The Durham/UKST Galaxy Redshift Survey – III. Large-scale structure via the two-point correlation function

We have investigated the statistical clustering properties of galaxies by calculating the two-point galaxy correlation function from the optically selected Durham/UKST Galaxy Redshift Survey. This survey is magnitude-limited to b _J∼17, contains ∼2500 galaxies sampled at a rate of one-in-three and surveys a ∼4×10⁶ ( h ⁻¹ Mpc)³ volume of space. We have empirically determined the optimal method of estimating the two-point correlation function from just such a magnitude-limited survey. Applying our methods to this survey, we find that our redshift-space results agree well with those from previous optical surveys. In particular, we confirm the previously claimed detections of large-scale power out to ∼40 h ⁻¹ Mpc scales. We compare with two common models of cosmological structure formation and find that our two-point correlation function has power significantly in excess of the standard cold dark matter model in the 10–30 h ⁻¹ Mpc region. We therefore support the observational results of the APM galaxy survey. Given that only the redshift-space clustering can be measured directly, we use standard modelling methods and indirectly estimate the real-space two-point correlation function from the projected two-point correlation function. We then invert this projected correlation function to obtain an estimate of the spatial two-point correlation function in real space. This correlation function in real space has a lower amplitude than that in redshift space, but a steeper slope.     

UBVRI photometry of the Durham–AAT redshift survey

Using the PDS microdensitometer at the Royal Greenwich Observatory, we have acquired U , B , V , R and I surface photometry from UK Schmidt photographic plates for all the galaxies with measured redshifts in the Durham–AAT redshift survey. By comparison with CCD photometry we show that such precision photographic photometry of galaxies off IIIa emulsions is capable of an accuracy as good as a few hundredths of a magnitude. We discuss the colour-related properties of these galaxies, and derive luminosity functions in each waveband. We show that when divided by colour, the faint-end slope of the luminosity function of the bluer galaxies is significantly steeper than that for the redder ones.     

The Durham/UKST Galaxy Redshift Survey — V. The catalogue

We present the radial velocities and blue, optical magnitudes for all of the galaxies within the Durham/UKST Galaxy Redshift Survey. This catalogue consists of ∼2500 galaxy redshifts to a limiting apparent magnitude of B _J⋍17 mag, covering a ∼1500-deg² area around the South Galactic Pole. The galaxies in this survey were selected from the Edinburgh/Durham Southern Galaxy Catalogue and were sampled, in order of apparent magnitude, at a rate of one galaxy in every three. The spectroscopy was performed at the 1.2-m UK Schmidt Telescope in Australia using the FLAIR multi-object spectrograph. We show that our radial velocity measurements made with this instrument have an empirical accuracy of ±150 km s⁻¹. The observational techniques and data reduction procedures used in the construction of this survey are also discussed. This survey demonstrates that the UKST can be used to make a three-dimensional map of the large-scale galaxy distribution, via a redshift survey to b _J⋍17 mag, over a wide area of the sky.     

Construction of design hyetographs for locations without observed data

A design hyetograph which represents the time distribution of design rainfall depth corresponding to a duration and a return period is essential in hydrologic design. However, for locations without observed data (ungauged sites), construction of design hyetographs is a difficult task because of the lack of data. Hence, an approach based on self‐organizing map (SOM) is proposed in this paper to construct design hyetographs at ungauged sites. SOM, which is a special kind of artificial neural networks (ANNs), is a powerful technique for extracting and visualizing salient features of data and for solving classification problems. The proposed approach is composed of three steps: classification, assignment and construction. First, the SOM‐based classification is performed to analyse gauged sites' design hyetographs. Second, based on the concept of indicator kriging, a method is developed to assign an ungauged site of interest to a certain cluster. Third, based on the spatial information, the clustering results, and the design hyetographs of gauged sites, the design hyetograph at the site of interest is constructed using the reciprocal‐distance‐squared method. An application is conducted to assess the advantages of the proposed approach over the conventional approaches. Moreover, cross‐validation tests are applied to evaluate the performance of the accuracy and the robustness of the proposed approach. The results confirm the improvement in performance by using the proposed approach instead of conventional approaches. The proposed approach is useful for constructing design hyetographs at ungauged sites. Copyright © 2009 John Wiley & Sons, Ltd.     

Improving the forecasts of extreme streamflow by support vector regression with the data extracted by self‐organizing map

During typhoons or storms, accurate forecasts of hourly streamflow are necessary for flood warning and mitigation. However, hourly streamflow is difficult to forecast because of the complex physical process and the high variability in time. Furthermore, under the global warming scenario, events with extreme streamflow may occur that leads to more difficulties in forecasting streamflows. Hence, to obtain more accurate hourly streamflow forecasts, an improved streamflow forecasting model is proposed in this paper. The computational kernel of the proposed model is developed on the basis of support vector machine (SVM). Additionally, self‐organizing map (SOM) is used to analyse observed data to extract data with specific properties, which are capable of providing valuable information for streamflow forecasting. After reprocessing, these extracted data and the observed data are used to construct the SVM‐based model. An application is conducted to clearly demonstrate the advantage of the proposed model. The comparison between the proposed model and the conventional SVM model, which is constructed without SOM, is performed. The results indicate that the proposed model is better performed than the conventional SVM model. Moreover, as regards the extreme events, the result shows that the proposed model reduces the forecasting error, especially the error of peak streamflow. It is confirmed that because of the use of data extracted by SOM, the improved forecasting performance is obtained. The proposed model, which can produce accurate forecasts, is expected to be useful to support flood warning systems. Copyright © 2012 John Wiley & Sons, Ltd.     

