Abstract: Tropical Storm Debby brought severe flooding to portions of southwestern Florida during the summer of 2012. Remotely-sensed images were collected to document the flooding and test the results of Hydrologic and Hydraulic (H & H) storm water models constructed by the Southwest Florida Water Management District (SWFWMD). One image, a satellite, multi-band SPOT image was provided to the SWFWMD by the Federal Emergency Management Agency (FEMA). This image was collected within 48 h of the storm event. The SWFWMD also contracted for a very high resolution (60 cm Ground Sample Distance (GSD)) fCIR image to be captured for selected watersheds in Citrus, Hernando and Pasco counties, the areas most impacted by the flooding. Modeled floodplain results were compared to remotely-sensed images that were georeferenced and analyzed using remote sensing techniques. The higher resolution fCIR images more clearly identified flooding for better comparison with modeled results. Although the fCIR images, which were collected three to four days after the storm event, under predicted the overall extent of the modeled floodplain, as the images could not confirm the presence of flooding in areas obscured by dense vegetation, they did consistently confirm both the location and shape of flooding simulated by the model. By using image analysis methods on the Near-Infrared (NIR) band of the fCIR image in conjunction with the Digital Elevation Model (DEM), however, it was possible to identify the extent of flooding in those obscured areas. Field surveys of high water elevations indicated that many locations had receded within hours of the storm event, limiting the ability of the fCIR image from capturing peak flood level in all areas. Overall, these remotely-sensed images provided a good validation of predicted flood levels for a design storm of the magnitude of Tropical Storm Debby.
Abstract: The 1895 discovery of a petrified tree near Clover Creek in south-central Idaho, USA, attracted worldwide attention and resulted in the naming of a new species of ancient oak, Quercinium pliocaenicum Schuster. For more than a century, the discovery has largely been forgotten, even though specimens reside in reputable museums. Reinvestigation of the locality in 2014/2015 resulted in newly-collected specimens and a wealth of new data. Optical microscopy confirms the cellular anatomy used for the original taxonomic study. X-ray diffraction, scanning electron microscopy, energy-dispersive electron spectroscopy, Raman spectroscopy and cathodoluminescence microscopy reveal details of the mineralization, showing the presence of opal-CT as the primary component, with chalcedony as a lesser constituent. This mineralogy suggests petrifaction occurred in at least two stages, beginning with opalization of cellular tissue, leaving open vessels that became filled with chalcedony during a later mineralization episode. Clover Creek oak represents relict flora growing in a wetter climate before the uplift of the Cascade Range created a rain shadow that caused profound desertification of the inland Pacific Northwest.
Abstract: The reconstruction of the chronology of historical buildings is a tricky issue, as usually there are not historical documents that allow the assessment of construction phases, and some materials are hardly reliable for the use of dating techniques (e.g., stone). However, in the last two decades, important advances on the use of absolute dating methods on building materials have increased the possibilities of reconstructing building chronologies, although some advances are still scarcely known among archaeologists and architects. Recent studies performed on several kinds of mortars, fired bricks, mud-bricks, and even stone surfaces have shown that it is possible to date them. Both radiocarbon and luminescence dating have been the most frequently used techniques but others such as archaeomagnetism can also be used in some cases. This paper intends to give an overview of the recent achievements on the use of absolute dating techniques for building materials.
Abstract: The systematic analysis of mortars from monuments or historic buildings and the simultaneous study of the construction environment show that it was common practice to use naturally occurring sand from local rivers or streams for the production of the mortars. There are cases though, mainly on islands, where sands of natural origin were limited, and marine or crushed sands were used possibly after elaboration. In all cases the particle size analysis of old mortar confirms the presence of even distribution of the granules. As regards the design of the repair mortars, there are criteria that should be taken into consideration in order to produce materials with compatible properties. The main properties concerning sands are the grain distribution and maximum size, the color, the content of fines, and soluble salts. The objective of this research is the study of the physical characteristics of the sands such as the sand equivalent, the gradation, the apparent density, the morphology of the grains, their mineralogical composition and the influence of these properties on the behavior of lime mortars, notably the mechanical and physical properties acquired.
Abstract: The Koyna-Warna area in Maharashtra, Western India, is one of the world’s best examples of reservoir-induced seismicity. The occurrence of earthquakes in the vicinity of Koyna Dam (Shivaji Sagar Lake) started since 1962, soon after the initiation of water impoundment. To understand the tectonics and seismicity of the region, recent Landsat 8 images and Sentinel radar data were evaluated in GIS, as well as SRTM and ASTER Digital Elevation Model data (DEM) and the DEM-derived morphometric maps. Geophysical and climate data were also included in the GIS database. The analysis of satellite data contributed towards understanding the tectonic framework of the Koyna reservoir area by visual lineament analysis. Thus, Landsat 8 and Sentinel radar data brought out the structural pattern and made visible larger fault zones. The detailed lineament analysis detected areas, presumed to have rocks of relatively higher permeability, supporting intrusion and infiltration of surface water. The resulting maps of weighted overlay procedures derived from causal morphometric factors that influence the susceptibility to ground motion revealed areas with higher, medium and lower susceptibility to soil amplification.
Abstract: Due to complicated and undefined systematic errors in satellite observation, data assimilation integrating model states with satellite observations is more complicated than field measurements-based data assimilation at a local scale. In the case of Synthetic Aperture Radar (SAR) soil moisture, the systematic errors arising from uncertainties in roughness conditions are significant and unavoidable, but current satellite bias correction methods do not resolve the problems very well. Thus, apart from the bias correction process of satellite observation, it is important to assess the inherent capability of satellite data assimilation in such sub-optimal but more realistic observational error conditions. To this end, time-evolving sequential ensembles of the Ensemble Kalman Filter (EnKF) is compared with stationary ensemble of the Ensemble Optimal Interpolation (EnOI) scheme that does not evolve the ensembles over time. As the sensitivity analysis demonstrated that the surface roughness is more sensitive to the SAR retrievals than measurement errors, it is a scope of this study to monitor how data assimilation alters the effects of roughness on SAR soil moisture retrievals. In results, two data assimilation schemes all provided intermediate values between SAR overestimation, and model underestimation. However, under the same SAR observational error conditions, the sequential ensembles approached a calibrated model showing the lowest Root Mean Square Error (RMSE), while the stationary ensemble converged towards the SAR observations exhibiting the highest RMSE. As compared to stationary ensembles, sequential ensembles have a better tolerance to SAR retrieval errors. Such inherent nature of EnKF suggests an operational merit as a satellite data assimilation system, due to the limitation of bias correction methods currently available.