A multi-tracer approach to delineate groundwater dynamics in the Rio Actopan Basin,Veracruz State,Mexico

Geochemistry and environmental tracers were used to understand groundwater resources, recharge processes, and potential sources of contamination in the Rio Actopan Basin, Veracruz State, Mexico. Total dissolved solids are lower in wells and springs located in the basin uplands compared with those closer to the coast, likely associated with rock/water interaction. Geochemical results also indicate some saltwater intrusion near the coast and increased nitrate near urban centers. Stable isotopes show that precipitation is the source of recharge to the groundwater system. Interestingly, some high-elevation springs are more isotopically enriched than average annual precipitation at higher elevations, indicating preferential recharge during the drier but cooler winter months when evapotranspiration is reduced. In contrast, groundwater below 1,200 m elevation is more isotopically depleted than average precipitation, indicating recharge occurring at much higher elevation than the sampling site. Relatively cool recharge temperatures, derived from noble gas measurements at four sites (11–20 °C), also suggest higher elevation recharge. Environmental tracers indicate that groundwater residence time in the basin ranges from 12,000 years to modern. While this large range shows varying groundwater flowpaths and travel times, ages using different tracer methods (¹⁴C, ³H/³He, CFCs) were generally consistent. Comparing multiple tracers such as CFC-12 with CFC-113 indicates piston-flow to some discharge points, yet binary mixing of young and older groundwater at other points. In summary, groundwater within the Rio Actopan Basin watershed is relatively young (Holocene) and the majority of recharge occurs in the basin uplands and moves towards the coast.     

Rainfall thresholds for the triggering of landslides considering previous soil moisture conditions (Asturias,NW Spain)

Given its geological and climatic conditions and its rugged orography, Asturias is one of the most landslide prone areas in the North of Spain. Most of the landslides occur during intense rainfall episodes. Thus, precipitation is considered the main triggering factor in the study area, reaching average annual values of 960 mm. Two main precipitation patterns are frequent: (i) long-lasting periods of moderate rainfall during autumn and winter and (ii) heavy short rainfall episodes during spring and early summer. In the present work, soil moisture conditions in the locations of 84 landslides are analysed during two rainfall episodes, which represent the most common precipitation patterns: October–November 2008 and June 2010. Empirical data allowed the definition of available water capacity percentages of 99–100% as critical soil moisture conditions for the landslide triggering. Intensity-duration rainfall thresholds were calculated for each episode, considering the periods with sustained high soil moisture levels before the occurrence of each analysed landslide event. For this purpose, data from daily water balance models and weather stations were used. An inverse relationship between the duration of the precipitation and its intensity, consistent with published intensity-duration thresholds, was observed, showing relevant seasonal differences.     

How to increase technology transfers to developing countries: a synthesis of the evidence

The existing United Nations Framework Convention on Climate Change (UNFCCC) has failed to deliver the rate of low-carbon technology transfer (TT) required to curb GHG emissions in developing countries. This failure has exposed the limitations of universalism and renewed interest in bilateral approaches to TT. Gaps are identified in the UNFCCC approach to climate change TT: missing links between international institutions and the national enabling environments that encourage private investment; a non-differentiated approach for (developing) country and technology characteristics; and a lack of clear measurements of the volume and effectiveness of TTs. Evidence from econometric literature and business experience on climate change TT is reviewed, so as to address the identified pitfalls of the UNFCCC process. Strengths and weaknesses of different methodological approaches are highlighted. International policy recommendations are offered aimed at improving the level of emission reductions achieved through TT.     

Geochemical aspects of accumulation of macroelements in the subcolloidal fraction of bottom sediments at the Razdol’naya River-Amur Bay cross-section (the Sea of Japan)

The concentration of Si, Al, Mg, K, Ca, Na, Sr, and Ba in the subcolloidal fraction of sediments at the Razdol’naya River-Amur Bay cross-section is determined using the atomic emission spectroscopy method. Computed is the mean content of studied elements in the soil and river bottom sediments (to the mixing zone). Revealed are river bottom sediments with the high concentration of macroelements corresponding to the zone of mixing of fresh river water and salt sea water. It is demonstrated that the additional accumulation of macroelements (Ca, Na, and Sr) in these sediments is associated with the formation of hydroxides of Fe and Mn and processes of sorption (Mg, Ca, Na, K, Sr, and Ba) on clay minerals (hydromica and smectites).     

