Detection and enumeration of sulphate-reducing bacteria in estuarine sediments by competitive PCR

The distribution of sulphate-reducing bacteria (SRB) in the sediments of the Colne River estuary, Essex, UK covering different saline concentrations of sediment porewater was investigated by the use of quantitative competitive PCR. Here, we show that a new PCR primer set and a new quantitative method using PCR are useful tools for the detection and the enumeration of SRB in natural environments. A PCR primer set selective for the dissimilatory sulphite reductase gene (dsr) of SRB was designed. PCR amplification using the single set of dsr-specific primers resulted in PCR products of the expected size from all 27 SRB strains tested, including Gram-negative and positive species. Sixty clones derived from sediment DNA using the primers were sequenced and all were closely related with the predicted dsr of SRB. These results indicate that PCR using the newly designed primer set are useful for the selective detection of SRB from a natural sample. This primer set was used to estimate cell numbers by dsr selective competitive PCR using a competitor, which was about 20% shorter than the targeted region of dsr. This procedure was applied to sediment samples from the River Colne estuary, Essex, UK together with simultaneous measurement of in situ rates of sulphate reduction. High densities of SRB ranging from 0.2 - 5.7 × 108 cells ml-1 wet sediment were estimated by the competitive PCR assuming that all SRB have a single copy of dsr. Using these estimates cell specific sulphate reduction rates of 10-17 to 10-15 mol of SO42- cell-1 day-1 were calculated, which is within the range of, or lower than, those previously reported for pure cultures of SRB. Our results show that the newly developed competitive PCR technique targeted to dsr is a powerful tool for rapid and reproducible estimation of SRB numbers in situ and is superior to the use of culture-dependent techniques.

Using airborne laser altimetry to improve river flood extents delineated from SAR data

Flood extent maps derived from SAR images are a useful source of data for validating hydraulic models of river flood flow. The accuracy of such maps is reduced by a number of factors, including changes in returns from the water surface caused by different meteorological conditions and the presence of emergent vegetation. The paper describes how improved accuracy can be achieved by modifying an existing flood extent delineation algorithm to use airborne laser altimetry (LiDAR) as well as SAR data. The LiDAR data provide an additional constraint that waterline (land-water boundary) heights should vary smoothly along the flooded reach. The method was tested on a SAR image of a flood for which contemporaneous aerial photography existed, together with LiDAR data of the un-flooded reach. Waterline heights of the SAR flood extent conditioned on both SAR and LiDAR data matched the corresponding heights from the aerial photo waterline significantly more closely than those from the SAR flood extent conditioned only on SAR data.

Seasonality of modern pollen and sediment deposition in an estuarine context: the Severn Estuary Levels, southwest England

Recent sedimentological and palynological research on subfossil Holocene banded sediments from the Severn Estuary Levels suggested seasonality of deposition, registered by variations in mineral grain-size and pollen assemblages between different parts of the bands. Here we provide data that strengthen this interpretation from sampling of modern sediments and pollen deposition on an active mudflat and saltmarsh on the margin of the Severn Estuary, and comparison with a vegetation survey and contemporary records of climate, river and tidal regimes. The results of grain-size analysis indicate deposition of comparatively coarse-grained silts during the relatively cool and windy conditions of winter and comparatively fine-grained sediments during relatively warm and calm summer months. Pollen analysis demonstrates the significance of long-term storage of pollen grains and fern spores in the estuarine waterbody, superimposed on which seasonal variations in pollen inputs from local and regional vegetation remain detectable. Copyright (C) 2007 John Wiley & Sons, Ltd.

The water quality of the River Carnon, west Cornwall, November 1992 to March 1994: the impacts of Wheal Jane discharges

In January 1992, there was a major pollutant event for the River Canon and downstream with its confluence to the River Fal and the Fal estuary in the west Cornwall. This incident was associated with the discharge of several million gallons of highly polluted water from the abandoned Wheal Jane tin mine that also extracted Ag, Cu and Zn ore. Later that year, the Centre for Ecology and Hydrology (CBH; then Institute of Hydrology) Wallingford undertook daily monitoring of the River Canon for a range of major, minor and trace elements to assess the nature and the dynamics of the pollutant discharges. These data cover an 18-month period when there remained major water-quality problems after the initial phase of surface water contamination. Here, a summary is provided of the water quality found, as a backdrop to set against subsequent remediation. Two types of water-quality determinant grouping were observed. The first type comprises the determinants B, Cs, Ca, Li, K, Na, SO4, Rb and Sr, and their concentrations are positively correlated with each other but inversely correlated with flow. This type of water-quality determinant shows variations in concentration that broadly link to the normal hydrogeochemical processes within the catchment, with limited confounding issues associated with mine drainage. The second type of water-quality determinant comprises Al, Be, Cd, Ce, Co, Cu, Fe, La, Pb, Pr, Nd, Ni, Si, Sb, U, Y and Zn, and concentrations for all this group are positively correlated. The determinants in this second group all have concentrations that are negatively correlated with pH. This group links primarily to pollutant mine discharge. The water-quality variations in the River Camon are described in relation to these two distinct hydrogeochemical groupings. (C) 2004 Elsevier B.V All rights reserved.

