Development of national and local exposure models of residential structures in Chile

Large-scale impacts from natural disasters suffered by society encourage researchers and public agencies to develop methods to evaluate, mitigate, respond, and recover from these events. A key aspect for the calculation of the potential earthquake losses is to properly describe the characteristics and value of assets exposed to seismic hazard. This article describes a methodology to develop an exposure model at a census-block resolution for residential structures in Chile using statistical data. The methodology is based on three steps: (1) obtaining dwelling count, construction material and location from census data, (2) defining classification rules for dwellings associated with houses and apartment buildings, and (3) assigning structural typologies and replacement cost. The resulting exposure model consists of a database with the number of residential structures classified into 18 structural typologies at each census block and the associated replacement cost. A total of 4,259,804 residential structures were identified in the national exposure model. Overall, clay brick and concrete block masonry account for 53.5 % of the structures of the country followed by timber (33.7 %), reinforced concrete (8.1 %), and adobe (4.6 %). Also, a methodology using remote digital survey techniques is proposed and used to obtain local exposure models for the cities of Iquique, Rancagua, and Osorno. The results of the national exposure model are compared with the local exposure models. An important feature of the proposed methodologies is that the building stock is classified into structural typologies, which is a key aspect for conducting seismic risk assessment. The methodologies used to construct the national and local exposure models may be extrapolated to other countries by adjusting the classification rules. The exposure models that were constructed represent an important input for risk calculations, by improving the technical capabilities for seismic risk management of the country.

     

GIS-based landslide susceptibility evaluation using fuzzy-AHP multi-criteria decision-making techniques in the Abha Watershed,Saudi Arabia

Landslides are natural geological disasters causing massive destructions and loss of lives, as well as severe damage to natural resources, so it is essential to delineate the area that probably will be affected by landslides. Landslide susceptibility mapping (LSM) is making increasing implications for GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. It is considered to be an effective tool to understand natural disasters related to mass movements and carry out an appropriate risk assessment. This study is based on an integrated approach of GIS and statistical modelling including fuzzy analytical hierarchy process (FAHP), weighted linear combination and MCE models. In the modelling process, eleven causative factors include slope aspect, slope, rainfall, geology, geomorphology, distance from lineament, distance from drainage networks, distance from the road, land use/land cover, soil erodibility and vegetation proportion were identified for landslide susceptibility mapping. These factors were identified based on the (1) literature review, (2) the expert knowledge, (3) field observation, (4) geophysical investigation, and (5) multivariate techniques. Initially, analytical hierarchy process linked with the fuzzy set theory is used in pairwise comparisons of LSM criteria for ranking purposes. Thereafter, fuzzy membership functions were carried out to determine the criteria weights used in the development of a landslide susceptibility map. These selected thematic maps were integrated using a weighted linear combination method to create the final landslide susceptibility map. Finally, a validation of the results was carried out using a sensitivity analysis based on receiver operator curves and an overlay method using the landslide inventory map. The study results show that the weighted overlay analysis method using the FAHP and eigenvector method is a reliable technique to map landslide susceptibility areas. The landslide susceptibility areas were classified into five categories, viz. very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility, and very high susceptibility. The very high and high susceptibility zones account for 15.11% area coverage. The results are useful to get an impression of the sustainability of the watershed in terms of landsliding and therefore may help decision makers in future planning and mitigation of landslide impacts.     

Examining the rainfall–topography relationship using non-stationary modelling technique in semi-arid Aseer region,Saudi Arabia

The mountainous region of Aseer, corresponding to the Afromontane phytogeographic region, is an eco-sensitive zone and has complex relationship between topography and rainfall. The region is located inland of the red sea escarpment edge in the west. Therefore, rainfall can occur during any month of the year in the mountain of the high Aseer region when moist air forces up the escarpment from the red sea. Monitoring the rainfall data and its topographical elevation variable in Aseer region is an essential requirement for feasible and accurate rainfall-based data for different applications, such as hydrological and ecological resource management in rugged terrain and remote areas. The relationship of elevation and rainfall are spatially non-stationary, non-linear, scale dependent, and often modelled by conventional regression models. Therefore, a local modelling technique, geographically weighted regression (GWR), was applied to deal with non-stationary, non-linear, scale-dependent problems. The GWR using topoclimatic data (elevation and rainfall) to analyse the cumulative rainfall data for rainy months (March to June) of the 4 years estimated from CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations) product for Aseer region. The bandwidth (scale-size) of the Aseer region rainfall–elevation relationship has stabilised at round off 12 km. By selecting the suitable bandwidth, the spatial pattern of the rainfall–elevation relationship was significantly enhanced by using the GWR than the traditional ordinary least squares (OLS) regression model. GWR local modelling techniques estimated well in terms of accuracy, predictive power and decreased residual autocorrelation. Additionally, GWR assesses the significance of local statistic at each location and identified the location of spatial clusters with local regression coefficients significantly improved as compared with global OLS model, thereby highlighting local variations. Therefore, the GWR, local modelling approach managed to produce more accurate estimates by taking into account local characteristics.     

