of grid precipitation data for Brazil: application in river discharge modelling of the Tocantins catchment

Here, we compared grid precipitation data — Climate Forecast System Reanalysis (CFSR) and WATCH Forcing Data methodology applied to ERA‐Interim (WFDEI) data — with Brazilian Weather Bureau (INMET) and Brazilian Water Agency (ANA) rain gauge data (n = 2027) for the period 1980–2010 in order to evaluate which grid data set better represents precipitation, and is thus more suitable for hydrological modelling of Brazilian water resources. We found that WFDEI outperformed CFSR according to three statistical indicators. We then applied and interpolated a simple bias correction to further improve WFDEI data before we used these data to model river discharge of the Tocantins catchment with the Soil and Water Assessment Tool (SWAT). Calibration (validation in parentheses; weighted averages of all gauges) had satisfactory statistical metrics: p‐factor = 0.52 (0.47); r‐factor = 0.84 (0.99); R² = 0.78 (0.71); bR² = 0.68 (0.47); NS = 0.70 (0.66); Pbias = ?4.5 (4.0). Finally, the calibrated SWAT model was used to assess the spatial distribution of the catchment's water resources. Annual green water flow (evapotranspiration) increased from the south‐east (640–840 mm yr^?1) to north‐west (1140–1440 mm) of the Tocantins catchment, while green water storage (soil water content) increased from south (330–1070 mm) to north (2180–3290 mm). Blue water (water yield) had a less clear pattern, with lower values in the south and the central borders of the catchment (20–560 mm) and higher values along the central axis and the north (920–1460 mm). Our analysis suggested that WFDEI was an accurate representation of Brazilian precipitation. For large catchments, we therefore recommend the use of WFDEI instead of sparse and often missing rain gauge data in modelling Brazilian water resources. Copyright © 2015 John Wiley & Sons, Ltd.