An assessment of large-scale flood modelling based on LiDAR data

Large-scale flood modelling approaches designed for regional to continental scales usually rely on relatively simple assumptions to represent the potentially highly complex river bathymetry at the watershed scale based on digital elevation models (DEMs) with a resolution in the range of 25–30 m. Here, high-resolution (1 m) LiDAR DEMs are employed to present a novel large-scale methodology using a more realistic estimation of bathymetry based on hydrogeomorphological GIS tools to extract water surface slope. The large-scale 1D/2D flood model LISFLOOD-FP is applied to validate the simulated flood levels using detailed water level data in four different watersheds in Quebec (Canada), including continuous profiles over extensive distances measured with the HydroBall technology. A GIS-automated procedure allows to obtain the average width required to run LISFLOOD-FP. The GIS-automated procedure to estimate bathymetry from LiDAR water surface data uses a hydraulic inverse problem based on discharge at the time of acquisition of LiDAR data. A tiling approach, allowing several small independent hydraulic simulations to cover an entire watershed, greatly improves processing time to simulate large watersheds with a 10-m resampled LiDAR DEM. Results show significant improvements to large-scale flood modelling at the watershed scale with standard deviation in the range of 0.30 m and an average fit of around 90%. The main advantage of the proposed approach is to avoid the need to collect expensive bathymetry data to efficiently and accurately simulate flood levels over extensive areas.     

DEM Extraction in Urban Areas Using High-Resolution TerraSAR-X Imagery

Three-dimensional (3D) spatial information is crucial for improving the quality of human life through urban planning and management, and it is widely utilized due to its rapid, periodic and inexpensive acquisition. In this context, extraction of digital surface and elevation models (DSM and DEM) is a significant research topic for space-borne optical and synthetic aperture radar (SAR) remote sensing. The DSMs include visible features on the earth’s surface such as vegetation, forest and elevated man-made objects, while DEMs contain only the bare ground. In this paper, using TerraSAR-X (TSX) high resolution Spotlight (HS) images, high-resolution interferometric DEM generation in a part of Istanbul urban area is aimed. This is not an easy task because of SAR imaging problems in complex geometry of urban settlements. The interferometric processing steps for DSM generation were discussed including critical parameters and thresholds to improve the quality of the final product and a 3 m gridded DSM was generated. The DSM-DEM conversion was performed by filtering and the quality of generated DEM was verified against a reference DEM from stereo photogrammetry with 3 m original grid spacing. The achieved root mean square error of height differences (RMSZ) varies from 7.09 to 8.11 m, depending on the terrain slope. The differential DEM, illustrates the height differences between generated DEM and the reference DEM, was generated to show the correlation between height differences and the coherence map. Finally, a perspective view of test area was created draping extracted DEM and a high-resolution IKONOS panchromatic image.     

Tetraether membrane lipid distributions in water-column particulate matter and sediments: a study of 47 European lakes along a north–south transect

We studied the distribution of glycerol dialkyl glycerol tetraethers (GDGTs) in water-column particulate matter and the top 5 cm of sediment from 47 lakes along a transect from southern Italy to the northern part of Scandinavia. Our objective was to investigate the biological sources and potential palaeoenvironmental applications of GDGTs in lacustrine sediments. Both archaea-derived isoprenoid and bacteria-derived branched GDGTs, produced by yet unknown soil bacteria, were identified in all lake sediments. GDGT distributions varied substantially. Crenarchaeotal GDGTs, including the characteristic GDGT crenarchaeol, were found in varying relative concentrations, and were more dominant in lakes from the Alps and some of the lakes from the more southern part of the latitudinal transect. In some lakes, we observed high amounts of the GDGT with no cyclopentane moieties relative to crenarchaeol. As methanogenic Euryarchaeota are known to biosynthesise this GDGT predominantly, these Archaea, rather than Crenarchaeota, may be its dominant biological source. In most of the lakes, high amounts of soil-bacteria-derived, branched GDGTs (>40% of total GDGTs) indicated a substantial contribution from soil erosion. Branched GDGTs dominated, especially in the northern lakes, possibly related to high soil-erosion rates. In many of the lakes, soil input affects the distribution of isoprenoidal GDGTs and prevents the reliable application of the TEX₈₆ temperature proxy for lake water temperature, which is based on in situ crenarchaeotal GDGTs production. In 9 out of the 47 lakes studied, the TEX₈₆ temperature proxy could be used reliably. When we compared the TEX₈₆ correlation with annual and winter lake-surface temperature, respectively, the relationship between TEX₈₆ and winter temperature was slightly stronger. This may indicate the season in which these GDGT-producing organisms have their peak production.     

Assessment of surface runoff depth changes in Sǎrǎţel River basin,Romania using GIS techniques

Sǎrǎ?el River basin, which is located in Curvature Subcarpahian area, has been facing an obvious increase in frequency of hydrological risk phenomena, associated with torrential events, during the last years. This trend is highly related to the increase in frequency of the extreme climatic phenomena and to the land use changes. The present study is aimed to highlight the spatial and quantitative changes occurred in surface runoff depth in Sǎrǎ?el catchment, between 1990–2006. This purpose was reached by estimating the surface runoff depth assignable to the average annual rainfall, by means of SCS-CN method, which was integrated into the GIS environment through the ArcCN-Runoff extension, for ArcGIS 10.1. In order to compute the surface runoff depth, by CN method, the land cover and the hydrological soil classes were introduced as vector (polygon data), while the curve number and the average annual rainfall were introduced as tables. After spatially modeling the surface runoff depth for the two years, the 1990 raster dataset was subtracted from the 2006 raster dataset, in order to highlight the changes in surface runoff depth.