Quantitative hazard and risk assessment for slow-moving landslides from Persistent Scatterer Interferometry

Preparation of reliable landslide hazard and risk maps is crucial for hazard mitigation and risk management. In recent years, various approaches have been developed for quantitative assessment of landslide hazard and risk. However, possibly due to the lack of new data, very few of these hazard and risk maps were updated after their first generation. In this study, aiming at an ongoing assessment, a novel approach for updating landslide hazard and risk maps based on Persistent Scatterer Interferometry (PSI) is introduced. The study was performed in the Arno River basin (central Italy) where most mass movements are slow-moving landslides which are properly within the detection precision of PSI point targets. In the Arno River basin, the preliminary hazard and risk assessment was performed by Catani et al. (Landslides 2:329–342, 2005) using datasets prior to 2002. In this study, the previous hazard and risk maps were updated using PSI point targets processed from 4 years (2003–2006) of RADARSAT images. Landslide hazard and risk maps for five temporal predictions of 2, 5, 10, 20 and 30 years were updated with the exposure of losses estimated in Euro (€). In particular, the result shows that in 30 years a potential loss of approximate €3.22 billion is expected due to these slow-moving landslides detected by PSI point targets.     

Modeling of the Guagua Pichincha volcano (Ecuador) lahars

Lahars, here defined as debris flows of volcanic origin, are rapid mass movements that pose a serious threat to cities located in the vicinity of many volcanoes. Quito, capital city of Ecuador and placed at the foot of the Pichincha volcano complex, is exposed to serious inundation hazard as part of the city is built on numerous deposits of large lahars that have occurred in the last 10,000 years.The objective of this paper is to model the potential lahars of the Pichincha volcano to predict inundation areas within the city of Quito. For this purpose two models that apply different approaches were utilized and their results were compared.The programs used were LAHARZ, a semi-empirical model conceived by the United States Geological Survey (USGS), and FLO-2D, a hydraulic model distributed by FLO Software Inc. LAHARZ is designed as a rapid, objective and reproducible automated method for mapping areas of potential lahar inundation (Proc. First Int. Conf. on Debris Flow Hazards Mitigation, San Francisco, USA, ASCE, 1998, p. 176). FLO-2D is a two-dimensional flood routing model for simulating overland flow on complex surfaces such as floodplains, alluvial fans or urbanized areas (FLO-2D Users manual, version 99.2). Both models run within geographical information systems (GIS).Fieldwork was focused on collecting all available information involved in lahar modeling. A total of 49 channel cross-sections were measured along the two main streams and stratigraphic investigations were carried out on the fans to estimate the volume of previous events. A global positioning system was utilized to determine the coordinates of each cross-section. Further data collection concerned topography, rainfall characteristics and ashfall thicknesses. All fieldwork was carried out in cooperation with the Instituto Geofisico of the Escuela Politecnica Nacional.Modeling in a GIS environment greatly aided the exportation of results for the creation of thematic maps and facilitated model comparison. Evaluation of the models was performed by comparing simulation results against each other and against the geometry of existing lahar deposits.     

Development and validation of a regional coupled atmosphere lake model for the Caspian Sea Basin

We present a validation analysis of a regional climate model coupled to a distributed one dimensional (1D) lake model for the Caspian Sea Basin. Two model grid spacings are tested, 50 and 20 km, the simulation period is 1989–2008 and the lateral boundary conditions are from the ERA-Interim reanalysis of observations. The model is validated against atmospheric as well as lake variables. The model performance in reproducing precipitation and temperature mean seasonal climatology, seasonal cycles and interannual variability is generally good, with the model results being mostly within the observational uncertainty range. The model appears to overestimate cloudiness and underestimate surface radiation, although a large observational uncertainty is found in these variables. The 1D distributed lake model (run at each grid point of the lake area) reproduces the observed lake-average sea surface temperature (SST), although differences compared to observations are found in the spatial structure of the SST, most likely as a result of the absence of 3 dimensional lake water circulations. The evolution of lake ice cover and near surface wind over the lake area is also reproduced by the model reasonably well. Improvements resulting from the increase of resolution from 50 to 20 km are most significant in the lake model. Overall the performance of the coupled regional climate—1D lake model system appears to be of sufficient quality for application to climate change scenario simulations over the Caspian Sea Basin.     

Storm surge frequency reduction in Venice under climate change

Increased tidal levels and storm surges related to climate change are projected to result in extremely adverse effects on coastal regions. Predictions of such extreme and small-scale events, however, are exceedingly challenging, even for relatively short time horizons. Here we use data from observations, ERA-40 re-analysis, climate scenario simulations, and a simple feature model to find that the frequency of extreme storm surge events affecting Venice is projected to decrease by about 30% by the end of the twenty-first century. In addition, through a trend assessment based on tidal observations we found a reduction in extreme tidal levels. Extrapolating the current +17 cm/century sea level trend, our results suggest that the frequency of extreme tides in Venice might largely remain unaltered under the projected twenty-first century climate simulations.     

