Cambios del nivel del mar durante el Holoceno en el Cantábrico a partir del estudio de la Turbera de Trengandín

[Resumen] El estudio de dos depósitos proporcionan nuevos datos acerca de los cambios del nivel del mar durante el Holoceno. De acuerdo con ellos, durante el Sub-Boreal el nivel del mar no estuvo por encima de -2 m con respecto al nivel actual. El análisis sugiere que el nivel del mar ascendió gradualmente desde los -50 m al inicio del Holoceno, y no hay evidencias que sustenten la existencia de un nivel del mar más alto que el actual, al menos hasta el Sub-Atlántico.[Abstract] The study of two deposits provides new data about sea level changes in the bay of Biscay during the Holocene. According to these data, the sea level was not above -2 m respect to present level during Sub-Boreal periodo The analysis suggests that sea level rose gradually from - 50 m at the beginning of the Holocene, and there is not evidence that support a level higher than present at least until Sub-Atlanti

Denudation and geomorphic change in the Anthropocene; a global overview

The effects of human activity on geomorphic processes, particularly those related to denudation/sedimentation, are investigated by reviewing case studies and global assessments covering the past few centuries. Evidence we have assembled from different parts of the world, as well as from the literature, show that certain geomorphic processes are experiencing an acceleration, especially since the mid-twentieth century. This suggests that a global geomorphic change is taking place, largely caused by anthropogenic landscape changes

Landslide Risk Assessment by Using a New Combination Model Based on a Fuzzy Inference System Method

Landslides are one of the most dangerous phenomena that pose widespread damage to property and human lives. Over the recent decades, a large number of models have been developed for landslide risk assessment to prevent the natural hazards. These models provide a systematic approach to assess the risk value of a typical landslide. However, often models only utilize the numerical data to formulate a problem of landslide risk assessment and neglect the valuable information provided by experts’ opinion. This leads to an inherent uncertainty in the process of modelling. On the other hand, fuzzy inference systems are among the most powerful techniques in handling the inherent uncertainty. This paper develops a powerful model based on fuzzy inference system that uses both numerical data and subjective information to formulate the landslide risk more reliable and accurate. The results show that the proposed model is capable of assessing the landslide risk index. Likewise, the performance of the proposed model is better in comparison with that of the conventional techniques