Evapotranspiration models of different complexity for multiple land cover types

A comparison between half‐hourly and daily measured and computed evapotranspiration (ET) using three models of different complexity, namely, the Priestley–Taylor (P‐T), the reference Penman–Monteith (P‐M) and the Common Land Model (CLM), was conducted using three AmeriFlux sites under different land cover and climate conditions (i.e. arid grassland, temperate forest and subhumid cropland). Using the reference P‐M model with a semiempirical soil moisture function to adjust for water‐limiting conditions yielded ET estimates in reasonable agreement with the observations [root mean square error (RMSE) of 64–87 W m^?2 for half‐hourly and RMSE of 0.5–1.9 mm day^?1 for daily] and similar to the complex Common Land Model (RMSE of 60–94 W m^?2 for half‐hourly and RMSE of 0.4–2.1 mm day^?1 for daily) at the grassland and cropland sites. However, the semiempirical soil moisture function was not applicable particularly for the P‐T model at the forest site, suggesting that adjustments to key model variables may be required when applied to diverse land covers. On the other hand, under certain land cover/environmental conditions, the use of microwave‐derived soil moisture information was found to be a reliable metric of regional moisture conditions to adjust simple ET models for water‐limited cases. Further studies are needed to evaluate the utility of the simplified methods for different landscapes. Copyright © 2011 John Wiley & Sons, Ltd.     

The importance of subsurface nepheloid layers in transport and delivery of sediments to the eastern Cariaco Basin,Venezuela

Optical transmissometer measurements were coupled with particulate organic matter (POM) observations to understand suspended sediment composition and distribution in the eastern Cariaco Basin during the rainy seasons of September 2003 and 2006. Our results suggest that nepheloid layers originating at the mouth of small mountainous rivers discharging into the eastern Basin are a major delivery mechanism of terrigenous sediments to the Basin interior. Intermediate nepheloid layers (INL) were observed near the shelf break (～100 m) and appear to effectively transport terrigenous material laterally from the shelf to deep waters, thereby providing a plausible supply mechanism of the terrestrial material observed in sediment traps. These findings highlight the importance of small, local rivers in the Cariaco Basin as sources of terrestrial material. In contrast, these nepheloid layers contained only limited POM. When this information is combined with published sediment trap POM data, it suggests that nepheloid layers may not be a primary mechanism for delivering terrigenous POM to the deeper waters of the basin during the rainy season. Rather, BNL may redistribute marine-derived POM from shallow waters to the Basin's interior by providing ballast materials, particularly during episodic events driven by wind and precipitation. Though we have determined that nepheloid layers play an important role in the seaward transport of particulate material in the Cariaco Basin, their composition and temporal variability have not been fully characterized. This is critical to understand lateral particle transport, since nepheloid layers constitute a significant source of sediment to the deep Cariaco Basin.     

An improved AMC‐coupled runoff curve number model

In the Soil Conservation Service Curve Number (SCS‐CN) method, the three levels of antecedent moisture condition (AMC) permit unreasonable sudden jumps in curve numbers, which result into corresponding jumps in the estimated runoff. A few recently developed SCS‐CN‐based models obviate this problem, yet they have several limitations. In this study, such a model incorporating a continuous function for antecedent moisture has been presented. It has several advantages over the other existing SCS‐CN‐based models. Its application to a large dataset from US watersheds showed to perform better than the existing SCS‐CN method and the others based on it. Copyright © 2010 John Wiley & Sons, Ltd.     

Concentration of Trace Metals and Biochemical Alterations in Various Species of Fishes along the West Coast of India

Ocean Science Journal - This study seeks to evaluate levels of seven trace metals (Cr, Mn, Fe, Cu, Zn, Pb and Hg) and biochemical (proteins, lipids and carbohydrates) alterations in muscle tissue...     

The solar, exoplanet and cosmological lithium problems

We review three Li problems. First, the Li problem in the Sun, for which some previous studies have argued that it may be Li-poor compared to other Suns. Second, we discuss the Li problem in planet hosting stars, which are claimed to be Li-poor when compared to field stars. Third, we discuss the cosmological Li problem, i.e. the discrepancy between the Li abundance in metal-poor stars (Spite plateau stars) and the predictions from standard Big Bang Nucleosynthesis. In all three cases we find that the “problems” are naturally explained by non-standard mixing in stars.     

Implementation and integrated numerical modeling of a landslide early warning system: a pilot study in Colombia

Landslide early warning systems (EWS) are an important tool to reduce landslide risks, especially where the potential for structural protection measures is limited. However, design, implementation, and successful operation of a landslide EWS is complex and has not been achieved in many cases. Critical problems are uncertainties related to landslide triggering conditions, successful implementation of emergency protocols, and the response of the local population. We describe here the recent implementation of a landslide EWS for the Combeima valley in Colombia, a region particularly affected by landslide hazards. As in many other cases, an insufficient basis of data (rainfall, soil measurements, landslide event record) and related uncertainties represent a difficult complication. To be able to better assess the influence of the different EWS components, we developed a numerical model that simulates the EWS in a simplified yet integrated way. The results show that the expected landslide-induced losses depend nearly exponentially on the errors in precipitation measurements. Stochastic optimization furthermore suggests an increasing adjustment of the rainfall landslide-triggering threshold for an increasing observation error. These modeling studies are a first step toward a more generic and integrated approach that bears important potential for substantial improvements in design and operation of a landslide EWS.