温室效应对青藏高原及青藏铁路沿线气候影响的数值模拟

在一个全球模式中嵌套了RegCM2区域气候模式,进行了CO2加倍对中国区域气候影响的数值试验,对青藏高原及青藏铁路沿线地区进行了重点分析。结果表明,在CO2加倍的情况下,这里的气温将明显升高,升高值一般在2．6～2．8℃以上,高于全国平均值。同时降水在青藏高原大部分地区也将明显增加;其中青藏铁路沿线的增加率一般在25％以上,远高于全国平均值水平。温室效应同时会使得青藏铁路沿线的日平均最高气温升高。     

A focal plane detector design for a wide-band Laue-lens telescope

The energy range above 60 keV is important for the study of many open problems in high energy astrophysics such as the role of Inverse Compton with respect to synchrotron or thermal processes in GRBs, non thermal mechanisms in SNR, the study of the high energy cut-offs in AGN spectra, and the detection of nuclear and annihilation lines. Recently the development of high energy Laue lenses with broad energy bandpasses from 60 to 600keV have been proposed for a Hard X ray focusing Telescope (HAXTEL) in order to study the X-ray continuum of celestial sources. The required focal plane detector should have high detection efficiency over the entire operative range, a spatial resolution of about 1mm, an energy resolution of a few keV at 500keV and a sensitivity to linear polarization. We describe a possible configuration of the focal plane detector based on several CdTe/CZT pixelated layers stacked together to achieve the required detection efficiency at high energy. Each layer can operate both as a separate position sensitive detector and polarimeter or work with other layers to increase the overall photopeak efficiency. Each layer has a hexagonal shape in order to minimize the detector surface required to cover the lens field of view. The pixels would have the same geometry so as to provide the best coupling with the lens point spread function and to increase the symmetry for polarimetric studies.     

A peak acceleration threshold for soil liquefaction: lessons learned from the 2012 Emilia earthquake (Italy)

National and international seismic codes and recommendations provide criteria for liquefaction exclusion based on a peak ground acceleration (PGA) threshold value. In this paper, after a brief review of the procedures and the values suggested in those documents, a database of liquefaction case histories was created, exploiting the background data used in the most relevant verification charts, currently employed in research and professional practice. This dataset was used to identify, on the basis of simple statistical analyses, a PGA threshold on the free ground surface below which liquefaction is unlikely to occur, regardless of the geological site conditions. The calculated value, which is on the order of 0.07–0.1 g, based on the model employed to fit the data, was analyzed in light of information collected during the 2012 Emilia seismic sequence in Italy, which produced many liquefaction events triggered by low acceleration values. The case history of the Emilia earthquake advises setting a PGA threshold for code and recommendations at the lower probability level of occurrence, in the order of 1 %.     

Lessons learned from two case histories of seismic microzonation in Italy

The prediction of the variability of the seismic ground motion in a given built-up area is considered an effective tool to plan appropriate urban development, to undertake actions on seismic risk mitigation and to understand the damage pattern caused by a strong-motion event. The procedures for studying the seismic response and the seismic microzonation of an urban area are well established; nevertheless, some controversial points still exists and are discussed here. In this paper, the selection of a reference input motion, the construction of a subsoil model and the seismic response analysis procedures are discussed in detail, based on the authors’ experience in two Italian case histories: the seismic microzonation of the city of Benevento, which was a predictive study, and the simulation of seismic response and damage distribution in the village of San Giuliano di Puglia, which was a retrospective analysis.     

Climate change and infectious diseases: Can we meet the needs for better prediction?

The next generation of climate-driven, disease prediction models will most likely require a mechanistically based, dynamical framework that parameterizes key processes at a variety of locations. Over the next two decades, consensus climate predictions make it possible to produce forecasts for a number of important infectious diseases that are largely independent of the uncertainty of longer-term emissions scenarios. In particular, the role of climate in the modulation of seasonal disease transmission needs to be unravelled from the complex dynamics resulting from the interaction of transmission with herd immunity and intervention measures that depend upon previous burdens of infection. Progress is also needed to solve the mismatch between climate projections and disease projections at the scale of public health interventions. In the time horizon of seasons to years, early warning systems should benefit from current developments on multi-model ensemble climate prediction systems, particularly in areas where high skill levels of climate models coincide with regions where large epidemics take place. A better understanding of the role of climate extremes on infectious diseases is urgently needed.     

Land surface coupling in regional climate simulations of the West African monsoon

Coupling of the Community Land Model (CLM3) to the ICTP Regional Climate Model (RegCM3) substantially improves the simulation of mean climate over West Africa relative to an older version of RegCM3 coupled to the Biosphere Atmosphere Transfer Scheme (BATS). Two 10-year simulations (1992–2001) show that the seasonal timing and magnitude of mean monsoon precipitation more closely match observations when the new land surface scheme is implemented. Specifically, RegCM3–CLM3 improves the timing of the monsoon advance and retreat across the Guinean Coast, and reduces a positive precipitation bias in the Sahel and Northern Africa. As a result, simulated temperatures are higher, thereby reducing the negative temperature bias found in the Guinean Coast and Sahel in RegCM3–BATS. In the RegCM3–BATS simulation, warmer temperatures in northern latitudes and wetter soils near the coast create excessively strong temperature and moist static energy gradients, which shifts the African Easterly Jet further north than observed. In the RegCM3–CLM3 simulation, the migration and position of the African Easterly Jet more closely match reanalysis winds. This improvement is triggered by drier soil conditions in the RegCM3–CLM3 simulation and an increase in evapotranspiration per unit precipitation. These results indicate that atmosphere–land surface coupling has the ability to impact regional-scale circulation and precipitation in regions exhibiting strong hydroclimatic gradients.