An extreme wave event in eastern Yucatán,Mexico: Evidence of a palaeotsunami event during the Mayan times     

Javier Lario  Chris Spencer  Teresa Bardají  Ángel Marchante  Victor H. Garduño-monroy  Jorge Macias  Sergio Ortega 《Sedimentology》2020,67(3):1481-1504

The Yucatán Peninsula, Mexico, has typically been considered a tectonically stable region with little significant seismic activity. The region though, is one that is regularly affected by hurricanes. A detailed survey of ca 100 km of the eastern Yucatán and Cozumel coast identified the presence of ridges containing individual boulders measuring >1 m in length. The boulder ridges reach 5 m in height and their origin is associated with extreme wave event activity. Previously modelled tsunami waves from known seismically active zones in the region (Muertos Thrust Belt and South Caribbean Deformed Belt) are not of sufficient scale in the area of the Yucatán Peninsula to have produced the boulder ridges recorded in this study. The occurrence of hurricanes in this region is more common, but two of the most destructive (Hurricane Gilbert 1988 and Hurricane Wilma 2005) produced coastal waves too small to have created the ridges recorded here. In this paper, a new tsunami model with a source area located on the Motagua/Swan Island Fault System has been generated that indicates a tsunami event may have caused the extreme wave events that resulted in the deposition of the boulder ridges.  相似文献   

Revisit the calibration errors on experimental slant total electron content (TEC) determined with GPS     

Wenfeng Nie  Tianhe Xu  Adria Rovira-Garcia  José Miguel Juan Zornoza  Jaume Sanz Subirana  Guillermo González-Casado  Wu Chen  Guochang Xu 《GPS Solutions》2018,22(3):85

The calibration errors on experimental slant total electron content (TEC) determined with global positioning system (GPS) observations is revisited. Instead of the analysis of the calibration errors on the carrier phase leveled to code ionospheric observable, we focus on the accuracy analysis of the undifferenced ambiguity-fixed carrier phase ionospheric observable determined from a global distribution of permanent receivers. The results achieved are: (1) using data from an entire month within the last solar cycle maximum, the undifferenced ambiguity-fixed carrier phase ionospheric observable is found to be over one order of magnitude more accurate than the carrier phase leveled to code ionospheric observable and the raw code ionospheric observable. The observation error of the undifferenced ambiguity-fixed carrier phase ionospheric observable ranges from 0.05 to 0.11 total electron content unit (TECU) while that of the carrier phase leveled to code and the raw code ionospheric observable is from 0.65 to 1.65 and 3.14 to 7.48 TECU, respectively. (2) The time-varying receiver differential code bias (DCB), which presents clear day boundary discontinuity and intra-day variability pattern, contributes the most part of the observation error. This contribution is assessed by the short-term stability of the between-receiver DCB, which ranges from 0.06 to 0.17 TECU in a single day. (3) The remaining part of the observation errors presents a sidereal time cycle pattern, indicating the effects of the multipath. Further, the magnitude of the remaining part implies that the code multipath effects are much reduced. (4) The intra-day variation of the between-receiver DCB of the collocated stations suggests that estimating DCBs as a daily constant can have a mis-modeling error of at least several tenths of 1 TECU.  相似文献   

3D-Monitoring Big Geo Data on a seaport infrastructure based on FIWARE     

Pablo Fernández  José Pablo Suárez  Agustín Trujillo  Conrado Domínguez  José Miguel Santana 《Journal of Geographical Systems》2018,20(2):139-157

Many organizations of all kinds are using new technologies to assist the acquisition and analysis of data. Seaports are a good example of this trend. Seaports generate data regarding the management of marine traffic and other elements, as well as environmental conditions given by meteorological sensors and buoys. However, this enormous amount of data, also known as Big Data, is useless without a proper system to organize, analyze and visualize it. SmartPort is an online platform for the visualization and management of a seaport data that has been built as a GIS application. This work offers a Rich Internet Application that allows the user to visualize and manage the different sources of information produced in a port environment. The Big Data management is based on the FIWARE platform, as well as “The Internet of Things” solutions for the data acquisition. At the same time, Glob3 Mobile (G3M) framework has been used for the development of map requirements. In this way, SmartPort supports 3D visualization of the ports scenery and its data sources.  相似文献   

Modeling spatial landslide susceptibility in volcanic terrains through continuous neighborhood spatial analysis and multiple logistic regression in La Ciénega watershed,Nevado de Toluca,Mexico     

Castro-Miguel  Rutilio  Legorreta-Paulín  Gabriel  Bonifaz-Alfonzo  Roberto  Aceves-Quesada  José Fernando  Castillo-Santiago  Miguel Ángel 《Natural Hazards》2022,113(1):767-788

Natural Hazards - Little study has been done on the effect of the pixel neighborhood information when modeling landslide susceptibility using multiple logistic regression (MLR). The present...  相似文献   

Opportunities accruing from the application of public private partnerships in down market urban housing in Kenya     

Giti  Daniel Mutegi  KÁkumu  Owiti Abiero  Ondieki  Edwin Oyaro 《GeoJournal》2021,86(6):2957-2974

GeoJournal - The purpose of this study was to investigate the opportunities which accrue from application of PPPs in development of down market urban housing in Kenya, hence attracting private...  相似文献   

