Macrozooplankton Community Dynamics in Relation to Environmental Variables in Willapa Bay,Washington, USA

Willapa Bay is a large, economically and ecologically important estuary on the Washington coast, USA for which the zooplankton community has not previously been studied. Thus, in 2006 and 2007, six stations within Willapa Bay were sampled biweekly for macrozooplankton, chlorophyll, and various abiotic variables to elucidate the processes underlying community composition and dynamics. Non-metric multidimensional scaling identified water temperature and upwelling values as major factors defining two distinct temporal communities. High densities and a community dominated by oceanic species (Calanus pacificus, Centropages abdominalis) marked the winter season, while summer (or the upwelling season) was dominated by estuarine species (Palaemonidae, Clevelandia ios). Smaller scale changes in the community were characterized by variation in chlorophyll a concentration and salinity and were marked by the presence of other taxa (Neotrypaea californiensis, Mysidae). These results point to the importance of physical processes, including the import of marine organisms and retention of estuarine organisms, in the structuring of the macrozooplankton community in Willapa Bay.     

Assessment of NO<Subscript>3</Subscript><Superscript>−</Superscript> contamination in a karstic aquifer,with the use of geochemical data and spatial analysis

Kopaida plain is a cultivated region of Eastern Greece, with specific characteristic related with the paleogeographic evolution and the changes in land use. The present article examines the contamination that derives from nitrates, in terms of contaminant levels, definition of sources and spatial distribution of contaminant plume. For this purpose, 50 water samples were collected from the karstic aquifer and analyzed for 15 parameters including major ions, trace elements, physicochemical parameters, and stable isotopes. The assessment of the above parameter values along with the notes derived by the statistical process revealed the existence of nitrate contamination which has been spatial defined with the aid of spatial interpolation techniques. The correlation of NO₃ ⁻ concentrations with the stable isotope values, defined the infiltration conditions and showed contaminant transport. Nitrate values revealed the potential environmental threat for local people, as 10% of the samples exceeded the parametric value of 50 ppm and 54% of them are above 25 ppm, indicating no optimal quality conditions. The origin of nitrate contamination seems to derive exclusively from the application of N-fertilizers, since the rest of potential sources were not verified by analytical data and field works.     

Application of chemometric methods to analyze the distribution and chemical fraction patterns of metals in sediment from a metropolitan river

Rivers in metropolitan areas are often highly polluted with materials that pose a threat to a large number of residents. Human influences lead to contaminants in metropolitan rivers having more complex sources than those in rural rivers. This complexity results in contamination that is unstable and rapidly changing. Here, the contents and chemical fractionation patterns of eleven toxic elements (As, Cd, Co, Cu, Cr, Mn, Ni, Pb, Zn, Y, and Hg) were evaluated in 13 samples collected from along the Beiyunhe River in Beijing, China. The results revealed that the metal contents were unevenly distributed along the river, with higher levels being observed in the downriver sites and the rendezvous sites. Additionally, more than 80% of the metals were found to be in the residual phase. The organic and sulfide phases were the most important extractable phases of most metals, with Ni, Co, Cu, and Cr primarily being associated with these phases and As, Cd, and Zn having a strong association with the iron/manganese oxide and hydroxide phases. Additionally, Mn was associated with the exchangeable and carbonate phases, with the lowest concentrations being observed in the organic and sulfide phases. Conversely, the metal exchangeable and carbonate phases were uniformly distributed throughout the river. Analysis of the metal sources revealed that particles input from the atmosphere comprised a considerable amount of the metals in the Beiyunhe River. However, these metals likely do not enter the sediment via atmospheric deposition directly, but rather through rainwater runoff into the river. The methods used in the present study will be useful in other studies that require analysis of complex data.     

2D stabilised analytic signal method in DC pole-pole potential data interpretation

Using analytic signal method, interpretation of pole-pole secondary electric potentials due to 2D conductive/resistive prisms is presented. The estimated parameters are the location, lateral extent or width and depth to top surface of the prism. Forward modelling is attempted by 2D-Finite Difference method. The proposed stabilised analytic signal algorithm (RES2AS) uses Tikhonov’s regularization scheme and FFT routines. The algorithm is tested on three theoretical examples and field data from the campus of Roorkee University. The stability of RES2AS is also tested on synthetic error prone secondary pole-pole potential data.     

Ensemble filter methods with perturbed observations applied to nonlinear problems

The ensemble Kalman filter (EnKF) has been shown repeatedly to be an effective method for data assimilation in large-scale problems, including those in petroleum engineering. Data assimilation for multiphase flow in porous media is particularly difficult, however, because the relationships between model variables (e.g., permeability and porosity) and observations (e.g., water cut and gas–oil ratio) are highly nonlinear. Because of the linear approximation in the update step and the use of a limited number of realizations in an ensemble, the EnKF has a tendency to systematically underestimate the variance of the model variables. Various approaches have been suggested to reduce the magnitude of this problem, including the application of ensemble filter methods that do not require perturbations to the observed data. On the other hand, iterative least-squares data assimilation methods with perturbations of the observations have been shown to be fairly robust to nonlinearity in the data relationship. In this paper, we present EnKF with perturbed observations as a square root filter in an enlarged state space. By imposing second-order-exact sampling of the observation errors and independence constraints to eliminate the cross-covariance with predicted observation perturbations, we show that it is possible in linear problems to obtain results from EnKF with observation perturbations that are equivalent to ensemble square-root filter results. Results from a standard EnKF, EnKF with second-order-exact sampling of measurement errors that satisfy independence constraints (EnKF (SIC)), and an ensemble square-root filter (ETKF) are compared on various test problems with varying degrees of nonlinearity and dimensions. The first test problem is a simple one-variable quadratic model in which the nonlinearity of the observation operator is varied over a wide range by adjusting the magnitude of the coefficient of the quadratic term. The second problem has increased observation and model dimensions to test the EnKF (SIC) algorithm. The third test problem is a two-dimensional, two-phase reservoir flow problem in which permeability and porosity of every grid cell (5,000 model parameters) are unknown. The EnKF (SIC) and the mean-preserving ETKF (SRF) give similar results when applied to linear problems, and both are better than the standard EnKF. Although the ensemble methods are expected to handle the forecast step well in nonlinear problems, the estimates of the mean and the variance from the analysis step for all variants of ensemble filters are also surprisingly good, with little difference between ensemble methods when applied to nonlinear problems.     