Taphonomic analysis of small mammal bone remains preyed upon by wildcats (Carnivora: Felidae) from the central Monte Desert (Mendoza,Argentina)

The present study analysed the taphonomic characteristics of small mammal bone accumulations produced by small felids in an area from the central Monte Desert (Mendoza, Argentina). In order to provide criteria to identify the role that these predators had in the formation of zooarchaeological assemblages, the anatomical representation, bone breakage patterns and degrees of digestive corrosion were evaluated. The main taphonomic results are: low average values for the relative abundance of skeletal elements; greater representation of mandibles, maxillae, isolated incisors, humeri and femora than the remaining elements; preponderance of cranial elements with high proportion of isolated teeth; elevated frequencies of proximal limb bones compared with distal parts; high degree of breakage in all skeletal elements and digestive corrosion on almost all diagnostic bones (mainly moderate and heavy). The values of the studied taphonomic variables indicate that small felids in this area made severe alterations to the bones of their prey (mainly rodents), attributable to the category of extreme modifier, while preserving enough skeletal elements to allow their taphonomic characterization. Tooth marks or grooves on bone surfaces produced by scratching and chewing were not detected. The low relative abundance of skeletal elements, the high degree of breakage and the elevated frequency of elements with digestion traces represent general taphonomic patterns that fall within those reported for other South American small carnivores.     

Community vulnerability to hazards: introducing local expert knowledge into the equation

The accuracies of three different evolutionary artificial neural network (ANN) approaches, ANN with genetic algorithm (ANN-GA), ANN with particle swarm optimization (ANN-PSO) and ANN with imperialist competitive algorithm (ANN-ICA), were compared in estimating groundwater levels (GWL) based on precipitation, evaporation and previous GWL data. The input combinations determined using auto-, partial auto- and cross-correlation analyses and tried for each model are: (i) GWL _t?1 and GWL _t?2; (ii) GWL _t?1, GWL _t?2 and P _t ; (iii) GWL _t?1, GWL _t?2 and E _t ; (iv) GWL _t?1, GWL _t?2, P _t and E _t ; (v) GWL _t?1, GWL _t?2 and P _t?1 where GWL _t , P _t and E _t indicate the GWL, precipitation and evaporation at time t, individually. The optimal ANN-GA, ANN-PSO and ANN-ICA models were obtained by trying various control parameters. The best accuracies of the ANN-GA, ANN-PSO and ANN-ICA models were obtained from input combination (i). The mean square error accuracies of the ANN-GA and ANN-ICA models were increased by 165 and 124% using ANN-PSO model. The results indicated that the ANN-PSO model performed better than the other models in modeling monthly groundwater levels.     

Modelling shallow landslide susceptibility: a new approach in logistic regression by using favourability assessment

A new method for estimating shallow landslide susceptibility by combining Geographical Information System (GIS), nonparametric kernel density estimation and logistic regression is described. Specifically, a logistic regression is applied to predict the spatial distribution by estimating the probability of occurrence of a landslide in a 16 km² area. For this purpose, a GIS is employed to gather the relevant sample information connected with the landslides. The advantages of pre-processing the explanatory variables by nonparametric density estimation (for continuous variables) and a reclassification (for categorical/discrete ones) are discussed. The pre-processing leads to new explanatory variables, namely, some functions which measure the favourability of occurrence of a landslide. The resulting model correctly classifies 98.55% of the inventaried landslides and 89.80% of the landscape surface without instabilities. New data about recent shallow landslides were collected in order to validate the model, and 92.20% of them are also correctly classified. The results support the methodology and the extrapolation of the model to the whole study area (278 km²) in order to obtain susceptibility maps.