9000 years of changes in peat organic matter composition in Store Mosse (Sweden) traced using FTIR-ATR     

Antonio Martínez Cortizas  Jenny K. Sjöström  Eleonor E. Ryberg  Malin E. Kylander  Joeri Kaal  Olalla López-Costas  Noemi Álvarez Fernández  Richard Bindler 《Boreas: An International Journal of Quaternary Research》2021,50(4):1161-1178

Store Mosse (the ‘Great Bog’ in Swedish) is one of the most extensive bog complexes in southern Sweden (~77 km²), where pioneering palaeoenvironmental research has been carried out since the early 20th century. This includes, for example, vegetation changes, carbon and nitrogen dynamics, peat decomposition, atmospheric metal pollution, mineral dust deposition, dendrochronology, and tephrochronology. Even though organic matter (OM) represents the bulk of the peat mass and its compositional change has the potential to provide crucial ecological information on bog responses to environmental factors, peat OM molecular composition has not been addressed in detail. Here, a 568-cm-deep peat sequence was studied at high resolution, by attenuated reflectance Fourier-transform infrared spectroscopy (FTIR-ATR) in the mid-infrared region (4000–400 cm^–1). Principal components analysis was performed on selected absorbances and change-point modelling was applied to the records to determine the timing of changes. Four components accounted for peat composition: (i) depletion/accumulation of labile (i.e. carbohydrates) and recalcitrant (i.e. lignin and other aromatics, aliphatics, organic acids and some N compounds) compounds, due to peat decomposition; (ii) variations in N compounds and carbohydrates; (iii) residual variation of lignin and organic acids; and (iv) residual variation of aliphatic structures. Peat decomposition showed two main patterns: a long-term trend highly correlated to peat age (r = 0.87), and a short-term trend, which showed five main phases of increased decomposition (at ~8.4–8.1, ~7.0–5.6, ~3.5–3.1, ~2.7–2.1 and ~1.6–1.3 ka) – mostly corresponding to drier climate and its effect on bog hydrology. The high peat accumulation event (~5.6–3.9 ka), described in earlier studies, is characterized by the lowest degree of peat decomposition of the whole record. Given that FTIR-ATR is a quick, non-destructive, cost-effective technique, our results indicate that it can be applied in a systematic way (including multicore studies) to peat research and provide relevant information on the evolution of peatlands.  相似文献   

Long- and short-term volcanic hazard assessment of El Chichón Volcano (Mexico) through Bayesian inference     

Alatorre-Ibargüengoitia  Miguel A.  Hernández-Urbina  Karina  Ramos-Hernández  Silvia G. 《Natural Hazards》2021,106(1):1011-1035

Natural Hazards - The 1982 eruption of El Chichón volcano constitutes the worst volcanic disaster in Mexico producing more than 2000 fatalities, thousands of displaced people and severe...  相似文献   

Extreme waves induced by cyclone Nargis at Myanmar coast: numerical modeling versus satellite observations     

Kyaw  Thit Oo  Esteban  Miguel  Mäll  Martin  Shibayama  Tomoya 《Natural Hazards》2021,106(3):1797-1818

Natural Hazards - The deltaic coast of Myanmar was severely hit by tropical cyclone Nargis in May 2008. In the present study, a top-down numerical simulation approach using the Weather Research and...  相似文献   

Development,urban planning and political decisions. A triad that built territories at risk     

Lara  Alejandro  Bucci  Felipe  Palma  Cristobal  Munizaga  Juan  Montre-Águila  Victor 《Natural Hazards》2021,109(2):1935-1957

Natural Hazards - Chilean geography exposes the country to high-level risks such as earthquakes and tsunamis. The disasters of 1930, 1960, 2010, and 2014 testify to the continuous link between...  相似文献   

Resource Model Updating For Compositional Geometallurgical Variables     

Prior  Ángel  Tolosana-Delgado  Raimon  van den Boogaart  K. Gerald  Benndorf  Jörg 《Mathematical Geosciences》2021,53(5):945-968

In the field of mineral resources extraction, one main challenge is to meet production targets in terms of geometallurgical properties. These properties influence the processing of the ore and are often represented in resource modeling by coregionalized variables with a complex relationship between them. Valuable data are available about geometalurgical properties and their interaction with the beneficiation process given sensor technologies during production monitoring. The aim of this research is to update resource models as new observations become available. A popular method for updating is the ensemble Kalman filter. This method relies on Gaussian assumptions and uses a set of realizations of the simulated models to derive sample covariances that can propagate the uncertainty between real observations and simulated ones. Hence, the relationship among variables has a compositional nature, such that updating these models while keeping the compositional constraints is a practical requirement in order to improve the accuracy of the updated models. This paper presents an updating framework for compositional data based on ensemble Kalman filter which allows us to work with compositions that are transformed into a multivariate Gaussian space by log-ratio transformation and flow anamorphosis. This flow anamorphosis, transforms the distribution of the variables to joint normality while reasonably keeping the dependencies between components. Furthermore, the positiveness of those variables, after updating the simulated models, is satisfied. The method is implemented in a bauxite deposit, demonstrating the performance of the proposed approach.

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