Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.     

Recovering the initial conditions of our local Universe from NOG and PSCz catalogues

We apply the ztrace algorithm to the optical NOG and infrared PSC z galaxy catalogues to reconstruct the pattern of primordial fluctuations that have generated our local Universe. We check that the density fields traced by the two catalogues are well correlated, and consistent with a linear relation [either in δ or in  log (1 +δ)  ] with relative bias (of NOG with respect to PSC z )   b _rel= 1.1 ± 0.1  . The relative bias relation is used to fill the optical zone of avoidance at  | b | < 20°  using the PSC z galaxy density field.
We perform extensive testing on simulated galaxy catalogues to optimize the reconstruction. The quality of the reconstruction is predicted to be good at large scales, up to a limiting wavenumber   k _lim≃ 0.4 h Mpc⁻¹  beyond which all information is lost. We find that the improvement arising from the denser sampling of the optical catalogue is compensated by the uncertainties connected to the larger zone of avoidance.
The initial conditions reconstructed from the NOG catalogue are found (analogously to those from the PSC z ) to be consistent with a Gaussian paradigm. We use the reconstructions to produce sets of initial conditions ready to be used for constrained simulations of our local Universe.     

High-T phase transition of synthetic ANaB(LiMg)CMg5Si8O22(OH)2 amphibole: an X-ray synchrotron powder diffraction and FTIR spectroscopic study

The synthetic amphibole Na_0.95(Li_0.95Mg_1.05)Mg₅Si₈O₂₂(OH)₂ was studied in situ at high-T, using IR OH-stretching spectroscopy and synchrotron X-ray powder diffraction. At room-T the sample has P2₁ /m symmetry, as shown by the FTIR spectrum. It shows in the OH region two well-defined and intense absorptions at 3,748 and 3,712 cm⁻¹, respectively, and two minor bands at 3,667 and 3,687 cm⁻¹. The main bands are assigned to the two independent O–H groups in the primitive structure. The two minor bands evidencing the presence of small amount of vacant A-site (^A□_0.05). With increasing T, these bands shift continuously and merge into a unique absorption at high temperature. A change as a function of increasing T is revealed by the evolution of the refined unit-cell parameters, whose trend shows a transition to C2/m at about 320–330°C. The spontaneous scalar strain, fitted with a tricritical 2–6 Landau potential, gives a T _c of 325(10)°C (β parameter = 0.27). Comparison with the second-order P2₁ /m ⇔ C2/m phase transition at 255°C for synthetic amphibole ^ANa_0.8^B(Na_0.8Mg_1.2)^CMg₅Si₈O₂₂(OH)₂ indicates that the substitution of Na with Li at the B-sites strongly affects the thermodynamic character and the T _c of the phase transition. The comparison of LNMSH amphiboles with cummingtonitic ones shows that the high-T thermodynamic behaviour is affected by A-site occupancy.     

Weathering characterization for landslides modeling in granitoid rock masses of the Capo Vaticano promontory (Calabria,Italy)

This work focuses on developing multidisciplinary researches concerning weathering profiles related to landscape evolution of the Capo Vaticano promontory on the Calabria Tyrrhenian side (southern Italy). In this area, the tectonic uplift, occurred at least since Pleistocene, together with the Mediterranean climatic conditions, is the main cause of deep weathering and denudation processes. The latter occurred on the outcropping rocks of the crystalline-metamorphic basement, made up of weathered granitoids, in turn belonging to the Monte Poro granitoid complex (intermediate to felsic plutonic rocks covered by Cenozoic sedimentary successions). Field observations coupled to borehole explorations, geophysical surveys, and minero-petrographical analyses allowed the characterization of the granitoid outcrops typical of the studied area in terms of kind and degree of slope instability. This characterization was based on suitable correlations verified between several factors as weathering degree, elastic properties of rocks, and discontinuity features. Weathering profiles are mainly composed by rock masses varying from completely weathered rock with corestones of highly weathered rock (classes IV–V) to slightly weathered rocks (class II). The weathered rocks are involved in several landslide typologies such as debris flow (frequency 48.5%), translational slide (frequency 33.3%), and minor rock fall and rotational slide (frequency 9%). The achieved data allowed the establishment of a general correlation between weathering degree and type of slope instability. Debris flow-type instabilities are predominant on the steeper slopes, involving very poor rock masses ascribed to the shallowest portions of the weathering class IV. Translational slides are less widespread than the previous ones and often involve a mixture of soil and highly weathered rocks. Rotational slides are more frequently close to the top of the slopes, where the thicknesses of more weathered rocks increase, and involve mainly rock masses belonging to the weathering classes IV and V. Rock falls mostly occur on the vertical escarpments of the road cuts and are controlled by the characteristics of the main discontinuities. The assessment of rock mass rating and slope mass rating, based on the application of the discontinuity data, allowed respectively an evaluation of the quality of rock masses and of the susceptibility of rock slopes to failure. The comparison between the last one and the real stability conditions along the cut slopes shows a good correspondence. Finally, the geological strength index system was also applied for the estimation of rock mass properties. The achieved results give a worthy support for a better understanding of the relationship between the distribution of landslides and the geological features related to different weathering degrees. Therefore, they can provide a reliable tool to evaluate the potential stability conditions of the rock slopes in the studied area and a general reference framework for the study of weathering processes in other regions with similar geological features.     

Mapping fractional landscape soils and vegetation components from Hyperion satellite imagery using an unsupervised machine-learning workflow

An unsupervised machine-learning workflow is proposed for estimating fractional landscape soils and vegetation components from remotely sensed hyperspectral imagery. The workflow is applied to EO-1 Hyperion satellite imagery collected near Ibirací, Minas Gerais, Brazil. The proposed workflow includes subset feature selection, learning, and estimation algorithms. Network training with landscape feature class realizations provide a hypersurface from which to estimate mixtures of soil (e.g. 0.5 exceedance for pixels: 75% clay-rich Nitisols, 15% iron-rich Latosols, and 1% quartz-rich Arenosols) and vegetation (e.g. 0.5 exceedance for pixels: 4% Aspen-like trees, 7% Blackberry-like trees, 0% live grass, and 2% dead grass). The process correctly maps forests and iron-rich Latosols as being coincident with existing drainages, and correctly classifies the clay-rich Nitisols and grasses on the intervening hills. These classifications are independently corroborated visually (Google Earth) and quantitatively (random soil samples and crossplots of field spectra). Some mapping challenges are the underestimation of forest fractions and overestimation of soil fractions where steep valley shadows exist, and the under representation of classified grass in some dry areas of the Hyperion image. These preliminary results provide impetus for future hyperspectral studies involving airborne and satellite sensors with higher signal-to-noise and smaller footprints.