Frontogenesis and Frontal Progression of a Trapping-Generated Estuarine Convergence Front and Its Influence on Mixing and Stratification

Estuarine fronts are well known to influence transport of waterborne constituents such as phytoplankton and sediment, yet due to their ephemeral nature, capturing the physical driving mechanisms and their influence on stratification and mixing is difficult. We investigate a repetitive estuarine frontal feature in the Snohomish River Estuary that results from complex bathymetric shoal/channel interactions. In particular, we highlight a trapping mechanism by which mid-density water trapped over intertidal mudflats converges with dense water in the main channel forming a sharp front. The frontal density interface is maintained via convergent transverse circulation driven by the competition of lateral baroclinic and centrifugal forcing. The frontal presence and propagation give rise to spatial and temporal variations in stratification and vertical mixing. Importantly, this front leads to enhanced stratification and suppressed vertical mixing at the end of the large flood tide, in contrast to what is found in many estuarine systems. The observed mechanism fits within the broader context of frontogenesis mechanisms in which varying bathymetry drives lateral convergence and baroclinic forcing. We expect similar trapping-generated fronts may occur in a wide variety of estuaries with shoal/channel morphology and/or braided channels and will similarly influence stratification, mixing, and transport.     

Influence of Pore Fluid Chemistry on the Mechanical Properties of Clay-Based Materials

The producers of nuclear waste, within all countries exploring options, including Canada, have determined the long-term solution to be a deep geological repository. In the Canadian concept, within the deep geologic repository a number of clay-based barriers will separate the containers from the surrounding geosphere. Following placement the surrounding groundwater will infiltrate into the repository. In order to analyze the performance of the repository under very complex conditions, accurate material properties are required. The chemistry of the host rock is an important aspect as the behaviour of clay-based barrier materials could be affected by the saturating saline groundwater. This paper investigates the saturated mechanical behaviour of light backfill (composed of 50 % silica sand and 50 % Na-bentonite clay) and dense backfill (composed of 70 % crushed granite, 25 % glacial lake clay and 5 % Na-bentonite clay) and the quantifying the effect of pore fluid chemistry on the strength and compressibility behaviour of the materials. The results indicate that light backfill behaviour is strongly influenced by its pore fluid chemistry while dense backfill shows limited effects. The material parameters of light backfill and dense backfill are interpreted for input into numerical simulations. These results and interpretation enrich the understanding of the mechanical response of light and dense backfill, two components of the sealing system of the Canadian deep geologic repository.     

Extreme Eutrophication in Shallow Estuaries and Lagoons of California Is Driven by a Unique Combination of Local Watershed Modifications That Trump Variability Associated with Wet and Dry Seasons

Rapidly growing human populations have caused heavy modifications to the watersheds of many Mediterranean climate estuaries, subjecting them to excessive nutrient enrichment and harmful macroalgal blooms. Despite these impacts, comprehensive studies in these systems are rare and comparisons between systems are lacking. We surveyed five southern California estuaries that ranged in size from 93 to 1,000 ha and incorporated differing land usages and watershed sizes. We sampled environmental variables (sediment redox potential, organic content, total nitrogen and total phosphorus, water column nitrate, ammonium, and salinity) and macroalgal cover and biomass quarterly at three locations within each estuary over 15 months to compare spatial and wet vs. dry season patterns. Maximum mean water column nitrate concentration across all estuaries ranged from 47 to 1,700 μM, showing that all estuaries were highly enriched with nitrogen, at least at some times. Mean macroalgal biomass ranged from 0 to 1,500 g wet wt m^?2. However, neither nutrient concentrations nor algal biomass showed consistent seasonal patterns as maximum values occurred in different seasons in different estuaries. Three-dimensional principal components analysis followed by regression analyses confirmed that macroalgal abundance was not directly related to water or sediment N concentrations. Rather each of these southern California estuaries showed individual patterns in all measured variables, which were most likely induced by a suite of physical modifications unique to each system and its watershed.     

Quantifying uncertainty of the semivariogram of transmissivity of an existing groundwater monitoring network

A method is presented for quantifying the uncertainty of the semivariogram of transmissivity and determining the required number of measurements. In this method, the estimated semivariogram and its 95% confidence limits are first determined from a finite number of measurements. The uncertainty of the estimated semivariogram is then quantified using the random field simulation technique. For a given value of the quantitative index of uncertainty, the required number of measured data can finally be obtained. Actual transmissivity data of an existing groundwater monitoring network are used in the application of the proposed method. The required numbers of measurements of transmissivity for four different values of the quantitative index of uncertainty are provided, from which reliable semivariograms of the transmissivity can be obtained. Copyright © 2004 John Wiley & Sons, Ltd.