Impacts of systematic precipitation bias on simulations of water and energy balances in Northwest America

At high latitudes and in mountainous areas, evaluation and validation of water and energy flux simu-lations are greatly affected by systematic precipitation errors. These errors mainly come from topographic effects and undercatch of precipitation gauges. In this study, the Land Dynamics （LAD） land surface model is used to investigate impacts of systematic precipitation bias from topography and wind-blowing on water and energy flux simulation in Northwest America. The results show that topographic and wind adjustment reduced bias of streamflow simulations when compared with observed streamflow at 14 basins. These systematic biases resulted in a -50%-100% bias for runoff simulations, a -20%-20% bias for evapotranspiration, and a -40%-40% bias for sensible heat flux, subject to different locations and adjustments, when compared with the control run. Uncertain gauge adjustment leads to a 25% uncertainty for precipitation, a 20% 100% uncertainty for runoff simulation, a less-than-10% uncertainty for evapotranspiration, and a less-than-20% uncertainty for sensible heat flux.     

Sand eddies induced by cyclic tilt of a retaining wall

The cyclic tilt of a retaining wall induces a peculiar motion in the backfill (sand), which exhibits closed trajectories (eddies). In this paper, the motion of the backfill has been optically traced and analyzed by means of particle image velocimetry, also known as digital image correlation. The results are of importance for cyclically loaded structures (e.g, piles for off-shore structures) and can also serve to test numerical simulations of large deformation.     

A topical evaluation and discussion of data movement technologies for data-intensive scientific applications

Transferring large volumes of information from one location to potentially many others that are geographically distributed and across varying networks is still prevalent in modern scientific data systems. This is despite the movement to push computation to the data and to reduce data movement needed to compute answers to challenging scientific problems, to disseminate information to the scientific community, and to acquire data for curation and enrichment. Because of this, it is imperative that decisions made regarding data movement systems and architectures be backed by both analytical rigor, and also by empirical evidence and measurement. The purpose of this study is to expand on the work performed by our research team over the last decade and to take a fresh look at the evaluation of multiple topical data transfer technologies in use cases derived from data-intensive scientific systems and applications in the areas of Earth science. We report on the evaluation of a set of data movement technologies against a set of empirically derived comparison dimensions. Based on this evaluation, we make recommendations towards the selection of appropriate data movement technologies in scientific applications and scenarios.     

Settlement-Size Larval Red Drum (<Emphasis Type="Italic">Sciaenops ocellatus</Emphasis>) Respond to Estuarine Chemical Cues

Planktonic larvae combine directed swimming and functional sensory systems to locate benthic habitats. Some adult marine fishes use chemical cues for orientation to specific habitats, but olfactory function for estuarine fish larvae has received little research attention. This laboratory study quantified behavioral responses of red drum (Sciaenops ocellatus) larvae to estuarine chemical cues to examine the role of water chemistry as an orientation cue for locating or remaining in settlement habitat. Spontaneous activity (kinesis) was measured for pre-settlement-size larvae exposed to artificial sea water (as a negative control) and one of six treatments (sterilized sea water, sea water from a channel at ebb tide, sea water from a channel at flood tide, sea water from seagrass habitat, tannic acid dissolved in sterilized sea water, or lignin dissolved in sterilized sea water). Larvae that reached a size of competency to settle (approximately 10 mm standard length) swam faster when exposed to lignin dissolved in sterilized sea water than in other treatments; smaller larvae showed no response. Olfactory preference (taxis) was tested using a paired-choice experiment. Settlement-size larvae preferred water from seagrass beds to artificial sea water. The observed chemokinesis and chemotaxis in response to lignin dissolved in sterilized sea water and sea water from a seagrass bed demonstrate that red drum larvae can distinguish and respond to different water masses and suggest that chemical stimuli from seagrass settlement habitat may aid in orientation and movement to or retention in suitable settlement sites.     

Assessment of pollution sources in the southeastern of the Riyadh and its impact on the population/Saudi Arabia

The rapid growth of Riyadh—capital of Saudi Arabia—is pushing the area to more pollution and incentive for reorganization. The aim of this research is to assess air pollutants in southeast of Riyadh and detect opinion of the population about their environment. The assessment was done by analyzing 405 questionnaires, evaluating thermal band of Landsat 8, and spatial analyzing of particular matter and chemicals in 19 air samples by geostatistical tool in the ArcMap. Most of the inhabitants stated that they are suffering from bad odor, sewage leakage, and dust mainly from a cement factory. The thermal band of Landsat clarified the location of the pollution sources mainly the 1st industrial city, Yammama Cement Factory, and power plant in Farouq area. The ordinary kriging maps showed that the highest concentration of PM₁₀ (>403 μg/m³) lied to the northern and western side of the study area and caused a health issue to most inhabitants.