The sediment trapping efficiency of the macro-tidal Daly Estuary, tropical Australia

Field studies were carried out on the water and sediment dynamics in the tropical, macro-tidal, Daly Estuary. The estuary is shallow, very-turbid, about 100 km long, and the entrance is funnel-shape. In the wet, high flow season, normal tidal ranges can be suppressed in the estuary, depending on inflow rates, and freshwater becomes dominant up to the mouth. At that time a fraction of the fine sediment load is exported offshore as a bottom-tagging nepheloid layer after the sediment falls out of suspension of the thin, near-surface, river plume. The remaining fraction and the riverine coarse sediment form a large sediment bar 10 km long, up to 6 m in height and extending across the whole width of the channel near the mouth. This bar, as well as shoals in the estuary, partially pond the mid- to upper-estuary. This bar builds up from the deposition of riverine sediment during a wet season with high runoff and can raise mean water level by up to 2 m in the upper estuary in the low flow season. This ponding effect takes about three successive dry years to disappear by the sediment forming the bar being redistributed all over the estuary by tidal pumping of fine and coarse sediment in the dry season, which is the low flow season. The swift reversal of the tidal currents from ebb to flood results in macro-turbulence that lasts about 20 min. Bed load transport is preferentially landward and occurs only for water currents greater than 0.6 m s(-1). This high value of the threshold velocity suggests that the sand may be cemented by the mud. The Daly Estuary thus is a leaky sediment trap with an efficiency varying both seasonally and inter-annually. (c) 2006 Elsevier Ltd. All rights reserved.

Uses of airborne scanning laser altimetry for river flood modelling and coastal geomorphology

Two ongoing projects at ESSC that involve the development of new techniques for extracting information from airborne LiDAR data and combining this information with environmental models will be discussed. The first project in conjunction with Bristol University is aiming to improve 2-D river flood flow models by using remote sensing to provide distributed data for model calibration and validation. Airborne LiDAR can provide such models with a dense and accurate floodplain topography together with vegetation heights for parameterisation of model friction. The vegetation height data can be used to specify a friction factor at each node of a model’s finite element mesh. A LiDAR range image segmenter has been developed which converts a LiDAR image into separate raster maps of surface topography and vegetation height for use in the model. Satellite and airborne SAR data have been used to measure flood extent remotely in order to validate the modelled flood extent. Methods have also been developed for improving the models by decomposing the model’s finite element mesh to reflect floodplain features such as hedges and trees having different frictional properties to their surroundings. Originally developed for rural floodplains, the segmenter is currently being extended to provide DEMs and friction parameter maps for urban floods, by fusing the LiDAR data with digital map data. The second project is concerned with the extraction of tidal channel networks from LiDAR. These networks are important features of the inter-tidal zone, and play a key role in tidal propagation and in the evolution of salt-marshes and tidal flats. The study of their morphology is currently an active area of research, and a number of theories related to networks have been developed which require validation using dense and extensive observations of network forms and cross-sections. The conventional method of measuring networks is cumbersome and subjective, involving manual digitisation of aerial photographs in conjunction with field measurement of channel depths and widths for selected parts of the network. A semi-automatic technique has been developed to extract networks from LiDAR data of the inter-tidal zone. A multi-level knowledge-based approach has been implemented, whereby low level algorithms first extract channel fragments based mainly on image properties then a high level processing stage improves the network using domain knowledge. The approach adopted at low level uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels. The higher level processing includes a channel repair mechanism.

Deriving global flood hazard maps of fluvial floods through a physical model cascade

Global flood hazard maps can be used in the assessment of flood risk in a number of different applications, including (re)insurance and large scale flood preparedness. Such global hazard maps can be generated using large scale physically based models of rainfall-runoff and river routing, when used in conjunction with a number of post-processing methods. In this study, the European Centre for Medium Range Weather Forecasts (ECMWF) land surface model is coupled to ERA-Interim reanalysis meteorological forcing data, and resultant runoff is passed to a river routing algorithm which simulates floodplains and flood flow across the global land area. The global hazard map is based on a 30 yr (1979–2010) simulation period. A Gumbel distribution is fitted to the annual maxima flows to derive a number of flood return periods. The return periods are calculated initially for a 25×25 km grid, which is then reprojected onto a 1×1 km grid to derive maps of higher resolution and estimate flooded fractional area for the individual 25×25 km cells. Several global and regional maps of flood return periods ranging from 2 to 500 yr are presented. The results compare reasonably to a benchmark data set of global flood hazard. The developed methodology can be applied to other datasets on a global or regional scale.